Can Drosophila melanogaster tell who's who?

The ortholog of human ssDNA-binding protein SSBP3 influences neurodevelopment and autism-like behaviors in Drosophila melanogaster

1p32.3 microdeletion/duplication is implicated in many neurodevelopmental disorders-like phenotypes such as developmental delay, intellectual disability, autism, macro/microcephaly, and dysmorphic features. The 1p32.3 chromosomal region harbors several genes critical for development; however, their validation and characterization remain inadequate. One such gene is the single-stranded DNA-binding protein 3 (SSBP3) and its Drosophila melanogaster ortholog is called sequence-specific single-stranded DNA-binding protein (Ssdp). Here, we investigated consequences of Ssdp manipulations on neurodevelopment, gene expression, physiological function, and autism-associated behaviors using Drosophila models. We found that SSBP3 and Ssdp are expressed in excitatory neurons in the brain. Ssdp overexpression caused morphological alterations in Drosophila wing, mechanosensory bristles, and head. Ssdp manipulations also affected the neuropil brain volume and glial cell number in larvae and adult flies. Moreover, Ssdp overexpression led to differential changes in synaptic density in specific brain regions. We observed decreased levels of armadillo in the heads of Ssdp overexpressing flies, as well as a decrease in armadillo and wingless expression in the larval wing discs, implicating the involvement of the canonical Wnt signaling pathway in Ssdp functionality. RNA sequencing revealed perturbation of oxidative stress-related pathways in heads of Ssdp overexpressing flies. Furthermore, Ssdp overexpressing brains showed enhanced reactive oxygen species (ROS), altered neuronal mitochondrial morphology, and up-regulated fission and fusion genes. Flies with elevated levels of Ssdp exhibited heightened anxiety-like behavior, altered decisiveness, defective sensory perception and habituation, abnormal social interaction, and feeding defects, which were phenocopied in the pan-neuronal Ssdp knockdown flies, suggesting that Ssdp is dosage sensitive. Partial rescue of behavioral defects was observed upon normalization of Ssdp levels. Notably, Ssdp knockdown exclusively in adult flies did not produce behavioral and functional defects. Finally, we show that optogenetic manipulation of Ssdp-expressing neurons altered autism-associated behaviors. Collectively, our findings provide evidence that Ssdp, a dosage-sensitive gene in the 1p32.3 chromosomal region, is associated with various anatomical, physiological, and behavioral defects, which may be relevant to neurodevelopmental disorders like autism. Our study proposes SSBP3 as a critical gene in the 1p32.3 microdeletion/duplication genomic region and sheds light on the functional role of Ssdp in neurodevelopmental processes in Drosophila.

Flexibility of neural circuits regulating mating behaviors in mice and flies

Mating is essential for the reproduction of animal species. As mating behaviors are high-risk and energy-consuming processes, it is critical for animals to make adaptive mating decisions. This includes not only finding a suitable mate, but also adapting mating behaviors to the animal's needs and environmental conditions. Internal needs include physical states (e.g., hunger) and emotional states (e.g., fear), while external conditions include both social cues (e.g., the existence of predators or rivals) and non-social factors (e.g., food availability). With recent advances in behavioral neuroscience, we are now beginning to understand the neural basis of mating behaviors, particularly in genetic model organisms such as mice and flies. However, how internal and external factors are integrated by the nervous system to enable adaptive mating-related decision-making in a state- and context-dependent manner is less well understood. In this article, we review recent knowledge regarding the neural basis of flexible mating behaviors from studies of flies and mice. By contrasting the knowledge derived from these two evolutionarily distant model organisms, we discuss potential conserved and divergent neural mechanisms involved in the control of flexible mating behaviors in invertebrate and vertebrate brains.

How Social Experience and Environment Impacts Behavioural Plasticity in Drosophila

An organism's behaviour is influenced by its social environment. Experiences such as social isolation or crowding may have profound short or long-term effects on an individual's behaviour. The composition of the social environment also depends on the genetics and previous experiences of the individuals present, leading to additional potential outcomes from each social interaction. In this article, we review selected literature related to the social environment of the model organism Drosophila melanogaster, and how Drosophila respond to variation in their social experiences throughout their lifetimes. We focus on the effects of social environment on behavioural phenotypes such as courtship, aggression, and group dynamics, as well as other phenotypes such as development and physiology. The consequences of phenotypic plasticity due to social environment are discussed with respect to the ecology and evolution of Drosophila. We also relate these studies to laboratory research practices involving Drosophila and other animals.

Artificial fly visual joint perception neural network inspired by multiple-regional collision detection

The biological visual system includes multiple types of motion sensitive neurons which preferentially respond to specific perceptual regions. However, it still keeps open how to borrow such neurons to construct bio-inspired computational models for multiple-regional collision detection. To fill this gap, this work proposes a visual joint perception neural network with two subnetworks - presynaptic and postsynaptic neural networks, inspired by the preferentialperception characteristics of three horizontal and vertical motion sensitive neurons. Related to the neural network and three hazard detection mechanisms, an artificial fly visual synthesized collision detection model for multiple-regional collision detection is originally developed to monitor possible danger occurrence in the case where one or more moving objects appear in the whole field of view. The experiments can clearly draw two conclusions: (i) the acquired neural network can effectively display the characteristics of visual movement, and (ii) the collision detection model, which outperforms the compared models, can effectively perform multiple-regional collision detection at a high success rate, and only takes about 0.24s to complete the process of collision detection for each virtual or actual image frame with resolution 110×60.

Early Life Experience Shapes Male Behavior and Social Networks in Drosophila

Living in a group creates a complex and dynamic environment in which behavior of individuals is influenced by and affects the behavior of others. Although social interaction and group living are fundamental adaptations exhibited by many organisms, little is known about how prior social experience, internal states, and group composition shape behavior in groups. Here, we present an analytical framework for studying the interplay between social experience and group interaction in Drosophila melanogaster. We simplified the complexity of interactions in a group using a series of experiments in which we controlled the social experience and motivational states of individuals to compare behavioral patterns and social networks of groups under different conditions. We show that social enrichment promotes the formation of distinct group structure that is characterized by high network modularity, high inter-individual and inter-group variance, high inter-individual coordination, and stable social clusters. Using environmental and genetic manipulations, we show that visual cues and cVA-sensing neurons are necessary for the expression of social interaction and network structure in groups. Finally, we explored the formation of group behavior and structure in heterogenous groups composed of flies with distinct internal states and documented emergent structures that are beyond the sum of the individuals that constitute it. Our results demonstrate that fruit flies exhibit complex and dynamic social structures that are modulated by the experience and composition of different individuals within the group. This paves the path for using simple model organisms to dissect the neurobiology of behavior in complex social environments.

What can a non-eusocial insect tell us about the neural basis of group behaviour?

Group behaviour has been extensively studied in canonically social swarming, shoaling and flocking vertebrates and invertebrates, providing great insight into the behavioural and ecological aspects of group living. However, the search for its neuronal basis is lagging behind. In the natural environment, Drosophila melanogaster, increasingly used as a model to study neuronal circuits and behaviour, spend their lives surrounded by several conspecifics of different stages, as well as heterospecifics. Despite their dynamic multi-organism natural environment, the neuronal basis of social behaviours has been typically studied in dyadic interactions, such as mating or aggression. This review will focus on recent studies regarding how the behaviour of fruit flies can be shaped by the nature of the surrounding group. We argue that the rich social environment of Drosophila melanogaster, its arsenal of neurogenetic tools and the ability to use large sample sizes for detailed quantitative behavioural analysis makes this species ideal for mechanistic studies of group behaviour.

MARGO (Massively Automated Real-time GUI for Object-tracking), a platform for high-throughput ethology

Fast object tracking in real time allows convenient tracking of very large numbers of animals and closed-loop experiments that control stimuli for many animals in parallel. We developed MARGO, a MATLAB-based, real-time animal tracking suite for custom behavioral experiments. We demonstrated that MARGO can rapidly and accurately track large numbers of animals in parallel over very long timescales, typically when spatially separated such as in multiwell plates. We incorporated control of peripheral hardware, and implemented a flexible software architecture for defining new experimental routines. These features enable closed-loop delivery of stimuli to many individuals simultaneously. We highlight MARGO's ability to coordinate tracking and hardware control with two custom behavioral assays (measuring phototaxis and optomotor response) and one optogenetic operant conditioning assay. There are currently several open source animal trackers. MARGO's strengths are 1) fast and accurate tracking, 2) high throughput, 3) an accessible interface and data output and 4) real-time closed-loop hardware control for for sensory and optogenetic stimuli, all of which are optimized for large-scale experiments.

MARGO (Massively Automated Real-time GUI for Object-tracking), a platform for high-throughput ethology

Fast object tracking in real time allows convenient tracking of very large numbers of animals and closed-loop experiments that control stimuli for many animals in parallel. We developed MARGO, a MATLAB-based, real-time animal tracking suite for custom behavioral experiments. We demonstrated that MARGO can rapidly and accurately track large numbers of animals in parallel over very long timescales, typically when spatially separated such as in multiwell plates. We incorporated control of peripheral hardware, and implemented a flexible software architecture for defining new experimental routines. These features enable closed-loop delivery of stimuli to many individuals simultaneously. We highlight MARGO's ability to coordinate tracking and hardware control with two custom behavioral assays (measuring phototaxis and optomotor response) and one optogenetic operant conditioning assay. There are currently several open source animal trackers. MARGO's strengths are 1) fast and accurate tracking, 2) high throughput, 3) an accessible interface and data output and 4) real-time closed-loop hardware control for for sensory and optogenetic stimuli, all of which are optimized for large-scale experiments.

Sensory perception of dead conspecifics induces aversive cues and modulates lifespan through serotonin in Drosophila

Sensory perception modulates health and aging across taxa. Understanding the nature of relevant cues and the mechanisms underlying their action may lead to novel interventions that improve the length and quality of life. We found that in the vinegar fly, Drosophila melanogaster, exposure to dead conspecifics in the environment induced cues that were aversive to other flies, modulated physiology, and impaired longevity. The effects of exposure to dead conspecifics on aversiveness and lifespan required visual and olfactory function in the exposed flies. Furthermore, the sight of dead flies was sufficient to produce aversive cues and to induce changes in the head metabolome. Genetic and pharmacologic attenuation of serotonergic signaling eliminated the effects of exposure on aversiveness and lifespan. Our results indicate that Drosophila have an ability to perceive dead conspecifics in their environment and suggest conserved mechanistic links between neural state, health, and aging; the roots of which might be unearthed using invertebrate model systems.