Rapid and reliable identification of Staphylococcus aureus capsular serotypes by means of artificial neural network-assisted Fourier-transform infrared spectroscopy

Autores
Grunert, Tom; Wenning, Mareike; Barbagelata, María Sol; Fricker, Martina; Sordelli, Daniel Oscar; Buzzola, Fernanda Roxana; Ehling Schulz, Monika
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Staphylococcus aureus capsular polysaccharides (CP) are important virulence factors and represent putative targets for vaccine development. Therefore, the purpose of this study was to develop a high-throughput method to identify and discriminate the clinically important S. aureus capsular serotypes 5, 8, and NT (nontypeable). A comprehensive set of clinical isolates derived from different origins and control strains, representative for each serotype, were used to establish a CP typing system based on Fourier transform infrared (FTIR) spectroscopy and chemometric techniques. By combining FTIR spectroscopy with artificial neuronal network (ANN) analysis, a system was successfully established, allowing a rapid identification and discrimination of all three serotypes. The overall accuracy of the ANN-assisted FTIR spectroscopy CP typing system was 96.7% for the internal validation and 98.2% for the external validation. One isolate in the internal validation and one isolate in the external validation failed in the classification procedure, but none of the isolates was incorrectly classified. The present study demonstrates that ANN-assisted FTIR spectroscopy allows a rapid and reliable discrimination of S. aureus capsular serotypes. It is suitable for diagnostic as well as large-scale epidemiologic surveillance of S. aureus capsule expression and provides useful information with respect to chronicity of infection.
Fil: Grunert, Tom. University of Veterinary Medicine; Austria
Fil: Wenning, Mareike. Technische Universitat Munchen; Alemania
Fil: Barbagelata, María Sol. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; Argentina
Fil: Fricker, Martina. University of Veterinary Medicine; Austria
Fil: Sordelli, Daniel Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; Argentina
Fil: Buzzola, Fernanda Roxana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; Argentina
Fil: Ehling Schulz, Monika. University of Veterinary Medicine; Austria
Materia
STAPHYLOCOCCUS AUREUS
FTIR
CAPSULE
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/21297
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/21297
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Rapid and reliable identification of Staphylococcus aureus capsular serotypes by means of artificial neural network-assisted Fourier-transform infrared spectroscopyGrunert, TomWenning, MareikeBarbagelata, María SolFricker, MartinaSordelli, Daniel OscarBuzzola, Fernanda RoxanaEhling Schulz, MonikaSTAPHYLOCOCCUS AUREUSFTIRCAPSULEhttps://purl.org/becyt/ford/4.3https://purl.org/becyt/ford/4Staphylococcus aureus capsular polysaccharides (CP) are important virulence factors and represent putative targets for vaccine development. Therefore, the purpose of this study was to develop a high-throughput method to identify and discriminate the clinically important S. aureus capsular serotypes 5, 8, and NT (nontypeable). A comprehensive set of clinical isolates derived from different origins and control strains, representative for each serotype, were used to establish a CP typing system based on Fourier transform infrared (FTIR) spectroscopy and chemometric techniques. By combining FTIR spectroscopy with artificial neuronal network (ANN) analysis, a system was successfully established, allowing a rapid identification and discrimination of all three serotypes. The overall accuracy of the ANN-assisted FTIR spectroscopy CP typing system was 96.7% for the internal validation and 98.2% for the external validation. One isolate in the internal validation and one isolate in the external validation failed in the classification procedure, but none of the isolates was incorrectly classified. The present study demonstrates that ANN-assisted FTIR spectroscopy allows a rapid and reliable discrimination of S. aureus capsular serotypes. It is suitable for diagnostic as well as large-scale epidemiologic surveillance of S. aureus capsule expression and provides useful information with respect to chronicity of infection.Fil: Grunert, Tom. University of Veterinary Medicine; AustriaFil: Wenning, Mareike. Technische Universitat Munchen; AlemaniaFil: Barbagelata, María Sol. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; ArgentinaFil: Fricker, Martina. University of Veterinary Medicine; AustriaFil: Sordelli, Daniel Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; ArgentinaFil: Buzzola, Fernanda Roxana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; ArgentinaFil: Ehling Schulz, Monika. University of Veterinary Medicine; AustriaAmerican Society for Microbiology2013-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/21297Grunert, Tom; Wenning, Mareike; Barbagelata, María Sol; Fricker, Martina; Sordelli, Daniel Oscar; et al.; Rapid and reliable identification of Staphylococcus aureus capsular serotypes by means of artificial neural network-assisted Fourier-transform infrared spectroscopy; American Society for Microbiology; Journal of Clinical Microbiology; 51; 7; 5-2013; 2261-22660095-1137CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://jcm.asm.org/content/51/7/2261.longinfo:eu-repo/semantics/altIdentifier/doi/10.1128/JCM.00581-13info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3697708/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:56:44Zoai:ri.conicet.gov.ar:11336/21297instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:56:44.308CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Rapid and reliable identification of Staphylococcus aureus capsular serotypes by means of artificial neural network-assisted Fourier-transform infrared spectroscopy
title Rapid and reliable identification of Staphylococcus aureus capsular serotypes by means of artificial neural network-assisted Fourier-transform infrared spectroscopy
spellingShingle Rapid and reliable identification of Staphylococcus aureus capsular serotypes by means of artificial neural network-assisted Fourier-transform infrared spectroscopy
Grunert, Tom
STAPHYLOCOCCUS AUREUS
FTIR
CAPSULE
title_short Rapid and reliable identification of Staphylococcus aureus capsular serotypes by means of artificial neural network-assisted Fourier-transform infrared spectroscopy
title_full Rapid and reliable identification of Staphylococcus aureus capsular serotypes by means of artificial neural network-assisted Fourier-transform infrared spectroscopy
title_fullStr Rapid and reliable identification of Staphylococcus aureus capsular serotypes by means of artificial neural network-assisted Fourier-transform infrared spectroscopy
title_full_unstemmed Rapid and reliable identification of Staphylococcus aureus capsular serotypes by means of artificial neural network-assisted Fourier-transform infrared spectroscopy
title_sort Rapid and reliable identification of Staphylococcus aureus capsular serotypes by means of artificial neural network-assisted Fourier-transform infrared spectroscopy
dc.creator.none.fl_str_mv Grunert, Tom
Wenning, Mareike
Barbagelata, María Sol
Fricker, Martina
Sordelli, Daniel Oscar
Buzzola, Fernanda Roxana
Ehling Schulz, Monika
author Grunert, Tom
author_facet Grunert, Tom
Wenning, Mareike
Barbagelata, María Sol
Fricker, Martina
Sordelli, Daniel Oscar
Buzzola, Fernanda Roxana
Ehling Schulz, Monika
author_role author
author2 Wenning, Mareike
Barbagelata, María Sol
Fricker, Martina
Sordelli, Daniel Oscar
Buzzola, Fernanda Roxana
Ehling Schulz, Monika
author2_role author
author
author
author
author
author
dc.subject.none.fl_str_mv STAPHYLOCOCCUS AUREUS
FTIR
CAPSULE
topic STAPHYLOCOCCUS AUREUS
FTIR
CAPSULE
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.3
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv Staphylococcus aureus capsular polysaccharides (CP) are important virulence factors and represent putative targets for vaccine development. Therefore, the purpose of this study was to develop a high-throughput method to identify and discriminate the clinically important S. aureus capsular serotypes 5, 8, and NT (nontypeable). A comprehensive set of clinical isolates derived from different origins and control strains, representative for each serotype, were used to establish a CP typing system based on Fourier transform infrared (FTIR) spectroscopy and chemometric techniques. By combining FTIR spectroscopy with artificial neuronal network (ANN) analysis, a system was successfully established, allowing a rapid identification and discrimination of all three serotypes. The overall accuracy of the ANN-assisted FTIR spectroscopy CP typing system was 96.7% for the internal validation and 98.2% for the external validation. One isolate in the internal validation and one isolate in the external validation failed in the classification procedure, but none of the isolates was incorrectly classified. The present study demonstrates that ANN-assisted FTIR spectroscopy allows a rapid and reliable discrimination of S. aureus capsular serotypes. It is suitable for diagnostic as well as large-scale epidemiologic surveillance of S. aureus capsule expression and provides useful information with respect to chronicity of infection.
Fil: Grunert, Tom. University of Veterinary Medicine; Austria
Fil: Wenning, Mareike. Technische Universitat Munchen; Alemania
Fil: Barbagelata, María Sol. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; Argentina
Fil: Fricker, Martina. University of Veterinary Medicine; Austria
Fil: Sordelli, Daniel Oscar. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; Argentina
Fil: Buzzola, Fernanda Roxana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones en Microbiología y Parasitología Médica. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones en Microbiología y Parasitología Médica; Argentina
Fil: Ehling Schulz, Monika. University of Veterinary Medicine; Austria
description Staphylococcus aureus capsular polysaccharides (CP) are important virulence factors and represent putative targets for vaccine development. Therefore, the purpose of this study was to develop a high-throughput method to identify and discriminate the clinically important S. aureus capsular serotypes 5, 8, and NT (nontypeable). A comprehensive set of clinical isolates derived from different origins and control strains, representative for each serotype, were used to establish a CP typing system based on Fourier transform infrared (FTIR) spectroscopy and chemometric techniques. By combining FTIR spectroscopy with artificial neuronal network (ANN) analysis, a system was successfully established, allowing a rapid identification and discrimination of all three serotypes. The overall accuracy of the ANN-assisted FTIR spectroscopy CP typing system was 96.7% for the internal validation and 98.2% for the external validation. One isolate in the internal validation and one isolate in the external validation failed in the classification procedure, but none of the isolates was incorrectly classified. The present study demonstrates that ANN-assisted FTIR spectroscopy allows a rapid and reliable discrimination of S. aureus capsular serotypes. It is suitable for diagnostic as well as large-scale epidemiologic surveillance of S. aureus capsule expression and provides useful information with respect to chronicity of infection.
publishDate 2013
dc.date.none.fl_str_mv 2013-05
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/21297
Grunert, Tom; Wenning, Mareike; Barbagelata, María Sol; Fricker, Martina; Sordelli, Daniel Oscar; et al.; Rapid and reliable identification of Staphylococcus aureus capsular serotypes by means of artificial neural network-assisted Fourier-transform infrared spectroscopy; American Society for Microbiology; Journal of Clinical Microbiology; 51; 7; 5-2013; 2261-2266
0095-1137
CONICET Digital
CONICET
url http://hdl.handle.net/11336/21297
identifier_str_mv Grunert, Tom; Wenning, Mareike; Barbagelata, María Sol; Fricker, Martina; Sordelli, Daniel Oscar; et al.; Rapid and reliable identification of Staphylococcus aureus capsular serotypes by means of artificial neural network-assisted Fourier-transform infrared spectroscopy; American Society for Microbiology; Journal of Clinical Microbiology; 51; 7; 5-2013; 2261-2266
0095-1137
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://jcm.asm.org/content/51/7/2261.long
info:eu-repo/semantics/altIdentifier/doi/10.1128/JCM.00581-13
info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3697708/
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv American Society for Microbiology
publisher.none.fl_str_mv American Society for Microbiology
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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