Data supporting "Single-cell detection of copy number changes reveals dynamic mechanisms of adaptation to antifungals in Candida albicans"

Zhou, Xin
Hilk, Audrey
Solis, Norma V
Scott, Nancy
Beach, Annette
Soisangwan, Natthapon
Billings, Clara L
Burrack, Laura S
Filler, Scott G
Selmecki, Anna
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Data supporting "Single-cell detection of copy number changes reveals dynamic mechanisms of adaptation to antifungals in Candida albicans"

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Anna Selmecki




Genomic copy number changes are associated with antifungal drug resistance and virulence across diverse fungal pathogens. Despite the high prevalence of both gain and loss events, the rate and dynamics of these genomic changes in the presence of antifungal drugs is not known for any organism. We optimized a dual-fluorescent reporter system in the diploid pathogen Candida albicans to quantify copy number variation (CNV) and loss of heterozygosity (LOH) at the single cell level with flow cytometry. We followed the rate and dynamics of CNV and LOH at two distinct genomic locations during parallel evolution experiments in the presence and absence of antifungal drugs in vitro and in a murine model of infection. Copy number changes were rapid and dynamic during adaptation to three different concentrations of the azole drug fluconazole. The fluorescent reporters revealed competing sub-populations with distinct genotypes in the drug-evolved lineages. Extensive whole genome sequencing identified recurrent genotypes that cause increased competitive fitness in the presence of antifungal drug. Specifically, at low concentrations of drug, chromosome 3 (Chr3) LOH frequently arose and led to significantly increased competitive fitness. In contrast, at high drug concentrations, Chr3 and Chr6 aneuploidy arose together, and these concurrent aneuploidies conferred multi-azole tolerance. In the murine model, copy number changes were only detected in isolates recovered from mice treated with fluconazole, and included whole-genome duplication events resulting in polyploidy. This study provides the first quantitative evidence for the incredible speed at which diverse genotypes arise and undergo dynamic population-level fluctuations during adaptation to antifungal drugs in vitro and in vivo.  


Most of data are flow cytometry data with file format .fcs and supplemented with a readme file (.pdf) providing the sample name and layout. There are also some yeast growth curve data with file format .xlsx

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National Institutes of Health (R01 AI143689)
Burroughs Wellcome Fund Investigator in the Pathogenesis of Infectious Diseases Award (#1020388)

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Zhou, Xin; Hilk, Audrey; Solis, Norma V; Scott, Nancy; Beach, Annette; Soisangwan, Natthapon; Billings, Clara L; Burrack, Laura S; Filler, Scott G; Selmecki, Anna. (2024). Data supporting "Single-cell detection of copy number changes reveals dynamic mechanisms of adaptation to antifungals in Candida albicans". Retrieved from the Data Repository for the University of Minnesota (DRUM),
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Main figures Fig1-3.zip2.15 GB
Main figures Fig 5C.zip4.4 GB
Main figures Fig 5E&6.zip1 GB
Extended Data Figures and Supplementary Tables.zip378.27 MB
Readme_Zhou_Selmecki_2024.pdfDescription of the data217.56 KB

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