High-Resolution Mapping of Protein Concentration Reveals Principles of Proteome Architecture and Adaptation
Bibliographic record
Abstract
A single yeast cell contains a hundred million protein molecules. How these proteins are organized to orchestrate living processes is a central question in biology. To probe this organization in vivo, we measured the local concentration of proteins based on the strength of their nonspecific interactions with a neutral reporter protein. We first used a cytosolic reporter and measured local concentrations for ~2,000 proteins in S. cerevisiae, with accuracy comparable to that of mass spectrometry. Localizing the reporter to membranes specifically increased the local concentration measured for membrane proteins. Comparing the concentrations measured by both reporters revealed that encounter frequencies between proteins are primarily dictated by their abundances. However, to change these encounter frequencies and restructure the proteome, as in adaptation, we find that changes in localization have more impact than changes in abundance. These results highlight how protein abundance and localization contribute to proteome organization and reorganization.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".