Functional genetic characterization of stress tolerance and biofilm formation in <i>Nakaseomyces</i> ( <i>Candida</i> ) <i>glabrata</i> via a novel CRISPR activation system
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Bibliographic record
Abstract
ABSTRACT The overexpression of genes frequently arises in Nakaseomyces (formerly Candida ) glabrata via gain-of-function mutations, gene duplication, or aneuploidies, with important consequences on pathogenesis traits and antifungal drug resistance. This highlights the need to develop specific genetic tools to mimic and study genetic amplification in this important fungal pathogen. Here, we report the development, validation, and applications of the first clustered regularly interspaced short palindromic repeats (CRISPR) activation (CRISPRa) system in N. glabrata for targeted genetic overexpression. Using this system, we demonstrate the ability of CRISPRa to drive high levels of gene expression in N. glabrata , and further assess optimal guide RNA targeting for robust overexpression. We demonstrate the applications of CRISPRa to overexpress genes involved in fungal pathogenesis and drug resistance and detect corresponding phenotypic alterations in these key traits, including the characterization of novel phenotypes. Finally, we capture strain variation using our CRISPRa system in two commonly used N. glabrata genetic backgrounds. Together, this tool will expand our capacity for functional genetic overexpression in this pathogen, with numerous possibilities for future applications. IMPORTANCE Nakaseomyces (formerly Candida ) glabrata is an important fungal pathogen that is now the second leading cause of candidiasis infections. A common strategy that this pathogen employs to resist antifungal treatment is through the upregulation of gene expression, but we have limited tools available to study this phenomenon. Here, we develop, optimize, and apply the use of CRISPRa as a means to overexpress genes in N. glabrata . We demonstrate the utility of this system to overexpress key genes involved in antifungal susceptibility, stress tolerance, and biofilm growth. This tool will be an important contribution to our ability to study the biology of this important fungal pathogen.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it