Meta‐analysis of the microbial biomarkers in the gut–lung crosstalk in COVID‐19, community‐acquired pneumonia and Clostridium difficile infections
Respiratory infections are the leading causes of mortality and the current pandemic COVID‐19 is one such trauma that imposed catastrophic devastation to the health and economy of the world. Unravelling the correlations and interplay of the human microbiota in the gut–lung axis would offer incredible...
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Veröffentlicht in: | Letters in applied microbiology 2022-11, Vol.75 (5), p.1293-1306 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Respiratory infections are the leading causes of mortality and the current pandemic COVID‐19 is one such trauma that imposed catastrophic devastation to the health and economy of the world. Unravelling the correlations and interplay of the human microbiota in the gut–lung axis would offer incredible solutions to the underlying mystery of the disease progression. The study compared the microbiota profiles of six samples namely healthy gut, healthy lung, COVID‐19 infected gut, COVID‐19 infected lungs, Clostridium difficile infected gut and community‐acquired pneumonia infected lungs. The metagenome data sets were processed, normalized, classified and the rarefaction curves were plotted. The microbial biomarkers for COVID‐19 infections were identified as the abundance of Candida and Escherichia in lungs with Ruminococcus in the gut. Candida and Staphylococcus could play a vital role as putative prognostic biomarkers of community‐acquired pneumonia whereas abundance of Faecalibacterium and Clostridium is associated with the C. difficile infections in gut. A machine learning random forest classifier applied to the data sets efficiently classified the biomarkers. The study offers an extensive and incredible understanding of the existence of gut–lung axis during dysbiosis of two anatomically different organs.
Significance and Impact of the Study: The human microbiota is emerging as an influential key player engaged in the onset and progression of pathogenic diseases. The post‐genomic era evidently unravels the little known indispensable microbiota profiles of the lung infections and their influence on the gut. Integration of machine learning concepts with the genomics complements successful and crucial evaluation of serious infectious disease treatment and prevention options. The current study of microbial profiles of gut–lung axis when extended to the brain, skin, oral, liver, faecal, vaginal and secretion fluids would offer incredible information of well‐established microbial interplay involved in health and wellness of humans. |
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ISSN: | 0266-8254 1472-765X |
DOI: | 10.1111/lam.13798 |