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Probing macromolecular crowding at the lipid membrane interface with genetically-encoded sensors.

Maryna LöweSebastian HänschEymen HachaniLutz SchmittStefanie Weidtkamp-PetersAlexej Kedrov
Published in: Protein science : a publication of the Protein Society (2023)
Biochemical processes within the living cell occur in a highly crowded environment, where macromolecules, first of all proteins and nucleic acids, occupy up to 30 % of the volume. The phenomenon of macromolecular crowding is not an exclusive feature of the cytoplasm and can be observed in the densely protein-packed, nonhomogeneous cellular membranes and at the membrane interfaces. Crowding affects diffusional and conformational dynamics of proteins within the lipid bilayer, alters kinetic and thermodynamic properties of biochemical reactions, and modulates the membrane organization. Despite its importance, the non-invasive quantification of the membrane crowding is not trivial. Here, we developed the genetically-encoded fluorescence-based sensor for probing the macromolecular crowding at the membrane interfaces. Two sensor variants, both composed of fluorescent proteins and a membrane anchor, but differing by the flexible linker domains were characterized in vitro, and the procedures for the membrane reconstitution were established. Steric pressure induced by membrane-tethered synthetic and protein crowders altered the sensors' conformation, causing increase in the intramolecular Förster's resonance energy transfer. Notably, the effect of protein crowders only weakly correlated with their molecular weight, suggesting that other factors, such as shape and charge contribute to the crowding via the quinary interactions. Finally, measurements performed in inner membrane vesicles of E. coli validated the crowding-dependent dynamics of the sensors in the physiologically relevant environment. The sensors offer broad opportunities to study interfacial crowding in a complex environment of native membranes, and thus add to the toolbox of methods for studying membrane dynamics and proteostasis. This article is protected by copyright. All rights reserved.
Keyphrases
  • energy transfer
  • molecular dynamics simulations
  • single molecule
  • single cell
  • gene expression
  • machine learning
  • protein protein
  • deep learning
  • ionic liquid
  • copy number