Physiological Evidence for Isopotential Tunneling in the Electron Transport Chain of Methane-Producing Archaea

Many, but not all, organisms use quinones to conserve energy in their electron transport chains. Fermentative bacteria and methane-producing archaea (methanogens) do not produce quinones but have devised other ways to generate ATP. Methanophenazine (MPh) is a unique membrane electron carrier found in Methanosarcina species that plays the same role as quinones in the electron transport chain. To extend the analogy between quinones and MPh, we compared the MPh pool sizes between two well-studied Methanosarcina species, Methanosarcina acetivorans C2A and Methanosarcina barkeri Fusaro, to the quinone pool size in the bacterium Escherichia coli. We found the quantity of MPh per cell increases as cultures transition from exponential growth to stationary phase, and absolute quantities of MPh were 3-fold higher in M. acetivorans than in M. barkeri. The concentration of MPh suggests the cell membrane of M. acetivorans, but not of M. barkeri, is electrically quantized as if it were a single conductive metal sheet and near optimal for rate of electron transport. Similarly, stationary (but not exponentially growing) E. coli cells also have electrically quantized membranes on the basis of quinone content. Consistent with our hypothesis, we demonstrated that the exogenous addition of phenazine increases the growth rate of M. barkeri three times that of M. acetivorans. Our work suggests electron flux through MPh is naturally higher in M. acetivorans than in M. barkeri and that hydrogen cycling is less efficient at conserving energy than scalar proton translocation using MPh

Course Portfolio for BIOC934: Genome Dynamics and Gene Expression

A graduate degree in Biochemistry or any molecular life science field requires a strong foundation in molecular biology. BIOC934 Genome Dynamics and Gene Expression is a course designed to challenge graduate students whose research interests lie in the areas of biochemistry, molecular biology, synthetic biology, bioinformatics, and systems biology of prokaryote and eukaryote systems. Graduate students in these disciplines require a rigorous and thorough examination of core concepts in addition to practice applying theory to new observations while traversing unfamiliar disciplinary terrain. This portfolio describes the design of BIOC934, its implementation, and observed outcomes to identify strengths of the course and strategies for enhancement

Methanogens: pushing the boundaries of biology

Methanogens are anaerobic archaea that grow by producing methane gas. These microbes and their exotic metabolism have inspired decades of microbial physiology research that continues to push the boundary of what we know about how microbes conserve energy to grow. The study of methanogens has helped to elucidate the thermodynamic and bioenergetics basis of life, contributed our understanding of evolution and biodiversity, and has garnered an appreciation for the societal utility of studying trophic interactions between environmental microbes, as methanogens are important in microbial conversion of biogenic carbon into methane, a high-energy fuel. This review discusses the theoretical basis for energy conservation by methanogens and identifies gaps in methanogen biology that may be filled by undiscovered or yet-to-be engineered organisms

Insights into the biotechnology potential of Methanosarcina

Methanogens are anaerobic archaea which conserve energy by producing methane. Found in nearly every anaerobic environment on earth, methanogens serve important roles in ecology as key organisms of the global carbon cycle, and in industry as a source of renewable biofuels. Environmentally, methanogenic archaea play an essential role in the reintroducing unavailable carbon to the carbon cycle by anaerobically converting low-energy, terminal metabolic degradation products such as one and two-carbon molecules into methane which then returns to the aerobic portion of the carbon cycle. In industry, methanogens are commonly used as an inexpensive source of renewable biofuels as well as serving as a vital component in the treatment of wastewater though this is only the tip of the iceberg with respect to their metabolic potential. In this review we will discuss how the efficient central metabolism of methanoarchaea could be harnessed for future biotechnology applications

Editorial: Rising stars in microbial physiology and metabolism: 2022

This Research Topic was initiated to highlight work by young authors, the rising stars in the field of microbial physiology and metabolism. Microbial physiology and metabolism is an interdisciplinary field of research that seeks to uncover how the metabolic pathways of a cell work together to determine cell fate and function, whether that be growth, replication, pathogenicity, predation, respiration and fermentation, homeostasis or death. Ultimately, researchers like the ones featured here seek to integrate biological information and physicochemical parameters to try to find the underlying rules governing microbial function so that we can understand, predict and design microbes and microbial communities to improve society

Methanogenesis by Methanosarcina acetivorans involves two structurally and functionally distinct classes of heterodisulfide reductase

Biochemical studies have revealed two distinct classes of Coenzyme B-Coenzyme M heterodisulfide (CoB-S-S-CoM) reductase (Hdr), a key enzyme required for anaerobic respiration in methaneproducing archaea. A cytoplasmic HdrABC enzyme complex is found in most methanogens, whereas a membrane-bound HdrED complex is found exclusively in members of the order Methanosarcinales. Unexpectedly, genomic data indicate that multiple copies of both Hdr classes are found in all sequenced Methanosarcinales genomes. The Methanosarcina acetivorans hdrED1 operon is constitutively expressed and required for viability under all growth conditions examined, consistent with HdrED being the primary Hdr. HdrABC appears to be specifically involved in methylotrophic methanogenesis, based on reduced growth and methanogenesis rates of an hdrA1C1B1 mutant on methylotrophic substrates and downregulation of the genes during growth on acetate. This conclusion is further supported by phylogenetic analysis showing that the presence of hdrA1 in an organism is specifically correlated with the presence of genes for methylotrophic methanogenesis. Examination of mRNA abundance in methanol-grown DhdrA1C1B1 strains relative to wild-type revealed upregulation of genes required for synthesis of (di)methylsulfide and for transport and biosynthesis of CoB-SH and CoM-SH, suggesting that the mutant has a defect in electron transfer from ferredoxin to CoB-S-S-CoM that causes cofactor limitation

Isoprene Production from Municipal Wastewater Biosolids by Engineered Archaeon \u3ci\u3eMethanosarcina acetivorans\u3c/i\u3e

Wastewater biosolids are a promising feedstock for production of value-added renewable chemicals. Methane-producing archaea (methanogens) are already used to produce renewable biogas via the anaerobic treatment of wastewater. The ability of methanogens to efficiently convert dissolved organic carbon into methane makes them an appealing potential platform for biorefining using metabolic engineering. We have engineered a strain of the methanogen Methanosarcina acetivorans to produce the volatile hemiterpene isoprene in addition to methane. The engineered strain was adapted to grow in municipal wastewater through cultivation in a synthetic wastewater medium. When introduced to municipal wastewater the engineered methanogens were able to compete with the indigenous microorganisms and produce 0.97 mM of isoprene (65.9 ± 21.3 g per m3 of effluent). The production of isoprene in wastewater appears to be dependent on the quantity of available methanogenic substrate produced during upstream digestion by heterotrophic fermenters. This shows that with minimal adaptation it is possible to drop-in engineered methanogens to existing wastewater environments and attain value-added products in addition to the processing of wastewater. This shows the potential for utilizing methanogens as a platform for low-cost production of renewable materials without expensive feedstocks or the need to build or adapt existing facilities

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

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

Charting a new frontier of science by integrating mathematical modeling to understand and predict complex biological systems

Biological systems are staggeringly complex. To untangle this complexity and make predictions about biological systems is a continuous goal of biological research. One approach to achieve these goals is to emphasize the use of quantitative measures of biological processes. Advances in quantitative biology data collection and analysis across scales (molecular, cellular, organismal, ecological) has transformed how we understand, categorize, and predict complex biological systems. Simultaneously, thanks to increased computational power, mathematicians, engineers and physical scientists -- collectively termed theoreticians -- have developed sophisticated models of biological systems at different scales. But there is still a disconnect between the two fields. This surge of quantitative data creates an opportunity to apply, develop, and evaluate mathematical models of biological systems and explore novel methods of analysis. The novel modeling schemes can also offer deeper understanding of principles in biology. In the context of this paper, we use “models” to refer to mathematical representations of biological systems. This data revolution puts scientists in a unique position to leverage information-rich datasets to improve descriptive modeling. Moreover, advances in technology allow inclusion of heterogeneity and variability within these datasets and mathematical models. This inclusion may lead to identifying previously undetermined variables driving or maintaining heterogeneity and diversity. Improved inclusion of variation may even improve biologically meaningful predictions about how systems will respond to perturbations. Although some of these practices are mainstream in specific sub-fields of biology, such practices are not widespread across all fields of biological sciences. With resources dedicated to better integrating biology and mathematical modeling, we envision a transformational improvement in the ability to describe and predict complex biological systems