The accumulation of amyloid-beta (Abeta) into plaques is a hallmark feature of Alzheimer’s disease (AD). While amyloid precursor protein (APP)-related proteins are found in most organisms, only Abeta fragments from human APP have been shown to induce amyloid deposits and progressive neurodegeneration. Therefore, it was suggested that neurotoxic effects are a specific property of human Abeta. Here we show that Abeta fragments derived from the Drosophila orthologue APPL aggregate into intracellular fibrils, amyloid deposits, and cause age-dependent behavioral deficits and neurodegeneration. We also show that APPL can be cleaved by a novel fly beta-secretase-like enzyme. This suggests that Abeta-induced neurotoxicity is a conserved function of APP proteins whereby the lack of conservation in the primary sequence indicates that secondary structural aspects determine their pathogenesis. In addition, we found that the behavioral phenotypes precede extracellular amyloid deposit formation, supporting results that intracellular Abeta plays a key role in AD.

How memories of past events influence behavior is a key question in neuroscience. The major associative learning center in Drosophila, the Mushroom Body (MB), communicates to the rest of the brain through Mushroom Body Output Neurons (MBONs). While 21 MBON cell types have their dendrites confined to small compartments of the MB lobes, analysis of EM connectomes revealed the presence of an additional 14 MBON cell types that are atypical in having dendritic input both within the MB lobes and in adjacent brain regions. Genetic reagents for manipulating atypical MBONs and experimental data on their functions has been lacking. In this report we describe new cell-type-specific GAL4 drivers for many MBONs, including the majority of atypical MBONs. Using these genetic reagents, we conducted optogenetic activation screening to examine their ability to drive behaviors and learning. These reagents provide important new tools for the study of complex behaviors in Drosophila.

Animals employ diverse learning rules and synaptic plasticity dynamics to record temporal and statistical information about the world. However, the molecular mechanisms underlying this diversity are poorly understood. The anatomically defined compartments of the insect mushroom body function as parallel units of associative learning, with different learning rates, memory decay dynamics and flexibility (Aso & Rubin 2016). Here we show that nitric oxide (NO) acts as a neurotransmitter in a subset of dopaminergic neurons in . NO's effects develop more slowly than those of dopamine and depend on soluble guanylate cyclase in postsynaptic Kenyon cells. NO acts antagonistically to dopamine; it shortens memory retention and facilitates the rapid updating of memories. The interplay of NO and dopamine enables memories stored in local domains along Kenyon cell axons to be specialized for predicting the value of odors based only on recent events. Our results provide key mechanistic insights into how diverse memory dynamics are established in parallel memory systems.

The insect mushroom body (MB) is a conserved brain structure that plays key roles in a diverse array of behaviors. The MB is the primary invertebrate model of neural circuits related to memory formation and storage, and its development, morphology, wiring, and function has been extensively studied. MBs consist of intrinsic Kenyon Cells that are divided into three major neuron classes (γ, α'/β' and α/β) and 7 cell subtypes (γd, γm, α'/β'ap, α'/β'm, α/βp, α/βs and α/βc) based on their birth order, morphology, and connectivity. These subtypes play distinct roles in memory processing, however the underlying transcriptional differences are unknown. Here, we used RNA sequencing (RNA-seq) to profile the nuclear transcriptomes of each MB neuronal cell subtypes. We identified 350 MB class- or subtype-specific genes, including the widely used α/β class marker and the α'/β' class marker Immunostaining corroborates the RNA-seq measurements at the protein level for several cases. Importantly, our data provide a full accounting of the neurotransmitter receptors, transporters, neurotransmitter biosynthetic enzymes, neuropeptides, and neuropeptide receptors expressed within each of these cell types. This high-quality, cell type-level transcriptome catalog for the MB provides a valuable resource for the fly neuroscience community.

We describe the development and application of methods for high-throughput neuroanatomy in Drosophila using light microscopy. These tools enable efficient multicolor stochastic labeling of neurons at both low and high densities. Expression of multiple membrane-targeted and distinct epitope-tagged proteins is controlled both by a transcriptional driver and by stochastic, recombinase-mediated excision of transcription-terminating cassettes. This MultiColor FlpOut (MCFO) approach can be used to reveal cell shapes and relative cell positions and to track the progeny of precursor cells through development. Using two different recombinases, the number of cells labeled and the number of color combinations observed in those cells can be controlled separately. We demonstrate the utility of MCFO in a detailed study of diversity and variability of Distal medulla (Dm) neurons, multicolumnar local interneurons in the adult visual system. Similar to many brain regions, the medulla has a repetitive columnar structure that supports parallel information processing together with orthogonal layers of cell processes that enable communication between columns. We find that, within a medulla layer, processes of the cells of a given Dm neuron type form distinct patterns that reflect both the morphology of individual cells and the relative positions of their arbors. These stereotyped cell arrangements differ between cell types and can even differ for the processes of the same cell type in different medulla layers. This unexpected diversity of coverage patterns provides multiple independent ways of integrating visual information across the retinotopic columns and implies the existence of multiple developmental mechanisms that generate these distinct patterns.

The visual system of Drosophila is an excellent model for determining the interactions that direct the differentiation of the nervous system’s many unique cell types. Glia are essential not only in the development of the nervous system, but also in the function of those neurons with which they become associated in the adult. Given their role in visual system development and adult function we need to both accurately and reliably identify the different subtypes of glia, and to relate the glial subtypes in the larval brain to those previously described for the adult. We viewed driver expression in subsets of larval eye disc glia through the earliest stages of pupal development to reveal the counterparts of these cells in the adult. Two populations of glia exist in the lamina, the first neuropil of the adult optic lobe: those that arise from precursors in the eye-disc/optic stalk and those that arise from precursors in the brain. In both cases, a single larval source gives rise to at least three different types of adult glia. Furthermore, analysis of glial cell types in the second neuropil, the medulla, has identified at least four types of astrocyte-like (reticular) glia. Our clarification of the lamina’s adult glia and identification of their larval origins, particularly the respective eye disc and larval brain contributions, begin to define developmental interactions which establish the different subtypes of glia.

How brains are hardwired to produce aggressive behavior, and how aggression circuits are related to those that mediate courtship, is not well understood. A large-scale screen for aggression-promoting neurons in Drosophila identified several independent hits that enhanced both inter-male aggression and courtship. Genetic intersections revealed that 8-10 P1 interneurons, previously thought to exclusively control male courtship, were sufficient to promote fighting. Optogenetic experiments indicated that P1 activation could promote aggression at a threshold below that required for wing extension. P1 activation in the absence of wing extension triggered persistent aggression via an internal state that could endure for minutes. High-frequency P1 activation promoted wing extension and suppressed aggression during photostimulation, whereas aggression resumed and wing extension was inhibited following photostimulation offset. Thus, P1 neuron activation promotes a latent, internal state that facilitates aggression and courtship, and controls the overt expression of these social behaviors in a threshold-dependent, inverse manner.

Nervous systems can process information in serial or in parallel, trading off efficiency for flexibility and speed. How these network architectures are implemented across sensorimotor pathways to control behavior is unclear. We investigate this tradeoff directly in Drosophila by comparing neuronal circuits underlying landing and takeoff, behaviors transforming similar visual cues to whole-body motor output. Using a whole-CNS connectome, electrophysiology, and behavioral analysis, we reconstruct the complete feedforward pathway for landing, including visual feature detectors, a dedicated ensemble of descending neurons (DNs), and a core premotor circuit in the nerve cord. Comparison to the takeoff pathway reveals that, despite encoding the same sensory feature and engaging similar muscle groups, neuronal circuits controlling the two behaviors are separated at every sensorimotor level. Extending this analysis to the complete DN population reveals a blueprint for descending motor control: DNs across the behavioral space utilized by the fly are organized as a set of parallel, loosely-overlapping ensembles that form a continuum from command-like control, with individual DNs determining behavioral output, to population coding, with multiple DNs controlling behavior synergistically. Distinct combinations of sensory feature detectors differentially recruit DN ensembles to enable flexible, context-dependent behavioral control.

Although all sensory circuits ascend to higher brain areas where stimuli are represented in sparse, stimulus-specific activity patterns, relatively little is known about sensory coding on the descending side of neural circuits, as a network converges. In insects, mushroom bodies have been an important model system for studying sparse coding in the olfactory system, where this format is important for accurate memory formation. In Drosophila, it has recently been shown that the 2,000 Kenyon cells of the mushroom body converge onto a population of only 34 mushroom body output neurons (MBONs), which fall into 21 anatomically distinct cell types. Here we provide the first, to our knowledge, comprehensive view of olfactory representations at the fourth layer of the circuit, where we find a clear transition in the principles of sensory coding. We show that MBON tuning curves are highly correlated with one another. This is in sharp contrast to the process of progressive decorrelation of tuning in the earlier layers of the circuit. Instead, at the population level, odour representations are reformatted so that positive and negative correlations arise between representations of different odours. At the single-cell level, we show that uniquely identifiable MBONs display profoundly different tuning across different animals, but that tuning of the same neuron across the two hemispheres of an individual fly was nearly identical. Thus, individualized coordination of tuning arises at this level of the olfactory circuit. Furthermore, we find that this individualization is an active process that requires a learning-related gene, rutabaga. Ultimately, neural circuits have to flexibly map highly stimulus-specific information in sparse layers onto a limited number of different motor outputs. The reformatting of sensory representations we observe here may mark the beginning of this sensory-motor transition in the olfactory system.

The Drosophila mushroom body (MB) is a key associative memory center that has also been implicated in the control of sleep. However, the identity of MB neurons underlying homeostatic sleep regulation, as well as the types of sleep signals generated by specific classes of MB neurons, has remained poorly understood. We recently identified two MB output neuron (MBON) classes whose axons convey sleep control signals from the MB to converge in the same downstream target region: a cholinergic sleep-promoting MBON class and a glutamatergic wake-promoting MBON class. Here, we deploy a combination of neurogenetic, behavioral, and physiological approaches to identify and mechanistically dissect sleep-controlling circuits of the MB. Our studies reveal the existence of two segregated excitatory synaptic microcircuits that propagate homeostatic sleep information from different populations of intrinsic MB "Kenyon cells" (KCs) to specific sleep-regulating MBONs: sleep-promoting KCs increase sleep by preferentially activating the cholinergic MBONs, while wake-promoting KCs decrease sleep by preferentially activating the glutamatergic MBONs. Importantly, activity of the sleep-promoting MB microcircuit is increased by sleep deprivation and is necessary for homeostatic rebound sleep (i.e., the increased sleep that occurs after, and in compensation for, sleep lost during deprivation). These studies reveal for the first time specific functional connections between subsets of KCs and particular MBONs and establish the identity of synaptic microcircuits underlying transmission of homeostatic sleep signals in the MB.