Final Report Systems Level Analysis of the Function and Adaptive Responses of Methanogenic Consortia
The purpose of this research was to determine whether the syntrophic microbial associations that are central to the functioning of methane-producing terrestrial wetlands can be predictively modeled with coupled multi-species genome-scale metabolic models. Such models are important because methane is an important greenhouse gas and there is a need to predictively model how the methane-producing microbial communities will respond to environmental perturbations, such as global climate change. The research discovered that the most prodigious methane-producing microorganisms on earth participate in a previously unrecognized form of energy exchange. The methane-producers Methanosaeta and Methanosarcina forge biological electrical connections with other microbes in order to obtain electrons to reduce carbon dioxide to methane. This direct interspecies electron transfer (DIET) was demonstrated in complex microbial communities as well as in defined co-cultures. For example, metatranscriptomic analysis of gene expression in both natural communities and defined co-cultures demonstrated that Methanosaeta species highly expressed genes for the enzymes for the reduction of carbon dioxide to methane. Furthermore, Methanosaeta’s electron-donating partners highly expressed genes for the biological electrical connections known as microbial nanowires. A series of studies involving transcriptomics, genome resequencing, and analysis of the metabolism of a series of strains with targeted gene deletions, further elucidated the mechanisms and energetics of DIET in methane-producing co-cultures, as well as in a co-culture of Geobacter metallireducens and Geobacter sulfurreducens, which provided a system for studying DIET with two genetically tractable partners. Genome-scale modeling of DIET in the G. metallireducens/G. sulfurreducens co-culture suggested that DIET provides more energy to the electron-donating partner that electron exchange via interspecies hydrogen transfer, but that the performance of DIET may be strongly influenced by environmental factors. These studies have significantly modified conceptual models for carbon and electron flow in methane-producing environments and have developed a computational framework for predictive modeling the influence of environmental perturbations on methane-producing microbial communities. The results have important implications for modeling the response of methane-producing microbial communities to climate change as well as for the bioenergy strategy of converting wastes and biomass to methane.