high-throughput-assay-to-examine-egg-laying-preferences-individual

High Throughput Assay to Examine Egg-Laying Preferences of Individual <em>Drosophila melanogaster</em>

Recently, egg-laying preference of Drosophila has emerged as a genetically tractable model to study the neural basis of simple decision-making processes. ...

Duke University

Selecting a suitable site to deposit their eggs is an important reproductive need of Drosophila females. Although their choosiness toward egg-laying sites is well documented, the specific neural mechanism that activates females' search for attractive egg-laying sites is not known. Here, we show that distention and contraction of females' internal reproductive tract triggered by egg delivery through the tract plays a critical role in activating such search. We found that females start to exhibit acetic acid (AA) attraction prior to depositing each egg but no attraction when they are not laying eggs. Artificially distending the reproductive tract triggers AA attraction in non-egg-laying females, whereas silencing the mechanosensitive neurons we identified that can sense the contractile status of the tract eliminates such attraction. Our work uncovers the circuit basis of an important reproductive need of Drosophila females and provides a simple model for dissecting the neural mechanism that underlies a reproductive need-induced behavioral modification.

Mechanosensitive neurons on the internal reproductive tract contribute to egg-laying-induced acetic acid attraction in Drosophila.

Drosophila melanogaster females are highly selective about the chemosensory quality of their egg-laying sites, an important trait that promotes the survival and fitness of their offspring. How egg-laying females respond to UV light is not known, however. UV is a well-documented phototactic cue for adult Drosophila, but it is an aversive cue for larvae. Here, we show that female flies exhibit UV aversion in response to their egg-laying demand. First, females exhibit egg-laying aversion of UV: they prefer to lay eggs on dark sites when choosing between UV-illuminated and dark sites. Second, they also exhibit movement aversion of UV: positional tracking of single females suggests that egg-laying demand increases their tendency to turn away from UV. Genetic manipulations of the retina suggest that egg-laying and movement aversion of UV are both mediated by the inner (R7) and not the outer (R1-R6) photoreceptors. Finally, we show that the Dm8 amacrine neurons, a synaptic target of R7 photoreceptors and a mediator of UV spectral preference, are dispensable for egg-laying aversion but essential for movement aversion of UV. This study suggests that egg-laying demand can temporarily convert UV into an aversive cue for female Drosophila and that R7 photoreceptors recruit different downstream targets to control different egg-laying-induced behavioral modifications.

Egg-laying demand induces aversion of UV light in Drosophila females.

Drosophila melanogaster egg-laying site selection offers a genetic model to study a simple form of value-based decision. We have previously shown that Drosophila females consistently reject a sucrose-containing substrate and choose a plain (sucrose-free) substrate for egg laying in our sucrose versus plain decision assay. However, either substrate is accepted when it is the sole option. Here we describe the neural mechanism that underlies females' sucrose rejection in our sucrose versus plain assay. First, we demonstrate that females explored the sucrose substrate frequently before most egg-laying events, suggesting that they actively suppress laying eggs on the sucrose substrate as opposed to avoiding visits to it. Second, we show that activating a specific subset of DA neurons triggered a preference for laying eggs on the sucrose substrate over the plain one, suggesting that activating these DA neurons can increase the value of the sucrose substrate for egg laying. Third, we demonstrate that neither ablating nor inhibiting the mushroom body (MB), a known Drosophila learning and decision center, affected females' egg-laying preferences in our sucrose versus plain assay, suggesting that MB does not mediate this specific decision-making task. We propose that the value of a sucrose substrate- as an egg-laying option-can be adjusted by the activities of a specific DA circuit. Once the sucrose substrate is determined to be the lesser valued option, females execute their decision to reject this inferior substrate not by stopping their visits to it, but by actively suppressing their egg-laying motor program during their visits.

Behavioral and circuit basis of sucrose rejection by Drosophila females in a simple decision-making task.

High-throughput analysis of animal behavior requires software to analyze videos. Such software typically depends on the experiments' being performed in good lighting conditions, but this ideal is difficult or impossible to achieve for certain classes of experiments. Here, we describe techniques that allow long-duration positional tracking in difficult lighting conditions with strong shadows or recurring "on"/"off" changes in lighting. The latter condition will likely become increasingly common, e.g., for Drosophila due to the advent of red-shifted channel rhodopsins. The techniques enabled tracking with good accuracy in three types of experiments with difficult lighting conditions in our lab. Our technique handling shadows relies on single-animal tracking and on shadows' and flies' being accurately distinguishable by distance to the center of the arena (or a similar geometric rule); the other techniques should be broadly applicable. We implemented the techniques as extensions of the widely-used tracking software Ctrax; however, they are relatively simple, not specific to Drosophila, and could be added to other trackers as well.

Long-duration animal tracking in difficult lighting conditions.

High-throughput analysis of animal behavior requires software to analyze videos. Such software analyzes each frame individually, detecting animals' body parts. But the image analysis rarely attempts to recognize "behavioral states"-e.g., actions or facial expressions-directly from the image instead of using the detected body parts. Here, we show that convolutional neural networks (CNNs)-a machine learning approach that recently became the leading technique for object recognition, human pose estimation, and human action recognition-were able to recognize directly from images whether Drosophila were "on" (standing or walking) or "off" (not in physical contact with) egg-laying substrates for each frame of our videos. We used multiple nets and image transformations to optimize accuracy for our classification task, achieving a surprisingly low error rate of just 0.072%. Classifying one of our 8 h videos took less than 3 h using a fast GPU. The approach enabled uncovering a novel egg-laying-induced behavior modification in Drosophila. Furthermore, it should be readily applicable to other behavior analysis tasks.

Ulrich Stern

Department of Neurobiology

Duke University

High Throughput Assay to Examine Egg-Laying Preferences of Individual Drosophila melanogaster

Ulrich Stern

.css-o250i3{font-size:18px;font-family:Open Sans,sans-serif;line-height:21.6px;}Department of Neurobiology

Duke University

High Throughput Assay to Examine Egg-Laying Preferences of Individual Drosophila melanogaster

Department of Neurobiology