PHYCUT: Scalable Multiplex CRISPR/Cas9 Editing for Genome Engineering in the Diatom <i>Phaeodactylum tricornutum</i>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT Diatoms are globally significant microalgae that contribute ∼ 20% of oxygen production and exhibit remarkable metabolic diversity. The marine diatom Phaeodactylum tricornutum has emerged as a promising synthetic biology platform for bioproduction of recombinant proteins, supported by a human-like N -linked glycosylation pathway. However, its α (1,3)-linked core fucose is immunogenic in humans and thus limits biopharmaceutical applications. One hurdle to efficient genome engineering in P. tricornutum is the lack of a robust system for simultaneous CRISPR/Cas9 editing at multiple sites. To overcome this limitation, we develop PHYCUT ( Ph aeodactylum tricornutum Cs y 4- C as9 m u ltiplex t ool), a versatile plasmid-based CRISPR/Cas9 system that uses the Csy4 endoribonuclease to process multi-guide RNA arrays. To highlight PHYCUT applications, we demonstrate multiplex editing of all three FucT genes responsible for α (1,3) fucosylation in P. tricornutum , yielding strains with markedly reduced fucosylation of secreted proteins. PHYCUT enables facile, multiplexed genome engineering in diatoms and provides a foundation for humanizing the P. tricornutum glycosylation pathway to support next-generation algal biotechnology.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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