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 brain's 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 fly's 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.

Petascale pipeline for precise alignment of images from serial section electron microscopy.

The reconstruction of neural circuits from serial section electron microscopy (ssEM) images is being accelerated by automatic image segmentation methods. Segmentation accuracy is often limited by the preceding step of aligning 2D section images to create a 3D image stack. Precise and robust alignment in the presence of image artifacts is challenging, especially as datasets are attaining the petascale. We present a computational pipeline for aligning ssEM images with several key elements. Self-supervised convolutional nets are trained via metric learning to encode and align image pairs, and they are used to initialize iterative fine-tuning of alignment. A procedure called vector voting increases robustness to image artifacts or missing image data. For speedup the series is divided into blocks that are distributed to computational workers for alignment. The blocks are aligned to each other by composing transformations with decay, which achieves a global alignment without resorting to a time-consuming global optimization. We apply our pipeline to a whole fly brain dataset, and show improved accuracy relative to prior state of the art. We also demonstrate that our pipeline scales to a cubic millimeter of mouse visual cortex. Our pipeline is publicly available through two open source Python packages.

Architecture and dynamics of a desmosome-endoplasmic reticulum complex.

The endoplasmic reticulum (ER) forms a dynamic network that contacts other cellular membranes to regulate stress responses, calcium signalling and lipid transfer. Here, 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 nanometre 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, mobility and expression of ER stress transcripts. These findings indicate that desmosomes and the keratin cytoskeleton regulate the distribution, function and dynamics 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.

A scalable and modular automated pipeline for stitching of large electron microscopy datasets.

Serial-section electron microscopy (ssEM) is the method of choice for studying macroscopic biological samples at extremely high resolution in three dimensions. In the nervous system, nanometer-scale images are necessary to reconstruct dense neural wiring diagrams in the brain, so -called connectomes. The data that can comprise of up to 108 individual EM images must be assembled into a volume, requiring seamless 2D registration from physical section followed by 3D alignment of the stitched sections. The high throughput of ssEM necessitates 2D stitching to be done at the pace of imaging, which currently produces tens of terabytes per day. To achieve this, we present a modular volume assembly software pipeline ASAP (Assembly Stitching and Alignment Pipeline) that is scalable to datasets containing petabytes of data and parallelized to work in a distributed computational environment. The pipeline is built on top of the Render Trautman and Saalfeld (2019) services used in the volume assembly of the brain of adult Drosophila melanogaster (Zheng et al. 2018). It achieves high throughput by operating only on image meta-data and transformations. ASAP is modular, allowing for easy incorporation of new algorithms without significant changes in the workflow. The entire software pipeline includes a complete set of tools for stitching, automated quality control, 3D section alignment, and final rendering of the assembled volume to disk. ASAP has been deployed for continuous stitching of several large-scale datasets of the mouse visual cortex and human brain samples including one cubic millimeter of mouse visual cortex (Yin et al. 2020); Microns Consortium et al. (2021) at speeds that exceed imaging. The pipeline also has multi-channel processing capabilities and can be applied to fluorescence and multi-modal datasets like array tomography.

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 fly's brain.

Animal brains of all sizes, from the smallest to the largest, work in broadly similar ways. Studying the brain of any one animal in depth can thus reveal the general principles behind the workings of all brains. The fruit fly Drosophila is a popular choice for such research. With about 100,000 neurons ­ compared to some 86 billion in humans ­ the fly brain is small enough to study at the level of individual cells. But it nevertheless supports a range of complex behaviors, including navigation, courtship and learning. Thanks to decades of research, scientists now have a good understanding of which parts of the fruit fly brain support particular behaviors. But exactly how they do this is often unclear. This is because previous studies showing the connections between cells only covered small areas of the brain. This is like trying to understand a novel when all you can see is a few isolated paragraphs. To solve this problem, Scheffer, Xu, Januszewski, Lu, Takemura, Hayworth, Huang, Shinomiya et al. prepared the first complete map of the entire central region of the fruit fly brain. The central brain consists of approximately 25,000 neurons and around 20 million connections. To prepare the map ­ or connectome ­ the brain was cut into very thin 8nm slices and photographed with an electron microscope. A three-dimensional map of the neurons and connections in the brain was then reconstructed from these images using machine learning algorithms. Finally, Scheffer et al. used the new connectome to obtain further insights into the circuits that support specific fruit fly behaviors. The central brain connectome is freely available online for anyone to access. When used in combination with existing methods, the map will make it easier to understand how the fly brain works, and how and why it can fail to work correctly. Many of these findings will likely apply to larger brains, including our own. In the long run, studying the fly connectome may therefore lead to a better understanding of the human brain and its disorders. Performing a similar analysis on the brain of a small mammal, by scaling up the methods here, will be a likely next step along this path.

Luciferin production and luciferase transcription in the bioluminescent copepod Metridia lucens.

Bioluminescent copepods are often the most abundant marine zooplankton and play critical roles in oceanic food webs. Metridia copepods exhibit particularly bright bioluminescence, and the molecular basis of their light production has just recently begun to be explored. Here we add to this body of work by transcriptomically profiling Metridia lucens, a common species found in temperate, northern, and southern latitudes. In this previously molecularly-uncharacterized species, we find the typical luciferase paralog gene set found in Metridia. More surprisingly, we recover noteworthy putative luciferase sequences that had not been described from Metridia species, indicating that bioluminescence produced by these copepods may be more complex than previously known. This includes another copepod luciferase, as well as one from a shrimp. Furthermore, feeding experiments using mass spectrometry and 13C labelled L-tyrosine and L-phenylalanine firmly establish that M. lucens produces its own coelenterazine luciferin rather than acquiring it through diet. This coelenterazine synthesis has only been directly confirmed in one other copepod species.

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 at synaptic resolution. To validate the dataset, we traced brain-spanning circuitry involving the mushroom body (MB), which has been extensively studied for its role in learning. All inputs to Kenyon cells (KCs), the intrinsic neurons of the MB, were mapped, revealing a previously unknown cell type, postsynaptic partners of KC dendrites, and unexpected clustering of olfactory projection neurons. These reconstructions show that this freely available EM volume supports mapping of brain-spanning circuits, which will significantly accelerate Drosophila neuroscience. VIDEO ABSTRACT.

Domain-Targeted Metabolomics Delineates the Heterocycle Assembly Steps of Colibactin Biosynthesis.

Modular polyketide synthases (PKSs) and nonribosomal peptide synthetases (NRPSs) comprise giant multidomain enzymes responsible for the "assembly line" biosynthesis of many genetically encoded small molecules. Site-directed mutagenesis, protein biochemical, and structural studies have focused on elucidating the catalytic mechanisms of individual multidomain proteins and protein domains within these megasynthases. However, probing their functions at the cellular level typically has invoked the complete deletion (or overexpression) of multidomain-encoding genes or combinations of genes and comparing those mutants with a control pathway. Here we describe a "domain-targeted" metabolomic strategy that combines genome editing with pathway analysis to probe the functions of individual PKS and NRPS catalytic domains at the cellular metabolic level. We apply the approach to the bacterial colibactin pathway, a genotoxic NRPS-PKS hybrid pathway found in certain Escherichia coli. The pathway produces precolibactins, which are converted to colibactins by a dedicated peptidase, ClbP. Domain-targeted metabolomics enabled the characterization of "multidomain signatures", or functional readouts of NRPS-PKS domain contributions to the pathway-dependent metabolome. These multidomain signatures provided experimental support for individual domain contributions to colibactin biosynthesis and delineated the assembly line timing events of colibactin heterocycle formation. The analysis also led to the structural characterization of two reactive precolibactin metabolites. We demonstrate the fate of these reactive intermediates in the presence and absence of ClbP, which dictates the formation of distinct product groups resulting from alternative cyclization cascades. In the presence of the peptidase, the reactive intermediates are converted to a known genotoxic scaffold, providing metabolic support of our mechanistic model for colibactin-induced genotoxicity. Domain-targeted metabolomics could be more widely used to characterize NRPS-PKS pathways with unprecedented genetic and metabolic precision.

Metabolite exchange between microbiome members produces compounds that influence Drosophila behavior.

Animals host multi-species microbial communities (microbiomes) whose properties may result from inter-species interactions; however, current understanding of host-microbiome interactions derives mostly from studies in which elucidation of microbe-microbe interactions is difficult. In exploring how Drosophila melanogaster acquires its microbiome, we found that a microbial community influences Drosophila olfactory and egg-laying behaviors differently than individual members. Drosophila prefers a Saccharomyces-Acetobacter co-culture to the same microorganisms grown individually and then mixed, a response mainly due to the conserved olfactory receptor, Or42b. Acetobacter metabolism of Saccharomyces-derived ethanol was necessary, and acetate and its metabolic derivatives were sufficient, for co-culture preference. Preference correlated with three emergent co-culture properties: ethanol catabolism, a distinct volatile profile, and yeast population decline. Egg-laying preference provided a context-dependent fitness benefit to larvae. We describe a molecular mechanism by which a microbial community affects animal behavior. Our results support a model whereby emergent metabolites signal a beneficial multispecies microbiome.

Linking Biosynthetic Gene Clusters to their Metabolites via Pathway- Targeted Molecular Networking.

The connection of microbial biosynthetic gene clusters to the small molecule metabolites they encode is central to the discovery and characterization of new metabolic pathways with ecological and pharmacological potential. With increasing microbial genome sequence information being deposited into publicly available databases, it is clear that microbes have the coding capacity for many more biologically active small molecules than previously realized. Of increasing interest are the small molecules encoded by the human microbiome, as these metabolites likely mediate a variety of currently uncharacterized human-microbe interactions that influence health and disease. In this mini-review, we describe the ongoing biosynthetic, structural, and functional characterizations of the genotoxic colibactin pathway in gut bacteria as a thematic example of linking biosynthetic gene clusters to their metabolites. We also highlight other natural products that are produced through analogous biosynthetic logic and comment on some current disconnects between bioinformatics predictions and experimental structural characterizations. Lastly, we describe the use of pathway-targeted molecular networking as a tool to characterize secondary metabolic pathways within complex metabolomes and to aid in downstream metabolite structural elucidation efforts.

Dynamical feature extraction at the sensory periphery guides chemotaxis.

Behavioral strategies employed for chemotaxis have been described across phyla, but the sensorimotor basis of this phenomenon has seldom been studied in naturalistic contexts. Here, we examine how signals experienced during free olfactory behaviors are processed by first-order olfactory sensory neurons (OSNs) of the Drosophila larva. We find that OSNs can act as differentiators that transiently normalize stimulus intensity-a property potentially derived from a combination of integral feedback and feed-forward regulation of olfactory transduction. In olfactory virtual reality experiments, we report that high activity levels of the OSN suppress turning, whereas low activity levels facilitate turning. Using a generalized linear model, we explain how peripheral encoding of olfactory stimuli modulates the probability of switching from a run to a turn. Our work clarifies the link between computations carried out at the sensory periphery and action selection underlying navigation in odor gradients.

Comparative metabolomics and structural characterizations illuminate colibactin pathway-dependent small molecules.

The gene cluster responsible for synthesis of the unknown molecule "colibactin" has been identified in mutualistic and pathogenic Escherichia coli. The pathway endows its producer with a long-term persistence phenotype in the human bowel, a probiotic activity used in the treatment of ulcerative colitis, and a carcinogenic activity under host inflammatory conditions. To date, functional small molecules from this pathway have not been reported. Here we implemented a comparative metabolomics and targeted structural network analyses approach to identify a catalog of small molecules dependent on the colibactin pathway from the meningitis isolate E. coli IHE3034 and the probiotic E. coli Nissle 1917. The structures of 10 pathway-dependent small molecules are proposed based on structural characterizations and network relationships. The network will provide a roadmap for the structural and functional elucidation of a variety of other small molecules encoded by the pathway. From the characterized small molecule set, in vitro bacterial growth inhibitory and mammalian CNS receptor antagonist activities are presented.

A red-shifted, fast-relaxing azobenzene photoswitch for visible light control of an ionotropic glutamate receptor.

The use of azobenzene photoswitches has become a dependable method for rapid and exact modulation of biological processes and material science systems. The requirement of ultraviolet light for azobenzene isomerization is not ideal for biological systems due to poor tissue penetration and potentially damaging effects. While modified azobenzene cores with a red-shifted cis-to-trans isomerization have been previously described, they have not yet been incorporated into a powerful method to control protein function: the photoswitchable tethered ligand (PTL) approach. We report the synthesis and characterization of a red-shifted PTL, L-MAG0460, for the light-gated ionotropic glutamate receptor LiGluR. In cultured mammalian cells, the LiGluR+L-MAG0460 system is activated rapidly by illumination with 400-520 nm light to generate a large ionic current. The current rapidly turns off in the dark as the PTL relaxes thermally back to the trans configuration. The visible light excitation and single-wavelength behavior considerably simplify use and should improve utilization in tissue.

A GAL4-driver line resource for Drosophila neurobiology.

We established a collection of 7,000 transgenic lines of Drosophila melanogaster. Expression of GAL4 in each line is controlled by a different, defined fragment of genomic DNA that serves as a transcriptional enhancer. We used confocal microscopy of dissected nervous systems to determine the expression patterns driven by each fragment in the adult brain and ventral nerve cord. We present image data on 6,650 lines. Using both manual and machine-assisted annotation, we describe the expression patterns in the most useful lines. We illustrate the utility of these data for identifying novel neuronal cell types, revealing brain asymmetry, and describing the nature and extent of neuronal shape stereotypy. The GAL4 lines allow expression of exogenous genes in distinct, small subsets of the adult nervous system. The set of DNA fragments, each driving a documented expression pattern, will facilitate the generation of additional constructs for manipulating neuronal function.