Biology subjects

Xiu, W.

Publications and source records attributed to Xiu, W..

3 recordsLinked to original sources

bioRxiv2026

Automated refinement of metagenomic bins and estimation of binning success using itBins

Most prokaryotic genomes in public databases are genomes reconstructed from metagenomes, forming a compendium of multiple contiguous sequences (contigs) assembled from shotgun sequencing data. Binning algorithms for assigning contigs to metagenome assembled genomes (MAGs) are manifold and continuously improving in accuracy. However, binning errors, i.e. the incorrect assignment of a contig and coding sequence to a MAG, often propagate through various databases and confound taxonomic, metabolic and/or evolutionary analyses. Here we present itBins, a fully automated python-based software that enables ultra-fast refinement of metagenomic bins using a rule-based approach harnessing information from %GC content (%GC for brevity), coverage, and taxonomy of individual contigs. When applied to the low, medium, and high complexity data of the Critical Assessment of Metagenome Interpretation (CAMI I) challenge [1], itBins produced higher F1 scores (the harmonic mean of precision and recall) for all levels compared to other automated refinement tools, i.e., MDMcleaner and Rosella. Compared to manual refinement via uBin, itBins performed similarly well across all three complexity levels of the CAMI I dataset. With an average speed of 61 ms per bin, itBins is faster than all other refinement tools by at least three orders of magnitude when input data is accordingly available (%GC, coverage, and taxonomy), and was similarly fast when input data preparation was included in the processing time. Application to 64 real-world metagenomes from highly complex river mesocosms resulted in 259 medium-quality and 19 high-quality MAGs refined by itBins, while the other automated refinement tools failed in generating output at all or within 5000 hours of runtime. Finally, itBins also utilizes marker genes to determine the overall binning success for individual metagenomes, providing a crucial benchmark for the user to estimate the ecological relevance of their binned data. The herein introduced software itBins is broadly applicable to any type of metagenome data, integrates well with other software like DASTool, and enables swift and reliable refinement of genomes from metagenomes along with estimation of the overall binning success. itBins is distributed via EUPL 1.2 license and available at Codeberg (codeberg.org/JMK/itBins), GitHub (github.com/ProbstLab/itBins) and through Bioconda [2](bioconda.github.io/recipes/itbins/README.html).

bioinformatics↗

bioRxiv2025

Methanotrophic acetogenesis drives a novel pathway of arsenic mobilization in reducing groundwaters

Geogenic arsenic (As) contamination in groundwater, widely used as drinking water, poses a global health risk, yet the microbial pathways linking electron donor oxidation to the reduction of As-bearing Fe(III) oxyhydroxides remain poorly understood. Here, we deployed Fe(III) (oxyhydr)oxide-coated pumice stones in high-As, high-methane groundwater in Cambodia for 270 days to capture planktonic metal-reducing microbial communities in-situ. These were used to inoculate anaerobic microcosms with methane or volatile fatty acids (VFAs) as electron donors over 200 days. Genome-resolved metagenomics revealed that methane oxidation via reverse methanogenesis led to acetate production, which in turn provided the primary electrons for Fe(III) and As(V) reduction in the microcosms, resulting in As(III) release. Our findings highlight an indirect coupling between methane oxidation and arsenic mobilization, with acetate as the key intermediate. This study offers new insights into the role of methane in subsurface biogeochemical cycling and its implications for arsenic contamination in groundwater systems. SynopsisThe study uses a novel in situ sampling procedure, coupled with metagenomic analysis, to identify anaerobic methane oxidation producing acetate, as a potentially important pathway to generate electron donors for microbial Fe(III) and As(V) reduction in aquifer sediments. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=72 SRC="FIGDIR/small/696296v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@801222org.highwire.dtl.DTLVardef@268d01org.highwire.dtl.DTLVardef@f342e2org.highwire.dtl.DTLVardef@ac1f9d_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Uranium mining fuels evolution in deep groundwater microbiomes

Deep-biosphere microbes have been underpinning global biogeochemical cycles throughout Earth history, yet their evolutionary responses to long-term anthropogenic disturbance remain poorly understood. Neutral-pH in-situ leaching (ISL), the dominant uranium-mining strategy, imposes persistent radiochemical and redox stress offering rare natural experiments across decades for observing subsurface microbial evolution. Here, by exploiting metagenomics and metatranscriptomics in examining microbial responses through various mining stages, we show that neutral U ISL causes substantial changes in microbial communities spanning 2,294 strains accompanied by diversification and selection of active microbial species. These changes occurred during elevated dissolved uranium and radiological activity which correlated with a substantial transcriptional change in energy metabolism, and with an overexpression of specific genes for oxidative-stress defence and DNA-repair pathways. Increased nucleotide diversity in 101 out of 392 species clusters and nonsynonymous/synonymous polymorphism ratios greater than one in 139 species clusters were predominantly observed in metatranscriptomes with elevated radiation, highlighting positive selection of transcriptionally active populations. These findings demonstrate that neutral U ISL drives functional and genetic diversification of subsurface microbiomes, revealing a dynamic and evolutionarily responsive deep biosphere.

genomics↗