MOE Key Laboratory of Biosystems Homeostasis & Protection, and Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, Zhejiang University, Hangzhou, Zhejiang, 310030, China.
State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310009, China.
Nat Commun. 2024 Sep 27;15(1):8361. doi: 10.1038/s41467-024-52713-8.
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.
下呼吸道（LRT）微生物组会影响人类健康，尤其是对重症患者的影响。然而，由于微生物数量少且宿主污染严重，全面描述 LRT 微生物组仍然具有挑战性。我们开发了一种基于 Chelex100 的低生物量微生物富集方法（CMEM），该方法可实现 LRT 样本的深度宏基因组分析，从而恢复接近完整的微生物基因组。我们将该方法应用于来自三个地理位置不同的医院的 157 名重症监护病房（ICU）患者的 453 个纵向 LRT 样本。我们在无需培养的情况下，共回收了 120 个高质量的宏基因组组装基因组（MAG）和相关质粒。我们检测到肺炎患者的纵向微生物组动态和医院特有的优势机会性病原体和耐药组存在差异。经诊断的肺炎和 ICU 住院时间与特定抗生素耐药基因（ARGs）的丰度相关。此外，CMEM 可以作为用于基因组解析分析的强大工具。基于 MAG 的分析揭示了机会性病原体菌株中的特异性耐药组和毒力组。进化分析发现，流行的机会性病原体中的移动组增加，高度保守的质粒以及与转座子和噬菌体相关的新重组热点。与流行病学数据的综合分析揭示了 ICU 中经常发生疑似患者间菌株传播的现象。综上所述，我们呈现了重症患者下呼吸道微生物组的基于基因组的功能、传播和进化图谱。
