Please use this identifier to cite or link to this item: http://sgc.anlis.gob.ar/handle/123456789/2277
Title: Combined approach to the identification of clinically infrequent non-tuberculous mycobacteria in Argentina
Authors: Monteserin, Johana 
Paul, Roxana 
López, Beatriz 
Cnockaert, M 
Tortoli, Enrico 
Menéndez, C 
García, M J 
Palomino, Juan Carlos 
Vandamme, P 
Ritacco, V 
San Martín, A 
Keywords: Micobacterias no Tuberculosas;ARN Ribosómico 16S;Infecciones por Mycobacterium no Tuberculosas
Issue Date: 2016
Journal: The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease 
Abstract: 
Setting: Over 150 potentially pathogenic non-tuberculous mycobacteria (NTM) species have been described, posing an onerous challenge for clinical laboratory diagnosis.

Objective: To evaluate different approaches for the identification of 40 clinically relevant NTM isolates whose species were not reliably identified using our routine diagnostic workflow comprising phenotypic tests and hsp65 polymerase chain reaction restriction analysis.

Design: We used 1) sequencing analysis of four conserved gene targets: 16S rRNA, rpoB, hsp65 and sodA; 2) two commercial reverse hybridisation assays; and 3) protein analysis using matrix-assisted laser desorption/ionisation time of flight mass spectrometry (MALDI-TOF MS).

Results: Combined, but not individual, sequence analysis allowed reliable species identification for 30/40 (75%) isolates, including species previously unknown to be circulating in Argentina. Commercial kits outperformed our routine identification in only 5/35 isolates, and misclassified many more. MALDI-TOF MS accurately identified species in 22/36 (61%) isolates and did not misidentify any.

Conclusions: Commercial kits did not resolve the problem of species of NTM isolates that elude identification. Combined DNA sequence analysis was the approach of choice. MALDI-TOF MS shows promise as a powerful, rapid and accessible tool for the rapid identification of clinically relevant NTM in the diagnostic laboratory, and its accuracy can be maximised by building up a customised NTM spectrum database.
Description: 
Fil: Monteserin, Johana. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Enfermedades Infecciosas; Argentina.

Fil: Paul, Roxana. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Enfermedades Infecciosas; Argentina.

Fil: Lopez, Beatriz. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Enfermedades Infecciosas; Argentina.

Fil: Cnockaert, M. University Ghent. Department of Biochemistry and Microbiology. Laboratory of Microbiology; Belgica.

Fil: Tortoli, Enrico. Istituto di Ricovero e Cura a Carattere Scientifico San Raffaele Scientific Institute; Italia.

Fil: Menéndez, C. Universidad Autónoma de Madrid. Facultad de Medicina. Departamento de Medicina Preventiva; España.

Fil: García, M. J. Universidad Autónoma de Madrid. Facultad de Medicina. Departamento de Medicina Preventiva; España.

Fil: Palomino, Juan Carlos. University Ghent. Department of Biochemistry and Microbiology. Laboratory of Microbiology; Belgica.

Fil: Vandamme, P. University Ghent. Department of Biochemistry and Microbiology. Laboratory of Microbiology; Belgica.

Fil: Ritacco, V. ANLIS Dr.C.G.Malbrán. Instituto Nacional de Enfermedades Infecciosas; Argentina.

Fil: Martin, A. University Ghent. Department of Biochemistry and Microbiology. Laboratory of Microbiology; Belgica.
URI: http://sgc.anlis.gob.ar/handle/123456789/2277
DOI: 10.5588/ijtld.16.0122
Rights: Closed Access
Appears in Collections:Publicaciones INEI

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