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Paired organs in animals are largely bilaterally symmetric despite inherent noise in most biological processes. How is precise organ shape and size achieved during development despite this noise? Examining paired organ development is a challenge because it requires repeated quantification of two structures in parallel within living embryos. Here we combine bilateral quantification of morphology through time with asymmetric perturbations to study regulation of organ shape, size, and symmetry in developing organ pairs.We present quantitative live imaging tools to measure the shape and size of the developing inner ears on both the left and right side simultaneously over time. By quantifying variation between the left and right inner ear (intrinsic noise) and between different individuals (extrinsic noise), we find that initial variability decreases over time in normal development to achieve symmetry. Early asymmetry is increased by environmental stress, but symmetry is still recovered over subsequent developmental time. Using multiple unilateral perturbations including Fgf signaling and ultraviolet light, we find that growth can be adjusted to compensate for a range of initial size and shape differences.We propose that symmetry in developmental systems does not emerge through precise deterministic bilateral development, but rather through feedback mechanisms that adjust morphogenesis rates to account for variation. Developmental Dynamics 246:451-465, 2016. © 2017 Wiley Periodicals, Inc.

Epithelial cells acquire functionally important shapes (e.g., squamous, cuboidal, columnar) during development. Here, we combine theory, quantitative imaging, and perturbations to analyze how tissue geometry, cell divisions, and mechanics interact to shape the presumptive enveloping layer (pre-EVL) on the zebrafish embryonic surface. We find that, under geometrical constraints, pre-EVL flattening is regulated by surface cell number changes following differentially oriented cell divisions. The division pattern is, in turn, determined by the cell shape distribution, which forms under geometrical constraints by cell-cell mechanical coupling. An integrated mathematical model of this shape-division feedback loop recapitulates empirical observations. Surprisingly, the model predicts that cell shape is robust to changes of tissue surface area, cell volume, and cell number, which we confirm in vivo. Further simulations and perturbations suggest the parameter linking cell shape and division orientation contributes to epithelial diversity. Together, our work identifies an evolvable design logic that enables robust cell-level regulation of tissue-level development.

The quantification of cell shape, cell migration, and cell rearrangements is important for addressing classical questions in developmental biology such as patterning and tissue morphogenesis. Time-lapse microscopic imaging of transgenic embryos expressing fluorescent reporters is the method of choice for tracking morphogenetic changes and establishing cell lineages and fate maps in vivo. However, the manual steps involved in curating thousands of putative cell segmentations have been a major bottleneck in the application of these technologies especially for cell membranes. Segmentation of cell membranes while more difficult than nuclear segmentation is necessary for quantifying the relations between changes in cell morphology and morphogenesis. We present a novel and fully automated method to first reconstruct membrane signals and then segment out cells from 3D membrane images even in dense tissues. The approach has three stages: 1) detection of local membrane planes, 2) voting to fill structural gaps, and 3) region segmentation. We demonstrate the superior performance of the algorithms quantitatively on time-lapse confocal and two-photon images of zebrafish neuroectoderm and paraxial mesoderm by comparing its results with those derived from human inspection. We also compared with synthetic microscopic images generated by simulating the process of imaging with fluorescent reporters under varying conditions of noise. Both the over-segmentation and under-segmentation percentages of our method are around 5%. The volume overlap of individual cells, compared to expert manual segmentation, is consistently over 84%. By using our software (ACME) to study somite formation, we were able to segment touching cells with high accuracy and reliably quantify changes in morphogenetic parameters such as cell shape and size, and the arrangement of epithelial and mesenchymal cells. Our software has been developed and tested on Windows, Mac, and Linux platforms and is available publicly under an open source BSD license (https://github.com/krm15/ACME).