Microbiota and immunity affect the host's susceptibility to SARS-CoV-2 infection and the severity of COVID-19. This study aimed to identify significant alterations in the microbiota composition, immune signaling pathways, their potential association, and candidate microRNA in COVID-19 patients using an in silico study model. Enrichment online databases and Python programming were utilized to analyze GSE164805, GSE180594, and GSE182279, as well as NGS data of microbiota composition (PRJNA650244 and PRJNA660302) associated with COVID-19, employing amplicon-based/marker gene sequencing methods. C1, TNF, C2, IL1, and CFH genes were found to have a significant impact on immune signaling pathways. Additionally, we observed a notable decrease in Bacteroides spp. and Faecalibacterium sp., while Escherichia coli, Streptococcus spp., and Akkermansia muciniphila showed increased abundance in COVID-19. Notably, A. muciniphila demonstrated an association with immunity through C1 and TNF, while Faecalibacterium sp. was linked to C2 and IL1. The correlation between E. coli and CFH, as well as IL1 and Streptococcus spp. with C2, was identified. hsa-let-7b-5p was identified as a potential candidate that may be involved in the interaction between the microbiota composition, immune response, and COVID-19. In conclusion, integrative in silico analysis shows that these microbiota members are potentially crucial in the immune responses against COVID-19.
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http://dx.doi.org/10.1007/s12033-024-01096-8 | DOI Listing |
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