A simple approach for preparation of affinity matrices: Simultaneous purification and reversible immobilization of a streptavidin mutein to agarose matrix
Bibliographic record
Abstract
SAVSBPM18 is an engineered streptavidin for affinity purification of both biotinylated biomolecules and recombinant proteins tagged with streptavidin binding peptide (SBP) tags. To develop a user-friendly approach for the preparation of the SAVSBPM18-based affinity matrices, a designer fusion protein containing SAVSBPM18 and a galactose binding domain was engineered. The galactose binding domain derived from the earthworm lectin EW29 was genetically modified to eliminate a proteolytic cleavage site located at the beginning of the domain. This domain was fused to the C-terminal end of SAVSBPM18. It allows the SAVSBPM18 fusions to bind reversibly to agarose and can serve as an affinity handle for purification of the fusion. Fluorescently labeled SAVSBPM18 fusions were found to be stably immobilized on Sepharose 6B-CL. The enhanced immobilization capability of the fusion to the agarose beads results from the avidity effect mediated by the tetrameric nature of SAVSBPM18. This approach allows the consolidation of purification and immobilization of SAVSBPM18 fusions to Sepharose 6B-CL in one step for affinity matrix preparation. The resulting affinity matrix has been successfully applied to purify both SBP tagged β-lactamase and biotinylated proteins. No significant reduction in binding capacity of the column was observed for at least six months.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".