MALDI-TOF MS in a Medical Mycology Laboratory: On Stage and Backstage

Abstract

The implementation of MALDI-TOF MS in medical microbiology laboratories has revolutionized practices and significantly reduced turnaround times of identification processes. However, although bacteriology quickly benefited from the contributions of this technique, adjustments were necessary to accommodate the specific characteristics of fungi. MALDI-TOF MS is now an indispensable tool in clinical mycology laboratories, both for the identification of yeasts and filamentous fungi, and other innovative uses are gradually emerging. Based on the practical experience of our medical mycology laboratory, this review will present the current uses of MALDI-TOF MS and the adaptations we implemented, to allow their practical execution in a daily routine. We will also introduce some less mainstream applications, like those for fungemia, or even still under development, as is the case for the determination of sensitivity to antifungal agents or typing methods.

Implementation of MALDI-TOF Mass Spectrometry to Identify Fungi From the Indoor Environment as an Added Value to the Classical Morphology-Based Identification Tool

“…. (20). Therefore, it seems that databases should be constantly updated and extended with new encountered fungal and yeasts species in order to improve the species coverage of MALDI-TOF MS reference databases, which is currently still a limitation, as noted by Bader (27), Becker et al (19), and Sanguinetti and Posteraro (26).…”

Combination of MALDI-TOF Mass Spectrometry and Machine Learning for Rapid Antimicrobial Resistance Screening: The Case of Campylobacter spp.

“…MALDI-TOF MS is a soft-ionized mass spectrometry method developed as an analytical tool to identify and understand the structure of unknown biomolecules (Gibson and Costello, 2000). In an evolving field, this automatic technique became the reference method for identifying microorganisms such as bacteria (Clark et al, 2013;Singhal et al, 2015), mycobacteria (Rodriguez-Granger et al, 2018;Rotcheewaphan et al, 2019) and fungi (Florio et al, 2018;Robert et al, 2021). The resolution power of the system operates at the species level and even at sub-species level for a number of pathogens in clinical microbiology (Fall et al, 2015;Feucherolles et al, 2021).…”

Fungal infections diagnosis – Past, present and future

“… Prior extraction step is required; Incapable of performing quantification; High initial instrument cost; Limit species coverage in the fungal reference databases of available MALDI-TOF MS systems; Databases require continuous updates to cover rarest and emergent fungal species. [ 34 , 35 , 77 , [79] , [80] , [81] , 176 ] Biochemical Phenotypic Identification Systems a Reduced costs; Allows quantitative and qualitative information; Accurate identification of an unknown sample; Several commercially available platforms. Laborious methods and time-consuming; Results are only provided after a few days; Low sensitivity to identify and distinguish emergent pathogenic species, such as C. auris.…”

“…Overall, common yeast and moulds are mostly well covered in commercially available databases, but the same does not happen for new, rarer, or cryptic species. It seems that the best approach to improve the identification of these species is to continuously update the commercial databases or to complement them with homemade reference libraries and other online databases, such as MicrobeNet (developed by CDC), and the Mass Spectrometry Identification platform [ 79 ].…”