Evidence map›Paper›PMID 39333527›Full record

ArticleNature communications2024

Deep longitudinal lower respiratory tract microbiome profiling reveals genome-resolved functional and evolutionary dynamics in critical illness.

Minghui Cheng, Yingjie Xu, Xiao Cui, Xin Wei, Yundi Chang, Jun Xu, Cheng Lei, Lei Xue, Yifan Zheng, Zhang Wang and 5 more

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Trial
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  6. Review
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  11. iScience · 2025
    Article
  12. Article
  13. Analysis of metagenomic data.Nature reviews. Methods primers · 2025
    Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors.

Minghui Cheng *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.
Yingjie Xu *Department of Pulmonary and Critical Care Medicine, the Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China.
Xiao Cui *Department of Intensive Care Unit, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China.
Xin Wei *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.ORCID 0000-0002-7401-4005
Yundi Chang *Department of Intensive Care Unit, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China.
Jun XuDepartment of Critical Care Medicine, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Cheng LeiDepartment of Pulmonary and Critical Care Medicine, the Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China.ORCID 0000-0003-1693-1224
Lei XueDepartment of Intensive Care Unit, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China.
Yifan ZhengMOE 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.
Zhang WangSchool of Life Sciences, South China Normal University, Guangzhou, Guangdong Province, China.ORCID 0000-0003-1278-8950
Lingtong HuangDepartment of Critical Care Medicine, the First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Min ZhengState 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.
Hong LuoDepartment of Pulmonary and Critical Care Medicine, the Second Xiangya Hospital, Central South University, Changsha, Hunan, 410011, China. luohonghuxi@csu.edu.cn.ORCID 0000-0002-9501-651X
Yuxin LengDepartment of Intensive Care Unit, Peking University Third Hospital, 49 North Garden Road, Haidian District, Beijing, 100191, China. lengyx@bjmu.edu.cn.ORCID 0000-0001-5634-8936
Chao JiangMOE 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. jiang_chao@zju.edu.cn.ORCID 0000-0003-0260-7271

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Critical IllnessIntensive Care UnitsMetagenomeMicrobiotaAgedBacteriaEvolution, MolecularFemaleGenome, BacterialHumansLongitudinal StudiesMaleMetagenomicsMiddle AgedPlasmidsPneumonia

Identifiers

PMID39333527
PMCPMC11436904

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.