The dataset contains all optical and electron microscopy files in .czi, .lsm, .lif and .tif formats; raw .stk files of SMdM and PALM acquisitions; .csv output files from the TECAN plate reader used in the in the publication with the title: “Structural and functional implications of phase separation of membrane protein LacY in Escherichia coli “. Files are organized based on the figure they were used in. Molecular dynamic simulations input files, trajectories and code for the analysis are available on Zenodo: 10.5281/zenodo.17335657.

Liquid-liquid phase-separation (LLPS) controls protein activity and dynamically organizes (macro)molecules in living systems without the need for membrane-bound compartments. Biomolecular condensates of water-soluble proteins have extensively been studied, but little is known about LLPS of membrane proteins. In this work we induce in vivo condensation of lactose permease (LacY), a widely-studied model monomeric inner membrane protein in Escherichia coli, and evaluate how it affects LacY function. We fused LacY with engineered, condensate-forming protein PopTag. We observe major changes in the localization and mobility of LacY-Pop. Molecular dynamics simulations show how the PopTag domain drives the condensate-like association dynamics of LacY-Pop through hydrophobic sticker interactions. LacY-Pop preserves native-level transport activity and outperforms the non-condensed LacY under mild hyperosmotic stress (osmotic upshift). In osmotically stressed cells, membrane-bound biomolecular condensates also reduce deformation of the cytoplasmic membrane. Perturbation experiments suggest that membrane curvature drives the accumulation of LacY-Pop at the poles of E. coli. Co-condensation of LacY and β-galactosidase LacZ slightly reduces their activity and results in remarkable cellular reorganization of the proteins. Our research shows the localization, dynamics, and function of phase-separated membrane proteins in bacteria and highlights the potential of LLPS for engineering complex metabolic networks in vivo.

Please note: This is a large dataset (160 GB). Downloading the data has to be done in sections of approx. 9 GB each.