Integrative immunoinformatics for Mycobacterial diseases in R platform

Identification of potential antigenic proteins and epitopes for the development of a monkeypox virus vaccine: an in silico approach

Virus assembly, budding, or surface proteins play important roles such as viral attachment to cells, fusion, and entry into cells. The present study aimed to identify potential antigenic proteins and epitopes that could be used to develop a vaccine or diagnostic assay against the Monkeypox virus (MPXV) which may cause a potential epidemic. To do this, 39 MPXV proteins (including assembly, budding, and surface proteins) were analyzed using an in silico approach. Of these 39 proteins, the F5L virus protein was found to be the best vaccine candidate due to its signal peptide properties, negative GRAVY value, low transmembrane helix content, moderate aliphatic index, large molecular weight, long-estimated half-life, beta wrap motifs, and being stable, soluble, and containing non-allergic features. Moreover, the F5L protein exhibited alpha-helical secondary structures, making it a potential "structural antigen" recognized by antibodies. The other viral protein candidates were A9 and A43, but A9 lacked beta wrap motifs, while A43 had a positive GRAVY value and was insoluble. These two proteins were not as suitable candidates as the F5L protein. The KRVNISLTCL epitope from the F5L protein demonstrated the highest antigen score (2.4684) for MHC-I, while the GRFGYVPYVGYKCI epitope from the A9 protein exhibited the highest antigenicity (1.754) for MHC-II. Both epitopes met the criteria for high antigenicity, non-toxicity, solubility, non-allergenicity, and the presence of cleavage sites. Molecular docking and dynamics (MD) simulations further validated their potential, revealing stable and energetically favorable interactions with MHC molecules. The immunogenicity assessment showed that GRFGYVPYVGYKCI could strongly induce immune responses through both IFN-γ and IL-4 pathways, suggesting its capacity to provoke a balanced Th1 and Th2 response. In contrast, KRVNISLTCL exhibited limited immunostimulatory potential. Overall, these findings lay the groundwork for future vaccine development, indicating that F5L, particularly the GRFGYVPYVGYKCI epitope, may serve as an effective candidate for peptide-based vaccine design against MPXV.

Towards the development of subunit vaccines against tuberculosis: The key role of adjuvant

According to the World Health Organization (WHO), tuberculosis (TB) is the leading cause of death triggered by a single infectious agent, worldwide. Bacillus Calmette-Guerin (BCG) is the only currently licensed anti-TB vaccine. However, other strategies, including modification of recombinant BCG vaccine, attenuated Mycobacterium tuberculosis (Mtb) mutant constructs, DNA and protein subunit vaccines, are under extensive investigation. As whole pathogen vaccines can trigger serious adverse reactions, most current strategies are focused on the development of safe anti-TB subunit vaccines; this is especially important given the rising TB infection rate in immunocompromised HIV patients. The whole Mtb genome has been mapped and major antigens have been identified; however, optimal vaccine delivery mode is still to be established. Isolated protein antigens are typically poorly immunogenic so adjuvants are required to induce strong and long-lasting immune responses. This article aims to review the developmental status of anti-TB subunit vaccine adjuvants.

Recent Advances in Genomics-Based Approaches for the Development of Intracellular Bacterial Pathogen Vaccines

Infectious diseases continue to be a leading cause of morbidity and mortality worldwide. The majority of infectious diseases are caused by intracellular pathogenic bacteria (IPB). Historically, conventional vaccination drives have helped control the pathogenesis of intracellular bacteria and the emergence of antimicrobial resistance, saving millions of lives. However, in light of various limitations, many diseases that involve IPB still do not have adequate vaccines. In response to increasing demand for novel vaccine development strategies, a new area of vaccine research emerged following the advent of genomics technology, which changed the paradigm of vaccine development by utilizing the complete genomic data of microorganisms against them. It became possible to identify genes related to disease virulence, genetic patterns linked to disease virulence, as well as the genetic components that supported immunity and favorable vaccine responses. Complete genomic databases, and advancements in transcriptomics, metabolomics, structural genomics, proteomics, immunomics, pan-genomics, synthetic genomics, and population biology have allowed researchers to identify potential vaccine candidates and predict their effects in patients. New vaccines have been created against diseases for which previously there were no vaccines available, and existing vaccines have been improved. This review highlights the key issues and explores the evolution of vaccines. The increasing volume of IPB genomic data, and their application in novel genome-based techniques for vaccine development, were also examined, along with their characteristics, and the opportunities and obstacles involved. Critically, the application of genomics technology has helped researchers rapidly select and evaluate candidate antigens. Novel vaccines capable of addressing the limitations associated with conventional vaccines have been developed and pressing healthcare issues are being addressed.

Peptide-Based Vaccines for Tuberculosis

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. As a result of the coronavirus disease 2019 (COVID-19) pandemic, the global TB mortality rate in 2020 is rising, making TB prevention and control more challenging. Vaccination has been considered the best approach to reduce the TB burden. Unfortunately, BCG, the only TB vaccine currently approved for use, offers some protection against childhood TB but is less effective in adults. Therefore, it is urgent to develop new TB vaccines that are more effective than BCG. Accumulating data indicated that peptides or epitopes play essential roles in bridging innate and adaptive immunity and triggering adaptive immunity. Furthermore, innovations in bioinformatics, immunoinformatics, synthetic technologies, new materials, and transgenic animal models have put wings on the research of peptide-based vaccines for TB. Hence, this review seeks to give an overview of current tools that can be used to design a peptide-based vaccine, the research status of peptide-based vaccines for TB, protein-based bacterial vaccine delivery systems, and animal models for the peptide-based vaccines. These explorations will provide approaches and strategies for developing safer and more effective peptide-based vaccines and contribute to achieving the WHO's End TB Strategy.

Development of ELISA based on Bacillus anthracis capsule biosynthesis protein CapA for naturally acquired antibodies against anthrax

Anthrax is a zoonotic disease caused by the gram-positive spore-forming bacterium Bacillus anthracis. Detecting naturally acquired antibodies against anthrax sublethal exposure in animals is essential for anthrax surveillance and effective control measures. Serological assays based on protective antigen (PA) of B. anthracis are mainly used for anthrax surveillance and vaccine evaluation. Although the assay is reliable, it is challenging to distinguish the naturally acquired antibodies from vaccine-induced immunity in animals because PA is cross-reactive to both antibodies. Although additional data on the vaccination history of animals could bypass this problem, such data are not readily accessible in many cases. In this study, we established a new enzyme-linked immunosorbent assay (ELISA) specific to antibodies against capsule biosynthesis protein CapA antigen of B. anthracis, which is non-cross-reactive to vaccine-induced antibodies in horses. Using in silico analyses, we screened coding sequences encoded on pXO2 plasmid, which is absent in the veterinary vaccine strain Sterne 34F2 but present in virulent strains of B. anthracis. Among the 8 selected antigen candidates, capsule biosynthesis protein CapA (GBAA_RS28240) and peptide ABC transporter substrate-binding protein (GBAA_RS28340) were detected by antibodies in infected horse sera. Of these, CapA has not yet been identified as immunoreactive in other studies to the best of our knowledge. Considering the protein solubility and specificity of B. anthracis, we prepared the C-terminus region of CapA, named CapA322, and developed CapA322-ELISA based on a horse model. Comparative analysis of the CapA322-ELISA and PAD1-ELISA (ELISA uses domain one of the PA) showed that CapA322-ELISA could detect anti-CapA antibodies in sera from infected horses but was non-reactive to sera from vaccinated horses. The CapA322-ELISA could contribute to the anthrax surveillance in endemic areas, and two immunoreactive proteins identified in this study could be additives to the improvement of current or future vaccine development.

Molecular insight into the genomic variation of SARS-CoV-2 strains from current outbreak

Coronavirus disease 2019 (COVID-19) is the newly emerging viral disease, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The epidemic sparked in December 2019 at Wuhan city, China that causes a large global outbreak and a major public health catastrophe. Till now, more than 129 million positive cases have been reported in which more than 2.81 million were dead, surveyed by Johns Hopkins University, USA. The diverse symptoms of COVID-19 and an increased number of positive cases throughout the world hypothesize that this virus assembles more variants that are preventing the pursuit of its adequate treatment as well as the development of the vaccine. In this study, 715 SARS-CoV-2 genomes were retrieved from the gisaid and NCBI viral resources involving 39 countries and 164 different types of variants were identified based on 108 Single Nucleotide Polymorphisms (SNPs) in which the ancestral type of SARS-CoV-2 was found as the most frequent and the most prevalent in China. Moreover, variant type A104 was identified as the most frequent in the USA and A52 in Japan. The study also recognized the most common SNPs such as 241, 3037, 8782, 11083, 14408, 23403, and 28144 as well as variants regarding base-pair, C > T. A total of 65 non-synonymous SNPs were recognized which were mostly located in nucleocapsid phosphoprotein, Non-structural protein 3(Nsp3), and spike glycoprotein encoding gene. Molecular divergence analysis revealed that this virus was phylogenetically related to Yunnan 2013 bat strain. This study indicates SARS-CoV-2 frequently alters their genetic material, which mostly affects the nucleocapsid phosphoprotein, and spike glycoprotein-encoding gene and makes it very challenging to develop SARS-Cov-2 vaccine and antibody-mediated rapid diagnostic kit.

Computational discovery and ex-vivo validation study of novel antigenic vaccine candidates against tuberculosis

Tuberculosis (TB) is a complex infectious bacterial disease, which has evolved with highly successful mechanisms to interfere with host defenses and existing classes of antibiotics to resist eradication. The single obtainable TB vaccine, Bacille Calmette-Guerin (BCG) has failed to provide regular defense for respiratory TB in adults. In this study, a bioinformatics and immunoinformatics approach was applied on Mycobacterium tuberculosis (Mtb) H37Rv proteomes to discover the potential subunit vaccine candidates that elicit both tuberculosis-specific T-cells and B-cell immune response. A total of 4049 proteins of MtbH37RvMtbH37Rv were retrieved and subjected to in silico sequence-based analysis. Finally, five (P9WL69 (Rv2599), P9WIG1 (Rv0747), P9WLQ1 (Rv1987), O53608 (Rv0063), O06624 (Rv1566c)) novel putative proteins were selected. Among the five putative antigenic vaccine candidates, P9WL69 protein was selected for the ex-vivo validation study. The P9WL69 protein encoding gene was amplified and cloned on pET21b vector. The success of the recombinant clone (pET21b-RV2599) was confirmed by colony PCR, insert release test and sequencing. Furthermore, the identified epitopes of the P9WL69 protein were considered for in silico docking and molecular dynamics simulation study using Toll-like Receptors (TLRs) (TLR-2, TLR-4, TLR-9), Mannose receptor, and Myeloid differentiation 88 (MYD88) to understand their binding affinity towards the development of immunogenic vaccines against tuberculosis.

Strongyloides stercoralis proteome: A reverse approach to the identification of potential immunogenic candidates

Strongyloides stercoralis is a parasite widely distributed in the tropical and subtropical areas in the world. Its treatment and diagnosis have a limitation as many other parasitic diseases. Nowadays, there is a great interest in designing an efficient epitope for vaccines or diagnostic. In this study, a bioinformatics-based screening approach has been incorporated in order to explore potential immunogens in the S. stercoralis proteome. Bioinformatic tools were used to predict diagnostic and vaccinology approaches. 12.851 cell immunology proteins from Uniprot were analyzed. Thirty-four immunogenic candidates were identified, they had higher antigenic activity, less than 2 α-helices, non-allergen activity and they do not have homology with host proteins, all of them have ortholog protein with Strongyloides ratti. Some of them presented a good binding with immunological cell (T and B cell). These proteins could be a good alternative as a candidate for the design of the novel vaccines or diagnostic tests of strongyloides stercoralis.

Identification of novel therapeutic target and epitopes through proteome mining from essential hypothetical proteins in Salmonella strains: An In silico approach towards antivirulence therapy and vaccine development

Salmonella strains are responsible for a huge mortality rate through foodborne ailment in the world that necessitated the discovery of novel drugs and vaccines. Essential hypothetical proteins (EHPs), whose structures and functions were previously unknown, could serve as potential therapeutic and vaccine targets. Antivirulence therapy shall emerge as a superior therapeutic approach that uses virulence factors as drug targets. This study annotated the biological functions of 96 out of total 106 essential hypothetical proteins in five strains of Salmonella and classified into nine important protein categories. 34 virulence factors were predicted among the EHPs, out of which, 11 were identified to be pathogen specific potential drug targets for antivirulence therapy. These targets were non-homologous to both human and gut microbiota proteome to avoid cross-reactivity with them. Seven identified targets had druggable property, while the rest four targets were novel targets. Four identified targets (DEG10320148, DEG10110027, DEG10110040 and DEG10110142) had antigenic properties and were further classified as: two membrane-bound Lipid-binding transmembrane proteins, a Zinc-binding membrane protein and an extracellular glycosylase. These targets could be potentially used for the development of subunit vaccines. The study further identified 11 highly conserved and exposed epitope sequences from these 4 vaccine targets. The three-dimensional structures of the vaccine targets were also elucidated along with highlighting the conformation of the epitopes. This study identified potential therapeutic targets for antivirulence therapy against Salmonella. It would therefore instigate in novel drug designing as well as provide important leads to new Salmonella vaccine development.

Recent Trends in System-Scale Integrative Approaches for Discovering Protective Antigens Against Mycobacterial Pathogens

Mycobacterial infections are one of the deadliest infectious diseases still posing a major health burden worldwide. The battle against these pathogens needs to focus on novel approaches and key interventions. In recent times, availability of genome scale data has revolutionized the fields of computational biology and immunoproteomics. Here, we summarize the cutting-edge ‘omics’ technologies and innovative system scale strategies exploited to mine the available data. These may be targeted using high-throughput technologies to expedite the identification of novel antigenic candidates for the rational next generation vaccines and serodiagnostic development against mycobacterial pathogens for which traditional methods have been failing.

Computational B-cell epitope identification and production of neutralizing murine antibodies against Atroxlysin-I

Epitope identification is essential for developing effective antibodies that can detect and neutralize bioactive proteins. Computational prediction is a valuable and time-saving alternative for experimental identification. Current computational methods for epitope prediction are underused and undervalued due to their high false positive rate. In this work, we targeted common properties of linear B-cell epitopes identified in an individual protein class (metalloendopeptidases) and introduced an alternative method to reduce the false positive rate and increase accuracy, proposing to restrict predictive models to a single specific protein class. For this purpose, curated epitope sequences from metalloendopeptidases were transformed into frame-shifted Kmers (3 to 15 amino acid residues long). These Kmers were decomposed into a matrix of biochemical attributes and used to train a decision tree classifier. The resulting prediction model showed a lower false positive rate and greater area under the curve when compared to state-of-the-art methods. Our predictions were used for synthesizing peptides mimicking the predicted epitopes for immunization of mice. A predicted linear epitope that was previously undetected by an experimental immunoassay was able to induce neutralizing-antibody production in mice. Therefore, we present an improved prediction alternative and show that computationally identified epitopes can go undetected during experimental mapping.

Proteome-scale identification of Leishmania infantum for novel vaccine candidates: A hierarchical subtractive approach

Vaccines are one of the most significant achievements in medical science. However, vaccine design is still challenging at all stages. The selection of antigenic peptides as vaccine candidates is the first and most important step for vaccine design. Experimental selection of antigenic peptides for the design of vaccines is a time-consuming, labor-intensive and expensive procedure. More recently, in the light of computer-aided biotechnology and reverse vaccinology, the precise selection of antigenic peptides and rational vaccine design against many pathogens have developed. In this study, the whole proteome of Leishmania infantum was analyzed using a pipeline of algorithms. From the set of 8045 proteins of L. infantum, sixteen novel antigenic proteins were derived using a hierarchical proteome subtractive analysis. These novel vaccine targets can be utilized as top candidates for designing the new prophylactic or therapeutic vaccines against visceral leishmaniasis. Significantly, all the sixteen novel vaccine candidates are non-allergen antigenic proteins that have not been used for the design of vaccines against visceral leishmaniasis until now.

Novel in silico tools for designing peptide-based subunit vaccines and immunotherapeutics

The conventional approach for designing vaccine against a particular disease involves stimulation of the immune system using the whole pathogen responsible for the disease. In the post-genomic era, a major challenge is to identify antigenic regions or epitopes that can stimulate different arms of the immune system. In the past two decades, numerous methods and databases have been developed for designing vaccine or immunotherapy against various pathogen-causing diseases. This review describes various computational resources important for designing subunit vaccines or epitope-based immunotherapy. First, different immunological databases are described that maintain epitopes, antigens and vaccine targets. This is followed by in silico tools used for predicting linear and conformational B-cell epitopes required for activating humoral immunity. Finally, information on T-cell epitope prediction methods is provided that includes indirect methods like prediction of Major Histocompatibility Complex and transporter-associated protein binders. Different studies for validating the predicted epitopes are also examined critically. This review enlists novel in silico resources and tools available for predicting humoral and cell-mediated immune potential. These predicted epitopes could be used for designing epitope-based vaccines or immunotherapy as they may activate the adaptive immunity. Authors emphasized the need to develop tools for the prediction of adjuvants to activate innate and adaptive immune system simultaneously. In addition, attention has also been given to novel prediction methods to predict general therapeutic properties of peptides like half-life, cytotoxicity and immune toxicity.

Identification of Mycobacterium tuberculosis adherence-mediating components: a review of key methods to confirm adhesin function

Anti-adhesion therapy represents a potentially promising avenue for the treatment and prevention of tuberculosis in a post-antibiotic era. Adhesins are surface-exposed microbial structures or molecules that enable pathogenic organisms to adhere to host surfaces, a fundamental step towards host infection. Although several Mycobacterium tuberculosis adhesins have been identified, it is predicted that numerous additional adherence-mediating components contribute to the virulence and success of this pathogen. Significant further research to discern and characterize novel M. tuberculosis adhesins is, therefore, required to gain a holistic account of M. tuberculosis adhesion to the host. This would enable the identification of potential drug and vaccine targets for attenuating M. tuberculosis adherence and infectivity. Several methods have been successfully applied to the study and identification of M. tuberculosis adhesins. In this manuscript, we review these methods, which include adherence assays that utilize wild-type and gene knockout mutant strains, epitope masking and competitive inhibition analyses, extracellular matrix protein binding assays, microsphere adhesion assays, M. tuberculosis auto-aggregation assays, and in silico analyses.

A Web-Based Platform for Designing Vaccines against Existing and Emerging Strains of Mycobacterium tuberculosis

Development of an effective vaccine against drug-resistant Mycobacterium tuberculosis (Mtb) is crucial for saving millions of premature deaths every year due to tuberculosis. This paper describes a web portal developed for assisting researchers in designing vaccines against emerging Mtb strains using traditional and modern approaches. Firstly, we annotated 59 genomes of Mycobacterium species to understand similarity/dissimilarity between tuberculoid, non-tuberculoid and vaccine strains at genome level. Secondly, antigen-based vaccine candidates have been predicted in each Mtb strain. Thirdly, epitopes-based vaccine candidates were predicted/discovered in above antigen-based vaccine candidates that can stimulate all arms of immune system. Finally, a database of predicted vaccine candidates at epitopes as well at antigen level has been developed for above strains. In order to design vaccine against a newly sequenced genome of Mtb strain, server integrates three modules for identification of strain-, antigen-, epitope-specific vaccine candidates. We observed that 103522 unique peptides (9mers) had the potential to induce an antibody response and/or promiscuous binder to MHC alleles and/or have the capability to stimulate T lymphocytes. In summary, this web-portal will be useful for researchers working on designing vaccines against Mtb including drug-resistant strains. Availability: The database is available freely at http://crdd.osdd.net/raghava/mtbveb/.

Identification of Novel Potential Vaccine Candidates against Tuberculosis Based on Reverse Vaccinology

Tuberculosis (TB) is a chronic infectious disease, considered as the second leading cause of death worldwide, caused by Mycobacterium tuberculosis. The limited efficacy of the bacillus Calmette-Guérin (BCG) vaccine against pulmonary TB and the emergence of multidrug-resistant TB warrants the need for more efficacious vaccines. Reverse vaccinology uses the entire proteome of a pathogen to select the best vaccine antigens by in silico approaches. M. tuberculosis H37Rv proteome was analyzed with NERVE (New Enhanced Reverse Vaccinology Environment) prediction software to identify potential vaccine targets; these 331 proteins were further analyzed with VaxiJen for the determination of their antigenicity value. Only candidates with values ≥0.5 of antigenicity and 50% of adhesin probability and without homology with human proteins or transmembrane regions were selected, resulting in 73 antigens. These proteins were grouped by families in seven groups and analyzed by amino acid sequence alignments, selecting 16 representative proteins. For each candidate, a search of the literature and protein analysis with different bioinformatics tools, as well as a simulation of the immune response, was conducted. Finally, we selected six novel vaccine candidates, EsxL, PE26, PPE65, PE_PGRS49, PBP1, and Erp, from M. tuberculosis that can be used to improve or design new TB vaccines.