Detecting Membrane Protein‐protein Interactions Using the Mammalian Membrane Two‐hybrid (MaMTH) Assay
Bibliographic record
Abstract
Protein-protein interactions (PPIs) play an integral role in numerous cellular processes. Membrane protein interactions, in particular, are critical in cellular responses to stresses and stimuli, with dysfunction of these PPIs (e.g., due to aberrant expression and/or mutation of interaction partners) leading to a diverse array of pathological states. Exploration of the interaction space and dynamics of membrane proteins is difficult due to the limitations of current techniques used to study proteins in the biochemically complex environment of biological membranes. In the protocols below, we describe a newly developed membrane protein interaction assay called the Mammalian-Membrane Two-Hybrid (MaMTH), designed specifically for the detection of integral membrane PPIs in the context of living mammalian cells. Prior to using MaMTH, cell lines of interest are genetically modified to encode a reporter of choice. MaMTH "bait" and "prey" constructs of interest are also generated using Gateway cloning technology. The assay is then performed by co-transfection of baits and preys, with bait-prey interaction quantifiably assessed by way of a reporter signal (e.g., light (luciferase), fluorescence (GFP). © 2017 by John Wiley & Sons, Inc.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".