Analysis of natural sequence variation and covariation in human immunodeficiency virus type 1 integrase

Abstract

Human immunodeficiency virus type 1 (HIV-1) integrase inhibitors are in clinical trials, and raltegravir and elvitegravir are likely to be the first licensed drugs of this novel class of HIV antivirals. Understanding resistance to these inhibitors is important to maximize their efficacy. It has been shown that natural variation and covariation provide valuable insights into the development of resistance for established HIV inhibitors. Therefore, we have undertaken a study to fully characterize natural polymorphisms and amino acid covariation within an inhibitor-naïve sequence set spanning all defined HIV-1 subtypes. Inter- and intrasubtype variation was greatest in a 50-amino-acid segment of HIV-1 integrase incorporating the catalytic aspartic acid codon 116, suggesting that polymorphisms affect inhibitor binding and pathways to resistance. The critical mutations that determine the resistance pathways to raltegravir and elvitegravir (N155H, Q148K/R/H, and E92Q) were either rare or absent from the 1,165-sequence data set. However, 25 out of 41 mutations associated with integrase inhibitor resistance were present. These mutations were not subtype associated and were more prevalent in the subtypes that had been sampled frequently within the database. A novel modification of the Jaccard index was used to analyze amino acid covariation within HIV-1 integrase. A network of 10 covarying resistance-associated mutations was elucidated, along with a further 15 previously undescribed mutations that covaried with at least two of the resistance positions. The validation of covariation as a predictive tool will be dependent on monitoring the evolution of HIV-1 integrase under drug selection pressure.

FIG. 1.

Amino acid variation in HIV-1 integrase. Subtype-specific alignments of HIV-1 were converted into frequency-based PSSMs, such that the amino acid diversity within each position of the subtype alignments was represented as a fraction of one. The variation within each position of a subtype PSSM was calculated relative to the equivalent position in the subtype B PSSM, and these values were averaged across a sliding window of 20 amino acid positions, with a step interval of 10.

FIG. 2.

Natural occurrence of HIV-1 integrase mutations by subtype (a) and inhibitor (b). (a) The frequency of integrase mutations associated with resistance to inhibitors (defined in Table 1) was calculated for the alignments of HIV-1 group M, N, and O subtypes and CRF_0101 and CRF_02 independently and within the whole 1,165-sequence data set (all). Multiple instances of differing amino acids associated with resistance at the same position were represented. White was used to indicate the absence of a resistance mutation in each alignment. The frequency of resistance mutations, if present within an alignment, was represented using a colored scale. (b) HIV-1 polymorphisms that have been associated with integrase inhibitor resistance were represented in black for primary mutations and gray for mutations associated with HIV-1 integrase inhibitor resistance (Table 1).

FIG. 3.

Neighbor-joining phylogenies of HIV-1 integrase subtype B sequences. (a) Gray dots were used to indicate the positions within the phylogeny that contained amino acid polymorphisms at 72 and 201. (b and c) Black dots indicate sequences that contained polymorphisms at positions 154 and 201. Phylogenies were generated using either real subtype B sequences from the Los Alamos database (n = 189) (a and b) or from a random sequence data set generated by permuting the original subtype B sequences (n = 1,000) (c).

FIG. 4.

(a) Correlation between original and corrected Z scores (Z and Z_D, respectively). Statistically significant amino acid covarying pairs (black diamonds) were distinguished from nonsignificant results (gray diamonds) using the corrected Z_D score, FDR, and a probability threshold of P < 0.001. The correlation coefficient between Z and Z_D was low (r² = 0.63). (b) Simulations of sequences constrained by the distance scaling factor D. Six sets of 1,000 simulated sequences were analyzed for covarying amino acids, where D was constrained between 0.1 to 0.3, 0.2 to 0.4, 0.3 to 0.5, 0.4 to 0.6, 0.5 to 0.7, and 0.6 to 0.8 within a set of sequences. The Z_D and Z scores were plotted against each other for each set, and a binomial line of best fit was calculated. The data generated using subtype B HIV-1 integrase sequences are shown as both a scatter plot and a liner of best fit. (c) Relationship between the Z score and P value for simulated data sets. FDR-corrected P values were estimated from the Z_D scores relating to each of the six simulated data sets. The minimum Z_D score required to produce a P value lower than a range of P values was plotted (the average D of six data sets is shown as a solid line; D = 0.1 to 0.3, dashed line; D = 0.6 to 0.8, dotted line).

FIG. 5.

Network of selected covarying amino acids within HIV-1 integrase. The relationships between polymorphisms associated with resistance to HIV-1 integrase inhibitors defined in Table 1 (white circles, black lines) were calculated. Circular nodes were used to represent an amino acid position, and edges (lines) joining two nodes indicate that those two amino acids covaried. The network was expanded to include amino acids that previously have not been considered resistance mutations (gray circles, gray lines). Additional integrase positions were included in the network if a new node had two more edges connecting to an established resistance-associated node. There were two instances in which two resistance-associated amino acid positions were linked by multiple novel amino acid positions; these nodes were represented by letters that relate to these amino acid positions.

FIG. 6.

Crystallographic structure of the HIV-1 integrase tetramer (chains A to D) containing the catalytic core domain and the N-terminal domain (Protein Database accession no. 1K6Y). Two chains (B, C) are colored (red, high diversity; dark blue, low diversity) using the subtype diversity measure (Fig. 1; also see Materials and Methods) and show the average diversity of windows of 5 amino acids within the integrase sequence. The remaining chains (A, D) are colored gray. Residues forming the active-site triad, Asp 64, Asp 112, and Glu 152, are shown as space-filled atoms and are annotated on the integrase B chain. The positions of the N-terminal domains within the crystal structure are shown as the chain N; however, the linker between the N-terminal domain and the catalytic core was not resolved. The C-terminal domains of HIV-1 integrase also were not present within this structure.