Ethoscopes: An open platform for high-throughput ethomics

The open toolbox for behavioral research

In this work, we describe a new open-source MATLAB toolbox for the control of behavioral experiments. The toolbox caters to very different types of experiments in different species, and with different underlying hardware. Typical examples are operant chambers in animals, with or without neurophysiology, behavioral experiments in human subjects, and neurophysiological recordings in humans such as EEG and fMRI. In addition, the toolbox supports communication via Ethernet to either control and monitor one or several experimental setups remotely or to implement distributed paradigms across different computers. This flexibility is possible, since the toolbox supports a wide range of hardware, some of which is custom developments. An example is a fast network-based digital-IO device for the communication with experimental hardware such as feeders or triggers in neurophysiological setups. We also included functions for online video analysis allowing paradigms to be contingent on responses to a screen, the head movement of a bird in an operant chamber, or the physical location of an animal in an open arena. While the toolbox is well tested and many components of it have been in use for many years, we do not see it as a finished product but rather a continuing development with a focus on easy extendibility and customization.

FlyVISTA, an Integrated Machine Learning Platform for Deep Phenotyping of Sleep in Drosophila

Animal behavior depends on internal state. While subtle movements can signify significant changes in internal state, computational methods for analyzing these "microbehaviors" are lacking. Here, we present FlyVISTA, a machine-learning platform to characterize microbehaviors in freely-moving flies, which we use to perform deep phenotyping of sleep. This platform comprises a high-resolution closed-loop video imaging system, coupled with a deep-learning network to annotate 35 body parts, and a computational pipeline to extract behaviors from high-dimensional data. FlyVISTA reveals the distinct spatiotemporal dynamics of sleep-associated microbehaviors in flies. We further show that stimulation of dorsal fan-shaped body neurons induces micromovements, not sleep, whereas activating R5 ring neurons triggers rhythmic proboscis extension followed by persistent sleep. Importantly, we identify a novel microbehavior ("haltere switch") exclusively seen during quiescence that indicates a deeper sleep stage. These findings enable the rigorous analysis of sleep in Drosophila and set the stage for computational analyses of microbehaviors.

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.

How does a fly die? Insights into ageing from the pathophysiology of Drosophila mortality

The fruit fly Drosophila melanogaster is a common animal model in ageing research. Large populations of flies are used to study the impact of genetic, nutritional and pharmacological interventions on survival. However, the processes through which flies die and their relative prevalence in Drosophila populations are still comparatively unknown. Understanding the causes of death in an animal model is essential to dissect the lifespan-extending interventions that are organism- or disease-specific from those broadly applicable to ageing. Here, we review the pathophysiological processes that can lead to fly death and discuss their relation to ageing.

Single-cell transcriptomics reveals that glial cells integrate homeostatic and circadian processes to drive sleep-wake cycles

The sleep-wake cycle is determined by circadian and sleep homeostatic processes. However, the molecular impact of these processes and their interaction in different brain cell populations are unknown. To fill this gap, we profiled the single-cell transcriptome of adult Drosophila brains across the sleep-wake cycle and four circadian times. We show cell type-specific transcriptomic changes, with glia displaying the largest variation. Glia are also among the few cell types whose gene expression correlates with both sleep homeostat and circadian clock. The sleep-wake cycle and sleep drive level affect the expression of clock gene regulators in glia, and disrupting clock genes specifically in glia impairs homeostatic sleep rebound after sleep deprivation. These findings provide a comprehensive view of the effects of sleep homeostatic and circadian processes on distinct cell types in an entire animal brain and reveal glia as an interaction site of these two processes to determine sleep-wake dynamics.

GoFish: A low-cost, open-source platform for closed-loop behavioural experiments on fish

Fish are the most species-rich vertebrate group, displaying vast ecological, anatomical and behavioural diversity, and therefore are of major interest for the study of behaviour and its evolution. However, with respect to other vertebrates, fish are relatively underrepresented in psychological and cognitive research. A greater availability of easily accessible, flexible, open-source experimental platforms that facilitate the automation of task control and data acquisition may help to reduce this bias and improve the scalability and refinement of behavioural experiments in a range of different fish species. Here we present GoFish, a fully automated platform for behavioural experiments in aquatic species. GoFish includes real-time video tracking of subjects, presentation of stimuli in a computer screen, an automatic feeder device, and closed-loop control of task contingencies and data acquisition. The design and software components of the platform are freely available, while the hardware is open-source and relatively inexpensive. The control software, Bonsai, is designed to facilitate rapid development of task workflows and is supported by a growing community of users. As an illustration and test of its use, we present the results of two experiments on discrimination learning, reversal, and choice in goldfish (Carassius auratus). GoFish facilitates the automation of high-throughput protocols and the acquisition of rich behavioural data. Our platform has the potential to become a widely used tool that facilitates complex behavioural experiments in aquatic species.

pi_tailtrack: A compact, inexpensive and open-source behaviour-tracking system for head-restrained zebrafish

Quantifying animal behaviour during microscopy is crucial to associate optically recorded neural activity with behavioural outputs and states. Here, I describe an imaging and tracking system for head-restrained larval zebrafish compatible with functional microscopy. This system is based on the Raspberry Pi computer, Pi NoIR camera and open-source software for the real-time tail segmentation and skeletonization of the zebrafish tail at over 100 Hz. This allows for precise and long-term analyses of swimming behaviour, which can be related to functional signals recorded in individual neurons. This system offers a simple but performant solution for quantifying the behaviour of head-restrained larval zebrafish, which can be built for 340€.

A reductionist paradigm for high-throughput behavioural fingerprinting in Drosophila melanogaster

Understanding how the brain encodes behaviour is the ultimate goal of neuroscience and the ability to objectively and reproducibly describe and quantify behaviour is a necessary milestone on this path. Recent technological progresses in machine learning and computational power have boosted the development and adoption of systems leveraging on high-resolution video recording to track an animal pose and describe behaviour in all four dimensions. However, the high temporal and spatial resolution that these systems offer must come as a compromise with their throughput and accessibility. Here, we describe coccinella, an open-source reductionist framework combining high-throughput analysis of behaviour using real-time tracking on a distributed mesh of microcomputers (ethoscopes) with resource-lean statistical learning (HCTSA/Catch22). Coccinella is a reductionist system, yet outperforms state-of-the-art alternatives when exploring the pharmacobehaviour in Drosophila melanogaster.

Differential adhesion during development establishes individual neural stem cell niches and shapes adult behaviour in Drosophila

Neural stem cells (NSCs) reside in a defined cellular microenvironment, the niche, which supports the generation and integration of newborn neurons. The mechanisms building a sophisticated niche structure around NSCs and their functional relevance for neurogenesis are yet to be understood. In the Drosophila larval brain, the cortex glia (CG) encase individual NSC lineages in membranous chambers, organising the stem cell population and newborn neurons into a stereotypic structure. We first found that CG wrap around lineage-related cells regardless of their identity, showing that lineage information builds CG architecture. We then discovered that a mechanism of temporally controlled differential adhesion using conserved complexes supports the individual encasing of NSC lineages. An intralineage adhesion through homophilic Neuroglian interactions provides strong binding between cells of a same lineage, while a weaker interaction through Neurexin-IV and Wrapper exists between NSC lineages and CG. Loss of Neuroglian results in NSC lineages clumped together and in an altered CG network, while loss of Neurexin-IV/Wrapper generates larger yet defined CG chamber grouping several lineages together. Axonal projections of newborn neurons are also altered in these conditions. Further, we link the loss of these 2 adhesion complexes specifically during development to locomotor hyperactivity in the resulting adults. Altogether, our findings identify a belt of adhesions building a neurogenic niche at the scale of individual stem cell and provide the proof of concept that niche properties during development shape adult behaviour.

Homeostatic control of deep sleep and molecular correlates of sleep pressure in Drosophila

Homeostatic control of sleep is typically addressed through mechanical stimulation-induced forced wakefulness and the measurement of subsequent increases in sleep. A major confound attends this approach: biological responses to deprivation may reflect a direct response to the mechanical insult rather than to the loss of sleep. Similar confounds accompany all forms of sleep deprivation and represent a major challenge to the field. Here, we describe a new paradigm for sleep deprivation in Drosophila that fully accounts for sleep-independent effects. Our results reveal that deep sleep states are the primary target of homeostatic control and establish the presence of multi-cycle sleep rebound following deprivation. Furthermore, we establish that specific deprivation of deep sleep states results in state-specific homeostatic rebound. Finally, by accounting for the molecular effects of mechanical stimulation during deprivation experiments, we show that serotonin levels track sleep pressure in the fly's central brain. Our results illustrate the critical need to control for sleep-independent effects of deprivation when examining the molecular correlates of sleep pressure and call for a critical reassessment of work that has not accounted for such non-specific effects.

Visual impairment cell non-autonomously dysregulates brain-wide proteostasis

Loss of hearing or vision has been identified as a significant risk factor for dementia but underlying molecular mechanisms are unknown. In different Drosophila models of blindness, we observe non-autonomous induction of stress granules in the brain and their reversal upon restoration of vision. Stress granules include cytosolic condensates of p62, ATF4 and XRP1. This cytosolic restraint of the ATF4 and XRP1 transcription factors dampens expression of their downstream targets during cellular stress. Cytosolic condensates of p62 and ATF4 were also evident in the thalamus and hippocampus of mouse models of congenital or degenerative blindness. These data indicate conservation of the link between loss of sensory input and dysregulation of stress responses critical for protein quality control in the brain.

Ethoscopy and ethoscope-lab: a framework for behavioural analysis to lower entrance barrier and aid reproducibility

Summary

High-throughput analysis of behaviour is a pivotal instrument in modern neuroscience, allowing researchers to combine modern genetics breakthrough to unbiased, objective, reproducible experimental approaches. To this extent, we recently created an open-source hardware platform (ethoscope; Geissmann Q, Garcia Rodriguez L, Beckwith EJ et al. Rethomics: an R framework to analyse high-throughput behavioural data. PLoS One 2019;14:e0209331) that allows for inexpensive, accessible, high-throughput analysis of behaviour in Drosophila or other animal models. Here we equip ethoscopes with a Python framework for data analysis, ethoscopy, designed to be a user-friendly yet powerful platform, meeting the requirements of researchers with limited coding expertise as well as experienced data scientists.

Availability and implementation

Ethoscopy is best consumed in a prebaked Jupyter-based docker container, ethoscope-lab, to improve accessibility and to encourage the use of notebooks as a natural platform to share post-publication data analysis. Ethoscopy is a Python package available on GitHub and PyPi. Ethoscope-lab is a docker container available on DockerHub. A landing page aggregating all the code and documentation is available at https://lab.gilest.ro/ethoscopy.

A simple method to account for thermal boundary layers during the estimation of CTmax in small ectotherms

As temperatures rise, understanding how ectotherms will become impacted by thermal stress is of critical importance. In this context, many researchers quantify critical temperatures - these are the upper (CTmax) and lower (CTmin) thermal limits at which organisms can no longer function. Most studies estimate CTs using bath-based methods where organisms are submerged within a set thermal environment. Plate-based methods (i.e. hot plates), however, offer huge opportunity for automation and are readily available in many lab settings. Plates, however, generate a unidirectional thermal boundary layer above their surface which means that the temperatures experienced by organisms of different sizes is different. This boundary layer effect can bias estimates of critical temperatures. Here, we test the hypothesis that biases in critical temperature estimation on hot plates are driven by organism height. We also quantify the composition of the boundary layer in order to correct for these biases. We assayed four differently sized species of UK ants for their CTmax in dry baths (with no boundary layer) and on hot plates (with a boundary layer). We found that hot plates overestimated the CTmax values of the different ants, and that this overestimate was larger for taller species. By statistically modelling the thickness of the thermal boundary layer, and combining with estimates of species height, we were able to correct this overestimation and eliminate methodological differences. Our study provides two main findings. First, we provide evidence that organism height is positively related to the bias present in plate-based estimates of CTmax. Second, we show that a relatively simple statistical model can correct for this bias. By using simple corrections for boundary layer effects, as we have done here, researchers could open up a new possibility space in the design and implementation of thermal tolerance assays using plates rather than restrictive dry or water baths.

Allnighter pseudokinase-mediated feedback links proteostasis and sleep in Drosophila

In nervous systems, retrograde signals are key for organizing circuit activity and maintaining neuronal homeostasis. We identify the conserved Allnighter (Aln) pseudokinase as a cell non-autonomous regulator of proteostasis responses necessary for normal sleep and structural plasticity of Drosophila photoreceptors. In aln mutants exposed to extended ambient light, proteostasis is dysregulated and photoreceptors develop striking, but reversible, dysmorphology. The aln gene is widely expressed in different neurons, but not photoreceptors. However, secreted Aln protein is retrogradely endocytosed by photoreceptors. Inhibition of photoreceptor synaptic release reduces Aln levels in lamina neurons, consistent with secreted Aln acting in a feedback loop. In addition, aln mutants exhibit reduced night time sleep, providing a molecular link between dysregulated proteostasis and sleep, two characteristics of ageing and neurodegenerative diseases.

A double-spiral maze and hi-resolution tracking pipeline to study dispersal by groups of minute insects

Minute insects such as parasitic micro-wasps have high basic and applied importance for their widespread use as biocontrol agents. Their dispersal is a phenotype of particular interest. Classically, it is evaluated using field releases, but those are time consuming, costly, and their results highly variable, preventing high-throughput and repeatability. Alternatively, dispersal can be studied using small-scale assays, but those neglect important higher-scale processes. Consequently, proper evaluation of dispersal is often complicated or lacking in academic studies and biocontrol breeding programs. Here we introduce a new method, the double-spiral maze, that allows the study of spatial propagation of groups of micro-wasps at relevant scales (several hours and meters), retaining high throughput and experimental power. The method records the location of every individual at every time, enabling accurate estimates of diffusion coefficients or other dispersal metrics. We describe this affordable, scalable, and easy-to-implement method, and illustrate its application with a species of agricultural interest.

Neuronal identity defines α-synuclein and tau toxicity

Pathogenic α-synuclein and tau are critical drivers of neurodegeneration, and their mutations cause neuronal loss in patients. Whether the underlying preferential neuronal vulnerability is a cell-type-intrinsic property or a consequence of increased expression levels remains elusive. Here, we explore cell-type-specific α-synuclein and tau expression in human brain datasets and use deep phenotyping as well as brain-wide single-cell RNA sequencing of >200 live neuron types in fruit flies to determine which cellular environments react most to α-synuclein or tau toxicity. We detect phenotypic and transcriptomic evidence of differential neuronal vulnerability independent of α-synuclein or tau expression levels. Comparing vulnerable with resilient neurons in Drosophila enabled us to predict numerous human neuron subtypes with increased intrinsic susceptibility to pathogenic α-synuclein or tau. By uncovering synapse- and Ca²⁺ homeostasis-related genes as tau toxicity modifiers, our work paves the way to leverage neuronal identity to uncover modifiers of neurodegeneration-associated toxic proteins.

Sleep benefits different stages of memory in Drosophila

Understanding the physiological mechanisms that modulate memory acquisition and consolidation remains among the most ambitious questions in neuroscience. Massive efforts have been dedicated to deciphering how experience affects behavior, and how different physiological and sensory phenomena modulate memory. Our ability to encode, consolidate and retrieve memories depends on internal drives, and sleep stands out among the physiological processes that affect memory: one of the most relatable benefits of sleep is the aiding of memory that occurs in order to both prepare the brain to learn new information, and after a learning task, to consolidate those new memories. Drosophila lends itself to the study of the interactions between memory and sleep. The fruit fly provides incomparable genetic resources, a mapped connectome, and an existing framework of knowledge on the molecular, cellular, and circuit mechanisms of memory and sleep, making the fruit fly a remarkable model to decipher the sophisticated regulation of learning and memory by the quantity and quality of sleep. Research in Drosophila has stablished not only that sleep facilitates learning in wild-type and memory-impaired animals, but that sleep deprivation interferes with the acquisition of new memories. In addition, it is well-accepted that sleep is paramount in memory consolidation processes. Finally, studies in Drosophila have shown that that learning itself can promote sleep drive. Nevertheless, the molecular and network mechanisms underlying this intertwined relationship are still evasive. Recent remarkable work has shed light on the neural substrates that mediate sleep-dependent memory consolidation. In a similar way, the mechanistic insights of the neural switch control between sleep-dependent and sleep-independent consolidation strategies were recently described. This review will discuss the regulation of memory by sleep in Drosophila, focusing on the most recent advances in the field and pointing out questions awaiting to be investigated.

High-throughput behavioral phenotyping of tiny arthropods: Chemosensory traits in a mesostigmatic hematophagous mite

Pest management using attractive and/or repellent semiochemicals is a key alternative to synthetic insecticides. Its implementation requires a good understanding of the intra- and interspecific chemical interactions of arthropod pests, their interactions with their abiotic environment, as well as their evolutionary dynamics. Although mites include many pest species and biocontrol agents of economic importance in agriculture, their chemical ecology is largely understudied compared to insects. We developed a high-throughput ethomics system to analyze these small arthropods and conducted a study on Dermanyssus gallinae, a problematic poultry parasite in the egg industry. Our purpose was to elucidate the role played by host-derived odorants (synthetic kairomone) and conspecific odorants (mite body odors) in D. gallinae. After validating our nanocomputer controlled olfactometric system with volatile semiochemicals of known biological activity, we characterized response traits to kairomonal and/or pheromonal volatile blends in mites from different populations. We were able to accurately characterize the repulsion or attraction behaviors in >1000 individual specimens in a standardized way. Our results confirm the presence of a volatile aggregation pheromone emitted by D. gallinae and bring new elements to the effect of odor source presentation. Our results also confirm the attractive effect on Dermanyssus gallinae of a blend of volatile compounds contained in hen odor, while highlighting a repellent effect at high concentration. Significant interindividual and interpopulation variation was noted particularly in responses to synthetic kairomone. This information lays a valuable foundation for further exploring the emergence risk of resistance to semiochemicals.

The translational genetics of ADHD and related phenotypes in model organisms

Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent neurodevelopmental disorder resulting from the interaction between genetic and environmental risk factors. It is well known that ADHD co-occurs frequently with other psychiatric disorders due, in part, to shared genetics factors. Although many studies have contributed to delineate the genetic landscape of psychiatric disorders, their specific molecular underpinnings are still not fully understood. The use of animal models can help us to understand the role of specific genes and environmental stimuli-induced epigenetic modifications in the pathogenesis of ADHD and its comorbidities. The aim of this review is to provide an overview on the functional work performed in rodents, zebrafish and fruit fly and highlight the generated insights into the biology of ADHD, with a special focus on genetics and epigenetics. We also describe the behavioral tests that are available to study ADHD-relevant phenotypes and comorbid traits in these models. Furthermore, we have searched for new models to study ADHD and its comorbidities, which can be useful to test potential pharmacological treatments.

A ShK-like Domain from Steinernema carpocapsae with Bioinsecticidal Potential

Entomopathogenic nematodes are used as biological control agents against a broad range of insect pests. We ascribed the pathogenicity of these organisms to the excretory/secretory products (ESP) released by the infective nematode. Our group characterized different virulence factors produced by Steinernema carpocapsae that underlie its success as an insect pathogen. A novel ShK-like peptide (ScK1) from this nematode that presents high sequence similarity with the ShK peptide from a sea anemone was successfully produced recombinantly in Escherichia coli. The secondary structure of ScK1 appeared redox-sensitive, exhibiting a far-UV circular dichroism spectrum consistent with an alpha-helical secondary structure. Thermal denaturation of the ScK1 allowed estimating the melting temperature to 59.2 ± 0.1 °C. The results from toxicity assays using Drosophila melanogaster as a model show that injection of this peptide can kill insects in a dose-dependent manner with an LD₅₀ of 16.9 µM per adult within 24 h. Oral administration of the fusion protein significantly reduced the locomotor activity of insects after 48 h (p < 0.05, Tukey's test). These data show that this nematode expresses insecticidal peptides with potential as next-generation insecticides.

PiSpy: An affordable, accessible, and flexible imaging platform for the automated observation of organismal biology and behavior

A great deal of understanding can be gleaned from direct observation of organismal growth, development, and behavior. However, direct observation can be time consuming and influence the organism through unintentional stimuli. Additionally, video capturing equipment can often be prohibitively expensive, difficult to modify to one's specific needs, and may come with unnecessary features. Here, we describe PiSpy, a low-cost, automated video acquisition platform that uses a Raspberry Pi computer and camera to record video or images at specified time intervals or when externally triggered. All settings and controls, such as programmable light cycling, are accessible to users with no programming experience through an easy-to-use graphical user interface. Importantly, the entire PiSpy system can be assembled for less than $100 using laser-cut and 3D-printed components. We demonstrate the broad applications and flexibility of PiSpy across a range of model and non-model organisms. Designs, instructions, and code can be accessed through an online repository, where a global community of PiSpy users can also contribute their own unique customizations and help grow the community of open-source research solutions.

Physiological and life history changes associated with seasonal adaptation in the cactophilic Drosophila mojavensis

Many insects inhabiting temperate climates are faced with changing environmental conditions throughout the year. Depending on the species, these environmental fluctuations can be experienced within a single generation or across multiple generations. Strategies for dealing with these seasonal changes vary across populations. Drosophila mojavensis is a cactophilic Drosophila species endemic to the Sonoran Desert. The Sonoran Desert regularly reaches temperatures of 50°C in the summer months. As individuals of this population are rare to collect in the summer months, we simulated the cycling temperatures experienced by D. mojavensis in the Sonoran Desert from April to July (four generations) in a temperature- and light-controlled chamber, to understand the physiological and life history changes that allow this population to withstand these conditions. In contrast to our hypothesis of a summer aestivation, we found that D. mojavensis continue to reproduce during the summer months, albeit with lower viability, but the adult survivorship of the population is highly reduced during this period. As expected, stress resistance increased during the summer months in both the adult and the larval stages. This study examines several strategies for withstanding the Sonoran Desert summer conditions which may be informative in the study of other desert endemic species.

Population dynamics of a poultry hematophagous mite: characterization of the population growth and identification of factors of its slowdown using closed mesocosms

BACKGROUND

A thorough knowledge of the population dynamics of pests and of the main factors affecting population growth is an important prerequisite for the development of effective control strategies. Failures of various treatments aimed at regulating populations of Dermanyssus gallinae are regularly reported in poultry farms and pullulations occur very quickly after first detection. To finely characterize population dynamics of D. gallinae, and to identify the factors modulating population growth, we conducted two successive multi-generation experiments using closed mesocosms equipped with or without automatic counters and housing a host full- or part-time (three nights per week).

RESULTS

Population growth was very rapid and the adult to juvenile ratio very different from the prediction by a mathematical model. A male-biased sex ratio was observed in some mesocosms from 21 days and in most mesocosms from 35 days of population growth originating from an inoculum of adult females. A dramatic slowdown in growth was measured in mesocosms equipped with trackers, where the mites' path to the host was constrained. The slowdown in population growth induced by the intermittent presence of the host compared to its full-time presence was much less marked.

CONCLUSION

These findings suggest avenues of research for new management methods. They question the relevance of a critical threshold based on traditional trap monitoring to manage D. gallinae. Our results highlight a unique characteristic of D. gallinae that makes it a recalcitrant case to threshold-based practices recommended for integrated pest management (IPM) against other arthropod pests. The dramatic effect of a physical constraint for the mite to access the host (unnatural constrained path) confirms an observation made in 1917 and is a reason to design perches that are less conducive to parasite traffic. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Infection increases activity via Toll dependent and independent mechanisms in Drosophila melanogaster

Host behavioural changes are among the most apparent effects of infection. ‘Sickness behaviour’ can involve a variety of symptoms, including anorexia, depression, and changed activity levels. Here, using a real-time tracking and behavioural profiling platform, we show that in Drosophila melanogaster, several systemic bacterial infections cause significant increases in physical activity, and that the extent of this activity increase is a predictor of survival time in some lethal infections. Using multiple bacteria and D. melanogaster immune and activity mutants, we show that increased activity is driven by at least two different mechanisms. Increased activity after infection with Micrococcus luteus, a Gram-positive bacterium rapidly cleared by the immune response, strictly requires the Toll ligand spätzle. In contrast, increased activity after infection with Francisella novicida, a Gram-negative bacterium that cannot be cleared by the immune response, is entirely independent of both Toll and the parallel IMD pathway. The existence of multiple signalling mechanisms by which bacterial infections drive increases in physical activity implies that this effect may be an important aspect of the host response.

Sickness behaviours are often observed during infection. Animals have been shown to change their feeding, mating, social and resting (sleeping) behaviours in response to infection. We show here that fruit-flies infected with bacteria respond by increasing their physical activity and decreasing the amount of time spent sleeping. This increase in activity is seen in some, but not all, bacterial infections, and appears to be driven by at least two different mechanisms: with some bacteria, activating the immune response is the only requirement to induce increased activity, while other bacteria induce increased activity independently of known immune detection pathways. The biological role of increased activity is unclear; flies in the wild may be driven to flee sites where infection risk or pathogen burden is high. Alternatively, increased activity could serve a less direct anti-microbial function. For example, active animals may be more likely to encounter potential mates or food resource.

Open Hardware in Science: The Benefits of Open Electronics

Openly shared low-cost electronic hardware applications, known as open electronics, have sparked a new open-source movement, with much untapped potential to advance scientific research. Initially designed to appeal to electronic hobbyists, open electronics have formed a global “maker” community and are increasingly used in science and industry. In this perspective article, we review the current costs and benefits of open electronics for use in scientific research ranging from the experimental to the theoretical sciences. We discuss how user-made electronic applications can help (I) individual researchers, by increasing the customization, efficiency, and scalability of experiments, while improving data quantity and quality; (II) scientific institutions, by improving access to customizable high-end technologies, sustainability, visibility, and interdisciplinary collaboration potential; and (III) the scientific community, by improving transparency and reproducibility, helping decouple research capacity from funding, increasing innovation, and improving collaboration potential among researchers and the public. We further discuss how current barriers like poor awareness, knowledge access, and time investments can be resolved by increased documentation and collaboration, and provide guidelines for academics to enter this emerging field. We highlight that open electronics are a promising and powerful tool to help scientific research to become more innovative and reproducible and offer a key practical solution to improve democratic access to science.

A Markerless Pose Estimator Applicable to Limbless Animals

The analysis of kinematics, locomotion, and spatial tasks relies on the accurate detection of animal positions and pose. Pose and position can be assessed with video analysis programs, the “trackers.” Most available trackers represent animals as single points in space (no pose information available) or use markers to build a skeletal representation of pose. Markers are either physical objects attached to the body (white balls, stickers, or paint) or they are defined in silico using recognizable body structures (e.g., joints, limbs, color patterns). Physical markers often cannot be used if the animals are small, lack prominent body structures on which the markers can be placed, or live in environments such as aquatic ones that might detach the marker. Here, we introduce a marker-free pose-estimator (LACE Limbless Animal traCkEr) that builds the pose of the animal de novo from its contour. LACE detects the contour of the animal and derives the body mid-line, building a pseudo-skeleton by defining vertices and edges. By applying LACE to analyse the pose of larval Drosophila melanogaster and adult zebrafish, we illustrate that LACE allows to quantify, for example, genetic alterations of peristaltic movements and gender-specific locomotion patterns that are associated with different body shapes. As illustrated by these examples, LACE provides a versatile method for assessing position, pose and movement patterns, even in animals without limbs.

Sleep correlates with behavioral decision making critical for reproductive output in Drosophila melanogaster

Balance between sleep, wakefulness and arousal is important for survival of organisms and species as a whole. While, the benefits of sleep both in terms of quantity and quality is widely recognized across species, sleep has a cost for organismal survival and reproduction. Here we focus on how sleep duration, sleep depth and sleep pressure affect the ability of animals to engage in courtship and egg-laying behaviors critical for reproductive success. Using isogenic lines from the Drosophila Genetic Reference Panel with variable sleep phenotypes we investigated the relationship between sleep and reproductive behaviors, courtship and oviposition. We found that three out of five lines with decreased sleep and increased arousal phenotypes, showed increased courtship and decreased latency to court as compared to normal and long sleeping lines. However, the male courtship phenotype is dependent on context and genotype as some but not all long sleeping-low courting lines elevate their courtship in the presence of short sleeping-high courting flies. We also find that unlike courtship, sleep phenotypes were less variable and minimally susceptible to social experience. In addition to male courtship, we also investigated egg-laying phenotype, a readout of female reproductive output and find oviposition to be less sensitive to sleep length and parameters that are indicative of switch between sleep and wake states. Taken together our extensive behavioral analysis here shows complex bidirectional interactions between genotype and environment and add to the growing evidence linking sleep duration and sleep-wake switch parameters to behavioral decision making critical to reproductive output.

Behavior Individuality: A Focus on Drosophila melanogaster

Among individuals, behavioral differences result from the well-known interplay of nature and nurture. Minute differences in the genetic code can lead to differential gene expression and function, dramatically affecting developmental processes and adult behavior. Environmental factors, epigenetic modifications, and gene expression and function are responsible for generating stochastic behaviors. In the last decade, the advent of high-throughput sequencing has facilitated studying the genetic basis of behavior and individuality. We can now study the genomes of multiple individuals and infer which genetic variations might be responsible for the observed behavior. In addition, the development of high-throughput behavioral paradigms, where multiple isogenic animals can be analyzed in various environmental conditions, has again facilitated the study of the influence of genetic and environmental variations in animal personality. Mainly, Drosophila melanogaster has been the focus of a great effort to understand how inter-individual behavioral differences emerge. The possibility of using large numbers of animals, isogenic populations, and the possibility of modifying neuronal function has made it an ideal model to search for the origins of individuality. In the present review, we will focus on the recent findings that try to shed light on the emergence of individuality with a particular interest in D. melanogaster.

Redundant functions of the SLC5A transporters Rumpel, Bumpel, and Kumpel in ensheathing glial cells

Neuronal processing is energy demanding, and relies on sugar metabolism. To nurture the Drosophila nervous system, the blood-brain barrier forming glial cells take up trehalose from the hemolymph and then distribute the metabolic products further to all neurons. This function is provided by glucose and lactate transporters of the solute carrier (SLC) 5A family. Here we identified three SLC5A genes that are specifically expressed in overlapping sets of CNS glial cells, rumpel, bumpel and kumpel. We generated mutants in all genes and all mutants are viable and fertile, lacking discernible phenotypes. Loss of rumpel causes subtle locomotor phenotypes and flies display increased daytime sleep. In addition, in bumpel kumpel double mutants, and to an even greater extent in rumpel bumpel kumpel triple mutants, oogenesis is disrupted at the onset of the vitollegenic phase. This indicates a partially redundant functions between these genes. Rescue experiments exploring this effect indicate that oogenesis can be affected by CNS glial cells. Moreover, expression of heterologous mammalian SLC5A transporters, with known transport properties, suggest that Bumpel and/or Kumpel transport glucose or lactate. Overall, our results imply a redundancy in SLC5A nutrient sensing functions in Drosophila glial cells, affecting ovarian development and behavior.

Sensory processing during sleep in Drosophila melanogaster

During sleep, most animal species enter a state of reduced consciousness characterized by a marked sensory disconnect. Yet some processing of the external world must remain intact, given that a sleeping animal can be awoken by intense stimuli (for example, a loud noise or a bright light) or by soft but qualitatively salient stimuli (for example, the sound of a baby cooing or hearing one's own name^1-3). How does a sleeping brain retain the ability to process the quality of sensory information? Here we present a paradigm to study the functional underpinnings of sensory discrimination during sleep in Drosophila melanogaster. We show that sleeping vinegar flies, like humans, discern the quality of sensory stimuli and are more likely to wake up in response to salient stimuli. We also show that the salience of a stimulus during sleep can be modulated by internal states. We offer a prototypical blueprint detailing a circuit involved in this process and its modulation as evidence that the system can be used to explore the cellular underpinnings of how a sleeping brain experiences the world.

The Regulation of Drosophila Sleep

Sleep is critical for diverse aspects of brain function in animals ranging from invertebrates to humans. Powerful genetic tools in the fruit fly Drosophila melanogaster have identified - at an unprecedented level of detail - genes and neural circuits that regulate sleep. This research has revealed that the functions and neural principles of sleep regulation are largely conserved from flies to mammals. Further, genetic approaches to studying sleep have uncovered mechanisms underlying the integration of sleep and many different biological processes, including circadian timekeeping, metabolism, social interactions, and aging. These findings show that in flies, as in mammals, sleep is not a single state, but instead consists of multiple physiological and behavioral states that change in response to the environment, and is shaped by life history. Here, we review advances in the study of sleep in Drosophila, discuss their implications for understanding the fundamental functions of sleep that are likely to be conserved among animal species, and identify important unanswered questions in the field.

Open-source computational framework for studying Drosophila behavioral phase

This protocol describes a standardized method for analyzing Drosophila behavioral rhythmicity under light dark cycles, temperature ramps, and free running conditions. The protocol constitutes a step-by-step guide from generation of appropriate Drosophila genetic crosses to behavioral experiments. We also provide an open-source computational framework using R for the analysis of the phase of behavior using circular statistics. An extended method for complete use is also provided.

For complete details on the use and execution of this protocol, please refer to Fernandez et al. (2020).

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R framework for analysis of Drosophila behavioral phase and circular statistics analysis

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Visualization of activity, phase of behavior, and rose plots

Investigating rare and ultrarare epilepsy syndromes with Drosophila models

One in three epilepsy cases is drug resistant, and seizures often begin in infancy, when they are life-threatening and when therapeutic options are highly limited. An important tool for prioritizing and validating genes associated with epileptic conditions, which is suitable for large-scale screening, is disease modeling in Drosophila. Approximately two-thirds of disease genes are conserved in Drosophila, and gene-specific fly models exhibit behavioral changes that are related to symptoms of epilepsy. Models are based on behavior readouts, seizure-like attacks and paralysis following stimulation, and neuronal, cell-biological readouts that are in the majority based on changes in nerve cell activity or morphology. In this review, we focus on behavioral phenotypes. Importantly, Drosophila modeling is independent of, and complementary to, other approaches that are computational and based on systems analysis. The large number of known epilepsy-associated gene variants indicates a need for efficient research strategies. We will discuss the status quo of epilepsy disease modelling in Drosophila and describe promising steps towards the development of new drugs to reduce seizure rates and alleviate other epileptic symptoms.

FreeClimber: automated quantification of climbing performance in Drosophila

Negative geotaxis (climbing) performance is a useful metric for quantifying Drosophila health. Manual methods to quantify climbing performance are tedious and often biased, while many available computational methods have challenging hardware or software requirements. We present an alternative: FreeClimber. This open source, Python-based platform subtracts a video's static background to improve detection for flies moving across heterogeneous backgrounds. FreeClimber calculates a cohort's velocity as the slope of the most linear portion of a mean vertical position versus time curve. It can run from a graphical user interface for optimization or a command line interface for high-throughput and automated batch processing, improving accessibility for users with different expertise. FreeClimber outputs calculated slopes, spot locations for follow-up analyses (e.g. tracking), and several visualizations and plots. We demonstrate FreeClimber's utility in a longitudinal study for endurance exercise performance in Drosophila mitonuclear genotypes using six distinct mitochondrial haplotypes paired with a common D. melanogaster nuclear background.

Sleep: Astrocytes Take Their Toll on Tired Flies

Calcium signalling in astrocytes modulates sleep, yet how astrocytes communicate with neural circuits that control sleep is unclear. A new study now uncovers a calcium-dependent relay between astrocytes and neurons that promotes sleep homeostasis in fruit flies.

The Sleep Nullifying Apparatus: A Highly Efficient Method of Sleep Depriving Drosophila

Sleep homeostasis, the increase in sleep observed following sleep loss, is one of the defining criteria used to identify sleep throughout the animal kingdom. As a consequence, sleep deprivation and sleep restriction are powerful tools that are commonly used to provide insight into sleep function. Nonetheless, sleep deprivation experiments are inherently problematic in that the deprivation stimulus itself may be the cause of observed changes in physiology and behavior. Accordingly, successful sleep deprivation techniques should keep animals awake and, ideally, result in a robust sleep rebound without also inducing a large number of unintended consequences. Here, we describe a sleep deprivation technique for Drosophila melanogaster. The Sleep Nullifying Apparatus (SNAP) administers a stimulus every 10s to induce negative geotaxis. Although the stimulus is predictable, the SNAP effectively prevents >95% of nighttime sleep even in flies with high sleep drive. Importantly, the subsequent homeostatic response is very similar to that achieved using hand-deprivation. The timing and spacing of the stimuli can be modified to minimize sleep loss and thus examine non-specific effects of the stimulus on physiology and behavior. The SNAP can also be used for sleep restriction and to assess arousal thresholds. The SNAP is a powerful sleep disruption technique that can be used to better understand sleep function.

Astroglial Calcium Signaling Encodes Sleep Need in Drosophila

Sleep is under homeostatic control, whereby increasing wakefulness generates sleep need and triggers sleep drive. However, the molecular and cellular pathways by which sleep need is encoded are poorly understood. In addition, the mechanisms underlying both how and when sleep need is transformed to sleep drive are unknown. Here, using ex vivo and in vivo imaging, we show in Drosophila that astroglial Ca²⁺ signaling increases with sleep need. We demonstrate that this signaling is dependent on a specific L-type Ca²⁺ channel and is necessary for homeostatic sleep rebound. Thermogenetically increasing Ca²⁺ in astrocytes induces persistent sleep behavior, and we exploit this phenotype to conduct a genetic screen for genes required for the homeostatic regulation of sleep. From this large-scale screen, we identify TyrRII, a monoaminergic receptor required in astrocytes for sleep homeostasis. TyrRII levels rise following sleep deprivation in a Ca²⁺-dependent manner, promoting further increases in astrocytic Ca²⁺ and resulting in a positive-feedback loop. Moreover, our findings suggest that astrocytes then transmit this sleep need to a sleep drive circuit by upregulating and releasing the interleukin-1 analog Spätzle, which then acts on Toll receptors on R5 neurons. These findings define astroglial Ca²⁺ signaling mechanisms encoding sleep need and reveal dynamic properties of the sleep homeostatic control system.

PiVR: An affordable and versatile closed-loop platform to study unrestrained sensorimotor behavior

Tools enabling closed-loop experiments are crucial to delineate causal relationships between the activity of genetically labeled neurons and specific behaviors. We developed the Raspberry Pi Virtual Reality (PiVR) system to conduct closed-loop optogenetic stimulation of neural functions in unrestrained animals. PiVR is an experimental platform that operates at high temporal resolution (70 Hz) with low latencies (<30 milliseconds), while being affordable ( Collapse

Key Words Collapse

MESH Headings

• Animals
• Behavior, Animal/physiology
• Chemotaxis
• Drosophila melanogaster/physiology
• Larva/physiology
• Light
• Locomotion
• Male
• Neurons/physiology
• Odorants
• Optogenetics
• Sensation/physiology
• Sensorimotor Cortex/physiology
• Software
• Taste/physiology
• Virtual Reality
• Zebrafish

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Grants

• R01 NS113048 NINDS NIH HHS
• R25 GM067110 NIGMS NIH HHS
• National Science Foundation
• National Institute of Health
• Gordon and Betty Moore Foundation

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Affiliation(s)

David Tadres Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, California, United States of America Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, California, United States of America Institute of Molecular Life Sciences, University of Zurich, Zurich, Switzerland

Matthieu Louis Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, Santa Barbara, California, United States of America Neuroscience Research Institute, University of California, Santa Barbara, Santa Barbara, California, United States of America Department of Physics, University of California, Santa Barbara, Santa Barbara, California, United States of America

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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.

Intellectual disability and autism spectrum disorders 'on the fly': insights from Drosophila

Intellectual disability (ID) and autism spectrum disorders (ASD) are frequently co-occurring neurodevelopmental disorders and affect 2-3% of the population. Rapid advances in exome and genome sequencing have increased the number of known implicated genes by threefold, to more than a thousand. The main challenges in the field are now to understand the various pathomechanisms associated with this bewildering number of genetic disorders, to identify new genes and to establish causality of variants in still-undiagnosed cases, and to work towards causal treatment options that so far are available only for a few metabolic conditions. To meet these challenges, the research community needs highly efficient model systems. With an increasing number of relevant assays and rapidly developing novel methodologies, the fruit fly Drosophila melanogaster is ideally positioned to change gear in ID and ASD research. The aim of this Review is to summarize some of the exciting work that already has drawn attention to Drosophila as a model for these disorders. We highlight well-established ID- and ASD-relevant fly phenotypes at the (sub)cellular, brain and behavioral levels, and discuss strategies of how this extraordinarily efficient and versatile model can contribute to 'next generation' medical genomics and to a better understanding of these disorders.

Exploring the Utility of 3-D-printed Laboratory Equipment

Many laboratories utilize different types of opto-mechanical positioning devices in their experiments. Such devices include lateral stages, which provide 1-dimenstional translational movement, 3-dimensional translation stages, and laboratory jacks, which provide a convenient way of changing the vertical position of a sample. Recent advances in and affordability of 3-D printing have opened up a variety of possibilities, not only providing versatile and custom-designed laboratory equipment but also reducing the cost of constructing typical laboratory opto-mechanical positioning stages. Here, we present the possibility of printing typical linear stages, thereby constructing a full XYZ stage. In addition, a vertical laboratory jack, which utilizes a scissor format, has also been printed using polylactic acid (PLA) filament. The design of these systems required modeling the strength of material to estimate the deflection, which was conducted by finite element analysis. The effectiveness of the proposed 3-D-printed positioning devices was tested by measuring the stroke and the repeatability. As an example of application, a multispectral reflection imaging device was constructed with the help of 3-D-printed linear stages and a laboratory scissor jack.

Automated behavioural analysis reveals the basic behavioural repertoire of the urochordate Ciona intestinalis

Quantitative analysis of animal behaviour in model organisms is becoming an increasingly essential approach for tackling the great challenge of understanding how activity in the brain gives rise to behaviour. Here we used automated image-based tracking to extract behavioural features from an organism of great importance in understanding the evolution of chordates, the free-swimming larval form of the tunicate Ciona intestinalis, which has a compact and fully mapped nervous system composed of only 231 neurons. We analysed hundreds of videos of larvae and we extracted basic geometric and physical descriptors of larval behaviour. Importantly, we used machine learning methods to create an objective ontology of behaviours for C. intestinalis larvae. We identified eleven behavioural modes using agglomerative clustering. Using our pipeline for quantitative behavioural analysis, we demonstrate that C. intestinalis larvae exhibit sensory arousal and thigmotaxis. Notably, the anxiotropic drug modafinil modulates thigmotactic behaviour. Furthermore, we tested the robustness of the larval behavioural repertoire by comparing different rearing conditions, ages and group sizes. This study shows that C. intestinalis larval behaviour can be broken down to a set of stereotyped behaviours that are used to different extents in a context-dependent manner.

Most sleep does not serve a vital function: Evidence from Drosophila melanogaster

Sleep appears to be a universally conserved phenomenon among the animal kingdom, but whether this notable evolutionary conservation underlies a basic vital function is still an open question. Using a machine learning-based video-tracking technology, we conducted a detailed high-throughput analysis of sleep in the fruit fly Drosophila melanogaster, coupled with a lifelong chronic and specific sleep restriction. Our results show that some wild-type flies are virtually sleepless in baseline conditions and that complete, forced sleep restriction is not necessarily a lethal treatment in wild-type D. melanogaster. We also show that circadian drive, and not homeostatic regulation, is the main contributor to sleep pressure in flies. These results offer a new perspective on the biological role of sleep in Drosophila and, potentially, in other species.

Rethomics: An R framework to analyse high-throughput behavioural data

The recent development of automatised methods to score various behaviours on a large number of animals provides biologists with an unprecedented set of tools to decipher these complex phenotypes. Analysing such data comes with several challenges that are largely shared across acquisition platform and paradigms. Here, we present rethomics, a set of R packages that unifies the analysis of behavioural datasets in an efficient and flexible manner. rethomics offers a computational solution to storing, manipulating and visualising large amounts of behavioural data. We propose it as a tool to bridge the gap between behavioural biology and data sciences, thus connecting computational and behavioural scientists. rethomics comes with a extensive documentation as well as a set of both practical and theoretical tutorials (available at https://rethomics.github.io).

Pergola: Boosting Visualization and Analysis of Longitudinal Data by Unlocking Genomic Analysis Tools

The growing appetite of behavioral neuroscience for automated data production is prompting the need for new computational standards allowing improved interoperability, reproducibility, and shareability. We show here how these issues can be solved by repurposing existing genomic formats whose structure perfectly supports the handling of time series. This allows existing genomic analysis and visualization tools to be deployed onto behavioral data. As a proof of principle, we implemented the conversion procedure in Pergola, an open source software, and used genomics tools to reproduce results obtained in mouse, fly, and worm. We also show how common genomics techniques such as principal component analysis, hidden Markov modeling, and volcano plots can be deployed on the reformatted behavioral data. These analyses are easy to share because they depend on the scripting of public software. They are also easy to reproduce thanks to their integration within Nextflow, a workflow manager using containerized software.

MAPLE (modular automated platform for large-scale experiments), a robot for integrated organism-handling and phenotyping

Lab organisms are valuable in part because of large-scale experiments like screens, but performing such experiments over long time periods by hand is arduous and error-prone. Organism-handling robots could revolutionize large-scale experiments in the way that liquid-handling robots accelerated molecular biology. We developed a modular automated platform for large-scale experiments (MAPLE), an organism-handling robot capable of conducting lab tasks and experiments, and then deployed it to conduct common experiments in Saccharomyces cerevisiae, Caenorhabditis elegans, Physarum polycephalum, Bombus impatiens, and Drosophila melanogaster. Focusing on fruit flies, we developed a suite of experimental modules that permitted the automated collection of virgin females and execution of an intricate and laborious social behavior experiment. We discovered that (1) pairs of flies exhibit persistent idiosyncrasies in social behavior, which (2) require olfaction and vision, and (3) social interaction network structure is stable over days. These diverse examples demonstrate MAPLE’s versatility for automating experimental biology.

Biological research can, at times, be mind-numbingly tedious: scientists often have to do the same experiment over and over on many different samples. When working with animals such as fruit flies, this means researchers have to physically handle large numbers of specimens, selecting certain individuals or moving them from one container to another to perform the study. This represents a serious bottleneck that slows down discovery.

Automation represents an obvious solution to this issue. In fact, it has already revolutionized fields like molecular biology, where robots can handle the liquids required for the experiments. Yet, it is not so easy to automate tasks that involve animals larger than a millimeter. To fill that gap, Alisch et al. have developed a robotic system called Modular Automated Platform for Large-scale Experiments (MAPLE) that can manipulate fruit flies and other small organisms.

Using gentle vacuum, MAPLE can pick up individual flies to move them from one compartment to another. These areas could be places where the insects grow or where experimental measurements are automatically gathered. Putting the robot to work, Alisch et al. used MAPLE to collect virgin female flies for genetic experiments, a common task in fruit flies laboratories. The system was also configured to load flies into arenas where their behavior could be measured. Finally, MAPLE assisted with an experiment that involved tracking the interactions of known individuals to examine if the flies exhibited social networks, and if those networks were stable. This logistically complicated experiment would have been difficult to run without the help of an automated system. Alisch et al. also show that the robot can be adjusted to work with various species often used for research, such as nematode worms, yeast, slime mould and even bumblebees. This allows the system to be useful in a range of research fields.

As MAPLE fits on a table top and is fairly affordable, the hope is that it could help many scientists do their experiments faster and with greater consistency, freeing up time for creative thinking and new ideas. Ultimately, this tool could help to speed up scientific progress.