Diverse memory paradigms in Drosophila reveal diverse neural mechanisms.

In this review, we aggregated the different types of learning and memory paradigms developed in adult Drosophila and attempted to assess the similarities and differences in the neural mechanisms supporting diverse types of memory. The simplest association memory assays are conditioning paradigms (olfactory, visual, and gustatory). A great deal of work has been done on these memories, revealing hundreds of genes and neural circuits supporting this memory. Variations of conditioning assays (reversal learning, trace conditioning, latent inhibition, and extinction) also reveal interesting memory mechanisms, whereas mechanisms supporting spatial memory (thermal maze, orientation memory, and heat box) and the conditioned suppression of innate behaviors (phototaxis, negative geotaxis, anemotaxis, and locomotion) remain largely unexplored. In recent years, there has been an increased interest in multisensory and multicomponent memories (context-dependent and cross-modal memory) and higher-order memory (sensory preconditioning and second-order conditioning). Some of this work has revealed how the intricate mushroom body (MB) neural circuitry can support more complex memories. Finally, the most complex memories are arguably those involving social memory: courtship conditioning and social learning (mate-copying and egg-laying behaviors). Currently, very little is known about the mechanisms supporting social memories. Overall, the MBs are important for association memories of multiple sensory modalities and multisensory integration, whereas the central complex is important for place, orientation, and navigation memories. Interestingly, several different types of memory appear to use similar or variants of the olfactory conditioning neural circuitry, which are repurposed in different ways.

Drosophila learning and memory centers and the actions of drugs of abuse.

Drug addiction and the circuitry for learning and memory are intimately intertwined. Drugs of abuse create strong, inappropriate, and lasting memories that contribute to many of their destructive properties, such as continued use despite negative consequences and exceptionally high rates of relapse. Studies in Drosophila melanogaster are helping us understand how drugs of abuse, especially alcohol, create memories at the level of individual neurons and in the circuits where they function. Drosophila is a premier organism for identifying the mechanisms of learning and memory. Drosophila also respond to drugs of abuse in ways that remarkably parallel humans and rodent models. An emerging consensus is that, for alcohol, the mushroom bodies participate in the circuits that control acute drug sensitivity, not explicitly associative forms of plasticity such as tolerance, and classical associative memories of their rewarding and aversive properties. Moreover, it is becoming clear that drugs of abuse use the mushroom body circuitry differently from other behaviors, potentially providing a basis for their addictive properties.

Cognitive limits of larval Drosophila: testing for conditioned inhibition, sensory preconditioning, and second-order conditioning.

Drosophila larvae are an established model system for studying the mechanisms of innate and simple forms of learned behavior. They have about 10 times fewer neurons than adult flies, and it was the low total number of their neurons that allowed for an electron microscopic reconstruction of their brain at synaptic resolution. Regarding the mushroom body, a central brain structure for many forms of associative learning in insects, it turned out that more than half of the classes of synaptic connection had previously escaped attention. Understanding the function of these circuit motifs, subsequently confirmed in adult flies, is an important current research topic. In this context, we test larval Drosophila for their cognitive abilities in three tasks that are characteristically more complex than those previously studied. Our data provide evidence for (i) conditioned inhibition, as has previously been reported for adult flies and honeybees. Unlike what is described for adult flies and honeybees, however, our data do not provide evidence for (ii) sensory preconditioning or (iii) second-order conditioning in Drosophila larvae. We discuss the methodological features of our experiments as well as four specific aspects of the organization of the larval brain that may explain why these two forms of learning are observed in adult flies and honeybees, but not in larval Drosophila.

Roles of feedback and feed-forward networks of dopamine subsystems: insights from Drosophila studies.

Across animal species, dopamine-operated memory systems comprise anatomically segregated, functionally diverse subsystems. Although individual subsystems could operate independently to support distinct types of memory, the logical interplay between subsystems is expected to enable more complex memory processing by allowing existing memory to influence future learning. Recent comprehensive ultrastructural analysis of the Drosophila mushroom body revealed intricate networks interconnecting the dopamine subsystems-the mushroom body compartments. Here, we review the functions of some of these connections that are beginning to be understood. Memory consolidation is mediated by two different forms of network: A recurrent feedback loop within a compartment maintains sustained dopamine activity required for consolidation, whereas feed-forward connections across compartments allow short-term memory formation in one compartment to open the gate for long-term memory formation in another compartment. Extinction and reversal of aversive memory rely on a similar feed-forward circuit motif that signals omission of punishment as a reward, which triggers plasticity that counteracts the original aversive memory trace. Finally, indirect feed-forward connections from a long-term memory compartment to short-term memory compartments mediate higher-order conditioning. Collectively, these emerging studies indicate that feedback control and hierarchical connectivity allow the dopamine subsystems to work cooperatively to support diverse and complex forms of learning.

Future avenues in Drosophila mushroom body research.

How does the brain translate sensory information into complex behaviors? With relatively small neuronal numbers, readable behavioral outputs, and an unparalleled genetic toolkit, the Drosophila mushroom body (MB) offers an excellent model to address this question in the context of associative learning and memory. Recent technological breakthroughs, such as the freshly completed full-brain connectome, multiomics approaches, CRISPR-mediated gene editing, and machine learning techniques, led to major advancements in our understanding of the MB circuit at the molecular, structural, physiological, and functional levels. Despite significant progress in individual MB areas, the field still faces the fundamental challenge of resolving how these different levels combine and interact to ultimately control the behavior of an individual fly. In this review, we discuss various aspects of MB research, with a focus on the current knowledge gaps, and an outlook on the future methodological developments required to reach an overall view of the neurobiological basis of learning and memory.

Sensory encoding and memory in the mushroom body: signals, noise, and variability.

To survive in changing environments, animals need to learn to associate specific sensory stimuli with positive or negative valence. How do they form stimulus-specific memories to distinguish between positively/negatively associated stimuli and other irrelevant stimuli? Solving this task is one of the functions of the mushroom body, the associative memory center in insect brains. Here we summarize recent work on sensory encoding and memory in the Drosophila mushroom body, highlighting general principles such as pattern separation, sparse coding, noise and variability, coincidence detection, and spatially localized neuromodulation, and placing the mushroom body in comparative perspective with mammalian memory systems.

An integrative sensor of body states: how the mushroom body modulates behavior depending on physiological context.

The brain constantly compares past and present experiences to predict the future, thereby enabling instantaneous and future behavioral adjustments. Integration of external information with the animal's current internal needs and behavioral state represents a key challenge of the nervous system. Recent advancements in dissecting the function of the Drosophila mushroom body (MB) at the single-cell level have uncovered its three-layered logic and parallel systems conveying positive and negative values during associative learning. This review explores a lesser-known role of the MB in detecting and integrating body states such as hunger, thirst, and sleep, ultimately modulating motivation and sensory-driven decisions based on the physiological state of the fly. State-dependent signals predominantly affect the activity of modulatory MB input neurons (dopaminergic, serotoninergic, and octopaminergic), but also induce plastic changes directly at the level of the MB intrinsic and output neurons. Thus, the MB emerges as a tightly regulated relay station in the insect brain, orchestrating neuroadaptations due to current internal and behavioral states leading to short- but also long-lasting changes in behavior. While these adaptations are crucial to ensure fitness and survival, recent findings also underscore how circuit motifs in the MB may reflect fundamental design principles that contribute to maladaptive behaviors such as addiction or depression-like symptoms.

Skewing information flow through pre- and postsynaptic plasticity in the mushroom bodies of Drosophila.

Animal brains need to store information to construct a representation of their environment. Knowledge of what happened in the past allows both vertebrates and invertebrates to predict future outcomes by recalling previous experience. Although invertebrate and vertebrate brains share common principles at the molecular, cellular, and circuit-architectural levels, there are also obvious differences as exemplified by the use of acetylcholine versus glutamate as the considered main excitatory neurotransmitters in the respective central nervous systems. Nonetheless, across central nervous systems, synaptic plasticity is thought to be a main substrate for memory storage. Therefore, how brain circuits and synaptic contacts change following learning is of fundamental interest for understanding brain computations tied to behavior in any animal. Recent progress has been made in understanding such plastic changes following olfactory associative learning in the mushroom bodies (MBs) of Drosophila A current framework of memory-guided behavioral selection is based on the MB skew model, in which antagonistic synaptic pathways are selectively changed in strength. Here, we review insights into plasticity at dedicated Drosophila MB output pathways and update what is known about the plasticity of both pre- and postsynaptic compartments of Drosophila MB neurons.

Divergent evolution of sleep in Drosophila species.

Living organisms synchronize their biological activities with the earth's rotation through the circadian clock, a molecular mechanism that regulates biology and behavior daily. This synchronization factually maximizes positive activities (e.g., social interactions, feeding) during safe periods, and minimizes exposure to dangers (e.g., predation, darkness) typically at night. Beyond basic circadian regulation, some behaviors like sleep have an additional layer of homeostatic control, ensuring those essential activities are fulfilled. While sleep is predominantly governed by the circadian clock, a secondary homeostatic regulator, though not well-understood, ensures adherence to necessary sleep amounts and hints at a fundamental biological function of sleep beyond simple energy conservation and safety. Here we explore sleep regulation across seven Drosophila species with diverse ecological niches, revealing that while circadian-driven sleep aspects are consistent, homeostatic regulation varies significantly. The findings suggest that in Drosophilids, sleep evolved primarily for circadian purposes. The more complex, homeostatically regulated functions of sleep appear to have evolved independently in a species-specific manner, and are not universally conserved. This laboratory model may reproduce and recapitulate primordial sleep evolution.

Evolution of connectivity architecture in the Drosophila mushroom body.

Brain evolution has primarily been studied at the macroscopic level by comparing the relative size of homologous brain centers between species. How neuronal circuits change at the cellular level over evolutionary time remains largely unanswered. Here, using a phylogenetically informed framework, we compare the olfactory circuits of three closely related Drosophila species that differ in their chemical ecology: the generalists Drosophila melanogaster and Drosophila simulans and Drosophila sechellia that specializes on ripe noni fruit. We examine a central part of the olfactory circuit that, to our knowledge, has not been investigated in these species-the connections between projection neurons and the Kenyon cells of the mushroom body-and identify species-specific connectivity patterns. We found that neurons encoding food odors connect more frequently with Kenyon cells, giving rise to species-specific biases in connectivity. These species-specific connectivity differences reflect two distinct neuronal phenotypes: in the number of projection neurons or in the number of presynaptic boutons formed by individual projection neurons. Finally, behavioral analyses suggest that such increased connectivity enhances learning performance in an associative task. Our study shows how fine-grained aspects of connectivity architecture in an associative brain center can change during evolution to reflect the chemical ecology of a species.

Automated assessment of cardiac dynamics in aging and dilated cardiomyopathy Drosophila models using machine learning.

The Drosophila model is pivotal in deciphering the pathophysiological underpinnings of various human ailments, notably aging and cardiovascular diseases. Cutting-edge imaging techniques and physiology yield vast high-resolution videos, demanding advanced analysis methods. Our platform leverages deep learning to segment optical microscopy images of Drosophila hearts, enabling the quantification of cardiac parameters in aging and dilated cardiomyopathy (DCM). Validation using experimental datasets confirms the efficacy of our aging model. We employ two innovative approaches deep-learning video classification and machine-learning based on cardiac parameters to predict fly aging, achieving accuracies of 83.3% (AUC 0.90) and 79.1%, (AUC 0.87) respectively. Moreover, we extend our deep-learning methodology to assess cardiac dysfunction associated with the knock-down of oxoglutarate dehydrogenase (OGDH), revealing its potential in studying DCM. This versatile approach promises accelerated cardiac assays for modeling various human diseases in Drosophila and holds promise for application in animal and human cardiac physiology under diverse conditions.

A generalized risk assessment index for forecasting insect population under the effect of temperature.

Life history traits have been studied under various environmental factors, but the ability to combine them into a simple function to assess pest response to climate is still lacking complete understanding. This study proposed a risk index derived by combining development, mortality, and fertility rates from a stage-structured dynamic mathematical model. The first part presents the theoretical framework behind the risk index. The second part of the study is concerned with the application of the index in two case studies of major economic pest: the brown planthopper (Nilaparvata lugens) and the spotted wing drosophila (Drosophila suzukii), pests of rice crops and soft fruits, respectively. The mathematical calculations provided a single function composed of the main thermal biodemographic rates. This function has a threshold value that determines the possibility of population increase as a function of temperature. The tests carried out on the two pest species showed the capability of the index to describe the range of favourable conditions. With this approach, we were able to identify areas where pests are tolerant to climatic conditions and to project them on a geospatial risk map. The theoretical background developed here provided a tool for understanding the biogeography of Nilaparvata lugens and Drosophila suzukii. It is flexible enough to deal with mathematically simple (N. lugens) and complex (D. Suzukii) case studies of crop insect pests. It produces biologically sound indices that behave like thermal performance curves. These theoretical results also provide a reasonable basis for addressing the challenge of pest management in the context of seasonal weather variations and climate change. This may help to improve monitoring and design management strategies to limit the spread of pests in invaded areas, as some non-invaded areas may be suitable for the species to develop.

Identification and genetic analysis of a pervasive 'needle-eye' sperm phenotype in Drosophila sterile hybrid males.

Interspecies hybrid sterility has been extensively studied, especially in the genus Drosophila. Hybrid sterility is more often found in the heterogametic (XY or ZW) sex, a trend called Haldane's rule. Although this phenomenon is pervasive, identification of a common genetic mechanism remains elusive, with modest support found for a range of potential theories. Here, we identify a single precise morphological phenotype, which we call 'needle-eye sperm', that is associated with hybrid sterility in three separate species pairs that span the Drosophila genus. The nature of the phenotype indicates a common point of meiotic failure in sterile hybrid males. We used 10 generations of backcross selection paired with whole-genome pooled sequencing to genetically map the regions underlying the needle-eye (NE) sperm phenotype. Surprisingly, the sterility phenotype was present in ~50% of males even after 10 generations of backcrossing, and only a single region of the X chromosome was associated with sterility in one direction of backcross. Owing to the common phenotype among sterile male hybrids, and the strong effect of individual loci, further exploration of these findings may identify a universal mechanism for the evolution of hybrid sterility.

Elevated sleep quota in a stress-resilient Drosophila species.

Sleep is broadly conserved across the animal kingdom but can vary widely between species. It is currently unclear which selective pressures and regulatory mechanisms influence differences in sleep between species. The fruit fly Drosophila melanogaster has become a successful model system for examining sleep regulation and function, but little is known about the sleep patterns in many related fly species. Here, we find that fly species with adaptations to extreme desert environments, including D. mojavensis, exhibit strong increases in baseline sleep compared with D. melanogaster. Long-sleeping D. mojavensis show intact homeostasis, indicating that desert flies carry an elevated drive for sleep. In addition, D. mojavensis exhibit altered abundance or distribution of several sleep/wake-related neuromodulators and neuropeptides that are consistent with their reduced locomotor activity and increased sleep. Finally, we find that in a nutrient-deprived environment, the sleep patterns of individual D. mojavensis are strongly correlated with their survival time and that disrupting sleep via constant light stimulation renders D. mojavensis more sensitive to starvation. Our results demonstrate that D. mojavensis is a novel model for studying organisms with high sleep drive and for exploring sleep strategies that provide resilience in extreme environments.

Studying foraging behavior to improve bait sprays application to control Drosophila suzukii.

BACKGROUND: Foraging behavior in insects is optimised for locating scattered resources in a complex environment. This behavior can be exploited for use in pest control. Inhibition of feeding can protect crops whereas stimulation can increase the uptake of insecticides. For example, the success of a bait spray, depends on either contact or ingestion, and thus on the insect finding it. METHODS: To develop an effective bait spray against the invasive pest, Drosophila suzukii, we investigated aspects of foraging behavior that influence the likelihood that the pest interacts with the baits, in summer and winter morphotypes. We video-recorded the flies' approach behavior towards four stimuli in a two-choice experiment on strawberry leaflets. To determine the most effective bait positioning, we also assessed where on plants the pest naturally forages, using a potted raspberry plant under natural environmental conditions. We also studied starvation resistance at 20 °C and 12 °C for both morphs. RESULTS: We found that summer morph flies spent similar time on all baits (agar, combi-protec, yeast) whereas winter morphs spent more time on yeast than the other baits. Both morphs showed a preference to feed at the top of our plant's canopy. Colder temperatures enhanced survival under starvation conditions in both morphs, and mortality was reduced by food treatment. CONCLUSIONS: These findings on feeding behavior support informed decisions on the type and placement of a bait to increase pest control.

Peripheral preprocessing in Drosophila facilitates odor classification.

The mammalian brain implements sophisticated sensory processing algorithms along multilayered ("deep") neural networks. Strategies that insects use to meet similar computational demands, while relying on smaller nervous systems with shallow architectures, remain elusive. Using Drosophila as a model, we uncover the algorithmic role of odor preprocessing by a shallow network of compartmentalized olfactory receptor neurons. Each compartment operates as a ratiometric unit for specific odor-mixtures. This computation arises from a simple mechanism: electrical coupling between two differently sized neurons. We demonstrate that downstream synaptic connectivity is shaped to optimally leverage amplification of a hedonic value signal in the periphery. Furthermore, peripheral preprocessing is shown to markedly improve novel odor classification in a higher brain center. Together, our work highlights a far-reaching functional role of the sensory periphery for downstream processing. By elucidating the implementation of powerful computations by a shallow network, we provide insights into general principles of efficient sensory processing algorithms.

Developmental neuroscience: Building sex-specific adult circuitry from common larval origins.

The development of sex-specific neural circuitry is critical for reproductive behaviors. A new study traces the developmental origin of female-specific neurons that underlie an adult mating behavior to larval neurons common to both sexes in Drosophila.

Temperature-driven coordination of circadian transcriptional regulation.

The circadian clock is an evolutionarily-conserved molecular oscillator that enables species to anticipate rhythmic changes in their environment. At a molecular level, the core clock genes induce circadian oscillations in thousands of genes in a tissue-specific manner, orchestrating myriad biological processes. While previous studies have investigated how the core clock circuit responds to environmental perturbations such as temperature, the downstream effects of such perturbations on circadian regulation remain poorly understood. By analyzing bulk-RNA sequencing of Drosophila fat bodies harvested from flies subjected to different environmental conditions, we demonstrate a highly condition-specific circadian transcriptome: genes are cycling in a temperature-specific manner, and the distributions of their phases also differ between the two conditions. Further employing a reference-based gene regulatory network (Reactome), we find evidence of increased gene-gene coordination at low temperatures and synchronization of rhythmic genes that are network neighbors. We report that the phase differences between cycling genes increase as a function of geodesic distance in the low temperature condition, suggesting increased coordination of cycling on the gene regulatory network. Our results suggest a potential mechanism whereby the circadian clock mediates the fly's response to seasonal changes in temperature.

Changes in the cellular makeup of motor patterning circuits drive courtship song evolution in Drosophila.

How evolutionary changes in genes and neurons encode species variation in complex motor behaviors is largely unknown. Here, we develop genetic tools that permit a neural circuit comparison between the model species Drosophila melanogaster and the closely related species D. yakuba, which has undergone a lineage-specific loss of sine song, one of the two major types of male courtship song in Drosophila. Neuroanatomical comparison of song-patterning neurons called TN1 across the phylogeny demonstrates a link between the loss of sine song and a reduction both in the number of TN1 neurons and the neurites supporting the sine circuit connectivity. Optogenetic activation confirms that TN1 neurons in D. yakuba have lost the ability to drive sine song, although they have maintained the ability to drive the singing wing posture. Single-cell transcriptomic comparison shows that D. yakuba specifically lacks a cell type corresponding to TN1A neurons, the TN1 subtype that is essential for sine song. Genetic and developmental manipulation reveals a functional divergence of the sex determination gene doublesex in D. yakuba to reduce TN1 number by promoting apoptosis. Our work illustrates the contribution of motor patterning circuits and cell type changes in behavioral evolution and uncovers the evolutionary lability of sex determination genes to reconfigure the cellular makeup of neural circuits.