Design of a Multi-Epitope Vaccine against Histoplasma capsulatum through Immunoinformatics Approaches

Abstract

Histoplasmosis is a widespread systemic disease caused by Histoplasma capsulatum, prevalent in the Americas. Despite its significant morbidity and mortality rates, no vaccines are currently available. Previously, five vaccine targets and specific epitopes for H. capsulatum were identified. Immunoinformatics has emerged as a novel approach for determining the main immunogenic components of antigens through in silico methods. Therefore, we predicted the main helper and cytotoxic T lymphocytes and B-cell epitopes for these targets to create a potential multi-epitope vaccine known as HistoVAC-TSFM. A total of 38 epitopes were found: 23 common to CTL and B-cell responses, 11 linked to HTL and B cells, and 4 previously validated epitopes associated with the B subunit of cholera toxin, a potent adjuvant. In silico evaluations confirmed the stability, non-toxicity, non-allergenicity, and non-homology of these vaccines with the host. Notably, the vaccine exhibited the potential to trigger both innate and adaptive immune responses, likely involving the TLR4 pathway, as supported by 3D modeling and molecular docking. The designed HistoVAC-TSFM appears promising against Histoplasma, with the ability to induce important cytokines, such as IFN-γ, TNF-α, IL17, and IL6. Future studies could be carried out to test the vaccine's efficacy in in vivo models.

Keywords: epizootic lymphangitis; fungi vaccine; histoplasmosis; immunoinformatic; multi-epitope.

Figure 1

Step-by-step prediction, filtering, and overlapping of epitopes by IEDB and ABCpred tools. In the end, 23 MHCI and 11 MHCII epitopes were selected.

Figure 2

Assembly of the final sequence of the multi-epitope vaccine and adjuvant. The EAAAK linker appears between adjuvant and multi-epitope sequences, while MHCI and MHCII epitopes have AAY GPGPG peptides as linkers.

Figure 3

Secondary and tertiary structures of the multi-epitope vaccine. On the left side (number 1), there is the structure of the protein predicted by ColabFold, as well as the corresponding Ramachandran plot. On the right side (number 2), there is the structure of the protein refined by GalaxyRefiner and its Ramachandran plot. Below is the secondary structure predicted by PsiPred.

Figure 4

Visualization of protein–protein docking. At the top, there is the docking visualized by the Chimera tool (vaccine in red and TLR4 in blue), and the contact regions by PDBepisa (vaccine in light blue and TLR4 in dark blue), respectively. Below are the interactions using the Ligplot tool.

Figure 5

In silico immune response simulation results by C-ImmSim for the adjuvant-linked vaccine. (A) a simulation of the production of immunoglobulins such as IgG and IgM, (B) the population of B cells, (C) the population of B cells by state (active or not), (D) the production of PLB cells, (E) the production of cytokines. In the graphs at the bottom of the figure, (F) shows the population of TH cells, (G) shows TH cells by state (active or not), (H) shows the population of Treg cells, and (I,J) show the population and state of cytotoxic T cells.

Figure 6

In silico immune response simulation results by C-ImmSim only for the multi-epitope vaccine. The analysis was carried out in the same order as in Figure 5. (A–D) represent the responses associated with B cells; (E) shows the graph of cytokine production; (F,G) represent TH cells; (H) shows the diagram of Treg cell populations; and (I,J) represent populations and states of cytotoxic T cells.

Figure 7

Prediction of MHCI epitopes using IEDB tools for canine alleles. Ten MHCI epitopes for humans are coincidentally excellent epitopes for canine alleles.

Figure 8

The insertion of the HistoVAC-TSFM sequence is present in red using the BamHI and BlpI restriction enzymes.