Sanu Shameer

To identify potential strategies for increasing the efficiency of tomato leaf metabolism, with a focus on the links between nitrogen/carbon metabolism, we explored a diel Flux Balance Analysis (FBA) model of a source leaf in which the metabolic output was varied up to the theoretically-achievable maximum. We noticed a potentially interesting switch in the use of glutamine synthetase (GS) isoforms –from the chloroplast isoform to the mitochondrial one- for nitrogen assimilation. To further explore this prediction, we characterized transgenic tomato plants over-expressing two tomato GS genes, GS1 and GS2, targeted to mitochondria. Both sets of transgenic plants were characterized as displaying faster growth rate, early flowering and increased fruit yield. In leaves, metabolomic profiling and enzyme activity analysis pointed that GS activity in mitochondria plays a role in increasing the intracellular synthesis and subsequent export of sugar. Consistent with these changes, higher sucrose concentration in leaf exudates and reduced activities of enzymes involved in leaf starch synthesis were observed. Moreover, mitochondrial GS activity affected chloroplast redox status in a manner that modulated photorespiration and nitrogen metabolism. The combined data reveal the influence of mitochondrial GS activity on both foliar carbon/nitrogen balance and regulation of source-sink metabolism in tomato plants.

Modélisation du réseau métabolique et analyse du métabolisme de Trypanosoma brucei dans une perspective de biologie des systèmes: Les progrès récents dans la modélisation informatique des réseaux biologiques permettent maintenant aux chercheurs d'étudier le métabolisme cellulaire des organismes. Dans ce projet, ces approches ont été utilisées pour analyser le métabolisme de Trypanosoma brucei. Ce parasite protozoaire est responsable de la trypanosomiase africaine, une maladie mortelle chez l'homme et qui entraine des dégâts importants dans les élevages. Ce parasite est principalement retrouvé dans les régions d'Afrique sub-sahariennes. Durant cette thèse, des informations sur le métabolisme de T. brucei ont été recueillies à partir d'études publiées, bases de données et de communication personnelle avec des experts qui étudient les différents aspects du métabolisme des trypanosomatides. Cette information a été mise à disposition de la communauté à travers la base de données TrypanoCyc. La base de données a été publiée en Novembre 2014 et a eu plus de 4200 visiteurs provenant de plus de cent pays depuis Novembre 2015. Un modèle métabolique à l'échelle du génome de T. brucei a également été reconstruit sur la base des informations recueillies. Ce modèle a permis de faciliter l'étude du métabolisme de T. brucei en utilisant une approche de biologie des systèmes. Des algorithmes basés sur l'analyse de balance des flux ont été conçus pour optimiser la visualisation et l'étude des propriétés métaboliques du parasite. En utilisant l'algorithme iMat, des modèles spécifiques de la forme sanguine de T. brucei ont été générés à partir des informations fournies par les études publiées et les annotations présentent dans. Enfin, un algorithme a été conçu pour optimiser encore ces modèles spécifiques afin d'améliorer la cohérence de leurs prédictions avec les résultats publiés. Les modèles ainsi créés, spécifiques à la forme sanguine, ont montré une meilleure puissance prédictive que le modèle initial à l'échelle du génome, en particulier pour prédire le comportement métabolique spécifique de différents mutants de T. brucei.

PlantCoreMetabolism is a manually curated charge- and proton-balanced model of plant primary metabolism published in 2018. Since it consists of reactions common to all plants, the model has been used to study metabolism in a wide range of plant systems, including C3 leaves, CAM leaves, fruit pericarp cells, maize roots, and stomatal guard cells. Here, we summarize the application of diel flux balance analysis (FBA) leaf models derived from the PlantCoreMetabolism model. Diel FBA models extend traditional FBA by optimizing metabolism over a 24-hour light-dark cycle, capturing metabolic processes spread across multiple temporal phases. In this methods paper, we also describe key use cases of diel FBA leaf models, provide case study tutorials to demonstrate the utility of a diel leaf model, and introduce flux visualization tools to facilitate future work with the model.

Summary: Crassulacean acid metabolism (CAM) leaves are characterized by nocturnal acidification and diurnal deacidification processes related with the timed actions of phosphoenolpyruvate carboxylase and Rubisco, respectively. How CAM leaves manage cytosolic proton homeostasis, particularly when facing massive diurnal proton effluxes from the vacuole, remains unclear. A 12‐phase flux balance analysis (FBA) model was constructed for a mature malic enzyme‐type CAM mesophyll cell in order to predict diel kinetics of intracellular proton fluxes. The charge‐ and proton‐balanced FBA model identified the mitochondrial phosphate carrier (PiC, Pi/H⁺ symport), which provides Pi to the matrix to sustain ATP biosynthesis, as a major consumer of cytosolic protons during daytime (> 50%). The delivery of Pi to the mitochondrion, co‐transported with protons, is required for oxidative phosphorylation and allows sufficient ATP to be synthesized to meet the high energy demand during CAM Phase III. Additionally, the model predicts that mitochondrial pyruvate originating from decarboxylation of malate is exclusively exported to the cytosol, probably via a pyruvate channel mechanism, to fuel gluconeogenesis. In this biochemical cycle, glyceraldehyde 3‐phosphate dehydrogenase (GAPDH) acts as another important cytosolic proton consumer. Overall, our findings emphasize the importance of mitochondria in CAM and uncover a hitherto unappreciated role in metabolic proton homeostasis.

To identify potential strategies for increasing the efficiency of tomato leaf metabolism, with a focus on the links between nitrogen/carbon metabolism, we explored a diel Flux Balance Analysis (FBA) model of a source leaf in which the metabolic output was varied up to the theoretically-achievable maximum. We noticed a potentially interesting switch in the use of glutamine synthetase (GS) isoforms –from the chloroplast isoform to the mitochondrial one- for nitrogen assimilation. To further explore this prediction, we characterized transgenic tomato plants over-expressing two tomato GS genes, GS1 and GS2 , targeted to mitochondria. Both sets of transgenic plants were characterized as displaying faster growth rate, early flowering and increased fruit yield. In leaves, metabolomic profiling and enzyme activity analysis pointed that GS activity in mitochondrial plays a role in increasing the intracellular synthesis and subsequent export of sugar. Consistent with these changes, higher sucrose concentration in leaf exudates and reduced activities of enzymes involved in leaf starch synthesis were observed. Moreover, mitochondrial GS activity affected chloroplast redox status in a manner that modulated photorespiration and nitrogen metabolism. The combined data reveal the influence of mitochondrial GS activity on both foliar carbon/nitrogen balance and regulation of source-sink metabolism in tomato plants.

SUMMARY: While flux balance analysis (FBA) provides a framework for predicting steady‐state leaf metabolic network fluxes, it does not readily capture the response to environmental variables without being coupled to other modelling formulations. To address this, we coupled an FBA model of 903 reactions of soybean (Glycine max) leaf metabolism with e‐photosynthesis, a dynamic model that captures the kinetics of 126 reactions of photosynthesis and associated chloroplast carbon metabolism. Successful coupling was achieved in an iterative formulation in which fluxes from e‐photosynthesis were used to constrain the FBA model and then, in turn, fluxes computed from the FBA model used to update parameters in e‐photosynthesis. This process was repeated until common fluxes in the two models converged. Coupling did not hamper the ability of the kinetic module to accurately predict the carbon assimilation rate, photosystem II electron flux, and starch accumulation of field‐grown soybean at two CO₂ concentrations. The coupled model also allowed accurate predictions of additional parameters such as nocturnal respiration, as well as analysis of the effect of light intensity and elevated CO₂ on leaf metabolism. Predictions included an unexpected decrease in the rate of export of sucrose from the leaf at high light, due to altered starch–sucrose partitioning, and altered daytime flux modes in the tricarboxylic acid cycle at elevated CO₂. Mitochondrial fluxes were notably different between growing and mature leaves, with greater anaplerotic, tricarboxylic acid cycle and mitochondrial ATP synthase fluxes predicted in the former, primarily to provide carbon skeletons and energy for protein synthesis.

Stoichiometric modeling of leaf metabolism reveals metabolic and morphological determinants for introducing Crassulacean acid metabolism and alternative water-s

Summary: Cell expansion is a significant contributor to organ growth and is driven by the accumulation of osmolytes to increase cell turgor pressure. Metabolic modelling has the potential to provide insights into the processes that underpin osmolyte synthesis and transport, but the main computational approach for predicting metabolic network fluxes, flux balance analysis, often uses biomass composition as the main output constraint and ignores potential changes in cell volume. Here we present growth‐by‐osmotic‐expansion flux balance analysis (GrOE‐FBA), a framework that accounts for both the metabolic and ionic contributions to the osmotica that drive cell expansion, as well as the synthesis of protein, cell wall and cell membrane components required for cell enlargement. Using GrOE‐FBA, the metabolic fluxes in dividing and expanding cells were analysed, and the energetic costs for metabolite biosynthesis and accumulation in the two scenarios were found to be surprisingly similar. The expansion phase of tomato fruit growth was also modelled using a multiphase single‐optimization GrOE‐FBA model and this approach gave accurate predictions of the major metabolite levels throughout fruit development, as well as revealing a role for transitory starch accumulation in ensuring optimal fruit development.

Crassulacean Acid Metabolism (CAM) evolved in arid environments as a water-saving alternative to C ₃ photosynthesis. There is great interest in engineering more drought-resistant crop species by introducing CAM into C ₃ plants. However, one of the open questions is whether full CAM or alternative water-saving flux modes would be more productive in the environments typically experienced by C ₃ crops. To study the effect of temperature and relative humidity on plant metabolism we coupled a time-resolved diel model of leaf metabolism to an environment-dependent gas-exchange model. This model allowed us to study the emergence of CAM or CAM-like behaviour as a result of a trade-off between leaf productivity and water-saving. We show that vacuolar storage capacity in the leaf is a major determinant of the extent of CAM and shapes the occurrence of phase II and IV of the CAM cycle. Moreover, the model allows us to study alternative flux routes and we identify mitochondrial isocitrate dehydrogenase (ICDH) and an isocitrate-citrate-proline-2OG cycle as a potential contributor to initial carbon fixation at night. Simulations across a wide range of environmental parameters show that the water-saving potential of CAM strongly depends on the environment and that the additional water-saving effect of carbon fixation by ICDH can reach up to 4% for the conditions tested.

Cell expansion is a significant contributor to organ growth and is driven by the accumulation of osmolytes to increase cell turgor pressure. Metabolic modelling has the potential to provide insights into the processes that underpin osmolyte synthesis and transport, but the main computational approach for predicting metabolic network fluxes, flux balance analysis (FBA), typically uses biomass composition as the main output constraint and ignores potential changes in cell volume. Here we present GrOE-FBA (Growth by Osmotic Expansion-Flux Balance Analysis), a framework that accounts for both the metabolic and ionic contributions to the osmotica that drive cell expansion, as well as the synthesis of protein, cell wall and cell membrane components required for cell enlargement. Using GrOE-FBA, the metabolic fluxes in dividing and expanding cell were analyzed, and the energetic costs for metabolite biosynthesis and accumulation in the two scenarios were found to be surprisingly similar. The expansion phase of tomato fruit growth was also modelled using a multi-phase single optimization GrOE-FBA model and this approach gave accurate predictions of the major metabolite levels throughout fruit development as well as revealing a role for transitory starch accumulation in ensuring optimal fruit development.