Vaccination of Rhesus Macaques with the Anthrax Vaccine Adsorbed Vaccine Produces a Serum Antibody Response That Effectively Neutralizes Receptor-Bound Protective Antigen In Vitro ▿

Anthrax toxin (ATx) is composed of the binary exotoxins lethal toxin (LTx) and edema toxin (ETx). They have separate effector proteins (edema factor and lethal factor) but have the same binding protein, protective antigen (PA). PA is the primary immunogen in the current licensed vaccine anthrax vaccine adsorbed (AVA [BioThrax]). AVA confers protective immunity by stimulating production of ATx-neutralizing antibodies, which could block the intoxication process at several steps (binding of PA to the target cell surface, furin cleavage, toxin complex formation, and binding/translocation of ATx into the cell). To evaluate ATx neutralization by anti-AVA antibodies, we developed two low-temperature LTx neutralization activity (TNA) assays that distinguish antibody blocking before and after binding of PA to target cells (noncomplexed [NC] and receptor-bound [RB] TNA assays). These assays were used to investigate anti-PA antibody responses in AVA-vaccinated rhesus macaques (Macaca mulatta) that survived an aerosol challenge with Bacillus anthracis Ames spores. Results showed that macaque anti-AVA sera neutralized LTx in vitro, even when PA was prebound to cells. Neutralization titers in surviving versus nonsurviving animals and between prechallenge and postchallenge activities were highly correlated. These data demonstrate that AVA stimulates a myriad of antibodies that recognize multiple neutralizing epitopes and confirm that change, loss, or occlusion of epitopes after PA is processed from PA83 to PA63 at the cell surface does not significantly affect in vitro neutralizing efficacy. Furthermore, these data support the idea that the full-length PA83 monomer is an appropriate immunogen for inclusion in next-generation anthrax vaccines

Prediction of human population responses to toxic compounds by a collaborative competition

\u3cp\u3eThe ability to computationally predict the effects of toxic compounds on humans could help address the deficiencies of current chemical safety testing. Here, we report the results from a community-based DREAM challenge to predict toxicities of environmental compounds with potential adverse health effects for human populations. We measured the cytotoxicity of 156 compounds in 884 lymphoblastoid cell lines for which genotype and transcriptional data are available as part of the Tox21 1000 Genomes Project. The challenge participants developed algorithms to predict interindividual variability of toxic response from genomic profiles and population-level cytotoxicity data from structural attributes of the compounds. 179 submitted predictions were evaluated against an experimental data set to which participants were blinded. Individual cytotoxicity predictions were better than random, with modest correlations (Pearson's r < 0.28), consistent with complex trait genomic prediction. In contrast, predictions of population-level response to different compounds were higher (r < 0.66). The results highlight the possibility of predicting health risks associated with unknown compounds, although risk estimation accuracy remains suboptimal.\u3c/p\u3