Dataset Information

Predicting the broadly neutralizing antibody susceptibility of the HIV reservoir.

ABSTRACT: Broadly neutralizing antibodies (bNAbs) against HIV-1 are under evaluation for both prevention and therapy. HIV-1 sequence diversity observed in most HIV-infected individuals and archived variations in critical bNAb epitopes present a major challenge for the clinical application of bNAbs, as preexistent resistant viral strains can emerge, resulting in bNAb failure to control HIV. In order to identify viral resistance in patients prior to antibody therapy and to guide the selection of effective bNAb combination regimens, we developed what we believe to be a novel Bayesian machine-learning model that uses HIV-1 envelope protein sequences and foremost approximated glycan occupancy information as variables to quantitatively predict the half-maximal inhibitory concentrations (IC50) of 126 neutralizing antibodies against a variety of cross clade viruses. We then applied this model to peripheral blood mononuclear cell-derived proviral Env sequences from 25 HIV-1-infected individuals mapping the landscape of neutralization resistance within each individual's reservoir and determined the predicted ideal bNAb combination to achieve 100% neutralization at IC50 values <1 ?g/ml. Furthermore, predicted cellular viral reservoir neutralization signatures of individuals before an analytical antiretroviral treatment interruption were consistent with the measured neutralization susceptibilities of the respective plasma rebound viruses, validating our model as a potentially novel tool to facilitate the advancement of bNAbs into the clinic.

SUBMITTER: Yu WH

PROVIDER: S-EPMC6777915 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Predicting the broadly neutralizing antibody susceptibility of the HIV reservoir.

Yu Wen-Han WH Su David D Torabi Julia J Fennessey Christine M CM Shiakolas Andrea A Lynch Rebecca R Chun Tae-Wook TW Doria-Rose Nicole N Alter Galit G Seaman Michael S MS Keele Brandon F BF Lauffenburger Douglas A DA Julg Boris B

JCI insight 20190905 17

Broadly neutralizing antibodies (bNAbs) against HIV-1 are under evaluation for both prevention and therapy. HIV-1 sequence diversity observed in most HIV-infected individuals and archived variations in critical bNAb epitopes present a major challenge for the clinical application of bNAbs, as preexistent resistant viral strains can emerge, resulting in bNAb failure to control HIV. In order to identify viral resistance in patients prior to antibody therapy and to guide the selection of effective b ...[more]

PMID: 31484826

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Project description:In clinical trials, HIV-1 broadly neutralizing antibodies (bnAbs) effectively lower plasma viremia and delay virus reemergence. The presence of less neutralization-susceptible strains prior to treatment decreases the efficacy of these antibody-based treatments, but neutralization sensitivity often cannot be predicted by sequence analysis alone. We found that phenotypically confirmed CXCR4-utilizing strains are less neutralization sensitive, especially to variable loop 3 (V3 loop)-directed bnAbs, than exclusively CCR5-utilizing strains in some, but not all, cases. Homology modeling suggested that the primary V3 loop bnAb epitope is equally accessible among CCR5- and CXCR4-using strains, although variants that exclusively use CXCR4 have V3 loop protrusions that interfere with CCR5 receptor interactions. Homology modeling also showed that among some, but not all, envelopes with decreased neutralization sensitivity, V1 loop orientation interfered with V3 loop-directed bnAb binding. Thus, there are likely different structural reasons for the coreceptor usage restriction and the different bnAb susceptibilities. Importantly, we show that individuals harboring envelopes with higher likelihood of using CXCR4 or greater predicted V1 loop interference have faster virus rebound and a lower maximum decrease in plasma viremia, respectively, after treatment with a V3 loop bnAb. Knowledge of receptor usage and homology models may be useful in developing future algorithms that predict treatment efficacy with V3 loop bnAbs.IMPORTANCE The efficacy of HIV-1 broadly neutralizing antibody (bnAb) therapies may be compromised by the preexistence of less susceptible variants. Sequence-based methods are needed to predict pretreatment variants' neutralization sensitivities. HIV-1 strains that exclusively use the CXCR4 receptor rather than the CCR5 receptor are less neutralization susceptible, especially to variable loop 3 (V3 loop) bnAbs in some, but not all, instances. While the inability to utilize the CCR5 receptor maps to a predicted protrusion in the envelope V3 loop, this viral determinant does not directly influence V3 loop bnAb sensitivity. Homology modeling predicts that contact between the envelope V1 loop and the antibody impacts V3 loop bnAb susceptibility in some cases. Among pretreatment envelopes, increased probability of using CXCR4 and greater predicted V1 interference are associated with faster virus rebound and a smaller decrease in the plasma virus level, respectively, after V3 loop bnAb treatment. Receptor usage information and homology models may be useful for predicting V3 loop bnAb therapy efficacy.

Project description:BACKGROUND: Recent efforts in HIV-1 vaccine design have focused on immunogens that evoke potent neutralizing antibody responses to a broad spectrum of viruses circulating worldwide. However, the development of effective vaccines will depend on the identification and characterization of the neutralizing antibodies and their epitopes. We developed bioinformatics methods to predict epitope networks and antigenic determinants using structural information, as well as corresponding genotypes and phenotypes generated by a highly sensitive and reproducible neutralization assay.282 clonal envelope sequences from a multiclade panel of HIV-1 viruses were tested in viral neutralization assays with an array of broadly neutralizing monoclonal antibodies (mAbs: b12, PG9,16, PGT121 - 128, PGT130 - 131, PGT135 - 137, PGT141 - 145, and PGV04). We correlated IC50 titers with the envelope sequences, and used this information to predict antibody epitope networks. Structural patches were defined as amino acid groups based on solvent-accessibility, radius, atomic depth, and interaction networks within 3D envelope models. We applied a boosted algorithm consisting of multiple machine-learning and statistical models to evaluate these patches as possible antibody epitope regions, evidenced by strong correlations with the neutralization response for each antibody. RESULTS: We identified patch clusters with significant correlation to IC50 titers as sites that impact neutralization sensitivity and therefore are potentially part of the antibody binding sites. Predicted epitope networks were mostly located within the variable loops of the envelope glycoprotein (gp120), particularly in V1/V2. Site-directed mutagenesis experiments involving residues identified as epitope networks across multiple mAbs confirmed association of these residues with loss or gain of neutralization sensitivity. CONCLUSIONS: Computational methods were implemented to rapidly survey protein structures and predict epitope networks associated with response to individual monoclonal antibodies, which resulted in the identification and deeper understanding of immunological hotspots targeted by broadly neutralizing HIV-1 antibodies.

Dataset Information

Predicting the broadly neutralizing antibody susceptibility of the HIV reservoir.

Publications

Predicting the broadly neutralizing antibody susceptibility of the HIV reservoir.

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