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METHODS article

Front. Plant Sci.
Sec. Plant Development and EvoDevo
Volume 15 - 2024 | doi: 10.3389/fpls.2024.1449195
This article is part of the Research Topic Advanced Imaging in Plants: Exploring Development and Function View all articles

An optimized live imaging and multiple cell layer growth analysis approach using Arabidopsis Sepals

Provisionally accepted
  • 1 Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, United States
  • 2 Plant Biology Section, School of Integrative Plant Science, College of Agriculture and Life Sciences, Cornell University, Ithaca, New York, United States

The final, formatted version of the article will be published soon.

    Arabidopsis thaliana sepals are excellent models for analyzing growth of entire organs due to their relatively small size, which can be captured at a cellular resolution under a confocal microscope. To investigate how differential growth of connected cell layers generate unique organ morphologies, it is necessary to live-image deep into the tissue. However, imaging deep cell layers of the sepal (or plant tissues in general) is practically challenging. Image processing is also difficult due to the low signal-to-noise ratio of the deeper tissue layers, an issue mainly associated with live imaging datasets. Addressing some of these challenges, we provide an optimized methodology for live imaging sepals, and subsequent image processing. For live imaging early-stage sepals, we found that the use of a bright fluorescent membrane marker, coupled with increased laser intensity and an enhanced Z-resolution produces high-quality images suitable for downstream image processing. Our optimized parameters allowed us to image the bottommost cell layer of the sepal (inner epidermal layer) without compromising viability. We used a 'voxel removal' technique to visualize the inner epidermal layer in MorphoGraphX image processing software. We also describe the MorphoGraphX parameters for creating a 2.5D mesh surface for the inner epidermis. Our parameters allow for the segmentation and parent tracking of individual cells through multiple time points, despite the weak signal of the inner epidermal cells. While we have used sepals to illustrate our approach, the methodology will be useful for researchers intending to live-image and track growth of deeper cell layers in 2.5D for any plant tissue.

    Keywords: Growth, 2.5D segmentation, live imaging, image processing, deep tissue imaging, Arabidopsis, MorphoGraphX, Sepals

    Received: 14 Jun 2024; Accepted: 29 Jul 2024.

    Copyright: © 2024 Singh Yadav and Roeder. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Adrienne H. Roeder, Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.