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Deep sequencing of protease inhibitor resistant HIV patient isolates reveals patterns of correlated mutations in Gag and protease.

ABSTRACT: While the role of drug resistance mutations in HIV protease has been studied comprehensively, mutations in its substrate, Gag, have not been extensively cataloged. Using deep sequencing, we analyzed a unique collection of longitudinal viral samples from 93 patients who have been treated with therapies containing protease inhibitors (PIs). Due to the high sequence coverage within each sample, the frequencies of mutations at individual positions were calculated with high precision. We used this information to characterize the variability in the Gag polyprotein and its effects on PI-therapy outcomes. To examine covariation of mutations between two different sites using deep sequencing data, we developed an approach to estimate the tight bounds on the two-site bivariate probabilities in each viral sample, and the mutual information between pairs of positions based on all the bounds. Utilizing the new methodology we found that mutations in the matrix and p6 proteins contribute to continued therapy failure and have a major role in the network of strongly correlated mutations in the Gag polyprotein, as well as between Gag and protease. Although covariation is not direct evidence of structural propensities, we found the strongest correlations between residues on capsid and matrix of the same Gag protein were often due to structural proximity. This suggests that some of the strongest inter-protein Gag correlations are the result of structural proximity. Moreover, the strong covariation between residues in matrix and capsid at the N-terminus with p1 and p6 at the C-terminus is consistent with residue-residue contacts between these proteins at some point in the viral life cycle.

SUBMITTER: Flynn WF

PROVIDER: S-EPMC4404092 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

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Deep sequencing of protease inhibitor resistant HIV patient isolates reveals patterns of correlated mutations in Gag and protease.

Flynn William F WF Chang Max W MW Tan Zhiqiang Z Oliveira Glenn G Yuan Jinyun J Okulicz Jason F JF Torbett Bruce E BE Levy Ronald M RM

PLoS computational biology 20150420 4

While the role of drug resistance mutations in HIV protease has been studied comprehensively, mutations in its substrate, Gag, have not been extensively cataloged. Using deep sequencing, we analyzed a unique collection of longitudinal viral samples from 93 patients who have been treated with therapies containing protease inhibitors (PIs). Due to the high sequence coverage within each sample, the frequencies of mutations at individual positions were calculated with high precision. We used this in ...[more]

PMID: 25894830

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Project description:BackgroundStrategies to control HIV for improving the quality of patient lives have been aided by the Highly Active Anti-Retroviral Therapy (HAART), which consists of a cocktail of inhibitors targeting key viral enzymes. Numerous new drugs have been developed over the past few decades but viral resistances to these drugs in the targeted viral enzymes are increasingly reported. Nonetheless the acquired mutations often reduce viral fitness and infectivity. Viral compensatory secondary-line mutations mitigate this loss of fitness, equipping the virus with a broad spectrum of resistance against these drugs. While structural understanding of the viral protease and its drug resistance mutations have been well established, the interconnectivity and development of structural cross-resistance remain unclear. This paper reports the structural analyses of recent clinical mutations on the drug cross-resistance effects from various protease and protease inhibitors (PIs) complexes.MethodsUsing the 2015 updated clinical HIV protease mutations, we constructed a structure-based correlation network and a minimum-spanning tree (MST) based on the following features: (i) topology of the PI-binding pocket, (ii) allosteric effects of the mutations, and (iii) protease structural stability.Results and conclusionAnalyis of the network and the MST of dominant mutations conferring resistance to the seven PIs (Atazanavir-ATV, Darunavir-DRV, Indinavir-IDV, Lopinavir-LPV, Nelfinavir-NFV, Saquinavir-SQV, and Tipranavir-TPV) showed that cross-resistance can develop easily across NFV, SQV, LPV, IDV, and DRV, but not for ATV or TPV. Through estimation of the changes in vibrational entropies caused by each reported mutation, some secondary mutations were found to destabilize protease structure. Our findings provide an insight into the mechanism of PI cross-resistance and may also be useful in guiding the selection of PI in clinical treatment to delay the onset of cross drug resistance.

Project description:UnlabelledBecause of recent advances in deep sequencing technology, detailed analysis of hepatitis C virus (HCV) quasispecies and their dynamic changes in response to direct antiviral agents (DAAs) became possible, although the role of quasispecies is not fully understood. In this study, to clarify the evolution of viral quasispecies and the origin of drug-resistant mutations induced by interferon (IFN)-based protease inhibitor therapy, the nonstructural-3 (NS3) region of genotype 1b HCV in 34 chronic hepatitis patients treated with telaprevir (TVR)/pegylated interferon (PEG-IFN)/ribavirin (RBV) was subjected to a deep sequencing study coupled with phylogenetic analysis. Twenty-six patients (76.5%) achieved a sustained viral response (SVR), while 8 patients did not (non-SVR; 23.5%). When the complexity of the quasispecies was expressed as the mutation frequency or Shannon entropy value, a significant decrease in the IFNL3 (rs8099917) TT group and a marginal decrease in the SVR group were found soon (12 h) after the introduction of treatment, whereas there was no decrease in the non-SVR group and no significant decrease in mutation frequency in the IFNL3 TG/GG group. In the analysis of viral quasispecies composition in non-SVR patients, major populations greatly changed, accompanied by the appearance of resistance, and the compositions were unlikely to return to the pretreatment composition even after the end of therapy. Clinically TVR-resistant variants were observed in 5 non-SVR patients (5/8, 62.5%), all of which were suspected to have acquired resistance by mutations through phylogenetic analysis. In conclusion, results of the study have important implications for treatment response and outcome in interferon-based protease inhibitor therapy.ImportanceIn the host, hepatitis C virus (HCV) consists of a variety of populations (quasispecies), and it is supposed that dynamic changes in quasispecies are closely related to pathogenesis, although this is poorly understood. In this study, recently developed deep sequencing technology was introduced, and changes in quasispecies associated with telaprevir (TVR)/pegylated interferon (PEG-IFN)/ribavirin (RBV) triple therapy and their clinical significance were investigated extensively by phylogenetic tree analysis. Through this study, the associations among treatment response, changes in viral quasispecies complexity in the early stage of treatment, changes in the quasispecies composition, and origin of TVR-resistant variant HCV were elucidated.

Dataset Information

Deep sequencing of protease inhibitor resistant HIV patient isolates reveals patterns of correlated mutations in Gag and protease.

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Deep sequencing of protease inhibitor resistant HIV patient isolates reveals patterns of correlated mutations in Gag and protease.

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