The use of multi-locus DNA sequence analysis has led to the description of previously unknown 'cryptic' Aspergillus species, whereas classical morphology-based identification of Aspergillus remains limited to the section or species-complex level. The current literature highlights two main features concerning these 'cryptic' Aspergillus species. First, the prevalence of such species in clinical samples is relatively high compared with emergent filamentous fungal taxa such as Mucorales, Scedosporium or Fusarium. Second, it is clearly important to identify these species in the clinical laboratory because of the high frequency of antifungal drug-resistant isolates of such Aspergillus species. Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) has recently been shown to enable the identification of filamentous fungi with an accuracy similar to that of DNA sequence-based methods. As MALDI-TOF MS is well suited to the routine clinical laboratory workflow, it facilitates the identification of these 'cryptic' Aspergillus species at the routine mycology bench. The rapid establishment of enhanced filamentous fungi identification facilities will lead to a better understanding of the epidemiology and clinical importance of these emerging Aspergillus species. Based on routine MALDI-TOF MS-based identification results, we provide original insights into the key interpretation issues of a positive Aspergillus culture from a clinical sample. Which ubiquitous species that are frequently isolated from air samples are rarely involved in human invasive disease? Can both the species and the type of biological sample indicate Aspergillus carriage, colonization or infection in a patient? Highly accurate routine filamentous fungi identification is central to enhance the understanding of these previously unknown Aspergillus species, with a vital impact on further improved patient care.

BackgroundSeveral Matrix-Assisted Laser Desorption/Ionization Time-of-Flight mass spectrometry protocols, which differ in identification criteria, have been developed for mold and dermatophyte identification. Currently, the most widely used approach is Bruker technology, although no consensus concerning the log(score) threshold has been established. Furthermore, it remains unknown how far increasing the number of spots to compare results might improve identification performance.In this study, we used in-house and Bruker reference databases as well as a panel of 422 isolates belonging to 126 species to test various thresholds. Ten distinct identification algorithms requiring one to four spots were tested.ResultsOur findings indicate that optimal results were obtained by applying a decisional algorithm in which only the highest score of four spots was taken into account with a 1.7 log(score) threshold. Testing the entire panel enabled identification of 87.41% (in-house database) and 35.15% (Bruker database) of isolates, with a positive predictive value (PPV) of 1 at the genus level for both databases as well as 0.89 PPV (in-house database) and 0.72 PPV (Bruker database) at the species level. Applying the same rules to the isolates for which the species were represented by at least three strains in the database enabled identification of 92.1% (in-house database) and 46.6% (Bruker database) of isolates, with 1 PPV at the genus level for both databases as well as 0.95 PPV (in-house database) and 0.93 PPV (Bruker database) at the species level.ConclusionsDepositing four spots per extract and lowering the threshold to 1.7, a threshold which is notably lower than that recommended for bacterial identification, decreased the number of unidentified specimens without altering the reliability of the accepted results. Nevertheless, regardless of the criteria used for mold and dermatophyte identification, commercial databases require optimization.Electronic supplementary materialThe online version of this article (doi:10.1186/s12866-017-0937-2) contains supplementary material, which is available to authorized users.