Christopher Salmon

There are now multiple Drosophila connectomes available, comprising both its brain and ‘spinal’ cord - comparing these connectomes requires first classifying neurons into cell types. Existing approaches for cell typing typically require extensive manual curation. Here we present a new method that automatically aligns connectomes via network topology alone. Using two complete male ventral nerve cord (VNC) connectomes as references, we assign cell types to ∼13,000 neurons intrinsic to the female VNC, and automatically identify sex-specific and sexually dimorphic cell types. We not only provide a comprehensive census of cell types across male and female nerve cords, but we uncover connectivity differences that underlie differences in function. We focus on circuits underlying song production in males and oviposition behaviors in females, and investigate the counterparts of these circuits across sexes. Our automated methods and analyses provide insights into sex differences in circuits that connect the brain and body, and pave the way for comparative connectomics at scale.

Just as genomes revolutionized molecular genetics, connectomes (maps of neurons and synapses) are transforming neuroscience. To date, the only species with complete connectomes are worms ^1-3 and sea squirts4 (10 ³ -10 ⁴ synapses). By contrast, the fruit fly is more complex (10 ⁸ synaptic connections), with a brain that supports learning and spatial memory ^5,6 and an intricate ventral nerve cord analogous to the vertebrate spinal cord ^7-11 . Here we report the first densely reconstructed adult fly connectome that unites the brain and ventral nerve cord, and we leverage this resource to investigate principles of neural control. We show that effector neurons (motor neurons, endocrine cells and efferent neurons targeting the viscera) are primarily influenced by sensory neurons in the same body part, forming local feedback loops. These local loops are linked by long-range circuits involving ascending and descending neurons organized into behavior-centric modules. Single ascending and descending neurons are often positioned to influence the voluntary movements of multiple body parts, together with the endocrine cells or visceral organs that support those movements. Brain regions involved in learning and navigation supervise these circuits. These results reveal an architecture that is distributed, parallelized and embodied, reminiscent of distributed control architectures in engineered systems ^12,13 .

Conditional expression of genes of interest is essential for interrogation of cellular development and function. Although tools exist for conditional gene expression, techniques for rapid-onset, temporally precise expression are lacking. The doxycyclineinducible TetOn expression system allows for this in numerous organ systems, however, transgenic TetOn expression cassettes become silenced in the nervous system during postnatal development. Here, we circumvent this silencing with uTTOP: in utero electroporation of Transposable TetOn Plasmids. When electroporated as transposable elements that integrate into the genome, the TetOn system allowed for robust DOX-dependent induction of expression across the postnatal lifespan of the mouse. We demonstrated induction in neurons of sensorimotor and retrospleninal cortex, hippocampus and the olfactory bulb. Latency to peak induction was ≤12 hours, a several fold increase in induction kinetics over existing methodology for in vivo conditional expression. To demonstrate the utility of uTTOP, we induced ectopic expression of Sonic hedgehog in adult mouse layer 2/3 cortical neurons, demonstrating that its expression can diversify expression of Kir4.1 in surrounding astrocytes. The rapid induction kinetics of uTTOP allowed us to show that Kir4.1 upregulation significantly lags onset of Shh expression by ∼2 days, a difference in expression time course that is likely not resolvable with current methods. Together, these data demonstrate that uTTOP is a powerful and flexible system for conditional gene expression in multiple brain areas across the mouse lifespan.

SUMMARY: Astrocytes have complex roles in central nervous system (CNS) health and disease. Underlying these roles is an elaborate architecture based on frequent, extremely fine, but seemingly haphazard branches, as well as prominent features including tripartite synaptic complexes and perivascular endfeet. While broad categories of structures in astrocytes are known, the fundamental building blocks that compose them and their organizing principles have yet to be adequately defined. This is largely due to the absence of high-resolution datasets that can reveal nanoscopic features of astrocytes (i.e. 10-20nm diameter in x, y, and z) and a lack of computational approaches that can effectively interrogate astrocyte shape, organization, and nanoarchitecture. Here, we produced and analyzed multiple, high-resolution datasets of layer 2/3 mouse somatosensory cortex using focused ion beam scanning electron microscopy (8nm intervals) and computer vision approaches to provide a principled, quantitative analysis of astrocytic nanoarchitecture. A decomposition of astrocytes into fundamental ‘parts’ led to the discovery of unique structural components, recurring structural motifs, and assembly of parts into an organized hierarchy. New relationships were also discerned between astrocytic processes and other CNS microanatomy including mitochondria, tripartite synapses, and cerebrovasculature. By deploying computational resources to quantitatively understand the organizing principles and nanoarchitecture of astrocytes, this study reveals the specialized anatomical adaptations of these complex cells within the CNS. One Sentence Summary: Using high-resolution serial electron microscopy datasets and computer vision, this study provides a systematic analysis of astrocytic nanoarchitecture from multiple samples of layer 2/3 of adult mouse neocortex, and presents quantitative evidence that astrocytes organize their morphology into purposeful, classifiable assemblies with unique structural and subcellular organelle adaptations related to their physiological functions.