Academic Journal
Deciphering viral infections at single-cell resolution: From immune dynamics to host-pathogen interactions.
| Τίτλος: | Deciphering viral infections at single-cell resolution: From immune dynamics to host-pathogen interactions. |
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| Συγγραφείς: | Zhou W; Department of Gastroenterology, University-Town Hospital of Chongqing Medical University, Chongqing, China., Xu P; Department of Clinical Laboratory, University-Town Hospital of Chongqing Medical University, Chongqing, China. Electronic address: panxu@hospital.cqmu.edu.cn. |
| Πηγή: | Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases [Infect Genet Evol] 2026 Sep; Vol. 143, pp. 105969. Date of Electronic Publication: 2026 Jun 17. |
| Τύπος έκδοσης: | Journal Article; Review |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Elsevier Science Country of Publication: Netherlands NLM ID: 101084138 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1567-7257 (Electronic) Linking ISSN: 15671348 NLM ISO Abbreviation: Infect Genet Evol Subsets: MEDLINE |
| Imprint Name(s): | Original Publication: Amsterdam ; New York : Elsevier Science, c2001- |
| Ιατρικοί όροι (MeSH): | Host-Pathogen Interactions*/immunology , Host-Pathogen Interactions*/genetics , Virus Diseases*/immunology , Virus Diseases*/virology , Virus Diseases*/genetics , Single-Cell Analysis*/methods, Humans ; Animals ; Single-Cell Gene Expression Analysis |
| Περίληψη: | Single-cell RNA sequencing (scRNA-seq) has emerged as a transformative technology in infectious disease research, enabling high-resolution characterization of cellular heterogeneity, immune dynamics, and host-pathogen interactions at the single-cell level. In the context of viral infections-including SARS-CoV-2, hepatitis B virus (HBV), human immunodeficiency virus (HIV), influenza virus, and respiratory syncytial virus (RSV)-scRNA-seq has provided critical insights into immune-cell heterogeneity, immune landscape remodeling, and the emergence of previously unrecognized cellular states. Beyond immune profiling, scRNA-seq enables direct detection of viral transcripts within infected cells. This allows discrimination between productively infected and bystander cells and reveals virus-induced transcriptional reprogramming within target tissues. Additionally, single-cell approaches facilitate the analysis of adaptive immune repertoires through integrated integrated T-cell receptor (TCR) and B-cell receptor (BCR) sequencing sequencing and uncover intra-host viral diversity and evolutionary dynamics at unprecedented resolution. This review summarizes recent advances in the application of scRNA-seq in viral infection research, with a focus on immune regulation, host-pathogen co-transcriptomics, inflammatory signaling pathways, biomarker discovery, and translational implications. Comparative single-cell studies across acute and chronic viral infections have further revealed both shared antiviral programs and virus-specific immune adaptations.We further discuss current technical limitations and emerging computational strategies, as well as future integration with spatial transcriptomics and multi-omics platforms. Collectively, these developments highlight the potential of single-cell technologies to advance mechanistic understanding and guide precision diagnostics and therapeutic strategies in viral diseases. (Copyright © 2026 The Authors. Published by Elsevier B.V. All rights reserved.) |
| Competing Interests: | Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. |
| Contributed Indexing: | Keywords: Comparative virology; Host–pathogen interactions; Immune heterogeneity; Single-cell RNA sequencing; Viral infections |
| Entry Date(s): | Date Created: 20260617 Date Completed: 20260725 Latest Revision: 20260725 |
| Update Code: | 20260726 |
| DOI: | 10.1016/j.meegid.2026.105969 |
| PMID: | 42309184 |
| Βάση Δεδομένων: | MEDLINE |
| ISSN: | 1567-7257 |
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| DOI: | 10.1016/j.meegid.2026.105969 |