Gene knock out of honey bee trypanosomatid parasite, <i>Lotmaria passim</i> , by CRISPR/Cas9 system
Bibliographic record
Abstract
Abstract Two trypanosomatid species, Lotmaria passim and Crithidia mellificae, have been shown to parasitize honey bees to date. L. passim appears to be more prevalent than C. mellificae and specifically infects the honey bee hindgut. Although the genomic DNA has been sequenced, the effects of infection on honey bee health and colony are poorly understood. To identify the genes that are important for infecting honey bees and to understand their functions, we applied the CRISPR/Cas9 system to establish a method to manipulate L. passim genes. By electroporation of plasmid DNA and subsequent selection by antibiotics, we first established an L. passim clone expressing tdTomato, GFP, or Cas9. We also successfully knocked out the endogenous miltefosine transporter and tyrosine amino transferase genes by replacement with antibiotics (hygromycin) resistant gene using the CRISPR/Cas9-induced homology-directed repair pathway. The L. passim clones expressing fluorescent markers, as well as the simple method for knocking out specific genes, could become useful approaches to understand the underlying mechanisms of honey bee-trypanosomatid parasite interactions.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".