Targeted integration by homologous recombination enables <i>in situ</i> tagging and replacement of genes in the marine microeukaryote <i>Diplonema papillatum</i>
Bibliographic record
Abstract
Diplonemids are a group of highly diverse and abundant marine microeukaryotes that belong to the phylum Euglenozoa and form a sister clade to the well-studied, mostly parasitic kinetoplastids. Very little is known about the biology of diplonemids, as few species have been formally described and just one, Diplonema papillatum, has been studied to a decent extent at the molecular level. Following up on our previous results showing stable but random integration of delivered extraneous DNA, we demonstrate here homologous recombination in D. papillatum. Targeting various constructs to the intended position in the nuclear genome was successful when 5' and 3' homologous regions longer than 1 kbp were used, achieving N-terminal tagging with mCherry and gene replacement of α- and β-tubulins. For more convenient genetic manipulation, we designed a modular plasmid, pDP002, which bears a protein-A tag and used it to generate and express a C-terminally tagged mitoribosomal protein. Lastly, we developed an improved transformation protocol for broader applicability across laboratories. Our robust methodology allows the replacement, integration as well as endogenous tagging of D. papillatum genes, thus opening the door to functional studies in this species and establishing a basic toolkit for reverse genetics of diplonemids in general.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".