The number of neurons in Drosophila and mosquito brains

Single nuclei RNA-sequencing of adult brain neurons derived from type 2 neuroblasts reveals transcriptional complexity in the insect central complex

In both Drosophila and mammals, the brain contains the most diverse population of cell types of any tissue. It is generally accepted that transcriptional diversity is an early step in generating neuronal and glial diversity, followed by the establishment of a unique gene expression profile that determines morphology, connectivity, and function. In Drosophila, there are two types of neural stem cells, called Type 1 (T1) and Type 2 (T2) neuroblasts. The diversity of T2-derived neurons contributes a large portion of the central complex (CX), a conserved brain region that plays a role in sensorimotor integration. Recent work has revealed much of the connectome of the CX, but how this connectome is assembled remains unclear. Mapping the transcriptional diversity of T2-derived neurons is a necessary step in linking transcriptional profile to the assembly of the adult brain. Here we perform single nuclei RNA sequencing of T2 neuroblast-derived adult neurons and glia. We identify clusters containing all known classes of glia, clusters that are male/female enriched, and 161 neuron-specific clusters. We map neurotransmitter and neuropeptide expression and identify unique transcription factor combinatorial codes for each cluster. This is a necessary step that directs functional studies to determine whether each transcription factor combinatorial code specifies a distinct neuron type within the CX. We map several columnar neuron subtypes to distinct clusters and identify two neuronal classes (NPF+ and AstA+) that both map to two closely related clusters. Our data support the hypothesis that each transcriptional cluster represents one or a few closely related neuron subtypes.

Inactivation of Laforin Phosphatase and Increased Glucose Uptake Underlie Glycogen Synthase-Mediated Neuronal Survival Under Oxidative Stress

Recent studies demonstrate that exposure of neurons to physiological stressors triggers glycogen synthase (GS) activation and glycogen synthesis as a transient cell survival mechanism. However, the mechanisms that regulate glycogen synthesis during stress and its role in neuronal physiology remain unclear. This study investigated the mechanisms that guide GS activation and glycogen accumulation under oxidative stress conditions as a model stressor. We use neuronal cell lines to demonstrate that hydrogen peroxide-induced oxidative stress activates GS and glycogen synthesis in neuronal cells. We further demonstrate that the stress-induced glycogen accumulation is dependent on the membrane localization of the Glut3 glucose transporters and increased glucose uptake during stress. The stress-induced activation of glycogen synthesis, however, is independent of intracellular glucose level, suggesting a parallel mechanism for activating GS and glucose uptake in neurons under physiological stress. We demonstrate that oxidative stress results in the inactivation of laforin phosphatase, leading to the membrane localization of Glut3 and activation of GS. Using the Drosophila model, we demonstrate that increased GS activity and concomitant glycogen accumulation are pro-survival mechanisms for neurons under oxidative stress. Our study thus offers novel insights into the pathways that regulate glycogen metabolism in neurons under oxidative stress and underscores their importance for neuronal survival.

Transcriptional complexity in the insect central complex: single nuclei RNA-sequencing of adult brain neurons derived from type 2 neuroblasts

In both invertebrates such as Drosophila and vertebrates such as mouse or human, the brain contains the most diverse population of cell types of any tissue. It is generally accepted that transcriptional diversity is an early step in generating neuronal and glial diversity, followed by the establishment of a unique gene expression profile that determines morphology, connectivity, and function. In Drosophila, there are two types of neural stem cells, called Type 1 (T1) and Type 2 (T2) neuroblasts. In contrast to T1 neuroblasts, T2 neuroblasts generate intermediate neural progenitors (INPs) that expand the number and diversity of cell types. The diversity of T2-derived neurons contributes a large portion of the central complex (CX), a conserved brain region that plays a role in sensorimotor integration. Recent work has revealed much of the connectome of the CX, but how this connectome is assembled remains unclear. Mapping the transcriptional diversity of neurons derived from T2 neuroblasts is a necessary step in linking transcriptional profile to the assembly of the adult brain. Here we perform single nuclei RNA sequencing of T2 neuroblast-derived adult neurons and glia. We identify clusters containing all known classes of glia, clusters that are male/female enriched, and 161 neuron-specific clusters. We map neurotransmitter and neuropeptide expression and identify unique transcription factor combinatorial codes for each cluster (presumptive neuron subtype). This is a necessary step that directs functional studies to determine whether each transcription factor combinatorial code specifies a distinct neuron type within the CX. We map several columnar neuron subtypes to distinct clusters and identify two neuronal classes (NPF+ and AstA+) that both map to two closely related clusters. Our data support the hypothesis that each transcriptional cluster represents one or a few closely related neuron subtypes.

Molecular profiling of invertebrate glia

Caenorhabditis elegans and Drosophila melanogaster are powerful experimental models for uncovering fundamental tenets of nervous system organization and function. Findings over the last two decades show that molecular and cellular features are broadly conserved between invertebrates and vertebrates, indicating that insights derived from invertebrate models can broadly inform our understanding of glial operating principles across diverse species. In recent years, these model systems have led to exciting discoveries in glial biology and mechanisms of glia-neuron interactions. Here, we summarize studies that have applied current state-of-the-art "-omics" techniques to C. elegans and D. melanogaster glia. Coupled with the remarkable acceleration in the pace of mechanistic studies of glia biology in recent years, these indicate that invertebrate glia also exhibit striking molecular complexity, specificity, and heterogeneity. We provide an overview of these studies and discuss their implications as well as emerging questions where C. elegans and D. melanogaster are well-poised to fill critical knowledge gaps in our understanding of glial biology.

Mosquito Cell Atlas: A single-nucleus transcriptomic atlas of the adult Aedes aegypti mosquito

The female mosquito's remarkable ability to hunt humans and transmit pathogens relies on her unique biology. Here, we present the Mosquito Cell Atlas (MCA), a comprehensive single-nucleus RNA sequencing dataset of more than 367,000 nuclei from 19 dissected tissues of adult female and male Aedes aegypti, providing cellular-level resolution of mosquito biology. We identify novel cell types and expand our understanding of sensory neuron organization of chemoreceptors to all sensory tissues. Our analysis uncovers male-specific cells and sexually dimorphic gene expression in the antenna and brain. In female mosquitoes, we find that glial cells in the brain, rather than neurons, undergo the most extensive transcriptional changes following blood feeding. Our findings provide insights into the cellular basis of mosquito behavior and sexual dimorphism. The MCA aims to serve as a resource for the vector biology community, enabling systematic investigation of cell-type specific expression across all mosquito tissues.

The unbearable slowness of being: Why do we live at 10 bits/s?

This article is about the neural conundrum behind the slowness of human behavior. The information throughput of a human being is about 10 bits/s. In comparison, our sensory systems gather data at ∼109 bits/s. The stark contrast between these numbers remains unexplained and touches on fundamental aspects of brain function: what neural substrate sets this speed limit on the pace of our existence? Why does the brain need billions of neurons to process 10 bits/s? Why can we only think about one thing at a time? The brain seems to operate in two distinct modes: the "outer" brain handles fast high-dimensional sensory and motor signals, whereas the "inner" brain processes the reduced few bits needed to control behavior. Plausible explanations exist for the large neuron numbers in the outer brain, but not for the inner brain, and we propose new research directions to remedy this.

Rigid propagation of visual motion in the insect's neural system

In the pursuit of developing an efficient artificial visual system for visual motion detection, researchers find inspiration from the visual motion-sensitive neural pathways in the insect's neural system. Although multiple proposed neural computational models exhibit significant performance aligned with those observed from insects, the mathematical basis for how these models characterize the sensitivity of visual neurons to corresponding motion patterns remains to be elucidated. To fill this research gap, this study originally proposed that the rigid propagation of visual motion is an essential mathematical property of the models for the insect's visual neural system, meaning that the dynamics of the model output remain consistent with the visual motion dynamics reflected in the input. To verify this property, this study uses the small target motion detector (STMD) neural pathway - one of the visual motion-sensitive pathways in the insect's neural system - as an exemplar, rigorously demonstrating that the dynamics of translational visual motion are rigidly propagated through the encoding of retinal measurements in STMD computational models. Numerical experiment results further substantiate the proposed property of STMD models. This study offers a novel theoretical framework for exploring the nature of the visual motion perception underlying the insect's visual neural system and brings an innovative perspective to the broader research field of insect visual motion perception and artificial visual systems.

NeuroMechFly v2: simulating embodied sensorimotor control in adult Drosophila

Discovering principles underlying the control of animal behavior requires a tight dialogue between experiments and neuromechanical models. Such models have primarily been used to investigate motor control with less emphasis on how the brain and motor systems work together during hierarchical sensorimotor control. NeuroMechFly v2 expands Drosophila neuromechanical modeling by enabling vision, olfaction, ascending motor feedback and complex terrains that can be navigated using leg adhesion. We illustrate its capabilities by constructing biologically inspired controllers that use ascending feedback to perform path integration and head stabilization. After adding vision and olfaction, we train a controller using reinforcement learning to perform a multimodal navigation task. Finally, we illustrate more bio-realistic modeling involving complex odor plume navigation, and fly-fly following using a connectome-constrained visual network. NeuroMechFly can be used to accelerate the discovery of explanatory models of the nervous system and to develop machine learning-based controllers for autonomous artificial agents and robots.

Unique tau- and synuclein-dependent metabolic reprogramming in neurons distinct from normal aging

Neuronal cells are highly specialized cells and have a specific metabolic profile to support their function. It has been demonstrated that the metabolic profiles of different cells/tissues undergo significant reprogramming with advancing age, which has often been considered a contributing factor towards aging-related diseases including Alzheimer's (AD) and Parkinson's (PD) diseases. However, it is unclear if the metabolic changes associated with normal aging predispose neurons to disease conditions or a distinct set of metabolic alterations happen in neurons in AD or PD which might contribute to disease pathologies. To decipher the changes in neuronal metabolism with age, in AD, or in PD, we performed high-throughput steady-state metabolite profiling on heads in wildtype Drosophila and in Drosophila models relevant to AD and PD. Intriguingly, we found that the spectrum of affected metabolic pathways is dramatically different between normal aging, Tau, or Synuclein overexpressing neurons. Genetic targeting of the purine and glutamate metabolism pathways, which were dysregulated in both old age and disease conditions partially rescued the neurodegenerative phenotype associated with the overexpression of wildtype and mutant tau. Our findings support a "two-hit model" to explain the pathological manifestations associated with AD where both aging- and Tau/Synuclein- driven metabolic reprogramming events cooperate with each other, and targeting both could be a potent therapeutic strategy.

The RNA exosome maintains cellular RNA homeostasis by controlling transcript abundance in the brain

Intracellular ribonucleases (RNases) are essential in all aspects of RNA metabolism, including maintaining accurate RNA levels. Inherited mutations in genes encoding ubiquitous RNases are associated with human diseases, primarily affecting the nervous system. Recessive mutations in genes encoding an evolutionarily conserved RNase complex, the RNA exosome, lead to syndromic neurodevelopmental disorders characterized by progressive neurodegeneration, such as Pontocerebellar Hypoplasia Type 1b (PCH1b). We establish a CRISPR/Cas9-engineered Drosophila model of PCH1b to study cell-type-specific post-transcriptional regulatory functions of the nuclear RNA exosome complex within fly head tissue. Here, we report that pathogenic RNA exosome mutations alter activity of the complex, causing widespread dysregulation of brain-enriched cellular transcriptomes, including rRNA processing defects-resulting in tissue-specific, progressive neurodegenerative effects in flies. These findings provide a comprehensive understanding of RNA exosome function within a developed animal brain and underscore the critical role of post-transcriptional regulatory machinery in maintaining cellular RNA homeostasis within the brain.

Reminiscences on the honeybee genome project and the rise of epigenetic concepts in insect science

The sequencing of the honeybee genome in 2006 was an important technological and logistic achievement experience. But what benefits have flown from the honeybee genome project? What does the annotated genomic assembly mean for the study of behavioural complexity and organismal function in honeybees? Here, I discuss several lines of research that have arisen from this project and highlight the rapidly expanding studies on insect epigenomics, emergent properties of royal jelly, the mechanism of nutritional control of development and the contribution of epigenomic regulation to the evolution of sociality. I also argue that the term 'insect epigenetics' needs to be carefully redefined to reflect the diversity of epigenomic toolkits in insects and the impact of lineage-specific innovations on organismal outcomes. The honeybee genome project helped pioneer advances in social insect molecular biology, and fuelled breakthrough research into the role of flexible epigenomic control systems in linking genotype to phenotype.

Interactions of drosophila cryptochrome

In this study, we investigate the intricate regulatory mechanisms underlying the circadian clock in Drosophila, focusing on the light-induced conformational changes in the cryptochrome (DmCry). Upon light exposure, DmCry undergoes conformational changes that prompt its binding to Timeless and Jetlag proteins, initiating a cascade crucial for the starting of a new circadian cycle. DmCry is subsequently degraded, contributing to the desensitization of the resetting mechanism. The transient and short-lived nature of DmCry protein-protein interactions (PPIs), leading to DmCry degradation within an hour of light exposure, presents a challenge for comprehensive exploration. To address this, we employed proximity-dependent biotinylation techniques, combining engineered BioID (TurboID) and APEX (APEX2) enzymes with mass spectrometry. This approach enabled the identification of the in vitro DmCry interactome in Drosophila S2 cells, uncovering several novel PPIs associated with DmCry. Validation of these interactions through a novel co-immunoprecipitation technique enhances the reliability of our findings. Importantly, our study suggests the potential of this method to reveal additional circadian clock- or magnetic field-dependent PPIs involving DmCry. This exploration of the DmCry interactome not only advances our understanding of circadian clock regulation but also establishes a versatile framework for future investigations into light- and time-dependent protein interactions in Drosophila.

Olfactory learning in Pieris brassicae butterflies is dependent on the intensity of a plant-derived oviposition cue

Butterflies, like many insects, use gustatory and olfactory cues innately to assess the suitability of an oviposition site and are able to associate colours and leaf shapes with an oviposition reward. Studies on other insects have demonstrated that the quality of the reward is a crucial factor in forming associative memory. We set out to investigate whether the large cabbage white Pieris brassicae (Linnaeus) has the ability to associate an oviposition experience with a neutral olfactory cue. In addition, we tested whether the strength of this association is dependent on the gustatory response to the glucosinolate sinigrin, which is a known oviposition stimulus for P. brassicae. Female butterflies were able to associate a neutral odour with an oviposition experience after a single oviposition experience, both in a greenhouse and in a semi-natural outdoor setting. Moreover, butterflies performed best when trained with concentrations of sinigrin that showed the strongest response by specific gustatory neurons on the forelegs. Our study provides novel insight into the role of both gustatory and olfactory cues during oviposition learning in lepidopterans and contributes to a better understanding of how these insects might be able to adapt to a rapidly changing environment.

Neural mechanism of circadian clock-based photoperiodism in insects and snails

The photoperiodic mechanism distinguishes between long and short days, and the circadian clock system is involved in this process. Although the necessity of circadian clock genes for photoperiodic responses has been demonstrated in many species, how the clock system contributes to photoperiodic mechanisms remains unclear. A comprehensive study, including the functional analysis of relevant genes and physiology of their expressing cells, is necessary to understand the molecular and cellular mechanisms. Since Drosophila melanogaster exhibits a shallow photoperiodism, photoperiodic mechanisms have been studied in non-model species, starting with brain microsurgery and neuroanatomy, followed by genetic manipulation in some insects. Here, we review and discuss the involvement of the circadian clock in photoperiodic mechanisms in terms of neural networks in insects. We also review recent advances in the neural mechanisms underlying photoperiodic responses in insects and snails, and additionally circadian clock systems in snails, whose involvement in photoperiodism has hardly been addressed yet. Brain neurosecretory cells, insulin-like peptide/diuretic hormone44-expressing pars intercerebralis neurones in the bean bug Riptortus pedestris and caudo-dorsal cell hormone-expressing caudo-dorsal cells in the snail Lymnaea stagnalis, both promote egg laying under long days, and their electrical excitability is attenuated under short and medium days, which reduces oviposition. The photoperiodic responses of the pars intercerebralis neurones are mediated by glutamate under the control of the clock gene period. Thus, we are now able to assess the photoperiodic response by neurosecretory cell activity to investigate the upstream mechanisms, that is, the photoperiodic clock and counter.

Irreducible Complexity of Hox Gene: Path to the Canonical Function of the Hox Cluster

The evolution of major taxa is often associated with the emergence of new gene families. In all multicellular animals except sponges and comb jellies, the genomes contain Hox genes, which are crucial regulators of development. The canonical function of Hox genes involves colinear patterning of body parts in bilateral animals. This general function is implemented through complex, precisely coordinated mechanisms, not all of which are evolutionarily conserved and fully understood. We suggest that the emergence of this regulatory complexity was preceded by a stage of cooperation between more ancient morphogenetic programs or their individual elements. Footprints of these programs may be present in modern animals to execute non-canonical Hox functions. Non-canonical functions of Hox genes are involved in maintaining terminal nerve cell specificity, autophagy, oogenesis, pre-gastrulation embryogenesis, vertical signaling, and a number of general biological processes. These functions are realized by the basic properties of homeodomain protein and could have triggered the evolution of ParaHoxozoa and Nephrozoa subsequently. Some of these non-canonical Hox functions are discussed in our review.

Exposure to Bisphenol F and Bisphenol S during development induces autism-like endophenotypes in adult Drosophila melanogaster

Bisphenol F (BPF) and Bisphenol S (BPS) are being widely used by the industry with the claim of "safer substances", even with the scarcity of toxicological studies. Given the etiological gap of autism spectrum disorder (ASD), the environment may be a causal factor, so we investigated whether exposure to BPF and BPS during the developmental period can induce ASD-like modeling in adult flies. Drosophila melanogaster flies were exposed during development (embryonic and larval period) to concentrations of 0.25, 0.5, and 1 mM of BPF and BPS, separately inserted into the food. When they transformed into pupae were transferred to a standard diet, ensuring that the flies (adult stage) did not have contact with bisphenols. Thus, after hatching, consolidated behavioral tests were carried out for studies with ASD-type models in flies. It was observed that 1 mM BPF and BPS caused hyperactivity (evidenced by open-field test, negative geotaxis, increased aggressiveness and reproduction of repetitive behaviors). The flies belonging to the 1 mM groups of BPF and BPS also showed reduced cognitive capacity, elucidated by the learning behavior through aversive stimulus. Within the population dynamics that flies exposed to 1 mM BPF and 0.5 and 1 mM BPS showed a change in social interaction, remaining more distant from each other. Exposure to 1 mM BPF, 0.5 and 1 mM BPS increased brain size and reduced Shank immunoreactivity of adult flies. These findings complement each other and show that exposure to BPF and BPS during the development period can elucidate a model with endophenotypes similar to ASD in adult flies. Furthermore, when analyzing comparatively, BPS demonstrated a greater potential for damage when compared to BPF. Therefore, in general these data sets contradict the idea that these substances can be used freely.

Deciphering the cellular heterogeneity of the insect brain with single-cell RNA sequencing

Insects show highly complicated adaptive and sophisticated behaviors, including spatial orientation skills, learning ability, and social interaction. These behaviors are controlled by the insect brain, the central part of the nervous system. The tiny insect brain consists of millions of highly differentiated and interconnected cells forming a complex network. Decades of research has gone into an understanding of which parts of the insect brain possess particular behaviors, but exactly how they modulate these functional consequences needs to be clarified. Detailed description of the brain and behavior is required to decipher the complexity of cell types, as well as their connectivity and function. Single-cell RNA-sequencing (scRNA-seq) has emerged recently as a breakthrough technology to understand the transcriptome at cellular resolution. With scRNA-seq, it is possible to uncover the cellular heterogeneity of brain cells and elucidate their specific functions and state. In this review, we first review the basic structure of insect brains and the links to insect behaviors mainly focusing on learning and memory. Then the scRNA applications on insect brains are introduced by representative studies. Single-cell RNA-seq has allowed researchers to classify cell subpopulations within different insect brain regions, pinpoint single-cell developmental trajectories, and identify gene regulatory networks. These developments empower the advances in neuroscience and shed light on the intricate problems in understanding insect brain functions and behaviors.

A cell atlas of the larval Aedes aegypti ventral nerve cord

Mosquito-borne diseases account for nearly 1 million human deaths annually, yet we have a limited understanding of developmental events that influence host-seeking behavior and pathogen transmission in mosquitoes. Mosquito-borne pathogens are transmitted during blood meals, hence adult mosquito behavior and physiology have been intensely studied. However, events during larval development shape adult traits, larvae respond to many of the same sensory cues as adults, and larvae are susceptible to infection by many of the same disease-causing agents as adults. Hence, a better understanding of larval physiology will directly inform our understanding of physiological processes in adults. Here, we use single cell RNA sequencing (scRNA-seq) to provide a comprehensive view of cellular composition in the Aedes aegypti larval ventral nerve cord (VNC), a central hub of sensory inputs and motor outputs which additionally controls multiple aspects of larval physiology. We identify more than 35 VNC cell types defined in part by neurotransmitter and neuropeptide expression. We also explore diversity among monoaminergic and peptidergic neurons that likely control key elements of larval physiology and developmental timing, and identify neuroblasts and immature neurons, providing a view of neuronal differentiation in the VNC. Finally, we find that larval cell composition, number, and position are preserved in the adult abdominal VNC, suggesting studies of larval VNC form and function will likely directly inform our understanding adult mosquito physiology. Altogether, these studies provide a framework for targeted analysis of VNC development and neuronal function in Aedes aegypti larvae.

Brain size scaling through development in the whitelined sphinx moth (Hyles lineata) shows mass and cell number comparable to flies, bees, and wasps

Factors regulating larval growth and determinants of adult body size are described for several holometabolous insects, but less is known about brain size scaling through development. Here we use the isotropic fractionation ("brain soup") method to estimate the number of brain cells and cell density for the whitelined sphinx moth (Lepidoptera: Hyles lineata) from the first instar through the adult stage. We measure mass and brain cell number and find that, during the larval stages, body mass shows an exponential relationship with head width, while the total number of brain cells increases asymptotically. Larval brain cell number increases by a factor of ten from nearly 8000 in the first instar to over 80,000 in the fifth instar. Brain cell number increases by another factor of 10 during metamorphosis, with the adult brain containing more than 900,000 cells. This is similar to increases during development in the vinegar fly (Drosophila melanogaster) and the black soldier fly (Hermetia illucens). The adult brain falls slightly below the brain-to-body allometry for wasps and bees but is comparable in the number of cells per unit brain mass, indicating a general conservation of brain cell density across these divergent lineages.

A Miniature Ultrasound Source for Neural Modulation

This work describes a unique ultrasound (US) exposure system designed to create very localized ( [Formula: see text]) sound fields at operating frequencies that are currently being used for preclinical US neuromodulation. This system can expose small clusters of neuronal tissue, such as cell cultures or intact brain structures in target animal models, opening up opportunities to examine possible mechanisms of action. We modified a dental descaler and drove it at a resonance frequency of 96 kHz, well above its nominal operating point of 28 kHz. A ceramic microtip from an ultrasonic wire bonder was attached to the end of the applicator, creating a 100- [Formula: see text] point source. The device was calibrated with a polyvinylidene difluoride (PVDF) membrane hydrophone, in a novel, air-backed, configuration. The experimental results were confirmed by simulation using a monopole model. The results show a consistent decaying sound field from the tip, well-suited to neural stimulation. The system was tested on an existing neurological model, Drosophila melanogaster, which has not previously been used for US neuromodulation experiments. The results show brain-directed US stimulation induces or suppresses motor actions, demonstrated through synchronized tracking of fly limb movements. These results provide the basis for ongoing and future studies of US interaction with neuronal tissue, both at the level of single neurons and intact organisms.

Descending neurons of the hoverfly respond to pursuits of artificial targets

Many animals use motion vision information to control dynamic behaviors. Predatory animals, for example, show an exquisite ability to detect rapidly moving prey, followed by pursuit and capture. Such target detection is not only used by predators but is also important in conspecific interactions, such as for male hoverflies defending their territories against conspecific intruders. Visual target detection is believed to be subserved by specialized target-tuned neurons found in a range of species, including vertebrates and arthropods. However, how these target-tuned neurons respond to actual pursuit trajectories is currently not well understood. To redress this, we recorded extracellularly from target-selective descending neurons (TSDNs) in male Eristalis tenax hoverflies. We show that they have dorso-frontal receptive fields with a preferred direction up and away from the visual midline. We reconstructed visual flow fields as experienced during pursuits of artificial targets (black beads). We recorded TSDN responses to six reconstructed pursuits and found that each neuron responded consistently at remarkably specific time points but that these time points differed between neurons. We found that the observed spike probability was correlated with the spike probability predicted from each neuron's receptive field and size tuning. Interestingly, however, the overall response rate was low, with individual neurons responding to only a small part of each reconstructed pursuit. In contrast, the TSDN population responded to substantially larger proportions of the pursuits but with lower probability. This large variation between neurons could be useful if different neurons control different parts of the behavioral output.

Associative learning in the box jellyfish Tripedalia cystophora

Associative learning, such as classical or operant conditioning, has never been unequivocally associated with animals outside bilatarians, e.g., vertebrates, arthropods, or mollusks. Learning modulates behavior and is imperative for survival in the vast majority of animals. Obstacle avoidance is one of several visually guided behaviors in the box jellyfish, Tripedalia cystophora Conant, 1897 (Cnidaria: Cubozoa), and it is intimately associated with foraging between prop roots in their mangrove habitat. The obstacle avoidance behavior (OAB) is a species-specific defense reaction (SSDR) for T. cystophora, so identifying such SSDR is essential for testing the learning capacity of a given animal. Using the OAB, we show that box jellyfish performed associative learning (operant conditioning). We found that the rhopalial nervous system is the learning center and that T. cystophora combines visual and mechanical stimuli during operant conditioning. Since T. cystophora has a dispersed central nervous system lacking a conventional centralized brain, our work challenges the notion that associative learning requires complex neuronal circuitry. Moreover, since Cnidaria is the sister group to Bilateria, it suggests the intriguing possibility that advanced neuronal processes, like operant conditioning, are a fundamental property of all nervous systems.

A rapid and dynamic role for FMRP in the plasticity of adult neurons

Fragile X syndrome (FXS) is a neuro-developmental disorder caused by silencing Fmr1, which encodes the RNA-binding protein FMRP. Although Fmr1 is expressed in adult neurons, it has been challenging to separate acute from chronic effects of loss of Fmr1 in models of FXS. We have used the precision of Drosophila genetics to test if Fmr1 acutely affects adult neuronal plasticity in vivo, focusing on the s-LNv circadian pacemaker neurons that show 24 hour rhythms in structural plasticity. We found that over-expressing Fmr1 for only 4 hours blocks the activity-dependent expansion of s-LNv projections without altering the circadian clock or activity-regulated gene expression. Conversely, acutely reducing Fmr1 expression prevented s-LNv projections from retracting. One FMRP target that we identified in s-LNvs is sif, which encodes a Rac1 GEF. Our data indicate that FMRP normally reduces sif mRNA translation at dusk to reduce Rac1 activity. Overall, our data reveal a previously unappreciated rapid and direct role for FMRP in acutely regulating neuronal plasticity in adult neurons, and underscore the importance of RNA-binding proteins in this process.

Unique morphology and photoperiodically regulated activity of neurosecretory canopy cells in the pond snail Lymnaea stagnalis

The pond snail Lymnaea stagnalis exhibits clear photoperiodism in egg laying; it lays more eggs in long-day conditions than in medium-day conditions. A key regulator of egg laying is neurosecretory caudo-dorsal cells (CDCs) producing an ovulation hormone in the cerebral ganglia. Paired small budding structures of the cerebral ganglia (viz. the lateral lobe) also promote egg laying in addition to spermatogenesis and maturation of female accessory sex organs. However, it remains unknown which cells in the lateral lobe are responsible for these. Previous anatomical and physiological studies prompted us to hypothesize that canopy cells in the lateral lobe modulate activity of CDCs. However, double labeling of the canopy cell and CDCs revealed no sign of direct neural connections, suggesting that activity of CDCs is regulated either humorally or through a neural pathway independent of canopy cells. In addition, our detailed anatomical re-evaluation confirmed previous observations that the canopy cell bears fine neurites along the ipsilateral axon and extensions from the plasma membrane of the cell body, although the function of these extensions remains unexplored. Furthermore, comparison of electrophysiological properties between long-day and medium-day conditions indicated that the canopy cell's activity is moderately under photoperiodic regulation: resting membrane potentials of long-day snails are shallower than those of medium-day snails, and spontaneously spiking neurons are only observed in long-day conditions. Thus, canopy cells appear to receive photoperiodic information and regulate photoperiod-dependent phenomena, but not provide direct neural inputs to CDCs.

How Flies See Motion

How neurons detect the direction of motion is a prime example of neural computation: Motion vision is found in the visual systems of virtually all sighted animals, it is important for survival, and it requires interesting computations with well-defined linear and nonlinear processing steps-yet the whole process is of moderate complexity. The genetic methods available in the fruit fly Drosophila and the charting of a connectome of its visual system have led to rapid progress and unprecedented detail in our understanding of how neurons compute the direction of motion in this organism. The picture that emerged incorporates not only the identity, morphology, and synaptic connectivity of each neuron involved but also its neurotransmitters, its receptors, and their subcellular localization. Together with the neurons' membrane potential responses to visual stimulation, this information provides the basis for a biophysically realistic model of the circuit that computes the direction of visual motion.

Sleep is required to consolidate odor memory and remodel olfactory synapses

Animals with complex nervous systems demand sleep for memory consolidation and synaptic remodeling. Here, we show that, although the Caenorhabditis elegans nervous system has a limited number of neurons, sleep is necessary for both processes. In addition, it is unclear if, in any system, sleep collaborates with experience to alter synapses between specific neurons and whether this ultimately affects behavior. C. elegans neurons have defined connections and well-described contributions to behavior. We show that spaced odor-training and post-training sleep induce long-term memory. Memory consolidation, but not acquisition, requires a pair of interneurons, the AIYs, which play a role in odor-seeking behavior. In worms that consolidate memory, both sleep and odor conditioning are required to diminish inhibitory synaptic connections between the AWC chemosensory neurons and the AIYs. Thus, we demonstrate in a living organism that sleep is required for events immediately after training that drive memory consolidation and alter synaptic structures.

The influence of age and sex on the absolute cell numbers of the human brain cerebral cortex

The human cerebral cortex is one of the most evolved regions of the brain, responsible for most higher-order neural functions. Since nerve cells (together with synapses) are the processing units underlying cortical physiology and morphology, we studied how the human neocortex is composed regarding the number of cells as a function of sex and age. We used the isotropic fractionator for cell quantification of immunocytochemically labeled nuclei from the cerebral cortex donated by 43 cognitively healthy subjects aged 25-87 years old. In addition to previously reported sexual dimorphism in the medial temporal lobe, we found more neurons in the occipital lobe of men, higher neuronal density in women's frontal lobe, but no sex differences in the number and density of cells in the other lobes and the whole neocortex. On average, the neocortex has ~10.2 billion neurons, 34% in the frontal lobe and the remaining 66% uniformly distributed among the other 3 lobes. Along typical aging, there is a loss of non-neuronal cells in the frontal lobe and the preservation of the number of neurons in the cortex. Our study made possible to determine the different degrees of modulation that sex and age evoke on cortical cellularity.

Pain: The agony and the AstC

Pain serves critical biological functions, but under some circumstances it is best suppressed. A new study identifies a channel, a neuropeptide, and a pair of neurons in the fly brain that suppress pain.

Visual processing in the fly, from photoreceptors to behavior

Originally a genetic model organism, the experimental use of Drosophila melanogaster has grown to include quantitative behavioral analyses, sophisticated perturbations of neuronal function, and detailed sensory physiology. A highlight of these developments can be seen in the context of vision, where pioneering studies have uncovered fundamental and generalizable principles of sensory processing. Here we begin with an overview of vision-guided behaviors and common methods for probing visual circuits. We then outline the anatomy and physiology of brain regions involved in visual processing, beginning at the sensory periphery and ending with descending motor control. Areas of focus include contrast and motion detection in the optic lobe, circuits for visual feature selectivity, computations in support of spatial navigation, and contextual associative learning. Finally, we look to the future of fly visual neuroscience and discuss promising topics for further study.

Generative network modeling reveals quantitative definitions of bilateral symmetry exhibited by a whole insect brain connectome

Comparing connectomes can help explain how neural connectivity is related to genetics, disease, development, learning, and behavior. However, making statistical inferences about the significance and nature of differences between two networks is an open problem, and such analysis has not been extensively applied to nanoscale connectomes. Here, we investigate this problem via a case study on the bilateral symmetry of a larval Drosophila brain connectome. We translate notions of 'bilateral symmetry' to generative models of the network structure of the left and right hemispheres, allowing us to test and refine our understanding of symmetry. We find significant differences in connection probabilities both across the entire left and right networks and between specific cell types. By rescaling connection probabilities or removing certain edges based on weight, we also present adjusted definitions of bilateral symmetry exhibited by this connectome. This work shows how statistical inferences from networks can inform the study of connectomes, facilitating future comparisons of neural structures.

In Defense of Modular Thinking

In this issue, Pessoa emphasizes the importance of viewing neural activity from a perspective that functional networks form dynamically in a way that dramatically changes the functional contribution of individual brain areas. In this response, I argue that we should strive toward pluralism in understanding neural activity at both the emergent network and modular levels, on the bases that a purely emergent understanding would be incomplete, and that there are computational advantages to anatomically stable modularity.

A searchable image resource of Drosophila GAL4 driver expression patterns with single neuron resolution

Precise, repeatable genetic access to specific neurons via GAL4/UAS and related methods is a key advantage of Drosophila neuroscience. Neuronal targeting is typically documented using light microscopy of full GAL4 expression patterns, which generally lack the single-cell resolution required for reliable cell type identification. Here, we use stochastic GAL4 labeling with the MultiColor FlpOut approach to generate cellular resolution confocal images at large scale. We are releasing aligned images of 74,000 such adult central nervous systems. An anticipated use of this resource is to bridge the gap between neurons identified by electron or light microscopy. Identifying individual neurons that make up each GAL4 expression pattern improves the prediction of split-GAL4 combinations targeting particular neurons. To this end, we have made the images searchable on the NeuronBridge website. We demonstrate the potential of NeuronBridge to rapidly and effectively identify neuron matches based on morphology across imaging modalities and datasets.

Efficient parameter calibration and real-time simulation of large-scale spiking neural networks with GeNN and NEST

Spiking neural networks (SNNs) represent the state-of-the-art approach to the biologically realistic modeling of nervous system function. The systematic calibration for multiple free model parameters is necessary to achieve robust network function and demands high computing power and large memory resources. Special requirements arise from closed-loop model simulation in virtual environments and from real-time simulation in robotic application. Here, we compare two complementary approaches to efficient large-scale and real-time SNN simulation. The widely used NEural Simulation Tool (NEST) parallelizes simulation across multiple CPU cores. The GPU-enhanced Neural Network (GeNN) simulator uses the highly parallel GPU-based architecture to gain simulation speed. We quantify fixed and variable simulation costs on single machines with different hardware configurations. As a benchmark model, we use a spiking cortical attractor network with a topology of densely connected excitatory and inhibitory neuron clusters with homogeneous or distributed synaptic time constants and in comparison to the random balanced network. We show that simulation time scales linearly with the simulated biological model time and, for large networks, approximately linearly with the model size as dominated by the number of synaptic connections. Additional fixed costs with GeNN are almost independent of model size, while fixed costs with NEST increase linearly with model size. We demonstrate how GeNN can be used for simulating networks with up to 3.5 · 106 neurons (> 3 · 1012synapses) on a high-end GPU, and up to 250, 000 neurons (25 · 109 synapses) on a low-cost GPU. Real-time simulation was achieved for networks with 100, 000 neurons. Network calibration and parameter grid search can be efficiently achieved using batch processing. We discuss the advantages and disadvantages of both approaches for different use cases.

Using Mosaic Cell Labeling to Visualize Polyploid Cells in the Drosophila Brain

Traditional methods used to study endoreplication have limitations when used to identify rare events of polyploidization in complex, densely-packed tissues. Here, we describe a method to identify and visualize polyploid cells in situ using an existing mosaic, multicolor labeling technique named "CoinFLP" (Bosch et al., Development 142(3):597-606, 2015). CoinFLP allows easy visualization of polyploid cells in situ and can be combined with other techniques such as immunofluorescence for cell-type-specific labeling and flow cytometry to perform quantifications and can also be used for genetic manipulations. Further, by modifying the time of labeling, this technique can also be used to distinguish events of cell fusion from endocycle (Nandakumar et al., eLife 25:9, 2020)-allowing one to infer the method of polyploidization.

Invertebrates as models of learning and memory: investigating neural and molecular mechanisms

In this Commentary, we shed light on the use of invertebrates as model organisms for understanding the causal and conserved mechanisms of learning and memory. We provide a condensed chronicle of the contribution offered by mollusks to the studies on how and where the nervous system encodes and stores memory and describe the rich cognitive capabilities of some insect species, including attention and concept learning. We also discuss the use of planarians for investigating the dynamics of memory during brain regeneration and highlight the role of stressful stimuli in forming memories. Furthermore, we focus on the increasing evidence that invertebrates display some forms of emotions, which provides new opportunities for unveiling the neural and molecular mechanisms underlying the complex interaction between stress, emotions and cognition. In doing so, we highlight experimental challenges and suggest future directions that we expect the field to take in the coming years, particularly regarding what we, as humans, need to know for preventing and/or delaying memory loss. This article has an associated ECR Spotlight interview with Veronica Rivi.

Bolwig Organ and Its Role in the Photoperiodic Response of Sarcophaga similis Larvae

Flesh-fly Sarcophaga similis larvae exhibit a photoperiodic response, in which short days induce pupal diapause for seasonal adaptation. Although the spectral sensitivity of photoperiodic photoreception is known, the photoreceptor organ remains unclear. We morphologically identified the Bolwig organ, a larval-photoreceptor identified in several other fly species, and examined the effects of its removal on the photoperiodic response in S. similis. Backfill-staining and embryonic-lethal-abnormal-vision (ELAV) immunohistochemical-staining identified ~34 and 38 cells, respectively, in a spherical body at the ocular depression of the cephalopharyngeal skeleton, suggesting that the spherical body is the Bolwig organ in S. similis. Forward-fill and immunohistochemistry revealed that Bolwig-organ neurons terminate in the vicinity of the dendritic fibres of pigment-dispersing factor-immunoreactive and potential circadian-clock neurons in the brain. After surgical removal of the Bolwig-organ regions, diapause incidence was not significantly different between short and long days, and was similar to that in the insects with an intact organ, under constant darkness. However, diapause incidence was not significantly different between the control and Bolwig-organ-removed insects for each photoperiod. These results suggest that the Bolwig organ contributes partially to photoperiodic photoreception, and that other photoreceptors may also be involved.

A theoretical approach to improving interspecies welfare comparisons

The number of animals bred, raised, and slaughtered each year is on the rise, resulting in increasing impacts to welfare. Farmed animals are also becoming more diverse, ranging from pigs to bees. The diversity and number of species farmed invite questions about how best to allocate currently limited resources towards safeguarding and improving welfare. This is of the utmost concern to animal welfare funders and effective altruism advocates, who are responsible for targeting the areas most likely to cause harm. For example, is tail docking worse for pigs than beak trimming is for chickens in terms of their pain, suffering, and general experience? Or are the welfare impacts equal? Answering these questions requires making an interspecies welfare comparison; a judgment about how good or bad different species fare relative to one another. Here, we outline and discuss an empirical methodology that aims to improve our ability to make interspecies welfare comparisons by investigating welfare range, which refers to how good or bad animals can fare. Beginning with a theory of welfare, we operationalize that theory by identifying metrics that are defensible proxies for measuring welfare, including cognitive, affective, behavioral, and neuro-biological measures. Differential weights are assigned to those proxies that reflect their evidential value for the determinants of welfare, such as the Delphi structured deliberation method with a panel of experts. The evidence should then be reviewed and its quality scored to ascertain whether particular taxa may possess the proxies in question to construct a taxon-level welfare range profile. Finally, using a Monte Carlo simulation, an overall estimate of comparative welfare range relative to a hypothetical index species can be generated. Interspecies welfare comparisons will help facilitate empirically informed decision-making to streamline the allocation of resources and ultimately better prioritize and improve animal welfare.

Drug effect and addiction research with insects - From Drosophila to collective reward in honeybees

Animals and humans share similar reactions to the effects of addictive substances, including those of their brain networks to drugs. Our review focuses on simple invertebrate models, particularly the honeybee (Apis mellifera), and on the effects of drugs on bee behaviour and brain functions. The drug effects in bees are very similar to those described in humans. Furthermore, the honeybee community is a superorganism in which many collective functions outperform the simple sum of individual functions. The distribution of reward functions in this superorganism is unique - although sublimated at the individual level, community reward functions are of higher quality. This phenomenon of collective reward may be extrapolated to other animal species living in close and strictly organised societies, i.e. humans. The relationship between sociality and reward, based on use of similar parts of the neural network (social decision-making network in mammals, mushroom body in bees), suggests a functional continuum of reward and sociality in animals.

Impacts of development and adult sex on brain cell numbers in the Black Soldier Fly, Hermetia illucens L. (Diptera: Stratiomyidae)

The Black Soldier Fly (Hermetia illucens, Diptera: Stratiomyidae) has been introduced across the globe, with numerous industry applications predicated on its tremendous growth during the larval stage. However, basic research on H. illucens biology (for example, studies of their central nervous system) are lacking. Despite their small brain volumes, insects are capable of complex behaviors; understanding how these behaviors are completed with such a small amount of neural tissue requires understanding processing power (e.g. number of cells) within the brain. Brain cell counts have been completed in only a few insect species (mostly Hymenoptera), and almost exclusively in adults. This limits the taxonomic breadth of comparative analyses, as well as any conclusions about how development and body size growth may impact brain cell populations. Here, we present the first images and cell counts of the H. illucens brain at four time points across development (early, mid, and late larval stages, and both male and female adults) using immunohistochemistry and isotropic fractionation. To assess sexual dimorphism in adults, we quantified the number of cells in the central brain vs. optic lobes of males and females separately. To assess if increases in body size during development might independently affect different regions of the CNS, we quantified the larval ventral nerve cord and central brain separately at all three stages. Together, these data provide the first description of the nervous system of a popular, farmed invertebrate and the first study of brain cell numbers using IF across developmental stages in any insect.

A Stereological Study of the Three Types of Ganglia of Male, Female, and Undifferentiated Scrobicularia plana (Bivalvia)

Neurotransmitters modulate gonadal maturation in bivalves. However, it remains unclear whether there are differences in the nervous system structure between sexes, maturation, and ganglia. Therefore, a stereological study was conducted on the ganglia of adult peppery furrow shell (Scrobicularia plana). Equal-sized males, females, and undifferentiated (gamete absence) animals were fixed with 10% formalin and processed for light microscopy. They were serially cut into 35 µm paraffin thick sections and stained with hematoxylin-eosin. Sections with cerebral (cerebropleural), pedal, and visceral ganglia were studied. The parameters estimated were the volumes of the ganglia, the total and relative volumes of their cortex (outer layer) and medulla (neuropil), and the total number of cells (neurons, glia, and pigmented) per ganglia and compartment. The volumes and numbers were estimated, respectively, by the Cavalieri principle and by the optical fractionator. Females show a larger glia to neuron numerical ratio. Further, females have a greater ganglionic volume than undifferentiated adults, with males showing intermediate values. These facts indicate that the ganglia size is related somehow to maturation. The cell size forms the basis of the differences because total cellularity is equal among the groups. The three ganglion types differ in total volumes and the volume ratio of the cortex versus the medulla. The greater volumes of the pedal ganglia (vis-a-vis the cerebral ones) and of the visceral ganglia (in relation to all others) imply more voluminous cortexes and medullae, but more neuronal and non-neuronal cells only in the visceral. The new fundamental data can help interpret bivalve neurophysiology.

Dlg Is Required for Short-Term Memory and Interacts with NMDAR in the Drosophila Brain

The vertebrates’ scaffold proteins of the Dlg-MAGUK family are involved in the recruitment, clustering, and anchoring of glutamate receptors to the postsynaptic density, particularly the NMDA subtype glutamate-receptors (NRs), necessary for long-term memory and LTP. In Drosophila, the only gene of the subfamily generates two main products, dlgA, broadly expressed, and dlgS97, restricted to the nervous system. In the Drosophila brain, NRs are expressed in the adult brain and are involved in memory, however, the role of Dlg in these processes and its relationship with NRs has been scarcely explored. Here, we show that the dlg mutants display defects in short-term memory in the olfactory associative-learning paradigm. These defects are dependent on the presence of DlgS97 in the Mushroom Body (MB) synapses. Moreover, Dlg is immunoprecipitated with NRs in the adult brain. Dlg is also expressed in the larval neuromuscular junction (NMJ) pre and post-synaptically and is important for development and synaptic function, however, NR is absent in this synapse. Despite that, we found changes in the short-term plasticity paradigms in dlg mutant larval NMJ. Together our results show that larval NMJ and the adult brain relies on Dlg for short-term memory/plasticity, but the mechanisms differ in the two types of synapses.

Intact Drosophila central nervous system cellular quantitation reveals sexual dimorphism

Establishing with precision the quantity and identity of the cell types of the brain is a prerequisite for a detailed compendium of gene and protein expression in the central nervous system (CNS). Currently, however, strict quantitation of cell numbers has been achieved only for the nervous system of Caenorhabditis elegans. Here, we describe the development of a synergistic pipeline of molecular genetic, imaging, and computational technologies designed to allow high-throughput, precise quantitation with cellular resolution of reporters of gene expression in intact whole tissues with complex cellular constitutions such as the brain. We have deployed the approach to determine with exactitude the number of functional neurons and glia in the entire intact larval Drosophila CNS, revealing fewer neurons and more glial cells than previously predicted. We also discover an unexpected divergence between the sexes at this juvenile developmental stage, with the female CNS having significantly more neurons than that of males. Topological analysis of our data establishes that this sexual dimorphism extends to deeper features of CNS organisation. We additionally extended our analysis to quantitate the expression of voltage-gated potassium channel family genes throughout the CNS and uncover substantial differences in abundance. Our methodology enables robust and accurate quantification of the number and positioning of cells within intact organs, facilitating sophisticated analysis of cellular identity, diversity, and gene expression characteristics.

A single-cell transcriptomic atlas tracking the neural basis of division of labour in an ant superorganism

Ant colonies with permanent division of labour between castes and highly distinct roles of the sexes have been conceptualized to be superorganisms, but the cellular and molecular mechanisms that mediate caste/sex-specific behavioural specialization have remained obscure. Here we characterized the brain cell repertoire of queens, gynes (virgin queens), workers and males of Monomorium pharaonis by obtaining 206,367 single-nucleus transcriptomes. In contrast to Drosophila, the mushroom body Kenyon cells are abundant in ants and display a high diversity with most subtypes being enriched in worker brains, the evolutionarily derived caste. Male brains are as specialized as worker brains but with opposite trends in cell composition with higher abundances of all optic lobe neuronal subtypes, while the composition of gyne and queen brains remained generalized, reminiscent of solitary ancestors. Role differentiation from virgin gynes to inseminated queens induces abundance changes in roughly 35% of cell types, indicating active neurogenesis and/or programmed cell death during this transition. We also identified insemination-induced cell changes probably associated with the longevity and fecundity of the reproductive caste, including increases of ensheathing glia and a population of dopamine-regulated Dh31-expressing neurons. We conclude that permanent caste differentiation and extreme sex-differentiation induced major changes in the neural circuitry of ants.

Using single-cell transcriptomics, the authors generate a brain cell atlas for the pharaoh ant including individuals of different sexes and castes and show changes in cell composition underlying division of labour and reproductive specialization.

Genetic regulation of central synapse formation and organization in Drosophila melanogaster

A goal of modern neuroscience involves understanding how connections in the brain form and function. Such a knowledge is essential to inform how defects in the exquisite complexity of nervous system growth influence neurological disease. Studies of the nervous system in the fruit fly Drosophila melanogaster enabled the discovery of a wealth of molecular and genetic mechanisms underlying development of synapses-the specialized cell-to-cell connections that comprise the essential substrate for information flow and processing in the nervous system. For years, the major driver of knowledge was the neuromuscular junction due to its ease of examination. Analogous studies in the central nervous system lagged due to a lack of genetic accessibility of specific neuron classes, synaptic labels compatible with cell-type-specific access, and high resolution, quantitative imaging strategies. However, understanding how central synapses form remains a prerequisite to understanding brain development. In the last decade, a host of new tools and techniques extended genetic studies of synapse organization into central circuits to enhance our understanding of synapse formation, organization, and maturation. In this review, we consider the current state-of-the-field. We first discuss the tools, technologies, and strategies developed to visualize and quantify synapses in vivo in genetically identifiable neurons of the Drosophila central nervous system. Second, we explore how these tools enabled a clearer understanding of synaptic development and organization in the fly brain and the underlying molecular mechanisms of synapse formation. These studies establish the fly as a powerful in vivo genetic model that offers novel insights into neural development.

Neuronal induction of BNIP3-mediated mitophagy slows systemic aging in Drosophila

The effects of aging on the brain are widespread and can have dramatic implications on the overall health of an organism. Mitochondrial dysfunction is a hallmark of brain aging, but, the interplay between mitochondrial quality control, neuronal aging, and organismal health is not well understood. Here, we show that aging leads to a decline in mitochondrial autophagy (mitophagy) in the Drosophila brain with a concomitant increase in mitochondrial content. We find that induction of BCL2-interacting protein 3 (BNIP3), a mitochondrial outer membrane protein, in the adult nervous system induces mitophagy and prevents the accumulation of dysfunctional mitochondria in the aged brain. Importantly, neuronal induction of BNIP3-mediated mitophagy increases organismal longevity and healthspan. Furthermore, BNIP3-mediated mitophagy in the nervous system improves muscle and intestinal homeostasis in aged flies, indicating cell non-autonomous effects. Our findings identify BNIP3 as a therapeutic target to counteract brain aging and prolong overall organismal health with age.

Transcription factor Acj6 controls dendrite targeting via a combinatorial cell-surface code

Transcription factors specify the fate and connectivity of developing neurons. We investigate how a lineage-specific transcription factor, Acj6, controls the precise dendrite targeting of Drosophila olfactory projection neurons (PNs) by regulating the expression of cell-surface proteins. Quantitative cell-surface proteomic profiling of wild-type and acj6 mutant PNs in intact developing brains, and a proteome-informed genetic screen identified PN surface proteins that execute Acj6-regulated wiring decisions. These include canonical cell adhesion molecules and proteins previously not associated with wiring, such as Piezo, whose mechanosensitive ion channel activity is dispensable for its function in PN dendrite targeting. Comprehensive genetic analyses revealed that Acj6 employs unique sets of cell-surface proteins in different PN types for dendrite targeting. Combined expression of Acj6 wiring executors rescued acj6 mutant phenotypes with higher efficacy and breadth than expression of individual executors. Thus, Acj6 controls wiring specificity of different neuron types by specifying distinct combinatorial expression of cell-surface executors.

The Neuromodulatory Basis of Aggression: Lessons From the Humble Fruit Fly

Aggression is an intrinsic trait that organisms of almost all species, humans included, use to get access to food, shelter, and mating partners. To maximize fitness in the wild, an organism must vary the intensity of aggression toward the same or different stimuli. How much of this variation is genetic and how much is externally induced, is largely unknown but is likely to be a combination of both. Irrespective of the source, one of the principal physiological mechanisms altering the aggression intensity involves neuromodulation. Any change or variation in aggression intensity is most likely governed by a complex interaction of several neuromodulators acting via a meshwork of neural circuits. Resolving aggression-specific neural circuits in a mammalian model has proven challenging due to the highly complex nature of the mammalian brain. In that regard, the fruit fly model Drosophila melanogaster has provided insights into the circuit-driven mechanisms of aggression regulation and its underlying neuromodulatory basis. Despite morphological dissimilarities, the fly brain shares striking similarities with the mammalian brain in genes, neuromodulatory systems, and circuit-organization, making the findings from the fly model extremely valuable for understanding the fundamental circuit logic of human aggression. This review discusses our current understanding of how neuromodulators regulate aggression based on findings from the fruit fly model. We specifically focus on the roles of Serotonin (5-HT), Dopamine (DA), Octopamine (OA), Acetylcholine (ACTH), Sex Peptides (SP), Tachykinin (TK), Neuropeptide F (NPF), and Drosulfakinin (Dsk) in fruit fly male and female aggression.

From Photons to Behaviors: Neural Implementations of Visual Behaviors in Drosophila

Neural implementations of visual behaviors in Drosophila have been dissected intensively in the past couple of decades. The availability of premiere genetic toolkits, behavioral assays in tethered or freely moving conditions, and advances in connectomics have permitted the understanding of the physiological and anatomical details of the nervous system underlying complex visual behaviors. In this review, we describe recent advances on how various features of a visual scene are detected by the Drosophila visual system and how the neural circuits process these signals and elicit an appropriate behavioral response. Special emphasis was laid on the neural circuits that detect visual features such as brightness, color, local motion, optic flow, and translating or approaching visual objects, which would be important for behaviors such as phototaxis, optomotor response, attraction (or aversion) to moving objects, navigation, and visual learning. This review offers an integrative framework for how the fly brain detects visual features and orchestrates an appropriate behavioral response.

Identifying Inputs to Visual Projection Neurons in Drosophila Lobula by Analyzing Connectomic Data

Electron microscopy (EM)-based connectomes provide important insights into how visual circuitry of fruit fly Drosophila computes various visual features, guiding and complementing behavioral and physiological studies. However, connectomic analyses of the lobula, a neuropil putatively dedicated to detecting object-like features, remains underdeveloped, largely because of incomplete data on the inputs to the brain region. Here, we attempted to map the columnar inputs into the Drosophila lobula neuropil by performing connectivity-based and morphology-based clustering on a densely reconstructed connectome dataset. While the dataset mostly lacked visual neuropils other than lobula, which would normally help identify inputs to lobula, our clustering analysis successfully extracted clusters of cells with homogeneous connectivity and morphology, likely representing genuine cell types. We were able to draw a correspondence between the resulting clusters and previously identified cell types, revealing previously undocumented connectivity between lobula input and output neurons. While future, more complete connectomic reconstructions are necessary to verify the results presented here, they can serve as a useful basis for formulating hypotheses on mechanisms of visual feature detection in lobula.