Why robust identification of rare yeasts is the need of the hour

Infections caused by rare yeasts are surging, mainly due to the increase in immunocompromised or seriously ill patients. With the increasing clinical significance of rare yeasts, there is an urgent need for a rapid diagnostic method. The current process relies on the PCR of the ribosomal gene's internal transcribed spacer (ITS) region, followed by sequencing and BLAST search, which are labor- and time-intensive. Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has revolutionized the rapid identification of yeasts at the species level. One limitation of MALDI-TOF MS is the inadequacy or lack of main spectrum profiles (MSPs) in the reference library, which results in low scores and no organism identification. The focus of this study was to create an in-house Bruker library for 141 rare yeast isolates, representing 25 genera and 68 species of which 31 species had no MSPs, and 37 species were poorly represented in the commercial Bruker library. Protein extraction using the ethanol/formic acid method with a few yeasts requiring a bead-beating step before protein extraction was employed for library construction. A minimum of 20 spectra and a log (score) of ≥1.9 were used for species-level identification. Upon library construction, all 141 rare yeast isolates were successfully identified to the species level with a log (score) of 2.0 or higher. In conclusion, MALDI-TOF MS with enriched in-house Bruker library is a powerful tool for identifying rare yeasts, offering speed, accuracy, and clinical relevance.

The infection caused by rare yeasts among immunocompromised or seriously ill patients is on the rise. Therefore, a comprehensive and rapid method for accurate identification is urgently needed. We have addressed this need by enriching the in-house Bruker library by adding 141 rare yeast isolates, representing 25 genera and 68 species. This comprehensive update has resulted in improved turnaround time, a development that will significantly enhance patient management by providing more timely and accurate identification of rare yeast infections, thereby improving patient outcomes. Moreover, the enriched library spectrum profiles generated in this study have been made publicly available through the Centers for Disease Control and Prevention's MicrobeNet database (https://MicrobeNet.cdc.gov), enabling collaboration in the scientific community.