In vivo thrombin activity in the diatom Phaeodactylum tricornutum: biotechnological insights
Bibliographic record
Abstract
Diatoms are responsible for 20% of global carbon dioxide fixation and have significant potential in various biotechnological and industrial applications. Recently, the pennate diatom Phaeodactylum tricornutum has emerged as a prominent platform organism for metabolic engineering and synthetic biology. The availability of its genome sequence has facilitated the development of new bioengineering tools. In this study, we used in silico analyses to identify sequences potentially encoding thrombin-like proteins, which are involved in recognizing and cleaving the thrombin sequence LVPRGS in P. tricornutum. Protein structure prediction and docking studies indicated a similar active site and ligand positioning compared to characterized human and bovine thrombin. The evidence and efficiency of the cleavage were determined in vivo using two fusion-protein constructs that included YFP to measure expression, protein accumulation, and cleavage. Western blot analysis revealed 50-100% cleavage between YFP and N-terminal fusion proteins. Our findings suggest the existence of a novel thrombin-like protease in P. tricornutum. This study advances the application of diatoms for the synthesis and production of complex proteins and enhances our understanding of the functional role of these putative thrombin sequences in diatom physiology. KEY POINTS: • Protein structure predictions reveal thrombin-like active sites in P. tricornutum. • Validated cleavage efficiency of thrombin-like protease on fusion proteins in vivo. • Study advances bioengineering tools for diatom-based biotechnological applications.
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.
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 | 0.000 |
| 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 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".