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Related Concept Videos

Mechanisms of Membrane-bending01:15

Mechanisms of Membrane-bending

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The living membranes are flexible due to their fluid mosaic nature; however, their bending into different shapes is an active process regulated by specific lipids and proteins. The membrane bending can be transient as seen in vesicles or stable for a long time as in microvilli. Cells regulate the size, location, and duration of the membrane curvature.
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Biological membranes show uneven distribution of different types of lipids in the inner and outer layers, resulting in transverse asymmetric membranes. The treatment of the erythrocyte membrane with the enzyme phospholipase confirmed the asymmetric nature of the lipid bilayer. The enzyme hydrolyzes lipids into fatty acids and hydrophilic groups. The phospholipase acts only on the outer layer of the membrane, while the inner layer remains intact. The phospholipase treatment resulted in 80%...
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Membrane Fluidity01:26

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Membrane fluidity is explained by the fluid mosaic model of the cell membrane, which describes the plasma membrane structure as a mosaic of components—including phospholipids, cholesterol, proteins, and carbohydrates—that gives the membrane a fluid character.
Mosaic nature of the membrane
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Scientists identified the plasma membrane in the 1890s and its principal chemical components (lipids and proteins) by 1915. The model for plasma membrane structure, proposed in 1935 by Hugh Davson and James Danielli, was the first model to be widely accepted in the scientific community. The model was based on the plasma membrane's "railroad track" appearance in early electron micrographs. Davson and Danielli theorized that the plasma membrane's structure resembled a sandwich...
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Biological membranes are more than just a barrier separating cell cytoplasm from the outside environment. They are highly dynamic and help maintain the integrity and physiological stability of the cells as well as membrane-bound organelles. Membranes also play vital roles in cell-to-cell and intracellular communication.
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The membrane domains concentrate specific lipids and proteins at one place within the membrane, which helps in cell signaling, adhesion, and other critical cellular processes. These domains can differ in size, composition, function, and lifespan.
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Updated: Jun 20, 2025

A Nanobar-Supported Lipid Bilayer System for the Study of Membrane Curvature Sensing Proteins in vitro
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Predicting lipid sorting in curved membranes.

Jackson Crowley1, Cécile Hilpert1, Luca Monticelli2

  • 1Molecular Microbiology and Structural Biochemistry, UMR 5086 CNRS & University of Lyon, Lyon, France.

Methods in Enzymology
|July 18, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a computational tool to predict how lipid types distribute in curved biological membranes. The method uses molecular dynamics simulations to reveal lipid preferences for positive or negative curvature, aiding in understanding membrane organization.

Keywords:
Biological membraneComputer simulationLipid bilayerLipid flip- flopLipid membraneLipid sortingMembrane curvatureMolecular dynamics

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Area of Science:

  • Biophysics
  • Computational Biology
  • Membrane Biophysics

Background:

  • Biological membranes exhibit complex curved shapes crucial for cellular functions.
  • Understanding lipid and protein roles in membrane curvature generation is essential.
  • Predicting lipid distribution (lateral and inter-leaflet) in curved membranes remains challenging.

Purpose of the Study:

  • To develop a simple computational tool for predicting lipid preference in membranes of varying curvature.
  • To analyze lipid distribution in response to positive and negative membrane curvature.
  • To provide scripts for building and analyzing molecular dynamics simulations of lipid behavior.

Main Methods:

  • Utilized molecular dynamics simulations of tubular membranes containing hydrophilic pores.
  • Employed spontaneous, barrierless lipid flip-flop facilitated by pores.
  • Minimized pressure differences and asymmetric membrane stresses using pore design.

Main Results:

  • Demonstrated that lipids with negative intrinsic curvature preferentially localize to the inner leaflet of tubules.
  • Observed increased preference for inner leaflet localization with smaller tubule radii.
  • Validated the computational tool's predictive capability using binary lipid mixtures.

Conclusions:

  • The developed computational tool effectively predicts lipid preference for specific membrane curvatures.
  • The method, based on spontaneous lipid inter-leaflet transport, enables exploration of lipid distribution in asymmetric membranes.
  • This approach offers an adaptable and efficient alternative to existing computational methods for studying membrane lipid organization.