Dataset Information

Putative vaccine candidates and drug targets identified by reverse vaccinology and subtractive genomics approaches to control Haemophilus ducreyi, the causative agent of chancroid.

ABSTRACT: Chancroid is a sexually transmitted infection (STI) caused by the Gram-negative bacterium Haemophilus ducreyi The control of chancroid is difficult and the only current available treatment is antibiotic therapy; however, antibiotic resistance has been reported in endemic areas. Owing to recent outbreaks of STIs worldwide, it is important to keep searching for new treatment strategies and preventive measures. Here, we applied reverse vaccinology and subtractive genomic approaches for the in silico prediction of potential vaccine and drug targets against 28 strains of H. ducreyi We identified 847 non-host homologous proteins, being 332 exposed/secreted/membrane and 515 cytoplasmic proteins. We also checked their essentiality, functionality and virulence. Altogether, we predicted 13 candidate vaccine targets and three drug targets, where two vaccines (A01_1275, ABC transporter substrate-binding protein; and A01_0690, Probable transmembrane protein) and three drug targets (A01_0698, Purine nucleoside phosphorylase; A01_0702, Transcription termination factor; and A01_0677, Fructose-bisphosphate aldolase class II) are harboured by pathogenicity islands. Finally, we applied a molecular docking approach to analyse each drug target and selected ZINC77257029, ZINC43552589 and ZINC67912117 as promising molecules with favourable interactions with the target active site residues. Altogether, the targets identified here may be used in future strategies to control chancroid worldwide.

SUBMITTER: de Sarom A

PROVIDER: S-EPMC6000166 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Putative vaccine candidates and drug targets identified by reverse vaccinology and subtractive genomics approaches to control <i>Haemophilus ducreyi</i>, the causative agent of chancroid.

de Sarom Alissa A Kumar Jaiswal Arun A Tiwari Sandeep S de Castro Oliveira Letícia L Barh Debmalya D Azevedo Vasco V Jose Oliveira Carlo C de Castro Soares Siomar S

Journal of the Royal Society, Interface 20180501 142

Chancroid is a sexually transmitted infection (STI) caused by the Gram-negative bacterium <i>Haemophilus ducreyi</i> The control of chancroid is difficult and the only current available treatment is antibiotic therapy; however, antibiotic resistance has been reported in endemic areas. Owing to recent outbreaks of STIs worldwide, it is important to keep searching for new treatment strategies and preventive measures. Here, we applied reverse vaccinology and subtractive genomic approaches for the < ...[more]

PMID: 29792307

Similar Datasets

Project description:Leptospira spp. are diderm (two membranes) bacteria that infect mammals causing leptospirosis, a public health problem with global implications. Thousands of people die every year due to leptospirosis, especially in developing countries with tropical climates. Prophylaxis is difficult due to multiple factors, including the large number of asymptomatic hosts that transmit the bacteria, poor sanitation, increasing numbers of slum dwellers, and the lack of an effective vaccine. Several leptospiral recombinant antigens were evaluated as a replacement for the inactivated (bacterin) vaccine; however, success has been limited. A prospective vaccine candidate is likely to be a surface-related protein that can stimulate the host immune response to clear leptospires from blood and organs. In this study, a comprehensive bioinformatics approach based on reverse and structural vaccinology was applied toward the discovery of novel leptospiral vaccine candidates. The Leptospira interrogans serovar Copenhageni strain L1-130 genome was mined in silico for the enhanced identification of conserved ?-barrel (?b) transmembrane proteins and outer membrane (OM) lipoproteins. Orthologs of the prospective vaccine candidates were screened in the genomes of 20 additional Leptospira spp. Three-dimensional structural models, with a high degree of confidence, were created for each of the surface-exposed proteins. Major histocompatibility complex II (MHC-II) epitopes were identified, and their locations were mapped on the structural models. A total of 18 ?b transmembrane proteins and 8 OM lipoproteins were identified. These proteins were conserved among the pathogenic Leptospira spp. and were predicted to have epitopes for several variants of MHC-II receptors. A structural and functional analysis of the sequence of these surface proteins demonstrated that most ?b transmembrane proteins seem to be TonB-dependent receptors associated with transportation. Other proteins identified included, e.g., TolC efflux pump proteins, a BamA-like OM component of the ?b transmembrane protein assembly machinery, and the LptD-like LPS assembly protein. The structural mapping of the immunodominant epitopes identified the location of conserved, surface-exposed, immunogenic regions for each vaccine candidate. The proteins identified in this study are currently being evaluated for experimental evidence for their involvement in virulence, disease pathogenesis, and physiology, in addition to vaccine development.

Project description:BackgroundReverse vaccinology accelerates the discovery of potential vaccine candidates (PVCs) prior to experimental validation. Current programs typically use one bacterial proteome to identify PVCs through a filtering architecture using feature prediction programs or a machine learning approach. Filtering approaches may eliminate potential antigens based on limitations in the accuracy of prediction tools used. Machine learning approaches are heavily dependent on the selection of training datasets with experimentally validated antigens (positive control) and non-protective-antigens (negative control). The use of one or few bacterial proteomes does not assess PVC conservation among strains, an important feature of vaccine antigens.ResultsWe present ReVac, which implements both a panoply of feature prediction programs without filtering out proteins, and scoring of candidates based on predictions made on curated positive and negative control PVCs datasets. ReVac surveys several genomes assessing protein conservation, as well as DNA and protein repeats, which may result in variable expression of PVCs. ReVac's orthologous clustering of conserved genes, identifies core and dispensable genome components. This is useful for determining the degree of conservation of PVCs among the population of isolates for a given pathogen. Potential vaccine candidates are then prioritized based on conservation and overall feature-based scoring. We present the application of ReVac, applied to 69 Moraxella catarrhalis and 270 non-typeable Haemophilus influenzae genomes, prioritizing 64 and 29 proteins as PVCs, respectively.ConclusionReVac's use of a scoring scheme ranks PVCs for subsequent experimental testing. It employs a redundancy-based approach in its predictions of features using several prediction tools. The protein's features are collated, and each protein is ranked based on the scoring scheme. Multi-genome analyses performed in ReVac allow for a comprehensive overview of PVCs from a pan-genome perspective, as an essential pre-requisite for any bacterial subunit vaccine design. ReVac prioritized PVCs of two human respiratory pathogens, identifying both novel and previously validated PVCs.

Dataset Information

Putative vaccine candidates and drug targets identified by reverse vaccinology and subtractive genomics approaches to control Haemophilus ducreyi, the causative agent of chancroid.

Publications

Putative vaccine candidates and drug targets identified by reverse vaccinology and subtractive genomics approaches to control <i>Haemophilus ducreyi</i>, the causative agent of chancroid.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure