Primary cilia are sensory organelles present in many cell types. Based on an array of microtubules termed axoneme they form a specialized membrane compartment partaking in various signaling processes. Primary cilia of pancreatic islet beta cells play a role in autocrine and paracrine signaling and are linked to diabetes. Yet, the structural basis for their functions is unclear. We present three-dimensional reconstructions of complete mouse and human beta cell cilia, revealing a disorganized 9+0 axoneme structure. Within the islet cilia are spatially confined within deep ciliary pockets or squeezed into narrow extracellular spaces between adjacent cells. Beta and alpha cell cilia physically interact with neighboring islet cells pushing and strongly bending their plasma membranes. Furthermore, beta cells can contain multiple cilia that can meet with other islet cell cilia in the extracellular space. Additionally, beta cell cilia establish connections with islet-projecting nerves. These findings highlight the pivotal role of beta cell primary cilia in islet cell connectivity, pointing at their potential functional role in integrating islet intrinsic and extrinsic signals. These novel insights contribute to understanding their significance in health and diabetes.

For most model organisms in neuroscience, research into visual processing in the brain is difficult because of a lack of high-resolution maps that capture complex neuronal circuitry. The microinsect Megaphragma viggianii, because of its small size and non-trivial behavior, provides a unique opportunity for tractable whole-organism connectomics. We image its whole head using serial electron microscopy. We reconstruct its compound eye and analyze the optical properties of the ommatidia as well as the connectome of the first visual neuropil-the lamina. Compared with the fruit fly and the honeybee, Megaphragma visual system is highly simplified: it has 29 ommatidia per eye and 6 lamina neuron types. We report features that are both stereotypical among most ommatidia and specialized to some. By identifying the "barebones" circuits critical for flying insects, our results will facilitate constructing computational models of visual processing in insects.

Methods of three-dimensional electron microscopy have been actively developed recently and open up great opportunities for morphological work. This approach is especially useful for studying microinsects, since it is possible to obtain complete series of high-resolution sections of a whole insect. Studies on the genus Megaphragma are especially important, since the unique phenomenon of lysis of most of the neuron nuclei was discovered in species of this genus. In this study we reveal the anatomical structure of the head of Megaphragma viggianii at all levels from organs to subcellular structures. Despite the miniature size of the body, most of the organ systems of M. viggianii retain the structural plan and complexity of organization at all levels. The set of muscles and the well-developed stomatogastric nervous system of this species correspond to those of larger insects, and there is also a well-developed tracheal system in the head of this species. Reconstructions of the head of M. viggianii at the cellular and subcellular levels were obtained, and of volumetric data were analyzed. A total of 689 nucleated cells of the head were reconstructed. The ultrastructure of M. viggianii is surprisingly complex, and the evolutionary benefits of such complexity are probably among the factors limiting the further miniaturization of parasitoid wasps.

Animal behavior is principally expressed through neural control of muscles. Therefore understanding how the brain controls behavior requires mapping neuronal circuits all the way to motor neurons. We have previously established technology to collect large-volume electron microscopy data sets of neural tissue and fully reconstruct the morphology of the neurons and their chemical synaptic connections throughout the volume. Using these tools we generated a dense wiring diagram, or connectome, for a large portion of the Drosophila central brain. However, in most animals, including the fly, the majority of motor neurons are located outside the brain in a neural center closer to the body, i.e. the mammalian spinal cord or insect ventral nerve cord (VNC). In this paper, we extend our effort to map full neural circuits for behavior by generating a connectome of the VNC of a male fly.

Evolution has generated an enormous variety of morphological, physiological, and behavioral traits in animals. How do behaviors evolve in different directions in species equipped with similar neurons and molecular components? Here we adopted a comparative approach to investigate the similarities and differences of escape behaviors in response to noxious stimuli and their underlying neural circuits between closely related drosophilid species. Drosophilids show a wide range of escape behaviors in response to noxious cues, including escape crawling, stopping, head casting, and rolling. Here we find that D. santomea, compared with its close relative D. melanogaster, shows a higher probability of rolling in response to noxious stimulation. To assess whether this behavioral difference could be attributed to differences in neural circuitry, we generated focused ion beam-scanning electron microscope volumes of the ventral nerve cord of D. santomea to reconstruct the downstream partners of mdIV, a nociceptive sensory neuron in D. melanogaster. Along with partner interneurons of mdVI (including Basin-2, a multisensory integration neuron necessary for rolling) previously identified in D. melanogaster, we identified two additional partners of mdVI in D. santomea. Finally, we showed that joint activation of one of the partners (Basin-1) and a common partner (Basin-2) in D. melanogaster increased rolling probability, suggesting that the high rolling probability in D. santomea is mediated by the additional activation of Basin-1 by mdIV. These results provide a plausible mechanistic explanation for how closely related species exhibit quantitative differences in the likelihood of expressing the same behavior.