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Identification of Unusual Clinical Yeast Isolates: A 2 Year Review of Internal Transcribed Spacer (ITS) Region Sequence Analysis E. Susan Slechta 1,Sheri.

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Presentation on theme: "Identification of Unusual Clinical Yeast Isolates: A 2 Year Review of Internal Transcribed Spacer (ITS) Region Sequence Analysis E. Susan Slechta 1,Sheri."— Presentation transcript:

1 Identification of Unusual Clinical Yeast Isolates: A 2 Year Review of Internal Transcribed Spacer (ITS) Region Sequence Analysis E. Susan Slechta 1,Sheri H. Hohmann 2, and Kimberly E. Hanson 2,3 1 ARUP Institute for Clinical and Experimental Pathology, Salt Lake City, UT, 2 Associated Regional and University Pathologists, Inc., Salt Lake City, UT, 3 Department of Pathology, University of Utah, Salt Lake City, UT. REFERENCES E. Susan Slechta ARUP Institute for Clinical and Experimental Pathology 500 Chipeta Way Salt Lake City, UT (801) x Sheri Hohmann ARUP Laboratories 500 Chipeta Way Salt Lake City, UT CONCLUSIONS INTRODUCTION RESULTS METHODS 1.Iwen, P. C., S. H Hinrichs, and M. E. Rupp Utilization of the Internal Transcribed Spacer Regions as Molecular Targets to Detect and Identify Human Fungal Pathogens. Medical Mycology 20: Leaw, S. N., H. C. Chang, H. F. Sun, R. Barton, J-P. Bouchara, and T. C. Chang Identification of Medically Important Yeast Species by Sequence Analysis of the Internal Transcribed Spacer Regions. Journal of Clinical Microbiology 44: Linton, C.J., Borman, A.M., Cheung, G.C., Holmes, A.D., Szekely, A., Palmer, M.D., Bridge, P.D., Campbell, C.K., and Johnson, E.M Molceulat Identification of Unusual Pathogenic Yeast Isolates by Large Ribosomal Subunit Gene Sequencing: 2 Years of Experience at the United Kingdom Mycology Reference Laboratory. Journal of Clinical Microbiology 45: Acknowledgements: We would like to thank Keith Simmon, June Pounder, and the Mycology Laboratory at ARUP for their assistance in this project. This research was supported in part by the ARUP Institute for Clinical and Experimental Pathology. Figure 2. Specimen Sources by Method of Identification Table 1 Yeast Identification Results a Figure 3. Phylogenetic Tree* REVISED ABSTRACT 18S rRNA ITS1 5.8S ITS2 28S rRNA ITS5 ITS4 Figure 1. ITS Region *Phylogenetic tree built in Mega 4 by the neighbor-joining method. Background: More than 150 different yeasts are recognized as human pathogens. Identification (ID) of these diverse organisms by conventional methods is time consuming and often inconclusive for atypical species. We implemented nucleic acid sequencing for yeasts that could not be identified by phenotypic testing. Our aim was to asses the utility of ITS sequence analysis using SmartGene IDNS, a curated microbial sequence database and software program. Methods: Yeast isolates submitted to the ARUP between Nov 2007 and Feb 2010 were evaluated using the following: germ tube formation, morphology on corn meal agar, color on CHROMagar, urease production, rapid trehalose assimilation and/or the API 20C AUX system. Fungal ITS 1 and 2 sequences were interrogated when API failed to yield a definitive ID. A sequence homology of ≥ 99% with a > 0.8% difference between species was required for species level ID, 97-99% identity for genus ID, and < 97% was considered unable to ID. Results: A total of 2934 isolates were evaluated. Overall, 95% (2776), encompassing 68 species, were fully identified by classical methods or API. Candida spp. accounted for the majority (95%, 2687) of phenotypic IDs. The remaining 158 isolates required sequence analysis, with 87% (137) identified to species, 11% (18) to genus, and 2% (3) remained unidentified. A total of 73 unique species were discerned by sequencing. Of these, 48 were common pathogens with atypical biochemical profiles and 25 were rarer yeasts not included in the API database. The genus level IDs included: 7 Candida spp., 3 Ustilago spp., 2 Cryptococcus spp., 2 Pichia spp., 1 Trichosporon spp. and 1 Sporopachydermia spp. Conclusions: Analysis of fungal ITS 1 and 2 regions using SmartGene software unambiguously identified 87% of yeast isolates not categorized by API. Our experience supports the use of molecular techniques as an adjunct to conventional methods for the identification of medically important yeasts. The spectrum of yeast species identified as opportunistic human pathogens is continually expanding as a result of the growing number of critically ill and immunocompromised patients. The widespread use of broad spectrum antibiotics, invasive procedures and long- term indwelling catheters are also associated with increased risk for invasive yeast infections. Early initiation of appropriate antifungal therapy improves clinical outcomes and informed therapeutic decisions increasingly require a rapid and accurate species level identification. Current phenotypic identification systems, however, are often unable to correctly identify less common or newly described pathogens and may fail to differentiate common organisms with rare or unique biochemical profiles. Furthermore, conventional methods are subjective, labor intensive and time consuming. To facilitate the identification (ID) of unusual yeasts, the ARUP Mycology Laboratory implemented sequence analysis of the Internal Transcribed Spacer (ITS) region using SmartGene IDNS (SmartGene Inc), a web-based database of approximately 109,000 ITS refernce sequences derived from Genbank. The aim of this study was to evaluate the use of SmartGene as a tool to classify ITS 1 and 2 nucleic acid sequences from clinically significant yeast isolates that could not be definitively characterized by classical methods. The antifungal susceptibility profiles of the isolates requiring molecular identification were also reviewed. Yeast Specimens. From September 2007 to February 2010, a total of 2934 clinical yeast isolates were submitted to the ARUP Mycology Reference Laboratory for identification. Conventional testing. Phenotypic assessments included: germ tube formation, morphology on corn meal agar, color on CHROMagar, urease production, rapid trehalose assimilation and/or analysis using the API 20C AUX system. DNA Amplification and ITS sequencing. Fungal ITS 1 and 2 sequences were interrogated for organisms isolated from significant sites when the API failed to yield a definitive ID. Genomic DNA was obtained using the PrepMan Lysis Kit (ABI). DNA amplification was achieved with ITS primers {ITS5 forward 5’GGAAGTAAAAGTCGTAACAAGG and ITS4 reverse 5’TCCTCCGCTTATTGATATGC} (FIGURE 1) on an ABI 9700 thermal cycler. Sequences were analyzed with SmartGene IDNS web based software. Reference sequences submitted from type or reference strains and/or GenBank entries published in the peer reviewed literature were selected for comparison to the clinical isolate. A sequence homology of ≥ 99% with > 0.8% difference between species was required for species level identification (ID), 97 to 99% identity for genus ID and <97% was considered unidentifiable. Susceptibility testing Susceptibility testing was performed upon request using the Sensititre® YeastOne panel (Trek Diagnostic Systems), a colorimetric microtitre broth dilution method based on the Clinical and Laboratory Standards Institute (CLSI) M27-A2 standard. The antifungal drugs tested included amphotericin B (AMB), flucytosine (5FC), fluconazole (FLC), itraconazole (ITC), voriconazole (VRC), posaconazole (POS) and caspofungin (CAS). CLSI breakpoints were applied to interpret susceptibility results. a Abbreviations used AMB= Amphotericin B, 5-FC = 5-Flucytosine, FLC = Fluconazole, ITC = Itraconazole, VRC =Voriconazole, POS = Posaconazole, CAS = Caspofungin. ND = Not Done. b Yellow boxes indicate dose dependent susceptibility and/or resistance to the indicated antifungal drug. for at least one specimen. Table 2 Susceptibility Test Results for Selected Sequenced Isolates. a,b 1. Despite the reference nature of our work, Candida albicans remained the most common yeast identified during the study period. 2. The majority (95%) of clinical isolates were successfully identified using routine phenotypic methods. 3. ITS sequencing was useful for a diverse group of rare organisms as well as common species with atypical biochemical profiles, and has the potential to discover novel species. 4. A significant number of isolates requiring molecular identification were Candida species with intrinsic antifungal resistance or potential for elevated fluconazole MICs (22%). For laboratories without timely access to molecular identification methods, susceptibility testing alone may provide valuable treatment information. a Organisms identified less than 3 times were removed from this table for readability. They represent 44 specimens out of the total 2985, 21 identified by classical methods and 23 by ITS sequencing. The full table is available for viewing upon request. D-763


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