4.7 Article

Time-lapse X-ray phase-contrast microtomography for in vivo imaging and analysis of morphogenesis

Journal

NATURE PROTOCOLS
Volume 9, Issue 2, Pages 294-304

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/nprot.2014.033

Keywords

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Funding

  1. US DOE [DE-AC02-06CH11357]
  2. 'Concept for the Future' program of Karlsruhe Institute of Technology
  3. German Federal Ministry of Education and Research [05K12CK2, 05K12VH1]
  4. COST action [MP1207]

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X-ray phase-contrast microtomography (XPC mu T) is a label-free, high-resolution imaging modality for analyzing early development of vertebrate embryos in vivo by using time-lapse sequences of 3D volumes. Here we provide a detailed protocol for applying this technique to study gastrulation in Xenopus laevis (African clawed frog) embryos. In contrast to mu MRI, XPC mu T images optically opaque embryos with subminute temporal and micrometer-range spatial resolution. We describe sample preparation, culture and suspension of embryos, tomographic imaging with a typical duration of 2 h (gastrulation and neurulation stages), intricacies of image pre-processing, phase retrieval, tomographic reconstruction, segmentation and motion analysis. Moreover, we briefly discuss our present understanding of X-ray dose effects (heat load and radiolysis), and we outline how to optimize the experimental configuration with respect to X-ray energy, photon flux density, sample-detector distance, exposure time per tomographic projection, numbers of projections and time-lapse intervals. The protocol requires an interdisciplinary effort of developmental biologists for sample preparation and data interpretation, X-ray physicists for planning and performing the experiment and applied mathematicians/computer scientists/physicists for data processing and analysis. Sample preparation requires 9-48 h, depending on the stage of development to be studied. Data acquisition takes 2-3 h per tomographic time-lapse sequence. Data processing and analysis requires a further 2 weeks, depending on the availability of computing power and the amount of detail required to address a given scientific problem.

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