微生物群
仿形(计算机编程)
基因组
基因组
计算生物学
生物
呼吸道
进化生物学
生物信息学
呼吸系统
遗传学
基因
计算机科学
解剖
操作系统
作者
Minghui Cheng,Yingjie Xu,Xiao Cui,Xin Wei,Yundi Chang,Jun Xu,Cheng Lei,Lei Xue,Yifan Zheng,Zhang Wang,Lingtong Huang,Min Zheng,Hong Luo,Yuxin Leng,Chao Jiang
标识
DOI:10.1038/s41467-024-52713-8
摘要
The lower respiratory tract (LRT) microbiome impacts human health, especially among critically ill patients. However, comprehensive characterizations of the LRT microbiome remain challenging due to low microbial mass and host contamination. We develop a chelex100-based low-biomass microbial-enrichment method (CMEM) that enables deep metagenomic profiling of LRT samples to recover near-complete microbial genomes. We apply the method to 453 longitudinal LRT samples from 157 intensive care unit (ICU) patients in three geographically distant hospitals. We recover 120 high-quality metagenome-assembled genomes (MAGs) and associated plasmids without culturing. We detect divergent longitudinal microbiome dynamics and hospital-specific dominant opportunistic pathogens and resistomes in pneumonia patients. Diagnosed pneumonia and the ICU stay duration were associated with the abundance of specific antibiotic-resistance genes (ARGs). Moreover, CMEM can serve as a robust tool for genome-resolved analyses. MAG-based analyses reveal strain-specific resistome and virulome among opportunistic pathogen strains. Evolutionary analyses discover increased mobilome in prevailing opportunistic pathogens, highly conserved plasmids, and new recombination hotspots associated with conjugative elements and prophages. Integrative analysis with epidemiological data reveals frequent putative inter-patient strain transmissions in ICUs. In summary, we present a genome-resolved functional, transmission, and evolutionary landscape of the LRT microbiota in critically ill patients.
科研通智能强力驱动
Strongly Powered by AbleSci AI