Multiplexed Size Separation of Intact Proteins in Solution Phase for Mass Spectrometry
Bibliographic record
Abstract
Reliable size-based protein separation is an invaluable biological technique. Unfortunately, size separation in solution is underutilized, owing perhaps to the poor resolution of conventional techniques. Here, we report an enhanced multiplexed GELFrEE (gel-eluted liquid fraction entrapment electrophoresis) device which incorporates eight independent separation channels, operating with high repeatability. This enables simultaneous size separation of independent proteome samples, each into 16 well resolved liquid fractions, covering 10-150 kDa in 1.5 h. A novel strategy to increase sample loads while maintaining electrophoretic resolution is presented by distributing the sample among the eight channels with subsequent pooling of collected fractions. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of the S. cerevisiae proteome following GELFrEE separation and sodium dodecyl sulfate (SDS) removal demonstrates the resolution and high correlation achieved between molecular weight and fraction number for the identified proteins. This device is highly orthogonal to solution isoelectric focusing, enabling our disclosure of a fully multiplexed high-throughput two-dimensional liquid electrophoretic (2D LE) platform that separates analogously to 2D polyacrylamide gel electrophoresis (PAGE). With 2D LE, a total of 128 well-resolved liquid fractions are obtained from 1 mg of S. cerevisiae proteins covering ranges 3.8 < pI < 7.8 and 10 kDa < MW < 150 kDa in an unprecedented 3.25 h total separation time.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".