From cells to form: A roadmap to study shape emergence in vivo

Abstract

Organogenesis arises from the collective arrangement of cells into progressively 3D-shaped tissue. The acquisition of a correctly shaped organ is then the result of a complex interplay between molecular cues, responsible for differentiation and patterning, and the mechanical properties of the system, which generate the necessary forces that drive correct shape emergence. Nowadays, technological advances in the fields of microscopy, molecular biology, and computer science are making it possible to see and record such complex interactions in incredible, unforeseen detail within the global context of the developing embryo. A quantitative and interdisciplinary perspective of developmental biology becomes then necessary for a comprehensive understanding of morphogenesis. Here, we provide a roadmap to quantify the events that lead to morphogenesis from imaging to image analysis, quantification, and modeling, focusing on the discrete cellular and tissue shape changes, as well as their mechanical properties.

Figure 1

Examples of image analysis sequences to quantify parameters related with retina morphogenesis in zebrafish. (A) Imaged nuclei were automatically segmented with StarDist (25). From this segmentation, nuclei volume information was extracted and represented as a color code. Scale bar 50μm (B) Outline of the retina detected by the Kappa (26) plugin to fit a Bezier curve and calculate curvature over time. (C) Schematic of a zebrafish embryo at 24 h postfertilization. Dashed lines feature the retina.

Figure 2

(A) To understand how somites can reach a symmetrical shape during zebrafish somitogenesis, Naganathan et al. use advanced techniques of image analysis to project 3D imaged data in 2D. Such projection allowed for semi-automated measurements of somite shape parameters in control and disrupted conditions. At the end, with the help of a model of surface length versus tension, the authors propose that somite length adjustment relies on somite surface tension ((76) reproduced with permission from SNCSC). (B) Schematics of a zebrafish embryo at 13 h postfertilization, with emphasis on tailbud growth, merging the knowledge gathered by the three works. (C) On a bottom-up approach Sanematsu et al. built a 3D Voronoi model of the Kupffer’s vesicle, the zebrafish left-right organizer. This model is used to test how drag forces generated by the vesicle’s movement can drive cell shape changes. The predictions are then tested through analysis of cell movement ((77) reproduced with permission from Elsevier). (D) The introduction and manipulation of magnetic beads in the zebrafish tailbud allowed measurement of the tissue yield stress. Together with cell tracking, Mongera et al. conclude that a jamming transition from fluid to solid-like behavior occurs from the progenitor zone to the presomitc mesoderm. Such a transition sustains a unidirectional extension of the tailbud, as confirmed by the theoretical model ((78) reproduced with permission from SNCSC).

Figure 3

(A) Using advanced frameworks of image cartography and single-cell segmentation, Mitchell et al. were able to determine that the folds appearing in the Drosophila gut are a result of a convergent extension pattern driven by cell shape changes. Such shape changes are promoted by out-of-plane contraction of the surrounding muscle. This is confirmed by induction of muscle contractility using optogenetic tools. The authors went further and were able to link muscle contraction with calcium spikes generated in areas where specific hox genes are present, thus directly linking gene expression with cell shape (and tissue shape) changes (adapted from (97)). (B) Schematic of a Drosophila embryo depicting the midgut in blue. (C) Schematic of a Drosophila follicle showing the extracellular matrix (in green) surrounding the cells. (D) Also using cartography projections of 3D data into 2D, Chen et al. show that follicle elongation is dependent on the reorientation of elongated cells, regulated by mechanical cues from the extracellular matrix (adapted from (23)).