Single-cell RNA sequencing in high-burden viral respiratory infections: Decoding immune cell subsets and immune-related differential gene expression

Abstract

Respiratory infections remain a major global health burden, ranking among the leading causes of mortality worldwide. Single-cell RNA sequencing (scRNA-seq) has emerged as a transformative technology for dissecting the cellular and molecular complexity of these infections. This review focuses on recent scRNA-seq studies investigating the immune landscape of high-burden viral respiratory infections, particularly COVID-19 and influenza, which are characterized by high transmissibility and clinical impact. We provide an overview of publicly available scRNA-seq datasets derived from human peripheral blood and bronchoalveolar lavage fluid (BALF), as well as lung tissues and explants from murine models, emphasizing their value in profiling immune heterogeneity. scRNA-seq has revealed significant remodeling of immune cell populations during infection, including the identification of novel subsets such as CD4⁺ c13-MKI67⁺ CCL5^low T cells, CD8⁺ CXCR3^high GZMA⁺ T cells, and CD56^high CD16⁻ GZMB⁺ NK cells. These subsets are frequently associated with differential expression of cytokines, chemokines, and interferon-stimulated genes that reflect disease severity and progression. In addition, scRNA-seq has highlighted key pathogen-induced pathways, including type I interferon, NF-κB, and JAK/STAT signaling, and has identified emerging immune-related biomarkers—such as PTX3, MCEMP1, CXCR4, IFIT1, ISG15, and STAT1—with potential diagnostic and prognostic utility. While scRNA-seq applications in respiratory infections of other microbial origins are limited, its role in mapping immune responses and guiding biomarker discovery in viral infections is rapidly expanding. This review synthesizes these findings to inform future translational research and immunodiagnostic strategies.