Detection of azole resistance in Aspergillus fumigatus complex isolates using MALDI-TOF mass spectrometry

Zvezdánova, Margarita Estreya; Arroyo, Manuel J.; Méndez, Gema; Candela, Ana; Mancera, Luis; Rodríguez, Julio García; Serra, Julia Lozano; Jiménez, Rosa María Rodríguez; Lozano, Irene Iglesias; Castro, Carmen; López, Concepción; Muñóz, Patricia; Guinea, Jesús; Escribano, Pilar; Rodríguez‐Sánchez, Belén

doi:10.1016/j.cmi.2021.06.005

Cited by 15 publications

(11 citation statements)

References 29 publications

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“…The application of break points relies on accurate species-level identification; this has improved for yeasts with the increasing use of MALDI-TOF mass spectrometry systems, but for moulds is still dependent on local database content 58 . Direct detection of antifungal resistance with the MALDI-TOF platform for yeasts 59 and moulds 60 is an exciting new direction; however, MALDI-TOF is too costly for many centres (thereby complicating international resistance surveillance initiatives) and reliance on culturing increases the time to diagnosis.…”

Section: Diagnostics and Surveillancementioning

confidence: 99%

Tackling the emerging threat of antifungal resistance to human health

et al. 2022

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Invasive fungal infections pose an important threat to public health and are an under-recognized component of antimicrobial resistance, an emerging crisis worldwide. Across a period of profound global environmental change and expanding at-risk populations, human-infecting pathogenic fungi are evolving resistance to all licensed systemic antifungal drugs. In this Review, we highlight the main mechanisms of antifungal resistance and explore the similarities and differences between bacterial and fungal resistance to antimicrobial control. We discuss the research and innovation topics that are needed for risk reduction strategies aimed at minimizing the emergence of resistance in pathogenic fungi. These topics include links between the environment and One Health, surveillance, diagnostics, routes of transmission, novel therapeutics and methods to mitigate hotspots for fungal adaptation. We emphasize the global efforts required to steward our existing antifungal armamentarium, and to direct the research and development of future therapies and interventions.

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Section: Diagnostics and Surveillancementioning

confidence: 99%

Tackling the emerging threat of antifungal resistance to human health

et al. 2022

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“…Matrix‐assisted laser desorption/ionisation time‐of‐flight mass spectrometry (MALDI‐TOF MS) has been investigated as a tool for Aspergillus spp. identification including cryptic species 34–36 . In addition, Zvezdanova et al reported that MALDI‐TOF MS has the potential ability to discriminate between susceptible and azole‐resistant A. fumigatus sensu stricto isolates 36 .…”

Section: Discussionmentioning

confidence: 99%

“…identification including cryptic species 34–36 . In addition, Zvezdanova et al reported that MALDI‐TOF MS has the potential ability to discriminate between susceptible and azole‐resistant A. fumigatus sensu stricto isolates 36 . It is essential to improve the mass spectrometry database of Aspergillus spp.…”

Section: Discussionmentioning

confidence: 99%

The accuracy and clinical impact of the morphological identification of Aspergillus species in the age of cryptic species: A single‐centre study

Takeda

Suzuki

Watanabe

et al. 2021

Mycoses

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Background Aspergillus spp. is identified morphologically without antifungal susceptibility tests (ASTs) in most clinical laboratories. The aim of this study was to examine the clinical impact of the morphological identification of Aspergillus spp. to ensure the adequate clinical management of Aspergillus infections. Patients/Methods Aspergillus isolates (n = 126) from distinct antifungal treatment‐naïve patients with aspergillosis were first identified morphologically, followed by species‐level identification via DNA sequencing. An AST for itraconazole (ITC) and voriconazole (VRC) was performed on each Aspergillus isolate. Results Based on the genetic test results, morphology‐based identification was accurate for >95% of the isolates at the species sensu lato level although the test concordance of Aspergillus spp. with low detection rates was low. The rates of cryptic species were found to be 1.2% among the isolates of A. fumigatus complex and 96.8% in the A. niger complex. Cryptic species with lower susceptibilities to antifungal drugs than sensu stricto species among the same Aspergillus section were as follows: The A. lentulus (n = 1) isolates had low susceptibilities to azoles among the A. fumigatus complex species (n = 86), and A. tubingensis isolates (n = 18) exhibited lower susceptibility to azoles among the A. niger complex species (n = 31). Conclusion Diagnostic accuracy was high at the A. fumigatus and A. niger complex level. However, in the presence of cryptic species, a solely morphological identification was insufficient. Particularly, ITC and VRC might be inappropriate for aspergillosis treatment when the A. niger complex is identified morphologically because it is possible that the Aspergillus isolate is A. tubingensis.

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“…Next, 1µl of HCCA matrix solution (Bruker Daltonics) have been added to each spot. The MALDI-TOF spectra has been acquired in positive linear mode in the range of 2,000 to 20,000 Da, using default settings [31], although only data between 2,000-12,000 m/z [32], [33] has been used.…”

Section: A Isolates Selection and Processingmentioning

confidence: 99%

Automatic antibiotic resistance prediction inKlebsiella pneumoniaebased on MALDI-TOF mass spectra

Guerrero-López

Candela

Sevilla-Salcedo

et al. 2021

Preprint

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Objectives: MALDI-TOF Mass Spectrometry (MS) is a reference method for microbial identification at clinical microbiology laboratories. We have designed and validated a new multiview model based on machine learning from MS spectra to predict antibiotic resistance mechanisms 24 h before phenotypic results are available. Methods: Antibiotic susceptibility of 402 clinical Klebsiella pneumoniae isolates was determined in two collections, discriminating among Wild Type (WT), Extended-Spectrum Beta-Lactamases (ESBL) producers, and ESBL and Carbapenemases (ESBL+CP) producers. Each isolate was subcultured 3 consecutive days and 2 independent spectra were acquired in each replica (6 MS spectra/isolate). Spectra were automatically classified by a kernelized Bayesian factor analysis model (KSSHIBA), using two independent strategies: 1) the model was designed with isolates from a single center and validated with isolates from the other center; and 2) in a second stage all isolates were used at the same time for design and validation processes. Results: Higher prediction values were obtained when integrating all isolates with hospital collection of origin information. Our model exhibited higher prediction capability than current state-of-the-art models, particularly in intercollection scenarios because local epidemiology could introduce relevant variables affecting prediction accuracy. Conclusions: Compared to previously reported studies, our model demonstrated the highest ability to predict ESBL and/or CP production in clinical K. pneumoniae isolates and it provided an efficient way to combine information from different centers. Its implementation in microbiological laboratories could improve the detection of multi-drug resistant isolates, optimizing the therapeutic decision.

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Detection of azole resistance in Aspergillus fumigatus complex isolates using MALDI-TOF mass spectrometry

Cited by 15 publications

References 29 publications

Tackling the emerging threat of antifungal resistance to human health

Tackling the emerging threat of antifungal resistance to human health

The accuracy and clinical impact of the morphological identification of Aspergillus species in the age of cryptic species: A single‐centre study

Automatic antibiotic resistance prediction inKlebsiella pneumoniaebased on MALDI-TOF mass spectra

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