Meta-analysis of the microbial biomarkers in the gut-lung crosstalk in COVID-19, community-acquired pneumonia and Clostridium difficile infections.
Aishwarya SK GunasekaranPublished in: Letters in applied microbiology (2022)
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.
Keyphrases
- coronavirus disease
- community acquired pneumonia
- sars cov
- clostridium difficile
- machine learning
- systematic review
- healthcare
- respiratory syndrome coronavirus
- public health
- endothelial cells
- climate change
- biofilm formation
- randomized controlled trial
- cardiovascular disease
- staphylococcus aureus
- risk assessment
- risk factors
- artificial intelligence
- pseudomonas aeruginosa
- health information
- human health
- induced pluripotent stem cells