Quinones-Mateu, M. E. | Search bioRxiv

bioRxiv2019

In Vivo Emergence of a Novel Protease Inhibitor Resistance Signature in HIV-1 Matrix

BackgroundProtease Inhibitors (PIs) are the second- and last-line therapy for the majority of HIV-infected patients worldwide. Only around 20% of individuals who fail PI regimens develop major resistance mutations in protease. We sought to explore the role of mutations in gag-protease genotypic and phenotypic changes within six Nigerian patients who failed PI-based regimens without known drug resistance associated protease mutations in order to identify novel determinants of PI resistance. MethodsTarget enrichment and NGS by Illumina Miseq were followed by haplotype reconstruction. Full length gag-protease regions were amplified from baseline (pre-PI) and virologic failure (VF) samples, sequenced and used to construct gag/protease pseudotyped viruses. Phylogenetic analysis was performed using maximum likelihood methods. Susceptibility to lopinavir (LPV) and darunavir (DRV) were measured using a single-cycle replication assay. Western blotting was used to analyse Gag cleavage. ResultsIn one of six participants (subtype CRF02_AG) we found 4-fold lower LPV susceptibility in viral clones during failure of second line treatment. A combination of four mutations (S126del, H127del, T122A and G123E) in p17 matrix of baseline virus generated a similar 4x decrease in susceptibility to LPV but not darunavir. These four amino acid changes were also able to confer LPV resistance to a subtype B gag-protease backbone. Western blotting did not demonstrate significant Gag cleavage differences between sensitive and resistant isolates. Resistant viruses had around 2-fold lower infectivity compared to sensitive clones in the absence of drug. NGS combined with haplotype reconstruction revealed resistant, less fit clones emerged from a minority population at baseline and thereafter persisted alongside sensitive fitter viruses. ConclusionsWe have used a multi-pronged genotypic and phenotypic approach to document emergence and temporal dynamics of a novel protease inhibitor resistance signature in p17 matrix, revealing the interplay between Gag associated resistance and fitness.

microbiology↗

bioRxiv2019

Detection of novel HIV-1 drug resistance mutations by support vector analysis of deep sequence data and experimental validation

The global HIV-1 pandemic comprises many genetically divergent subtypes. Most of our understanding of drug resistance in HIV-1 derives from subtype B, which predominates in North America and western Europe. However, about 90% of the pandemic represents non-subtype B infections. Here, we use deep sequencing to analyze HIV-1 from infected individuals in Uganda who were either treatment-naive or who experienced virologic failure on ART without the expected patterns of drug resistance. Our objective was to detect potentially novel associations between mutations in HIV-1 integrase and treatment outcomes in Uganda, where most infections are subtypes A or D. We retrieved a total of 380 archived plasma samples from patients at the Joint Clinical Research Centre (Kampala), of which 328 were integrase inhibitor-naive and 52 were raltegravir (RAL)-based treatment failures. Next, we developed a bioinformatic pipeline for alignment and variant calling of the deep sequence data obtained from these samples from a MiSeq platform (Illumina). To detect associations between within-patient polymorphisms and treatment outcomes, we used a support vector machine (SVM) for feature selection with multiple imputation to account for partial reads and low quality base calls. Candidate point mutations of interest were experimentally introduced into the HIV-1 subtype B NL4-3 backbone to determine susceptibility to RAL in U87.CD4.CXCR4 cells. Finally, we carried out replication capacity experiments with wild-type and mutant viruses in TZM-bl cells in the presence and absence of RAL. Our analyses not only identified the known major mutation N155H and accessory mutations G163R and V151I, but also novel mutations I203M and I208L as most highly associated with RAL failure. The I203M and I208L mutations resulted in significantly decreased susceptibility to RAL (44.0-fold and 54.9-fold, respectively) compared to wild-type virus (EC50=0.32 nM), and may represent novel pathways of HIV-1 resistance to modern treatments.\n\nAuthor summaryThere are many different types of HIV-1 around the world. Most of the research on how HIV-1 can become resistant to drug treatment has focused on the type (B) that is the most common in high-income countries. However, about 90% of infections around the world are caused by a type other than B. We used next-generation sequencing to analyze samples of HIV-1 from patients in Uganda (mostly infected by types A and D) for whom drug treatment failed to work, and whose infections did not fit the classic pattern of adaptation based on B. Next, we used machine learning to detect mutations in these virus populations that could explain the treatment outcomes. Finally, we experimentally added two candidate mutations identified by our analysis to a laboratory strain of HIV-1 and confirmed that they conferred drug resistance to the virus. Our study reveals new pathways that other types of HIV-1 may use to evolve resistance to drugs that make up the current recommended treatment for newly diagnosed individuals.

microbiology↗