Pavan Ramdya

Complementary Function and Integrated Wiring of the Evolutionarily Distinct Drosophila Olfactory Subsystems

To sense myriad environmental odors, animals have evolved multiple, large families of divergent olfactory receptors. How and why distinct receptor repertoires and their associated circuits are functionally and anatomically integrated is essentially unknown. We have addressed these questions through comprehensive comparative analysis of the Drosophila olfactory subsystems that express the ionotropic receptors (IRs) and odorant receptors (ORs). We identify ligands for most IR neuron classes, revealing their specificity for select amines and acids, which complements the broader tuning of ORs for esters and alcohols. IR and OR sensory neurons exhibit glomerular convergence in segregated, although interconnected, zones of the primary olfactory center, but these circuits are extensively interdigitated in higher brain regions. Consistently, behavioral responses to odors arise from an interplay between IR- and OR-dependent pathways. We integrate knowledge on the different phylogenetic and developmental properties of these receptors and circuits to propose models for the functional contributions and evolution of these distinct olfactory subsystems.

Mechanosensory interactions drive collective behaviour in Drosophila

Collective behaviour enhances environmental sensing and decision-making in groups of animals. Experimental and theoretical investigations of schooling fish, flocking birds and human crowds have demonstrated that simple interactions between individuals can explain emergent group dynamics. These findings indicate the existence of neural circuits that support distributed behaviours, but the molecular and cellular identities of relevant sensory pathways are unknown. Here we show that Drosophila melanogaster exhibits collective responses to an aversive odour: individual flies weakly avoid the stimulus, but groups show enhanced escape reactions. Using high-resolution behavioural tracking, computational simulations, genetic perturbations, neural silencing and optogenetic activation we demonstrate that this collective odour avoidance arises from cascades of appendage touch interactions between pairs of flies. Inter-fly touch sensing and collective behaviour require the activity of distal leg mechanosensory sensilla neurons and the mechanosensory channel NOMPC. Remarkably, through these inter-fly encounters, wild-type flies can elicit avoidance behaviour in mutant animals that cannot sense the odour—a basic form of communication. Our data highlight the unexpected importance of social context in the sensory responses of a solitary species and open the door to a neural-circuit-level understanding of collective behaviour in animal groups.

Evolving olfactory systems on the fly

The detection of odour stimuli in the environment is universally important for primal behaviours such as feeding, mating, kin interactions and escape responses. Given the ubiquity of many airborne chemical signals and the similar organisation of animal olfactory circuits, a fundamental question in our understanding of the sense of smell is how species-specific behavioural responses to odorants can evolve. Recent comparative genomic, developmental and physiological studies are shedding light on this problem by providing insights into the genetic mechanisms that underlie anatomical and functional evolution of the olfactory system. Here we synthesise these data, with a particular focus on insect olfaction, to address how new olfactory receptors and circuits might arise and diverge, offering glimpses into how odour-evoked behaviours could adapt to an ever-changing chemosensory world.

Fluorescence Behavioral Imaging (FBI) tracks identity in heterogeneous groups of Drosophila

Distinguishing subpopulations in group behavioral experiments can reveal the impact of differences in genetic, pharmacological and life-histories on social interactions and decision-making. Here we describe Fluorescence Behavioral Imaging (FBI), a toolkit that uses transgenic fluorescence to discriminate subpopulations, imaging hardware that simultaneously records behavior and fluorescence expression, and open-source software for automated, high-accuracy determination of genetic identity. Using FBI, we measure courtship partner choice in genetically mixed groups of Drosophila.

The neurogenetics of group behavior in Drosophila melanogaster

ABSTRACT Organisms rarely act in isolation. Their decisions and movements are often heavily influenced by direct and indirect interactions with conspecifics. For example, we each represent a single node within a social network of family and friends, and an even larger network of strangers. This group membership can affect our opinions and actions. Similarly, when in a crowd, we often coordinate our movements with others like fish in a school, or birds in a flock. Contributions of the group to individual behaviors are observed across a wide variety of taxa but their biological mechanisms remain largely unknown. With the advent of powerful computational tools as well as the unparalleled genetic accessibility and surprisingly rich social life of Drosophila melanogaster, researchers now have a unique opportunity to investigate molecular and neuronal determinants of group behavior. Conserved mechanisms and/or selective pressures in D. melanogaster can likely inform a much wider phylogenetic scale. Here, we highlight two examples to illustrate how quantitative and genetic tools can be combined to uncover mechanisms of two group behaviors in D. melanogaster: social network formation and collective behavior. Lastly, we discuss future challenges towards a full understanding how coordinated brain activity across many individuals gives rise to the behavioral patterns of animal societies. Summary: We highlight studies that exploited computational tools and the genetic accessibility and rich social life of Drosophila melanogaster to reveal molecular and neuronal determinants of social networks and collective behavior.

FlyLimbTracker: An active contour based approach for leg segment tracking in unmarked, freely behaving Drosophila

Understanding the biological underpinnings of movement and action requires the development of tools for quantitative measurements of animal behavior. Drosophila melanogaster provides an ideal model for developing such tools: the fly has unparalleled genetic accessibility and depends on a relatively compact nervous system to generate sophisticated limbed behaviors including walking, reaching, grooming, courtship, and boxing. Here we describe a method that uses active contours to semi-automatically track body and leg segments from video image sequences of unmarked, freely behaving D. melanogaster. We show that this approach yields a more than 6-fold reduction in user intervention when compared with fully manual annotation and can be used to annotate videos with low spatial or temporal resolution for a variety of locomotor and grooming behaviors. FlyLimbTracker, the software implementation of this method, is open-source and our approach is generalizable. This opens up the possibility of tracking leg movements in other species by modifications of underlying active contour models.

Climbing favours the tripod gait over alternative faster insect gaits

To escape danger or catch prey, running vertebrates rely on dynamic gaits with minimal ground contact. By contrast, most insects use a tripod gait that maintains at least three legs on the ground at any given time. One prevailing hypothesis for this difference in fast locomotor strategies is that tripod locomotion allows insects to rapidly navigate three-dimensional terrain. To test this, we computationally discovered fast locomotor gaits for a model based on Drosophila melanogaster. Indeed, the tripod gait emerges to the exclusion of many other possible gaits when optimizing fast upward climbing with leg adhesion. By contrast, novel two-legged bipod gaits are fastest on flat terrain without adhesion in the model and in a hexapod robot. Intriguingly, when adhesive leg structures in real Drosophila are covered, animals exhibit atypical bipod-like leg coordination. We propose that the requirement to climb vertical terrain may drive the prevalence of the tripod gait over faster alternative gaits with minimal ground contact.

Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs—locomotor bouts—matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior.

Imaging neural activity in the ventral nerve cord of behaving adult Drosophila

To understand neural circuits that control limbs, one must measure their activity during behavior. Until now this goal has been challenging, because limb premotor and motor circuits have been largely inaccessible for large-scale recordings in intact, moving animals—a constraint that is true for both vertebrate and invertebrate models. Here, we introduce a method for 2-photon functional imaging from the ventral nerve cord (VNC) of behaving adult Drosophila melanogaster. We use this method to reveal patterns of activity across nerve cord populations during grooming and walking and to uncover the functional encoding of moonwalker ascending neurons (MANs), moonwalker descending neurons (MDNs), and a previously uncharacterized class of locomotion-associated A1 descending neurons. Finally, we develop a genetic reagent to destroy the indirect flight muscles and to facilitate experimental access to the VNC. Taken together, these approaches enable the direct investigation of circuits associated with complex limb movements.The Drosophila ventral nerve cord (VNC) is functionally equivalent to the vertebrate spinal cord. This study reports a 2-photon imaging approach for recording neural activity in the VNC of walking and grooming adult flies.