Files
Abstract
Reactive metabolites are often generated as deliberate or unintended products from a number of reactions within the cell. While the reactivity of these metabolites can play a role in improving the metabolic robustness of an organism, their unbridled accumulation an perturb the metabolic network and hinder cell fitness, necessitating the presence of cellular mechanisms controlling their abundance. The well-conserved Rid superfamily of enzymes are responsible for the hydrolysis of enamine/imine species generated as reactive intermediates from a number of amino acid metabolic pathways. 2-aminoacrylate, a particularly reactive enamine, is generated by the pyridoxal 5’-phosphate-dependent biosynthetic serine/threonine alpha,beta-eliminase. Loss of RidA in Salmonella enterica allows for the accumulation of 2AA, which can damage a number of other pyridoxal 5’-phosphate-dependent enzymes and perturb cell growth. The work that follows describes an examination into the metabolic network factors that control 2AA generation by the biosynthetic serine/threonine alpha,beta-eliminase. The data comparing 2AA stress between Escherichia coli and S. enterica highlight how conserved components can be resuctured into distinct network architectures to influence the physiology of an organism. The second part of this work focuses on using transcriptomics and metabolomics methods as a high-throughput means to effectively describe the rewiring of metabolic network structure during 2AA stress. Transcriptomic and metabolomic readouts are increasingly being used as a rapid means to inform the physiological state of an orgaism/cell and offer a cost effective and accelerated means for physiological characterization. Importantly, generation of a model describing regulatory and metabolic consequences of a given stress using these tools is not confined to the observation of a growth phenotype or rigorous mechanistic/kinetic characterization, as has been the case during genetic and biochemical characterization of 2AA stress. Nonetheless, implementing classical biochemical genetic approaches to ‘omics’ workflows can prove valuable as a means to connect metabolic outputs to physiological phenomena and establish causal relationships. Generally, the work herein advocates for the continued use of careful genetic and environmental manipulations within these experiments as a means to separate physiologically relevant effects of a particular disease state or environmental stress from the total of all effects observed.