PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk...

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ASPB 2018 Frank Skraly July 17, 2018 Transporter manipulation in food crops for increased yield

Transcript of PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk...

Page 1: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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ASPB 2018Frank Skraly

July 17, 2018

Transporter manipulation in food crops for increased yield

Page 2: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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Yield10 company overview

Yield10 Bioscience (NasdaqCM:YTEN) is developing technologies to enhance global food security• Headquartered in Woburn, MA USA• Oilseeds center of excellence in Saskatoon, Canada

Yield10 brings extensive expertise and a track record in optimizing the flow of carbon in living systems to the agriculture sector to increase yield in key row crops

• Yield10 is targeting step-change (10-20%) increases in seed yield • Technology based on 20 years of cutting-edge crop metabolic engineering research• 15 recent patent applications for increased crop yield • Open innovation business model provides low hurdle for work with Ag majors

Yield10 focuses on its core strengths of advanced bioscience and innovation• Discover and de-risk yield technologies for major North American crops:

corn and the two oilseed crops soybean and canola

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Page 3: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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The Yield10 platform

• Increasing crop yield is an extremely complex and challenging problem• Screening thousands of individual plant genes has not delivered commercial yield traits

• However, the sector has used this approach to generate billions of individual data points

• Modifying combinations of genes, metabolic and/or regulatory, will be necessary

• GRAIN’s purpose is to be able to convert vast amounts of data into actionable gene modifications

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REGULATORY MODELING

METABOLIC MODELING

FAST FIELD TESTING

Actionable gene modifications

“GRAIN”(Gene-ranking artificial intelligence network)

Page 4: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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Metabolic modeling

Purely stoichiometric Optimize production of biomass, oil, protein, etc. View optimal metabolism (vs. observed metabolism) Show effects of local metabolic changes on entire plant

Eliminate unrealistic reactions from flux-balance analysis Identify slow/difficult reactions within known metabolism Challenge conventional wisdom

FLUX-BALANCE ANALYSIS

KINETICS/THERMODYNAMICSMETABOLIC MODELING

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Page 5: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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Crop Expression Trial Group Location Best seed yield increaseCamelina constitutive field Yield10 Canada 23%

Camelina seed-specific greenhouse Yield10 Canada 24%

Camelina seed-specific field Yield10 Canada 7%

Canola constitutive field Yield10 Canada 13%

Camelina constitutive field Schnell (Mich. St.) U.S. 52%

CCP1 (C3003): Trait that increases seed yield

● Transporter found in some algal species ● Induced at low CO2● Localizes to mitochondrial membrane

What is CCP1?

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Page 6: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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CCP1 is helpful in plants during photorespiration

CCP1+

WT

Carbon assimilation in Camelina(mmol m-2 s-1)

low oxygen airData from laboratory of Prof. Danny Schnell (Michigan State Univ.)

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Page 7: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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Photorespiration needs predicted by model

Flux-balance analysis, optimizing leaf biomass

What mitochondrial factors should increase during photorespiration?

MITOCHONDRION

Glu

2-OG OAA

Asp Malate

OAA

All of these remove electrons from the mitochondrion

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Page 8: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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CCP1 facilitates OAA uptake into mitochondria

Relative OAA uptake in mitochondriaisolated from yeast cells

CCP1+WT

OAA (oxaloacetate)is an electron carrier

2 e ̄

MalateOAAmalate

dehydrogenase

Data from laboratory of Prof. Danny Schnell (Michigan State Univ.)8

Page 9: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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Modeling suggests CCP1 role in optimum yield

NH3

OAA

Gly

Ser

OAAMALATE

MALATE

MALATE OAA

MALATE

OAAGLYCERATE

HYDROXYPYRUVATE

● Collect electrons from mitochondrion and chloroplast● Send to peroxisome or cytosol for hydroxypyruvate reductase (HPR)

CHLOROPLAST

PEROXISOME MITOCHONDRION

MALATE

OAA

Photosynthesis

CCP1

e-

e-

e-

CYTOSOL

HPR1

GLYCERATE

HYDROXYPYRUVATE

HPR2 e-PYRUVATE

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Page 10: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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Role of CCP1 during photorespiration in the leaf

● HPR flux must be very high at times during photorespiration● Modeling shows that lack of electron shuttling to HPR means >20% yield loss● Accumulation of photorespiratory intermediates could also be a problem

CCP1 may facilitate photorespiration

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Page 11: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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NAD(P)

ΔrG'm ≈ +31.3 kJ/molMalate

NAD(P)H

Oxaloacetate

Can CCP1 benefit seed metabolism?

malate dehydrogenase(MDH)

The TCA cycle must run during sugar metabolism in the seed,but one of its steps is very unfavorable:

Pi

ΔrG'm ≈ +43.5 kJ/molADP

H2O

ATPcompare with

spontaneous ATP formation

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Page 12: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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Cultured soybean embryo flux data

apparent flux through MDH

Allen et al., Plant J. 58:220–234 (2009)

Carbon efficiency is already >90%

SUGARS

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Page 13: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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Can CCP1 benefit seed metabolism?

CCP1 may increase sink strength, NOT carbon efficiency

MAL

Asp

PYR

PYR

ADP

MAL

ATP

FADH2

OAA

Ac-CoA

PiNADH

ADP

ATP

CIT

MAL OAA CIT

PYR

PEP

2PG

PEP

2PG

2-OG

Pi

CO2

TCA cycle

SUCROSE

CHLOROPLAST

CYTOSOL

MITOCHONDRION

CCP1

MDH

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Page 14: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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The reverse glyoxylate shunt (rGS)

2 CO2 + 2 HCO3- → OAA

NET

1

1

1

2

2

2

1

1

1

1

What if we could eliminate

photorespirationaltogether?

CO2HCO3─

RELATIVE FLUXES

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Page 15: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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Yield10 rGS data

Camelina greenhouse study: Best plants

Maximum relative theoretical yield with rGS under photorespiratory conditions = 212%

Malik, M.R., Tang, J., Sharma, N. et al. Plant Cell Rep. (2018). https://doi.org/10.1007/s00299-018-2308-315

WT100%

228%

173%

216%G

ram

s per

Pla

nt

Page 16: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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Summary

• Yield10 uses modeling and experimentation to identify and de-risk yield gene traits

• Metabolic modeling is a key part of this – but needs to be validated with results

• C3003 (CCP1) has shown significant oilseed yield increases in field trials

• Modeling has helped to explain its role and to suggest further targets

• The reverse glyoxylate shunt (rGS) pathway doubles seed yield in greenhouse studies,

demonstrating that improving carbon conversion efficiency has high yield potential

• Top rGS yield increases agree with model’s predictions

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Page 17: PowerPoint Presentation · • Yield10 uses modeling and experimentation to identify and de-risk yield gene traits • Metabolic modeling is a key part of this – but needs to be

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Thank you

Questions?

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[email protected]