Summary
This project aims to understand the spatiotemporal dynamics of human enterovirus (HEV) infection across cells and tissues, focusing on CVB3, EV-D68, and EV-A71, to inform the development of effective countermeasures and vaccines.
Mapping spatiotemporal dynamics during enterovirus infection across cells and tissues
US · IL
NIH
grant
awarded
#nih-3R01AI169460-04S1
What they want
The project will take an integrative approach to understand how tissues and cells respond to infection by CVB3, EV-D68, and EV-A71. This involves profiling single-cell transcriptomes to quantify viral replication levels and host response over the course of infection. In parallel, the mutational spectrum of replicating viruses will be mapped using a novel ultra-deep sequencing approach. The project will utilize innovative technologies such as ultra-deep virus population sequencing, deep learning, and single-cell analysis. Additionally, mice with deletions of specific type-I IFN subtypes will be used to determine the significance of interferon diversity in controlling HEV infections.
Deliverables
- Quantification of viral replication levels and host response across cells and tissues
- Mapping of the mutational spectrum of replicating viruses
- Determination of cell types infected by HEVs
- Identification of host responses in each cell and tissue
- Identification of viral mutants emerging in different tissues
- Data to inform development of effective and broad-spectrum vaccines and antiviral compounds
Technical requirements
- single-cell transcriptomics
- ultra-deep sequencing
- ultra-deep virus population sequencing
- deep learning
- single-cell analysis
- use of type-I IFN subtype deletion mice models
