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.

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The neural circuits responsible for animal behavior remain largely unknown. We 31 summarize new methods and present the circuitry of a large fraction of the brain of the fruit fly 32 Drosophila melanogaster. Improved methods include new procedures to prepare, image, align, 33 segment, find synapses in, and proofread such large data sets. We define cell types, refine 34 computational compartments, and provide an exhaustive atlas of cell examples and types, many of 35 them novel. We provide detailed circuits consisting of neurons and their chemical synapses for 36 most of the central brain. We make the data public and simplify access, reducing the effort needed 37 to answer circuit questions, and provide procedures linking the neurons defined by our analysis 38 with genetic reagents. Biologically, we examine distributions of connection strengths, neural motifs 39 on different scales, electrical consequences of compartmentalization, and evidence that 40 maximizing packing density is an important criterion in the evolution of the fly's brain. 41 1 of 57 53 Producing this data set required advances in sample preparation, imaging, image alignment, ma-54 chine segmentation of cells, synapse detection, data storage, proofreading software, and protocols 55 to arbitrate each decision. A number of new tests for estimating the completeness and accuracy 56 were required and therefore developed, in order to verify the correctness of the connectome. 57 These data describe whole-brain properties and circuits, as well as contain new methods to 58 classify cell types based on connectivity. Computational compartments are now more carefully 59 defined, we identify actual synaptic circuits, and each neuron is annotated by name and putative 60 cell type, making this the first complete census of neuropils, tracts, cells, and connections in this 61 2 of 57 Manuscript submitted to eLife Figure 2. Brain regions contained and defined in the hemibrain, following the naming conventions of (Ito et al., 2014) with the addition of (R) and (L) to specify the side of the soma for that region. Gray italics indicate master regions not explicitly defined in the hemibrain. Region LA is not included in the volume. The regions are hierarchical, with the more indented regions forming subsets of the less indented. The only exceptions are dACA, lACA, and vACA which are considered part of the mushroom body but are not contained in the master region MB.portion of the brain. We compare the statistics and structure of different brain regions, and for 62 the brain as a whole, without the confounds introduced by studying different circuitry in different 63 animals. 64 All data are publicly available through web interfaces. This includes a browser interface, Ne-65 uPrint (Clements et al., 2020), designed so that any interested user can query the hemibrain con-66 nectome even without specific training. NeuPrint can query the connectivity, partners, connection 67 strengths and morphologies of all specified neurons, thus making identifica...

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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.

We are exposed to millions of microbial and dietary antigens via the gastrointestinal tract, which likely play a key role in type 1 diabetes (T1D). We differentiated the effects of these two major environmental factors on gut immunity and T1D. Diabetes-prone BioBreeding (BBdp) rats were housed in specific pathogen-free (SPF) or germ-free (GF) conditions and weaned onto diabetes-promoting cereal diets or a protective low-antigen hydrolyzed casein (HC) diet, and T1D incidence was monitored. Fecal microbiota 16S rRNA genes, immune cell distribution, and gene expression in the jejunum were analyzed. T1D was highest in cereal-SPF (65%) and cereal-GF rats (53%) but inhibited and delayed in HC-fed counterparts. Nearly all HC-GF rats remained diabetes-free, whereas HC-fed SPF rats were less protected (7 vs. 29%). Bacterial communities differed in SPF rats fed cereal compared with HC. Cereal-SPF rats displayed increased gut CD3+ and CD8α+ lymphocytes, ratio of Ifng to Il4 mRNA, and Lck expression, indicating T-cell activation. The ratio of CD3+ T cells expressing the Treg marker Foxp3+ was highest in HC-GF and lowest in cereal-SPF rats. Resident CD163+ M2 macrophages were increased in HC-protected rats. The cathelicidin antimicrobial peptide (Camp) gene was upregulated in the jejunum of HC diet–protected rats, and CAMP+ cells colocalized with CD163. A cereal diet was a stronger promoter of T1D than gut microbes in association with impaired gut immune homeostasis.

Cathelicidin antimicrobial peptide (CAMP) is a naturally occurring secreted peptide that is expressed in several organs with pleiotropic roles in immunomodulation, wound healing, and cell growth. We previously demonstrated that gut Camp expression is upregulated when type 1 diabetes–prone rats are protected from diabetes development. Unexpectedly, we have also identified novel CAMP expression in the pancreatic β-cells of rats, mice, and humans. CAMP was present even in sterile rat embryo islets, germ-free adult rat islets, and neogenic tubular complexes. Camp gene expression was downregulated in young BBdp rat islets before the onset of insulitis compared with control BBc rats. CAMP treatment of dispersed islets resulted in a significant increase in intracellular calcium mobilization, an effect that was both delayed and blunted in the absence of extracellular calcium. Additionally, CAMP treatment promoted insulin and glucagon secretion from isolated rat islets. Thus, CAMP is a promoter of islet paracrine signaling that enhances islet function and glucoregulation. Finally, daily treatment with the CAMP/LL-37 peptide in vivo in BBdp rats resulted in enhanced β-cell neogenesis and upregulation of potentially beneficial gut microbes. In particular, CAMP/LL-37 treatment shifted the abundance of specific bacterial populations, mitigating the gut dysbiosis observed in the BBdp rat. Taken together, these findings indicate a novel functional role for CAMP/LL-37 in islet biology and modification of gut microbiota.

Choosing a mate is one of the most consequential decisions a female will make during her lifetime. This is particularly true for species in which females either mate repeatedly with the same partner or mate infrequently but use the sperm from a single copulation to fertilize eggs over an extended period of time. Drosophila melanogaster uses the latter strategy. Here, we characterize the neural circuitry that implements mating decisions in the female brain. A female fly signals her mating choice by opening her vaginal plates to allow a courting male to copulate1,2. Vaginal plate opening (VPO) occurs in response to the male courtship song and is dependent upon the female's mating status. We sought to understand how these exteroceptive (song) and interoceptive (mating status) inputs are integrated to control VPO. We show that VPO is triggered by a pair of female-specific descending neurons, the vpoDNs. The vpoDNs receive excitatory input from vpoEN auditory neurons, which are tuned to specific features of the melanogaster song. The song responses of vpoDNs, but not vpoENs, are attenuated upon mating, accounting for the reduced receptivity of mated females. This modulation is mediated by pC1 neurons, which encode the female’s mating status3,4 and also provide excitatory input to vpoDNs. The vpoDNs thus directly integrate the external and internal signals to control the mating decisions of Drosophila females.