scholarly journals Polymorphism of 41 kD Flagellin Gene and Its Human B-Cell Epitope in Borrelia burgdorferi Strains of China

2016 ◽  
Vol 2016 ◽  
pp. 1-7
Author(s):  
Huixin Liu ◽  
Wei Liu ◽  
Xuexia Hou ◽  
Lin Zhang ◽  
Qin Hao ◽  
...  
Keyword(s):  
Lyme Disease ◽  
Borrelia Burgdorferi ◽  
B Cell ◽  
Early Stage ◽  
Cell Epitope ◽  
Gene Encoding ◽  
Epitope Region ◽  
B Cell Epitopes ◽  
B Cell Epitope ◽  
Human B Cell

The 41 kD flagellin of Borrelia burgdorferi (B. burgdorferi) is a major component of periplasmic flagellar filament core and a good candidate for serodiagnosis in early stage of Lyme disease. Here, we chose 89 B. burgdorferi strains in China, amplified the gene encoding the 41 kD flagellin, and compared the sequences. The results showed that genetic diversity presented in the 41 kD flagellin genes of all 89 strains among the four genotypes of B. burgdorferi, especially in the genotype of B. garinii. Some specific mutation sites for each genotype of the 41 kD flagellin genes were found, which could be used for genotyping B. burgdorferi strains in China. Human B-cell epitope analysis showed that thirteen of 15 nonsynonymous mutations occurred in the epitope region of 41 kD flagellin and thirty of 42 B-cell epitopes were altered due to all 13 nonsynonymous mutations in the epitope region, which may affect the function of the antigen. Nonsynonymous mutations and changed human B-cell epitopes exist in 41 kD flagellin of B. burgdorferi sensu lato strains; these changes should be considered in serodiagnosis of Lyme disease.

scholarly journals Comparative Analysis of Human B Cell Epitopes Based on BCG Genomes

2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
Machao Li ◽  
Haican Liu ◽  
Xiuqin Zhao ◽  
Kanglin Wan
Keyword(s):  
B Cell ◽  
Vaccine Development ◽  
Protective Efficacy ◽  
Cell Epitope ◽  
Genetic Characteristics ◽  
B Cell Epitopes ◽  
B Cell Epitope ◽  
Immune Epitope Database ◽  
Global Health Problem ◽  
Human B Cell

Background. Tuberculosis is a huge global health problem. BCG is the only vaccine used for about 100 years against TB, but the reasons for protection variability in populations remain unclear. To improve BCG efficacy and develop a strategy for new vaccines, the underlying genetic differences among BCG subtypes should be understood urgently.Methods and Findings. Human B cell epitope data were collected from the Immune Epitope Database. Epitope sequences were mapped with those of 15 genomes, including 13 BCGs,M. bovisAF2122/97, andM. tuberculosisH37Rv, to identify epitopes distribution. Among 398 experimentally verified B cell epitopes, 321 (80.7%) were conserved, while the remaining 77 (19.3%) were lost to varying degrees in BCGs. The variable protective efficacy of BCGs may result from the degree of B cell epitopes deficiency.Conclusions. Here we firstly analyzed the genetic characteristics of BCGs based on B cell epitopes and found that B cell epitopes distribution may contribute to vaccine efficacy. Restoration of important antigens or effective B cell epitopes in BCG could be a useful strategy for vaccine development.

scholarly journals Data curation to improve the pattern recognition performance of B-cell epitope prediction by support vector machine

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Li Cen Lim ◽  
Yee Ying Lim ◽  
Yee Siew Choong
Keyword(s):  
Pattern Recognition ◽  
Support Vector Machine ◽  
B Cell ◽  
Recognition Performance ◽  
Cell Epitope ◽  
Epitope Prediction ◽  
Support Vector ◽  
B Cell Epitopes ◽  
Prediction Module ◽  
B Cell Epitope

Abstract B-cell epitope will be recognized and attached to the surface of receptors in B-lymphocytes to trigger immune response, thus are the vital elements in the field of epitope-based vaccine design, antibody production and therapeutic development. However, the experimental approaches in mapping epitopes are time consuming and costly. Computational prediction could offer an unbiased preliminary selection to reduce the number of epitopes for experimental validation. The deposited B-cell epitopes in the databases are those with experimentally determined positive/negative peptides and some are ambiguous resulted from different experimental methods. Prior to the development of B-cell epitope prediction module, the available dataset need to be handled with care. In this work, we first pre-processed the B-cell epitope dataset prior to B-cell epitopes prediction based on pattern recognition using support vector machine (SVM). By using only the absolute epitopes and non-epitopes, the datasets were classified into five categories of pathogen and worked on the 6-mers peptide sequences. The pre-processing of the datasets have improved the B-cell epitope prediction performance up to 99.1 % accuracy and showed significant improvement in cross validation results. It could be useful when incorporated with physicochemical propensity ranking in the future for the development of B-cell epitope prediction module.

scholarly journals An Introduction to B-Cell Epitope Mapping and In Silico Epitope Prediction

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Lenka Potocnakova ◽  
Mangesh Bhide ◽  
Lucia Borszekova Pulzova
Keyword(s):  
B Cell ◽  
In Silico ◽  
Epitope Mapping ◽  
Cell Epitope ◽  
Epitope Prediction ◽  
Diagnostic Tools ◽  
Accurate Identification ◽  
B Cell Epitopes ◽  
Epitope Identification ◽  
B Cell Epitope

Identification of B-cell epitopes is a fundamental step for development of epitope-based vaccines, therapeutic antibodies, and diagnostic tools. Epitope-based antibodies are currently the most promising class of biopharmaceuticals. In the last decade, in-depth in silico analysis and categorization of the experimentally identified epitopes stimulated development of algorithms for epitope prediction. Recently, various in silico tools are employed in attempts to predict B-cell epitopes based on sequence and/or structural data. The main objective of epitope identification is to replace an antigen in the immunization, antibody production, and serodiagnosis. The accurate identification of B-cell epitopes still presents major challenges for immunologists. Advances in B-cell epitope mapping and computational prediction have yielded molecular insights into the process of biorecognition and formation of antigen-antibody complex, which may help to localize B-cell epitopes more precisely. In this paper, we have comprehensively reviewed state-of-the-art experimental methods for B-cell epitope identification, existing databases for epitopes, and novel in silico resources and prediction tools available online. We have also elaborated new trends in the antibody-based epitope prediction. The aim of this review is to assist researchers in identification of B-cell epitopes.

scholarly journals In Silico Identification and in Vitro Analysis of B and T-Cell Epitopes of the Black Turtle Bean (Phaseolus Vulgaris L.) Lectin

2018 ◽  
Vol 49 (4) ◽  
pp. 1600-1614 ◽  
Author(s):  
Shudong He ◽  
Jinlong Zhao ◽  
Walid Elfalleh ◽  
Mohamed Jemaà ◽  
Hanju  Sun ◽  
...  
Keyword(s):  
Amino Acids ◽  
T Cell ◽  
Phaseolus Vulgaris ◽  
B Cell ◽  
Cell Epitope ◽  
T Cell Epitope ◽  
T Cell Epitopes ◽  
Phaseolus Vulgaris L ◽  
B Cell Epitopes ◽  
B Cell Epitope

Background/Aims: The incidence of lectin allergic disease is increasing in recent decades, and definitive treatment is still lacking. Identification of B and T-cell epitopes of allergen will be useful in understanding the allergen antibody responses as well as aiding in the development of new diagnostics and therapy regimens for lectin poisoning. In the current study, we mainly addressed these questions. Methods: Three-dimensional structure of the lectin from black turtle bean (Phaseolus vulgaris L.) was modeled using the structural template of Phytohemagglutinin from P. vulgaris (PHA-E, PDB ID: 3wcs.1.A) with high identity. The B and T-cell epitopes were screened and identified by immunoinformatics and subsequently validated by ELISA, lymphocyte proliferation and cytokine profile analyses. Results: Seven potential B-cell epitopes (B1 to B7) were identified by sequence and structure based methods, while three T-cell epitopes (T1 to T3) were identified by the predictions of binding score and inhibitory concentration. The epitope peptides were synthesized. Significant IgE binding capability was found in B-cell epitopes (B2, B5, B6 and B7) and T2 (a cryptic B-cell epitope). T1 and T2 induced significant lymphoproliferation, and the release of IL-4 and IL-5 cytokine confirmed the validity of T-cell epitope prediction. Abundant hydrophobic amino acids were found in B-cell epitope and T-cell epitope regions by amino acid analysis. Positively charged amino acids, such as His residue, might be more favored for B-cell epitope. Conclusion: The present approach can be applied for the identification of epitopes in novel allergen proteins and thus for designing diagnostics and therapies in lectin allergy.

scholarly journals Immunodominant linear B cell epitopes in the spike and membrane proteins of SARS-CoV-2 identified by immunoinformatics prediction and immunoassay

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kanokporn Polyiam ◽  
Waranyoo Phoolcharoen ◽  
Namphueng Butkhot ◽  
Chanya Srisaowakarn ◽  
Arunee Thitithanyanont ◽  
...  
Keyword(s):  
B Cell ◽  
Cleavage Site ◽  
Vaccine Development ◽  
Cell Epitope ◽  
Epitope Prediction ◽  
E Proteins ◽  
B Cell Epitopes ◽  
C Terminus ◽  
B Cell Epitope ◽  
Linear B

AbstractSARS-CoV-2 continues to infect an ever-expanding number of people, resulting in an increase in the number of deaths globally. With the emergence of new variants, there is a corresponding decrease in the currently available vaccine efficacy, highlighting the need for greater insights into the viral epitope profile for both vaccine design and assessment. In this study, three immunodominant linear B cell epitopes in the SARS-CoV-2 spike receptor-binding domain (RBD) were identified by immunoinformatics prediction, and confirmed by ELISA with sera from Macaca fascicularis vaccinated with a SARS-CoV-2 RBD subunit vaccine. Further immunoinformatics analyses of these three epitopes gave rise to a method of linear B cell epitope prediction and selection. B cell epitopes in the spike (S), membrane (M), and envelope (E) proteins were subsequently predicted and confirmed using convalescent sera from COVID-19 infected patients. Immunodominant epitopes were identified in three regions of the S2 domain, one region at the S1/S2 cleavage site and one region at the C-terminus of the M protein. Epitope mapping revealed that most of the amino acid changes found in variants of concern are located within B cell epitopes in the NTD, RBD, and S1/S2 cleavage site. This work provides insights into B cell epitopes of SARS-CoV-2 as well as immunoinformatics methods for B cell epitope prediction, which will improve and enhance SARS-CoV-2 vaccine development against emergent variants.

An Immunodominant, Cross-Reactive B-Cell Epitope Region Is Located at the C-Terminal Part of the Hamster Polyomavirus Major Capsid Protein VP1

2000 ◽  
Vol 13 (4) ◽  
pp. 533-545 ◽  
Author(s):  
HASSEN SIRAY ◽  
CORNELIUS FRÖMMEL ◽  
TATYANA VORONKOVA ◽  
STEFANIE HAHN ◽  
WOLFGANG ARNOLD ◽  
...  
Keyword(s):  
B Cell ◽  
Capsid Protein ◽  
Major Capsid Protein ◽  
Cell Epitope ◽  
Terminal Part ◽  
Epitope Region ◽  
B Cell Epitope ◽  
Hamster Polyomavirus ◽  
Capsid Protein Vp1

SELECTION OF CRYPTIC B-CELL EPITOPES USING INFORMATIONAL ANALYSIS OF PROTEIN SEQUENSES

2006 ◽  
Vol 04 (02) ◽  
pp. 389-402 ◽  
Author(s):  
ELENA SVIRSHCHEVSKAYA ◽  
LUDMILA ALEKSEEVA ◽  
ALEXEI MARCHENKO ◽  
SERGEI BENEVOLENSKII ◽  
VALENTINA M. BERZHEC ◽  
...  
Keyword(s):  
B Cell ◽  
Information Structure ◽  
Cell Epitope ◽  
Protein Sequences ◽  
Major Protein ◽  
Protein Antigens ◽  
B Cell Epitopes ◽  
Fel D 1 ◽  
B Cell Epitope ◽  
Selection Of

Sub-unit vaccines are synthetic or recombinant peptides representing T- or B-cell epitopes of major protein antigens from a particular pathogen. Epitope selection requires the synthesis of peptides that overlap the protein sequences and screening for the most effective ones. In this study a new method of immunogenic peptide selection based on the analysis of information structure of protein sequences is suggested. The analysis of known B-cell epitope location in the information structure of Aspergillus fumigatus proteins Asp f 2 and Asp f 3 has shown that epitopes are scattered along the sequences of proteins for the exception of sites with Increased Degree Information Coordination (IDIC). Based on these results peptides from different allergens such as Asp f 2, Der p 1, and Fel d 1 were selected and produced in a recombinant form in the context of yeast virus-like particles (VLPs). Immunization of mice with VLPs containing peptides form allergens has induced the production of IgG able to recognize full-length antigens. This result suggests that the analysis of information structure of proteins can be used for the selection of peptides possessing cryptic B-cell epitope activity.

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

2010 ◽  
Vol 2010 ◽  
pp. 1-14 ◽  
Author(s):  
Salvador Eugenio C. Caoili
Keyword(s):  
B Cell ◽  
Protein Function ◽  
Cell Epitope ◽  
Epitope Prediction ◽  
Cross Reactivity ◽  
Sequence Alignments ◽  
B Cell Epitopes ◽  
B Cell Epitope ◽  
Physicochemical Factors ◽  
Structural Differences

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.

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