ABSTRACT
Abstract 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.
Resumen El objetivo de este estudio fue comparar el desempeño de dos sistemas MALDI-TOF MS en la identificación de bacterias anaerobias estrictas de interés clínico. La secuenciación del gen 16S ARNr fue el método de referencia utilizado cuando se observaron discrepancias o inconsistencias entre plataformas. Se recuperaron 333 aislados de muestras clínicas de diferentes centros de la Ciudad Autónoma de Buenos Aires entre 2016 y 2021. Los aislados se identificaron por duplicado mediante dos sistemas MALDI-TOF MS: el BD Bruker Biotyper (Bruker Daltonics, Bremen, Alemania) y el Vitek MS (bioMèrieux, Marcy-l'Etoile, Francia). A través del sistema Vitek MS, los mismos fueron identificados a nivel de especie o complejo de especies en un 65,5% (n: 218) y de género en un 71,2% (n: 237), mientras que no se identificaron en un 29,4% (n: 98) y fue incorrecta en el 5,1% (n: 17). Mediante el sistema Bruker Biotyper, dichos valores fueron del 85,3% (n: 284), del 89,7% (n: 299), del 14,1% (n: 47) y del 0,6% (n: 2), respectivamente. La diferencia entre ambos métodos fue estadísticamente significativa (p<0,0001). En conclusión, los sistemas MALDI-TOF MS aceleran la identificación microbiana. Son especialmente útiles para los microorganismos de crecimiento lento, como las bacterias anaerobias, que son difíciles de identificar con los métodos tradicionales. El sistema Bruker demostró ser más preciso que el Vitek MS. Para que estos métodos sean realmente efectivos es fundamental actualizar las bases de datos de ambos sistemas e incrementar el número de espectros de referencia dentro de las plataformas.
ABSTRACT
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.
Subject(s)
Bacteria, Anaerobic , Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization/methods , Bacteria, Anaerobic/genetics , RNA, Ribosomal, 16S/genetics , ArgentinaABSTRACT
Two commercial MALDI-TOF MS systems were used to identify 18 isolates, belonging to the Peptoniphilus genus; also the 16S rRNA sequencing identity was compared against the MALDI-TOF MS system results. Bruker Biotyper system provided higher accuracy than Vitek MS system, however, adding spectra could allow a more reliable species level identification.
Subject(s)
Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization , Bacterial Typing Techniques/methods , RNA, Ribosomal, 16S/genetics , Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization/methodsABSTRACT
BACKGROUND: The epidemiology of osteoarticular infections (IOA) has changed in recent years. The incidence of Kingella kingae in Latin America is unknown. AIMS: To describe the epidemiology in patients with IOA in a children hospital. To estimate the incidence of IOA due to K. kingae and compare with other etiologies. METHODS: Prospective cohort. Patients older than 1 month hospitalized between March, 1th 2017 and February, 28th 2019 with suspected IOA and diagnostic procedure (biopsy or arthrocentesis) were included. STATA 13 was used. RESULTS: n: 84 patients. The etiology was identified in 58 patients (69.1%). Staphylococus aureus predominated (n: 44; 52.4%) and K. kingae (n: 9; 10.8%). In the period studied, the incidence of IOA by K. kingae was 10.8 cases per 100 hospitalized IOA. In multivariate analysis, age less than 4 years (OR 13.8, 95% CI 5.5-82.7), recent respiratory symptoms (OR 5.7, 95% CI 3.5-31.6, p 0.04) and normalization before the fifth day of C-reactive protein (CRP) (OR 3.38 95% CI 1.8-16.3, p 0.01) were associated with IOA by K. kingae. CONCLUSIONS: In this cohort of children the incidence of K. kingae was 10.8 cases per 100 IOA. Kingella kingae represented the second documented etiology, after S. aureus. Age under 4 years, recent respiratory symptoms and normalization before the fifth day of quantitative CRP were statistically associated with IOA by K. kingae.
Subject(s)
Arthritis, Infectious , Kingella kingae , Neisseriaceae Infections , Child , Hospitals, Pediatric , Humans , Prospective Studies , Staphylococcus aureusABSTRACT
Resumen Introducción: La epidemiología de las infecciones osteo-articulares (IOA) se ha modificado en los últimos años. La incidencia de Kingella kingae en Latinoamérica es desconocida. Objetivo: Describir la epidemiología de los niños con IOA. Estimar la incidencia de IOA causadas por K. kingae y compararlas con otras etiologías. Material y Métodos: Cohorte prospectiva. Se incluyeron pacientes mayores de 1 mes de edad, hospitalizados entre el 1 de marzo de 2017 y 28 de febrero de 2019, con sospecha de IOA y procedimiento diagnóstico (biopsia o artrocentesis). Se utilizó STATA 13. Resultados: n: 84 pacientes. Se identificó la etiología en 58 pacientes (69,1%). Predominaron Staphylococcus aureus (n: 44; 52,4%) y K. kingae (n: 9; 10,8%). En el período estudiado, la incidencia de IOA por K. kingae fue de 10,8 casos cada 100 IOA hospitalizadas. En el análisis multivariado, la edad inferior a 4 años (OR 13,8, IC95% 5,5-82,7), el cuadro respiratorio reciente (OR 5,7, IC95% 3,5-31,6, p 0,04) y la normalización antes del quinto día de la proteína C reactiva (PCR) (OR 3,8 IC95% 1,8- 16,3, p 0,01) se asociaron con las IOA por K. kingae. Conclusiones: En esta cohorte de niños, la incidencia de K.kingae fue de 10,8 casos cada 100 IOA. Kingella kingae representó la segunda etiología documentada, luego de S. aureus. La edad inferior a 4 años, el cuadro respiratorio reciente y la normalización antes del quinto día de la PCR cuantitativa se asociaron estadísticamente con IOA por K. kingae.
Abstract Background: The epidemiology of osteoarticular infections (IOA) has changed in recent years. The incidence of Kingella kingae in Latin America is unknown. Aims: To describe the epidemiology in patients with IOA in a children hospital. To estimate the incidence of IOA due to K. kingae and compare with other etiologies. Methods: Prospective cohort. Patients older than 1 month hospitalized between March, 1th 2017 and February, 28th 2019 with suspected IOA and diagnostic procedure (biopsy or arthrocentesis) were included. STATA 13 was used. Results: n: 84 patients. The etiology was identified in 58 patients (69.1%). Staphylococus aureus predominated (n: 44; 52.4%) and K. kingae (n: 9; 10.8%). In the period studied, the incidence of IOA by K. kingae was 10.8 cases per 100 hospitalized IOA. In multivariate analysis, age less than 4 years (OR 13.8, 95% CI 5.5-82.7), recent respiratory symptoms (OR 5.7, 95% CI 3.5-31.6, p 0.04) and normalization before the fifth day of C-reactive protein (CRP) (OR 3.38 95% CI 1.8-16.3, p 0.01) were associated with IOA by K. kingae. Conclusions: In this cohort of children the incidence of K. kingae was 10.8 cases per 100 IOA. Kingella kingae represented the second documented etiology, after S. aureus. Age under 4 years, recent respiratory symptoms and normalization before the fifth day of quantitative CRP were statistically associated with IOA by K. kingae.
