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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Single nucleotide variants drive evolutionary phage-host arms race in anaerobic carbon dioxide-converting microbiome

Microbial bioconversions are shaped by environmental perturbations and the adaptation of resident microbiomes. Prokaryotes coexist with bacteriophages, yet their coevolutionary trajectories remain underexplored. Here, we investigate the effects of a cultivation vessel leak on an anaerobic consortium performing carbon dioxide reduction. Using time-series shotgun metagenomic sequencing, we reconstruct microbial and viral genomes to track community shifts. We further apply single-nucleotide variant profiling and CRISPR array analysis to monitor viral microdiversity and host defense mechanisms. After bioaugmentation restores bioconversion efficiency, the consortium undergoes pronounced restructuring, with new dominant taxa emerging from the rare biosphere. We identify patterns consistent with phage predation selectively removing certain species, while others exhibit resilience to infection. This shift aligns with a widespread viral outbreak and a transient increased frequency of single nucleotide variants in bacterial CRISPR–Cas defense genes. Expansion of CRISPR spacers further supports that CRISPR-mediated processes influence microbial resilience. Concurrently, phages infecting resilient hosts exhibited adaptive evolution, marked by high genetic heterogeneity. Selective pressure varies across their genomes, targeting infectivity genes and protospacer-adjacent motifs. These findings highlight a dynamic evolutionary arms race driven by the selection of beneficial genetic variants, providing a mechanistic framework for multi-omics investigations, and informing biotechnological applications, including phage-based microbiome manipulation.

Ghiotto, G↗
DOE OSTI2021

Brockarchaeota, a novel archaeal phylum with unique and versatile carbon cycling pathways

Geothermal environments, such as hot springs and hydrothermal vents, are hotspots for carbon cycling and contain many poorly described microbial taxa. Here, we reconstructed 15 archaeal metagenome-assembled genomes (MAGs) from terrestrial hot spring sediments in China and deep-sea hydrothermal vent sediments in Guaymas Basin, Gulf of California. Phylogenetic analyses of these MAGs indicate that they form a distinct group within the TACK superphylum, and thus we propose their classification as a new phylum, ‘Brockarchaeota’, named after Thomas Brock for his seminal research in hot springs. Based on the MAG sequence information, we infer that some Brockarchaeota are uniquely capable of mediating non-methanogenic anaerobic methylotrophy, via the tetrahydrofolate methyl branch of the Wood-Ljungdahl pathway and reductive glycine pathway. The hydrothermal vent genotypes appear to be obligate fermenters of plant-derived polysaccharides that rely mostly on substrate-level phosphorylation, as they seem to lack most respiratory complexes. In contrast, hot spring lineages have alternate pathways to increase their ATP yield, including anaerobic methylotrophy of methanol and trimethylamine, and potentially use geothermally derived mercury, arsenic, or hydrogen. Their broad distribution and their apparent anaerobic metabolic versatility indicate that Brockarchaeota may occupy previously overlooked roles in anaerobic carbon cycling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Genomic profiles of four novel cyanobacteria MAGs from Lake Vanda, Antarctica: insights into photosynthesis, cold tolerance, and the circadian clock

Cyanobacteria in polar environments face environmental challenges, including cold temperatures and extreme light seasonality with small diurnal variation, which has implications for polar circadian clocks. However, polar cyanobacteria remain underrepresented in available genomic data, and there are limited opportunities to study their genetic adaptations to these challenges. This paper presents four new Antarctic cyanobacteria metagenome-assembled genomes (MAGs) from microbial mats in Lake Vanda in the McMurdo Dry Valleys in Antarctica. The four MAGs were classified as Leptolyngbya sp. BulkMat.35, Pseudanabaenaceae cyanobacterium MP8IB2.15, Microcoleus sp. MP8IB2.171, and Leptolyngbyaceae cyanobacterium MP9P1.79. The MAGs contain 2.76 Mbp – 6.07 Mbp, and the bin completion ranges from 74.2–92.57%. Furthermore, the four cyanobacteria MAGs have average nucleotide identities (ANIs) under 90% with each other and under 77% with six existing polar cyanobacteria MAGs and genomes. This suggests that they are novel cyanobacteria and demonstrates that polar cyanobacteria genomes are underrepresented in reference databases and there is continued need for genome sequencing of polar cyanobacteria. Analyses of the four novel and six existing polar cyanobacteria MAGs and genomes demonstrate they have genes coding for various cold tolerance mechanisms and most standard circadian rhythm genes with the Leptolyngbya sp. BulkMat.35 and Leptolyngbyaceae cyanobacterium MP9P1.79 contained kaiB3, a divergent homolog of kaiB.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Comparison of wild-type KT2440 and genome-reduced EM42 Pseudomonas putida strains for muconate production from aromatic compounds and glucose

Pseudomonas putida KT2440 is a robust, aromatic catabolic bacterium that has been widely engineered to convert bio-based and waste-based feedstocks to target products. Towards industrial domestication of P. putida KT2440, rational genome reduction has been previously conducted, resulting in P. putida strain EM42, which exhibited characteristics that could be advantageous for production strains. Here, we compared P. putida KT2440-and EM42-derived strains for cis,cis-muconic acid production from an aromatic compound, p-coumarate, and in separate strains, from glucose. To our surprise, the EM42-derived strains did not outperform the KT2440-derived strains in muconate production from either substrate. In bioreactor cultivations, KT2440-and EM42-derived strains produced muconate from p-coumarate at titers of 45 g/L and 37 g/L, respectively, and from glucose at 20 g/L and 13 g/L, respectively. To provide additional insights about the differences in the parent strains, we analyzed growth profiles of KT2440 and EM42 on aromatic compounds as the sole carbon and energy sources. In general, the EM42 strain exhibited reduced growth rates but shorter growth lags than KT2440. We also observed that EM42-derived strains resulted in higher growth rates on glucose compared to KT2440-derived strains, but only at the lowest glucose concentrations tested. Transcriptomics revealed that genome reduction in EM42 had global effects on transcript levels and showed that the EM42-derived strains that produce muconate from glucose exhibit reduced modulation of gene expression in response to changes in glucose concentrations. Overall, our results highlight that additional studies are warranted to understand the effects of genome reduction on microbial metabolism and physiology, especially when intended for use in production strains.

09 BIOMASS FUELS↗
DOE OSTI2025

Coupling flux balance analysis with reactive transport modeling through machine learning for rapid and stable simulation of microbial metabolic switching

Integrating genome-scale metabolic networks with reactive transport models (RTMs) provides a detailed description of the dynamic changes in microbial growth and metabolism. Despite promising demonstrations in the past, computational inefficiency has been pointed out as a critical issue to overcome because it requires repeated application of linear programming (LP) to obtain flux balance analysis (FBA) solutions in every time step and spatial grid. To address this challenge, we propose a new simulation method where we train and validate artificial neural networks (ANNs) using randomly sampled FBA solutions and incorporate the resulting surrogate FBA model (represented as algebraic equations) into RTMs as source/sink terms. We demonstrate the efficiency of our method via a case study of Shewanella oneidensis MR-1. During aerobic growth on lactate, S. oneidensis produces metabolic byproducts (such as pyruvate and acetate), which are subsequently consumed as alternative carbon sources when the preferred nutrients are depleted. To effectively simulate these complex dynamics, we used a cybernetic approach that models metabolic switches as the outcome of dynamic competition among multiple growth options. In both zero-dimensional batch and one-dimensional column configurations, the ANN-based surrogate models achieved substantial reduction of computational time by several orders of magnitude compared to the original LP-based FBA models. Moreover, the ANN models produced robust solutions without any special measures to prevent numerical instability. These developments significantly promote our ability to utilize genome-scale networks in complex, multi-physics, and multi-dimensional ecosystem modeling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

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

ABSTRACT 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 CO 2 and H 2 . Flux balance analysis modeling showed increased flux through CO 2 -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.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Modeling methane dynamics in three wetlands in Northeastern China by using the CLM-Microbe model

Wetlands account for up to 70% of the natural source of methane (CH 4 ) in terrestrial ecosystems on a global scale. Soil microbes are the ultimate producers and biological consumers of CH 4 in wetlands. Therefore, simulating microbial mechanisms of CH 4 production and consumptionwould improve the predictability of CH 4 flux in wetland ecosystems. In this study, we applied a microbial-explicit model, the CLM-Microbe, to simulate CH 4 flux in three major natural wetlands in northeastern China. The CLM-Microbe model was able to capture the seasonal variation of gross primary productivity (GPP), dissolved organic carbon (DOC), and CH 4 flux. The CLM-Microbe model explained more than 40% of the variation in GPP and CH 4 flux across sites. Marsh wetlands had higher CH 4 flux than mountain peatlands. Ebullition dominated the CH 4 transport pathway in all three wetlands. The methanogenesis dominates while methanotroph makes a minor contribution to the CH 4 flux, making all wetlands a CH 4 source. Sensitivity analysis indicated that microbial growth and death rates are the key factors governing CH 4 emission and vegetation physiological properties (flnr) and maintenance respiration predominate GPP variation. Explicitly simulating microbial processes allows genomic information to be incorporated, laying a foundation for better predicting CH 4 dynamics under the changing environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

MicroFisher: Fungal taxonomic classification for metatranscriptomic and metagenomic data using multiple short hypervariable markers

AbstractProfiling the taxonomic and functional composition of microbes using metagenomic (MG) and metatranscriptomic (MT) sequencing is advancing our understanding of microbial functions. However, the sensitivity and accuracy of microbial classification using genome– or core protein-based approaches, especially the classification of eukaryotic organisms, is limited by the availability of genomes and the resolution of sequence databases. To address this, we propose the MicroFisher, a novel approach that applies multiple hypervariable marker genes to profile fungal communities from MGs and MTs. This approach utilizes the hypervariable regions of ITS and large subunit (LSU) rRNA genes for fungal identification with high sensitivity and resolution. Simultaneously, we propose a computational pipeline (MicroFisher) to optimize and integrate the results from classifications using multiple hypervariable markers. To test the performance of our method, we applied MicroFisher to the synthetic community profiling and found high performance in fungal prediction and abundance estimation. In addition, we also used MGs from forest soil and MTs of root eukaryotic microbes to test our method and the results showed that MicroFisher provided more accurate profiling of environmental microbiomes compared to other classification tools. Overall, MicroFisher serves as a novel pipeline for classification of fungal communities from MGs and MTs.

Wang, Haihua↗
DOE OSTI2022

Improved Mobilome Delineation in Fragmented Genomes

The mobilome of a microbe, i.e., its set of mobile elements, has major effects on its ecology, and is important to delineate properly in each genome. This becomes more challenging for incomplete genomes, and even more so for metagenome-assembled genomes (MAGs), where misbinning of scaffolds and other losses can occur. Genomic islands (GIs), which integrate into the host chromosome, are a major component of the mobilome. Our GI-detection software TIGER, unique in its precise mapping of GI termini, was applied to 74,561 genomes from 2,473 microbial species, each species containing at least one MAG and one isolate genome. A species-normalized deficit of ∼1.6 GIs/genome was measured for MAGs relative to isolates. To test whether this undercount was due to the higher fragmentation of MAG genomes, TIGER was updated to enable detection of split GIs whose termini are on separate scaffolds or that wrap around the origin of a circular replicon. This doubled GI yields, and the new split GIs matched the quality of single-scaffold GIs, except that highly fragmented GIs may lack central portions. Cross-scaffold search is an important upgrade to GI detection as fragmented genomes increasingly dominate public databases. TIGER2 better captures MAG microdiversity, recovering niche-defining GIs and supporting microbiome research aims such as virus-host linking and ecological assessment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Decomposing a San Francisco estuary microbiome using long-read metagenomics reveals species- and strain-level dominance from picoeukaryotes to viruses

ABSTRACT Although long-read sequencing has enabled obtaining high-quality and complete genomes from metagenomes, many challenges still remain to completely decompose a metagenome into its constituent prokaryotic and viral genomes. This study focuses on decomposing an estuarine metagenome to obtain a more accurate estimate of microbial diversity. To achieve this, we developed a new bead-based DNA extraction method, a novel bin refinement method, and obtained 150 Gbp of Nanopore sequencing. We estimate that there are ~500 bacterial and archaeal species in our sample and obtained 68 high-quality bins (>90% complete, <5% contamination, ≤5 contigs, contig length of >100 kbp, and all ribosomal and tRNA genes). We also obtained many contigs of picoeukaryotes, environmental DNA of larger eukaryotes such as mammals, and complete mitochondrial and chloroplast genomes and detected ~40,000 viral populations. Our analysis indicates that there are only a few strains that comprise most of the species abundances. IMPORTANCE Ocean and estuarine microbiomes play critical roles in global element cycling and ecosystem function. Despite the importance of these microbial communities, many species still have not been cultured in the lab. Environmental sequencing is the primary way the function and population dynamics of these communities can be studied. Long-read sequencing provides an avenue to overcome limitations of short-read technologies to obtain complete microbial genomes but comes with its own technical challenges, such as needed sequencing depth and obtaining high-quality DNA. We present here new sampling and bioinformatics methods to attempt decomposing an estuarine microbiome into its constituent genomes. Our results suggest there are only a few strains that comprise most of the species abundances from viruses to picoeukaryotes, and to fully decompose a metagenome of this diversity requires 1 Tbp of long-read sequencing. We anticipate that as long-read sequencing technologies continue to improve, less sequencing will be needed.

Lui, Lauren M.↗
DOE OSTI2022

Functional characterization of prokaryotic dark matter: the road so far and what lies ahead

Eight-hundred thousand to one trillion prokaryotic species may inhabit our planet. Yet, fewer than two-hundred thousand prokaryotic species have been described. This uncharted fraction of microbial diversity, and its undisclosed coding potential, is known as the “microbial dark matter” (MDM). Next-generation sequencing has allowed to collect a massive amount of genome sequence data, leading to unprecedented advances in the field of genomics. Still, harnessing new functional information from the genomes of uncultured prokaryotes is often limited by standard classification methods. These methods often rely on sequence similarity searches against reference genomes from cultured species. This hinders the discovery of unique genetic elements that are missing from the cultivated realm. It also contributes to the accumulation of prokaryotic gene products of unknown function among public sequence data repositories, highlighting the need for new approaches for sequencing data analysis and classification. Increasing evidence indicates that these proteins of unknown function might be a treasure trove of biotechnological potential. Here, we outline the challenges, opportunities, and the potential hidden within the functional dark matter (FDM) of prokaryotes. We also discuss the pitfalls surrounding molecular and computational approaches currently used to probe these uncharted waters, and discuss future opportunities for research and applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Improving growth of Cupriavidus necator H16 on formate using adaptive laboratory evolution-informed engineering

Conversion of CO 2 to value-added products presents an opportunity to reduce GHG emissions while generating revenue. Formate, which can be generated by the electrochemical reduction of CO 2 , has been proposed as a promising intermediate compound for microbial upgrading. Here we present progress towards improving the soil bacterium Cupriavidus necator H16, which is capable of growing on formate as its sole source of carbon and energy using the Calvin-Benson-Bassham (CBB) cycle, as a host for formate utilization. Using adaptive laboratory evolution, we generated several isolates that exhibited faster growth rates on formate. The genomes of these isolates were sequenced, and resulting mutations were systematically reintroduced by metabolic engineering, to identify those that improved growth. Further, the metabolic impact of several mutations was investigated further using RNA-seq transcriptomics. We found that deletion of a transcriptional regulator implicated in quorum sensing, PhcA, reduced expression of several operons and led to improved growth on formate. Growth was also improved by deleting large genomic regions present on the extrachromosomal megaplasmid pHG1, particularly two hydrogenase operons and the megaplasmid CBB operon, one of two copies present in the genome. Based on these findings, we generated a rationally engineered ..delta..phcA and megaplasmid-deficient strain that exhibited a 24% faster maximum growth rate on formate. Moreover, this strain achieved a 7% growth rate improvement on succinate and a 19% increase on fructose, demonstrating the broad utility of microbial genome reduction. This strain has the potential to serve as an improved microbial chassis for biological conversion of formate to value-added products.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Genome-Resolved Metagenomics and Detailed Geochemical Speciation Analyses Yield New Insights into Microbial Mercury Cycling in Geothermal Springs

Geothermal systems emit substantial amounts of aqueous, gaseous, and methylated mercury, but little is known about microbial influences on mercury speciation. Here, we report results from genome-resolved metagenomics and mercury speciation analysis of acidic warm springs in the Ngawha Geothermal Field (< 55°C, pH < 4.5), Northland Region, Aotearoa New Zealand. Our aim was to identify the microorganisms genetically equipped for mercury methylation, demethylation, or Hg(II) reduction to volatile Hg(0) in these springs. Dissolved total and methylated mercury concentrations in two adjacent springs with different mercury speciation ranked among the highest reported from natural sources (250 to 16,000 ng liter -1 and 0.5 to 13.9 ng liter -1 , respectively). Total solid mercury concentrations in spring sediments ranged from 1,274 to 7,000 μg g -1 . In the context of such ultrahigh mercury levels, the geothermal microbiome was unexpectedly diverse and dominated by acidophilic and mesophilic sulfur- and iron-cycling bacteria, mercury- and arsenic-resistant bacteria, and thermophilic and acidophilic archaea. By integrating microbiome structure and metagenomic potential with geochemical constraints, we constructed a conceptual model for biogeochemical mercury cycling in geothermal springs. The model includes abiotic and biotic controls on mercury speciation and illustrates how geothermal mercury cycling may couple to microbial community dynamics and sulfur and iron biogeochemistry.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Northern peatland microbial communities exhibit resistance to warming and acquire electron acceptors from soil organic matter

The response of microbial communities that regulate belowground carbon turnover to climate change drivers in peatlands is poorly understood. Here, we leverage a whole ecosystem warming experiment to elucidate the key processes of terminal carbon decomposition and community responses to temperature rise. Our dataset of 697 metagenome-assembled genomes (MAGs) represents the microbial community from the surface (10 cm) to 2 m deep into the peat column, with only 3.7% of genomes overlapping with other well-studied peatlands. Community composition has yet to show a significant response to warming after 3 years, suggesting that metabolically diverse soil microbial communities are resistant to climate change. Surprisingly, abundant and active methanogens in the genus Candidatus Methanoflorens, Methanobacterium , and Methanoregula show the potential for both acetoclastic and hydrogenotrophic methanogenesis. Nonetheless, the predominant pathways for anaerobic carbon decomposition include sulfate/sulfite reduction, denitrification, and acetogenesis, rather than methanogenesis based on gene abundances. Multi-omics data suggest that organic matter cleavage provides terminal electron acceptors, which together with methanogen metabolic flexibility, may explain peat microbiome composition resistance to warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Microbial species and intraspecies units exist and are maintained by ecological cohesiveness coupled to high homologous recombination

Abstract Recent genomic analyses have revealed that microbial communities are predominantly composed of persistent, sequence-discrete species and intraspecies units (genomovars), but the mechanisms that create and maintain these units remain unclear. By analyzing closely-related isolate genomes from the same or related samples and identifying recent recombination events using a novel bioinformatics methodology, we show that high ecological cohesiveness coupled to frequent-enough and unbiased (i.e., not selection-driven) horizontal gene flow, mediated by homologous recombination, often underlie these diversity patterns. Ecological cohesiveness was inferred based on greater similarity in temporal abundance patterns of genomes of the same vs. different units, and recombination was shown to affect all sizable segments of the genome (i.e., be genome-wide) and have two times or greater impact on sequence evolution than point mutations. These results were observed in bothSalinibacter ruber, an environmental halophilic organism, andEscherichia coli, the model gut-associated organism and an opportunistic pathogen, indicating that they may be more broadly applicable to the microbial world. Therefore, our results represent a departure compared to previous models of microbial speciation that invoke either ecology or recombination, but not necessarily their synergistic effect, and answer an important question for microbiology: what a species and a subspecies are.

Science & Technology - Other Topics↗
DOE OSTI2020

Accurate and complete genomes from metagenomes

Genomes are an integral component of the biological information about an organism; thus, the more complete the genome, the more informative it is. Historically, bacterial and archaeal genomes were reconstructed from pure (monoclonal) cultures, and the first reported sequences were manually curated to completion. However, the bottleneck imposed by the requirement for isolates precluded genomic insights for the vast majority of microbial life. Shotgun sequencing of microbial communities, referred to initially as community genomics and subsequently as genome-resolved metagenomics, can circumvent this limitation by obtaining metagenome-assembled genomes (MAGs); but gaps, local assembly errors, chimeras, and contamination by fragments from other genomes limit the value of these genomes. Here, we discuss genome curation to improve and, in some cases, achieve complete (circularized, no gaps) MAGs (CMAGs). To date, few CMAGs have been generated, although notably some are from very complex systems such as soil and sediment. Through analysis of about 7000 published complete bacterial isolate genomes, we verify the value of cumulative GC skew in combination with other metrics to establish bacterial genome sequence accuracy. The analysis of cumulative GC skew identified potential misassemblies in some reference genomes of isolated bacteria and the repeat sequences that likely gave rise to them. We discuss methods that could be implemented in bioinformatic approaches for curation to ensure that metabolic and evolutionary analyses can be based on very high-quality genomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Platform for efficient large-scale storage and analysis of multi-omics data in plant and microbial systems (Final Technical Report)

Genomic variation at the sequence level fundamentally affects the phenotypic state of all organisms at all stages of development, while dynamic processes such as changes in the epigenome (e.g. DNA methylation state) and transcriptome regulate the specific phenotype expressed at any given state of development based upon that genomic variation. In plants, DNA methylation is a particularly important mechanism for both regulating transcriptomic expression and for management of genomic variations that could be deleterious to the organism due to the presence of active retrotransposons in plant genomes. While DNA methylation is heritable, it is also dynamic through a given plant’s development and life cycle, particularly during the development from seed to mature specimen suggesting variations in DNA methylation could be critical regulators of biologically and commercially important phenotypes such as time to flowering; in addition, plant DNA methylation is more complex than that of animals, with methylation of CHG and CHH trinucleotides evident in addition to the better-known CG methylation. The complexity of plant DNA methylation and its interplay with genomic sequence variation, transcriptomics and other epigenomic factors demand a storage and analysis framework that can cope with the complexity both within a single specimen and with analyses that span many individuals and even many species, such as attempts to extend models from model organisms to commercially relevant species. In addition to complexity, the rapid development and proliferation of sequencing technology has led to an explosion of data volume that conventional storage and analysis solutions will likely be unable to cope with in the long run. We proposed to study these with suitable distributed storage and computation and therefore for the application of cloud computing to biological analyses; integrate with existing data sources and compatible with virtually any interface use case, from fully automated shell scripts to notebooks and do all these at scale in this STTR grant.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Predominance of Methanomicrobiales and diverse hydrocarbon–degrading taxa in the Appalachian coalbed biosphere revealed through metagenomics and genome–resolved metabolisms

Coalbed deposits are a unique subsurface environment and represent an underutilized resource for methane generation. Microbial communities extant in coalbed deposits are responsible for key subsurface biogeochemical cycling and could be utilized to enhance methane production in areas where existing gas wells have depleted methane stores, or in coalbeds that are unmined, or conversely be utilized for mitigation of methane release. Here we utilize metagenomics and metagenome-assembled genomes to identify extant microbial lineages and genome-resolved microbial metabolisms of coalbed produced water, which has not yet been explored in the Appalachian Basin. Our analyses resulted in the recovery of over 40 metagenome-assembled genomes (MAGs) from eight coalbed methane wells. The most commonly identified taxa among samples were hydrogenotrophic methanogens from the order Methanomicrobiales and these dominant MAGs were highly similar to one another. Conversely, low-abundance coalbed bacterial populations were taxonomically and functionally diverse, mostly belonging to a variety of Proteobacteria classes, and encoding various hydrocarbon solubilization and degradation pathways. Further, the data presented herein provides novel insights into Appalachian Basin coalbed microbial ecology, and our findings provide new perspectives on underrepresented Methanocalculus species and low-relative abundance bacterial assemblages in coalbed environments, and their potential roles in stimulation or mitigation of methane release.

59 BASIC BIOLOGICAL SCIENCES↗