Deciphering the lung microbiota in COVID-19 patients: insights from culture analysis, FilmArray pneumonia panel, ventilation impact, and mortality trends

Sci Rep. 2024 Dec 3;14(1):30035. doi: 10.1038/s41598-024-81738-8.

Abstract

Few studies have analyzed the role of the lung microbiome in the diagnosis of pulmonary coinfection in ventilated ICU COVID-19 patients. We characterized the lung microbiota in COVID-19 patients with severe pneumonia on invasive mechanical ventilation using full-length 16S rRNA gene sequencing and established its relationship with coinfections, mortality, and the need for mechanical ventilation for more than 7 days. This study included 67 COVID-19 ICU patients. DNA extracted from mini-bronchoalveolar lavage fluid and endotracheal aspirates was amplified by PCR with specific 16S primers (27F and 1492R). General and relative bacterial abundance analysis was also conducted. Alpha diversity was measured by the Shannon and Simpson indices, and differences in the microbiota were established using beta diversity. A linear discriminant analysis (LDA) effect size algorithm was implemented to describe biomarkers. Streptococcus spp. represented 51% of the overall microbial abundance. There were no differences in alpha diversity between the analyzed variables. There was variation in bacterial composition between samples that had positive and negative cultures. The genera Veillonella sp., Granulicatella sp., Enterococcus sp. and Lactiplantibacillus sp., with LDA scores > 2, were biomarkers associated with negative cultures. Rothia sp., with an LDA score > 2, was a biomarker associated with mortality.

MeSH terms

  • Aged
  • Bacteria / classification
  • Bacteria / genetics
  • Bacteria / isolation & purification
  • Bronchoalveolar Lavage Fluid / microbiology
  • COVID-19* / microbiology
  • COVID-19* / mortality
  • COVID-19* / virology
  • Coinfection / microbiology
  • Coinfection / mortality
  • Female
  • Humans
  • Intensive Care Units
  • Lung* / microbiology
  • Male
  • Microbiota* / genetics
  • Middle Aged
  • RNA, Ribosomal, 16S* / genetics
  • Respiration, Artificial*
  • SARS-CoV-2 / genetics
  • SARS-CoV-2 / isolation & purification

Substances

  • RNA, Ribosomal, 16S