Imaging Morphogenesis: Technological Advances and Biological Insights

Background Our understanding of developmental processes relies fundamentally on their in vivo observation. Morphogenesis, the shaping of an organism by cell movements, cell-cell interactions, collective cell behavior, cell shape changes, cell divisions, and cell death, is a dynamic process on many scales, from fast subcellular rearrangements to slow structural changes at the whole-organism level. The ability to capture, simultaneously, the fast dynamic behavior of individual cells, as well as their system-level interactions over long periods of time, is crucial for an understanding of the underlying biological mechanisms. Arriving at a complete picture of morphogenesis requires not only observation of single-cell to tissue-level morphological dynamics, but also quantitative measurement of protein dynamics, changes in gene expression, and readouts of physical forces acting during development. Live-imaging approaches based on light microscopy are of key importance to obtaining such information at the system level and with high spatiotemporal resolution. Live imaging of embryonic development. Nuclei-labeled Drosophila (top) and zebrafish (bottom) embryos were imaged with a simultaneous multiview light-sheet microscope (SiMView). The embryos are shown at 3 and 22 hours postfertilization, respectively. Color indicates depth in the image. Scale bars: 50 µm. Advances Live imaging with light microscopy requires carefully balancing competing parameters, among which spatiotemporal resolution and light exposure of the living specimen are chief. To maximize the quantity and quality of information extracted from the specimen under observation, optimal use must be made of the limited number of photons that can be collected under physiological conditions. Emerging techniques for noninvasive in vivo imaging can record morphogenetic processes at temporal scales from seconds to days and at spatial scales from hundreds of nanometers to several millimeters, with minimal energy load on the specimen. These approaches are able to capture cellular dynamics in entire vertebrate and higher invertebrate embryos throughout their development. It has become possible to follow cell movements, cell shape dynamics, subcellular protein localization, and changes in gene expression simultaneously, for the entire undisturbed living system. The application of these methods to the study of morphogenesis in the fly, fish, and mouse has led to fundamental insights into the mechanisms underlying epithelial folding, the control of tissue morphogenesis by signaling pathways, and the role of physical forces in local and tissue-wide morphogenetic changes. Outlook Current efforts in microscopy technology development are aimed at advancing deep-tissue in vivo imaging, improving spatial resolution, and increasing temporal sampling. To unlock their full potential, these methods need to be matched with new computational approaches and physical models that help convert the resulting, highly complex image data sets into biological insights. With the availability of system-level data on cell behavior and gene expression, and the potential for a system-level analysis of biophysical tissue properties, we are reaching the point at which it will be feasible to develop computational approaches that incorporate these data into a single model capable of dissecting morphogenesis at the whole-organism level. Morphogenesis, the development of the shape of an organism, is a dynamic process on a multitude of scales, from fast subcellular rearrangements and cell movements to slow structural changes at the whole-organism level. Live-imaging approaches based on light microscopy reveal the intricate dynamics of this process and are thus indispensable for investigating the underlying mechanisms. This Review discusses emerging imaging techniques that can record morphogenesis at temporal scales from seconds to days and at spatial scales from hundreds of nanometers to several millimeters. To unlock their full potential, these methods need to be matched with new computational approaches and physical models that help convert highly complex image data sets into biological insights.