Biology subjects

Bolduc, B.

Publications and source records attributed to Bolduc, B..

12 recordsLinked to original sources

bioRxiv2026

CheckAMG: Accurate Identification of Auxiliary Viral Genes with Genome-Language Models

Viruses shape microbial metabolism through auxiliary viral genes (AVGs) that reprogram host metabolism, physiology, and gene regulation during infection. Identifying AVGs is complicated by ambiguous viral versus cellular assignment, inconsistent curation, and reliance on sequence homology that misses divergent functions. Here we present CheckAMG, which pairs annotation-based AVG prediction, curated with a per-gene viral scoring system and ontological mapping of metabolic function, with a finetuned genome-language model for annotation-independent discovery. Benchmarked against DRAM-V and VIBRANT across three ecosystems, CheckAMG produced more strongly supported auxiliary metabolic gene (AMG) calls, and uniquely among AMG tools reports auxiliary physiological (APGs) and regulatory (AReGs) genes. Applied to 1,005,980 fragmented or complete soil and human-gut viral genomes, CheckAMG identified 541,199 AVGs tracking biome-specific protein clusters and functions, including 109,107 proteins with no detectable sequence similarity to any reference database. CheckAMG thus provides a reproducible, scalable framework for identifying the genes through which viruses reprogram host biology.

bioinformatics↗

bioRxiv2026

First community challenge for automated virus taxonomy

The rapid rate of virus discovery renders manual curation by taxonomy experts increasingly impractical, creating a need for reliable software that can reproducibly assign viral contigs to taxa at all fifteen ranks of the virus taxonomy. We led an open community challenge for the computational taxonomic classification of viruses and assembled a dataset of virus sequences combining expert-curated and metagenomic sequences. Seventeen teams contributed a total of thirty-four automated, fully reproducible classification pipelines. Most tools correctly assigned viruses belonging to established species, genera, or families, but viruses that are unclassified at those lower ranks remain challenging. This study provides datasets, open-source software, novel approaches, and recommendations to benchmark computational taxonomic classification of viruses, and support organizing the many viruses discovered in big omics data.

microbiology↗

bioRxiv2025

Scalable and systematic hierarchical virus taxonomy with vConTACT3

Viruses are key players in diverse ecosystems, but studying their impacts is technically and taxonomically challenging. Taxonomic complexities derive from undersampling, diverse DNA and RNA genomes with multiple evolutionary origins, and lack of a universal barcode gene. While virus ecogenomics has expanded access to and understanding of the virosphere, available classification tools poorly scale to modern discovery-based datasets, lack taxonomic resolution, and/or are unable to classify novel sequence space. Here we develop, benchmark, and release vConTACT3, a machine learning-based tool that improves scalability and accuracy, adds extensive user-requested features, expands classification to both eukaryote and prokaryote viruses for 4/6 officially recognized realms, and establishes accurate hierarchical taxonomy from genus to order. Application to 48,069 public virus genomes provided new taxonomy assignments for thousands of taxa, revealed support for fewer taxonomic ranks than currently available, and systematically identified taxonomically problematic areas across the virosphere.

bioinformatics↗

bioRxiv2025

RNA virus ecogenomics along a subarctic permafrost thaw gradient

Climate change thaws permafrost, which releases greenhouse gases partly from dormant microorganisms awakening and metabolizing organic matter. Though DNA viruses that infect these soil microbes have been studied, little is known on soil RNA viruses, which typically infect microeukaryotes. Here we identify and characterize 2,651 RNA viruses from a 4-year time series of bulk soil metatranscriptomes derived from the climatically fragile Stordalen Mire ecosystem --a long studied permafrost peatland. RNA virus diversity was structured by habitat (palsa, bog, and fen), and these patterns correlated with pH and carbon dioxide and methane emissions. Further, host prediction, virus-encoded metabolite-transforming and information-processing functions suggested roles in ecosystem-scale carbon fluxes and contribute to greenhouse gases emissions. Together, these RNA virus ecogenomic data in permafrost provide essential baseline information for integration into predictive models to support hypothesis testing.

microbiology↗

bioRxiv2025

From Archaea to the atmosphere: remotely sensing Arctic methane

Global atmospheric methane concentrations are rapidly rising and becoming isotopically more depleted, implying an unresolved microbial contribution. Rising Arctic temperatures are variably altering soil methane cycling, causing consequential uncertainty in the atmospheric methane budget. We demonstrated in an Arctic wetland that below-ground microbiota and methane-cycling features parallelled above-ground plant communities. To upscale emissions, we applied machine learning to remote sensing data to identify habitats, which were assigned average emissions. To upscale dynamically, we incorporated climate data, remotely-sensed water table variation, and habitat classes into a temporally-resolved biogeochemical model, to predict methane flux and isotope dynamics. This accurately estimated more depleted 13C-methane than previously used for Arctic habitats in global source partitioning. Remote-sensing of these rapidly changing inaccessible landscapes can thus help constrain the role of the Arctic in ongoing changes in global methane emissions.

microbiology↗

bioRxiv2022

kb_DRAM: Annotating and functional profiling of genomes with DRAM in KBase

SummaryAnnotation is predicting the location of and assigning function to genes in a genome. DRAM is a tool developed to annotate bacterial, archaeal and viral genomes derived from pure cultures or metagenomes. DRAM distills multiple gene annotations to summaries of functional potential. Despite these benefits, a downside of DRAM is processing requires large computation resources, which limits its accessibility, and it did not integrate with downstream metabolic modelling tools. To alleviate these constraints, DRAM and the viral counterpart, DRAM-v, are now available and integrated in the freely accessible KBase cyberinfrastructure. With kb_DRAM users can generate DRAM annotations and functional summaries from microbial or viral genomes in a point and click interface, as well as generate genome scale metabolic models from these DRAM annotations. Availability and ImplementationThe kb_DRAM software is available at https://github.com/shafferm/kb_DRAM. The kb_DRAM apps on KBase can be found in the catalog at https://narrative.kbase.us/#catalog/modules/kb_DRAM. A narrative with examples of running all KBase apps is available at https://kbase.us/n/88325/84/. ContactMichael Shaffer, michael.t.shaffer@colostate.edu; Kelly Wrighton, kelly.wrighton@colostate.edu Supplementary InformationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2020

MetaPop: A pipeline for macro- and micro-diversity analyses and visualization of microbial and viral metagenome-derived populations

BackgroundMicrobes and their viruses are hidden engines driving Earths ecosystems from the oceans and soils to humans and bioreactors. Though gene marker approaches can now be complemented by genome-resolved studies of inter- (macrodiversity) and intra- (microdiversity) population variation, analytical tools to do so remain scattered or under-developed. ResultsHere we introduce MetaPop, an open-source bioinformatic pipeline that provides a single interface to analyze and visualize microbial and viral community metagenomes at both the macro- and micro-diversity levels. Macrodiversity estimates include population abundances and - and {beta}-diversity. Microdiversity calculations include identification of single nucleotide polymorphisms, novel codon-constrained linkage of SNPs, nucleotide diversity ({pi} and {theta}) and selective pressures (pN/pS and Tajimas D) within and fixation indices (FST) between populations. MetaPop will also identify genes with distinct codon usage. Following rigorous validation, we applied MetaPop to the gut viromes of autistic children that underwent fecal microbiota transfers and their neurotypical peers. The macrodiversity results confirmed our prior findings for viral populations (microbial shotgun metagenomes were not available), that diversity did not significantly differ between autistic and neurotypical children. However, by also quantifying microdiversity, MetaPop revealed lower average viral nucleotide diversity ({pi}) in autistic children. Analysis of the percentage of genomes detected under positive selection was also lower among autistic children, suggesting that higher viral {pi} in neurotypical children may be beneficial because it allows populations to better bet hedge in changing environments. Further, comparisons of microdiversity pre- and post-FMT in the autistic children revealed that the delivery FMT method (oral versus rectal) may influence viral activity and engraftment of microdiverse viral populations, with children who received their FMT rectally having higher microdiversity post-FMT. Overall, these results show that analyses at the macro-level alone can miss important biological differences. ConclusionsThese findings suggest that standardized population and genetic variation analyses will be invaluable for maximizing biological inference, and MetaPop provides a convenient tools package to explore the dual impact of macro- and micro-diversity across microbial communities.

bioinformatics↗

bioRxiv2020

Cenote-Taker 2 Democratizes Virus Discovery and Sequence Annotation

Viruses, despite their great abundance and significance in biological systems, remain largely mysterious. Indeed, the vast majority of the perhaps hundreds of millions of viral species on the planet remain undiscovered. Additionally, many viruses deposited in central databases like GenBank and RefSeq are littered with genes annotated as "hypothetical protein" or the equivalent. Cenote-Taker2, a virus discovery and annotation tool available on command line and with a graphical user interface with free high-performance computation access, utilizes highly sensitive models of hallmark virus genes to discover familiar or divergent viral sequences from user-input contigs. Additionally, Cenote-Taker2 uses a flexible set of modules to automatically annotate the sequence features of contigs, providing more gene information than comparable tools. The outputs include readable and interactive genome maps, virome summary tables, and files that can be directly submitted to GenBank. We expect Cenote-Taker2 to facilitate virus discovery, annotation, and expansion of the known virome.

microbiology↗

bioRxiv2020

DRAM for distilling microbial metabolism to automate the curation of microbiome function

Microbial and viral communities transform the chemistry of Earths ecosystems, yet the specific reactions catalyzed by these biological engines are hard to decode due to the absence of a scalable, metabolically resolved, annotation software. Here, we present DRAM (Distilled and Refined Annotation of Metabolism), a framework to translate the deluge of microbiome-based genomic information into a catalog of microbial traits. To demonstrate the applicability of DRAM across metabolically diverse genomes, we evaluated DRAM performance on a defined, in silico soil community and previously published human gut metagenomes. We show that DRAM accurately assigned microbial contributions to geochemical cycles, and automated the partitioning of gut microbial carbohydrate metabolism at substrate levels. DRAM-v, the viral mode of DRAM, established rules to identify virally-encoded auxiliary metabolic genes (AMGs), resulting in the metabolic categorization of thousands of putative AMGs from soils and guts. Together DRAM and DRAM-v provide critical metabolic profiling capabilities that decipher mechanisms underpinning microbiome function.

microbiology↗

bioRxiv2019

The human gut virome database

The gut microbiome profoundly impacts human health and disease, but viruses that infect these microbes are likely also important. Problematically, viral sequences are often missed due to insufficient reference viral genomes. Here we (i) built a human gut virome database, GVD, from 648 viral particle metagenomes or microbial metagenomes from 572 individuals previously searched for viruses, (ii) assessed its effectiveness, and (iii) conducted meta-analyses. GVD contains 13,203 unique viral populations (approximately species-level taxa) organized into 702 novel genera, which roughly doubles known phage genera and improves viral detection rates over NCBI viral RefSeq nearly 60-fold. Applying GVD, we assessed and rejected the idea of a core gut virome in healthy individuals, and found through meta-analyses that technical artifacts are more impactful than any treatment effect across the entire meta-study dataset. Together, this foundational resource and these findings will help human microbiome researchers better identify viral roles in health and disease.

bioinformatics↗

bioRxiv2019

Gene sharing networks to automate genome-based prokaryotic viral taxonomy

Viruses of bacteria and archaea are likely to be critical to all natural, engineered and human ecosystems, and yet their study is hampered by the lack of a universal or scalable taxonomic framework. Here, we introduce vConTACT 2.0, a network-based application to establish prokaryotic virus taxonomy that scales to thousands of uncultivated virus genomes, and integrates confidence scores for all taxonomic predictions. Performance tests using vConTACT 2.0 demonstrate near-identical correspondence to the current official viral taxonomy (>85% genus-rank assignments at 96% accuracy) through an integrated distance-based hierarchical clustering approach. Beyond "known viruses", we used vConTACT 2.0 to automatically assign 1,364 previously unclassified reference viruses to tentative taxa, and scaled it to modern metagenomic datasets for which the reference network was robust to adding 16,000 viral contigs. Together these efforts provide a systematic reference network and an accurate, scalable taxonomic analysis tool that is critically needed for the research community.

bioinformatics↗

bioRxiv2018

Soil viruses are underexplored players in ecosystem carbon processing

Rapidly thawing permafrost harbors ~30-50% of global soil carbon, and the fate of this carbon remains unknown. Microorganisms will play a central role in its fate, and their viruses could modulate that impact via induced mortality and metabolic controls. Because of the challenges of recovering viruses from soils, little is known about soil viruses or their role(s) in microbial biogeochemical cycling. Here, we describe 53 viral populations (vOTUs) recovered from seven quantitatively-derived (i.e. not multiple-displacement-amplified) viral-particle metagenomes (viromes) along a permafrost thaw gradient. Only 15% of these vOTUs had genetic similarity to publicly available viruses in the RefSeq database, and ~30% of the genes could be annotated, supporting the concept of soils as reservoirs of substantial undescribed viral genetic diversity. The vOTUs exhibited distinct ecology, with dramatically different distributions along the thaw gradient habitats, and a shift from soil-virus-like assemblages in the dry palsas to aquatic-virus-like in the inundated fen. Seventeen vOTUs were linked to microbial hosts (in silico), implicating viruses in infecting abundant microbial lineages from Acidobacteria, Verrucomicrobia, and Deltaproteoacteria, including those encoding key biogeochemical functions such as organic matter degradation. Thirty-one auxiliary metabolic genes (AMGs) were identified, and suggested viral-mediated modulation of central carbon metabolism, soil organic matter degradation, polysaccharide-binding, and regulation of sporulation. Together these findings suggest that these soil viruses have distinct ecology, impact host-mediated biogeochemistry, and likely impact ecosystem function in the rapidly changing Arctic.

microbiology↗