Light sheet microscopy is a versatile imaging technique with a unique combination of capabilities. It provides high imaging speed, high signal-to-noise ratio and low levels of photobleaching and phototoxic effects. These properties are crucial in a wide range of applications in the life sciences, from live imaging of fast dynamic processes in single cells to long-term observation of developmental dynamics in entire large organisms. When combined with tissue clearing methods, light sheet microscopy furthermore allows rapid imaging of large specimens with excellent coverage and high spatial resolution. Even samples up to the size of entire mammalian brains can be efficiently recorded and quantitatively analyzed. Here, we provide an overview of the history of light sheet microscopy, review the development of tissue clearing methods, and discuss recent technical breakthroughs that have the potential to influence the future direction of the field.

The fruit fly is an excellent model system for investigating the sequence of epithelial tissue invaginations constituting the process of gastrulation. By combining recent advancements in light sheet fluorescence microscopy (LSFM) and image processing, the three-dimensional fly embryo morphology and relevant gene expression patterns can be accurately recorded throughout the entire process of embryogenesis. LSFM provides exceptionally high imaging speed, high signal-to-noise ratio, low level of photoinduced damage, and good optical penetration depth. This powerful combination of capabilities makes LSFM particularly suitable for live imaging of the fly embryo.The resulting high-information-content image data are subsequently processed to obtain the outlines of cells and cell nuclei, as well as the geometry of the whole embryo tissue by image segmentation. Furthermore, morphodynamics information is extracted by computationally tracking objects in the image. Towards that goal we describe the successful implementation of a fast fitting strategy of Gaussian mixture models.The data obtained by image processing is well-suited for hypothesis testing of the detailed biomechanics of the gastrulating embryo. Typically this involves constructing computational mechanics models that consist of an objective function providing an estimate of strain energy for a given morphological configuration of the tissue, and a numerical minimization mechanism of this energy, achieved by varying morphological parameters.In this chapter, we provide an overview of in vivo imaging of fruit fly embryos using LSFM, computational tools suitable for processing the resulting images, and examples of computational biomechanical simulations of fly embryo gastrulation.

Photoreceptors for visual perception, phototaxis or light avoidance are typically clustered in eyes or related structures such as the Bolwig organ of Drosophila larvae. Unexpectedly, we found that the class IV dendritic arborization neurons of Drosophila melanogaster larvae respond to ultraviolet, violet and blue light, and are major mediators of light avoidance, particularly at high intensities. These class IV dendritic arborization neurons, which are present in every body segment, have dendrites tiling the larval body wall nearly completely without redundancy. Dendritic illumination activates class IV dendritic arborization neurons. These novel photoreceptors use phototransduction machinery distinct from other photoreceptors in Drosophila and enable larvae to sense light exposure over their entire bodies and move out of danger.

The processing of sensory input and the generation of behavior involves large networks of neurons, which necessitates new technology for recording from many neurons in behaving animals. In the larval zebrafish, light-sheet microscopy can be used to record the activity of almost all neurons in the brain simultaneously at single-cell resolution. Existing implementations, however, cannot be combined with visually driven behavior because the light sheet scans over the eye, interfering with presentation of controlled visual stimuli. Here we describe a system that overcomes the confounding eye stimulation through the use of two light sheets and combines whole-brain light-sheet imaging with virtual reality for fictively behaving larval zebrafish.

Developments in electrical and optical recording technology are scaling up the size of neuronal populations that can be monitored simultaneously. Light-sheet imaging is rapidly gaining traction as a method for optically interrogating activity in large networks and presents both opportunities and challenges for understanding circuit function.

The ability to visualize and quantitatively measure dynamic biological processes in vivo and at high spatiotemporal resolution is of fundamental importance to experimental investigations in developmental biology. Light-sheet microscopy is particularly well suited to providing such data, since it offers exceptionally high imaging speed and good spatial resolution while minimizing light-induced damage to the specimen. We review core principles and recent advances in light-sheet microscopy, with a focus on concepts and implementations relevant for applications in developmental biology. We discuss how light-sheet microcopy has helped advance our understanding of developmental processes from single-molecule to whole-organism studies, assess the potential for synergies with other state-of-the-art technologies, and introduce methods for computational image and data analysis. Finally, we explore the future trajectory of light-sheet microscopy, discuss key efforts to disseminate new light-sheet technology, and identify exciting opportunities for further advances.

Two-dimensional dispersions of colloidal particles with a range of surface chemistries and electrostatic potentials are characterized under a series of solution ionic strengths. A combination of optical imaging techniques are employed to monitor both the colloid structure and the electrostatic surface potential of individual particles in situ. We find that like-charge multiparticle interactions can be tuned from exclusively repulsive to long-range attractive by changing the particle surface composition. This behavior is strongly asymmetric with respect to the sign of the surface potential. Collective long-range attractive interactions are only observed among negatively charged particles.

We describe an implementation of maximum likelihood classification for single particle electron cryo-microscopy that is based on the FREALIGN software. Particle alignment parameters are determined by maximizing a joint likelihood that can include hierarchical priors, while classification is performed by expectation maximization of a marginal likelihood. We test the FREALIGN implementation using a simulated dataset containing computer-generated projection images of three different 70S ribosome structures, as well as a publicly available dataset of 70S ribosomes. The results show that the mixed strategy of the new FREALIGN algorithm yields performance on par with other maximum likelihood implementations, while remaining computationally efficient.

The ways in which cells set the size of intracellular structures is an important but largely unsolved problem [1]. Early embryonic divisions pose special problems in this regard. Many checkpoints common in somatic cells are missing from these divisions, which are characterized by rapid reductions in cell size and short cell cycles [2]. Embryonic cells must therefore possess simple and robust mechanisms that allow the size of many of their intracellular structures to rapidly scale with cell size.