CRISPR-Based Genetic Manipulation of Candida Species: Historical Perspectives and Current Approaches
Bibliographic record
Abstract
The Candida genus encompasses a diverse group of ascomycete fungi that have captured the attention of the scientific community, due to both their role in pathogenesis and emerging applications in biotechnology; the development of gene editing tools such as CRISPR, to analyze fungal genetics and perform functional genomic studies in these organisms, is essential to fully understand and exploit this genus, to further advance antifungal drug discovery and industrial value. However, genetic manipulation of Candida species has been met with several distinctive barriers to progress, such as unconventional codon usage in some species, as well as the absence of a complete sexual cycle in its diploid members. Despite these challenges, the last few decades have witnessed an expansion of the Candida genetic toolbox, allowing for diverse genome editing applications that range from introducing a single point mutation to generating large-scale mutant libraries for functional genomic studies. Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 technology is among the most recent of these advancements, bringing unparalleled versatility and precision to genetic manipulation of Candida species. Since its initial applications in Candida albicans , CRISPR-Cas9 platforms are rapidly evolving to permit efficient gene editing in other members of the genus. The technology has proven useful in elucidating the pathogenesis and host-pathogen interactions of medically relevant Candida species, and has led to novel insights on antifungal drug susceptibility and resistance, as well as innovative treatment strategies. CRISPR-Cas9 tools have also been exploited to uncover potential applications of Candida species in industrial contexts. This review is intended to provide a historical overview of genetic approaches used to study the Candida genus and to discuss the state of the art of CRISPR-based genetic manipulation of Candida species, highlighting its contributions to deciphering the biology of this genus, as well as providing perspectives for the future of Candida genetics.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".