Analyses of HIV-1 integrase sequences prior to South African national HIV-treatment program and available of integrase inhibitors in Cape Town, South Africa

Abstract

HIV-Integrase (IN) has proven to be a viable target for highly specific HIV-1 therapy. We aimed to characterize the HIV-1 IN gene in a South African context and identify resistance-associated mutations (RAMs) against available first and second generation Integrase strand-transfer inhibitors (InSTIs). We performed genetic analyses on 91 treatment-naïve HIV-1 infected patients, as well as 314 treatment-naive South African HIV-1 IN-sequences, downloaded from Los Alamos HIV Sequence Database. Genotypic analyses revealed the absence of major RAMs in the cohort collected before the broad availability of combination antiretroviral therapy (cART) and INSTI in South Africa, however, occurred at a rate of 2.85% (9/314) in database derived sequences. RAMs were present at IN-positions 66, 92, 143, 147 and 148, all of which may confer resistance to Raltegravir (RAL) and Elvitegravir (EVG), but are unlikely to affect second-generation Dolutegravir (DTG), except mutations in the Q148 pathway. Furthermore, protein modeling showed, naturally occurring polymorphisms impact the stability of the intasome-complex and therefore may contribute to an overall potency against InSTIs. Our data suggest the prevalence of InSTI RAMs, against InSTIs, is low in South Africa, but natural polymorphisms and subtype-specific differences may influence the effect of individual treatment regimens.

Figure 1

HIV-1 Integrase molecular phylogenetic analysis inferred by the maximum likelihood (ML) method. The ML phylogenetic tree inferred in RAxmL contains 91 patient sequences and HIV-1 reference sequences dataset from 2010 were acquired from HIV-1 LANL database. The evolutionary distances were computed using the general time reverse (GTR) model of nucleic acid substitution with an estimated Gamma shape parameter and invariant sites. The genetic distance is displayed in the scale bar at the bottom of the figure; while the majority of the sequences clusters with HIV-1 subtype C. 87 of the samples clustered with Subtype C reference strains (91.1%), five with Subtype B (5,6%) and one with Subtype A1 strains (1.1%).

Figure 2

HIV-1C_ZA Integrase mutation profiling. Integrase mutation profiling of consensus sequences generated using the database-derived HIV-1C_ZA sequences HIV-1B (n = 5278), HIV-1C (n = 1416), cohort sequences HIV-1C-ZA (n = 87) identified 17 naturally occurring polymorphisms D25E, V31I, M50I, I72V, F100Y, L101I, T112V, T124A, T125A, K136Q, V201I, T218I, L234I, A265V, R269K, D278A and S283G. Among the 17 mutations 11 were further increased in our cohort

Figure 3

Homology derived molecular model of consensus HIV-1C_ZA. Homology derived a molecular model of Con_C_ZA. Figure A shows an intasome consisting of a tetramer of subtype C_ZA and substrate DNA. This structure was generated using the cryoEM structure of HIV-1B IN intasome (PDB file 5U1C) using ‘Prime’ of Schrodinger Suit using the protocol discussed in Neogi et al., 2016. Inset in panel shows the proximity of I50 to DNA. Two I50 residues from two different subunit interact with DNA from two different sides. Figure B shows the position of E25 (in subunit colored green) that forms a ion-pair with K188 of subunit colored magenta. This is a symmetric interaction as E25 from magenta subunit interacts with K188 of green subunit. This interaction is important in maintaining the tetramer of IN. Figure C shows the active site residues D64, D116 and E152 of IN in one subunit (colored green) together with Y100 and I100 in the same and in the neighboring subunit. This figure also shows the position of I201 in two neighboring subunits. This interaction also appears critical for the maintenance tetramer organization of IN.