category
bioRxiv
date
Feb 18, 2026
slug
status
Published
summary
创新性地利用DNA甲基化模式关联耐药基因与宿主细菌,开发基于甲基化基序的contig相似性评分算法,在临床样本中实现91%的物种级准确率,并发现传统方法遗漏的耐药基因。
tags
测序技术
type
Post
📄 原文题目
Nanopore metagenomic sequencing links clinically relevant resistance determinants to pathogens
🔗 原文链接
💡 AI 核心解读
创新性地利用DNA甲基化模式关联耐药基因与宿主细菌,开发基于甲基化基序的contig相似性评分算法,在临床样本中实现91%的物种级准确率,并发现传统方法遗漏的耐药基因。
📝 英文原版摘要
Metagenomic sequencing can detect pathogens and antimicrobial resistance genes directly from clinical samples without culture, but linking resistance genes to their bacterial hosts remains challenging. Here, we exploit DNA methylation patterns in nanopore sequencing data to associate plasmid-encoded resistance genes with their host bacteria in metagenomic samples. We developed a contig similarity score based on shared methylation motifs and validated this approach using mock metagenomic communities of clinically relevant carbapenem-resistant Enterobacterales, achieving 91% accuracy at the taxonomic species level. We then applied our framework to nanopore metagenomic data from patient rectal swabs collected during routine hospital screening. Comparison with established culture-based diagnostics and whole-genome sequencing confirmed that our approach correctly associated plasmid- as well as chromosomally encoded resistance genes, including all detected carbapenemases, with their pathogenic hosts while identifying additional clinically relevant resistance genes missed by routine testing. Our results demonstrate that nanopore metagenomics can provide actionable resistance-pathogen associations for clinical surveillance.
- 作者:NotionNext
- 链接:https://tangly1024.com/article/30b48bd6-1f96-818d-b635-f206e7aa91f3
- 声明:本文采用 CC BY-NC-SA 4.0 许可协议,转载请注明出处。
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