Here we apply the CHRR algorithm to do flux sampling of metabolic models of different Arabidopsis genotypes exposed to different temperature treatments.
All of the experimental data used for the analyses are provided in the ExperimentalData folder. This contains the gas exchange (infrared gas analysis) and metabolite concentration (assay) data in ExpData.xlsx and the proteomics data in ProteinConc.xlsx.
In order to find feasible metabolic paths from carbon uptake via rubisco to downstream fumarate accumulation we adapted the "min-path" methods outlined by Ranganathan & Maranas (2010) as outlined in M-M-Graph.ipynb in the MetaboMetaboGraph folder.
We constructed metabolic models for Col-0 (wild-type) and fum2 Arabidopsis thaliana plants (grown in control conditions and grown in control conditions with one week exposure to cold) using adaptations of the Arnold and Nikoloski (2014) model. We then constrained the models with diurnal flux data calculated from the gas exchange, metabolite assay, and proteomics data sets as outline in the folder FluxSampling following the following analysis pipeline:
SetUpModel.ipynb==>ConstrainModel.ipynb==>MakeModel.ipynbto generate the modelsArabidopsisSampling.m==>FluxSamplingAnalysis.ipynbto generate and analyse flux sampling solutions
All models with the applied constraints, used for generating the flux sampling results, are available in the FluxSampling folder. The original Arnold and Nikoloski (2014) model was adapted to include cyclic electron transport and diurnal storage of malate, fumarate and starch.
For those who do not wish to access the code, we have provided a list of all metabolic reactions, their identifiers and their set lower and upper bounds. The 4 files (for the two conditions and the two genotypes) can be found in the FluxSampling folder of this repository.
All flux sampling distributions for all of the reaction in each of the models were plotted to pdf files and can be found in the FluxSampling folder.
A summary of the major carbon fluxes is avaiable in the SupplementaryMaterials folder.
We are currently revising a journal submission. For the latest DOI of the software please see: 10.5281/zenodo.3996223
Preliminary results for this work were presentation at the SEB 2019 conference in Seville in a talk titled "Using metabolic modelling to understand the limitations to photosynthesis under changing environmental conditions".