Biology subjects

Quince, C.

Publications and source records attributed to Quince, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Widespread detection of Polyethylene glycol reveals chronic human exposure through pharmaceutical drugs

Polyethylene glycol (PEG) is a synthetic polymer ubiquitous in pharmaceuticals, personal care products, food additives, and industrial manufacturing. Despite its widespread use and potential importance as an exposure chemical, the prevalence of PEG exposure and its excretion in human populations remain largely uncharacterized. Moreover, PEG detected in human biofluids is frequently assumed to arise from analytical contamination during sample preparation, potentially obscuring its contribution to the human exposome and confounding metabolic phenotyping studies. Here, we show that PEG is as component of the human xenobiotic exposome and is further metabolized into PEG hydoxy acid and diacid metabolites in humans. We further find that PEG exposure is associated with alterations in microbiome composition and short-chain fatty acid metabolism, suggesting its biological impact of its exposure. We identify PEG exposure in approximately 2.3% of publicly available metabolomics data files and provide a reusable 85,484 candidate PEG and PEGylated MS/MS spectral library for future use for the metabolomic community. Together, these findings establish PEG signal in human biofluids can reflect genuine exposure, and that PEG exposure is neither metabolically inert nor biologically silent.

biochemistry↗

bioRxiv2026

Advancing long-read metagenomic binning via single-copy-gene guided contrastive learning

Long-read sequencing advances metagenomics by producing highly contiguous assemblies and more complete metagenome-assembled genomes (MAGs). However, current long-read metagenomic binners fail to incorporate the rich information of long-read assemblies into representation learning and exhibit limited performance on complex datasets. Here, we show that a higher proportion of long-read assembled contigs contain single-copy genes (SCGs) and more SCGs per contig. Therefore, we developed SCGBinner, which leverages SCG-guided contrastive learning to exploit the advantage of long-read data for learning high-quality contig embeddings. SCGBinner consistently outperforms other binning methods across five simulated and seven real-world long-read datasets, especially on real-world high-diversity samples. For a deep agricultural soil metagenome, SCGBinner recovered 71% more high-quality MAGs and 38% more near-complete MAGs than the second-best method. Notably, SCGBinner uniquely recovered 449 novel high-quality species, which shed light on the predicted ecological roles of 65 uncharacterised families and 93 novel genera. Overall, SCGBinner could harness the potential of long-read sequencing to provide unprecedented insights into the microbial dark matter of complex microbial communities.

bioinformatics↗

bioRxiv2026

REMAG: recovery of eukaryotic genomes from metagenomic data using contrastive learning

Metagenome-assembled genomes (MAGs) are central to exploring microbial communities. Yet, despite the relevance of protists and fungi to diverse ecosystems, eukaryotic MAG recovery lags behind that of prokaryotes. A major bottleneck is that most state-of-the-art binning pipelines exclusively rely on prokaryotic single-copy core gene reference databases and are optimized for smaller genomes. To address this gap, we present REMAG (Recovery of Eukaryotic MAGs), a tool designed to recover high-quality eukaryotic genomes suited for longread metagenomic data. REMAG leverages finetuned HyenaDNA genomic foundation models to efficiently filter eukaryotic contigs. It then employs a dual-encoder Siamese network trained with Barlow Twins contrastive loss to learn a shared embedding space by integrating contig composition and differential coverage. Finally, high-quality bins are extracted using greedy iterative Leiden clustering optimized with eukaryotic single-copy core gene constraints. In benchmarks based on simulated mixed prokaryotic/eukaryotic communities and real datasets of varying sizes and origin, we demonstrate REMAGs ability to recover more near-complete eukaryotic genomes than existing state-of-the-art tools, which often produce highly fragmented eukaryotic bins. REMAG provides an automated eukaryotic binning method that scales effectively with the increasing size and sequencing depth of metagenomic datasets.

bioinformatics↗

bioRxiv2025

SNooPy: a statistical framework for long-read metagenomic variant calling

Current long-read single-nucleotide variant callers were designed primarily for genomic data--particularly human genomes. While some have been used on metagenomic data, their underlying assumptions and training procedures fail to account for the inherent complexity of metagenomic samples. To date, no long-read variant caller has been purpose-built for metagenomic applications. To address this gap, we present SNooPy, a SNP-calling tool that implements a new statistical framework tailored to long-read metagenomic data. Unlike previous genomic methods, our approach makes no assumptions about the number of haplotypes present, their evolutionary relationships, or their sequence divergence. We demonstrate that SNooPy outperforms both traditional statistical and deep learning-based SNP callers. Our results suggest that future integration of this framework with deep learning approaches could further enhance variant calling performance. SNooPy is freely available on github.com/rolandfaure/snoopy.

bioinformatics↗

bioRxiv2025

Inferring antibiotic resistance selection in the environment can be confounded by correlations between resistance genes and unrelated functional traits

Antimicrobial resistance (AMR) is a silent pandemic that is coupled with other crises such as climate change in the polycrisis humanity is facing. One of the key questions is whether antibiotic resistance genes (ARGs) are selected for at the low antibiotic concentrations typical for most environments. Many studies have observed changes in the relative abundance of ARGs from one environmental compartment to the next, e.g. from wastewater treatment plant influent to effluent. Fewer studies have directly tested for selection by incubating environmental samples in mesocosms or laboratory models at different concentrations of antibiotics to infer minimal selective concentrations. We developed a mathematical model to demonstrate that these studies can be confounded by shifts in the microbial community composition that occur when a microbiome is transported from one environmental compartment to another or when incubated under different conditions. Such community shifts will confound tests of selection when there is an association between carriage of ARGs and other functional traits. As an example, we show that there is a phylum-dependent association between the number of ARGs and the number of ribosomal RNA genes, which are both higher in fast growing, copiotrophic bacteria. We then show that specific growth rate or nutrient concentration upshifts increased the proportion of copiotrophs in the community and thus the relative abundance of ARGs. This result generalizes to community shifts for other reasons if there is some association between ARGs and ecological niches. Therefore, most studies of selection for ARGs in the environment are confounded. Solutions are proposed. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/681873v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1ea4638org.highwire.dtl.DTLVardef@1a8471dorg.highwire.dtl.DTLVardef@d4d127org.highwire.dtl.DTLVardef@1ef891b_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIARG copy numbers are correlated with 16S rRNA gene copy numbers C_LIO_LIHigh rRNA gene numbers are typical for copiotrophs, which have high growth rates C_LIO_LIHence, copiotrophs tend to have higher ARG numbers C_LIO_LIChanges in environmental conditions that increase copiotrophs increase ARGs C_LIO_LIThus, ARGs can increase without selection due to shifts in community composition C_LI

microbiology↗

bioRxiv2025

Optimizing storage, high-molecular weight DNA extraction and genome reconstructions from human faecal samples.

Metagenomic sequencing has become an essential tool for assessing the composition and functional potential of microbial communities. However, established metagenomic DNA extraction protocols are limited by trade-offs between universal taxonomic representation, DNA quality, quantity and molecule length, making them mostly unsuitable for 3rd generation sequencing. MethodsWe assessed the effectiveness of high molecular weight (HMW) DNA workflows from faecal samples, using different combinations of collection, storage and extraction kits. Faecal samples were either immediately processed, frozen at -80{degrees}C or stored in DNA/RNA Shield, GutAlive or OMNIgeneGUT and then subjected to three different DNA isolation kits, each modified for mechanical, chemical and enzymatic cell lysis steps, totalling 32 evaluated combinations. Isolated DNA was assessed for its quality and quantity, while taxonomic consistency was evaluated using metataxonomics and validated with metagenomic sequencing. ResultsThe yield of HMW DNA differed substantially between storage and DNA extraction protocols. Specifically, storage protocol had the highest impact on HMW DNA recovery, with DNA/RNA Shield storage yielding on average 51% more HMW DNA >30kb. Similarly, the sample storage had independently the effect size of R2 = 26.9% on the microbiome composition, and since the DNA extraction protocol in our study inherently combines both DNA extraction kit and lysis type, the latter had the largest effect size (R2 = 12.8%). While all kits had specific dis/advantages and biases, DNA/RNA Shield and Maxwell RSC PureFood GMO and Authentication kit performed best overall for long-read metagenomics. The protocol was validated on a) isolate genomes and b) 4 faecal samples, demonstrating both increased DNA yield at >30kb molecule length. Using the MG-TK pipeline these metagenomes yielded genomes on average, per sample, 48 Pacific Biosciences (PacBio) and 55 Oxford Nanopore Technologies (ONT) circular bacterial metagenomic assembled genomes. ConclusionThe current gold-standard of freezing faecal samples was surprisingly inconsistent and inefficient for long-read metagenomics, necessitating rethinking gut microbial study designs. We provide a simple and cheap protocol that preserves both taxonomic composition and HMW DNA quality, while our bioinformatics workflow allows for complete bacterial genome reconstruction.

molecular biology↗

bioRxiv2025

Geographic Variation and Host Genetics Shape the Human Skin Microbiome

The human skin microbiome is shaped by a complex interplay of host physiology, environmental exposure, and microbial interactions across domains of life. However, the relative contributions of host genetics and geography remain unresolved. Here, we present the first application of ultra-low coverage human genome imputation from skin metagenomic data, analysing 1,756 samples from multiple skin types and timepoints, with matched genotypes from 327 individuals across five countries. We also generate expanded Skin Microbial Genome Collection (eSMGC), comprising 675 prokaryotic, 12 fungal, 2,344 viral, and 4,935 plasmid genomes, correcting extensive false positives in existing references. Intercountry comparisons reveal that geography explains more microbiome variation than skin type, and that host genetics contributes previously uncharacterized structure--exemplified by distinct profiles in Chinese individuals. Genome-wide association analysis identifies 107 SNPs linked to 22 microbial taxa, including phages and plasmids, implicating host genes in skin structure, immunity, and lipid metabolism. Cutibacterium acnes and its phages exhibit geographic divergence and phage-host co-adaptation. Finally, host-infecting viruses, particularly papillomaviruses, are associated with elevated microbial diversity and immune-modulatory functions. These findings establish host genetics as a determinant of skin microbiome ecology and highlight the value of multi-domain, geographically diverse analyses.

microbiology↗

bioRxiv2025

High-quality metagenome assembly from nanopore reads with nanoMDBG

Third-generation long-read sequencing technologies, have been shown to significantly enhance the quality of metagenome assemblies. The results obtained using the highly accurate reads generated by PacBio HiFi have been particularly notable yielding hundreds of circularized, complete genomes as metagenome-assembled genomes (MAGs) without manual intervention. Oxford Nanopore Technologies (ONT) has recently improved the accuracy of its sequencing reads, achieving a per-base error rate of approximately 1-2%. Given the high-throughput, convenience and low-cost of ONT sequencing this could accelerate the uptake of long read metagenomics. However, current metagenome assemblers are optimized for PacBio HiFi data and underperform on the latest ONT data and do not scale to the large data sets that it enables. We present nanoMDBG, an evolution of the metaMDBG HiFi assembler, designed to support newer ONT sequencing data through a novel pre-processing step that performs fast and accurate error correction in minimizer-space. Across a range of ONT datasets, including a large 400 Gbp soil sample sequenced specifically for this study, nanoMDBG reconstructs up to twice as many high-quality MAGs as the next best ONT assembler, metaFlye, while requiring a third of the CPU time and memory. As a result of these advances, we show that the latest ONT technology can now produce results comparable to those obtained using PacBio HiFi sequencing at the same sequencing depth.

bioinformatics↗

bioRxiv2025

Rapid Assembly and Functional Differentiation of the Soil Surface Microbiome in Temperate Agricultural soil

The surface of dryland soils is typically covered by biological soil crusts (BSC) dominated by cyanobacteria, lichens or moss which contribute key ecosystem functions. However, while photosynthetic biota have been observed on the surface of temperate agricultural soils, understanding of the development, biodiversity and functional significance of these communities is extremely limited. We investigated the temporal development of the soil surface community following tillage and during subsequent growth of a wheat crop. Amplicon analysis showed that establishment of the soil surface microbiome was rapid over the winter period, with distinct communities of phototrophs, bacteria and protists detected 60 days after tillage. There was rapid succession with yellow-green algae (Xanthophyceae) dominating early stages of development, followed by Cyanobacteria and Charophytes and finally moss. Temporal dynamics of fungal and protist communities was influenced by eDNA deposition from plant pathogens inhabiting the crop canopy and wild animal parasites. For all groups, assembly processes in the surface soil became increasingly dominated by dispersal limitation over time while assembly of bulk soil communities became predominantly influenced by drift. Metagenome analysis showed that the soil surface had developed a distinct functional profile relative to bulk soil after 9 months, enriched in photosynthetic processes which were largely from eukaryotic algae rather than cyanobacteria. Additionally the 3-Hydroxypropionate bicycle and reductive TCA carbon fixation pathways were enriched in surface soil. The abundance of genes involved in heterotrophic carbon, nitrogen, phosphorus and sulphur cycling processes were also enriched in surface soil. This included reads of carbohydrate active enzymes, nitrification, denitrification and sulphate reduction genes, largely attributed to the enrichment of Actinobacteria, Bacteroidetes and Proteobacteria in the soil surface. Overall, we show overlap in dominant phototrophic taxa between temperate agricultural and BSC in arid soils, but with notable differences, including abundance of Xanthphycae and Charophytes. Furthermore, the functional signatures of the soil surface communities indicate that they may play an important role in the delivery of ecosystem functions in temperate agricultural systems.

microbiology↗

bioRxiv2024

Comparative genomic analysis of a metagenome-assembled genome reveals distinctive symbiotic traits in a Mucoromycotina fine root endophyte arbuscular mycorrhizal fungus

BackgroundRecent evidence shows that arbuscular mycorrhizal (AM) symbiosis is established by two distinct fungal groups, with the distinctive fine root endophyte morphotype formed by fungi from the sub-phylum Mucoromycotina rather than the sub-phylum Glomeromycotina. While Mucoromycotina AM fungi are globally distributed, there is currently no understanding of the genomic basis for their symbiosis or how this symbiosis compares to that of other mycorrhizal symbionts. ResultsWe used culture-independent metagenome sequencing to assemble and characterise the metagenome-assembled genome (MAG) of a putative fine root endophyte, which we show belonged to the family Planticonsortiaceae within the order Densosporales. The MAG shares key traits with Glomeromycotina fungi, which indicate obligate biotrophy, including the absence of fatty acid and thiamine biosynthesis pathways, limited enzymatic abilities to degrade plant cell walls, and a high abundance of calcium transporters. In contrast to Glomeromycotina fungi, it exhibits a higher capacity for degradation of microbial cell walls, a complete cellulose degradation pathway, low abundances of copper, nitrate and ammonium transporters, and a complete pathway for vitamin B6 biosynthesis. ConclusionThese differences highlight the potential for contrasting interactions between Mucoromycotina and Glomeromycotina AM fungi with their host plant and the environment which could support niche differentiation and complementary ecological functions.

microbiology↗

bioRxiv2024

Highly accurate metagenome-assembled genomes from human gut microbiota using long-read assembly, binning, and consolidation methods

Long-read metagenomic sequencing is a powerful approach for cataloging the microbial diversity present in complex microbiomes, including the human gut microbiome. We performed a deep-sequencing experiment using PacBio HiFi reads to obtain metagenome-assembled genomes (MAGs) from a pooled human gut microbiome. We performed long-read metagenome assembly using two methods (hifiasm-meta, metMDBG), used improved bioinformatic and proximity ligation binning strategies to cluster contigs and identify MAGs, and developed a novel framework to compare and consolidate MAGs (pb-MAG-mirror). We found proximity ligation binning yielded more MAGs than bioinformatic binning, but our novel comparison framework resulted in higher MAG yields than either binning strategy individually. In total, from 255 Gbp of total HiFi data we produced 595 total MAGs (including 175 high-quality MAGs) using hifiasm-meta, and 547 total MAGs (including 277 high-quality MAGs) with metaMDBG. Hifiasm-meta assembled almost twice as many strain-level MAGs as metaMDBG (246 vs. 156), but both assembly methods produced up to five strains for a species. Approximately 85% of the MAGs were assigned to known species, but we recovered >35 high-quality MAGs that represent uncultured diversity. Based on strict similarity scores, we found 125 MAGs were unequivocally shared across the assembly methods at the strain level, representing [~]22% of the total MAGs recovered per method. Finally, we detected more total viral sequences in the metaMDBG assembly versus the hifiasm-meta assembly ([~]6,700 vs. [~]4,500). Overall, we find the use of HiFi sequencing, improved metagenome assembly methods, and complementary binning strategies is highly effective for rapidly cataloging microbial genomes in complex microbiomes.

microbiology↗

bioRxiv2023

Macroevolutionary dynamics in micro-organisms: generalists give rise to specialists across biomes in the ubiquitous bacterial phylum Myxococcota.

Prokaryotes dominate the Tree of Life, but our understanding of the macroevolutionary processes generating this diversity is still limited. Habitat transitions are thought to be a key driver of prokaryote diversity, but we still know relatively little about how prokaryotes successfully transition and persist across environments, and how this varies between biomes and lineages. Here, we investigate biome transitions and specialisation in natural populations of a focal bacterial phylum, the Myxococcota, sampled across a range of replicated soils and freshwater and marine sediments in Cornwall (UK). By targeted deep sequencing of the protein-coding gene rpoB, we found >2000 unique Myxococcota lineages, with the majority (77%) being biome specialists and <5% able to live across the salt barrier. Discrete character evolution models revealed that biome specialists very rarely transitioned to specialising in another biome. Instead, generalists mediated transitions between biome specialists. Multistate hidden-state speciation and extinction models found variation in speciation rate across the tree, but this variation was independent of biome association and specialisation. Overall, our results help explain how microbes transition between biomes and are consistent with "the jack-of-all-trades" trade-off, where generalists suffer a cost in any individual environment, resulting in rapid evolution of niche specialists.

microbiology↗

bioRxiv2023

Efficient High-Quality Metagenome Assembly from Long Accurate Reads using Minimizer-space de Bruijn Graphs

We introduce a novel metagenomics assembler for high-accuracy long reads. Our approach, implemented as metaMDBG, combines highly efficient de Bruijn graph assembly in minimizer space, with both a multi-k' approach for dealing with variations in genome coverage depth and an abundance-based filtering strategy for simplifying strain complexity. The resulting algorithm is more efficient than the state-of-the-art but with better assembly results. metaMDBG was 1.5 to 12 times faster than competing assemblers and requires between one-tenth and one-thirtieth of the memory across a range of data sets. We obtained up to twice as many high-quality circularised prokaryotic metagenome assembled genomes (MAGs) on the most complex communities, and a better recovery of viruses and plasmids. metaMDBG performs particularly well for abundant organisms whilst being robust to the presence of strain diversity. The result is that for the first time it is possible to efficiently reconstruct the majority of complex communities by abundance as nearcomplete MAGs.

bioinformatics↗

bioRxiv2022

Reproducible spatial structure formation and stable community composition in the cyanosphere predicts metabolic interactions

Understanding how microbial communities maintain stable compositional diversity is key for predicting community function. Studies from species pairwise interactions and synthetic communities indicate that metabolic interactions and spatial organisation can influence coexistence, but the relevance of these factors in more complex communities is unclear. Model systems often lack multi-species complexity, thereby making it difficult to study community diversity temporally. Here we used a spatially-organised cyanobacterial enrichment community to investigate compositional diversity and its stability. Over a year of passaging in media without significant carbon source, we found that the community maintains relatively high diversity, with 17 co-existing bacterial species. Using short and long read shotgun metagenomics sequencing from different time point samples, we have reconstructed complete genomes. Genomic annotation of these species revealed complementary metabolic functions involving carbon breakdown and vitamin biosynthesis suggesting interactions amongst community members. Using isolated species, we provide experimental support for carbon provision through cyanobacterial slime and growth on the component substrates by representative members of the Proteobacteria and Actinobacteriota phyla. Additionally, we experimentally show vitamin provision and uptake between prototrophic and auxotrophic members. We also found genomic capability for (an)oxygenic photosynthesis and sulfur cycling in several species. We show consistent formation of oxygen gradients across photogranule structures, supporting niches that can sustain these specific metabolic functions. These findings indicate that spatial niche formation and metabolic interactions enable maintenance of community compositional stability and diversity. SIGNIFICANCE STATEMENTMicrobes exist as species-diverse communities in nature and understanding their stability is an open challenge in microbial ecology. We established and maintained a spatially-organised, photosynthetic microbial community from a freshwater reservoir through long-term culturing in laboratory medium. We found that this community maintained a taxonomically-diverse set of 17 bacterial species. Combining genomic and physiological assays, we characterised a novel filamentous cyanobacterium capable of carbohydrate-rich slime secretion supporting growth of other microbes. We predict inter-species vitamin exchanges and identify sulfur cycling and alternative types of photosynthesis that are likely to be favoured in oxygen-free zones identified within the spatial structures. Our findings indicate that metabolic interactions and spatial structures can enable stable microbial coexistence in natural ecosystems.

microbiology↗

bioRxiv2022

Crop management shapes the diversity and activity of DNA and RNA viruses in the rhizosphere

BackgroundThe rhizosphere is a hotspot for microbial activity and contributes to ecosystem services including plant health and biogeochemical cycling. The activity of microbial viruses, and their influence on plant-microbe interactions in the rhizosphere, remains undetermined. Given the impact of viruses on the ecology and evolution of their host communities, determining how soil viruses influence microbiome dynamics is crucial to build a holistic understanding of rhizosphere functions. ResultsHere, we aimed to investigate the influence of crop management on the composition and activity of bulk soil, rhizosphere soil, and root viral communities. We combined viromics, metagenomics, and metatranscriptomics on soil samples collected from a 3-year crop rotation field trial of oilseed rape (Brassica napus L.). By recovering 1,059 dsDNA viral populations and 16,541 ssRNA bacteriophage populations, we expanded the number of underexplored Leviviricetes genomes by > 5 times. Through detection of viral activity in metatranscriptomes, we uncovered evidence of "Kill-the-Winner" dynamics, implicating soil bacteriophages in driving bacterial community succession. Moreover, we found the activity of viruses increased with proximity to crop roots and identified that soil viruses may influence plant-microbe interactions through the reprogramming of bacterial host metabolism. We have provided the first evidence of crop rotation-driven impacts on soil microbial communities extending to viruses. To this aim, we present the novel principal of "viral priming", which describes how the consecutive growth of the same crop species primes viral activity in the rhizosphere through local adaptation. ConclusionsOverall, we reveal unprecedented spatial and temporal diversity in viral community composition and activity across root, rhizosphere soil and bulk soil compartments. Our work demonstrates that the roles of soil viruses need greater consideration to exploit the rhizosphere microbiome for food security, food safety, and environmental sustainability.

ecology↗

bioRxiv2021

Meta-exoproteomics identifies active plant-microbe interactions operating in the rhizosphere

The advance of DNA sequencing technologies has drastically changed our perception of the complexity and structure of the plant microbiome and its role in augmenting plant health. By comparison, our ability to accurately identify the metabolically active fraction of soil microbiota and their specific functional role is relatively limited. Here, we combined our recently developed protein extraction method and an iterative bioinformatics pipeline to enable the capture and identification of extracellular proteins (meta-exoproteomics) expressed in the rhizosphere of Brassica spp. First, we validated our method in the laboratory by successfully identifying proteins related to the host plant (Brassica rapa) and a bacterial inoculant, Pseudomonas putida BIRD-1, revealing the latter expressed numerous rhizosphere specific proteins linked to the acquisition of plant-derived nutrients. Next, we analysed natural field-soil microbial communities associated with Brassica napus L (Oil Seed rape). By combining deep-sequencing metagenomics with meta-exoproteomics, a total of 1882 proteins were identified in bulk and rhizosphere samples. Importantly, meta-exoproteomics identified a clear shift (p<0.001) in the metabolically active fraction of the soil microbiota responding to the presence of B. napus roots that was not apparent in the composition of the total microbial community (metagenome). This metabolic shift was associated with the stimulation of rhizosphere-specialised bacteria, such as Gammaproteobacteria, Betaproteobacteria and Flavobacteriia and the upregulation of plant beneficial functions related to phosphorus and nitrogen mineralisation. By providing the first meta-proteomic level assessment of the active plant microbiome at the field-scale, this study demonstrates the importance of moving past a genomic assessment of the plant microbiome in order to determine ecologically important plant: microbe interactions driving plant growth.

microbiology↗

bioRxiv2021

Novel microbial syntrophies identified by longitudinal metagenomics

Identifying species interactions in a microbial community and how this relates to community function is a key challenge. Towards addressing this challenge, we present here an extensive genome-resolved, longitudinal dataset and associated metadata. We collected weekly samples of microbial communities and recorded operating conditions from industrial methane producing anaerobic digestion reactors for a year. This allowed us to recover 2240 dereplicated metagenome assembled genomes (dMAGs), together with their coverage dynamics and functional annotations from which functional traits were inferred. Of these dMAGs, 1910 were novel species, with 22 representing novel orders and classes. Methanogenic communities are expected to be strongly structured by syntrophic and other associations between the methanogens and syntrophs that produce their substrates. We identified 450 potential syntrophic dMAGs by searching for pairs of methanogenic and non-methanogenic dMAGs that had highly correlated time-series. Genomes of potential syntrophs were enriched for oxidoreductases and sugar transport genes and there was a strong taxonomic signal in their associations with methanogens. Of particular note, we found that Bathyarchaeiea associated specifically with methanogens from the Thermoplasmata, and Thermococci classes. Same syntrophic associations were only rarely observed across multiple reactors, suggesting that syntrophies might be facultative, with particular strains within a species forming syntrophic associations only sometimes and not necessarily always with the same methanogenic partner. The presented results show that longitudinal metagenomics is a highly valuable approach for identifying species and their interactions in microbial communities. One Sentence SummaryLongitudinal study of microbial communities identifies novel species and predicts their interactions and role in community function.

microbiology↗

bioRxiv2021

Impact of sulfamethoxazole on a riverine microbiome

The continued emergence of bacterial pathogens presenting antimicrobial resistance is widely recognised as a global health threat and recent attention focused on potential environmental reservoirs of antibiotic resistance genes (ARGs). Freshwater environments such as rivers represent a potential hotspot for ARGs and antibiotic resistant bacteria as they are receiving systems for effluent discharges from wastewater treatment plants (WWTPs). Effluent also contains low levels of different antimicrobials including antibiotics and biocides. Sulfonamides are antibacterial chemicals widely used in clinical, veterinary and agricultural settings and are frequently detected in sewage sludge and manure in addition to riverine ecosystems. The impact of such exposure on ARG prevalence and diversity is unknown, so the aim of this study was to investigate the release of a sub-lethal concentration of the sulfonamide compound sulfamethoxazole (SMX) on the river bacterial microbiome using a flume system. This system was a semi-natural in vitro flume using river water (30 L) and sediment with circulation to mimic river flow. A combination of omics approaches were conducted to study the impact of SMX exposure on the microbiomes within the flumes. Metagenomic analysis showed that the addition of low concentrations of SMX (<4 g L-1) had a limited effect on the bacterial resistome in the water fraction only, with no impact observed in the sediment. Metaproteomics did not show differences in ARGs expression with SMX exposure in water. Overall, the river bacterial community was resilient to short term exposure to sub-lethal concentrations of SMX which mimics the exposure such communities experience downstream of WWTPs throughout the year.

microbiology↗