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Cell-free gene expression (CFE) systems are powerful tools for transcribing and translating genes outside of a living cell. Synthesis of membrane proteins is of particular interest, but their yield in CFE is substantially lower than that for soluble proteins. In this paper, we study the CFE of membrane proteins and develop a quantitative kinetic model. We identify that ribosome stalling during the translation of membrane proteins is a strong predictor of membrane protein synthesis due to aggregation between the ribosome nascent chains. Synthesis can be improved by the addition of lipid membranes, which incorporate protein nascent chains and, therefore, kinetically compete with aggregation. We show that the balance between peptide-membrane association and peptide aggregation rates determines the yield of the synthesized membrane protein. We define a membrane protein expression score that can be used to rationalize the engineering of lipid composition and the N-terminal domain of a native and computationally designed membrane proteins produced through CFE.
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Physical limits to membrane curvature sensing by a single protein
Membrane curvature sensing is essential for a diverse range of biological processes. Recent experiments have revealed that a single nanometer-sized septin protein has different binding rates to membrane-coated glass beads of 1-µm and 3-µm diameters, even though the septin is orders of magnitude smaller than the beads. This sensing ability is especially surprising since curvature-sensing proteins must deal with persistent thermal fluctuations of the membrane, leading to discrepancies between the bead's curvature and the local membrane curvature sensed instantaneously by a protein. Using continuum models of fluctuating membranes, we investigate whether it is feasible for a protein acting as a perfect observer of the membrane to sense micron-scale curvature either by measuring local membrane curvature or by using bilayer lipid densities as a proxy. To do this, we develop algorithms to simulate lipid density and membrane shape fluctuations. We derive physical limits to the sensing efficacy of a protein in terms of protein size, membrane thickness, membrane bending modulus, membrane-substrate adhesion strength, and bead size. To explain the experimental protein-bead association rates, we develop two classes of predictive models: (i) for proteins that maximally associate to a preferred curvature and (ii) for proteins with enhanced association rates above a threshold curvature. We find that the experimentally observed sensing efficacy is close to the theoretical sensing limits imposed on a septin-sized protein. Protein-membrane association rates may depend on the curvature of the bead, but the strength of this dependence is limited by the fluctuations in membrane height and density.
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- Award ID(s):
- 1945141
- PAR ID:
- 10507155
- Publisher / Repository:
- Physical Review E
- Date Published:
- Journal Name:
- Physical Review E
- Volume:
- 108
- Issue:
- 6
- ISSN:
- 2470-0045
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1103/PhysRevE.108.064407
