A comparative evaluation of CRISPR-Cas9 allele editing systems in <i>Candida auris</i> : challenging research in a challenging bug
Bibliographic record
Abstract
Abstract Candida auris is an emergent fungal pathogen of significant interest for molecular research because of its unique nosocomial persistence, high stress tolerance and common multidrug resistance. To investigate the molecular mechanisms of these or other phenotypes, a handful of CRISPR-Cas9 based allele editing tools have been optimized for C. auris . Nonetheless, allele editing in this species remains a significant challenge, and different systems have different advantages and disadvantages. In this work, we compare four systems to introduce the genetic elements necessary for the production of Cas9 and the guide RNA molecule in the genome of C. auris, replacing the ENO1 , LEU2 and HIS1 loci respectively, while the fourth system makes use of an episomal plasmid. We observed that the editing efficiency of all four systems was significantly different and strain dependent. Alarmingly, we did not detect correct integration of linear CRISPR cassette constructs in integration-based systems, in over 4,900 screened transformants. Still, all transformants, whether correctly edited or not, grew on selective nourseothricin media, suggesting common random ectopic integration of the CRISPR cassette. Although the plasmid-based system showed a low transformation success compared to the other systems, it has the highest editing efficiency with 41.9% correct transformants on average. In an attempt to improve editing efficiencies of integration-based systems by silencing the non-homologous end joining (NHEJ) DNA repair pathway, we deleted two main NHEJ factors, KU70 and LIG4 . However, no improved editing or targeting efficiencies were detected in ku7011, lig411, or ku7011/lig411 backgrounds. Our research highlights important challenges in precise genome editing of C. auris and sheds light on the advantages and limitations of several methods with the aim to guide scientists in selecting the most appropriate tool for molecular work in this enigmatic fungal pathogen. Author summary Candida auris is a rapidly emerging fungal pathogen that poses serious challenges to global healthcare. Understanding the genetic mechanisms that underlie its nosocomial persistence, virulence, multidrug resistance and other traits is essential for developing new treatments and preventing the spread and burden of C. auris infections. However, precise genetic manipulation in C. auris has proven difficult due to inefficient genome editing tools. This study compares four different CRISPR-based allele editing systems in C. auris , identifying their strengths and limitations. The findings provide crucial insights into selecting the best tools for genetic research in C. auris , guiding future efforts to combat this formidable pathogen.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".