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Teman SJ, Gaydos JK, Norman SA, Huggins JL, Lambourn DM, Calambokidis J, Ford JKB, Hanson MB, Haulena M, Zabek E, Cottrell P, Hoang L, Morshed M, Garner MM, Raverty S. Epizootiology of a Cryptococcus gattii outbreak in porpoises and dolphins from the Salish Sea. DISEASES OF AQUATIC ORGANISMS 2021; 146:129-143. [PMID: 34672263 DOI: 10.3354/dao03630] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Cryptococcus gattii is a fungal pathogen that primarily affects the respiratory and nervous systems of humans and other animals. C. gattii emerged in temperate North America in 1999 as a multispecies outbreak of cryptococcosis in British Columbia (Canada) and Washington State and Oregon (USA), affecting humans, domestic animals, and wildlife. Here we describe the C. gattii epizootic in odontocetes. Cases of C. gattii were identified in 42 odontocetes in Washington and British Columbia between 1997 and 2016. Species affected included harbor porpoises Phocoena phocoena (n = 26), Dall's porpoises Phocoenoides dalli (n = 14), and Pacific white-sided dolphins Lagenorhynchus obliquidens (n = 2). The probable index case was identified in an adult male Dall's porpoise in 1997, 2 yr prior to the initial terrestrial outbreak. The spatiotemporal extent of the C. gattii epizootic was defined, and cases in odontocetes were found to be clustered around terrestrial C. gattii hotspots. Case-control analyses with stranded, uninfected odontocetes revealed that risk factors for infection were species (Dall's porpoises), age class (adult animals), and season (winter). This study suggests that mycoses are an emerging source of mortality for odontocetes, and that outbreaks may be associated with anthropogenic environmental disturbance.
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Affiliation(s)
- Sarah J Teman
- The SeaDoc Society, Karen C. Drayer Wildlife Health Center - Orcas Island Office, UC Davis School of Veterinary Medicine, Eastsound, WA 98245, USA
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Eucalyptus globulus Essential Oil as a Natural Food Preservative: Antioxidant, Antibacterial and Antifungal Properties In Vitro and in a Real Food Matrix (Orangina Fruit Juice). APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10165581] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
The potential application of Eucalyptus globulus essential oil (EGEO) as a natural beverage preservative is described in this research. The chemical composition of EGEO was determined using gas chromatography analyses and revealed that the major constituent is 1,8-cineole (94.03% ± 0.23%). The in vitro antioxidant property of EGEO was assessed using different tests. Percentage inhibitions of EGEO were dose-dependent. In addition, EGEO had a better metal ion chelating effect with an IC50 value of 8.43 ± 0.03 mg/mL, compared to ascorbic acid (140.99 ± 3.13 mg/mL). The in vitro antimicrobial effect of EGEO was assessed against 17 food spoilage microorganisms. The diameter of the inhibitory zone (DIZ) ranged from 15 to 85 mm for Gram-positive bacteria and from 10 to 49 mm for yeast strains. Candida albicans, C.parapsilosis and Saccharomyces cerevisiae were the most sensitive fungal species to the EGEO vapor with DIZ varying from 59 to 85 mm. The anti-yeast effectiveness of EGEO alone and in association with heat processing was estimated in a real juice matrix (Orangina fruit juices) in a time-dependent manner. The combination of EGEO-heat treatment (70 °C for 2 min) at different concentrations (0.8 to 4 µL/mL) was effective at reducing S. cerevisiae growth in the fruit juice of Orangina, compared to juice preserved with synthetic preservatives. Current findings suggest EGEO as an effective and potent inhibitor of food spoilage fungi in a real Orangina juice, and might be a potential natural source of preservative for the food industry.
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Safavieh M, Coarsey C, Esiobu N, Memic A, Vyas JM, Shafiee H, Asghar W. Advances in Candida detection platforms for clinical and point-of-care applications. Crit Rev Biotechnol 2017; 37:441-458. [PMID: 27093473 PMCID: PMC5083221 DOI: 10.3109/07388551.2016.1167667] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Invasive candidiasis remains one of the most serious community and healthcare-acquired infections worldwide. Conventional Candida detection methods based on blood and plate culture are time-consuming and require at least 2-4 days to identify various Candida species. Despite considerable advances for candidiasis detection, the development of simple, compact and portable point-of-care diagnostics for rapid and precise testing that automatically performs cell lysis, nucleic acid extraction, purification and detection still remains a challenge. Here, we systematically review most prominent conventional and nonconventional techniques for the detection of various Candida species, including Candida staining, blood culture, serological testing and nucleic acid-based analysis. We also discuss the most advanced lab on a chip devices for candida detection.
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Affiliation(s)
- Mohammadali Safavieh
- Division of Biomedical Engineering, Division of Renal medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Cambridge, MA, USA
| | - Chad Coarsey
- Department of Computer Engineering and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, USA
- College of Engineering and Computer Science, Asghar-Lab, Micro and Nanotechnologies for Medicine, Boca Raton, FL, USA
| | - Nwadiuto Esiobu
- Biological Sciences Department, Florida Atlantic University, Davie, FL, USA
| | - Adnan Memic
- Center of Nanotechnology, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Jatin Mahesh Vyas
- Department of Medicine, Division of Infectious Disease, Massachusetts General Hospital, Boston, MA, USA
| | - Hadi Shafiee
- Division of Biomedical Engineering, Division of Renal medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Cambridge, MA, USA
| | - Waseem Asghar
- Department of Computer Engineering and Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, USA
- College of Engineering and Computer Science, Asghar-Lab, Micro and Nanotechnologies for Medicine, Boca Raton, FL, USA
- Biological Sciences Department, Florida Atlantic University, Davie, FL, USA
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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. J Clin Microbiol 2015; 53:2439-50. [PMID: 25994160 DOI: 10.1128/jcm.00802-15] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2015] [Accepted: 05/11/2015] [Indexed: 12/29/2022] Open
Abstract
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 isolates), and Vitek 2 (2,853 isolates) systems. The random-effects pooled identification ratios at the species level were 0.89 (95% confidence interval [CI], 0.80 to 0.95) for the API ID32C system, 0.89 (95% CI, 0.83 to 0.93) for the AuxaColor system, and 0.93 (95% CI, 0.89 to 0.96) for the Vitek 2 system (P for heterogeneity, 0.255). Overall, the accuracy of studies using phenotypic analysis-based comparison methods was comparable to that of studies using molecular analysis-based comparison methods. Subanalysis of studies conducted on Candida yeasts showed that the Vitek 2 system was significantly more accurate (pooled ratio, 0.94 [95% CI, 0.85 to 0.99]) than the API ID32C system (pooled ratio, 0.84 [95% CI, 0.61 to 0.99]) and the AuxaColor system (pooled ratio, 0.76 [95% CI, 0.67 to 0.84]) with respect to uncommon species (P for heterogeneity, <0.05). Subanalysis of studies conducted on non-Candida yeasts (i.e., Cryptococcus, Rhodotorula, Saccharomyces, and Trichosporon) revealed pooled identification accuracies of ≥98% for the Vitek 2, API ID32C (excluding Cryptococcus), and AuxaColor (only Rhodotorula) systems, with significant low or null levels of heterogeneity (P > 0.05). Nonetheless, clinical microbiologists should reconsider the usefulness of these systems, particularly in light of new diagnostic tools such as matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry, which allow for considerably shortened turnaround times and/or avoid the requirement for additional tests for species identity confirmation.
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Wang SY, Chen HC, Liu JR, Lin YC, Chen MJ. Identification of yeasts and evaluation of their distribution in Taiwanese Kefir and Viili starters. J Dairy Sci 2009; 91:3798-805. [PMID: 18832201 DOI: 10.3168/jds.2007-0468] [Citation(s) in RCA: 56] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
The objective of the present study was to investigate yeast communities in kefir grains and viili starters in Taiwan through conventional microbiological cultivation and polymerase chain reaction-denaturing gradient gel electrophoresis (PCR-DGGE). The DNA sequencing was used as a validity technique to ensure that all isolates within each group belonged to just one species, and to confirm the identified results of PCR-DGGE. Results indicated that a combination of conventional microbiological cultivation with PCR-DGGE and sequencing could successfully identify 4 yeast species from both types of cultures in Taiwan. Kluyveromyces marxianus, Saccharomyces turicensis, and Pichia fermentans were found in Taiwanese kefir grains with a distribution of 76, 22, and 2%, respectively, whereas Klu. marxianus, Saccharomyces unisporus and P. fermentans were identified in viili starters corresponding to 58, 11, and 31% of the total cell counts, respectively. Furthermore, the culture-independent method was applied to identify the yeast species using DGGE. Only 2 yeast species, Klu. marxianus and S. turicensis, were found in kefir grains and 2, Klu. marxianus and P. fermentans, in viili starters. These results suggest that in samples containing multiple species, PCR-DGGE may fail to detect some species. Sequences of yeast isolates reported in this study have been deposited in the GenBank database under accession nos. DQ139802, AF398485, DQ377652, and AY007920.
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Affiliation(s)
- S Y Wang
- Experimental Farm, National Taiwan University, Taipei, Taiwan, Republic of China
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Candida nivariensis, an emerging pathogenic fungus with multidrug resistance to antifungal agents. J Clin Microbiol 2008; 46:933-8. [PMID: 18199788 DOI: 10.1128/jcm.02116-07] [Citation(s) in RCA: 105] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
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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Linton CJ, Borman AM, Cheung G, Holmes AD, Szekely A, Palmer MD, Bridge PD, Campbell CK, Johnson EM. Molecular identification of unusual pathogenic yeast isolates by large ribosomal subunit gene sequencing: 2 years of experience at the United kingdom mycology reference laboratory. J Clin Microbiol 2007; 45:1152-8. [PMID: 17251397 PMCID: PMC1865856 DOI: 10.1128/jcm.02061-06] [Citation(s) in RCA: 82] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Rapid identification of yeast isolates from clinical samples is particularly important given their innately variable antifungal susceptibility profiles. We present here an analysis of the utility of PCR amplification and sequence analysis of the hypervariable D1/D2 region of the 26S rRNA gene for the identification of yeast species submitted to the United Kingdom Mycology Reference Laboratory over a 2-year period. A total of 3,033 clinical isolates were received from 2004 to 2006 encompassing 50 different yeast species. While more than 90% of the isolates, corresponding to the most common Candida species, could be identified by using the AUXACOLOR2 yeast identification kit, 153 isolates (5%), comprised of 47 species, could not be identified by using this system and were subjected to molecular identification via 26S rRNA gene sequencing. These isolates included some common species that exhibited atypical biochemical and phenotypic profiles and also many rarer yeast species that are infrequently encountered in the clinical setting. All 47 species requiring molecular identification were unambiguously identified on the basis of D1/D2 sequences, and the molecular identities correlated well with the observed biochemical profiles of the various organisms. Together, our data underscore the utility of molecular techniques as a reference adjunct to conventional methods of yeast identification. Further, we show that PCR amplification and sequencing of the D1/D2 region reliably identifies more than 45 species of clinically significant yeasts and can also potentially identify new pathogenic yeast species.
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Affiliation(s)
- Christopher J Linton
- Mycology Reference Laboratory, Health Protection Agency South-West Regional Laboratory, Myrtle Road, Bristol BS2 8EL, United Kingdom.
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Fotedar R, al-Hedaithy SS. Identification of chlamydospore-negative Candida albicans using CHROMagar Candida medium. Mycoses 2003; 46:96-103. [PMID: 12870197 DOI: 10.1046/j.1439-0507.2003.00867.x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
This study was undertaken to evaluate the utility of CHROMagar Candida medium for the identification of chlamydospore-negative Candida albicans. A total of 60 isolates including 45 chlamydospore-negative C. albicans, 10 chlamydospore-positive C. albicans (positive controls) and five non-C. albicans (negative controls) were investigated. On the basis of germ tube test, assimilation of trehalose (Tre), glucosamine (GlcN), N-acetyl glucosamine (GlcNAc), secretory aspartyl production and serotyping, the 45 chlamydospore-negative C. albicans isolates were assigned to the reported three groups. Eighteen isolates showing positive germ tube test, negative for the assimilation of Tre, GlcN/GlcNAc, strong producers of proteinase (2+) and assigned to serotype B belonged to group I. Whereas, the isolates in group II and group III showed common characteristics including assimilation of Tre, GlcN/GlcNAc, moderate production of proteinase (1+) and were serotype A, except for the fact that group II isolates were germ tube positive and group III isolates were negative. Using CHROMagar Candida medium, all the 45 chlamydospore-negative and 10 positive control isolates were accurately identified on the basis of characteristic green color at 37 degrees C for 48 h of incubation. On the other hand at an optimum incubation temperature of 37 degrees C none of the non-C. albicans (negative controls) showed characteristic green color thus yielding a 100% sensitivity and specificity. Isolates in group-I showed a slow growth rate and no visible growth was observed at 24 h, whereas, groups II, III and the control isolates showed visible growth at 24 h. Besides differences in growth rates, these isolates also varied in their characteristic colony color which gradually changed over a period of time. The results of this study clearly suggest that CHROMagar Candida medium is not only a simple, reliable and cost effective method for the identification of chlamydospore-negative atypical C. albicans, but can also be used to differentiate various groups of chlamydospore-negative C. albicans.
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Affiliation(s)
- R Fotedar
- Department of Pathology, Medical Mycology Unit, College of Medicine, King Khalid University Hospital, Riyadh, Saudi Arabia.
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Romney MG, Bryce EA, Rennie RP, Sand CA. Rapid identification of clinical yeast isolates using the colorimetric AUXACOLOR system. Diagn Microbiol Infect Dis 2000; 36:137-8. [PMID: 10705057 DOI: 10.1016/s0732-8893(99)00115-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
Abstract
The AUXACOLOR colorimetric system (Sanofi Diagnostics Pasteur, Marnes-la-Coquette, France) for the identification of clinical yeast isolates, was compared in its identification of 100 yeast strains to conventional identification methods. Of the 94 correctly identified isolates, 47% (n = 44) were identified by 24 h, and 100% (n = 94) were identified by 48 h. AUXACOLOR is a simple, rapid and accurate method for the identification of yeast pathogens.
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Affiliation(s)
- M G Romney
- Division of Medical Microbiology and Infection Control, Vancouver Hospital and Health Sciences Centre, 855 West 12th Avenue, Vancouver, British Columbia, Canada
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Sheppard DC, René P, Harris AD, Miller MA, Laverdière M, deSouza E, Robson HG. Simple strategy for direct identification of medically important yeast species from positive blood culture vials. J Clin Microbiol 1999; 37:2040-1. [PMID: 10325374 PMCID: PMC85023 DOI: 10.1128/jcm.37.6.2040-2041.1999] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/1999] [Accepted: 03/22/1999] [Indexed: 11/20/2022] Open
Abstract
We compared direct inoculation of the Auxacolor yeast identification system from positive blood culture vials to standard identification with the API 20C AUX (API 20C), using 44 prospectively collected clinical specimens and 25 seeded blood culture vials. Direct inoculation of the Auxacolor system was accurate and more rapid than standard identification with the API 20C.
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Affiliation(s)
- D C Sheppard
- Department of Microbiology, Royal Victoria Hospital, Montreal, Quebec, Canada.
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Verweij PE, Breuker IM, Rijs AJ, Meis JF. Comparative study of seven commercial yeast identification systems. J Clin Pathol 1999; 52:271-3. [PMID: 10474518 PMCID: PMC501331 DOI: 10.1136/jcp.52.4.271] [Citation(s) in RCA: 56] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
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. RESULTS The percentage of correctly identified isolates varied between 59.6% and 80.8%. Overall, the highest performance was obtained with Api Candida (78.8%) and Auxacolor (80.8%). Among germ tube negative yeast isolates, Auxacolor and Api Candida both identified 93.1% of isolates correctly. All systems failed to identify C norvegensis, C catenulata, C haemulonii, and C dubliniensis. In comparison with Auxacolor, the Api Candida is less expensive and requires less bench time. CONCLUSIONS Auxacolor and Api Candida appeared to be the most useful systems for identification of germ tube negative yeast isolates in clinical microbiology laboratories, although one should be aware that several germ tube negative Candida species cannot be identified by these systems.
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Affiliation(s)
- P E Verweij
- Department of Medical Microbiology, University Hospital Nijmegen, The Netherlands.
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Campbell CK, Davey KG, Holmes AD, Szekely A, Warnock DW. Comparison of the API Candida system with the AUXACOLOR system for identification of common yeast pathogens. J Clin Microbiol 1999; 37:821-3. [PMID: 9986865 PMCID: PMC84570 DOI: 10.1128/jcm.37.3.821-823.1999] [Citation(s) in RCA: 32] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Two commercial systems for the identification of yeasts were evaluated by using 159 clinical isolates that had also been identified by conventional biochemical and morphological methods. The API Candida system correctly identified 146 isolates (91.8%), and the AUXACOLOR system correctly identified 145 isolates (91.2%). However, of the 146 isolates identified by the API Candida system, 23 required supplemental biochemical tests or morphological assessment to obtain the correct identification. The AUXACOLOR system gave no identification in 13 cases (8.2%), while the API Candida system gave an unreadable profile in only one case. Incorrect identifications were more common with the API Candida system (12 isolates; 7.5%) than with the AUXACOLOR system (1 isolate; 0.6%).
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Affiliation(s)
- C K Campbell
- Mycology Reference Laboratory, Public Health Laboratory Service, Bristol, United Kingdom
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PAUGAM A, BENCHETRIT M, FIACRE A, TOURTE-SCHAEFER C, DUPOUY-CAMET J. Comparison of four commercialized biochemical systems for clinical yeast identification by colour-producing reactions. Med Mycol 1999. [DOI: 10.1046/j.1365-280x.1999.00191.x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
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Sheppard DC, deSouza E, Hashmi Z, Robson HG, René P. Evaluation of the auxacolor system for biochemical identification of medically important yeasts. J Clin Microbiol 1998; 36:3726-7. [PMID: 9817909 PMCID: PMC105276 DOI: 10.1128/jcm.36.12.3726-3727.1998] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
We compared the Auxacolor yeast identification system (Sanofi Diagnostics Pasteur) with the API 20C Aux (bioMerieux-Vitek) using 105 isolates of medically important yeasts. The Auxacolor system provided more rapid, accurate results and displayed less interobserver variability than the API 20C Aux.
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Affiliation(s)
- D C Sheppard
- Division of Microbiology, Royal Victoria Hospital, McGill University, Montreal, Quebec, Canada.
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Ramani R, Gromadzki S, Pincus DH, Salkin IF, Chaturvedi V. Efficacy of API 20C and ID 32C systems for identification of common and rare clinical yeast isolates. J Clin Microbiol 1998; 36:3396-8. [PMID: 9774605 PMCID: PMC105341 DOI: 10.1128/jcm.36.11.3396-3398.1998] [Citation(s) in RCA: 74] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
The abilities of the API 20C and ID 32C yeast identification systems to identify 123 common and 120 rare clinical yeast isolates were compared. API 20C facilitated correct identification of 97% common and 88% rare isolates while ID 32C facilitated correct identification of 92% common and 85% rare isolates.
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Affiliation(s)
- R Ramani
- Wadsworth Center, New York State Department of Health, Albany, New York, USA
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Bernal S, Martín Mazuelos E, Chávez M, Coronilla J, Valverde A. Evaluation of the new API Candida system for identification of the most clinically important yeast species. Diagn Microbiol Infect Dis 1998; 32:217-21. [PMID: 9884839 DOI: 10.1016/s0732-8893(98)00119-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The API Candida system (bioMérieux) a new yeast identification system, was evaluated for its reliability in identifying 198 clinical yeast isolates in comparison with the API 20C system (bioMérieux) that was used as reference standard. The API Candida system correctly identified 91.4% and 71.7% of the isolates, with and without additional tests, respectively. The API Candida system identified 96.3% of common isolates studied, and 66.6% of uncommon isolates. We think that API Candida system is an easy and good yeast identification system and it could be used in a routine clinical microbiology laboratory.
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Affiliation(s)
- S Bernal
- Servicio de Microbiología Clínica, Hospital Universitario de Valme, Seville, Spain
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Willemsen M, Breynaert J, Lauwers S. Comparison of Auxacolor with API 20 C Aux in yeast identification. Clin Microbiol Infect 1997; 3:369-375. [PMID: 11864135 DOI: 10.1111/j.1469-0691.1997.tb00628.x] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
OBJECTIVE: To compare Auxacolor with API 20 C Aux for identification of yeasts. METHODS: A total of 206 isolates belonging to 25 species was used in this study. Conventional yeast identification methods were used as a reference. RESULTS: With API 20 C Aux, the correct identification rate was 89.3% after 2 days, while 94.7% of the strains were correctly identified after 3 days. One of 14 strains of Candida tropicalis and 10 of 16 strains of Trichosporon cutaneum were not correctly identified. With Auxacolor, the percentages of correct identification after 1 and 2 days were 60.1% and 69.4%, respectively. Most strains of 11 of the 20 species considered in the system were correctly identified, including several of the most frequent yeast species. Several less commonly encountered yeast species were not correctly identified. Suggestions for improvement of the Auxacolor system are given. CONCLUSIONS: For the most frequent yeast species, Auxacolor, after adaptation and correction of the identification table, provides a useful alternative to API 20 C Aux. For less frequently encountered yeast species, the use of API 20 C Aux is preferable.
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Affiliation(s)
- Maria Willemsen
- Department of Microbiology, Akademisch Ziekenhuis, Vrije Universiteit Brussels, Brussels, Belgium
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