Cellular harmonics for the morphology-invariant analysis of molecular organization at the cell surface

Hanieh Mazloom-Farsibaf, Qiongjing Zou, Rebecca Hsieh, Gaudenz Danuser, Meghan K. Driscoll

Research output: Contribution to journalArticlepeer-review

Abstract

The spatiotemporal organization of membrane-associated molecules is central to the regulation of cellular signals. Powerful new microscopy techniques enable the three-dimensional visualization of localization and activation of these molecules; however, the quantitative interpretation and comparison of molecular organization on the three-dimensional cell surface remains challenging because cells themselves vary greatly in morphology. Here we introduce u-signal3D, a framework to assess the spatial scales of molecular organization at the cell surface in a cell-morphology-invariant manner. We validated the framework by analyzing synthetic signaling patterns painted onto observed cell morphologies, as well as measured distributions of cytoskeletal and signaling molecules. To demonstrate the framework’s versatility, we further compared the spatial organization of cell surface signals both within, and between, cell populations, and powered an upstream machine-learning-based analysis of signaling motifs.

Original languageEnglish (US)
Pages (from-to)777-788
Number of pages12
JournalNature Computational Science
Volume3
Issue number9
DOIs
StatePublished - Sep 2023

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Computer Science Applications
  • Computer Networks and Communications

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