Molecular mechanisms of metal hyperaccumulation and ...

Molecular mechanisms of metal hyperaccumulation and

hypertolerance and the functional characterization of the FRD3

gene in Arabidopsis halleri (L.) O’Kane and Al-Shehbaz ssp. halleri

Dissertation to obtain the degree

Doctor Philosophiae (Doctor of Philosophy, PhD)

at the Faculty of Biology and Biotechnology

Ruhr-University Bochum

International Graduate School of Biosciences

Ruhr-University Bochum

Department of Plant Physiology

submitted by

José Romário Fernandes de Melo

from

Vitória da Conquista, Brazil

Bochum

September, 2015

1st Supervisor: Prof. Dr. Ute Krämer

2ndSupervisor: Prof. Dr. Dominik Begerow

Molekulare Mechanismen der Metallhyperakkumulation und

-hypertoleranz und funktionelle Charakterisierung des FRD3 Gens

in Arabidopsis halleri (L.) O’Kane and Al-Shehbaz ssp. halleri

Dissertation zur Erlangung des Grades eines Doktors der Naturwissenschaften

der Fakultät für Biologie und Biotechnologie an der

internationalen Graduiertenschule Biowissenschaften

der Ruhr-Universität Bochum

angefertigt am

Lehrstuhl für Pflanzenphysiologie

vorgelegt von

José Romário Fernandes de Melo

aus

Vitória da Conquista, Brasilien

Bochum

September, 2015

Referent: Prof. Dr. Ute Krämer

Korreferent: Prof. Dr. Dominik Begerow

Acknowledgements

I would like to thank Prof. Dr. Ute Krämer for the opportunity and the DFG grant to

develop my thesis in her group, for the scientific guidance and the many

demonstrations of how to pursue a cutting-edge research career. I thank my second

supervisor Prof. Dr. Dominik Begerow for his assistance during my PhD. I would like

to acknowledge the contribution of Dr. Ricardo Stein with his insightful discussions,

suggestions, and help in the multivariate analysis. I am deeply grateful to Dr. Camille

Larue for her help with µPIXE experiments, teaching how to operate the Nuclear

Microprobe equipment and the massive help for data treatment. Thanks to Petra

Düchting for conducting the ICP run on a large number of samples and to PD. Dr.

Markus Piotrowski for the help with the HPLC method. My thanks also to Prof. Dr.

Bernd Marschner and Dr. Birgit Hütter from the Soil Sciences and Soil Ecology

Department for providing the facilities for the soil C-N analysis. I thank the gardeners

Andreas Aufermann, Martin Pullack and the colleagues Klaus Hagemann and Nicole

Schmelzer for help in daily tasks. I would like to express my gratitude to Dr. Heike

Holländer-Czytko, Dr. Scott Sinclair, Dr. Justyna Cebula and Dr. Ines Kubigsteltig for

their assistance in the lab whenever I needed. I thank Dr. Marc Hanikenne and Dr.

Ina Talke for the availability in answering my questions about their previous data and

transgenic material which I used for my work. I am very grateful to all members of

the Plant Physiology Department who were directly or indirectly involved in my

journey throughout the PhD work. I am happy to recall the nice times shared with

former lab mates Dr. Stefan Reuscher, Dr. Michele Oliva, Kai Uwe-Best, Dr.

Vasantika Singh and Dr. Jamshaid Ali. I am cheerful for the friendship of Joachim

Schab, Andreas Aufermann and Stephan Höreth in the many moments of laud

laughs. Last, but not least, all this would not be possible without the unequivocal

support from my family in Brazil, who even that far away made me feel strong

enough across this life-changing odyssey. In this moment, as a Biologist, I thank my

parents Eliezita and Jeová for providing me the priceless beauty of life. I must

recognize the strength of my father, who proved that not even the odds of life are

able take away who wishes to see a son become a Doctor. And finally, to my

sunshine Simone Praß, whose support was fundamentally essential in this journey.

I

Table of Contents

Table of Contents ........................................................................................................... I

List of figures ............................................................................................................... IV

List of tables ................................................................................................................. VI

List of abbreviations ................................................................................................... VII

1 Introduction ............................................................................................................. 9

1.1 Plant mineral nutrition and homeostasis ............................................................. 9

1.2 Transition metals ................................................................................................ 9

1.3 Essential metals and other elements may be hazardous to living organisms ... 12

1.3.1 Toxic effects of metals in plants ........................................................................ 13

1.3.2 Plants can also take up non-essential toxic elements ...................................... 15

1.3.3 All plants possess basal metal tolerance .......................................................... 16

1.4 The importance of metals for humans .............................................................. 19

1.4.1 Transfer of heavy metals from plants to humans .............................................. 20

1.5 Metal hyperaccumulation and hypertolerance in plants .................................... 21

1.5.1 Evolutionary adaptation to metal-contaminated soils ........................................ 22

1.5.2 Elemental defense hypothesis .......................................................................... 24

1.5.3 Potential use of hyperaccumulators for human benefit and environmental safety ............................................................................................................................. 25

1.5.4 Molecular mechanisms contributing to metal hyperaccumulation and hypertolerance in plants ................................................................................................ 27

1.6 The role of FRD3 in metal homeostasis ........................................................... 33

1.7 Aims of the thesis ............................................................................................. 35

2 Material and Methods ........................................................................................... 36

2.1 List of Equipment .............................................................................................. 36

2.2 Plant material and growth conditions ................................................................ 40

2.2.1 Soil experiments with A. halleri ......................................................................... 41

2.2.2 Hydroponic experiments with A. halleri ............................................................. 43

2.2.3 Soil experiments with A. thaliana ...................................................................... 44

2.2.4 Plate experiments with A. thaliana .................................................................... 45

2.3 Plant genotyping ............................................................................................... 47

2.3.1 DNA extraction ................................................................................................. 47

2.3.2 Quantification of relative transcript levels ......................................................... 48

2.4 Analyses of plant tissues .................................................................................. 49

II

2.4.1 Multi-element analysis ...................................................................................... 49

2.4.2 Determination stress parameters ...................................................................... 52

2.4.2.1 Determination of lipid peroxidation products ..................................................... 52

2.4.2.2 Determination of anthocyanin concentrations ................................................... 53

2.4.2.3 Determination of chlorophyll concentration ....................................................... 53

2.4.2.4 Estimation of H2O2 concentrations .................................................................... 54

2.4.2.5 Quantification of Fe deficiency responses ........................................................ 55

2.4.2.6 Quantitative mapping of elements by Particle-Induced X-ray Emission (µPIXE) ............................................................................................................................. 55

2.5 Xylem exudate analysis .................................................................................... 56

2.6 Soil analyses .................................................................................................... 58

2.6.1 Pre-processing ................................................................................................. 58

2.6.2 Total element concentrations in soil ................................................................. 58

2.6.3 Exchangeable concentration of elements in soil ............................................... 58

2.6.4 Soil pH analysis ................................................................................................ 59

2.6.5 Determination of C-N concentrations ................................................................ 59

2.7 Statistical analysis ............................................................................................ 60

2.7.1 Multivariate analysis ......................................................................................... 60

2.7.2 Univariate statistical analysis ............................................................................ 63

3 Results ................................................................................................................... 64

3.1 Phenotypic characterization of RNAi lines ........................................................ 64

3.1.1 Confirmation of HMA3-, HMA4- and FRD3-RNAi lines ..................................... 64

3.1.2 Environment and soil characterization of A. halleri sites ................................... 66

3.1.3 Validation of experimental set-up ..................................................................... 67

3.1.4 Comparisons between wild type and RNAi lines grown on soil ........................ 71

3.1.5 Exploratory analysis of the leaf ionome, plant performance and stress markers ............................................................................................................................. 75

3.1.6 Leaf ionome, plant performance and stress markers are differently affected by soil properties ........................................................................................................... 79

3.1.7 Silencing of AhHMA4 and AhFRD3 dramatically alters the leaf heavy metal accumulation of A. halleri .............................................................................................. 83

3.2 Functional characterization of the FRD3 gene .................................................. 92

3.2.1 AhFRD3 is essential for Pb accumulation in leaves of Arabidopsis halleri and also contributes to heavy metal tolerance ..................................................................... 92

3.2.2 Characterization of an A. thaliana frd3 loss-of-function mutant with respect to Pb accumulation and tolerance ..................................................................................... 98

3.2.3 AhFRD3 promotes root-to-shoot partitioning of Pb ......................................... 104

III

3.2.4 The comparison of the predicted amino acid sequences of FRD3 proteins of A. halleri and A. thaliana ............................................................................................. 110

3.2.5 Pb is localized mostly in the vasculature and trichomes of A. halleri leaves ... 111

3.2.6 FRD3 promotes Pb mobility across shoot tissues in A. halleri ........................ 112

3.2.7 Introduction of AhFRD3 in A. thaliana wild type enhances leaf Pb accumulation ............................................................................................................... 117

4 Discussion .......................................................................................................... 122

4.1 Global analysis of RNAi-mediated silencing of candidate genes HMA3, HMA4 and FRD3 on metal hyperaccumulation and hypertolerance ............................ 122

4.1.1 Zn, Cd, and Pb accumulation is strongly affected by the silencing of HMA4 and FRD3 .................................................................................................................... 122

4.1.2 Leaf Pb accumulation in A. halleri can reach very high levels under controlled conditions.................................................................................................... 125

4.1.3 Plant growth and biochemical stress markers were less affected by RNAi-mediated silencing of HMA3, HMA4 and FRD3 .......................................................... 126

4.2 The role of FRD3 in Pb accumulation ............................................................. 129

4.2.1 Leaf Pb accumulation in A. halleri depends on the highly expressed FRD3 gene ....................................................................................................................... 129

4.2.2 An upregulation of Fe acquisition mechanisms leads to Pb accumulation in seedlings of the A. thaliana mutant ............................................................................. 130

4.2.3 FRD3 contributes only marginally to Fe homeostasis in A. halleri under the experimental conditions employed .............................................................................. 135

4.2.4 Root-to-shoot Pb transport depends on FRD3 ............................................... 137

4.2.5 Modifications in the predicted FRD3 protein sequence of A. halleri ................ 140

4.2.6 A. halleri sequesters Pb in the leaf vasculature and trichomes base .............. 141

4.2.7 AhFRD3 is a good candidate for exploring phytoremediation technology development ................................................................................................................ 141

5 Conclusion .......................................................................................................... 143

6 Summary ............................................................................................................. 145

7 Zusammenfassung ............................................................................................. 147

8 References .......................................................................................................... 149

9 Appendix ............................................................................................................. 164

10 Erklärung ............................................................................................................. 189

IV

List of figures

Figure 1 Metal homeostasis and metalloproteins for the maintenance of the photosynthetic machinery in the chloroplast. ................................................................. 11

Figure 2 Location of superoxide dismutases in plant cells and cellular responses against reactive oxygen species. .................................................................................. 12

Figure 3 Metal-induced generation of ROS and ROS-mediated lipid peroxidation. ...... 14

Figure 4 Historical increase of toxic trace elements in the atmosphere. ....................... 15

Figure 5 Potential mechanisms for basal metal tolerance in root cells of higher plants ............................................................................................................................. 17

Figure 6 Illustration of the current model for metal hyperaccumulation and hypertolerance based on experimental evidence obtained in studies on A. halleri and N. caerulescens. ........................................................................................................... 29

Figure 7 Evolutionary changes in A. halleri compared to A. thaliana regarding Zn hyperaccumulation. ....................................................................................................... 31

Figure 8 Confirmation of transgenic lines. .................................................................... 65

Figure 9 Reduction of AhHMA3, AhHMA4 and AhFRD3 transcript levels in independent RNAi lines. ................................................................................................ 66

Figure 10 Test of toxicity of metalliferous soils. ............................................................ 69

Figure 11 Test of growth conditions on non-metalliferous soils. ................................... 70

Figure 12 Plant biomass of A. halleri wild type (Lan accession) on native soils. .......... 71

Figure 13 Photographs of HMA3-, HMA4-, and FRD3-RNAi and wild-type lines on Langelsheim soil. .......................................................................................................... 73

Figure 14 Photographs of HMA3-, HMA4-, and FRD3-RNAi and wild-type lines on Malmedy soil. ................................................................................................................ 74 Figure 15 Leaf ionome ordination diagram showing variation of multi-element concentration. ................................................................................................................ 76

Figure 16 Plant growth and stress markers ordination diagram. .................................. 78

Figure 17 Ordination diagram showing the correlation between leaf ionome and soil properties. ..................................................................................................................... 80

Figure 18 Ordination diagram showing correlation between growth and stress markers and soil properties. .......................................................................................... 82

Figure 19 Partial redundancy analysis of samples from metalliferous soils. ................. 84

Figure 20 Leaf metal concentrations of A. halleri plants cultivated on metalliferous soil from Langelsheim. .................................................................................................. 86

Figure 21 Partial redundancy analysis of samples from non-metalliferous soils. .......... 88

Figure 22 Leaf metal concentrations of A. halleri plants cultivated on non-metalliferous soil from Malmedy. ................................................................................... 89 Figure 23 Plant growth and stress markers of A. halleri plants cultivated on metalliferous soils from Langelsheim and Littfeld. ......................................................... 91

V

Figure 24 Root biomass and chlorophyll concentrations in FRD3-RNAi lines and wild type. .............................................................................................................................. 93

Figure 25 The role of AhFRD3 in leaf Pb accumulation is independent of soil mineral and chemical properties. ............................................................................................... 95

Figure 26 Silencing of FRD3 does not robustly affect Mn concentrations in leaves of A. halleri. ....................................................................................................................... 96

Figure 27 Small upregulation of Fe deficiency responsive genes in FRD3-RNAi lines . 97

Figure 28 The A. thaliana frd3-1 mutant is moderately hypersensitive to Pb. ............... 99

Figure 29 A. thaliana Col-0, cad1-3 and frd3-1 grown on LPP agar-solidified medium. ...................................................................................................................... 100 Figure 30 A loss-of-function frd3-1 mutant of A. thaliana accumulates more Pb in its shoots and displays enhanced Fe deficiency responses under Pb exposure, in contrast to A. halleri..................................................................................................... 101

Figure 31 Fe, Zn, and Mn shoot and root concentrations in wild-type and frd3-1 mutant seedlings after cultivation in Pb-containing media. .......................................... 103

Figure 32 Root-to-shoot partitioning of Pb is impaired in a FRD3-RNAi line, and citrate concentration in its xylem exudates is reduced. ............................................... 105

Figure 33 HPLC chromatogram of xylem exudates from A. halleri (wild type and FRD3-RNAi line 18.2) and A. thaliana (wild-type and frd3-1 mutant). ......................... 107

Figure 34 Metal concentration in roots and shoots of FRD3-RNAi and wild-type plants cultivated hydroponically. .................................................................................. 109

Figure 35 Alignment of predicted amino acid sequence of FRD3 proteins of A. halleri and A. thaliana. ........................................................................................................... 111

Figure 36 µPIXE-based identification of regions of interest containing Pb in leaves of A. halleri. ..................................................................................................................... 112

Figure 37 Silencing of FRD3 affects only Pb content in shoots of A. halleri. .............. 113

Figure 38 Principal component analysis showing variation in tissue element contents (data from Table 16) in shoots of A. halleri. ................................................................. 116

Figure 39 A. thaliana plants expressing AhFRD3 accumulate higher Pb concentrations in their leaves than wild type non-transformed plants. ........................ 120

Figure 40 Model for FRD3 function in A. thaliana based on the literature. ................. 133

Figure 41 Model for FRD3 function in A. halleri based on the results of this work. ..... 140

VI

List of tables

Table 1 Hyperaccumulation of trace elements in land plants. ....................................... 22

Table 2 Common set of metal homeostasis genes that are more highly expressed in both A. halleri and N. caerulescens compared to non-accumulator relatives. ............... 28

Table 3 Location of soil collection for controlled experiments. ...................................... 42

Table 4 Composition of modified 0.25x Hoagland medium (Hoagland and Arnon 1950; Becher et al. 2004). ............................................................................................. 44

Table 5 Composition of 1x low-phosphate/low-pH (LPP) medium (Fischer et al. 2014) with addition of micronutrients. ............................................................................ 46

Table 6 List of primers used for plant genotyping and quantification of transcript levels. ............................................................................................................................ 49

Table 7 Composition of calibration standards for ICP-OES analysis of plant samples. 52

Table 8 Standard compounds for the analysis of xylem exudates by HPLC. ................ 57

Table 9 Composition of calibration standards for ICP-OES on soil samples. ................ 60

Table 10 Step-by-step pipeline for univariate statistics using R software. .................... 63

Table 11 Mineral and chemical properties of soils from A. halleri sites used in this study .............................................................................................................................. 67

Table 12 Eigenvalues from principal component analysis of 16 elements of the leaf ionome and element scores for the first four PCs. ........................................................ 77

Table 13 Eigenvalues from redundancy analysis of 16 elements of the ionome and element scores for the first four RDAs. .......................................................................... 81

Table 14 µPIXE/RBS quantification of Pb (µg g-1) in leaves of soil-grown A. halleri wild-type and FRD3-RNAi plants. ................................................................................ 112

Table 15 Metal content in different tissues of A. halleri wild type and FRD3-RNAi. .... 115

Table 16 Mean ± SD (n = 6) leaf Fe and Cd concentrations in wild type, frd3-1, and transgenic lines bearing AhFRD3 after cultivation on heavy metal-contaminated soil. 121

Table 17 Mean ± SD (n = 6) leaf Pb, Fe, Zn and Mn concentrations in wild type, frd3-1, and 35S:AhFRD3 overexpressing line cultivated on non-contaminated soil. .......... 121

VII

List of abbreviations

µPIXE ......................................................................................... Particle-induced X-ray emission AIC ..................................................................................................... Akaike information criterion ANOVA ......................................................................................................... Analysis of variance ATP ......................................................................................................... Adenosine triphosphate BHT ...................................................................................................... Butylated hydroxytoluene CaMV ..................................................................................................... Cauliflower mosaic virus cDNA .......................................................................................................... Complementary DNA CDS .......................................................................................................... Coding DNA sequence Chl a ........................................................................................................................ Chlorophyll a Chl b ........................................................................................................................ Chlorophyll b Col-0 ........................................................................................................................... Colombia 0 dNTPs ................................................................................. Deoxyribose nucleoside triphosphate DW ............................................................................................................................... Dry weight EDTA ............................................................................................... Ethylen-diamine tetraacetate EMS ........................................................................................................ Ethyl methane sulfonate FER .................................................................................................................................. Ferritin FRD ..................................................................................................... Ferric reductase defective FRO ........................................................................................................ Ferric reduction oxidase gDNA ..................................................................................................................... Genomic DNA GFP ...................................................................................................... Green fluorescent protein GUS ....................................................................................................................... Glucuronidase h ........................................................................................................................................ Hours HA ............................................................................................... Human influenza hemagglutinin HMA ............................................................................................................ Heavy metal ATPase HPLC .................................................................................. High pressure liquid chromatography ICP-OES .............................................Inductively-coupled plasma optical emission spectrometry IRT ....................................................................................................... Iron-regulated transporter Lan ........................................................................................................... Langelsheim accession LPP .......................................................................................................... Low-phosphate/low-pH MATE .................................................................................................... Multidrug and toxin efflux MDA ................................................................................................................... Malondialdehyde min ................................................................................................................................... Minutes MS ............................................................................................................. Murashige and Skoog MTP .......................................................................................................... Metal tolerance protein NA .......................................................................................................................... Nicotianamine NAS ........................................................................................................ Nicotianamine synthase

O2

- ............................................................................................................................... Superoxide

PCA ................................................................................................ Principal component analysis PCR .................................................................................................. Polymerase Chain Reaction PFA ......................................................................................................... Perfluoroalkoxy alkanes PSI ......................................................................................................................... Photosystem I PSII ....................................................................................................................... Photosystem II qRT-PCR .......................................................... Quantitative real time polymerase chain reaction QTL .............................................................................................................. Quantitative trait loci RBS ..................................................................................................... Rutherford Backscattering RDA ............................................................................................................ Redundancy analysis RNA .................................................................................................................... Ribonucleic acid RNAi ................................................................................................................. RNA interference ROIs ............................................................................................................... Regions of interest ROS ...................................................................................................... Reactive oxygen species rpm .......................................................................................................... Revolutions per minute

VIII

s .................................................................................................................................... Seconds SD ................................................................................................................... Standard deviation SDS ......................................................................................................... Sodium dodecyl sulfate SOD ........................................................................................................... Superoxide dismutase TAE ....................................................................................................... Tris-acetate-EDTA buffer TBA .................................................................................................................. Thiobarbituric acid TBARS .................................................................................. Thiobarbituric acid reactive species TC .......................................................................................................................... Tissue culture TCA ............................................................................................................... Trichloroacetic acid Tchl ..................................................................................................................... Total chlorophyll TrC ................................................................................................................ Transformed control v/v ........................................................................................................................ Volume/volume w/v ........................................................................................................................ Weight/volume WT ................................................................................................................................. Wild type YSL .................................................................................................................... Yellow stripe-like ZIP ........................................... Zinc-regulated transporter, iron-regulated transporter-like protein

9

Introduction

1 Introduction

1.1 Plant mineral nutrition and homeostasis

Mineral nutrients are essential for the growth and development of plants. Several

elements have been described as essential and others as beneficial. By definition,

essential elements share the following properties: (i) the plant is unable to complete

its life cycle in their absence; (ii) the elements’ role must not be replaceable; and (iii)

the elements must be directly involved in plant metabolism (Arnon and Stout, 1939).

Other elements, which are not essential for the completion of a plant’s life cycle, are

essential only under certain conditions or for certain plant species, or stimulate plant

growth when present, are considered beneficial (Marschner, 1995a). In vascular

plants, examples of beneficial elements are Al, Co, Na, Se, and Si (Marschner,

1995a; Pilon-Smits et al., 2009; White and Brown, 2010). The essential mineral

nutrients of higher and lower plants were grouped into macronutrients (Ca, K, Mg, N,

P and S) and micronutrients (B, Cl, Cu, Fe, Mn, Mo, Ni and Zn) – the latter are also

called trace elements – (Marschner, 1995a). Despite some ongoing discussions on

these definitions, macronutrients are considered as the elements required by plants

in large amounts (between 1,000 and 40,000 µg g-1 DW) and micronutrients are

required in smaller amounts (between 0.1 and 150 µg g-1 DW) (White and Brown,

2010).

1.2 Transition metals

Amongst mineral nutrients, there are several of the so-called transition metals (for

example Cu, Fe, Mn, and Zn), which are required for the activities of various metal-

dependent proteins (metalloproteins) in all plant organs. The vital importance of

these metals has been associated with their requirement for the functionality of a

large number of metabolic pathways (Clarkson and Hanson, 1980). Half of all

proteins in plants, animal and microbial life combined are estimated to contain a

metal as a cofactor (Thomson and Gray, 1998). More than 1,500 proteins are

suggested to be functionally dependent on Cu, Fe, Mn, Ni, and Zn in the model

species Arabidopsis thaliana alone (Krämer et al., 2007).

10

Introduction

Most enzymes involved in the biosynthesis and metabolism of nucleic acids require

divalent metal ions for proper activity (Wilcox, 1996). Nucleases, ribozymes and

metallohydrolases usually use two or more of these metal ions for the hydrolysis of a

variety of molecules, such as DNA, RNA, and proteins (Cowan, 1998; Wilcox, 1996).

Eukaryotic genomes are rich in regions encoding proteins containing Zn-finger

structures, which are known to have roles such as DNA-binding for transcriptional

activation, protein-protein interactions and lipid binding, for example (Laity et al.,

2001). The control of transcription of DNA into messenger RNA is mediated by

transcription factors that bind cis elements of DNA. Some of those are proteins that

fold part of their structure around a Zn2+ cation to form the functional Zn finger DNA-

binding domain (Berg, 1990; Latchman, 1997). The role of Zn in Zn-containing

proteins can be either structural – as in Zn fingers – or catalytic (Vallee and Auld,

1990; Vallee and Falchuk, 1993). Alcohol dehydrogenase and carbonic anhydrase

are two well-known examples of Zn-dependent enzymes. The former catalyzes the

interconversion between aldehydes and alcohols – for example the reduction of

acetaldehyde to ethanol – and contains two Zn atoms, one with a catalytic and

another one with a structural function (Coleman, 1992). Carbonic anhydrase

contains a single catalytic Zn atom per subunit and catalyzes the interconversion of

carbon dioxide (CO2) and water (H2O) to bicarbonate (HCO3

-) and protons (H+) in the

following reaction: CO2 + H2O ⇄ HCO3-+ H

+ (Badger and Price, 1994). This protein

localizes in the cytoplasm, mitochondrion, and chloroplast, where in the latter

contributes to increase CO2 concentrations around Ribulose-1,5-bisphosphate-

carboxylase/oxygenase (Rubisco) to initiate the Calvin-Benson cycle in some plant

species and various photosynthetic organisms (Badger and Price, 1994; Marschner,

1995c; Merchant and Helmann, 2012).

Metal-containing proteins are abundant in the photosynthetic machinery of plants. Fe

and Mn are the most abundant trace elements in thylakoids of photosynthetic

organisms (Merchant and Dreyfuss, 1998). Fe is present in proteins of the

photosystem I (PSI), photosystem II (PSII), the cytochrome b6f complex and

ferredoxin. Mn ions participate in photosynthetic O2 evolution in PSII (Figure 1)

(Raven et al., 1999; Taiz and Zeiger, 2010; Yruela, 2013). Metal deficiencies in

plants are a common cause of leaf chlorosis. Fe deficiency-induced chlorosis is

associated to a significantly decrease of the chlorophyll content, as Fe-requiring

11

Introduction

steps are indispensable in chlorophyll biosynthesis (Marschner, 1995c). Cu is a

cofactor of plastocyanin, the most abundant Cu-containing protein in plants, which

has the function of transferring electrons from the cytochrome b6f complex to PSI

(Figure 1) (Palmer and Guerinot, 2009). Other Cu-containing proteins in plants are

involved in pollen formation and fertilization, lignin biosynthesis for the lignification of

the cell wall (polyphenol oxidase), lipid metabolism, and mitochondrial electron

transport chain (cytochrome c oxidase) (Marschner, 1995c).

Figure 1 Metal homeostasis and metalloproteins for the maintenance of the photosynthetic machinery in the chloroplast. Different colors indicate the metal associated with the respective proteins: Cu (blue), Fe (dark pink), Mn (violet) and Zn (light grey). The Fe-containing cofactors in PSII, PSI and cyt b6f complex are labelled in pink. Proteins involved in Fe/S cluster biogenesis are represented by boxes. Copper chaperone (CCS) for Cu/Zn superoxide dismutase is shown in blue. The Mn ions forming the Mn-cluster together with Ca, which participates in the photosynthetic O2 evolution in the photosystem II, are represented by purple spheres. CA, carbonic anhydrase; CCB, cofactor assembly on complex C subunit B; CCS, copper chaperone for Cu/Zn superoxide dismutase; CnfU, NifU-like protein; Cyt, cytochrome; Fd, ferredoxin; FNR, ferredoxin:NADP(H) reductase; FRO, ferric reductase oxidase; HCF, High Chlorophyll Fluorescence; HMA, heavy metal P-type ATPase; MAR1/IREG3, multiple antibiotic resistance1/iron-regulated protein3; NAP, non-intrinsic ABC protein; NFS, Nifs-like cysteine desulfurase; PAA, P-type ATPase of Arabidopsis; Pc, plastocyanin; PIC, permease in chloroplasts; PPD, PsbP-domain protein; SOD, superoxide dismutase; Ycf, Hypothetical Chloroplast Reading Frame; Y3IP, Ycf3-Interacting Protein. (Integral figure and adapted legend from Yruela 2013).

12

Introduction

Among other functions, Cu, Fe, Mn, and Zn contribute to the scavenging of reactive

oxygen species (ROS) – in this case superoxide anion (O2−) – in the cytosol,

chloroplast and other subcellular compartments through the activity of superoxide

dismutases (SODs: CuZnSOD, FeSOD, and MnSOD) (Figure 2). These enzymes

are essential antioxidant defense for nearly all living organisms (Beauchamp and

Fridovich, 1971). The levels of SODs are strongly controlled in plants according to

environmental conditions and the availability of their respective metal cofactors Cu,

Fe, and Zn (Harris, 1992; Kliebenstein et al., 1998). The coordination of the

expression of SOD genes in response to availability of Cu, Zn, and Fe helps in

protecting the cells from hazardous ROS (Alscher et al., 2002; Chi et al., 2013).

Figure 2 Location of superoxide dismutases in plant cells and cellular responses against reactive oxygen species. Under non-stress conditions, the scavenging of reactive oxygen species (ROS) by plant cells is in balance. A variety of stress conditions (abiotic and/or biotic) can induce the generation of ROS, such

as superoxide anion (O2

-

) by the reduction of molecular oxygen (O2). The generated O2

-

is dismutated by superoxide dismutases (SODs) into hydrogen peroxide (H2O2) and O2. The former can act as the substrate of other antioxidant enzymes, such as catalase (CAT), ascorbate peroxidase (APX), glutathione peroxidase (GPX), and peroxiredoxin (Prx). (Figures obtained from Alscher et al., 2002 and Chi et al., 2013).

1.3 Essential metals and other elements may be hazardous to living

organisms

The chemical properties that render transition metals important for biological

systems also make them prone to becoming toxic when present in excess or

mislocalized. Critically high concentrations of transition metal ions can decrease the

survival of microorganisms (Babich and Stotzky, 1978), impair growth and

development of plants (Marschner, 1995e), and can be the causative agents of a

13

Introduction

number of human pathologies, including neurodegenerative processes (Hamai et al.,

2001).

1.3.1 Toxic effects of metals in plants

The toxicity levels in µg g-1 of some metals in plants are suggested as follows: 20-30

(Cu); >500 (Fe); 200-3,500 (Mn); and 100-300 (Zn) (Beckett and Davis, 1977;

Marschner, 1995c; White and Brown, 2010). If present in excessive concentrations,

transition metals can displace other chemically similar cations from their binding sites

in essential proteins, thereby inactivating these proteins and consequently inhibiting

plant growth and reducing crop yield (White and Brown, 2010). A high supply of Zn

to plants can rapidly induce Zn toxicity and very often chlorosis is observed in young

leaves. This chlorosis may be a secondary effect caused by an induced deficiency of

Fe2+ or Mg2+, which might be displaced by Zn2+ due to the similar ionic radii of these

three elements (Boardman and McGuire, 1990; Woolhouse, 1983). Another example

is that the carbon fixation can be compromised by the toxic effects of Zn. In this

case, Zn2+ displaces Mg2+ in Rubisco rendering the loss of activity of this protein

(Van Assche and Clijsters, 1986; Wildner and Henkel, 1979). Mn excess may induce

Fe deficiency if Mn2+ displaces Fe2+ from the binding sites in Fe-containing

biomolecules, such as catalase, cytochrome c oxidase, consequently decreasing

their overall cellular activities (Horst, 1988; Terry and Zayed, 1995).

A number of studies have shown that metals like Cd, Cu, Fe, Cr, Ni, mercury, and

vanadium lead to ROS production in plants (Benavides et al., 2005; Gallego et al.,

1996). If tissues experience supra-optimal metal concentrations, imbalanced metal

homeostasis or accumulation of non-essential heavy metals, metal-induced oxidative

stress may occur via Haber-Weiss and Fenton reactions (Figure 3) (Halliwell and

Gutteridge, 1984). As a result, the production of ROS, such as Superoxide (O2

-),

hydrogen peroxide (H2O2) and hydroxyl radicals (OH-), will increase. These ROS

react rapidly with DNA, proteins and lipids, causing oxidative damage (Aust et al.,

1985; Ercal et al., 2001). Lipid peroxidation is one of the side effects caused by the

redox potential of essential metals and other heavy metals in plant tissues (Gallego

et al., 1996; Panda et al., 2003). Polyunsaturated fatty acids – such as those from

cellular membranes – are targeted by free radicals thereby unfolding downstream

chain reactions in which the free radicals may capture a hydrogen moiety from an

14

Introduction

unsaturated carbon to form water. This results in an unpaired electron on the fatty

acid molecule that can subsequently capture oxygen, thus forming peroxi-radicals

(Figure 3) (Halliwell and Gutteridge, 1984; Imlay et al., 1988).

Figure 3 Metal-induced generation of ROS and ROS-mediated lipid peroxidation.

The dismutation of O2

-

by SODs catalyzes the formation of intracellular H2O2, which can be converted

into highly reactive OH-

radicals via Fenton reaction mediated by the redox potential of essential transition metals (and heavy metals too) or via Haber-Weiss Reaction. (Figures obtained from Held 2015 and https://classconnection.s3.amazonaws.com/214/flashcards/640214/png/screen_shot_2011-09-02_at_12.47.41_pm1314992874028.png).

The maintenance of a well-coordinated metal homeostasis including uptake,

buffering, translocation, and storage is required in order to prevent metal

https://classconnection.s3.amazonaws.com/214/flashcards/640214/png/screen_shot_2011-09-02_at_12.47.41_pm1314992874028.png

https://classconnection.s3.amazonaws.com/214/flashcards/640214/png/screen_shot_2011-09-02_at_12.47.41_pm1314992874028.png

15

Introduction

accumulation at toxicity levels in tissues, cells, or subcellular compartments

(Clemens et al., 2002).

1.3.2 Plants can also take up non-essential toxic elements

Plants take up metals which are not essential and known to be toxic including the

heavy metals Cd and Pb, because the selectivity of mineral uptake by plants is

limited (Marschner, 1995b). In addition to the low background amounts of these

hazardous elements naturally available in soils, increasing concentrations have been

released into the environment as a result of anthropogenic activities (Hong et al.,

1996). The unprecedented dynamics since the Industrial Revolution – such as a

dramatic increase in mining activities and in the use of fossil fuels, advances in

technology, and the release of toxic waste into fresh water – significantly contributed

to the contamination of soil and water resources and progressively made toxic trace

elements more available to living beings (Figure 4) (Nriagu, 1996; Vitousek et al.,

1997).

Figure 4 Historical increase of toxic trace elements in the atmosphere. Results of mine production and anthropogenic emissions of trace metals (Figure from Nriagu 1996).

Non-essential trace elements can cause toxicity symptoms at far lower exposure

concentrations than essential metals. A number of studies have examined the effects

of Cd exposure in plants, including crops of economic importance (Das et al., 1997).

Leaf and stem biomass production of tomato plants exposed to Cd concentrations as

16

Introduction

low as 10 µM were strongly affected, and the levels of chlorophylls a and b were

decreased too. In the same plants, enzymatic activities of enzymes involved in

oxidative stress protection were significantly increased (López-Millán et al., 2009),

further confirming that excess Cd elicits oxidative stress in crops such as maize, pea

and wheat (Lin et al., 2007; Lozano-Rordriguez et al., 1997), and white mustard

(Sinapis alba L.) exposed to low concentrations of Cd (Fargašová, 2001). It is known

that the uptake of Cd occurs through the Fe transporter IRT1 in A. thaliana roots

(Rogers et al., 2000; Vert et al., 2002). Cd may completely displace Zn ions in Zn-

containing enzymes in eukaryotes (Day et al., 1984).

The toxic effects of Pb in plants have also been studied. In rice, the length, shoot

and root fresh weight of growing seedlings were reduced by up to 43% when

seedlings were grown on medium containing an unphysiologically high concentration

of 1 mM Pb. Seed germination was also reduced by 30%. Lipid peroxidation was

strongly enhanced in shoots of those seedlings, in which the Pb treatment led to

177% increase in lipid peroxidation (Verma and Dubey, 2003). Lower, but still

unrealistically high concentrations of Pb (100 µM) produced toxic effects on root

elongation and branching in young seedlings of different maize cultivars

(Obroucheva et al., 1998). In this study, all Pb concentrations (ranging from 0.1 mM

to 2 mM) supplied to maize seedlings had weak or no effect on shoot development

and biomass. Another report has shown similar results for other plant species such

as wheat, barley and cucumber (Titov et al., 1995). This is comprehensible given the

fact that most plants which can take up Pb from soils are unable to load this metal

into xylem vessels in roots for translocation into shoots, and consequently

accumulate far higher concentrations of Pb in the roots compared to the shoots

(Baker et al., 1994; Godzik, 1993; Reeves and Brooks, 1983). Because soils can

naturally contain trace amounts of non-essential toxic elements, and some of these

elements are still continuously released into the environment by human activities as

smelting (Bi et al., 2006), plants can be exposed from basal to very high

concentrations of hazardous elements.

1.3.3 All plants possess basal metal tolerance

The physiological range of essential metal concentrations between deficiency and

toxicity is narrow, and therefore plants rely on several mechanisms to limit

17

Introduction

concentrations of free aqueous essential metals and non-essential trace elements

within and between tissues, named basal metal tolerance (Clemens, 2006a). A

representation of some of the tolerance mechanisms in plants, at the cellular level, is

shown in Figure 5.

Figure 5 Potential mechanisms for basal metal tolerance in root cells of higher plants. 1. Mycorrhiza act by restricting root metal uptake. 2. Cell wall and/or root exudates can bind metals and reduce their toxic action in roots as well as root metal uptake. 3. Reduced protein levels of transporters acting in root metal uptake upon metal excess. 4. Active export of metals from the cytosol into the apoplast. 5. Metal chelation in the cytosol driven by the presence of low-molecular weight metal ligands including phytochelatins (PCs). 6. Repair and protection of plasma membrane under stress conditions. 7. ATP-dependent transport of PC‐metal complex into the cell vacuole. 8. Removal of metals from the cytosol through their transport into the vacuole for detoxification, e.g. through so-called cation diffusion facilitator proteins. PC: phytochelatins, Cd: cadmium, HSPs: Heat shock proteins, MTs: Metals, ATP: Adenosine triphosphate (Figure obtained from Hall, 2002).

For instance, the excess of Zn in the roots of A. thaliana and almost all other plants

is mainly stored inside root vacuoles via vacuolar sequestration of Zn by Metal

Tolerance Proteins 1 (MTP1) and 3 (MTP3) (Arrivault et al., 2006; Desbrosses-

Fonrouge et al., 2005; Krämer, 2005). The Heavy Metal ATPase3 (HMA3) is another

protein acting in the vacuolar sequestration of metals in roots of A. thaliana (Morel et

al., 2009). HMA3 was able to promote Cd efflux from the cytosol into the vacuole,

and an hma3-1 mutant was hypersensitive to Cd and other metals (Co, Pb, and Zn),

whereas transgenic plants overexpressing AtHMA3 were more tolerant to these

metals than wild-type plants.

18

Introduction

The cytosolic chelation of metals by low-molecular-weight molecules is also

important in basal metal tolerance in many plant species. The metal-induced

biosynthesis of phytochelatins (PCs; (γ-Glu-Cys)n-Gly [n = 2 −11]) from tripeptide

glutathione (γ-ECG) has been demonstrated in plants (Grill et al., 1989). The heavy

metal-binding property of phytochelatins contributes to basal tolerance to Zn, Cd and

Cu (Ha et al., 1999; Mendoza-Cozatl et al., 2008; Persson et al., 2006). The

mechanism of basal Pb tolerance in A. thaliana was also suggested to function

primarily through Pb chelation by phytochelatins (Fischer et al., 2014). These

authors showed that two different cad1 mutants lacking the enzyme phytochelatin

synthase (PCS), that catalyzes the synthesis of phytochelatins (PC) from glutathione

(GSH), are hypersensitive to very low external Pb supply (50 nM Pb) in a medium

specially designed for preventing the precipitation of poorly soluble Pb salts.

Metal chelation by the non-proteinogenic amino acid nicotianamine (NA) was

demonstrated to play roles in Cu, Fe, and Zn homeostasis based on studies in pea,

tobacco, tomato, A. thaliana and barley (Curie et al., 2009; Wirén et al., 1999). In

experiments with tomato plants using immunogold-labeled NA it was demonstrated

that NA was mostly localized in the cytosol of cells from plants grown under normal

Fe supply (10 µM Fe), and highly concentrated in cell vacuoles of plants grown

under high Fe supply (100 µM Fe) (Pich et al., 2001). Later, the concentrations of

Fe(II)-NA complexes were shown to be 10-20 times higher in vacuoles of two

different pea mutants that over-accumulate Fe in leaves [bronze (brz) and

degenerated leaves (dgl)] than in the wild-type vacuoles (reviewed in Curie et al.

2009). Another strategy for metal tolerance in plants is the binding of metals to the

cell wall. A wall-less strain of the algae Chlamydomonas reinhardtii Dangeard – a

model organism for studies of photosynthetic cells – was more sensitive to a range

of metals, including Cd and Cu, than the walled wild-type strain (Macfie et al., 1994).

Later, these authors showed that Cd, Co, Cu, and Ni were bound to the cell wall

(Macfie and Welbourn, 2000). Plant cell walls are rich in compounds that bind

divalent and trivalent metal cations, such as polysaccharides. The cell wall of

Fallopia japonica (Polygonum cuspidatum) – a species found in metal-contaminated

soils in Asia – retained up to 94% Cu, 88% Zn, and 79% Cd of the total

concentrations of these metals in the roots of those plants (Nishizono et al., 1989),

thus contributing to counteract the intra-cellular accumulation of heavy metals.

19

Introduction

1.4 The importance of metals for humans

Since several metals are essential for all living organisms they are required by a vast

range of biochemical processes in humans. These include metabolic and signaling

functions of cells, organ functioning and body development (Blanusa et al., 2005). A

total of 27 metals have been detected in human tissues among which nine transition

metals (Fe, Zn, Cu, Mn, Cr, Co, Mo, and Ni) and the metalloid Se are generally

considered essential trace metals. Within trace elements, Fe and Zn are the most

abundant in the human body (Choi and Koh, 1998; Reilly, 2004). As components of

metalloenzymes, these two metals participate in biological reactions in which

metalloenzymes take part, for instance acid-catalyzed hydrolysis (hydrolases), redox

reactions (oxidases) and rearrangements of carbon–carbon bonds (isomerases and

synthetases) (Reilly, 2004). In an adult human body Fe (present in a total content of

4-5 g) is found incorporated to hemoglobin in erythrocytes, to myoglobin in muscles

and stored in hepatocytes and reticuloendothelial macrophages. The utilization of Fe

for the synthesis of heme and Fe-sulfur (Fe/S) prosthetic groups occurs in the

mitochondrion, which is the major site for Fe usage (Chifman et al., 2014). Zn is also

an abundant trace metal in the human body and an essential component of many

proteins, such as metalloenzymes, zinc-finger transcription factors, RING finger

proteins, or metallothionein proteins (Choi and Koh, 1998). Zn is particularly

abundant in the central nervous system (10 µg g-1 FW in the brain alone), where it is

highly localized in the cerebral cortex and hippocampus (Eom et al., 2001). Given

the systematic colocalization of Zn with glutamate within excitatory synapses,

researchers have proposed that it may function as a transynaptic messenger (Choi

and Koh, 1998). These examples highlight the importance of maintaining metal

homeostasis in the human body.

Metals can disturb organ functions and cause diseases through excess or imbalance

in the human body (Blanusa et al., 2005). The metal-induced generation of oxidative

stress may lead to degenerative diseases, such as cancer, Alzheimer’s disease, and

Parkinson’s disease (Afonso et al., 2007). Investigations using cultured cell lines

from patients with Alzheimer’s disease and Down’s syndrome revealed that the

CuZnSOD activity is increased by 30% and 42%, respectively, in those cultures in

comparison to the cultures from healthy individuals (Zemlan et al., 1989). In Down’s

20

Introduction

patients the increased CuZnSOD activity is associated with an additional functional

copy of the CuZnSOD gene present in the extra chromosome 21, which results in a

corresponding increase in CuZnSOD mRNA levels (Sherman et al., 1983). This

increased CuZnSOD activity, together with other indirect enhancers of ROS

production and lower activity of antioxidant enzymes such as catalase (CAT) and

glutathione peroxidase (GPX), was proposed to contribute to altered morphogenesis,

altered mental activity as well as development of Alzheimer's neuropathology related

to the Down's phenotype (Perluigi et al., 2014; Zemlan et al., 1989). As previously

mentioned, the highest concentrations of Zn in the brain are found in the

hippocampus. In patients with Alzheimer’s disease, significantly elevated levels of Zn

were found in this same region as well as in senile plaques (beta-amyloid protein

deposits found in the brain in Alzheimer disease and normal aging) where Zn can

reach millimolar concentrations (Cornett et al., 1998; Lovell et al., 1998). Despite the

fact that these observations have been associated with the clinical conditions of

Alzheimer’s disease patients, it is not clear yet whether this is one of the causes or a

secondary consequence of the disease. Wilson’s disease is a genetic disorder of

which the causes are directly related to Cu toxicity due to a mutation in the copper

transporter ATPase, Cu+ transporting, beta polypeptide gene (ATP7B) (Forbes and

Cox, 2000). As a consequence of this mutation, irregular functioning of the major

copper binding plasma protein ceruloplasmin leads to the elevation of copper

concentrations in the brain, liver, and kidneys, culminating in liver cirrhosis,

neurological impairment and renal failure (Shimizu et al., 1999).

1.4.1 Transfer of heavy metals from plants to humans

The accumulation of a variety of hazardous substances by living organisms poses

environmental and human health risks (Kelly et al., 2007). In the terrestrial food web

plants belong to the first trophic level of autotrophs/producers. Toxic metal contents

of plants progressively contribute to the toxin burden at higher trophic levels (Cheng

et al., 1984; Hunter and Johnson, 1982; Roberts and Johnson, 1978). Jointly, the

Food and Agriculture Organization of the United Nations (FAO) and WHO Expert

Committee on Food Additives (JECFA) established that a monthly intake of Cd or Pb

above 25 µg kg-1 body weight carries pathological risks in humans (WHO, 2001,

2010). These WHO guidelines also suggested provisional tolerable levels of Cd and

21

Introduction

Pb in drinking water (Cd: 3 µg L-1; Pb: 10 µg L-1) and in the air (Cd: 5 ng m3; Pb: 0.5

µg m3) per year. Among others, one significant source of toxic trace element

acquisition by humans is through smoking, since tobacco leaves accumulate

relatively high concentrations of Cd (up to 6.78 µg g-1 dry biomass) (Lugon-Moulin et

al., 2006).

1.5 Metal hyperaccumulation and hypertolerance in plants

Plant species with the ability to accumulate Ni concentrations over 1,000 µg g-1 dry

biomass in above-ground tissues were designated Ni hyperaccumulators (Jaffre et

al., 1976). Plant species which display the ability of accumulating extraordinarily high

amounts of other metals have since been called metal hyperaccumulators. Metal

hyperaccumulation was found in a large number of species from different orders and

various families (about 50% in the Brassicaceae family) that are able to accumulate

exceptionally high concentrations of metals or metalloids in their leaves (Krämer,

2010). They do so without showing metal toxicity symptoms, suggesting the

existence of a closely associated mechanism of tolerance to elevated metal

concentrations (Baker and Brooks, 1989; Reeves and Brooks, 1983). Metal

hyperaccumulation was reported in around 500 plant species, and different

thresholds for hyperaccumulation have been suggested for each respective

accumulated metal (Table 1). With regard to Ni hyperaccumulation alone, 390 taxa

of Ni hyperaccumulators were reported in 42 families (Krämer, 2010). The

hyperaccumulation phenomenon is a rare trait found in only 0.2% of all angiosperm

taxa – (Baker and Brooks, 1989; Krämer, 2010; van der Ent et al., 2012; Verbruggen

et al., 2009).

The extraordinarily high concentrations of metals in hyperaccumulators would be

lethal in non-accumulator species. As mentioned earlier, plants share several

common metal tolerance mechanisms, and therefore basal metal tolerance is

ubiquitous (Clemens, 2001). Hyperaccumulators are highly tolerant to the metal that

they accumulate. The term “hypertolerance” was coined in order to distinguish the

tolerance in highly tolerant plant species (i.e. hyperaccumulators or plants originating

from metal contaminated areas) from basal tolerance present in all plants (Chaney et

al., 1997). This hypertolerance may be specific to one or several metals, but can also

22

Introduction

be pleiotropic as a secondary consequence of tolerance to another chemically

similar metal (Schat and Vooijs, 1997).

Table 1 Hyperaccumulation of trace elements in land plants.

Element Critical deficiency

level (µg g-1) Critical toxicity level (µg g-1)

Hyperaccumulation criterion (µg g-1)

To date Newly

suggested Taxa Families

Lead n. r. 0.6-28 >1,000 - 14 7

Cadmium n. r. 6-10 >100 - 5 2

Zinc 15-20 100-300 >10,000 >3,000 15 6

Manganese 10-20 200-3,500 >10,000 - 10 6

Nickel 0.002-0.004 10-50 >1,000 - 390 342

Copper 1-5 20-30 >1,000 >300 35 15

Cobalt n. r. 0.4-several >1,000 >300 26 11

Selenium n. r. 3-100 >1,000 - 20 7

From (Krämer, 2010). The critical concentrations for deficiency and toxicity represent the concentrations in which the maximum dry matter yield is decreased by more than 10% (Bouma, 1983; Ohki, 1984). n.r.: no known requirement.

The interesting characteristics of plant metal hyperaccumulation and metal

hypertolerance, especially given the fact that these plants are adapted to metal-

contaminated soils, have attracted the interests of plant biologists and ecologists for

several decades (Antonovics et al., 1971; Baker, 1987; Baker and Brooks, 1989;

Gregory and Bradshaw, 1965).

1.5.1 Evolutionary adaptation to metal-contaminated soils

The soil is the primary source of mineral nutrients, but it also contains non-essential

elements that can enter plants. Hence, soil diversity may impose ecological

discontinuities that exert strong selective pressure in plants (Wallace, 1858). The

tolerance of metal hyperaccumulators to extremely high levels of metals in leaves

apparently enables these plants to colonize soils containing toxic levels of metals.

The fact that some plant species are capable of inhabiting hostile environments that

are either naturally metal-rich, or have been contaminated by anthropogenic

activities, is considered as a great model of natural selection in plants. It was

concluded to be an even more powerful example of evolution in action than the

23

Introduction

industrial melanism in moths (Antonovics et al., 1971) – following aerial deposition of

dark smoke particles on the bark of trees during the industrial revolution (Kettlewell,

1961). The strategy most commonly associated with metal hypertolerance in plants

is metal exclusion (Baker, 1981). It classifies the group of species capable of

avoiding the translocation of metals from roots into shoots (Vos et al., 1991), and

those plants are so-called metal “excluders”.

Plant adaptation to the harsh conditions of serpentine soils – high in Ni, Cr, Co, and

Fe, but poor in Ca, P, and N – was extensively studied at the physiological level.

One observation in plants grown on serpentine soils was the foliar accumulation of

significantly higher levels of Ni and Mg. Nevertheless, most of the serpentine-tolerant

species are not Ni hyperaccumulators (Brady et al., 2005). The mechanisms

conferring plants tolerance to the adverse conditions of serpentine soils are not yet

understood. Different theories suggest the existence of pre-adaptive factors in non-

serpentine populations which could facilitate the adaptation to serpentine soils. The

gene flow between serpentine and non-serpentine populations is one of those

theories, which hypothesize the flow of alleles that could confer tolerance of non-

serpentine population to serpentine soils (Boyd and Martens, 1998a). However,

evidence to support this hypothesis is absent.

Another type of soil requiring plant adaptation are calamine soils, which are enriched

in Cd, Pb, and Zn (Paulowska et al., 1997). These soils are also colonized by

hyperaccumulators. Amongst the well-documented flora of metal-tolerant plants

naturally growing on these soils (Ernst, 1974) are the two Zn/Cd hyperaccumulator

hypertolerant species, Noccaea caerulescens (formerly Thlaspi caerulescens), and

Arabidopsis halleri (Auquier and Leval, 1974; Ernst, 1968). These species are so-

called pseudometallophytes, since populations are naturally found and persist in

both metal-contaminated (metalliferous) and non-contaminated (non-metalliferous)

environments (Baker, 1987).

A more advanced understanding of the evolution of plant adaptations to such

adverse conditions is yet to be achieved. Some environmental factors were

suggested as the likely agents playing a role in the repeated evolution of metal

hyperaccumulation. The pre-adaptation to harsh edaphic conditions, in which the

tolerance to low nutrient availability and drought conditions, could allow these plants

24

Introduction

to colonize less populated environments and consequently face less competition

(Antonovics et al., 1971; Brady et al., 2005). Another hypothesis that involves

competition avoidance is “elemental allelopathy”. This hypothesis postulates that in

the soil surrounding a metal hyperaccumulator plant, metal enrichment through

hyperaccumulator leaf shattering and subsequent decomposition would impede the

growth of competing plants (Boyd and Martens, 1998b). A different hypothesis is

based on several alterations in the metal homeostasis of metal-hypertolerant

species, including enhanced metal uptake in roots and efficient root-to-shoot

translocation, which provide advantages to colonize metalliferous environments

(Hanikenne and Nouet, 2011). The evidence supporting this hypothesis will be

discussed in detail in the section 1.5.4. The hypothesis of defense against herbivory

and pathogens was suggested in a number of studies and is considerably supported

in the literature (Boyd, 2007; Jhee et al., 2006; Martens and Boyd, 1994, 2002;

Pollard and Baker, 1997).

1.5.2 Elemental defense hypothesis

“Elemental defense” was the term suggested in the 90’s (Martens and Boyd, 1994)

to denote the accumulation of potentially toxic metal concentrations in plant leaves

conferring a defense mechanism against biotic attack, i.e. herbivory or pathogen

infection. In that case, the element under examination was Ni (Martens and Boyd,

1994). The characteristic of elemental defense is that the defensive compounds are

not synthesized by plants, but acquired from the soil and accumulated to very high

levels in plant tissues. The advantage of this is that elements cannot be metabolized

or degraded by the herbivores, and may have an overall lower metabolic cost when

compared to organic plant defenses by secondary metabolites that are metabolically

costly to synthesize, such as glucosinolates (Boyd, 2007; Kazemi-Dinan et al.,

2015).

Field trials supported this hypothesis by showing that the Ni hyperaccumulator

Streptanthus polygaloides suffered less herbivore damage when containing higher

levels of Ni in leaf tissues (Martens and Boyd, 2002). Later investigations using the

same plant species demonstrated that high Ni concentrations led to reduced

oviposition from Lepidopterans accompanied by increased flower production,

consistent with a fitness benefit for the plants. Surprisingly, the glucosinolate

25

Introduction

concentrations were similar in plants containing both high and low Ni concentrations

(Jhee et al., 2006), suggesting that there is no trade-off of glucosinolates against

elemental defense.

The defensive effects of Zn and Cd have been similarly tested in Zn/Cd

hyperaccumulator species. In studies using T. caerulescens, different herbivores

(locusts, slugs, and caterpillars) showed significant preference for feeding on plants

accumulating less Zn in their leaves (Behmer et al., 2005; Pollard and Baker, 1997).

In another study, leaves of T. caerulescens containing high levels of Cd alone

suggested the effectiveness of Cd in reducing leaf damage caused by thrips as well

as in considerably decreasing thrips colonization (Jiang et al., 2005). More recently,

a study using A. halleri HMA4-RNAi lines, which contain significantly less Zn and Cd

than the wild type, demonstrated that high leaf concentrations of Zn and Cd,

individually, significantly reduced the feeding of several specialist herbivores tested

(Brassicaceae specialists: caterpillars of Pieris napi, larvae of Athalia rosae and

adults of Phaedon cochleariae) (Kazemi-Dinan et al., 2014). The study also showed

a negative correlation between Zn or Cd concentrations in an artificial diet and the

survival of a generalist herbivore, whereby both metals combined had an additive

effect. Interestingly, leaf glucosinolate concentrations did not differ between the wild

type and HMA4-RNAi lines, similar to what was observed in Ni hyperaccumulator S.

polygaloides (Jhee et al., 2006).

1.5.3 Potential use of hyperaccumulators for human benefit and

environmental safety

The molecular understanding of metal hyperaccumulation by plants has attracted

considerable interest of scientists, especially of those who envisage a potential use

of metal-hyperaccumulating mechanisms in several biotechnologies. If successfully

developed, such technologies can help to safely elevate the concentration of

essential metals (Zn, Fe, or others) in edible plant parts – for example the so-called

biofortification – thus enriching the diets via mineral-enriched grains and combating

human nutritional deficiencies (Clemens et al., 2002). Another example of such

technology is the environmental cleanup using green plants to remove toxic metals

from contaminated soils, namely phytoremediation (Cunningham and Berti, 1993;

Salt et al., 1995; Salt et al., 1998). The low cost of phytoremediation for effective soil

26

Introduction

cleanup, associated with the reduced risks for human health and less use of

chemicals, are some of the most attractive advantages for this technology (Pilon-

Smits, 2005).

A present obstacle in phytoremediation is that most metal hyperaccumulator plants

are not ideal for phytoremediation purposes. The ideal plant would need to be fast

growing, accumulate and tolerate high amounts of various metals in the above

ground tissues, produce high biomass, develop deep roots, and be easy to harvest

(Clemens et al., 2002). Several studies have tested the possibility of extracting

metals from soils through genetically modified plants upon introduction of plant and

bacterial genes involved in heavy metal chelation, accumulation and tolerance

(Barabasz et al., 2012; Bennett et al., 2003; Siemianowski et al., 2011; Van Huysen

et al., 2004). Indian mustard [Brassica juncea (L.) Czern.] overexpressing γ-

glutamylcysteine synthetase (ECS) or glutathione synthetase (GS) genes from

Escherichia coli accumulated 1.5-fold more Cd, 2-fold more Zn, and up to 3-fold

more Pb in shoots relative to wild-type shoots after greenhouse cultivation on soil

collected from a contaminated area in Leadville, Colorado, USA (Bennett et al.,

2003). The concentrations of these metals in leaves of those transgenic plants

reached on average up to 1,750 µg Cd g-1 DW (WT = 1,000 µg Cd g-1 DW), 130 µg

Pb g-1 DW (WT = 10 µg Pb g-1 DW), and 200 µg Zn g-1 DW (WT = 50 µg Zn g-1 DW).

The authors also showed that the transgenic plants removed more metals from the

soil (6% Zn and 25% Cd of the total soil content) compared to what was removed by

wild-type plants (2% Zn and 12% Cd of the total soil content). In another study,

tomato plants expressing A. halleri HMA4 (AhHMA4-1p::AhHMA4) were able

enhance root-to-shoot translocation of Zn and thereby transgenic plants

accumulated up to 2-fold more Zn in the shoots compared to non-transformed wild-

type shoot under a subset of growth conditions tested (Barabasz et al., 2012). The

undesired secondary consequences observed in those transgenic lines compared

with the wild type was Zn excess triggered Fe deficiency, what caused a decrease in

both chlorophyll levels and Fe concentrations of the youngest leaves (Barabasz et

al., 2012). These observations indicate that a more complete understanding of the

alterations in metal homeostasis networks of hyperaccumulator species is urgently

needed.

27

Introduction

1.5.4 Molecular mechanisms contributing to metal hyperaccumulation and

hypertolerance in plants

Hyperaccumulators can maintain the homeostasis of essential metals even when

accumulating levels of certain metals, such as Zn, Cd, Pb, Ni or Cu, at leaf

concentrations up to four orders of magnitude higher than in closely related non-

accumulator species (Krämer, 2010). Amongst those hyperaccumulators some

Arabidopsis relatives has been gradually receiving more attention (Clauss and Koch,

2006; Hanikenne and Nouet, 2011; Roosens et al., 2008). A. halleri and N.

caerulescens have been studied more frequently, and emerged as models for

hyperaccumulation and hypertolerance traits, for instance, because they are both

pseudometallophytes and possess constitutive Zn (and variable Cd)

hyperaccumulation and hypertolerance (Krämer, 2010; Milner and Kochian, 2008).

These two species share relatively high sequence similarity with A. thaliana within

coding regions (A. halleri: 94%, N. caerulescens: 88%), from which they have

diverged 3.5 to 5.8 and 20 million years ago, respectively (Clauss and Koch, 2006).

A. halleri and N. caerulescens share altered metal partitioning between roots and

shoots, metal tolerance, and significantly higher expression of an overlapping set of

metal homeostasis-related genes when compared with non-accumulator species

(Table 2). The processes contributing to metal hyperaccumulation in plants comprise

the enhanced mobilization of metals in the soil, uptake and sequestration by the

roots, efficient root-to-shoot translocation, correct distribution and storage in aerial

organs (Clemens et al., 2002; Hanikenne and Nouet, 2011) (Figure 6).

28

Introduction

Table 2 Common set of metal homeostasis genes that are more highly expressed in both A. halleri and N. caerulescens compared to non-accumulator relatives.

Name Protein family Putative substrate

A. halleri N. caerulescens

Cellular uptake

ZIP4 ZIP Zn, (Cu?) Root Root-shoot

ZIP6 ZIP Zn Root-shoot Shoot

ZIP9 ZIP Zn Root Root

ZIP10 ZIP Zn Root Root

IRT3 ZIP Zn, Fe Root Root-shoot

Xylem loading/unloading

HMA4 P-type ATPase Zn, Cd Root-shoot Root-shoot

FRD3 MATE Citrate Root-shoot Root

Vacuolar sequestration

HMA3 P-type ATPase Zn, Cd Root-shoot Root-shoot

MTP1 CDF Zn Root-shoot Root-shoot

MTP8 CDF Mn Root-shoot Root

Remobilization from the Vacuole

NRAMP3 NRAMP Fe, Mn, Cd Root-shoot Root

Endomembrane transport

MTP11 CDF Mn Shoot Shoot

Transport of metal chelates

YSL3 YSL NA-metal - Root-shoot


YSL6 YSL NA-metal Shoot -


Synthesis of metal ligands

NAS1 NAS SAM1 - Shoot

NAS2 NAS SAM Root Root

NAS3 NAS SAM Shoot -

NAS4 NAS SAM - Shoot

Adapted from Hanikenne and Nouet 2011. 1S-adenosylmethionine (Higuchi et al., 1999). Bold

identifies genes which are the focus of this thesis.

29

Introduction

Figure 6 Illustration of the current model for metal hyperaccumulation and hypertolerance based on experimental evidence obtained in studies on A. halleri and N. caerulescens.

Metal uptake in roots is enhanced by metal transporters from the ZIP family. NA-metal complexes

facilitate the symplastic transport from the epidermis to the vasculature. Efficient metal loading into

the xylem is highly enhanced by HMA4. In the shoots, the xylem unloading may also be enhanced by

HMA4, ZIPs, and possibly by YSL proteins. Enhanced vacuolar metal compartmentalization functions

as an efficient mechanism for cellular detoxification of the metals hyperaccumulated (Figure from

Hanikenne and Nouet 2011).

Interestingly, enhanced gene expression has not been found to involve alterations in

functions of one or a few “master regulator” transcription factors. It could involve cis-

regulatory mutations in multiple genes, but this has so far only been directly

demonstrated for HMA4 (Hanikenne et al., 2008). Instead, gene copy number

expansion is common among highly expressed candidate genes in metal

30

Introduction

hyperaccumulation and hypertolerance. For example, in both A. halleri and N.

caerulescens, researchers have observed increased genomic copy number of the

HMA4 gene encoding a key hyperaccumulation protein acting in root-to-shoot

translocation of metals (Figure 7) (Craciun et al., 2012; Hanikenne et al., 2008; Ueno

et al., 2011) and, in A. halleri, of a gene encoding the metal-specific tonoplast

membrane protein MTP1 that exports Zn ions from the cytosol into the cell vacuole

(Drager et al., 2004; Krämer, 2005; Ueno et al., 2011). The up-regulation of

transcript levels of ZIP4, ZIP9, ZIP10, and IRT3 has been reported in roots of both A.

halleri and N. caerulescens (Hammond et al., 2006; Talke et al., 2006; van de Mortel

et al., 2006; Weber et al., 2004). Transcript levels of these genes are increased in

response to Zn deficiency in A. thaliana, and ZIP4 and IRT3 are constitutively more

highly expressed in roots of A. halleri as a consequence of HMA4 action that

depletes Zn in the root symplasm by exporting Zn into the xylem for root-to-shoot

translocation (Hanikenne et al., 2008). However the individual role of those genes in

metal hyperaccumulation and hypertolerance is yet to be determined.

A number of genes encoding metal ligands (Nicotianamine Synthase, NAS) and

transporters of metal chelates (Yellow Stripe 1-like, YSL) are more highly expressed

in roots and shoots of metal hyperaccumulators species (Table 2) (Gendre et al.,

2007; Talke et al., 2006; van de Mortel et al., 2006). The enhanced biosynthesis of

low-molecular weight metal chelator nicotianamine through NAS2 has been recently

suggested to contribute to Zn hyperaccumulation in A. halleri (Deinlein et al., 2012).

The authors showed that RNA interference-mediated silencing of NAS2 in A. halleri

resulted in strongly reduced root NA levels and associated decreased Zn

translocation from roots into shoots. The high expression of NAS2 in roots of

hyperaccumulators may possibly promote more efficient symplastic Zn transport

from the root epidermis to the vascular tissues, leading to more effective Zn

accumulation in shoots (Deinlein et al., 2012). According to the present working

model, the chelation of Zn by NA allows symplastic cell-to-cell movement through the

plasmodesmata and/or prevents vacuolar storage of Zn in roots (Clemens et al.,

2013; Deinlein et al., 2012; Hanikenne and Nouet, 2011). In addition or alternatively,

metals could be transported from epidermis towards the vasculature through the

apoplastic pathway, with cellular uptake in the endodermal layer. The role of NA in

this hypothetical pathway is presently unknown. Transcript levels of metal-NA

31

Introduction

transporters YSL3, YSL5 and YSL7 are highly abundant in both shoots and roots of

T. caerulescens (Table 2). YSL3 from that species mediates the influx of Ni-NA

complex in yeast and is hypothesized to contribute to root-to-shoot Ni-NA transport

and xylem unloading in leaves, promoting the delivery of Ni-NA to subcellular

storage sites (Gendre et al., 2007). In A. halleri shoots, YSL6 was found to be more

highly expressed than in A. thaliana, suggesting this gene as candidate for metal

tolerance.

Figure 7 Evolutionary changes in A. halleri compared to A. thaliana regarding Zn hyperaccumulation. Genomic copy number triplication of HMA4 combined with higher promoter activity of all HMA4 copies

in A. halleri leads to enhanced long-distance root-to-shoot Zn translocation by increasing the xylem

loading of this metal in roots. (Figure from Hanikenne et al. 2008).

Plant mechanisms of hypertolerance to heavy metals may differ considerably

between species. In hyperaccumulator species, several QTL mapping studies have

identified genomic regions which co-segregate with Zn and Cd tolerance (Assuncao

32

Introduction

et al., 2006; Courbot et al., 2007; Filatov et al., 2006; Willems et al., 2007). In an

interspecific cross between A. halleri and non-accumulator A. lyrata (back-cross 1

population), a major QTL that explained 43% of the phenotypic variation in tolerance

to Cd co-localized with the genomic region encoding metal transporter HMA4

(Courbot et al., 2007). Another study using the same back-cross 1 population

showed that three QTL regions controlling Zn tolerance in A. halleri co-localized with

HMA4, MTP1-A and MTP1-B proteins (Willems et al., 2007). HMA4 encodes a metal

pump protein Heavy Metal ATPase4, which belong to the P1B-type ATPases family.

Proteins of this family are found in all life forms and act in the transmembrane

transport of monovalent (Cu+, Ag+) or divalent (Cu2+, Zn2+, Co2+, Pb2+, Cd2+) cations

(Palmgren and Nissen, 2011). The HMA4 protein in A. thaliana is localized in the

plasma membrane, and promoter activity and transcript levels have been detected in

root pericycle and xylem parenchyma cells and in the vascular bundle of leaves

(Courbot et al., 2007; Hanikenne et al., 2008). In A. halleri, the HMA4 protein

localization in roots was shown to be similar to what is reported in A. thaliana (Nouet

et al., 2015). Root elongation analysis of A. thaliana Col-0 transgenic seedlings

transformed with HMA4 cDNA from A. halleri suggested that roots of those

transgenic seedlings were more tolerant to high concentrations of Zn (120 µM) and

Cd (30 µM) supplied to the growth media than roots of the wild-type non-transformed

seedlings (Hanikenne et al., 2008). The complementation of hma2/hma4 double

mutant of A. thaliana with a AhHMA4::GFP fusion under the control of each of the

three AhHMA4 promoters complemented the strong Zn deficiency phenotype in

rosettes of that mutant and, additionally, provided higher Zn and Cd tolerance in

roots of the complemented mutant (Nouet et al., 2015). These results are additional

evidence that HMA4 is not only involved in Zn/Cd hyperaccumulation in shoots, but

also plays a role in Zn/Cd tolerance by metal exclusion from the root tissues.

From those many differentially expressed metal homeostasis genes in

hyperaccumulators, the list of validated candidate genes also includes the HMA3

gene. Similar to HMA4, HMA3 encodes a membrane protein from the same P1B-type

ATPases family. In A. thaliana, HMA3 protein is localized in the vacuolar membrane

and promotes the transport of Cd into vacuoles of protoplasts, thus detoxifying or

storing cytosolic Cd. Further, overexpression of AtHMA3 cDNA increased tolerance

to Cd, Co, Pb, and Zn in A. thaliana transformants compared to the wild type (Morel

33

Introduction

et al., 2009). An HMA3 orthologue was characterized in N. caerulescens and shown

to be more highly expressed in metal hypertolerant ecotype Ganges than in the less

tolerant ecotype Prayon, partially due to increased genomic copy number (Ueno et

al., 2011). The protein was localized in the tonoplast membrane in shoots and

displayed high specificity for Cd transport, in yeast transport assays. NcHMA3 and

AhHMA3 share 88% identical amino acids (Ueno et al., 2011). These findings

suggest that the highly expressed HMA3 in both roots and shoot of A. halleri might

play a role in metal hyperaccumulation and/or hypertolerance.

The FRD3 gene was the second most highly expressed gene in roots of A. halleri

relative to A. thaliana in a microarray- and qRT-PCR-based study (Table 2) (Talke et

al., 2006). The function of A. thaliana FRD3 is to promote Fe solubility in both root

and shoot apoplast and to facilitate root-to-shoot Fe transport and apoplastic Fe

distribution in leaves (Durrett et al., 2007; Green and Rogers, 2004). In A. halleri,

FRD3 may have a similar function and contribute to a balanced Fe homeostasis in

tissues containing very high fluxes or levels of the heavy metals Zn or Cd, conditions

known to induce Fe deficiency in A. thaliana. An alternative hypothesis could be that

AhFRD3 contributes to the hyperaccumulation of Zn or Cd, or even mediate the

homeostasis of a different metal.

All these modifications in the metal homeostasis network enable hyperaccumulators

to survive with extraordinary amounts of metals in their above ground tissues

(Hanikenne and Nouet, 2011; Krämer, 2010). Many of the candidate genes still

remain to be functionally characterized. Their molecular and functional

characterization is necessary in order to determine whether and how they contribute

to metal hyperaccumulation and/or hypertolerance.

1.6 The role of FRD3 in metal homeostasis

A. thaliana FRD3 encodes a plasma membrane protein that belongs to the multidrug

and toxin efflux (MATE) family. MATE family proteins occur in living organisms from

all kingdoms. In plants, MATE proteins can be involved in the detoxification of

secondary metabolites (Omote et al., 2006). The A. thaliana genome alone encodes

58 members of this protein family (Hvorup et al., 2003). The transport of a wide

range of plant metabolites, such as glucosides, alkaloids, and terpenoids, across the

34

Introduction

plasma membrane and vesicular membranes mediated by different MATE proteins is

proposed to occur in short distances from source cells to neighboring cells or may

even initiate long-distance translocation to other tissues and distant organs (Yazaki,

2005). The involvement of FRD3 in Fe homeostasis of A. thaliana is well established

(Delhaize, 1996; Green and Rogers, 2004; Rogers and Guerinot, 2002). Roots of

three different frd3 mutants constitutively expressed root Fe deficiency responses

and misexpressed Fe deficiency-regulated genes in roots, such as iron-regulated

transporter (IRT1) and Ferritin (FER) (Rogers and Guerinot, 2002). These authors

showed that different frd3 mutants over-accumulate other metals, such as Zn and

Mn, in both roots and shoots, in accordance with earlier findings (Delhaize, 1996). In

wild type seedlings, the FRD3 protein is localized in the root pericycle and vascular

cylinder cells. In the frd3-1 mutant, Fe accumulated in the central vascular portion of

roots when compared to roots of wild-type seedlings (Green and Rogers, 2004). In

that study, there was no difference in shoot levels of Fe between wild type and frd3

mutants. However, in frd3 mutants intracellular levels of Fe were about 50% of the

levels found in wild-type cells, suggesting that leaf cells of frd3 mutants have less

access to apoplastic Fe for uptake into leaf cells. Xylem exudate of the frd3-1 mutant

contained significantly lower citrate levels than wild-type xylem exudate. The FRD3-

mediated cellular export of citrate was then demonstrated in Xenopus laevis oocytes.

Indeed, Fe deficiency phenotypes of the frd3-1 mutant were rescued through

external supply of citrate to the growth medium (Durrett et al., 2007). More recently,

a natural variation study using A. thaliana wild ecotypes found the FRD3 coding

region to co-localize with a Zn tolerance QTL and identified FRD3 variants affecting

enhanced or reduced Zn tolerance (Pineau et al., 2012). The variants were

associated with amino acids that potentially play a key role in the FRD3-mediated

citrate transport, since the substitutions N116S and L117P in combination abrogated

the citrate export capacity of the ecotype Shahdara. A different study addressing

transcriptional and post-transcriptional regulation of FRD3 in A. thaliana and A.

halleri found alternative transcription initiation sites in A. thaliana FRD3 promoters,

with differentially regulated transcription in response to Zn supply. Only one single

transcript variant was found in A. halleri, which displayed higher transcript stability

and was not affected by Zn supply, contrary of what was observed in A. thaliana

(Charlier et al., 2015). OsFRDL1, an AtFRD3 orthologue from rice, was functionally

characterized as plasma membrane citrate efflux transporter indispensable for the

35

Introduction

maintenance of Fe homeostasis (Yokosho et al., 2009), analogous to AtFRD3

function in A. thaliana. The soybean FRD3 orthologue GmFRD3 was shown to play a

similar role in Fe homeostasis according to preliminary evidence (Rogers et al.,

2009). Although A. halleri possesses only a single copy of AhFRD3, the transcript

levels are ~15-fold higher in roots and ~6-fold higher in shoots than in A. thaliana

(Talke et al., 2006). So far, FRD3 function has not been characterized in any metal

hyperaccumulator or hypertolerant species.

1.7 Aims of the thesis

This thesis makes a contribution to the characterization of the roles of HMA3, HMA4

and FRD3 in heavy metal hyperaccumulation and hypertolerance. The use of RNA

interference technology allowed the silencing of each of these genes separately

[lines generated and initially characterized by Dr. Ina Talke (Hanikenne et al., 2008)].

Since no knockout mutant collections are available for any hyperaccumulator

species to date, these RNAi lines constitute precious plant material for the molecular

analysis of these complex traits. Initially, the RNAi lines were cultivated on a variety

of metalliferous and non-metalliferous soils, which host natural populations of A.

halleri in the wild. Subsequently, the following questions were addressed:

- What is the contribution of each of these genes to metal hyperaccumulation

and hypertolerance in A. halleri?

- How do these candidate genes contribute to the leaf ionome or the prevention

of stress on diverse soils in A. halleri?

Based on initial results obtained in this work, a primary focus was placed on the

functional characterization of A. halleri FRD3 in comparison to its orthologue in A.

thaliana.

36

Methods

2 Material and Methods

2.1 List of Equipment

Equipment Type Brand City Country

384 multi-well PCR plates

White Roche Applied Science

Mannheim Germany

96-well plates Gamma sterilized

TPP Techno Plastic Products AG

Trasadingen Switzerland

Analytical sieve

Ø 200 mm 2 mm stainless steel

LINKER Industrie-Technik

Kassel Germany

Balances

Acculab VICON Series 0.01g

Sartorius Stedim Biotech

Göttingen Germany

Kern 470 KERN & Sohn Baligen Germany

Semi-Micro XA105 dual range

Mettler-Toledo GmbH

Giessen Germany

Benchtop magnetic stirrer

MR3002 S Heidolph Instruments Labortechnik

Schwabach Germany

Benchtop magnetic stirrer

iKamag RCT IKA WERKE Janke & Kunke

Staufen Germany

CEM Microwave

MARSXpress CEM Matthews USA

self-regulating pressure MARSXpress vessels

CEM Matthews USA

Centrifuges 5417C Eppendorf AG Hamburg Germany

Microfuge 22R

Beckman Coulter

Indianapolis USA

Ceramic beads 1.4/2.8mm zirconium oxide beads

Bertin Technologies

Montigny le bretonneux

France

Digital camera D200 Nikon Inc. Melville USA

Drying cabinet TK/L E117 Ehret Emmendingen Germany

Electric dispensing pipettes

Research Pro Eppendorf AG Hamburg Germany

37

Methods


Falcon tubes 50 mL 114x28 mm, PP

Sarstedt Nümbrecht Germany

Freeze dryer Christ Alpha 2-4 LD

SciQuip Ltd Shropshire United Kingdom

Gel documentation

Gel Doc XR+ System

Bio-Rad Laboratories GmbH

Munique Germany

Gel electrophoresis

Sub-Cell GT Cell


Munique Germany

Greiner centrifuge tubes

15 mL 120x17 mm, PP, round bottom

Sigma-Aldrich Chemie

Taufkirchen Germany

Grinding mill Precellys 24 Bertin Technologies

Montigny le bretonneux

France

Growth cabinet BB-XXL3+ CLF Plant Climatics

Wertingen Germany

Growth cabinet (sterile)

BB-XL4 CLF Plant Climatics

Wertingen Germany

HPLC system

LaChrom Elite pump L-2130, autosampler L-2200, Column oven L-2300, pre-column SecurityGard cartridge AQ C18, 4 x 3 mm ID, column SYNERGI 4u Hydro-RP 80A – 150 x 4.6 mm, diode array detector L-2450

Hitachi High Technologies America, Inc.

Schaumburg USA

Ice machine Ice flaker AF206

Scotman Ice Systems

Ipswich United Kingdom

Microplate spectrometer

FLUOstar Omega

BMG Labtech Ortenberg Germany

38

Methods


Microtubes

0.2 mL PCR single tube thin wall flat cap

Life Science Products, Inc.

Frederick USA

0.5 mL Multiply-Pro single tube with flat lid


1.0 mL Eppendorf Safe-Lock microcentrifuge tube

USA Scientific, Inc.

Ocala USA

2.0 ml Eppendorf Safe-Lock microcentrifuge tube

USA Scientific, Inc.

Ocala USA

2.0 mL Microtube PP flat


Mortar Porcelain 150 mm 56/6A

Morgan Technical Ceramics W. Haldenwanger

Waldkraiburg Germany

Optical emission spectrometer

iCAP 6500 Duo

Thermo Scientific

Waltham USA

ASX-520 Autosampler

CETAC Technologies

Omaha USA

Overhead shaker

Reax2 Heidolph Instruments Labortechnik

Schwabach Germany

Paper bags 14x6x32 cm Perga-Plastic GmbH

Walldürn-Altheim

Germany

Pestle Porcelain 55mm Diam 56/6A Glazed

Morgan Technical Ceramics W. Haldenwanger

Waldkraiburg Germany

39

Methods


pH meter

WTW pH522 WTW Scientific and Technical Workshops

Weilheim Germany

Electrode InLab semi-micro

Mettler-Toledo GmbH

Schwerzen-bach

Switzerland

Pipettes

0.2-2.0 µL 0.5-10 µL 2.0-20 µL 10-100 µL 20-200 µL 50-1000 µL

Eppendorf AG Hamburg Germany

Plastic containers

30Ltr Blue Open Top Keg

Amphorea Packaging

Cheshire United Kingdom

Real time PCR machine

LightCycler 480 II

Roche Applied Science

Indianapolis United States of America

Shaker Model 3005 GFL Burgwedel Germany

Soil CN analyzer

Vario EL cube Elementar Analysis Systems

Hanau Germany

Soil mixer Mix130 Atika Burgau Germany

Square Petri dish

120x120x17 mm with vents

Greiner Bio-One Mosonmag-yaróvár

Hungary

Thermocycler PTC-200 Peltier Dual Block


Munique Germany

Thermomixer Comfort Eppendorf AG Hamburg Germany

TPP Centrifuge tubes

15 mL 120x17.1 mm, PP, conical bottom

TPP Techno Plastic Products AG

Trasadingen Switzerland

Ultrapure water filtration

PURELAB flex ELGA LabWater, Veolia Water STI

Antony France

UV Spectrophotometer

Nanodrop 2000

Thermo Scientific/PeqLab

Erlangen Germany

Vertical laminar flow cabinet

Fortuna clean air

Scanlaf A/S Lynge Denmark

Vortex Genie 2 SI Scientific Industries, Inc.

New York USA

40

Methods

2.2 Plant material and growth conditions

A. halleri (L.) O’Kane and Al-Shehbaz ssp. halleri [Langelsheim accession – (Lan)]

and A. thaliana (L.) Heynhold (accession Columbia) were used as wild type. Two

additional control lines were used for A. halleri experiments: one F1 plant – obtained

from a cross between Lan 3.1 and Lan 5 genotypes – regenerated from tissue

culture following mock transformation (TC) and a F1 plant that was transformed with

a cauliflower mosaic virus (CaMV) 35S promoter-GUS-intron construct (Vancanneyt

et al., 1990). The 35S-GUS transformant line served as a control for the plant

transformation, by showing that the insertion of a DNA construct bearing an

exogenous gene did not affect the transcription of the candidate genes analyzed or

plant performance. This line was named TrC. The Langelsheim accession of A

halleri was the background for the HMA3-, HMA4- and FRD3-RNAi lines. The A.

thaliana frd3-1 is an ethyl methane sulfonate (EMS) mutagenized mutant in the Col-0

background. Seeds of the frd3-1 mutant were kindly provided by Dr. Mike Haydon. A.

thaliana Col-0 transgenic plants transformed with genomic AhFRD3 and

35S:AhFRD3 constructs (Appendix B.7-8 and C.1-2) were also used.

For the generation of A. halleri RNAi lines, gateway-compatible binary vectors

bearing RNAi constructs generated with short Polymerase Chain Reaction (PCR)

fragments of AhHMA3, AhHMA4, AhFRD3 were used for gene silencing. All

constructs were generated by Dr. Ina Talke and introduced by her into A. halleri

using Agrobacterium tumefaciens-mediated stable transformation as essentially as

described in Hanikenne et. al. (2008). In brief, short PCR amplified fragments from

the coding DNA sequence (CDS) of each gene (331-bp long fragment of AhHMA3,

457-bp long fragment of AhHMA4, 441-bp long fragment of AhFRD3) (appendix B.2,

B.4 and B.6) were subcloned into pK7GWIWG2(I) (for HMA3-RNAi) and pJawohl8-

RNAi (for both HMA4-RNAi and FRD3-RNAi), respectively. Details of fragments,

vectors, and constructs are given in the Appendix C.1-2.

Using the floral dip method (Clough and Bent, 1998), A. thaliana Col-0 was

transformed with the genomic AhFRD3 (gAhFRD3 lines, a 4881-bp long genomic

AhFRD3 fragment, from the Langelsheim accession of A. halleri in pMDC100

vector), an AhFRD3 overexpression construct (35S:AhFRD3, an 1,867-bp long

cDNA fragment in pB7WG2 vector), and an overexpression construct of the AhFRD3

translationally fused to a triple human influenza hemagglutinin (HA) protein tag

41

Methods

(35S:AhFRD3:HA, an 1,867-bp long cDNA fragment fused to the HA-encoding

sequence into pGreen35S vector) (Appendix B.8 and C.1). All constructs were

generated by Dr. Mark Hanikenne, who also transformed the plants. The first screen

for transformed seedlings and single-locus insertion was performed by Norman

Ertych, on 0.5x Murashige and Skoog (MS) medium using the following

concentrations of antibiotics: 50 µg mL-1 Kanamycin and 25 µg mL-1

Phosphinothricin, until the T3 generation. Further propagation to the T4 generation

was carried out by self-pollination until no segregation of antibiotic resistance was

observed.

2.2.1 Soil experiments with A. halleri

Wild type and RNAi plants of A. halleri were maintained in the glasshouse under

ambient light conditions with supplemental lighting (400 Watt Son-T Agro bulbs,

Philips, Belgium) and 10 h light / 22°C day and 14 h dark 20°C night. Vegetatively

propagated clones were prepared by making cuttings placed onto 1:1 (v/v) soil/sand

mixture in climate-controlled growth chambers (BB-XXL 3+ GroBank) for rooting

during three weeks, and thereafter transplanted onto a 1:1 (v/v) mixture of native soil

from A. halleri sites and Vermiculite (Dämmstoff GmbH, Sprockhövel, Germany) for

another five weeks under the same conditions. Plant growth was carried out in short

days 10 h light / 22 °C day and 14 h dark / 20 °C night with 90 µmol m-2 s-1 light

intensity (Master TL-D 58W/840 Reflex and Master PL-L 18W840/4P lamps, Philips,

Hamburg, Germany).

Seven different soils collected at sites where A. halleri accessions grow naturally

were used for soil experiments. Four of these soils are metalliferous and three non-

metalliferous. Locations of soil collection are given in Table 3. More information

about each of the sites for soils collection is given in Figures S1-S7. Before use, 1:1

mixture of each soil with Vermiculite was prepared using a concrete mixer for 10 min.

42

Methods

Table 3 Location of soil collection for controlled experiments.

Location/City GPS coordinate Status District Country

Langelsheim N 51.94870° E 010.34884°

Metalliferous Goslar Germany

Littfeld N 51.00540°

E 008.006606° Metalliferous

Siegen-Wittgenstein

Germany

Evín-Malmaison N 50.42945° E 003.02304°

Metalliferous Pas-de-Calais France

Bestwig N 51° 18.525' E 008° 24.578'

Metalliferous Hochsauerland Germany

Malmedy N 50° 29.724' E 006° 04.156'

Nonmetalliferous Liège Belgium

Wehbach N 50° 48' 49.8'' E 007° 50' 56.3''

Nonmetalliferous Altenkirchen Germany

Rodacherbrunn N 50° 25.597' E 011° 33.561'

Nonmetalliferous Saale-Orla-Kreis Germany

Directly before the initiation of the treatments, whole plant fresh biomass was

recorded after carefully washing out soil by submerging the roots in deionized water,

with additional very gentle agitation when necessary, and blotting dry with tissue

paper. After five weeks of treatment, soil from roots was removed in the same

manner and whole plant, shoot and root fresh biomass were recorded. Shoots were

then washed at least three times in ultrapure water, and all leaves were excised and

gently blotted dry with tissue paper. Leaves were placed in 50 mL Falcon tubes,

immediately frozen in liquid nitrogen and stored at -80 °C until use. The samples

were used for measurements of: multi-element concentrations by inductively-coupled

plasma optical emission spectrometry (ICP-OES), concentrations of chlorophyll, lipid

peroxidation by quantifying TBARS, anthocyanin, and hydrogen peroxide by

spectrophotometry, and quantification of transcript levels of specific genes.

Samples were ground by using a chilled 1.3 cm glass marble per Falcon and

vortexed for around 2 minutes (cycles of 15 s vortex, 10 s in liquid nitrogen). Tissue

samples were never in direct contact with liquid nitrogen, to minimize the introduction

of air moisture into the sample during the manipulation. Tissues from each individual

plant were sampled immediately after grinding: 300 mg frozen tissue for ICP-OES,

50 mg frozen tissue for TBARS, anthocyanin, and hydrogen peroxide measurements

and 20 mg frozen tissue for chlorophyll determination, all from the same sample.

43

Methods

An additional experiment with wild type and FRD3-RNAi line 18.2 grown on

Langelsheim soil was performed for multi-elemental mapping using particle-induced

X-ray emission (µPIXE). The experimental set up was the same as described above.

Three leaves per genotype were sampled for the analysis as described in Methods

section 2.4.2.6.

2.2.2 Hydroponic experiments with A. halleri

Clones of wild type and FRD3-RNAi line 18.2 plants were initially rooted in 0.1x

modified Hoagland medium for two weeks and then transferred to 0.25x modified

Hoagland (Table 4) buffered to pH 4.0 with sodium acetate-acetic acid and

supplemented with 40 µM Pb acetate (‘Pb treatment’) for an additional two weeks.

Growth medium was changed each day. Temperature, light and humidity settings

were the same as described above for A. halleri cultivation. Before harvesting, plants

were covered overnight with a plastic lid for root pressure generation by the plants

and, consequently, enhance the amount of xylem exudation. Xylem exudate was

collected for organic acid analysis (details in Methods section 2.5). Leaves and roots

were harvested for the measurements of multi-element concentration and root

surface Fe(III) chelate reductase activity (see Methods sections 2.4.1 and 2.4.2.5 for

details). Root tissues used for multi-element quantification by ICP-OES were

desorbed before the analysis (desorption protocol is also described in the section

2.4.1).

44

Methods

Table 4 Composition of modified 0.25x Hoagland medium (Hoagland and Arnon 1950; Becher et al. 2004).

Stock Solution Final Concentration Stock volume used

for 1 L solution

1 M Ca(NO3)2 1.5 mmol L-1 1.5 mL

1 M KH2PO4 0.14 mmol L-1 0.14 mL

1 M MgSO4 0.75 mmol L-1 0.75 mL

1 M KNO3 1.25 mmol L-1 1.25 mL

1000 X stock mix

0.5 mM CuSO4 0.5 µmol L-1

1 mL

1.0 mM ZnSO4 5.0 µmol L-1

5.0 mM MnSO4 5.0 µmol L-1

25 mM H3BO3 25.0 µmol L-1

0.1 mM Na2MoO4 0.1 µmol L-1

50 mM KCl 0.1 µmol L-1

5.0 mM Fe-HBED* 5.0 µmol L-1 1 mL

Buffer

0.2 M (NaOAc-HOAc) pH 4.0 0.6 mmol L-1 3 mL

* N,N’-Di(2-hydroxybenzyl)ethylenediamine-N,N’-diacetic Acid.

2.2.3 Soil experiments with A. thaliana

Seeds of wild-type Col-0, frd3-1 mutant and transgenic lines were germinated on

compost [3:1:1 (v/v) mixture compost/sand/pumice] for three weeks in a climate-

controlled growth chamber (BB-XXL 3+ GroBank) under short-day conditions

(described above in section 2.2.1), and subsequently transplanted onto a mixture of

1:4 (v/v) Langelsheim soil and compost for an additional period of five weeks (‘heavy

metal treatment’). Six individuals per genotype were used in these soil experiments,

which were repeated two times independently. Transplanting, washing, and

harvesting procedures were followed as for A. halleri plants (described above in

section 2.2.1). Shoots were harvested, washed, blotted dry with tissue paper and

only leaves were excised, using scissors, for multi-element analysis as described

below in section 2.4.1.

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2.2.4 Plate experiments with A. thaliana

Thirty seeds of wild-type Col-0 and frd3-1 (15 seeds each) were germinated on 12

cm square Petri dish plates containing 60 mL of modified hydroponic Hoagland

solution (low phosphate 0.14 mM KH2PO4) supplemented with 1% (w/v) sucrose

(Carls Roth, Karlsruhe, Gemany) and 1% (w/v) Agar Type M (Sigma-Aldrich Chemie,

Taufkirchen, Germany). The altered pH of 4.0 was found experimentally, within a pH

range from 4.0 to 6.0, to maintain both the plants’ morphological appearance and

leaf mineral profiles similar to plants grown on the commonly used Hoagland media.

For Pb treatment, Pb acetate (Merck KGaA, Darmstadt, Germany) was added at the

following concentrations: no Pb (control), 1 µM, 5 µM, 25 µM and 50 µM. Seeds were

vapor-phase sterilized for 3 h with chlorine gas, produced by the addition of 5 mL

37% (w/v) HCl (VWR chemicals, Darmstadt, Germany) in 150 mL 13% sodium

hypochlorite (AppliChem, Darmstadt, Germany). The sterilization was performed

inside a vacuum chamber (without vacuum) in a fume hood. After sterilization, seeds

were soaked in ultrapure water for 60 min before plating. Seeds were plated

individually along a horizontal line at ~ 0.5 cm distance using a sterile Pasteur glass

pipette. Thereafter, plates were stratified at 4 °C in the dark for 48 h and then

transferred into a climate-controlled growth chamber (BB-XL 4 Sterile GroBank).

Sterile plant growth was carried out in a long-day cycle (16 h light/22 °C and 8 h

dark/18 °C, and 60% humidity) under 120 µmol m-2 s-1 light intensity (Master TL-D

36W/840 Reflex and Master TL-D 18 W/840 Reflex lamps, Philips, Hamburg,

Germany).

The experimental design comprised 15 plates in total for one independent

experiment. Each treatment was replicated on three plates, and each plate was

considered one replicate, with pooling of tissues for biomass from seedlings in the

same plate. Each experiment was repeated two times independently. Sterile plant

growth was performed on vertically-oriented plates for 16 days.

At the end of the experiment, plates were photographed for recording the

appearance of seedlings and for the measurement of root length. Root length was

measured individually for 10 seedlings per genotype in each plate, using ImageJ

1.46r (Schneider et al., 2012). Fresh biomass was recorded for the pool of these 10

seedlings per genotype, followed by the separation of tissues into shoots and roots

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Methods

before the desorption procedure (see section 2.4.1 for desorption protocol). The

remaining five seedlings per genotype were pooled and separated into shoots and

roots for the measurement of chlorophyll concentrations (only in shoots) and root

surface Fe(III) chelate reductase activity (only in roots). From all plates, seedlings at

the same position were used for the analyses as follows: ten outermost seedlings of

each genotype were used for root length and multi-element analysis; five centermost

seedlings of each genotype were used for determination of chlorophyll concentration

and for the quantification of root surface Fe(III) chelate reductase activity.

One additional assay was performed to test the tolerance of frd3-1 mutant to Pb

alongside the wild type and Pb hypersensitive mutant cad1-3 mutant using the

modified low-phosphate/low-pH (LPP) medium (Fischer et al., 2014) (Table 5) with

additional 40% of micronutrient concentrations used in 0.25x Hoagland medium. Pb

treatments were carried out by adding 5 µM and 10 µM Pb acetate to culture media.

The temperature, light and humidity settings were the same as described above,

however seedlings were grown for 20 days because plant growth on this media is

slower than usually.

Table 5 Composition of 1x low-phosphate/low-pH (LPP) medium (Fischer et al. 2014) with addition of micronutrients.

Stock Solution Final Concentration Stock volume used

for 1 L solution

1 M Ca(NO3)2 280 µmol L-1 280 µL

1 M (NH4)2PO4 10 µmol L-1 10 µL

1 M MgSO4 200 µmol L-1 200 µL

1 M KNO3 600 µmol L-1 600 µL

1 M NH4NO3 90 µmol L-1 90 µL

1000 X stock mix

0.5 mM CuSO4 0.5 µmol L-1

400 mL

1.0 mM ZnSO4

2.6 µmol L-1

5.0 mM MnSO4 5.0 µmol L-1

25 mM H3BO3 25.0 µmol L-1

0.1 mM Na2MoO4 0.1 µmol L-1

50 mM KCl 0.1 µmol L-1

5.0 mM Fe-HBED 5.0 µmol L-1 1 mL

Buffer

1 M MES-KOH pH 5.0 5 mmol L-1 5 mL

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Methods

2.3 Plant genotyping

2.3.1 DNA extraction

A modified simple and rapid method for DNA extraction PCR (Edwards et al., 1991)

was used for plant genotyping. Young leaves were harvested in liquid nitrogen and

ground in a 1.5 mL microtube using a mix of 1.4mm and 2.8mm ceramic beads in

Precellys 24 (Bertin Technologies) at 6,500 rpm for 20 s. A total of 50 mg (FW)

frozen leaf material was mixed with 400 µL extraction buffer [200 mM Tris HCl pH

7.5, 250 mM NaCl, 25 mM ethylen-diamine tetraacetate (EDTA), (w/v) 0.5% SDS]

and vortexed for 5 s. The mixture was centrifuged at 13,000 rpm for 1 min to

sediment tissue debris. In a new tube, 300 µL of the supernatant was mixed with the

same volume of isopropanol, inverted 4 times and left at room temperature for 2 min,

in order to precipitate the DNA. A centrifugation at 13,000 rpm for 5 min was

performed for pelleting the DNA, and the supernatant was discarded. The pellet was

dried at room temperature for 10 min. The pellet was resuspended with 25 µL

ultrapure water, centrifuged at 13,000 for 20 s, and only the clear supernatant was

transferred to a new tube for PCR analysis. In our hands, this DNA was suitable for

reproducible genotyping by PCR after storage at -20 °C for four years.

From each DNA preparation, 2 µL were used for quantification by photometric

analysis of the ratio A260/A280 in NanoDrop 2000 Spectrophotometer (Life

Technologies GmbH, Darmstadt, Germany). A total of 300 ng genomic DNA (gDNA)

preparation was used in a 10 µL PCR reaction containing: 7.3 µL ultrapure water, 1

µL 10x buffer, 0.25 µL MgCl2, 0.2 µL deoxyribose nucleoside triphosphate (dNTPs),

0.5 µL of 10 µM primer mix (forward and reverse) (Table 6), 0.25 u of RedTaq

polymerase (Sigma-Aldrich Chemie GmbH, Taufkirchen in Munique, Germany), and

0.5 µL DNA preparation as template. PCR was performed in a thermocycler DNA

Engine Peltier Thermo Cycler with the following program: 95 °C 5 min pre-

denaturation, 35 cycles of 95° C 45 s denaturation, 60 °C 30 s annealing, 72 °C 1

min elongation, and 72 °C 10 min final elongation. Three µL PCR products were

used for verification of the amplicon size in 1% (w/v) agarose gel stained with SYBR-

Safe DNA (Life Technologies, Darmstadt, Germany) to a final dilution of 1:20,000.

PCR samples were mixed with 1x loading dye (PEQLAB, Erlangen, Germany) in

order to render the samples denser than the running buffer and to monitor the gel

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Methods

electrophoresis procedure. The gel was run for 30 min at 100 V in 1x Tris-acetate-

EDTA buffer (TAE, 40 mM Tris, 20 mM acetic acid, 1 mM EDTA, pH 8). The

documentation of the gel was performed in a Gel Doc XR+ system.

2.3.2 Quantification of relative transcript levels

Between 20 mg and 50 mg (A. halleri) and 100 mg (A. thaliana) of fresh tissue was

homogenized in a 1.5 mL microtube using a mix of 1.4mm and 2.8 mm ceramic

beads in the Precellys grinding mill at 6,500 rpm for 10 s (repeated twice). Total RNA

of root or shoot tissues was extracted using RNeasy plant mini kit (Qiagen, Hilden,

Germany) following the manufacturer’s recommendations. Two µL were used for

quantification and spectrophotometric analysis of the A260/A280 ratio in NanoDrop

2000 Spectrophotometer. RNA integrity was checked in 1% (w/v) agarose gel (as

described above) using 1.5 µg of total RNA. cDNA synthesis was performed using

0.75 µg of total RNA together with oligo (dT18) primers (final concentration of 10 µM),

1 µM of dNTP mix containing dATP, dCTP, dGTP, dTTP and 200 u RevertAid™ H

minus M murine leukemia virus reverse transcriptase cDNA Synthesis Kit (Life

Technologies GmbH, Darmstadt, Germany).

For quantitative real time PCR, diluted cDNA (1:50 v/v in ultrapure water) was used

for relative transcript level determination. Each reaction consisted of 5 µL 2x SYBR

Green Master Mix, 1 µL of 5 µM forward and reverse primer mix (2.5 µM each)

(Table 6) and 4 µL of diluted cDNA. The reactions were performed in 384-well plates

for SYBR Green Master Mix (Applied Biosystems) on a LightCycler®480 II System

(Roche) with the following cycling program: initial denaturation at 95 °C for 5 min, 40

cycles at 95 °C for 1 min and at 60 °C for 1 min, followed by final elongation at 60 °C

for 10 min and melting curve phase starting at 95 °C with a ramp rate of 0.11 °C s-1.

Melting curve analysis was performed for each plate to unsure that primers were

specific by amplifying only a single PCR product. For the quantification of transcript

levels, the reaction efficiencies (re) and cycle thresholds (CT) were determined using

linregPCR software (Ramakers et al., 2003). The threshold signal was set at 0.2

arbitrary fluorescence units. Transcript levels of each gene of interest (GOI) were

calculated relative to a constitutively expressed endogenous control gene

[housekeeping (HK)] using the following formula: ∆𝐶𝑇 = 𝑟𝑒(𝐺𝑂𝐼)−𝐶𝑇(𝐺𝑂𝐼)/

𝑟𝑒(𝐻𝐾)−𝐶𝑇(𝐻𝐾) (Czechowski et al., 2005). As HK genes were used the Elongation

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Methods

Factor 1α (EF1α, At5g60390) for GOIs of high expression and Helicase (HEL,

At1g58050) for GOIs of low expression. The arithmetic mean and standard deviation

(SD) of relative transcript levels for one GOI were calculated from at least three

independent quantifications. Each quantification data point was a result of two qRT-

PCR reactions from the same cDNA per plate.

Table 6 List of primers used for plant genotyping and quantification of transcript levels.

Primer name Sequence (5’-3’) Purpose Technique

pK7-P35s-F caaccacgtcttcaaagcaagtgg genotyping PCR

pK7-intron-R ggtggcacttgttggtatgagac

pJaw-intr-f catcttgacaatgaatcgtgatcgg genotyping PCR

HMA4-rnai-r caccttcatcgctgcagcaac

pJaw-intr-r ccgatcacgattcattgtcaagatg genotyping PCR

FRD3-rnai-r cacctgctgtggctggttgg

Ah/At-HMA3-f taacgatgccccggcttta Transcript levels

qRT-PCR Ah/At-HMA3-r ttgcaagtgctgaccctgaga

HMA4-qrt-ah-f tgaaggtggtggtgattgca Transcript levels

qRT-PCR HMA4-qrt-ah-r tccacattgcccaacttcg

FRD3_Ah_f04 aatgatggtcttgccgttg Transcript levels

qRT-PCR FRD3_Ah_r04 tgcatcccgtgttctacag

frd3-at-qrt-f2 cgatattcccacttgtgagcc Transcript levels

qRT-PCR frd3-at-qrt-r2 ttctccatcgtgtcttcctctg

FER1_At_qRT_f ccgccgctaatcccgctctg Transcript levels

qRT-PCR FER1_At_qRT_r aacgaccactgctctgccgc

FRO3_At_qRT_f gattctactggcttctcttgg Transcript levels

qRT-PCR FRO3_At_qRT_r ctaatccggccttcactaac

OPT3_At_qRT_f ctcgatgcagggaccgcgtt Transcript levels

qRT-PCR OPT3_At_qRT_r ttccaggagccgtgggacagg

2.4 Analyses of plant tissues

2.4.1 Multi-element analysis

For leaf tissues from soil-grown plants, shoot and root tissues from plate

experiments and leaf and root tissues of hydroponically-grown plants, the

concentrations of multiple elements were measured by ICP-OES. For tissues which

were in direct contact with the growth medium (shoots and roots of plate

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Methods

experiments, and roots of hydroponic experiments), desorption was performed in

each independent sample or sample pool to remove apoplastically bound cations

using the following steps performed in Falcon tubes on ice: (a) incubation of sample

for 10 min in 50 mL ice-cold desorption solution with gentle shaking; repeat step (a)

two more times; (b) rinse roots for 1 min in ice-cold 50 mL ultrapure water with gentle

shaking; repeat step (b) and blot dry. The desorption solution for Pb experiments

was experimentally established [5 mM Ca(NO3)2, 10 mM Na2EDTA, buffered to pH

4.0 by addition of 0.6 mM sodium acetate (NaOAc-HOAc)] by comparison with

commonly used desorption solution (5 mM CaCl2, 1 mM MES-KOH, buffered to pH

5.7). In a desorption test prior to the experiments, 80% of the Pb concentration was

removed from desorbed samples when compared to non-desorbed ones. After

desorption, samples were dried at 70 °C in a drying cabinet for 48 h followed by 24 h

at room temperature, for equilibration under ambient humidity conditions. Samples

that did not need to be desorbed were dried and equilibrated at room temperature as

described.

Between 1 mg and 20 mg of dry tissue were placed into one perfluoroalkoxy alkanes

(PFA) vessels (MARSXpress, Matthews, USA) and 3 mL 65% (w/w) HNO3 was

added. Samples were carefully mixed by gentle shaking and vessels were closed

with screw lids containing self-regulating pressure vent plugs. Digestion was

performed in a CEM microwave for 50 min (15 min ramp to 190 °C, and 15 min

digest at 190 °C, and 20 min cooling to room temperature). Digested samples were

transferred into a 15 mL polypropylene centrifuge tube (TPP, Trasadingen,

Switzerland). Vessel walls and lids were rinsed twice with 3.5 mL ultrapure water to

remove digest remains. Samples were cooled to room temperature and volumes

were adjusted to 10 mL with ultrapure water. Subsequently, samples were filtered

through Whatman cellulose filter n° 595½ (GE Healthcare Life Sciences, Solingen,

Germany). Element concentrations were measured in the samples by ICP-OES

immediately, or following storage at 4 °C. If necessary, samples were diluted by

adding 6.5% (w/w) HNO3.

Liquid samples were introduced into the plasma of the ICP-OES instrument (iCAP

6500 Duo) as an aerosol using a concentric glass nebulizer (Thermo Scientific,

Waltham, MA, USA). Emission was measured at wavelengths given in Table 8 and

Table 10. The quantification of Ca and K was executed through radial observation of

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Methods

the plasma, whereas all the other elements were quantified axially. Series dilution

standards from analytical grade chemicals (Bernd Kraft, Duisburg, Gemany) were

used to calibrate the instrument for accurate quantification of each element.

Concentrations range of standards is given in Table 8 and Table 10. A solution of

6.5% (w/w) HNO3 was used as the blank. Quality Control (QC) was performed using

an intermediate calibration standard (n° 3 of 5), a certified reference material (Polish

Virginia Tobacco Leaves, INCT-PVTL-6, Warsaw, Poland) and the blank before and

after the measurement of the samples as well as after every 40 samples. The

instrument was set up with camera temperature at -47 °C, optics temperature at 38

°C, plasma power at 1150 W, nebulizer at 0.5 L min-1, cooling gas at 12 L min-1, and

auxiliary gas at 0.5 L min-1 (for A. thaliana samples), 1.0 L min-1 (for A. halleri

samples), and 1.5 L min-1 (for soil samples).

Element concentrations were calculated as follows:

Metal concentration (µg g-1) = ICP outcome (µg mL

-1)*volume (mL)*dilution factor*1,000

DW (mg)

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Methods

Table 7 Composition of calibration standards for ICP-OES analysis of plant samples.

Concentration (µg mL-1)

Element Standard 1 Standard 2 Standard 3 Standard 4 Standard 5 wavelength

B 0.05 0.1 0.2 0.6 - 249,7

Ca 10 20 40 250 350 318,1

Cd 0.1 0.25 0.6 2.5 10 228,8

Co 0.005 0.01 0.02 0.05 0.1 228,6

Cr 0.005 0.01 0.02 0.05 0.1 205,5

Cu 0.005 0.02 0.1 0.2 0.5 324,7

Fe 0.15 0.05 0.5 2 10 238,2

K 10 50 150 250 - 766,4

Mg 2.5 5 10 50 100 279,0

Mn 0.05 0.1 0.2 1 4 257,6

Mo 0.005 0.01 0.02 0.1 0.5 202,0

Ni 0.025 0.1 0.4 2 8 231,6

P 1 5 10 20 40 185,9

Pb 0.025 0.1 0.4 2 8 220,3

S 1 5 10 20 40 182,0

Se 0.05 0.1 0.2 0.5 1 196,0

Zn 0.1 0.5 2.2 10 50 606,2

2.4.2 Determination stress parameters

2.4.2.1 Determination of lipid peroxidation products

The method for malondialdehyde (MDA) quantification with corrections for interfering

compounds was used for the quantification of lipid peroxidation by the TBARS assay

(Hodges et al., 1999). Five hundred µL of 80% (v/v) ethanol were added into a 1.5

mL reaction tube containing 50 mg of frozen leaf powder and the suspension was

vortexed for 10 s. The sample was centrifuged at 10,000 rpm for 2 min at room

temperature. A 200 µL aliquot of the upper aqueous phase was added to a new 2.0

mL screw cap micro tube (Sarstedt, Nümbrecht, Germany) containing 200 µL of the

reaction mix with either +TBA solution [40 µL of 100% (w/v) trichloroacetic acid

(TCA), 20 µL of 0.1% (w/v) BHT, 130 µL of 1% (w/v) TBA, and 10 µL of ultrapure

water] or –TBA solution [40 µL of 100% (w/v) TCA, 20 µL of 0.1% (w/v) BHT, and

140 µL of ultrapure water]. Samples were mixed vigorously by vortexing for 5 s and

incubated at 95°C for 25 min in a thermomixer with shaking at 1,600 rpm each 12

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Methods

min. Samples were cooled down at room temperature for 5 min and centrifuged at

3,000 rpm for 10 min. Aliquots of 200 µL of each supernatant were used for

recording the absorbance at 440 nm, 532 nm, and 600 nm using a microplate reader

spectrophotometer (BMG Labtech, Ortenberg, Germany). The blank was used by

adding 200 µL 80% (v/v) ethanol to +TBA and –TBA solutions. MDA equivalents

were calculated as follows:

1) [A532(+TBA) - A600(+TBA) - A532(−TBA) - A600(−TBA)] = X

2) (A440(+TBA)-A600(+TBA) * 0.0571] = Y

3) MDA equivalents (nmol mL-1) = X-Y

157000 * 10

6 * 0.5

2.4.2.2 Determination of anthocyanin concentrations

The concentration of total anthocyanins was measured following extraction of leaf

anthocyanins from 50 mg of frozen leaf powder with 2 mL methanol and HCl.

Volumes of 2 mL 100% (v/v) methanol containing 1% (v/v) 37%HCl were added to

each sample followed by vortexing for 10 s. Micro tubes were placed in a cardboard

box and left to extract at 4 °C in the dark overnight. Samples were centrifuged at

14,000 rpm for 1 min and 200 µL of the supernatant were used for recording the

absorbances at 536 nm and 600 nm using a microplate spectrophotometer (BMG

Labtech, Ortenberg, Germany). An aliquot of 200 µL 100% (v/v) methanol containing

1% (v/v) HCl was also incubated overnight for use as the blank. Total anthocyanin

concentrations were expressed as cyanidin 3-glucoside equivalents, using the molar

extinction coefficient ε = 33,000 (Wellmann et al., 1976) and calculated as follows:

Total anthocyanins (µmol g FW-1) = A536 - (0.33 ∗ A600)/FW.

2.4.2.3 Determination of chlorophyll concentration

Concentrations of chlorophylls were measured after the extraction of chlorophyll from

leaf material with methanol. Subsamples of 20 mg frozen leaf powder were used for

total chlorophyll (Tchl) extraction upon the addition of 2 mL 100% (v/v) methanol as

follows: incubation at 70 °C for 15 min with 10 s shaking every 5 min, and

subsequent incubation on ice for 5 min. Samples were covered with aluminum foil

during the incubation and were exposed to light as little as possible during the

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Methods

extraction. An aliquot of 100% (v/v) methanol was also incubated for use as the

blank. Samples were centrifuged at 14,000 rpm at 4 °C for 1 min, and 200 µL of the

supernatant were used to record the absorbances at 652 nm and 665 nm (Porra et

al., 1989) in a microplate reader spectrophotometer (BMG Labtech, Ortenberg,

Germany). Chlorophyll a (Chl a) and chlorphyll b (Chl b) and total chlorophyll

concentrations were determined in µg mL-1 and converted into mg g FW-1 using the

following calculations:

Chl a = (16.29 * A665 - 8.54 * A652) * 2

mg FW

Chl b = (30.66 * A652 - 13.58 * A665) * 2

mg FW

Tchl = (22.12 * A652 + 2.71 * A665) * 2

mg FW

2.4.2.4 Estimation of H2O2 concentrations

The H2O2 concentrations in leaf tissues were measured after the reaction of leaf

extract with KI (Sigma-Aldrich Chemie, Taufkirchen, Germany). Subsamples of 50

mg frozen leaf powder were used for extraction in 0.5 mL 0.1 % (w/v) TCA. Samples

were vortexed for 15 s, followed by centrifugation at 12,000 rpm for 15 min at 4 °C.

Subsequently, 0.25 mL of the cleared supernatant was mixed with 0.25 mL 0.1 M

potassium phosphate buffer pH 7.0 and 1 mL of 1 M KI. The samples were mixed by

inversion three times and incubated at room temperature in the dark for 1 h. An

aliquot of 200 µL for each sample was used to record the absorbance at 390 nm

using a microplate spectrophotometer (BMG Labtech, Ortenberg, Germany). An

aliquot of 200 µL 0.1 % (w/v) TCA was added to the reaction mix and used as the

blank. The concentrations of H2O2 in µmol g-1 FW was calculated by fitting the

absorbance of each individual sample to a linear regression (Y = 0.011x + 0.0459, R²

= 0.98) generated from the absorbance of a dilution series of known concentrations

of H2O2 alongside each of the measurements (VWR Chemicals, Darmstadt,

Germany) (Alexieva et al., 2001).

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Methods

2.4.2.5 Quantification of Fe deficiency responses

Root surface Fe(III) chelate reductase activity was quantified for hydroponically-

grown A. halleri plants (described above in section 2.2.2) and for A. thaliana

seedlings grown on agar-solidified media in vertically-oriented square plates

(described above in section 2.2.4). Roots of individual A. halleri plants were excised,

carefully rinsed with ultrapure water and incubated in the dark for 30 min in 1 mL of a

solution containing 0.1 mM Fe(III)NaEDTA and 0.3 mM Ferrozine [3-(2-pyridyl)-5,6-

diphenyl-1,2,4-triazine-4’,4”-disulfonic acid] (Sigma-Aldrich Chemie, Taufkirchen,

Germany) in ultrapure water (Yi and Guerinot, 1996). For A. thaliana, roots of five

seedlings per plate were excised and pooled for each assay. Absorbance at 562 nm

was recorded using a microplate spectrophotometer (BMG Labtech, Ortenberg,

Germany) to calculate the amount of Fe(II) formed using the molar extinction

coefficient of 28.6 mM-1 cm-1 (Gibbs, 1976).

2.4.2.6 Quantitative mapping of elements by Particle-Induced X-ray Emission

(µPIXE)

Experiments were performed in two different nuclear microprobe facilities. Beamtime

was granted through proposal acceptance from the French Nuclear Microprobe at

the Atomic Energy Commission in Saclay (Paris-Saclay, France) and from the

Multidisciplinary Applications of Ion Beam in Aquitaine Region (AIFIRA) platform in

the Center for Nuclear Studies of Bordeaux-Gradignan (Bordeaux, France), both

granted to Dr. Camille Larue. At least three replicates were analyzed for each

genotype. One replicate consisted of one sample from independent plants. Data

acquisition was performed under vacuum, which implies that samples were imaged

in a vacuum-dehydrated state.

For the elemental mapping of whole-mount leaves, leaf samples were excised from

soil-grown A. halleri plants (described above in section 2.2.1), thoroughly rinsed with

ultrapure water, placed on a sample holder with a flat surface (custom-made by the

workshop of each nuclear microprobe facilities) and freeze-dried under 0.030 mbar

with a condenser at -85 °C for 48 h (Christ Alpha 2-4 LD Freeze Dryer, Shropshire,

United Kingdom).

The data treatment was performed in three steps: (i) design of elemental maps and

definition of regions of interest (ROIs); (ii) determination of matrix composition; (iii)

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Methods

elemental quantification. During data acquisition, PIXE spectra were saved

simultaneously with Rutherford Backscattering (RBS) data for each single pixel of

the map. In (i), the PIXE spectra of the scanned samples were processed using the

software Supavisio (http://barbotteau.software.informer.com) and RISMIN (Daudin et

al., 2003) in order to draw elemental maps. In the maps, ROIs were chosen for

elemental quantification in specific areas, for instance vein, interveinal space,

trichome, and trichome base for leaf tissues. Extraction of the spectra from the

specific ROIs was performed subsequently.

In (ii), the RBS spectra were fitted in order to determine the matrix composition of

either the whole sample or the ROIs by using SIMNRA software (Mayer, 1997). It

permits to determine elemental composition of the light matrix (H, C, N, O, K, Ca) –

since X-rays from these elements cannot be detected by PIXE – and the sample

thickness. The measurements of PIXE coupled with RBS enable the acquisition of

fully quantitative results when compared to semi-quantitative results generated by

other imaging techniques (Ramos et al., 2013).

In (iii), the extracted data from step (ii) were uploaded into the Gupix software

(Campbell et al., 2000), which was used to identify all elements (from Na to U)

present in the samples and their respective ROIs, and also to determine the

concentrations for each element.

2.5 Xylem exudate analysis

Shoots of hydroponically-grown A. halleri and soil-grown A. thaliana plants were

excised between 0.5 cm and 1 cm above the roots with sharp a razor blade, and

xylem sap was collected using a 0.5-10 µL micropipette and 0.5-20 µL tips

(Eppendorf, Hamburg, Germany) for 2 h. The first drop of xylem exudate was blotted

dry with tissue paper to avoid contamination by the content of damaged cells.

Exudates were transferred to sterile 0.5 mL microtubes which were kept on ice

continuously and later stored at -20 °C until further analysis by high pressure liquid

chromatography (HPLC).

An HPLC system (Hitachi High Technologies, Schaumburg, USA) was used with a

running buffer of 25 mM potassium phosphate (pH 2.2) and isocratic conditions, at

0.5 mL min-1 flow rate, 20 °C column temperature and detection at 210 nm. The

running buffer was filtered (Whatman NC45, 0.45 µm, filter membrane) and then

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Methods

degassed under vacuum with ultrasound for 15 min before use. Prior to injection,

each sample was mixed with 7 µL of 250 mM running buffer, 7 µL of glutaconic acid

(internal standard), and ultrapure water was added to final volume of 70 µL. The

solution was vortexed for 5 s, centrifuged briefly and left to stand for 30 min at room

temperature. Samples were then filtered by centrifugation through Corning Costar

Spin-X columns for 1 min at 10,000 rpm, and 50 µL were injected into the HPLC

system. Standard compounds used are given in Table 8. The concentrations of

organic acids in xylem exudates in µM were calculated by fitting the absorbance of

each individual sample to a linear regression respective to each standard compound,

which were generated from the absorbance of standard compounds dilution series of

0.01-1 mM.

Table 8 Standard compounds for the analysis of xylem exudates by HPLC. Compound Purity Brand Cat. N. Retention time (min)

citric acid 99% J.T.Baker 5949-929-1 13.45

D-galacturonic acid >97% Fluka 48280-5G 3.52

D-glucuronic acid >98% Sigma 65269-10G 3.51

DL-isocitric acid >93% Sigma I1252 6.20

formic acid 98% J.T.Baker 200-579-1 4.47

fumaric acid 99% Fluka 4910-5G 15.07

glutaconic acid >97% Sigma 49360-5G 37.03

DL-lactic acid ~90% Sigma 69785 6.97

L-ascorbic acid Reagent grade Sigma A0278-25G 6.79

L-(+)-tartaric acid 99.50% Sigma 251380 4.15

maleic acid >99% Sigma M0375 16.86

L-(-)-malic acid 95-100% Sigma M1000 5.74

malonic acid 99% Sigma M1296 6.34

oxalic acid 99% Sigma 241172 3.35

pyruvic acid 98% Sigma 107360 5.05

succinic acid 99% Sigma S3674 14.99

trans-aconitic acid 98% Sigma 122750 25.91

58

Methods

2.6 Soil analyses

2.6.1 Pre-processing

The seven different soils used in this work were collected at the locations given

Table 3. The 30 cm upper layer of soils was collected using a shovel and sieved in

the field through a 5 mm mesh sieve. An average of 150 kg of sieved soil from each

location were collected and transported to the glasshouse in 30 L plastic barrels

drums (Amphorea Packaging, Cheshire, United Kingdom), where they were stored

until use. After soil preparation for each experiment (described above in section

2.2.1), 100 g of soil were subsampled in paper bags (Perga-Plastic, Walldürn-

Altheim, Germany) and air dried in the laboratory at room temperature for one week.

Each subsample was sieved through a 2 mm mesh analytical sieve (LINKER

Industrie-Technik, Kassel, Germany). Total and exchangeable metal concentrations

were determined by ICP-OES. Soil total C and N concentrations and soil pH were

also measured. Between three and six replicate measurements were performed per

soil.

2.6.2 Total element concentrations in soil

Subsamples of 0.25 g dry soil were placed into MARSXpress vessels (MARSXpress,

Matthews, USA) and digested after adding 2.25 mL 37% (w/v) HCl and 0.75 mL 65%

(w/w) HNO3 (Sigma-Aldrich Chemie GmbH, Taufkirchen, Germany) in a microwave

(MARSXpress, Matthews, USA) for 50 min (15 min ramp to 160 °C, and 15 min

digest at 160 °C, and 20 min cooling to room temperature). Samples were

transferred into a 15 mL centrifuge tube (TPP, Trasadingen, Switzerland). Volumes

were adjusted to 10 mL with ultrapure water and then filtered through Whatman

cellulose filter n° 595½ (GE Healthcare Life Sciences, Solingen, Germany). ICP-OES

measurement was performed following the procedure describe above (details in

section 2.4.1) using the standards given in Table 9.

2.6.3 Exchangeable concentration of elements in soil

Subsamples of 1 g soil were mixed with 10 mL unbuffered 0.01 M BaCl2 in a 15 mL

conical bottom centrifuge tube (TPP, Trasadingen, Switzerland) and then shaken

horizontally overnight at 150 rpm and room temperature in a Reax2 overhead shaker

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Methods

(Heidolph, Schwabach, Germany). Subsequently, suspensions were filtered through

Whatman cellulose filter n° 595½ (GE Healthcare Life Sciences, Solingen,

Germany), and 1 mL 65% (w/w) HNO3 was added to each solution. Metal

concentrations were measured as described above.

2.6.4 Soil pH analysis

Subsamples of 3 g soil were mixed with 0.01 M CaCl2 in a 15 mL conical bottom

Greiner tube (Sigma-Aldrich Chemie, Taufkirchen in Munique, Germany), vortexed

for 10 s and then shaken overnight as specified above. After centrifugation at 3,000

g at 20 °C for 10 min, the pH of the supernatant was measured immediately using a

pH meter (WTW, Weilheim, German) with a InLab semi-micro electrode (Mettler-

Toledo, Giessen, Germany).

2.6.5 Determination of C-N concentrations

Samples of 50 g of dried sieved soil (2 mm mesh) were ground using mortar and

pestle until a fine powder was obtained. From the soil powder, a subsample of 20 mg

was taken for measuring the total C and N concentrations. The C and N

determination were kindly performed by Ms. Bettina Röhm and Ms. Heidrun Kerkhoff

in the Institute of Geography, Department of Soil and Ecology Sciences in the Ruhr-

University of Bochum, using a Vario EL cube (Elementar Analysis Systems, Hanau,

Germany), as described (Don et al., 2007).

60

Methods

Table 9 Composition of calibration standards for ICP-OES on soil samples.

Concentration (µg mL-1)

Element Standard 1 Standard 2 Standard 3 Standard 4 Standard 5 wavelength

Ag 0.005 0.02 0.07 0.3 1 328,0

Al 1 3 10 30 100 396,1

As 0.005 0.02 0.07 0.3 1 189,0

B 0.05 0.1 0.3 0.7 1.5 208,9

Ca 0.1 0.5 3 20 100 318,1

Cd 0.01 0.03 0.1 0.3 1 226,5

Co 0.005 0.02 0.07 0.3 1 228,6

Cr 0.005 0.02 0.1 0.5 2 205,5

Cu 0.3 1 3 10 30 324,7

Fe 1 4 15 50 200 238,2

Hg 0.005 0.01 0.02 0.05 0.1 184,9

K 1 3 10 30 100 769,8

Mg 2.5 10 50 150 500 279,0

Mn 1 3 7 20 50 260,5

Mo 0.005 0.03 0.2 1 5 202,0

Ni 0.025 0.1 0.5 2 8 231,6

P 1 3 6 15 40 185,9

Pb 0.05 0.25 1.2 6.25 30 220,3

S 0.1 0.3 1 3 10 182,0

Se 0.05 0.1 0.15 0.5 1 196,0

Zn 0.1 0.5 3 20 100 213,8

2.7 Statistical analysis

All statistical analyses performed in this thesis were carried out in R software version

3.0.2 (R-Core-Team, 2013).

2.7.1 Multivariate analysis

Several parameters were measured of A. halleri plants cultivated on the different

hosting soils of natural A. halleri populations. Those were considered as variables for

statistical analysis: for plant growth, whole-plant biomass production, root and shoot

tissues final biomass; for leaf composition, the concentrations of 16 elements namely

B, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Mo, Ni, P, Pb, S, Zn; for plant stress markers,

leaf concentrations of chlorophyll, TBARS, anthocyanins, and hydrogen peroxide. In

addition, soil properties were considered as environmental parameters, i.e. 16

61

Methods

elements as given above plus Al, C, N, and soil pH. All these variables together were

compiled into a large dataset containing more than 17,000 data points. Multivariate

statistics were employed to understand the structure of the data as well as to identify

major factors which account for the variation observed in leaf multi-element profiles

and/or plant performance in the different genotypes analyzed.

As the variables were on very different scales of magnitude, data transformations

were necessary in order to standardize the dataset before proceeding with further

analysis. For example, considering the absolute values measured for element

concentrations in A. halleri leaves, Zn varied from 16 up to 27,000 µg g-1 and Pb

from 0.4 up to 1,000 µg g-1, whereas total chlorophyll varied between 0.56 and 2.48.

The data was first Log10(x+1) transformed and then normalized. The Log10

transformation allowed for rescaling the dataset and the addition of 1 to the

measurements prevented the incidence of negative Log values in the dataset. The

normalization was achieved by the following calculation: z = x - μ

σ. In which x is the

Log transformed value from the measurements, µ is the population mean and σ is

the standard deviation (Legendre and Gallagher, 2001; Zuur et al., 2007). Thus, the

dataset was rescaled to values between zero and the multiples of the standard

deviation. The function used for standardization was ‘decostand’ in the package

‘vegan’ (Oksanen et al., 2015).

The whole dataset was loaded in R and was subdivided into independent matrices

containing groups of related variables, such as: plant ionome matrix (all measured

element concentrations in leaf tissues), growth and stress markers matrix (biomass,

concentrations of chlorophyll, anthocyanins, TBARS, and H2O2), genotype matrix

(relative transcript levels of HMA3, HMA4 and FRD3 in the wild-type controls,

HMA3-, HMA4-, and FRD3-RNAi lines), and soil matrix (all measured elements in

soil samples and pH values of the different seven soils). These matrices comprised

variables measured in plants cultivated on all seven different soils and the soils

themselves. The plant ionome, growth and stress markers matrices were used

independently (each as a group of response variables) to generate unsconstrained

ordination plots of principal component analysis (PCA). When a matrix of response

variables was used as a function of a matrix of explanatory variables (for example,

plant ionome matrix as a function of soil matrix, or plant stress markers as a function

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Methods

of plant ionome), constrained ordination plots were obtained by redundancy analysis

(RDA). Both PCA and RDA were performed using the function ‘rda’ in the package

‘vegan’ (Oksanen et al., 2015).

The RDAs were performed after model selection based on Akaike information

criterion (AIC), which identifies explanatory variables that significantly contribute to

explain the variation in the response variables. Model selection was carried out by

automatic selection procedures in both forward and backward selection (Aho et al.,

2014) using the function ‘step’ in the package ‘stats’ (R-Core-Team, 2013). The

selected model was then evaluated for its significance using an ANOVA-like

permutation test for RDA with 999 permutations. The permutation test was

performed using the function ‘anova.cca’ in the package ‘vegan’ (Oksanen et al.,

2015). An adjusted R² was calculated in order to predict how much of the variation in

the response variables was explained by the explanatory variables present in the

model. For that, ‘RsquareAdj’ function was used in the package ‘vegan’ (Legendre et

al., 2011).

Partial RDAs were performed to enable the addition of more than one explanatory

variable to the statistical model. This methodology is also known as variation

partitioning (Kernan and Helliwell, 2001; Liu, 1997). For instance, the use of partial

RDA allows the removal of the variation in the response variables that is explained

by one of the explanatory variables, and allows for the analysis of the residual

variation. This methodology was applied to predict how much of the variation in the

leaf ionome and in the tolerance markers was explained by the differential transcript

levels observed in the RNAi lines (genotype matrix), after removing the variation

explained by the soil parameters. The variation explained by the soil was used as a

covariable in a partial RDA performed to correlate the leaf ionome matrix with the

genotype matrix, as well as the tolerance markers matrix with genotype matrix. The

partial RDAs were performed using the same function and package as for RDAs,

with the addition of the co-variables accordingly (Zuur et al., 2007).

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Methods

2.7.2 Univariate statistical analysis

The pipeline for univariate statistics is described in Table 10. The use of these tests

across the experiments carried out for this thesis was performed according to the

distribution (parametric or non-parametric) of the residuals in each dataset analyzed.

Table 10 Step-by-step pipeline for univariate statistics using R software.

Function Purpose Package

Normality and homogeneity of variance

1) hist Computes histogram of a dataset providing the data distribution

graphics

2) shapiro.test Performs the Shapiro-Wilk test of normality stats

3) leveneTest Computes Levene's test for homogeneity of variance across groups

cara

Parametric Statistics (for normally distributed residuals)

4) t.test Performs one or two sample Student’s t-Test and compare the means between two groups of values

stats

5) cohensDb Calculates the Cohen’s d measure of effect size. The value is given in standard deviation units.

lsrc

6) aov Fit an analysis of variance model by a call to linear model for each stratum. It was used for both one-way ANOVA and factorial (or two-way) ANOVA

stats

7) etaSquaredd (η²) Calculates η², which give measures of effect size: 0.02 ~ small, 0.13 ~ medium, and 0.26 ~ large.

lsr

8) TukeyHSD Generates a confidence intervals on the differences between multiple means being compared, based on Tukey's ‘Honest Significant Difference’ method

stats

Non-Parametric Statistics (for non-normally distributed residuals)

9) wilcox.test Performs one- and two-sample Wilcoxon tests on the data. Two-sample test is also referred as Mann-Whitney U teste.

stats

10) p.adjust Returns adjusted p-values from a given set of p-values using one of several methods, to correct for multiple-comparison. The bonferronid method was performed.

stats

a (Fox et al., 2014).

b (Cohen, 1988).

c (Navarro, 2013).

d (Pierce et al., 2004).

c (Mann and Whitney,

1947). e (Bland and Altman, 1995)

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Results

3 Results

3.1 Phenotypic characterization of RNAi lines

3.1.1 Confirmation of HMA3-, HMA4- and FRD3-RNAi lines

To investigate the individual contribution HMA3, HMA4 and FRD3 to metal

hyperaccumulation and hypertolerance in A. halleri, transgenic RNA interference

lines were generated by previous members of the laboratory to silence each of these

genes individually. The integration of silencing constructs into the genome was

confirmed by PCR using primers specific for each different construct and genomic

DNA as a template. The results confirmed the genotype of each of the RNAi lines

(Figure 8). The amplification of the HMA3-RNAi construct was expected to produce a

PCR fragment of 1.05 kb in length, with primers designed to anneal in the 35S

promoter and in the intron, respectively, thus amplifying a fragment comprising part

of the 35S promoter, the HMA3-sense fragment and part of the intron (Figure 8a).

Primers for the HMA4-RNAi construct were designed to amplify the region between

the intron and the HMA4-sense fragment, thus producing a fragment of 650 bp long

(Figure 8b). The expected PCR product for the FRD3-RNAi construct was 626 bp

long, because the primers amplified part of the intron and the FRD3 sense fragment

(Figure 8c). The EF1α gene was amplified as a positive control to ensure the quality

and quantity of the genomic DNA used as template for each sample (Figure 8d).

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Results

Figure 8 Confirmation of transgenic lines. (a) AhHMA3-RNAi lines, (b) AhHMA4-RNAi lines, (c) AhFRD3-RNAi lines, and (d) the EF1a gene as an endogenous control for each line. 1% (w/v) TAE/agarose gel of PCR products using genomic DNA as a template in a PCR with primers specific for each of the RNA interference construct or EF1a gene. M: 1 kb ladder, +: template was plasmid DNA harboring the RNAi construct for each respective target gene (a-c) or plasmid DNA with AtEF1a (d), WT: wild type (Langelsheim accession), TC: tissue culture wild type, TrC: Transformed wild type control (35S-GUS construct), -: no-template negative control using H2O as template.

Quantitative real time RT-PCR using specific primers was performed in order to

analyze that transcript levels of each target gene. All three independent RNAi lines of

HMA3-RNAi, HMA4-RNAi and FRD3-RNAi displayed significantly reduced transcript

levels when compared to the wild-type transcript levels (Figure 9). The HMA3

transcript levels in the three independent HMA3-RNAi lines were similar to each

other, and the reduction compared with the wild-type transcript levels were 77%,

72%, and 76% in the lines 1.2, 4.1, and 5.2, respectively (Figure 9a). The reduction

in HMA4 transcript levels in the independent HMA4-RNAi lines 3.1.1, 4.2.1, and

4.3.2 compared with the wild-type transcript levels were 63%, 82%, and 65%,

respectively. The HMA4-RNAi line 4.2.1 displayed the lowest HMA4 transcript levels,

but they were not statistically significantly lower than for the other two independent

HMA4-RNAi lines (Figure 9b). FRD3 transcript levels in independent FRD3-RNAi

lines 7.1, 9.1, and 18.2 showed a reduction by 68%, 61% and 85%, respectively, of

kb + WT TC TrC 1.2 4.1 5.2 3.1.1 4.2.1 4.3.2 7.1 9.1 18.2 -

WT HMA3-RNAi HMA4-RNAi FRD3-RNAi

kb M

(b)

(c) (c)

(d)

1.05 0.75

0.5

1.0 1.5

0.65

0.63

0.58

(a)

0.75

0.5

1.0 1.5

0.5

0.25

0.75 1.0 1.5

0.25

0.5 0.75

1.0

66

Results

the wild-type transcript levels. Although FRD3 transcript levels in FRD3-RNAi line

18.2 were lower than in the other two independent lines, no significant difference

was detected (Figure 9c). It was concluded that the selected lines were suitable for

addressing the effects of the post-transcriptional silencing of candidate gene

expression on metal hyperaccumulation and hypertolerance in A. halleri.

Figure 9 Reduction of AhHMA3, AhHMA4 and AhFRD3 transcript levels in independent RNAi lines. (a) AhHMA3, (b) AhHMA4, and (c) AhFRD3. Bargraphs show arithmetic means + SD [n = 4 (each RNAi line) to 12 (four individuals for each of the three independent wild-type lines)]. Transcript levels are given relative to EF1α (b) and Helicase (a and c). EF1α transcript levels were used to calculate relative transcript levels of HMA4 (i.e. Ct between 15 and 20) and Helicase to calculate relative transcript levels of genes with lower expression (i.e. Ct between 20 and 35). Different characters above the bars indicate statistically significant difference by one-way ANOVA, followed by post-hoc Tukey HSD test and eta-Squared (η²) effect size test (a: p < 0.001, F = 36.9, η² = 0.89; b: p < 0.001, F = 17.2, η² = 0.72; c: p < 0.001, F = 21.5, η² = 0.82). Three clones of each line were cultivated hydroponically for four weeks, and total RNA was extracted from roots for the quantification of transcript levels as described (section 2.3.2 Methods).

3.1.2 Environment and soil characterization of A. halleri sites

Based on the literature and preliminary analysis of A. hallei plants and soil from

several European sites, seven sites were selected as the sources of soils hosting

natural populations of A. halleri for cultivating transgenic RNAi lines in order to carry

out their phenotypically characterization (Figure S1-S7). The sites were chosen

because of their soil metal profile, such as heavy metal concentration in the soil and

in leaves of local A. halleri plants, A. halleri population size (number of plants found

at the site, i.e. hundreds or a higher number of individuals), and appearance of the

(b)

a

b

b

b

HMA4-RNAi

(c)

a

b b

b

FRD3-RNAi

(a)

a

b b

b

HMA3-RNAi

67

Results

plants growing in the site (healthy plants with green leaves and a branched shoot of

individual plants). Exchangeable metal concentrations were used to compare

availability of metals to plant roots. Metalliferous soils contained several-fold higher

exchangeable concentrations of Zn (3.7- to 170-fold), Cd (2.2- to 105-fold), and Pb

(1.8- to 258-fold) than non-metalliferous soils (Table 11). The exception was

exchangeable Zn concentrations in soil from Evín-Malmaison, which were

comparable to non-contaminated soils.

Table 11 Mineral and chemical properties of soils from A. halleri sites used in this study.

Exchangeable metal concentration (µg g-1)

Site Zn Cd Pb C/N ratio (%) pH

Langelsheim 63.4 ± 5.3 0.74 ± 0.1 1.01 ± 0.1 20.0 ± 0.19 6.9 ± 0.1

Littfeld 399 ± 130 2.11 ± 1.0 12.9 ± 9.0 12.7 ± 1.69 7.1 ± 0.2

Evín-Malmaison 1.55 ± 0.5 0.29 ± <0.1 0.27 ± 0.1 31.3 ± 1.78 7.5 ± <0.1

Bestwig 8.55 ± 2.2 0.13 ± <0.1 0.23 ± 0.1 42.7 ± 1.32 7.5 ± 0.1

Malmedy 2.34 ± 0.8 0.02 ± <0.1 0.05 ± <0.1 20.9 ± 0.12 5.5 ± 0.1

Wehbach 1.23 ± 0.3 0.04 ± <0.1 0.13 ± <0.1 14.6 ± 0.12 4.9 ± <0.1

Rodacherbrunn 1.49 ± 0.2 0.06 ± <0.1 0.05 ± <0.1 13.0 ± 0.13 4.4 ± 0.1

Bold type: metalliferous. Normal type: non-metalliferous.

3.1.3 Validation of experimental set-up

To test whether wild-type A. halleri plants, i.e. plants of the Lan accession used for

this study, grow as healthy as native A. halleri plants on the soil from each of the

sites and to confirm the toxicity of metalliferous soils to non-tolerant plants, wild-type

A. halleri Langelsheim accession (Lan) and A. thaliana – a non-tolerant non-

accumulator sister species of A. halleri - were cultivated alongside A. halleri native

accessions collected from sites where the soils were sampled. By the end of the

cultivation period of five weeks, A. thaliana plants had died on all metalliferous soils

and survived only on non-metalliferous soils. The final plant size of wild-type Lan

plants were similar to the respective native accessions on all soils (Figure 10 and

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Results

Figure 11). Plant size of wild-type Lan plants was much smaller on Evín-Malmaison

soil when compared to plant sizes on other soils. However, the plant size of Lan

plants was comparable to the native Evín-Malmaison accession cultivated on the

same soil. When cultivated on Bestwig soil, wild-type Lan plants produced

significantly more biomass than after cultivation on other soils (Figure 12). It is

important to highlight that Langelsheim soil is the substrate where the wild-type Lan

line grows naturally in the field and all other wild-type controls and RNAi lines were

generated from plants with Lan background, thus the plants used for the experiments

in this thesis are likely more adapted to that soil.

69

Results

Figure 10 Test of toxicity of metalliferous soils. Three-week-old clones of each respective A. halleri native accession, the Lan accession used as the genetic background for transgenic lines and three-week-old seedlings of A. thaliana Col-0 were transplanted into metalliferous soils from Langelsheim, Littfeld, Evín-Malmaison and Bestwig. Plants were cultivated for an additional five weeks under controlled conditions in a growth chamber. Scale bar: 30 mm.

A. halleri native accession

A. halleri wild type Lan

A. thaliana Col-0

Soil

La

nge

lshe

im

Littf

eld

E

vín

-Ma

lma

ison

B

estw

ig

70

Results

Figure 11 Test of growth conditions on non-metalliferous soils. Three-week-old clones of the respective A. halleri native accession, the Lan accession used as the genetic background for transgenic lines and three-week-old seedlings of A. thaliana Col-0 were transplanted into non-metalliferous soils from Malmedy, Wehbach, and Rodacherbrunn, respectively. Plants were cultivated for an additional five weeks under controlled conditions in a growth chamber. Scale bar: 30 mm.

Ma

lme

dy

Wehba

ch

Rod

ache

rbru

nn

A. halleri

native accession

A. halleri wild type Lan

A. thaliana Col-0

Soil

71

Results

Figure 12 Plant biomass of A. halleri wild type (Lan accession) on native soils. A. halleri wild-type Lan was grown on its metal-contaminated native soil from Langelsheim and on six other soils hosting natural populations of A. halleri for five weeks. Diagram shows plant final biomass. Shown are mean values + SD [n = 4]. Different characters next to the bars indicate statistically significant differences by Analysis of Variance (One-Way ANOVA), followed by Post-Hoc test Tukey

HSD and eta-Squared (n²) effect size test (p < 0.001, F: 55.7, n² = 0.82). Bar color indicates soil type:

metalliferous (red) and non-metalliferous (black).

These results suggested that growth conditions and soils were suitable for the

cultivation of wild-type A. halleri plants. Next, HMA3-, HMA4- and FRD3-RNAi lines

were cultivated alongside the control lines (Lan, TC and TrC) to investigate the

consequences of the silencing of these candidate genes on metal

hyperaccumulation and hypertolerance. In the following sections, whenever the term

wild type is used, it refers to all three independent control lines, unless indicated

otherwise.

3.1.4 Comparisons between wild type and RNAi lines grown on soil

The appearance of HMA3-, HMA4- and FRD3-RNAi lines was only slightly different

from the wild type upon cultivation on all seven different soils hosting natural A.

halleri populations. If candidate genes contribute to metal hypertolerance, HMA3-,

HMA4- and FRD3-RNAi lines would be expected to show metal toxicity symptoms on

metalliferous soils.

After five weeks of cultivation on metalliferous native soil from Langelsheim, plant

size of HMA3-RNAi lines was not different than wild-type control lines, and they did

not show visual toxicity symptoms (Figure 13). In contrast, two of the three HMA4-

RNAi lines appeared smaller in size than the wild-type lines. The HMA4-RNAi line

b

b

b

b

a

c

b

72

Results

4.2.1 showed the strongest growth impairment and exhibited a few purple leaves,

suggesting that these plants experienced physiological stress. The HMA4-RNAi line

4.2.1 is also the one that exhibited the lowest HMA4 transcript levels in comparison

to the wild type and the other HMA4-RNAi lines (see Figure 9b). All three FRD3-

RNAi lines were smaller in size than the wild-type lines, but did not show leaf

chlorosis or symptoms of physiological stress. The soil from Langelsheim contained

very high concentrations of exchangeable Zn, Cd and Pb concentrations in

comparison to all other soils tested, second only compared with the soil from Littfeld.

No consistent differences were found between wild-type genotypes and RNAi lines

for any of the target genes on any of the other metalliferous soils (Figure S9-11).

Overall stress symptoms correlated with the magnitude of heavy metal

concentrations on metalliferous soils. Only for plants grown on Evín-Malmaison soil,

stress symptoms were severe despite moderate exchangeable soil concentrations of

all measured heavy metals (Figure S10). None of the quantified parameters in soils

allowed a conclusion to explain such strong stress symptoms on plants grown on

that soil. Exchangeable Zn concentrations were similar or even lower than the Zn

concentrations in certain non-metalliferous soils. Other soil parameters such as soil

pH and C:N ratio were between the ranges found in the different metalliferous soils.

The analysis of exchangeable concentrations of the remaining 13 elements analyzed

in the soil (B, Ca, Fe, K, Mg, P, S, Mn, Cu, Al, Co, Cr, and Ni) did not reveal any

alteration that could potentially cause toxicity or deficiency in plants grown on that

soil in comparison to the other six soils tested. Evín-Malmaison soil might be heavily

contaminated with a toxin that was not measured, but for which the candidate genes

tested have no role. Additional parameters that might influence plant growth and

development – soil microbial activity or beneficial microorganisms – were not

assessed.

After plant cultivation on different non-metalliferous soils from Malmedy, Wehbach

and Rodacherbrunn, the HMA3-, HMA4-, and FRD3-RNAi lines displayed no evident

differences compared with wild-type lines (Figure 14, Figure S12-13). There were no

stress symptoms such as the ones observed in leaves of plants grown on

metalliferous soils.

73

Results

Figure 13 Photographs of HMA3-, HMA4-, and FRD3-RNAi and wild-type lines on Langelsheim soil. Shown are photographs of one representative individual for each of the three independent RNAi lines per target gene and wild-type control lines. (a-c) Wild-type (WT) (a) Lan, (b) TC, and (c) TrC, HMA3-RNAi lines (d) 1.2, (e) 4.1, and (f) 5.2, HMA4-RNAi lines (g) 3.1.1, (h) 4.2.1, and (i) 4.3.2, and FRD3-RNAi lines (j) 7.1, (k) 9.1 and (l) 18.2. Three-week-old clones were transplanted into metalliferous soil from Langelsheim and cultivated in a growth chamber for an additional five weeks. Violet arrows: purple leaves. Scale bar: 30 mm.

(a) (b) (c)

(d) (e) (f)

(h) (i) (g)

(j) (k) (l)

74

Results

Figure 14 Photographs of HMA3-, HMA4-, and FRD3-RNAi and wild-type lines on Malmedy soil. Shown are photographs of one representative individual for each of the three independent RNAi lines per target gene and wild-type control lines. (a-c) Wild-type (WT) (a) Lan, (b) TC, and (c) TrC, HMA3-RNAi lines (d) 1.2, (e) 4.1, and (f) 5.2, HMA4-RNAi lines (g) 3.1.1, (h) 4.2.1, and (i) 4.3.2, and FRD3-RNAi lines (j) 7.1, (k) 9.1 and (l) 18.2. Three-week-old clones were transplanted into non-metalliferous soil from Malmedy and cultivated in a growth chamber for an additional five weeks. Scale bar: 30 mm.

The leaf ionome and biochemical assays performed in these experiments were used

to quantitatively assess leaf element concentrations and stress symptoms. The

results of these quantifications will be presented using multivariate analysis.

(a) (b) (c)

(d) (e) (f)

(g) (h) (i)

(j) (k) (l)

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Results

3.1.5 Exploratory analysis of the leaf ionome, plant performance and stress

markers

To identify the factors affecting the leaf metal concentrations in A. halleri plants, a

PCA was performed using the concentrations of 16 elements of the leaf ionome.

About 85% of the total variation in the leaf ionome was explained by the first six axes

of the PCA, whose eigenvalues were larger than the mean of all eigenvalues (Figure

S8a). The first four axes accounted for 71.6% of the total variation and were then

selected for further analysis based on the broken-stick model (Figure S8c). Most of

the variation (46%) within these four axes was explained by PC1 and PC2 combined.

Pb was the element contributing to most of the variation in PC1, followed by Cd, Zn,

and Mg which were positively associated with PC1 (Figure 15). The accumulation of

these elements occurred preferentially in plants grown on metalliferous soils (shades

of red), which are soils containing far higher concentrations of Zn, Cd, and Pb than

non-metalliferous soils (shades of grey) (Table 11). The concentrations of P, Fe, K,

and Co were negatively associated with PC1 and plants cultivated on non-

metalliferous soils contained higher leaf concentrations of these elements. In the

PC2 axis, the elements accounting for most of the variation were B, Mo, Ni, Ca, and

K, among which only Ni was positively associated with this axis (Table 12). The PC3

and PC4 combined accounted for about 26% of the total variation in the leaf ionome.

S, Cu and Mn were the elements contributing the most to the variation observed in

the PC3, whilst Cr, Fe and Ni contributed more to the variation on PC4 (Table 12).

The biplot of the first two PC axes showed that leaf ionomes were mainly separated

by soil type. Samples from plants cultivated on metalliferous and non-metalliferous

soils clearly formed two large clusters, and each of the seven different soils from

native sites of A. halleri prompted the formation sub-clusters, sometimes overlapping

with one another (Figure 15). In this regard, an almost complete overlap was the

case for samples from plants cultivated on Langelsheim (darker red) and Evín-

Malmaison (red), suggesting that the leaf ionome of plants cultivated on these two

soils were very similar. Within the sub-clusters, only slight separation could be

identified between RNAi lines and the wild-type. Most evident was the separation

between wild-type (filled squares) and FRD3-RNAi (crosses) in all seven soils and

between wild-type and HMA4-RNAi lines (triangles) mostly on metalliferous soils.

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Figure 15 Leaf ionome ordination diagram showing variation of multi-element concentration. PC1 and PC2 of principal component analysis of leaf element concentrations from plants grown in a plant growth chamber on seven soils hosting natural A. halleri populations. Different shades reflect soil exchangeable concentrations of heavy metals Zn, Cd, and Pb [darkest = highest heavy metal concentrations, lightest = lowest heavy metal concentrations (based on data shown in Table 11]. Red: metalliferous soils (from darkest to lightest: Littfeld, Langelsheim, Evín-Malmaison, Bestwig) black: non-metalliferous soils (from darkest to lightest: Wehbach, Malmedy, Rodacherbrunn). PCA was

conducted employing standardized Log10(x + 1) leaf element concentrations. : wild-type lines, :

HMA3-RNAi lines, : HMA4-RNAi lines, +: FRD3-RNAi lines.

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Table 12 Eigenvalues from principal component analysis of 16 elements of the leaf ionome and element scores for the first four PCs.

principal component axes

Parameters 1 2 3 4

Eigenvalue % of total variation explained

25.0 21.1 15.5 10.8

Cumulative % variation explained

25.0 46.1 64.5 71.6

Element scores

Pb 1.768 0.563 -0.401 -0.258

Cd 1.731 -0.564 -0.243 -0.479

Zn 1.459 -0.006 -0.501 -0.542

P -1.433 -0.619 -0.366 -0.487

Fe -1.168 -0.374 -0.387 -1.151

K -1.160 -1.257 -0.496 -0.436

Mg 1.159 -0.814 0.628 -0.125

Co -1.034 -0.920 -0.848 0.397

B 0.016 -1.749 0.468 -0.543

Mo 0.386 -1.711 -0.207 0.009

Ca 0.826 -1.483 0.296 -0.440

Ni -0.920 1.341 -0.210 -1.084

S 0.075 0.070 -1.811 -0.079

Cu 0.635 -0.034 -1.668 -0.347

Mn 0.375 0.128 -1.532 0.647

Cr 0.359 0.871 0.309 -1.568

To assess the global effects of soil composition and genotypes on plant growth and

stress, a PCA was performed using quantifications of nine stress markers. More than

48% of the total variation in these markers was explained by the first PC axis, of

which eigenvalues were larger than the mean of all eigenvalues (Figure S8b). The

first two axes accounted for 67.5% of the total variation and were then selected for

further analysis based on the broken-stick model (Figure S8d). The markers

contributing to most of the variation observed in PC1 were plant growth rate and

shoot biomass, which were negatively associated with this axis (scores: -1.256 and

-1.147, respectively). TBARS and H2O2 concentration were positively associated with

PC1, but contributed less to the variation (scores: 0.514 and 0.756, respectively).

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Concentrations of chlorophyll a, b and total chlorophylls did not vary between

genotypes and were not informative. This suggests that whole plant and shoot

biomass are the most sensitive markers of plant performance, followed by TBARS

and H2O2 concentrations. In the biplot of the first two PC axes for plant performance

and stress markers there was again a clear separation between samples from plants

grown on metalliferous and non-metalliferous soils, but differences were less

pronounced than the separation observed for the leaf ionomes (Figure 16). Samples

from plants grown on non-metalliferous soils showed almost no variation concerning

the markers analyzed, as those samples clustered mostly around the plot centroid. In

contrast, samples from plants cultivated on metalliferous soils were more variable,

suggesting that plants containing higher concentrations of TBARS and H2O2 also

produced less biomass, which is in line with expectations. Different from the ionome,

less separation was observed between RNAi lines and the wild type suggesting that

soils had a far larger impact on plant performance than silencing of the candidate

genes (see also above).

Figure 16 Plant growth and stress markers ordination diagram. PC1 and PC2 of principal component analysis of plant performance and stress markers quantified in plants grown in a plant growth chamber on seven soils hosting natural A. halleri populations. Plant_FW: plant growth rate, Chla: chlorophyll a, Chlb: chlorophyll b, Tchl: total chlorophylls, TBARS: Thiobarbituric acid reactive substances, H2O2: Hydrogen Peroxide. Different shades reflect soil exchangeable concentrations of heavy metals Zn, Cd, and Pb [darkest = highest heavy metal concentrations, lightest = lowest heavy metal concentrations (based on data shown in Table 11]. Red: metalliferous soils (from darkest to lightest: Littfeld, Langelsheim, Evín-Malmaison, Bestwig) black: non-metalliferous soils (from darkest to lightest: Wehbach, Malmedy, Rodacherbrunn). PCA was conducted employing standardized Log10(x + 1) biomass measurements and Log10(x + 1) stress

markers. : wild-type lines, : HMA3-RNAi lines, : HMA4-RNAi lines, +: FRD3-RNAi lines.

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These results suggested that overall, the elements comprising the leaf ionome of A.

halleri were highly variable after plant growth on the different soils tested. Moreover,

the differences between wild-type and RNAi lines were more pronounced regarding

the leaf ionomes than plant growth and stress markers.

PCA is only an ordination method and does not allow the identification of specific soil

properties contributing to the variation observed in leaf ionome or stress markers.

Therefore, further analysis was followed using Redundancy Analysis (RDA) in order

to identify those properties and whether they help to explain the differences existing

between wild-type and RNAi lines.

3.1.6 Leaf ionome, plant performance and stress markers are differently

affected by soil properties

In order to understand which of the soil properties influenced the leaf multi-element

accumulation and plant growth and stress markers, multiple regression models were

used. RDA is analogous to regression analysis, which estimates the relationships

between variables and ascertain potential causal effect of a particular variable upon

another (Sykes, 1993). Multiple regression allows the investigation of correlations

between different matrices of variables and then the estimation of how much of the

variation in one matrix (response variables) is explained by the other matrix

(explanatory variables). Hence, after splitting the dataset into leaf ionome matrix

(response variables), plant growth and tolerance markers matrix (response

variables), genotypes matrix (explanatory variables) and soil property matrix

(explanatory variables), RDA plots of eigenvectors were created. In the soil property

matrix, exchangeable concentrations of minerals were used for the analysis.

The leaf ionome was analyzed first. The AIC was used to select a model with the

best predictive accuracy for soil properties that explained the variation observed in

the leaf ionome. The best predictive model comprised soil concentrations of Cd, Cr,

Mn, N, Ni and soil pH as the factors with statistically significant predictive value

(Table S1). The selected model for correlations between leaf ionome and soil

properties explained 63% of the total variation observed in the leaf ionome (ANOVA

permutation test for RDA: p < 0.001, F = 91.4, adjusted R² = 0.63). Almost 60% of

the total variation in the leaf ionome was explained by the first four axes of this RDA.

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The first two axes combined accounted for 41.2% of the total variation, whereas

axes RDA3 and RDA4 combined explained 16.8%.

An RDA plot of the first two axes was then generated (Figure 17). In the RDA1, most

of the variation was explained by the positive correlation between leaf Pb, Cd, Zn

and the soil exchangeable concentrations of Cd and soil pH. The leaf concentrations

of Pb, Cd, Zn were negatively correlated with the soil exchangeable concentrations

of Mn and Ni. Leaf concentrations of P, K, Co and Fe were negatively correlated with

soil Cd, and soil pH, but positively correlated with soil Mn and Ni. This is exactly the

opposite of what was observed for leaf Pb, Cd and Zn. In the RDA2, leaf

concentrations of B, Mo, Ca, Mg and Ni were positively correlated with soil N and Cr,

but the correlations were not as strong as the ones observed in the RDA1 axis

(Figure 17, and Table 13). The analysis of RDA3 and RDA4 suggested that the

16.8% of variation explained by the combination of these two axes was mostly

accountable to the negative correlation between leaf concentrations of Cu, Mn, S

and soil N, Cr, pH (Table 13).

Figure 17 Ordination diagram showing the correlation between leaf ionome and soil properties. Leaf ionome (response variable) and soil ionome (explanatory variable) were used for this multiple regression model. Model fit was evaluated by ANOVA permutation test for RDA: p < 0.001, F = 91.43, adjusted R² = 0.63. Different shades reflect soil exchangeable concentrations of heavy metals Zn, Cd, and Pb [darkest = highest heavy metal concentrations, lightest = lowest heavy metal concentrations (based on data shown in Table 11]. Red: metalliferous soils (from darkest to lightest: Littfeld, Langelsheim, Evín-Malmaison, Bestwig) black: non-metalliferous soils (from darkest to lightest: Wehbach, Malmedy, Rodacherbrunn). RDA was conducted employing standardized Log10(x + 1) leaf

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element concentrations, Log10(x + 1) soil exchangeable element concentrations, and soil pH. : wild-

type lines, : HMA3-RNAi lines, : HMA4-RNAi lines, +: FRD3-RNAi lines.

Table 13 Eigenvalues from redundancy analysis of 16 elements of the ionome and element scores for the first four RDAs.

RDA axes

Parameters 1 2 3 4

Eigenvalue % of total variation explained 22.3 18.9 12.2 4.6

Cumulative % variation explained 22.3 41.2 53.3 58.0

Accumulated constrained eigenvalues 34.9 29.5 19.0 7.2

Element scores of the plant ionome

Pb -1.776 -0.247 0.385 -0.355

Cd -1.348 0.635 -0.086 -0.255

Zn -1.140 -0.056 -0.136 -0.146

P 1.540 0.037 0.220 -0.954

Fe 1.141 0.025 0.187 0.440

K 1.309 0.751 0.310 -0.416

Mg -0.937 1.131 -0.207 0.306

Co 1.302 0.426 0.785 0.384

B 0.366 1.581 -0.324 0.177

Mo 0.047 1.570 0.366 0.779

Ca -0.428 1.506 -0.102 -0.750

Ni 0.610 -1.645 -0.588 0.203

S -0.144 -0.562 1.330 -0.357

Cu -0.689 -0.238 1.392 0.284

Mn -0.402 -0.358 1.632 0.164

Cr -0.563 -0.706 -0.826 0.313

Element scores of the soil properties

sCd -0.950 0.031 0.196 -0.060

N 0.434 0.773 -0.302 0.273

spH -0.902 0.055 -0.313 -0.070

sCr 0.024 0.266 -0.172 0.408

sNi 0.663 -0.315 0.275 0.299

sMn 0.803 -0.093 0.311 0.240

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Results

The analysis of plant growth and stress markers was also carried out. The statistical

model explained 55% of the total variation observed in stress markers (ANOVA

permutation test for RDA: p < 0.001, F = 65.0, adjusted R² = 0.55). The first two axes

explained 47.6% of the total variation and were then used to generate a RDA plot

(Figure 18). Most of the variation observed in tolerance markers was accounted for

by two different correlations: a negative one between plant biomass and soil

exchangeable concentrations of Pb and Cd, and soil pH and N, and a positive

correlation between H2O2, TBARS, anthocyanin and these same soil parameters.

This indicates again, as the PCA did earlier, that the more oxidative stress plants

experienced the lower biomass they produced. In addition, the oxidative stress

increases with increasing concentrations of Pb, Cd, and N in the soil.

Figure 18 Ordination diagram showing correlation between growth and stress markers and soil properties. Growth and stress markers (response variable) and soil properties (explanatory variable) were used for this multiple regression model. Model fit was evaluated by ANOVA permutation test for RDA: p < 0.001, F = 64.95, adjusted R² = 0.55). Chla: chlorophyll a, Chlb: chlorophyll b, Tchl: total chlorophyll, TBARS: Thiobarbituric acid reactive substances, H2O2: Hydrogen Peroxide, Plant_FW: plant growth rate, Shoot_FW: shoot biomass, Root_FW: root biomass. sCd: soil cadmium, sCo: soil cobalt, sCu: soil copper, N: soil nitrogen, spH: soil pH, sPb: soil lead. Different shades reflect soil exchangeable concentrations of heavy metals Zn, Cd, and Pb [darkest = highest heavy metal concentrations, lightest = lowest heavy metal concentrations (based on data shown in Table 12]. Red: metalliferous soils (from darkest to lightest: Littfeld, Langelsheim, Evín-Malmaison, Bestwig) black: non-metalliferous soils (from darkest to lightest: Wehbach, Malmedy, Rodacherbrunn). RDA was conducted employing standardized Log10(x + 1) plant growth rate, Log10(x + 1) for shoot and root

biomass, Log10(x + 1) soil exchangeable element concentrations, and soil pH. : wild-type lines,

: HMA3-RNAi lines, : HMA4-RNAi lines, +: FRD3-RNAi lines.

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Results

Next, the question addressed is whether and how the reduced transcript levels of

HMA3, HMA4 or FRD3 influenced the leaf ionome and/or plant growth and stress

markers of A. halleri plants grown on soils hosting natural populations of this

species. Knowing how much of the variation in the leaf ionome and stress markers

was explained by the soil properties (63% and 55%, respectively), the residual

variation can be partitioned in order to identify the factors explaining the remaining

37% and 45% of variation in the leaf ionome and stress markers, respectively. This

will be addressed using partial RDA.

3.1.7 Silencing of AhHMA4 and AhFRD3 dramatically alters the leaf heavy

metal accumulation of A. halleri

Up to here, the analyses were based on PCA of the leaf ionome and stress markers

alone, or on the multivariate correlation between leaf ionome or stress markers with

soil properties using RDA. These analyses have helped to understand how those

response variables varied throughout experiments using different types of soil as

well as which of the soil properties were the best predictors for the variation

observed in those variables. However, the analyses employed did not specifically

identify the extent to which knockdown of any specific gene function by RNAi was

responsible for the observed variation. In order to directly address the impact caused

by the silencing of HMA3, HMA4 and FRD3 on the leaf ionome and stress markers,

the transcript levels of each of these genes were used as another variable in an

additional analysis.

The variation explained by the soil properties was decomposed into primary

components and then used as a covariable in a partial RDA. The eigenvectors were

obtained from the correlation between the residual variation from the matrices of leaf

ionome or stress markers and the matrix of transcript levels. As the metal-

contamination in the soil strongly contributed to the variation observed in both leaf

ionome and stress markers in previous models (Figure 17 and Figure 18), the

following analyses will be based on a split dataset containing samples from plants

cultivated on either metalliferous or non-metalliferous soils alone.

First, we analyzed all samples from plants cultivated on the four metalliferous soils.

The partial RDA model explained 14% of the total variation observed in the leaf

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Results

ionome (ANOVA permutation test for RDA: p < 0.001, F = 42.2, semi-partial R² =

0.14). The first two RDA axes were used to generate a partial RDA plot. HMA4-RNAi

lines (blue) and FRD3-RNAi lines (red) largely contributed to the variation observed

in both axes (Figure 19). Within the variation explained by the transcript levels, the

RDA1 axis accounted for 22% of that variation, which was explained by RNAi lines

(HMA4-RNAi and FRD3-RNAi) and leaf concentrations of Zn and Cd. The RDA2 axis

explained 10.8% of the variation, which was mostly accounted to the separation of

wild type (black) and HMA3-RNAi (yellow) from both HMA4-RNAi and FRD3-RNAi,

and also leaf Pb concentrations. Wild type and HMA3-RNAi were positioned near the

RDA plot centroid, suggesting that their leaf ionomes were very similar. This

suggested that the HMA3 transcript levels did not exhibit significant predictive value

for the analysis of leaf ionomic variation in the set of A. halleri genotypes studied in

this experiment (see also Table S1).

Figure 19 Partial redundancy analysis of samples from metalliferous soils. Diagram shows the first two dimensions of partial redundancy analysis for samples from plants cultivated on four metalliferous soils from Langelsheim, Littfeld, Evín-Malmaison and Bestwig. Shown are samples (symbols), leaf element concentrations (positions of larger characters), and their matrix correlations with transcript levels of AhHMA4 and AhFRD3 (arrows with smaller characters), for a model based on standardized (z-scores) of Log10(x + 1) leaf element concentrations and Log10(x + 1)

transcript levels using Log10(x + 1) soil exchangeable element concentrations as a co-variable. :

wild type, : HMA3-RNAi, : HMA4-RNAi, : FRD3-RNAi. Different shades represent independent RNAi lines for each of the target genes (the lighter the lower the transcript levels detected). Model fit was evaluated by ANOVA permutation test for RDA (p < 0.001, F = 42.2, adjusted R² = 0.14).

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Results

HMA4-RNAi was associated with lowered leaf Zn/Cd concentrations. This is in

accordance with a previous report in which these same HMA4-RNAi lines were

cultivated on hydroponic media (Hanikenne et al., 2008). FRD3-RNAi lines were

associated with strongly decreased leaf Pb concentrations. This was somewhat

surprising, since FRD3 of A. thaliana is known to act in Fe homeostasis and

partitioning in that species. The silencing of HMA4 and FRD3 did not affect the

accumulation of other elements as strongly as it influenced leaf Zn, Cd and Pb

concentrations. The comparison of leaf concentrations of Zn, Cd, Pb, and Fe in all

different RNAi lines cultivated on metalliferous soil from Langelsheim are shown in

Figure 20 as a representative illustration for the leaf heavy metal variation in plants

grown on different metalliferous soils.

These results confirmed a strong reduction of leaf Zn and Cd concentrations only in

HMA4-RNAi lines in comparison to the wild type. Leaf Zn concentrations in HMA4-

RNAi lines varied from 2 to 39% of the wild-type leaf Zn levels (one-way ANOVA, p <

0.001) (Figure 20a). Leaf Cd concentrations were significantly reduced to 43 and 8%

in HMA4-RNAi lines 3.1.1 and 4.2.1, respectively (one-way ANOVA, p < 0.001), but

not in line 4.3.2 (Figure 20b). The same trend was observed between independent

experiments on Langelsheim soil as well as on other metalliferous soils. A strong

reduction in leaf Pb concentrations was observed in all three independent FRD3-

RNAi lines, which contained between 3 and 14% of the wild-type leaf Pb

concentrations (one-way ANOVA, p < 0.001) (Figure 20c). The leaves of HMA4-

RNAi lines 3.1.1 and 4.2.1 contained 43 and 13%, respectively, of the Pb

concentrations found in wild-type leaves, but only line 4.2.1 displayed a reduction in

leaf Pb concentrations comparable to those of FRD3-RNAi lines. Leaf Fe

concentrations were very similar between wild type and almost all different RNAi

lines, with exception of HMA3-RNAi line 5.2, in which leaf Fe concentrations were

significantly higher (Figure 20d). However, the significantly higher leaf Fe

concentrations in HMA3-RNAi line 5.2 were not consistently observed between

independent experiments or using different soil types. Wild type and HMA3-RNAi

lines displayed comparable leaf metal concentrations for Zn, Cd, Pb and Fe, which is

in agreement with the RDA-based classification of HMA3 transcript levels as a non-

predictive variable for leaf ionome variation in the partial RDA presented earlier.

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Figure 20 Leaf metal concentrations of A. halleri plants cultivated on metalliferous soil from Langelsheim. (a-d) Bargraphs show for wild type (black), HMA3-RNAi (yellow), HMA4-RNAi (blue) and FRD3-RNAi lines (red) (a) leaf Zn concentrations, (b) leaf Cd concentrations, (c) leaf Pb concentrations, (d) leaf Fe concentrations. Shown are mean values + SD [n = 4 (RNAi lines) or 12 (4 replicates for each of the three different genotypes used as wild-type controls)] representative of one out of four independent experiments. Different characters above the bars indicate statistically significant differences detected in a one-way ANOVA, followed by post-hoc Tukey HSD test and eta-Squared (η²) effect size test (a: one-way ANOVA, p < 0.001, F = 174.2, η² = 0.98; b: one-way ANOVA, p < 0.001, F = 16.9, η² = 0.80; c: one-way ANOVA, p < 0.001. F = 22.9, η² = 0.84; d: one-way ANOVA, p < 0.001, F = 6.7, η² = 0.61). Three-week-old clones were transplanted into their native soil (Langelsheim) and cultivated for five weeks before harvest.

To test whether these results were dependent on the soil heavy metal-

contamination, another partial RDA was performed for samples from plants grown on

non-metalliferous soils (Figure 21). The outcome was similar to the analysis of plants

from metalliferous soils and the model explained 12% of the variation (ANOVA

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Results

permutation test for RDA: p < 0.001, F = 18.4, semi-partial R² = 0.12). This suggests

that the silencing of HMA4 and FRD3 strongly affects Zn, Cd, and Pb accumulation

in A. halleri independently of the concentrations of heavy metals present in soils of A.

halleri natural habitats. However, the variation accounted for by each of the partial

RDA axes was far lower (RDA1: 14.5% and RDA2: 5.4%) than in the analysis of

samples from plants grown on metalliferous soils. The comparison of leaf

concentrations of Zn, Cd, Pb, and Fe in all different RNAi lines cultivated on non-

contaminated soil from Malmedy are shown in Figure 22 as a representative

illustration for the leaf heavy metal variation in plants grown on different non-

metalliferous soils. The results were similar to those of plants grown metalliferous

soils, but the magnitude of the concentrations of heavy metals was overall smaller.

Leaf Zn concentrations were significantly reduced only in HMA4-RNAi lines, which

contained between 5 and 30% of the wild-type leaf Zn concentrations (one-way

ANOVA, p < 0.001). Leaf Cd concentrations, however, were reduced to 17% of the

wild-type leaf Cd solely in HMA4-RNAi line 4.2.1 (one-way ANOVA, p < 0.001), but

not in lines 3.1.1 and 4.3.2. In all three FRD3-RNAi lines, leaf Pb concentrations

were significantly reduced to about 34% of the wild type leaf Pb concentrations (one-

way ANOVA, p < 0.001). In most of the independent HMA3- and HMA4-RNAi lines

leaf Pb concentrations were not significantly different from those of the wild type

(Figure 22c). These results suggest that the silencing of HMA4 affected Zn

hyperaccumulation at comparable magnitudes in both metalliferous and non-

metalliferous soils. Leaf Cd accumulation was more affected by the silencing of

HMA4 rather on metalliferous soils. The silencing of FRD3 caused notable

reductions in leaf Pb concentrations on both types of soils, but more on metalliferous

soils than on non-metalliferous ones. These observations suggest that FRD3 and

HMA4 might be more important for A. halleri in contaminated areas than in non-

contaminated ones. The silencing of HMA3 caused apparently stronger effects on

leaf Cd and Pb accumulation in plants on non-metalliferous soils. However, the

results were variable between independent HMA3-RNAi lines on Malmedy soil and

the differences between these lines and the wild type were not consistently

significant on other non-metalliferous.

In the RDA analysis of samples from plants grown on non-metalliferous soils (Figure

21) the FRD3 transcript levels and leaf Mg concentration were apparently correlated,

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and such strong correlation was not observed in the analysis of plants grown on

metalliferous soils (Figure 19). However, the leaf Mg concentrations were only

slightly reduced in FRD3-RNAi lines when compared to the concentrations found in

the wild type and no statistically significantly differences in Mg concentrations

between these genotypes were observed after cultivation on non-metalliferous soils

(Figure S15). Leaf Mg concentrations were significantly higher in some of the HMA3-

and HMA4-RNAi lines when compared with FRD3-RNAi lines on Malmedy and

Rodacherbrunn soils, and because FRD3 is not silenced in HMA3- and HMA4-RNAi

lines the relationship between leaf Mg concentrations and FRD3 transcript levels

might have arisen through lines other than the wild type and FRD3-RNAi.

Figure 21 Partial redundancy analysis of samples from non-metalliferous soils. Diagram shows the first two dimensions of partial redundancy analysis plot for samples from plants cultivated on three non-metalliferous soils from Malmedy, Wehbach and Rodacherbrunn. Shown are samples (symbols), leaf element concentrations (positions of larger characters), and their matrix correlations with transcript levels of AhHMA4 and AhFRD3 (arrows with smaller characters), for a model based on standardized (z-scores) of Log10(x + 1) leaf element concentrations and Log10(x +

1) transcript levels using Log10(x + 1) soil exchangeable element concentrations as a covariable. :

wild type, : HMA3-RNAi, : HMA4-RNAi, : FRD3-RNAi. Different shades represent independent RNAi lines for each of the target genes (the lighter the shade, the lower the transcript levels detected). Model fit was evaluated by ANOVA permutation test for RDA (p < 0.001, F = 12.0, adjusted R² = 0.12).

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Figure 22 Leaf metal concentrations of A. halleri plants cultivated on non-metalliferous soil from Malmedy. (a-d) Bargraphs show for wild type (black), HMA3-RNAi (yellow), HMA4-RNAi (blue) and FRD3-RNAi lines (red) (a) leaf Zn concentrations, (b) Leaf Cd concentrations, (c) Leaf Pb concentrations, (d) Leaf Fe concentrations. Shown are mean values + SD [n = 4 (RNAi lines) or 12 (4 replicates for each of the three different genotypes used as wild-type controls)] representative of one independent experiment. Different characters above the bars indicate statistically significant differences detected in a one-way ANOVA, followed by post-hoc Tukey HSD test and eta-Squared (η²) effect size test (a: one-way ANOVA, p < 0.001, F = 93.7, η² = 0.96; b: one-way ANOVA, p < 0.001, F = 17.5, η² = 0.81; c: one-way ANOVA, p < 0.001, F = 9.7, η² = 0.70, d: one-way ANOVA, p > 0.05). Three-week-old clones were transplanted into non-metalliferous soil from Malmedy and cultivated for five weeks before harvest.

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Results

The partial RDA analysis of plant growth and stress markers of samples from plants

cultivated on either metalliferous or non-metalliferous soils suggested that none of

the sets of RNAi lines seemed to undergo large effects on any of the stress markers

quantified by comparison to the magnitude of the effects resulting from soil

composition (Figure S16), because they all clustered at the RDA plot centroid. The

statistical models showed that transcript levels explained less than 4% of the

variation observed in those markers (ANOVA permutation test for RDA on

metalliferous soils: p < 0.001, F = 6.8, semi-partial R² = 0.03; non-metalliferous soils:

p < 0.001, F = 1.8, semi-partial R² = 0.02) (Table S1). A clustering pattern for HMA3-,

HMA4- and FRD3-RNAi lines was still visible for samples from metalliferous soils

(Figure S16a), but not for samples from non-metalliferous soils (Figure S16b). This

suggests that on some soils (but not on all) there might be differences between RNAi

lines and the wild type. Accordingly, the comparative analysis of those markers

between genotypes grown on each of the seven soils tested showed differences

between RNAi lines and wild type only for some of the markers in plants grown on

Langelsheim and Littfeld soils, which have the highest heavy metal contents. Plant

growth rate and shoot biomass were significantly reduced to 47-58% and 46-56% of

the wild-type (p < 0.001), respectively, in FRD3-RNAi lines grown on Langelsheim

soil (Figure 23a-b). HMA4-RNAi line 4.2.1 also displayed a similar strong reduction in

plant growth rate and shoot biomass, but the other two independent HMA4-RNAi

lines and all three HMA3-RNAi lines did not differ significantly from the wild type on

that soil. These differences were also observed in the same genotypes grown on

Littfeld soil. Leaf anthocyanin and TBARS concentrations were increased by 30-90%

and 79-125% (p < 0.001), respectively, in two of the three HMA4-RNAi lines when

compared with the wild-type concentrations on Langelsheim soil (Figure 23c-d).

Concentrations of these two markers in most of the independent HMA3- and FRD3-

RNAi lines were similar to or not significantly different from the wild-type

concentrations. After cultivation on Littfeld soil, leaf anthocyanin concentrations in

FRD3-RNAi lines were 100% higher than the concentrations found in the wild type

(p < 0.001), whereas HMA3- and HMA4-RNAi lines displayed anthocyanin

concentrations similar to those of the wild type (Figure 23e). Leaf H2O2

concentrations were significantly different from those of the wild type only in HMA4-

RNAi lines, in which the concentrations were reduced to 52-68% of the wild type

H2O2 concentrations (p < 0.001) (Figure 23f). H2O2 levels in FRD3-RNAi lines were

91

Results

comparable to the wild-type levels, and the levels observed in HMA3-RNAi lines

were not significantly different for any of the markers on any of the different soils.

Figure 23 Plant growth and stress markers of A. halleri plants cultivated on metalliferous soils from Langelsheim and Littfeld. (a-f) Bargraphs show for wild type (black), HMA3-RNAi (yellow), HMA4-RNAi (blue) and FRD3-RNAi lines (red). (a-d) Langelsheim soil (a) plant growth rate, (b) shoot biomass, (c) leaf anthocyanin concentrations, (d) leaf MDA equivalents (TBARS). (e-f) Littfeld soil (e) leaf anthocyanin concentrations and (f) leaf H2O2 concentrations. Different characters above the bars indicate statistically significant differences detected in a one-way ANOVA, followed by post-hoc Tukey HSD test and eta-Squared (η²) effect size test (a: one-way ANOVA, p < 0.001, F = 4.7, η² = 0.53; b: one-way ANOVA, p < 0.001, F = 4.5, η² = 0.52; c: one-way ANOVA, p < 0.001, F = 19.5, η² = 0.82; d: one-way ANOVA, p < 0.001, F = 4.2, η² = 0.50; e: one-way ANOVA, p < 0.001, F = 14.6, η² = 0.78; f: one-way ANOVA, p < 0.001, F = 8.5, η² = 0.67). Three-week-old clones were transplanted onto metalliferous soil from Langelsheim and Littfeld and cultivated for five weeks before harvest.

Since the HMA3-RNAi lines exhibited no strong phenotypes in comparison to the

wild type, and first insights had been gained on the role of the HMA4 gene in

previous studies and the role of FRD3 in A. halleri remained to be characterized, we

a a a

ab ab

a a

b b

b

HMA3- HMA4- FRD3-

RNAi lines

Littfeld

a a

b

a a a

a

b

b b

b

Langelsheim

a a a a

a

a

b b

b b

Langelsheim a

bc

b

c

bc bc

b

c cd

cd

Langelsheim

a

a a

b ab

b b ab ab b

Langelsheim

HMA3- HMA4- FRD3-

RNAi lines

b

a a

a

b b b

b

a b

a

b

a

Littfeld

HMA3- HMA4- FRD3-

RNAi lines

(d) (e) (f)

(c) (b) (a)

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Results

decided to further examine the specific mechanisms underlying the FRD3-dependent

Pb accumulation in A. halleri.

3.2 Functional characterization of the FRD3 gene

3.2.1 AhFRD3 is essential for Pb accumulation in leaves of Arabidopsis halleri

and also contributes to heavy metal tolerance

FRD3-RNAi plants were morphologically normal when cultivated alongside wild-type

plants on Langelsheim soil. However, they appeared smaller (Figure 13). Weekly

biomass production in FRD3-RNAi lines was reduced to between 45% and 58% of

the wild type (Figure 23). Shoot and root biomass were affected by metal toxicity in a

manner similarly to the plant growth rate, albeit with statistically significant

differences between FRD3-RNAi lines and the wild type only for shoot (48-60% of

wild-type biomass, Figure 23b) and not for root biomass (45-50% of wild-type

biomass Figure 24a). However, the 50% reduction in root biomass in FRD3-RNAi

lines was not significantly different likely due to the large variation in root biomass

within wild-type roots. This indicated that these lines produced less biomass than the

wild type on their native soil, possibly as a result of sensitivity to the high

concentrations of heavy metals contained in the soil.

A. thaliana frd3 mutant seedlings are known to exhibit Fe deficiency induced

chlorosis in leaves, which manifests itself in lowered leaf chlorophyll concentrations.

After five weeks of growth on Langelsheim soil, leaf chlorophyll concentrations were

determined. Contrary to A. thaliana frd3 loss-of-function mutants, no difference was

found for total chlorophyll between any of the FRD3-RNAi lines and the wild type

(Figure 24).

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Results

Figure 24 Root biomass and chlorophyll concentrations in FRD3-RNAi lines and wild type. (a) root biomass (one-way ANOVA, p = 0.07) and (b) total leaf chlorophyll concentration (one-way ANOVA, p = 0.09). Shown are arithmetic means + SD [n = 4 (FRD3-RNAi lines) or 12 (4 replicates for each of the three different genotypes used as wild-type controls)] representative of one out of four independent experiments. Three-week-old clones were transplanted to their native (Langelsheim) soil and cultivated for five weeks before harvest. ns: not significant.

Concerning metal hyperaccumulation, wild-type plants accumulated exceptionally

high concentrations of Pb in their leaves (mean = 408.3 µg g-1 DW). All three FRD3-

RNAi lines were strongly impaired in their ability to accumulate Pb in leaves, and

contained only 3.2% to 14.7% of the average leaf Pb concentration found in wild-

type lines (Figure 20c). As A. halleri is a known Zn and Cd hyperaccumulator, the

leaf concentrations of these elements were also determined in order to examine

whether the silencing of AhFRD3 would modify the leaf accumulation of Zn and Cd.

A significant difference in Zn concentrations was found only in leaves of one FRD3-

RNAi line 18.2 (Figure 20a). Nonetheless, the levels of leaf Zn observed in FRD3-

RNAi line 18.2 were still above the criterion for hyperaccumulation of this metal in

plants, which is established at >10,000 ppm (Baker and Brooks, 1989) or 3,000 ppm

(Krämer, 2010). Similar to Zn, the silencing of AhFRD3 did not significantly alter leaf

accumulation of Cd in FRD3-RNAi lines, in which Cd concentrations were

maintained between 93% and 111% of those in the wild type (Figure 20b). These

data suggested that the silencing of AhFRD3 by RNAi did not cause major or robust

alterations in Zn and Cd accumulation in leaves.

(a)

ns

FRD3-RNAi

(b)

ns

FRD3-RNAi

94

Results

The multivariate data analysis presented in the previous results section of this thesis

suggested that the observed effects of FRD3 silencing are very likely to occur

independently of soil mineral and/or chemical properties. This led us to a more

detailed examination of the leaf Pb accumulation of plants grown on a variety of A.

halleri native soils. Regardless of soil type, FRD3-RNAi lines accumulated

significantly less Pb than wild-type plants (Figure 25a-f). Leaf Pb concentrations in

FRD3-RNAi lines relative to the wild type on those different soils were between 8

and 15% (Littfeld soil), 23 and 26% (Evín-Malmaison soil), 19 and 29% (Bestwig

soil), all of which were metalliferous. On non-metalliferous soils, leaf Pb

concentrations in FRD3-RNAi lines were between 30 and 32% (Malmedy soil), 34

and 44% (Wehbach soil), and 50% and 75% (Rodacherbrunn soil) of the wild type

leaf Pb concentrations. Despite the fact that no statistically significant reduction was

detected in Pb accumulation for FRD3-RNAi lines after cultivation on the non-

metalliferous soil from Rodacherbrunn (Figure 25f), likely because of its very low soil

Pb content, RNAi lines showed a trend for lowered Pb concentrations when

compared to leaf Pb concentrations in the wild-type. When cultivated on Evín-

Malmaison soil, the average for leaf Pb concentrations in the wild type was 580 µg

g-1 DW, and 991 µg g-1 DW was the highest concentration accumulated by any

individual plant on this soil (Figure 25b). These data are surprising considering that

Pb is a non-essential element and is usually found at low concentrations in other

plants – between 17 µg g-1 DW in roots and tubers, and 37 µg g-1 DW in leaves of

vegetables (Fischer et al., 2014).

95

Results

Figure 25 The role of AhFRD3 in leaf Pb accumulation is independent of soil mineral and chemical properties. Bargraphs show leaf Pb concentrations in the wild-type and FRD3-RNAi lines upon cultivation in (a) metalliferous Littfeld soil (one-way ANOVA, p < 0.001, F = 40.6, η² = 0.86), (b) metalliferous Evín-Malmaison soil (one-way ANOVA, p < 0.01, F = 12.2, η² = 0.65), (c) metalliferous Bestwig soil (one-way ANOVA, p < 0.01, F = 13.4, η² = 0.74), (d) non-metalliferous Malmedy soil (one-way ANOVA, p < 0.001, F = 35.8, η² = 0.84), (e) non-metalliferous Wehbach soil (one-way ANOVA, p < 0.05, F = 6.6, η² = 0.48), and (f) non-metalliferous Rodacherbrunn soil (one-way ANOVA, p = 0.1). Shown are means + SD [n = 4 (FRD3-RNAi lines) and 12 (4 replicates for each of three the independent wild-type lines)] from one experiment representative of three independent experiments for metalliferous soils and one experiment for non-metalliferous soils. Different characters above the bars indicate statistically significant difference between the wild type and the respective FRD3-RNAi line by one-way ANOVA, followed by post-hoc Tukey HSD test and eta-Squared effect (η²) size test. Three-week-old clones were transplanted and cultivated for five weeks on different soils hosting natural populations of A. halleri. ns: not significant.

Of particular interest was Fe status and Fe homeostasis in FRD3-RNAi transgenic

lines. Leaf Fe concentrations did not significantly differ between FRD3-RNAi lines

and wild-type plants cultivated on native Langelsheim soil (Figure 20d). In fact, this is

different from expectations based on the frd3 mutant phenotypes. Unlike Fe, leaves

b

a

b b

(d) (e)

b

a

b b

ns

(f)

FRD3-RNAi FRD3-RNAi FRD3-RNAi

b

a

b b

(a)

a

b b b

(b)

a

b

b b

(c)


96

Results

of FRD3-RNAi 9.1 and 18.2 lines exhibited significantly higher concentrations of Mn

(232 to 234% of the wild type), whereas Mn levels of FRD3-RNAi line 7.1 did not

differ from the wild type (Figure 26).

Figure 26 Silencing of FRD3 does not robustly affect Mn concentrations in leaves of A. halleri. Bargraph shows wild-type and FRD3-RNAi lines for leaf Mn concentrations (p < 0.001, F = 26.0, η² = 0.80). Shown are means + SD [n = 4 (FRD3-RNAi lines) or 12 (4 replicates for each of the three independent wild-type lines)] from one experiment representative of four independent experiments. Different characters above the bars indicate statistically significant difference between the wild type and the respective FRD3-RNAi line by one-way ANOVA, followed by post-hoc Tukey HSD test and eta-Squared effect (η²) size test. Three-week-old clones were transplanted and cultivated for five

weeks on native Langelsheim soil before harvest and analysis.

Not only metal over-accumulation but also transcript levels of a variety of genes are

reported to be increased in leaves of plants experiencing physiological Fe deficiency

(Schuler et al., 2012; Waters et al., 2012; Zhai et al., 2014). To obtain additional

information on the Fe status in above-ground tissues of FRD3-RNAi lines, transcript

levels of Ferritin 1 (FER1), Fe(III) chelate reductase 3 (FRO3) and Oligopeptide

Transporter 3 (OPT3) were determined in leaves of these RNAi lines and the wild

type grown on Langelsheim soil. None of these three Fe deficiency marker genes

displayed statistically significant upregulation in FRD3-RNAi lines when compared to

the wild type (Figure 27a-c). On the one hand, FER1 transcript levels were

inconsistent between the independent RNAi lines. FRD3-RNAi 7.1 and 18.2 lines

displayed increased transcript levels (46 and 120% of the wild type) whilst line 9.1

displayed a 38% reduction in transcript levels (Figure 27a). On the other hand, all

three independent FRD3-RNAi lines contained higher transcript levels of FRO3 and

OPT3 in comparison to the wild type, but not statistically significant. These results

b b

a a

FRD3-RNAi

97

Results

are consistent with the observed changes in leaf Fe accumulation, in which leaves of

FRD3-RNAi lines contained slightly, but not statistically significant, reduced levels of

Fe. In summary, leaves of A. halleri FRD3-RNAi are physiologically slightly more Fe-

deficient than the wild type, but the alteration is far less dramatic than previously

reported in seedlings of A. thaliana frd3 mutants.

Figure 27 Small upregulation of Fe deficiency responsive genes in FRD3-RNAi lines Bargraphs show transcript levels relative to Helicase (HEL) in wild-type and FRD3-RNAi lines for (a) FER1 (one-way ANOVA, p = 0.1), (b) FRO3 (one-way ANOVA, p = 0.06), and (c) OPT3 (one-way ANOVA, p = 0.08). Shown are means + SD [n = 4 (FRD3-RNAi lines) or 12 (4 replicates for each of the three independent wild-type lines)] of one experiment representative of four independent experiments. Three-week-old clones were transplanted and cultivated on native Langelsheim soil for five weeks before harvest of leaves. ns: not significant.

Taken together, observations in FRD3-RNAi lines include (i) a dramatic decrease in

leaf Pb accumulation, (ii) a moderate decrease in biomass production on the native

soil, possibly caused by heavy metal sensitivity, (iii) only marginally altered Zn and

Cd accumulation, and (v) only a slight physiological Fe deficiency in shoots. This

suggests that the main role of A. halleri FRD3 on native soils might be in leaf Pb

accumulation. It remains possible, however, that FRD3 is more important for plant

survival and fitness in natural contaminated environments than our experiments

suggested, which were conducted under controlled plant growth chamber conditions.

(a)

ns

(b)

ns

(c)

ns


98

Results

3.2.2 Characterization of an A. thaliana frd3 loss-of-function mutant with

respect to Pb accumulation and tolerance

Having observed the role of AhFRD3 and Pb accumulation in A. halleri, the

investigation of whether A. thaliana FRD3 promotes leaf Pb accumulation and basal

Pb tolerance was carried out. Both A. thaliana wild-type and frd3-1 mutant plants did

not survive cultivation on the highly heavy metal-contaminated Langelsheim soil

used for the experiments with A. halleri. We established an agar-solidified growth

medium containing Pb for the cultivation of seedlings on plates. Pb is well-known for

its pH-dependent and low solubility, partly caused by the ease of formation of Pb-

phosphate precipitates (Ma et al., 1995; Martinez and Motto, 2000). Therefore,

experiments were carried out on a low-pH Hoagland medium with reduced

phosphate concentration, in order to preserve Pb solubility. By testing media in a pH

range from 4.0 to 6.0 with the addition of only 50% phosphate to the media and

increasing concentrations of Pb acetate, the pH 4.0 was the most appropriate for the

experiments, because this was the lowest medium pH in which wild-type A. thaliana

seedlings were morphologically similar to seedlings grown on regular Hoagland

growth medium and no visible Pb precipitation was observed (Figure S17).

In order to test whether the frd3-1 mutant was sensitive to Pb, we evaluated plant

biomass and root elongation of plants grown on agar-solidified media containing

increasing concentrations of Pb (0 for control, 1, 5, 25 and 50 µM lead acetate).

Seedlings of frd3-1 were chlorotic, with slightly shorter roots and a smaller rosette

than the wild type, and this was observed across all media including control medium

without added Pb (Figure 28a). The analysis of plant biomass revealed that wild-type

and frd3-1 biomass did not differ statistically in control medium or 1 µM Pb medium.

However, in the 5 µM Pb medium, wild-type plant biomass was still similar to plants

grown on the control medium, whereas biomass was significantly reduced by about

50% in frd3-1 when compared with frd3-1 plants on control medium (p < 0.01)

(Figure 28b). In both media containing 25 µM and 50 µM Pb no statistically

significant differences were observed between the two genotypes.

99

Results

Figure 28 The A. thaliana frd3-1 mutant is moderately hypersensitive to Pb. (a) Photographs of wild-type and frd3-1 seedlings on control, 5 µM Pb and 50 µM Pb media after 16 days of cultivation. Diagrams show, for wild-type and frd3-1 seedlings grown on control and Pb-containing media, (b) plant biomass (Factorial AVOVA, p < 0.05, F = 3.6, η² = 0.41) and (c) root length (p < 0.05, F = 223.4, η² = 0.43). Shown are mean values + SD [n = 3 for plant biomass (replicate was petri dish plate, each containing 10 pooled seedlings) and n = 30 for root length (measured individually for each of the 10 seedlings in three petri dish plates)]. Different characters above the bars indicate statistically significant difference among mean values by Analysis of Variance (Factorial ANOVA) followed by Post-Hoc test Tukey HSD and eta-Squared (η²) effect size test (between genotypes). A. thaliana Col-0 and frd3-1 mutant seedlings were grown on modified ¼ Hoagland solid medium supplemented with Pb in long days (16 h light at 22°C and 8 h dark at 18°C, 120 µmol m

-2 s

-1)

for 16 days.

Similar to the plant biomass, root length of wild type and frd3-1 did not differ

significantly between genotypes in either control or 1 µM Pb media, although frd3-1

roots were shorter than wild-type roots. Significant differences in root length were

observed between wild-type and frd3-1 seedlings in media containing 5 µM, 25 µM

and 50 µM Pb (Figure 28c). However, in spite of the differences between means

(a)

frd3-1 Col-0

0 µM Pb

frd3-1 Col-0

5 µM Pb

frd3-1 Col-0

50 µM Pb

(b)

a a

a

ab

a

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cd d

cd

bc

(c)

a a

a a a

c

d

ef

f g

Pb conc. in medium (µM) Pb conc. in medium (µM)

100

Results

being significant, the extent of root growth inhibition was not as severe as reported

for the Pb sensitive cad1-3 and cad1-6 mutants (Fischer et al., 2014).

We cultivated wild-type, frd3-1, and cad1-3 on the low-phosphate low-pH (LPP)

medium suggested by Fischer et al. (2014) for Pb tolerance studies. The results

suggested that frd3-1 was not sensitive to Pb on that medium when compared to

wild-type and cad1-3 mutant seedlings (Figure 29). In fact, on LPP medium, roots of

frd3-1 were slightly longer than the wild-type roots.

Figure 29 A. thaliana Col-0, cad1-3 and frd3-1 grown on LPP agar-solidified medium. A. thaliana Col-0, frd3-1, and cad1-3 were cultivated on Low-Phosphate Low-pH (LPP) medium supplemented with Pb in long days (16 h light at 22°C and 8 h dark at 18°C, 120 µmol m

-2 s

-1) for 20

days.

Next, we examined the Fe deficiency responses and metal concentrations in shoots

and roots of wild-type and frd3-1 seedlings. The increase in root surface Fe(III)

chelate reductase activity is a well-established marker for Fe deficiency. Fe(III)

chelate reductase activity significantly increased with the increasing Pb

concentrations in the media, whereas no statistically significant increase in activity

was observed for the wild type even at the highest concentration of Pb (Figure 30a).

This finding suggests that increasing concentrations of Pb in the media strongly

enhanced physiological Fe deficiency in the frd3-1 mutant, but only slightly in the

wild type.

The metal concentrations in shoots and roots of both genotypes were also analyzed

in order to test whether AtFRD3 is also involved in Pb accumulation in A. thaliana. In

all different media, shoot Pb concentrations in the wild type did not differ significantly

from frd3-1. However, in the presence of higher Pb concentrations in the media (25

frd3-1 Col-0

0 µM Pb

cad1-3 frd3-1 Col-0

5 µM Pb

cad1-3 frd3-1 Col-0

10 µM Pb

cad1-3

101

Results

µM and 50 µM Pb), there was a trend for higher Pb concentrations in shoots of frd3-

1 seedlings than wild-type seedlings (Figure 30b). This was surprising because the

observations in A. halleri FRD3-RNAi plants led us to expect less Pb in the shoots of

frd3-1 than in the wild-type shoots. Similar to the shoots, roots of frd3-1 contained

more Pb than wild-type roots when Pb was present in the media, but a statistically

significant difference was detected only in roots at the two highest Pb concentrations

(Figure 30c).

Figure 30 A loss-of-function frd3-1 mutant of A. thaliana accumulates more Pb in its shoots and displays enhanced Fe deficiency responses under Pb exposure, in contrast to A. halleri. Bargraphs show, for wild-type and frd3-1 seedlings grown on control and Pb-containing, (a) Fe(III) chelate reductase activity (p < 0.05, F = 52.9, η² = 0.73), (b) shoot Pb concentrations (p < 0.05, F = 5.9, η² = 0.23), and (c) root Pb concentrations (p < 0.01, F = 25.9, η² = 0.56). Shown are mean values + SD [n = 3 independent petri plates, each containing 10 seedlings, of which tissues were pooled for analysis)]. Different characters above the bars indicate statistically significant difference among mean values by Analysis of Variance (Factorial ANOVA) followed by Post-Hoc test Tukey HSD and eta-Squared (η²) effect size test (between genotypes). A. thaliana Col-0 and frd3-1 mutant seedlings were grown on modified ¼ Hoagland solid medium supplemented with Pb in long-day conditions (16 h light at 22°C and 8 h dark at 18°C, 120 µmol m

-2 s

-1) for 16 days.

The concentrations of Fe, Zn, and Mn in shoots and roots of wild-type and frd3-1

seedlings were measured (Figure 31). Shoots of frd3-1 contained about 40% lower

Fe concentrations compared with the wild-type shoots upon cultivation on control

medium (p < 0.05, Figure 31a), and about 30% lower Fe concentrations under

exposure to low Pb concentrations (p > 0.05). When cultivated in 1 µM Pb, shoot Fe

levels in the wild type were about 40% of the Fe in the wild-type shoots on Pb-free

control medium (p < 0.05) and remained similarly low at higher Pb concentrations. In

shoots of Pb-exposed frd3-1 plants, the dependence of shoot Fe concentrations on

(c)

c c c c

bc

bc

bc ab

a

a

(b)

d d d d d d

cd

bc

ab

a

(a)

e

de

e

cd

e e

bc

e

a

de

(µm

ol F

e(I

I) g

FW

-1 h

-1)

Pb conc. in medium (µM) Pb conc. in medium (µM) Pb conc. in medium

(µM)

102

Results

medium Pb levels was similar to the wild type. Shoot Zn concentrations did not differ

statistically between the two genotypes regardless of the Pb concentration added to

the media (Figure 31b). With regard to shoot Mn, frd3-1 shoots contained lower Mn

concentrations than the wild-type shoots in all media. However, this was statistically

significant only in the control, 1 µM Pb and 5 µM Pb media (p < 0.05) (Figure 30c).

This was intriguing, since based on the frd3 mutants phenotypes higher

concentrations of Mn in shoots were expected.

Roots of the frd3-1 mutant contained substantially higher Fe concentrations than

wild-type roots in all media used (p < 0.05) (Figure 31d). At high Pb concentrations in

the media (25 µM and 50 µM Pb), root Fe concentrations in frd3-1 were significantly

lower than its root Fe concentrations found under control, 1 µM and 5 µM Pb

exposure. Root Zn concentrations were variable in the genotypes and the only

differences found were the significantly reduced root Zn concentrations of the wild-

type on high Pb media (25 µM and 50 µM Pb) compared with frd3-1 roots in the

control medium (Figure 31e). The root Mn concentrations in the frd3-1 were

significantly higher than the wild-type roots, with exception of seedlings grown on the

medium with the highest Pb concentration, in which no statistically significant

difference was detected between genotypes.

Together these findings demonstrate that, firstly, AtFRD3 does not promote Pb

accumulation in A. thaliana since the alterations in shoot Pb accumulation in the

frd3-1 are opposite to that observed in A. halleri FRD3-RNAi. Secondly, the data

suggest that Pb accumulation in frd3-1 is likely to occur via Fe uptake pathways.

This occurred as a consequence of highly enhanced Fe deficiency responses

exhibited by the frd3-1 mutant plants under control conditions and progressively with

increasing Pb concentrations in the medium, as suggested by root surface ferric

chelate reductase activity as a marker for Fe deficiency. The data also suggested

that the highest concentrations of Pb in the media induced a slight decrease in shoot

Mn concentrations.

103

Results

Figure 31 Fe, Zn, and Mn shoot and root concentrations in wild-type and frd3-1 mutant seedlings after cultivation in Pb-containing media. Bargraphs show for wild-type and frd3-1 seedlings grown on control media and media containing increasing concentrations of Pb, (a) shoot Fe concentration, (b) shoot Zn concentration, (c) shoot Mn concentration, (d) root Fe concentration, (e) root Zn concentration, and (f) root Mn concentration. Shown are mean values + SD [n = 3 replicate petri dishes, each containing 10 seedlings, which were pooled per dish for analysis)]. Different characters above the bars indicate statistically significant difference among mean values by Analysis of Variance (Factorial ANOVA) followed by Post-Hoc test Tukey HSD and eta-Squared (η²) effect size test (between genotypes). ns: not significant. A. thaliana Col-0 and frd3-1 mutant seedlings were grown on modified ¼ Hoagland solid medium supplemented with Pb, in long days conditions (16 h light at 22°C and 8 h dark at 18°C, 120 µmol m

-2 s

-1) for 16

days.

a

b

b b

b b

b b

b b

(a)

ns

(b)

a

b b

b

ab

b

ab

b

a a

(c)

a

b

ab

c c

d d d d

cd

(d)

a

b

b

ab

ab

ab

ab ab

ab

ab

(e)

a

c bc

c c c c

ab

ab ab

(f)

Pb conc. in medium (µM) Pb conc. in medium (µM) Pb conc. in medium (µM)

104

Results

3.2.3 AhFRD3 promotes root-to-shoot partitioning of Pb

To determine how AhFRD3 enhances shoot Pb accumulation in A. halleri,

hydroponically grown plants were used to obtain data for roots, since soil

experiments are prohibitive for analytical root measurements except root biomass.

Three-week-old individuals of the FRD3-RNAi 18.2 line and wild type were cultivated

either in control (no added Pb) and heavy metal-amended (40 µM Pb) modified

Hoagland solution. These treatments were administered for two weeks.

Pb was below 17 µg g-1 dry weight in roots of both genotypes grown under control

conditions. Note that in control medium, to which no Pb was added, the low plant Pb

concentrations were likely derived from Pb already present in plant tissues prior to

the experiment, because the source plants used for making clones were cultivated

on a mixture of 5% (v/v) Pb-contaminated native soil from Langelsheim and minitray

commercial potting soil. When 40 µM Pb was included in the hydroponic medium,

roots of the FRD3-RNAi accumulated 44% more Pb than those of the wild-type roots

(p < 0.01) (Figure 32a). Leaf Pb concentrations were significantly lower in the FRD3-

RNAi than in the wild type, in accordance with results from soil-grown plants (Figure

32b).

The use of hydroponically grown plants also permitted the assessment of root Fe

deficiency responses in A. halleri, which are characteristically induced in all A.

thaliana frd3 mutants (Green and Rogers, 2004; Rogers and Guerinot, 2002).

Analysis of root surface Fe(III) chelate reductase activity showed that there are no

significant differences between roots of the FRD3-RNAi and the wild type in any of

the two treatments (Figure 32c). Despite a trend for slightly higher Fe(III) chelate

reductase activity in FRD3-RNAi roots under control conditions, this increase was

quantitatively far less pronounced than the difference between A. thaliana wild-type

and frd3 mutants. FRD3-RNAi plants displayed a less than 2-fold higher activity than

wild-type roots, whereas in A. thaliana frd3 mutants several independent reports

demonstrated between 2-fold and 22-fold higher activity in roots of those mutants

when compared with the wild-type roots (Delhaize, 1996; Durrett et al., 2007; Rogers

and Guerinot, 2002). This finding is in accordance with what was found in leaves of

soil-grown A. halleri plants regarding the upregulation of genes in response to Fe-

105

Results

deficiency. In that case, all independent FRD3-RNAi lines also did not to show signs

of pronounced Fe deficiency in above ground tissues (Figure 27).

Figure 32 Root-to-shoot partitioning of Pb is impaired in a FRD3-RNAi line, and citrate concentration in its xylem exudates is reduced. Bargraphs show for wild type and FRD3-RNAi and each treatment (a) root Pb concentration (in 40 µM Pb only: p < 0.01, t = -4.2, Cohen’s D = 2.4), (b) leaf Pb concentration (0 µM: p < 0.01, t = 3.8, cohen’s D = 2.2; 40 µM: p < 0.05, t = 2.4, cohen’s D = 1.7), (c) root surface Fe(III) chelate reductase activity (0 µM: p = 0.09; 40 µM: p = 0.9), (d) citrate concentration in xylem exudates (0 µM: p < 0.05, t = 3.0, Cohen’s D = 1.8; 40 µM p = 0.2), (e) malate concentration in xylem exudates (0 µM: p = 0.3; 40 µM p = 0.5), and (f) Fumarate concentration in xylem exudates (0 µM: p = 0.2; 40 µM p = 0.5). Shown are mean values + SD (n = 6). Asterisks above the bars indicates statistically significant difference between wild-type and FRD3-RNAi in each treatment by Student’s independent t-test (* = p < 0.05; ** = p < 0.01) followed by Cohen’s D effect size test. ns: not significant. Two-week-old wild-type TC and FRD3-RNAi line 18.2 plants were treated for two weeks with modified Hoagland solution (0 µM) and the same solution supplemented with lead acetate (40 µM).

(a)

**

(b)

**

*

(c)

ns

ns

(µm

ol F

e(I

I) g

FW

-1 h

-1)

(d)

Pb in the media

ns ns

(e)

Pb in the media

ns

ns

(f)

Pb in the media

*

ns

106

Results

In A. thaliana, FRD3 is thought to mediate citrate efflux from root pericycle cells into

xylem vessels. Thus, the hypothesis that less citrate is present in the xylem exudates

of the FRD3-RNAi line 18.2 was tested. Xylem exudates were collected from

hydroponically-grown A. halleri plants for two hours, and then analyzed for the

organic acid profile using HPLC. Independent of the presence of Pb in the media,

xylem exudates of the FRD3-RNAi contained less citrate when compared to the wild

type (p < 0.05 at 0 µM Pb, p > 0.05 at 40 µM Pb; Figure 32d). Concentrations of both

malate and fumarate did not differ significantly between genotypes under either

control or Pb-amended medium (Figure 32e-f), but there was a trend for both malate

and fumarate concentrations to be lower in xylem exudates of the FRD3-RNAi plants

in comparison to the wild type.

Our HPLC method detected the existence of two other compounds (peak X1 and X2)

which did not fit to any of the calibration standard compounds used in the analysis

(Figure 33). Interestingly, one of these compounds (peak X1) seemed inversely

related to the expression of FRD3 in A. halleri and was not detected in A. thaliana

xylem exudates. This compound is now a good candidate for future identification

through Mass Spectrometry.

107

Results

Figure 33 HPLC chromatogram of xylem exudates from A. halleri (wild type and FRD3-RNAi line 18.2) and A. thaliana (wild-type and frd3-1 mutant). Y-axis corresponds to milliabsorbance units (left y-axis: A. thaliana; right y-axis: A. halleri). Peaks were normalized to the volume of each sample. X1 and X2

peaks correspond to unknown compounds identified in the analyzed xylem exudates that did not fit to any of the standard compounds used in the method

employed (see Table 8 in the methods section 2.5).

A. halleri A. thaliana

Wild type wild type

FRD3-RNAi frd3-1

0

20

40

60

80

100

120

140

160

180

200

Ab

so

rba

nce

at 2

10 n

m (

mA

U)

Retention time (min) 0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40

X2

Citrate

Fumarate

Citrate

Malate

X1

Injection Peak

20

80

100

120

140

0

40

60

108

Results

To gain detailed insights into plant Fe status, the element concentrations were

analyzed in roots. Roots of FRD3-RNAi plants contained significantly higher Fe

levels than the wild-type plants, regardless of the Pb status in the media (Figure

34a). Root Zn concentrations were slightly higher in roots of the FRD3-RNAi than in

the wild-type roots (15 and 26% in control and 40 µM Pb condition, respectively).

However, the increase in Zn concentrations did not significantly differ between the

genotypes in both conditions (Figure 34b). Mn concentrations were higher in FRD3-

RNAi roots than in the wild type only under control conditions, but not upon

cultivation in 40 µM Pb (Figure 34c). Leaf metal concentrations were also measured,

aiming to compare these with the accumulation profile in above-ground tissues of

plants grown on soil (Figure 20 and Figure 26). Leaf Fe, Zn and Mn concentrations

did not show any statistically significant differences between wild type and the FRD3-

RNAi, regardless of whether Pb was added to the media (Figure 34d-f). Despite the

fact that leaf Zn concentrations were not significantly different between the

genotypes in both conditions, there was a trend in which FRD3-RNAi line 18.2

contained less Zn in leaves than the wild type (Figure 34e), consistent with what was

found for this line upon growth on soil (Figure 20).

These findings suggested that the FRD3-RNAi line 18.2 analyzed in detail displays

similar phenotypes to frd3 mutants of A. thaliana with respect to root Fe and Mn

concentrations and published citrate levels in the xylem sap, but not regarding Zn

concentrations. However, the magnitude of the differences observed between the

FRD3-RNAi line 18.2 and wild type is generally smaller than between frd3 mutants

and wild-type plants of A. thaliana.

In conclusion, these data support that in the hydroponic experiments conducted

here, adult A. halleri plants may regulate Fe homeostasis distinctly from A. thaliana

seedlings when FRD3 expression is strongly reduced. Additionally, different from

what was reported previously in A. thaliana, FRD3 has a role in promoting root-to-

shoot partitioning of Pb in A. halleri, which was far more pronounced than any role in

root-to-shoot Fe partitioning in the experiments conducted here.

109

Results

Figure 34 Metal concentration in roots and shoots of FRD3-RNAi and wild-type plants cultivated hydroponically. Bargraphs show for wild type and FRD3-RNAi and each treatment (a) root Fe concentration (0 µM: p < 0.001, t = -6.5 Cohen’s D = 3.8; 40 µM: p < 0.001, t = -7.8 Cohen’s D = 4.5), (b) root Zn concentration (0 µM: p = 0.4; 40 µM: p = 0.05), (c) root Mn concentration (0 µM: p < 0.01, t = -3.8, Cohen’s D = 2.1; 40 µM: p = 0.4), (d) leaf Fe concentration (0 µM: p = 0.8; 40 µM: p = 0.6), (e) leaf Zn concentration (0 µM: p = 0.08; 40 µM: p = 0.2), (f) leaf Mn concentration (0 µM: p = 0.4; 40 µM: p = 0.1). Shown are mean values + SD (n = 6). Asterisks above the bars indicates statistically significant difference between wild-type and FRD3-RNAi in each treatment by Student’s independent t-test (* = p < 0.05; ** = p < 0.01) followed by Cohen’s D effect size test. ns: not significant. Two-week-old wild-type TC and FRD3-RNAi line 18.2 plants were treated for two weeks with modified Hoagland solution (0 µM) and the same solution supplemented with lead acetate (40 µM).

ns

ns

(b)

***

***

(a)

**

ns

(c)

ns

ns

(f) (e)

ns

ns

(d)

ns

ns

Pb in the media Pb in the media Pb in the media

110

Results

3.2.4 The comparison of the predicted amino acid sequences of FRD3

proteins of A. halleri and A. thaliana

The alignment of the predicted amino acid sequences of FRD3 proteins suggested

that A. halleri FRD3 is four amino acids longer (530 aa) than A. thaliana FRD3 (526

aa), as a result of an insertion after the 12th amino acid (Figure 35). Besides that,

another 25 amino acids were changed in the predicted FRD3 sequence of A. halleri

in comparison to A. thaliana FRD3. Amongst those changes, the N116S substitution

was reported to be part of a combination of modifications that abrogates citrate efflux

in certain accessions of A. thaliana (Pineau et al., 2012). However, our xylem

exudate analyses suggested that the FRD3 protein of A. halleri wild type plants is

functional with regard to loading citrate into the root xylem (Figure 32c).

TM I

TM II

TM III TM IV

TM V TM VI

TM VII

TM VIII TM IX

TM X TM XI

TM XII

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Results

Figure 35 Alignment of predicted amino acid sequence of FRD3 proteins of A. halleri and A. thaliana. A. halleri FRD3 (predicted from the coding sequence obtained by the sequencing of PCR-amplified cDNA fragment of willd-type Langelsheim accession Lan3.1) was used for sequence alignment with FRD3 of A. thaliana (obtained in the TAIR database) by ClustalW2. Asterisks (*) indicate fully conserved amino acids, colons (:) indicate conservation within groups of amino acids of strongly similar properties, period, (.) indicates conservation between amino acids within groups of weakly similar properties, and dash (-) indicates gap between the compared sequences. Black lines above the sequence represent the 12 alpha-helical transmembrane regions characteristic of MATE proteins.

3.2.5 Pb is localized mostly in the vasculature and trichomes of A. halleri

leaves

Maps of Pb in leaves of the wild type TC and FRD3-RNAi line 18.2 were generated

and ROIs (trichome, trichome base, nerve, and interveinal) were selected with the

aim of determining the concentration of Pb only in regions where Pb was accurately

detected (i.e. above detection limits). Although the detection of Pb was accurate

enough for determining Pb concentrations across the leaf area analyzed, the

beamtime acquisition was too limited to achieve a visible pixel map for Pb.

Therefore, in the overlay with other elements Pb is not visible (Figure 36). However,

the sum of the Pb signal provided sufficient statistics to obtain local Pb quantification

in ROIs (Table 14). In wild-type leaves, Pb was found at higher concentrations in the

veins (633 µg g-1) and at the base of the trichomes (1121 µg g-1) than in the

interveinal space (244 µg g-1). Leaf Pb concentrations in the FRD3-RNAi line 18.2

were below detection limits of this technique (Table 14). This was in general in

agreement with the observations of substantially lower leaf Pb concentrations in

FRD3-RNAi plants (Figure 20c and Figure 25). In conclusion, Pb is apparently

retained in the veins and stored at the base of trichome in wild-type plants, likely to

prevent Pb from entering photosynthetically active cells.

112

Results

Figure 36 µPIXE-based identification of regions of interest containing Pb in leaves of A. halleri. Elemental distribution in leaves of A. halleri wild type TC and FRD3-RNAi line 18.2 grown on native metal-contaminated soil from Langelsheim. Samples were freeze-dried under vacuum. Shown is a representative map of three replicates for wild-type lines and two for FRD3-RNAi lines. Region of interest rich in Pb are delimited by white lines. bt: trichome base. Ca: blue and K: green. Scale bar: 50 µm.

Table 14 µPIXE/RBS quantification of Pb (µg g-1) in leaves of soil-grown A. halleri wild-type and FRD3-RNAi plants.

ROI Wild Type FRD3-RNAi

Whole leaf 268 ± 198 Udl

Interveinal 244 ± 128 Udl

Vein 633 ± 477 0

Trichome 256 ± 110 Udl

Trichome base 1,121 ± u Udl

u: undetermined (only one replicate); udl: under detection limit (≤ 30 ppm).

3.2.6 FRD3 promotes Pb mobility across shoot tissues in A. halleri

After observing that Pb is localized mainly in the veins and trichomes of leaves, and

to understand how the concentrations of Pb and other metals are modified between

different parts of the shoot in A. halleri, we dissected the aerial portion of wild-type

(TC and TrC lines) and FRD3-RNAi (7.1 and 18.2 lines) into leaf blade, petiole and

stem, and analyzed their elemental contents by ICP-OES. Elemental contents (in µg)

were determined by multiplying metal concentration (in µg g-1) and dry biomass (in g)

of each sample.

First, the total metal contents of the shoots were determined by the summation of

metal contents of all above-ground tissues per plant (leaf blade, petiole and stem) for

the comparison between the different genotypes and lines. In agreement with results

presented above, the total shoot Pb content was significantly higher in wild-type

Wild type FRD3-RNAi

113

Results

shoots than in FRD3-RNAi lines (Figure 37a). No statistically significant differences

for total shoot Fe, Zn, or Mn contents were found between wild-type and FRD3-RNAi

lines (Figure 37b-d). The mean total shoot Mn content in FRD3-RNAi line 18.2 was

on average 69% higher than in line 7.1 and wild-type shoots. These results are in

agreement with the Mn concentrations measured in FRD3-RNAi line 18.2 in earlier

soil experiments (Figure 26). To highlight again, the FRD3-RNAi line 18.2 is also the

one that displayed the strongest reduction of FRD3 transcript levels.

Figure 37 Silencing of FRD3 affects only Pb content in shoots of A. halleri. Three-week-old clones of wild-type (pooled TC and TrC lines) and FRD3-RNAi lines 7.1 and 18.2 were cultivated on native Langelsheim soil for five weeks. Bargraphs show for wild-type lines (filled bars) and FRD3-RNAi lines (open bars) (a) total shoot Pb content (p < 0.001, F = 20.3, η² = 0.34), (b) total shoot Fe content (p = 0.9), (c) total shoot Zn content (p = 0.8), (d) total shoot Mn content (p = 0.5). Shown are mean values + SD [n = 6 (wild type) and 3 (FRD3-RNAi lines)] from one representative experiment. Different characters above the bars indicate statistically significant differences detected in a one-way ANOVA, followed by post-hoc Tukey HSD test and eta-Squared (η²) effect size test.

Shoots were also analyzed separately by different tissues and ages. Pb contents in

leaves and petioles of different ages were between 45 and 95% higher in the wild

type when compared with FRD3-RNAi lines (p < 0.001). These differences were

largest in older and intermediately aged leaves (Table 15). In stems, Pb contents

were at comparable levels between those genotypes, except in older stems where

Pb content was 60% higher in the wild type than in FRD3-RNAi lines. These data

suggested that, besides the impaired root-to-shoot translocation of Pb, FRD3-RNAi

(c)

ns

FRD3-RNAi

a

b b

(a)

FRD3-RNAi

(b)

ns

FRD3-RNAi

(d)

ns

FRD3-RNAi

114

Results

plants have defects in transferring Pb from stems into petioles and, subsequently,

into leaves when compared to the wild type.

Fe contents were mostly similar between genotypes and significantly difference

between wild type and FRD3-RNAi lines was detected only in intermediately aged

petioles, in which the wild type contained 56-62% of the Fe content in FRD3-RNAi

lines petioles (p < 0.01). The differences found for Zn content between wild type and

FRD3-RNAi lines in different tissues and ages were not clearly consistent such as

the differences found for Pb content, when considering the silencing of FRD3. For

instance, Zn contents in wild type young leaves were significantly higher (59%) only

when compared with FRD3-RNAi line 7.1 young leaves (p < 0.01), but not compared

with FRD3-RNAi line 18.2. In older and intermediately aged petioles however, Zn

content was comparable between wild type and FRD3-RNAi line 7.1, and both

contained significantly lower Zn than in FRD3-RNAi line 18.2 (p < 0.01). Mn content

was significantly higher in both older and young leaves of FRD3-RNAi line 18.2 when

compared with the wild type and FRD3-RNAi line 7.1 (p < 0.05), but the differences

were not significant in other tissues (Table 15).

Together, these results suggested that the differences between the FRD3-RNAi lines

and the wild type with regard to Fe, Zn, and Mn contents were quantitatively smaller

and more variable between replicates as well as tissues and ages, different from the

described observations for Pb contents.

115

Results

Table 15 Metal content in different tissues of A. halleri wild type and FRD3-RNAi.

Genotype Tissue Age Mean ± sd metal content (µg)

Pb Fe Zn Mn

WT

Leaf Old

31.9±8.9a 2.5±0.4 1,465.8±307.8 5.5±0.9b

FRD3-RNAi 7.1 12.8±2.6b 2.5±0.4 1,107.2±222.4 6.5±1.4b

FRD3-RNAi 18.2 1.6±0.8b 2.6±0.9 972.9±403.3 11.1±4.1a

WT

Leaf Int.

24.2±3.7a 1.4±0.2 724.0±120.1a 3.5±0.4

FRD3-RNAi 7.1 5.7±1.0b 1.9±0.7 378.5±27.1b 2.9±0.3

FRD3-RNAi 18.2 2.0±1.2b 1.8±0.9 424.5±221.7b 5.3±2.7

WT

Leaf young

7.4±2.2a 0.7±0.2 233.5±64.5a 1.4±0.3b

FRD3-RNAi 7.1 2.6±0.5b 0.6±0.1 96.9±27.8b 0.8±0.1c

FRD3-RNAi 18.2 2.1±0.7b 1.0±0.2 179.8±23.5a 2.2±0.2a

WT

Petiole Old

29.2±2.9a 0.41±0.05 105.4±22.9b 0.05±0.02

FRD3-RNAi 7.1 16.5±1.0b 0.41±0.10 161.7±16.8b 0.16±0.07

FRD3-RNAi 18.2 6.8±0.4b 0.79±0.03 348.5±32.5a 0.31±0.08

WT

Petiole Int.

13.3±3.1a 0.23±0.06b 74.7±20.4b 0.05±0.06

FRD3-RNAi 7.1 7.0±2.6b 0.41±0.09a 66.2±21.2b 0.06±0.03

FRD3-RNAi 18.2 4.8±1.2b 0.37±0.03a 134.2±25.7a 0.11±0.06

WT

Petiole Young

5.2±1.3a 0.18±0.03 40.0±9.3a 0.01±0.01

FRD3-RNAi 7.1 2.5±0.5b 0.14±0.05 26.6±8.6b <0.01±0.01

FRD3-RNAi 18.2 2.6±0.6b 0.18±0.03 60.1±7.2a 0.01±0.02

WT

Stem Old

51.2±6.3 0.8±0.4 101.5±29.0 <0.10±0.05

FRD3-RNAi 7.1 21.0±nd 1.4±nd 74.3±nd 0.10±nd

FRD3-RNAi 18.2 20.9±nd 0.7±nd 215.8±nd <0.10±nd

WT

Stem Int.

24.2±4.4 0.7±0.2 69.1±12.9 <0.1±0.03



WT

Stem Young

43.9±nd 1.9±nd 109.3±nd 0.2±nd


FRD3-RNAi 18.2 39.4±nd 1.3±nd 99.7±nd <0.1±nd

Three-week-old clones of wild type and FRD3-RNAi lines 7.1 and 18.2 were transferred and cultivated on their native soil from Langelsheim for an additional five weeks before harvest. nd: not determined (values from one or two pools of samples due to limiting amount of material). Int.: intermediately aged tissues. n = 6 (wild type) and 3 (FRD3-RNAi lines). Different characters indicate statistically significant differences detected in a one-way ANOVA, followed by post-hoc Tukey HSD test.

The contents of other elements were analyzed in order to gain more detailed insights

about the effects of AhFRD3 silencing on other essential elements, such as

macronutrients. A Principal Component Analysis (PCA) was performed on the

complete ionome, in a tissue-ordinated manner, to reveal global differences between

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Results

FRD3-RNAi lines and the wild type. The first two principal components accounted for

85.2% of the total variation, and were therefore used for generating a biplot (Figure

38). A robust separation was detected in the Principal Component 1 (PC1),

accounting for more than 75% of the total variation between organs (leaves in the left

and petioles/stems in the right) and age (older leaves in the left and young leaves in

the right). PC2 represented almost 10% of the total variation, and this was explained

mostly by the tissue’s age and Pb content.

Figure 38 Principal component analysis showing variation in tissue element contents (data from Table 16) in shoots of A. halleri. Different symbols denote tissue type and symbol size determines tissue age. Old: old tissues, intermediate: intermediately aged tissues, young: young tissues.

Concerning the variation in multi-element contents, Pb was the element which clearly

dominates the variance in PC2, whereas all other elements clustered together in the

mid-left portion of the biplot. This multi-element content analysis confirmed that

amongst all components of the shoot ionome, Pb was the element most affected by

the silencing of AhFRD3.

WT FRD3-RNAi

117

Results

3.2.7 Introduction of AhFRD3 in A. thaliana wild type enhances leaf Pb

accumulation

Based on the finding that FRD3 contributes to leaf Pb accumulation in A. halleri, we

hypothesized that transgenic A. thaliana plants expressing AhFRD3 accumulate

more Pb in their above-ground tissues. To directly address this question, A. thaliana

wild-type plants were transformed with three different AhFRD3 constructs: the full

length genomic AhFRD3 region including its native promoter, and two different

constructs designed for AhFRD3 overexpression (with and without HA epitope tag)

under the control of the CaMV 35S promoter. Three independent lines for gAhFRD3

construct, two independent lines for 35S:AhFRD3:HA and one line for 35S:AhFRD3

were used for these experiments. All transgenic lines were homozygous and in the

T4 generation. The transcript levels of AtFRD3 were quantified in the wild type and

frd3-1 mutant, and AhFRD3 transcript levels were quantified in all transgenic lines.

AhFRD3 transcript levels were significantly higher in transgenic lines transformed

with gAhFRD3 than AtFRD3 transcript levels the wild type. A. thaliana plants

transformed with either 35S:AhFRD3:HA or 35S:AhFRD3 displayed significantly

higher AhFRD3 transcript levels than the AhFRD3 transcript levels in transgenic A.

thaliana plants transformed with gAhFRD3 and also than AtFRD3 transcript levels in

the wild type (Figure 39b). AtFRD3 transcript levels were significantly higher in the

frd3-1 mutant than in the wild type. This is in accordance with what was reported for

this mutant. The mutation in frd3-1 causes an amino acid substitution turning the

FRD3 protein non-functional, and the FRD3 transcript levels are increased likely as a

consequence of the lack of FRD3 protein function (Rogers and Guerinot, 2002).

The selected transgenic lines were cultivated on a heavy metal-contaminated and

also non-contaminated soil alongside with the wild type (Col-0) and the frd3-1

mutant. The heavy metal-contaminated soil used for these experiments was a 1:4

(v/v) mixture of Langelsheim and compost, because A. thaliana cannot survive on

100% Langelsheim soil (Figure 10). The Langelsheim soil contains higher

concentrations of Fe, in addition to the high levels of heavy metals. Therefore, we

cultivated the wild type, frd3-1 and the one overexpressing line on non-contaminated

soil alongside the heavy metal-contaminated soil experiment. The growth on non-

contaminated soil served as a control growth medium for the frd3-1 mutant, in which

118

Results

the Fe deficiency defects can be reverted by increasing the Fe concentration in the

growth medium.

After five weeks of cultivation on heavy metal-contaminated soil, all independent

lines of transgenic plants bearing the gAhFRD3, 35S:AhFRD3:HA and 35S:AhFRD3

constructs appeared morphologically normal, and they were slightly larger than the

wild type (Figure 39a). The frd3-1 mutant plants were chlorotic and smaller in

comparison with the wild type and transgenic lines. Leaf Pb concentrations in the

frd3-1 mutant were 22% lower than in the wild type (p > 0.05). In the three

independent lines transformed with gAhFRD3 construct, leaf Pb concentrations were

70, 43 and 23% higher than in the wild type (p < 0.05 for the former two lines)

(Figure 39c). Leaf Pb concentrations in the two independent lines transformed with a

35S:AhFRD3:HA overexpression construct were also higher than in the wild type by

102 and 30 % (p < 0.001 only for the former line). The overexpressing transgenic line

35S:AhFRD3 also contained significantly higher leaf Pb concentrations (96%) in

comparison to the wild type (p < 0.001) (Figure 39c).

Leaf Fe concentrations were similar in all transgenic lines and the wild type. Leaves

of frd3-1 mutant contained 93.4% of Fe concentrations found in the wild type (p >

0.05) (Table 16). Compared with the wild type, leaf Zn concentrations in one

transgenic line of gAhFRD3 and in 35S:AhFRD3 were increased by 26 and 28% (p <

0.001), respectively, but not in other transgenic lines (Figure 39d). Leaf Mn

concentrations of almost all transgenic lines were lower than those of the wild type,

with exception of one line of gAhFRD3 construct (3% higher Mn than the wild type).

However, only one line of gAhFRD3 construct and one line of 35S:AhFRD3:HA

construct displayed significantly lower leaf Mn concentrations (both 19% lower) when

compared to wild-type leaves (p < 0.01) (Figure 39e). In the other transgenic lines,

leaf Mn concentrations were between 96 and 85% of the wild type Mn concentrations

(p > 0.05). As the soil used for these experiments contained also high levels of Cd,

leaf Cd concentrations were analyzed. Leaf Cd concentrations in two transgenic

lines for the gAhFRD3 construct and the 35S:AhFRD3 were 35, 49, and 63% higher,

respectively, than those of the wild type (p < 0.05). In the other transgenic lines leaf

Cd concentrations were between 17 and 25% higher than in the wild-type leaves (p >

0.05) (Table 16).

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Results

(a)

Col-0 frd3-1 F1-P01 F2-P05 F3-P01 i2-P01 i3-P01 J1-P02

(b)

a a a

b b b b

c

gA

hF

RD

3

35S

:AhF

RD

3:H

A

35S

:AhF

RD

3

gA

hF

RD

3

35S

:AhF

RD

3:H

A

35S

:AhF

RD

3

gA

hF

RD

3

35S

:AhF

RD

3:H

A

35S

:AhF

RD

3

gA

hF

RD

3

35S

:AhF

RD

3:H

A

35S

:AhF

RD

3

(c)

a a

a

b b b bc

c

c

(d)

a a a

b b b ab

b

(e)

a

b b

c b

c c

b

c b

c

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Results

Figure 39 A. thaliana plants expressing AhFRD3 accumulate higher Pb concentrations in their leaves than wild type non-transformed plants. Photos are shown in (a). Diagrams show: (b) FRD3 transcript levels (one-way ANOVA, p < 0.001, F = 25.6, eta-Squared: 0.92), (c) leaf Pb concentrations (one-way ANOVA, p < 0.001, F = 15.9, eta-Squared: 0.74), (d) leaf Zn concentration (one-way ANOVA, p < 0.001, F = 11.2, eta-Squared: 0.66), and (d) leaf Mn concentration (one-way ANOVA, p < 0.001, F = 13.8, eta-Squared: 0.71). Shown are mean values + SD (n = 6). Letter above the bars indicates statistically significant difference among all genotypes by Analysis of Variance (One-Way ANOVA) followed by Post-Hoc test Tukey HSD and eta-Squared (η²) effect size test. Three-week-old plants [wild type Col, frd3-1 mutant, and transgenic lines expressing different AhFRD3 constructs [gAhFRD3 (F1-P01, F2-P05, and F3-P01), 35S:AhFRD3:HA (i2-P01, and i3-P01) and 35S:AhFRD3 (J1-P02)] in Col wild-type background] were grown on 1:4 (v/v) mixture of heavy metal-contaminated soil and compost for five weeks before harvest. Scale bar: 3 cm.

When grown on non-contaminated soil, leaf Pb concentrations displayed a similar

trend as the observed on heavy metal contaminated soil. 35S:AhFRD3

overexpressing plants accumulated around 38% higher leaf Pb concentration than

the wild type (Table 17). With regard to Fe, Zn and Mn, the 35S:AhFRD3

overexpressing plants exhibited around 17% higher both leaf Zn and Mn

concentrations than the wild type (p > 0.05), and 2.5% lower leaf Fe concentrations

when compared to the wild type (p > 0.05). Leaves of frd3-1 mutant contained higher

concentrations of Pb (30%), Zn (267%) and Mn (257%) when compared to leaves of

the wild type, suggesting again that significantly enhanced Fe deficiency responses

leads to higher Pb concentrations in that mutant.

These results together suggested that the introduction of AhFRD3 in A. thaliana

enhances primarily leaf Pb accumulation. The two FRD3 overexpressing constructs

35S:AhFRD3:HA and 35S:AhFRD3 seem more promising, since Pb concentrations

were usually highest in leaves of plants bearing those constructs. This finding is

promising for identifying factors important for phytoremediation of contaminated

soils.

121

Results

Table 16 Mean ± SD (n = 6) leaf Fe and Cd concentrations in wild type, frd3-1, and transgenic lines bearing AhFRD3 after cultivation on heavy metal-contaminated soil.

Leaf concentrations in µg.g-1

Genotype Fe Cd

Wild type 59.00 ± 6.19 28.46 ± 3.46 c

frd3-1 55.08 ± 12.89 48.50 ± 1.94 a

F1-P01 62.83 ± 9.06 38.37 ± 4.69 b

F2-P05 69.69 ± 5.82 33.42 ± 5.29 bc

F3-P01 55.34 ± 2.12 42.56 ± 3.10 b

i2-P01 68.38 ± 6.57 35.58 ± 5.90 bc

i3-P01 66.51 ± 9.44 33.67 ± 5.51 bc

J1-P02 59.53 ± 13.31 46.36 ± 4.56 ab

Different characters represent statistically significant differences between genotypes by Analysis of Variance (One-Way ANOVA) followed by Post-Hoc test Tukey HSD (α = 0.05).

Table 17 Mean ± SD (n = 6) leaf Pb, Fe, Zn and Mn concentrations in wild type, frd3-1, and 35S:AhFRD3 overexpressing line cultivated on non-contaminated soil.

Concentrations in µg.g-1

Genotype Pb Fe Zn Mn Cd

Wild type 1.12 ± 0.44 68.86 ± 1.95 55.66 ± 5.29 a 31.78 ± 3.08 a 0.28 ± 0.08 a

frd3-1 1.46 ± 0.42 73.32 ± 6.42 204.37 ± 12.15 b 145.46 ± 4.92 b 1.80 ± 0.12 b

J1-P02 1.55 ± 0.31 67.17 ± 4.48 65.67 ± 6.00 a 37.46 ± 5.20 a 0.43 ± 0.08 a

Different characters represent statistically significant difference between genotypes by Analysis of Variance (One-Way ANOVA) followed by Post-Hoc test Tukey HSD (α = 0.05).

122

Discussion

4 Discussion

4.1 Global analysis of RNAi-mediated silencing of candidate genes

HMA3, HMA4 and FRD3 on metal hyperaccumulation and

hypertolerance

Knock-down RNAi lines of A. halleri in which transcript levels of AhHMA3, AhHMA4

and AhFRD3 were significantly reduced, were used to gain insight into the molecular

mechanisms underlying metal hyperaccumulation and hypertolerance. Upon

cultivation on a set of soils including metalliferous and non-metalliferous soils, the

datasets of leaf ionomes and measurements of a range of growth and stress

parameters in these plants were analyzed using multivariate statistical models. This

approach revealed some aspects of the relationships between plant ionome, metal

tolerance, soil properties and gene function in heavy metal accumulation and

hypertolerance.

4.1.1 Zn, Cd, and Pb accumulation is strongly affected by the silencing of

HMA4 and FRD3

In general, the comparison between all genotypes grown on different soils hosting

natural population of A. halleri suggested that the soil properties are the most

influential factor impacting on leaf multi-element accumulation in the plants used in

this study. Multivariate regression analysis determined that edaphic factors explained

64% of the total variance observed in the leaf ionome (Figure 15 and Table 12).

Contributing to this, leaf Zn, Cd and Pb were positively correlated with soil Cd and

pH, whereas they were negatively correlated with soil N, Mn, and Ni concentrations

(Figure 17). This was surprising because, according to the literature, a negative

correlation between soil pH and the bio-availability of heavy metals in soil for uptake

and accumulation in plants in general is well-documented (Han et al., 2011; Harter,

1983). However, pH of all metalliferous soils used in this study was higher, alongside

several orders of magnitude higher metal concentrations, than in the non-

metalliferous soils (Table 11). Consequently, it is likely that pH does not causally

increase heavy metal accumulation in A. halleri and the observed correlation is a

123

Discussion consequence of the higher pH of soils containing higher concentrations of heavy

metals.

Leaf concentrations of Pb, Cd, and Zn in hyperaccumulator species have been

frequently correlated with their own availability in the soil (Bert et al., 2002; Bert et

al., 2000). More recently, leaf Pb and soil Pb exhibited highly positive correlations in

several plant species colonizing the surroundings of contaminated areas (Salazar

and Pignata, 2014). The prediction of trace element accumulation in plant tissues

based on soil properties and composition has been poorly investigated. This is a

difficult task given the complexity of soil chemistry, mineral availability and organic

components. The analysis of Cu and Co accumulation in shoots of two metallophyte

species, Crepidorhopalon tenuis and Anisopappus chinensis, has shown positive

correlations between soil pH, Mn and Cu content and shoot Cu accumulation,

whereas shoot Co concentration was negatively correlated with soil Mn content

(Lange et al., 2014).

In studies addressing the genetic basis of plant ionome, little attention has been

given to the influence of edaphic factors on plant element accumulation. Therefore,

the removal of soil influence on plant phenotypic variation was undertaken here,

followed by the analysis of the residual variation. Partial RDA models suggested that

the hyperaccumulation of Zn/Cd and the accumulation of Pb in leaves of A. halleri

are mostly dependent on HMA4 and FRD3 genes, respectively (Figure 19 and

Figure 21). The dependence of Zn/Cd hyperaccumulation on HMA4 was previously

revealed using the same RNA interference lines (Hanikenne et al., 2008). However,

the direct evidence for the involvement of HMA4 in Zn/Cd hyperaccumulation was

based on experiments using hydroponic media. The advantage of such media is that

their composition can be precisely controlled, but the disadvantage is that they are

very different from soils and thus somewhat artificial. Based on this earlier work, the

basis of Zn/Cd hyperaccumulation was proposed to lie in the genomic triplication of

HMA4 and alteration of cis-regulatory elements, which dramatically enhance its

HMA4 gene expression (Hanikenne et al., 2008), and, consequently, root-to-shoot

translocation of Zn and Cd are substantially increased. HMA4 was also associated

with Zn and Cd hypertolerance in QTL mapping studies (Roosens et al., 2008;

Willems et al., 2007). Excitingly, the results presented here validate the molecular

124

Discussion role of HMA4 in A. halleri plants cultivated on several different soils that host A.

halleri populations in natural field conditions. Moreover, a moderate contribution of

HMA4 to leaf Pb accumulation in A. halleri was observed on metalliferous soils

(Figure 20), what has not been reported so far.

Silencing of HMA3 did not affect the accumulation of any element of the leaf ionome

to a degree resembling the effects of silencing of HMA4 or FRD3 (Figure 19 and

Figure 21). Across the data analyses performed on metal accumulation, HMA3-RNAi

lines always clustered with wild-type plants, regardless of the soil type. This

suggests that A. halleri plants are able to maintain their metal homeostasis in green

tissues even with strongly reduced HMA3 transcript levels. It was suggested that in

A. thaliana, HMA3 is a protein acting in Cd compartmentalization in root vacuoles,

thus restricting the mobility of Cd for root-to-shoot movement and its accumulation in

shoots (Chao et al., 2012; Park et al., 2012). An analogous role was suggested for

HMA3 of the metal hyperaccumulator species N. caerulescens (Ueno et al., 2011).

Similar to the observations in A. thaliana accessions and genotypes disrupted in

HMA3 function, leaf Cd concentrations were slightly increased in HMA3-RNAi lines

on metalliferous soil from Langelsheim (6-29% higher) and non-metalliferous soil

from Malmedy (25-39% higher), but average concentrations in HMA3-RNAi lines

were not statistically significant from leaf Cd concentrations of the wild type (Figure

20 and Figure 22). This is consistent with a small contribution of HMA3 to restricting

leaf Cd accumulation in A. halleri. After cultivation on other soils, leaf Cd

concentrations were similar or lower than the concentrations of the wild-type leaves

and also not significantly different. This is also in agreement with the RDA model in

which no positive or negative correlation between Cd accumulation and HMA3

transcript levels was detected. Taken together, these data suggest that under the

conditions employed here, the candidate gene HMA3 makes no major contribution to

overall accumulation of Cd, Zn or Pb in leaves.

The most striking phenotype observed in FRD3-RNAi lines when compared with the

wild type was a strong positive correlation between FRD3 transcript levels and leaf

Pb concentrations (Figure 19 and Figure 21). Accordingly, all independent knock-

down FRD3-RNAi lines displayed strongly reduced leaf Pb concentrations,

independent of the soil type on which they were cultivated (Figure 25). A. thaliana

125

Discussion frd3 mutants, by comparison, displayed Zn and Mn over-accumulation in their leaves

as a consequence of disrupted Fe supply to target sites in leaves eliciting Fe

deficiency responses in roots (Rogers and Guerinot, 2002). In A. halleri, Zn and Mn

concentrations were not correlated with FRD3 transcript levels across wild-type,

FRD3-RNAi lines and other genotypes in the RDA analysis (Figure 19 and Figure

21). These data suggest that FRD3 is likely to play a role in Pb accumulation in A.

halleri, in contrast to what is reported in A. thaliana.

4.1.2 Leaf Pb accumulation in A. halleri can reach very high levels under

controlled conditions

The Langelsheim accession of A. halleri is able to accumulate an average of 400 µg

Pb g-1 leaf DW when cultivated on native soil from Langelsheim (Figure 20c), and up

to 990 µg Pb g-1 leaf DW after cultivation on Evín-Malmaison soil (Figure 25b).

These concentrations were measured in analyses of leaf tissues alone, i.e. excluding

petioles and stems.

So far, the hyperaccumulation of Zn and Cd is well-known in A. halleri (Baker and

Brooks, 1989; Brooks, 1998), but the species has never been reported to

hyperaccumulate Pb, i.e. to contain leaf Pb concentrations above 1,000 µg Pb g-1

DW. Accumulation of Pb by different wild individuals of A. halleri was reported to

vary between 5 µg g-1 shoot DW (in the Czech Bohemian forest) and 376 µg g-1

shoot DW (in Katowice, Poland) (Bert et al., 2002), but plants containing more than

100 µg Pb g-1 DW were sampled near roads or active metallurgical factories

(Dahmani-Muller et al., 2000). Thus, the latter may have been contaminated via

aerial deposition on leaves from leaded fuel or particles from factory smoke (Bert et

al., 2002). Field data from a large European collection of A. halleri populations

identified few individuals that contained hyperaccumulator levels of Pb in shoots (Dr.

Ricardo Stein, personal communication). However, targeted experiments are

required to determine the significance of these observations.

A number of species were previously reported to hyperaccumulate Pb at their native

sites in the field (according to the definition of metal hyperaccumulation). The highest

concentrations of Pb reported in shoots of vascular plants were 8,200 µg g-1 DW in

Thlaspi rotundifolium (Reeves and Brooks, 1983). Shoot Pb concentrations of 662 µg

126

Discussion g-1 DW were reported in N. caerulescens at Black Rocks in the United Kingdom

(Baker et al., 1994). T. praecox growing in Slovenia reached Pb concentrations of

3,500 µg g-1 DW in shoots. Fagopyrum esculentum Moench accumulated 8,000 µg

Pb g-1 DW in shoots. In our experiments, we found that Pb concentrations can reach

740 µg Pb g-1 DW when including petioles and stems in the samples of wild-type

plants grown on Langelsheim soil (data shown in Table 16 as Pb content). One

individual grown on Evín-Malmaison soil contained 990 µg Pb g-1 DW in leaves

alone, and these levels could potentially exceed 1,000 µg Pb g-1 DW if petioles and

stems were included in the analysis. This suggests that A. halleri Langelsheim

accession, even upon the short-term growth period of five weeks, can accumulate

more than double the levels of Pb concentrations reported in shoot tissues of

samples collected in their native sites in the field (Bert et al., 2002). Our experiments

were carried out under controlled cultivation conditions in a growth chamber. Thus,

the contamination by aerial deposition of Pb hypothesized to occur in field samples

can be excluded. However, in order to conclude more precisely, our experiments

should be repeated with a larger number of individuals and using different A. halleri

accessions.

4.1.3 Plant growth and biochemical stress markers were less affected by

RNAi-mediated silencing of HMA3, HMA4 and FRD3

The RDA analysis of plant growth and stress markers in all genotypes suggested

that soil concentrations of Cd and Pb were positively correlated with plant H2O2 and

anthocyanin accumulation as well as negatively correlated with plant and shoot

biomass (Figure 18). These results are in agreement with numerous previous studies

demonstrating the toxicity of these metals, for example an experiment carried out in

hydroponic solutions which reported about 50% reduction in whole plant and shoot

biomass in soybean plants grown upon high Cd concentrations (Xue et al., 2013).

Another example is a study of toxic effects of Pb on rice seedlings, which displayed

reduced shoot and root biomass after cultivation in medium containing high

concentrations of Pb (1 mM) (Verma and Dubey, 2003).

Two out of three HMA4-RNAi lines displayed a significant increase in leaf TBARS

and anthocyanin concentrations compared with the wild type after cultivation on their

native metalliferous soil from Langelsheim (Figure 23c-d). This suggests that HMA4

127

Discussion contributes to metal tolerance in A. halleri plants grown on metalliferous soils. These

results are also in agreement with previously reported decreased metal tolerance in

HMA4-RNAi lines grown on hydroponics supplemented with high concentrations of

Zn and Cd (Hanikenne et al., 2008). These authors found that root elongation of

HMA4-RNAi lines was inhibited to 3-15% by 30 µM Cd and to 12-37% by 1.5 mM Zn

when compared with the root elongation of HMA4-RNAi lines under control

conditions. The wild type root elongation was about 68% and 60%, respectively, of

the wild type root elongation in control conditions. The Zn/Cd tolerance conferred to

A. halleri by high expression of HMA4 may be directly related to root-to-shoot

partitioning of those elements, thus decreasing the metal load of root cells

(Hanikenne et al., 2008). In this perspective, the increased TBARS and anthocyanin

concentrations in leaves of HMA4-RNAi lines could be also a consequence of root

damage caused by Zn and Cd toxicity in below-ground tissues. Alternatively, other

highly expressed metal-related genes may act to detoxify those metals in the

absence of HMA4. At the subcellular scale, metal detoxification may occur by metal

binding through glutathione and phytochelatins (Clemens, 2006b; Grill et al., 1989),

and compartmentalization of metals potentially by MTP1 and HMA3 proteins

(Krämer, 2005; Ueno et al., 2011). Therefore, the stress markers assessed here limit

a more specific understanding of the reduced metal tolerance in knock-down HMA4-

RNAi lines. Further experiments using these RNAi lines are necessary to verify if the

status of transcript levels of other genes involved metal-induced stress and metal

detoxification, such as those mentioned above, are upregulated as a consequence of

the reduced HMA4 transcript levels.

The RDA analysis performed did not suggest strong effects of the silencing of FRD3

on the stress markers analyzed in either metalliferous or non-metalliferous soils

(Figure S16). The most common symptom exhibited by frd3 mutants in A. thaliana is

leaf chlorosis induced by Fe deficiency (Rogers and Guerinot, 2002; Roschzttardtz et

al., 2011). Decreases in chlorophyll concentrations were not observed for any of the

A. halleri RNAi lines, including FRD3-RNAi lines, in comparison to the wild type on

any of the soils tested, as suggested by the RDA and partial RDA analysis (Figure

18 and Figure S16). The analysis of growth and stress markers on specific soils

revealed reduced growth rate and shoot biomass in FRD3-RNAi lines on

metalliferous soil from Langelsheim and increased anthocyanin concentrations in

128

Discussion these lines on metalliferous soil from Littfeld (Figure 23), which could be linked to

metal toxicity. These results suggest that FRD3 contributes to plant growth and

shoot biomass production on highly heavy metal-contaminated soils. Since the root-

to-shoot partitioning of Pb in A. halleri was affected by the silencing of FRD3 (Figure

25 and Figure 32), the reduced growth rate and shoot biomass in FRD3-RNAi lines

grown on metalliferous soils could be a consequence of Pb toxicity in roots. Previous

studies using different plant species (such as maize and rice), showed that whole

plant and shoot biomass and root elongation were significantly reduced by the toxic

concentrations of Pb in hydroponic culture (Obroucheva et al., 1998; Verma and

Dubey, 2003). However, no role of a specific gene contributing to Pb tolerance was

tested in those studies. A more detailed discussion on the role of FRD3 in Pb

tolerance in A. halleri is provided in the coming section 4.2.

HMA3-RNAi lines developed as healthy as the wild type after five weeks of

cultivation on all different soils tested (Figure 13 and Figure S9-S13). If HMA3 acts in

heavy metal detoxification in A. halleri as was reported for A. thaliana (Morel et al.,

2009), HMA3-RNAi lines were expected to display toxicity symptoms, at least on

metalliferous soils, such as impaired plant growth and development (Benavides et

al., 2005), heavy metal-induced leaf chlorosis (Morel et al., 2009) and altered

homeostasis of nutrients including Zn (Das et al., 1997). However, none of these

symptoms were observed in HMA3-RNAi lines in comparison to the wild type (Figure

20 and Figure 23). It is well-known that plant metal homeostasis is very complex.

The modus operandi of the metal homeostasis of metal-hypertolerant species is still

unclear, as a number of metal-related genes are up-regulated at the transcript level

in comparison to non-tolerant species (Assuncao et al., 2001; Talke et al., 2006; van

de Mortel et al., 2006). Several of these genes have not even been assigned a

function yet (Becher et al., 2004). The possibility that other highly expressed genes

contribute to avoiding metal toxicity in the absence of HMA3 cannot be ignored. In

this regard, the expression analysis of genes known to play a role in metal tolerance

as well as other candidate genes would be the first step to gain more insights on the

lack of phenotype in HMA3-RNAi lines under the experimental conditions employed

here.

129

Discussion Knockdown of HMA3, HMA4 and FRD3 in A. halleri may cause metal toxicity

symptoms different than the accumulation of H2O2 or anthocyanins, lipid peroxidation

or chlorophyll degradation. The metalliferous soils used for cultivation here contain a

mixture of several different heavy metals at strongly elevated levels. This did not

allow a precise conclusion on which specific metal caused the observed symptoms.

Further experiments using either artificial soil or hydroponic culture containing high

concentrations of each of those heavy metals individually could be more informative

approaches, particularly to gain insights about the roles of HMA3 and FRD3 in A.

halleri. In addition, growing HMA3-, HMA4- and FRD3-RNAi lines on metalliferous

soils for periods longer than five weeks and accompanied by other environmental

factors which were not part of our controlled experiments, such as the presence of

herbivores, may impose somewhat different limitations to those RNAi genotypes

under field conditions. A common garden experiment could provide such conditions

to address questions on plant performance and fitness, in addition to metal

tolerance. Especially HMA4- and FRD3-RNAi lines, which displayed remarkably

reduced levels of Zn/Cd and Pb in leaves, are the best genotypes to the suggested

experiments.

4.2 The role of FRD3 in Pb accumulation

4.2.1 Leaf Pb accumulation in A. halleri depends on the highly expressed

FRD3 gene

The gene FRD3 encoding a multidrug and toxin efflux family (MATE) protein is one

of the metal-related genes most highly expressed in A. halleri relative to A. thaliana

(Talke et al., 2006). A major finding of this this thesis was that leaves of FRD3-RNAi

lines, in which FRD3 transcripts levels are much lower than the wild type, contained

between 3.2% and 14.7% of the wild-type leaf Pb concentrations when grown on its

native soil from Langelsheim (Figure 20). The lowest concentrations of Pb in leaves

were detected in the FRD3-RNAi 18.2, which displayed the lowest levels of FRD3

transcripts (Figure 9c). Interestingly, the reduced leaf Pb concentrations in FRD3-

RNAi lines occurred also when they were cultivated on various other metalliferous

and non-metalliferous soils from A. halleri native sites (Figure 25a-f), suggesting that

the silencing of FRD3 in A. halleri impairs leaf Pb accumulation regardless of the soil

type. In the Indian mustard Hirschfeldia incana the transcript levels of HiHMA4 and

130

Discussion Metallothionein 2A (HiMT2A) were induced in roots and shoots upon Pb exposure

(Auguy et al., 2013). In that work, about 50% inhibition of root growth was found in

hma4 and mt2a A. thaliana T-DNA mutants compared with the wild type under 40

µM Pb treatment, suggesting a potential role of those genes in Pb tolerance.

However, leaf Pb concentrations between wild type and mutants were at comparable

levels and no introduction of HiHMA4 and HiMT2A genes in A. thaliana mutants was

tested for phenotype complementation (Auguy et al., 2013).

Leaf concentrations of other heavy metals, such as Zn and Cd, or essential

macronutrients were not affected by the silencing of FRD3 to the same extent as leaf

Pb concentrations were. For instance, after the cultivation on native Langelsheim

soil, leaf Zn concentrations were significantly reduced only in FRD3-RNAi line 18.2,

but not in the lines 7.1 and 9.1 (Figure 34b). The reduced levels of Zn in leaves of

FRD3-RNAi 18.2 were still 88% of the wild-type leaf Zn concentrations. In addition,

leaf Zn concentrations were not significantly different between wild-type and FRD3-

RNAi lines after the cultivation on other soils hosting natural A. halleri populations

(Figure S19).

4.2.2 An upregulation of Fe acquisition mechanisms leads to Pb accumulation

in seedlings of the A. thaliana mutant

A main goal of this work was to functionally characterize FRD3 of A. halleri and

compare this with FRD3 of A. thaliana, a non-accumulator non-tolerant sister species

of A. halleri. A number of independent studies have shown that Fe homeostasis is

drastically altered in frd3 mutants, even when they were grown under Fe sufficient

conditions (Delhaize, 1996; Rogers and Guerinot, 2002). The model presented in

Figure 40 illustrates the consequences of the absence of a functional FRD3 in A.

thaliana. When FRD3 is knocked out in this species, frd3 seedlings constitutively

express strategy I Fe deficiency responses and display higher expression of Fe

deficiency-regulated genes in the roots, such as FRO2 and IRT1 (Rogers and

Guerinot, 2002). It was proposed that frd3 mutants of A. thaliana are defective in

releasing citrate into the root xylem (Durrett et al., 2007; Roschzttardtz et al., 2011),

and thus impaired in maintaining Fe mobility and solubility in the apoplast (Green

and Rogers, 2004). Citrate was reported as the main Fe chelator in the xylem sap,

which promotes long distance transport of Fe from roots to shoots in different plant

131

Discussion species (Durrett et al., 2007; Rellan-Alvarez et al., 2010; Tiffin, 1966a, b, 1970;

Yokosho et al., 2009), proposed in the form of [Fe(III)3-Cit3] (Rellan-Alvarez et al.,

2010). In leaves of A. thaliana, citrate is required for Fe solubility in the apoplasm,

and therefore is essential for providing Fe in a usable form permitting the reduction

of Fe3+ to Fe2+ and its subsequent uptake by leaf cells and cells in reproductive

organs (Roschzttardtz et al., 2011). As a consequence of Fe deficiency, Zn and Mn

over-accumulation were consistently reported in roots and shoots of different frd3

mutants (Delhaize, 1996; Rogers and Guerinot, 2002). The increase in Fe

concentrations in shoots was controversially discussed in different reports, and it

was suggested to occur due to: (i) Fe3+ ions moving up through the xylem into the

shoots because of root Fe overloading, and consequent saturation of cell wall

binding sites in the root vasculature; or (ii) either malate or other organic acids

serving as low affinity Fe3+ chelators, but are inefficient in appropriately distributing

Fe to leaf cells.

When the comparison of wild-type and frd3-1 seedlings was performed on our

modified agar-solidified Hoagland media containing a gradient of Pb-acetate, shoot

Fe concentrations of the frd3-1 mutant were significantly lower than in the wild-type

only in the control medium without Pb, but not when Pb was present in the media

(Figure 31a). However, root Fe concentrations were between 4-fold and 9-fold higher

in frd3-1 than in the wild-type (Figure 31d). These latter data are consistently in

accordance with a previous report for frd3-1 phenotype. Fe accumulation in roots

and leaf chlorosis in frd3-1 plants is caused by reduced Fe concentrations inside the

leaf cells, even when the frd3-1 shoot Fe concentrations are comparable to the Fe

levels in wild-type shoots (Green and Rogers, 2004). The shoot Fe concentrations in

both genotypes grown on media containing Pb were between 50 and 100 µg g-1 DW,

thus within the range for Fe sufficiency in plants (Marschner, 1995d). We did not

measure intracellular levels of metals in our experiments.

132

Discussion

ZnII

MnII

WT

frd3

A. thaliana

ZnII

Leaves

Fe-deficiency signalling

FeIII

Xylem

ZnII

Chlorotic leaves

MnII

ZnII

MnII

FRD3

Citrate

IRT/ZIP FeIII

reductase

Unkown

FeII

FeIII

FeIII Fe

III

FeII

HMA4

ATP

ADP + Pi

FRO2

IRT1

ZIP Other

FeIII

MnII

ZnII

MnII

FeIII

Xylem

ZnII

MnII

FeII

FeIII

CdII

CdII

FeIII

ATP

ADP + Pi

FRO2

IRT1

ZIP Other

FeIII

FeIII

Epidermis Cortex Endodermis

Pericycle

133

Discussion Figure 40 Model for FRD3 function in A. thaliana based on the literature. FRD3-mediated citrate efflux from the root pericycle cells is required for root-to-shoot Fe

III mobility in

the xylem and for FeIII solubility in the apoplast (Durrett et al., 2007). The [Fe

III-Cit]-complex is

transported into shoots in the xylem sap and it is likely more efficient than other FeIII-organic acid

complexes for correctly delivering FeIII to photosynthetically active cells (Durrett et al., 2007; Rellan-

Alvarez et al., 2010). In the frd3 mutants, the absence of FRD3 in roots induces physiological Fe deficiency in leaf cells due to Fe

III precipitation in the xylem and leaf apoplast (Green and Rogers,

2004; Rogers and Guerinot, 2002; Roschzttardtz et al., 2011; Schuler et al., 2012). As a consequence, shoot-to-root Fe deficiency signaling activates the root Fe deficiency response through increases in FRO2 and IRT1 levels, which in turn enhance Fe, Zn and Mn uptake into roots through IRT1, resulting in their accumulation in roots (Rogers and Guerinot, 2002). Zn and Mn are also accumulated in shoots at very high levels (Green and Rogers, 2004). The model is based largely on experiments conducted with seedlings.

Interestingly, frd3-1 was sensitive to Pb on medium containing 5 µM Pb (Figure 28).

On media with Pb concentrations higher than 5 µM, only the root length of frd3-1

seedlings was significantly reduced in comparison to the wild-type in the same

conditions (Figure 28c), but not plant biomass (Figure 28b). These observations

seemed linked to a strongly increased Fe deficiency response exhibited by frd3-1

roots, resulting in an enhanced Pb accumulation in frd3-1 in comparison to the wild

type on the media with high Pb concentrations. In support of this hypothesis, the

frd3-1 roots displayed between 2-fold and 3.4-fold higher root surface Fe(III) chelate

reductase activity than wild-type roots across all Pb containing media (Figure 30a).

To confirm this hypothesis, more Fe-deficiency markers should be tested in addition

to root surface Fe(III) reductase activity. Moreover, in the media with the two highest

concentrations of Pb, both shoots and roots of frd3-1 mutant contained higher levels

of Pb than those of the wild type (Figure 30b-c). There was a trend for lower Fe

concentrations in both wild-type and frd3-1 roots in comparison to the control

medium when seedlings were grown on media containing high Pb concentrations

(Figure 30d). A similar trend was observed for shoot Mn concentrations in both

genotypes and for root Mn concentrations in frd3-1 only, suggesting that Pb in high

concentrations might displace Fe and Mn for uptake and root-to-shoot translocation.

On non-contaminated soil, leaves of older frd3-1 plants contained 30% higher Pb

concentrations compared with wild-type leaves (Table 17). In that experiment, frd3-1

plants displayed the usual frd3 Fe deficiency phenotypes evidenced by over-

accumulation of Zn and Mn (367% and 457% of the Zn and Mn of the wild type,

respectively), consistent with the leaf phenotype of soil grown frd3 mutants (Rogers

134

Discussion and Guerinot, 2002). When these genotypes were grown on metal-contaminated

soil, which contains also very high Fe concentrations, Zn and Mn concentrations in

frd3-1 leaves were only 29% and 16% higher than in wild-type leaves, and frd3-1

mutant leaf Pb concentrations were 88% of those in the wild type. This is a far lower

extent to what was observed in leaves of A. halleri FRD3-RNAi lines, which

contained less than 15% of wild type Pb concentrations (Figure 25), after cultivation

on various heavily metal-contaminated soils, in which Pb and Fe are also present at

very high concentrations, as well as non-contaminated ones.

After the plate experiments with A. thaliana were complete, a publication was

released suggesting the use of a modified so-called low-phosphate low-pH (LPP)

medium to test various mutants for Pb sensitivity (Fischer et al., 2014). Compared to

commonly used hydroponics, this medium contains very low levels of phosphate, no

micronutrients other than Fe, and a low pH of 5.0 (see Table 5, methods section

2.2.2). The authors found that cad1-3 and cad1-6, both of which are unable to

synthesize heavy-metal binding phytochelatins (Howden et al., 1995; Tennstedt et

al., 2009), were hypersensitive to Pb under their conditions. The comparison of A.

thaliana wild-type, cad1-3 and frd3-1 cultivated on agar-solidified LPP medium

demonstrated that frd3-1 behaved similar to the wild type in the range of Pb

concentrations tested (Figure 29), suggesting that frd3-1 mutant is not sensitive to

Pb on that media. In the experiments using our modified Hoagland solution cad1-3

was not used. We believe that the enhanced Pb accumulation through increased Fe-

deficiency observed in frd3-1 would have worsened cad1-3 phenotype after the

growth on our media. It is necessary to compare the wild type and frd3-1 alongside

with cad1-3 on our modified Hoagland media to experimentally demonstrate that

cad1-3 displays Pb hypersensitivity also when cultivated on our modified Hoagland

conditions.

As mentioned above, when Pb is present in the medium, it may compete with other

metals for the uptake by plant roots, or inhibit the proteins mediating metal uptake or

subsequent transport. Although the mechanisms through which plants uptake Pb are

still poorly understood, it was demonstrated that the uptake of the non-essential

heavy metal Cd can be mediated by the Fe transporter IRT1 in A. thaliana roots

under Fe deficiency (Vert et al., 2002). To confirm that higher Pb concentrations

135

Discussion accumulated by frd3-1 seedlings occurred due to their constitutive expression of Fe

deficiency responses, additional experiments could be conducted in which wild-type

and frd3-1 seedlings are cultivated on media lacking Fe, to induce Fe deficiency

responses also in the wild type. If Fe deficient wild-type seedlings accumulate more

Pb than Fe-sufficient seedlings, this would support the idea that Pb accumulation in

frd3-1 mutant is also a secondary consequence of Fe deficiency in this mutant, at

least in younger stages.

4.2.3 FRD3 contributes only marginally to Fe homeostasis in A. halleri under

the experimental conditions employed

By knocking down AhFRD3 transcript levels in A. halleri plants we expected to

observe at least some of the known phenotypes exhibited by frd3 knockout mutants

in A. thaliana, such as leaf chlorosis, shoot over-accumulation of Zn and Mn, root

over-accumulation of Fe, Zn and Mn, and significantly higher Fe(III) chelate

reductase activity in roots.

When A. halleri FRD3-RNAi lines were grown on its native soil from Langelsheim, no

leaf chlorosis was observed (Figure 24b). The leaf Fe concentrations in those RNAi

lines were not significantly different from the wild-type leaf Fe (Figure 20d and Figure

22d). After cultivation on hydroponic culture, leaf Fe concentrations of FRD3-RNAi

line 18.2 were also similar to those in the wild type (Figure 31b). As leaf chlorosis is

a hallmark for Fe-deficient plants (Marschner, 1995d) and a typical phenotype for

frd3 mutants in A. thaliana, due to their physiological Fe deficiency in leaf cells

(Green and Rogers, 2004), these results suggested that FRD3-RNAi lines did not

suffer severe physiological Fe deficiency as A. thaliana frd3 seedlings usually do.

FRD3-RNAi 9.1 and 18.2 lines leaf Mn concentrations were 233% and 234% higher

than in wild-type leaves, respectively, but no significant difference was found

between FRD3-RNAi line 7.1 and the wild type after cultivation on Langelsheim soil

(Figure 26). This was qualitatively similar and quantitatively different from most of the

Mn concentrations reported in frd3 mutants, in which leaf Mn levels were reported

between 500% and 800% of those in the wild type (Delhaize, 1996; Rogers and

Guerinot, 2002). Moreover, the differences in leaf Mn concentrations between FRD3-

RNAi lines and wild type after cultivation on Langelsheim soil were not observed

136

Discussion when the plants were cultivated on other soils from natural A. halleri habitats. For

example, leaf Mn concentrations were either not significantly different between

FRD3-RNAi lines and wild type for plants grown on Rodachebrunn soil (p = 0.44) or

were significantly lower in leaves of only FRD3-RNAi 9.1 line after the cultivation on

Evín-Malmaison soil (p < 0.05) (Figure S18). In plants cultivated on hydroponic

medium, leaf Mn concentrations were similar between FRD3-RNAi line 18.2 and the

wild type (Figure 34f). These findings add more support to the hypothesis that

above-ground tissues of FRD3-RNAi lines did not exhibit strongly altered Mn

accumulation when compared to wild type, thus differing from the phenotypes of A.

thaliana frd3 mutants. It is important to highlight again that leaf Pb concentrations in

all three FRD3-RNAi lines were lower than wild-type leaf Pb concentrations

independent of the hydroponic growth media or the type of soil used.

In addition to the element concentrations, the analysis of leaf transcript levels of Fe

deficiency marker genes did not reveal any significantly difference in Fe status

between FRD3-RNAi lines and the wild type plants cultivated on Langelsheim soil

(Figure 27a-c). Various A. thaliana ecotypes subjected to Fe deficiency showed

upregulation of FRO3 (1.9- to 18.4-fold) and OPT3 (2.2- to 3.1-fold) in shoots after

24 h of Fe deficiency treatment, and also displayed down-regulation of FER1 under

the same conditions (Waters et al., 2012). By showing neither significant

upregulation of FRO3 or OPT3 nor down-regulation of FER1, our data demonstrate

that, also at the transcript level, FRD3-RNAi plants cultivated on A. halleri native soil

from Langelsheim did not display strong physiological Fe deficiency in their green

tissues. It should be noted that the Langelsheim soil used in this experiment contains

high concentrations of heavy metals, such as Zn and Cd, known to be able to induce

Fe deficiency in sensitive plants.

Different from what was observed in leaves, the analysis of root tissues of A. halleri

FRD3-RNAi and wild type cultivated on hydroponic media showed that root Fe

concentrations were significantly higher in FRD3-RNAi line 18.2 than in the wild type

roots upon both control and Pb-amended conditions (Figure 34a). Root Mn

concentrations in the FRD3-RNAi line 18.2 were significantly higher than in the wild-

type roots only under control conditions (Figure 34c). However, the differences

observed for root Fe and Mn concentrations between FRD3-RNAi and wild type were

137

Discussion quantitatively much smaller than what was reported in frd3 mutants of A. thaliana

(Delhaize, 1996; Rogers and Guerinot, 2002). For root Zn concentrations, no

statistically significant difference was detected between the two genotypes (Figure

34b).

In A. thaliana roots, the Fe transporters IRT1 and IRT2 are upregulated under Fe

starvation (Eide et al., 1996; Vert et al., 2001). This leads to a substantial increase of

Fe concentrations in the roots (Vert et al., 2002). A comparative study using a

subspecies of A. halleri (A. halleri spp. gemmifera) and A. thaliana demonstrated that

the transcript levels of these two transporters were around 100-fold (IRT1) and 10-

fold (IRT2) more highly expressed in A. thaliana roots than in A. halleri roots, after

cultivation on Fe deficient medium (Shanmugam et al., 2011). The transcript levels of

IRT1 and IRT2 were only marginally increased in A. halleri upon Fe deficiency in

comparison to Fe sufficient conditions (Shanmugam et al., 2011). As this evidence

suggested that the principal genes for Fe uptake are much lower expressed and

differentially regulated in A. halleri than A. thaliana, this might explain the moderate

phenotypes observed in roots of FRD3-RNAi lines versus their wild-type lines in

comparison to phenotypes of frd3 mutants of A. thaliana. It would thus be useful to

address in the future whether the Langelsheim accession of A. halleri responds to Fe

deficiency in a similar manner as A. halleri ssp. gemmifera.

4.2.4 Root-to-shoot Pb transport depends on FRD3

The observations that FRD3-RNAi line 18.2 contained lower citrate concentrations in

the xylem sap compared with the wild type xylem sap (Figure 32d) and that roots of

that RNAi line contained significantly higher concentrations of Pb than the wild type

roots suggested that citrate might act in maintaining Pb in soluble form in the

apoplast – similar to the reported role of citrate in apoplastic Fe mobility in A.

thaliana – permitting the root-to-shoot translocation of Pb. In support to this

hypothesis, there is indirect evidence in the literature for the formation of Pb-citrate

complexes, potentially [Pb(II)3-Citrate] in wheat roots (Varga and Fodor, 1997). The

concentrations of other organic acids that could potentially chelate and solubilize Pb,

such as malate and fumarate, were lower in FRD3-RNAi 18.2 xylem sap than in the

wild-type xylem sap, but not significantly different (Figure 32b-c). Therefore, it is less

likely that malate and fumarate are involved in root-to-shoot Pb translocation in A.

138

Discussion halleri. There is a possibility that one or both of two unidentified peaks correspond to

a major FRD3 substrate in A. halleri that remains to be identified.

As mentioned earlier, citrate is thought to be the main chelator of FeIII in the xylem

sap in some plants including A. thaliana. Citrate efflux from the root pericycle cells is

up-regulated in A. halleri (Figure 32d) if compared to citrate levels reported for A.

thaliana (Durrett et al., 2007). Probably the concentrations of citrate in the xylem sap

of FRD3-RNAi 18.2 (150 µM) were still at levels sufficient to maintain a proper Fe

solubility and mobility in the vascular tissues of those plants. One explanation for the

strongly altered translocation of Pb, but not of other metals, from roots to shoots in

FRD3-RNAi 18.2 could be the absence of the unknown compound “X1” identified in

the HPLC analysis of xylem sap (Figure 33). This compound was present in the

xylem sap of the wild type, at the retention time of approximately 5.5 min, but not in

the FRD3-RNAi xylem sap. In A. thaliana xylem sap it was not detected too. In the

literature there is no report for organic compounds produced by plants which

specifically chelates Pb in the xylem sap and most plant species accumulate very

small concentrations of Pb in green tissues when grown on soils or realistic

experimental Pb concentrations (Chary et al., 2008; Fischer et al., 2014; Intawongse

and Dean, 2006). As our HLPC method was a reversed-phase chromatography, the

peak X1 compound should be more polar than the other organic acids analyzed,

because it was detected quite early after the injection peak. A very polar compound

reported to promote Pb mobility and accumulation in plants is EDTA (Luo et al.,

2006; Saifullah et al., 2009; Vassil et al., 1998), but it is not synthesized by plants,

was not present in the growth media used for the experiments in this thesis. In

addition, the wavelength for UV detection of EDTA – 250 nm or higher (Cagnasso et

al., 2007) – is different than the 210 nm used in our method. Therefore, the re-

sampling of xylem sap from A. halleri wild type plants is required for the identification

of the “X1” compound through mass spectrometry.

Based on the experimental evidence obtained here, the following model is suggested

for the biological function of FRD3 in leaf Pb accumulation (Figure 41).

139

Discussion

A. halleri

Fe-deficiency signalling

PbII

ZnII

FRD3

Citrate

IRT/ZIP FeIII

reductase

HMA3

HMA4

Epidermis Cortex Endodermis

Pericycle

WT

FRD3

-RN

Ai

ZnII

Leaves

FeIII

FeII

ZnII

MnII

PbII

FeIII

FeII

ATP

ADP + Pi

FRO2

IRT1

ZIP? Others

CdII

Xylem

CdII

FeIII

PbII

PbII

?

CdII

ZnII

MnII

PbII

FeIII

FeII

?

CdII

FRO2

IRT1

ZIP? Others

ATP

ADP + Pi

ZnII

Leaves

FeIII

FeII

CdII

PbII

ZnII

CdII

FeIII

FeIII

FeIII

Pb

II

Pb

II

“X1”

PbII

PbII

140

Discussion

Figure 41 Model for FRD3 function in A. halleri based on the results of this work. FRD3-mediated citrate efflux from the root pericycle cells is up-regulated in A. halleri and, in accordance with highly expressed FRD3 in A. halleri when compared to A. thaliana, ~3-fold higher citrate levels are found in xylem exudates of the former in comparison to the latter. The high availability of citrate in the xylem maintains the solubility of the comparably high concentrations of Pb

II,

in addition to FeIII as an essential nutrient. A. halleri might also release unknown chelators (“X1”

compound) that might specifically act in root-shoot PbII mobility, and there might then be genes acting

redundantly, or partially redundantly, with FRD3 in maintaining root-to-shoot mobility of FeIII, but not

PbII. In addition, HMA4 is also highly expressed in the pericycle cells and can hypothetically mediate

the loading of PbII into the xylem. In the FRD3-RNAi lines, the significantly reduced expression of

FRD3 in root pericycle cells reduces xylem citrate. Thus, PbII is chelated less efficiently and should

supposedly accumulate in the vasculature. In these transgenic lines, xylem citrate levels are significantly reduced when compared to the wild type, but still 50% higher than in the A. thaliana wild type. Similar to what occurs in A. thaliana, shoot-to-root Fe deficiency signaling enhances Fe, Zn, and Mn uptake and accumulation in roots, however at a much lower extent. Zn and Fe status in shoots are unaltered under the conditions tested, whereas the accumulation Mn is variable between independent RNAi lines. No chlorosis was observed in leaves of FRD3-RNAi lines. In A. halleri, root-to-shoot Fe

III

translocation and apoplastic FeIII movement in shoot might still be possible at the citrate levels found

in FRD3-RNAi lines. Alternatively, root-to-shoot FeIII translocation and apoplastic Fe

III movement may

use a different chelator in addition to, or instead of, citrate.

4.2.5 Modifications in the predicted FRD3 protein sequence of A. halleri

Because A. halleri is evolutionarily very closely related to A. thaliana and shares with

it a high percentage of the FRD3 genomic (88%), coding (95%) and predicted protein

(94%) sequence identity, FRD3 proteins of both species are likely to have shared or

similar functions. The N116S amino acid substitution found in the predicted FRD3

protein sequence of A. halleri (Figure 35) did not seem to affect the citrate

concentration in the xylem sap, since the xylem citrate levels in wild type A. halleri

(Figure 32c) were in the range of other hyperaccumulator species (Lu et al., 2013)

and higher than what has been reported for A. thaliana (Durrett et al., 2007; Schuler

et al., 2012). In addition to this, the abrogation of citrate efflux in A. thaliana was

suggested to be caused by N116S in combination with L117P (Pineau et al., 2012).

The latter substitution was not found in the predicted FRD3 sequence of A. halleri,

which has a Leucine (L) in position 117 such as in A. thaliana. The citrate transport

capability of A. halleri FRD3 can be directly tested by the heterologous expression of

this cDNA in Xenopus laevis oocytes in efflux experiments using two-electrode

voltage clamping technique. Unfortunately due to technical issues, even despite

several attempts, the cloning of FRD3-expression constructs into the required vector

for the transport assay was not achieved until the completion of this thesis.

141

Discussion

4.2.6 A. halleri sequesters Pb in the leaf vasculature and trichomes base

The analysis of different tissues in plants grown on metal-contaminated soil

suggested that after Pb is transported into above-ground tissues A. halleri plants

restrict Pb accumulation in the leaf mesophyll and direct a proportion of Pb to old

stems and petioles (Table 15). This is contrary to the preferential transport of other

essential nutrients into the leaf blade (Table 15 and Figure 38). In addition to that,

the experiments using µPIXE showed that the highest concentrations of Pb in leaves

of A. halleri wild type were found in the vascular tissue and at the base of the

trichomes (Figure 36). The sequestration of Pb in trichomes can be interpreted as a

mechanism of tolerance, when plants try to avoid heavy metal accumulation in the

leaf mesophyll. This hypothesis is consistent with a number of studies using A.

halleri, in which the analysis of trichomes revealed that the highest concentrations of

Zn and Cd were sequestered exactly at the base of the trichomes (Fukuda et al.,

2008; Kupper et al., 2000; Sarret et al., 2002; Zhao et al., 2000). Therefore, our data

suggest that the detoxification of Pb in leaves of A. halleri share at least a small

portion of the routes for the detoxification of Zn and Cd.

4.2.7 AhFRD3 is a good candidate for exploring phytoremediation technology

development

The introduction of different constructs containing AhFRD3 into the model species A.

thaliana suggested that AhFRD3 may be useful for enhancing leaf Pb accumulation

in non-accumulator species. A. thaliana transgenic plants overexpressing AhFRD3

under the control of 35S CaMV promoter accumulated approximately 100% more Pb

in their leaves when compared with the wild type (Figure 39c). The leaf

concentrations of Zn were about 29% higher only in two transgenic lines, one

expressing the gAhFRD3 and another 35S:AhFRD3 construct (Figure 39d). Both

overexpressing constructs 35S:AhFRD3:HA and 35S:AhFRD3 were more effective

to promote leaf Pb accumulation in A. thaliana than the gAhFRD3 construct. These

results are to certain extent similar to earlier findings of enhanced Se accumulation

in A. thaliana transgenic plants transformed with Selenocysteine Methyltransferase

(SMT) from Se hyperaccumulator species Astragalus bisulcatus (Ellis et al., 2004).

This gene encodes an enzyme involved in Se tolerance through the conversion of

seleno amino acids into non-protein derivatives, such as Se-methylselenocysteine

142

Discussion

(MeSeCys). In that study, it was shown that SMT-transformed plants contained 100-

800% increased shoot Se concentrations compared with plants transformed with an

empty vector. Other studies have reported transgenic-mediated increase in shoot

accumulation of different metals. However, most of the genes tested were not

originated from metal hyperaccumulator species. For instance, an increase of about

100% Se concentrations in shoots was reported for Indian mustard plants

overexpressing the ATP Sulfurylase 1 (APS1) compared with non-transformed plants

(Van Huysen et al., 2004). In that case, the APS1 gene introduced into Indian

mustard was cloned from A. thaliana. In shrub tobacco (Nicotiana glauca R.

Graham) grown on Pb contaminated soil, Pb concentrations were reported to

increase by 50% in shoots of transgenic plants overexpressing PCS1 compared with

wild type non-transformed plants (Gisbert et al., 2003). In that study, the PCS1 gene

was cloned from wheat (Triticum aestivum).

In this thesis, we used A. thaliana to test our hypothesis because it is a species more

closely related to A. halleri and share high percentage of the FRD3 protein

sequence. Since A. thaliana is not a Pb accumulator and therefore does not possess

enhanced Pb uptake mechanisms, one interesting approach may be the introduction

of overexpressing 35S:AhFRD3:HA and 35S:AhFRD3 constructs into Pb

accumulator species, such as H. incana (Auguy et al., 2013) and T. praecox Wulf

(Vogel-Mikus et al., 2005). Both species are confirmed to preferentially retain Pb in

the roots due to inefficient root-to-shoot translocation mechanisms. This strategy

could be used to directly test whether AhFRD3 alone is able to enhance root-to-

shoot translocation and promote shoot Pb hyperaccumulation in other metal-

hyperaccumulator species.

143

Conclusion

5 Conclusion

Together, the exploratory analyses conducted here have helped to gain insights on

the contribution of metal-related candidate genes to metal (hyper)accumulation and

tolerance in A. halleri. Multivariate models can thus be used as a powerful approach

for accurately identifying the main effects of candidate gene silencing on plant

phenotypes using a large number of samples. This helps narrowing the focus down

to the most severe phenotypes. Furthermore, the model-based control of interfering

factors that might obscure key results, such as the influence of soil properties,

improved the outcomes.

The contribution of HMA3 gene to metal hyperaccumulation and hypertolerance was

not clearly evident under the experimental conditions employed. Leaf metal

concentrations in HMA3-RNAi lines were either not significantly different from the

wild type or not consistent between the three independent RNAi lines. With the use

of HMA4-RNAi lines, the requirement of AhHMA4 for Zn and Cd hyperaccumulation

was demonstrated in a variety of soils on which natural populations of A. halleri grow

in the field. This reinforced previous hypotheses suggesting that HMA4 role in Zn/Cd

hyperaccumulation is required on both metalliferous and non-metalliferous soils.

Moreover, to a certain degree, HMA4 contributes to leaf Pb accumulation in

metalliferous soils. On the basis of the stress markers analyzed as an estimation of

metal tolerance, our data suggested that the contribution of HMA4 to metal tolerance

is more important on metalliferous soils.

The silencing of the FRD3 gene impaired leaf Pb accumulation in A. halleri on both

metalliferous and non-metalliferous soils. Moreover, FRD3 was found to contribute to

plant growth and to suppress metal toxicity in A. halleri on metalliferous soils. On

non-metalliferous soils, only Pb accumulation was significantly affected in FRD3-

RNAi lines, whereas only mild metal toxicity symptoms were observed upon growth

on a subset of highly metalliferous soils regarding the stress markers analyzed.

Therefore, FRD3 is apparently more important for A. halleri metal accumulation and

tolerance in metalliferous environments. Further analysis of FRD3-RNAi lines

suggested that the major role of FRD3 in A. halleri is promoting root-to-shoot

translocation of Pb, thus enabling A. halleri to accumulate high levels of Pb in

144

Conclusion

shoots. In the shoots, Pb is sequestered at the base of trichomes and in the leaf

vasculature likely as a mechanism of metal tolerance in order to prevent heavy

metal-induced damages in photosynthetic cells. FRD3 silencing does not strongly

interfere with the accumulation of other metals under the growth conditions

employed.

The data presented here suggest the possibility that the function of FRD3 in A.

halleri is different from that of FRD3 in A. thaliana at the level of protein function or in

the physiological context of the respective organisms. Phenotypes of A. halleri

FRD3-RNAi plants were different, in orders of magnitude, from the frd3 mutants of A.

thaliana. Finally, the data suggest that the transfer of A. halleri FRD3 into a different

plant species may enhance root-to-shoot translocation of Pb, thus enabling the

generation of transgenic plants with the ability to accumulate Pb in shoots. This is of

relevance for phytoremediation.

145

Summary

6 Summary

Arabidopsis halleri is a metal hypertolerant Zn/Cd hyperaccumulator species, which

colonizes environments with heavily metal-contaminated soils and also non-

contaminated areas. This species displays several fold higher transcript levels of a

number of metal-related genes when compared to other non-tolerant metal non-

accumulator species, including its sister species Arabidopsis thaliana. The aim of

this thesis was to understand the contribution of three candidate genes (AhHMA3,

AhHMA4, and AhFRD3) to metal hyperaccumulation and hypertolerance in A. halleri

by comparing wild-type and RNAi lines cultivated on a variety of hosting soils of

natural A. halleri populations. The AhFRD3 gene was functionally characterized

based on initial results of this work.

Plants of three independent lines of HMA3-, HMA4-, and FRD3-RNAi displaying

significantly reduced transcript levels of HMA3, HMA4, and FRD3, respectively, by

RNAi interference technology were grown under controlled conditions for five weeks

on seven different contaminated and non-contaminated soils alongside the wild type.

The results confirmed that, on all different soils tested, the silencing of HMA4 gene

reduced the leaf Zn and Cd hyperaccumulation in HMA4-RNAi lines. The silencing of

FRD3 gene significantly reduced leaf Pb concentrations in FRD3-RNAi lines when

compared to the wild type. The changes in leaf metal concentrations observed in

HMA3-RNAi were mostly not significantly different compared with the wild type. The

analysis of plant performance and stress markers, as a measure of tolerance to

heavy metals, revealed less contribution of those three genes to plant growth and to

prevent metal-induced stress than their contribution to heavy metal

hyperaccumulation. The data suggested that HMA4 and FRD3 contribute to plant

growth and the prevention of oxidative stress only in some of the metalliferous soils.

The functional characterization of the FRD3 gene in A. halleri suggested that root-to-

shoot transport of Pb was reduced in FRD3-RNAi lines compared with the wild type

likely due to lower citrate concentrations, or potentially the absence of a yet unknown

compound, in the xylem sap. This impaired root-to-shoot translocation of Pb and

compromised the accumulation of Pb in leaf tissues. In leaves of the wild type, Pb

146

Summary

was mostly localized in the vasculature and at the base of the trichomes, consistent

with the hypothesis of heavy metal tolerance in shoots. The analysis of Pb

accumulation in A. thaliana wild type and frd3-1 mutant on artificial media containing

Pb suggested that leaf Pb concentrations in this species are increased likely through

a different mechanism than the observed in A. halleri. The frd3-1 mutant displayed

higher concentrations of Pb in both roots and shoots in comparison to the wild-type.

In addition, Pb accumulation in A. thaliana was enhanced by Fe deficiency-induced

metal uptake responses.

In summary, under the experimental conditions employed here, the results of this

thesis support the hypothesis that FRD3 gene is essential for leaf Pb accumulation in

A. halleri, what differs from its orthologous major role in Fe homeostasis in A.

thaliana. The role of HMA4 in Zn and Cd hyperaccumulation was confirmed to be

essential for A. halleri on a variety of native soils, on which this species naturally

grows in nature. This work releases original data that enrich the current

understanding on metal hypertolerant hyperaccumulator species A. halleri and

provides valuable information to further hypothesis testing approaches on A. halleri

evolutionary studies.

147

Zusammenfassung

7 Zusammenfassung

Arabidopsis halleri ist eine metall-hypertolerante, Zink (Zn) und Cadmium (Cd)

hyperakkumulierende Pflanze, welche sowohl schwermetallkontaminierte als auch

nichtkontaminierte Standorte besiedelt. Verglichen mit anderen Pflanzen, wie der

nichthyperakkumulierenden Schwesterspezies Arabidopsis thaliana, welche keine

Hypertoleranz gegenüber Schwermetallen aufweist, zeigt A. halleri deutlich erhöhte

Transkriptmengen von Metalhomöostasegenen. Das Ziel dieser Arbeit war es, den

Einfluss von drei Kandidatengenen (AhHMA3, AhHMA4, AhFRD3) auf die

Metallhyperakkumulation und –toleranz in A. halleri zu verstehen. Hierfür wurden

Wildtyp und RNAi-Linien vergleichend auf verschiedenen Böden natürlich

vorkommender A. halleri Populationen kultiviert. Das Gen AhFRD3 wurde, basierend

auf Ergebnissen dieser Arbeit, funktionell charakterisiert.

Jedes dieser drei Gene wurde einzeln über RNA-Interferenz in seiner Expression

gehemmt. Je drei Pflanzen unabhängig transformierter Linien mit signifikant

reduzierten Transkriptmengen für HMA3, HMA4 und FRD3 wurden parallel zum

Wildtyp für funf Wochen auf unterschiedlichen natürlichen Böden unter kontrollierten

Bedingungen kultiviert. Die Ergebnisse dieser Arbeit zeigen, dass die Reduktion von

HMA4 die Akkumulation von Zn und Cd in den HMA4-RNAi-Linien vermindert. Die

Hemmung der Expression von FRD3 durch RNAi reduziert die Pb-Konzentrationen

in FRD3-RNAi-Linien – verglichen mit dem Wildtyp – auf allen getesteten Böden

signifikant. Die in den HMA3-RNAi-Pflanzen beobachteten Änderungen in den

Metallkonzentrationen der Blätter waren im Vergleich zum Wildtyp hingegen nur

gering und nicht signifikant. Die Analyse von Wachstumsparametern und

Stressmarkern in den Mutanten wiesen auf einen geringeren Einfluss der drei

Kandidatengene auf die Pflanzenentwicklung und den Schutz vor

schwermetallinduziertem Stress hin, als deren Beitrag zur

Schwermetallakkumulation vermuten ließ. Allerdings legen die Daten nahe, dass

HMA4 und FRD3 Einfluss auf das Pflanzenwachstum und den Schutz vor oxidativem

Stress auf einigen metallhaltigen Böden nehmen.

148

Zusammenfassung

Die funktionelle Charakterisierung des FRD3-Gens in A. halleri lässt vermuten, dass

der Wurzel-Spross-Transport von Pb in FRD3-RNAi Linien reduziert ist, was auf

geringere Citratkonzentrationen oder möglicherweise das Fehlen einer noch

unbekannten Verbindung im Xylemsaft zurückzuführen sein könnte. Dies stört die

Verteilung von Pb zwischen Wurzel und Spross und beeinträchtigt so dessen

Akkumulation in den Blättern. In Wildtypblättern findet sich Pb hauptsächlich in den

Leitgeweben und an der Basis der Trichome, was mit der Hypothese der

Schwermetalltoleranz im Sproß übereinstimmt. Die Untersuchung von A. thaliana-

Wildtyppflanzen und frd3-1-Mutanten auf bleihaltigem Nährmedium legt nahe, dass

die Pb-Gehalte in dieser Spezies möglicherweise über einen anderen Mechanismus

reguliert werden, als in A. halleri beobachtet. Die frd3-Mutante zeigt sowohl in den

Wurzeln als auch im Sproß mehr Pb als der Wildtyp. Weiterhin konnte die

Bleiakkumulation durch Eisenmangelbedingungen und die damit einhergehenden

Änderungen der Metallhomöostase in A. thaliana verstärkt werden.

Zusammenfassend stärken die Ergebnisse dieser Arbeit die Annahme, dass FRD3

essentiell für die Aufnahme von Blei in den Spross von A. halleri ist. Im Unterschied

dazu stellt FRD3 in A. thaliana einen elementaren Bestandteil der Eisenhomöostase

dar. Die Rolle von HMA4 in der Hyperakkumulation von Zn und Cd konnte nochmals

auf Böden, welche diese Spezies auch in der Natur besiedelt, gezeigt werden.

Die in dieser Arbeit bereitgestellten Daten erweitern das Verständnis der

zugrundeliegenden Mechanismen von hypertoleranten und hyperakkumulierenden

Pflanzen wie A. halleri. Darüberhinaus liefern sie wertvolle Informationen für das

Testen weiterer Hypotesenansätze zur Evolutionsforschung von A. halleri.

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9 Appendix

A. Supplementary Data

Figure S1 Langelsheim site. Partial view of the Langelsheim site and a local A. halleri individual (inset). Located in the district of Goslar, Lower Saxony, Germany. Heavily metal-contaminated site due to historical mining activities. Today, most of the area where A. halleri plants are found is probably on mining waste (Ernst et al., 2004). Photos: Romário Melo.

Figure S2 Littfeld site. Partial view of the Littfeld site and a local A. halleri individual (inset). Located in the district of Siegen-Wittgenstein, North Rhine-Westphalia, Germany. The area is known for its Zn and Pb mining activities during the middle ages and 19

th century. The place for soil sampling was on

mining waste and it is colonized by A. halleri plants and other metallicolous plant species.

(http://www.mindat.org/loc-29163.html). Photos: Romário Melo.

http://www.mindat.org/loc-29163.html

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Figure S3 Evín-Malmaison site. Partial view of the Evín-Maimaison site and a local A. halleri individual (inset). Located in the department of Pas-de-Calais, Nord-Pas-de-Calais region, France. A. halleri population is found along the shores of the Canal de la Deûle, which links northern France and the Belgian border in Deûlémont. Plants grow on a highly metal-contaminated soil in an open sunny area as well as surrounded by dense vegetation of bushes and tall trees inside the shady woods. The soil contamination was caused by Pb-Zn smelter near the urbanized area, which is also close to another Zn smelter in the city of Auby – where A. halleri populations are found too. The dust emissions were reduced from several tons day

-1 to ~300 kg day

-1 after the implementation of off-gas

filters by regulatory standards in 1970 (Manceau et al., 2000). Photos: Romário Melo.

Figure S4 Bestwig site. Partial view of the Bestwig site and a local A. halleri individual (inset). Located in the district of Hochsauerland, North Rhine-Westphalia, Germany. One of the largest A. halleri populations found so far, with a number of individuals above 10,000 plants. Plants grow on heaps of Zn and Pb mine tailings (http://www.mindat.org/loc-132239.html). Photos: Romário Melo.

http://www.mindat.org/loc-132239.html

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Figure S5 Malmedy site. Partial view of the Malmedy site and a local A. halleri individual (inset). Located in the province of Liège, Belgium. Plants of A. halleri are found growing in a shadowed humid

area, inside the woods with dense vegetation of bushes and tall trees. Photos: Romário Melo.

Figure S6 Wehbach site. Partial view of the Wehbach site and a local A. halleri individual (inset). Located in the district of Altenkirchen, North Rhineland-Palatinate, Germany. Population of A. halleri colonizes the region alongside a road and nearby private gardens. The area is shadowed due to dense vegetation of tall trees. Photos: Romário Melo.

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Figure S7 Rodacherbrunn site. Partial view of the Rodacherbrunn site and a local A. halleri individual (inset). Located in the district of Saale-Orla-Kreis, Thuringia, Germany. A. halleri plants colonize a large meadow surrounded by woods of tall trees. The area is mostly open to sun light, but some plants are also found inside the forest in shady spots. Photos: Romário Melo.

Figure S8. Kaiser-Guttman criterion and broken-stick model to indicate the number of interpretable axes in PCA.

Bargraphs show the analysis of (a, c) leaf ionome and (b, d) plant growth and stress using the

heuristic procedures of Kaiser-Guttman criterion for retaining components with eigenvalues (λs) >

larger than the average of all eigenvalues (a, b), and broken-stick model for retaining eigenvalues

(grey bars) which are larger than the length of the corresponding piece of stick (black bars) (c, d).

(Borcard et al., 2011; Jackson, 1993).

(a)

(c)

(b)

(d)

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Figure S9 Photographs of HMA3-, HMA4-, and FRD3-RNAi and wild-type lines on Littfeld soil. Shown are photographs of one representative individual for each of the three independent RNAi lines per target gene and wild-type control lines. (a-c) Wild-type (WT) (a) Lan, (b) TC, and (c) TrC, HMA3-RNAi lines (d) 1.2, (e) 4.1, and (f) 5.2, HMA4-RNAi lines (g) 3.1.1, (h) 4.2.1, and (i) 4.3.2, and FRD3-RNAi lines (j) 7.1, (k) 9.1 and (l) 18.2. Three-week-old clones were transplanted into metalliferous soil from Langelsheim and cultivated in a growth chamber for an additional five weeks. Violet arrows: purple leaves. Scale bar: 30 mm.

(g) (h) (i)

(a) (b) (c)

(d) (e) (f)

(j) (k) (l)

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Figure S10 Photographs of HMA3-, HMA4-, and FRD3-RNAi and wild-type lines on Evín-Malmaison soil. Shown are photographs of one representative individual for each of the three independent RNAi lines per target gene and wild-type control lines. (a-c) Wild-type (WT) (a) Lan, (b) TC, and (c) TrC, HMA3-RNAi lines (d) 1.2, (e) 4.1, and (f) 5.2, HMA4-RNAi lines (g) 3.1.1, (h) 4.2.1, and (i) 4.3.2, and FRD3-RNAi lines (j) 7.1, (k) 9.1 and (l) 18.2. Three-week-old clones were transplanted into metalliferous soil from Evín-Malmaison and cultivated in a growth chamber for an additional five weeks. Violet arrows: purple leaves, yellow arrows: senescent leaves, gray arrows: necrotic spots. Scale bar: 30 mm.

(d) (e) (f)

(h) (i) (j)

(g) (k) (l)

(a) (c) (b)

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Figure S11 Photographs of HMA3-, HMA4-, and FRD3-RNAi and wild-type lines on Bestwig soil. Shown are photographs of one representative individual for each of the three independent RNAi lines per target gene and wild-type control lines. (a-c) Wild-type (WT) (a) Lan, (b) TC, and (c) TrC, HMA3-RNAi lines (d) 1.2, (e) 4.1, and (f) 5.2, HMA4-RNAi lines (g) 3.1.1, (h) 4.2.1, and (i) 4.3.2, and FRD3-RNAi lines (j) 7.1, (k) 9.1 and (l) 18.2. Three-week-old clones were transplanted into metalliferous soil from Bestwig and cultivated in a growth chamber for an additional five weeks. Scale bar: 30 mm.

(a) (b) (c) (a)

(g) (h) (i)

(j) (k) (l)

(e) (f) (d)

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Figure S12 Photograph of HMA3-, HMA4-, and FRD3-RNAi and wild-type lines on Wehbach soil. Shown are photographs of one representative individual for each of the three independent RNAi lines per target gene and wild-type control lines. (a-c) Wild-type (WT) (a) Lan, (b) TC, and (c) TrC, HMA3-RNAi lines (d) 1.2, (e) 4.1, and (f) 5.2, HMA4-RNAi lines (g) 3.1.1, (h) 4.2.1, and (i) 4.3.2, and FRD3-RNAi lines (j) 7.1, (k) 9.1 and (l) 18.2. Three-week-old clones were transplanted into non-metalliferous soil from Wehbach and cultivated in a growth chamber for an additional five weeks. Scale bar: 30 mm.

(a) (b) (c)

(d) (e) (f)

(j) (k) (l)

(g) (h) (i)

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Figure S13 Photographs of HMA3-, HMA4-, and FRD3-RNAi and wild-type lines on Rodacherbrunn soil. Shown are photographs of one representative individual for each of the three independent RNAi lines per target gene and wild-type control lines. (a-c) Wild-type (WT) (a) Lan, (b) TC, and (c) TrC, HMA3-RNAi lines (d) 1.2, (e) 4.1, and (f) 5.2, HMA4-RNAi lines (g) 3.1.1, (h) 4.2.1, and (i) 4.3.2, and FRD3-RNAi lines (j) 7.1, (k) 9.1 and (l) 18.2. Three-week-old clones were transplanted into non-metalliferous soil from Rodacherbrunn and cultivated in a growth chamber for an additional five weeks. Scale bar: 30 mm.

(a) (b) (c)

(d) (e) (f)

(g) (h) (i)

(j) (k) (l)

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Figure S15. Leaf Mg concentrations of A. halleri plants cultivated on non-metalliferous soils. (a-c) Bargraphs show leaf Mg concentrations for wild type (black bar), HMA3-RNAi (yellow bars),

HMA4-RNAi (blue bars) and FRD3-RNAi lines (red bars) on (a) Malmedy soil (one-way ANOVA, p <

0.001, F = 28.9, η² = 0.86), (b) Wehbach soil (one-way ANOVA, p = 0.05), (c) Rodacherbrunn soil

(one-way ANOVA, p < 0.001. F = 8.6, η² = 0.69). Shown are mean values + SD [n = 4 (RNAi lines) or

12 (4 replicates for each of the three different genotypes used as wild-type controls)] from one

experiment. Different characters above the bars indicate statistically significant differences detected in

a one-way ANOVA, followed by post-hoc Tukey HSD test and eta-Squared (η²) effect size test.

Malmedy

HMA3- HMA4- FRD3-

RNAi lines

a a a a a

b b bc

bc

b

Wehbach

HMA3- HMA4- FRD3-

RNAi lines

ns

Rodacherbrunn

HMA3- HMA4- FRD3-

RNAi lines

a a

a a

a ab

ab

bc bc

bc

b c a

174

Appendix

Figure S16. Partial redundancy analysis of stress markers in samples from metalliferous and non-metalliferous soils. (a-b) Diagrams show the first two dimensions of partial redundancy analysis (RDA) plot for sample from plants cultivated on (a) four metalliferous soils and (b) three non-metalliferous soils. Shown are samples (different symbols), plant performance and stress markers (positions of bigger characters), and their matrix correlations with transcript levels of AhHMA3, AhHMA4, AhFRD3 (arrows with smaller characters), for model based on standardized (z-scores) of Log10(x + 1) stress markers and transcript

levels using Log10(x + 1) soil exchangeable element concentrations as a covariable. : wild type, :

HMA3-RNAi, : HMA4-RNAi, : FRD3-RNAi. Different shades represent independent RNAi lines for each of the target genes (the lighter the shade, the lower the transcript levels detected).

a

b

175

Appendix

Figure S17. A. thaliana wild type and frd3-1 mutant grown on media with different pH.

A. thaliana Col-0 and frd3-1 mutant plants were grown on modified 0.25x Hoagland solid medium without Pb. Photographs were taken after 16 days of cultivation. The decrease in the media pH affected both genotypes at the same extent, by slightly reducing the root length. The frd3-1 was chlorotic and had shorter roots in all media tested.

Figure S18. FRD3-RNAi leaf Mn concentration is variable between different soils. Three-week-old clones were cultivated for five weeks on Evín-Malmaison (a) and Rodacherbrunn (b) soils. Bar plots show comparisons between wild-type and FRD3-RNAi lines for leaf Mn concentrations of plants grown on (a) Evín-Malmaison soil (one-way ANOVA, p < 0.05, F = 6.89, η² = 0.51), and (b) Rodacherbrunn soil (one-way ANOVA, p = 0.44). Shown are mean values + SD [n = 4 (FRD3-RNAi lines) and 12 (4 replicates for each of the three independent wild-type lines)] of three independent experiments for (a) and one experiment for (b). Different characters above the bars indicate statistically significant difference between the wild type and the respective FRD3-RNAi line by one-way ANOVA, followed by post-hoc Tukey HSD test and eta-Squared effect (η²) size test. ns: not significant.

frd3-1 Col-0

pH 4.0

frd3-1 Col-0

pH 6.0

frd3-1 Col-0

pH 5.0

a

a ab

b

ns

FRD3-RNAi FRD3-RNAi

176

Appendix

Figure S19. Zn concentrations in FRD3-RNAi lines were mostly not significantly different from the wild-type on different native soils.

Three-week-old clones were cultivated for five weeks on different native soils. Bar plots show

comparisons of leaf Zn concentrations between wild-type and FRD3-RNAi lines on (a) metalliferous

Littfeld soil (one-way ANOVA, p = 0.08), (b) metalliferous Evín-Malmaison soil (one-way ANOVA, p =

0.69), (c) metalliferous Bestwig soil (one-way ANOVA, p = 0.26), (d) non-metalliferous Malmedy soil

(one-way ANOVA, p = 0.44), (e) non-metalliferous Wehbach soil (one-way ANOVA, p < 0.01, F = 5.8,

η² = 0.46), and (f) non-metalliferous Rodacherbrunn soil (one-way ANOVA, p < 0.05, F = 3.9, η² =

0.37). Shown are representative mean values + SD [n = 4 (FRD3-RNAi lines) and 12 (4 replicates for

each of three the independent wild-type lines)] of at least three independent experiments for

metalliferous soils and one experiment for non-metalliferous soils. Different characters above the bars

indicate statistically significant difference between the wild type and the respective FRD3-RNAi line by

one-way ANOVA, followed by post-hoc Tukey HSD test and eta-Squared effect (η²) size test. ns: not

significant.

(a) (b) (c)

ns ns ns

ns

a

b

a

a

a

ab

b

ab

(d) (e) (f)


177

Appendix

Table S1. Selection of the best predictive models using Akaike Information Criterion (AIC).

Matrices AIC output

Response Explanatory Predictor variables selected1 n F-value

Adjusted R²

Leaf ionome Soil properties sCd + sN + spH + sCr + sNi + sMn 4 91.8 0.63

Model with all variables AIC = 882.68

AIC = 570.48

Leaf ionome Transcript levels AhHMA4 + AhFRD3 4 42.2 0.14

All variables on metalliferous soils: AIC = 500.06

AIC = 477.82

Leaf ionome Transcript levels AhHMA4 + AhFRD3 4 18.4 0.12

All variables on non-metalliferous soils: AIC = 383.61

AIC = 367.59

Stress markers Transcript levels AhHMA3 + AhHMA4 4 6.8 0.03

All variables on metalliferous soils: AIC = 396.5

AIC = 393.22

Stress markers Transcript levels None of the genes was significantly selected

4 1.8 0.02

All variables on non-metalliferous soils: AIC = 304.2

1 Listed in the order of decreasing explanatory power.

178

Appendix

B. Sequences and constructs

B.1

AhHMA3 open reading frame (ORF) (2,274 nt)

ATGGCAGAAGGTGAAGAGGCCAAGAAGAAGAATTTACAGACAAGTTACTTCGACGTCGTTGGAATCTGCTGTACA

TCGGAGGTTTCTATCGTCGGTGACGTTCTCCGTCCACTTGACGGCGTCAAAGAATTCTCCGTTATCGTCCCTTCT

AGAACCGTCATCGTTGTCCATGACACTTTCTTGATTTCTCCGCTTCAAATCGTCAAGGCTCTGAATCAAGCAAGA

CTAGAAGCAAGTGTGAGACCATACGGAGAAACAAGCTTGAAGAGTCAATGGCCAAGTCCTTTTGCAATACTTTCT

GGGGTATTTCTTGCTCTCTCCTTCTTCAAATACTTTTATAGTCTGCTTGAATGGCTCGCTGTTGTTGCCGTGGTG

GCCGGGATTTTCCCCATCCTTGCTAAAGCTGTTGCTTCGGTCACAAGGTTCAGACTTGATATCAACGCTCTCACT

TTTATTGCTGTGATAGCAACACTATGTATGCAGAATTTCACAGAAGCTGCCACAATTGTGTTTCTATTCTCAGTT

GCAGATTGGCTAGAGTCTAGTGCTGCTCATAAGGCAAGCACAGTAATGTCATCACTGATGAGCTTAGCGCCACGA

AAGGCAGTGATAGCGGAAACTGGACACGAAGTCGATGTAGATGAGGTTAGGATCAACACAATTGTTTCAGTGAAA

GCTGGAGAAAGTATACCGATTGATGGAGTTGTGGTGGATGGAAGCTGTGATGTGGATGAGAAAACATTGACAGGA

GAGTCATTCCCTGTCTCCAAACAGAGAGATTCAACTGTTTTGGCTGCAACCATAAATCTTAATGGTTATATAAAG

GTGAAAACTACAGCTCTAGCCCGGGACTGCGTAGTCGCGAAAATGACTAAGCTTGTAGAAGAAGCTCAAAAAAGC

CAAACCAAAACTCAAAGGTTTATAGATAAATGTTCTCGCTACTACACTCCAGCTGTTGTCGTGTTAGCAGCATGT

TTTGCGGTGATCCCGGTATTGTTAAAGCTTCAGGACCTTAGCCATTGGTTTCACTTAGCACTTGTAGTGTTAGTA

AGTGGTTGTCCATGTGGTCTTATCTTATCCACACCTATTGCTACCTTTTGTGCTCTCACTAAGGCAGCCATGTCG

GGGTTTCTGATCAAAACTGGTGATTGTCTAGAGACTCTTGCAAAGATCAAGATTGTTGCTTTTGACAAAACAGGA

ACTATTACAAAGGCTGAGTTCATGGTCTCGGATTTTAGGTCTCTTTCTCACAATATCAATCTGCACAACTTGCTT

TACTGGGTCTCGAGCATTGAGAGCAAGTCAAGTCATCCGATGGCAGCGGCGCTTATTGACTATGCAAGATCAGTT

TCTGTTGAGCCTAAGCCTGATCTCGTTGAGAACTTTCAAAACTTTCCAGGAGAAGGAGTTTATGGGAGAATAGAT

GGTCAAGATATCTACATTGGAAACAAAAGAATTGCACAGAGAGCTGGATGCTTAACAGTTCCGGATATGGAAGCT

AATATGAAGCGAGGTAAGACCATTGGTTACATATACATTGGAGCAAAACTGTCCGGAAGTTTCAACCTTATTGAC

AGTTGTCGATATGGGGTTGCTCAAGCTCTCAAGGAGCTCAAGTCTTTAGGAATCAAAACTGCAATGCTCACAGGA

GATAACCGAGACGCAGCCCTGTCTACTCAAGAACAGTTAGAGAATGCTTTGGATATTGTTCACTCTGAACTCCTT

CCACAAGACAAAGCAAGAATCATCGATGAATTCAAGATCCAAGGGCCTACAATGATGGTAGGAGACGGGCTTAAC

GATGCACCGGCTTTAGCGAAAGCAGACATTGGCCTTTCAATGGGGATCTCAGGGTCAGCACTTGCAACAGAGACA

GGAGACATCATTCTTATGTCAAACGATATAAGGAAGATCCCGAAAGGGATGAGACTAGCGAAGAGAAGTCATAAG

AAAGTGATTGAGAATGTTGTTTTGTCTGTGAGCATAAAAGGAGCAATCATGGTTCTTGCTTTTGTAGGTTACCCT

CTGGTTTGGGCAGCTGTACTTGCAGATGCAGGAACTTGTTTGCTTGTGATACTCAATAGTATGATGCTTCTACGC

GATGAGCGTGAAGCCGTGTCTACATGTTACCGTGCTTCTTCTTCGCCGGTGAAACTTGAGGAGGATGAAGCAGAG

GATCTAGAAGTTGGCTTGTTGCAGAAGAGTGAGGAGACAAATAAAAAGAGTTGTTGCTCTGGTTCTTGTAGTGGC

CCTAAGGACAATCAACAAAAGTGA

ATG: Translational start codon, TGA; Translational stop codon, bold: AhHMA3-RNAi fragment.

179

Appendix

B.2

AhHMA3-RNAi fragment used in intron-spliced hairpin construct (nt 1911-2241)

GATCCCGAAAGGGATGAGACTAGCGAAGAGAAGTCATAAGAAAGTGATTGAGAATGTTGTTTTGTCTGTGAGCAT

AAAAGGAGCAATCATGGTTCTTGCTTTTGTAGGTTACCCTCTGGTTTGGGCAGCTGTACTTGCAGATGCAGGAAC

TTGTTTGCTTGTGATACTCAATAGTATGATGCTTCTACGCGATGAGCGTGAAGCCGTGTCTACATGTTACCGTGC

TTCTTCTTCGCCGGTGAAACTTGAGGAGGATGAAGCAGAGGATCTAGAAGTTGGCTTGTTGCAGAAGAGTGAGGA

GACAAATAAAAAGAGTTGTTGCTCTGGTTCT

Schematic representation of the portion of the AhHMA3-RNAi construct designed for the intron-

spliced hairpin formation between sense and anti-sense 330-nt-long HMA3 fragments. This construct

was subcloned downstream of the CaMV 35S promoter in the pK7GWIWG2(I) (From Norman Ertych

Diploma thesis, University of Potsdam, 2007).

pK7-P35s-F

P35S T35S

pK7-intron-R

180

Appendix

B.3

AhHMA4 open reading frame (ORF) (3,492 nt)

ATGGCGTCACAAAACAAAGAAGAAGAGAAAAAGAAAGTGAAGAAGTTGCAAAAGAGTTACTTCGATGTTCTCGGA

ATCTGTTGTACATCGGAAGTTCCTATCATCGAGAATATTCTCAAGTCACTTGACGGCGTTAAAGAATATTCCGTC

ATCGTTCCCTCGAGAACCGTGATCGTTGTTCACGACAGCCTCCTCATCTCTCCCTTCCAAATTGCTAAGGCATTG

AACCAAGCTAGGTTAGAAGCAAACGTGAGAGTAAACGGAGAAACCAACTTCAAGAACAAATGGCCAAGCCCTTTC

GCGGTGGTTTCCGGCATACTTCTCCTCCTCTCCTTCTTAAAGTTTGTCTACCCGCCTTTACGCTGGCTTGCAGTC

GTAGCAGTTGCCGCCGGTATATATCCGATACTTGCCAAAGCCTTTGCTTCCATTAGAAGGCTTAGGCTCGACATC

AACATATTGGTCATTATAACCGTGATAGCAACACTTGCAATGCAAGATTTCATGGAGGCTGCAGCAGTTGTGTTC

TTGTTCACCATAGCCGACTGGCTTGAAACAAGAGCTAGCTACAGGGCGACAGCAGTAATGCAGTCTCTGATGAGC

TTAGCTCCACAGAAGGCAATAATAGCAGAGACTGGTGAAGAAGTTGAAGTAGATGAGGTTAAGGTTAGCACAGTT

GTAGCGGTTAAAGCTGGTGAAACCATTCCAATTGATGGAATTGTGGTGGATGGTAACTGTGAAGTAGACGAGAAA

ACCTTAACGGGCGAAGCATTTCCTGTGCCGAAACAGAAAGATTCTTCGGTTTGGGCTGGAACCATCAATCTAAAT

GGTTACATAAGTGTGAAAACAACTTCTTTAGCGGGTGATTGCGTGGTTGCGAAGATGGCTAAGCTAGTAGAAGAA

GCTCAGAGCAGTAAAACCAAATCCCAAAGACTAATAGACAAATGTTCTCAGTACTATACTCCAGCGATCATCGTA

GTATCAGCTTGCGTCGCCATTGTCCCGGTTATTATGAAGGTCCACAACCTTAAACATTGGTTCCACCTAGCATTA

GTTGTGTTAGTCAGTGGCTGTCCCTGTGGTCTTATCCTCTCTACACCAGTTGCTACTTTCTGTGCACTTACTAAA

GCGGCTACTTCAGGGCTTCTGATCAAAAGTGCTGATTATCTTGACACTCTCTCAAAGATCAAAATCGCTGCTTTC

GACAAAACCGGGACTATTACCAGAGGAGAGTTCATTGTCATAGATTTCAAGTCACTCTCTAGAGATATAAGCCTA

CGTAGCTTGCTTTACTGGGTATCAAGTGTTGAAAGCAAATCAAGTCATCCAATGGCTGCAACAATCGTGGACTAC

GCGAAATCCGTTTCTGTTGAGCCTAGGCCTGAAGAGGTAGAGGACTACCAGAATTTTCCAGGTGAAGGAATCTAC

GGGAAGATTGATGGGAACGATATCTACATCGGGAACAAAAGGATTGCTTCTCGAGCTGGTTGTTCAACAGTTCCA

GAGACTGAAATTGATACCAAAGGTGGGAAGACTGTTGGATACGTCTATGTAGGTGAAAGACTAGCTGGAGTTTTC

AATCTTTCTGATGCTTGTAGATCAGGTGTATCTCAAGCAATGAAAGAACTAAAATCTCTAGGAATCAAAACCGCA

ATGCTAACGGGAGATAGTCAAGCTGCGGCAATGCATGCTCAAGAACAGCTAGGGAATGCTTTGGATGTTGTGCAT

GGAGAACTTCTTCCAGAAGATAAATCTAAAATCATACAAGAGTTCAAGAAAGAAGGACCAACCGCAATGGTAGGG

GACGGTGTGAATGATGCACCAGCTTTAGCTACAGCTGATATTGGTATCTCCATGGGGATTTCTGGCTCTGCTCTT

GCAACACAGACTGGTCATATTATTCTGATGTCTAATGACATAAGAAGGATACCACAAGCGGTGAAGCTAGCGAGA

AGAGCTCGGCGCAAAGTTATTGAAAACGTGTGTCTTTCCATCATTTTAAAAGCAGGAATACTGGCTTTGGCATTT

GCTGGTCATCCTTTGATTTGGGCAGCGGTTCTTGTTGACGTAGGAACTTGTTTGCTTGTGATTCTCAATAGTATG

TTGCTGCTGCGAGAGAAGAAAAAGATTGGGAACAAAAAGTGTTACAGGGCTTCTACATCTATGTTGAATGGTAGG

AAACTCGAAGGCGATGATGATGATGCTGTGGACTTAGAAGCAGGCTTGTTAACAAAAAGCGGGAATGGTCAATGT

AAATCAAGCTGTTGTGGAGATAAGAAAAATCAAGAGAAGGTTGTGATGATGAAACCAAGTAGTAAAACCAGTTCT

GATCATTCTCACCCTGGTTGTTGTGGCGATAAGAAGCAAGGCAATGTGAAGCCGCTTGTGAGAGATGGCGGTTGC

AGTGAGGAAACTAGGAAAGCAGTGGGAGACATGGTTTCATTGAGCTCATGTAAGAAGTCTAGTCATGTCAAACAT

GACCTGAAAATGAAAGGTGGTTCAGGTTGTTGTGCTAACAAAAGTGAGAAGGTAGAGGGAGTAGTGGCAAAGAGC

TGTTGTGAGAAACCAAAACAGCAAATGGAGAGTGCTGGAGACTGCAAATCTAGCCATTGCGAGGAGAAGAAGCAT

GCTGAGGAAATTGTTCTCCCGGTGCAGATGATTGGTCAGGCATTAACTGGTTTGGAAATAGAGTTGCAGACAAAG

GAAACTTGCAAAACAAGATGTTGTGACAATAAAGAGAAGGCTAAGAAAAAAGGTTTGTTGCTTTCTAGTGAGGAC

ACATCTTACCTGGAGAAGGGAGTGCTGATTAAAGATGAAGGAAACTGCAAGTCTGCCTGCCAGAAAACGGGGACA

GTGAAACAAAGCTGCCATGAGAAGGCACCTCTTGATATAGAAACCAAGTTGGTTAGTTGTGGAAACACAGAGGGG

GAAGTGGGAGAACAAACTGATCTGGAGATAAAGATTGAAGGAGACTGCAAGTCTGGTTGCTGCAGCGATGAAAAA

CAAACTGGGGAAATAACTCTGGCTTCTGAGGAAGAGGCAGACAGCACGGATTGTTCCTCGGGATGTTGTATGGAC

AAAGAAGAAGTGACACAAATCTGCGGCTTGGAAACTGAAGGTGGTGGTGATTGCAAATCACATTGTTGTGGAACT

GGGTTGACACAAGAAGGGTCTTCGAAGTTGGGCAATGTGGAGACTGCTCAATCCGGAGGCTGTGGAACAGTGAAA

GTCTCTAGTCAAAGCTGTTGCACTAGTTCTACTGATCTGGTGCTATCTGACTTGCAAGTGACGAAGGATGAGCAT

TGTAAGAGCTCACACGGAGCCGTCAAGGTAGAGACCTGTTGCAAAGTGAAGATTCCAGAGGCTTGTGCACCGGAA

TGTAAGGAAAAAGAGAAGCGTCACAGTGGTAAAAGCTGTTGCAGGAGTTATGCAAAAGAGTTTTGCAGCCACCGC

CACCACCACCACCACCACCACCATCACCATGTGAGTGCTTGA

ATG: Translational start codon, TGA; Translational stop codon, bold: AhHMA4-RNAi fragment.

181

Appendix

B.4

AhHMA4-RNAi fragment used in intron-spliced hairpin construct (nt 2540-2998)

GGCAAAGAGCTGTTGTGAGAAACCAAAACAGCAAATGGAGAGTGCTGGAGACTGCAAATCTAGCCATTGCGAGGA

GAAGAAGCATGCTGAGGAAATTGTTCTCCCGGTGCAGATGATTGGTCAGGCATTAACTGGTTTGGAAATAGAGTT

GCAGACAAAGGAAACTTGCAAAACAAGATGTTGTGACAATAAAGAGAAGGCTAAGAAAAAAGGTTTGTTGCTTTC

TAGTGAGGACACATCTTACCTGGAGAAGGGAGTGCTGATTAAAGATGAAGGAAACTGCAAGTCTGCCTGCCAGAA

AACGGGGACAGTGAAACAAAGCTGCCATGAGAAGGCACCTCTTGATATAGAAACCAAGTTGGTTAGTTGTGGAAA

CACAGAGGGGGAAGTGGGAGAACAAACTGATCTGGAGATAAAGATTGAAGGAGACTGCAAGTCTGGTTGCTGCAG

CGATGAA

Schematic representation of the T-DNA in pJAWOHL8-AhHMA4-RNAi construct under the control of

35S promoter, ensuring its overexpression. The integrated intron for the spliced hairpin formation

between sense and anti-sense 441 nt long FRD3 fragments. (Figure based on information provided

by a former member of the laboratory, Dr. Ina Talke, who generated the RNAi constructs and

transgenic lines).

B.5

AhFRD3 open reading frame (ORF) (1,593 nt)

ATGACGGAAACTGGTGATGATCTTGCTACGGTTCCAACCAGCGTGAGCAAGTCAATCCCATTTCTTGTTATCTTC

AAAGATTTAAGACATGTATTCAGTAGGGATACAATTGGGCGAGAGATTCTAGGCATGGCGTTTCCAACAGCTTTG

GCTTTAGCTGCTGATCCAATCGCTTCTCTGATTGATACCGCTTTTGTCGGGCGTTTAGGAGCGGCTCAGCTAGCG

GCGGTTGGAGTCTCCATTGCCATATTCAATCAAGCTTCTAGAATTACCATGTTCCCACTTGTGAGCCTCACGACT

TCGTTTGTGGCAGAGGAAGACACGATGGAGAAGATGAAAGAAGAAGCGAACAAAGCCAGTCTTGTTCATGCAGAA

ACTATACTTGTTCAAGATTCATTGGAAAAGGGCATTTCTTCACCTACAAGTAACAATACCAACCAGCCACAGCAA

CCCCCAGCTTTGGATACAAAGTCAAATAGTGGAAACAAAGCGACTAAAAAGGGGAAGAGGACCATTAGAACAGCA

TCAACAGCTATGATATTGGGGTTAATCCTCGGTCTTGTGCAAGCTATTTTCTTGATTTTCAGCTCGAAGTTGCTT

CTAGGCTTCATGGGAGTGAAACCAAATTCGCCAATGTTATCACCAGCAAACAAGTACTTGAGTATACGAGCTTTG

GGGGCACCTGCATTGCTTCTATCTCTAGCTATGCAAGGCGTCTTTCGTGGCTTCAAGGATACCAAAACTCCTCTC

TTTGCCACTGTCGTAGCAGATGTTATCAACATCGCTCTCGACCCCATCTTCATTTTTGTGCTTCGTCTCGGGATC

AGCGGTGCAGCCATTGCCCATGTCATTTCTCAGTACTTCATGACTCTAATATTGTTCGTCTGCCTCGCAAAGAAA

GTTAATTTGATTCCACCAAACTTCGGGGATTTGCAGTTCGGAAGGTTCCTTAAAAATGGGATACTATTGCTGGCG

AGGACTATAGCAGTGACGTTTTGTCAGACCTTAGCAGCAGCAATGGCGGCTCGGCTGGGTACAACACCAATGGCT

GCTTTTCAGATTTGTTTACAAGTCTGGTTAACATCTTCTCTTCTCAATGATGGTCTTGCCGTTGCTGGTCAGGCG

ATCCTGGCTTGTTCGTTTGCTGAGAAGGACTATAACAAAGTGACTGCTGCTGCATCCCGTGTTCTACAGATGGGT

TTTGTGTTAGGACTTGGACTGTCCGTTTTTGTTGGACTAGGTCTCTACTTTGGTTCCGGAATATTCTCCAAGGAC

CCTGCTGTTATTCACCTCATGACCATTGGAATACCGTTTATAGCAGCCACGCAGCCAATAAACTCACTCGCCTTT

GTATTGGATGGAGTCAATTTTGGAGCATCTGATTTTGCTTACACTGCATACTCCATGGTGGGAGTGGCGGCCATA

AGCATTGGAGCAGTAATATATATGGCAAAGACCAATGGTTTCATAGGAATATGGATAGCTCTTACAATCTATATG

GGTCTCCGTGCTATTACTGGAATTGCCAGGATGGCAACAGGAACTGGACCGTGGAGGTTCTTGCGTGGACGATCA

TCCTCTTCATCTTCCTAG

ATG: Translational start codon, TGA; Translational stop codon, bold: AhFRD3-RNAi fragment.

P35S HMA4 antisense HMA4 sense T35S Intron

pJaw intr-F

HMA4-RNAi-R

182

Appendix

B.6

AhFRD3-RNAi fragment used in intron-spliced hairpin construct (nt 8-449)

AAACTGGTGATGATCTTGCTACGGTTCCAACCAGCGTGAGCAAGTCAATCCCATTTCTTGTTATCTTCAAAGATT

TAAGACATGTATTCAGTAGGGATACAATTGGGCGAGAGATTCTAGGCATGGCGTTTCCAACAGCTTTGGCTTTAG

CTGCTGATCCAATCGCTTCTCTGATTGATACCGCTTTTGTCGGGCGTTTAGGAGCGGCTCAGCTAGCGGCGGTTG

GAGTCTCCATTGCCATATTCAATCAAGCTTCTAGAATTACCATGTTCCCACTTGTGAGCCTCACGACTTCGTTTG

TGGCAGAGGAAGACACGATGGAGAAGATGAAAGAAGAAGCGAACAAAGCCAGTCTTGTTCATGCAGAAACTATAC

TTGTTCAAGATTCATTGGAAAAGGGCATTTCTTCACCTACAAGTAACAATACCAACCAGCCACAGCA

Schematic representation of the T-DNA of binary pJAWOHL8-AhFRD3-RNAi plasmid. The AhFRD3-

RNAi construct under the control of 35S promoter, ensuring its overexpression. The integrated intron

for the spliced hairpin formation between sense and anti-sense 441-nt-long FRD3 fragments. (From

Norman Ertych Diploma thesis, University of Potsdam, 2007). LB: left border, RB: right border, Pnos:

nopaline synthase promoter, t35s: 35S terminator, p35s: 35S promoter, pat: Phosphinothricin-N-

Acetyltransferase.

183

Appendix

B.7

AhFRD3 genomic fragment (4881 bp)

GAGTATTATCTTGTCACCATGTTTTATTCGTGTTTTTTAGCACATACACTTAGTTCTAATAATTGTGTCTTTTAC

AAACAATTTATCTATTTAAACTTTCATCTCTTTGTAGCTCTATATATGTATATATATTATGTTTTTAAAAGTGGT

TTAAATTTATTATTTCTTTTTGTTTGATATTTTTCATAGAAAGTTACATTTTTTGCTATTTAGCATTCATATATA

TATATACTTTGTTATCTATATCATTATTATTTTTTTCTAAATAAATATCTATTTTGGTTATTTATTTAATTTTTT

TGAAGATTGTCTCTTTTTAACATAATACAATTTAAAATATTACGTCTTTTTATCGTAATATTTTGATGAATATAT

TTTTATAGCTAGTTATATTTATAATAGTTTAGAAAATTGAAAAATTGCATCTACTCATTATAACTTTTTGTGTAA

TATTTTTTATTTATGGTCGTATTGTTTCACCATAATATTTTCTAATTATAATAATACAAATCTTAAAAAGTATTT

GTGAGAGTTTACGTTTCTTTATCATATTTTTTGTAAAATATATCTTTATTTATTGTTAAAAAAAATTGTTTTGAA

ACTTGTTGTCTCAATTCATTATGACATTTCGTTTTTCTTCAAAATAGCCTAAAATCATTTCCCCCGCGACATCGC

GGGGGGTCTAAGTCCTAGTAATAATAATAATAATAATCTTAATTATAAAGAAATAATATGGATAGATAAAATTAA

ACAATTAATAGTGTCATACAAAAAATTCTAATTAAATGTTAAAAAGAAAATAGCATTAATTTTTTACATGCATAG

CTTCAGAAACAAAAAATATCAAATGTCAAATACATACCGGACTAACCCCTAGTTTACTTAATAGAAATATATTAC

GATGTTTATGCGTACCTATTTTCCTTCAATTAGATATTGGTGTCTTAAGTTTGGACGGAAATAAAGAGCTAGAGC

CGGACCAACAAAATTGGGGGCCCCAAACAATTTAAAAAAAAATAATATCAATATTTTCATAAAATAAAAAAAAAA

ACTAGAATAAAATAATTTGTTAAAGCAAATTACTCTTGATTGTTTTAGAATTTCTTTAAATAAAATATTTTCTCT

TATTAGATGGAAAATCTTGTGGTTGTAGAGAAAAAATAACTTACTATTTTTTTTTTACCATTCAATTATATATAA

TAATTATATATTTTTTAGGTACACACAATATTTTAAAATCTATATATAATAATTGATATAAATATATATATAAAA

AAAAATTTTGTGGGGTCCCTCTAAAATGGGCCCATTGCAATGTCCTCCGGTCCGGCTCTGTAAGAGCATCTCCAT

CAGATAGAAACCCTCAAAGTTTCTCAAAAAAAAAAAAATTATTATTTTAAGATTGTAATTTTTTTTTCTTTTTTT

TTTATTAATTGGACCATTGGAACTATGACATGTGGCATGACATCAGAGAAACAGTTTCTCAAAATGTCTGTGCAG

AGAAACAGTTTCTCAAAATGTCTCTTTTCTCTCTTCTTTTTATAATTTTTTATTAATAAATGTCTCTTCAAGACA

TCCTTGATGGAGATGCTCTAAAGAGCACCAAAAAAAAGTTAGGGAAGGAAACCTTTGTTTTCTTTAATAAATATA

GAACAAAATATCTTTTGTTTTATTTTTATTTTATTAAATAAGCAAAGATATGCATGCTCATTACGTGTCTATAAA

TATACAAATACATTTGTACACATAAAATGTACTATAAACGTTCCTTTTGCTTCCCCGATTCTTCGAAACACTTAT

TGATATCTTCAGATCCACAACAAATTAATTACAGAGACAGTTACGGAGGAAAAGATTTATGACGGAAACTGGTGA

TGATCTTGCTACGGTTCCAACCAGCGTGAGCAAGTCAATCCCATTTCTTGTTATCTTCAAAGATTTAAGGTGTGT

GTGTGTGTGTATGTATTAAAGAAATGGTGATGGATACTTTAAAAGAAGTGATGCATAACGTTAATTTATTTATGT

AAAATTGCAGACATGTATTCAGTAGGGATACAATTGGGCGAGAGATTCTAGGCATGGCGTTTCCAACAGCTTTGG

CTTTAGCTGCTGATCCAATCGCTTCTCTGATTGATACCGCTTTTGTCGGGCGTTTAGGAGCGGCTCAGCTAGCGG

CGGTTGGAGTCTCCATTGCCATATTCAATCAAGCTTCTAGAATTACCATGTTCCCACTTGTGAGCCTCACGACTT

CGTTTGTGGCAGAGGAAGACACGATGGAGAAGATGAAAGAAGAAGCGAACAAAGCCAGTCTTGTTCATGCAGAAA

CTATACTTGTTCAAGATTCATTGGAAAAGGGCATTTCTTCACCTACAAGTAACAATACCAACCAGCCACAGCAAC

CCCCAGGTAAACTCCGCAAATCTCACTCGACATTGATCACAACTTCTATAAAAGTTTTTTTACTGTTGGTTTATT

TCCTTCACTCTTTTTTTCTTTCCAATTTGTTGTGTTTTGGTTGTGTGAAACTAGCTTTGGATACAAAGTCAAATA

GTGGAAACAAAGCGACTAAAAAGGGGAAGAGGACCATTAGAACAGCATCAACAGCTTTGATATTGGGGTTAATCC

TCGGTCTTATGCAAGCTATTTTCTTGATTTTCAGCTCGAAGTTGCTTCTAGGCTTCATGGGAGCGAAACCAGTAA

GTTTTCATAGACATGCACATATTTTTTTATAGGACAAAATGTTTTTGACTAATTTGAGTTTACTTTGGATAACAG

AATTCGCCAATGTTATCACCAGCAAACAAGTACTTGAGTATACGAGCTTTGGGGGCTCCTGCATTGCTTCTATCT

CTAGCTATGCAAGGCGTCTTTCGTGGCTTCAAGGATACCAAAACTCCTCTCTTTGCCACTGGTAATTAAGTTATA

AATTAGATCATATCTTTAATGATCACTCTTCTTAATTTTTATGATATGATTACTCACCCTAGCTAATATAATATT

TTGCCTTAATGCATGAAACAGTCGTAGCAGATGTTATCAACATCGCTCTCGACCCCATCTTCATTTTTGTGCTTC

GTCTCGGGATCAGCGGTGCAGCCATTGCCCATGTCATTTCTCAGTAAGAGAAATCACTTAACTTTTTCACACATG

CAAAAGTGATCATTATTGAATAGTAATCGCTAGGCGCATTCTTGTTTTTAGTACAGCTATAAATAGACTTGTGAA

ATCATAACCGTACAAACTAAAACTAATGATTTGTTTGTGTATACGTGAAGGTACTTCATGACTCTAATATTGTTC

GTCTGCCTCGCAAAGAAAGTTAATTTGATTCCACCAAACTTCGGTGATTTGCAGTTCGGAAGATTCCTTAAAAAT

GGTACGTTGGATGCATATTCATTAAAAGTTGTGGGATCTTGCAATAATCAAAAATACAAGATCCGTCGTACGTGC

TAATATGCACAGACTCCAAAAAATATATTAACTTGGTTCAAATCAAAAAGTTGTCTATATAATAGTAGAGTAGAG

TTTAACCAAAATAAGGTCTGTATTTAAAATGTAAGAATATATTTAAGTATAGTTGAGAAAATGGGAAGTGTGGAT

GTCTAACAAGTACTACTAAAAATGAAAGGGATACTATTGCTGGCGAGGACTATAGCAGTGACGTTTTGTCAGACC

TTAGCAGCAGCAATGGCGGCTCGGCTGGGTACAACACCAATGGCTGCTTTTCAGATTTGTTTACAAGTCTGGTTA

ACATCTTCTCTTCTCAATGATGGTCTTGCCGTTGCTGGTCAGGTAATCATGTTTTCTCATTTGTATAGTTATATG

GTTGATCAAGTTTTATATGGAAAATGATCATTCAATACGTTGCAGGCGATCCTGGCTTGTTCGTTTGCTGAGAAG

GACTATAACAAAGTGACTGCTGTTGCATCCCGTGTTCTACAGGTTCGGTCCAAAAATCATATTACCAAACCTTTC

TTTAAAAATTAAAATAACTTTTGTAACTAAAACAAAAAACGAATTTGATATGCAGATGGGTTTTGTGTTAGGACT

TGGACTGTCCGTTTTTGTTGGACTAGGTCTCTACCTTGGCTCCGGAATATTCTCCAAGGACCCTGCTGTTATTCA

CCTCATGACCATTGGAATACCGGTATTAATAATCAATAATAAATACTATAGTATAAAAAAACATTGAAAAGGATT

TTACTAATGAGAAGAGGTTATATATATTTATTTATGCAGTTTATAGCAGCCACGCAGCCAATAAACTCACTCGCC

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Appendix

TTTGTATTGGATGGAGTCAATTTTGGAGCATCTGATTTTGCTTACACTGCATACTCCATGGTACGCACACCATAT

ATGCTATGAAATGACTAATTTTTATTTTTTTGAAATGACTTAAAACTCTACTTTTTTTTTTGTTCTTGTAATCCA

ATTATGATAAATCAGGTGGGAGTGGCGGCCATAAGCATTGGAGCAGAAATATATATGGCAAAGACCAATGGTTTC

ATAGGAATATGGATAGCTCTTACAATCTATATGGGTCTCCGTGCTATTACTGGAATTGCCAGGTATTTAAATTGG

GTCATTAATGGGCCTTTACAATAGCCCATTATATAGTAGAAGCAGTCGTTGACTCTGGTGTTTGAATTTATGCAG

GATGGCAACAGGAACTGGACCGTGGAGGTTCTTGCGTGGACGATCATCCTCTTCATCTTCCTAGGACTTAGTTTA

TTTATATCGAGTTGCATCTCCTTCTTCCTTCTTCGTTTTTGTTTCTGGTTCTTGTGGTTCTTTTTTTTTTTACAT

TTTGTTTGAGAGAGTTATCTTTTAACAGTTTTACATAAATAATTGGAGCAGAAGTTTATCTAGAATGCATATTAA

GTTATC

ATG: Translational start codon, TGA; Translational stop codon, bold: AhFRD3 ORF.

B.8

AhFRD3 cDNA fragment (1867 bp)

TACTATAAACGTTCCTTTTGCTTCCCCGATTCTTCGAAACACTTATTGATATCTTCAGATCCACAACAAATTAAT

TACAGAGACAGTTACGAAGGAAAAGATTTATGACGGAAACTGGTGATGATCTTGCTACGGTTCCAACCAGCGTGA

GCAAGTCAATCCCATTTCTTGTTATCTTCAAAGATTTAAGACATGTATTCAGTAGGGATACAATTGGGCGAGAGA

TTCTAGGCATGGCGTTTCCAACAGCTTTGGCTTTAGCTGCTGATCCAATCGCTTCTCTGATTGATACCGCTTTTG

TCGGGCGTTTAGGAGCGGCTCAGCTAGCGGCGGTTGGAGTCTCCATTGCCATATTCAATCAAGCTTCTAGAATTA

CCATGTTCCCACTTGTGAGCCTCACGACTTCGTTTGTGGCAGAGGAAGACACGATGGAGAAGATGAAAGAAGAAG

CGAACAAAGCCAGTCTTGTTCATGCAGAAACTATACTTGTTCAAGATTCATTGGAAAAGGGCATTTCTTCACCTA

CAAGTAACAATACCAACCAGCCACAGCAACCCCCAGCTTTGGATACAAAGTCAAATAGTGGAAACAAAGCGACTA

AAAAGGGGAAGAGGACCATTAGAACAGCATCAACAGCTATGATATTGGGGTTAATCCTCGGTCTTGTGCAAGCTA

TTTTCTTGATTTTCAGCTCGAAGTTGCTTCTAGGCTTCATGGGAGTGAAACCAAATTCGCCAATGTTATCACCAG

CAAACAAGTACTTGAGTATACGAGCTTTGGGGGCACCTGCATTGCTTCTATCTCTAGCTATGCAAGGCGTCTTTC

GTGGCTTCAAGGATACCAAAACTCCTCTCTTTGCCACTGTCGTAGCAGATGTTATCAACATCGCTCTCGACCCCA

TCTTCATTTTTGTGCTTCGTCTCGGGATCAGCGGTGCAGCCATTGCCCATGTCATTTCTCAGTACTTCATGACTC

TAATATTGTTCGTCTGCCTCGCAAAGAAAGTTAATTTGATTCCACCAAACTTCGGGGATTTGCAGTTCGGAAGGT

TCCTTAAAAATGGGATACTATTGCTGGCGAGGACTATAGCAGTGACGTTTTGTCAGACCTTAGCAGCAGCAATGG

CGGCTCGGCTGGGTACAACACCAATGGCTGCTTTTCAGATTTGTTTACAAGTCTGGTTAACATCTTCTCTTCTCA

ATGATGGTCTTGCCGTTGCTGGTCAGGCGATCCTGGCTTGTTCGTTTGCTGAGAAGGACTATAACAAAGTGACTG

CTGCTGCATCCCGTGTTCTACAGATGGGTTTTGTGTTAGGACTTGGACTGTCCGTTTTTGTTGGACTAGGTCTCT

ACTTTGGTTCCGGAATATTCTCCAAGGACCCTGCTGTTATTCACCTCATGACCATTGGAATACCGTTTATAGCAG

CCACGCAGCCAATAAACTCACTCGCCTTTGTATTGGATGGAGTCAATTTTGGAGCATCTGATTTTGCTTACACTG

CATACTCCATGGTGGGAGTGGCGGCCATAAGCATTGGAGCAGTAATATATATGGCAAAGACCAATGGTTTCATAG

GAATATGGATAGCTCTTACAATCTATATGGGTCTCCGTGCTATTACTGGAATTGCCAGGATGGCAACAGGAACTG

GACCGTGGAGGTTCTTGCGTGGACGATCATCCTCTTCATCTTCCTAGGACTTAGTTTATTTATATCGAGTTGCAT

CTCCTTCTTCCTTCTTCGTTTTTGTTTCTGGTTCAGGTGGTTCTTTTTTTTTTTACATTTTGTTTGAGAGACCGT

TATCTTTTAATCAGTTTTACATAAATAATTGGAGCAGAAGTTTATCTAGAATGCATATTAAGTTATC

ATG: Translational start codon, TGA; Translational stop codon, bold: AhFRD3 ORF.

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Appendix

C. Vector maps

C1

Schematic representation of vectors used for transformation of A. thaliana plants with (a) 35S:AhFRD3, (b) 35S:AhFRD3:HA, (c) genomic AhFRD3, and A. halleri transformant control line TrC with (d) 35S-GUS. LB: left border, RB: right border, Sm/SpR: Spectinomycin/streptinomycin, TS35: 35S terminator, attR: recombination sites, CmR: chloramphenicol-resistance marker, ccdB: negative selection marker, T-DNA: transfer DNA, nos-bar-nos: plant selection marker Bar (herbicide glufosinate), pSA ori: replication locus, npt: Neomycin Phosphotransferase, ColE1: ColE1 replicon, pVS1: pVS1 plamid, pBR322: pBR322 plasmid, PIV2: portable intron, int: intron. p35S Gus Int vector is described in Vancanneyt et al. 1990.

(d) (c)

pMDC100

10,527 bp

pGreen35S

5,058 bp

(b)

pB7WG2

10,898 bp

(a)

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Appendix

C2

Schematic representation of vectors used for transformation of A. halleri plants with (a) AhHMA3-

RNAi construct and (b) AhHMA4-RNAi and AhFRD3-RNAi constructs. LB: left border, RB: right

border, Sm/SpR: Spectinomycin/streptinomycin, TS35: 35S terminator, attR: recombination sites,

CmR: chloramphenicol-resistance marker, ccdB: negative selection marker, Kan: Kanamycin

resistance gene.

(a) (b)

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Appendix

D. Curriculum vitae

Personal Information

Name: José Romário Fernandes de Melo

Email: [email protected]

Date of birth: 24.10.1985

Place of birth: Vitória da Conquista, Bahia, Brazil

Nationality: Brazilian

Languages: Portuguese (native), English, German, Spanish

Scientific Education

2004-2008. Bachelor in Biology. Southwest Bahia State University, Vitória da Conquista, Bahia, Brazil.

2008-2010. Masters in Plant Biotechnology. Federal University of Lavras, Minas Gerais, Brazil.

Since03/2011. PhD in the Department of Plant Physiology. Ruhr-University Bochum, Bochum, North Rhine-Westphalia, Germany. Supervisor: Prof. Dr. Ute Krämer.

Research Articles (from the PhD work)

Melo JRF, Larue C, Piotrowski M, Talke I, Hanikenne M, Krämer U. The FRD3 gene plays a key role in Pb accumulation in A. halleri. In preparation. Melo JRF, Stein JR, Talke I, Krämer U. The role of HMA3, HMA4, and FRD3 in Metal hyperaccumulation and Hypertolerance in A. halleri. In preparation. Ricardo J. Stein, Stephan Hoereth, J. Romário F. Melo, Mario L. Garbin, Stephan Clemens, Ute Krämer. Environmental-geographic profiles of intra-species ionomic variation in the metal hyperaccumulator Arabidopsis halleri. PNAS. (submitted).

Additional Research Articles (during the PhD work)

Melo, JRF, Figueira, AR, Moreira CN, Oliveira AC (2015) Characterization of Cowpea aphid-borne mosaic virus (CABMV) in Bahia State, Brazil, suggests potential regional isolation. Afr. J. Biotechnol. 14(9):735-744. Doi: 10.5897/AJB2015.1440. Cerqueira-Silva CBM, Melo JRF, Corrêa RX, Oliveira AC (2012) Selection of pathometric variables to assess resistance and infectivity in the passion fruit woodiness pathosystem. Europ J. Plant Pathol. 134(3):489-495. Doi: 10.1007/s10658-012-0030-5.

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Appendix

Conference contributions

Poster: Mechanisms of metal hyperaccumulation and hypertolerance in Arabidopsis

halleri. SPP kick-off meeting. Königswinter, March 2012.

Poster: The role of HMA4 encoding a P1B-ATPase metal cation pump in maintaining metal homeostasis in the Zn/Cd hyperaccumulator species Arabidopsis halleri. Plant Genome Evolution Conference. Amsterdam, September 2013.

Training

RNAseq Workshop Düsseldorf. Heinrich-Heine University Düsseldorf. May 2012.

Particle-Induced X-ray Emission (µPIXE). Nuclear Microprobe at the Atomic Energy Commission in Saclay (Paris-Saclay, France). October 2014.

Immunolocalization of proteins in plants. Institute of Science and Technology Austria, Klosterneuburg, Austria. Oct 2013 and May 2014.

Awards

Research Stay Grant. Cellular and subcellular localization of proteins (HMA3 and HMA4) to determine their roles in heavy metal hyperaccumulation and hypertolerance of Arabidopsis halleri. Research School, Ruhr University Bochum, 2013-2014.

Travel Grant. Plant Genome Evolution Conference. Amsterdam, September 2013. Research School, Ruhr University Bochum, September 2013.

Invited Talks

How the highly expressed metal-related genes of A. halleri contribute to its metal hyperaccumulation and hypertolerance traits. Lessons from the Field Workshop. Bochum, June 2013.

Mechanisms of metal hyperaccumulation and hypertolerance in Arabidopsis halleri. Universitè Libre de Bruxelles. February 2015.

Student supervision

Bachelor Thesis. Jana Glowka. The involvement of candidate genes in heavy metal tolerance in Arabidopsis (2013). Department of Plant Physiology, Ruhr University of Bochum, Germany.

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Appendix

10 Erklärung

Hiermit erkläre ich, dass ich die Arbeit selbstständig verfasst und bei keiner anderen

Fakultät eingereicht und dass ich keine anderen als die angegebenen Hilfsmittel

verwendet habe. Es handelt sich bei der heute von mir eingereichten Dissertation

um sechs in Wort und Bild völlig übereinstimmende Exemplare.

Weiterhin erkläre ich, dass digitale Abbildungen nur die originalen Daten enthalten

und in keinem Fall inhaltsverändernde Bildbearbeitung vorgenommen wurde.

Bochum, den 11.09.2015

_________________________________

(Unterschrift)

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