Reconnoitering Mycobacterium tuberculosis lipoproteins to design subunit vaccine by immunoinformatics approach
Abstract
Background: Tuberculosis is an aerosol transmitted disease of human beings caused by Mycobacterium tuberculosis (Mtb). The only available vaccine for Mtb is Bacillus Calmette-Guérin (BCG). Currently no alternative or booster is available for BCG. The objective of this predictive approach was based on binding of MHC-I and MHC-II and B cell epitopes of Mtb for mouse host.
Methods: Immunoinformatics approach was used to design subunit vaccine (SV) by joining 8 MHC-I bindings, 6 MHC-II bindings, and 8 B-Cell epitopes with AAV, GPGPG, and KK amino acid linkers, respectively. The efficacy of the SV was enhanced through Mtb protein Rv3763 (LpqH, PDB ID= 4ZJM) as an adjuvant at the N-terminal of SV. The in silico analyses evaluated the SV to predict allergenicity, antigenicity, and physico-chemical properties.
Results: Predictions revealed that SV is non-allergic and highly antigenic. The physico-chemical analysis showed that the SV was stable and basic in nature. The three-dimensional structure of SV was stable with a high binding affinity against the mouse TLR2 receptor. In silico cloning suggested the effective transformation of SV into the eukaryotic expression vector.
Conclusion: This study permits preclinical validation of the designed SV in mouse host to confirm its immunogenic potential and efficacy, which will help in controlling tuberculosis.
Keywords: Immunoinformatics; Docking; Subunit vaccine; Lipoprotein; Tuberculosis
Full Text:
PDFReferences
World Health Organization. BCG vaccine: WHO position paper, February 2018–recommendations. Vaccine. Jun 7 (2018); 36(24): 3408-3410.
Gideon HP, Flynn JL. Latent tuberculosis: what the host “sees”? Immunologic research. Aug 1 (2011); 50(2-3): 202-212.
Andersen P, Doherty TM. The success and failure of BCG—implications for a novel tuberculosis vaccine. Nature Reviews Microbiology, (2005); 3 (8): 656-662.
Fine PE. Variation in protection by BCG: implications of and for heterologous immunity. The Lancet. Nov 18 (1995); 346 (8986): 1339-1345.
Crampin AC, Glynn JR, Fine PE. What has Karonga taught us? Tuberculosis studied over three decades [State of the art series. Tuberculosis. Edited by ID Rusen. Number 4 in the series]. The international journal of tuberculosis and lung disease. Feb 1 (2009); 13(2): 153-1564.
Glick BR, Delovitch TL, Patten CL. Medical Biotechnology. Washington DC. 2014. 632-663. ASM Press.
Flores-Valdez Mario Alberto . Why is it important to improve vaccines against latent tuberculosis? Frontier for young mind. https://kids.frontiersin.org/article/10.3389/frym.2016.00019 (2016).
Sutcliffe IC, Harrington DJ. Lipoproteins of Mycobacterium tuberculosis: an abundant and functionally diverse class of cell envelope components. FEMS microbiology reviews. Nov 1 (2004); 28(5): 645-659.
Noss EH, Pai RK, Sellati TJ, Radolf JD, Belisle J, Golenbock DT, Boom WH, Harding CV. Toll-like receptor 2-dependent inhibition of macrophage class II MHC expression and antigen processing by 19-kDa lipoprotein of Mycobacterium tuberculosis. The Journal of immunology. Jul 15 (2001); 167(2): 910-918.
Andreatta M, Nielsen M. Gapped sequence alignment using artificial neural networks: application to the MHC class I system. Bioinformatics, Feb 15 (2016); 32 (4): 511-517.
Wang P, Sidney J, Kim Y, Sette A, Lund O, Nielsen M, Peters B. Peptide binding predictions for HLA DR, DP and DQ molecules. BMC bioinformatics. Dec 1 (2010); 11(1): 568.
Saha S, Raghava GP. AlgPred: prediction of allergenic proteins and mapping of IgE epitopes. Nucleic acids research. Jul 1 (2006); 34(suppl_2): 202-209.
Wiederstein M, Sippl MJ. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic acids research. Jul 1 (2007); 35(suppl_2): 407-410.
Wierecky J, Müller MR, Wirths S, Halder-Oehler E, Dörfel D, Schmidt S., Häntschel M, Brugger W, Schröder S, Horger MS, Kanz L. Immunologic and clinical responses after vaccinations with peptide-pulsed dendritic cells in metastatic renal cancer patients. Cancer research. Jun 1 (2006); 66(11): 5910-5918.
Gasteiger E, Hoogland C, Gattiker A, Wilkins MR, Appel RD, Bairoch A. Protein identification and analysis tools on the ExPASy server. In: The proteomics protocols handbook. 2005; 571-607. Humana press.
Schneidman-Duhovny D, Inbar Y, Nussinov R, Wolfson HJ. PatchDock and SymmDock: servers for rigid and symmetric docking. Nucleic acids research. Jul 1 (2005); 33(suppl_2): 363-367.
Pandey RK, Kumbhar BV, Srivastava S, Malik R, Sundar S, Kunwar A, Prajapati VK. Febrifugine analogues as Leishmania donovani trypanothione reductase inhibitors: binding energy analysis assisted by molecular docking, ADMET and molecular dynamics simulation. Journal of Biomolecular Structure and Dynamics. Jan 2 (2017); 35(1): 141-158.
Drage MG, Pecora ND, Hise AG, Febbraio M, Silverstein RL, Golenbock DT, Boom WH, Harding CV. TLR2 and its co-receptors determine responses of macrophages and dendritic cells to lipoproteins of Mycobacterium tuberculosis. Cellular immunology. Jan 1 (2009); 258 (1): 29-37
Grote A, Hiller K, Scheer M, Münch R, Nörtemann B, Hempel DC, Jahn D. JCat: a novel tool to adapt codon usage of a target gene to its potential expression host. Nucleic acids research. Jul 1 (2005); 33 (suppl_2): 526-531.
Skwarczynski M, Toth I. Peptide-based synthetic vaccines. Chem Sci [Internet] (2016); 7(2): 842-854.
Purcell AW, Mccluskey J, Rossjohn J. More than one reason to rethink the use of peptides in vaccine design. Nat Rev Drug Discov [Internet] (2007); 6(5): 404-414. Available from: http://dx.doi.org/10.1038/nrd2224.
Becker K, Sander P. Mycobacterium tuberculosis lipoproteins in virulence and immunity–fighting with a double‐edged sword. FEBS letters, Nov 1 (2016); 590(21): 3800-3819.
Rothbard JB, Taylor WR. A sequence pattern common to T cell epitopes. The EMBO journal. Jan 1 (1998); 7(1): 93-100.
Janeway C, Travers P, Walport M, Shlomchik M. Chapter 5: Antigen presentation to T lymphocytes. Immunobiology, (2001); 5: 168.
Joffre OP, Segura E, Savina A, Amigorena S. Cross-presentation by dendritic cells. Nature Reviews Immunology. Aug (2012); 12 (8): 557-569.
Makrides SC. Strategies for achieving high-level expression of genes in Escherichia coli. Microbiol. Mol. Biol. Rev. Sep 1 (1996); 60(3): 512-538.
DOI: http://dx.doi.org/10.62940/als.v8i3.1183
Refbacks
- There are currently no refbacks.