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At least 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The global anaerobic metabolism regulator fnr is necessary for the degradation of food dyes and drugs by Escherichia coli

ABSTRACT The microbiome is an underappreciated contributor to intestinal drug metabolism with broad implications for drug efficacy and toxicity. While considerable progress has been made toward identifying the gut bacterial genes and enzymes involved, the role of environmental factors in shaping their activity remains poorly understood. Here, we focus on the gut bacterial reduction of azo bonds (R-N = N-R’), found in diverse chemicals in both food and drugs. Surprisingly, the canonical azoR gene in Escherichia coli was dispensable for azo bond reduction. Instead, azoreductase activity was controlled by the fumarate and nitrate reduction ( fnr ) regulator, consistent with a requirement for the anoxic conditions found within the gastrointestinal tract. Paired transcriptomic and proteomic analysis of the fnr regulon revealed that in addition to altering the expression of multiple reductases, FNR is necessary for the metabolism of L-Cysteine to hydrogen sulfide, enabling the degradation of azo bonds. Furthermore, we found that FNR indirectly regulates this process through the small noncoding regulatory RNA fnrS . Taken together, these results show how gut bacteria sense and respond to their intestinal environment to enable the metabolism of chemical groups found in both dietary and pharmaceutical compounds. IMPORTANCE This work has broad relevance due to the ubiquity of dyes containing azo bonds in food and drugs. We report that azo dyes can be degraded by human gut bacteria through both enzymatic and nonenzymatic mechanisms, even from a single gut bacterial species. Furthermore, we revealed that environmental factors, oxygen, and L-Cysteine control the ability of E. coli to degrade azo dyes due to their impacts on bacterial transcription and metabolism. These results open up new opportunities to manipulate the azoreductase activity of the gut microbiome through the manipulation of host diet, suggest that azoreductase potential may be altered in patients suffering from gastrointestinal disease, and highlight the importance of studying bacterial enzymes for drug metabolism in their natural cellular and ecological context.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A roadmap to understanding and anticipating microbial gene transfer in soil communities

Engineered microbes are being programmed using synthetic DNA for applications in soil to overcome global challenges related to climate change, energy, food security, and pollution. However, we cannot yet predict gene transfer processes in soil to assess the frequency of unintentional transfer of engineered DNA to environmental microbes when applying synthetic biology technologies at scale. This challenge exists because of the complex and heterogeneous characteristics of soils, which contribute to the fitness and transport of cells and the exchange of genetic material within communities. Here, we describe knowledge gaps about gene transfer across soil microbiomes. Here, we propose strategies to improve our understanding of gene transfer across soil communities, highlight the need to benchmark the performance of biocontainment measures in situ, and discuss responsibly engaging community stakeholders. We highlight opportunities to address knowledge gaps, such as creating a set of soil standards for studying gene transfer across diverse soil types and measuring gene transfer host range across microbiomes using emerging technologies. By comparing gene transfer rates, host range, and persistence of engineered microbes across different soils, we posit that community-scale, environment-specific models can be built that anticipate biotechnology risks. Such studies will enable the design of safer biotechnologies that allow us to realize the benefits of synthetic biology and mitigate risks associated with the release of such technologies.

bioccontainment↗
DOE OSTI2021

SubTap, a Versatile 3D Printed Platform for Eavesdropping on Extracellular Interactions

Improvements in experimental techniques and instrumentation have led to the discovery that the microbiome plays an essential role in human and environmental health. Nevertheless, there remain major impediments to conducting large-scale interrogations of the microbiome in a high-throughput manner, particularly in the field of exometabolomics.

3D printing↗
DOE OSTI2023

Drivers of stability and transience in composition-functioning links during serial propagation of litter-decomposing microbial communities

ABSTRACT Biotic factors that influence the temporal stability of microbial community functioning are an emerging research focus for the control of natural and engineered systems. The discovery of common features within community ensembles that differ in functional stability over time is a starting point to explore biotic factors. We serially propagated a suite of soil microbial communities through five generations of 28-day microcosm incubations to examine microbial community compositional and functional stability during plant litter decomposition. Using dissolved organic carbon (DOC) abundance as a target function, we hypothesized that microbial diversity, compositional stability, and associated changes in interactions would explain the relative stability of the ecosystem function between generations. Communities with initially high DOC abundance tended to converge towards a “low DOC” phenotype within two generations, but across all microcosms, functional stability between generations was highly variable. By splitting communities into two cohorts based on their relative DOC functional stability, we found that compositional shifts, diversity, and interaction network complexity were associated with the stability of DOC abundance between generations. Further, our results showed that legacy effects were important in determining compositional and functional outcomes, and we identified taxa associated with high DOC abundance. In the context of litter decomposition, achieving functionally stable communities is required to utilize soil microbiomes to increase DOC abundance and long-term terrestrial DOC sequestration as one solution to reduce atmospheric carbon dioxide concentrations. Identifying factors that stabilize function for a community of interest may improve the success of microbiome engineering applications. IMPORTANCE Microbial community functioning can be highly dynamic over time. Identifying and understanding biotic factors that control functional stability is of significant interest for natural and engineered communities alike. Using plant litter–decomposing communities as a model system, this study examined the stability of ecosystem function over time following repeated community transfers. By identifying microbial community features that are associated with stable ecosystem functions, microbial communities can be manipulated in ways that promote the consistency and reliability of the desired function, improving outcomes and increasing the utility of microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Application of quasimetagenomics methods to define microbial diversity and subtype Listeria monocytogenes in dairy and seafood production facilities

Microorganisms frequently colonize surfaces within food production facilities. Detection of Listeria monocytogenes in this setting relies on culture-dependent methods, but the complex dynamics of bacterial interactions within these environments and their impact on pathogen detection remain largely unexplored. To address this challenge, we applied both 16S rRNA and shotgun quasimetagenomic (enriched microbiome) sequencing of swab culture enrichments from five seafood and seven dairy production environments. Utilizing 16S rRNA amplicon sequencing, we observed variability between 355 samples taken from these 12 production facilities and a distinctive microbiome for each environment. With shotgun quasimetagenomic sequencing, we were able to assemble L. monocytogenes metagenome-assembled genomes (MAGs) from 28 of the 32 culture-positive samples. We compared these MAGs to their corresponding whole-genome sequencing assemblies, which resulted in two polyphyletic clades consisting of L. monocytogenes lineages I and II with 13,195 and 25,556 single-nucleotide polymorphism sites, respectively. The remaining four MAGs did not produce sufficient genome coverage. To understand and establish limits for pathogen detection and subtyping using shotgun quasimetagenomics, these same data sets were downsampled in slilico to produce a titration series of abundances of L. monocytogenes and analyzed. Pathogen detection was achieved for all downsampled data sets, even those with only 3× genome coverage. This study contributes to the understanding of microbial diversity within food production environments and presents insights into the level of genome coverage needed in a metagenome sequencing data set to detect, subtype, and source track a foodborne pathogen.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

The short chain fatty acid receptor, FFA2, contributes to gestational glucose homeostasis

The structure of the human gastrointestinal microbiota can change during pregnancy, which may influence gestational metabolism; however, a mechanism of action remains unclear. Here we observed that in wild-type (WT) mice the relative abundance of Actinobacteria and Bacteroidetes increased during pregnancy. Along with these changes, short-chain fatty acids (SCFAs), which are mainly produced through gut microbiota fermentation, significantly changed in both the cecum and peripheral blood throughout gestation in these mice. SCFAs are recognized by G protein-coupled receptors (GPCRs) such as free fatty acid receptor-2 (FFA2), and we have previously demonstrated that the fatty acid receptor-2 gene ( Ffar2 ) expression is higher in pancreatic islets during pregnancy. Using female Ffar2 -/- mice, we explored the physiological relevance of signaling through this GPCR and found that Ffar2-deficient female mice developed fasting hyperglycemia and impaired glucose tolerance in the setting of impaired insulin secretion compared with WT mice during, but not before, pregnancy. Insulin tolerance tests were similar in Ffar2 -/- and WT mice before and during pregnancy. Next, we examined the role of FFA2 in gestational β-cell mass, observing that Ffar2 -/- mice had diminished gestational expansion of β-cells during pregnancy. Interestingly, mouse genotype had no significant impact on the composition of the gut microbiome, but did affect the observed SCFA profiles, suggesting a functional difference in the microbiota. Altogether, these results suggest a potential link between increased Ffar2 expression in islets and the alteration of circulating SCFA levels, possibly explaining how changes in the gut microbiome contribute to gestational glucose homeostasis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Gut Microbial Alterations Associated With Protection From Autoimmune Uveitis

The bacteria that live normally in our intestinal tract, or the gut microbiota contribute to the pathogenesis of extra intestinal autoimmune disease via their ability to dynamically educate the immune system. For example, in a mouse model of relapsing, remitting multiple sclerosis (MS), experimental autoimmune encephalomyelitis or EAE, several studies demonstrated that commensal microorganisms are essential in causing clinical disease activity. Interestingly, MS patients have a distinct gut microbiota to healthy controls. Several studies have also illustrated the importance of the gut microbiome in the development of other diseases, including Type 1 diabetes, metabolic syndrome, rheumatoid arthritis, and ankylosing spondylitis. Furthermore, HLA=B27 transgenic rats, which develop spontaneous spondyloarthropathy analogous to patients who have ankylosing spondylitis, associated with uveitis in humans, do not develop intestinal or peripheral join inflammation when raised in a germ-free environment. Our group has shown that HLA-B27 transgenic rats have an altered intestinal microbiota compared to healthy control rats. Given the similarities between the central nervous system (CNS) and the retina, as well as co-expression of potentially immunogenic self-antigens from the CNS and joint in the eye, we hypothesized that modulating the gut microbiome can result in amelioration of autoimmune uveitis. Although uveitis is a heterogeneous collection of diseases, in general immune-mediated, non-infectious, uveitis is thought to be due to a combination of genetic and environmental factors. It arises from an imbalance between the regulatory and effector arms of the immune system, result in an inappropriate immune reaction at an otherwise immune-privileged tissue site, the eye. Th1 and Th17 T lymphocytes are examples of effector immune cell subsets that my contribute to inflammatory disease of the eye, whereas regulatory T cells (Tregs) are an example of a regulatory immune cell subset that is typically required to downregulate an immune response to prevent uncontrolled disease. Experimental autoimmune uveitis (EAU) is a very robust, widely use model of T lymphoocyte mediated uveitis that can be induced in a certain strains of mice (e.g. B10.RIII) by immunizing these animals with a specific retinal antigen, interphotoreceptor binding protein (IRBP), but requires co-administration of an adjuvant containing killed Mycobacterium antigen. Lastly, this model of inducible uveitis is analogous to the EAE model of demyelinating disease mentioned above. EAU is a thought to be predominantly Th1 and Th17 mediated.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Metaproteomics reveals insights into microbial structure, interactions, and dynamic regulation in defined communities as they respond to environmental disturbance

Abstract Background Microbe-microbe interactions between members of the plant rhizosphere are important but remain poorly understood. A more comprehensive understanding of the molecular mechanisms used by microbes to cooperate, compete, and persist has been challenging because of the complexity of natural ecosystems and the limited control over environmental factors. One strategy to address this challenge relies on studying complexity in a progressive manner, by first building a detailed understanding of relatively simple subsets of the community and then achieving high predictive power through combining different building blocks (e.g., hosts, community members) for different environments. Herein, we coupled this reductionist approach with high-resolution mass spectrometry-based metaproteomics to study molecular mechanisms driving community assembly, adaptation, and functionality for a defined community of ten taxonomically diverse bacterial members of Populus deltoides rhizosphere co-cultured either in a complex or defined medium. Results Metaproteomics showed this defined community assembled into distinct microbiomes based on growth media that eventually exhibit composition and functional stability over time. The community grown in two different media showed variation in composition, yet both were dominated by only a few microbial strains. Proteome-wide interrogation provided detailed insights into the functional behavior of each dominant member as they adjust to changing community compositions and environments. The emergence and persistence of select microbes in these communities were driven by specialization in strategies including motility, antibiotic production, altered metabolism, and dormancy. Protein-level interrogation identified post-translational modifications that provided additional insights into regulatory mechanisms influencing microbial adaptation in the changing environments. Conclusions This study provides high-resolution proteome-level insights into our understanding of microbe-microbe interactions and highlights specialized biological processes carried out by specific members of assembled microbiomes to compete and persist in changing environmental conditions. Emergent properties observed in these lower complexity communities can then be re-evaluated as more complex systems are studied and, when a particular property becomes less relevant, higher-order interactions can be identified.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Identification of carbohydrate gene clusters obtained from in vitro fermentations as predictive biomarkers of prebiotic responses

Prebiotic fibers are non-digestible substrates that modulate the gut microbiome by promoting expansion of microbes having the genetic and physiological potential to utilize those molecules. Although several prebiotic substrates have been consistently shown to provide health benefits in human clinical trials, responder and non-responder phenotypes are often reported. These observations had led to interest in identifying, a priori, prebiotic responders and non-responders as a basis for personalized nutrition. In this study, we conducted in vitro fecal enrichments and applied shotgun metagenomics and machine learning tools to identify microbial gene signatures from adult subjects that could be used to predict prebiotic responders and non-responders. Using short chain fatty acids as a targeted response, we identified genetic features, consisting of carbohydrate active enzymes, transcription factors and sugar transporters, from metagenomic sequencing of in vitro fermentations for three prebiotic substrates: xylooligosacharides, fructooligosacharides, and inulin. A machine learning approach was then used to select substrate-specific gene signatures as predictive features. These features were found to be predictive for XOS responders with respect to SCFA production in an in vivo trial. Our results confirm the bifidogenic effect of commonly used prebiotic substrates along with inter-individual microbial responses towards these substrates. We successfully trained classifiers for the prediction of prebiotic responders towards XOS and inulin with robust accuracy (≥ AUC 0.9) and demonstrated its utility in a human feeding trial. Overall, the findings from this study highlight the practical implementation of pre-intervention targeted profiling of individual microbiomes to stratify responders and non-responders.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Athletic equipment microbiota are shaped by interactions with human skin

Background: Americans spend the vast majority of their lives in built environments. Even traditionally outdoor pursuits, such as exercising, are often now performed indoors. Bacteria that colonize these indoor ecosystems are primarily derived from the human microbiome. The modes of human interaction with indoor surfaces and the physical conditions associated with each surface type determine the steady-state ecology of the microbial community. Results: Bacterial assemblages associated with different surfaces in three athletic facilities, including floors, mats, benches, free weights, and elliptical handles, were sampled every other hour (8 am to 6 pm) for 2 days. Surface and equipment type had a stronger influence on bacterial community composition than the facility in which they were housed. Surfaces that were primarily in contact with human skin exhibited highly dynamic bacterial community composition and non-random co-occurrence patterns, suggesting that different host microbiomes—shaped by selective forces—were being deposited on these surfaces through time. Bacterial assemblages found on the floors and mats changed less over time, and species co-occurrence patterns appeared random, suggesting more neutral community assembly. Conclusions: These longitudinal patterns highlight the dramatic turnover of microbial communities on surfaces in regular contact with human skin. By uncovering these longitudinal patterns, this study promotes a better understanding of microbe-human interactions within the built environment.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

A comparison of methods used to unveil the genetic and metabolic pool in the built environment

BACKGROUND:A majority of indoor residential microbes originate from humans, pets, and outdoor air and are not adapted to the built environment (BE). Consequently, a large portion of the microbes identified by DNA-based methods are either dead or metabolically inactive. Although many exceptions have been noted, the ribosomal RNA fraction of the sample is more likely to represent either viable or metabolically active cells. We examined methodological variations in sample processing using a defined, mock BE microbial community to better understand the scope of technique-based vs. biological-based differences in both ribosomal transcript (rRNA) and gene (DNA) sequence community analysis. Based on in vitro tests, a protocol was adopted for the analysis of the genetic and metabolic pool (DNA vs. rRNA) of air and surface microbiomes within a residential setting. RESULTS:We observed differences in DNA/RNA co-extraction efficiency for individual microbes, but overall, a greater recovery of rRNA using FastPrep (> 50%). Samples stored with various preservation methods at - 80°C experienced a rapid decline in nucleic acid recovery starting within the first week, although post-extraction rRNA had no significant degradation when treated with RNAStable. We recommend that co-extraction samples be processed as quickly as possible after collection. The in vivo analysis revealed significant differences in the two components (genetic and metabolic pool) in terms of taxonomy, community structure, and microbial association networks. Rare taxa present in the genetic pool showed higher metabolic potential (RNA:DNA ratio), whereas commonly detected taxa of outdoor origins based on DNA sequencing, especially taxa of the Sphingomonadales order, were present in lower relative abundances in the viable community. CONCLUSIONS:Although methodological variations in sample preparations are high, large differences between the DNA and RNA fractions of the total microbial community demonstrate that direct examination of rRNA isolated from a residential BE microbiome has the potential to identify the more likely viable or active portion of the microbial community. In an environment that has primarily dead and metabolically inactive cells, we suggest that the rRNA fraction of BE samples is capable of providing a more ecologically relevant insight into the factors that drive indoor microbial community dynamics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Protist diversity and community complexity in the rhizosphere of switchgrass are dynamic as plants develop

Abstract Background Despite their widespread distribution and ecological importance, protists remain one of the least understood components of the soil and rhizosphere microbiome. Knowledge of the roles that protists play in stimulating organic matter decomposition and shaping microbiome dynamics continues to grow, but there remains a need to understand the extent to which biological and environmental factors mediate protist community assembly and dynamics. We hypothesize that protists communities are filtered by the influence of plants on their rhizosphere biological and physicochemical environment, resulting in patterns of protist diversity and composition that mirror previously observed diversity and successional dynamics in rhizosphere bacterial communities. Results We analyzed protist communities associated with the rhizosphere and bulk soil of switchgrass (SG) plants ( Panicum virgatum ) at different phenological stages, grown in two marginal soils as part of a large-scale field experiment. Our results reveal that the diversity of protists is lower in rhizosphere than bulk soils, and that temporal variations depend on soil properties but are less pronounced in rhizosphere soil. Patterns of significantly prevalent protists groups in the rhizosphere suggest that most protists play varied ecological roles across plant growth stages and that some plant pathogenic protists and protists with omnivorous diets reoccur over time in the rhizosphere. We found that protist co-occurrence network dynamics are more complex in the rhizosphere compared to bulk soil. A phylogenetic bin-based null model analysis showed that protists’ community assembly in our study sites is mainly controlled by homogenous selection and dispersal limitation, with stronger selection in rhizosphere than bulk soil as SG grew and senesced. Conclusions We demonstrate that environmental filtering is a dominant determinant of overall protist community properties and that at the rhizosphere level, plant control on the physical and biological environment is a critical driver of protist community composition and dynamics. Since protists are key contributors to plant nutrient availability and bacterial community composition and abundance, mapping and understanding their patterns in rhizosphere soil is foundational to understanding the ecology of the root-microbe-soil system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Metapangenomics reveals depth-dependent shifts in metabolic potential for the ubiquitous marine bacterial SAR324 lineage

Abstract Background Oceanic microbiomes play a pivotal role in the global carbon cycle and are central to the transformation and recycling of carbon and energy in the ocean’s interior. SAR324 is a ubiquitous but poorly understood uncultivated clade of Deltaproteobacteria that inhabits the entire water column, from ocean surface waters to its deep interior. Although some progress has been made in elucidating potential metabolic traits of SAR324 in the dark ocean, very little is known about the ecology and the metabolic capabilities of this group in the euphotic and twilight zones. To investigate the comparative genomics, ecology, and physiological potential of the SAR324 clade, we examined the distribution and variability of key genomic features and metabolic pathways in this group from surface waters to the abyss in the North Pacific Subtropical Gyre, one of the largest biomes on Earth. Results We leveraged a pangenomic ecological approach, combining spatio-temporally resolved single-amplified genome, metagenomic, and metatranscriptomic datasets. The data revealed substantial genomic diversity throughout the SAR324 clade, with distinct depth and temporal distributions that clearly differentiated ecotypes. Phylogenomic subclade delineation, environmental distributions, genomic feature similarities, and metabolic capacities revealed strong congruence. The four SAR324 ecotypes delineated in this study revealed striking divergence from one another with respect to their habitat-specific metabolic potentials. The ecotypes living in the dark or twilight oceans shared genomic features and metabolic capabilities consistent with a sulfur-based chemolithoautotrophic lifestyle. In contrast, those inhabiting the sunlit ocean displayed higher plasticity energy-related metabolic pathways, supporting a presumptive photoheterotrophic lifestyle. In epipelagic SAR324 ecotypes, we observed the presence of two types of proton-pumping rhodopsins, as well as genomic, transcriptomic, and ecological evidence for active photoheterotrophy, based on xanthorhodopsin-like light-harvesting proteins. Conclusions Combining pangenomic and both metagenomic and metatranscriptomic profiling revealed a striking divergence in the vertical distribution, genomic composition, metabolic potential, and predicted lifestyle strategies of geographically co-located members of the SAR324 bacterial clade. The results highlight the utility of metapangenomic approaches employed across environmental gradients, to decipher the properties and variation in function and ecological traits of specific phylogenetic clades within complex microbiomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

METABOLIC: high-throughput profiling of microbial genomes for functional traits, metabolism, biogeochemistry, and community-scale functional networks

Background Advances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent; however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and microbial contributions to biogeochemical cycling. Results We present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry studies using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the microbiome, potential microbial metabolic handoffs and metabolite exchange, reconstruction of functional networks, and determination of microbial contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, community-scale microbial functional networks using a newly defined metric “MW-score” (metabolic weight score), and metabolic Sankey diagrams. METABOLIC takes ~ 3 h with 40 CPU threads to process ~ 100 genomes and corresponding metagenomic reads within which the most compute-demanding part of hmmsearch takes ~ 45 min, while it takes ~ 5 h to complete hmmsearch for ~ 3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut. Conclusion METABOLIC enables the consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available under GPLv3 at https://github.com/AnantharamanLab/METABOLIC.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Marine DNA methylation patterns are associated with microbial community composition and inform virus-host dynamics

Background: DNA methylation in prokaryotes is involved in many different cellular processes including cell cycle regulation and defense against viruses. To date, most prokaryotic methylation systems have been studied in culturable microorganisms, resulting in a limited understanding of DNA methylation from a microbial ecology perspective. Here, we analyze the distribution patterns of several microbial epigenetics marks in the ocean microbiome through genome-centric metagenomics across all domains of life. Results: We reconstructed 15,056 viral, 252 prokaryotic, 56 giant viral, and 6 eukaryotic metagenome-assembled genomes from northwest Pacific Ocean seawater samples using short- and long-read sequencing approaches. These metagenome-derived genomes mostly represented novel taxa, and recruited a majority of reads. Thanks to single-molecule real-time (SMRT) sequencing technology, base modification could also be detected for these genomes. This showed that DNA methylation can readily be detected across dominant oceanic bacterial, archaeal, and viral populations, and microbial epigenetic changes correlate with population differentiation. Furthermore, our genome-wide epigenetic analysis of Pelagibacter suggests that GANTC, a DNA methyltransferase target motif, is related to the cell cycle and is affected by environmental conditions. Yet, the presence of this motif also partitions the phylogeny of the Pelagibacter phages, possibly hinting at a competitive co-evolutionary history and multiple effects of a single methylation mark. Conclusions: Overall, this study elucidates that DNA methylation patterns are associated with ecological changes and virus-host dynamics in the ocean microbiome.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2012

Inferring Correlation Networks from Genomic Survey Data

High-throughput sequencing based techniques, such as 16S rRNA gene profiling, have the potential to elucidate the complex inner workings of natural microbial communities - be they from the world's oceans or the human gut. A key step in exploring such data is the identification of dependencies between members of these communities, which is commonly achieved by correlation analysis. However, it has been known since the days of Karl Pearson that the analysis of the type of data generated by such techniques (referred to as compositional data) can produce unreliable results since the observed data take the form of relative fractions of genes or species, rather than their absolute abundances. Using simulated and real data from the Human Microbiome Project, we show that such compositional effects can be widespread and severe: in some real data sets many of the correlations among taxa can be artifactual, and true correlations may even appear with opposite sign. Additionally, we show that community diversity is the key factor that modulates the acuteness of such compositional effects, and develop a new approach, called SparCC (available at https://bitbucket.org/yonatanf/sparcc), which is capable of estimating correlation values from compositional data. To illustrate a potential application of SparCC, we infer a rich ecological network connecting hundreds of interacting species across 18 sites on the human body. Using the SparCC network as a reference, we estimated that the standard approach yields 3 spurious species-species interactions for each true interaction and misses 60% of the true interactions in the human microbiome data, and, as predicted, most of the erroneous links are found in the samples with the lowest diversity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Predicting drug-metagenome interactions: Variation in the microbial β-glucuronidase level in the human gut metagenomes

Characterizing the gut microbiota in terms of their capacity to interfere with drug metabolism is necessary to achieve drug efficacy and safety. Although examples of drug-microbiome interactions are well-documented, little has been reported about a computational pipeline for systematically identifying and characterizing bacterial enzymes that process particular classes of drugs. The goal of our study is to develop a computational approach that compiles drugs whose metabolism may be influenced by a particular class of microbial enzymes and that quantifies the variability in the collective level of those enzymes among individuals. The present paper describes this approach, with microbial β-glucuronidases as an example, which break down drug-glucuronide conjugates and reactivate the drugs or their metabolites. We identified 100 medications that may be metabolized by β-glucuronidases from the gut microbiome. These medications included morphine, estrogen, ibuprofen, midazolam, and their structural analogues. The analysis of metagenomic data available through the Sequence Read Archive (SRA) showed that the level of β-glucuronidase in the gut metagenomes was higher in males than in females, which provides a potential explanation for the sex-based differences in efficacy and toxicity for several drugs, reported in previous studies. Our analysis also showed that infant gut metagenomes at birth and 12 months of age have higher levels of β-glucuronidase than the metagenomes of their mothers and the implication of this observed variability was discussed in the context of breastfeeding as well as infant hyperbilirubinemia. Overall, despite important limitations discussed in this paper, our analysis provided useful insights on the role of the human gut metagenome in the variability in drug response among individuals. Importantly, this approach exploits drug and metagenome data available in public databases as well as open-source cheminformatics and bioinformatics tools to predict drug-metagenome interactions.

59 BASIC BIOLOGICAL SCIENCES↗