Antigen Discovery in Bacterial Panproteomes

Yero, Daniel; Conchillo-Solé, Òscar; Daura, Xavier

doi:10.1007/978-1-0716-0795-4_5

Cited by 8 publications

(7 citation statements)

References 96 publications

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“…The introduction of fast sequencing technologies and as a result genomic data is added to databases enabled researchers to discover new vaccine candidates that were harder to detect in traditional vaccine development ( Moriel et al, 2008 ; Naz et al, 2021 ). The identification of putative surface-associated antigens can be done using advanced bioinformatic approaches ( Yero et al, 2021 ). It has been shown that reverse vaccinology is a safe, effective, and reliable method for identifying surface-associated proteins from the pathogen genome without the need to cultivate the microbes ( Yero et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

“…The identification of putative surface-associated antigens can be done using advanced bioinformatic approaches ( Yero et al, 2021 ). It has been shown that reverse vaccinology is a safe, effective, and reliable method for identifying surface-associated proteins from the pathogen genome without the need to cultivate the microbes ( Yero et al, 2021 ). An effective meningococcal vaccine has been developed using the reverse vaccinology method ( Abdullah et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

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Reverse Vaccinology and Immunoinformatic Assisted Designing of a Multi-Epitopes Based Vaccine Against Nosocomial Burkholderia cepacia

2022

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Burkholderia cepacia is a Gram-negative nosocomial pathogen and is considered as a troublesome bacterium due to its resistance to many common antibiotics. There is no licensed vaccine available to prevent the pathogen infections, thus making the condition more alarming and warrant the search for novel therapeutic and prophylactic approaches. In order to identify protective antigens from pathogen proteome, substantial efforts are put forth to prioritized potential vaccine targets and antigens that can be easily evaluated experimentally. In this vaccine design investigation, it was found that B. cepacia completely sequenced proteomes available in NCBI genome database has a total of 28,966 core proteins. Out of total, 25,282 proteins were found redundant while 3,684 were non-redundant. Subcellular localization revealed that 18 proteins were extracellular, 31 were part of the outer membrane, 75 proteins were localized in the periplasm, and 23 were virulent proteins. Five proteins namely flagellar hook protein (FlgE), fimbria biogenesis outer membrane usher protein, Type IV pilus secretin (PilQ), cytochrome c4, flagellar hook basal body complex protein (FliE) were tested for positive for antigenic, non-toxic, and soluble epitopes during predication of B-cell derived T-cell epitopes. A vaccine peptide of 14 epitopes (joined together via GPGPG linkers) and cholera toxin B subunit (CTBS) adjuvant (joined to epitopes peptide via EAAAK linker) was constructed. Binding interaction of the modeled vaccine with MHC-I, MHC-II, and Toll-like receptor 4 (TLR-4) immune receptors was studied using molecular docking studies and further analyzed in molecular dynamics simulations that affirms strong intermolecular binding and stable dynamics. The maximum root mean square deviation (RMSD) score of complexes in the simulation time touches to 2 Å. Additionally, complexes binding free energies were determined that concluded robust interaction energies dominated by van der Waals. The total energy of each complex is < −190 kcal/mol. In summary, the designed vaccine showed promising protective immunity against B. cepacia and needs to be examined in experiments.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Reverse Vaccinology and Immunoinformatic Assisted Designing of a Multi-Epitopes Based Vaccine Against Nosocomial Burkholderia cepacia

2022

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“…The genomic revolution will greatly aid in disclosing new vaccine candidates that, by traditional vaccine development, are hard to detect [29]. Next-generation sequencing of bacterial pathogens and advanced bioinformatics practices in vaccinology are now commonly employed for the identification of putative surface-associated antigens [30]. The meningococcal serogroup B (4CMenB) vaccine was effectively developed using the RV approach [31].…”

Section: Introductionmentioning

confidence: 99%

Designing a Recombinant Vaccine against Providencia rettgeri Using Immunoinformatics Approach

et al. 2022

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Antibiotic resistance (AR) is the resistance mechanism pattern in bacteria that evolves over some time, thus protecting the bacteria against antibiotics. AR is due to bacterial evolution to make itself fit to changing environmental conditions in a quest for survival of the fittest. AR has emerged due to the misuse and overuse of antimicrobial drugs, and few antibiotics are now left to deal with these superbug infections. To combat AR, vaccination is an effective method, used either therapeutically or prophylactically. In the current study, an in silico approach was applied for the design of multi-epitope-based vaccines against Providencia rettgeri, a major cause of traveler’s diarrhea. A total of six proteins: fimbrial protein, flagellar hook protein (FlgE), flagellar basal body L-ring protein (FlgH), flagellar hook-basal body complex protein (FliE), flagellar basal body P-ring formation protein (FlgA), and Gram-negative pili assembly chaperone domain proteins, were considered as vaccine targets and were utilized for B- and T-cell epitope prediction. The predicted epitopes were assessed for allergenicity, antigenicity, virulence, toxicity, and solubility. Moreover, filtered epitopes were utilized in multi-epitope vaccine construction. The predicted epitopes were joined with each other through specific GPGPG linkers and were joined with cholera toxin B subunit adjuvant via another EAAAK linker in order to enhance the efficacy of the designed vaccine. Docking studies of the designed vaccine construct were performed with MHC-I (PDB ID: 1I1Y), MHC-II (1KG0), and TLR-4 (4G8A). Findings of the docking study were validated through molecular dynamic simulations, which confirmed that the designed vaccine showed strong interactions with the immune receptors, and that the epitopes were exposed to the host immune system for proper recognition and processing. Additionally, binding free energies were estimated, which highlighted both electrostatic energy and van der Waals forces to make the complexes stable. Briefly, findings of the current study are promising and may help experimental vaccinologists to formulate a novel multi-epitope vaccine against P. rettgeri.

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“…In the recent past, bioinformatics and genomics have proved successful in the prediction of possible vaccine candidates in bacterial genomes [ 12 ]. Advances in bioinformatics, immunoinformatic, and reverse vaccinology pipelines are now commonly used in the area of vaccine candidate’s prioritization and vaccine designing [ 13 ]. Reverse vaccinology (RV) is a methodology employed for the prediction of good vaccine targets from a pathogen’s genome [ 14 ] and has been successfully used in the development of meningococcal serogroup B (4CMenB) [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Computational Based Designing of a Multi-Epitopes Vaccine against Burkholderia mallei

et al. 2022

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The emergence of antibiotic resistance in bacterial species is a major threat to public health and has resulted in high mortality as well as high health care costs. Burkholderia mallei is one of the etiological agents of health care-associated infections. As no licensed vaccine is available against the pathogen herein, using reverse vaccinology, bioinformatics, and immunoinformatics approaches, a multi-epitope-based vaccine against B. mallei was designed. In completely sequenced proteomes of B. mallei, 18,405 core, 3671 non-redundant, and 14,734 redundant proteins were predicted. Among the 3671 non-redundant proteins, 3 proteins were predicted in the extracellular matrix, 11 were predicted as outer membrane proteins, and 11 proteins were predicted in the periplasmic membrane. Only two proteins, type VI secretion system tube protein (Hcp) and type IV pilus secretin proteins, were selected for epitope prediction. Six epitopes, EAMPERMPAA, RSSPPAAGA, DNRPISINL, RQRFDAHAR, AERERQRFDA, and HARAAQLEPL, were shortlisted for multi-epitopes vaccine design. The predicted epitopes were linked to each other via a specific GPGPG linker and the epitopes peptide was then linked to an adjuvant molecule through an EAAAK linker to make the designed vaccine more immunologically potent. The designed vaccine was also found to have favorable physicochemical properties with a low molecular weight and fewer transmembrane helices. Molecular docking studies revealed vaccine construct stable binding with MHC-I, MHC-II, and TLR-4 with energy scores of −944.1 kcal/mol, −975.5 kcal/mol, and −1067.3 kcal/mol, respectively. Molecular dynamic simulation assay noticed stable dynamics of the docked vaccine-receptors complexes and no drastic changes were observed. Binding free energies estimation revealed a net value of −283.74 kcal/mol for the vaccine-MHC-I complex, −296.88 kcal/mol for the vaccine-MHC-II complex, and −586.38 kcal/mol for the vaccine-TLR-4 complex. These findings validate that the designed vaccine construct showed promising ability in terms of binding to immune receptors and may be capable of eliciting strong immune responses once administered to the host. Further evidence from experimentations in mice models is required to validate real immune protection of the designed vaccine construct against B. mallei.

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Antigen Discovery in Bacterial Panproteomes

Cited by 8 publications

References 96 publications

Reverse Vaccinology and Immunoinformatic Assisted Designing of a Multi-Epitopes Based Vaccine Against Nosocomial Burkholderia cepacia

Reverse Vaccinology and Immunoinformatic Assisted Designing of a Multi-Epitopes Based Vaccine Against Nosocomial Burkholderia cepacia

Designing a Recombinant Vaccine against Providencia rettgeri Using Immunoinformatics Approach

Computational Based Designing of a Multi-Epitopes Vaccine against Burkholderia mallei

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