Margarita Estreya Zvezdanova1, Manuel J Arroyo2, Gema Méndez2, Ana Candela1, Luis Mancera2, Julio García Rodríguez3, Julia Lozano Serra4, Rosa Jiménez5, Inmaculada Lozano6, Carmen Castro7, Concepción López8, Patricia Muñoz9, Jesús Guinea10, Pilar Escribano11, Belén Rodríguez-Sánchez1. 1. Clinical Microbiology and Infectious Diseases Department, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain. 2. Clover Bioanalytical Software, Av. de la Innovación, Granada, Spain. 3. Clinical Microbiology Department, Hospital La Paz, Madrid, Spain. 4. Clinical Microbiology Department, Hospital General de Albacete, Albacete, Spain. 5. Clinical Microbiology Department, Complejo Hospitalario de Toledo, Toledo, Spain. 6. Clinical Microbiology Department, Hospital Universitario Puerta del Mar, Cádiz, Spain. 7. Clinical Microbiology Department, Hospital de Valme, Seville, Spain. 8. Clinical Microbiology Department, Hospital Universitario Miguel Servet, Zaragoza, Spain; Instituto de Investigación Sanitaria Aragón, Universidad de Zaragoza, Zaragoza, Spain. 9. Clinical Microbiology and Infectious Diseases Department, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain; CIBER de Enfermedades Respiratorias (CIBERES CB06/06/0058), Madrid, Spain; Medicine Department, School of Medicine, Universidad Complutense de Madrid, Madrid, Spain. 10. Clinical Microbiology and Infectious Diseases Department, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain; CIBER de Enfermedades Respiratorias (CIBERES CB06/06/0058), Madrid, Spain. 11. Clinical Microbiology and Infectious Diseases Department, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain. Electronic address: pilar.escribano.martos@gmail.com.
Abstract
OBJECTIVES: The main goal of this study was to accurately detect azole resistance in species of the Aspergillus fumigatus complex by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). METHODS: Identification of isolates (n = 868) was done with MALDI-TOF MS using both commercial and in-house libraries. To determine azole susceptibility, the EUCAST E.Def. 9.3.2 method was applied as the reference standard. Identification of resistant isolates was confirmed by DNA sequence analysis. Protein spectra obtained by MALDI-TOF MS were analysed to differentiate species within the A. fumigatus complex and to detect azole-resistant A. fumigatus sensu stricto isolates. RESULTS: Correct discrimination of A. fumigatus sensu stricto from cryptic species was accomplished in 100% of the cases applying principal component analysis (PCA) to protein spectra generated by MALDI-TOF MS. Furthermore, a specific peak (4586 m/z) was found to be present only in cryptic species. The application of partial least squares (PLS) discriminant analysis allowed 98.43% (±0.038) discrimination between susceptible and azole-resistant A. fumigatus sensu stricto isolates. Finally, based on PLS and SVM, A. fumigatus sensu stricto isolates with different cyp51A gene mutations were correctly clustered in 91.5% of the cases. CONCLUSIONS: MALDI-TOF MS combined with peak analysis is a novel tool that allows the differentiation of A. fumigatus sensu stricto from other species within the A. fumigatus complex, as well as the detection of azole-resistant A. fumigatus sensu stricto. Although further studies are still needed, the results reported here show the great potential of MALDI-TOF and machine learning for the rapid detection of azole-resistant Aspergillus fumigatus isolates from clinical origins.
OBJECTIVES: The main goal of this study was to accurately detect azole resistance in species of the Aspergillus fumigatus complex by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). METHODS: Identification of isolates (n = 868) was done with MALDI-TOF MS using both commercial and in-house libraries. To determine azole susceptibility, the EUCAST E.Def. 9.3.2 method was applied as the reference standard. Identification of resistant isolates was confirmed by DNA sequence analysis. Protein spectra obtained by MALDI-TOF MS were analysed to differentiate species within the A. fumigatus complex and to detect azole-resistant A. fumigatus sensu stricto isolates. RESULTS: Correct discrimination of A. fumigatus sensu stricto from cryptic species was accomplished in 100% of the cases applying principal component analysis (PCA) to protein spectra generated by MALDI-TOF MS. Furthermore, a specific peak (4586 m/z) was found to be present only in cryptic species. The application of partial least squares (PLS) discriminant analysis allowed 98.43% (±0.038) discrimination between susceptible and azole-resistant A. fumigatus sensu stricto isolates. Finally, based on PLS and SVM, A. fumigatus sensu stricto isolates with different cyp51A gene mutations were correctly clustered in 91.5% of the cases. CONCLUSIONS: MALDI-TOF MS combined with peak analysis is a novel tool that allows the differentiation of A. fumigatus sensu stricto from other species within the A. fumigatus complex, as well as the detection of azole-resistant A. fumigatus sensu stricto. Although further studies are still needed, the results reported here show the great potential of MALDI-TOF and machine learning for the rapid detection of azole-resistant Aspergillus fumigatus isolates from clinical origins.
Authors: Matthew C Fisher; Ana Alastruey-Izquierdo; Judith Berman; Tihana Bicanic; Elaine M Bignell; Paul Bowyer; Michael Bromley; Roger Brüggemann; Gary Garber; Oliver A Cornely; Sarah J Gurr; Thomas S Harrison; Ed Kuijper; Johanna Rhodes; Donald C Sheppard; Adilia Warris; P Lewis White; Jianping Xu; Bas Zwaan; Paul E Verweij Journal: Nat Rev Microbiol Date: 2022-03-29 Impact factor: 78.297
Authors: Lucas C Lazari; Rodrigo M Zerbinati; Livia Rosa-Fernandes; Veronica Feijoli Santiago; Klaise F Rosa; Claudia B Angeli; Gabriela Schwab; Michelle Palmieri; Dmitry J S Sarmento; Claudio R F Marinho; Janete Dias Almeida; Kelvin To; Simone Giannecchini; Carsten Wrenger; Ester C Sabino; Herculano Martinho; José A L Lindoso; Edison L Durigon; Paulo H Braz-Silva; Giuseppe Palmisano Journal: J Oral Microbiol Date: 2022-02-27 Impact factor: 5.474