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Bogovic, J.

Publications and source records attributed to Bogovic, J..

11 recordsLinked to original sources

Sexual dimorphism in the complete connectome of the Drosophila male central nervous system

Sex differences in behaviour exist across all animals, typically under strong genetic regulation. In Drosophila, fruitless/doublesex transcription factors can identify dimorphic neurons but their organisation into functional circuits remains unclear. We present the connectome of the entire Drosophila male central nervous system. This contains 166,691 neurons spanning the brain and nerve cord, fully proofread and annotated including fruitless/doublesex expression and 11,691 types. We provide the first comprehensive comparison between male and female brain connectomes to synaptic resolution, finding 7,205 isomorphic, 114 dimorphic, 262 male-specific and 69 female-specific types. This resource enables analysis of full sensory-to-motor circuits underlying complex behaviours and the impact of dimorphic elements. Sex-specific/dimorphic neurons are concentrated in higher brain centres while the sensory and motor periphery are largely isomorphic. Within higher centres, male-specific connections are organised into hotspots defined by male-specific neurons or arbours. Numerous circuit switches reroute sensory information to form antagonistic circuits controlling opposing behaviours.

neuroscience↗

Connectome-driven neural inventory of a complete visual system

Vision provides animals with detailed information about their surroundings, conveying diverse features such as color, form, and movement across the visual scene. Computing these parallel spatial features requires a large and diverse network of neurons, such that in animals as distant as flies and humans, visual regions comprise half the brains volume. These visual brain regions often reveal remarkable structure-function relationships, with neurons organized along spatial maps with shapes that directly relate to their roles in visual processing. To unravel the stunning diversity of a complex visual system, a careful mapping of the neural architecture matched to tools for targeted exploration of that circuitry is essential. Here, we report a new connectome of the right optic lobe from a male Drosophila central nervous system FIB-SEM volume and a comprehensive inventory of the flys visual neurons. We developed a computational framework to quantify the anatomy of visual neurons, establishing a basis for interpreting how their shapes relate to spatial vision. By integrating this analysis with connectivity information, neurotransmitter identity, and expert curation, we classified the [~]53,000 neurons into 727 types, about half of which are systematically described and named for the first time. Finally, we share an extensive collection of split-GAL4 lines matched to our neuron type catalog. Together, this comprehensive set of tools and data unlock new possibilities for systematic investigations of vision in Drosophila, a foundation for a deeper understanding of sensory processing.

neuroscience↗

A Connectome of the Male Drosophila Ventral Nerve Cord

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.

neuroscience↗

OME-Zarr: a cloud-optimized bioimaging file format with international community support

A growing community is constructing a next-generation file format (NGFF) for bioimaging to overcome problems of scalability and heterogeneity. Organized by the Open Microscopy Environment (OME), individuals and institutes across diverse modalities facing these problems have designed a format specification process (OME-NGFF) to address these needs. This paper brings together a wide range of those community members to describe the cloud-optimized format itself - OME-Zarr - along with tools and data resources available today to increase FAIR access and remove barriers in the scientific process. The current momentum offers an opportunity to unify a key component of the bioimaging domain -- the file format that underlies so many personal, institutional, and global data management and analysis tasks.

bioinformatics↗

Architecture and dynamics of a novel desmosome-endoplasmic reticulum organelle

The endoplasmic reticulum (ER) forms a dynamic network that contacts other cellular membranes to regulate stress responses, calcium signaling, and lipid transfer. Using high-resolution volume electron microscopy, we find that the ER forms a previously unknown association with keratin intermediate filaments and desmosomal cell-cell junctions. Peripheral ER assembles into mirror image-like arrangements at desmosomes and exhibits nanometer proximity to keratin filaments and the desmosome cytoplasmic plaque. ER tubules exhibit stable associations with desmosomes, and perturbation of desmosomes or keratin filaments alters ER organization and mobility. These findings indicate that desmosomes and the keratin cytoskeleton pattern the distribution of the ER network. Overall, this study reveals a previously unknown subcellular architecture defined by the structural integration of ER tubules with an epithelial intercellular junction. One-Sentence SummaryThe desmosome adhesive junction regulates the organization and dynamics of the endoplasmic reticulum network.

cell biology↗

Rapid reconstruction of neural circuits using tissue expansion and lattice light sheet microscopy

Electron microscopy (EM) allows for the reconstruction of dense neuronal connectomes but suffers from low throughput, limiting its application to small numbers of reference specimens. We developed a protocol and analysis pipeline using tissue expansion and lattice light-sheet microscopy (ExLLSM) to rapidly reconstruct selected circuits across many samples with single synapse resolution and molecular contrast. We validate this approach in Drosophila, demonstrating that it yields synaptic counts similar to those obtained by EM, can be used to compare counts across sex and experience, and to correlate structural connectivity with functional connectivity. This approach fills a critical methodological gap in studying variability in the structure and function of neural circuits across individuals within and between species.

neuroscience↗

Automatic whole cell organelle segmentation in volumetric electron microscopy

Cells contain hundreds of different organelle and macromolecular assemblies intricately organized relative to each other to meet any cellular demands. Obtaining a complete understanding of their organization is challenging and requires nanometer-level, threedimensional reconstruction of whole cells. Even then, the immense size of datasets and large number of structures to be characterized requires generalizable, automatic methods. To meet this challenge, we developed an analysis pipeline for comprehensively reconstructing and analyzing the cellular organelles in entire cells imaged by focused ion beam scanning electron microscopy (FIB-SEM) at a near-isotropic size of 4 or 8 nm per voxel. The pipeline involved deep learning architectures trained on diverse samples for automatic reconstruction of 35 different cellular organelle classes - ranging from endoplasmic reticulum to microtubules to ribosomes - from multiple cell types. Automatic reconstructions were used to directly quantify various previously inaccessible metrics about these structures, including their spatial interactions. We show that automatic organelle reconstructions can also be used to automatically register light and electron microscopy images for correlative studies. We created an open data and open source web repository, OpenOrganelle, to share the data, computer code, and trained models, enabling scientists everywhere to query and further reconstruct the datasets.

cell biology↗

A Connectome and Analysis of the Adult Drosophila Central Brain

The neural circuits responsible for animal behavior remain largely unknown. We summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses in, and proofread such large data sets. We define cell types, refine computational compartments, and provide an exhaustive atlas of cell examples and types, many of them novel. We provide detailed circuits consisting of neurons and their chemical synapses for most of the central brain. We make the data public and simplify access, reducing the effort needed to answer circuit questions, and provide procedures linking the neurons defined by our analysis with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs on different scales, electrical consequences of compartmentalization, and evidence that maximizing packing density is an important criterion in the evolution of the flys brain.

bioinformatics↗

A Connectome of the Adult Drosophila Central Brain

The neural circuits responsible for behavior remain largely unknown. Previous efforts have reconstructed the complete circuits of small animals, with hundreds of neurons, and selected circuits for larger animals. Here we (the FlyEM project at Janelia and collaborators at Google) summarize new methods and present the complete circuitry of a large fraction of the brain of a much more complex animal, the fruit fly Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, segment, find synapses, and proofread such large data sets; new methods that define cell types based on connectivity in addition to morphology; and new methods to simplify access to a large and evolving data set. From the resulting data we derive a better definition of computational compartments and their connections; an exhaustive atlas of cell examples and types, many of them novel; detailed circuits for most of the central brain; and exploration of the statistics and structure of different brain compartments, and the brain as a whole. We make the data public, with a web site and resources specifically designed to make it easy to explore, for all levels of expertise from the expert to the merely curious. The public availability of these data, and the simplified means to access it, dramatically reduces the effort needed to answer typical circuit questions, such as the identity of upstream and downstream neural partners, the circuitry of brain regions, and to link the neurons defined by our analysis with genetic reagents that can be used to study their functions. Note: In the next few weeks, we will release a series of papers with more involved discussions. One paper will detail the hemibrain reconstruction with more extensive analysis and interpretation made possible by this dense connectome. Another paper will explore the central complex, a brain region involved in navigation, motor control, and sleep. A final paper will present insights from the mushroom body, a center of multimodal associative learning in the fly brain.

neuroscience↗

Cortical Column and Whole Brain Imaging of Neural Circuits with Molecular Contrast and Nanoscale Resolution

Optical and electron microscopy have made tremendous inroads in understanding the complexity of the brain, but the former offers insufficient resolution to reveal subcellular details and the latter lacks the throughput and molecular contrast to visualize specific molecular constituents over mm-scale or larger dimensions. We combined expansion microscopy and lattice light sheet microscopy to image the nanoscale spatial relationships between proteins across the thickness of the mouse cortex or the entire Drosophila brain, including synaptic proteins at dendritic spines, myelination along axons, and presynaptic densities at dopaminergic neurons in every fly neuropil domain. The technology should enable statistically rich, large scale studies of neural development, sexual dimorphism, degree of stereotypy, and structural correlations to behavior or neural activity, all with molecular contrast.\n\nOne Sentence SummaryCombined expansion and lattice light sheet microscopy enables high speed, nanoscale molecular imaging of neural circuits over large volumes.

neuroscience↗

A Complete Electron Microscopy Volume Of The Brain Of Adult Drosophila melanogaster

Drosophila melanogaster has a rich repertoire of innate and learned behaviors. Its 100,000-neuron brain is a large but tractable target for comprehensive neural circuit mapping. Only electron microscopy (EM) enables complete, unbiased mapping of synaptic connectivity; however, the fly brain is too large for conventional EM. We developed a custom high-throughput EM platform and imaged the entire brain of an adult female fly. We validated the dataset by tracing brain-spanning circuitry involving the mushroom body (MB), intensively studied for its role in learning. Here we describe the complete set of olfactory inputs to the MB; find a new cell type providing driving input to Kenyon cells (the intrinsic MB neurons); identify neurons postsynaptic to Kenyon cell dendrites; and find that axonal arbors providing input to the MB calyx are more tightly clustered than previously indicated by light-level data. This freely available EM dataset will significantly accelerate Drosophila neuroscience.\n\nHIGHLIGHTS- A complete adult fruit fly brain was imaged, using electron microscopy (EM)\n- The EM volume enables brain-spanning mapping of neuronal circuits at the synaptic level\n- Olfactory projection neurons cluster more tightly in mushroom body calyx than expected from light-level data\n- The primary postsynaptic targets of Kenyon cells (KCs) in the MB are other KCs, as well as the anterior paired lateral (APL) neuron\n- A newly discovered cell type, MB-CP2, integrates input from several sensory modalities and provides microglomerular input to KCs in MB calyx\n- A software pipeline was created in which EM-traced skeletons can be searched for within existing large-scale light microscopy (LM) databases of neuronal morphology, facilitating cell type identification and discovery of relevant genetic driver lines

neuroscience↗