RT Journal Article SR Electronic T1 Extracting nanoscale morphology from localizations JF bioRxiv FD Cold Spring Harbor Laboratory SP 2023.01.26.525798 DO 10.1101/2023.01.26.525798 A1 Zach Marin A1 Lukas A. Fuentes A1 Joerg Bewersdorf A1 David Baddeley YR 2023 UL http://biorxiv.org/content/early/2023/01/27/2023.01.26.525798.abstract AB Membrane surface reconstruction at the nanometer scale is required for understanding mechanisms of subcellular shape change. This historically has been the domain of electron microscopy, but extraction of surfaces from specific labels is a difficult task in this imaging modality. Existing methods for extracting surfaces from fluorescence microscopy have poor resolution or require high-quality super-resolution data that is manually cleaned and curated. Here we present a new method for extracting surfaces from generalized single-molecule localization microscopy (SMLM) data. This makes it possible to study the shape of specifically-labelled continuous structures inside of cells. We validate our method using simulations and demonstrate its reconstruction capabilities on SMLM data of the endoplasmic reticulum and mitochondria. Our method is implemented in the open-source Python Microscopy Environment.SIGNIFICANCE We introduce a novel tool for reconstruction of subcellular membrane surfaces from single-molecule localization microscopy data and use it to visualize and quantify local shape and membrane-membrane interactions. We benchmark its performance on simulated data and demonstrate its fidelity to experimental data.Competing Interest StatementJ. B. discloses a significant financial interest in Bruker Corp. and Hamamatsu Photonics.