Respiratory Microbiome Dynamics in COVID-19: A Comprehensive Multi-Omics Study

The outcomes of SARS-CoV-2 infection exhibit significant heterogeneity, and the role of the airway microbiota remains insufficiently understood. In a cohort comprising 561 participants, an integrated multi-omics approach was employed. This approach combined 16S/ITS amplicons (n = 542), total RNA metatranscriptomics (n = 495), and total DNA metagenomics (n = 113), with 101 samples analyzed using all three omics. Metatranscriptomes resolved lineage dynamics across major infection waves and identified microbial coinfections; shotgun metagenomes recovered 190 MAGs, including 13 putative novel species, expanding the catalog of respiratory taxa. Cross‑omics testing showed species‑level biomarkers and resistome burden were more linked to clinical outcomes than genus‑level signals, highlighting the value of high‑resolution profiling. Functional analyses revealed outcome‑based shifts in microbial processes and host metatranscriptomic signatures enriched for interferon programs and tissue remodeling pathways. This work delineates mechanisms associated with COVID‑19 severity, uncovers candidate biomarkers, and provides a multi‑omics framework for integrated pathogen–microbiome–host surveillance in future respiratory pandemics.