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. 2019 Dec 24;9(1):19780.
doi: 10.1038/s41598-019-55613-w.

Designing a Multi-Epitopic Vaccine Against the Enterotoxigenic Bacteroides Fragilis Based on Immunoinformatics Approach

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Free PMC article

Designing a Multi-Epitopic Vaccine Against the Enterotoxigenic Bacteroides Fragilis Based on Immunoinformatics Approach

Mahnoor Majid et al. Sci Rep. .
Free PMC article

Abstract

Enterotoxigenic Bacteroides fragilis is an enteric pathogen which is described as a causative agent of various intestinal infections and inflammatory diseases. Moreover, various research studies have reported it to be a leading factor in the development of colorectal cancer. As a part of the normal human microbiome, its treatment has become quite a challenge due to the alarming resistance against the available antibiotics. Although, this particular strain of B. fragilis shows susceptibility to few antibiotics, it is pertinent to devise an effective vaccine strategy for its elimination. There is no vaccine available against this pathogen up to date; therefore, we systematically ventured the outer membrane toxin producing proteins found exclusively in the toxigenic B. fragilis through the in-silico approaches to predict a multi-epitopic chimeric vaccine construct. The designed protein constitutes of epitopes which are predicted for linear B cells, Helper and T cells of outer membrane proteins expected to be putative vaccine candidates. The finalized proteins are only expressed in the enterotoxigenic B. fragilis, thus proving them to be exclusive. The 3D structure of the protein was first predicted followed by its refinement and validation via utilizing the bioinformatic approaches. Docking of the designed protein with the TLR2 receptor forecasted apt binding. Upon immune simulation, notable levels were observed in the expression of the immune cells.

Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Schematic presentation of the final multi-epitope vaccine protein. The 512-amino acid long protein sequence containing an adjuvant (light purple) at the amino terminal end linked with the multi-epitope sequence through an EAAAK linker (purple). B-cell epitopes and HTL epitopes are linked using GPGPG linkers (blue) while the CTL epitopes are linked with the help of AAY linkers (dark blue). A 6x-His tag is added at the Carboxy terminus for purification and identification purposes.
Figure 2
Figure 2
Graphical representation of secondary structure features of the final subunit vaccine sequence. (a,b) The protein is predicted to comprise helices (8.0%), beta strands (25.0%) and coils (66.0%) (c) Based on the accessibility of the amino acid residues, 52% were predicted to be exposed, 21% medium exposed and 25% were predicted to be buried in the designed protein.
Figure 3
Figure 3
Protein modelling, refinement and validation. (a) The final 3D model of the multi-epitope vaccine obtained after homology modelling on I-TASSER. (b) Refined model obtained via ModeRefiner (c) The refined 3D structure by GalaxyRefine. Validation of the refined model with (d) Ramachandran plot analysis showing 93.7%, 4.5% and 1.8% of protein residues in favoured, allowed, and disallowed (outlier) regions respectively and (e) ProSA-web, giving a Z-score of −6.04.
Figure 4
Figure 4
Discontinuous B-cell epitopes predicted by the ElliPro. (a–g) Three-dimensional representation of conformational or discontinuous epitopes of the highest antigenic chimeric protein of Enterotoxigenic Bacteroides fragilis. The epitopes are represented by yellow surface, and the bulk of the protein is represented in grey sticks.
Figure 5
Figure 5
Molecular docking of subunit vaccine with immune receptor (TLR2). (a) Docked complexes for Vaccine-TLR2 complex with protein colored sea green, chain A of TLR2 colored medium blue and the interface colored yellow and magenta, and (b) adjuvant-TLR2 complex with adjuvant colored sea green, A chain of TLR2 colored medium blue and the interface colored in magenta and yellow. (c) Interface active residues for Chimeric vaccine-TLR2 complex with protein active residues colored yellow and TLR2 active residues colored in magenta, and (d) Adjuvant-TLR2 complex with protein active residues colored yellow and TLR2 active residues colored magenta.
Figure 6
Figure 6
Codon optimization of the final vaccine protein. The CAI of the optimized codon is 0.988 and the average GC content is predicted to be 51.36% as illustrated in the graph.
Figure 7
Figure 7
Final protein in-silico restriction cloning into the pET28a(+) vector. The red part represents the gene sequence of the designed vaccine protein and the black part indicates the backbone of the E. coli vector. The 6xHis tag is situated at the carboxy terminal of the cloned construct.
Figure 8
Figure 8
Molecular simulations of the chimeric protein. (a) Immunoglobulin production in response to the subsequent antigen injections (black vertical lines); subclasses of immune cells are indicated by colored peaks. (b) The changes observed in B-cell populations after given three injections. (c) The development of T-helper, and (d) T-cytotoxic cell populations per state after the injections. Cells which are not presented with the antigen are indicated by the resting state whereas T cells which show tolerance to the antigen are indicated by the anergic state as a result of repeated exposures.

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References

    1. Lloyd-Price J, Abu-Ali G, Huttenhower C. The healthy human microbiome. Genome Med. 2016;8:51. doi: 10.1186/s13073-016-0307-y. - DOI - PMC - PubMed
    1. Blount, K. F., Shannon, W. D., Deych, E. & Jones, C. Restoration of Bacterial Microbiome Composition and Diversity Among Treatment Responders in a Phase 2 Trial of RBX2660: An Investigational Microbiome Restoration Therapeutic. Open Forum Infect. Dis. 6 (2019). - PMC - PubMed
    1. Sender, R., Fuchs, S. & Milo, R. Revised Estimates for the Number of Human and Bacteria Cells in the Body. PLoS Biol. 14 (2016). - PMC - PubMed
    1. Weiss GA, Hennet T. Mechanisms and consequences of intestinal dysbiosis. Cell. Mol. Life Sci. 2017;74:2959–2977. doi: 10.1007/s00018-017-2509-x. - DOI - PubMed
    1. Petersen C, Round JL. Defining dysbiosis and its influence on host immunity and disease. Cell. Microbiol. 2014;16:1024–1033. doi: 10.1111/cmi.12308. - DOI - PMC - PubMed
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