Plant metabolic networks are increasingly being modelled at a large scale through the use of stoichiometric biochemical reaction networks consisting of the the entirety of characterized enzymes in compartmentalized tissue-specific cells and organs. The growing number of published large-scale network models of plant metabolism has been generated by coupling high-throughput data with automated optimization-based methods (algorithms) applied on networks of reactions specific to plants and photosynthetic microorganisms. These large-scale plant network models have been employed to tackle different questions from determining the set of feasible steady-state flux distributions under different modeling scenarios to discriminating hypotheses about (in)active pathways, to designing metabolic engineering strategies aimed at improving the production of biomass/ specific compounds of interest. Extensions of these methods could potentially be used to investigate time-dependent behavior and to determine metabolic processes involved in plant acclimation to changing conditions.
This research topic aims to present the latest research efforts addressing the issues of: (1) comparing the predictions from the contending large-scale models of plant metabolism in model species (e.g., Arabidopsis and maize) with respect to different biological questions (i.e., prediction of fluxes, flux ratios, biomass and/or product yield) and their compliance to measurements, (2) illustrating the usage of existing as well as novel methods for integrating high-throughput data in large-scale plant models with the goal to arrive at more accurate predictions of molecular phenotypes (3) investigating the costs of different plant tasks/objectives together with their trade-offs and relations to the underlying metabolic functions in primary and secondary metabolism, (4) moving towards multi-scale models in which metabolic network models are integrated with plant development and physiology. We welcome all types of articles including original research, methods, opinions, and reviews that provide insights in large-scale modeling of plant metabolism and its interrogation through data integration from various level of biological organization.
Plant metabolic networks are increasingly being modelled at a large scale through the use of stoichiometric biochemical reaction networks consisting of the the entirety of characterized enzymes in compartmentalized tissue-specific cells and organs. The growing number of published large-scale network models of plant metabolism has been generated by coupling high-throughput data with automated optimization-based methods (algorithms) applied on networks of reactions specific to plants and photosynthetic microorganisms. These large-scale plant network models have been employed to tackle different questions from determining the set of feasible steady-state flux distributions under different modeling scenarios to discriminating hypotheses about (in)active pathways, to designing metabolic engineering strategies aimed at improving the production of biomass/ specific compounds of interest. Extensions of these methods could potentially be used to investigate time-dependent behavior and to determine metabolic processes involved in plant acclimation to changing conditions.
This research topic aims to present the latest research efforts addressing the issues of: (1) comparing the predictions from the contending large-scale models of plant metabolism in model species (e.g., Arabidopsis and maize) with respect to different biological questions (i.e., prediction of fluxes, flux ratios, biomass and/or product yield) and their compliance to measurements, (2) illustrating the usage of existing as well as novel methods for integrating high-throughput data in large-scale plant models with the goal to arrive at more accurate predictions of molecular phenotypes (3) investigating the costs of different plant tasks/objectives together with their trade-offs and relations to the underlying metabolic functions in primary and secondary metabolism, (4) moving towards multi-scale models in which metabolic network models are integrated with plant development and physiology. We welcome all types of articles including original research, methods, opinions, and reviews that provide insights in large-scale modeling of plant metabolism and its interrogation through data integration from various level of biological organization.