EpitoCore: Mining Conserved Epitope Vaccine Candidates in the Core Proteome of Multiple Bacteria Strains

Abstract

In reverse vaccinology approaches, complete proteomes of bacteria are submitted to multiple computational prediction steps in order to filter proteins that are possible vaccine candidates. Most available tools perform such analysis only in a single strain, or a very limited number of strains. But the vast amount of genomic data had shown that most bacteria contain pangenomes, i.e., their genomic information contains core, conserved genes, and random accessory genes specific to each strain. Therefore, in reverse vaccinology methods it is of the utmost importance to define core proteins and core epitopes. EpitoCore is a decision-tree pipeline developed to fulfill that need. It provides surfaceome prediction of proteins from related strains, defines core proteins within those, calculate their immunogenicity, predicts epitopes for a given set of MHC alleles defined by the user, and then reports if epitopes are located extracellularly and if they are conserved among the core homologs. Pipeline performance is illustrated by mining peptide vaccine candidates in Mycobacterium avium hominissuis strains. From a total proteome of ~4,800 proteins per strain, EpitoCore predicted 103 highly immunogenic core homologs located at cell surface, many of those related to virulence and drug resistance. Conserved epitopes identified among these homologs allows the users to define sets of peptides with potential to immunize the largest coverage of tested HLA alleles using peptide-based vaccines. Therefore, EpitoCore is able to provide automated identification of conserved epitopes in bacterial pangenomic datasets.

Keywords: bioinformatics; epitope prediction; pangenome; prokaryotes; reverse vaccinology; vaccine candidates.

Figure 1

EpitoCore decision tree. Briefly, users retrieve fasta files for organism of interest, and perform transmembrane (TMHMM) and cellular localization (PSORT-B) predictions separately. TMHMM output is further divided into proteins with helix outside or not of the signal sequence. Homologs within surfaceome predictions are clustered with CMG Biotools. Core clusters had their epitopes ranked by IEDB, and that output is aligned to protein topology. Conserved epitopes in all strains are then reported. Numbers 1–7 in workflow show location where each in house script is called.

Figure 2

Distribution of homologs within clusters for TMHMM dataset. Proteins with membrane helix outside the signal peptide were clustered, and cluster composition was quantified. Majority of the clusters had, as expected, at least seven proteins, one from each of the analyzed strains, defining the core group. Clusters with six or less components are in principle defined as accessory proteins from the pangenome. Only core proteins were considered for immunogenic analysis.

Figure 3

True core proteins with discrepant surfaceome prediction. To evaluate if clustering could be biased when performed on a smaller dataset, we also executed CMG Biotools in the whole proteome dataset of all strains. Protein composition for most groups was identical regardless if clustering was performed before or after surfaceome prediction (zero missing proteins when clusters are compared) (A). For core proteins (column 7), 98% of the protein groups were identical. For accessory proteins (groups 1–6), this was closer to 55%. When hiding identical clusters (B), it is evident that for most accessory clusters, the number of missing elements adds to the exact number of strains used. This illustrates protein groups with 7 components if no prediction is performed, i.e., true core proteins.

Figure 4

Immunogenicity Scores for TMHMM dataset and definition of valid epitopes. (A) All sequences within each cluster were submitted to MHC II immunogenicity scoring, to all tested alleles. Sequences with percentile score lower than 0.05 were selected. Cluster immunogenicity is given by the mean distribution of all scored epitopes under this value, for all proteins. Highly immunogenic clusters were defined as those with a mean score lower than 0.02 (black dots). (B) Example of a homolog from cluster 71 (Cytochrome c subunit III protein). Immunogenicity prediction defined four regions of this protein to contain possible epitopes (Before panel, in pink). As shown in the figure, three of those regions are within the transmembrane domain. Protein topology alignment allowed the removal of such regions, which were then considered invalid epitopes (After panel). (C) Valid epitopes were then checked if they are conserved within all homologs of its cluster. Most clusters contained conserved identical epitopes in all homologs (count 7, pink). Epitopes present in 5 or less components of the cluster were not considered for further analysis.