An internal expectation guides Drosophila egg-laying decisions

Connectomic analysis of taste circuits in Drosophila

Our sense of taste is critical for regulating food consumption. The fruit fly Drosophila represents a highly tractable model to investigate mechanisms of taste processing, but taste circuits beyond sensory neurons are largely unidentified. Here, we use a whole-brain connectome to investigate the organization of Drosophila taste circuits. We trace pathways from four populations of sensory neurons that detect different taste modalities and project to the subesophageal zone (SEZ), the primary taste region of the fly brain. We find that second-order taste neurons are primarily located within the SEZ and largely segregated by taste modality, whereas third-order neurons have more projections outside the SEZ and more overlap between modalities. Taste projections out of the SEZ innervate regions implicated in feeding, olfactory processing, and learning. We analyze interconnections within and between taste pathways, characterize modality-dependent differences in taste neuron properties, identify other types of inputs onto taste pathways, and use computational simulations to relate neuronal connectivity to predicted activity. These studies provide insight into the architecture of Drosophila taste circuits.

WENDY: Covariance dynamics based gene regulatory network inference

Determining gene regulatory network (GRN) structure is a central problem in biology, with a variety of inference methods available for different types of data. For a widely prevalent and challenging use case, namely single-cell gene expression data measured after intervention at multiple time points with unknown joint distributions, there is only one known specifically developed method, which does not fully utilize the rich information contained in this data type. We develop an inference method for the GRN in this case, netWork infErence by covariaNce DYnamics, dubbed WENDY. The core idea of WENDY is to model the dynamics of the covariance matrix, and solve this dynamics as an optimization problem to determine the regulatory relationships. To evaluate its effectiveness, we compare WENDY with other inference methods using synthetic data and experimental data. Our results demonstrate that WENDY performs well across different data sets.

Whole-brain annotation and multi-connectome cell typing of Drosophila

The fruit fly Drosophila melanogaster has emerged as a key model organism in neuroscience, in large part due to the concentration of collaboratively generated molecular, genetic and digital resources available for it. Here we complement the approximately 140,000 neuron FlyWire whole-brain connectome1 with a systematic and hierarchical annotation of neuronal classes, cell types and developmental units (hemilineages). Of 8,453 annotated cell types, 3,643 were previously proposed in the partial hemibrain connectome2, and 4,581 are new types, mostly from brain regions outside the hemibrain subvolume. Although nearly all hemibrain neurons could be matched morphologically in FlyWire, about one-third of cell types proposed for the hemibrain could not be reliably reidentified. We therefore propose a new definition of cell type as groups of cells that are each quantitatively more similar to cells in a different brain than to any other cell in the same brain, and we validate this definition through joint analysis of FlyWire and hemibrain connectomes. Further analysis defined simple heuristics for the reliability of connections between brains, revealed broad stereotypy and occasional variability in neuron count and connectivity, and provided evidence for functional homeostasis in the mushroom body through adjustments of the absolute amount of excitatory input while maintaining the excitation/inhibition ratio. Our work defines a consensus cell type atlas for the fly brain and provides both an intellectual framework and open-source toolchain for brain-scale comparative connectomics.

A High-Throughput Method for Quantifying Drosophila Fecundity

The fruit fly, Drosophila melanogaster, is an experimentally tractable model system that has recently emerged as a powerful "new approach methodology" (NAM) for chemical safety testing. As oogenesis is well conserved at the molecular and cellular level, measurements of Drosophila fecundity can be useful for identifying chemicals that affect reproductive health across species. However, standard Drosophila fecundity assays have been difficult to perform in a high-throughput manner because experimental factors such as the physiological state of the flies and environmental cues must be carefully controlled to achieve consistent results. In addition, exposing flies to a large number of different experimental conditions (such as chemical additives in the diet) and manually counting the number of eggs laid to determine the impact on fecundity is time-consuming. We have overcome these challenges by combining a new multiwell fly culture strategy with a novel 3D-printed fly transfer device to rapidly and accurately transfer flies from one plate to another, the RoboCam, a low-cost, custom-built robotic camera to capture images of the wells automatically, and an image segmentation pipeline to automatically identify and quantify eggs. We show that this method is compatible with robust and consistent egg laying throughout the assay period and demonstrate that the automated pipeline for quantifying fecundity is very accurate (r2 = 0.98 for the correlation between the automated egg counts and the ground truth). In addition, we show that this method can be used to efficiently detect the effects on fecundity induced by dietary exposure to chemicals. Taken together, this strategy substantially increases the efficiency and reproducibility of high-throughput egg-laying assays that require exposing flies to multiple different media conditions.

Entomopathogenic Bacillus cereus impairs the fitness of the spotted-wing drosophila, Drosophila suzukii

Drosophila suzukii is a notorious pest which causes devastating damage to thin-skinned fruits, and the larvae feed on the fruit, causing extensive agricultural economic loss. The current application of insecticides to manage this pest results in serious resistance and environmental hazards, so an alternative strategy for D. suzukii biocontrol is urgently needed. Here, we reported that entomopathogenic Bacillus cereus has the potential to biocontrol D. suzukii. We isolated and identified the bacterial strain, B. cereus H1, that was detrimental to the fitness of both D. suzukii progenies and parents. D. suzukii was robustly repelled to depositing eggs on the halves with metabolites of B. cereus H1. Both males and females of D. suzukii were susceptible to B. cereus H1. B. cereus H1 significantly arrested larval development with at least 40% lethal larvae. The median lethal time (LT50) of males and females of D. suzukii challenged with B. cereus H1 was 3 and 2 d, respectively. Moreover, B. cereus H1 disrupted the intestinal integrity and pH value of D. suzukii and resulted in an increase in bacterial load of guts and hemolymph. Mechanistically, infection of B. cereus H1 led to the activation of the dual oxidase (DUOX)-ROS-Jun N-terminal kinase (JNK) pathway. The findings showed that the entomopathogen B. cereus H1 could potentially act as a biological control agent against D. suzukii, advancing fundamental concepts of integrated pest management programs against D. suzukii.

Oviposition experience affects oviposition preference in Drosophila melanogaster

Learning, memorizing, and recalling of potential ovipositing sites can influence oviposition preference. Classical conditioning experiments have shown that vinegar flies can learn the association of olfactory, gustatory, or visual stimuli with either positive or negative unconditioned stimuli. However, less is known about whether similar associations are formed in an ecologically more relevant context like during oviposition. Our experiments reveal that Drosophila melanogaster females increase their preference for substrates they have already experienced. However, this change of preference requires that the flies not only smelled or touched the substrates but also oviposited on them. We furthermore show that such an experience results in long-term memory lasting for at least 4 days, i.e., a duration that so far was shown only for aversive conditioning. Our study thus reveals a different form of associative learning in D. melanogaster that might be highly relevant for settling novel ecological niches.

A high-throughput method for quantifying Drosophila fecundity

Measurements of Drosophila fecundity are used in a wide variety of studies, such as investigations of stem cell biology, nutrition, behavior, and toxicology. In addition, because fecundity assays are performed on live flies, they are suitable for longitudinal studies such as investigations of aging or prolonged chemical exposure. However, standard Drosophila fecundity assays have been difficult to perform in a high-throughput manner because experimental factors such as the physiological state of the flies and environmental cues must be carefully controlled to achieve consistent results. In addition, exposing flies to a large number of different experimental conditions (such as chemical additives in the diet) and manually counting the number of eggs laid to determine the impact on fecundity is time-consuming. We have overcome these challenges by combining a new multiwell fly culture strategy with a novel 3D-printed fly transfer device to rapidly and accurately transfer flies from one plate to another; the RoboCam, a low-cost, custom built robotic camera to capture images of the wells automatically; and an image segmentation pipeline to automatically identify and quantify eggs. We show that this method is compatible with robust and consistent egg laying throughout the assay period; and demonstrate that the automated pipeline for quantifying fecundity is very accurate (r2 = 0.98 for the correlation between the automated egg counts and the ground truth) In addition, we show that this method can be used to efficiently detect the effects on fecundity induced by dietary exposure to chemicals. Taken together, this strategy substantially increases the efficiency and reproducibility of high throughput egg laying assays that require exposing flies to multiple different media conditions.

Neuronal substrates of egg-laying behaviour at the abdominal ganglion of Drosophila melanogaster

Egg-laying in Drosophila is the product of post-mating physiological and behavioural changes that culminate in a stereotyped sequence of actions. Egg-laying harbours a great potential as a paradigm to uncover how the appropriate motor circuits are organized and activated to generate behaviour. To study this programme, we first describe the different phases of the egg-laying programme and the specific actions associated with each phase. Using a combination of neuronal activation and silencing experiments, we identify neurons (OvAbg) in the abdominal ganglion as key players in egg-laying. To generate and functionally characterise subsets of OvAbg, we used an intersectional approach with neurotransmitter specific lines-VGlut, Cha and Gad1. We show that OvAbg/VGlut neurons promote initiation of egg deposition in a mating status dependent way. OvAbg/Cha neurons are required in exploration and egg deposition phases, though activation leads specifically to egg expulsion. Experiments with the OvAbg/Gad1 neurons show they participate in egg deposition. We further show a functional connection of OvAbg neurons with brain neurons. This study provides insight into the organization of neuronal circuits underlying complex motor behaviour.

Increased sugar valuation contributes to the evolutionary shift in egg-laying behavior of the fruit pest Drosophila suzukii

Behavior evolution can promote the emergence of agricultural pests by changing their ecological niche. For example, the insect pest Drosophila suzukii has shifted its oviposition (egg-laying) niche from fermented fruits to ripe, non-fermented fruits, causing significant damage to a wide range of fruit crops worldwide. We investigate the chemosensory changes underlying this evolutionary shift and ask whether fruit sugars, which are depleted during fermentation, are important gustatory cues that direct D. suzukii oviposition to sweet, ripe fruits. We show that D. suzukii has expanded its range of oviposition responses to lower sugar concentrations than the model D. melanogaster, which prefers to lay eggs on fermented fruit. The increased response of D. suzukii to sugar correlates with an increase in the value of sugar relative to a fermented strawberry substrate in oviposition decisions. In addition, we show by genetic manipulation of sugar-gustatory receptor neurons (GRNs) that sugar perception is required for D. suzukii to prefer a ripe substrate over a fermented substrate, but not for D. melanogaster to prefer the fermented substrate. Thus, sugar is a major determinant of D. suzukii's choice of complex substrates. Calcium imaging experiments in the brain's primary gustatory center (suboesophageal zone) show that D. suzukii GRNs are not more sensitive to sugar than their D. melanogaster counterparts, suggesting that increased sugar valuation is encoded in downstream circuits of the central nervous system (CNS). Taken together, our data suggest that evolutionary changes in central brain sugar valuation computations are involved in driving D. suzukii's oviposition preference for sweet, ripe fruit.

Behavioral neuroscience: Computation in individual neurons

Information coding is generally thought to emerge from fast activity across thousands of neurons. A recent study shows that many features of a sophisticated decision-action sequence are encoded by the slow activity of individual command neurons.

Whole-brain annotation and multi-connectome cell typing quantifies circuit stereotypy in Drosophila

The fruit fly Drosophila melanogaster combines surprisingly sophisticated behaviour with a highly tractable nervous system. A large part of the fly's success as a model organism in modern neuroscience stems from the concentration of collaboratively generated molecular genetic and digital resources. As presented in our FlyWire companion paper 1 , this now includes the first full brain connectome of an adult animal. Here we report the systematic and hierarchical annotation of this ~130,000-neuron connectome including neuronal classes, cell types and developmental units (hemilineages). This enables any researcher to navigate this huge dataset and find systems and neurons of interest, linked to the literature through the Virtual Fly Brain database 2 . Crucially, this resource includes 4,552 cell types. 3,094 are rigorous consensus validations of cell types previously proposed in the hemibrain connectome 3 . In addition, we propose 1,458 new cell types, arising mostly from the fact that the FlyWire connectome spans the whole brain, whereas the hemibrain derives from a subvolume. Comparison of FlyWire and the hemibrain showed that cell type counts and strong connections were largely stable, but connection weights were surprisingly variable within and across animals. Further analysis defined simple heuristics for connectome interpretation: connections stronger than 10 unitary synapses or providing >1% of the input to a target cell are highly conserved. Some cell types showed increased variability across connectomes: the most common cell type in the mushroom body, required for learning and memory, is almost twice as numerous in FlyWire as the hemibrain. We find evidence for functional homeostasis through adjustments of the absolute amount of excitatory input while maintaining the excitation-inhibition ratio. Finally, and surprisingly, about one third of the cell types proposed in the hemibrain connectome could not yet be reliably identified in the FlyWire connectome. We therefore suggest that cell types should be defined to be robust to inter-individual variation, namely as groups of cells that are quantitatively more similar to cells in a different brain than to any other cell in the same brain. Joint analysis of the FlyWire and hemibrain connectomes demonstrates the viability and utility of this new definition. Our work defines a consensus cell type atlas for the fly brain and provides both an intellectual framework and open source toolchain for brain-scale comparative connectomics.

A rise-to-threshold process for a relative-value decision

Whereas progress has been made in the identification of neural signals related to rapid, cued decisions1-3, less is known about how brains guide and terminate more ethologically relevant decisions in which an animal's own behaviour governs the options experienced over minutes4-6. Drosophila search for many seconds to minutes for egg-laying sites with high relative value7,8 and have neurons, called oviDNs, whose activity fulfills necessity and sufficiency criteria for initiating the egg-deposition motor programme9. Here we show that oviDNs express a calcium signal that (1) dips when an egg is internally prepared (ovulated), (2) drifts up and down over seconds to minutes-in a manner influenced by the relative value of substrates-as a fly determines whether to lay an egg and (3) reaches a consistent peak level just before the abdomen bend for egg deposition. This signal is apparent in the cell bodies of oviDNs in the brain and it probably reflects a behaviourally relevant rise-to-threshold process in the ventral nerve cord, where the synaptic terminals of oviDNs are located and where their output can influence behaviour. We provide perturbational evidence that the egg-deposition motor programme is initiated once this process hits a threshold and that subthreshold variation in this process regulates the time spent considering options and, ultimately, the choice taken. Finally, we identify a small recurrent circuit that feeds into oviDNs and show that activity in each of its constituent cell types is required for laying an egg. These results argue that a rise-to-threshold process regulates a relative-value, self-paced decision and provide initial insight into the underlying circuit mechanism for building this process.

Odor-regulated oviposition behavior in an ecological specialist

Colonization of a novel ecological niche can require, or be driven by, evolution of an animal's behaviors promoting their reproductive success. We investigated the evolution and sensory basis of oviposition in Drosophila sechellia, a close relative of Drosophila melanogaster that exhibits extreme specialism for Morinda citrifolia noni fruit. D. sechellia produces fewer eggs than other drosophilids and lays these almost exclusively on noni substrates. We show that visual, textural and social cues do not explain this species-specific preference. By contrast, we find that loss of olfactory input in D. sechellia, but not D. melanogaster, essentially abolishes egg-laying, suggesting that olfaction gates gustatory-driven noni preference. Noni odors are detected by redundant olfactory pathways, but we discover a role for hexanoic acid and the cognate Ionotropic receptor 75b (Ir75b) in odor-evoked oviposition. Through receptor exchange in D. melanogaster, we provide evidence for a causal contribution of odor-tuning changes in Ir75b to the evolution of D. sechellia's oviposition behavior.