Torbett, Bruce EWANG, SHIYI2024-02-122024-02-122023WANG_washington_0250E_26304.pdfhttp://hdl.handle.net/1773/51052Thesis (Ph.D.)--University of Washington, 2023HIV resistance often leads to antiretroviral therapy (ART) failures, involving two crucial mutation categories: drug-resistance mutations (DRMs) and compensatory mutations. DRMs reside in HIV enzyme active sites (protease, reverse transcriptase, and integrase), hindering drug binding, while compensatory mutations restore enzyme stability and function, compensating for DRMs. With the increase of drug potency, more compensatory mutations are involved in compensating for one DRM, forming complex mutational patterns. However, the interplay between DRMs and compensatory mutations remains elusive. In this thesis work, I combined a long-read sequencing approach and bioinformatic tools to unveil the complex mutational patterns driving HIV resistance development. Long-read sequencing yielded 4.5kb gag-pol sequences from individual HIV genomes within clinical serum samples, preserving co-varying mutations critical for pattern identification. Mutational patterns were inferred based on pairwise correlations detected in the sequencing data and quantified using a custom bioinformatic tool. I utilized Hamming-distance-based phylogenetic analysis (HDBPA) and paired post-ART HIVs with their pre-ART most recent common ancestors (MRCAs) based on sequence similarity. In this way, I divided mutations in mutational patterns into different categories (mutations inherited from pre-ART MRCA, and mutations acquired during ART) and revealed the order of mutation development. I demonstrated the utility of this approach by studying the HIV evolution in two PWHs facing ART failures. The findings revealed different mutational patterns selected and enriched during ART and inferred evolutionary pathways taken by HIVs during resistance development. Alongside substitution mutation involved in HIV evolution, I participated in a collaborative study, aiming to measure linkage disequilibrium between recombination events and SNVs. The findings revealed novel correlations between p6Gag insertions and Gag cleavage site mutations in drug-resistant HIV genomes. Taken together, my work deciphered mutational patterns and recombination events driving HIV evolution during ART using long-read sequencing and custom bioinformatics tools. The findings of this study indicated interactions both within HIV proteins and among proteins, which could guide anti-viral drug design. The methods introduced could be used for identifying complex mutational patterns required for resistance development and revealing the order of mutation development in HIV as well as other fast-evolving viruses and bacteria.application/pdfen-USCC BY-NDAntiviral Drug ResistanceCombination Antiretroviral TherapyComputational BiologyHIVNanopore SequencingVirologyBioinformaticsLaboratory medicineThesis