Studying polyphosphorylation, a novel PTM, in mammalian cell lines
Bibliographic record
Abstract
Polyphosphates are long chains of phosphates attached to one another via high‐energy phosphoanhydride bonds. The literature reports their implication in a variety of medically related functions, such as apoptosis, blood coagulation, and inflammation. The mechanisms involved with polyphosphate and its functions have been studied in bacteria and in yeast, but the synthesis pathway of polyphosphate in mammals is still unknown. Moreover, the concentrations of polyphosphate in mammalian cells (<1mM) are much lower than the ones found in yeast (100–200mM). This makes it challenging to study polyphosphate biology and polyphosphorylation in mammalian cell lines. Recently, Azevedo, et al. (2015) identified a new PTM in yeast called polyphosphorylation and two targets of this PTM: Nsr1 and Top1. It consists of the non‐enzymatic covalent attachment of polyphosphate chains to lysine residues found in a poly‐acidic serine and lysine‐rich (PASK) motif. Our lab has since identified 24 novel yeast targets being polyphosphorylated. Our next aim was to test if human proteins can also be polyphosphorylated. In order to modulate the concentrations of polyphosphate in the cell, we transfected mammalian cells with PPK1, an E. coli enzyme that synthesizes polyphosphate. This ectopic expression allowed us to perform a small “screen” and identify 6 human proteins that can be polyphosphorylated: nucleolin, hNop56, Mesd chaperone, DEK, eIF5B and UPF3B. We will present our latest work focused on determining the molecular function of polyphosphorylation in mammalian cells. Support or Funding Information This project is funded by the Canadian Institutes of Health Research (CIHR). This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".