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Abstract Hydrogen, as an energy carrier, is attractive to many stakeholders based on the assumption that the extensive global network of natural gas infrastructure can be repurposed to transport hydrogen as part of a zero‐carbon energy future. Therefore, utility companies and governments are rapidly advancing efforts to pilot blending low‐carbon hydrogen into existing natural gas systems, many with the goal of eventually shifting to pure hydrogen. However, hydrogen has fundamentally different physical and chemical properties to natural gas, with major consequences for safety, energy supply, climate, and cost. We evaluate the suitability of using existing natural gas infrastructure for distribution of hydrogen. We summarize differences between hydrogen and natural gas, assess the latest science and engineering of each component of the natural gas value chain for hydrogen distribution, and discuss proposed solutions for building an effective hydrogen value chain. We find that every value chain component is challenged by reuse. Hydrogen blending can circumvent many challenges but offers only a small reduction in greenhouse gas emissions due to hydrogen's low volumetric energy density. Furthermore, a transition to pure hydrogen is not possible without significant retrofits and replacements. Even if technical and economic barriers are overcome, serious safety and environmental risks remain.

Summary: Methanogenesis allows methanogenic archaea to generate cellular energy for their growth while producing methane. Thermophilic hydrogenotrophic species of the genus Methanothermobacter have been recognized as robust biocatalysts for a circular carbon economy and are already applied in power-to-gas technology with biomethanation, which is a platform to store renewable energy and utilize captured carbon dioxide. Here, we generated curated genome-scale metabolic reconstructions for three Methanothermobacter strains and investigated differences in the growth performance of these same strains in chemostat bioreactor experiments with hydrogen and carbon dioxide or formate as substrates. Using an integrated systems biology approach, we identified differences in formate anabolism between the strains and revealed that formate anabolism influences the diversion of carbon between biomass and methane. This finding, together with the omics datasets and the metabolic models we generated, can be implemented for biotechnological applications of Methanothermobacter in power-to-gas technology, and as a perspective, for value-added chemical production.

Hydrogen holds tremendous potential to decarbonize many economic sectors, from chemical and material industries to energy storage and generation. However, hydrogen is a tiny, leak-prone molecule that can indirectly warm the climate. Thus, hydrogen emissions from its value chain (production, conversion, transportation/distribution, storage, and end-use) could considerably undermine the anticipated climate benefits of a hydrogen economy. Several studies have identified value chain components that may intentionally and/or unintentionally emit hydrogen. However, the amount of hydrogen emitted from infrastructure is unknown as emissions have not yet been empirically quantified. Without the capacity to make accurate direct measurements, over the past two decades, some studies have attempted to estimate total value chain and component-level hydrogen emissions using various approaches, e.g., assumptions, calculations via proxies, laboratory experiments, and theory-based models (simulations). Here, we synthesize these studies to provide an overview of the available knowledge on hydrogen emissions across value chains. Briefly, the largest ranges in estimated emissions rates are associated with liquefaction (0.15%–10%), liquid hydrogen transporting and handling (2%–20%), and liquid hydrogen refueling (2%–15%). Moreover, present and future value chain emission rate estimates vary widely (0.2%–20%). Field measurements of hydrogen emissions throughout the value chain are critically needed to sharpen our understanding of hydrogen emissions and, with them, accurately assess the climate impact of hydrogen deployment.

Rice paddies are major contributors to anthropogenic greenhouse gas emissions via methane (CH4) flux. The accurate quantification of CH4 emissions from rice paddies remains problematic, in part due to uncertainties and omissions in the contribution of microbial aggregates on the soil surface to carbon fluxes. Herein, we comprehensively evaluated the contribution of one form of microbial aggregates, periphytic biofilm (PB), to carbon dioxide (CO2) and CH4 emissions from paddies distributed across three climatic zones, and quantified the pathways that drive net CH4 production as well as CO2 fixation. We found that PB accounted for 7.1%–38.5% of CH4 emissions and 7.2%–12.7% of CO2 fixation in the rice paddies. During their growth phase, PB fixed CO2 and increased the redox potential, which promoted aerobic CH4 oxidation. During the decay phase, PB degradation reduced redox potential and increased soil organic carbon availability, which promoted methanogenic microbial community growth and metabolism and increased CH4 emissions. Overall, PB acted as a biotic converter of atmospheric CO2 to CH4, and aggravated carbon emissions by up to 2,318 kg CO2 equiv ha−1 season−1. Our results provide proof-of-concept evidence for the discrimination of the contributions of surface microbial aggregates (i.e., PB) from soil microbes, and a profound foundation for the estimation and simulation of carbon fluxes in a potential novel approach to the mitigation of CH4 emissions by manipulating PB growth. Public summary: • Field experiments were conducted in tropical, subtropical, and temperate rice paddies • Periphytic biofilm promoted CO2 fixation and CH4 emission • Periphytic biofilm acted as a biotic converter of atmospheric CO2 to CH4

Bulk production of medium-chain carboxylates (MCCs) with 6–12 carbon atoms is of great interest to biotechnology. Open cultures (e.g., reactor microbiomes) have been utilized to generate MCCs in bioreactors. When in-line MCC extraction and prevention of product inhibition is required, the bioreactors have been operated at mildly acidic pH (5.0–5.5). However, model chain-elongating bacteria grow optimally at neutral pH values. Here, we isolated a chain-elongating bacterium (strain 7D4C2) that grows at mildly acidic pH. We studied its metabolism and compared its whole genome and the reverse β-oxidation (rBOX) genes to other bacteria. Strain 7D4C2 produces lactate, acetate, n-butyrate, n-caproate, biomass, and H2/CO2 from hexoses. With only fructose as substrate (pH 5.5), the maximum n-caproate specificity (i.e., products per other carboxylates produced) was 60.9 ± 1.5%. However, this was considerably higher at 83.1 ± 0.44% when both fructose and n-butyrate (electron acceptor) were combined as a substrate. A comparison of 7D4C2 cultures with fructose and n-butyrate with an increasing pH value from 4.5 to 9.0 showed a decreasing n-caproate specificity from ∼92% at mildly acidic pH (pH 4.5-5.0) to ∼24% at alkaline pH (pH 9.0). Moreover, when carboxylates were extracted from the broth (undissociated n-caproic acid was ∼0.3 mM), the n-caproate selectivity (i.e., product per substrate fed) was 42.6 ± 19.0% higher compared to 7D4C2 cultures without extraction. Based on the 16S rRNA gene sequence, strain 7D4C2 is most closely related to the isolates Caproicibacter fermentans (99.5%) and Caproiciproducens galactitolivorans (94.7%), which are chain-elongating bacteria that are also capable of lactate production. Whole-genome analyses indicate that strain 7D4C2, C. fermentans, and C. galactitolivorans belong to the same genus of Caproiciproducens. Their rBOX genes are conserved and located next to each other, forming a gene cluster, which is different than for other chain-elongating bacteria such as Megasphaera spp. In conclusion, Caproiciproducens spp., comprising strain 7D4C2, C. fermentans, C. galactitolivorans, and several unclassified strains, are chain-elongating bacteria that encode a highly conserved rBOX gene cluster. Caproiciproducens sp. 7D4C2 (DSM 110548) was studied here to understand n-caproate production better at mildly acidic pH within microbiomes and has the additional potential as a pure-culture production strain to convert sugars into n-caproate.

ABSTRACT Across human populations, 16S rRNA gene-based surveys of gut microbiomes have revealed that the bacterial family Christensenellaceae and the archaeal family Methanobacteriaceae cooccur and are enriched in individuals with a lean, compared to an obese, body mass index (BMI). Whether these association patterns reflect interactions between metabolic partners, as well as whether these associations play a role in the lean host phenotype with which they associate, remains to be ascertained. Here, we validated previously reported cooccurrence patterns of the two families and their association with a lean BMI with a meta-analysis of 1,821 metagenomes derived from 10 independent studies. Furthermore, we report positive associations at the genus and species levels between Christensenella spp. and Methanobrevibacter smithii, the most abundant methanogen of the human gut. By coculturing three Christensenella spp. with M. smithii, we show that Christensenella spp. efficiently support the metabolism of M. smithii via H2 production far better than Bacteroides thetaiotaomicron does. Christensenella minuta forms flocs colonized by M. smithii even when H2 is in excess. In culture with C. minuta, H2 consumption by M. smithii shifts the metabolic output of C. minuta’s fermentation toward acetate rather than butyrate. Together, these results indicate that the widespread cooccurrence of these microorganisms is underpinned by both physical and metabolic interactions. Their combined metabolic activity may provide insights into their association with a lean host BMI. IMPORTANCE The human gut microbiome is made of trillions of microbial cells, most of which are Bacteria, with a subset of Archaea. The bacterial family Christensenellaceae and the archaeal family Methanobacteriaceae are widespread in human guts. They correlate with each other and with a lean body type. Whether species of these two families interact and how they affect the body type are unanswered questions. Here, we show that species within these families correlate with each other across people. We also demonstrate that particular species of these two families grow together in dense flocs, wherein the bacteria provide hydrogen gas to the archaea, which then make methane. When the archaea are present, the ratio of bacterial products (which are nutrients for humans) is changed. These observations indicate that when these species grow together, their products have the potential to affect the physiology of their human host.

Abstract Background Syngas fermentation, the bioconversion of CO, CO2, and H2 to biofuels and chemicals, has undergone considerable optimization for industrial applications. Even more, full-scale plants for ethanol production from syngas fermentation by pure cultures are being built worldwide. The composition of syngas depends on the feedstock gasified and the gasification conditions. However, it remains unclear how different syngas mixtures affect the metabolism of carboxidotrophs, including the ethanol/acetate ratios. In addition, the potential application of mixed cultures in syngas fermentation and their advantages over pure cultures have not been deeply explored. In this work, the effects of CO2 and H2 on the CO metabolism by pure and mixed cultures were studied and compared. For this, a CO-enriched mixed culture and two isolated carboxidotrophs were grown with different combinations of syngas components (CO, CO:H2, CO:CO2, or CO:CO2:H2). Results The CO metabolism of the mixed culture was somehow affected by the addition of CO2 and/or H2, but the pure cultures were more sensitive to changes in gas composition than the mixed culture. CO2 inhibited CO oxidation by the Pleomorphomonas-like isolate and decreased the ethanol/acetate ratio by the Acetobacterium-like isolate. H2 did not inhibit ethanol or H2 production by the Acetobacterium and Pleomorphomonas isolates, respectively, but decreased their CO consumption rates. As part of the mixed culture, these isolates, together with other microorganisms, consumed H2 and CO2 (along with CO) for all conditions tested and at similar CO consumption rates (2.6 ± 0.6 mmol CO L−1 day−1), while maintaining overall function (acetate production). Providing a continuous supply of CO by membrane diffusion caused the mixed culture to switch from acetate to ethanol production, presumably due to the increased supply of electron donor. In parallel with this change in metabolic function, the structure of the microbial community became dominated by Geosporobacter phylotypes, instead of Acetobacterium and Pleomorphomonas phylotypes. Conclusions These results provide evidence for the potential of mixed-culture syngas fermentation, since the CO-enriched mixed culture showed high functional redundancy, was resilient to changes in syngas composition, and was capable of producing acetate or ethanol as main products of CO metabolism.

Inhibition by ammonium at concentrations above 1000 mgN/L is known to harm the methanogenesis phase of anaerobic digestion. We anaerobically digested swine waste and achieved steady state COD-removal efficiency of around 52% with no fatty-acid or H2 accumulation. As the anaerobic microbial community adapted to the gradual increase of total ammonia-N (NH3-N) from 890±295 to 2040±30 mg/L, the Bacterial and Archaeal communities became less diverse. Phylotypes most closely related to hydrogenotrophic Methanoculleus (36.4%) and Methanobrevibacter (11.6%), along with acetoclastic Methanosaeta (29.3%), became the most abundant Archaeal sequences during acclimation. This was accompanied by a sharp increase in the relative abundances of phylotypes most closely related to acetogens and fatty-acid producers (Clostridium, Coprococcus, and Sphaerochaeta) and syntrophic fatty-acid Bacteria (Syntrophomonas, Clostridium, Clostridiaceae species, and Cloacamonaceae species) that have metabolic capabilities for butyrate and propionate fermentation, as well as for reverse acetogenesis. Our results provide evidence countering a prevailing theory that acetoclastic methanogens are selectively inhibited when the total ammonia-N concentration is greater than ~1000 mgN/L. Instead, acetoclastic and hydrogenotrophic methanogens coexisted in the presence of total ammonia-N of ~2000 mgN/L by establishing syntrophic relationships with fatty-acid fermenters, as well as homoacetogens able to carry out forward and reverse acetogenesis.

Hydrogen, as an energy carrier, is attractive to many stakeholders based on the assumption that the extensive global network of natural gas infrastructure can be repurposed to transport hydrogen as part of a zero‐carbon energy future. Therefore, utility companies and governments are rapidly advancing efforts to pilot blending low‐carbon hydrogen into existing natural gas systems, many with the goal of eventually shifting to pure hydrogen. However, hydrogen has fundamentally different physical and chemical properties to natural gas, with major consequences for safety, energy supply, climate, and cost. We evaluate the suitability of using existing natural gas infrastructure for distribution of hydrogen. We summarize differences between hydrogen and natural gas, assess the latest science and engineering of each component of the natural gas value chain for hydrogen distribution, and discuss proposed solutions for building an effective hydrogen value chain. We find that every value chain component is challenged by reuse. Hydrogen blending can circumvent many challenges but offers only a small reduction in greenhouse gas emissions due to hydrogen's low volumetric energy density. Furthermore, a transition to pure hydrogen is not possible without significant retrofits and replacements. Even if technical and economic barriers are overcome, serious safety and environmental risks remain. [ABSTRACT FROM AUTHOR]

Tree ensemble machine learning models are increasingly used in microbiome science as they are compatible with the compositional, high-dimensional, and sparse structure of sequence-based microbiome data. While such models are often good at predicting phenotypes based on microbiome data, they only yield limited insights into how microbial taxa may be associated. We developed endoR, a method to interpret tree ensemble models. First, endoR simplifies the fitted model into a decision ensemble. Then, it extracts information on the importance of individual features and their pairwise interactions, displaying them as an interpretable network. Both the endoR network and importance scores provide insights into how features, and interactions between them, contribute to the predictive performance of the fitted model. Adjustable regularization and bootstrapping help reduce the complexity and ensure that only essential parts of the model are retained. We assessed endoR on both simulated and real metagenomic data. We found endoR to have comparable accuracy to other common approaches while easing and enhancing model interpretation. Using endoR, we also confirmed published results on gut microbiome differences between cirrhotic and healthy individuals. Finally, we utilized endoR to explore associations between human gut methanogens and microbiome components. Indeed, these hydrogen consumers are expected to interact with fermenting bacteria in a complex syntrophic network. Specifically, we analyzed a global metagenome dataset of 2203 individuals and confirmed the previously reported association between Methanobacteriaceae and Christensenellales. Additionally, we observed that Methanobacteriaceae are associated with a network of hydrogen-producing bacteria. Our method accurately captures how tree ensembles use features and interactions between them to predict a response. As demonstrated by our applications, the resultant visualizations and summary outputs facilitate model interpretation and enable the generation of novel hypotheses about complex systems. Author summary: Machine learning models have proven to be successful at predicting diseases and other human phenotypes from microbiome data; however, gaining insight from such complex models is often challenging. To this end, we developed endoR, an R-package for enhanced interpretation of tree ensemble models (e.g., random forests), the most popular and highest-performing machine learning models applied to microbiome data to date. Our method simplifies models and extracts information on associations between microbiome data, host metadata and covariates, and a predicted trait (e.g., disease versus healthy). endoR has two main strengths: i) the ability to capture interactions between predictors, and ii) regularization steps that avoid overfitting. Through extensive validations, we show that endoR is comparable in accuracy to other common approaches while easing and enhancing model interpretation. We applied endoR to gain insight into a complex syntrophic network of human gut methanogens and bacterial fermenters. Overall, endoR is a powerful tool for gaining insight from tree ensemble models applied to microbiome data. [ABSTRACT FROM AUTHOR]

A geochemical gradient established by mixing between reduced, hyperalkaline (pH > 11), H2‐rich fluids generated through the process of serpentinization and surrounding surface water (pH ∼ 8) in the Samail Ophiolite of Oman provides an opportunity to characterize the geochemical and biological factors that influence the distribution of H2 oxidizing chemotrophs, hydrogenotrophs. In this study, 16S rRNA gene amplicon sequencing was implemented to characterize hydrogenotrophs in sediments underlying surface expressed serpentinized fluids in Oman. Hydrogenotroph phylotype distribution was evaluated as functions of chemical energy supplies for their given metabolic redox reactions. Through this approach, it was discovered that hydrogenotrophic taxa are likely constrained to sediments with overlying fluids that have <∼60 μm O2, including microorganisms of the genus, Hydrogenophaga. Sulfate reducers of the family, Thermodesulfovibrionaceae, likely require >∼10 μm SO4−2 for survival. In sediments with fluids having >∼10 μm SO4−2, sulfate reducers likely outcompete microorganisms of the methanogen genus, Methanobacterium, for H2. Additionally, differences in distribution between Thermodesulfovibrionaceae and Methanobacterium may be driven by the availability of electron acceptors and the redox reaction that is most energy yielding in the fluid. Taken together, observations from the Oman geochemical gradient result in a hydrogenotroph niche model that can be used to evaluate global distribution patterns of hydrogenotrophs in continental serpentinized fluids. On a global scale, based on previous studies, Methanobacterium is constrained to fluids that have <∼10 μm SO4−2. Plain Language Summary: A subsurface geological process called serpentinization produces H2 as a result of reduced rock from the upper mantle reacting with water. Microbial hydrogenotrophs can tap into this geological supply of H2 and oxidize it for energy. Hydrogenotrophic community composition varies in serpentinization‐hosted ecosystems across the globe. To determine geochemical and biological factors that may influence hydrogenotroph community composition, we evaluated the correspondence between the distribution of hydrogenotrophs among pools of serpentinized fluid in Oman and the chemical energy supplies used by their metabolisms. In doing so we discovered that sulfate reducers and methanogens (that reduce CO2 to CH4 by oxidizing H2) are differentially distributed. We attribute this difference in distribution to variation in the availability of their respective electron acceptors. Additionally, we discovered that O2, known to be toxic to hydrogenotrophs like sulfate reducers and methanogens, may constrain the hydrogenotrophs of this study to systems that are relatively O2 poor (<60 μm). Finally, in comparing hydrogenotroph distribution to chemical energy supply, we were able to characterize environmental thresholds for energy and substrates, below which survival may be limited. In all, this study provides a framework for assessing factors that may influence hydrogenotroph distribution in serpentinization‐hosted systems across the globe. Key Points: Hydrogenotroph distribution indicates O2 concentrations >60 micromolality are likely toxic to serpentinized fluid hydrogenotrophsElectron acceptor availability in serpentinized fluids likely drives the lack of co‐existence between sulfate reducer and methanogensThe energy threshold of serpentinized fluid methanogens is comparable to the energy required to convert 1 mol ADP to 1 mol ATP [ABSTRACT FROM AUTHOR]

Temperature can fluctuate widely between different seasons, and this may greatly impact many biological processes. However, little is known about its influence on the functioning of benthic microbial communities. Here we investigated the nutrient accumulation capability of periphytic biofilm under temperature fluctuations (17–35°C). Periphytic biofilm maintained the same nutrient accumulation capacity after experiencing the 'warming-hot-cooling' temperature fluctuation under both lab and outdoor conditions as those without temperature disturbance. In response to temperature increase, both community composition and species richness changed greatly and the increase in biodiversity was identified as being the underlying mechanism boosting the sustainable function in nutrient accumulation, indicating zero net effects of community changes. These findings provide insights into the underlying mechanisms of how benthic microbial communities adapt to temperature fluctuations to maintain nutrient accumulation capacity and elucidate that periphytic biofilm plays important roles in influencing nutrient cycling in aquatic ecosystems under temperature changes such as seasonal fluctuations. [ABSTRACT FROM AUTHOR]

Bulk production of medium-chain carboxylates (MCCs) with 6–12 carbon atoms is of great interest to biotechnology. Open cultures (e.g., reactor microbiomes) have been utilized to generate MCCs in bioreactors. When in-line MCC extraction and prevention of product inhibition is required, the bioreactors have been operated at mildly acidic pH (5.0–5.5). However, model chain-elongating bacteria grow optimally at neutral pH values. Here, we isolated a chain-elongating bacterium (strain 7D4C2) that grows at mildly acidic pH. We studied its metabolism and compared its whole genome and the reverse β-oxidation (rBOX) genes to other bacteria. Strain 7D4C2 produces lactate, acetate, n -butyrate, n -caproate, biomass, and H2/CO2 from hexoses. With only fructose as substrate (pH 5.5), the maximum n -caproate specificity (i.e., products per other carboxylates produced) was 60.9 ± 1.5%. However, this was considerably higher at 83.1 ± 0.44% when both fructose and n -butyrate (electron acceptor) were combined as a substrate. A comparison of 7D4C2 cultures with fructose and n -butyrate with an increasing pH value from 4.5 to 9.0 showed a decreasing n -caproate specificity from ∼92% at mildly acidic pH (pH 4.5-5.0) to ∼24% at alkaline pH (pH 9.0). Moreover, when carboxylates were extracted from the broth (undissociated n -caproic acid was ∼0.3 mM), the n -caproate selectivity (i.e., product per substrate fed) was 42.6 ± 19.0% higher compared to 7D4C2 cultures without extraction. Based on the 16S rRNA gene sequence, strain 7D4C2 is most closely related to the isolates Caproicibacter fermentans (99.5%) and Caproiciproducens galactitolivorans (94.7%), which are chain-elongating bacteria that are also capable of lactate production. Whole-genome analyses indicate that strain 7D4C2, C. fermentans , and C. galactitolivorans belong to the same genus of Caproiciproducens. Their rBOX genes are conserved and located next to each other, forming a gene cluster, which is different than for other chain-elongating bacteria such as Megasphaera spp. In conclusion, Caproiciproducens spp., comprising strain 7D4C2, C. fermentans , C. galactitolivorans , and several unclassified strains, are chain-elongating bacteria that encode a highly conserved rBOX gene cluster. Caproiciproducens sp. 7D4C2 (DSM 110548) was studied here to understand n -caproate production better at mildly acidic pH within microbiomes and has the additional potential as a pure-culture production strain to convert sugars into n -caproate. [ABSTRACT FROM AUTHOR]

Medium-chain fatty acids (MCFA) are important biofuel precursors. Carbon monoxide (CO) is a sustainable electron and carbon donor for fatty acid elongation, since it is metabolized to MCFA precursors, it is toxic to most methanogens, and it is a waste product generated in the gasification of waste biomass. The main objective of this work was to determine if the inhibition of methanogenesis through the continuous addition of CO would lead to increased acetate or MCFA production during fermentation of ethanol. The effects of CO partial pressures ( PCO; 0.08-0.3 atm) on methanogenesis, fatty acids production, and the associated microbial communities were studied in batch cultures fed with CO and ethanol. Methanogenesis was partially inhibited at PCO ≥ 0.11 atm. This inhibition led to increased acetate production during the first phase of fermentation (0-19 days). However, a second addition of ethanol (day 19) triggered MCFA production only at PCO ≥ 0.11 atm, which probably occurred through the elongation of acetate with CO-derived ethanol and H2:CO2. Accordingly, during the second phase of fermentation (days 20-36), the distribution of electrons to acetate decreased at higher PCO, while electrons channeled to MCFA increased. Most probably, Acetobacterium, Clostridium, Pleomorphomonas, Oscillospira, and Blautia metabolized CO to H2:CO2, ethanol and/or fatty acids, while Peptostreptococcaceae, Lachnospiraceae, and other Clostridiales utilized these metabolites, along with the provided ethanol, for MCFA production. These results are important for biotechnological systems where fatty acids production are preferred over methanogenesis, such as in chain elongation systems and microbial fuel cells. [ABSTRACT FROM AUTHOR]