Predicting H5N1 lineage specific human CD8+ T-cell-reactive epitopes for vaccine selection

Xueting Qiu, The University of Texas School of Public Health

Abstract

Highly pathogenic avian influenza A (HPAI) H5N1 viruses have circulated continuously, posing a great threat to human and animal health for close to two decades. One major perspective to prevent a potential H5N1 pandemic is to stockpile vaccine candidates. The cytotoxic T-lymphocytes (CD8+ T-cell) tends to target more conserved influenza virus proteins. However, no systematic analysis of conserved CD8+ T-cell-reactive epitopes across all H5N1 clades has been conducted. Therefore, this study was undertaken to identify and map conserved epitopes across the hypothesized phylogenetic tree and to correlate these observations with the geographic distribution of predicted human CD8+ reactive epitopes. Conserved epitopes were predicted from twenty-seven WHO-endorsed vaccine candidates and twenty-eight clade-defining strains. Comparative genetic analyses and epitope conservancy analyses were conducted in a representative dataset consisting of 951 H5N1 Hemagluttinin (HA) sequences collected from infected birds and humans between 1996 and 2013. Epitope distributions were mapped to form “fingerprint” patterns for each HPAI H5N1 clade or for each geographic location of currently circulating H5N1 strains, respectively. Vaccine coverage was calculated to evaluate whether the vaccine candidates can effectively predict the conserved epitopes among H5N1 clades or among currently circulating strains. Population coverage of HLA-A*02:01 which binds to viral epitopes to stimulate human immune response, was queried in different geographic or ethnic populations. Forty-nine possible conserved CD8+ T-cell-reactive epitopes along 28 different amino acid positions of the HA surface protein were predicted. Although many H5N1 clades have emerged over time, reconstruction of the viruses’ history suggested that only four clades (clades 1, 2.1-2.3) have continued to persist and circulate in birds and human populations since 2012. Epitope “fingerprint” patterns representative of each H5N1 lineage or of each geographic location for currently circulating strains, provided a rapid evaluation of the effectiveness of vaccine candidates. The highly conserved epitopes in certain positions proposed a new perspective to develop a universal epitope-based vaccine candidate for HPAI H5N1. The vaccine coverage analyses showed high coverage in all H5N1 isolates at certain epitope positions, however, the positions with lower coverage may explain why the vaccine candidates do not always function well. The similar pattern was found in the currently circulating strains, but the mean overall coverage of each vaccine candidates and the time of most recent common ancestor (TMRCA) between the currently circulating strains and their closest vaccine candidates suggested that both the prediction of conserved epitopes and the surveillance of H5N1 genetic characteristics are important to evaluate the effectiveness of vaccine strains. Population coverage of HLA-A*02:01 varied in different populations, and was inversely correlated with the percentage of H5N1 isolates among geographic locations. These findings emphasized the importance of pre-existing immune protection can affect the extent or scale of H5N1 pandemic in different populations. The usage of conserved epitopes for HPAI H5N1 universal vaccine development is to determine the best combination of conserved epitopes among different H5N1 genes that maximize the human population coverage of HLA groups. Taken together, our results suggest combining molecular epidemiology of HPAI H5N1 with HLA paratope protective coverage mapping may be valuable to pre-pandemic planning and vaccine design.

Subject Area

Evolution and Development|Epidemiology

Recommended Citation

Qiu, Xueting, "Predicting H5N1 lineage specific human CD8+ T-cell-reactive epitopes for vaccine selection" (2015). Texas Medical Center Dissertations (via ProQuest). AAI1604156.
https://digitalcommons.library.tmc.edu/dissertations/AAI1604156

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