Evaluation of the AUXACOLOR system, a new method of clinical yeast identification.

Davey, K. G.; Chant, P M; Downer, C S; Campbell, Colin; Warnock, David W.

doi:10.1136/jcp.48.9.807

Cited by 29 publications

(28 citation statements)

References 9 publications

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“…It is also plausible that technical problems occurred during the isolate testing, which might account for differences in the identification ratios across the enrolled studies. In the aforementioned study by Davey et al (33), incorrect or nonidentification results with the AuxaColor system were distributed over 15 of the 16 species tested, despite the absence of doubtful results due to inexplicable spontaneous color changes, as reported elsewhere (42). In another study, turbidity readings with the API ID32C system were often troublesome (43), but this was not perceived by the authors to be a cause of erroneous results.…”

Section: Discussionmentioning

confidence: 84%

“…For the AuxaColor system, a five-digit analytical profile number, generated on the basis of the reactivity of the isolate, can be enhanced by two additional digits that depend on morphological and physiological characteristics of the isolate. In the study by Davey et al, only 23 (57.5%) of 40 C. albicans isolates were correctly identified with the AuxaColor system, but 10 of the 40 isolates failed to produce chlamydospores, with seven of those isolates having profiles otherwise correct for C. albicans (33). In contrast, in two of our studies, conducted in 2007 and 2013, only 6 (2.4%) of 252 and 5 (3.6%) of 140 C. albicans isolates, respectively, were misidentified or not identified with the Vitek 2 system (51, 56).…”

Section: Discussionmentioning

confidence: 99%

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Are the Conventional Commercial Yeast Identification Methods Still Helpful in the Era of New Clinical Microbiology Diagnostics? A Meta-Analysis of Their Accuracy

et al. 2015

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Accurate identification of pathogenic species is important for early appropriate patient management, but growing diversity of infectious species/strains makes the identification of clinical yeasts increasingly difficult. Among conventional methods that are commercially available, the API ID32C, AuxaColor, and Vitek 2 systems are currently the most used systems in routine clinical microbiology. We performed a systematic review and meta-analysis to estimate and to compare the accuracy of the three systems, in order to assess whether they are still of value for the species-level identification of medically relevant yeasts. After adopting rigorous selection criteria, we included 26 published studies involving Candida and non-Candida yeasts that were tested with the API ID32C (674 isolates), AuxaColor (1,740 T he epidemiology of yeast infections, particularly those involving the bloodstream (i.e., fungemia) or other normally sterile sites, continues to evolve throughout the world (1), likely due to the diversity of susceptible hosts, including mainly patients undergoing transplantations or receiving treatment for underlying malignant diseases (2). Prophylactic use of antifungals has also contributed to alterations in the patterns of such infections, leading to increases in the incidence of non-albicans Candida species, compared to Candida albicans (3-6). Although the latter species is the most frequently isolated yeast in hospital settings (7), the emergence of less-common or "cryptic" non-albicans Candida species, as well as uncommon yeasts such as Rhodotorula, Geotrichum, Pichia, Malassezia, Saccharomyces, and cryptococci other than Cryptococcus neoformans (8), poses a threat due to their potential to develop antifungal resistance (9-12) or their intrinsically decreased susceptibility to one or more antifungal agents (13-15). As differences in antifungal drug susceptibilities can exist not only among genera but also among members of the same genus or species complex (8), accurate species identification is important for initiating early effective antifungal therapy, especially when susceptibility testing results are not promptly available.As simple, rapid, reliable alternatives to traditional methods based on the Wickerham assimilation/fermentation patterns (16), manual (e.g., AuxaColor [Bio-Rad, Marnes-la-Coquette, France]) and automated (i.e., Vitek 2 [bioMérieux, Marcy l'Etoile, France]) commercial identification systems are currently being used in clinical microbiology laboratories, but their ability to identify yeast isolates to the species level is dependent on the types and numbers of biochemical (carbohydrate/enzyme) substrates tested (17). Although with a limited database of only 26 taxa/species (updated to include 33 yeast species in a newer version of the system [AuxaColor 2], which was launched in 2002), the AuxaColor system uses colorimetric tests for assimilation substrates,

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Section: Discussionmentioning

confidence: 84%

Section: Discussionmentioning

confidence: 99%

Are the Conventional Commercial Yeast Identification Methods Still Helpful in the Era of New Clinical Microbiology Diagnostics? A Meta-Analysis of Their Accuracy

et al. 2015

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“…[4][5][6][7] The identification rates, however, depend on the panel of yeasts which is used to evaluate the kit. The present study was designed to evaluate the performance of the kits in the setting of identification of isolates encountered routinely in a clinical microbiology laboratory.…”

Section: Discussionmentioning

confidence: 99%

Comparative study of seven commercial yeast identification systems.

Verweij¹,

Breuker²,

Rijs³

et al. 1999

J Clin Pathol

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Aims-To compare the performance of seven commercial yeast identification methods with that of a reference method, and to compare the costs of the commercial kits. Methods-Clinical yeast isolates (n = 52), comprising 19 species, were identified using Vitek, Api ID 32C, Api 20C AUX, Yeast Star, Auxacolor, RapID Yeast Plus system, and Api Candida and compared with a reference method which employed conventional tests.

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“…The isolates were also cultured on Dalmau plates (Oxoid cornmeal agar supplemented with 1% Tween 80, with a sterile coverslip placed over a single streak of the organism) to establish the additional morphological characteristics required to obtain complete Auxacolor2 profiles. All C. nivariensis isolates were then also tested in the API 20C system (bioMerieux, Marcy l'Etoile, France), again, exactly as described previously (7). Molecular methods.…”

Section: Methodsmentioning

confidence: 99%

Candida nivariensis , an Emerging Pathogenic Fungus with Multidrug Resistance to Antifungal Agents

Borman¹,

Petch

Linton³

et al. 2008

J Clin Microbiol

118

110

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In 2005, Candida nivariensis, a yeast species genetically related to Candida glabrata, was described following its isolation from three patients in a single Spanish hospital. Between 2005 and 2006, 16 fungal isolates with phenotypic similarities to C. nivariensis were submitted to the United Kingdom Mycology Reference Laboratory for identification. The strains originated from various clinical specimens, including deep, usually sterile sites, from patients at 12 different hospitals in the United Kingdom. PCR amplification and sequencing of the D1D2 and internal transcribed spacer 1 (ITS1) regions of the nuclear ribosomal gene cassette confirmed that these isolates from the United Kingdom are genetically identical to C. nivariensis. Biochemically, C. glabrata and C. nivariensis are distinguished by their differential abilities to assimilate trehalose. However, in contrast to the original published findings, we found that C. glabrata isolates, but not C. nivariensis isolates, are capable of assimilating this substrate. Antifungal susceptibility tests revealed that C. nivariensis isolates are less susceptible than C. glabrata isolates to itraconazole, fluconazole, and voriconazole and to have significantly higher flucytosine MICs than C. glabrata strains. Finally, C. nivariensis could be rapidly distinguished from the other common pathogenic fungus species by pyrosequencing of the ITS2 region. In the light of these data, we believe that C. nivariensis should be regarded as a clinically important emerging pathogenic fungus.

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Evaluation of the AUXACOLOR system, a new method of clinical yeast identification.

Cited by 29 publications

References 9 publications

Are the Conventional Commercial Yeast Identification Methods Still Helpful in the Era of New Clinical Microbiology Diagnostics? A Meta-Analysis of Their Accuracy

Are the Conventional Commercial Yeast Identification Methods Still Helpful in the Era of New Clinical Microbiology Diagnostics? A Meta-Analysis of Their Accuracy

Comparative study of seven commercial yeast identification systems.

Candida nivariensis , an Emerging Pathogenic Fungus with Multidrug Resistance to Antifungal Agents

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