SARS-CoV-2 Variant-Dependent Alterations in Nasopharyngeal Microbiota and Host Inflammatory Response
SARS-CoV-2 infection alters both the nasopharyngeal microbiota and host inflammatory environment. In this study, nasopharyngeal samples collected in Chile during different phases of the pandemic were analyzed using 16S rRNA gene sequencing (V3–V4) and RT-qPCR quantification of IL-2, TNF-a, IFN-? and IL-1ra. Machine-learning models (Random Forest and K-Nearest Neighbors) were applied to integrate microbial community profiles, cytokine expression, and SARS-CoV-2 variants (Gamma, Lambda, Delta). The results show variant-dependent immunomicrobial signatures characterized by TNF-a-driven inflammation and the expansion of opportunistic bacterial genera such as Acinetobacter, Prevotella, and Staphylococcus. These findings provide a comprehensive overview of the interplay between viral infection, microbiome structure, and inflammatory responses and highlight the utility of combining microbiome and cytokine profiling with machine-learning approaches to discriminate infection outcomes across SARS-CoV-2 variants. Overall design: Nasopharyngeal swab samples were collected in Chile between April 2021 and August 2021 for SARS-CoV-2 diagnosis and variant identification. Samples were tested by RT-qPCR, and variants (Gamma, Lambda, Delta) were determined using Hydrolysis Probe–based assays. Bacterial community profiling was performed by sequencing the V3–V4 region of the 16S rRNA gene using Illumina MiSeq technology. Raw reads were demultiplexed and processed using the DADA2 pipeline for quality filtering, denoising, chimera removal, and generation of amplicon sequence variants (ASVs). The resulting ASV table, taxonomic assignments (SILVA-138), and sample metadata constitute the processed data provided in this submission. The study aims to characterize variant-associated changes in nasopharyngeal microbial communities during SARS-CoV-2 infection.