Engineering of a wheat germ expression system to provide compatibility with a high throughput pET-based cloning platform
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Wheat germ cell-free methods provide an important approach for the production of eukaryotic proteins. We have developed a protein expression vector for the TNT((R)) SP6 High-Yield Wheat Germ Cell-Free (TNT WGCF) expression system (Promega) that is also compatible with our T7-based Escherichia coli intracellular expression vector pET15_NESG. This allows cloning of the same PCR product into either one of several pET_NESG vectors and this modified WGCF vector (pWGHisAmp) by In-Fusion LIC cloning (Zhu et al. in Biotechniques 43:354-359, 2007). Integration of these two vector systems allowed us to explore the efficacy of the TNT WGCF system by comparing the expression and solubility characteristics of 59 human protein constructs in both WGCF and pET15_NESG E. coli intracellular expression. While only 30% of these human proteins could be produced in soluble form using the pET15_NESG based system, some 70% could be produced in soluble form using the TNT WGCF system. This high success rate underscores the importance of eukaryotic expression host systems like the TNT WGCF system for eukaryotic protein production in a structural genomics sample production pipeline. To further demonstrate the value of this WGCF system in producing protein suitable for structural studies, we scaled up, purified, and analyzed by 2D NMR two (15)N-, (13)C-enriched human proteins. The results of this study indicate that the TNT WGCF system is a successful salvage pathway for producing samples of difficult-to-express small human proteins for NMR studies, providing an important complementary pathway for eukaryotic sample production in the NESG NMR structure production pipeline.
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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 | 0.000 |
| 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 it