Low LC‐MS/MS detection of glycopeptides released from pmol levels of recombinant erythropoietin using nanoflow HPLC‐chip electrospray ionization
Bibliographic record
Abstract
The test used by anti-doping laboratories to detect the misuse of recombinant erythropoietin (rhEPO) is based on its different migration pattern on isoelectric focusing (IEF) gel compared with the endogenous human erythropoietin (hEPO) that can possibly be explained by structural differences. While there is definitely a need to identify those differences by LC-MS/MS, the extensive characterization that was achieved for the rhEPO was never performed on human endogenous EPO because its standard is not available in sufficient amount. The goal of this study was to develop an analytical method to detect pmol amounts of N-linked and O-linked glycopeptides of the recombinant hormone as a model. Using a nanoflow HPLC-Chip electrospray ionization/ion trap mass spectrometer, the diagnostic ion at m/z 366 of oligosaccharides was monitored in the product ion spectra to identify the four theoretical glycosylation sites, Asn24, Asn38, Asn83 and Ser126, respectively, on glycopeptides 22-37, 38-55, 73-96 and 118-136. With 3 pmol of starting material applied on Chip, only the desialylated N-glycopeptides 22-37 and 38-55/38-43 could be observed, and of all the glycan isoforms, those with the smaller structures were predominantly detected. While the preservation of the sialic acid moieties decreased the detection of all the N-glycopeptides, it allowed a more extensive characterization of the O-linked glycopeptide 118-136. The technique described herein provides a mean to detect glycopeptides from commercially available pharmaceutical preparations of rhEPO with the sensitivity required to analyze pmol amounts of hEPO, which could ultimately lead to the identification of structural differences between the recombinant and the human forms of the hormone.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".