Doctor of Philosophy / Department of Diagnostic Medicine and Pathobiology / Raymond R. R. Rowland / Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) is the most costly virus to the swine industry, worldwide. This study explored the application of deep sequencing techniques to understand better the virus-host interaction. On the virus side, PRRSV exists as a quasispecies. The first application of deep sequencing was to investigate amino acid substitutions in hypervariable regions during acute infection and after virus rebound. The appearance and disappearance of mutations, especially the generation of a new N-glycosylation site in GP5, indicated they are likely the result of immune selection. The second application of deep sequencing was to investigate the quasispecies makeup in pigs with severe combined immunodeficiency (SCID) that lack B and T cells. The results showed the same pattern of amino acid substitutions in SCID and normal littermates and no different mutations were identified between SCID and normal littermates. This suggests the mutations that appear during the early stages of infection are the product of the virus becoming adapted to replication in pigs. The third application of deep sequencing was to investigate the locations of recombination events between GFP-expressing PRRSV infectious clones. The results identified different cross-over occurred within three conserved regions between EGFP and GFPm genes. And finally, the fourth goal was applied to develop a set of sequencing tools for analyzing the host antibody repertoire. A simple method was developed to amplify swine VDJ repertoires. Shared and abundant VDJ sequences that are likely expressed by PRRSV-activated B cells were determined in pigs that had different neutralization activities. These sequences are potentially correlated with different antibody responses.
| Identifer | oai:union.ndltd.org:KSU/oai:krex.k-state.edu:2097/18664 |
| Date | January 1900 |
| Creators | Chen, Nanhua |
| Publisher | Kansas State University |
| Source Sets | K-State Research Exchange |
| Language | en_US |
| Detected Language | English |
| Type | Dissertation |
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