In a recent study published in Scientific Reports, a group of researchers designed and evaluated a multi-epitope vaccine targeting the main outer membrane protein (MOMP) protein of Chlamydia pneumoniae (C. pneumoniae; Cpn) using immunoinformatics.
They assessed the vaccine’s interaction with immune receptors and expressed it in silico on a baculovirus vector for potential protection against Cpn infections.
Background
Chlamydia is a class of prokaryotic microorganisms with distinct life stages that, especially the species Cpn, affects human health by causing respiratory to neurological issues.
Despite the increasing resistance to macrolides as treatment, there is no effective vaccine for Cpn. However, the MOMP shows promise because of its immunogenic properties, and the extracellular structure of cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) could potentially enhance the vaccine response.
Despite advancements in understanding Cpn’s pathogenesis and early-phase vaccine developments, further research is needed to delve deeper into multi-epitope vaccine strategies, assess resistance to existing treatments, and understand interactions with human immune receptors for comprehensive protection against Cpn infections.
About the study
The proteome sequences of Cpn were sourced from UniProt, while the human CTLA-4 amino acid sequence came from the National Center for Biotechnology Information (NCBI).
The SignalP 6.0 server was employed to predict the signal peptide of the major outer membrane protein, while the extracellular structure of CTLA-4 was analyzed using DeepTMHMM.
For epitope prediction, both BCPREDS and ABCpred tools were utilized for MOMP, with specific settings applied for epitope length and results. NetNHCIIpan and SYFPEITHI online software helped predict helper T lymphocyte (HTL) epitopes from selected proteins.
EpiJen and NetCTLpan were used to predict the cytotoxic T lymphocytes (CTL) epitope, while ElliPro was used for conformational epitope prediction.
For vaccine design, dominant epitopes were linked using Alanine-Tyrosine-Tyrosine
(AYY) and Lysine-Lysine (KK) linkers. The CTLA-4 extracellular structure was tethered to the cell epitope with a Glutamic Acid-Alanine-Alanine-Lysine (EAKK) linker. Tools such as ProtParam and VaxiJen assessed the vaccine’s properties.
The secondary structure of proteins was predicted using the Prabi server, and the vaccine’s tertiary structure was modeled with trRosetta, then refined using GalaxyRefine. Molecular docking was carried out with LZerD Web Server.
Molecular dynamics simulations were executed using GROMACS 2021.5. In the molecular dynamics simulation, principal component analysis (PCA) was carried out to determine the motion’s direction and magnitude using eigenvectors and eigenvalues, respectively.
Using Gromacs 2021.5, this PCA was applied to complexes formed by multi-epitope vaccines with Toll-Like Receptor-2 (TLR-2), and TLR-4, B7-1, B7-2, projecting the results onto two dimensions.
Finally, for in silico cloning, back translation of the vaccine sequences used SMS2 Nanjing Tate Sacrament Mirror and the optimized sequence was integrated into the pFastBac1 vector using the SnapGene tool.
Study results
The researchers obtained the amino acid sequences for the MOMP and CTLA-4 protein from the NCBI database. Using the SignalP 6.0 Server software, they found that the MOMP protein exhibited a signal peptide between amino acids 23–24, indicating potential secretion to different cells. Furthermore, analysis using DeepTMHMM-2.0 software indicated that the extracellular structural domain of human CTLA-4 spanned amino acids 38–165.
To bolster prediction accuracy, both BCPREDS and ABCpred were employed to anticipate B-cell linear epitopes of the MOMP protein, resulting in the discernment of four such epitopes. CTL and T-cell epitopes of the MOMP protein were subsequently predicted using various software, and selected sequences were highlighted as dominant epitopes.
In the quest to design a multi-epitope vaccine, the team capitalized on the known immune-enhancing properties of the extracellular structure of CTLA-4. By combining this with the dominant MOMP epitopes previously identified, a vaccine blueprint was developed.
This vaccine, broken down into four key components, was connected via specific links to ensure stability and efficacy. Biochemical property analysis using ProtParam indicated that the formulated vaccine, comprising 289 amino acids, was both stable and appropriate for development. Additionally, the vaccine’s antigenicity was confirmed, and its non-allergenic nature was established.
The vaccine’s secondary structure, as predicted by the Prabi server, revealed specific percentages of alpha helixes, extended strands, beta-turns, and random coils. The vaccine’s tertiary structure was established using the Yanglab online software, and subsequent refinements were made with GalaxyRefine software.
To ensure the accuracy of the vaccine’s tertiary structure, validation processes were conducted using ProSA-Web and SWISS-MODEL online software. Both validation processes presented favorable results.
Molecular docking of the vaccine to specific receptors was undertaken using the LZerD Web Server. Following docking, molecular dynamics simulations using Gromacs 2021.5 were conducted on the constructed vaccines to understand their stability when interacting with certain proteins. Results from these simulations affirmed the stability and flexibility of the vaccine complexes with targeted proteins.
PCA was then performed using GROMACS 2021.5 to ascertain conformational differences between the vaccine complexes. Notably, the TLR-4 system exhibited a wider first principal component (PC1) range, suggesting it had comparatively weaker stability.
Lastly, for in silico cloning, the SMS2 Nanjing Tide BioMirror software was utilized for reverse translation of the vaccine structures. After codon optimization, the proposed gene sequence was integrated into the pFastBac1 vector using SnapGene software.
The analysis suggests that this vaccine construct should express efficiently within the pFastBac1 vector.
