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Essay on Biomembrane Structure.

ABSTRACT: Of all the macromolecular assemblies of life, the least understood is the biomembrane. This is especially true in regard to its atomic structure. Ideas on biomembranes, developed in the last 200 years, culminated in the fluid mosaic model of the membrane. In this essay, I provide a historical outline of how we arrived at our current understanding of biomembranes and the models we use to describe them. A selection of direct experimental findings on the nano-scale structure of biomembranes is taken up to discuss their physical nature, and special emphasis is put on the surprising insights that arise from atomic scale descriptions.

SUBMITTER: Gerle C

PROVIDER: S-EPMC6556169 | biostudies-literature | 2019 Jun

REPOSITORIES: biostudies-literature

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Essay on Biomembrane Structure.

Gerle Christoph C

The Journal of membrane biology 20190315 2-3

Of all the macromolecular assemblies of life, the least understood is the biomembrane. This is especially true in regard to its atomic structure. Ideas on biomembranes, developed in the last 200 years, culminated in the fluid mosaic model of the membrane. In this essay, I provide a historical outline of how we arrived at our current understanding of biomembranes and the models we use to describe them. A selection of direct experimental findings on the nano-scale structure of biomembranes is take ...[more]

PMID: 30877332

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Project description:AbstractIn biology, heterosynaptic plasticity maintains homeostasis in synaptic inputs during associative learning and memory, and initiates long-term changes in synaptic strengths that nonspecifically modulate different synapse types. In bioinspired neuromorphic circuits, heterosynaptic plasticity may be used to extend the functionality of two-terminal, biomimetic memristors. In this article, we explore how changes in the pH of droplet interface bilayer aqueous solutions modulate the memristive responses of a lipid bilayer membrane in the pH range 4.97-7.40. Surprisingly, we did not find conclusive evidence for pH-dependent shifts in the voltage thresholds (V*) needed for alamethicin ion channel formation in the membrane. However, we did observe a clear modulation in the dynamics of pore formation with pH in time-dependent, pulsed voltage experiments. Moreover, at the same voltage, lowering the pH resulted in higher steady-state currents because of increased numbers of conductive peptide ion channels in the membrane. This was due to increased partitioning of alamethicin monomers into the membrane at pH 4.97, which is below the pKa (~5.3-5.7) of carboxylate groups on the glutamate residues of the peptide, making the monomers more hydrophobic. Neutralization of the negative charges on these residues, under acidic conditions, increased the concentration of peptide monomers in the membrane, shifting the equilibrium concentrations of peptide aggregate assemblies in the membrane to favor greater numbers of larger, increasingly more conductive pores. It also increased the relaxation time constants for pore formation and decay, and enhanced short-term facilitation and depression of the switching characteristics of the device. Modulating these thresholds globally and independently of alamethicin concentration and applied voltage will enable the assembly of neuromorphic computational circuitry with enhanced functionality.Impact statementWe describe how to use pH as a modulatory "interneuron" that changes the voltage-dependent memristance of alamethicin ion channels in lipid bilayers by changing the structure and dynamical properties of the bilayer. Having the ability to independently control the threshold levels for pore conduction from voltage or ion channel concentration enables additional levels of programmability in a neuromorphic system. In this article, we note that barriers to conduction from membrane-bound ion channels can be lowered by reducing solution pH, resulting in higher currents, and enhanced short-term learning behavior in the form of paired-pulse facilitation. Tuning threshold values with environmental variables, such as pH, provide additional training and learning algorithms that can be used to elicit complex functionality within spiking neural networks.Graphical abstractSupplementary informationThe online version contains supplementary material available at 10.1557/s43577-022-00344-z.

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Essay on Biomembrane Structure.

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Essay on Biomembrane Structure.

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