University of Massachusetts Medical School Faculty Publications

UMMS Affiliation

Graduate School of Biomedical Sciences; Program in Bioinformatics and Integrative Biology; Department of Medicine, Division of Infectious Diseases and Immunology; Program in Molecular Medicine

Publication Date

2020-04-17

Document Type

Article Preprint

Disciplines

Bioinformatics | Computational Biology | Genomics | Immunology and Infectious Disease | Infectious Disease | Respiratory Tract Diseases | Virology | Virus Diseases

Abstract

Influenza virus infections are major causes of morbidity and mortality. Research using cultured cells, bulk tissue, and animal models cannot fully capture human disease dynamics. Many aspects of virus-host interactions in a natural setting remain unclear, including the specific cell types that are infected and how they and neighboring bystander cells contribute to the overall antiviral response. To address these questions, we performed single-cell RNA sequencing (scRNA-Seq) on cells from freshly collected nasal washes from healthy human donors and donors diagnosed with acute influenza during the 2017-18 season. We describe a previously uncharacterized goblet cell population, specific to infected individuals, with high expression of MHC class II genes. Furthermore, leveraging scRNA-Seq reads, we obtained deep viral genome coverage and developed a model to rigorously identify infected cells that detected influenza infection in all epithelial cell types and even some immune cells. Our data revealed that each donor was infected by a unique influenza variant and that each variant was separated by at least one unique non-synonymous difference. Our results demonstrate the power of massively-parallel scRNA-Seq to study viral variation, as well as host and viral transcriptional activity during human infection.

Keywords

Genomics, influenza virus infection, virus-host interactions, RNA sequencing, goblet cell population, viral variation

Rights and Permissions

The copyright holder for this preprint (which was not peer-reviewed) is the author/funder. It is made available under a CC-BY-ND 4.0 International license.

DOI of Published Version

10.1101/2020.04.15.042978

Source

bioRxiv 2020.04.15.042978; doi: https://doi.org/10.1101/2020.04.15.042978. Link to preprint on bioRxiv service

Journal/Book/Conference Title

bioRxiv

Creative Commons License

Creative Commons Attribution-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-No Derivative Works 4.0 License.

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