In silico approaches to design multi-epitope vaccines and uncover potential drug targets against Corynebacterium diphtheriae and Clostridioides difficile
Autor(a) principal: | |
---|---|
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 |
Resumo: | 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. |
id |
UFMG_8a562457bbd2d655567fab99ec9639b3 |
---|---|
oai_identifier_str |
oai:repositorio.ufmg.br:1843/33916 |
network_acronym_str |
UFMG |
network_name_str |
Repositório Institucional da UFMG |
repository_id_str |
|
spelling |
Anderson Miyoshihttp://lattes.cnpq.br/9198272608157135Sandeep TiwariSérgio Costa OliveiraSiomar de Castro SoaresRommel Thiago Jucá RamosÁlvaro Cantini Nuneshttp://lattes.cnpq.br/8618828602070110Mariana Passos Santana2020-08-06T20:30:19Z2020-08-06T20:30:19Z2019-07-19http://hdl.handle.net/1843/33916Immunization 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.Imunização é uma estratégia crucial para prevenir a disseminação de patógenos sem agravar a resistência. A sociedade está enfrentando uma ameaça sem precedentes devido ao uso exacerbado de antimicrobianos, que são responsáveis por acelerar a problemática da resistência que provavelmente nos conduzirá a um aumento do custo com saúde pública. Ademais, o crescente número de epidemias de patógenos anteriormente controlados está diretamente associado com uma baixa abrangência de programas de imunização, desvantagens das vacinas convencionais e dificuldades socioeconômicas. O uso de tecnologias inovadoras pode resultar na resolução de muitos desses problemas de forma customizada e com um custo efetivo reduzido. Dentre os patógenos bacterianos que apresentam uma alta taxa de morbidade e mortalidade, nós destacamos dois cruciais: Corynebacterium diphtheriae e Clostridioides difficile, os agentes causadores da difteria e C. difficile infecções (CDI) (e.g. diarreia até colite pseudomembranosa). A difteria era considerada a principal causadora da mortalidade infantil, mas com o advento da vacina diftérica (i.e. vacina fundamentada na toxina diftérica inativada), o número de casos da doença reduziu significativamente. Entretanto, esta moléstia continua a ser um problema, especialmente considerando variantes não toxigênicos de C. diphtheriae e a emergência de linhagens multidroga resistentes. Tal-qualmente, a conjuntura do surgimento de linhagens C. difficile multidroga resistentes se tornou um transtorno, visto que afeta o tratamento recomendado das CDI, posto que são baseados em antibióticos específicos. Considerando isto, possivelmente, o tratamento via antibióticos se tornará obsoleto devido à alta capacidade de adaptação desta bactéria ao meio ambiente (genoma variável em razão da presença de elementos móveis). Isto posto, a concepção de vacinas inovadoras e mais inclusivas pode sanar os inconvenientes e melhor/resolver a disseminação destes patógenos Portanto, nós utilizamos a estratégia de imunoinformática (abordagem in silico) para conceber duas vacinas multiepitopo (uma para cada patógeno) considerando as linhagens toxigênicas e não toxigênicas de C. diphtheriae e C. difficile. Os resultados preditos para cada vacina demonstraram que ambas induzem resposta imune celular e humoral devido a presença da epitopos MHC-I, MHC-II e células B. Ademais, as vacinas e os complexos (vacina + receptores Toll-like) foram classificados como estáveis, não alergênicos e antigênicos. A abordagem in silico reduz consideravelmente o custo e o tempo gasto com o design e das vacinas e com a seleção dos alvos vacinais (vacinologia reversa) e drogas (genômica subtrativa), entretanto, considerando que as análises foram realizadas apenas in silico, a validação experimental é imprescindível para confirmar os resultados.CNPq - Conselho Nacional de Desenvolvimento Científico e TecnológicoCAPES - Coordenação de Aperfeiçoamento de Pessoal de Nível SuperiorengUniversidade Federal de Minas GeraisPrograma de Pós-Graduação em GenéticaUFMGBrasilICB - DEPARTAMENTO DE BIOLOGIA GERALGenômicaImunizaçãoVacinologiaCorynebacterium diphtheriaeClostridium difficileResistência a Múltiplos MedicamentosClostridioides difficileCorynebacterium diftheriaeimmunoinformaticsreverse vaccinologysubtractive genomicsmultidrug resistanceIn silico approaches to design multi-epitope vaccines and uncover potential drug targets against Corynebacterium diphtheriae and Clostridioides difficileinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGORIGINALMPS bbtfinal.pdfMPS bbtfinal.pdfapplication/pdf9769210https://repositorio.ufmg.br/bitstream/1843/33916/1/MPS%20bbtfinal.pdf9ccda3cb2251805db5525bc2502ba681MD51LICENSElicense.txtlicense.txttext/plain; charset=utf-82119https://repositorio.ufmg.br/bitstream/1843/33916/2/license.txt34badce4be7e31e3adb4575ae96af679MD521843/339162020-08-06 17:30:19.052oai:repositorio.ufmg.br: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Repositório de PublicaçõesPUBhttps://repositorio.ufmg.br/oaiopendoar:2020-08-06T20:30:19Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false |
dc.title.pt_BR.fl_str_mv |
In silico approaches to design multi-epitope vaccines and uncover potential drug targets against Corynebacterium diphtheriae and Clostridioides difficile |
title |
In silico approaches to design multi-epitope vaccines and uncover potential drug targets against Corynebacterium diphtheriae and Clostridioides difficile |
spellingShingle |
In silico approaches to design multi-epitope vaccines and uncover potential drug targets against Corynebacterium diphtheriae and Clostridioides difficile Mariana Passos Santana Clostridioides difficile Corynebacterium diftheriae immunoinformatics reverse vaccinology subtractive genomics multidrug resistance Genômica Imunização Vacinologia Corynebacterium diphtheriae Clostridium difficile Resistência a Múltiplos Medicamentos |
title_short |
In silico approaches to design multi-epitope vaccines and uncover potential drug targets against Corynebacterium diphtheriae and Clostridioides difficile |
title_full |
In silico approaches to design multi-epitope vaccines and uncover potential drug targets against Corynebacterium diphtheriae and Clostridioides difficile |
title_fullStr |
In silico approaches to design multi-epitope vaccines and uncover potential drug targets against Corynebacterium diphtheriae and Clostridioides difficile |
title_full_unstemmed |
In silico approaches to design multi-epitope vaccines and uncover potential drug targets against Corynebacterium diphtheriae and Clostridioides difficile |
title_sort |
In silico approaches to design multi-epitope vaccines and uncover potential drug targets against Corynebacterium diphtheriae and Clostridioides difficile |
author |
Mariana Passos Santana |
author_facet |
Mariana Passos Santana |
author_role |
author |
dc.contributor.advisor1.fl_str_mv |
Anderson Miyoshi |
dc.contributor.advisor1Lattes.fl_str_mv |
http://lattes.cnpq.br/9198272608157135 |
dc.contributor.advisor-co1.fl_str_mv |
Sandeep Tiwari |
dc.contributor.referee1.fl_str_mv |
Sérgio Costa Oliveira |
dc.contributor.referee2.fl_str_mv |
Siomar de Castro Soares |
dc.contributor.referee3.fl_str_mv |
Rommel Thiago Jucá Ramos |
dc.contributor.referee4.fl_str_mv |
Álvaro Cantini Nunes |
dc.contributor.authorLattes.fl_str_mv |
http://lattes.cnpq.br/8618828602070110 |
dc.contributor.author.fl_str_mv |
Mariana Passos Santana |
contributor_str_mv |
Anderson Miyoshi Sandeep Tiwari Sérgio Costa Oliveira Siomar de Castro Soares Rommel Thiago Jucá Ramos Álvaro Cantini Nunes |
dc.subject.por.fl_str_mv |
Clostridioides difficile Corynebacterium diftheriae immunoinformatics reverse vaccinology subtractive genomics multidrug resistance |
topic |
Clostridioides difficile Corynebacterium diftheriae immunoinformatics reverse vaccinology subtractive genomics multidrug resistance Genômica Imunização Vacinologia Corynebacterium diphtheriae Clostridium difficile Resistência a Múltiplos Medicamentos |
dc.subject.other.pt_BR.fl_str_mv |
Genômica Imunização Vacinologia Corynebacterium diphtheriae Clostridium difficile Resistência a Múltiplos Medicamentos |
description |
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. |
publishDate |
2019 |
dc.date.issued.fl_str_mv |
2019-07-19 |
dc.date.accessioned.fl_str_mv |
2020-08-06T20:30:19Z |
dc.date.available.fl_str_mv |
2020-08-06T20:30:19Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
format |
doctoralThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1843/33916 |
url |
http://hdl.handle.net/1843/33916 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.publisher.none.fl_str_mv |
Universidade Federal de Minas Gerais |
dc.publisher.program.fl_str_mv |
Programa de Pós-Graduação em Genética |
dc.publisher.initials.fl_str_mv |
UFMG |
dc.publisher.country.fl_str_mv |
Brasil |
dc.publisher.department.fl_str_mv |
ICB - DEPARTAMENTO DE BIOLOGIA GERAL |
publisher.none.fl_str_mv |
Universidade Federal de Minas Gerais |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFMG instname:Universidade Federal de Minas Gerais (UFMG) instacron:UFMG |
instname_str |
Universidade Federal de Minas Gerais (UFMG) |
instacron_str |
UFMG |
institution |
UFMG |
reponame_str |
Repositório Institucional da UFMG |
collection |
Repositório Institucional da UFMG |
bitstream.url.fl_str_mv |
https://repositorio.ufmg.br/bitstream/1843/33916/1/MPS%20bbtfinal.pdf https://repositorio.ufmg.br/bitstream/1843/33916/2/license.txt |
bitstream.checksum.fl_str_mv |
9ccda3cb2251805db5525bc2502ba681 34badce4be7e31e3adb4575ae96af679 |
bitstream.checksumAlgorithm.fl_str_mv |
MD5 MD5 |
repository.name.fl_str_mv |
Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG) |
repository.mail.fl_str_mv |
|
_version_ |
1803589213285777408 |