Recovery of highly contiguous genomes from complex terrestrial habitats reveals over 15,000 novel prokaryotic species and expands characterization of soil and sediment microbial communities DOI Creative Commons
Mantas Sereika, Aaron J. Mussig, Chenjing Jiang

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 21, 2024

Abstract Genomes are fundamental to understanding microbial ecology and evolution. The emergence of high-throughput, long-read DNA sequencing has enabled recovery genomes from environmental samples at scale. However, expanding the genome catalogue soils sediments been challenging due enormous complexity these environments. Here, we performed deep, Nanopore 154 soil sediment collected across Denmark through an optimised bioinformatics pipeline, recovered 15,314 novel species, including 4,757 high-quality genomes. span 1,086 genera provide first reference for 612 previously known genera, phylogenetic diversity prokaryotic tree life by 8 %. assemblies also thousands complete rRNA operons, biosynthetic gene clusters CRISPR-Cas systems, all which were underrepresented highly fragmented in previous terrestrial catalogues. Furthermore, incorporation MAGs into public databases significantly improved species-level classification rates metagenomic datasets, thereby enhancing microbiome characterization. With this study, demonstrate that bioinformatics, allows cost-effective complex ecosystems, remain largest untapped source biodiversity filling gaps life.

Language: Английский

Longitudinal metagenomic analysis on antibiotic resistome, mobilome, and microbiome of river ecosystems in a sub-tropical metropolitan city DOI Creative Commons
Xuemei Mao, Xiaole Yin,

Yu Yang

et al.

Water Research, Journal Year: 2025, Volume and Issue: 274, P. 123102 - 123102

Published: Jan. 5, 2025

Language: Английский

Citations

0
Species-resolved profiling of antibiotic resistance genes in complex metagenomes through long-read overlapping with Argo DOI Creative Commons
Xi Chen, Xiaole Yin, Xiaoqing Xu

et al.

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: Feb. 18, 2025

Environmental surveillance of antibiotic resistance genes (ARGs) is critical for understanding and mitigating the spread antimicrobial resistance. Current short-read-based ARG profiling methods are limited in their ability to provide detailed host information, which indispensable tracking transmission assessing risk ARGs. Here, we present Argo, a novel approach that leverages long-read overlapping rapidly identify quantify ARGs complex environmental metagenomes at species level. Argo significantly enhances resolution detection by assigning taxonomic labels collectively clusters reads, rather than individual reads. By benchmarking performance identification using simulation, confirm advantage over existing metagenomic strategies terms accuracy. Using sequenced mock communities with varying quality scores read lengths, along global fecal dataset comprising 329 human non-human primate samples, demonstrate Argo's capability deliver comprehensive species-resolved profiles real settings.

Language: Английский

Citations

0
Lightweight taxonomic profiling of long-read sequenced metagenomes with Lemur and Magnet DOI Creative Commons
Nicolae Sapoval, Yunxi Liu, Kristen Curry

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: June 3, 2024

The advent of long-read sequencing microbiomes necessitates the development new taxonomic profilers tailored to shotgun metagenomic datasets. Here, we introduce Lemur and Magnet, a pair tools optimized for lightweight accurate profiling is marker-gene-based method that leverages an EM algorithm reduce false positive calls while preserving true positives; Magnet whole-genome read mapping based provides detailed presence absence bacterial genomes. We demonstrate can run in minutes hours on laptop with 32 GB RAM, even large inputs, crucial feature given portability machines. Furthermore, marker gene database used by only 4 contains information from over 300,000 RefSeq are open-source available at https://github.com/treangenlab/lemur https://github.com/treangenlab/magnet.

Language: Английский

Citations

0
PanTax: Strain-level taxonomic classification of metagenomic data using pangenome graphs DOI Creative Commons
Wenhai Zhang, Yuansheng Liu, Jialu Xu

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 17, 2024

Abstract Microbes are omnipresent, thriving in a range of habitats from oceans to soils and even within our gastrointestinal tracts. They play vital role maintaining ecological equilibrium promoting the health their hosts. Consequently, understanding strain diversity microbial communities is crucial, as variations between strains can lead distinct phenotypic expressions or diverse biological functions. However, current methods for taxonomic classification metagenomic sequencing data have several limitations, including reliance solely on species resolution, support either short long reads, confinement given single species. Most notably, majority existing classifiers rely linear representative genome reference, which fails capture diversity, thereby introducing single-reference biases. Here, we present PanTax, pangenome graph-based method that overcomes shortcomings genome-based approaches, because graphs possess capability depict genetic variability across multiple evolutionarily environmentally related genomes. PanTax provides comprehensive solution compatibility with both Extensive benchmarking results demonstrate drastically outperforms state-of-the-art primarily evidenced by its significantly higher precision recall (at levels), while comparable better performance other aspects various datasets. user-friendly open-source tool publicly accessible at https://github.com/LuoGroup2023/PanTax .

Language: Английский

Citations

0
Recovery of highly contiguous genomes from complex terrestrial habitats reveals over 15,000 novel prokaryotic species and expands characterization of soil and sediment microbial communities DOI Creative Commons
Mantas Sereika, Aaron J. Mussig, Chenjing Jiang

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 21, 2024

Abstract Genomes are fundamental to understanding microbial ecology and evolution. The emergence of high-throughput, long-read DNA sequencing has enabled recovery genomes from environmental samples at scale. However, expanding the genome catalogue soils sediments been challenging due enormous complexity these environments. Here, we performed deep, Nanopore 154 soil sediment collected across Denmark through an optimised bioinformatics pipeline, recovered 15,314 novel species, including 4,757 high-quality genomes. span 1,086 genera provide first reference for 612 previously known genera, phylogenetic diversity prokaryotic tree life by 8 %. assemblies also thousands complete rRNA operons, biosynthetic gene clusters CRISPR-Cas systems, all which were underrepresented highly fragmented in previous terrestrial catalogues. Furthermore, incorporation MAGs into public databases significantly improved species-level classification rates metagenomic datasets, thereby enhancing microbiome characterization. With this study, demonstrate that bioinformatics, allows cost-effective complex ecosystems, remain largest untapped source biodiversity filling gaps life.

Language: Английский

Citations

0