Metabolic Model Maurice Cheung 9 June 2021 Acknowledgements Organisers of Crops in silico Rahul Shaw My former postdoc YaleNUS College a small liberal arts college in Singapore collaboration between ID: 933557
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Slide1
Integrating Crop Growth Model and Constraint-BasedMetabolic Model
Maurice Cheung
9 June 2021
Slide2AcknowledgementsOrganisers of Crops
in silico
Rahul ShawMy former postdocYale-NUS Collegea small liberal arts college in Singaporecollaboration between Yale and NUS (National University of Singapore)
primarily undergraduate institution (PUI)
Slide3Crop growth model x Constraint-based metabolic model
Allow the predictions of metabolic flux patterns under different environmental conditions
Shaw and Cheung, unpublished
Slide4Construction of genome-scale metabolic modelsDNA sequences of an organism including all of its genesFunctional annotations of genes in the organismExtract metabolic enzymes from annotated genomes
Metabolic reactions catalysed by the enzymesMathematic model containing 100s – 1000s reactions and metabolites
Slide5Genome-scale metabolic models
Roche Applied Science "Biochemical Pathways" wall chart; http://web.expasy.org/pathways/
Slide6Gene-Protein-Reaction associations
Genome-scale models contains information on gene-protein-reaction associations
allows integration of
transcriptomic
and
proteomic
data
Proteome
Transcriptome
Metabolic network
Slide7Genome-scale models of crop plantsMaize (2010; 2011)Rice (2014; 2015)Tomato (2016)
Soybean (2019)
Poolman
, M. G.,
Kundu
, S., Shaw, R., & Fell, D. A. (2014). Frontiers in Plant Science, 5, 1–7.
Lakshmanan
, M., Lim, S.-H.,
Mohanty
, B., Kim, J. K., Ha, S.-H., & Lee, D.-L. (2015). Plant Physiology, 169, pp.15.01379
Dal’Molin
, C. G.,
Quek
, L.-E. L.-E.,
Palfreyman
, R. W.,
Brumbley
, S. M., Nielsen, L. K., (2010). Plant Physiology, 154(4), 1871–85.
Saha
, R.,
Suthers
, P. F., &
Maranas
, C. D. (2011).
PLoS ONE, 6(7), e21784.
Yuan, H., Cheung, C. Y. M., Poolman, M. G., Hilbers, P. A. J., & van Riel, N. A. W. (2016). The Plant Journal, 85, 289–304. Moreira, T.B., Shaw, R., Luo, X., Ganguly, O., Kim, H.-S., Coelho, L.G.F., Cheung, C.Y.M., Williams, T.C.R. (2019). Plant Physiology, 180, 1912-29.
Slide8Curation of rice genome-scale metabolic model:senescence and vitamin synthesis
To model resource remobilisationDegradation of biomassNeed to curate degradation pathwaysEspecially chlorophyll degradationAlso amino-acids etc.
Vitamin
in seed biomass
B2, B3, B5, B6 and folate
Curate for vitamin synthesis pathways
Mass- and charge-balancing
Energy conservation
Gene-protein-reaction associations
Connect with transcriptomes and proteomes
Wang et al. (2020) Nature Communications, 11, 1254
Slide9FBA is the most commonly used modelling technique for analysing genome-scale metabolic models
Constraint-based modelling:
Flux balance analysis (FBA)
Carbohydrate
Protein
Lipid
Nucleic acids
Pi
SO
4
2-
NO
3
-
CO
2
Slide10Limitations of constraint-based metabolic modellingNot easy to incorporate
environmental factorsWater availabilityTemperatureThese factors are affected by climate change
Töpfer et al. (2020) The Plant Cell, 32(12), 3689-3705
Gas exchange model x constraint-based model
IPCC AR5 (2014) Figure SPM.7
Slide11Crop growth model – WOFOSTMechanistic crop growth model
Relate environmental factors to crop growthWOrld FOod STudies (WOFOST) model
Incorporate environmental factorslight, temperature, water and macro-nutrients (N, P, K)Predict crop growthSeed, leaf, stem
de Wit et al. (2019) Agricultural Systems, 168, 154-167
Slide12Rice organ growth predicted by WOFOSTWOFOST model outputs:
biomass of leaf, stem, seed
vegetative, reproductive, grain filling stagesnormal and water-limited (stress) conditions
asdsad
Shaw and Cheung, unpublished
Slide13Using organ growth / degradation rates as constraints for flux balance model
Calculate
change in biomass based on WOFOST outputUse change in biomass as constraints to FBA modelleaf, stem, seedper dayDifferent constraints for normal and water-limited conditions
Shaw and Cheung, unpublished
Slide14Multi-organ rice genome-scale metabolic model3 organs –
leaf, stem, seedConnected by common pool (CP)phloem and xylemEach organ has its own biomass equations
Can access N, S, P from CP Effectively from rootOnly leaf received photonsDiel modelling framework
Shaw and Cheung, unpublished
Slide15Set up FBA model for normal & water-limited stress
Biomass constraints as the only difference between normal and water-limited conditions
Run simulations day-wise for 100 daysVegetative, reproductive, grain filling stages
Shaw and Cheung, unpublished
Slide16Predictions from FBA modelCompare between normal and water-limited conditions
Photosynthesissimilar at vegetative stagelevel off earlier for water-limitedN assimilation
low at the end of grain filling under normal conditionincrease at the end of grain filling in water-limited condition
Shaw and Cheung, unpublished
Slide17Transport of amino-acids for grain fillingGly
, Arg, Ser are the most efficient amino-acids as N source to the seed under both conditionsPredicted from FBA model
Patterns of amino-acids transport to the seed are very different between two conditionslargely follow the pattern of seed development
Shaw and Cheung, unpublished
Slide18Metabolic changes across developmental stages and environmental conditions
Number of unique reactions in each “stage-condition”Many unique reactions in grain-filling stage
under water-limited stressVery little difference between 2 conditions during vegetative stage
Shaw and Cheung, unpublished
Slide19Metabolic interactions between organs: Resource (re-)allocation
Flux solutions from FBA allow us to study metabolic flux distributionsPattern of resource allocation is similar between normal and water-limited conditions
Leaf is the main source organ supplying sucrose and amino-acids to the other organs
Shaw and Cheung, unpublished
Slide20Future of crop plant modelling: Multi-scale modelsMany
models at different scales developed and being perfected over decadesThere are limitations /
assumptions made for each modelling frameworkIntegrate models of different scales to overcome the limitations
For new (and experienced) modellers:
Have expertise in at least one type of modellingUnderstand its assumptions and limitationsKnow
how to connect to other types of modelsDon’t be afraid to learn new types of modelsNeed to know enough about other types of model
Figure out the
connection points
between models
Remember to
enjoy the process of modelling
!
good luck; have fun :)
Shaw and Cheung, unpublished