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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Effects of soluble electron shuttles on microbial iron reduction and methanogenesis

In many aquatic and terrestrial ecosystems, iron (Fe) reduction by microorganisms is a key part of biogeochemical cycling and energy flux. The presence of redox-active electron shuttles in the environment potentially enables a phylogenetically diverse group of microbes to use insoluble iron as a terminal electron acceptor. We investigated the impact that different electron shuttles had on respiration, microbial physiology, and microbial ecology. We tested eight different electron shuttles, seven quinones and riboflavin, with redox potentials between 0.217 and −0.340 V. Fe(III) reduction coupled with acetate oxidation was observed with all shuttles. Once Fe(III) reduction began to plateau, a rapid increase in acetate consumption was observed and coincided with the onset of methane production, except in the incubations with the shuttle 9,10-anthraquinone-2-carboxylic acid (AQC). The rates of iron reduction, acetate consumption, methanogenesis, and the microbial communities varied significantly across the different shuttles independent of redox potential. In general, shuttles appeared to reduce the overall diversity of the community compared to no shuttle controls, but certain shuttles were exceptions to this trend. Geobacteraceae were the predominant taxonomic family in all enrichments except in the presence of AQC or 1,2-dihydroxyanthraquinone (AQZ), but each shuttle enriched a unique community significantly different from the no shuttle control conditions. This suggests that the presence of different redox-active electron shuttles can have a large influence on the microbial ecology and total carbon flux in the environment.

Anaerobic Redox Reactions↗
DOE OSTI2023

Variation in Sphingomonas traits across habitats and phylogenetic clades

Whether microbes show habitat preferences is a fundamental question in microbial ecology. If different microbial lineages have distinct traits, those lineages may occur more frequently in habitats where their traits are advantageous. Sphingomonas is an ideal bacterial clade in which to investigate how habitat preference relates to traits because these bacteria inhabit diverse environments and hosts. Here we downloaded 440 publicly available Sphingomonas genomes, assigned them to habitats based on isolation source, and examined their phylogenetic relationships. We sought to address whether: (1) there is a relationship between Sphingomonas habitat and phylogeny, and (2) whether there is a phylogenetic correlation between key, genome-based traits and habitat preference. We hypothesized that Sphingomonas strains from similar habitats would cluster together in phylogenetic clades, and key traits that improve fitness in specific environments should correlate with habitat. Genome-based traits were categorized into the Y-A-S trait-based framework for high growth yield, resource acquisition, and stress tolerance. We selected 252 high quality genomes and constructed a phylogenetic tree with 12 well-defined clades based on an alignment of 404 core genes. Sphingomonas strains from the same habitat clustered together within the same clades, and strains within clades shared similar clusters of accessory genes. Additionally, key genome-based trait frequencies varied across habitats. We conclude that Sphingomonas gene content reflects habitat preference. This knowledge of how environment and host relate to phylogeny may also help with future functional predictions about Sphingomonas and facilitate applications in bioremediation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Innovative Biomonitoring and Remediation of Heavy Metals Using Phytotechnologies at the Savannah River Site (SRS) Coal Combustion Product (CCP) Impoundment Sites

The Savannah River Site (SRS) contains legacy coal combustion product (CCP) impoundments that are impacted by elevated concentrations of heavy metals and radionuclides, posing long-term risks to soil health, ecosystem functioning, and environmental sustainability. Traditional environmental monitoring approaches rely primarily on chemical analyses to quantify contaminant concentrations but often provide limited information regarding biological responses or ecosystem recovery. This project addressed these limitations by integrating environmental chemistry, microbial ecology, artificial intelligence (AI), and bioremediation into a comprehensive framework for environmental diagnostics and restoration of contaminated soils. The overarching goal of this collaborative project between Florida A&M University (FAMU) and the University of Georgia's Savannah River Ecology Laboratory (SREL) was to develop innovative biomonitoring and remediation strategies for heavy metal-contaminated CCP impoundment sites at the Savannah River Site. Specifically, the project sought to (i) characterize heavy metal contamination, (ii) determine microbial responses to contamination, (iii) isolate indigenous heavy metal-resistant microorganisms for remediation applications, (iv) develop a microbial ecological health index using machine learning, and (v) optimize fungal-mediated bioremediation using artificial intelligence.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Comparison of metagenomes from fermentation of various agroindustrial residues suggests a common model of community organization

The liquid residue resulting from various agroindustrial processes is both rich in organic material and an attractive source to produce a variety of chemicals. Using microbial communities to produce chemicals from these liquid residues is an active area of research, but it is unclear how to deploy microbial communities to produce specific products from the different agroindustrial residues. To address this, we fed anaerobic bioreactors one of several agroindustrial residues (carbohydrate-rich lignocellulosic fermentation conversion residue, xylose, dairy manure hydrolysate, ultra-filtered milk permeate, and thin stillage from a starch bioethanol plant) and inoculated them with a microbial community from an acid-phase digester operated at the wastewater treatment plant in Madison, WI, United States. The bioreactors were monitored over a period of months and sampled to assess microbial community composition and extracellular fermentation products. We obtained metagenome assembled genomes (MAGs) from the microbial communities in each bioreactor and performed comparative genomic analyses to identify common microorganisms, as well as any community members that were unique to each reactor. Collectively, we obtained a dataset of 217 non-redundant MAGs from these bioreactors. This metagenome assembled genome dataset was used to evaluate whether a specific microbial ecology model in which medium chain fatty acids (MCFAs) are simultaneously produced from intermediate products (e.g., lactic acid) and carbohydrates could be applicable to all fermentation systems, regardless of the feedstock. MAGs were classified using a multiclass classification machine learning algorithm into three groups, organisms fermenting the carbohydrates to intermediate products, organisms utilizing the intermediate products to produce MCFAs, and organisms producing MCFAs directly from carbohydrates. This analysis revealed common biological functions among the microbial communities in different bioreactors, and although different microorganisms were enriched depending on the agroindustrial residue tested, the results supported the conclusion that the microbial ecology model tested was appropriate to explain the MCFA production potential from all agricultural residues.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Translating macroecological models to predict microbial establishment probability in an agricultural inoculant introduction

The use of potentially beneficial microorganisms in agriculture (microbial inoculants) has rapidly accelerated in recent years. For microbial inoculants to be effective as agricultural tools, these organisms must be able to survive and persist in novel environments while not destabilizing the resident community or spilling over into adjacent natural ecosystems. Despite the importance of propagule pressure to species introductions, few tools exist in microbial ecology to predict the outcomes of agricultural microbial introductions. Here, we adapt a macroecological propagule pressure model to a microbial scale and present an experimental approach for testing the role of propagule pressure in microbial inoculant introductions. We experimentally determined the risk-release relationship for an IAA-expressing Pseudomonas simiae inoculant in a model monocot system. We then used this relationship to simulate establishment outcomes under a range of application frequencies (propagule number) and inoculant concentrations (propagule size). Our simulations show that repeated inoculant applications may increase establishment, even when increased inoculant concentration does not alter establishment probabilities. Applying ecological modeling approaches like those presented here to microbial inoculants may aid their sustainable use and provide a monitoring tool for microbial inoculants.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Metagenome-assembled genomes provide insight into the metabolic potential during early production of Hydraulic Fracturing Test Site 2 in the Delaware Basin

Demand for natural gas continues to climb in the United States, having reached a record monthly high of 104.9 billion cubic feet per day (Bcf/d) in November 2023. Hydraulic fracturing, a technique used to extract natural gas and oil from deep underground reservoirs, involves injecting large volumes of fluid, proppant, and chemical additives into shale units. This is followed by a “shut-in” period, during which the fracture fluid remains pressurized in the well for several weeks. The microbial processes that occur within the reservoir during this shut-in period are not well understood; yet, these reactions may significantly impact the structural integrity and overall recovery of oil and gas from the well. To shed light on this critical phase, we conducted an analysis of both pre-shut-in material alongside production fluid collected throughout the initial production phase at the Hydraulic Fracturing Test Site 2 (HFTS 2) located in the prolific Wolfcamp formation within the Permian Delaware Basin of west Texas, USA. Specifically, we aimed to assess the microbial ecology and functional potential of the microbial community during this crucial time frame. Prior analysis of 16S rRNA sequencing data through the first 35 days of production revealed a strong selection for a Clostridia species corresponding to a significant decrease in microbial diversity. Here, we performed a metagenomic analysis of produced water sampled on Day 33 of production. This analysis yielded three high-quality metagenome-assembled genomes (MAGs), one of which was a Clostridia draft genome closely related to the recently classified Petromonas tenebris. This draft genome likely represents the dominant Clostridia species observed in our 16S rRNA profile. Annotation of the MAGs revealed the presence of genes involved in critical metabolic processes, including thiosulfate reduction, mixed acid fermentation, and biofilm formation. These findings suggest that this microbial community has the potential to contribute to well souring, biocorrosion, and biofouling within the reservoir. Our research provides unique insights into the early stages of production in one of the most prolific unconventional plays in the United States, with important implications for well management and energy recovery.

natural gas↗
DOE OSTI2023

Soil microbiome engineering for sustainability in a changing environment

Recent advances in microbial ecology and synthetic biology have the potential to mitigate damage caused by anthropogenic activities that are deleteriously impacting Earth’s soil ecosystems. Here, we discuss challenges and opportunities for harnessing natural and synthetic soil microbial communities, focusing on plant growth promotion under different scenarios. We explore current needs for microbial solutions in soil ecosystems, how these solutions are being developed and applied, and the potential for new biotechnology breakthroughs to tailor and target microbial products for specific applications. We highlight several scientific and technological advances in soil microbiome engineering, including characterization of microbes that impact soil ecosystems, directing how microbes assemble to interact in soil environments, and the developing suite of gene-engineering approaches. This Review underscores the need for an interdisciplinary approach to understand the composition, dynamics and deployment of beneficial soil microbiomes to drive efforts to mitigate or reverse environmental damage by restoring and protecting healthy soil ecosystems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Functional Traits Resolve Mechanisms Governing the Assembly and Distribution of Nitrogen-Cycling Microbial Communities in the Global Ocean

Microorganisms drive much of the marine nitrogen (N) cycle, which jointly controls the primary production in the global ocean. However, our understanding of the microbial communities driving the global ocean N cycle remains fragmented. Focusing on “who is doing what, where, and how?”, this study draws a clear picture describing the global biogeography of marine N-cycling microbial communities by utilizing the Tara Oceans shotgun metagenomes. The marine N-cycling communities are highly variable taxonomically but relatively even at the functional trait level, showing clear functional redundancy properties. The functional traits and taxonomic groups are shaped by the same set of geo-environmental factors, among which, depth is the major factor impacting marine N-cycling communities, differentiating mesopelagic from epipelagic communities. Latitudinal diversity gradients and distance-decay relationships are observed for taxonomic groups, but rarely or weakly for functional traits. The composition of functional traits is strongly deterministic as revealed by null model analysis, while a higher degree of stochasticity is observed for taxonomic composition. Integrating multiple lines of evidence, in addition to drawing a biogeographic picture of marine N-cycling communities, this study also demonstrated an essential microbial ecological theory—determinism governs the assembly of microbial communities performing essential biogeochemical processes; the environment selects functional traits rather than taxonomic groups; functional redundancy underlies stochastic taxonomic community assembly.

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 OSTI2025

Meta Biome: a multiscale model integrating agent-based and metabolic networks to reveal spatial regulation in gut mucosal microbial communities

ABSTRACT Mucosal microbial communities (MMCs) are complex ecosystems near the mucosal layers of the gut essential for maintaining health and modulating disease states. Despite advances in high-throughput omics technologies, current methodologies struggle to capture the dynamic metabolic interactions and spatiotemporal variations within MMCs. In this work, we presentMetaBiome, a multiscale model integrating agent-based modeling (ABM), finite volume methods, and constraint-based models to explore the metabolic interactions within these communities. Integrating ABM allows for the detailed representation of individual microbial agents each governed by rules that dictate cell growth, division, and interactions with their surroundings. Through a layered approach—encompassing microenvironmental conditions, agent information, and metabolic pathways—we simulated different communities to showcase the potential of the model. Using ourin-silicoplatform, we explored the dynamics and spatiotemporal patterns of MMCs in the proximal small intestine and the cecum, simulating the physiological conditions of the two gut regions. Our findings revealed how specific microbes adapt their metabolic processes based on substrate availability and local environmental conditions, shedding light on spatial metabolite regulation and informing targeted therapies for localized gut diseases.MetaBiome provides a detailed representation of microbial agents and their interactions, surpassing the limitations of traditional grid-based systems. This work marks a significant advancement in microbial ecology, as it offers new insights into predicting and analyzing microbial communities. IMPORTANCE Our study presents a novel multiscale model that combines agent-based modeling, finite volume methods, and genome-scale metabolic models to simulate the complex dynamics of mucosal microbial communities in the gut. This integrated approach allows us to capture spatial and temporal variations in microbial interactions and metabolism that are difficult to study experimentally. Key findings from our model include the following: (i) prediction of metabolic cross-feeding and spatial organization in multi-species communities, (ii) insights into how oxygen gradients and nutrient availability shape community composition in different gut regions, and (iii) identification of spatiallyregulated metabolic pathways and enzymes inE. coli. We believe this work represents a significant advance in computational modeling of microbial communities and provides new insights into the spatial regulation of gut microbiome metabolism. The multiscale modeling approach we have developed could be broadly applicable for studying other complex microbial ecosystems.

Microbiology↗
DOE OSTI2023

Synergistic interactions between anammox and dissimilatory nitrate reducing bacteria sustains reactor performance across variable nitrogen loading ratios

Anaerobic ammonium oxidizing (anammox) bacteria are utilized for high efficiency nitrogen removal from nitrogen-laden sidestreams in wastewater treatment plants. The anammox bacteria form a variety of competitive and mutualistic interactions with heterotrophic bacteria that often employ denitrification or dissimilatory nitrate reduction to ammonium (DNRA) for energy generation. These interactions can be heavily influenced by the influent ratio of ammonium to nitrite, NH 4 + :NO 2 - , where deviations from the widely acknowledged stoichiometric ratio (1:1.32) have been demonstrated to have deleterious effects on anammox efficiency. Thus, it is important to understand how variable NH 4 + :NO 2 - ratios impact the microbial ecology of anammox reactors. We observed the response of the microbial community in a lab scale anammox membrane bioreactor (MBR) to changes in the influent NH 4 + :NO 2 - ratio using both 16S rRNA gene and shotgun metagenomic sequencing. Ammonium removal efficiency decreased from 99.77 ± 0.04% when the ratio was 1:1.32 (prior to day 89) to 90.85 ± 0.29% when the ratio was decreased to 1:1.1 (day 89–202) and 90.14 ± 0.09% when the ratio was changed to 1:1.13 (day 169–200). Over this same timespan, the overall nitrogen removal efficiency (NRE) remained relatively unchanged (85.26 ± 0.01% from day 0–89, compared to 85.49 ± 0.01% from day 89–169, and 83.04 ± 0.01% from day 169–200). When the ratio was slightly increased to 1:1.17–1:1.2 (day 202–253), the ammonium removal efficiency increased to 97.28 ± 0.45% and the NRE increased to 88.21 ± 0.01%. Analysis of 16S rRNA gene sequences demonstrated increased relative abundance of taxa belonging to Bacteroidetes, Chloroflexi, and Ignavibacteriae over the course of the experiment. The relative abundance of Planctomycetes, the phylum to which anammox bacteria belong, decreased from 77.19% at the beginning of the experiment to 12.24% by the end of the experiment. Analysis of metagenome assembled genomes (MAGs) indicated increased abundance of bacteria with nrfAH genes used for DNRA after the introduction of lower influent NH 4 + :NO 2 - ratios. The high relative abundance of DNRA bacteria coinciding with sustained bioreactor performance indicates a mutualistic relationship between the anammox and DNRA bacteria. Understanding these interactions could support more robust bioreactor operation at variable nitrogen loading ratios.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

How do soil microbes shape ecosystem biogeochemistry in the context of global change?

Earth system models disagree on the future of global soil carbon C, with projections ranging from losses of 70 Pg to gains of 250 Pg by the year 2100 (Todd-Brown et al., 2014). This disagreement is due, in part, to the high degree of uncertainty in the mechanisms that control soil C, the largest dynamic pool of organic C on Earth. It remains unclear how climate change, rising atmospheric CO2 levels, and other environmental changes will combine to affect global soil C. As key engineers of biogeochemical cycling, microbes play a crucial role in soil C responses to these environmental changes. Yet, the path toward representing microbes in soil models remains uncertain. Furthermore, we address four burning questions relevant for modelling microbial ecological, evolutionary, and biogeochemical processes in soils: (1) What is the role of soil microbes in biogeochemical cycling? (2) Does microbial community composition matter for soil carbon cycling? (3) Which ecological and evolutionary processes contribute to functional changes? (4) How should we model microbial eco-evolutionary mechanisms in soil C models?

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Scale-dependent tipping points of bacterial colonization resistance

The commonly observed stability of natural microbiomes is important for their function, yet the ubiquity of microbiome stability remains enigmatic. The strongest form of stability, colonization resistance, protects residents against invaders and is often associated with specific porous structures, such as skin follicles or intestinal crypts. By systematically probing the colonization of fly gut–derived bacteria in microfluidic pores of varying sizes, we revealed that colonization patterns and invasion rates strongly depend on the pore size. Mathematical modeling shows that bacteria spontaneously tend to organize into a dense colonization-resistant state in pores exceeding a critical size. The scale dependence of stability and resilience could bias ecological filtering in microbiomes and should be considered in the design of microbial ecology experiments.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Yeasts from temperate forests

Yeasts are ubiquitous in temperate forests. While this broad habitat is well-defined, the yeasts inhabiting it and their life cycles, niches, and contributions to ecosystem functioning are less understood. Yeasts are present on nearly all sampled substrates in temperate forests worldwide. They associate with soils, macroorganisms, and other habitats and no doubt contribute to broader ecosystem-wide processes. Researchers have gathered information leading to hypotheses about yeasts' niches and their life cycles based on physiological observations in the laboratory as well as genomic analyses, but the challenge remains to test these hypotheses in the forests themselves. Here, we summarize the habitat and global patterns of yeast diversity, give some information on a handful of well-studied temperate forest yeast genera, discuss the various strategies to isolate forest yeasts, and explain temperate forest yeasts' contributions to biotechnology. Here, we close with a summary of the many future directions and outstanding questions facing researchers in temperate forest yeast ecology. Yeasts present an exciting opportunity to better understand the hidden world of microbial ecology in this threatened and global habitat.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Cytochrome Nanowire XRD

Microbial metabolism plays an important role in the global cycling of carbon, nutrients, and metals. Recent discovery of microorganisms sharing energy using direct electrical connections might represent a prominent strategy by which anaerobic microorganisms interact with the diversity of environments. The purpose of the proposed research is to apply these newly developed principles of electron exchange in microbial communities to the study of biogeochemical cycling in climate and subsurface systems. Previous studies revealed that soil bacteria Geobacter sulfurreducens produce conductive pili nanofilaments that facilitate long-range electron transport to extracellular electron acceptors and other cells. This discovery has already transformed our understanding of the function of microbial communities in diverse environments, making basic contributions to microbial ecology and helping to improve practical applications such as increasing current output of microbial fuel cells and enhancing the conversion of organic waste to methane. Microbial electron exchange via pili may also contribute to methane production in terrestrial environments that are major sources of atmospheric methane. However, the mechanism of electron transport through pili is not well understood. Initial studies have suggested that pili exhibit metallic-like conductivity similar to conducting polymer polyaniline. However, these studies were limited to electrical measurements. X-ray diffraction studies have suggested that aromatic amino acids tyrosine and phenylalanine are closely packed in pili. But these studies used homology modeling to predict the pilus assembly and information about the number of monomers in each pilus assembly unit and their organization are still lacking. The central hypothesis of this proposal is aromatics in pili enable intermolecular electron delocalization due to pi-stacking that can give rise to metallic-like conductivity. By analyzing pili structure using infrared scattering-scanning near field optical microscope (IR s-SNOM) and combining with solution NMR, Focused Ion Beam (FIB and computational capabilities, this work will provide comprehensive understanding of the conduction mechanism from a structure-function perspective. The specific aims are: 1) With infrared scattering scanning near field optical microscope (IR s-SNOM), image the organization and density of pilin monomers and pH-induced conformational changes in a pilus filament. 2) With solution NMR, resolve pH-induced structural changes in the pilin monomer. 3) Using Focused Ion Beam (FIB), draw electrodes on single pili to measure their conductivity. 4) With computational modeling using the NWChem, simulate the effect of environment on the electronic properties of pili as a function of pH. The proposed work will gain the nanoscale insight into the structure of the pili, as the basis for understanding interspecies electrical communications. The improved understanding will be harnessed to accelerate bioenergy production and bioremediation using pili as well as for predictive modeling of carbon cycling in diverse environments to reach the central goals of DOE-BER to develop sustainable energy sources, regulate the contaminants in the subsurface and understand the effects of greenhouse gas emissions on biosphere. The proposed studies will provide design principles for engineering of electrical interactions among these communities by manipulating the amino acid composition of pili. Moreover, these studies will identify the forces that maintain the function of these communities in the face of environmental perturbation. Therefore, these studies will help to address the need "to incorporate process understanding of biogeochemical cycling into a scalable hierarchy of predictive capabilities" specified in EMSL's Science Themes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Diversity and Distribution of Hydrocarbon-Degrading Genes in the Cold Seeps from the Mediterranean and Caspian Seas

Marine cold seeps are unique ecological niches characterized by the emergence of hydrocarbons, including methane, which fosters diverse microbial communities. This study investigates the diversity and distribution of hydrocarbon-degrading genes and organisms in sediments from the Caspian and Mediterranean Seas, utilizing 16S rRNA and metagenomic sequencing to elucidate microbial community structure and functional potential. Our findings reveal distinct differences in hydrocarbon degrading gene profiles between the two seas, with pathways for aerobic and anaerobic hydrocarbon degradation co-existing in sediments from both basins. Aerobic pathways predominate in the surface sediments of the Mediterranean Sea, while anaerobic pathways are favored in the surface sediments of the anoxic Caspian Sea. Additionally, sediment depths significantly influence microbial diversity, with variations in gene abundance and community composition observed at different depths. Aerobic hydrocarbon-degrading genes decrease in diversity with depth in the Mediterranean Sea, whereas the diversity of aerobic hydrocarbon-degrading genes increases with depth in the Caspian Sea. These results enhance our understanding of microbial ecology in cold seep environments and have implications for bioremediation practices targeting hydrocarbon pollutants in marine ecosystems.

Microbiology↗
DOE OSTI2021

Deeplasmid: deep learning accurately separates plasmids from bacterial chromosomes

Plasmids are mobile genetic elements that play a key role in microbial ecology and evolution by mediating horizontal transfer of important genes, such as antimicrobial resistance genes. Many microbial genomes have been sequenced by short read sequencers and have resulted in a mix of contigs that derive from plasmids or chromosomes. New tools that accurately identify plasmids are needed to elucidate new plasmid-borne genes of high biological importance. We have developed Deeplasmid, a deep learning tool for distinguishing plasmids from bacterial chromosomes based on the DNA sequence and its encoded biological data. It requires as input only assembled sequences generated by any sequencing platform and assembly algorithm and its runtime scales linearly with the number of assembled sequences. Deeplasmid achieves an AUC–ROC of over 89%, and it was more accurate than five other plasmid classification methods. Finally, as a proof of concept, we used Deeplasmid to predict new plasmids in the fish pathogen Yersinia ruckeri ATCC 29473 that has no annotated plasmids. Deeplasmid predicted with high reliability that a long assembled contig is part of a plasmid. Using long read sequencing we indeed validated the existence of a 102 kb long plasmid, demonstrating Deeplasmid's ability to detect novel plasmids.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Ontology-Enriched Specifications Enabling Findable, Accessible, Interoperable, and Reusable Marine Metagenomic Datasets in Cyberinfrastructure Systems

Marine microbial ecology requires the systematic comparison of biogeochemical and sequence data to analyze environmental influences on the distribution and variability of microbial communities. With ever-increasing quantities of metagenomic data, there is a growing need to make datasets Findable, Accessible, Interoperable, and Reusable (FAIR) across diverse ecosystems. FAIR data is essential to developing analytical frameworks that integrate microbiological, genomic, ecological, oceanographic, and computational methods. Although community standards defining the minimal metadata required to accompany sequence data exist, they haven’t been consistently used across projects, precluding interoperability. Moreover, these data are not machine-actionable or discoverable by cyberinfrastructure systems. By making ‘omic and physicochemical datasets FAIR to machine systems, we can enable sequence data discovery and reuse based on machine-readable descriptions of environments or physicochemical gradients. In this work, we developed a novel technical specification for dataset encapsulation for the FAIR reuse of marine metagenomic and physicochemical datasets within cyberinfrastructure systems. This includes using Frictionless Data Packages enriched with terminology from environmental and life-science ontologies to annotate measured variables, their units, and the measurement devices used. This approach was implemented in Planet Microbe, a cyberinfrastructure platform and marine metagenomic web-portal. Here, we discuss the data properties built into the specification to make global ocean datasets FAIR within the Planet Microbe portal. We additionally discuss the selection of, and contributions to marine-science ontologies used within the specification. Finally, we use the system to discover data by which to answer various biological questions about environments, physicochemical gradients, and microbial communities in meta-analyses. This work represents a future direction in marine metagenomic research by proposing a specification for FAIR dataset encapsulation that, if adopted within cyberinfrastructure systems, would automate the discovery, exchange, and re-use of data needed to answer broader reaching questions than originally intended.

59 BASIC BIOLOGICAL SCIENCES↗