Modelling bacteria and bacteriophage population dynamics
Autor(a) principal: | |
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Data de Publicação: | 2006 |
Outros Autores: | , , |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/1822/5974 |
Resumo: | Moreover, it is necessary to evaluate and to understand the phage and bacteria population dynamics in order to foresee its potential for use in vivo. To understand how natural communities are affected by environmental factors and will respond in time, it is important to develop predictive models. The aim of the present work was the development of a dynamic model that predicts the interaction between a Salmonella phage and its respective host. Simulated data are compared with the data obtained experimentally to assess the suitability of the model for two multiplicity of infection (MOI): 0.1 and 1.0. For a high multiplicity of infection (MOI=1.0), the simulated and experimental data have a better correlation than for a low MOI (0.1). In this case, the differences were also more notorious for bacterial concentration. From the results it can be concluded that the model produces better correlations in terms of phage concentration, when a higher MOI is used. So, for a high MOI (MOI=1), given the initial values and the parameters used in the model, we can predict the concentration of phage and bacteria. In this way, the model can be used to predict the amount of phage obtained in the production process. It is expected that the developed model may help the optimization of phage production and the guidance of the experimental studies of population dynamics by identifying and evaluating the relative contribution of phage and bacteria in the course and outcome of an infection. |
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Modelling bacteria and bacteriophage population dynamicsBacteriophageModelPhage therapyMoreover, it is necessary to evaluate and to understand the phage and bacteria population dynamics in order to foresee its potential for use in vivo. To understand how natural communities are affected by environmental factors and will respond in time, it is important to develop predictive models. The aim of the present work was the development of a dynamic model that predicts the interaction between a Salmonella phage and its respective host. Simulated data are compared with the data obtained experimentally to assess the suitability of the model for two multiplicity of infection (MOI): 0.1 and 1.0. For a high multiplicity of infection (MOI=1.0), the simulated and experimental data have a better correlation than for a low MOI (0.1). In this case, the differences were also more notorious for bacterial concentration. From the results it can be concluded that the model produces better correlations in terms of phage concentration, when a higher MOI is used. So, for a high MOI (MOI=1), given the initial values and the parameters used in the model, we can predict the concentration of phage and bacteria. In this way, the model can be used to predict the amount of phage obtained in the production process. It is expected that the developed model may help the optimization of phage production and the guidance of the experimental studies of population dynamics by identifying and evaluating the relative contribution of phage and bacteria in the course and outcome of an infection.Universidade do MinhoSantos, Sílvio Roberto BrancoAzeredo, JoanaNicolau, AnaFerreira, Eugénio C.2006-10-252006-10-25T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/1822/5974engPHAGE TECHNOLOGIES WORKSHOP, Nottingham, 2006 - "Phage Technologies Workshop". [S.l. : s.n.], 2006.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-05-11T06:37:15Zoai:repositorium.sdum.uminho.pt:1822/5974Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-11T06:37:15Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Modelling bacteria and bacteriophage population dynamics |
title |
Modelling bacteria and bacteriophage population dynamics |
spellingShingle |
Modelling bacteria and bacteriophage population dynamics Santos, Sílvio Roberto Branco Bacteriophage Model Phage therapy |
title_short |
Modelling bacteria and bacteriophage population dynamics |
title_full |
Modelling bacteria and bacteriophage population dynamics |
title_fullStr |
Modelling bacteria and bacteriophage population dynamics |
title_full_unstemmed |
Modelling bacteria and bacteriophage population dynamics |
title_sort |
Modelling bacteria and bacteriophage population dynamics |
author |
Santos, Sílvio Roberto Branco |
author_facet |
Santos, Sílvio Roberto Branco Azeredo, Joana Nicolau, Ana Ferreira, Eugénio C. |
author_role |
author |
author2 |
Azeredo, Joana Nicolau, Ana Ferreira, Eugénio C. |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Santos, Sílvio Roberto Branco Azeredo, Joana Nicolau, Ana Ferreira, Eugénio C. |
dc.subject.por.fl_str_mv |
Bacteriophage Model Phage therapy |
topic |
Bacteriophage Model Phage therapy |
description |
Moreover, it is necessary to evaluate and to understand the phage and bacteria population dynamics in order to foresee its potential for use in vivo. To understand how natural communities are affected by environmental factors and will respond in time, it is important to develop predictive models. The aim of the present work was the development of a dynamic model that predicts the interaction between a Salmonella phage and its respective host. Simulated data are compared with the data obtained experimentally to assess the suitability of the model for two multiplicity of infection (MOI): 0.1 and 1.0. For a high multiplicity of infection (MOI=1.0), the simulated and experimental data have a better correlation than for a low MOI (0.1). In this case, the differences were also more notorious for bacterial concentration. From the results it can be concluded that the model produces better correlations in terms of phage concentration, when a higher MOI is used. So, for a high MOI (MOI=1), given the initial values and the parameters used in the model, we can predict the concentration of phage and bacteria. In this way, the model can be used to predict the amount of phage obtained in the production process. It is expected that the developed model may help the optimization of phage production and the guidance of the experimental studies of population dynamics by identifying and evaluating the relative contribution of phage and bacteria in the course and outcome of an infection. |
publishDate |
2006 |
dc.date.none.fl_str_mv |
2006-10-25 2006-10-25T00:00:00Z |
dc.type.driver.fl_str_mv |
conference object |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/1822/5974 |
url |
https://hdl.handle.net/1822/5974 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
PHAGE TECHNOLOGIES WORKSHOP, Nottingham, 2006 - "Phage Technologies Workshop". [S.l. : s.n.], 2006. |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
mluisa.alvim@gmail.com |
_version_ |
1817545034375888896 |