Integrated SDS Removal and Peptide Separation by Strong-Cation Exchange Liquid Chromatography for SDS-Assisted Shotgun Proteome Analysis
Bibliographic record
Abstract
We report an improved shotgun method for analyzing proteomic samples containing sodium dodecyl sulfate (SDS). This method is based on the use of strong-cation exchange (SCX) liquid chromatography (LC) for SDS removal that can be integrated with peptide separation as the first dimension of the two-dimensional LC tandem mass spectrometry workflow. To optimize the performance of SDS removal, various experimental conditions, including the concentrations of chemical reagents and salts in the sample, the SDS concentration, and the SCX mobile phase composition, were investigated. It was found that a peptide recovery rate of about 90% could be achieved while removing SDS efficiently. One key finding was that, by increasing the SDS concentration to a certain level (0.5%) in the digested peptide sample, the sample recovery rate could be increased. The peptide recovery rate of BSA digests was found to be 90.6 ± 1.0% (n = 3), and SDS in the SCX fractions collected was not detectable by pyrolysis GC-MS, i.e., below the detection limit of 0.00006% for the undesalted SCX fractions. The peptide recovery rates were found to be 90.9% ± 2.7 (n = 3) and 89.5% ± 0.5% (n = 3) for the digests of the membrane-protein-enriched fractions of E. coli cell lysates and the MCF-7 breast cancer cell line, respectively. Compared to the methods that use acid-labile surfactants, such as RapiGest and PPS, for the MCF-7 membrane fraction sample, the SDS method identified, on average (n = 3), more peptides (∼5%) and proteins (∼16%) than the RapiGest method, while the RapiGest method identified more peptides (∼21%) and proteins (∼7%) from the E. coli membrane fraction than the SDS method. In both cases, the two methods identified more peptides and proteins than the PPS method. Since SCX is widely used as the first dimension of 2D-LC MS/MS, integration of SDS removal with peptide separation in SCX does not add any extra steps to the sample handling process. We demonstrated the application of this method for 2D-LC MS/MS profiling of the MCF-7 membrane protein fraction and identified 6889 unique peptides, corresponding to 2258 unique proteins or protein groups from two replicate experiments with a false peptide discovery rate of ∼0.8%, compared to 5172 unique peptides and 1847 unique proteins identified by the RapiGest method.
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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 | 0.003 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".