Applications of single-cell RNA sequencing in fungal infections
- 1Department of Dermatology, The Affiliated Hospital of Qingdao University
Abstract
Fungal infection elicits markedly different cellular responses depending on the pathogen, tissue involved, host immune status, and stage of disease. Bulk measurements capture broad changes but can obscure the cell populations associated with fungal control, persistence, or tissue injury. Single-cell RNA sequencing (scRNA-seq) offers a way to resolve this heterogeneity, although fungal infection studies remain uneven in both technical feasibility and disease coverage. We review evidence from cutaneous, mucosal, pulmonary, central nervous system, and systemic infections, with attention to tissue context, experimental design, and the strength of supporting validation. Across these studies, myeloid, lymphoid, epithelial, and stromal compartments show substantial remodeling, yet similarly named cell states do not necessarily have equivalent functions in different tissues or infections. Direct fungal single-cell studies are fewer, but they reveal variation in developmental stage, morphogenesis, stress responses, and responses to antifungal exposure. Most evidence still centers on Candida , whereas studies of Aspergillus, Cryptococcus, Pneumocystis, Coccidioides , and chronic cutaneous mycoses remain restricted to particular models or sample types. Interpretation is complicated by dissociation-related bias, unequal cell recovery, sparse fungal RNA, cross-species mapping, and small human cohorts. Spatial and functional validation are therefore important for distinguishing transcriptional associations from mechanisms. At present, single-cell approaches are most useful for defining context-dependent states and generating mechanistic questions; broader clinical application will require standardized sampling, independent validation, and scalable assays.
Related
- Complementary single-nucleus and single-cell RNA sequencing reveal tumor state evolution and microenvironmental rewiring in NSCLC
- Patient classification using single-cell RNA-sequencing data with deep learning convolutional neural networks
- Systematic evaluation of integration methods and parameters on single-cell RNA-sequencing biological insights: a case study on cattle embryos
- Single-cell RNA sequencing reveals PANoptosis signatures of acinar cells, macrophages, and neutrophils during injury and repair in acute pancreatitis
- scLncR: an integrated and flexible pipeline for lncRNA analysis in single-cell RNA sequencing data
BibTeX
@article{shen2026applications,
title = {{Applications of single-cell RNA sequencing in fungal infections}},
author = {Xi Shen and Guanzhi Chen and Lingyue Sun},
journal = {Frontiers in Microbiology},
year = {2026},
month = oct,
doi = {10.3389/fmicb.2026.1996773},
url = {https://www.frontiersin.org/articles/10.3389/fmicb.2026.1996773/full},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Applications of single-cell RNA sequencing in fungal infections
AU - Xi Shen
AU - Guanzhi Chen
AU - Lingyue Sun
PY - 2026
DA - 2026/10/06
JO - Frontiers in Microbiology
DO - 10.3389/fmicb.2026.1996773
UR - https://www.frontiersin.org/articles/10.3389/fmicb.2026.1996773/full
AB - Fungal infection elicits markedly different cellular responses depending on the pathogen, tissue involved, host immune status, and stage of disease. Bulk measurements capture broad changes but can obscure the cell populations associated with fungal control, persistence, or tissue injury. Single-cell RNA sequencing (scRNA-seq) offers a way to resolve this heterogeneity, although fungal infection studies remain uneven in both technical feasibility and disease coverage. We review evidence from cutaneous, mucosal, pulmonary, central nervous system, and systemic infections, with attention to tissue context, experimental design, and the strength of supporting validation. Across these studies, myeloid, lymphoid, epithelial, and stromal compartments show substantial remodeling, yet similarly named cell states do not necessarily have equivalent functions in different tissues or infections. Direct fungal single-cell studies are fewer, but they reveal variation in developmental stage, morphogenesis, stress responses, and responses to antifungal exposure. Most evidence still centers on Candida , whereas studies of Aspergillus, Cryptococcus, Pneumocystis, Coccidioides , and chronic cutaneous mycoses remain restricted to particular models or sample types. Interpretation is complicated by dissociation-related bias, unequal cell recovery, sparse fungal RNA, cross-species mapping, and small human cohorts. Spatial and functional validation are therefore important for distinguishing transcriptional associations from mechanisms. At present, single-cell approaches are most useful for defining context-dependent states and generating mechanistic questions; broader clinical application will require standardized sampling, independent validation, and scalable assays.
SN - 1664-302X
ER -