Biology subjects

Roux, S.

Publications and source records attributed to Roux, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

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. ImportanceMicrobes 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.

ecology↗

bioRxiv2025

Genomic and metagenomic survey of microbial carbonic anhydrase genes reveals novel clades, high diversity, and biome-specificity

Carbonic anhydrase (CA) enzymes catalyze the interconversion of carbon dioxide and bicarbonate with an efficiency exceeded only by superoxide dismutase. CA enzymes have convergently evolved multiple times from phylogenetically distant organisms into structurally unrelated classes (, {beta}, {gamma},{delta} ,{zeta} , , {theta}, {iota}) with conserved physiological functions involved in photosynthesis, respiration, pH homeostasis, CO2 transport, and carbonyl sulfide hydrolysis that play central roles in medicine and the environment. Here, we leverage the recent surge in publicly available genomes and metagenomes to re-examine our understanding of the abundance, diversity, and phylogenetic relationships of the three major CA classes in Bacteria/Archaea and microbial Eukaryotes (Fungi, algae). We recovered a total of 57,218 -, {beta}-, and {gamma}-CA sequences from 24,184 metagenomes and genomes, including the first detection of -CA from an Archaeal species. CA sequences formed 3,859 protein clusters (1,188 with [≥] 3 sequences) that were taxonomically conserved at higher levels (i.e., Superkingdom, Phylum, Class). When viewed within a phylogenetic framework, the majority of subclades contained CAs representing multiple Superkingdoms, although numerous novel {beta}-CA clades appear unique to Fungi. Queries of CA Hidden Markov models (HMMs) against all public meta-genome and -transcriptome datasets revealed that CA is a ubiquitous enzyme present in virtually all sampled environments. However, CA clusters that were taxonomically conserved also appeared environment-specific, generating high CA diversity. This work represents an important contribution to the evolution, diversity, and environmental distribution of an enzyme that is key for life and has broad environmental and industrial applications.

genomics↗

bioRxiv2024

Gaia: A Context-Aware Sequence Search and Discovery Tool for Microbial Proteins

Protein sequence similarity search is fundamental to genomics research, but current methods are typically not able to consider crucial genomic context information that can be indicative of protein function, especially in microbial systems. Here we present Gaia (Genomic AI Annotator), a sequence annotation platform that enables rapid, context-aware protein sequence search across genomic datasets. Gaia leverages gLM2, a mixed-modality genomic language model trained on both amino acid sequences and their genomic neighborhoods to generate embeddings that integrate sequence-structure-context information. This approach allows for the identification of functionally related genes that are found in conserved genomic contexts, which may be missed by traditional sequence- or structure-based search alone. Gaia enables real-time search of a curated database comprising over 85M protein clusters (defined at 90% sequence identity) from 131,744 microbial genomes. We compare the sequence, structure and context sensitivity of gLM2 embedding-based search against existing tools like MMseqs2 and Foldseek. We showcase Gaia-enabled discoveries of phage tail proteins and siderophore synthesis loci that were previously difficult to annotate with traditional tools. Gaia search is freely available at https://gaia.tatta.bio.

bioinformatics↗

bioRxiv2024

Multi-laboratory Study Establishes Reproducible Methods for Plant-Microbiome Research in Fabricated Ecosystems

Inter-laboratory replicability is crucial yet challenging in microbiome research. Leveraging microbiomes to promote soil health and plant growth requires understanding underlying molecular mechanisms using reproducible experimental systems. In a global collaborative effort involving five laboratories, we aimed to help advance reproducibility in microbiome studies by testing our ability to replicate synthetic community assembly experiments. Our study compared fabricated ecosystems constructed using two different synthetic bacterial communities, the model grass Brachypodium distachyon, and sterile EcoFAB 2.0 devices. All participating laboratories observed consistent inoculum-dependent changes in plant phenotype, root exudate composition, and final bacterial community structure where Paraburkholderia sp. OAS925 could dramatically shift microbiome composition. Comparative genomics and exudate utilization linked the pH-dependent colonization ability of Paraburkholderia, which was further confirmed with motility assays. The study provides detailed protocols, benchmarking datasets, and best practices to help advance replicable science and inform future multi-laboratory reproducibility studies.

microbiology↗

bioRxiv2024

Dynamics and determinants of the gut mobilome in early life

As mobile genetic elements (MGE) are critical yet understudied determinants of gut microbiome composition, we characterized the gut virome and plasmidome in 195 samples from 28 mother-infant dyads delivered by caesarean section. Infant mobilome increased in richness over the first 6 postnatal weeks, demonstrating high individual-specificity and temporal stability, establishing a personal persistent mobilome. Formula-fed infants exhibited greater mobilome richness than breastfed infants, with plasmid composition influenced by antibiotic exposure and birth weight. Plasmids constituted a significant reservoir of antibiotic resistance genes (ARG), with around 5% of infant gut plasmid taxonomic units carrying ARG. Notably, ARG profiles did not differ with antibiotic exposure at birth. We found that mother-infant sharing of viral and plasmid strains primarily occurred after 6 months of age. Overall, our integrative analysis offers novel insights into the dynamics, modulation, origin, and clinical implications of MGE in the developing gut microbiome.

genomics↗

bioRxiv2024

Neurons as biosensors for discriminating neurological disorders in a brain-on-chip platform: Application to Alzheimer s Disease using patient CSF

Alzheimers disease (AD) is characterized by the accumulation of aggregated amyloid beta peptide (A{beta}) leading to progressive neuronal loss and dysfunction. Current ADs diagnosis involves biomarkers assays in cerebrospinal fluid (CSF) as A{beta} to validate the diagnosis. However, these methods are time-consuming, expensive, and can result in inaccurate diagnoses by not accounting for differential diagnose. To overcome these challenges, researchers are exploring new technologies for detecting AD biomarkers in biological fluids, though progress is hindered by an incomplete understanding of AD mechanisms and CSF composition. In this study, we used a standardized microfluidic platform to investigate the effects of synthetic A{beta} peptides and cerebrospinal fluid (CSF) from AD and healthy patients on neuronal functional activity. First, human neurons derived from induced pluripotent stem cells (iPSCs) were characterized. Then, to modulate the functional activity of neurons, tetrodotoxin (TTX), a specific sodium channel blocker, was used as a control for inhibiting neuronal activity. Subsequently, glutamatergic neurons were chronically exposed to A{beta}O and patients CSF. MEA recordings were performed before and after the treatments to assess changes in network activity. Our results demonstrated that extracting key electrophysiological metrics allows for discrimination between healthy and AD CSF samples. This system could offer the potential for differential diagnosis and development of personalized therapeutic strategies.

neuroscience↗

bioRxiv2024

The OMG dataset: An Open MetaGenomic corpus for mixed-modality genomic language modeling

Biological language model performance depends heavily on pretraining data quality, diversity, and size. While metagenomic datasets feature enormous biological diversity, their utilization as pretraining data has been limited due to challenges in data accessibility, quality filtering and deduplication. Here, we present the Open MetaGenomic (OMG) corpus, a genomic pretraining dataset totalling 3.1T base pairs and 3.3B protein coding sequences, obtained by combining two largest metagenomic dataset repositories (JGIs IMG and EMBLs MGnify). We first document the composition of the dataset and describe the quality filtering steps taken to remove poor quality data. We make the OMG corpus available as a mixed-modality genomic sequence dataset that represents multi-gene encoding genomic sequences with translated amino acids for protein coding sequences, and nucleic acids for intergenic sequences. We train the first mixed-modality genomic language model (gLM2) that leverages genomic context information to learn robust functional representations, as well as coevolutionary signals in protein-protein interfaces and genomic regulatory syntax. Furthermore, we show that deduplication in embedding space can be used to balance the corpus, demonstrating improved performance on downstream tasks. The OMG dataset is publicly hosted on the Hugging Face Hub at https://huggingface.co/datasets/tattabio/OMG and gLM2 is available at https://huggingface.co/tattabio/gLM2_650M.

systems biology↗

bioRxiv2024

Tunturi virus isolates and metagenome-assembled viral genomes provide insights into the virome of Acidobacteriota in Arctic tundra soils

BackgroundArctic soils are climate-critical areas, where microorganisms play crucial roles in nutrient cycling processes. Acidobacteriota are phylogenetically and physiologically diverse bacteria that are abundant and active in Arctic tundra soils. Still, surprisingly little is known about acidobacterial viruses in general and those residing in the Arctic in particular. Here, we applied both culture-dependent and -independent methods to study the virome of Acidobacteriota in Arctic soils. ResultsFive virus isolates, Tunturi 1-5, were obtained from Arctic tundra soils, Kilpisjarvi, Finland (69{degrees}N), using Tunturibacter spp. strains originating from the same area as hosts. The new virus isolates have tailed particles with podo-(Tunturi 1, 2, 3), sipho-(Tunturi 4), or myovirus-like (Tunturi 5) morphologies. The dsDNA genomes of the viral isolates are 63-98 kbp long, except Tunturi 5, which is a jumbo phage with a 309-kbp genome. Tunturi 1 and Tunturi 2 share 88% overall nucleotide identity, while the other three are not related to one another. For over half of the open reading frames in Tunturi genomes, no functions could be predicted. To further assess the Acidobacteriota-associated viral diversity in Kilpisjarvi soils, bulk metagenomes from the same soils were explored and a total of 1881 viral operational taxonomic units (vOTUs) were bioinformatically predicted. Almost all vOTUs (98%) were assigned to the class Caudoviricetes. For 125 vOTUs, including five (near-)complete ones, Acidobacteriota hosts were predicted. Acidobacteriota-linked vOTUs were abundant across sites, especially in fens. Terriglobia-associated proviruses were observed in Kilpisjarvi soils, being related to proviruses from distant soils and other biomes. Approximately genus- or higher-level similarities were found between Tunturi viruses, Kilpisjarvi vOTUs, and other soil vOTUs, suggesting some shared groups of Acidobacteriota viruses across soils. ConclusionsThis study provides acidobacterial virus isolates as laboratory models for future research and adds insights into the diversity of viral communities associated with Acidobacteriota in tundra soils. Predicted virus-host links and viral gene functions suggest various interactions between viruses and their host microorganisms. Largely unknown sequences in the isolates and metagenome-assembled viral genomes highlight a need for more extensive sampling of Arctic soils to better understand viral functions and contributions to ecosystem-wide cycling processes in the Arctic.

microbiology↗

bioRxiv2024

Insights into the role of root exudates in bacteriophage infection dynamics

Bacteriophages impact soil bacteria through lysis, altering the availability of organic carbon and plant nutrients. However, the magnitude of nutrient uptake by plants from lysed bacteria remains unknown, partly because this process is challenging to investigate in the field. In this study, we extend ecosystem fabrication (EcoFAB 2.0) approaches to study plant-bacteria-phage interactions by comparing the impact of phage-lysed and uninfected 15N-labeled bacterial necromass on plant nitrogen acquisition and rhizosphere exometabolites composition. We show that grass Brachypodium distachyon derives some nitrogen from amino acids in uninfected Pseudomonas putida necromass but not from virocell necromass. Additionally, the bacterial necromass elicits the formation of rhizosphere exometabolites, some of which (guanosine), alongside tested aromatic acids (p-coumaric and benzoic acid), show distinct effects on bacteriophage-induced lysis when tested in vitro. The study highlights the dynamic feedback between bacterial necromass and plants and suggests that root exudate metabolites can impact bacteriophage infection dynamics.

plant biology↗

bioRxiv2024

Chronic potentiation of metabotropic glutamate receptor 2 with a nanobody accelerates amyloidogenesis in Alzheimer's disease.

Immunotherapy of Alzheimers disease (AD) is a promising approach to reduce the accumulation of amyloid-beta (A{beta}), a critical event in the onset of the disease. Targeting the group II metabotropic glutamate receptors, mGlu2 and mGlu3, could be important in controlling A{beta} production, although their respective contribution remains unclear due to the lack of selective tools. Here, we show that enhancing mGlu2 receptor activity increases A{beta}1-42 peptide production whereas activation of mGlu3 has no effect. We show that such a difference likely results from the direct interaction of APP with mGlu3, but not with mGlu2 receptors, that prevents APP amyloidogenic cleavage and A{beta}1-42 peptides production. We then show that chronic treatments of the AD model 5xFAD mice with a brain-penetrating mGlu2-potentiating nanobody accelerated amyloid aggregation and exacerbated memory deficits, but had no effect in control mice. Our results confirm that a selective mGluR2 activation exacerbates AD disease development, suggesting that therapeutic benefices could be obtained with blockers of this receptor. Our study also provides the proof-of-concept that chronic administration of nanobodies targeting neuroreceptors can be envisioned to treat brain diseases.

neuroscience↗

bioRxiv2023

Characterization and hierarchy of the spermatogonial stem cell compartment in human spermatogenesis by spectral cytometry using a 16-colors panel

About one in six couples experience fertility problems, and male infertility accounts for about half of these cases. Spermatogenesis originates from a small pool of spermatogonial stem cells (SSCs), which are of interest for the treatment of infertility but remain poorly characterized in humans. Using multiparametric spectral flow cytometric analysis with a 16-colours (16-C) panel of cell markers, we identify novel markers of SSCs and provide insights into unravelling and resolving the heterogeneity of the human spermatogonial cells. This 16-C panel of markers allowed the identification of a primitive SSCs state with the {beta}-2M-CD51/61- ITGA6+SSEA4+TSPAN33+THY1+CD9+EPCAMmedCD155+CD148+CD47highCD7high phenotype, with a profile close to the most primitive SSCs states 0 and SSC1-B previously defined by sc-RNAseq approach. The hierarchy of events in the spermatogonial stem cell and progenitor compartment of human spermatogenesis has been delineated. This highlights the importance of a multi-parametric and spectral cytometry approach. The in-depth characterization of testicular cells should help to overcome the lack of stem cell knowledge, that hinders the understanding of the regenerative potential of SSCs, and is a critical parameter for the successful development of new SSCs-based cell therapies.

developmental biology↗

bioRxiv2023

A functional microbiome catalog crowdsourced from North American rivers

Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial processes governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling, sequencing, and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. Specifically, GROWdb encompasses 1,469 microbial species from 27 phyla, including novel lineages from 10 families and 128 genera, and defines the core river microbiome for the first time at genome level. GROWdb analyses coupled to extensive geospatial information revealed local and regional drivers of microbial community structuring, while also presenting a myriad of foundational hypotheses about ecosystem function. Building upon the previously conceived River Continuum Concept1, we layer on microbial functional trait expression, which suggests the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures2, 3 so that it can be widely accessed across disciplines for watershed predictive modeling and microbiome-based management practices.

microbiology↗

bioRxiv2023

Population ecology and potential biogeochemical impacts of ssDNA and dsDNA soil viruses along a permafrost thaw gradient

Climate change is disproportionately warming northern peatlands, which may release large carbon stores via increased microbial activity. While there are many unknowns about such microbial responses, virus roles are especially poorly characterized with studies to date largely restricted to "bycatch" from bulk metagenomes. Here, we used optimized viral particle purification techniques on 20 samples along a highly contextualized peatland permafrost thaw gradient, extracted and sequenced viral particle DNA using two library kits to capture single-stranded (ssDNA) and double-stranded (dsDNA) virus genomes (40 total viromes), and explored their diversity and potential ecosystem impacts. Both kits recovered similar dsDNA virus numbers, but only one also captured thousands of ssDNA viruses. Combining these data, we explored population-level ecology using genomic representation from 9,560 viral operational taxonomic units (vOTUs); nearly a 4-fold expansion from permafrost-associated soils, and 97% of which were novel when compared against large datasets from soils, oceans, and the human gut. In silico predictions identified putative hosts for 44% (4,149 dsDNA + 17 ssDNA) of the identified vOTUs spanning 2 eukaryotic, 12 archaeal, and 30 bacterial phyla. The recovered vOTUs encoded 1,684 putative auxiliary metabolic genes (AMGs) and other metabolic genes carried by [~]10% of detected vOTUs, of which 46% were related to carbon processing and 644 were novel. These AMGs grouped into five functional categories and 11 subcategories, and nearly half (47%) of the AMGs were involved in carbon utilization. Of these, 112 vOTUs encoded 123 glycoside hydrolases spanning 15 types involved in the degradation of polysaccharides (e.g., cellulose) to monosaccharides (e.g., galactose), or further monosaccharide degradation, which suggests virus involvement in myriad metabolisms including fermentation and central carbon metabolism. These findings expand the scope of viral roles in microbial carbon processing and suggest viruses may be critical for understanding the fate of soil organic carbon in peatlands.

microbiology↗

bioRxiv2023

You can move, but you can't hide: identification of mobile genetic elements with geNomad

Identifying and characterizing mobile genetic elements (MGEs) in sequencing data is essential for understanding their diversity, ecology, biotechnological applications, and impact on public health. Here, we introduce geNomad, a classification and annotation framework that combines information from gene content and a deep neural network to identify sequences of plasmids and viruses. geNomad uses a large dataset of marker proteins to provide functional gene annotation and taxonomic assignment of viral genomes. Using a conditional random field model, geNomad also detects proviruses integrated into host genomes with high precision. In benchmarks that included diverse MGE and chromosome sequences, geNomad significantly outperformed other tools in all evaluated clades of plasmids and viruses. Leveraging geNomads speed and scalability, we were able to process public metagenomes and metatranscriptomes, leading to the discovery of millions of new viruses and plasmids that are available through the IMG/VR and IMG/PR databases. We anticipate that geNomad will enable further advancements in MGE research, and it is available at https://portal.nersc.gov/genomad.

bioinformatics↗

bioRxiv2023

Virus diversity and activity is driven by snowmelt and host dynamics in a high-altitude watershed soil ecosystem

Viruses, including phages, impact nearly all organisms on Earth, including microbial communities and their associated biogeochemical processes. In soils, highly diverse viral communities have been identified, with a global distribution seemingly driven by multiple biotic and abiotic factors, especially soil temperature and moisture. However, our current understanding of the stability of soil viral communities across time, and their response to strong seasonal change in environmental parameters remains limited. Here, we investigated the diversity and activity of environmental DNA and RNA viruses, including phages, across dynamics seasonal changes in a snow-dominated mountainous watershed by examining paired metagenomes and metatranscriptomes. We identified a large number of DNA and RNA viruses taxonomically divergent from existing environmental viruses, including a significant proportion of RNA viruses target fungal hosts and a large and unsuspected diversity of positive single-stranded RNA phages (Leviviricetes), highlighting the under-characterization of the global soil virosphere. Among these, we were able to distinguish subsets of active phages which changed across seasons, consistent with a "seed-bank" viral community structure in which new phage activity, for example replication and host lysis, is sequentially triggered by changes in environmental conditions. Zooming in at the population level, we further identified virus-host dynamics matching two existing ecological models: "Kill-The-Winner" which proposes that lytic phages are actively infecting abundant bacteria, and "Piggyback-The-Persistent" which argues that when the host is growing slowly it is more beneficial to remain in a lysogenic state. The former was associated with summer months of high and rapid microbial activity, and the latter to winter months of limited and slow host growth. Taken together, these results suggest that the high diversity of viruses in soils is likely associated with a broad range of host interaction types each adapted to specific host ecological strategies and environmental conditions. Moving forward, while as our understanding of how environmental and host factors drive viral activity in soil ecosystems progresses, integrating these viral impacts in complex natural microbiome models will be key to accurately predict ecosystem biogeochemistry.

microbiology↗

bioRxiv2023

Long-term CRISPR array dynamics and stable host-virus co-existence in subsurface fractured shales

Viruses are the most ubiquitous biological entities on earth. Even so, elucidating the impact of viruses on microbial communities and associated ecosystem processes often requires identification of strong host-virus linkages - an undeniable challenge in many ecosystems. Subsurface fractured shales present a unique opportunity to first make these strong linkages and subsequently reveal complex long-term host-virus dynamics and trends in CRISPR array size and frequency. Here, we sampled two replicated sets of fractured shale wells for nearly 800 days (Denver-Julesburg Basin, Colorado, USA). We identified a relatively diverse microbial community with widely encoded CRISPR viral defense systems, which facilitated 2,110 CRISPR-based viral linkages across 90 host MAGs representing 25 phyla. Leveraging these linkages with timeseries data across differing well ages, we observed how patterns of host-virus co-existence develop and converge in this closed ecosystem through time. We observed a transition to smaller CRISPR arrays in older, more established wells, potentially reflecting a natural progression where CRISPR arrays harbor fewer, yet more effective spacers that target viral genes with fewer mutations. Together, our findings shed light on the complexities of host-virus temporal dynamics as well as possible drivers of spacer loss and acquisition within CRISPR arrays of diverse microbial populations through time.

microbiology↗

bioRxiv2022

A standardized quantitative analysis strategy for stable isotope probing metagenomics

Stable isotope probing (SIP) facilitates culture-independent identification of active microbial populations within complex ecosystems through isotopic enrichment of nucleic acids. Many SIP studies rely on 16S rRNA 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 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 analytic 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. ImportanceAnswering the question of who is eating what? within complex microbial communities is paramount for our ability to model, predict, and modulate microbiomes for improved human and planetary health. This question is often 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 microorganisms taxonomic identity and genome composition, while providing quantitative estimates of the microorganisms 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.

microbiology↗

bioRxiv2022

Highly diverse and unknown viruses may enhance Antarctic endoliths' adaptability

Rock-dwelling microorganisms are key players in ecosystem functioning of Antarctic ice free-areas. Yet, little is known about their diversity and ecology. Here, we performed metagenomic analyses on rocks from across Antarctica comprising >75,000 viral operational taxonomic units (vOTUS). We found largely undescribed, highly diverse and spatially structured virus communities potentially influencing bacterial adaptation and biogeochemistry. This catalog lays the foundation for expanding knowledge of the virosphere in extreme environments.

microbiology↗