On-line aptamer affinity solid-phase extraction capillary electrophoresis-mass spectrometry for the determination of SARS-CoV-2 nucleocapsid protein
Bibliographic record
Abstract
• An aptamer affinity sorbent was prepared against the SARS-CoV-2 N protein. • AA-SPE-CE-MS allowed the unequivocal and accurate determination of the N protein. • The method required important adaptations compared to previous studies. • Up to 500 times sensitivity enhancement compared to CE-MS was achieved. • The method was applied to saliva samples. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for coronavirus disease 2019 (COVID-19), which has sparked a significant global health crisis in recent years. Among its structural proteins, the nucleocapsid protein (N protein) stands out as one of the most abundant. Despite being well-recognized as an immunodominant antigen in host immune responses and a promising diagnostic biomarker, further insight into this protein with novel analytical methods is crucial for understanding the disease mechanisms. This study focuses on the development of an aptamer affinity sorbent for the purification, preconcentration, separation, characterization, and quantification of the N protein using on-line aptamer affinity solid-phase extraction capillary electrophoresis-mass spectrometry (AA-SPE-CE-MS). Microcartridges packed with a sorbent composed of magnetic bead (MB) particles modified with an aptamer against the N protein were utilized. A rigorous optimization of several method parameters resulted in the use of a lab-made hydroxypropyl cellulose (HPC)-coated capillary to prevent protein adsorption and a neutral background electrolyte (BGE) of 10 mM ammonium acetate (pH 7.0) for the separation. The sample was loaded in the BGE, and the retained protein was subsequently eluted with 1 M acetic acid (pH 2.3). The developed method demonstrated repeatability in terms of migration times and peak areas, exhibited linearity between 2.5 and 25 µg mL −1 , and achieved a limit of detection (LOD) of 0.5 µg mL −1 , providing a sensitivity enhancement of 500 times compared to CE-MS. It was finally applied to the analysis of the N protein in human saliva, pointing out its potential for establishing accurate SARS-CoV-2 complementary analytical methods.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".