Biology subjects

Woodcroft, B. J.

Publications and source records attributed to Woodcroft, B. J..

At least 19 recordsLinked to original sources

bioRxiv2026

Models trained with noisy genomes extend bacterial phenotype prediction into deep time

Predicting phenotype from genotype in extant organisms is increasingly tractable through the accumulation of genome sequences and the development of machine-learning algorithms. Here we show that machine learning can be applied to reconstructed ancestral gene content, extending these predictions into the past. We trained models on a diverse set of bacterial phenotypes and found that introducing noise into gene content profiles allows predictions to generalize over larger evolutionary distances. For phenotypes with signal spread across many genes - such as metabolic oxygen use, cell envelope architecture and optimal growth temperature - noise augmentation extends resolution back to the root of the bacterial domain, while for other phenotypes - including GC content and sporulation - the range remains more limited. We therefore conclude that the last bacterial common ancestor (LBCA) was likely an anaerobic, double-membraned, and moderately thermophilic bacterium (46-75{degrees}C). Moreover, this work provides a general approach for learning about the genomic basis of phenotypes and drawing inferences about their early evolution.

evolutionary biology↗

bioRxiv2025

Occurrence and temporal dynamics of denitrifying protist endosymbionts in the wastewater microbiome

Effective wastewater treatment is of critical importance for preserving public health and protecting natural environments. Key processes in wastewater treatment, such as denitrification, are performed by a diverse community of prokaryotic and eukaryotic microbes. However, the diversity of the microbiome and the potential role of the different microbial taxa in some wastewater treatment plant setups is not fully understood. We aimed to investigate the presence and diversity of denitrifying bacteria of the candidate family Azoamicaceae that form obligate symbioses with protists in wastewater treatment plants. Our analyses showed that denitrifying endosymbionts belonging to the Ca. Azoamicus genus are present in 20-50% of wastewater treatment plants worldwide. Time-resolved amplicon data from four Danish wastewater treatment plants showed high temporal fluctuations in the abundance and composition of the denitrifying endosymbiont community. Fifteen high-quality metagenome-assembled genomes of denitrifying endosymbionts, four of which were circular, were recovered. Genome annotation showed that a newly described, globally widespread species, Ca. Azoamicus parvus, lacked a nitrous oxide reductase, suggesting that its denitrification pathway is incomplete. This observation further expands the diversity of metabolic potentials found in denitrifying endosymbionts and indicates that the contribution of microbial eukaryote holobionts to the wastewater ecosystem dynamics of nitrogen removal and greenhouse gas production may have been underestimated and needs further study.

microbiology↗

bioRxiv2025

Mobile genetic elements that shape microbial diversity and functions inthawing permafrost soils

The worlds ecosystems are shaped by microbiota. Their niches and their impacts depend on functional profiles influenced by gene gains and losses. While culture-based experiments demonstrate that mobile genetic elements (MGEs) can mediate gene flux, quantitative field data on the rates and impacts of MGE activity remains scarce. Here we leverage large-scale soil meta-omic data to develop and apply analytics for studying MGEs in complex natural systems. In our model permafrost-thaw ecosystem, Stordalen Mire, we identify [~]2.1 million MGE recombinases across 89 microbial phyla to assess ecological distributions, affected functions, past mobility, and current activity. This revealed MGEs shaping natural genetic diversity via differential impacts on major phyla; affecting a wide range of functions, including diverse regulatory and metabolic genes affecting carbon flux and nutrient cycling; and moving at rates that should significantly influence the realized functional profiles of natural microbiomes. These findings and this systematic meta-omic framework open new avenues to better investigate MGE diversity, activity, mobility, and impacts in nature.

microbiology↗

bioRxiv2024

Bin Chicken: targeted metagenomic coassembly for the efficient recovery of novel genomes

Recovery of microbial genomes from metagenomic datasets has provided genomic representation for hundreds of thousands of species from diverse biomes. However, low abundance microorganisms are often missed due to insufficient genomic coverage. Here we present Bin Chicken, an algorithm which substantially improves genome recovery through automated, targeted selection of metagenomes for coassembly based on shared marker gene sequences derived from raw reads. Marker gene sequences that are divergent from known reference genomes can be further prioritised, providing an efficient means of recovering highly novel genomes. Applying Bin Chicken to public metagenomes and coassembling 800 sample-groups recovered 77,562 microbial genomes, including the first genomic representatives of 6 phyla, 41 classes, and 24,028 species. These genomes expand the genomic tree of life and uncover a wealth of novel microbial lineages for further research.

microbiology↗

bioRxiv2024

CompareM2 is a genomes-to-report pipeline for comparing microbial genomes

Here, we present CompareM2, a genomes-to-report pipeline for comparative analysis of bacterial and archaeal genomes derived from isolates and metagenomic assemblies. CompareM2 is easy to install and operate, and integrates community-adopted tools to perform genome quality control and annotation, taxonomic and functional predictions, as well as comparative analyses of core- and pan-genome partitions and phylogenetic relations. The central results generated via the CompareM2 workflow are emphasized in a portable dynamic report document. CompareM2 is free software and welcomes modifications and pull requests from the community on its Git repository at https://github.com/cmkobel/comparem2.

bioinformatics↗

bioRxiv2024

Microflora Danica: the atlas of Danish environmental microbiomes

The last 20 years have witnessed unprecedented advances in revealing the microbiomes underpinning important processes in natural and human associated environments. Recent large-scale metagenome surveys record the variety of microbial life in the oceans1, wastewater2, human gut3,4, and earth5,6, with compilations encompassing thousands of public datasets7-13. So far, large-scale microbiome studies either miss functional information or consistency in sample processing, and although they may cover thousands of locations, these are missing resolution, sparsely located, or lacking metadata. Here, we present Microflora Danica, an atlas of Danish environmental microbiomes, encompassing 10,686 shotgun metagenomes and 449 full-length 16S and 18S rRNA datasets linked to a detailed 5 level habitat classification scheme. We determine that while human-disturbed habitats have high alpha diversity, the same species reoccur, revealing hidden homogeneity and underlining the importance of natural systems for total species (gamma) diversity. In-depth studies of nitrifiers, a functional group closely linked to climate change, challenge existing perceptions regarding habitat preference and discover several novel nitrifiers as more abundant than canonical nitrifiers. Together, the Microflora Danica dataset provides an unprecedented resource and the foundation for answering fundamental questions underlying microbial ecology: what drives microbial diversity, distribution and function.

microbiology↗

bioRxiv2024

Quantifying microbial DNA in metagenomes improves microbial trait estimation

Shotgun metagenomics is a powerful tool for studying the genomic traits of microbial community members, such as genome size, gene content, etc. While such traits can be used to better understand the ecology and evolution of microbial communities, the accuracy of their estimations can be critically influenced by both known and unknown factors. One factor that can bias trait estimations is the proportion of eukaryotic DNA in a metagenome, as some bioinformatic tools assume that all DNA reads in a metagenome are non-eukaryotic. Here, we help resolve a recent debate about the influence of eukaryotic DNA in the estimation of average genome size from a global soil sample dataset using a new bioinformatic tool. Contrary to what was assumed, our reanalysis of this dataset revealed that soil samples can contain a substantial proportion of eukaryotic DNA ([~]38.8%), which severely inflated average genome size estimates. We report that correcting for this bias significantly improves the statistical support for the negative relationship between average bacterial genome size and soil pH. These results highlight that metagenomes can contain large quantities of eukaryotic DNA, and that new methods that correct for this can improve microbial trait estimation.

microbiology↗

bioRxiv2024

Large-scale estimation of bacterial and archaeal DNA prevalence in metagenomes reveals biome-specific patterns

Metagenomes often contain many reads derived from eukaryotes. However, there is usually no reliable method for estimating the prevalence of non-microbial reads in a metagenome, forcing many analysis techniques to make the often-faulty assumption that all reads are microbial. For instance, the success of metagenome-assembled genome (MAG) recovery efforts is assessed by the number of reads mapped to recovered MAGs, a procedure which will underestimate the true fidelity if eukaryotic reads are present. Here we present "SingleM microbial_fraction" (SMF), a scalable algorithm that robustly estimates the number of bacterial and archaeal reads in a metagenome, and the average microbial genome size. SMF does not use eukaryotic reference genome data and can be applied to any Illumina metagenome. Based on SMF, we propose the "Domain-Adjusted Mapping Rate" (DAMR) as an improved metric to assess microbial genome recovery from metagenomes. We benchmark SMF on simulated and real data, and demonstrate how DAMRs can guide genome recovery. Applying SMF to 136,284 publicly available metagenomes, we report substantial variation in microbial fractions and biome-specific patterns of microbial abundance, providing insights into how microorganisms and eukaryotes are distributed across Earth. Finally, we show that substantial amounts of human host DNA sequence data have been deposited in public metagenome repositories, possibly counter to ethical directives that mandate screening of these reads prior to release. As the adoption of metagenomic sequencing continues to grow, we foresee SMF being a valuable tool for the appraisal of genome recovery efforts, and the recovery of global patterns of microorganism distribution.

bioinformatics↗

bioRxiv2024

SingleM and Sandpiper: Robust microbial taxonomic profiles from metagenomic data

Determining the taxonomy and relative abundance of microorganisms in metagenomic data is a foundational problem in microbial ecology. To address the limitations of existing approaches, we developed SingleM, which estimates community composition using conserved regions within universal marker genes. SingleM accurately profiles complex communities of known microbial species, and is the only tool that detects species without genomic representation, even those representing novel phyla. Given SingleMs computational efficiency, we applied it to 248,559 publicly available metagenomes and show that the vast majority of samples from marine, freshwater, sediment and soil environments are dominated by novel species lacking genomic representation (median relative abundance 75.0%). SingleM also provides a way to identify metagenomes for the recovery of novel metagenome-assembled genomes from lineages of interest, and can incorporate user-recovered genomes into its reference database to improve profiling resolution. Quantifying the full diversity of Bacteria and Archaea in metagenomic data shows that microbial genome databases are far from saturated.

microbiology↗

bioRxiv2023

An evolutionary timescale for Bacteria calibrated using the Great Oxidation Event

Most of lifes diversity and history is microbial but it has left a meagre fossil record, greatly hindering understanding of evolution in deep time. However, the co-evolution of life and the Earth system has left signatures of bacterial metabolism in the geochemical record, most conspicuously the Great Oxidation Event (GOE) [~]2.33 billion years ago (Ga, (Poulton et al. 2021)), in which oxygenic photosynthesis and tectonism (Eguchi, Seales, and Dasgupta 2019) transformed Earths biosphere from dominantly anaerobic to aerobic. Here, we combine machine learning and phylogenetic reconciliation to infer ancestral transitions to aerobic lifestyles during bacterial evolution. Linking these transitions to the GOE provides new constraints to infer the timetree of Bacteria. We find that extant bacterial phyla are truly ancient, having radiated in the Archaean and the Proterozoic: the oldest include Bacillota (Firmicutes), which radiated 3.1-3.7 Ga, Cyanobacteria (3.3-3.5 Ga) and Patescibacteria (3-3.5 Ga). We show that most bacterial phyla were ancestrally anaerobic and that most transitions to an aerobic lifestyle post-dated the GOE. Our analyses trace oxygen production and consumption back to Cyanobacteria. From that starting point, horizontal transfer seeded aerobic lifestyles across bacterial diversity over hundreds of millions of years. Our analyses demonstrate that the diversification of aerobes proceeded in two waves corresponding to the GOE and to a second sustained rise in atmospheric O2 at the dawn of the Palezoic (Krause et al. 2022).

evolutionary biology↗

bioRxiv2023

Borg extrachromosomal elements of methane-oxidizing archaea have conserved and expressed genetic repertoires

Borgs are huge extrachromosomal elements (ECE) of anaerobic methane-consuming "Candidatus Methanoperedens" archaea. Here, we used nanopore sequencing to validate published complete genomes curated from short reads and to reconstruct new genomes. 13 complete and four near-complete linear genomes share 40 genes that define a largely syntenous genome backbone. We use these conserved genes to identify new Borgs from peatland soil and to delineate Borg phylogeny, revealing two major clades. Remarkably, Borg genes encoding OmcZ nanowire-like electron-exporting cytochromes and cell surface proteins are more highly expressed than those of host Methanoperedens, indicating that Borgs augment the Methanoperedens activity in situ. We reconstructed the first complete 4.00 Mbp genome for a Methanoperedens that is inferred to be a Borg host and predicted its methylation motifs, which differ from pervasive TC and CC methylation motifs of the Borgs. Thus, methylation may enable Methanoperedens to distinguish their genomes from those of Borgs. Very high Borg to Methanoperedens ratios and structural predictions suggest that Borgs may be capable of encapsulation. The findings clearly define Borgs as a distinct class of ECE with shared genomic signatures, establish their diversification from a common ancestor with genetic inheritance, and raise the possibility of periodic existence outside of host cells.

microbiology↗

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

Methylotrophy in the Mire: direct and indirect routes for methane production in thawing permafrost

While wetlands are major sources of biogenic methane (CH4), our understanding of resident microbial metabolisms is incomplete, which compromises prediction of CH4 emissions under ongoing climate change. Here, we employed genome-resolved multi-omics to expand our understanding of methanogenesis in the thawing permafrost peatland of Stordalen Mire, in arctic Sweden. In quadrupling the genomic representation of the sites methanogens and examining their encoded metabolisms, we revealed that nearly 20% (72) of the metagenome-assembled genomes (MAGs) encoded potential for methylotrophic methanogenesis. Further, 27% of the transcriptionally active methanogens expressed methylotrophic genes; for Methanosarcinales and Methanobacteriales MAGs, these data indicated use of methylated oxygen compounds (e.g., methanol), while for Methanomassiliicoccales, they primarily implicated methyl sulfides and methylamines. In addition to methanogenic methylotrophy, >1700 bacterial MAGs across 19 phyla encoded anaerobic methylotrophic potential, with expression across 12 phyla. Metabolomic analyses revealed the presence of diverse methylated compounds in the Mire, including some known methylotrophic substrates. Active methylotrophy was observed across all stages of a permafrost thaw gradient in Stordalen, with the most frozen non-methanogenic palsa found to host bacterial methylotrophy, and the partially thawed bog and fully thawed fen seen to house both methanogenic and bacterial methylotrophic activity. Methanogenesis across increasing permafrost thaw is thus revised from sole dominance of hydrogenotrophic production, and the appearance of acetoclastic at full thaw, to consider co-occurrence of methylotrophy throughout. Collectively, these findings indicate that methanogenic and bacterial methylotrophy may be an important and previously underappreciated component of carbon cycling and emissions in these rapidly changing wetland habitats.

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↗

bioRxiv2022

CheckM2: a rapid, scalable and accurate tool for assessing microbial genome quality using machine learning

Advances in DNA sequencing and bioinformatics have dramatically increased the rate of recovery of microbial genomes from metagenomic data. Assessing the quality of metagenome-assembled genomes (MAGs) is a critical step prior to downstream analysis. Here, we present CheckM2, an improved method of predicting the completeness and contamination of MAGs using machine learning. We demonstrate the effectiveness of CheckM2 on synthetic and experimental data, and show that it outperforms the original version of CheckM in predicting MAG quality. CheckM2 is substantially faster than CheckM and its database can be rapidly updated with new high-quality reference genomes. We show that CheckM2 accurately predicts genome quality for MAGs from novel lineages, even those with sparse genomic representation, or reduced genome size (e.g. symbionts) such as those found in the Patescibacteria and the DPANN superphylum. CheckM2 provides accurate genome quality predictions across the microbial tree of life, giving increased confidence when inferring novel biological conclusions from MAGs.

bioinformatics↗

bioRxiv2021

Recoding enhances the metabolic capabilities of two novel methylotrophic Asgardarchaeota lineages

Asgardarchaeota have been proposed as the closest living relatives to eukaryotes, and a total of 72 metagenome-assembled genomes (MAGs) representing six primary lineages in this archaeal phylum have thus far been described. These organisms are predicted to be fermentative organoheterotrophs contributing to carbon cycling in sediment ecosystems. Here, we double the genomic catalogue of Asgardarchaeota by obtaining 71 MAGs from a range of habitats around the globe, including deep subsurface, shallow lake, and geothermal spring sediments. Phylogenomic inferences followed by taxonomic rank normalisation confirmed previously established Asgardarchaeota classes and revealed four novel lineages, two of which were consistently recovered as monophyletic classes. We therefore propose the names Candidatus Hodarchaeia class nov. and Cand. Jordarchaeia class nov., derived from the gods Hod and Jord in Norse mythology. Metabolic inference suggests that both novel classes represent methylotrophic acetogens, encoding the transfer of methyl groups, such as methylated amines, to coenzyme M with acetate as the end product in remnants of a methanogen-derived core metabolism. This inferred mode of energy conservation is predicted to be enhanced by genetic code expansions, i.e. recoding, allowing the incorporation of the rare 21st and 22nd amino acids selenocysteine (Sec) and pyrrolysine (Pyl). We found Sec recoding in Jordarchaeia and all other Asgardarchaeota classes, which likely benefit from increased catalytic activities of Sec-containing enzymes. Pyl recoding on the other hand is restricted to Hodarchaeia in the Asgardarchaeota, making it the first reported non-methanogenic lineage with an inferred complete Pyl machinery, likely providing this class with an efficient mechanism for methylamine utilisation. Furthermore, we identified enzymes for the biosynthesis of ester-type lipids, characteristic of Bacteria and Eukaryotes, in both novel classes, supporting the hypothesis that mixed ether-ester lipids are a shared feature among Asgardarchaeota.

microbiology↗

bioRxiv2020

Undinarchaeota illuminate the evolution of DPANN archaea

Introductory paragraphThe evolution and diversification of Archaea is central to the history of life on Earth. Cultivation-independent approaches have revealed the existence of at least ten archaeal lineages whose members have small cell and genome sizes and limited metabolic capabilities and together comprise the tentative DPANN archaea. However, the phylogenetic diversity of DPANN and the placement of the various lineages of this group in the archaeal tree remain debated. Here, we reconstructed additional metagenome assembled genomes (MAGs) of a thus far uncharacterized archaeal phylum-level lineage UAP2 (Candidatus Undinarchaeota) affiliating with DPANN archaea. Comparative genome analyses revealed that members of the Undinarchaeota have small estimated genome sizes and, while potentially being able to conserve energy through fermentation, likely depend on partner organisms for the acquisition of vitamins, amino acids and other metabolites. Phylogenomic analyses robustly recovered Undinarchaeota as a major independent lineage between two highly supported clans of DPANN: one clan comprising Micrarchaeota, Altiarchaeota and Diapherotrites, and another encompassing all other DPANN. Our analyses also suggest that DPANN archaea may have exchanged core genes with their hosts by horizontal gene transfer (HGT), adding to the difficulty of placing DPANN in the archaeal tree. Together, our findings provide crucial insights into the origins and evolution of DPANN archaea and their hosts.

evolutionary biology↗

bioRxiv2020

Diverse Arctic lake sediment microbiota shape methane emission temperature sensitivity

Northern post-glacial lakes are a significant and increasing source of atmospheric carbon (C), largely through ebullition (bubbling) of microbially-produced methane (CH4) from the sediments1. Ebullitive CH4 flux correlates strongly with temperature, suggesting that solar radiation is the primary driver of these CH4 emissions2. However, here we show that the slope of the temperature-CH4 flux relationship differs spatially, both within and among lakes. Hypothesizing that differences in microbiota could explain this heterogeneity, we compared site-specific CH4 emissions with underlying sediment microbial (metagenomic and amplicon), isotopic, and geochemical data across two post-glacial lakes in Northern Sweden. The temperature-associated increase in CH4 emissions was greater in lake middles--where methanogens were more abundant--than edges, and sediment microbial communities were distinct between lake edges and middles. Although CH4 emissions projections are typically driven by abiotic factors1, regression modeling revealed that microbial abundances, including those of CH4-cycling microorganisms and syntrophs that generate H2 for methanogenesis, can be useful predictors of porewater CH4 concentrations. Our results suggest that deeper lake regions, which currently emit less CH4 than shallower edges, could add substantially to overall CH4 emissions in a warmer Arctic with longer ice-free seasons and that future CH4 emission predictions from northern lakes may be improved by accounting for spatial variations in sediment microbiota.

microbiology↗