Desenvolvimento de uma vacina multiepítopo para a cólera e vibriose e o desenvolvimento de um software de imunoinformática para a construção de novos imunógenos: Vaxpipe

Abstract

The genus Vibrio, composed of Gram-negative and predominantly flagellated bacteria, inhabits coastal aquatic ecosystems such as estuaries and river mouths, where proliferation is favored by temperatures above 20 °C. While most species exhibit commensal behavior, some represent significant risks to human health, causing severe infections transmitted through the ingestion of contaminated water or seafood or through wound exposure to aquatic environments. These infections, termed vibriosis, range from self-limiting gastroenteritis to lethal systemic complications, including septicemia and necrotizing fasciitis, which may necessitate amputations. Vibrio cholerae stands out as the most prominent pathogen within the genus, responsible for cholera, an acute diarrheal disease endemic in regions with poor sanitation. The antigenic diversity and adaptive capacity of these pathogens demand innovative prophylactic strategies. Multiepitope vaccines consolidate the most conserved and immunogenic epitopes into a single immunogen, thereby ensuring broad population coverage against diverse pathogens and enhanced safety by obviating the use of whole inactivated pathogens or virulence‐associated proteins. This study proposes an integrated computational approach for the development of a multi-epitope vaccine against Vibrio, by using 29 complete genomes from 6 species from the genus and combining reverse vaccinology, which identifies candidate antigens from genomic data, with immunoinformatics to predict and recombine immunogenic epitopes. Six conserved antigenic proteins were identified, from which 28 epitopes were predicted: 24 exhibiting simultaneous recognition by cytotoxic T lymphocytes and B cells, and four recognized by helper T lymphocytes and B cells. These epitopes were integrated into a synthetic vaccine sequence, designated vme-VAC/MST-1, designed to display high antigenicity, physicochemical stability, and absence of toxicity or allergenicity in In silico analyses. Concurrently, the entire computational process was automated into a pipeline named Vaxpipe, developed in Python, with user-friendly interfaces accessible to non-bioinformaticians. This system integrates tools for predicting immunogenic epitopes, aiming to expedite the rational development of vaccines. The program initiates from selected vaccine targets, processes all epitopes, assembles the recombinant protein, predicts characteristics such as toxicity and allergenicity, and returns the sequence of the multi-epitope protein to the user. While In silico results are promising, experimental validations In vitro and In vivo are essential to confirm the efficacy of the proposed immunogen against the Vibrio genus, as well as all proteins generated by the Vaxpipe pipeline. This work not only advances the design of a broad-spectrum vaccine against vibriosis but also establishes a replicable protocol, implemented in robust and user-friendly software for application in similar approaches in complex pathogens.