Language
English
Publication Date
1-1-2023
Journal
PLOS Computational Biology
DOI
10.1371/journal.pcbi.1010360
PMID
36626370
PMCID
PMC9870173
PubMedCentral® Posted Date
1-10-2023
PubMedCentral® Full Text Version
Post-print
Abstract
Human respiratory syncytial virus (RSV) is a major cause of lower respiratory infection. Despite more than 60 years of research, there is no licensed vaccine. While B cell response is a major focus for vaccine design, the T cell epitope profile of RSV is also important for vaccine development. Here, we computationally predicted putative T cell epitopes in the Fusion protein (F) and Glycoprotein (G) of RSV wild circulating strains by predicting Major Histocompatibility Complex (MHC) class I and class II binding affinity. We limited our inferences to conserved epitopes in both F and G proteins that have been experimentally validated. We applied multidimensional scaling (MDS) to construct T cell epitope landscapes to investigate the diversity and evolution of T cell profiles across different RSV strains. We find the RSV strains are clustered into three RSV-A groups and two RSV-B groups on this T epitope landscape. These clusters represent divergent RSV strains with potentially different immunogenic profiles. In addition, our results show a greater proportion of F protein T cell epitope content conservation among recent epidemic strains, whereas the G protein T cell epitope content was decreased. Importantly, our results suggest that RSV-A and RSV-B have different patterns of epitope drift and replacement and that RSV-B vaccines may need more frequent updates. Our study provides a novel framework to study RSV T cell epitope evolution. Understanding the patterns of T cell epitope conservation and change may be valuable for vaccine design and assessment.
Keywords
Humans, Respiratory Syncytial Virus, Human, Epitopes, T-Lymphocyte, Viral Fusion Proteins, Respiratory Syncytial Virus Infections, Antibodies, Viral
Published Open-Access
yes
Recommended Citation
Chen, Jiani; Tan, Swan; Avadhanula, Vasanthi; et al., "Diversity and Evolution of Computationally Predicted T Cell Epitopes Against Human Respiratory Syncytial Virus" (2023). Faculty and Staff Publications. 1839.
https://digitalcommons.library.tmc.edu/baylor_docs/1839