Back

Aneuploidy, polyploidy, and loss of heterozygosity distinguish serial bloodstream isolates of Candida albicans

Scott, N. E.; Zhou, X.; Wash, E.; Zajac, C.; Kline, S. E.; Erayil, S. E.; Selmecki, A.

2025-10-27 microbiology
10.1101/2025.10.27.684856 bioRxiv
Show abstract

BackgroundThe opportunistic pathogen Candida albicans is the leading species causing invasive Candida infections worldwide. Genomic variation is widespread in clinical isolates and complicates identification of genetic variants underlying antifungal drug resistance and tolerance. Our understanding of genomic and phenotypic diversity during invasive infections is limited and studies of serial isolates from individual patients are uncommon. We performed comparative analyses of 101 C. albicans bloodstream isolates from 55 patients in the Minnesota Minneapolis-Saint Paul region, including serial isolates from 19 patients. We analyzed the phylogenetic relationships of these isolates relative to 199 globally-collected public C. albicans genomes. ResultsThis studys regional isolates span the phylogenetic diversity of C. albicans; 6 isolates represent novel outliers to known clades. Serial isolates from individual patients were separated by limited single nucleotide polymorphisms. Nevertheless, we identified extensive large-scale genomic variation between serial isolates including polyploidy, aneuploidy, copy number variation, loss of heterozygosity, and chromosomal rearrangements. We demonstrated how a heterozygous ERG251 loss of function variant drives azole tolerance in a clinical isolate from a patient with a history of recurrent infections. Using serial isolates, we demonstrated that polyploidy provides an adaptive advantage in the presence of fluconazole despite the absence of overt antifungal drug resistance. ConclusionsOur analysis of serial isolates reveals the genomic plasticity of C. albicans during invasive infections and identifies variation driving antifungal drug tolerance. Our findings reveal limitations in current antifungal susceptibility testing and highlight the need to account for genomic and phenotypic variation during invasive Candida infections.

Published in Microbial Genomics (predicted rank #13) · training set

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.