Separation and Identification of Peptides from Gel-Isolated Membrane Proteins Using a Microfabricated Device for Combined Capillary Electrophoresis/Nanoelectrospray Mass Spectrometry
Bibliographic record
Abstract
The coupling of microfabricated devices to nanoelectrospray mass spectrometers using both a triple quadrupole and a quadrupole time-of-flight mass spectrometer (QqTOF MS) is presented for the analysis of trace-level membrane proteins. Short disposable nanoelectrospray emitters were directly coupled to the chip device via a low dead volume connection. The analytical performance of this integrated device in terms of sensitivity and reproducibility was evaluated for standard peptide mixtures. A concentration detection limit ranging from 3.2 to 43.5 nM for different peptides was achieved in selected ion monitoring, thus representing a 10-fold improvement in sensitivity compared to that of microelectrospray using the same chip/mass spectrometer. Replicate injections indicated that reproducibility of migration time was typically less than 3.1% RSD whereas RSD values of 6-13% were observed on peak areas. Although complete resolution of individual components is not typically achieved for complex digests, the present chip capillary electrophoresis (chip-CE) device enabled proper sample cleanup and partial separation of multicomponent samples prior to mass spectral identification. Analyses of protein digests were typically achieved in less than 1.5 min with peak widths of 1.8-2.5 s (half-height definition) as indicated from individual reconstructed ion electropherograms. The application of this chip-CE/QqTOF MS system is further demonstrated for the identification of membrane proteins which form a subset of the Haemophilus influenzae proteome. Bands first separated by 1D-gel electrophoresis were excised and digested, and extracted tryptic peptides were loaded on the chip without any further sample cleanup or on-line adsorption preconcentration. Accurate molecular mass determination (< 5 ppm) in peptide-mapping experiments was obtained by introducing an internal standard via a postseparation channel. The analytical potential of this integrated device for the identification of trace-level proteins from different strains of H. influenzae is demonstrated using both peptide mass-fingerprint database searching and on-line tandem mass spectrometry.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".