Post on 13-Dec-2015
Measuring Dynamic Biological Measuring Dynamic Biological Responses of Plants to Global Responses of Plants to Global
Change using Short-lived Change using Short-lived RadioisotopesRadioisotopes
Calvin Howell
Duke University Physics
Triangle Universities Nuclear Laboratory
March 1, 2006 University of Notre Dame 2
OutlineOutline
• The TUNL-Phytotron Collaboration
• Motivation
• Status of Plant Studies with Radioisotopes
• Plant Physiology Basics
• Demonstration of Technique
• Immediate Plans
March 1, 2006 University of Notre Dame 3
C.R. Howell (Physics)C. Reid (Biology)E. Bernhardt (Biology)A.S. Crowell (Physics Postdoc)M. Kiser (Physics graduate student)R. Phillips (Biology Postdoc)
TUNL-Phytotron Collaboration
March 1, 2006 University of Notre Dame 4
What is a Phytotron?What is a Phytotron?
• CControlled EEnvironment FFacility• Growth chambers can control many factors:
– Soil type
– Air Temperature
– Light levels (total & UV)
– Carbon dioxide concentrationCarbon dioxide concentration
– Relative humidity
– Nutrients
– Air pollutants
March 1, 2006 University of Notre Dame 5
OutlineOutline
• The TUNL-Phytotron Collaboration
• Motivation
• Status of Plant Studies with Radioisotopes
• Plant Physiology Basics
• Demonstration of Technique
• Immediate Plans
March 1, 2006 University of Notre Dame 6
MotivationsMotivations
“Industrial Revolution”
March 1, 2006 University of Notre Dame 7
MotivationsMotivations
Intergovernmental Panel on Climate Change (IPCC): Climate Change 2001, “The Carbon Cycle and Atmospheric Carbon Dioxide”
Climate models predict Climate models predict atmospheric COatmospheric CO22 levels levels
will double by the end will double by the end of this century!of this century!
How will plants respond?How will plants respond?
March 1, 2006 University of Notre Dame 8
Carbon BudgetCarbon Budget
Sinks in units of billions of metric tons of carbon (GtC)Sinks in units of billions of metric tons of carbon (GtC)
Fluxes in units of billions of metric tons of carbon per year (GtC/year)Fluxes in units of billions of metric tons of carbon per year (GtC/year)
Intergovernmental Panel on Climate Change (IPCC): Climate Change 2001, “The Carbon Cycle and Atmospheric Carbon Dioxide”
March 1, 2006 University of Notre Dame 9
Carbon BudgetCarbon Budget
Sinks in units of billions of metric tons of carbon (GtC)Sinks in units of billions of metric tons of carbon (GtC)
Fluxes in units of billions of metric tons of carbon per year (GtC/year)Fluxes in units of billions of metric tons of carbon per year (GtC/year)
Intergovernmental Panel on Climate Change (IPCC): Climate Change 2001, “The Carbon Cycle and Atmospheric Carbon Dioxide”
March 1, 2006 University of Notre Dame 10
Interesting AsideInteresting Aside
• Total tonnage of CO2 produced by vehicles over 124,000 mile lifetime
• Assuming ~10 year lifetime, vehicles emit more than their own weight in CO2 per year
13 mpg
36 mpg
22 mpg
18 mpg
65 mpg
http://www.sierraclub.org/globalwarming/suvreport/pollution.asp
March 1, 2006 University of Notre Dame 11
March 1, 2006 University of Notre Dame 12
Grassland ResponseGrassland ResponseMultiple Factors:(C) CO2 ; 680 ppm(T) Temperature; +80 W/m2
(P) Precipitation; +50%(N) Nitrogen; +7g/m2 year
M. Rebecca Shaw et al., Science 298:1987-1990 (2002) – Carnegie Institute of Washington and Stanford Univ.
March 1, 2006 University of Notre Dame 13
FACE StudiesFACE Studies• Free Air CO2 Enrichment (FACE)
experiments– Large-scale research programs to
study effects of increased CO2 levels– Many environmental variables– Difficult to correlate growth
parameters with high precision
• Findings from forest stands– Initially, carbon stored in woodInitially, carbon stored in wood– 2 years later, less found in wood, but 2 years later, less found in wood, but
more than double in fine rootsmore than double in fine roots– Nearly half of carbon uptake in short-Nearly half of carbon uptake in short-
lived tissues, such as foliagelived tissues, such as foliage– Increase in net primary production of Increase in net primary production of
25%25%– Growth rate increased about 26%Growth rate increased about 26%– Limited N Limited N no appreciable change no appreciable change
Duke FACTS-I Aerial ViewDuke FACTS-I Aerial View
March 1, 2006 University of Notre Dame 14
FACE SitesFACE Sites
March 1, 2006 University of Notre Dame 15
OutlineOutline
• The TUNL-Phytotron Collaboration
• Motivation
• Status of Plant Studies with Radioisotopes
• Plant Physiology Basics
• Demonstration of Technique
• Immediate Plans
March 1, 2006 University of Notre Dame 16
Introduction to Plant Studies with Introduction to Plant Studies with RadioisotopesRadioisotopes
• 14C used in mid-1940’s – Long half-life (~5730 years)– Weak beta emitter– Tracer measured by destructive harvesting
• Use of 11C for in vivo studies demonstrated in 1963• 1973 – More and Troughton at the Department of
Scientific and Industrial Research in New Zealand showed that useful amounts of 11C can be produced using small van de Graaf accelerators– Labs in USA, Canada, Scotland, New Zealand, and Germany
start using 11C for mechanistic studies of photosynthate transport in the mid 1970’s
– Present studies at: Julich, Germany; Univ. Tokyo; BNL; TUNL-Duke
March 1, 2006 University of Notre Dame 17
Features of using short-lived of using short-lived radioisotope tracersradioisotope tracers
• AdvantagesAdvantages– In vivo In vivo measurementmeasurement
– Use same specimen for Use same specimen for numerous experimentsnumerous experiments
– Conducive to studies Conducive to studies of dynamic phenomenaof dynamic phenomena
– Much greater Much greater sensitivity than that of sensitivity than that of carbon-14carbon-14
• ConsiderationsConsiderations– Experiments must be Experiments must be
performed near performed near acceleratoraccelerator
– Only observe short-Only observe short-term phenomena term phenomena
– For imaging, For imaging, sophisticated data sophisticated data acquisition and data acquisition and data analysis requiredanalysis required
March 1, 2006 University of Notre Dame 18
Planned Research at the TUNL-Phytotron Facility
1. Studies of CO2 uptake and carbon translation under different environmental conditions
2. Root exudate measurements 3. Studies of exchange between plant roots and mycorhhiza
associations; ectomycorrhizal fungi (EMF)4. Nutrient uptake and translocation under different environmental
conditions
March 1, 2006 University of Notre Dame 19
OutlineOutline
• The TUNL-Phytotron Collaboration
• Motivation
• Status of Plant Studies with Radioisotopes
• Plant Physiology Basics
• Demonstration of Technique
• Immediate Plans
March 1, 2006 University of Notre Dame 20
Plant Physiology 101Plant Physiology 101
• Carbohydrates produced by photosynthesis
• Sugars produced in mature leaves and transported via phloem tissue
Light
H2O
CO2
Sugars
Chloroplasts trap light energy
6H6H22O + 6COO + 6CO22 + light + light C C66HH1212OO66 + 6O + 6O22
SugarSugar
From Discover Science, Scott, Foresman, & Co., 1993
March 1, 2006 University of Notre Dame 21
Plant Physiology 101Plant Physiology 101
a) Sugars loaded into a sieve tubeb) Loading of the phloem sets up
water potential gradient that facilitates movement of water into dense phloem sap from the neighboring xylem
c) As hydrostatic pressure in phloem sieve tube increases, pressure flow begins, and sap moves through the phloem
d) At the sink, incoming sugars actively transported out of phloem and removed as complex carbohydrates
e) Loss of solute produces high water potential in phloem, and water passes out, returning eventually to xylem
http://home.earthlink.net/~dayvdanls/plant_transport.html
March 1, 2006 University of Notre Dame 22
Phloem Transport BasicsPhloem Transport Basics
Sugars from LeafSugars from Leaf
StorageStorage
• Stems
• Roots
GrowthGrowth
• New Shoots
• Roots
ReproductionReproduction
• Seeds
March 1, 2006 University of Notre Dame 23
OutlineOutline
• The TUNL-Phytotron Collaboration
• Motivation
• Status of Plant Studies with Radioisotopes
• Plant Physiology Basics
• Demonstration of Technique
• Immediate Plans
March 1, 2006 University of Notre Dame 24
Carbon-11 ProductionCarbon-11 Production
p + 14N 11C + ++1
5
2 3 4
2
3
1 Produce H- ions in negative ion source
4
5
Accelerate H- ions toward +5MV terminal
Strip off electrons with carbon foil (H- p)
Accelerate protons away from +5MV terminal
Bend p in magnet and collide on 14N target
March 1, 2006 University of Notre Dame 25
Production Block DiagramProduction Block Diagram
(CuO granules)
Average proton beam current = 1 ATotal irradiation time = 20 minutesGas cell pressure = 100 PSIGDesired activity = ~10 mCi
14N(p,)11C
T > 600ºC
March 1, 2006 University of Notre Dame 26
1111C ProductionC Production
110 min10514 F
N
1
2/1
min034.02ln
11
tC 114
1411
tN
NC
]1[)0()()( 11
1414111111
t
NNCCCCeNtNtA
NN
CC
N
N
1414
1111
March 1, 2006 University of Notre Dame 27
1111C PositronsC Positrons
+
1111C C 1111B + B + ++ + + ee
2115
116 ])()([ cmBmCmQ eNN
6
1
22112116 6)()(
iieN BcmcCmcCm
5
1
22112115 5)()(
iieN BcmcBmcBm
21111 ]2)()([ cmBmCmQ e
MeVQ 96.0
March 1, 2006 University of Notre Dame 28
Development ExperimentsDevelopment Experiments
• Study barley plants grown in ambient (350 PPM) and elevated (700 PPM) levels of CO2
• Label plants under both conditions
• Analyze differences in carbon uptake and translocation
March 1, 2006 University of Notre Dame 29
Single Detector MeasurementsSingle Detector Measurements
• Use detectors collimated for specific areas of plant to trace carbon allocation on a coarse (source/sink) scale
• Develop quantitative flow models to describe dynamics
March 1, 2006 University of Notre Dame 30
Single Detector MeasurementsSingle Detector Measurements
March 1, 2006 University of Notre Dame 31
Circuit DiagramCircuit Diagram
BGO DetectorBGO Detector
HVHV+1300V+1300V
Spect. Amp.Spect. Amp.
SCA Scaler
March 1, 2006 University of Notre Dame 32
Qualitative ResultsQualitative Results
Data corrected for half-life and relative detector efficiency
BarleyGrown@350PPMLabeled@350PPM
BarleyGrown@700PPMLabeled@700PPM
March 1, 2006 University of Notre Dame 33
Flow ModelFlow Model
Discrete observation times: tk where k = 0,1,2,.…Yk = counts in Sink B at time tk
Uk = counts in Total Sink at time tk
Leaf
Shoot
Root
Source
TotalSink
Sink A
Sink BSink B
Yk = - a1 Yk-1 - a2 Yk-2 - … - an Yk-n + b0 Uk + b1 Uk-1 + … + bm Uk-m
Input-Output AnalysisInput-Output Analysis:: (1)(1) Statistical, data-based modelingStatistical, data-based modeling(2)(2) No assumptions about mechanism(s) involvedNo assumptions about mechanism(s) involved
March 1, 2006 University of Notre Dame 34
Flow ModelFlow Model
Best Model: YYkk = = -a-a22 Y Yk-2k-2 + b+ b00 U Ukk + b + b22 U Uk-2k-2
Extract Physically Significant Quantities:
(1)(1) GainGain – fraction of inputinput that shows up at the outputoutput(2)(2) Average transit timeAverage transit time
March 1, 2006 University of Notre Dame 35
Flow ModelFlow ModelLeaf
Shoot
Root
Source
TotalSink
Sink A
Sink BSink B
Shoot Export
Treat entire plant asTreat entire plant as Total Sink Total Sink to probe leaf exportto probe leaf export
Leaf
Shoot
Root
Sink A’
TotalSink
Sink B’Sink B’Leaf Export
March 1, 2006 University of Notre Dame 36
Modeling ProcedureModeling Procedure• Fit data with model using method of least squares
• This gives the model parameters a2, b0, and b2 and the statistical error in these parameters
• To determine the gain and average transit time, look at the output of the system with a unit impulse input
kU1 for k=0
0 for k022022 kkkk UbUbYaY
N
kkYGGain
0 G
YktTimeTransAvg
k
N
k 0..
March 1, 2006 University of Notre Dame 37
One ExampleOne Example
5.1866
(0.0006)
0.6435
(0.0006)
0.43223
(0.00009)
-0.23666
(0.00008)
-0.69610
(0.00008)Run 2
7.7238
(0.0007)
0.6294
(0.0006)
0.29420
(0.00007)
-0.15852
(0.00006)
-0.78443
(0.00015)Run 1
< t > (min)Gb2b0a2
.)(0004.0.)(00997.063645.0 statsystG
March 1, 2006 University of Notre Dame 38
ResultsResultsBest Model: YYkk = = -a-a22 Y Yk-2k-2 + b+ b00 U Ukk + b + b22 U Uk-2k-2
[CO2] (ppm)
Age (days)
Leaf Export Fraction
Shoot Export Fraction
Leaf-to-Shoot Transit
Time (min)
Shoot-to-Root Transit Time (min)
350350 10-1210-12 0.78 ± 0.030.78 ± 0.03 0.28 ± 0.010.28 ± 0.01 20.39 ± 5.0220.39 ± 5.02 6.78 ± 2.306.78 ± 2.30
700700 10-1210-12 0.90 ± 0.030.90 ± 0.03 0.64 ± 0.010.64 ± 0.01 17.71 ± 1.0317.71 ± 1.03 6.45 ± 1.276.45 ± 1.27
350350 18-2118-21 0.92 ± 0.050.92 ± 0.05 0.39 ± 0.030.39 ± 0.03 25.03 ± 1.3425.03 ± 1.34 6.48 ± 0.016.48 ± 0.01
700700 18-2118-21 0.80 ± 0.030.80 ± 0.03 0.52 ± 0.0050.52 ± 0.005 22.01 ± 8.4122.01 ± 8.41 15.76 ± 2.9915.76 ± 2.99
March 1, 2006 University of Notre Dame 39
2D Imaging2D Imaging
● Approximate plant as planar source● Build up image through a sequence of exposures● Enhanced spatial resolution via coincidence detection
CsF detectors-High stopping power-High count rate capability
March 1, 2006 University of Notre Dame 40
Then We Have…Then We Have…
Leaf
Shoot
Root
Source
TotalSink
More Accurate
Flow Model
Enhanced ResolutionEnhanced Resolution Observe Fine Details of Observe Fine Details of Dynamic BehaviorDynamic Behavior
March 1, 2006 University of Notre Dame 41
2D Imaging2D Imaging
March 1, 2006 University of Notre Dame 42
Coincidence CircuitCoincidence Circuit
March 1, 2006 University of Notre Dame 43
EfficiencyEfficiency
• Some pixels “see” more of the array than others• Account for this by simulations
March 1, 2006 University of Notre Dame 44
EfficiencyEfficiency
March 1, 2006 University of Notre Dame 45
EfficiencyEfficiency
March 1, 2006 University of Notre Dame 46
EfficiencyEfficiency
From Above
From Side
March 1, 2006 University of Notre Dame 47
Prototype EfficiencyPrototype Efficiency
x (cm)
y (c
m) x (cm)
y (cm)
W
W
March 1, 2006 University of Notre Dame 48
Spatial Probability DistributionsSpatial Probability Distributions
11 22
33 44 55
66 77 88
99 1010
1111 1212
1313 1414
1515 1616 1717
1818 1919 2020
2121 2222
2323 2424
March 1, 2006 University of Notre Dame 49
Prototype ResolutionPrototype Resolution
W
W
x (cm)
y (cm)
x (cm)
y (c
m)
March 1, 2006 University of Notre Dame 50
Image ReconstructionImage Reconstruction
(1)(1) Add SPD for each Add SPD for each coincidence event for a coincidence event for a given exposure timegiven exposure time
(2) Subtract off background events scaled to the exposure time
(3) Correct for relative detection efficiency
(4) Correct for 11C half-life each minute of exposure
x (cm)
y (c
m)
March 1, 2006 University of Notre Dame 51
Image ReconstructionImage Reconstruction
(1) Add SPD for each coincidence event for a given exposure time
(2)(2) Subtract off background Subtract off background events scaled to the events scaled to the exposure timeexposure time
(3) Correct for relative detection efficiency
(4) Correct for 11C half-life each minute of exposure
x (cm)
y (c
m)
March 1, 2006 University of Notre Dame 52
Image ReconstructionImage Reconstruction
(1) Add SPD for each coincidence event for a given exposure time
(2) Subtract off background events scaled to the exposure time
(3)(3) Correct for relative Correct for relative detection efficiencydetection efficiency
(4) Correct for 11C half-life each minute of exposure
x (cm)
y (c
m)
March 1, 2006 University of Notre Dame 53
Image ReconstructionImage Reconstruction
(1) Add SPD for each coincidence event for a given exposure time
(2) Subtract off background events scaled to the exposure time
(3) Correct for relative detection efficiency
(4)(4) Correct for Correct for 1111C half-life C half-life each minute of exposureeach minute of exposure
x (cm)
y (c
m)
March 1, 2006 University of Notre Dame 54
For ExampleFor Example
x (cm)
y (c
m)
March 1, 2006 University of Notre Dame 55
Immediate PlansImmediate Plans
• Install radioactive handling system
• Develop root exudate experiment
• Build high-resolution 2D PET imager
• Start full research program
March 1, 2006 University of Notre Dame 56
Radioisotope Production
1. 11CO2 (half life = 20 min.)
14N + p 11C + Target: gas
3. 18F- (half life = 109 min.) 18O + p 18F + n
Target: 18O enriched water
2. 13NO3- (half live = 10 min.)
16O + p 13N + Target: 18O depleted water
4. H218O (half life = 2 min.)
16O + p 15O + d
Target: water
March 1, 2006 University of Notre Dame 57Ep (MeV)
14N(p,)11C Cross Section
March 1, 2006 University of Notre Dame 58
Radioactive Materials Handling System
March 1, 2006 University of Notre Dame 59
Root Exudate Experiment
March 1, 2006 University of Notre Dame 60
High resolution 2D imagers
5 cm x 5 cm x 1.5 cm2mm x 2mm pixels (0.1 mm gap)
20 cm x 30 cm field of view