Manipulation of the orchard soil microbiome: Implications for soil-borne disease suppression and apple production

Mark Mazzola, Tracey Somera, Christopher Van Horn, Rachel Leisso, Shiri Freilich

Goal: Recruit a soil/rhizosphere microbiome that supports tree establishment and is resistant to pathogen invasion

Employ orchard management practices to facilitate design of a disease suppressive soil microbiome

Rootstock genotype recruitment of an “effective” microbiome

Integration of these two factors to optimize soil-borne disease control

Intervention

Microbiome

Microbiome

Replant Disease

Replant soil Non-replant soil

System of study: Replant Disease of Apple Fumigation

Control

Control Treated

Ilyonectria(robusta, olidium)

Phytophthora(cactorum, syringae, cambivora, megasperma)

Pythium(at least 17 species)

Rhizoctonia (solani AG 5, 6 binuc. AG’s G, I, Q)

Pratylenchus penetrans (lesion nematode)

Mazzola, 1997; 1998; Mazzola et al., 2002Paulitz et al., 2003, Allain-Boulé et al., 2004

Causal Pathogen Complex:

Replant

Two prominent lines of commercialapple rootstocks used in PNW:

Malling (M) or Malling:Merton (MM)-E. Malling, U.K.Replant disease susceptibleSupport high populations of Pratylenchus penetrans

Geneva (G) USDA-ARS/Cornell Univ., Geneva, NYReplant disease-susceptible to highly tolerantGenerally support lower populations of P. penetrans

Does rootstock genotype influence composition of the microbiome recruited to the rhizosphere?

Gala/M.9

Gala/G.11

ANOSIM P = 0.0001 (OTU data)

Rhizosphere bacteria: Two years post-planting

Plant-driven selection: Rootstock genotypes host distinct rhizosphere microbial consortia

Mazzola et al. 2015; Wang & Mazzola 2019

M.26

G.210

Rhizosphere bacteria: 7 days post-planting

ANOSIM P = 0.0026 (OTU data)

G.210

M.26

G.890

G.41

G.935M.9

M.26

Composition of endophytic microbiome differs significantly among rootstock genotypes. NMDS of OTU data.

Plant-driven selection: Rootstock genotypes support different endophytic microbial consortia

Van Horn and Mazzola, unpublished

Plant-driven selection: Rootstock genotypes attract different functional microbial consortia

Gardnerspantry.ca

Mycorrhizal fungi

Rootstock trial Wapato, WA

Honeycrisp on M.9, G.41 or G.935

1. Soils collected from rhizosphere of 12-year-old orchard planting.

3. Relative plant growth as influenced by previous rootstock was assessed

4. Examined bacterial/fungal community fromGala seedling rhizosphere

Does rhizosphere microbiome designed by previous rootstock influence health and performance of ‘replant’ orchards?

Photo: Gennaro Fazio

2. Bioassay conducted using these soils with Gala seedlings as the ‘reporter’

Soil source Rhizosphere soil source

Previous rootstock-specific rhizosphere microbiomesinfluence subsequent plant health and performance

Mazzola and Hewavitharana, 2019.

G.935

G.41

M.9

Similarity of the Gala seedling rhizosphere bacterial community

Previous rootstock influences subsequent rhizosphere microbiome, plant health and growth performance

NMDS of T-RFLP derived data

Mazzola and Hewavitharana, 2019.

Lesion nematode root densities from Gala seedlings as affected by previous rootstock genotype:

Mazzola and Hewavitharana, 2019.

What host attributes drive microbiome composition?

Primary root exudate metabolites

= G.935 = M.26

Phenolic compounds differing significantly between root exudates of G.935 and M.26 rootstocks.

Leisso, Rudell and Mazzola, 2017; 2018.

Defining root exudates that influence the soil microbiome

Rootstock genotype differences were detected among 85 targeted (identified) compounds

Root exudates of G.935 and M.26 exhibited more differences in compounds that serve as microbial substrate (sugars, etc.) than those with potential to inhibit pathogens (phenolics, triterpenoids)

Sorbitol (higher in G.935), malic acid, several triterpenoids, and phloridzin (higher in M.26) were among the most abundant metabolites detected in apple root exudates.

Leisso, Rudell and Mazzola, 2018.

Influence of differentially abundant metabolites on the soil microbiome:

Sorbitol

Control

Phloridzin

Bacterial density

Fungal density

Sorbitol/Phloridzin

ANOSIM

Control vs. Phl P = 0.1258Control vs. Sor P = 0.0032Sorbitol vs. Phl P = 0.0049

Effect of certain differentially abundant metabolites on in vitro growth of potential root pathogens

benzoic acid

G41 G935 M26 M9Nic29

ng p

er

g d

ry w

eig

ht

roots

0

5000

10000

15000

20000

25000

30000

aa

b b

4-hydroxybenzoic acid

G41 G935 M26 M9Nic29

ng p

er g d

ry w

eig

ht ro

ots

0

10

20

30

a

abab

b

Phloridzin demonstrated limited to no inhibitory activity (in vitro) toward the target pathogens.

aa a

b

a a

b

c

a

ab

bc

c

Phloridzin

Apple rootstocks do recruit or sustain rhizosphere and endophytic microbial communities that differ in a genotype-dependent fashion

These rootstock-specific outcomes may be shaped by differentially abundant rhizosphere metabolites that selectively alter microbiome composition and/or inhibit activity of potential soil-borne pathogens

Rootstock genotype: Summary

The rootstock genotype-dependent microbiome reared in a previous orchard may influence pathogen dynamics and plant growth in a subsequent orchard planting

Soil amendment driven selection

Brassicaceae seed meal (SM) amendment

Orchard management practices employed to facilitate design of a disease suppressive soil microbiome

Myrosinase

• Relative contribution of soil microbiome to seed meal-induced pest suppression varies in a temporal manner. (Cohen and Mazzola, 2006; Weerakoon et al. 2012)

• SM amplified components of the microbiome contributing to disease control differ with target pathogen. (Cohen and Mazzola, 2006; Weerakoon et al. 2012; Mazzola et al. 2015)

• Modification of the microbiome to a disease-suppressive state may be dependent on generation of SM-derived chemistries (Weerakoon et al. 2012) and altered microbiome may function to induce host defense responses. (Wang et al., unpubl.)

• Rhizosphere/soil microbiome may be essential to Brassica SM derived disease/pest suppression. (Mazzola et al.,2002; Cohen and Mazzola, 2006; Hoagland et al., 2008)

Chemistry vs Soil Biology in Brassica Seed Meal-Induced Pest Control:

• Disease control may be attained irrespective of Brassica spp. glucosinolate content or production of biologically active chemistries. (Mazzola et al.2002; Cohen et al. 2005)

Management of rhizosphere microbiome: Field trials

Treatments:No treatment control Brassica juncea/Sinapis alba (1:1; BjSa SM) applied 9 Sept. 2009; rate 6.6 t/ha1,3-dichloropropene/chloropicrin fumigation (Telone C17)Planted 12 May 2010

Brassica SM amendment for replant disease control:

Mazzola et al. 2015.

SR Orchard:

Pratylenchus penetrans

plpnemweb.ucdavis.edu

Pathogen dynamics post-planting

Pythium spp.

-0.5 -0.4 -0.3 -0.2 -0.1 0.1 0.2 0.3

Coordinate 1

-0.48

-0.36

-0.24

-0.12

0.12

0.24

0.36

0.48

Co

ord

ina

te 2

NMDS of OTU data: SR orchard, Rock Island, WA

Similarity of Rhizosphere Microbiome: End of 2nd growing season

Brassica seed meal

Control/

Fumigation

Mazzola et al. 2015.

N. Allin and G.L. Barron

J.O. Becker, J. Borneman

Oidiodendron truncatum

NMDS of OTU data: BB Orchard Othello, WA (2018)

Pairwise comparison (ANOSIM):Con vs Fum: P = 0.4127SM vs Con: P = 0.0001SM vs Fum: P = 0.0001

Mazzola et al. unpubl.

Similarity of Rhizosphere Microbiome:

N. Allin and G.L. Barron

Somera & Mazzola, unpubl.

Brassica SM amendment has consistently increased Arthrobotrys spp. representation in rhizosphere fungal community

P = 0.041

Seed meal induced biological suppression of Pythium spp.;GC orchard soil, Manson, WA

Brassica juncea seed meal

Incubate 2-8 wks

Infest soil w/ Pythiumabappressoriumoospores

AITC is depleted from soil within 1-2 days postseed meal application

Seed meal induced Pythium-suppressive soil

Disease suppression associated with amplification of various antagonists.

Weerakoon et al., 2012

Chaetomium globosumHypocrea lixiiHypocrea longipilosaHypocrea virensTrichoderma hamatum

Interaction between rootstock genotype x seed meal on soil microbiome and soil-borne disease control efficacy.

Wang & Mazzola, 2019

Control vs. SM 2.2t/haANOSIM P = 0.1367; R = 0.0875

= Control = SM 2.2 t/ha = SM 4.4 t/ha = SM 6.6 t/ha

B. Juncea : S. alba SM

SM 2.2t/ha

Control

Control

SM 2.2t/ha

Interaction of reduced rate seed meal soil amendment and rootstock genotype: Field trial

Control

SM 2.2 t/ha Gala/M.26

SM 6.6 t/ha

Telone C35 fumigation

Soil Treatments Planting Material

Gala/G.41SM 4.4 t/ha

Seed meal formulation

SM = 1:1 Brassica juncea- Sinapis alba SM

April 2016 June 2016

Wang & Mazzola, 2019

Significant shifts in the rhizosphere microbiome were observed at lower SM amendment rates for Gala/G.41 than for Gala/M.26

Microbiome composition was similar between SM 2.2 t/ha and control treatment (ANOSIM P = 0.27)

= Control = Telone-C35 = SM 2.2 t/ha = SM 4.4 t/ha = SM 6.6 t/ha

SM 2.2 t/ha

Increase in trunk diameter over three growing seasons at the CV orchard replant site.

Increase in tree diameter (mm)

Wang & Mazzola, 2019

Rootstock

Soil treatment M.26 G.41

Control 14.97a 12.32a

Telone-C35 (fumigation) 19.21b 15.85b

Bj/Sa SM 2.2 t ha-1 16.90ab 15.82b

Bj/Sa SM 4.4 t ha-1 18.78b 17.98b

Bj/Sa SM 6.6 t ha-1 14.04a 18.04b

October 2016

Soil treatmentz Gala/M.26 Gala/G.41

Control 1247b 756b

Telone-C35 400a 234a

Bj/Sa SM 2.2 t ha-1 166a 99a

Bj/Sa SM 4.4 t ha-1 10a 78a

Bj/Sa SM 6.6 t ha-1 98a 29a

October 2017

Gala/M.26 Gala/G.41

2142b 997b

1335ab 758b

513a 231a

530a 76a

568a 88a

plpnemweb.ucdavis.edu

Brassica SM treatments consistently provided long-term lesion nematode suppression

Wang & Mazzola, 2019

Impact of pre-plant soil treatment on potential post-harvest fungal pathogen soil density two-years post-planting

Alternaria alternata—Fruit spot of apple

Glomerella spp.—Bitter rot of apple

C.L. Xiao

OSU Ext.Wang & Mazzola, 2019

• Apple rootstock rhizosphere facilitates microbial recruitment in a genotype-dependent manner

• The rootstock-directed microbiome may be transferred in a genotype-dependent manner to a subsequent planting and influence plant growth

• The SM modified microbiome can yield a soil system more resilient to pathogen re-infestation than that attained in response to fumigation

• Optimal amendment-based disease suppression may require identification and use of an appropriate plant genotype (rootstock).

Summary:

• Brassica SM amendment disease suppression requires activity of a transformed soil microbiome