Origami: Single-cell 3D shape dynamics oriented along the apico-basal axis of folding epithelia from fluorescence microscopy data

Mendonca, Tania; Jones, Ana A.; Pozo, Jose M.; Baxendale, Sarah; Whitfield, Tanya T.; Frangi, Alejandro F.

Abstract

A common feature of morphogenesis is the formation of three-dimensional structures from the folding of two-dimensional epithelial sheets, aided by cell shape changes at the cellularlevel. Changes in cell shape must be studied in the context of cell-polarised biomechanical processes within the epithelial sheet. In epithelia with highly curved surfaces, finding singlecell alignment along a biological axis can be difficult to automate in silico. We present 'Origami', a MATLAB-based image analysis pipeline to compute direction-variant cell shape features along the epithelial apico-basal axis. Our automated method accurately computed direction vectors denoting the apico-basal axis in regions with opposing curvature in synthetic epithelia and fluorescence images of zebrafish embryos. As proof of concept, we identified different cell shape signatures in the developing zebrafish inner ear, where the epithelium deforms in opposite orientations to form different structures. Origami is designed to be user-friendly and is generally applicable to fluorescence images of curved epithelia.

Citation

Mendonca, T., Jones, A. A., Pozo, J. M., Baxendale, S., Whitfield, T. T., & Frangi, A. F. (2021). Origami: Single-cell 3D shape dynamics oriented along the apico-basal axis of folding epithelia from fluorescence microscopy data. PLoS Computational Biology, 17(11), Article e1009063. https://doi.org/10.1371/journal.pcbi.1009063

• Journal Article Type: Article
• Acceptance Date: Oct 13, 2021
• Online Publication Date: Nov 1, 2021
• Publication Date: Nov 1, 2021
• Deposit Date: May 3, 2023
• Publicly Available Date: May 25, 2023
• Journal: PLoS Computational Biology
• Print ISSN: 1553-734X
• Electronic ISSN: 1553-7358
• Publisher: Public Library of Science (PLoS)
• Peer Reviewed: Peer Reviewed
• Volume: 17
• Issue: 11
• Article Number: e1009063
• DOI: https://doi.org/10.1371/journal.pcbi.1009063
• Keywords: Computational Theory and Mathematics; Cellular and Molecular Neuroscience; Genetics; Molecular Biology; Ecology; Modeling and Simulation; Ecology, Evolution, Behavior and Systematics
• Public URL: https://nottingham-repository.worktribe.com/output/13465757