Matrix-Assisted Laser Desorption Ionization Time-of-Flight for Fungal Identification

Introduction

The identification of yeasts and filamentous fungi (molds) has historically relied on a combination of phenotypic and morphologic characteristics. Recent studies, however, have uncovered a vast array of species-complexes and cryptic species that can only be reliably identified by the use of more delineated and targeted testing platforms, such as sequencing and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). Around 2010, MALDI-TOF MS technology was launched into the clinical microbiology field, and was a game-changer because clinical laboratories could now identify organisms from crude protein suspensions within minutes, at low processing costs, and minimal processing time. The accuracy of MALDI-TOF MS for organism identification was equivalent to DNA sequencing, and its ease of use led it to be a highly sought after platform in multiple fields including clinical microbiology, veterinary care, the food and beverage industry, and environmental microbiology. Currently, there are two main MALDI-TOF MS systems on the market: MALDI BioTyper (MBT; Bruker Scientific, Billerica, MA) and VITEK MS (BioMerieux, Marcy-l’Etoile, France). The MBT was cleared by the Food and Drug Administration (FDA) in 2013 for bacteria and yeast identification only, although a separate FilFungal database became available in 2012 for mold identification for research use only (RUO). In contrast, the VITEK MS version 3.0 was cleared by the FDA in 2017 with a database that expanded bacteria, yeasts, mold, and mycobacteria. The critical role of databases and processing methods is addressed in this review because methods have evolved considerably over time.

Today, MALDI-TOF MS has become a mainstream platform in most clinical laboratories for bacterial identification. However, its application in clinical mycology for yeast and mold identification has been lagging, which is mostly attributable to the lack of standardized processes and poor fungal database representation. In fact, clinical mycology expertise is sorely lacking in laboratories worldwide and MALDI-TOF MS has the potential to fill this knowledge gap. In 2018, a survey of 348 tertiary care hospitals in China were reported to have insufficient clinical mycology testing capacity. ¹ Similarly, 241 laboratories surveyed across seven Asian countries reported that only 53.5% of participants had designated mycology laboratories and that nearly all participants used traditional microscopy and culture methods for fungal identification; only 16.9% and 12.3% performed DNA sequencing and MALDI-TOF MS, respectively, for organism identification. ² Participant surveys from the 2019 and 2020 College of American Pathologists mycology proficiency testing program, which comprises up to approximately 1000 laboratories (most from the United States), also showed that only approximately 50% of laboratories used MALDI-TOF MS for yeast identification, whereas less than 7% of laboratories used MALDI-TOF MS for mold identification.

Clearly, the waning availability of mycologic expertise in front-line laboratories and the need for accurate fungal identification (particularly for capture of cryptic species that generally have higher resistance profiles) leads to an urgent need to expand the application of MALDI-TOF MS into clinical mycology. This review provides an overview of the current status of MALDI-TOF MS for fungal identification, including key findings in the literature, processing and database considerations, updates in technology, and future prospects.