Metabolic Synergy between Human Symbionts Bacteroides and Methanobrevibacter.

Trophic interactions between microbes are postulated to determine whether a host microbiome is healthy or causes predisposition to disease. Two abundant taxa, the Gram-negative heterotrophic bacterium Bacteroides thetaiotaomicron and the methanogenic archaeon Methanobrevibacter smithii, are proposed to have a synergistic metabolic relationship. Both organisms play vital roles in human gut health; B. thetaiotaomicron assists the host by fermenting dietary polysaccharides, whereas M. smithii consumes end-stage fermentation products and is hypothesized to relieve feedback inhibition of upstream microbes such as B. thetaiotaomicron. To study their metabolic interactions, we defined and optimized a coculture system and used software testing techniques to analyze growth under a range of conditions representing the nutrient environment of the host. We verify that B. thetaiotaomicron fermentation products are sufficient for M. smithii growth and that accumulation of fermentation products alters secretion of metabolites by B. thetaiotaomicron to benefit M. smithii. Studies suggest that B. thetaiotaomicron metabolic efficiency is greater in the absence of fermentation products or in the presence of M. smithii. Under certain conditions, B. thetaiotaomicron and M. smithii form interspecies granules consistent with behavior observed for syntrophic partnerships between microbes in soil or sediment enrichments and anaerobic digesters. Furthermore, when vitamin B12, hematin, and hydrogen gas are abundant, coculture growth is greater than the sum of growth observed for monocultures, suggesting that both organisms benefit from a synergistic mutual metabolic relationship. IMPORTANCE The human gut functions through a complex system of interactions between the host human tissue and the microbes which inhabit it. These diverse interactions are difficult to model or examine under controlled laboratory conditions. We studied the interactions between two dominant human gut microbes, B. thetaiotaomicron and M. smithii, using a seven-component culturing approach that allows the systematic examination of the metabolic complexity of this binary microbial system. By combining high-throughput methods with machine learning techniques, we were able to investigate the interactions between two dominant genera of the gut microbiome in a wide variety of environmental conditions. Our approach can be broadly applied to studying microbial interactions and may be extended to evaluate and curate computational metabolic models. The software tools developed for this study are available as user-friendly tutorials in the Department of Energy KBase.

Metabolic Feedback Inhibition Influences Metabolite Secretion by the Human Gut Symbiont Bacteroides thetaiotaomicron.

Microbial metabolism and trophic interactions between microbes give rise to complex multispecies communities in microbe-host systems. Bacteroides thetaiotaomicron (B. theta) is a human gut symbiont thought to play an important role in maintaining host health. Untargeted nuclear magnetic resonance metabolomics revealed B. theta secretes specific organic acids and amino acids in defined minimal medium. Physiological concentrations of acetate and formate found in the human intestinal tract were shown to cause dose-dependent changes in secretion of metabolites known to play roles in host nutrition and pathogenesis. While secretion fluxes varied, biomass yield was unchanged, suggesting feedback inhibition does not affect metabolic bioenergetics but instead redirects carbon and energy to CO2 and H2 Flux balance analysis modeling showed increased flux through CO2-producing reactions under glucose-limiting growth conditions. The metabolic dynamics observed for B. theta, a keystone symbiont organism, underscores the need for metabolic modeling to complement genomic predictions of microbial metabolism to infer mechanisms of microbe-microbe and microbe-host interactions.IMPORTANCE Bacteroides is a highly abundant taxon in the human gut, and Bacteroides thetaiotaomicron (B. theta) is a ubiquitous human symbiont that colonizes the host early in development and persists throughout its life span. The phenotypic plasticity of keystone organisms such as B. theta is important to understand in order to predict phenotype(s) and metabolic interactions under changing nutrient conditions such as those that occur in complex gut communities. Our study shows B. theta prioritizes energy conservation and suppresses secretion of "overflow metabolites" such as organic acids and amino acids when concentrations of acetate are high. Secreted metabolites, especially amino acids, can be a source of nutrients or signals for the host or other microbes in the community. Our study suggests that when metabolically stressed by acetate, B. theta stops sharing with its ecological partners.

BioSIMP: Using Software Testing Techniques for Sampling and Inference in Biological Organisms.

Years of research in software engineering has given us novel ways to reason about, test, and predict the behavior of complex software systems that contain hundreds of thousands of lines of code. Many of these techniques have been inspired by nature such as genetic algorithms, swarm intelligence, and ant colony optimization. In this paper we reverse the direction and present BioSIMP, a process that models and predicts the behavior of biological organisms to aid in the emerging field of systems biology. It utilizes techniques from testing and modeling of highly-configurable software systems. Using both experimental and simulation data we show that BioSIMP can find important environmental factors in two microbial organisms. However, we learn that in order to fully reason about the complexity of biological systems, we will need to extend existing or create new software engineering techniques.

High-throughput mutation, selection, and phenotype screening of mutant methanogenic archaea.

Bacterial and archaeal genomes can contain 30% or more hypothetical genes with no predicted function. Phylogenetically deep-branching microbes, such as methane-producing archaea (methanogens), contain up to 50% genes with unknown function. In order to formulate hypotheses about the function of hypothetical gene functions in the strict anaerobe, Methanosarcina acetivorans, we have developed high-throughput anaerobic techniques to UV mutagenize, screen, and select for mutant strains in 96-well plates. Using these approaches we have isolated 10 mutant strains that exhibit a variety of physiological changes including increased or decreased growth rate relative to the parent strain when cells use methanol and/or acetate as carbon and energy sources. This method provides an avenue for the first step in identifying new gene functions: associating a genetic mutation with a reproducible phenotype. Mutations in bona fide methanogenesis genes such as corrinoid methyltransferases and proton-translocating F420H2:methanophenazine oxidoreductase (Fpo) were also generated, opening the door to in vivo functional complementation experiments. Irradiation-based mutagenesis such as from ultraviolet (UV) light, combined with modern genome sequencing, is a useful procedure to discern systems-level gene function in prokaryote taxa that can be axenically cultured but which may be resistant to chemical mutagens.

Methods for Detecting Microbial Methane Production and Consumption by Gas Chromatography.

Methane is an energy-dense fuel but is also a greenhouse gas 25 times more detrimental to the environment than CO2. Methane can be produced abiotically by serpentinization, chemically by Sabatier or Fisher-Tropsh chemistry, or biotically by microbes (Berndt et al., 1996; Horita and Berndt, 1999; Dry, 2002; Wolfe, 1982; Thauer, 1998; Metcalf et al., 2002). Methanogens are anaerobic archaea that grow by producing methane gas as a metabolic byproduct (Wolfe, 1982; Thauer, 1998). Our lab has developed and optimized three different gas chromatograph-utilizing assays to characterize methanogen metabolism (Catlett et al., 2015). Here we describe the end point and kinetic assays that can be used to measure methane production by methanogens or methane consumption by methanotrophic microbes. The protocols can be used for measuring methane production or consumption by microbial pure cultures or by enrichment cultures.

Rerouting Cellular Electron Flux To Increase the Rate of Biological Methane Production.

Methanogens are anaerobic archaea that grow by producing methane, a gas that is both an efficient renewable fuel and a potent greenhouse gas. We observed that overexpression of the cytoplasmic heterodisulfide reductase enzyme HdrABC increased the rate of methane production from methanol by 30% without affecting the growth rate relative to the parent strain. Hdr enzymes are essential in all known methane-producing archaea. They function as the terminal oxidases in the methanogen electron transport system by reducing the coenzyme M (2-mercaptoethane sulfonate) and coenzyme B (7-mercaptoheptanoylthreonine sulfonate) heterodisulfide, CoM-S-S-CoB, to regenerate the thiol-coenzymes for reuse. In Methanosarcina acetivorans, HdrABC expression caused an increased rate of methanogenesis and a decrease in metabolic efficiency on methylotrophic substrates. When acetate was the sole carbon and energy source, neither deletion nor overexpression of HdrABC had an effect on growth or methane production rates. These results suggest that in cells grown on methylated substrates, the cell compensates for energy losses due to expression of HdrABC with an increased rate of substrate turnover and that HdrABC lacks the appropriate electron donor in acetate-grown cells.