Sequence-based prediction for vaccine strain selection and identification of antigenic variability in foot-and-mouth disease virus

Identifying when past exposure to an infectious disease will protect against newly emerging strains is central to understanding the spread and the severity of epidemics, but the prediction of viral cross-protection remains an important unsolved problem. For foot-and-mouth disease virus (FMDV) research in particular, improved methods for predicting this cross-protection are critical for predicting the severity of outbreaks within endemic settings where multiple serotypes and subtypes commonly co-circulate, as well as for deciding whether appropriate vaccine(s) exist and how much they could mitigate the effects of any outbreak. To identify antigenic relationships and their predictors, we used linear mixed effects models to account for variation in pairwise cross-neutralization titres using only viral sequences and structural data. We identified those substitutions in surface-exposed structural proteins that are correlates of loss of cross-reactivity. These allowed prediction of both the best vaccine match for any single virus and the breadth of coverage of new vaccine candidates from their capsid sequences as effectively as or better than serology. Sub-sequences chosen by the model-building process all contained sites that are known epitopes on other serotypes. Furthermore, for the SAT1 serotype, for which epitopes have never previously been identified, we provide strong evidence - by controlling for phylogenetic structure - for the presence of three epitopes across a panel of viruses and quantify the relative significance of some individual residues in determining cross-neutralization. Identifying and quantifying the importance of sites that predict viral strain cross-reactivity not just for single viruses but across entire serotypes can help in the design of vaccines with better targeting and broader coverage. These techniques can be generalized to any infectious agents where cross-reactivity assays have been carried out. As the parameterization uses pre-existing datasets, this approach quickly and cheaply increases both our understanding of antigenic relationships and our power to control disease

Recent advances in B-cell epitope prediction methods

Identification of epitopes that invoke strong responses from B-cells is one of the key steps in designing effective vaccines against pathogens. Because experimental determination of epitopes is expensive in terms of cost, time, and effort involved, there is an urgent need for computational methods for reliable identification of B-cell epitopes. Although several computational tools for predicting B-cell epitopes have become available in recent years, the predictive performance of existing tools remains far from ideal. We review recent advances in computational methods for B-cell epitope prediction, identify some gaps in the current state of the art, and outline some promising directions for improving the reliability of such methods

Functional and Immunological Relevance of Anaplasma marginale Major Surface Protein 1a Sequence and Structural Analysis.

Bovine anaplasmosis is caused by cattle infection with the tick-borne bacterium, Anaplasma marginale. The major surface protein 1a (MSP1a) has been used as a genetic marker for identifying A. marginale strains based on N-terminal tandem repeats and a 5'-UTR microsatellite located in the msp1a gene. The MSP1a tandem repeats contain immune relevant elements and functional domains that bind to bovine erythrocytes and tick cells, thus providing information about the evolution of host-pathogen and vector-pathogen interactions. Here we propose one nomenclature for A. marginale strain classification based on MSP1a. All tandem repeats among A. marginale strains were classified and the amino acid variability/frequency in each position was determined. The sequence variation at immunodominant B cell epitopes was determined and the secondary (2D) structure of the tandem repeats was modeled. A total of 224 different strains of A. marginale were classified, showing 11 genotypes based on the 5'-UTR microsatellite and 193 different tandem repeats with high amino acid variability per position. Our results showed phylogenetic correlation between MSP1a sequence, secondary structure, B-cell epitope composition and tick transmissibility of A. marginale strains. The analysis of MSP1a sequences provides relevant information about the biology of A. marginale to design vaccines with a cross-protective capacity based on MSP1a B-cell epitopes

T‐cell epitope content comparison (EpiCC) of swine H1 influenza A virus hemagglutinin

Background: Predicting vaccine efficacy against emerging pathogen strains is a significant problem in human and animal vaccine design. T‐cell epitope cross‐conservation may play an important role in cross‐strain vaccine efficacy. While influenza A virus (IAV) hemagglutination inhibition (HI) antibody titers are widely used to predict protective efficacy of 1 IAV vaccine against new strains, no similar correlate of protection has been identified for T‐cell epitopes. Objective: We developed a computational method (EpiCC) that facilitates pairwise comparison of protein sequences based on an immunological property—T‐cell epitope content—rather than sequence identity, and evaluated its ability to classify swine IAV strain relatedness to estimate cross‐protective potential of a vaccine strain for circulating viruses. Methods: T‐cell epitope relatedness scores were assessed for 23 IAV HA sequences representing the major H1 swine IAV phylo‐clusters circulating in North American swine and HA sequences in a commercial inactivated vaccine (FluSure XP®). Scores were compared to experimental data from previous efficacy studies. Results: Higher EpiCC scores were associated with greater protection by the vaccine against strains for 23 field IAV strain vaccine comparisons. A threshold for EpiCC relatedness associated with full or partial protection in the absence of cross‐reactive HI antibodies was identified. EpiCC scores for field strains for which FluSure protective efficacy is not yet available were also calculated. Conclusion: EpiCC thresholds can be evaluated for predictive accuracy of protection in future efficacy studies. EpiCC may also complement HI cross‐reactivity and phylogeny for selection of influenza strains in vaccine development

SVM-based prediction of linear B-cell epitopes using Bayes Feature Extraction

10.1186/1471-2164-11-S4-S21BMC Genomics11SUPPL. 4S2

Immunoinformatics and Similarity Analysis of House Dust Mite Tropomyosin

Background: Dermatophagoides farinae and Dermatophagoides pteronyssinus are house dust mites (HDM) that they cause severe asthma and allergic symptoms. Tropomyosin protein plays an important role in mentioned immune and allergic reactions to HDMs. Here, tropomyosin protein from Dermatophagoides spp. was comprehensively screened in silico for its allergenicity, antigenicity and similarity/conservation.Materials and Methods: The amino acid sequences of D. farinae tropomyosin, D. pteronyssinus and other mites were retrieved. We included alignments and evaluated conserved/ variable regions along sequences, constructed their phylogenetic tree and estimated overall mean distances. Then, followed by with prediction of linear B-cell epitope based on different approaches, and besides in-silico evaluation of IgE epitopes allergenicity (by SVMc, IgE epitope, ARPs BLAST, MAST and hybrid method). Finally, comparative analysis of results by different approaches was made.Results: Alignment results revealed near complete identity between D. farina and D. pteronyssinus members, and also there was close similarity among Dermatophagoides spp. Most of the variations among mites' tropomyosin were approximately located at amino acids 23 to 80, 108 to 120, 142 to 153 and 220 to 230. Topology of tree showed close relationships among mites in tropomyosin protein sequence, although their sequences in D. farina, D. pteronyssinus and Psoroptes ovis are more similar to each other and clustered. Dermanyssus gallinae (AC: Q2WBI0) has less relationship to other mites, being located in a separate branch. Hydrophilicity and flexibility plots revealed that many parts of this protein have potential to be hydrophilic and flexible. Surface accessibility represented 7 different epitopes. Beta-turns in this protein are with high probability in the middle part and its two terminals. Kolaskar and Tongaonkar method analysis represented 11 immunogenic epitopes between amino acids 7-16. From comparative analysis of predicted probable consensus epitope regions by machine learning approaches these epitopes were gained: AA23-48, AA59-80, AA91-110, AA114-143, AA154-168, AA182-200, AA208-225, and AA254-272. Prediction of allergenic proteins by AlgPred server showed 10 matches for IgE epitope, and prediction by hybrid approach showed that IgE epitope is undoubtedly the major allergen.Conclusion: Immunoinformatic approaches in allergenic protein analysis are now reliable tools for explanation/interpretation of clinically observed complexities. Results of present study, would help in HDM immunotherapy against several species of parasites as a wide range epitopic desensitization or prevention (vaccine) regime

Virulence factors of Moraxella catarrhalis outer membrane vesicles are major targets for cross-reactive antibodies and have adapted during evolution

Moraxella catarrhalis is a common human respiratory tract pathogen. Its virulence factors associated with whole bacteria or outer membrane vesicles (OMVs) aid infection, colonization and may induce specific antibodies. To investigate pathogen-host interactions, we applied integrated bioinformatic and immunoproteomic (2D-electrophoresis, immunoblotting, LC-MS/MS) approaches. We showed that OMV proteins engaged exclusively in complement evasion and colonization strategies, but not those involved in iron transport and metabolism, are major targets for cross-reacting antibodies produced against phylogenetically divergent M. catarrhalis strains. The analysis of 31 complete genomes of M. catarrhalis and other Moraxella revealed that OMV protein-coding genes belong to 64 orthologous groups, five of which are restricted to M. catarrhalis. This species showed a two-fold increase in the number of OMV protein-coding genes relative to its ancestors and animal-pathogenic Moraxella. The appearance of specific OMV factors and the increase in OMV-associated virulence proteins during M. catarrhalis evolution is an interesting example of pathogen adaptation to optimize colonization. This precisely targeted cross-reactive immunity against M. catarrhalis may be an important strategy of host defences to counteract this phenomenon. We demonstrate that cross-reactivity is closely associated with the anti-virulent antibody repertoire which we have linked with adaptation of this pathogen to the host