High-Level Expression, Single-Step Immunoaffinity Purification and Characterization of Human Tetraspanin Membrane Protein CD81
Bibliographic record
Abstract
The study of membrane protein structure and function requires their high-level expression and purification in fully functional form. We previously used a tetracycline-inducible stable mammalian cell line, HEK293S-TetR, for regulated high-level expression of G-protein coupled receptors. We here report successfully using this method for high-level expression of de novo oligo-DNA assembled human CD81 gene. CD81 is a member of the vital tetraspanin membrane protein family. It has recently been identified as the putative receptor for the Hepatitis C Virus envelope E2 glycoprotein (HCV-E2). In this study we used a single-step rho-1D4-affinity purification method to obtain >95% purity from HEK293S-TetR-inducible stable cell lines. Using ELISA assay we determined that the affinity of the purified CD81 receptor for HCV-E2 protein is 3.8+/-1.2 nM. Using fluorescent confocal microscopy we showed that the inducibly overexpressed CD81 receptor in HEK293S-TetR cells is correctly located on the plasma membrane. We demonstrated that the combination of high-level expression of CD81 with efficient single-step immunoaffinity purification is a useful method for obtaining large quantities of CD81 membrane receptor suitable for detailed structural analyses of this elusive tetraspanin protein. Furthermore, this simple single-step immunoaffinity purification to high purity of membrane protein could be useful broadly for other membrane protein purifications, thus accelerating the determination of structures for large numbers of difficult-to-obtain membrane proteins.
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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) | 0.000 | 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 | 0.001 |
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".