RAB21 Activity Assay Using GST-fused APPL1
Bibliographic record
Abstract
The Rab family of small GTPases are essential regulators of membrane trafficking events. As with other small GTPase families, Rab GTPases cycle between an inactive GDP-bound state and an active GTP-bound state. Guanine nucleotide exchange factors (GEFs) promote Rab activation with the exchange of bound GDP for GTP, while GTPase-activating proteins (GAPs) regulate Rab inactivation with GTP hydrolysis. Numerous methods have been established to monitor the activation status of Rab GTPases. Of those, FRET-based methods are used to identify when and where a Rab GTPase is activated in cells. Unfortunately, the generation of such probes is complex, and only a limited number of Rabs have been probed this way. Biochemical purification of activated Rabs from cell or tissue extracts is easily achievable through the use of a known Rab effector domain to pull down a specific GTP-bound Rab form. Although this method is not ideal for detailed subcellular localization, it can offer temporal resolution of Rab activity. The identification of a growing number of specific effectors now allows tests for activation levels of many Rab GTPases in specific conditions. Here, we described an affinity purification approach using GST fused APPL1 (a known RAB21 effector) to test RAB21 activation in mammalian cells. This method was successfully used to assay changes in RAB21 activation status under nutrient rich versus starved conditions and to test the requirement of the MTMR13 RAB21 GEF in this process.
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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 | 0.000 | 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 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".