PLoS ONEBioinformaticsPeer-reviewed journal article
Geospatial HIV-1 subtype C gp120 sequence diversity and its predicted impact on broadly neutralizing antibody sensitivity
Jyoti SutariD, Suprit DeshpandeiD, Ranajoy MullickiD, Nitin K. HingankariD, Vainav V. PateliD, Jayanta BhattacharyaiD
Abstract
Evolving diversity in globally circulating HIV-1 subtypes presents formidable challenge in defining and developing neutralizing antibodies for prevention and treatment. HIV-1 subtype C is responsible for majority of global HIV-1 infections. Broadly neutralizing antibodies (bnAbs) capable of neutralizing distinct HIV-1 subtypes by targeting conserved vulnerable epitopes on viral envelope protein (Env) are being considered as promising antiviral agents for prevention and treatment. In the present study, we examined the diversity in genetic signatures and attributes that differentiate region-specific global HIV-1 subtype C gp120 sequences associated with virus neutralization outcomes to key bnAbs having distinct epitope specificities. A total of 1814 full length HIV-1 subtype C gp120 sequence from 37 countries were retrieved from Los Alamos National Laboratory HIV database (www.hiv.lanl.gov). The amino acid sequences were assessed for their phylogenetic association, variable loop lengths and prevalence of potential N-linked glycosylation sites (pNLGS). Responses of these sequences to bnAbs were predicted with a machine learning algorithm bNAb-ReP and compared with those reported in the CATNAP database. Phylogenetically, sequences from Asian countries including India clustered together however differed significantly when compared with pan African subtype C sequences. Variable loop lengths within Indian and African clusters were distinct from each other, specifically V1, V2 and V4 loops. Furthermore, V1V2 and V2 alone sequences were also found to vary significantly in their charges. Pairwise analyses at each of the 25 pNLG sites indicated distinct country specific profiles. Highly significant differences (p<0.001***) were observed in prevalence of four pNLGS (N130, N295, N392 and N448) between South Africa and India, having most disease burden associated with subtype C. Our findings highlight that the distinctly evolving clusters within global intra-subtype C gp120 sequences are likely to influence the disparate region-specific sensitivity of circulating HIV-1 subtype C to bnAbs.
- organism: human
- assay: protein sequence
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: protein structure prediction
- approach: machine learning (classical)
- Citations
- 15
- FWCI
- 1.26
- Field percentile
- top 24%
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