Frontiers in MicrobiologyBioinformaticsPeer-reviewed journal article
Gut Microbiome Dynamics and Predictive Value in Hospitalized COVID-19 Patients: A Comparative Analysis of Shallow and Deep Shotgun Sequencing
Katarzyna KoperaiD, Tomasz GromowskiiD, Witold WydmańskiiD, Karolina Skonieczna‐ŻydeckaiD, Agata MuszyńskaiD, Kinga ZielińskaiD, Anna Wierzbicka-WośiD, Mariusz KaczmarczykiD, Roland Kadaj-LipkaiD, Danuta Cembrowska-LechiD, Kornelia Januszkiewicz, Katarzyna KotfisiD, Wojciech WitkiewicziD, Magdalena NalewajskaiD, Wiktoria FeretiD, Wojciech M. MarlicziD, Igor ŁoniewskiiD, Paweł P. ŁabajiD, Grażyna M. RydzewskaiD, Tomasz KościółekiD
Abstract
The COVID-19 pandemic caused by SARS-CoV-2 has led to a wide range of clinical presentations, with respiratory symptoms being common. However, emerging evidence suggests that the gastrointestinal (GI) tract is also affected, with angiotensin-converting enzyme 2, a key receptor for SARS-CoV-2, abundantly expressed in the ileum and colon. The virus has been detected in GI tissues and fecal samples, even in cases with negative respiratory results. GI symptoms have been associated with an increased risk of ICU admission and mortality. The gut microbiome, a complex ecosystem of around 40 trillion bacteria, plays a crucial role in immunological and metabolic pathways. Dysbiosis of the gut microbiota, characterized by a loss of beneficial microbes and decreased microbial diversity, has been observed in COVID-19 patients, potentially contributing to disease severity. We conducted a comprehensive gut microbiome study in 204 hospitalized COVID-19 patients using both shallow and deep shotgun sequencing methods. We aimed to track microbiota composition changes induced by hospitalization, link these alterations to clinical procedures (antibiotics administration) and outcomes (ICU referral, survival), and assess the predictive potential of the gut microbiome for COVID-19 prognosis. Shallow shotgun sequencing was evaluated as a cost-effective diagnostic alternative for clinical settings.
- organism: human
- assay: metagenomics
- research focus: differential expression
- research focus: benchmarking
- approach: statistical model
- approach: experimental assay
- Citations
- 9
- FWCI
- 1.23
- Field percentile
- top 23%
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