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Dynamic substrate preferences and predicted metabolic properties of a simple microbial consortium

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https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1478-2
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Abstract

Abstract Microorganisms are typically found as complex microbial communities that altogether govern global biogeochemical cycles. Microbes have developed highly regulated metabolic capabilities to efficiently use available substrates including preferential substrate usage that can result in diauxic shifts. This and other metabolic behaviors have been discovered in studies of microbes in monoculture when grown on low-complexity ( e.g. two-component) mixtures of substrates, however, little is known about how species partition environmental substrates through substrate competition in more complex substrate mixtures. Here we use exometabolomic profiling to examine the time-varying substrate depletion from a mixture of 19 amino acids and glucose by two Pseudomonads and one Bacillus species isolated from ground water. We examine if the first substrates depleted result in maximal growth rate, or relate to growth medium or biomass composition and find surprisingly few correlations. Patterns of substrate depletion are modeled, and these models are used to examine if substrate usage preferences and substrate depletion kinetics of three microbial isolates can be used to predict the metabolism of the pooled isolates in co-culture. We find that most of the substrates fit the model predictions, indicating that the microbes are not altering their behaviors for these substrates in the presence of competitors. Glucose and histidine were depleted more slowly than predicted, while proline, glycine, glutamate, lysine, and arginine were all consumed significantly faster; these compounds highlight substrates that could be involved in species-species interactions within the consortium. Author Contributions OE, TRN conceived and designed the experiments OE, BPB, SMK, SJ, RL performed the experiments OE, BPB, SJ, TRN analyzed the data OE, TRN wrote the manuscript TRN contributed materials and analysis tools

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