Shachar-Hill, Y. | Search bioRxiv

bioRxiv2022

Accurate flux predictions using tissue-specific gene expression in plant metabolic modeling

MotivationThe accurate prediction of complex phenotypes such as metabolic fluxes in living systems is a grand challenge for systems biology and central to efficiently identifying biotechnological interventions that can address pressing industrial needs. The application of gene expression data to improve the accuracy of metabolic flux predictions using mechanistic modeling methods such as Flux Balance Analysis (FBA) has not been previously demonstrated in multi-tissue systems, despite their biotechnological importance. We hypothesized that a method for generating metabolic flux predictions informed by relative expression levels between tissues would improve prediction accuracy. ResultsRelative gene expression levels derived from multiple transcriptomic and proteomic datasets were integrated into Flux Balance Analysis predictions of a multi-tissue, diel model of Arabidopsis thalianas central metabolism. This integration dramatically improved the agreement of flux predictions with experimentally based flux maps from 13C Metabolic Flux Analysis (MFA) compared with a standard parsimonious FBA approach. Disagreement between FBA predictions and MFA flux maps, as measured by weighted averaged percent error values, dropped from between 169-180% and 94-103% in high light and low light conditions, respectively, to between 10-12% and 9-11%, depending on the gene expression dataset used. The incorporation of gene expression data into the modeling process also substantially altered the predicted carbon and energy economy of the plant. AvailabilityCode is available from https://github.com/Gibberella/ArabidopsisGeneExpressionWeights Contactyairhill@msu.edu

systems biology↗

bioRxiv2022

Introduction of a condensed, reverse tricarboxylic acid cycle for additional CO2 fixation in plants

Plants employ the Calvin-Benson cycle (CBC) to fix atmospheric CO2 for the production of biomass. The flux of carbon through the CBC is limited by the activity and selectivity of ribulose-1,5-bisphosphate carboxylase/oxygenase (RuBisCO). Alternative pathways that do not use RuBisCO to fix CO2 exist but occur only in anaerobic microorganisms. Rather than modifying existing routes of carbon metabolism in plants, we have developed a synthetic carbon fixation cycle that does not exist in nature, but is inspired by metabolisms of bacterial autotrophs. This synthetic cycle uses endogenous plant metabolites to fix CO2 and yield glyoxylate as a product. In this work, we build and characterize a condensed, reverse tricarboxylic acid (crTCA) cycle in vitro and in planta. We demonstrate that a simple, synthetic cycle can be used to fix carbon in vitro under aerobic and mesophilic conditions and that these enzymes retain activity when expressed transiently in planta. We then evaluate stable transgenic lines of Camelina sativa that have both phenotypic and physiologic changes. Transgenic C. sativa are shorter than controls with increased rates of photosynthetic CO2 assimilation and changes in photorespiratory metabolism. This first iteration of a build-test-learn phase of the crTCA cycle provides promising evidence that this pathway can be used to increase photosynthetic capacity in plants.

plant biology↗