Top-down analysis of immunoglobulin G isotypes 1 and 2 with electron transfer dissociation on a high-field Orbitrap mass spectrometer
Bibliographic record
Abstract
Abstract The increasing importance of immunoglobulins G (IgGs) as biotherapeutics calls for improved structural characterization methods designed for these large (~ 150 kDa) macromolecules. Analysis workflows have to be rapid, robust, and require minimal sample preparation. In a previous work we showed the potential of Orbitrap Fourier transform mass spectrometry (FTMS) combined with electron transfer dissociation (ETD) for the top-down investigation of an intact IgG1, resulting in ~ 30% sequence coverage. Here, we describe a top-down analysis of two IgGs1 (adalimumab and trastuzumab) and one IgG2 (panitumumab) performed with ETD on a mass spectrometer equipped with a high-field Orbitrap mass analyzer. For the IgGs1, sequence coverage comparable to the previous results was achieved in a two-fold reduced number of summed transients, which corresponds, taken together with the significantly increased spectra acquisition rate, to ~ six-fold improvement in analysis time. Furthermore, we studied the influence of ion-ion interaction times on ETD product ions for IgGs1, and the differences in fragmentation behavior between IgGs1 and IgG2, which present structural differences. Overall, these results reinforce the hypothesis that gas phase dissociation using both energy threshold-based and radical-driven ion activations is directed to specific regions of the polypeptide chains mostly by the location of disulfide bonds. Significance of the study Compared with our previous report, the results presented herein demonstrate the power of technological advances of the next generation Orbitrap™ platform, including the use of a high-field compact (i.e., D20) Orbitrap mass analyzer, and a dedicated manipulation strategy for large protein ions (via their trapping in the HCD collision cell along with reduction of the pressure in the cell). Notably, these important developments became recently commercially available in the top-end Orbitrap platforms under the name of “Protein Mode”. Furthermore, we continued exploring the advantages offered by the summation (averaging) of transients (time-domain data) for improving the signal-to-noise ratio of top-down mass spectra. Finally, for the first time we report the application of the hybrid ion activation technique that combines electron transfer dissociation and higher energy collisional dissociation, known as EThcD, on intact monoclonal antibodies. Under these specific instrumental parameters, EThcD produces a partially complementary fragmentation pattern compared to ETD, increasing the overall sequence coverage especially at the protein termini.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".