Comparison of two MALDI-TOF MS systems for the identification of clinically relevant anaerobic bacteria in Argentina

Autores
Litterio, Mirta; Castello, Liliana; Venuta, María Elena; Abel, Sofía; Fernández Canigia, Liliana; Legaria, María Cristina; Rollet, Raquel; Vaustat, Claudia Daniela; Azula, Natalia; Fox, Bárbara; Otero, Silvina; Maldonado, María Laura; Mangieri, Natalia Alejandra; Rossetti, María Adelaida; Predari, Silvia Carla; Cejas, Daniela; Barberis, Claudia
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The aim of this study was to compare the performance of two MALDI-TOF MS systems in the identification of clinically relevant strict anaerobic bacteria. The 16S rRNA gene sequencing was the gold standard method when discrepancies or inconsistencies were observed between platforms. A total of 333 isolates were recovered from clinical samples of different centers in Buenos Aires City between 2016 and 2021. The isolates were identified in duplicate using two MALDI-TOF MS systems, BD Bruker Biotyper (Bruker Daltonics, Bremen, Germany) and Vitek MS (bioMèrieux, Marcy-l´Etoile, France). Using the Vitek MS system, the identification of anaerobic isolates yielded the following percentages: 65.5% (n: 218) at the species or species-complex level, 71.2% (n: 237) at the genus level, 29.4% (n: 98) with no identification and 5.1% (n: 17) with misidentification. Using the Bruker Biotyper system, the identification rates were as follows: 85.3% (n: 284) at the species or species-complex level, 89.7% (n: 299) at the genus level, 14.1% (n: 47) with no identification and 0.6% (n: 2) with misidentification. Differences in the performance of both methods were statistically significant (p-values <0.0001). In conclusion, MALDI-TOF MS systems speed up microbial identification and are particularly effective for slow-growing microorganisms, such as anaerobic bacteria, which are difficult to identify by traditional methods. In this study, the Bruker system showed greater accuracy than the Vitek system. In order to be truly effective, it is essential to update the databases of both systems by increasing the number of each main spectrum profile within the platforms.
Fil: Litterio, Mirta. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; Argentina
Fil: Castello, Liliana. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; Argentina
Fil: Venuta, María Elena. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; Argentina
Fil: Abel, Sofía. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; Argentina
Fil: Fernández Canigia, Liliana. Hospital Alemán; Argentina
Fil: Legaria, María Cristina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica; Argentina
Fil: Rollet, Raquel. Gobierno de la Ciudad de Buenos Aires. Hospital de Infecciosas "Dr. Francisco Javier Muñiz"; Argentina
Fil: Vaustat, Claudia Daniela. Gobierno de la Ciudad de Buenos Aires. Hospital de Infecciosas "Dr. Francisco Javier Muñiz"; Argentina
Fil: Azula, Natalia. Centro de Educaciones Médicas e Investigación Clínica "Norberto Quirno"; Argentina
Fil: Fox, Bárbara. Hospital Alemán; Argentina
Fil: Otero, Silvina. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; Argentina
Fil: Maldonado, María Laura. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; Argentina
Fil: Mangieri, Natalia Alejandra. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; Argentina
Fil: Rossetti, María Adelaida. Gobierno de la Provincia de Buenos Aires. Hospital Interzonal General de Agudos Presidente Peron.; Argentina
Fil: Predari, Silvia Carla. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; Argentina
Fil: Cejas, Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Microbiología, Inmunología y Biotecnología. Cátedra de Microbiología; Argentina
Fil: Barberis, Claudia. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica; Argentina
Materia
MALDI-TOF MS
anaerobic bacteria
Argentina
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:11336/232180
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/232180
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Comparison of two MALDI-TOF MS systems for the identification of clinically relevant anaerobic bacteria in ArgentinaComparación de dos sistemas MALDI-TOF MS en la identificación de bacterias anaerobias de relevancia clínica en ArgentinaLitterio, MirtaCastello, LilianaVenuta, María ElenaAbel, SofíaFernández Canigia, LilianaLegaria, María CristinaRollet, RaquelVaustat, Claudia DanielaAzula, NataliaFox, BárbaraOtero, SilvinaMaldonado, María LauraMangieri, Natalia AlejandraRossetti, María AdelaidaPredari, Silvia CarlaCejas, DanielaBarberis, ClaudiaMALDI-TOF MSanaerobic bacteriaArgentinahttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1The aim of this study was to compare the performance of two MALDI-TOF MS systems in the identification of clinically relevant strict anaerobic bacteria. The 16S rRNA gene sequencing was the gold standard method when discrepancies or inconsistencies were observed between platforms. A total of 333 isolates were recovered from clinical samples of different centers in Buenos Aires City between 2016 and 2021. The isolates were identified in duplicate using two MALDI-TOF MS systems, BD Bruker Biotyper (Bruker Daltonics, Bremen, Germany) and Vitek MS (bioMèrieux, Marcy-l´Etoile, France). Using the Vitek MS system, the identification of anaerobic isolates yielded the following percentages: 65.5% (n: 218) at the species or species-complex level, 71.2% (n: 237) at the genus level, 29.4% (n: 98) with no identification and 5.1% (n: 17) with misidentification. Using the Bruker Biotyper system, the identification rates were as follows: 85.3% (n: 284) at the species or species-complex level, 89.7% (n: 299) at the genus level, 14.1% (n: 47) with no identification and 0.6% (n: 2) with misidentification. Differences in the performance of both methods were statistically significant (p-values <0.0001). In conclusion, MALDI-TOF MS systems speed up microbial identification and are particularly effective for slow-growing microorganisms, such as anaerobic bacteria, which are difficult to identify by traditional methods. In this study, the Bruker system showed greater accuracy than the Vitek system. In order to be truly effective, it is essential to update the databases of both systems by increasing the number of each main spectrum profile within the platforms.Fil: Litterio, Mirta. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; ArgentinaFil: Castello, Liliana. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; ArgentinaFil: Venuta, María Elena. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; ArgentinaFil: Abel, Sofía. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; ArgentinaFil: Fernández Canigia, Liliana. Hospital Alemán; ArgentinaFil: Legaria, María Cristina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica; ArgentinaFil: Rollet, Raquel. Gobierno de la Ciudad de Buenos Aires. Hospital de Infecciosas "Dr. Francisco Javier Muñiz"; ArgentinaFil: Vaustat, Claudia Daniela. Gobierno de la Ciudad de Buenos Aires. Hospital de Infecciosas "Dr. Francisco Javier Muñiz"; ArgentinaFil: Azula, Natalia. Centro de Educaciones Médicas e Investigación Clínica "Norberto Quirno"; ArgentinaFil: Fox, Bárbara. Hospital Alemán; ArgentinaFil: Otero, Silvina. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; ArgentinaFil: Maldonado, María Laura. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; ArgentinaFil: Mangieri, Natalia Alejandra. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; ArgentinaFil: Rossetti, María Adelaida. Gobierno de la Provincia de Buenos Aires. Hospital Interzonal General de Agudos Presidente Peron.; ArgentinaFil: Predari, Silvia Carla. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; ArgentinaFil: Cejas, Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Microbiología, Inmunología y Biotecnología. Cátedra de Microbiología; ArgentinaFil: Barberis, Claudia. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica; ArgentinaAsociación Argentina de Microbiología2024-02info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/232180Litterio, Mirta; Castello, Liliana; Venuta, María Elena; Abel, Sofía; Fernández Canigia, Liliana; et al.; Comparison of two MALDI-TOF MS systems for the identification of clinically relevant anaerobic bacteria in Argentina; Asociación Argentina de Microbiología; Revista Argentina de Microbiología; 56; 1; 2-2024; 33-610325-75411851-7617CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S0325754124000014info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ram.2023.12.001info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:38:06Zoai:ri.conicet.gov.ar:11336/232180instacron: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:34982025-09-29 09:38:06.726CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Comparison of two MALDI-TOF MS systems for the identification of clinically relevant anaerobic bacteria in Argentina
Comparación de dos sistemas MALDI-TOF MS en la identificación de bacterias anaerobias de relevancia clínica en Argentina
title Comparison of two MALDI-TOF MS systems for the identification of clinically relevant anaerobic bacteria in Argentina
spellingShingle Comparison of two MALDI-TOF MS systems for the identification of clinically relevant anaerobic bacteria in Argentina
Litterio, Mirta
MALDI-TOF MS
anaerobic bacteria
Argentina
title_short Comparison of two MALDI-TOF MS systems for the identification of clinically relevant anaerobic bacteria in Argentina
title_full Comparison of two MALDI-TOF MS systems for the identification of clinically relevant anaerobic bacteria in Argentina
title_fullStr Comparison of two MALDI-TOF MS systems for the identification of clinically relevant anaerobic bacteria in Argentina
title_full_unstemmed Comparison of two MALDI-TOF MS systems for the identification of clinically relevant anaerobic bacteria in Argentina
title_sort Comparison of two MALDI-TOF MS systems for the identification of clinically relevant anaerobic bacteria in Argentina
dc.creator.none.fl_str_mv Litterio, Mirta
Castello, Liliana
Venuta, María Elena
Abel, Sofía
Fernández Canigia, Liliana
Legaria, María Cristina
Rollet, Raquel
Vaustat, Claudia Daniela
Azula, Natalia
Fox, Bárbara
Otero, Silvina
Maldonado, María Laura
Mangieri, Natalia Alejandra
Rossetti, María Adelaida
Predari, Silvia Carla
Cejas, Daniela
Barberis, Claudia
author Litterio, Mirta
author_facet Litterio, Mirta
Castello, Liliana
Venuta, María Elena
Abel, Sofía
Fernández Canigia, Liliana
Legaria, María Cristina
Rollet, Raquel
Vaustat, Claudia Daniela
Azula, Natalia
Fox, Bárbara
Otero, Silvina
Maldonado, María Laura
Mangieri, Natalia Alejandra
Rossetti, María Adelaida
Predari, Silvia Carla
Cejas, Daniela
Barberis, Claudia
author_role author
author2 Castello, Liliana
Venuta, María Elena
Abel, Sofía
Fernández Canigia, Liliana
Legaria, María Cristina
Rollet, Raquel
Vaustat, Claudia Daniela
Azula, Natalia
Fox, Bárbara
Otero, Silvina
Maldonado, María Laura
Mangieri, Natalia Alejandra
Rossetti, María Adelaida
Predari, Silvia Carla
Cejas, Daniela
Barberis, Claudia
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv MALDI-TOF MS
anaerobic bacteria
Argentina
topic MALDI-TOF MS
anaerobic bacteria
Argentina
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The aim of this study was to compare the performance of two MALDI-TOF MS systems in the identification of clinically relevant strict anaerobic bacteria. The 16S rRNA gene sequencing was the gold standard method when discrepancies or inconsistencies were observed between platforms. A total of 333 isolates were recovered from clinical samples of different centers in Buenos Aires City between 2016 and 2021. The isolates were identified in duplicate using two MALDI-TOF MS systems, BD Bruker Biotyper (Bruker Daltonics, Bremen, Germany) and Vitek MS (bioMèrieux, Marcy-l´Etoile, France). Using the Vitek MS system, the identification of anaerobic isolates yielded the following percentages: 65.5% (n: 218) at the species or species-complex level, 71.2% (n: 237) at the genus level, 29.4% (n: 98) with no identification and 5.1% (n: 17) with misidentification. Using the Bruker Biotyper system, the identification rates were as follows: 85.3% (n: 284) at the species or species-complex level, 89.7% (n: 299) at the genus level, 14.1% (n: 47) with no identification and 0.6% (n: 2) with misidentification. Differences in the performance of both methods were statistically significant (p-values <0.0001). In conclusion, MALDI-TOF MS systems speed up microbial identification and are particularly effective for slow-growing microorganisms, such as anaerobic bacteria, which are difficult to identify by traditional methods. In this study, the Bruker system showed greater accuracy than the Vitek system. In order to be truly effective, it is essential to update the databases of both systems by increasing the number of each main spectrum profile within the platforms.
Fil: Litterio, Mirta. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; Argentina
Fil: Castello, Liliana. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; Argentina
Fil: Venuta, María Elena. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; Argentina
Fil: Abel, Sofía. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; Argentina
Fil: Fernández Canigia, Liliana. Hospital Alemán; Argentina
Fil: Legaria, María Cristina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica; Argentina
Fil: Rollet, Raquel. Gobierno de la Ciudad de Buenos Aires. Hospital de Infecciosas "Dr. Francisco Javier Muñiz"; Argentina
Fil: Vaustat, Claudia Daniela. Gobierno de la Ciudad de Buenos Aires. Hospital de Infecciosas "Dr. Francisco Javier Muñiz"; Argentina
Fil: Azula, Natalia. Centro de Educaciones Médicas e Investigación Clínica "Norberto Quirno"; Argentina
Fil: Fox, Bárbara. Hospital Alemán; Argentina
Fil: Otero, Silvina. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; Argentina
Fil: Maldonado, María Laura. Gobierno de la Ciudad de Buenos Aires. Hospital de Pediatría "Juan P. Garrahan"; Argentina
Fil: Mangieri, Natalia Alejandra. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; Argentina
Fil: Rossetti, María Adelaida. Gobierno de la Provincia de Buenos Aires. Hospital Interzonal General de Agudos Presidente Peron.; Argentina
Fil: Predari, Silvia Carla. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; Argentina
Fil: Cejas, Daniela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Microbiología, Inmunología y Biotecnología. Cátedra de Microbiología; Argentina
Fil: Barberis, Claudia. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica; Argentina
description The aim of this study was to compare the performance of two MALDI-TOF MS systems in the identification of clinically relevant strict anaerobic bacteria. The 16S rRNA gene sequencing was the gold standard method when discrepancies or inconsistencies were observed between platforms. A total of 333 isolates were recovered from clinical samples of different centers in Buenos Aires City between 2016 and 2021. The isolates were identified in duplicate using two MALDI-TOF MS systems, BD Bruker Biotyper (Bruker Daltonics, Bremen, Germany) and Vitek MS (bioMèrieux, Marcy-l´Etoile, France). Using the Vitek MS system, the identification of anaerobic isolates yielded the following percentages: 65.5% (n: 218) at the species or species-complex level, 71.2% (n: 237) at the genus level, 29.4% (n: 98) with no identification and 5.1% (n: 17) with misidentification. Using the Bruker Biotyper system, the identification rates were as follows: 85.3% (n: 284) at the species or species-complex level, 89.7% (n: 299) at the genus level, 14.1% (n: 47) with no identification and 0.6% (n: 2) with misidentification. Differences in the performance of both methods were statistically significant (p-values <0.0001). In conclusion, MALDI-TOF MS systems speed up microbial identification and are particularly effective for slow-growing microorganisms, such as anaerobic bacteria, which are difficult to identify by traditional methods. In this study, the Bruker system showed greater accuracy than the Vitek system. In order to be truly effective, it is essential to update the databases of both systems by increasing the number of each main spectrum profile within the platforms.
publishDate 2024
dc.date.none.fl_str_mv 2024-02
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/11336/232180
Litterio, Mirta; Castello, Liliana; Venuta, María Elena; Abel, Sofía; Fernández Canigia, Liliana; et al.; Comparison of two MALDI-TOF MS systems for the identification of clinically relevant anaerobic bacteria in Argentina; Asociación Argentina de Microbiología; Revista Argentina de Microbiología; 56; 1; 2-2024; 33-61
0325-7541
1851-7617
CONICET Digital
CONICET
url http://hdl.handle.net/11336/232180
identifier_str_mv Litterio, Mirta; Castello, Liliana; Venuta, María Elena; Abel, Sofía; Fernández Canigia, Liliana; et al.; Comparison of two MALDI-TOF MS systems for the identification of clinically relevant anaerobic bacteria in Argentina; Asociación Argentina de Microbiología; Revista Argentina de Microbiología; 56; 1; 2-2024; 33-61
0325-7541
1851-7617
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://linkinghub.elsevier.com/retrieve/pii/S0325754124000014
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ram.2023.12.001
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 Asociación Argentina de Microbiología
publisher.none.fl_str_mv Asociación Argentina de Microbiología
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 13.070432

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