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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Oral microbiome and mycobiome dynamics in cancer therapy-induced oral mucositis

Cancer therapy-induced oral mucositis is a frequent major oncological problem, secondary to cytotoxicity of chemo-radiation treatment. Oral mucositis commonly occurs 7–10 days after initiation of therapy; it is a dose-limiting side effect causing significant pain, eating difficulty, need for parenteral nutrition and a rise of infections. The pathobiology derives from complex interactions between the epithelial component, inflammation, and the oral microbiome. Our longitudinal study analysed the dynamics of the oral microbiome (bacteria and fungi) in nineteen patients undergoing chemo-radiation therapy for oral and oropharyngeal squamous cell carcinoma as compared to healthy volunteers. The microbiome was characterized in multiple oral sample types using rRNA and ITS sequence amplicons and followed the treatment regimens. Microbial taxonomic diversity and relative abundance may be correlated with disease state, type of treatment and responses. Identification of microbial-host interactions could lead to further therapeutic interventions of mucositis to re-establish normal flora and promote patients’ health. Data presented here could enhance, complement and diversify other studies that link microbiomes to oral disease, prophylactics, treatments, and outcome.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Long-read metagenomics of soil communities reveals phylum-specific secondary metabolite dynamics

Abstract Microbial biosynthetic gene clusters (BGCs) encoding secondary metabolites are thought to impact a plethora of biologically mediated environmental processes, yet their discovery and functional characterization in natural microbiomes remains challenging. Here we describe deep long-read sequencing and assembly of metagenomes from biological soil crusts, a group of soil communities that are rich in BGCs. Taking advantage of the unusually long assemblies produced by this approach, we recovered nearly 3,000 BGCs for analysis, including 712 full-length BGCs. Functional exploration through metatranscriptome analysis of a 3-day wetting experiment uncovered phylum-specific BGC expression upon activation from dormancy, elucidating distinct roles and complex phylogenetic and temporal dynamics in wetting processes. For example, a pronounced increase in BGC transcription occurs at night primarily in cyanobacteria, implicating BGCs in nutrient scavenging roles and niche competition. Taken together, our results demonstrate that long-read metagenomic sequencing combined with metatranscriptomic analysis provides a direct view into the functional dynamics of BGCs in environmental processes and suggests a central role of secondary metabolites in maintaining phylogenetically conserved niches within biocrusts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Feature selection and causal analysis for microbiome studies in the presence of confounding using standardization

Abstract Background Microbiome studies have uncovered associations between microbes and human, animal, and plant health outcomes. This has led to an interest in developing microbial interventions for treatment of disease and optimization of crop yields which requires identification of microbiome features that impact the outcome in the population of interest. That task is challenging because of the high dimensionality of microbiome data and the confounding that results from the complex and dynamic interactions among host, environment, and microbiome. In the presence of such confounding, variable selection and estimation procedures may have unsatisfactory performance in identifying microbial features with an effect on the outcome. Results In this manuscript, we aim to estimate population-level effects of individual microbiome features while controlling for confounding by a categorical variable. Due to the high dimensionality and confounding-induced correlation between features, we propose feature screening, selection, and estimation conditional on each stratum of the confounder followed by a standardization approach to estimation of population-level effects of individual features. Comprehensive simulation studies demonstrate the advantages of our approach in recovering relevant features. Utilizing a potential-outcomes framework, we outline assumptions required to ascribe causal, rather than associational, interpretations to the identified microbiome effects. We conducted an agricultural study of the rhizosphere microbiome of sorghum in which nitrogen fertilizer application is a confounding variable. In this study, the proposed approach identified microbial taxa that are consistent with biological understanding of potential plant-microbe interactions. Conclusions Standardization enables more accurate identification of individual microbiome features with an effect on the outcome of interest compared to other variable selection and estimation procedures when there is confounding by a categorical variable.

59 BASIC BIOLOGICAL 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 OSTI2021

Microbiomes of commercially-available pine nuts and sesame seeds

Metagenomic analysis of food is becoming more routine and can provide important information pertaining to the shelf life potential and the safety of these products. However, less information is available on the microbiomes associated with low water activity foods. Pine nuts and sesame seeds, and food products which contain these ingredients, have been associated with recalls due to contamination with bacterial foodborne pathogens. The objective of this study was to identify the microbial community of pine nuts and sesame seeds using targeted 16S rRNA sequencing technology. Ten different brands of each seed type were assessed, and core microbiomes were determined. A total of 21 and 16 unique taxa with proportional abundances >1% in at least one brand were identified in the pine nuts and sesame seeds, respectively. Members of the core pine nut microbiome included the genera Alishewanella, Aminivibrio, Mycoplasma, Streptococcus, and unassigned OTUs in the families of Desulfobacteraceae and Xanthomonadaceae. For sesame seeds, the core microbiome included Aminivibrio, Chryseolina, Okibacterium, and unassigned OTUs in the family Flavobacteriaceae. The microbiomes of these seeds revealed that these products are dominated by environmental bacterial genera commonly isolated from soil, water, and plants; bacterial genera containing species known as commensal organisms were also identified. Understanding these microbiomes can aid in the risk assessment of these products by identifying food spoilage potential and community members which may co-enrich with foodborne bacterial pathogens.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

The microbiome of a Pacific moon jellyfish Aurelia coerulea

The impact of microbiome in animal physiology is well appreciated, but characterization of animal-microbe symbiosis in marine environments remains a growing need. This study characterizes the microbial communities associated with the moon jellyfish Aurelia coerulea, first isolated from the East Pacific Ocean and has since been utilized as an experimental system. We find that the microbiome of this Pacific Aurelia culture is dominated by two taxa, a Mollicutes and Rickettsiales. The microbiome is stable across life stages, although composition varies. Mining the host sequencing data, we assembled the bacterial metagenome-assembled genomes (MAGs). The bacterial MAGs are highly reduced, and predict a high metabolic dependence on the host. Analysis using multiple metrics suggest that both bacteria are likely new species. We therefore propose the names Ca. Mariplasma lunae (Mollicutes) and Ca. Marinirickettsia aquamalans (Rickettsiales). Finally, comparison with studies of Aurelia from other geographical populations suggests the association with Ca. Mariplasma lunae occurs in Aurelia from multiple geographical locations. The low-diversity microbiome of Aurelia provides a relatively simple system to study host-microbe interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Neotropical termite microbiomes as sources of novel plant cell wall degrading enzymes

In this study, we used shotgun metagenomic sequencing to characterise the microbial metabolic potential for lignocellulose transformation in the gut of two colonies of Argentine higher termite species with different feeding habits, Cortaritermes fulviceps and Nasutitermes aquilinus. Our goal was to assess the microbial community compositions and metabolic capacity, and to identify genes involved in lignocellulose degradation. Individuals from both termite species contained the same five dominant bacterial phyla (Spirochaetes, Firmicutes, Proteobacteria, Fibrobacteres and Bacteroidetes) although with different relative abundances. However, detected functional capacity varied, with C. fulviceps (a grass-wood-feeder) gut microbiome samples containing more genes related to amino acid metabolism, whereas N. aquilinus (a wood-feeder) gut microbiome samples were enriched in genes involved in carbohydrate metabolism and cellulose degradation. The C. fulviceps gut microbiome was enriched specifically in genes coding for debranching- and oligosaccharide-degrading enzymes. These findings suggest an association between the primary food source and the predicted categories of the enzymes present in the gut microbiomes of each species. To further investigate the termite microbiomes as sources of biotechnologically relevant glycosyl hydrolases, a putative GH10 endo-β-1,4-xylanase, Xyl10E, was cloned and expressed in Escherichia coli. Functional analysis of the recombinant metagenome-derived enzyme showed high specificity towards beechwood xylan (288.1 IU/mg), with the optimum activity at 50 °C and a pH-activity range from 5 to 10. These characteristics suggest that Xy110E may be a promising candidate for further development in lignocellulose deconstruction applications.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Phyllosphere exudates select for distinct microbiome members in sorghum epicuticular wax and aerial root mucilage

Phyllosphere exudates create specialized microhabitats that shape microbial community diversity. We explored the microbiome associated with two sorghum phyllosphere exudates, the epicuticular wax and aerial root mucilage. We assessed the microbiome associated with the wax from sorghum plants over two growth stages, and the root mucilage additionally from nitrogen-fertilized and non-fertilized plants. In parallel, we isolated and characterized hundreds of bacteria from wax and mucilage, and integrated data from cultivation-independent and cultivation-dependent approaches to gain insights into exudate diversity and bacterial phenotypes. We found that Sphingomonadaceae and Rhizobiaceae families were the major taxa in the wax regardless of water availability and plant developmental stage to plants. The cultivation-independent mucilage-associated bacterial microbiome contained Erwiniaceae, Flavobacteriaceae, Rhizobiaceae, Pseudomonadaceae, Sphingomonadaceae, and its structure was strongly influenced by sorghum development but only modestly influenced by fertilization. In contrast, the fungal community structure of mucilage was strongly affected by the year of sampling but not by fertilization or plant developmental stage, suggesting a decoupling of fungal-bacterial dynamics in the mucilage. Our bacterial isolate collection from wax and mucilage had several isolates that matched 100% to detected amplicon sequence variants, and were enriched on media that selected for phenotypes including phosphate solubilization, putative diazotrophy, resistance to desiccation, capability to grow on methanol as a carbon source, and ability to grow in the presence of linalool and β-caryophyllene (terpenes in sorghum wax). This work expands our understanding of the microbiome of phyllosphere exudates and supports our long-term goal to translate microbiome research to support sorghum cultivation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Beyond microbial abundance: metadata integration enhances disease prediction in human microbiome studies

Multiple studies have highlighted the interaction of the human microbiome with physiological systems such as the gut, immune, liver, and skin, via key axes. Advances in sequencing technologies and high-performance computing have enabled the analysis of large-scale metagenomic data, facilitating the use of machine learning to predict disease likelihood from microbiome profiles. However, challenges such as compositionality, high dimensionality, sparsity, and limited sample sizes have hindered the development of actionable models. One strategy to improve these models is by incorporating key metadata from both the human host and sample collection/processing protocols. This remains challenging due to sparsity and inconsistency in metadata annotation and availability. In this paper, we introduce a machine learning-based pipeline for predicting human disease states by integrating host and protocol metadata with microbiome abundance profiles from 68 different studies, processed through a consistent pipeline. Our findings indicate that metadata can enhance machine learning predictions, particularly at higher taxonomic ranks like Kingdom and Phylum, though this effect diminishes at lower ranks. Our study leverages a large collection of microbiome datasets comprising 11,208 samples, therefore enhancing the robustness and statistical confidence of our findings. This work is a critical step toward utilizing microbiome and metadata for predicting diseases such as gastrointestinal infections, diabetes, cancer, and neurological disorders.

Mathematics and Computing↗
DOE OSTI2025

Tropical Forest Soil Microbiome Modulates Leaf Heat Tolerance More Strongly Under Warming Than Ambient Conditions

ABSTRACT It is unclear how plants respond to increasing temperatures. Leaf heat tolerance (LHT) is often at its upper limit in tropical forests, suggesting that climate change might negatively impact these forests. We hypothesized that intraspecific variation in LHT might be associated with changes in the soil microbiome, which might also respond to climate. We hypothesized that warming would increase LHT through changes in the soil microbiome: we combined an in situ tropical warming experiment with a shade house experiment in Puerto Rico. The shade house experiment consisted of growing seedlings of Guarea guidonia , a dominant forest species, under different soil microbiome treatments (reduced arbuscular mycorrhizal fungi, reduced plant pathogens, reduced microbes, and unaltered) and soil inoculum from the field experiment. Heat tolerance was determined using chlorophyll fluorescence ( F V /F m ) on individual seedlings in the field and on groups of seedlings (per pot) in the shade house. We sequenced soil fungal DNA to analyze the impacts of the treatments on the soil microbiome. In the field, seedlings from ambient temperature plots showed higher F V /F m values under high temperatures (0.648 at 46°C and 0.067 at 52°C) than seedlings from the warming plots (0.535 at 46°C and 0.031 at 52°C). In the shade house, the soil microbiome treatments significantly influenced the fungal community composition and LHT ( T crit and F V /F m ). Reduction in fungal pathogen abundance and diversity altered F V /F m before T 50 for seedlings grown with soil inoculum from the warming plots but after T 50 for seedlings grown with soil inoculum from the ambient plots. Our findings emphasize that the soil microbiome plays an important role in modulating the impacts of climate change on plants. Understanding and harnessing this relationship might be vital for mitigating the effects of warming on forests, emphasizing the need for further research on microbial responses to climate change.

Hernandes Villani, Gabriela [Department of Plant B↗
DOE OSTI2023

A standardized quantitative analysis strategy for stable isotope probing metagenomics

ABSTRACT Stable isotope probing (SIP) facilitates culture-independent identification of active microbial populations within complex ecosystems through isotopic enrichment of nucleic acids. Many DNA-SIP studies rely on 16S rRNA gene sequences to identify active taxa, but connecting these sequences to specific bacterial genomes is often challenging. Here, we describe a standardized laboratory and analysis framework to quantify isotopic enrichment on a per-genome basis using shotgun metagenomics instead of 16S rRNA gene sequencing. To develop this framework, we explored various sample processing and analysis approaches using a designed microbiome where the identity of labeled genomes and their level of isotopic enrichment were experimentally controlled. With this ground truth dataset, we empirically assessed the accuracy of different analytical models for identifying active taxa and examined how sequencing depth impacts the detection of isotopically labeled genomes. We also demonstrate that using synthetic DNA internal standards to measure absolute genome abundances in SIP density fractions improves estimates of isotopic enrichment. In addition, our study illustrates the utility of internal standards to reveal anomalies in sample handling that could negatively impact SIP metagenomic analyses if left undetected. Finally, we present SIPmg , an R package to facilitate the estimation of absolute abundances and perform statistical analyses for identifying labeled genomes within SIP metagenomic data. This experimentally validated analysis framework strengthens the foundation of DNA-SIP metagenomics as a tool for accurately measuring the in situ activity of environmental microbial populations and assessing their genomic potential. IMPORTANCE Answering the questions, “who is eating what?” and “who is active?” within complex microbial communities is paramount for our ability to model, predict, and modulate microbiomes for improved human and planetary health. These questions can be pursued using stable isotope probing to track the incorporation of labeled compounds into cellular DNA during microbial growth. However, with traditional stable isotope methods, it is challenging to establish links between an active microorganism’s taxonomic identity and genome composition while providing quantitative estimates of the microorganism’s isotope incorporation rate. Here, we report an experimental and analytical workflow that lays the foundation for improved detection of metabolically active microorganisms and better quantitative estimates of genome-resolved isotope incorporation, which can be used to further refine ecosystem-scale models for carbon and nutrient fluxes within microbiomes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

favela3/Maize.N-cycle.Function

Supplemental sequence processing and R statistical analysis for publication which compares the microbiome of 27 Zea cultivars: 12 Inbred maize genotypes, 9 hybrids, and 6 wild teosinte. The project contains amplicon data for various genes: 16S rRNA, ITS, bacterial amoA, Archeal amoA, nirS, nirK, and nosZ. In addition to functional potential assay data, and N2O flux.

Favela, Alonso↗
DOE OSTI2022

Metagenome-assembled genomes of phytoplankton microbiomes from the Arctic and Atlantic Oceans

Abstract Background Phytoplankton communities significantly contribute to global biogeochemical cycles of elements and underpin marine food webs. Although their uncultured genomic diversity has been estimated by planetary-scale metagenome sequencing and subsequent reconstruction of metagenome-assembled genomes (MAGs), this approach has yet to be applied for complex phytoplankton microbiomes from polar and non-polar oceans consisting of microbial eukaryotes and their associated prokaryotes. Results Here, we have assembled MAGs from chlorophyll a maximum layers in the surface of the Arctic and Atlantic Oceans enriched for species associations (microbiomes) with a focus on pico- and nanophytoplankton and their associated heterotrophic prokaryotes. From 679 Gbp and estimated 50 million genes in total, we recovered 143 MAGs of medium to high quality. Although there was a strict demarcation between Arctic and Atlantic MAGs, adjacent sampling stations in each ocean had 51–88% MAGs in common with most species associations between Prasinophytes and Proteobacteria . Phylogenetic placement revealed eukaryotic MAGs to be more diverse in the Arctic whereas prokaryotic MAGs were more diverse in the Atlantic Ocean. Approximately 70% of protein families were shared between Arctic and Atlantic MAGs for both prokaryotes and eukaryotes. However, eukaryotic MAGs had more protein families unique to the Arctic whereas prokaryotic MAGs had more families unique to the Atlantic. Conclusion Our study provides a genomic context to complex phytoplankton microbiomes to reveal that their community structure was likely driven by significant differences in environmental conditions between the polar Arctic and warm surface waters of the tropical and subtropical Atlantic Ocean.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Investigation of Spaceflight Induced Changes to Astronaut Microbiomes

The International Space Station (ISS) is a uniquely enclosed environment that has been continuously occupied for the last two decades. Throughout its operation, protecting the health of the astronauts on-board has been a high priority. The human microbiome plays a significant role in maintaining human health, and disruptions in the microbiome have been linked to various diseases. To evaluate the effects of spaceflight on the human microbiome, body swabs and saliva samples were collected from four ISS astronauts on consecutive expeditions. Astronaut samples were analyzed using shotgun metagenomic sequencing and microarrays to characterize the microbial biodiversity before, during, and after the astronauts’ time onboard the ISS. Samples were evaluated at an individual and population level to identify changes in microbial diversity and abundance. No significant changes in the number or relative abundance of taxa were observed between collection time points when samples from all four astronauts were analyzed together. When the astronauts’ saliva samples were analyzed individually, the saliva samples of some astronauts showed significant changes in the relative abundance of taxa during and after spaceflight. The relative abundance of Prevotella in saliva samples increased during two astronauts’ time onboard the ISS while the relative abundance of other commensal taxa such as Neisseria, Rothia, and Haemophilus decreased. The abundance of some antimicrobial resistance genes within the saliva samples also showed significant changes. Most notably, elfamycin resistance gene significantly increased in all four astronauts post-flight and a CfxA6 beta-lactam marker significantly increased during spaceflight but returned to normal levels post-flight. The combination of both shotgun metagenomic sequencing and microarrays showed the benefit of both technologies in monitoring microbes on board the ISS. There were some changes in each astronaut’s microbiome during spaceflight, but these changes were not universal for all four astronauts. Two antimicrobial resistance gene markers did show a significant change in abundance in the saliva samples of all four astronauts across their collection times. These results provide insight for future ISS microbial monitoring studies and targets for antimicrobial resistance screenings.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Identification and characterization of a skin microbiome on Caenorhabditis elegans suggests environmental microbes confer cuticle protection

ABSTRACT In the wild, C. elegans are emersed in environments teeming with a veritable menagerie of microorganisms. The C. elegans cuticular surface serves as a barrier and first point of contact with their microbial environments. In this study, we identify microbes from C. elegans natural habitats that associate with its cuticle, constituting a simple “skin microbiome.” We rear our animals on a modified CeMbio, mCeMbio, a consortium of ecologically relevant microbes. We first combine standard microbiological methods with an adapted micro skin-swabbing tool to describe the skin-resident bacteria on the C. elegans surface. Furthermore, we conduct 16S rRNA gene sequencing studies to identify relative shifts in the proportion of mCeMbio bacteria upon surface-sterilization, implying distinct skin- and gut-microbiomes. We find that some strains of bacteria, including Enterobacter sp. JUb101 , are primarily found on the nematode skin, while others like Stenotrophomonas indicatrix JUb19 and Ochrobactrum vermis MYb71 are predominantly found in the animal’s gut. Finally, we show that this skin microbiome promotes host cuticle integrity in harsh environments. Together, we identify a skin microbiome for the well-studied nematode model and propose its value in conferring host fitness advantages in naturalized contexts. IMPORTANCE The genetic model organism C. elegans has recently emerged as a tool for understanding host–microbiome interactions. Nearly all of these studies either focus on pathogenic or gut-resident microbes. Little is known about the existence of native, nonpathogenic skin microbes or their function. We demonstrate that members of a modified C. elegans model microbiome, mCeMbio, can adhere to the animal's cuticle and confer protection from noxious environments. We combine a novel micro-swab tool, the first 16S microbial sequencing data from relatively unperturbed C. elegans , and physiological assays to demonstrate microbially mediated protection of the skin. This work serves as a foundation to explore wild C. elegans skin microbiomes and use C. elegans as a model for skin research.

16S RNA↗
DOE OSTI2024

Seasonality and longer-term development generate temporal dynamics in the Populus microbiome

ABSTRACT Temporal variation in community composition is central to our understanding of the assembly and functioning of microbial communities, yet the controls over temporal dynamics for microbiomes of long-lived plants, such as trees, remain unclear. Temporal variation in tree microbiomes could arise primarily from seasonal (i.e., intra-annual) fluctuations in community composition or from longer-term changes across years as host plants age. To test these alternatives, we experimentally isolated temporal variation in plant microbiome composition using a common garden and clonally propagated plants, and we used amplicon sequencing to characterize bacterial/archaeal and fungal communities in the leaf endosphere, root endosphere, and rhizosphere of two Populus spp. over four seasons across two consecutive years. Microbial community composition differed among seasons and years (which accounted for up to 21% of the variation in microbial community composition) and was correlated with seasonal dissimilarity in climatic conditions. However, microbial community dissimilarity was also positively correlated with time, reflecting longer-term compositional shifts as host trees aged. Together, our findings demonstrate that temporal patterns in tree microbiomes arise from both seasonal fluctuations and longer-term changes, which interact to generate unique seasonal patterns each year. In addition to shedding light on two important controls over the assembly of plant microbiomes, our results also suggest future studies of tree microbiomes should account for background temporal dynamics when testing the drivers of spatial patterns in microbial community composition and temporal responses of plant microbiomes to environmental change. IMPORTANCE Microbiomes are integral to the health of host plants, but we have a limited understanding of the factors that control how the composition of plant microbiomes changes over time. Especially little is known about the microbiome of long-lived trees, relative to annual and non-woody plants. We tested how tree microbiomes changed between seasons and years in poplar (genus Populus ), which are widespread and ecologically important tree species that also serve as important biofuel feedstocks. We found the composition of bacterial, archaeal, and fungal communities differed among seasons, but these seasonal differences depended on year. This dependence was driven by longer-term changes in microbial composition as host trees developed across consecutive years. Our findings suggest that temporal variation in tree microbiomes is driven by both seasonal fluctuations and longer-term (i.e., multiyear) development.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Tetranucleotide frequencies differentiate genomic boundaries and metabolic strategies across environmental microbiomes

Microbiomes are constrained by physicochemical conditions, nutrient regimes, and community interactions across diverse environments, yet genomic signatures of this adaptation remain unclear. Metagenome sequencing is a powerful technique to analyze genomic content in the context of natural environments, establishing concepts of microbial ecological trends. Here, we developed a data discovery tool-a tetranucleotide-informed metagenome stability diagram-that is publicly available in the integrated microbial genomes and microbiomes (IMG/M) platform for metagenome ecosystem analyses. We analyzed the tetranucleotide frequencies from quality-filtered and unassembled sequence data of over 12,000 metagenomes to assess ecosystem-specific microbial community composition and function. We found that tetranucleotide frequencies can differentiate communities across various natural environments and that specific functional and metabolic trends can be observed in this structuring. Our tool places metagenomes sampled from diverse environments into clusters and along gradients of tetranucleotide frequency similarity, suggesting microbiome community compositions specific to gradient conditions. Within the resulting metagenome clusters, we identify protein-coding gene identifiers that are most differentiated between ecosystem classifications. We plan for annual updates to the metagenome stability diagram in IMG/M with new data, allowing for refinement of the ecosystem classifications delineated here. This framework has the potential to inform future studies on microbiome engineering, bioremediation, and the prediction of microbial community responses to environmental change. IMPORTANCE: Microbes adapt to diverse environments influenced by factors like temperature, acidity, and nutrient availability. We developed a new tool to analyze and visualize the genetic makeup of over 12,000 microbial communities, revealing patterns linked to specific functions and metabolic processes. This tool groups similar microbial communities and identifies characteristic genes within environments. By continually updating this tool, we aim to advance our understanding of microbial ecology, enabling applications like microbial engineering, bioremediation, and predicting responses to environmental change.

Kellom, Matthew↗
DOE OSTI2026

Viromics approaches for the study of viral diversity and ecology in microbiomes

Viruses are found across all ecosystems and infect every type of organism on Earth. Traditional culture-based methods have proven insufficient to explore this viral diversity at scale, driving the development of viromics, the sequence-based analysis of uncultivated viruses. Viromics approaches have been particularly useful for studying viruses of microorganisms, which can act as crucial regulators of microbiomes across ecosystems. They have already revealed the broad geographic distribution of viral communities and are progressively uncovering the expansive genetic and functional diversity of the global virome. Moving forward, large-scale viral ecogenomics studies combined with new experimental and computational approaches to identify virus activity and host interactions will enable a more complete characterization of global viral diversity and its effects.

Ecology↗