A “Tagless” Strategy for Identification of Stable Protein Complexes Genome-wide by Multidimensional Orthogonal Chromatographic Separation and iTRAQ Reagent Tracking
Bibliographic record
Abstract
Tandem affinity purification is the principal method for purifying and identifying stable protein complexes system-wide in whole cells. Although highly effective, this approach is laborious and impractical in organisms where genetic manipulation is not possible. Here, we propose a novel "tagless" strategy that combines multidimensional separation of endogenous complexes with mass spectrometric monitoring of their composition. In this procedure, putative protein complexes are identified based on the comigration of collections of polypeptides through multiple orthogonal separation steps. We present proof-of-principle evidence for the feasibility of key aspects of this strategy. A majority of Escherichia coli proteins are shown to remain in stable complexes during fractionation of a crude extract through three chromatographic steps. We also demonstrate that iTRAQ reagent-based tracking can quantify relative migration of polypeptides through chromatographic separation media. LC MALDI MS and MS/MS analysis of the iTRAQ-labeled peptides gave reliable relative quantification of 37 components of 13 known E. coli complexes: 95% of known complex components closely co-eluted and 57% were automatically grouped by a prototype computational clustering method. With further technological improvements in each step, we believe this strategy will dramatically improve the efficiency of the purification and identification of protein complexes in cells.
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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 | 0.001 | 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".