Uncovering COVID-19 dynamics in Tunisian patients: a meta-transcriptomic approach

The global COVID-19 pandemic, caused by SARS-CoV-2, has raised major public health concerns worldwide. Tunisia, among the hardest-hit African countries, has faced significant challenges. In this context, strengthening surveillance and research is crucial for an effective pandemic response. This study aims to deepen the understanding of the interaction between SARS-CoV-2 and the human host in Tunisia. The primary objectives were to characterize the virus, identify differentially expressed host genes, and characterize potential biomarkers associated with COVID-19. Additionally, we aimed to analyze the microbial composition of COVID-19 patients to explore potential co-infections and their implications. A meta-transcriptomic analysis was conducted on 34 clinical samples collected from Tunisian patients, encompassing severe, moderate, and negative (control) phenotypes for COVID-19. Our integrated approach enabled the simultaneous analysis of the SARS-CoV-2 virus, host gene expression patterns and microbiome. Our results detailed the interactions of SARS-CoV-2 in our studied cohort and revealed the presence of both Omicron and Delta variants. We identified enhanced innate immune responses and interferon signals, highlighting candidate genes as disease biomarkers. Microbial analysis revealed a diverse microbial community in COVID-19 patients, with significant compositional differences between severe and moderate cases. This pioneering meta-transcriptomic study in Tunisia and North Africa expands our knowledge of the SARS-CoV-2-host interaction and the microbial landscape of COVID-19 patients. The differentially regulated genes and microbial profiles identified here represent promising leads for understanding disease pathogenesis and may serve as potential therapeutic targets. These findings underscore the importance of comprehensive metatranscriptomic approaches in uncovering the complexities of COVID-19 and guiding effective public health strategies.