Identifying behavioral circuits in Drosophila melanogaster: moving targets in a flying insect

Linking neural circuits to the mechanics of animal behavior in Drosophila larval locomotion

The motions that make up animal behavior arise from the interplay between neural circuits and the mechanical parts of the body. Therefore, in order to comprehend the operational mechanisms governing behavior, it is essential to examine not only the underlying neural network but also the mechanical characteristics of the animal's body. The locomotor system of fly larvae serves as an ideal model for pursuing this integrative approach. By virtue of diverse investigation methods encompassing connectomics analysis and quantification of locomotion kinematics, research on larval locomotion has shed light on the underlying mechanisms of animal behavior. These studies have elucidated the roles of interneurons in coordinating muscle activities within and between segments, as well as the neural circuits responsible for exploration. This review aims to provide an overview of recent research on the neuromechanics of animal locomotion in fly larvae. We also briefly review interspecific diversity in fly larval locomotion and explore the latest advancements in soft robots inspired by larval locomotion. The integrative analysis of animal behavior using fly larvae could establish a practical framework for scrutinizing the behavior of other animal species.

Ion Channel Degeneracy, Variability, and Covariation in Neuron and Circuit Resilience

The large number of ion channels found in all nervous systems poses fundamental questions concerning how the characteristic intrinsic properties of single neurons are determined by the specific subsets of channels they express. All neurons display many different ion channels with overlapping voltage- and time-dependent properties. We speculate that these overlapping properties promote resilience in neuronal function. Individual neurons of the same cell type show variability in ion channel conductance densities even though they can generate reliable and similar behavior. This complicates a simple assignment of function to any conductance and is associated with variable responses of neurons of the same cell type to perturbations, deletions, and pharmacological manipulation. Ion channel genes often show strong positively correlated expression, which may result from the molecular and developmental rules that determine which ion channels are expressed in a given cell type.

Serotonin receptor 5-HT7 in Drosophila mushroom body neurons mediates larval appetitive olfactory learning

Serotonin (5-HT) and dopamine are critical neuromodulators known to regulate a range of behaviors in invertebrates and mammals, such as learning and memory. Effects of both serotonin and dopamine are mediated largely through their downstream G-protein coupled receptors through cAMP-PKA signaling. While the role of dopamine in olfactory learning in Drosophila is well described, the function of serotonin and its downstream receptors on Drosophila olfactory learning remain largely unexplored. In this study we show that the output of serotonergic neurons, possibly through points of synaptic contacts on the mushroom body (MB), is essential for training during olfactory associative learning in Drosophila larvae. Additionally, we demonstrate that the regulation of olfactory associative learning by serotonin is mediated by its downstream receptor (d5-HT7) in a cAMP-dependent manner. We show that d5-HT7 expression specifically in the MB, an anatomical structure essential for olfactory learning in Drosophila, is critical for olfactory associative learning. Importantly our work shows that spatio-temporal restriction of d5-HT7 expression to the MB is sufficient to rescue olfactory learning deficits in a d5-HT7 null larvae. In summary, our results establish a critical, and previously unknown, role of d5-HT7 in olfactory learning.

Molecular and cytological analysis of widely-used Gal4 driver lines for Drosophila neurobiology

Background

The Drosophila central nervous system (CNS) is a convenient model system for the study of the molecular mechanisms of conserved neurobiological processes. The manipulation of gene activity in specific cell types and subtypes of the Drosophila CNS is frequently achieved by employing the binary Gal4/UAS system. However, many Gal4 driver lines available from the Bloomington Drosophila Stock Center (BDSC) and commonly used in Drosophila neurobiology are still not well characterized. Among these are three lines with Gal4 driven by the elav promoter (BDSC #8760, #8765, and #458), one line with Gal4 driven by the repo promoter (BDSC #7415), and the 69B-Gal4 line (BDSC #1774). For most of these lines, the exact insertion sites of the transgenes and the detailed expression patterns of Gal4 are not known. This study is aimed at filling these gaps.

Results

We have mapped the genomic location of the Gal4-bearing P-elements carried by the BDSC lines #8760, #8765, #458, #7415, and #1774. In addition, for each of these lines, we have analyzed the Gal4-driven GFP expression pattern in the third instar larval CNS and eye-antennal imaginal discs. Localizations of the endogenous Elav and Repo proteins were used as markers of neuronal and glial cells, respectively.

Conclusions

We provide a mini-atlas of the spatial activity of Gal4 drivers that are widely used for the expression of UAS–target genes in the Drosophila CNS. The data will be helpful for planning experiments with these drivers and for the correct interpretation of the results.

MicroRNAs Regulate Multiple Aspects of Locomotor Behavior in Drosophila

Locomotion is an ancient and fundamental output of the nervous system required for animals to perform many other complex behaviors. Although the formation of motor circuits is known to be under developmental control of transcriptional mechanisms that define the fates and connectivity of the many neurons, glia and muscle constituents of these circuits, relatively little is known about the role of post-transcriptional regulation of locomotor behavior. MicroRNAs have emerged as a potentially rich source of modulators for neural development and function. In order to define the microRNAs required for normal locomotion in Drosophila melanogaster, we utilized a set of transgenic Gal4-dependent competitive inhibitors (microRNA sponges, or miR-SPs) to functionally assess ca. 140 high-confidence Drosophila microRNAs using automated quantitative movement tracking systems followed by multiparametric analysis. Using ubiquitous expression of miR-SP constructs, we identified a large number of microRNAs that modulate aspects of normal baseline adult locomotion. Addition of temperature-dependent Gal80 to identify microRNAs that act during adulthood revealed that the majority of these microRNAs play developmental roles. Comparison of ubiquitous and neural-specific miR-SP expression suggests that most of these microRNAs function within the nervous system. Parallel analyses of spontaneous locomotion in adults and in larvae also reveal that very few of the microRNAs required in the adult overlap with those that control the behavior of larval motor circuits. These screens suggest that a rich regulatory landscape underlies the formation and function of motor circuits and that many of these mechanisms are stage and/or parameter-specific.

Neural Control of Startle-Induced Locomotion by the Mushroom Bodies and Associated Neurons in Drosophila

Startle-induced locomotion is commonly used in Drosophila research to monitor locomotor reactivity and its progressive decline with age or under various neuropathological conditions. A widely used paradigm is startle-induced negative geotaxis (SING), in which flies entrapped in a narrow column react to a gentle mechanical shock by climbing rapidly upwards. Here we combined in vivo manipulation of neuronal activity and splitGFP reconstitution across cells to search for brain neurons and putative circuits that regulate this behavior. We show that the activity of specific clusters of dopaminergic neurons (DANs) afferent to the mushroom bodies (MBs) modulates SING, and that DAN-mediated SING regulation requires expression of the DA receptor Dop1R1/Dumb, but not Dop1R2/Damb, in intrinsic MB Kenyon cells (KCs). We confirmed our previous observation that activating the MB α'β', but not αβ, KCs decreased the SING response, and we identified further MB neurons implicated in SING control, including KCs of the γ lobe and two subtypes of MB output neurons (MBONs). We also observed that co-activating the αβ KCs antagonizes α'β' and γ KC-mediated SING modulation, suggesting the existence of subtle regulation mechanisms between the different MB lobes in locomotion control. Overall, this study contributes to an emerging picture of the brain circuits modulating locomotor reactivity in Drosophila that appear both to overlap and differ from those underlying associative learning and memory, sleep/wake state and stress-induced hyperactivity.

Reflections on contributing to "big discoveries" about the fly clock: Our fortunate paths as post-docs with 2017 Nobel laureates Jeff Hall, Michael Rosbash, and Mike Young

In the early 1980s Jeff Hall and Michael Rosbash at Brandeis University and Mike Young at Rockefeller University set out to isolate the period (per) gene, which was recovered in a revolutionary genetic screen by Ron Konopka and Seymour Benzer for mutants that altered circadian behavioral rhythms. Over the next 15 years the Hall, Rosbash and Young labs made a series of groundbreaking discoveries that defined the molecular timekeeping mechanism and formed the basis for them being awarded the 2017 Nobel Prize in Physiology or Medicine. Here the authors recount their experiences as post-docs in the Hall, Rosbash and Young labs from the mid-1980s to the mid-1990s, and provide a perspective of how basic research conducted on a simple model system during that era profoundly influenced the direction of the clocks field and established novel approaches that are now standard operating procedure for studying complex behavior.

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2017 Nobel Prize awarded to Hall, Rosbash and Young for circadian clock mechanisms.

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Work on fruit flies in the 1980s and 1990s were key to deciphering clock mechanisms.

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Authors recount their experiences as postdocs in the Hall, Rosbash and Young labs.

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The broad impacts of basic research on fruit fly clock genes.

Variations on a theme: bumblebee learning flights from the nest and from flowers

On leaving a significant place to which they will return, bees and wasps perform learning flights to acquire visual information to guide them back. The flights are set in different contexts, such as from their nest or a flower, which are functionally and visually different. The permanent and inconspicuous nest hole of a bumblebee worker is locatable primarily through nearby visual features, whereas a more transient flower advertises itself by its colour and shape. We compared the learning flights of bumblebees leaving their nest or a flower in an experimental situation in which the nest hole, flower and their surroundings were visually similar. Consequently, differences in learning flights could be attributed to the bee's internal state when leaving the nest or flower rather than to the visual scene. Flights at the flower were a quarter as long as those at the nest and more focused on the flower than its surroundings. Flights at the nest covered a larger area with the bees surveying a wider range of directions. For the initial third of the learning flight, bees kept within about 5 cm of the flower and nest hole, and tended to face and fixate the nest, flower and nearby visual features. The pattern of these fixations varied between nest and flower, and these differences were reflected in the bees' return flights to the nest and flower. Together, these findings suggest that learning flights are tuned to the bees' inherent expectations of the visual and functional properties of nests and flowers.

Mushroom body output neurons encode valence and guide memory-based action selection in Drosophila

Animals discriminate stimuli, learn their predictive value and use this knowledge to modify their behavior. In Drosophila, the mushroom body (MB) plays a key role in these processes. Sensory stimuli are sparsely represented by ∼2000 Kenyon cells, which converge onto 34 output neurons (MBONs) of 21 types. We studied the role of MBONs in several associative learning tasks and in sleep regulation, revealing the extent to which information flow is segregated into distinct channels and suggesting possible roles for the multi-layered MBON network. We also show that optogenetic activation of MBONs can, depending on cell type, induce repulsion or attraction in flies. The behavioral effects of MBON perturbation are combinatorial, suggesting that the MBON ensemble collectively represents valence. We propose that local, stimulus-specific dopaminergic modulation selectively alters the balance within the MBON network for those stimuli. Our results suggest that valence encoded by the MBON ensemble biases memory-based action selection.

A group of segmental premotor interneurons regulates the speed of axial locomotion in Drosophila larvae

BACKGROUND

Animals control the speed of motion to meet behavioral demands. Yet, the underlying neuronal mechanisms remain poorly understood. Here we show that a class of segmentally arrayed local interneurons (period-positive median segmental interneurons, or PMSIs) regulates the speed of peristaltic locomotion in Drosophila larvae.

RESULTS

PMSIs formed glutamatergic synapses on motor neurons and, when optogenetically activated, inhibited motor activity, indicating that they are inhibitory premotor interneurons. Calcium imaging showed that PMSIs are rhythmically active during peristalsis with a short time delay in relation to motor neurons. Optogenetic silencing of these neurons elongated the duration of motor bursting and greatly reduced the speed of larval locomotion.

CONCLUSIONS

Our results suggest that PMSIs control the speed of axial locomotion by limiting, via inhibition, the duration of motor outputs in each segment. Similar mechanisms are found in the regulation of mammalian limb locomotion, suggesting that common strategies may be used to control the speed of animal movements in a diversity of species.

Lactobacilli-Host mutualism: "learning on the fly"

Metazoans establish with microorganisms complex interactions for their mutual benefits. Drosophila, which has already proven useful host model to study several aspects of innate immunity and host-bacteria pathogenic associations has become a powerful model to dissect the mechanisms behind mutualistic host-microbe interactions. Drosophila microbiota is composed of simple and aerotolerant bacterial communities mostly composed of Lactobacillaceae and Acetobactereaceae. Drosophila mono- or poly-associated with lactobacilli strains constitutes a powerful model to dissect the complex interplay between lactobacilli and host biologic traits. Thanks to the genetic tractability of both Drosophila and lactobacilli this association model offers a great opportunity to reveal the underlying molecular mechanisms. Here, we review our current knowledge about how the Drosophila model is helping our understanding of how lactobacilli shapes host biology.

Neuromodulatory control of sleep in Drosophila melanogaster: integration of competing and complementary behaviors

The transition between wake and sleep states is characterized by rapid and generalized changes in both sensory and motor processing. Sleep is antagonistic to the expression of important behaviors, like feeding, reproduction and learning whose relative importance to an individual will depend on its circumstances at that moment. An understanding of how the decision to sleep is affected by these other drives and how this process is coordinated across the entire brain remains elusive. Neuromodulation is an important regulatory feature of many behavioral circuits and the reconfiguring of these circuits by modulators can have both long-term and short-term consequences. Drosophila melanogaster has become an important model system for understanding the molecular and genetic bases of behaviors and in recent years neuromodulatory systems have been shown to play a major role in regulation of sleep and other behaviors in this organism. The fly, with its increasingly well-defined behavioral circuitry and powerful genetic tools, is a system poised to provide new insight into the complex issue of how neuromodulation can coordinate situation-specific behavioral needs with the brain's arousal state.

Multiple mechanisms switch an electrically coupled, synaptically inhibited neuron between competing rhythmic oscillators

Rhythmic oscillations are common features of nervous systems. One of the fundamental questions posed by these rhythms is how individual neurons or groups of neurons are recruited into different network oscillations. We modeled competing fast and slow oscillators connected to a hub neuron with electrical and inhibitory synapses. We explore the patterns of coordination shown in the network as a function of the electrical coupling and inhibitory synapse strengths with the help of a novel visualization method that we call the "parameterscape." The hub neuron can be switched between the fast and slow oscillators by multiple network mechanisms, indicating that a given change in network state can be achieved by degenerate cellular mechanisms. These results have importance for interpreting experiments employing optogenetic, genetic, and pharmacological manipulations to understand circuit dynamics.

Temperature integration at the AC thermosensory neurons in Drosophila

Temperature sensation has a strong impact on animal behavior and is necessary for animals to avoid exposure to harmful temperatures. It is now well known that thermoTRP (transient receptor potential) channels in thermosensory neurons detect a variable range of temperature stimuli. However, little is known about how a range of temperature information is relayed and integrated in the neural circuits. Here, we show novel temperature integration between two warm inputs via Drosophila TRPA channels, TRPA1 and Pyrexia (Pyx). The internal AC (anterior cell) thermosensory neurons, which express TRPA1, detect warm temperatures and mediate temperature preference behavior. We found that the AC neurons were activated twice when subjected to increasing temperatures. The first response was at ∼25°C via TRPA1 channel, which is expressed in the AC neurons. The second response was at ∼27°C via the second antennal segments, indicating that the second antennal segments are involved in the detection of warm temperatures. Further analysis reveals that pyx-Gal4-expressing neurons have synapses on the AC neurons and that mutation of pyx eliminates the second response of the AC neurons. These data suggest that AC neurons integrate both their own TRPA1-dependent temperature responses and a Pyx-dependent temperature response from the second antennal segments. Our data reveal the first identification of temperature integration, which combines warm temperature information from peripheral to central neurons and provides the possibility that temperature integration is involved in the plasticity of behavioral outputs.

A GAL4-driver line resource for Drosophila neurobiology

We established a collection of 7,000 transgenic lines of Drosophila melanogaster. Expression of GAL4 in each line is controlled by a different, defined fragment of genomic DNA that serves as a transcriptional enhancer. We used confocal microscopy of dissected nervous systems to determine the expression patterns driven by each fragment in the adult brain and ventral nerve cord. We present image data on 6,650 lines. Using both manual and machine-assisted annotation, we describe the expression patterns in the most useful lines. We illustrate the utility of these data for identifying novel neuronal cell types, revealing brain asymmetry, and describing the nature and extent of neuronal shape stereotypy. The GAL4 lines allow expression of exogenous genes in distinct, small subsets of the adult nervous system. The set of DNA fragments, each driving a documented expression pattern, will facilitate the generation of additional constructs for manipulating neuronal function.