Quantitative proteomic comparison of stationary/G0 phase cells and tetrads in budding yeast
Bibliographic record
Abstract
Most of the microbial cells on earth under natural conditions exist in a dormant condition, commonly known as quiescent state. Quiescent cells exhibit low rates of transcription and translation suggesting that cellular abundance of proteins may be similar in quiescent cells. Therefore, this study aim to compare the proteome of budding yeast cells from two quiescent states viz. stationary phase/G0 and tetrads. Using iTRAQ (isobaric tag for relative and absolute quantitation) based quantitative proteomics we identified 289 proteins, among which around 40 proteins exhibited ±1.5 fold change consistently from the four biological replicates. Proteomics data was validated by western blot and denstiometric analysis of Hsp12 and Spg4. Level of budding yeast 14-3-3 proteins was found to be similar in both the quiescent states, whereas Hsp12 and Spg4 expressed only during stress. FACS (fluorescence-activated cell sorting) analysis showed that budding yeast cells were arrested at G1 stages both in tetrads as well as in stationary phase. We also observed that quiescent states did not express Ime1 (inducer of meiosis). Taken together, our present study demonstrates that the cells in quiescent state may have similar proteome, and accumulation of proteins like Hsp12, Hsp26, and Spg4 may play an important role in retaining viability of the cells during dormancy.
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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 | 0.001 | 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".