Life on the Metabolic Edge: Individual and Mutualistic Methanogenic Systems

Methanogenesis is the biological production of methane gas by methanogens, single-celled, anaerobic archaea utilizing one of the oldest strategies of life. Methanogens generate the biomass and energy they need to live from simple carbon compounds, producing methane gas. They have evolved in a variety of anaerobic environments and consortia, many forming tight metabolic relationships with other species. Methanogenesis is therefore regulated by interactions both within the cell and between other organisms. This research explores these interactions in two parts. In the first part, we investigate how methane production is influenced through intracellular interactions involving the coenzyme M-coenzyme B heterodisulfide reductase. Hdr reduces a coenzyme heterodisulfide formed in the terminal step of the pathway, an essential step in methanogenesis. Two classes of Hdr have been identified: a variably expressed cytoplasmic HdrABC and a constitutively expressed membrane-bound HdrED. The generalist methanogen Methanosarcina acetivorans contains operons that encode both, making it an ideal model to explore their interactions within the cell. Crosslinking-mass spectrometry shows that HdrED forms a multienzyme complex with two essential methanogenic enzymes, creating a physical link between the carbon fixation pathways and the electron transport system. This complex may function as a biological router for carbon and electrons in the cell. In contrast, genetic overexpression of the cytoplasmic HdrABC decouples the production of methane from the electron transport chain. This allows increased substrate uptake and methane production without increasing cell growth or biomass. In the second part, we show a potentially syntrophic relationship between the methanogen Methanobrevibacter smithii (M. smithii ) and the bacterium Bacteroides thetaiotaomicron (B. theta), then explore how computational software testing techniques can be applied to high-throughput experiments. Syntrophic relationships are mutualistic metabolic relationships in which the members’ combined metabolisms perform a process that could not be accomplished individually. We first develop a defined coculture system for high-throughput comparisons of monoculture and coculture phenotypes. We then show that B. theta benefits from the presence of M. smithii, which removes the products that inhibit fermentation. Finally, we introduce the BioSIMP process, which uses software testing techniques of sampling and machine learning methods to model and predict experimental outcomes