LAUSR

The taxonomy of Aspergillus species has recently been revolutionized with the introduction of cryptic species and section concepts. However, their species-level identification in routine laboratories remains a challenge. The aim of this study was to prospectively assess the identification accuracy of cryptic species of Aspergillus in various laboratories using the mass spectrometry identification (MSI) platform, an independent and freely accessible online mass spectrometry database. Over a 12-month period, when a select set of MSI users identified cryptic species, they were contacted and requested to send the isolates to our laboratory for sequence-based identification. Sequence and MSI identification results were then compared. During the study period, 5108 Aspergillus isolates were identified using MSI including 1477 (28.9%) cryptic species. A total of 245 isolates that corresponded to 56 cryptic species and 13 sections were randomly selected for DNA sequencing confirmation. Agreement between the two methods was 99.6% at the section level and 66.1% at the species level. However, almost all discrepancies (72/83, 86.7%) were misidentifications between closely related cryptic species belonging to the same section. Fifty-one isolates from noncryptic species were also identified, thus yielding 100% and 92.2% agreement at the section and species level, respectively. Although the MSI fungus database is a reliable tool to identify Aspergillus at the section level, the database still requires adjustment to correctly identify rare or cryptic species at the species level. Nevertheless, the application properly differentiated between cryptic and sensu stricto species in the same section, thus alerting on possible specific isolate characteristics.