Due to this predictive potential, metabolic models have been applied to identify metabolic interactions between different organisms, to study host-microbiome interactions, to predict novel drug targets to fight microbial pathogens, and for the rational design of microbial genotypes and growth-media conditions for the industrial production or degradation of biochemicals. Metabolic models not only have demonstrated their ability to predict phenotypes on the level of cellular growth and gene knockouts, but also provide potential molecular mechanisms in form of gene and reaction activities, which can be validated experimentally. Although different microbial metabolic modelling approaches exist, they can be summarised by a theoretical framework that provides a unifying view on microbial growth. Mathematical analysis has shown great potential for dissecting the functioning of metabolic networks on the level of topological, stoichiometric, and kinetic models, which together provide a wide array of methods. In systems biology, the reconstruction of metabolic networks plays an essential role, as the network represents an organism’s capabilities to interact with its biotic and abiotic environment and to transform nutrients into biomass. Those catalysed reactions form a complex metabolic network of numerous biochemical transformations, which the organism is presumably able to perform. A majority of metabolic reactions are catalysed by enzymes, which are encoded in the genome of the respective organism. It provides metabolites and energy for all cellular processes.
Anything you have to do repeatedly may be ripe for automation.- Doug McIlroy Metabolism is central for organismal life.
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