Systematic internal transcribed spacer sequence analysis for identification of clinical mold isolates in diagnostic

Diana E Ciardo1, Katja Lucke, Alex Imhof

  • 1Institut für Medizinische Mikrobiologie, Universität Zürich, Gloriastr. 30/32, 8006 Zürich, Switzerland.

Insights

Internal transcribed spacer (ITS) sequencing significantly improves mold identification in diagnostic mycology labs. This molecular method offers higher accuracy and species-level identification compared to traditional phenotypic methods.

Area of Science:

  • Medical Mycology
  • Molecular Diagnostics
  • Clinical Microbiology

Background:

  • Accurate mold identification is crucial in diagnostic mycology laboratories for effective patient treatment.
  • Traditional phenotypic identification methods can be time-consuming and may lack accuracy, especially at the species level.

Purpose of the Study:

  • To evaluate the implementation and efficacy of internal transcribed spacer (ITS) sequencing for routine mold identification in a diagnostic mycology laboratory.
  • To compare the performance of ITS sequencing with traditional phenotypic identification methods.

Main Methods:

  • A 5-year retrospective study (2005-2009) analyzing 6,900 mold isolates.
  • 233 selected isolates underwent internal transcribed spacer (ITS) sequence analysis following a defined workflow.
  • DNA extraction optimization was performed to enhance molecular identification efficacy.

Main Results:

  • ITS sequencing successfully identified 78.6% of analyzed mold isolates (57.1% at species level, 21.5% at genus level).
  • In comparison, phenotypic characterization achieved taxonomic assignment for only 47.6% of isolates, with just 13.3% identified at the species level.
  • Optimized DNA extraction further improved the success rate of molecular identification.

Conclusions:

  • Internal transcribed spacer (ITS) sequencing is a highly effective tool for routine mold identification in diagnostic mycology.
  • Molecular identification using ITS sequencing significantly outperforms traditional phenotypic methods in terms of accuracy and species-level resolution.
  • This study provides evidence for the systematic implementation of sequence-based identification in routine laboratory workflows.

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