Effects of Ammonium Bicarbonate on the Electrospray Mass Spectra of Proteins: Evidence for Bubble-Induced Unfolding
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Bibliographic record
Abstract
Many protein investigations by electrospray ionization (ESI) mass spectrometry (MS) strive to ensure a "native" solvent environment, i.e., nondenaturing conditions up to the point of gas-phase ion formation. Ideally, these studies would employ a volatile pH buffer to mitigate changes in H(+) concentration that can occur during ESI. Ammonium acetate is a commonly used additive, despite its low buffering capacity at pH 7. Ammonium bicarbonate provides greatly improved pH stabilization, thus offering an interesting alternative. Surprisingly, protein analyses in bicarbonate at pH 7 tend to result in the formation of very high charge states, similar to those obtained when electrospraying unfolded proteins in a denaturing solvent. This effect has been reported previously (Sterling, H. J.; Cassou, C. A.; Susa, A. C.; Williams, E. R. Anal. Chem. 2012, 84, 3795), but its exact mechanistic origin remains unclear. ESI-mediated unfolding does not take place in acetate under otherwise identical conditions. We demonstrate that heating of protein-containing bicarbonate solutions results in extensive foaming, caused by CO2 outgassing. In contrast, acetate solutions do not generate foam. Protein denaturation caused by gas bubbles is a well-known phenomenon. Adsorption to the gas/liquid interface is accompanied by major conformational changes that allow the protein to act as a surfactant. The foaming of beer is a manifestation of this effect. Bubble formation in bicarbonate during ESI is facilitated by collisional and blackbody droplet heating. Our data imply that heat and bubbles act synergistically to cause unfolding during the electrospray process, while proteins reside in ESI droplets. Because of this effect we advise against the use of ammonium bicarbonate for native ESI-MS. Ammonium acetate represents a gentler droplet environment, despite its low buffering capacity.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it