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. 2017 Feb 14;18(2):402.
doi: 10.3390/ijms18020402.

An In Silico Identification of Common Putative Vaccine Candidates against Treponema pallidum: A Reverse Vaccinology and Subtractive Genomics Based Approach

Arun Kumar Jaiswal  1   2 , Sandeep Tiwari  3 , Syed Babar Jamal  4 , Debmalya Barh  5   6 , Vasco Azevedo  7 , Siomar C Soares  8
Affiliations

An In Silico Identification of Common Putative Vaccine Candidates against Treponema pallidum: A Reverse Vaccinology and Subtractive Genomics Based Approach

Arun Kumar Jaiswal et al. Int J Mol Sci. .

Abstract

Sexually transmitted infections (STIs) are caused by a wide variety of bacteria, viruses, and parasites that are transmitted from one person to another primarily by vaginal, anal, or oral sexual contact. Syphilis is a serious disease caused by a sexually transmitted infection. Syphilis is caused by the bacterium Treponema pallidum subspecies pallidum. Treponema pallidum (T. pallidum) is a motile, gram-negative spirochete, which can be transmitted both sexually and from mother to child, and can invade virtually any organ or structure in the human body. The current worldwide prevalence of syphilis emphasizes the need for continued preventive measures and strategies. Unfortunately, effective measures are limited. In this study, we focus on the identification of vaccine targets and putative drugs against syphilis disease using reverse vaccinology and subtractive genomics. We compared 13 strains of T. pallidum using T. pallidum Nichols as the reference genome. Using an in silicoapproach, four pathogenic islands were detected in the genome of T. pallidum Nichols. We identified 15 putative antigenic proteins and sixdrug targets through reverse vaccinology and subtractive genomics, respectively, which can be used as candidate therapeutic targets in the future.

Keywords: drug target; sexually transmitted infections (STIs); vaccine target.

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Conflict of interest statement

The authors declare that they have no conflict of interest.

Figures

Figure 1
Figure 1
Complete workflow with the number of genes selected in each step and methodologies used. The sentences in black describe the analyses made and the software used in each step. The sentences in red represent the number of proteins selected in each step. CDS = coding DNA sequence; MVD = Molegro Virtual Docker.
Figure 2
Figure 2
Genomic islands (GIs) of T. pallidum Nichols strains as predicted by the genomic island prediction software (GIPSy) using Treponema denticola as a closely related non-pathogenic organism. The outermost circle highlighted in red shows the four pathogenicity islands from 10 GIs. Guanine-Cytosine (GC) content is shown in black.
Figure 3
Figure 3
3D graphic representation of the docking analyses for the most druggable protein cavity of drug target. (A) Tp_Nichols130 (uvrB, Uvr ABC system protein B) with potamogetonin (CID 5742898); (B) Tp_Nichols593 (pfp, pyrophosphate—fructose 6-phosphate 1-phosphotransferase) with jacarandic acid (CID 73645); (C) Tp_Nichols609 (asnA, aspartate-ammonia ligase) with leptophyllin B (CID 10447482); (D) Tp_Nichols754 (recA, RecA protein) with dihydrochelirubine (CID 440589); (E) Tp_Nichols9904 (ndh, NADH dehydrogenase) with leptophyllin B (CID 10447482); (F) Tp_Nichols1011 (dxs 1-deoxy-d-xylulose-5-phosphate synthase) with pinoresinol (CID 234817).
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