Background: The traditional techniques for diagnosis of invasive fungal infections in the clinical microbiology laboratory need improvement. These techniques are prone to delay results due to their time-consuming process, or result in misidentification of the fungus due to low sensitivity or low specificity. The aim of this study was to develop a method for the rapid detection and identification of fungal pathogens.

Methods: The internal transcribed spacer two fragments of fungal ribosomal DNA were amplified using a polymerase chain reaction for all samples. Next, the products were hybridized with the probes immobilized on the surface of a microarray. These species-specific probes were designed to detect nine different clinical pathogenic fungi including Candida albicans, Candida tropocalis, Candida glabrata, Candida parapsilosis, Candida krusei, Candida lusitaniae, Candida guilliermondii, Candida keyfr, and Cryptococcus neoformans. The hybridizing signals were enhanced with gold nanoparticles and silver deposition, and detected using a flatbed scanner or visually.

Results: Fifty-nine strains of fungal pathogens, including standard and clinically isolated strains, were correctly identified by this method. The sensitivity of the assay for Candida albicans was 10 cells/mL. Ten cultures from clinical specimens and 12 clinical samples spiked with fungi were also identified correctly.

Conclusions: This technique offers a reliable alternative to conventional methods for the detection and identification of fungal pathogens. It has higher efficiency, specificity and sensitivity compared with other methods commonly used in the clinical laboratory.

Download full-text PDF

Source
http://dx.doi.org/10.1515/CCLM.2010.284DOI Listing

Publication Analysis

Top Keywords

fungal pathogens
12
candida
9
detection identification
8
identification fungal
8
candida albicans
8
fungal
6
clinical
5
application oligonucleotide
4
oligonucleotide microarray-based
4
microarray-based nano-amplification
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!