Phosphoproteomic network analysis in the sea urchin <i>Strongylocentrotus purpuratus</i> reveals new candidates in egg activation
Bibliographic record
Abstract
Fertilization triggers a dynamic symphony of molecular transformations induced by a rapid rise in intracellular calcium. Most prominent are surface alterations, metabolic activation, cytoskeletal reorganization, and cell-cycle reentry. While the activation process appears to be broadly evolutionarily conserved, and protein phosphorylation is known to play a key role, the signaling networks mediating the response to fertilization are not well described. To address this gap, we performed a time course phosphoproteomic analysis of egg activation in the sea urchin Strongylocentrotus purpuratus, a system that offers biochemical tractability coupled with exquisite synchronicity. By coupling large-scale phosphopeptide enrichment with unbiased quantitative MS, we identified striking changes in global phosphoprotein patterns at 2- and 5-min postfertilization as compared to unfertilized eggs. Overall, we mapped 8796 distinct phosphosite modifications on 2833 phosphoproteins, of which 15% were differentially regulated in early egg activation. Activated kinases were identified by phosphosite mapping, while enrichment analyses revealed conserved signaling cascades not previously associated with egg activation. This work represents the most comprehensive study of signaling associated with egg activation to date, suggesting novel mechanisms that can be experimentally tested and providing a valuable resource for the broader research community. All MS data have been deposited in the ProteomeXchange with identifier PXD002239 (http://proteomecentral.proteomexchange.org/dataset/PXD002239).
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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".