LocalZProjector and DeProj: a toolbox for local 2D projection and accurate morphometrics of large 3D microscopy images.

BACKGROUND: Quantitative imaging of epithelial tissues requires bioimage analysis tools that are widely applicable and accurate. In the case of imaging 3D tissues, a common preprocessing step consists of projecting the acquired 3D volume on a 2D plane mapping the tissue surface. While segmenting the tissue cells is amenable on 2D projections, it is still very difficult and cumbersome in 3D. However, for many specimen and models used in developmental and cell biology, the complex content of the image volume surrounding the epithelium in a tissue often reduces the visibility of the biological object in the projection, compromising its subsequent analysis. In addition, the projection may distort the geometry of the tissue and can lead to strong artifacts in the morphology measurement. RESULTS: Here we introduce a user-friendly toolbox built to robustly project epithelia on their 2D surface from 3D volumes and to produce accurate morphology measurement corrected for the projection distortion, even for very curved tissues. Our toolbox is built upon two components. LocalZProjector is a configurable Fiji plugin that generates 2D projections and height-maps from potentially large 3D stacks (larger than 40 GB per time-point) by only incorporating signal of the planes with local highest variance/mean intensity, despite a possibly complex image content. DeProj is a MATLAB tool that generates correct morphology measurements by combining the height-map output (such as the one offered by LocalZProjector) and the results of a cell segmentation on the 2D projection, hence effectively deprojecting the 2D segmentation in 3D. In this paper, we demonstrate their effectiveness over a wide range of different biological samples. We then compare its performance and accuracy against similar existing tools. CONCLUSIONS: We find that LocalZProjector performs well even in situations where the volume to project also contains unwanted signal in other layers. We show that it can process large images without a pre-processing step. We study the impact of geometrical distortions on morphological measurements induced by the projection. We measured very large distortions which are then corrected by DeProj, providing accurate outputs.

Roadmap for the multiscale coupling of biochemical and mechanical signals during development.

The way in which interactions between mechanics and biochemistry lead to the emergence of complex cell and tissue organization is an old question that has recently attracted renewed interest from biologists, physicists, mathematicians and computer scientists. Rapid advances in optical physics, microscopy and computational image analysis have greatly enhanced our ability to observe and quantify spatiotemporal patterns of signalling, force generation, deformation, and flow in living cells and tissues. Powerful new tools for genetic, biophysical and optogenetic manipulation are allowing us to perturb the underlying machinery that generates these patterns in increasingly sophisticated ways. Rapid advances in theory and computing have made it possible to construct predictive models that describe how cell and tissue organization and dynamics emerge from the local coupling of biochemistry and mechanics. Together, these advances have opened up a wealth of new opportunities to explore how mechanochemical patterning shapes organismal development. In this roadmap, we present a series of forward-looking case studies on mechanochemical patterning in development, written by scientists working at the interface between the physical and biological sciences, and covering a wide range of spatial and temporal scales, organisms, and modes of development. Together, these contributions highlight the many ways in which the dynamic coupling of mechanics and biochemistry shapes biological dynamics: from mechanoenzymes that sense force to tune their activity and motor output, to collectives of cells in tissues that flow and redistribute biochemical signals during development.

Timed Collinear Activation of Hox Genes during Gastrulation Controls the Avian Forelimb Position.

Limb position along the body is highly consistent within one species but very variable among vertebrates. Despite major advances in our understanding of limb patterning in three dimensions, how limbs reproducibly form along the antero-posterior axis remains largely unknown. Hox genes have long been suspected to control limb position; however, supporting evidences are mostly correlative and their role in this process is unclear. Here, we show that limb position is determined early in development through the action of Hox genes. Dynamic lineage analysis revealed that, during gastrulation, the forelimb, interlimb, and hindlimb fields are progressively generated and concomitantly patterned by the collinear activation of Hox genes in a two-step process. First, the sequential activation of Hoxb genes controls the relative position of their own collinear domains of expression in the forming lateral plate mesoderm, as demonstrated by functional perturbations during gastrulation. Then, within these collinear domains, we show that Hoxb4 anteriorly and Hox9 genes posteriorly, respectively, activate and repress the expression of the forelimb initiation gene Tbx5 and instruct the definitive position of the forelimb. Furthermore, by comparing the dynamics of Hoxb genes activation during zebra finch, chicken, and ostrich gastrulation, we provide evidences that changes in the timing of collinear Hox gene activation might underlie natural variation in forelimb position between different birds. Altogether, our results that characterize the cellular and molecular mechanisms underlying the regulation and natural variation of forelimb positioning in avians show a direct and early role for Hox genes in this process.