Protocol for reconstituting enzymatic activities for ultra-large histone methyltransferases NSD1 and SETD2 using a baculovirus expression system
Bibliographic record
Abstract
Expression and reconstitution of large proteins in the human proteome are challenging and often require the use of a mammalian cell expression system that is costly and inefficient. Here, we present a protocol to reconstitute catalytically active, full-length NSD1 (nuclear receptor binding SET domain protein 1) and SETD2 (SET domain containing 2, histone lysine methyltransferase) using a clonal baculovirus expression system. We describe steps for producing baculovirus, clonal selection, and protein reconstitution. We then detail procedures for using animatic assays. For complete details on the use and execution of this protocol, please refer to Hsu et al. 1 • Instructions for clonal selection of baculovirus using the Sf9 expression system • Expression and purification of large methyltransferases NSD1 and SETD2 • Steps for a histone methyltransferase assay for catalytic activity of NSD1 and SETD2 Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. Expression and reconstitution of large proteins in the human proteome are challenging and often require the use of a mammalian cell expression system that is costly and inefficient. Here, we present a protocol to reconstitute catalytically active, full-length NSD1 (nuclear receptor binding SET domain protein 1) and SETD2 (SET domain containing 2, histone lysine methyltransferase) using a clonal baculovirus expression system. We describe steps for producing baculovirus, clonal selection, and protein reconstitution. We then detail procedures for using animatic assays.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".