Natural neural circuits, optimized by millions of years of evolution, are fast, low power, robust, and adapt in response to experience, all characteristics we would love to have in systems we ourselves design. Recently there have been enormous advances in understanding how neurons implement computations within the brain of living creatures. Can we use this new-found knowledge to create better artificial system? What lessons can we learn from the neurons themselves, that can help us create better neuromorphic circuits?

Upon inflammation, leukocytes extravasate through endothelial cells. When they extravasate in a paracellular manner, it is generally accepted that neighbouring endothelial cells physically disconnect to open cell-cell junctions, allowing leukocytes to cross. When carefully examining endothelial junctions, we found a partial membrane overlap of endothelial cells beyond VE-cadherin distribution. These overlaps are regulated by actin polymerization and, although marked by, do not require PECAM-1, nor VE-cadherin. Neutrophils prefer wider membrane overlaps as exit sites. Detailed 3D analysis of endothelial membrane dynamics during paracellular neutrophil transmigration in real-time, at high spatiotemporal resolution using resonant confocal and lattice light-sheet imaging, revealed that overlapping endothelial membranes form a tunnel during neutrophil transmigration. These tunnels are formed by the neutrophil lifting the membrane of the upper endothelial cell while indenting and crawling over the membrane of the underlying endothelial cell. Our work shows that endothelial cells do not simply retract upon passage of neutrophils but provide membrane tunnels, allowing neutrophils to extravasate. This discovery defines the 3D multicellular architecture in which the paracellular transmigration of neutrophils occurs.

Interplay between models and experimental data advances discovery and understanding in biology, particularly when models generate predictions that allow well-designed experiments to distinguish between alternative mechanisms. To illustrate how this feedback between models and experiments can lead to key insights into biological mechanisms, we explore three examples from cellular slime mold chemotaxis. These examples include studies that identified chemotaxis as the primary mechanism behind slime mold aggregation, discovered that cells likely measure chemoattractant gradients by sensing concentration differences across cell length, and tested the role of cell-associated chemoattractant degradation in shaping chemotactic fields. Although each study used a different model class appropriate to their hypotheses - qualitative, mathematical, or simulation-based - these examples all highlight the utility of modeling to formalize assumptions and generate testable predictions. A central element of this framework is the iterative use of models and experiments, specifically: matching experimental designs to the models, revising models based on mismatches with experimental data, and validating critical model assumptions and predictions with experiments. We advocate for continued use of this interplay between models and experiments to advance biological discovery.

A crystal structure of the anaerobic Ni-Fe-S carbon monoxide dehydrogenase (CODH) from Rhodospirillum rubrum has been determined to 2.8-Å resolution. The CODH family, for which the R. rubrum enzyme is the prototype, catalyzes the biological oxidation of CO at an unusual Ni-Fe-S cluster called the C-cluster. The Ni-Fe-S C-cluster contains a mononuclear site and a four-metal cubane. Surprisingly, anomalous dispersion data suggest that the mononuclear site contains Fe and not Ni, and the four-metal cubane has the form [NiFe3S4] and not [Fe4S4]. The mononuclear site and the four-metal cluster are bridged by means of Cys531 and one of the sulfides of the cube. CODH is organized as a dimer with a previously unidentified [Fe4S4] cluster bridging the two subunits. Each monomer is comprised of three domains: a helical domain at the N terminus, an α/β (Rossmann-like) domain in the middle, and an α/β (Rossmann-like) domain at the C terminus. The helical domain contributes ligands to the bridging [Fe4S4] cluster and another [Fe4S4] cluster, the B-cluster, which is involved in electron transfer. The two Rossmann domains contribute ligands to the active site C-cluster. This x-ray structure provides insight into the mechanism of biological CO oxidation and has broader significance for the roles of Ni and Fe in biological systems.

Novel technologies are required for three-dimensional cell biology and biophysics. By three-dimensional we refer to experimental conditions that essentially try to avoid hard and flat surfaces and favour unconstrained sample dynamics. We believe that light-sheet-based microscopes are particularly well suited to studies of sensitive three-dimensional biological systems. The application of such instruments can be illustrated with examples from the biophysics of microtubule dynamics and three-dimensional cell cultures. Our experience leads us to suggest that three-dimensional approaches reveal new aspects of a system and enable experiments to be performed in a more physiological and hence clinically more relevant context.

Light sheet fluorescence microscopy (LSFM) uses a thin sheet of light to excite only fluorophores within the focal volume. Light sheet microscopes (LSMs) have a true optical sectioning capability and, hence, provide axial resolution, restrict photobleaching and phototoxicity to a fraction of the sample and use cameras to record tens to thousands of images per second. LSMs are used for in-depth analyses of large, optically cleared samples and long-term three-dimensional (3D) observations of live biological specimens at high spatio-temporal resolution. The independently operated illumination and detection trains and the canonical implementations, selective/single plane illumination microscope (SPIM) and digital scanned laser microscope (DSLM), are the basis for many LSM designs. In this Primer, we discuss various applications of LSFM for imaging multicellular specimens, developing vertebrate and invertebrate embryos, brain and heart function, 3D cell culture models, single cells, tissue sections, plants, organismic interaction and entire cleared brains. Further, we describe the combination of LSFM with other imaging approaches to allow for super-resolution or increased penetration depth and the use of sophisticated spatio-temporal manipulations to allow for observations along multiple directions. Finally, we anticipate developments of the field in the near future.

Capturing dynamic processes in live samples is a nontrivial task in biological imaging. Although fluorescence provides high specificity and contrast compared to other light microscopy techniques, the photophysical principles of this method can have a harmful effect on the sample. Current advances in light sheet microscopy have created a novel imaging toolbox that allows for rapid acquisition of high-resolution fluorescent images with minimal perturbation of the processes of interest. Each unique design has its own advantages and limitations. In this review, we describe several cutting edge light sheet microscopes and their optimal applications.

Light sheet-based fluorescence microscopy (LSFM) is emerging as a powerful imaging technique for the life sciences. LSFM provides an exceptionally high imaging speed, high signal-to-noise ratio, low level of photo-bleaching, and good optical penetration depth. This unique combination of capabilities makes light sheet-based microscopes highly suitable for live imaging applications. Here, we provide an overview of light sheet-based microscopy assays for in vitro and in vivo imaging of biological samples, including cell extracts, soft gels, and large multicellular organisms. We furthermore describe computational tools for basic image processing and data inspection.

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.