Modelling bacteria and bacteriophage population dynamics

Detalhes bibliográficos
Autor(a) principal: Santos, Sílvio Roberto Branco
Data de Publicação: 2006
Outros Autores: Azeredo, Joana, Nicolau, Ana, Ferreira, Eugénio C.
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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spelling 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
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