A bio-coupling approach using a dextran-binding domain to immobilize an engineered streptavidin to Sephadex for easy preparation of affinity matrix
Bibliographic record
Abstract
An engineered streptavidin, SAVSBPM18 with reversible biotin binding capability, has been successfully applied to purify biotinylated and streptavidin-binding peptide (SBP) tagged proteins. To simplify the preparation for the SAVSBPM18 affinity matrix without chemical conjugation, two bio-coupling approaches were developed based on a 14-kDa dextran-binding domain (DBD) from a Leuconostoc mesenteroides dextransucrase. The first approach offers simplicity for bio-coupling by creating a direct fusion, SAVSBPM18-Linker-DBD. Purification of the fusion from crude extract and its immobilization to Sephadex can be consolidated in one-step. The second approach aims at flexibility. A SnoopCatcher (SC) was fused to DBD to create SC-Linker-DBD. This fusion can covalently capture any recombinant proteins tagged with a SnoopTag (ST) including SAVSBPM18-Linker-ST via the formation of an isopeptide bond at the interface through the SnoopCatcher-SnoopTag interaction. Although monomeric DBD binds to dextran with nanomolar affinity, DBD tetramerized via streptavidin (SAVSBPM18-Linker-ST·SC-Linker-DBD) showed an even tighter binding to Sephadex. The majority of the fluorescently labelled DBD tetramers were retained on the Sephadex surface even after four months. Affinity columns generated using either approach effectively purified both SBP-tagged and biotinylated proteins. These columns are reusable and functional even after a year of frequent use.
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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 | 0.001 | 0.000 |
| 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 | 0.000 |
| 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".