Effect of diversity in gp41 membrane proximal external region of primary HIV-1 Indian subtype C sequences on interaction with broadly neutralizing antibodies 4E10 and 10E8

Predicted resistance to broadly neutralizing antibodies (bnAbs) and associated HIV-1 envelope characteristics among seroconverting adults in Botswana

We used HIV-1C sequences to predict (in silico) resistance to 33 known broadly neutralizing antibodies (bnAbs) and evaluate the different HIV-1 Env characteristics that may affect virus neutralization. We analyzed proviral sequences from adults with documented HIV-1 seroconversion (N = 140) in Botswana (2013-2018). HIV-1 env sequences were used to predict bnAb resistance using bNAb-ReP, to determine the number of potential N-linked glycosylation sites (PNGS) and evaluate Env variable region characteristics (VC). We also assessed the presence of signature mutations that may affect bnAb sensitivity in vitro. We observe varied results for predicted bnAb resistance among our cohort. 3BNC117 showed high predicted resistance (72%) compared to intermediate levels of resistance to VRC01 (57%). We predict low resistance to PGDM100 and 10-1074 and no resistance to 4E10. No difference was observed in the frequency of PNGS by bNAb susceptibility patterns except for higher number of PNGs in V3 bnAb resistant strains. Associations of VC were observed for V1, V4 and V5 loop length and net charge. We also observed few mutations that have been reported to confer bnAb resistance in vitro. Our results support use of sequence data and machine learning tools to predict the best bnAbs to use within populations.

Predicted broadly neutralizing antibody (bnAb) resistance and associated envelope characteristics of adults with HIV-1 seroconversion in Botswana

We used HIV-1C sequences to predict (in silico) resistance to 33 known broadly neutralizing antibodies (bNAbs) and evaluate the different HIV-1 env characteristics that may affect virus neutralization. We analyzed proviral sequences from adults with documented HIV-1 seroconversion (N=140) in Botswana (2013-2018). HIV-1 env sequences were used to predict bnAb resistance using bNAb-ReP, to determine the number of potential N-linked glycosylation sites (PNGS) and evaluate env variable region characteristics (VC). We also assessed the presence of signature mutations that may affect bnAb sensitivity in vitro. We observe varied results for predicted bnAb resistance among our cohort. 3BNC117 showed high predicted resistance (72%) compared to intermediate levels of resistance to VRC01 (57%). We predict low resistance to PGDM100 and 10-1074 and no resistance to 4E10. No difference was observed in the frequency of PNGS by bNAb susceptibility patterns except for higher number of PNGs in V3 bnAb resistant strains. Associations of VC were observed for V1, V4 and V5 loop length and net charge. We also observed few mutations that have been reported to confer bnAb resistance in vitro. Our results support use of sequence data and machine learning tools to predict the best bnAbs to use within populations.

Geospatial HIV-1 subtype C gp120 sequence diversity and its predicted impact on broadly neutralizing antibody sensitivity

Evolving diversity in globally circulating HIV-1 subtypes presents a 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. In the present study, we examined the diversity in genetic signatures and attributes that differentiate region-specific 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. Subtype C sequences from Asian countries including India differed phylogenetically when compared with that from African countries. Variable loop lengths and charges within Indian and African clusters were also found to be distinct from each other, specifically for V1, V2 and V4 loops. 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 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.

Applying next-generation sequencing to unravel the mutational landscape in viral quasispecies

Next-generation sequencing (NGS) has revolutionized the scale and depth of biomedical sciences. Because of its unique ability for the detection of sub-clonal variants within genetically diverse populations, NGS has been successfully applied to analyze and quantify the exceptionally-high diversity within viral quasispecies, and many low-frequency drug- or vaccine-resistant mutations of therapeutic importance have been discovered. Although many works have intensively discussed the latest NGS approaches and applications in general, none of them has focused on applying NGS in viral quasispecies studies, mostly due to the limited ability of current NGS technologies to accurately detect and quantify rare viral variants. Here, we summarize several error-correction strategies that have been developed to enhance the detection accuracy of minority variants. We also discuss critical considerations for preparing a sequencing library from viral RNAs and for analyzing NGS data to unravel the mutational landscape.

Analysis of sequence diversity and selection pressure in HIV-1 clade C gp41 from India

Evaluation of viral diversity is critical for the rational design of treatment modalities against Human immunodeficiency virus (HIV). Predominated by HIV-1 clade C (HIV-1C), the epidemic in India represents the third largest population infected with HIV-1 globally. Glycoprotein 41 (gp41) is critical for viral replication and is a target for the design of therapeutic strategies. However, documentation of viral diversity of gp41 gene in infected individuals from India remains limited. Present study employed high throughput sequencing to examine variation in gp41 amplicons generated from blood derived viruses in 24 HIV-1C infected individuals from Mumbai, India. Sequence diversity profiles were documented in different functional domains of gp41. Furthermore, through a meta-analysis approach, all reported gp41 sequences from India (N = 70) were compared with those from South Africa (N = 126), country with the largest HIV epidemic globally, also predominated by HIV-1C. A total of 44 positions displayed statistically significant differential (p < 0.05) Shannon entropy in the two regions. This comparison also identified 11 codon sites undergoing distinct selection, 8 of which remained differentially selected in an extended comparison of data from Asia (N = 137) and Africa(N = 383). Assessment of correlated mutation networks associated with differentially selected residues revealed common as well as distinct interaction networks. Furthermore, codon usage analysis revealed 17 differentially selected codons (Mann-Whitney test, p < 0.001) in Asia and Africa. Dissimilar trends in GC content across codon positions were also observed. In depth understanding of these divergent evolutionary signatures through extended analysis with larger data-sets would assist development of effective interventions being considered for HIV-1C.