Shaping membrane interfaces in lipid vesicles mimicking the cytoplasmic leaflet of myelin through variation of cholesterol and myelin basic protein contents
Bibliographic record
Abstract
Myelin basic protein (MBP) is an intrinsically disordered protein and in the central nervous system (CNS) mainly responsible for connecting the cytoplasmic surfaces of the multilamellar, compact myelin. Increased posttranslational modification of MBP is linked to both, the natural development (from adolescent to adult brains) of myelin, and features of multiple sclerosis. Here, we study how a combination of this intrinsically disordered myelin protein with varying the natural cholesterol content may alter the characteristics of myelin-like membranes and interactions between these membranes. Large unilamellar vesicles (LUVs) with a composition mimicking the cytoplasmic leaflet of myelin were chosen as the model system, in which different parameters contributing to the interactions between the lipid membrane and MBP were investigated. While we use cryo-transmission electron microscopy (TEM) for imaging, dynamic light scattering (DLS) and electrophoretic measurements through continuously-monitored phase-analysis light scattering (cmPALS) were used for a more global overview of particle size and charge, and electron paramagnetic resonance (EPR) spectroscopy was utilized for local behavior of lipids in the vesicles' membranes in aqueous solution. The cholesterol content was varied from 060 % in these LUVs and measurements were performed in the presence and absence of MBP. We find that the composition of the lipid layers is relevant to the interaction with MBP. Not only the size, the shape and the aggregation behavior of the vesicles depend on the cholesterol content, but also within each membrane, cholesterol's freedom of movement, its environmental polarity and its distribution were found to depend on the content using the EPR-active spin-labeled cholesterol (CSOSL). In addition, DLS and EPR measurements probing the transition temperatures of the lipid phases allow a correlation of specific behavior with the human body temperature of 37 °C. Overall, our results aid in understanding the importance of the native cholesterol content in the healthy myelin membrane, which serves as the basis for stable and optimum protein-bilayer interactions. Although studied in this specific myelin-like system, from a more general and materials science-oriented point of view, we could establish how membrane and vesicle properties depend on cholesterol and/or MBP content, which might be useful generally when specific membrane and vesicle characteristics are sought for.
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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 | 0.001 |
| 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".