Testing a sequencing panel for identification of clinically relevant fungi

Invasive fungal infections are a severe health threat, especially for immunocompromised patients. Correct identification of the fungal pathogen is critical for effective treatment, which reduces both mortality and healthcare costs. Traditional methods like fungal culture may be slow and have low sensitivity, especially for mixed infections and uncommon or difficult-to-culture fungal pathogens. Molecular methods have the potential to identify certain fungi faster and more accurately. In this study, a sequencing panel for clinically relevant fungi was evaluated, using PCR to amplify target sequences, followed by Nanopore sequencing and bioinformatic analysis using reference databases. The ITS-region is traditionally used for fungal identification, but cannot identify all species. To improve identification accuracy, the panel was therefore expanded with five additional genetic markers, which was the aim of this study. Amplification of all targets in a multiplex PCR was tested to streamline the analysis process. The two tested reference strains C. albicans and A. fumigatus were successfully identified by all six genetic markers demonstrating their usefulness. Simultaneous amplification via multiplex PCR, however, only worked for three of the six markers, indicating a need for further optimization. Other areas for development include optimizing the DNA extraction protocol, testing the panel on clinical samples and with additional fungal species, and establishing a bioinformatic pipeline capable of handling multi-locus analysis. To summarize, amplicon-based sequencing using multiple genetic markers showed promise as a strategy for fungal identification but further optimization is needed before the method can be implemented in clinical diagnostics.

Publication Details

Journal
KTH Publication Database DiVA (KTH Royal Institute of Technology)
Published
2025-01-01
Primary Topic
Antifungal resistance and susceptibility
Type
article
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article

Testing a sequencing panel for identification of clinically relevant fungi

KTH Publication Database DiVA (KTH Royal Institute of Technology)
Antifungal resistance and susceptibility
article

Testing a sequencing panel for identification of clinically relevant fungi

article en

Abstract

Invasive fungal infections are a severe health threat, especially for immunocompromised patients. Correct identification of the fungal pathogen is critical for effective treatment, which reduces both mortality and healthcare costs. Traditional methods like fungal culture may be slow and have low sensitivity, especially for mixed infections and uncommon or difficult-to-culture fungal pathogens. Molecular methods have the potential to identify certain fungi faster and more accurately. In this study, a sequencing panel for clinically relevant fungi was evaluated, using PCR to amplify target sequences, followed by Nanopore sequencing and bioinformatic analysis using reference databases. The ITS-region is traditionally used for fungal identification, but cannot identify all species. To improve identification accuracy, the panel was therefore expanded with five additional genetic markers, which was the aim of this study. Amplification of all targets in a multiplex PCR was tested to streamline the analysis process. The two tested reference strains C. albicans and A. fumigatus were successfully identified by all six genetic markers demonstrating their usefulness. Simultaneous amplification via multiplex PCR, however, only worked for three of the six markers, indicating a need for further optimization. Other areas for development include optimizing the DNA extraction protocol, testing the panel on clinical samples and with additional fungal species, and establishing a bioinformatic pipeline capable of handling multi-locus analysis. To summarize, amplicon-based sequencing using multiple genetic markers showed promise as a strategy for fungal identification but further optimization is needed before the method can be implemented in clinical diagnostics.

KTH Publication Database DiVA (KTH Royal Institute of Technology)
Good health and well-being
Openalex Percentile: Top 44%
Antifungal resistance and susceptibility
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