Design and development of a multi‐epitope vaccine for the prevention of latent tuberculosis infection

Abstract

BackgroundLatent tuberculosis infection (LTBI) often progresses to active tuberculosis, necessitating the development of novel vaccine to prevent LTBI. In this study, we aimed to design a Mycobacterium tuberculosis (M. tuberculosis) vaccine that could elicit a potent immune response to prevent LTBI.MethodsWe used bioinformatics and immunoinformatics techniques to develop a multi‐epitope vaccine (MEV) called C624P. The vaccine contained six cytotoxic T lymphocytes (CTL), two helper T lymphocytes (HTL), and four B‐cell epitopes derived from six antigens associated with LTBI and the Mycobacterium tuberculosis region of difference. We added Toll‐like receptor (TLR) agonists and PADRE peptide to the MEV to enhance its immunogenicity. We then analyzed the C624P vaccine's physical and chemical properties, spatial structure, molecular docking with TLRs, and immunological features.ResultsThe C624P vaccine displayed good antigenicity and immunogenicity scores of 0.901398 and 3.65609, respectively. The vaccine structure was stable, with 42.82% α‐helix content, a Z‐value of −7.84, and a favored Ramachandran plot area of 85.84% after majorization. Molecular docking analysis showed that the C624P vaccine could bind tightly to TLR2 (−1011.0 kcal/mol) and TLR4 (−941.4 kcal/mol). Furthermore, the C624P vaccine effectively stimulated T and B lymphocytes, resulting in high levels of Th1 cytokines such as IFN‐γ and IL‐2.ConclusionsThe C624P vaccine represents a promising MEV for preventing LTBI. The vaccine's good antigenicity, immunogenicity, stability, and ability to activate immune responses suggest its effectiveness in preventing LTBI. Our study demonstrated the utility of bioinformatics and immunoinformatics techniques in designing safe and effective tuberculosis vaccines.

Construction of novel multi-epitope-based diagnostic biomarker HP16118P and its application in the differential diagnosis of Mycobacterium tuberculosis latent infection

“…5 b. These selected antigens allowed us to construct our novel LTBI diagnostic biomarkers by identifying dominant epitopes associated with HTL, CTL, and B cells [ 34 , 45 , 46 ]. Given epitopes’ inherent limitations in immunogenicity, we enhanced our biomarker with the TLR-2 agonist PSMα4 and helper epitopes HBD-3 and PADRE, augmenting their immunogenic potential and stability [ 47 – 51 ].…”

Immunoinformatics and structural aided approach to develop multi-epitope based subunit vaccine against Mycobacterium tuberculosis

“…Immunoinformatic approaches have been employed on several occasions to develop vaccines against a variety of pathogens that are currently in the late stages of their clinical development, such as Plasmodium falciparum 89 , Salmonella specie 90 , Streptococcus pyogene 91 , Brucella melitensis 92 , Candida tropicalis 93 , Staphylococcus aureus 94 , and Bacillus anthracis 95 . Similarly, using the immunoinformatics approach, numerous multi-epitope vaccines have been developed to target active 96 – 99 and latent TB 20 , 100 , 101 . Among these, one is DNA-based 98 , and another is a mRNA-based vaccine 99 .…”

“…In a recent study, Jiang et al performed an immunoinformatics analysis to develop a multi-epitope vaccine against Mtb . The investigation centered on the C624P vaccine, which holds promise as a latent tuberculosis infection (LTBI) preventive measure, showcasing commendable antigenicity, immunogenicity, stability, and the capacity to activate immune responses 20 . In contrast to most of the past research, which uses exosome vesicles or known antigenic proteins to identify epitopes, the current study aims to address the global demand for an effective TB vaccine by developing an in silico multi-epitope vaccine by integrating highly antigenic, non-allergenic and non-toxic epitopes from novel immunogenic proteins.…”