Dynamic substrate preferences predict metabolic properties of a simple microbial consortium

Abstract

BackgroundMixed cultures of different microbial species are increasingly being used to carry out a specific biochemical function in lieu of engineering a single microbe to do the same task. However, knowing how different species’ metabolisms will integrate to reach a desired outcome is a difficult problem that has been studied in great detail using steady-state models. However, many biotechnological processes, as well as natural habitats, represent a more dynamic system. Examining how individual species use resources in their growth medium or environment (exometabolomics) over time in batch culture conditions can provide rich phenotypic data that encompasses regulation and transporters, creating an opportunity to integrate the data into a predictive model of resource use by a mixed community.ResultsHere we use exometabolomic profiling to examine the time-varying substrate depletion from a mixture of 19 amino acids and glucose by two Pseudomonas and one Bacillus species isolated from ground water. Contrary to studies in model organisms, we found surprisingly few correlations between resource preferences and maximal growth rate or biomass composition. We then modeled patterns of substrate depletion, and used these models to examine if substrate usage preferences and substrate depletion kinetics of individual isolates can be used to predict the metabolism of a co-culture of the isolates. We found that most of the substrates fit the model predictions, except for glucose and histidine, which were depleted more slowly than predicted, and proline, glycine, glutamate, lysine and arginine, which were all consumed significantly faster.ConclusionsOur results indicate that a significant portion of a model community’s overall metabolism can be predicted based on the metabolism of the individuals. Based on the nature of our model, the resources that significantly deviate from the prediction highlight potential metabolic pathways affected by species-species interactions, which when further studied can potentially be used to modulate microbial community structure and/or function.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1478-2) contains supplementary material, which is available to authorized users.

Ecophysiological Study of Paraburkholderia sp. Strain 1N under Soil Solution Conditions: Dynamic Substrate Preferences and Characterization of Carbon Use Efficiency

“…1N on SESOM. Within each phase of substrate use, there is co-utilization of multiple substrates, which is similar to observations for other fast-growing Bacillus and Pseudomonad species(17,31). The co-existence of sequential (multiauxic) and simultaneous substrate use (co-utilization)…”

“…1N's biomass production in the first phase, lactate in the second, and reducing sugars coupled with valine in the final phase ( (10). Other observations of the co-existence of multiauxic and simultaneous substrate use tend to reinforce the idea that substrate selection is still based on affording the highest growth rate possible (31,49). Bacillus cereus is one other example of a fast-growing, r-selected organism that has been observed to selectively uptake substrates based on a mechanism outside of maximizing growth rate (31).…”

Inferring Metabolic Mechanisms of Interaction within a Defined Gut Microbiota

“…Then, in conditions with many putative interactions, sampling can be performed with finer time resolution to attain a clearer picture of the actual coupling of metabolite consumption and production with changes in growth of individual species, as previously performed with yeast and lactic-acid bacteria (Ponomarova et al, 2017). This framework, and others that model substrate utilization within a microbial community over time, could be modified with the strain abundance normalization procedure used within ConYE to identify dynamic features of emergent metabolic behavior in these communities (Erbilgin et al, 2017).…”

Web of microbes (WoM): a curated microbial exometabolomics database for linking chemistry and microbes

“…The WoM can be used to view data with additional factors to consider such as time points, synthetic consortia, native microbiomes and theoretical actions. In a recent study, time course analysis of three isolates mono-cultured in a defined amino acid medium was used to predict a model for amino acid consumption by a consortium containing all three isolates; the experimental tri-culture consumption data fit the model [ 19 ]. The tri-culture time-point results have been uploaded to the WoM each as unique ‘organisms’ to be compared in the One Environment or Web views showing the consumption patterns over time (Additional file 1 : Figure S8).…”