Literature DB >> 21458582

In silico prediction of binding of promiscuous peptides to multiple MHC class-II molecules identifies the Th1 cell epitopes from secreted and transmembrane proteins of Schistosoma japonicum in BALB/c mice.

Ben Peng Zhao1, Lei Chen, Yan Li Zhang, Jian Mei Yang, Kan Jia, Chuan Yu Sui, Chun Xiu Yuan, Jiao Jiao Lin, Xin Gang Feng.   

Abstract

It has not so far been possible to identify rapidly and effectively the anti-schistosomiasis Th cell epitopes that are capable of simulating IFN-γ (Interferon-gamma)-mediated Th1-type protective immunity in response to radiation-attenuated schistosome cercaria. With the advance of the omics studies of schistosomes, an approach that used reverse vaccinology probably resolved the above problems. In this "proof-of-principle" study, first, we selected 31 secreted or transmembrane protein sequences sampled from sequences of the transcriptome of Schistosoma japonicum, and analyzed characteristics of these proteins by using conventional bioinformatics tools. Second, putative promiscuous Th cell epitopes within these proteins were predicted using three to four different immuno-informatics algorithms for the prediction of MHC (Major Histocompatibility Complex) class-II binding peptides. We predicted using these in silico approaches promiscuous Th cell epitopes that are capable of binding to both murine and human MHC class-II molecules. To validate our in silico prediction experimentally, BALB/c mice were immunized with the five predicted peptides, and the proliferative responses and cytokine production of lymphocytes from the immunized BALB/c mice were assessed in vitro by modified MTT (Methyl Thiazolyl Tetrazolium), ELISA (Enzyme-linked Immunosorbent Assay) and flow cytometry methods. The results showed that two of the five predicted peptides could induce a Th1-type response in vitro. These results suggest that promiscuous Th1 cell epitopes from secreted or transmembrane proteins of S. japonicum can be identified using a strategy of reverse vaccinology.
Copyright © 2011 Institut Pasteur. Published by Elsevier SAS. All rights reserved.

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Year:  2011        PMID: 21458582     DOI: 10.1016/j.micinf.2011.03.005

Source DB:  PubMed          Journal:  Microbes Infect        ISSN: 1286-4579            Impact factor:   2.700


  6 in total

1.  The utility and limitations of current Web-available algorithms to predict peptides recognized by CD4 T cells in response to pathogen infection.

Authors:  Francisco A Chaves; Alvin H Lee; Jennifer L Nayak; Katherine A Richards; Andrea J Sant
Journal:  J Immunol       Date:  2012-03-30       Impact factor: 5.422

2.  In silico identification of epitopes in Mycobacterium avium subsp. paratuberculosis proteins that were upregulated under stress conditions.

Authors:  Ratna B Gurung; Auriol C Purdie; Douglas J Begg; Richard J Whittington
Journal:  Clin Vaccine Immunol       Date:  2012-04-11

3.  Molecular characterization and identification of Th1 epitopes of a Schistosoma japonicum protein similar to prosaposin.

Authors:  Yan Li Zhang; Yun Yan Li; Ben Peng Zhao; Chun Xiu Yuan; Jian Mei Yang; Jiao Jiao Lin; Xin Gang Feng
Journal:  Parasitol Res       Date:  2013-12-21       Impact factor: 2.289

4.  Immune-Informatic Analysis and Design of Peptide Vaccine From Multi-epitopes Against Corynebacterium pseudotuberculosis.

Authors:  Daniela Droppa-Almeida; Elton Franceschi; Francine Ferreira Padilha
Journal:  Bioinform Biol Insights       Date:  2018-05-14

5.  Refining wet lab experiments with in silico searches: A rational quest for diagnostic peptides in visceral leishmaniasis.

Authors:  Bruno Cesar Bremer Hinckel; Tegwen Marlais; Stephanie Airs; Tapan Bhattacharyya; Hideo Imamura; Jean-Claude Dujardin; Sayda El-Safi; Om Prakash Singh; Shyam Sundar; Andrew Keith Falconar; Bjorn Andersson; Sergey Litvinov; Michael A Miles; Pascal Mertens
Journal:  PLoS Negl Trop Dis       Date:  2019-05-06

Review 6.  An Overview of Current Uses and Future Opportunities for Computer-Assisted Design of Vaccines for Neglected Tropical Diseases.

Authors:  Raquel Robleda-Castillo; Albert Ros-Lucas; Nieves Martinez-Peinado; Julio Alonso-Padilla
Journal:  Adv Appl Bioinform Chem       Date:  2021-02-15
  6 in total

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