Real-Time Monitoring of Membrane-Protein Reconstitution by Isothermal Titration Calorimetry
Bibliographic record
Abstract
Phase diagrams offer a wealth of thermodynamic information on aqueous mixtures of bilayer-forming lipids and micelle-forming detergents, providing a straightforward means of monitoring and adjusting the supramolecular state of such systems. However, equilibrium phase diagrams are of very limited use for the reconstitution of membrane proteins because of the occurrence of irreversible, unproductive processes such as aggregation and precipitation that compete with productive reconstitution. Here, we exemplify this by dissecting the effects of the K(+) channel KcsA on the process of bilayer self-assembly in a mixture of Escherichia coli polar lipid extract and the nonionic detergent octyl-β-d-glucopyranoside. Even at starting concentrations in the low micromolar range, KcsA has a tremendous impact on the supramolecular organization of the system, shifting the critical lipid/detergent ratios at the onset and completion of vesicle formation by more than 2-fold. Thus, equilibrium phase diagrams obtained for protein-free lipid/detergent mixtures would be misleading when used to guide the reconstitution process. To address this issue, we demonstrate that, even under such nonequilibrium conditions, high-sensitivity isothermal titration calorimetry can be exploited to monitor the progress of membrane-protein reconstitution in real time, in a noninvasive manner, and at high resolution to yield functional proteoliposomes with a narrow size distribution for further downstream applications.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".