Perfluorooctanoic acid and ammonium perfluorooctanoate: volatile surfactants for proteome analysis?
Bibliographic record
Abstract
RATIONALE: Fluorinated surfactants are being explored as mass spectrometry (MS)-friendly alternatives to sodium dodecyl sulfate (SDS) for proteome analysis. Previous work demonstrates perfluorooctanoic acid (PFOA) to be compatible with electrospray ionization (ESI)-MS. The high volatility of PFOA provides an intrinsic approach to potentially eliminate the surfactant during ESI, or alternatively through solvent evaporation prior to MS. The ammonium salt of PFOA, ammonium perfluorooctanoate (APFO), is likely favored for proteome experiments; the MS and liquid chromatography (LC)/MS tolerance of APFO has not been established for proteome applications. METHODS: Standard proteins and peptides, as well as a yeast proteome mixture, were individually spiked with surfactants (APFO, PFOA, SDS), and subjected to direct infusion ESI-MS, LC/MS/MS and LC/UV. The level of fluorinated surfactant remaining after solvent evaporation under varying conditions (time, pH, salt and protein content) was quantified and compared to the threshold tolerance level of the surfactant in an MS experiment (determined herein). RESULTS: Whereas PFOA is found ineffective at assisting protein solubilization, APFO is as effective as SDS for resolubilization of acetone-precipitated yeast proteins (~100% recovery). Unfortunately, the LC and MS threshold tolerance of APFO is only minimally greater than SDS (~2-fold higher concentration to cause 50% suppression). Nonetheless, the benefits of APFO in a proteome experiment are realized following a one-step evaporation protocol for removal of the surfactant in acidified solvent. CONCLUSIONS: APFO is considered a favoured alternative to SDS for proteome solubilization. Strictly speaking, APFO is not an 'MS-friendly' surfactant for proteome characterization; the detergent not only suppresses ESI signals at high concentration, but also perturbs reversed phase separation. However, the simplicity of APFO removal ahead of LC/MS justifies its use over the conventional SDS.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".