A benchmark dataset for validating <i>FKS1</i> mutations in <i>Candida auris</i>

Echinocandins are the recommended first-line treatment for invasive infections caused by <i>Candida auri</i>s, a multi-drug-resistant yeast that has emerged in healthcare facilities globally. Increasing instances of echinocandin-resistant cases highlight the need for rapid detection and response. We developed a benchmark dataset comprising 100 <i>C. auris</i> echinocandin-resistant and -susceptible isolates to demonstrate the utility of the bioinformatics tool, MycoSNP-nf, for detecting echinocandin resistance-related <i>FKS1</i> mutations and to assess their concordance with antifungal susceptibility testing results. This benchmark may help validate MycoSNP-nf and other bioinformatics tools aimed at detecting these mechanisms using whole-genome sequencing data.

Authors

Institutions

Publication Details

Journal
Microbiology Spectrum
Published
2025-06-18
DOI
https://doi.org/10.1128/spectrum.03147-24
Citations
3
Primary Topic
Antifungal resistance and susceptibility
Type
article
Field-Weighted Citation Impact
4.19
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A benchmark dataset for validating FKS1 mutations in Candida auris

Lalitha Gade, Nancy A. Chow, Zachary B. Mudge, Amanda Ribeiro dos Santos et al.
3 citations
Microbiology Spectrum
Antifungal resistance and susceptibility
4.19
article

A benchmark dataset for validating FKS1 mutations in Candida auris

Lalitha Gade, Nancy A. Chow, Zachary B. Mudge, Amanda Ribeiro dos Santos, Kaitlin Forsberg, Shawn R. Lockhart, Meghan Lyman, D. Joseph Sexton, Luisa F. López, Elizabeth Misas, Malavika Rajeev, Lindsay A. Parnell, Anastasia P. Litvintseva
article en
3 citations

Abstract

Echinocandins are the recommended first-line treatment for invasive infections caused by <i>Candida auri</i>s, a multi-drug-resistant yeast that has emerged in healthcare facilities globally. Increasing instances of echinocandin-resistant cases highlight the need for rapid detection and response. We developed a benchmark dataset comprising 100 <i>C. auris</i> echinocandin-resistant and -susceptible isolates to demonstrate the utility of the bioinformatics tool, MycoSNP-nf, for detecting echinocandin resistance-related <i>FKS1</i> mutations and to assess their concordance with antifungal susceptibility testing results. This benchmark may help validate MycoSNP-nf and other bioinformatics tools aimed at detecting these mechanisms using whole-genome sequencing data.

Microbiology SpectrumVol. 13(8)
Centers for Disease Control and Prevention (US), United States Department of Health and Human Services (US), The Centers (US), Centers for Disease Control and Prevention (KE)
Partnerships for the goals
Openalex Percentile: Top 6%
Antifungal resistance and susceptibility
4.19
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A benchmark dataset for validating <i>FKS1</i> mutations in <i>Candida auris</i> — Lalitha Gade, Nancy A. Chow, et al. · Microbiology Spectrum (2025) | TGRS Research Map | TGRS