Differentiation between Candida dubliniensis and Candida albicans by Fatty Acid Methyl Ester Analysis Using Gas-Liquid Chromatography

Author:

Peltroche-Llacsahuanga Heidrun1,Schmidt Silke1,Seibold Michael2,Lütticken Rudolf1,Haase Gerhard1

Affiliation:

1. Institute of Medical Microbiology, University Hospital RWTH Aachen, Aachen,1 and

2. Robert Koch-Institute, Berlin,2 Germany

Abstract

ABSTRACT Candida dubliniensis is often found in mixed culture with C. albicans , but its recognition is hampered as the color of its colonies in primary culture on CHROMagar Candida varies. Furthermore, definite identification of C. dubliniensis is difficult to achieve, time-consuming, and expensive. Therefore, a method to discriminate between these two closely related yeast species by fatty acid methyl ester (FAME) analysis using gas-liquid chromatography (Sherlock Microbial Identification System [MIS]; MIDI, Inc., Newark, Del.) was developed. Although the chromatograms of these two species revealed no obvious differences when applying FAME analysis, a new library (CADLIB) was successfully created using Sherlock Library Generation Software (MIDI). The amount and frequency of FAME was analyzed using library training files ( n = 10 for each species), preferentially those comprising reference strains. For testing the performance of the CADLIB, clinical isolates genetically assigned to the respective species ( C. albicans , n = 32; C. dubliniensis , n = 28) were chromatographically analyzed. For each isolate tested, MIS computed a similarity index (SI) indicating a hierarchy of possible strain fits. When using the newly created library CADLIB, the SIs for C. albicans and C. dubliniensis ranged from 0.11 to 0.96 and 0.53 to 0.93 (for all but one), respectively. Only three isolates of C. albicans (9.4%) were misidentified as C. dubliniensis , whereas all isolates of C. dubliniensis were correctly identified. Resulting differentiation accuracy was 90.6% for C. albicans and 100% for C. dubliniensis . Cluster analysis and principal component analysis of the resulting FAME profiles showed two clearly distinguishable clusters matching up with two assigned species for the strains tested. Thus, the created library proved to be well suited to discriminate between these two species.

Publisher

American Society for Microbiology

Subject

Microbiology (medical)

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