Benchmarking B-Cell Epitope Prediction for the Design of Peptide-Based Vaccines: Problems and Prospects

To better support the design of peptide-based vaccines, refinement of methods to predict B-cell epitopes necessitates meaningful benchmarking against empirical data on the cross-reactivity of polyclonal antipeptide antibodies with proteins, such that the positive data reflect functionally relevant cross-reactivity (which is consistent with antibody-mediated change in protein function) and the negative data reflect genuine absence of cross-reactivity (rather than apparent absence of cross-reactivity due to artifactual masking of B-cell epitopes in immunoassays). These data are heterogeneous in view of multiple factors that complicate B-cell epitope prediction, notably physicochemical factors that define key structural differences between immunizing peptides and their cognate proteins (e.g., unmatched electrical charges along the peptide-protein sequence alignments). If the data are partitioned with respect to these factors, iterative parallel benchmarking against the resulting subsets of data provides a basis for systematically identifying and addressing the limitations of methods for B-cell epitope prediction as applied to vaccine design

On the Meaning of Affinity Limits in B-Cell Epitope Prediction for Antipeptide Antibody-Mediated Immunity

B-cell epitope prediction aims to aid the design of peptide-based immunogens (e.g., vaccines) for eliciting antipeptide antibodies that protect against disease, but such antibodies fail to confer protection and even promote disease if they bind with low affinity. Hence, the Immune Epitope Database (IEDB) was searched to obtain published thermodynamic and kinetic data on binding interactions of antipeptide antibodies. The data suggest that the affinity of the antibodies for their immunizing peptides appears to be limited in a manner consistent with previously proposed kinetic constraints on affinity maturation in vivo and that crossreaction of the antibodies with proteins tends to occur with lower affinity than the corresponding reaction of the antibodies with their immunizing peptides. These observations better inform B-cell epitope prediction to avoid overestimating the affinity for both active and passive immunization; whereas active immunization is subject to limitations of affinity maturation in vivo and of the capacity to accumulate endogenous antibodies, passive immunization may transcend such limitations, possibly with the aid of artificial affinity-selection processes and of protein engineering. Additionally, protein disorder warrants further investigation as a possible supplementary criterion for B-cell epitope prediction, where such disorder obviates thermodynamically unfavorable protein structural adjustments in cross-reactions between antipeptide antibodies and proteins

Functional analysis of GALT variants found in classic galactosemia patients using a novel cell‐free translation method

Classic galactosemia is an autosomal recessive disorder caused by deleterious variants in the galactose-1-phosphate uridylyltransferase () gene. GALT enzyme deficiency leads to an increase in the levels of galactose and its metabolites in the blood causing neurodevelopmental and other clinical complications in affected individuals. Two variants NM_000155.3:c.347T>C (p.Leu116Pro) and NM_000155.3:c.533T>G (p.Met178Arg) were previously detected in Filipino patients. Here, we determine their functional effects on the GALT enzyme through analysis and a novel experimental approach using a HeLa-based cell-free protein expression system. Enzyme activity was not detected for the p.Leu116Pro protein variant, while only 4.5% of wild-type activity was detected for the p.Met178Arg protein variant. Computational analysis of the variants revealed destabilizing structural effects and suggested protein misfolding as the potential mechanism of enzymological impairment. Biochemical and computational data support the classification of p.Leu116Pro and p.Met178Arg variants as pathogenic. Moreover, the protein expression method developed has utility for future studies of variants

Characterization of Philippine drug-susceptible and multi-drug resistant mycobacterium tuberculosis isolates through combined 15-locus MIRU-VNTR genotyping and mutation analysis of drug resistance genes

Molecular genotyping, an important strategy to characterize bacterial strains infecting patients, allows identification of M. tuberculosis (MTb) complex members with varying responses to anti-mycobacterial therapy. M. tuberculosis Interspersed Repeating Units – Variable Number of Tandem Repeats (MIRU-VNTR) is a fast, reproducible and cost-effective PCR-based method capable of differentiating MTb strains. This study focused on evaluating the utility of MIRU-VNTRs to differentiate 54 MTB isolates from the Lung Center of the Philippines (LCP) through amplification of twelve MIRU-VNTRs and three Exact Tandem Repeats (ETRs). Digital codes were determined per isolate through calculation of VNTR repeats and analyzed using the MIRU-VNTRplus program (http://www.miruvntrplus.org/MIRU/index.faces). Values of the Hunter-Gaston discriminatory index (HGDI) suggest that five of fifteen (33.33%) MIRU-VNTRs are highly discriminating (\u3e0.75). All MIRU-VNTRs and ETRs except ETRC had HGDI values indicative of good resolving power (≥0.5). Among the LCP isolates, four Mtb clusters closely related to the East AfricanIndian strain family were identified on the basis of MIRU-VNTR profiles and mutation data on rpoB, katG and gyrA genes obtained through gene sequencing, which is consistent with previous reports regarding the existence of a distinct Manila family of MTb strains. The said four clusters have been designated as EAI-M1 through EAI-M4, in order of increasing propensity to develop drug resistance. Among these clusters, rpoB, katG and gyrA mutations were observed that are highly similar to those already reported in literature. Our results demonstrate that a 15-locus MIRU-VNTR genotyping strategy in combination with mutation profiling of drug resistance-related genes could serve as a molecular-epidemiology tool for characterizing and monitoring drug-susceptible and multi-drug resistant MTb strains in the Philippines