Metatranscriptomic Insights into Host-Microbiome Interactions Underlying Asymptomatic COVID-19 Cases

Abstract

In recent years, the research on Coronavirus disease 2019 (COVID-19) has surged rapidly due to its infectious nature and epidemiological importance as a pandemic. Association of other pathogenic microbes or different human microbiomes with COVID-19 severity is well established. While much is known about COVID-19, studies exploring how host-pathogen interactions at the transcriptomic level influence disease severity are still limited. This research focuses on metatranscriptomic perspective of COVID-19 patients from different Bangladeshi cohorts. Metatranscriptomic sequencing was performed using the extracted RNA of forty different nasopharyngeal samples. After preprocessing and assembly of the genome sequence data, taxonomic identification and diversity along with antibiotic resistance pattern was analyzed using different bioinformatic pipelines. COVID-19 positive and asymptomatic positive patients had a higher abundance of pathogenic and multidrug resistant bacteria whereas the Healthy or recovered patients had higher fungal population. Differential gene expression analysis was also performed to identify the upregulated and downregulated genes responsible for different biological and immunological pathways of humans. Here, immunological response related genes were mostly upregulated in positive cases which was also evident in the proinflammatory cytokines upregulation. Moreover, asymptomatic positive cases showed low TLR-4 expression, which is key to recognizing pathogen-associated molecular patterns (PAMPs) and triggering pro-inflammatory immune responses. This study can clarify the gene expression and signaling pattern of COVID-19 patients with different severity. This may also suggest that some populations exhibit reduced basal expression of TLR-4, which may suppress innate immune activation following infection and contribute to asymptomatic clinical outcomes; however, this hypothesis requires further investigation. Future studies should aim to validate these associations using larger, ethnically diverse cohorts with comprehensive clinical and demographic data.