Multifocus microscopy (MFM) allows high-resolution instantaneous three-dimensional (3D) imaging and has been applied to study biological specimens ranging from single molecules inside cells nuclei to entire embryos. We here describe pattern designs and nanofabrication methods for diffractive optics that optimize the light-efficiency of the central optical component of MFM: the diffractive multifocus grating (MFG). We also implement a “precise color” MFM layout with MFGs tailored to individual fluorophores in separate optical arms. The reported advancements enable faster and brighter volumetric time-lapse imaging of biological samples. In live microscopy applications, photon budget is a critical parameter and light-efficiency must be optimized to obtain the fastest possible frame rate while minimizing photodamage. We provide comprehensive descriptions and code for designing diffractive optical devices, and a detailed methods description for nanofabrication of devices. Theoretical efficiencies of reported designs is ≈90% and we have obtained efficiencies of > 80% in MFGs of our own manufacture. We demonstrate the performance of a multi-phase MFG in 3D functional neuronal imaging in living C. elegans.

Additional authors include:

Xin Jin, Joan Pulupa, Christine Cho, Mustafa Mir, Mohamed El Beheiry, Xavier Darzacq, Marcelo Nollmann, Maxime Dahan, Carl Wu, Timothée Lionnet, J. Alexander Liddle, and Cornelia I. Bargmann

Imaging and localizing single molecules with high accuracy in a 3D volume is a challenging task. Here we combine multifocal microscopy, a recently developed volumetric imaging technique, with point spread function engineering to achieve an increased depth for single molecule imaging. Applications in 3D single molecule localization-based super-resolution imaging is shown over an axial depth of 4 µm as well as for the tracking of diffusing beads in a fluid environment over 8 µm.

During larval life most of the thoracic neuroblasts (NBs) in Drosophila undergo a second phase of neurogenesis to generate adult-specific neurons that remain in an immature, developmentally stalled state until pupation. Using a combination of MARCM and immunostaining with a neurotactin antibody Truman et al. (2004) identified 24 adult specific NB lineages within each thoracic hemineuromere of the larval ventral nervous system (VNS) but because the neurotactin labeling of lineage tracts disappearing early in metamorphosis they were unable extend the identification of the these lineages into the adult. Here we show that immunostaining with an antibody against the cell adhesion molecule Neuroglian reveals the same larval secondary lineage projections through metamorphosis and by identifying each neuroglian positive tract at selected stages we have traced the larval hemilineage tracts for all three thoracic neuromeres through metamorphosis into the adult. To validate tract identifications we used the genetic toolkit developed by Harris et al. (2015) to preserve hemilineage specific GAL4 expression patterns from larval into the adult stage. The immortalized expression proved a powerful confirmation of the analysis of the neuroglian scaffold. This work has enabled us to directly link the secondary, larval NB lineages to their adult counterparts. The data provide an anatomical framework that 1) makes it possible to assign most neurons to their parent lineage and 2) allows more precise definitions of the neuronal organization of the adult VNS based in developmental units/rules. This article is protected by copyright. All rights reserved.

Despite significant advances in neuroscience, the neural bases of intelligence remain poorly understood. Arguably the most elusive aspect of intelligence is the ability to make robust inferences that go far beyond one's experience. Animals categorize objects, learn to vocalize and may even estimate causal relationships - all in the face of data that is often ambiguous and sparse. Such inductive leaps are thought to result from the brain's ability to infer latent structure that governs the environment. However, we know little about the neural computations that underlie this ability. Recent advances in developing computational frameworks that can support efficient structure learning and inductive inference may provide insight into the underlying component processes and help pave the path for uncovering their neural implementation.

Dopaminergic neurons serve multiple functions, including reinforcement processing during associative learning [1-12]. It is thus warranted to understand which dopaminergic neurons mediate which function. We study larval Drosophila, in which only approximately 120 of a total of 10,000 neurons are dopaminergic, as judged by the expression of tyrosine hydroxylase (TH), the rate-limiting enzyme of dopamine biosynthesis [5, 13]. Dopaminergic neurons mediating reinforcement in insect olfactory learning target the mushroom bodies, a higher-order "cortical" brain region [1-5, 11, 12, 14, 15]. We discover four previously undescribed paired neurons, the primary protocerebral anterior medial (pPAM) neurons. These neurons are TH positive and subdivide the medial lobe of the mushroom body into four distinct subunits. These pPAM neurons are acutely necessary for odor-sugar reward learning and require intact TH function in this process. However, they are dispensable for aversive learning and innate behavior toward the odors and sugars employed. Optogenetical activation of pPAM neurons is sufficient as a reward. Thus, the pPAM neurons convey a likely dopaminergic reward signal. In contrast, DL1 cluster neurons convey a corresponding punishment signal [5], suggesting a cellular division of labor to convey dopaminergic reward and punishment signals. On the level of individually identified neurons, this uncovers an organizational principle shared with adult Drosophila and mammals [1-4, 7, 9, 10] (but see [6]). The numerical simplicity and connectomic tractability of the larval nervous system [16-19] now offers a prospect for studying circuit principles of dopamine function at unprecedented resolution.

Genes are regulated by transcription factors that bind to regions of genomic DNA called enhancers. Considerable effort is focused on identifying transcription factor binding sites, with the goal of predicting gene expression from DNA sequence. Despite this effort, general, predictive models of enhancer function are currently lacking. Here we combine quantitative models of enhancer function with manipulations using engineered transcription factors to examine the extent to which enhancer function can be controlled in a quantitatively predictable manner. Our models, which incorporate few free parameters, can accurately predict the contributions of ectopic transcription factor inputs. These models allow the predictable 'tuning' of enhancers, providing a framework for the quantitative control of enhancers with engineered transcription factors.

The successive nuclear division cycles in the syncytial Drosophila embryo are accompanied by ingression and regression of plasma membrane furrows, which surround individual nuclei at the embryo periphery, playing a central role in embryo compartmentalization prior to cellularization. Here, we demonstrate that cell cycle changes in dynamin localization and activity at the plasma membrane (PM) regulate metaphase furrow formation and PM organization in the syncytial embryo. Dynamin was localized on short PM furrows during interphase, mediating endocytosis of PM components. Dynamin redistributed off ingressed PM furrows in metaphase, correlating with stabilized PM components and the associated actin regulatory machinery on long furrows. Acute inhibition of dynamin in the temperature sensitive shibire mutant embryo resulted in morphogenetic consequences in the syncytial division cycle. These included inhibition of metaphase furrow ingression, randomization of proteins normally polarized to intercap PM and disruption of the diffusion barrier separating PM domains above nuclei. Based on these findings, we propose that cell cycle changes in dynamin orchestrate recruitment of actin regulatory machinery for PM furrow dynamics during the early mitotic cycles in the Drosophila embryo.

Cataloging the neuronal cell types that comprise circuitry of individual brain regions is a major goal of modern neuroscience and the BRAIN initiative. Single-cell RNA sequencing can now be used to measure the gene expression profiles of individual neurons and to categorize neurons based on their gene expression profiles. While the single-cell techniques are extremely powerful and hold great promise, they are currently still labor intensive, have a high cost per cell, and, most importantly, do not provide information on spatial distribution of cell types in specific regions of the brain. We propose a complementary approach that uses computational methods to infer the cell types and their gene expression profiles through analysis of brain-wide single-cell resolution in situ hybridization (ISH) imagery contained in the Allen Brain Atlas (ABA). We measure the spatial distribution of neurons labeled in the ISH image for each gene and model it as a spatial point process mixture, whose mixture weights are given by the cell types which express that gene. By fitting a point process mixture model jointly to the ISH images, we infer both the spatial point process distribution for each cell type and their gene expression profile. We validate our predictions of cell type-specific gene expression profiles using single cell RNA sequencing data, recently published for the mouse somatosensory cortex. Jointly with the gene expression profiles, cell features such as cell size, orientation, intensity and local density level are inferred per cell type.

Primary cilia are ubiquitous, microtubule-based organelles that play diverse roles in sensory transduction in many eukaryotic cells. They interrogate the cellular environment through chemosensing, osmosensing, and mechanosensing using receptors and ion channels in the ciliary membrane. Little is known about the mechanical and structural properties of the cilium and how these properties contribute to ciliary perception. We probed the mechanical responses of primary cilia from kidney epithelial cells [Madin-Darby canine kidney-II (MDCK-II)], which sense fluid flow in renal ducts. We found that, on manipulation with an optical trap, cilia deflect by bending along their length and pivoting around an effective hinge located below the basal body. The calculated bending rigidity indicates weak microtubule doublet coupling. Primary cilia of MDCK cells lack interdoublet dynein motors. Nevertheless, we found that the organelles display active motility. 3D tracking showed correlated fluctuations of the cilium and basal body. These angular movements seemed random but were dependent on ATP and cytoplasmic myosin-II in the cell cortex. We conclude that force generation by the actin cytoskeleton surrounding the basal body results in active ciliary movement. We speculate that actin-driven ciliary movement might tune and calibrate ciliary sensory functions.

Escape behaviors deliver organisms away from imminent catastrophe. Here, we characterize behavioral responses of freely swimming larval zebrafish to looming visual stimuli simulating predators. We report that the visual system alone can recruit lateralized, rapid escape motor programs, similar to those elicited by mechanosensory modalities. Two-photon calcium imaging of retino-recipient midbrain regions isolated the optic tectum as an important center processing looming stimuli, with ensemble activity encoding the critical image size determining escape latency. Furthermore, we describe activity in retinal ganglion cell terminals and superficial inhibitory interneurons in the tectum during looming and propose a model for how temporal dynamics in tectal periventricular neurons might arise from computations between these two fundamental constituents. Finally, laser ablations of hindbrain circuitry confirmed that visual and mechanosensory modalities share the same premotor output network. We establish a circuit for the processing of aversive stimuli in the context of an innate visual behavior.