Antibodyomics: bioinformatics technologies for understanding B-cell immunity to HIV-1.

ABSTRACT

Numerous antibodies have been identified from HIV-1-infected donors that neutralize diverse strains of HIV-1. These antibodies may provide the basis for a B cell-mediated HIV-1 vaccine. However, it has been unclear how to elicit similar antibodies by vaccination. To address this issue, we have undertaken an informatics-based approach to understand the genetic and immunologic processes controlling the development of HIV-1-neutralizing antibodies. As DNA sequencing comprises the fastest growing database of biological information, we focused on incorporating next-generation sequencing of B-cell transcripts to determine the origin, maturation pathway, and prevalence of broadly neutralizing antibody lineages (Antibodyomics1, 2, 4, and 6). We also incorporated large-scale robotic analyses of serum neutralization to identify and quantify neutralizing antibodies in donor cohorts (Antibodyomics3). Statistical analyses furnish another layer of insight (Antibodyomics5), with physical characteristics of antibodies and their targets through molecular dynamics simulations (Antibodyomics7) and free energy perturbation analyses (Antibodyomics8) providing information-rich output. Functional interrogation of individual antibodies (Antibodyomics9) and synthetic antibody libraries (Antibodyomics10) also yields multi-dimensional data by which to understand and improve antibodies. Antibodyomics, described here, thus comprise resolution-enhancing tools, which collectively embody an information-driven discovery engine aimed toward the development of effective B cell-based vaccines.