In silico approaches to design multi-epitope vaccines and uncover potential drug targets against Corynebacterium diphtheriae and Clostridioides difficile

• Autor(a) principal: Mariana Passos Santana
• Data de Publicação: 2019
• Tipo de documento: Tese
• Idioma: eng
• Título da fonte: Repositório Institucional da UFMG
• Texto Completo: http://hdl.handle.net/1843/33916
• topic: Clostridioides difficile; Corynebacterium diftheriae; immunoinformatics; reverse vaccinology; subtractive genomics; multidrug resistance; Genômica; Imunização; Vacinologia; Corynebacterium diphtheriae; Clostridium difficile; Resistência a Múltiplos Medicamentos

Immunization is a crucial strategy to prevent the dissemination of pathogens without aggravating resistance. The society is facing an unprecedented hazard due to the exacerbate use of antimicrobials that accelerated the overall antimicrobial resistant problematic that utterly leads to an increase in the cost within the health system. Furthermore, the continuous outbreaks of previously controlled pathogens can be linked with a low immunization coverage due to conventional vaccines drawbacks and socioeconomic difficulties. The use of cutting-edge technology may resolute many of those problems in a customized and cost-effective way. Among the bacterial pathogens that present a high morbidity and mortality rates, we highlight two crucial pathogens: Corynebacterium diphtheriae and Clostridioides difficile, the causative agents of diphtheria and C. difficile infections (CDI) (e.g. diarrhea to pseudomembrane colitis). Diphtheria was considered the main cause of child mortality but the development of the diphtheria vaccine, which is based in an inactivated form of the diphtheria toxin, significantly decrease the number of cases. However, this disease continuous to be a problem, especially considering the emergence of variants of non-toxigenic C. diphtheriae and multidrug resistant strains. Likewise, the occurrence of C. difficile multidrug resistance strains became an issue since it became more challenging to treat the disease. CDI recommended treatment is based on specific antibiotics that possible, in a near future, may became obsolete due to the high capacity of the bacterium to adapt to the surrounding environment (variable genome due to the presence of mobile elements). Therefore, the design of innovative and more inclusive vaccines may circumvent the hitches and ameliorate/resolve the spread of those life-threatening pathogens. Bearing this, we applied an immunoinformatics strategy (in silico approach) to design two multi-epitope vaccines (one for each pathogen) encompassing toxigenic and non-toxigenic strains of C. diphtheriae and C. difficile. The results predict that both vaccines can induce cellular and humoral response due to the presence of predicted MHC-I, MHC-II and B cell epitopes. Furthermore, the vaccines and the complex (vaccine + Toll-like receptors) were classified as stable, non-allergenic and antigenic. The in silico approach considerable reduced the cost and time that would be spend designing the vaccines and selecting the vaccine (reverse vaccinology) and drug targets (subtractive genomics); nonetheless, considering that the analyses were performed only in silico, experimental validations are required to confirm the results.