Metabolic modeling of a mutualistic microbial community

Abstract

The rate of production of methane in many environments depends upon mutualistic interactions between sulfate‐reducing bacteria and methanogens. To enhance our understanding of these relationships, we took advantage of the fully sequenced genomes of Desulfovibrio vulgaris and Methanococcus maripaludis to produce and analyze the first multispecies stoichiometric metabolic model. Model results were compared to data on growth of the co‐culture on lactate in the absence of sulfate. The model accurately predicted several ecologically relevant characteristics, including the flux of metabolites and the ratio of D. vulgaris to M. maripaludis cells during growth. In addition, the model and our data suggested that it was possible to eliminate formate as an interspecies electron shuttle, but hydrogen transfer was essential for syntrophic growth. Our work demonstrated that reconstructed metabolic networks and stoichiometric models can serve not only to predict metabolic fluxes and growth phenotypes of single organisms, but also to capture growth parameters and community composition of simple bacterial communities. ### Synopsis Biological communities present tremendous modeling challenges because of the complex network of diverse interactions between species. A class of communities that has not been extensively modeled—but is of particular interest from ecological, geological, and engineering perspectives—is represented by microbial communities that thrive in oxygen‐free (anoxic) environments. These communities are vital components in numerous environments ranging from freshwater sediments and guts of insects and animals to wastewater treatment plants. They play a significant role in global cycling of carbon. Unlike communities of macro‐organisms, the flow of carbon through anaerobic communities depends to a large extent on the transfer of metabolites between species. Thus, it is essential that modelers of these communities first consider the metabolic networks determining the interactions among species. We report here on a metabolic model of a simple anaerobic community. This simple community consists of a bacterium and an archaeon that cooperate in a special mutualistic interaction called ‘syntrophy’ to degrade lactate into acetate and methane as the sole means of gaining energy for growth. The cooperation is based on the transfer of electrons from the bacterium to the archaeon in the form of hydrogen or formate. The archaeon uses the electrons to reduce carbon dioxide into methane. If the electrons are not transferred, then the archaeon will not have an energy source for growth. In turn, the bacteria will be unable to gain energy by oxidizing lactate unless their metabolites, primarily hydrogen and acetate, are kept at sufficiently low concentrations to make the reaction thermodynamically favorable. Such methanogenic syntrophies often form the final step of anaerobic trophic cascades and are therefore necessary for maintaining a continuous flux of metabolites through the community ([Figure 1][1]). Although a variety of anaerobic syntrophic associations have been examined, they have been characterized primarily in terms of bulk system properties and not as an integrated metabolic network ([Schink and Stams, 2002][2]). To develop a foundation for a more mechanistic understanding of syntrophic growth, we established a syntrophic interaction between two species whose genomes have been sequenced— Desulfovibrio vulgaris and Methanococcus maripaludis. D. vulgaris is a bacterium that can oxidize and obtain energy from a wide variety of carbon sources by sulfate respiration. M. maripaludis is an archaeon that obtains energy for growth by producing methane from carbon dioxide and hydrogen. The complete genome sequences of these two organisms were used as a basis to construct flux‐balance models of the central metabolisms of each growing independently and in syntrophic association. The models consist of a series of linear equations, each expressing a relationship between metabolites and the rate of flux through the reaction ([Edwards et al , 2002][3]). Because of the number of unknowns in the model, fluxes were calculated using linear optimization of a specific reaction, usually biomass production ([Price et al , 2004][4]). The single‐organism flux‐balance models were first refined by comparing the predicted biomass yields to experimental observations. These analyses provided insight into the physiology of growth of each species. Specifically, analysis of the D. vulgaris submodel suggested that two protons must be translocated to produce one ATP during respiration of sulfate. The M. maripaludis model provided insight into the likely number of protons that must be translocated during methane production and generated predictions about the influence of acetate consumption on biomass yield. The two models were then combined to form one model describing growth and metabolite accumulation when the organisms were growing syntrophically. A flux diagram showing the metabolic networks contained in the combined two‐species model, and an example of a simulation result is shown in [Figure 2][5]. Experimental data for lactate and hydrogen uptake rates during growth of the syntrophic culture were used as inputs to the model to test whether it could accurately capture the main features of syntrophic growth. The model was able to predict fluxes of acetate, methane, and carbon dioxide. In addition, the model consistently predicted roughly two‐fold more D. vulgaris biomass than M. maripaludis biomass even when it was set to optimize M. maripaludis biomass. This result demonstrates the stoichiometric coupling of growth of this association and is consistent with our experimental data which showed a ratio of D. vulgaris to M. maripaludis cells of approximately 2–2.5 throughout growth in batch culture. The model and experimental studies...