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.

Inference of epistatic effects leading to entrenchment and drug resistance in HIV-1 protease

“…The results presented here advance recent work in the field, using Potts models to study HIV-1 evolution (Barton et al 2016b;Butler et al 2016), by providing systematic prospective predictions quantifying the influence of specific multi-residue patterns on the tolerance of drug resistance mutations. Recent publications have reported that mutations near or distal to Gag cleavage sites play a role in promoting cleavage by drug-resistant and enzymatically deficient proteases, by selecting for mutations that increase substrate contacts with the protease active site, altering the flexibility of the cleavage site vicinity, or by as of yet unknown mechanisms Kolli et al 2009;Breuer et al 2011;Parry et al 2011;Fun et al 2012;Flynn et al 2015). This suggests that viral coevolution of Gag with selective protease mutations may further stabilize multiple resistance mutations; thus, the analysis of protease mutation patterns can be extended to include amino acid substitutions within Gag and the Gag-Pol polyprotein.…”

“…This process is then repeated for each position by selecting the merger of characters which minimizes the RMSD in MI between all pairs of positions ij with the original alphabet size Q ¼ 21 and reduced alphabet size Q ¼ Q 0 , and is stopped once Q ¼ 2. Due to residue conservation at many loci in the HIV-1 protease genome, the average number of characters per position is 2, and several previous studies of HIV-1 have used a binary alphabet to extract meaningful information from sequences (Wu et al 2003;Ferguson et al 2013;Shekhar et al 2013;Flynn et al 2015). However, using a binary alphabet (wildtype, mutant) marginalizes potentially informative distinctions between amino acids at certain positions, especially PI-associated sites, that acquire multiple mutations from the wildtype.…”

Wide variation in susceptibility of transmitted/founder HIV-1 subtype C Isolates to protease inhibitors and association with in vitro replication efficiency

“…Protease sequences were analysed using the Stanford Drug Resistance Algorithm for the presence of known resistance mutations and polymorphisms27. Additionally, a mutual information statistical approach (with correction for multiple comparisons) was used to identify novel mutations in Gag associated with LPV EC 50 28.…”

HIV Genome-Wide Protein Associations: a Review of 30 Years of Research

“…It is known that drug-resistant mutations in drug-targeted proteins lead to treatment failure in HIV-infected patients (556). However, recent studies also suggest that protein-protein interactions may provide novel drug resistance mechanisms for HIV to escape the inhibition of antiviral drugs (4,85,557,558). In principle, current findings rely on the hypothesis that the drug resistance of anti-HIV inhibitors could be established by sequence changes outside druginhibited proteins, owing to the physical interactions between drug-inhibited proteins and other HIV proteins.…”

“…Moreover, Gag mutations such as V128I, Y132F, K415R, Q430R, A431V, L449FV, S451GT, R452S, and P453TL are significantly associated with protease drug resistance (502,505). As new PI-associated Gag mutations have been consistently reported (558,570), further studies are required to map all PI-associated Gag mutations and to evaluate their impacts in studies with large patient populations.…”