Pathogen proteins eliciting antibodies do not share epitopes with host proteins: a bioinformatics approach

Antigenic and conserved peptides from diverse Helicobacter pylori antigens

Since the revolutionary finding of Helicobacter pylori as a common bacterial infection, that a high research effort for its eradication has been conducted. Epitope based-vaccine presents advantages over protein-based, as they can be designed to contain epitopes from diverse proteins, therefore, more easily representing the immune-variability of the bacterial population, while minimizing the toxicity associated to some whole proteins. In the present work, an iterative method, to design antigenic and conserved B-epitopes from diverse virulent factors of H. pylori, was established. The method considered the trade-off between epitopes antigenicity and conservation among the bacterial population. For the method validation, five virulent factors from H. pylori were selected. From each virulent factor, two epitopes were predicted, each with twelve residues of aminoacids. The corresponding ten peptides were synthesised and evaluated by enzyme-linked immunosorbent assay using polyclonal antibodies raised against a specific H. pylori strain. All ten peptides were recognised by the antibodies and were consequently antigenic and conserved. This result could strongly contribute to the design of a multivalent epitope-based vaccine, representing the immunogenetic variability within the bacterial population, leading to a sustained and effective immunogenic protection.

A systematic bioinformatics approach for large-scale identification and characterization of host-pathogen shared sequences

Background

Biology has entered the era of big data with the advent of high-throughput omics technologies. Biological databases provide public access to petabytes of data and information facilitating knowledge discovery. Over the years, sequence data of pathogens has seen a large increase in the number of records, given the relatively small genome size and their important role as infectious and symbiotic agents. Humans are host to numerous pathogenic diseases, such as that by viruses, many of which are responsible for high mortality and morbidity. The interaction between pathogens and humans over the evolutionary history has resulted in sharing of sequences, with important biological and evolutionary implications.

Results

This study describes a large-scale, systematic bioinformatics approach for identification and characterization of shared sequences between the host and pathogen. An application of the approach is demonstrated through identification and characterization of the Flaviviridae-human share-ome. A total of 2430 nonamers represented the Flaviviridae-human share-ome with 100% identity. Although the share-ome represented a small fraction of the repertoire of Flaviviridae (~ 0.12%) and human (~ 0.013%) non-redundant nonamers, the 2430 shared nonamers mapped to 16,946 Flaviviridae and 7506 human non-redundant protein sequences. The shared nonamer sequences mapped to 125 species of Flaviviridae, including several with unclassified genus. The majority (~ 68%) of the shared sequences mapped to Hepacivirus C species; West Nile, dengue and Zika viruses of the Flavivirus genus accounted for ~ 11%, ~ 7%, and ~ 3%, respectively, of the Flaviviridae protein sequences (16,946) mapped by the share-ome. Further characterization of the share-ome provided important structural-functional insights to Flaviviridae-human interactions.

Conclusion

Mapping of the host-pathogen share-ome has important implications for the design of vaccines and drugs, diagnostics, disease surveillance and the discovery of unknown, potential host-pathogen interactions. The generic workflow presented herein is potentially applicable to a variety of pathogens, such as of viral, bacterial or parasitic origin.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07657-4.

Peptides of H. sapiens and P. falciparum that are predicted to bind strongly to HLA-A*24:02 and homologous to a SARS-CoV-2 peptide

AIM

This study is looking for a common pathogenicity between SARS-CoV-2 and Plasmodium species, in individuals with certain HLA serotypes.

METHODS

1. Tblastx searches of SARS-CoV-2 are performed by limiting searches to five Plasmodium species that infect humans. 2. Aligned sequences in the respective organisms' proteomes are searched with blastp. 3. Binding predictions of the identified SARS-CoV-2 peptide to HLA supertype representatives are performed. 4. Blastp searches of predicted epitopes that bind strongly to the identified HLA allele are performed by limiting searches to H. sapiens and Plasmodium species, separately. 5. Peptides with minimum 60% identity to the predicted epitopes are found in results. 6. Peptides among those, which bind strongly to the same HLA allele, are predicted. 7. Step-4 is repeated by limiting searches to H. sapiens, followed by the remaining steps until step-7, for peptides sourced by Plasmodium species after step-6.

RESULTS

SARS-CoV-2 peptide with single letter amino acid code CFLGYFCTCYFGLFC has the highest identity to P. vivax. Its YFCTCYFGLF part is predicted to bind strongly to HLA-A*24:02. Peptides in the human proteome both homologous to YFCTCYFGLF and with a strong binding affinity to HLA-A*24:02 are YYCARRFGLF, YYCHCPFGVF, and YYCQQYFFLF. Such peptides in the Plasmodium species' proteomes are FFYTFYFELF, YFVACLFILF, and YFPTITFHLF. The first one belonging to P. falciparum has a homologous peptide (YFYLFSLELF) in the human proteome, which also has a strong binding affinity to the same HLA allele.

CONCLUSION

Immune responses to the identified-peptides with similar sequences and strong binding affinities to HLA-A*24:02 can be related to autoimmune response risk in individuals with HLA-A*24:02 serotypes, upon getting infected with SARS-CoV-2 or P. falciparum.

Pathogen Moonlighting Proteins: From Ancestral Key Metabolic Enzymes to Virulence Factors

Moonlighting and multitasking proteins refer to proteins with two or more functions performed by a single polypeptide chain. An amazing example of the Gain of Function (GoF) phenomenon of these proteins is that 25% of the moonlighting functions of our Multitasking Proteins Database (MultitaskProtDB-II) are related to pathogen virulence activity. Moreover, they usually have a canonical function belonging to highly conserved ancestral key functions, and their moonlighting functions are often involved in inducing extracellular matrix (ECM) protein remodeling. There are three main questions in the context of moonlighting proteins in pathogen virulence: (A) Why are a high percentage of pathogen moonlighting proteins involved in virulence? (B) Why do most of the canonical functions of these moonlighting proteins belong to primary metabolism? Moreover, why are they common in many pathogen species? (C) How are these different protein sequences and structures able to bind the same set of host ECM protein targets, mainly plasminogen (PLG), and colonize host tissues? By means of an extensive bioinformatics analysis, we suggest answers and approaches to these questions. There are three main ideas derived from the work: first, moonlighting proteins are not good candidates for vaccines. Second, several motifs that might be important in the adhesion to the ECM were identified. Third, an overrepresentation of GO codes related with virulence in moonlighting proteins were seen.

Moonlighting Proteins: The Case of the Hexokinases

Moonlighting proteins are defined as proteins with two or more functions that are unrelated and independent to each other, so that inactivation of one of them should not affect the second one and vice versa. Intriguingly, all the glycolytic enzymes are described as moonlighting proteins in some organisms. Hexokinase (HXK) is a critical enzyme in the glycolytic pathway and displays a wide range of functions in different organisms such as fungi, parasites, mammals, and plants. This review discusses HXKs moonlighting functions in depth since they have a profound impact on the responses to nutritional, environmental, and disease challenges. HXKs’ activities can be as diverse as performing metabolic activities, as a gene repressor complexing with other proteins, as protein kinase, as immune receptor and regulating processes like autophagy, programmed cell death or immune system responses. However, most of those functions are particular for some organisms while the most common moonlighting HXK function in several kingdoms is being a glucose sensor. In this review, we also analyze how different regulation mechanisms cause HXK to change its subcellular localization, oligomeric or conformational state, the response to substrate and product concentration, and its interactions with membrane, proteins, or RNA, all of which might impact the HXK moonlighting functions.

In silico T cell epitope identification for SARS-CoV-2: Progress and perspectives

Growing evidence suggests that T cells may play a critical role in combating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Hence, COVID-19 vaccines that can elicit a robust T cell response may be particularly important. The design, development and experimental evaluation of such vaccines is aided by an understanding of the landscape of T cell epitopes of SARS-CoV-2, which is largely unknown. Due to the challenges of identifying epitopes experimentally, many studies have proposed the use of in silico methods. Here, we present a review of the in silico methods that have been used for the prediction of SARS-CoV-2 T cell epitopes. These methods employ a diverse set of technical approaches, often rooted in machine learning. A performance comparison is provided based on the ability to identify a specific set of immunogenic epitopes that have been determined experimentally to be targeted by T cells in convalescent COVID-19 patients, shedding light on the relative performance merits of the different approaches adopted by the in silico studies. The review also puts forward perspectives for future research directions.

Genome-wide analysis of 10664 SARS-CoV-2 genomes to identify virus strains in 73 countries based on single nucleotide polymorphism

Since the onslaught of SARS-CoV-2, the research community has been searching for a vaccine to fight against this virus. However, during this period, the virus has mutated to adapt to the different environmental conditions in the world and made the task of vaccine design more challenging. In this situation, the identification of virus strains is very much timely and important task. We have performed genome-wide analysis of 10664 SARS-CoV-2 genomes of 73 countries to identify and prepare a Single Nucleotide Polymorphism (SNP) dataset of SARS-CoV-2. Thereafter, with the use of this SNP data, the advantage of hierarchical clustering is taken care of in such a way so that Average Linkage and Complete Linkage with Jaccard and Hamming distance functions are applied separately in order to identify the virus strains as clusters present in the SNP data. In this regard, the consensus of both the clustering results are also considered while Silhouette index is used as a cluster validity index to measure the goodness of the clusters as well to determine the number of clusters or virus strains. As a result, we have identified five major clusters or virus strains present worldwide. Apart from quantitative measures, these clusters are also visualized using Visual Assessment of Tendency (VAT) plot. The evolution of these clusters are also shown. Furthermore, top 10 signature SNPs are identified in each cluster and the non-synonymous signature SNPs are visualised in the respective protein structures. Also, the sequence and structural homology-based prediction along with the protein structural stability of these non-synonymous signature SNPs are reported in order to judge the characteristics of the identified clusters. As a consequence, T85I, Q57H and R203M in NSP2, ORF3a and Nucleocapsid respectively are found to be responsible for Cluster 1 as they are damaging and unstable non-synonymous signature SNPs. Similarly, F506L and S507C in Exon are responsible for both Clusters 3 and 4 while Clusters 2 and 5 do not exhibit such behaviour due to the absence of any non-synonymous signature SNPs. In addition to all these, the code, SNP dataset, 10664 labelled SARS-CoV-2 strains and additional results as supplementary are provided through our website for further use.

Moonlighting Proteins at the Candidal Cell Surface

The cell wall in Candida albicans is not only a tight protective envelope but also a point of contact with the human host that provides a dynamic response to the constantly changing environment in infection niches. Particularly important roles are attributed to proteins exposed at the fungal cell surface. These include proteins that are stably and covalently bound to the cell wall or cell membrane and those that are more loosely attached. Interestingly in this regard, numerous loosely attached proteins belong to the class of “moonlighting proteins” that are originally intracellular and that perform essentially different functions in addition to their primary housekeeping roles. These proteins also demonstrate unpredicted interactions with non-canonical partners at an a priori unexpected extracellular location, achieved via non-classical secretion routes. Acting both individually and collectively, the moonlighting proteins contribute to candidal virulence and pathogenicity through their involvement in mechanisms critical for successful host colonization and infection, such as the adhesion to host cells, interactions with plasma homeostatic proteolytic cascades, responses to stress conditions and molecular mimicry. The documented knowledge of the roles of these proteins in C. albicans pathogenicity has utility for assisting the design of new therapeutic, diagnostic and preventive strategies against candidiasis.

A hypothesis explaining why so many pathogen virulence proteins are moonlighting proteins

Moonlighting or multitasking proteins refer to those proteins with two or more functions performed by a single polypeptide chain. Proteins that belong to key ancestral functions and metabolic pathways such as primary metabolism typically exhibit moonlighting phenomenon. We have collected 698 moonlighting proteins in MultitaskProtDB-II database. A survey shows that 25% of the proteins of the database correspond to moonlighting functions related to pathogens virulence activity. Why is the canonical function of these virulence proteins mainly from ancestral key biological functions (especially of primary metabolism)? Our hypothesis is that these proteins present a high conservation between the pathogen protein and the host counterparts. Therefore, the host immune system will not elicit protective antibodies against pathogen proteins. The fact of sharing epitopes with host proteins (known as epitope mimicry) might be the cause of autoimmune diseases. Although many pathogen proteins can be antigenic, only a few of them would elicit a protective immune response. This would also explain the lack of successful vaccines based in these conserved moonlighting proteins.

Identification of drug resistance and immune-driven variations in hepatitis C virus (HCV) NS3/4A, NS5A and NS5B regions reveals a new approach toward personalized medicine

Cellular immune responses (T cell responses) during hepatitis C virus (HCV) infection are significant factors for determining the outcome of infection. HCV adapts to host immune responses by inducing mutations in its genome at specific sites that are important for HLA processing/presentation. Moreover, HCV also adapts to resist potential drugs that are used to restrict its replication, such as direct-acting antivirals (DAAs). Although DAAs have significantly reduced disease burden, resistance to these drugs is still a challenge for the treatment of HCV infection. Recently, drug resistance mutations (DRMs) observed in HCV proteins (NS3/4A, NS5A and NS5B) have heightened concern that the emergence of drug resistance may compromise the effectiveness of DAAs. Therefore, the NS3/4A, NS5A and NS5B drug resistance variations were investigated in this study, and their prevalence was examined in a large number of protein sequences from all HCV genotypes. Furthermore, potential CD4+ and CD8+ T cell epitopes were predicted and their overlap with genetic variations was explored. The findings revealed that many reported DRMs within NS3/4A, NS5A and NS5B are not drug-induced; rather, they are already present in HCV strains, as they were also detected in HCV-naïve patients. This study highlights several hot spots in which HLA and drug selective pressure overlap. Interestingly, these overlapping mutations were frequently observed among many HCV genotypes. This study implicates that knowledge of the host HLA type and HCV subtype/genotype can provide important information in defining personalized therapy.

Developing a vaccine to prevent otitis media caused by nontypeable Haemophilus influenzae

Nontypeable Haemophilus influenzae (NTHi) is a predominant organism of the upper respiratory nasopharyngeal microbiota. Its disease spectrum includes otitis media, sinusitis, non-bacteremic pneumonia and invasive infections. Protein-based vaccines to prevent NTHi infections are needed to alleviate these infections in children and vulnerable populations such as the elderly and those with chronic obstructive pulmonary disease (COPD). One NTHi protein is included in a pneumococcal conjugate vaccine and has been shown to provide efficacy. Our lab has been interested in understanding the immunogenicity of NTHi vaccine candidates P6, protein D and OMP26 for preventing acute otitis media in young children. We expect that continued investigation and progress in the development of an efficacious protein based vaccine against NTHi infections is achievable in the near future.

A review of reverse vaccinology approaches for the development of vaccines against ticks and tick borne diseases

The field of reverse vaccinology developed as an outcome of the genome sequence revolution. Following the introduction of live vaccinations in the western world by Edward Jenner in 1798 and the coining of the phrase 'vaccine', in 1881 Pasteur developed a rational design for vaccines. Pasteur proposed that in order to make a vaccine that one should 'isolate, inactivate and inject the microorganism' and these basic rules of vaccinology were largely followed for the next 100 years leading to the elimination of several highly infectious diseases. However, new technologies were needed to conquer many pathogens which could not be eliminated using these traditional technologies. Thus increasingly, computers were used to mine genome sequences to rationally design recombinant vaccines. Several vaccines for bacterial and viral diseases (i.e. meningococcus and HIV) have been developed, however the on-going challenge for parasite vaccines has been due to their comparatively larger genomes. Understanding the immune response is important in reverse vaccinology studies as this knowledge will influence how the genome mining is to be conducted. Vaccine candidates for anaplasmosis, cowdriosis, theileriosis, leishmaniasis, malaria, schistosomiasis, and the cattle tick have been identified using reverse vaccinology approaches. Some challenges for parasite vaccine development include the ability to address antigenic variability as well the understanding of the complex interplay between antibody, mucosal and/or T cell immune responses. To understand the complex parasite interactions with the livestock host, there is the limitation where algorithms for epitope mining using the human genome cannot directly be adapted for bovine, for example the prediction of peptide binding to major histocompatibility complex motifs. As the number of genomes for both hosts and parasites increase, the development of new algorithms for pan-genomic mining will continue to impact the future of parasite and ricketsial (and other tick borne pathogens) disease vaccine development.

Prediction of Antigenic B and T Cell Epitopes via Energy Decomposition Analysis: Description of the Web-Based Prediction Tool BEPPE

Unraveling the molecular basis of immune recognition still represents a challenging task for current biological sciences, both in terms of theoretical knowledge and practical implications. Here, we describe the physical-chemistry methods and computational protocols for the prediction of antibody-binding epitopes and MHC-II loaded epitopes, starting from the atomic coordinates of antigenic proteins (PDB file). These concepts are the base of the Web tool BEPPE (Binding Epitope Prediction from Protein Energetics), a free service that returns a list of putative epitope sequences and related blast searches against the Uniprot human complete proteome. BEPPE can be employed for the study of the biophysical processes at the basis of the immune recognition, as well as for immunological purposes such as the rational design of biomarkers and targets for diagnostics, therapeutics, and vaccine discovery.

Homology, similarity, and identity in peptide epitope immunodefinition

The tendency to use the terms homology, similarity, and identity interchangeably persists in comparative biology. When translated to immunology, overlapping the concepts of homology, similarity, and identity complicates the exact definition of the self-nonself dichotomy and, in particular, affects immunopeptidomics, an emerging field aimed at cataloging and distinguishing immunoreactive peptide epitopes from silent nonreactive amino acid sequences. The definition of similar/dissimilar peptides in immunology is discussed with special attention to the analysis of immunological (dis)similarity between two or more protein sequences that equates to measuring sequence similarity with the use of a proper measurement unit such as a length determinant.

Comparing the similarity of different groups of bacteria to the human proteome

Numerous aspects of the relationship between bacteria and human have been investigated. One aspect that has recently received attention is sequence overlap at the proteomic level. However, there has not yet been a study that comprehensively characterizes the level of sequence overlap between bacteria and human, especially as it relates to bacterial characteristics like pathogenicity, G-C content, and proteome size. In this study, we began by performing a general characterization of the range of bacteria-human similarity at the proteomic level, and identified characteristics of the most- and least-similar bacterial species. We then examined the relationship between proteomic similarity and numerous other variables. While pathogens and nonpathogens had comparable similarity to the human proteome, pathogens causing chronic infections were found to be more similar to the human proteome than those causing acute infections. Although no general correspondence between a bacterium’s proteome size and its similarity to the human proteome was noted, no bacteria with small proteomes had high similarity to the human proteome. Finally, we discovered an interesting relationship between similarity and a bacterium’s G-C content. While the relationship between bacteria and human has been studied from many angles, their proteomic similarity still needs to be examined in more detail. This paper sheds further light on this relationship, particularly with respect to immunity and pathogenicity.

In silico identification of potential antigenic proteins and promiscuous CTL epitopes in Mycobacterium tuberculosis

Cell-mediated immunity is critical for the control of Mycobacterium tuberculosis infection. We hypothesized that those proteins of M. tuberculosis (MTB) that do not have homologs in humans as well as human gut flora, would mount a good antigenic response in man, and employed a bioinformatics approach to identify MTB antigens capable of inducing a robust cell-mediated immune response in humans. In the first step we identified 624 MTB proteins that had no homologs in humans. Comparison of this set of proteins with the proteome of 77 different microbes that comprise the human gut flora narrowed down the list to 180 proteins unique to MTB. Twenty nine of the 180 proteins are known to be associated with dormancy. Since dormancy associated proteins are known to harbor CTL epitopes, we selected four representative unique proteins and subjected them to epitope analysis using ProPred1. Nineteen novel promiscuous epitopes were identified in the four proteins. Population coverage for 7 of the 19 shortlisted epitopes including Rv3852 (58-KPAEAPVSL, 112-VPLIVAVTL, 118-VTLSLLALL and 123-LALLLIRQL), Rv2706c (66-RPLSGVSFL) Rv3466 (8- RIVEVFDAL and 38-RSLERLECL) was >74%. These novel promiscuous epitopes are conserved in other virulent MTB strains, and can therefore be further investigated for their immunological relevance and usefulness as vaccine candidates.

Limitations to the structure-based design of HIV-1 vaccine immunogens

In spite of 25 years of intensive research, no effective human immunodeficiency virus type 1 (HIV-1) vaccine has yet been developed. One reason for this is that investigators have concentrated mainly on the structural analysis of HIV-1 antigens because they assumed that it should be possible to deduce vaccine-relevant immunogens from the structure of viral antigens bound to neutralizing monoclonal antibodies. This unwarranted assumption arises from misconceptions regarding the nature of protein epitopes and from the belief that it is justified to extrapolate from the antigenicity to the immunogenicity of proteins. Although the structure of the major HIV-1 antigenic sites has been elucidated, this knowledge has been of little use for designing an HIV-1 vaccine. Little attention has been given to the fact that protective immune responses tend to be polyclonal and involve antibodies directed to several different epitopes. It is concluded that only trial and error, empirical investigations using numerous immunization protocols may eventually allow us to identify which mixtures of immunogens are likely to be the best candidates for an HIV-1 vaccine.

Identification and characterization of nematode specific protective epitopes of Brugia malayi TRX towards development of synthetic vaccine construct for lymphatic filariasis

Although multi-epitope vaccines have been evaluated for various diseases, they have not yet been investigated for lymphatic filariasis. Here, we report for the first time identification of two immunodominant B epitopes (TRXP1 and TRXP2) from the antioxidant Brugia malayi thioredoxin by studying their immune responses in mice model and human subjects. TRXP1 was also found to harbor a T epitope recognized by human PBMCs and mice splenocytes. Further, the epitopic peptides were synthesized as a single peptide conjugate (PC1) and their prophylactic efficacy was tested in a murine model of filariasis with L3 larvae. PC1 conferred a significantly high protection (75.14%) (P < 0.0001) compared to control (3.7%) and recombinant TRX (63.03%) (P < 0.018) in experimental filariasis. Our results suggest that multi-epitope vaccines could be a promising strategy in the control of lymphatic filariasis.

The key role of genomics in modern vaccine and drug design for emerging infectious diseases

It can be argued that the arrival of the “genomics era” has significantly shifted the paradigm of vaccine and therapeutics development from microbiological to sequence-based approaches. Genome sequences provide a previously unattainable route to investigate the mechanisms that underpin pathogenesis. Genomics, transcriptomics, metabolomics, structural genomics, proteomics, and immunomics are being exploited to perfect the identification of targets, to design new vaccines and drugs, and to predict their effects in patients. Furthermore, human genomics and related studies are providing insights into aspects of host biology that are important in infectious disease. This ever-growing body of genomic data and new genome-based approaches will play a critical role in the future to enable timely development of vaccines and therapeutics to control emerging infectious diseases.

Bioinformatics annotation of the hypothetical proteins found by omics techniques can help to disclose additional virulence factors

The advent of genomics should have facilitated the identification of microbial virulence factors, a key objective for vaccine design. When the bacterial pathogen infects the host it expresses a set of genes, a number of them being virulence factors. Among the genes identified by techniques as microarrays, in vivo expression technology, signature-tagged mutagenesis and differential fluorescence induction there are many related to cellular stress, basal metabolism, etc., which cannot be directly involved in virulence, or at least cannot be considered useful candidates to be deleted for designing a live attenuated vaccine. Among the genes disclosed by these methodologies there are a number of hypothetical or unknown proteins. As they can hide some true virulence factors, we have reannotated all of these hypothetical proteins from several respiratory pathogens by a careful and in-depth analysis of each one. Although some of the re-annotations match with functions that can be related to microbial virulence, the identification of virulence factors remains difficult.

Rare peptide segments are found significantly more often in proto-oncoproteins than control proteins: implications for immunology and oncology

There is some evidence to suggest that peptide segments that are found rarely or never in the host proteome play a role in the immune response to disease-related proteins, both those derived from microbes and those derived from the host itself. We conjecture that this pattern may extend to human proto-oncoproteins. Our hypothesis in this study is that the frequency of rare peptide segments in sets of human proto-oncoproteins is significantly higher than in sets of control proteins, and we show that this is the case. Possible immunological implications of this observation are discussed.