3D membrane segmentation and quantification of intact thick cells using cryo soft X-ray transmission microscopy: A pilot study

Research output: Contribution to journalArticle

Abstract

Structural analysis of biological membranes is important for understanding cell and subcellular organelle function as well as their interaction with the surrounding environment. Imaging of whole cells in three dimension at high spatial resolution remains a significant challenge, particularly for thick cells. Cryo-transmission soft X-ray microscopy (cryo-TXM) has recently gained popularity to image, in 3D, intact thick cells (∼10μm) with details of subcellular architecture and organization in near-native state. This paper reports a new tool to segment and quantify structural changes of biological membranes in 3D from cryo-TXM images by tracking an initial 2D contour along the third axis of the microscope, through a multi-scale ridge detection followed by an active contours-based model, with a subsequent refinement along the other two axes. A quantitative metric that assesses the grayscale profiles perpendicular to the membrane surfaces is introduced and shown to be linearly related to the membrane thickness. Our methodology has been validated on synthetic phantoms using realistic microscope properties and structure dimensions, as well as on real cryo-TXM data. Results demonstrate the validity of our algorithms for cryo-TXM data analysis.

Details

Authors
  • Rubén Cárdenes
  • Chong Zhang
  • Oxana Klementieva
  • Stephan Werner
  • Peter Guttmann
  • Christoph Pratsch
  • Josep Cladera
  • Bart H. Bijnens
Organisations
External organisations
  • Pompeu Fabra University
  • Bellvitge University Hospital-IDIBELL
  • Helmholtz-Zentrum Berlin for Materials and Energy
  • Autonomous University of Barcelona
  • Catalan Institution for Research and Advanced Studies
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Basic Medicine
Original languageEnglish
Article numbere0174324
JournalPLoS ONE
Volume12
Issue number4
Publication statusPublished - 2017 Apr 1
Publication categoryResearch
Peer-reviewedYes