Omics and Bioinformatics Approaches to Identify Novel Antigens for Vaccine Investigation and Development

A special issue of Vaccines (ISSN 2076-393X).

Deadline for manuscript submissions: closed (31 May 2020) | Viewed by 49583

Special Issue Editors


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Guest Editor
Departamento de Bioquímica y Biología Molecular, Universidad de Córdoba Edificio Severo Ochoa Planta Baja, Campus de Rabanales, 14071 Córdoba, Spain
Interests: proteomics; mass spectrometry; bacterial surface proteins; bioactive peptides; bioactive molecules; metabolites; functional foods; fermented milk; kefir
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Special Issue Information

Dear Colleagues,

Infectious diseases remain a major societal challenge, enhanced by global threats, including the emergence of multiresistant pathogens, climate change and the associated emergence and re-emergence of new and old pathogens, and the easy and fast spread of infectious diseases at a global scale. Vaccines have been proven as highly efficient for conferring protection to various infectious diseases. The fast developing field of omics sciences is delivering a deluge of nucleotide and protein sequence data, which is imposible to achieve without powerful bioinformatics tools and databases. This Special Issue, entitled “Omics and Bioinformatics Approaches to Identify Novel Antigens for Vaccine Investigation and Development”, aims to gather papers that use omics approaches such as genomics and proteomics to identify antigens for subunit vaccine investigation and development, as well as papers on bioinformatics tools, databases, and high-throughput techniques and instrumentation, in order to help in vaccine research and development. Research and review articles, and commentaries are all welcome.

Dr. Jorge H. Leitão
Prof. Dr. Manuel J. Rodríguez Ortega
Guest Editors

Manuscript Submission Information

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Keywords

  • omics
  • genomics
  • proteomics
  • antigen identification
  • bioinformatics tools
  • subunit vaccine
  • high-throughput techniques

Published Papers (10 papers)

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Editorial

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5 pages, 215 KiB  
Editorial
Omics and Bioinformatics Approaches to Identify Novel Antigens for Vaccine Investigation and Development
by Jorge H. Leitão and Manuel J. Rodríguez-Ortega
Vaccines 2020, 8(4), 653; https://doi.org/10.3390/vaccines8040653 - 3 Nov 2020
Cited by 4 | Viewed by 2194
Abstract
Despite the outstanding technological advances achieved in the last few decades, infectious diseases remain a major societal challenge. From the variolation carried out in ancient China during the 15th century to the more advanced RNA and DNA vaccines presently available, vaccines have been [...] Read more.
Despite the outstanding technological advances achieved in the last few decades, infectious diseases remain a major societal challenge. From the variolation carried out in ancient China during the 15th century to the more advanced RNA and DNA vaccines presently available, vaccines have been proven as highly effective therapeutic tools to combat various infectious diseases. Vaccine research and development is now empowered with recent advances in Omics sciences and the developments of powerful bioinformatics tools. This Special Issue has gathered a total of nine original papers, including seven research papers and two reviews, illustrating the use of Omics data and bioinformatics in the research, design and development of vaccines against pathogens and cancer. The integration of knowledge from Omics and Bioinformatics will certainly boost vaccine research and development, leading to novel therapeutic tools against new and old pathogens and cancer in the near future. Full article

Research

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22 pages, 1766 KiB  
Article
Characterization of the Burkholderia cenocepacia J2315 Surface-Exposed Immunoproteome
by Sílvia A. Sousa, António M.M. Seixas, Manoj Mandal, Manuel J. Rodríguez-Ortega and Jorge H. Leitão
Vaccines 2020, 8(3), 509; https://doi.org/10.3390/vaccines8030509 - 6 Sep 2020
Cited by 11 | Viewed by 3454
Abstract
Infections by the Burkholderia cepacia complex (Bcc) remain seriously life threatening to cystic fibrosis (CF) patients, and no effective eradication is available. A vaccine to protect patients against Bcc infections is a highly attractive therapeutic option, but none is available. A strategy combining [...] Read more.
Infections by the Burkholderia cepacia complex (Bcc) remain seriously life threatening to cystic fibrosis (CF) patients, and no effective eradication is available. A vaccine to protect patients against Bcc infections is a highly attractive therapeutic option, but none is available. A strategy combining the bioinformatics identification of putative surface-exposed proteins with an experimental approach encompassing the “shaving” of surface-exposed proteins with trypsin followed by peptide identification by liquid chromatography and mass spectrometry is here reported. The methodology allowed the bioinformatics identification of 263 potentially surface-exposed proteins, 16 of them also experimentally identified by the “shaving” approach. Of the proteins identified, 143 have a high probability of containing B-cell epitopes that are surface-exposed. The immunogenicity of three of these proteins was demonstrated using serum samples from Bcc-infected CF patients and Western blotting, validating the usefulness of this methodology in identifying potentially immunogenic surface-exposed proteins that might be used for the development of Bcc-protective vaccines. Full article
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14 pages, 2348 KiB  
Article
Search of Potential Vaccine Candidates against Trueperella pyogenes Infections through Proteomic and Bioinformatic Analysis
by Ángela Galán-Relaño, Lidia Gómez-Gascón, Antonio Rodríguez-Franco, Inmaculada Luque, Belén Huerta, Carmen Tarradas and Manuel J. Rodríguez-Ortega
Vaccines 2020, 8(2), 314; https://doi.org/10.3390/vaccines8020314 - 17 Jun 2020
Cited by 7 | Viewed by 2478
Abstract
Trueperella pyogenes is an opportunistic pathogen, responsible for important infections in pigs and significant economic losses in swine production. To date, there are no available commercial vaccines to control diseases caused by this bacterium. In this work, we performed a comparative proteomic analysis [...] Read more.
Trueperella pyogenes is an opportunistic pathogen, responsible for important infections in pigs and significant economic losses in swine production. To date, there are no available commercial vaccines to control diseases caused by this bacterium. In this work, we performed a comparative proteomic analysis of 15 T. pyogenes clinical isolates, by “shaving” live cells, followed by LC-MS/MS, aiming at the identification of the whole set of surface proteins (i.e., the “pan-surfome”) as a source of antigens to be tested in further studies as putative vaccine candidates, or used in diagnostic tools. A total of 140 surface proteins were detected, comprising 25 cell wall proteins, 10 secreted proteins, 23 lipoproteins and 82 membrane proteins. After describing the “pan-surfome”, the identified proteins were ranked in three different groups based on the following criteria: to be (i) surface-exposed, (ii) highly conserved and (iii) widely distributed among different isolates. Two cell wall proteins, three lipoproteins, four secreted and seven membrane proteins were identified in more than 70% of the studied strains, were highly expressed and highly conserved. These proteins are potential candidates, alone or in combination, to obtain effective vaccines against T. pyogenes or to be used in the diagnosis of this pathogen. Full article
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17 pages, 3537 KiB  
Article
Immunoinformatics and Structural Analysis for Identification of Immunodominant Epitopes in SARS-CoV-2 as Potential Vaccine Targets
by Sumit Mukherjee, Dmitry Tworowski, Rajesh Detroja, Sunanda Biswas Mukherjee and Milana Frenkel-Morgenstern
Vaccines 2020, 8(2), 290; https://doi.org/10.3390/vaccines8020290 - 9 Jun 2020
Cited by 54 | Viewed by 10162
Abstract
A new coronavirus infection, COVID-19, has recently emerged, and has caused a global pandemic along with an international public health emergency. Currently, no licensed vaccines are available for COVID-19. The identification of immunodominant epitopes for both B- and T-cells that induce protective responses [...] Read more.
A new coronavirus infection, COVID-19, has recently emerged, and has caused a global pandemic along with an international public health emergency. Currently, no licensed vaccines are available for COVID-19. The identification of immunodominant epitopes for both B- and T-cells that induce protective responses in the host is crucial for effective vaccine design. Computational prediction of potential epitopes might significantly reduce the time required to screen peptide libraries as part of emergent vaccine design. In our present study, we used an extensive immunoinformatics-based approach to predict conserved immunodominant epitopes from the proteome of SARS-CoV-2. Regions from SARS-CoV-2 protein sequences were defined as immunodominant, based on the following three criteria regarding B- and T-cell epitopes: (i) they were both mapped, (ii) they predicted protective antigens, and (iii) they were completely identical to experimentally validated epitopes of SARS-CoV. Further, structural and molecular docking analyses were performed in order to understand the binding interactions of the identified immunodominant epitopes with human major histocompatibility complexes (MHC). Our study provides a set of potential immunodominant epitopes that could enable the generation of both antibody- and cell-mediated immunity. This could contribute to developing peptide vaccine-based adaptive immunotherapy against SARS-CoV-2 infections and prevent future pandemic outbreaks. Full article
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22 pages, 1759 KiB  
Article
Proteomic and Bioinformatic Analysis of Streptococcus suis Human Isolates: Combined Prediction of Potential Vaccine Candidates
by Esther Prados de la Torre, Antonio Rodríguez-Franco and Manuel J. Rodríguez-Ortega
Vaccines 2020, 8(2), 188; https://doi.org/10.3390/vaccines8020188 - 18 Apr 2020
Cited by 8 | Viewed by 3555
Abstract
Streptococcus suis is a Gram-positive bacterium responsible for major infections in pigs and economic losses in the livestock industry, but also an emerging zoonotic pathogen causing serious diseases in humans. No vaccine is available so far against this microorganism. Conserved surface proteins are [...] Read more.
Streptococcus suis is a Gram-positive bacterium responsible for major infections in pigs and economic losses in the livestock industry, but also an emerging zoonotic pathogen causing serious diseases in humans. No vaccine is available so far against this microorganism. Conserved surface proteins are among the most promising candidates for new and effective vaccines. Until now, research on this pathogen has focused on swine isolates, but there is a lack of studies to identify and characterize surface proteins from human clinical isolates. In this work, we performed a comparative proteomic analysis of six clinical isolates from human patients, all belonging to the major serotype 2, by “shaving” the live bacterial cells with trypsin, followed by LC-MS/MS analysis. We identified 131 predicted surface proteins and carried out a label-free semi-quantitative analysis of protein abundances within the six strains. Then, we combined our proteomics results with bioinformatic tools to help improving the selection of novel antigens that can enter the pipeline of vaccine candidate testing. Our work is then a complement to the reverse vaccinology concept. Full article
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22 pages, 4071 KiB  
Article
Study of Humoral Responses against Lomentospora/Scedosporium spp. and Aspergillus fumigatus to Identify L. prolificans Antigens of Interest for Diagnosis and Treatment
by Idoia Buldain, Aize Pellon, Beñat Zaldibar, Aitziber Antoran, Leire Martin-Souto, Leire Aparicio-Fernandez, Maialen Areitio, Emilio Mayayo, Aitor Rementeria, Fernando L. Hernando and Andoni Ramirez-Garcia
Vaccines 2019, 7(4), 212; https://doi.org/10.3390/vaccines7040212 - 10 Dec 2019
Cited by 10 | Viewed by 3485
Abstract
The high mortality rates of Lomentospora prolificans infections are due, above all, to the tendency of the fungus to infect weakened hosts, late diagnosis and a lack of effective therapeutic treatments. To identify proteins of significance for diagnosis, therapy or prophylaxis, immunoproteomics-based studies [...] Read more.
The high mortality rates of Lomentospora prolificans infections are due, above all, to the tendency of the fungus to infect weakened hosts, late diagnosis and a lack of effective therapeutic treatments. To identify proteins of significance for diagnosis, therapy or prophylaxis, immunoproteomics-based studies are especially important. Consequently, in this study murine disseminated infections were carried out using L. prolificans, Scedosporium aurantiacum, Scedosporium boydii and Aspergillus fumigatus, and their sera used to identify the most immunoreactive proteins of L. prolificans total extract and secreted proteins. The results showed that L. prolificans was the most virulent species and its infections were characterized by a high fungal load in several organs, including the brain. The proteomics study showed a high cross-reactivity between Scedosporium/Lomentospora species, but not with A. fumigatus. Among the antigens identified were, proteasomal ubiquitin receptor, carboxypeptidase, Vps28, HAD-like hydrolase, GH16, cerato-platanin and a protein of unknown function that showed no or low homology with humans. Finally, Hsp70 deserves a special mention as it was the main antigen recognized by Scedosporium/Lomentospora species in both secretome and total extract. In conclusion, this study identifies antigens of L. prolificans that can be considered as potential candidates for use in diagnosis and as therapeutic targets and the production of vaccines. Full article
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23 pages, 2973 KiB  
Article
Integrated Bioinformatic Analyses and Immune Characterization of New Neisseria gonorrhoeae Vaccine Antigens Expressed during Natural Mucosal Infection
by Tianmou Zhu, Ryan McClure, Odile B. Harrison, Caroline Genco and Paola Massari
Vaccines 2019, 7(4), 153; https://doi.org/10.3390/vaccines7040153 - 17 Oct 2019
Cited by 13 | Viewed by 4541
Abstract
There is an increasingly severe trend of antibiotic-resistant Neisseria gonorrhoeae strains worldwide and new therapeutic strategies are needed against this sexually-transmitted pathogen. Despite the urgency, progress towards a gonococcal vaccine has been slowed by a scarcity of suitable antigens, lack of correlates of [...] Read more.
There is an increasingly severe trend of antibiotic-resistant Neisseria gonorrhoeae strains worldwide and new therapeutic strategies are needed against this sexually-transmitted pathogen. Despite the urgency, progress towards a gonococcal vaccine has been slowed by a scarcity of suitable antigens, lack of correlates of protection in humans and limited animal models of infection. N. gonorrhoeae gene expression levels in the natural human host does not reflect expression in vitro, further complicating in vitro-basedvaccine analysis platforms. We designed a novel candidate antigen selection strategy (CASS), based on a reverse vaccinology-like approach coupled with bioinformatics. We utilized the CASS to mine gonococcal proteins expressed during human mucosal infection, reported in our previous studies, and focused on a large pool of hypothetical proteins as an untapped source of potential new antigens. Via two discovery and analysis phases (DAP), we identified 36 targets predicted to be immunogenic, membrane-associated proteins conserved in N. gonorrhoeae and suitable for recombinant expression. Six initial candidates were produced and used to immunize mice. Characterization of the immune responses indicated cross-reactive antibodies and serum bactericidal activity against different N. gonorrhoeae strains. These results support the CASS as a tool for the discovery of new vaccine candidates. Full article
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17 pages, 2411 KiB  
Article
Immunoinformatics-Aided Design and Evaluation of a Potential Multi-Epitope Vaccine against Klebsiella Pneumoniae
by Hamza Arshad Dar, Tahreem Zaheer, Muhammad Shehroz, Nimat Ullah, Kanwal Naz, Syed Aun Muhammad, Tianyu Zhang and Amjad Ali
Vaccines 2019, 7(3), 88; https://doi.org/10.3390/vaccines7030088 - 12 Aug 2019
Cited by 82 | Viewed by 8636
Abstract
Klebsiella pneumoniae is an opportunistic gram-negative bacterium that causes nosocomial infection in healthcare settings. Despite the high morbidity and mortality rate associated with these bacterial infections, no effective vaccine is available to counter the pathogen. In this study, the pangenome of a total [...] Read more.
Klebsiella pneumoniae is an opportunistic gram-negative bacterium that causes nosocomial infection in healthcare settings. Despite the high morbidity and mortality rate associated with these bacterial infections, no effective vaccine is available to counter the pathogen. In this study, the pangenome of a total of 222 available complete genomes of K. pneumoniae was explored to obtain the core proteome. A reverse vaccinology strategy was applied to the core proteins to identify four antigenic proteins. These proteins were then subjected to epitope mapping and prioritization steps to shortlist nine B-cell derived T-cell epitopes which were linked together using GPGPG linkers. An adjuvant (Cholera Toxin B) was also added at the N-terminal of the vaccine construct to improve its immunogenicity and a stabilized multi-epitope protein structure was obtained using molecular dynamics simulation. The designed vaccine exhibited sustainable and strong bonding interactions with Toll-like receptor 2 and Toll-like receptor 4. In silico reverse translation and codon optimization also confirmed its high expression in E. coli K12 strain. The computer-aided analyses performed in this study imply that the designed multi-epitope vaccine can elicit specific immune responses against K. pneumoniae. However, wet lab validation is necessary to further verify the effectiveness of this proposed vaccine candidate. Full article
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Review

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20 pages, 1517 KiB  
Review
From Bivariate to Multivariate Analysis of Cytometric Data: Overview of Computational Methods and Their Application in Vaccination Studies
by Simone Lucchesi, Simone Furini, Donata Medaglini and Annalisa Ciabattini
Vaccines 2020, 8(1), 138; https://doi.org/10.3390/vaccines8010138 - 20 Mar 2020
Cited by 13 | Viewed by 5929
Abstract
Flow and mass cytometry are used to quantify the expression of multiple extracellular or intracellular molecules on single cells, allowing the phenotypic and functional characterization of complex cell populations. Multiparametric flow cytometry is particularly suitable for deep analysis of immune responses after vaccination, [...] Read more.
Flow and mass cytometry are used to quantify the expression of multiple extracellular or intracellular molecules on single cells, allowing the phenotypic and functional characterization of complex cell populations. Multiparametric flow cytometry is particularly suitable for deep analysis of immune responses after vaccination, as it allows to measure the frequency, the phenotype, and the functional features of antigen-specific cells. When many parameters are investigated simultaneously, it is not feasible to analyze all the possible bi-dimensional combinations of marker expression with classical manual analysis and the adoption of advanced automated tools to process and analyze high-dimensional data sets becomes necessary. In recent years, the development of many tools for the automated analysis of multiparametric cytometry data has been reported, with an increasing record of publications starting from 2014. However, the use of these tools has been preferentially restricted to bioinformaticians, while few of them are routinely employed by the biomedical community. Filling the gap between algorithms developers and final users is fundamental for exploiting the advantages of computational tools in the analysis of cytometry data. The potentialities of automated analyses range from the improvement of the data quality in the pre-processing steps up to the unbiased, data-driven examination of complex datasets using a variety of algorithms based on different approaches. In this review, an overview of the automated analysis pipeline is provided, spanning from the pre-processing phase to the automated population analysis. Analysis based on computational tools might overcame both the subjectivity of manual gating and the operator-biased exploration of expected populations. Examples of applications of automated tools that have successfully improved the characterization of different cell populations in vaccination studies are also presented. Full article
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23 pages, 3675 KiB  
Review
SANTAVACTM: Summary of Research and Development
by Petr G. Lokhov, Mikayel Mkrtichyan, Grigor Mamikonyan and Elena E. Balashova
Vaccines 2019, 7(4), 186; https://doi.org/10.3390/vaccines7040186 - 17 Nov 2019
Cited by 7 | Viewed by 4090
Abstract
SANTAVAC is an antigen composition developed via proteomics and cell culture technology that is intended for the development of cancer vaccines against various solid tumors. Its mechanism of action is based on the heterogeneity of endothelial cells, the polypeptides of which are similar [...] Read more.
SANTAVAC is an antigen composition developed via proteomics and cell culture technology that is intended for the development of cancer vaccines against various solid tumors. Its mechanism of action is based on the heterogeneity of endothelial cells, the polypeptides of which are similar to the surface antigens of tumor-vessel cells, allowing targeted destruction by vaccination. While research and development work with SANTAVAC is ongoing, the existing data provide strong evidence that allogeneic SANTAVAC is an ideal candidate for the development of cancer vaccines with significant efficacy and safety. The SANTAVAC compositions described here demonstrated the ability to inhibit the growth of tumor vessel-specific endothelial cells up to 60 fold, with minimal effect on normal vasculature. Innovation, background, description of product development, and summary of nonclinical studies with SANTAVAC to date are presented in this review. Full article
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