The epidemiology of candidemia has substantially changed over the last decades with the emergence of individual species formerly classified into the nonalbicans Candida species group, known for variability in susceptibility to antifungals and typically isolated from those most unlikely to battle the infection, the immunocompromised and other compromised subpopulations. This inherent variability highlights the need for the proper identification of Candida spp. to enhance regional choices for prophylaxis and empirical treatment and to further characterize the epidemiology of infections. For example, recent studies of Candida species outbreaks showed an increased incidence of bloodstream infections in neonatal intensive care units (NICUs) caused by C. parapsilosis. Species-specific differentiation of two closely related yeasts, Candida albicans and C. dubliniensis, is important to better understand the epidemiology and virulence of C. dubliniensis.
MALDI-TOF MS shows its potential for the rapid identification of
C. albicans and related species. In a study by Pinto et al., MALDI-TOF MS was performed on a 264-strain library composed of clinical and reference strains. Discordant and unreliable identifications were resolved by sequencing of the internal transcribed spacer (ITS) region of the rRNA gene cluster. In this analysis, 20 (67%; 16 species) and 24 (80%) of 30 reference strains were identified to the species (spectral score, ≥2.0) and genus (score, ≥1.70) levels, respectively. Of clinical isolates, 140/167 (84%) strains were correctly identified with scores of ≥2.0, and 160/167 (96%) strains were correctly identified with scores of ≥1.70; among
Candida spp. (
n = 148), correct species assignment with scores of ≥2.0, and ≥1.70 were obtained for 86% and 96% of isolates, respectively (versus 76.4% correct assignments by biochemical methods). MALDI-TOF MS identified uncommon
Candida spp., differentiated
C. parapsilosis from
C. orthopsilosis and
C. metapsilosis, and distinguished between
C. glabrata,
C. nivariensis, and
C. bracarensis. Yeasts with scores of <1.70 included 4/12
Cryptococcus neoformans isolates. When protein extraction was used, there were no misidentifications in the data set (
266).
A total of 18 type collection strains and 267 recent clinical isolates (
Candida [
n = 250],
Cryptococcus,
Saccharomyces,
Trichosporon,
Geotrichum,
Pichia, and
Blastoschizomyces spp.) were identified by BioTyper analysis. The results were compared with those obtained by conventional phenotyping and biochemical tests including the API ID 32C system (bioMérieux) and other biochemical tests. After complementation of the database, with species identification from 26S rRNA gene sequencing, accurate species identification by MALDI-TOF MS was achieved for all isolates. In contrast, the API ID 32C biochemical diagnostic system identified 244 isolates (
210).
Discrimination between
C. albicans and
C. dubliniensis is possible by using MS methods, as demonstrated by analysis of reference strains from type culture collections and other well-characterized isolates. The spectra of
C. albicans and
C. dubliniensis easily differentiated species, and further study revealed that each species consists of several clades, which could be distinguished by MALDI-TOF MS (
267).
Dermatological yeast isolates were tested by Seyfarth et al. using MALDI-TOF MS, the API ID 32C system, and sequencing of the ITS regions of ribosomal DNA. The accuracy of MALDI-TOF MS compared to the results derived from ITS sequence analysis was 94%, whereas API ID 32C was accurate for only 84.3% of the isolates. Species tested included
C. albicans (41.9%),
C. parapsilosis (20.3%),
C. glabrata (10.8%), and
C. krusei (6 isolates) (8.1%). Rarely isolated yeasts, including
C. colliculosa,
C. famata,
C. guilliermondii,
C. lusitaniae, and
C. tropicalis, as well as
Geotrichum candidum,
Rhodotorula mucilaginosa, and
Trichosporon mucoides were also correctly identified. For the API ID system,
C. kruseiwas incorrectly identified as
C. inconspicua/C. norvegensis,
Candida tropicalis, or
Geotrichum capitatum. In contrast, all
C. krusei strains were correctly identified with discriminatory power comparatively similar to that of ITS sequence analysis (
268).
Similar to the BioTyper, accurate results were observed by using the Confidence Axima system (Shimadzu) with Shimadzu Launchpad software and the SARAMIS database (AnagnosTec GmbH). Nonalbicans
Candida spp. (
n = 73) isolated from noninvasive samples were tested by using the Vitek-2 systems YST and API CAUX, identifying 67 yeast isolates to the species level and 6 to the genus level. Discrepancies were resolved by SeptiFast LightCycler multiplex PCR,
C. glabrata-specific PCR, and enzymatic digestion (
269).
For the Andromas system, the accuracy for identification of
Candida spp. is also quite high. Using the Andromas software and MALDI-TOF MS, Bille et al. analyzed 162 yeast isolates and found 96.3% accuracy for the first acquisition of spectra and 98.8% accuracy after a second acquisition (
53).
After constructing an in-house database (
270), Marklein et al. used the BioTyper system to identify 267 clinical isolates and 18 collection strains of yeast and yeast-like fungi (
210).
Candida spp. were correctly identified for 240/250 (96%) clinical isolates on the first attempt, with no false-positive results. Investigation of the discrepancies between biochemical MALDI-TOF MS identifications by 26S rRNA gene sequencing resulted in 100% identification to the species level. The same procedure used for identification of the 17 clinical isolates of yeast-like fungi identified 100% of isolates to the species level.
Stevenson et al. reported accurate identification of 194 clinical isolates after implementation of a database containing 109 type and reference strains of yeasts from 44 different species. Correct identification to the species level with a score of ≥1.8 was obtained for 192 (99%) isolates (
271). Finally, in the largest set of yeasts ever tested for analysis of MALDI-TOF MS performance for identification, Bader et al. tested two systems, BioTyper and SARAMIS (
264). Twenty-one species, representing 1,148 isolates of yeast, were tested, with large sample sizes for
C. albicans,
C. glabrata,
C. parapsilosis, and
C. tropicalis and fewer samples for other
Candida and non-
Candida species. The results obtained with these two systems were comparable, with identification rates at the species level of ≥99% for isolates that were represented in the respective databases. Both methods each misidentified two single isolates absent from the respective databases as a wrong species, while the biochemical approach (ID 32C; bioMérieux) misidentified 30 isolates as a wrong species, instead of reporting them as "unknown." In contrast, the success rate for classical identification techniques was 96.7%. Closely related species (e.g.,
Candida orthopsilosis,
C. metapsilosis, and
C. parapsilosis or
Candida glabrata and
C. bracarensis) were resolved by both MALDI-TOF MS systems but not by the biochemical approach.
ЭТО ЕСЛИ КРАТКО.....
Ну а если серьезно, пока предлагаю потерпеть. Кандиде посвящено столько терабайт интернета, не уверен, что она этого заслуживает...