With recent advances in high-throughput Electron Microscopy (EM) imaging it is now possible to image an entire nervous system of organisms like Drosophila melanogaster. One of the bottlenecks to reconstruct a connectome from these large volumes (œ 100 TiB) is the pixel-wise prediction of membranes. The time it would typically take to process such a volume using a convolutional neural network (CNN) with a sliding window approach is in the order of years on a current GPU. With sliding windows, however, a lot of redundant computations are carried out. In this paper, we present an extension to the Caffe library to increase throughput by predicting many pixels at once. On a sliding window network successfully used for membrane classification, we show that our method achieves a speedup of up to 57×, maintaining identical prediction results.

Biophysically accurate multicompartmental models of individual neurons have significantly advanced our understanding of the input-output function of single cells. These models depend on a large number of parameters that are difficult to estimate. In practice, they are often hand-tuned to match measured physiological behaviors, thus raising questions of identifiability and interpretability. We propose a statistical approach to the automatic estimation of various biologically relevant parameters, including 1) the distribution of channel densities, 2) the spatiotemporal pattern of synaptic input, and 3) axial resistances across extended dendrites. Recent experimental advances, notably in voltage-sensitive imaging, motivate us to assume access to: i) the spatiotemporal voltage signal in the dendrite and ii) an approximate description of the channel kinetics of interest. We show here that, given i and ii, parameters 1-3 can be inferred simultaneously by nonnegative linear regression; that this optimization problem possesses a unique solution and is guaranteed to converge despite the large number of parameters and their complex nonlinear interaction; and that standard optimization algorithms efficiently reach this optimum with modest computational and data requirements. We demonstrate that the method leads to accurate estimations on a wide variety of challenging model data sets that include up to about 10(4) parameters (roughly two orders of magnitude more than previously feasible) and describe how the method gives insights into the functional interaction of groups of channels.

We have developed methods to achieve efficient CRISPR-Cas9–mediated gene knockout in ex vivo mouse embryonic salivary epithelial explants. Salivary epithelial explants provide a valuable model for characterizing cell signaling, differentiation, and epithelial morphogenesis, but research has been limited by a paucity of efficient gene perturbation methods. Here, we demonstrate highly efficient gene perturbation by transient transduction of guide RNA–expressing lentiviruses into Cas9-expressing salivary epithelial buds isolated from Cas9 transgenic mice. We first show that salivary epithelial explants can be cultured in low-concentration, nonsolidified Matrigel suspensions in 96-well plates, which greatly increases sample throughput compared to conventional cultures embedded in solidified Matrigel. We further show that salivary epithelial explants can grow and branch with FGF7 alone, while supplementing with insulin, transferrin, and selenium (ITS) enhances growth and branching. We then describe an efficient workflow to produce experiment-ready, high-titer lentiviruses within 1 wk after molecular cloning. To track transduced cells, we designed the lentiviral vector to coexpress a nuclear fluorescent reporter with the guide RNA. We routinely achieved 80% transduction efficiency when antibiotic selection was used. Importantly, we detected robust loss of targeted protein products when testing 9 guide RNAs for 3 different genes. Moreover, targeting the β1 integrin gene (Itgb1) inhibited branching morphogenesis, which supports the importance of cell–matrix adhesion in driving branching morphogenesis. In summary, we have established a lentivirus-based method that can efficiently perturb genes of interest in salivary epithelial explants, which will greatly facilitate studies of specific gene functions using this system.

Whole-cell recording is a key technique for investigating synaptic and cellular mechanisms underlying various brain functions. However, because of its high sensitivity to mechanical disturbances, applying the whole-cell recording method to freely moving animals has been challenging. Here, we describe a technique for obtaining such recordings in freely moving, drug-free animals with a high success rate. This technique involves three major steps: obtaining a whole-cell recording from awake head-fixed animals, reliable and efficient stabilization of the pipette with respect to the animal's head using an ultraviolet (UV)-transparent collar and UV-cured adhesive, and rapid release of the animal from head fixation without loss of the recording. This technique has been successfully applied to obtain intracellular recordings from the hippocampus of freely moving rats and mice exploring a spatial environment, and should be generally applicable to other brain areas in animals engaged in a variety of natural behaviors.

Light-sheet microscopy is a powerful method for imaging the development and function of complex biological systems at high spatiotemporal resolution and over long time scales. Such experiments typically generate terabytes of multidimensional image data, and thus they demand efficient computational solutions for data management, processing and analysis. We present protocols and software to tackle these steps, focusing on the imaging-based study of animal development. Our protocols facilitate (i) high-speed lossless data compression and content-based multiview image fusion optimized for multicore CPU architectures, reducing image data size 30–500-fold; (ii) automated large-scale cell tracking and segmentation; and (iii) visualization, editing and annotation of multiterabyte image data and cell-lineage reconstructions with tens of millions of data points. These software modules are open source. They provide high data throughput using a single computer workstation and are readily applicable to a wide spectrum of biological model systems.

The efficient silylation of alcohols with di- and trialkynylsilanes was achieved under base-catalyzed conditions to afford alkynyl silyl ethers and symmetrical alkynyl silaketals in good yield. A selective alcoholysis of dialkynyl silyl ethers to mixed silaketals was also demonstrated. These products served as substrates for enyne ring-closing metathesis and, consequently, as precursors to stereochemically defined 1,3-dienes.

Genetic transformation in insects holds great promise as a tool for genetic manipulation in species of particular scientific, economic, or medical interest. A number of transposable elements have been tested recently as potential vectors for transformation in a range of insects. Minos is one of the most promising elements because it appears to be active in diverse species and has the capacity to carry large inserts. We report here the use of the Minos element as a transformation vector in the red flour beetle Tribolium castaneum (Coleoptera), an important species for comparative developmental and pest management studies. Transgenic G(1) beetles were recovered from 32.4% of fertile G(0)’s injected with a plasmid carrying a 3xP3-EGFP-marked transposon and in vitro synthesized mRNA encoding the Minos transposase. This transformation efficiency is 2.8-fold higher than that observed when using a plasmid helper. Molecular and genetic analyses show that several independent insertions can be recovered from a single injected parent, but that the majority of transformed individuals carry single Minos insertions. These results establish Minos as one of the most efficient vectors for genetic transformation in insects. In combination with piggyBac-based transgenesis, our work allows the introduction of sophisticated multicomponent genetic tools in Tribolium.

Epidermal Growth Factor Receptor (EGFR) signaling has a conserved role in ethanol-induced behavior in flies and mice, affecting ethanol-induced sedation in both species. However it is not known what other effects EGFR signaling may have on ethanol-induced behavior, or what roles other Receptor Tyrosine Kinase (RTK) pathways may play in ethanol induced behaviors. We examined the effects of both the EGFR and Fibroblast Growth Factor Receptor (FGFR) RTK signaling pathways on ethanol-induced enhancement of locomotion, a behavior distinct from sedation that may be associated with the rewarding effects of ethanol. We find that both EGFR and FGFR genes influence ethanol-induced locomotion, though their effects are opposite - EGFR signaling suppresses this behavior, while FGFR signaling promotes it. EGFR signaling affects development of the Drosophila mushroom bodies in conjunction with the JNK MAP kinase basket (bsk), and with the Ste20 kinase tao, and we hypothesize that the EGFR pathway affects ethanol-induced locomotion through its effects on neuronal development. We find, however, that FGFR signaling most likely affects ethanol-induced behavior through a different mechanism, possibly through acute action in adult neurons.

Intercepting a moving object requires prediction of its future location. This complex task has been solved by dragonflies, who intercept their prey in midair with a 95% success rate. In this study, we show that a group of 16 neurons, called target-selective descending neurons (TSDNs), code a population vector that reflects the direction of the target with high accuracy and reliability across 360°. The TSDN spatial (receptive field) and temporal (latency) properties matched the area of the retina where the prey is focused and the reaction time, respectively, during predatory flights. The directional tuning curves and morphological traits (3D tracings) for each TSDN type were consistent among animals, but spike rates were not. Our results emphasize that a successful neural circuit for target tracking and interception can be achieved with few neurons and that in dragonflies this information is relayed from the brain to the wing motor centers in population vector form.

The reward system is a collection of circuits that reinforce behaviors necessary for survival [1, 2]. Given the importance of reproduction for survival, actions that promote successful mating induce pleasurable feeling and are positively reinforced [3, 4]. This principle is conserved in Drosophila, where successful copulation is naturally rewarding to male flies, induces long-term appetitive memories [5], increases brain levels of neuropeptide F (NPF, the fly homolog of neuropeptide Y), and prevents ethanol, known otherwise as rewarding to flies [6, 7], from being rewarding [5]. It is not clear which of the multiple sensory and motor responses performed during mating induces perception of reward. Sexual interactions with female flies that do not reach copulation are not sufficient to reduce ethanol consumption [5], suggesting that only successful mating encounters are rewarding. Here, we uncoupled the initial steps of mating from its final steps and tested the ability of ejaculation to mimic the rewarding value of full copulation. We induced ejaculation by activating neurons that express the neuropeptide corazonin (CRZ) [8] and subsequently measured different aspects of reward. We show that activating Crz-expressing neurons is rewarding to male flies, as they choose to reside in a zone that triggers optogenetic stimulation of Crz neurons and display conditioned preference for an odor paired with the activation. Reminiscent of successful mating, repeated activation of Crz neurons increases npf levels and reduces ethanol consumption. Our results demonstrate that ejaculation stimulated by Crz/Crz-receptor signaling serves as an essential part of the mating reward mechanism in Drosophila. VIDEO ABSTRACT.