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The value of morphological characterisation of bacterial colonies in microbial diagnosis and clinical decision-making

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Resumo:During the course of infection, microorganisms go through genetic and physiological changes to survive the selective pressures imposed by the human immune system and the antibiotic treatments. Colony morphological manifestations of such antimicrobial responses are fairly immediate and inexpensive to obtain experimentally, and can be a very useful tool in clinical decision making. Several morphotypes have already been associated to chronic infections and device-associated infections. For example, P. aeruginosa mucoid variants are typically isolated from cystic fibrosis lungs at chronic stages. These colony variants are markedly resistant to common antibiotics, such as gentamicin, aminoglycosides, ciprofloxacin and imipenem. Likewise, S. aureus small colony variants, often isolated from several chronic device-associated infections, display augmented resistance to several classes of antibiotics and, able to live intracellularly, and therefore surviving the action of both antibiotics and host immune defences. Therefore, the aim of this work is to introduce a novel computer-assisted microbial morphotyping platform in support of microbial diagnosis and further clinical decision-making. A dataset of morphotypes, extracted from the publicly available at MorphoCol database (http://morphocol.org), exemplifies how the platform assists in the manual morphological characterisation, collects data from automatic image processing tools, clusters colonies that show observable similar morphologies and describes the antibiotic susceptibility of the individual groups. Results show that key colony features, such as size, consistency and texture, can be in fact predictors of pathogenic potential of bacteria. Therefore, new colonies may be matched against the described groups, enabling the formulation of a preliminary diagnosis and therapeutics based on the previous reports.
Autores principais:Sousa, Ana Margarida
Outros Autores:Pereira, Maria Olívia; Lourenço, Anália
Assunto:Clinical decision making Data mining Colony morphology Antibiotic susceptibility
Ano:2014
País:Portugal
Tipo de documento:outro
Tipo de acesso:acesso aberto
Instituição associada:Universidade do Minho
Idioma:inglês
Origem:RepositóriUM - Universidade do Minho
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author Sousa, Ana Margarida
author2 Pereira, Maria Olívia
Lourenço, Anália
author2_role author
author
author_facet Sousa, Ana Margarida
Pereira, Maria Olívia
Lourenço, Anália
author_role author
contributor_name_str_mv RepositóriUM - Universidade do Minho
country_str PT
creators_json_txt [{\"Person.name\":\"Sousa, Ana Margarida\"},{\"Person.name\":\"Pereira, Maria Olívia\"},{\"Person.name\":\"Lourenço, Anália\"}]
datacite.contributors.contributor.contributorName.fl_str_mv RepositóriUM - Universidade do Minho
datacite.creators.creator.creatorName.fl_str_mv Sousa, Ana Margarida
Pereira, Maria Olívia
Lourenço, Anália
datacite.date.Accepted.fl_str_mv 2014-10-01T00:00:00Z
datacite.date.available.fl_str_mv 2015-02-16T14:14:51Z
datacite.date.embargoed.fl_str_mv 2015-02-16T14:14:51Z
datacite.rights.fl_str_mv http://purl.org/coar/access_right/c_abf2
datacite.subjects.subject.fl_str_mv Clinical decision making
Data mining
Colony morphology
Antibiotic susceptibility
datacite.titles.title.fl_str_mv The value of morphological characterisation of bacterial colonies in microbial diagnosis and clinical decision-making
dc.contributor.none.fl_str_mv RepositóriUM - Universidade do Minho
dc.creator.none.fl_str_mv Sousa, Ana Margarida
Pereira, Maria Olívia
Lourenço, Anália
dc.date.Accepted.fl_str_mv 2014-10-01T00:00:00Z
dc.date.available.fl_str_mv 2015-02-16T14:14:51Z
dc.date.embargoed.fl_str_mv 2015-02-16T14:14:51Z
dc.format.none.fl_str_mv application/pdf
dc.identifier.none.fl_str_mv https://hdl.handle.net/1822/33908
dc.language.none.fl_str_mv eng
dc.rights.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.subject.none.fl_str_mv Clinical decision making
Data mining
Colony morphology
Antibiotic susceptibility
dc.title.fl_str_mv The value of morphological characterisation of bacterial colonies in microbial diagnosis and clinical decision-making
dc.type.none.fl_str_mv http://purl.org/coar/resource_type/c_1843
description During the course of infection, microorganisms go through genetic and physiological changes to survive the selective pressures imposed by the human immune system and the antibiotic treatments. Colony morphological manifestations of such antimicrobial responses are fairly immediate and inexpensive to obtain experimentally, and can be a very useful tool in clinical decision making. Several morphotypes have already been associated to chronic infections and device-associated infections. For example, P. aeruginosa mucoid variants are typically isolated from cystic fibrosis lungs at chronic stages. These colony variants are markedly resistant to common antibiotics, such as gentamicin, aminoglycosides, ciprofloxacin and imipenem. Likewise, S. aureus small colony variants, often isolated from several chronic device-associated infections, display augmented resistance to several classes of antibiotics and, able to live intracellularly, and therefore surviving the action of both antibiotics and host immune defences. Therefore, the aim of this work is to introduce a novel computer-assisted microbial morphotyping platform in support of microbial diagnosis and further clinical decision-making. A dataset of morphotypes, extracted from the publicly available at MorphoCol database (http://morphocol.org), exemplifies how the platform assists in the manual morphological characterisation, collects data from automatic image processing tools, clusters colonies that show observable similar morphologies and describes the antibiotic susceptibility of the individual groups. Results show that key colony features, such as size, consistency and texture, can be in fact predictors of pathogenic potential of bacteria. Therefore, new colonies may be matched against the described groups, enabling the formulation of a preliminary diagnosis and therapeutics based on the previous reports.
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eu_rights_str_mv openAccess
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fulltext.url.fl_str_mv https://repositorium.uminho.pt/bitstreams/07f6f87e-cea3-4db5-9a60-85be26ab955c/download
id rum_eaae4a147ec690fcccf2c359a4f47ed2
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instacron_str repositorium
institution Universidade do Minho
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oai_identifier_str oai:repositorium.uminho.pt:1822/33908
organization_str_mv urn:organizationAcronym:repositorium
person_str_mv Sousa, Ana Margarida
Pereira, Maria Olívia
Lourenço, Anália
publishDate 2014
reponame_str RepositóriUM - Universidade do Minho
repository_id_str urn:repositoryAcronym:rum
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spelling engporDuring the course of infection, microorganisms go through genetic and physiological changes to survive the selective pressures imposed by the human immune system and the antibiotic treatments. Colony morphological manifestations of such antimicrobial responses are fairly immediate and inexpensive to obtain experimentally, and can be a very useful tool in clinical decision making. Several morphotypes have already been associated to chronic infections and device-associated infections. For example, P. aeruginosa mucoid variants are typically isolated from cystic fibrosis lungs at chronic stages. These colony variants are markedly resistant to common antibiotics, such as gentamicin, aminoglycosides, ciprofloxacin and imipenem. Likewise, S. aureus small colony variants, often isolated from several chronic device-associated infections, display augmented resistance to several classes of antibiotics and, able to live intracellularly, and therefore surviving the action of both antibiotics and host immune defences. Therefore, the aim of this work is to introduce a novel computer-assisted microbial morphotyping platform in support of microbial diagnosis and further clinical decision-making. A dataset of morphotypes, extracted from the publicly available at MorphoCol database (http://morphocol.org), exemplifies how the platform assists in the manual morphological characterisation, collects data from automatic image processing tools, clusters colonies that show observable similar morphologies and describes the antibiotic susceptibility of the individual groups. Results show that key colony features, such as size, consistency and texture, can be in fact predictors of pathogenic potential of bacteria. Therefore, new colonies may be matched against the described groups, enabling the formulation of a preliminary diagnosis and therapeutics based on the previous reports.application/pdfporThe value of morphological characterisation of bacterial colonies in microbial diagnosis and clinical decision-makingSousa, Ana MargaridaPereira, Maria OlíviaLourenço, AnáliaHostingInstitutionOrganizationalRepositóriUM - Universidade do Minhoe-mailmailto:repositorium@usdb.uminho.ptrepositorium@usdb.uminho.ptCITATIONSousa, A. M.; Pereira, Maria Olívia; Lourenço, Anália, The value of morphological characterisation of bacterial colonies in microbial diagnosis and clinical decision-making. ICAR 2014 - III International Conference on Antimicrobial Research. Madrid, Spain, Oct. 1-3, 511-511, 2014.2015-02-16T14:14:51Z2014-102015-02-09T18:05:48Z2014-10-01T00:00:00ZHandlehttps://hdl.handle.net/1822/33908http://purl.org/coar/access_right/c_abf2open accessClinical decision makingData miningColony morphologyAntibiotic susceptibility375807 bytesother research producthttp://purl.org/coar/resource_type/c_1843otherhttp://purl.org/coar/access_right/c_abf2application/pdffulltexthttps://repositorium.uminho.pt/bitstreams/07f6f87e-cea3-4db5-9a60-85be26ab955c/download
spellingShingle The value of morphological characterisation of bacterial colonies in microbial diagnosis and clinical decision-making
Sousa, Ana Margarida
Clinical decision making
Data mining
Colony morphology
Antibiotic susceptibility
status SINGLETON
subject.fl_str_mv Clinical decision making
Data mining
Colony morphology
Antibiotic susceptibility
title The value of morphological characterisation of bacterial colonies in microbial diagnosis and clinical decision-making
title_full The value of morphological characterisation of bacterial colonies in microbial diagnosis and clinical decision-making
title_fullStr The value of morphological characterisation of bacterial colonies in microbial diagnosis and clinical decision-making
title_full_unstemmed The value of morphological characterisation of bacterial colonies in microbial diagnosis and clinical decision-making
title_short The value of morphological characterisation of bacterial colonies in microbial diagnosis and clinical decision-making
title_sort The value of morphological characterisation of bacterial colonies in microbial diagnosis and clinical decision-making
topic Clinical decision making
Data mining
Colony morphology
Antibiotic susceptibility
topic_facet Clinical decision making
Data mining
Colony morphology
Antibiotic susceptibility
url https://hdl.handle.net/1822/33908
visible 1