Thanks to John Young for feedback on experimental design, Eric Luth for manuscript revision, and Madeleine Hatfield for figure design assistance. This work was funded by Simmons University and the Department of Biology.

NOTE: An overview of the protocol is presented in Figure 1.
1. Preparation for filming
<ol>
	<li>Place four three-well dishes side by side on a white surface, covering each with a glass slide.</li>
	<li>Position a camera (here, a Raspberry Pi system, but any camera capable of high-definition video is sufficient) above the dishes.
	<ol>
		<li>Check to ensure that all dishes are in frame and focus.</li>
		<li>Check to ensure that there is no glare on the slides that will limit the visibility of flies in the dish. Eliminate the glare by adjusting the plate position or dimming the lights in the recording space.</li>
		<li>Use high resolution (minimum 1920 x 1080 pixels) to accurately visualize fly limbs.</li>
	</ol>
	</li>
	<li>Mark the position of the dishes and camera on the bench where the recording is taking place. 
	NOTE: This will limit time spent on step 2 in future use of the apparatus. Performing the assays at the same time and in the same space will limit variability in behavior based on factors beyond intended manipulations.</li>
	<li>Lightly anesthetize the 4-9 day-old flies with cold on an ice block covered with parafilm and a paper towel (CO2 anesthetization will have a significant impact on behavior).
	<ol>
		<li>Tap the flies onto the block, and once anesthetized, move the flies to observation chambers as quickly as possible using a paintbrush. 
		NOTE: This transfer should happen as quickly as possible, as excessive exposure to anesthetization of any kind can negatively impact flies.</li>
	</ol>
	</li>
	<li>Place a single fly in each well.</li>
	<li>Allow files to acclimate to their new environment for 30 min post-anesthetization. Do not touch or disturb the wells containing flies after this point, as added stressors will impact behavior.</li>
</ol>
2. Recording the flies
<ol>
	<li>After the 30-min acclimation, record the flies using a camera.</li>
	<li>Use a Raspberry Pi camera run through PiSpy11 for behavioral data collection. 
	NOTE: The software is free and available on GitHub (https://github.com/gpask/PiSpy),&#160;and a Pi system can easily be set up for under $300. Other cameras, if available already, are also sufficient for recording footage</li>
	<li>Start a recording with Pi with the following command flow.
	<ol>
		<li>Open the terminal and type cd PiSpy. Then, type python3 PiSpy.py, enter the desired recording length, and enter the desired frame rate. Select the desired resolution and click Quick Capture.</li>
		<li>Use the Preview Camera function to ensure the flies are in focus and sufficiently visible.</li>
	</ol>
	</li>
	<li>Record the flies for 10 min at a recommended frame rate of 24 fps and save the file (PiSpy automatically saves to the videos folder).</li>
</ol>
3. Video analysis (Figure 2)
<ol>
	<li>To analyze the video, import the file into the Elan 6.8 software12. 
	NOTE: This software, while originally developed for psycholinguistic tallows for detailed annotation of videos and in-depth analysis of the grooming behaviors</li>
	<li>Assign each row as illustrated below to annotate the footage of individuals manually.
	<ol>
		<li>Do this with the following command flow: Tier &#62; Add New Tier &#62; Type Location in the dish on Tier Name &#62; Add.</li>
	</ol>
	</li>
	<li>Depending on the needs of a study, note and quantify various specific behaviors (anterior and posterior grooming, walking, sleeping, and standing).
	<ol>
		<li>Make annotations following the steps below.
		<ol>
			<li>Double-click the tier to be annotated. Right-click and drag the cursor along the selected tier for a period in which a single grooming bout is exhibited. Left-click, select New Annotation and double-click the newly highlighted time period. Type the abbreviation for the behavior exhibited at that time point.</li>
		</ol>
		</li>
		<li>Observe the videos slowly, scrub through them with a mouse, and annotate. Zoom into a single fly well during annotation to prevent false identification of behaviors. These could include tapping on the edge of the glass by the fly or shifting the legs, which might initially look like grooming.</li>
	</ol>
	</li>
	<li>Once the video is completely annotated, obtain a breakdown of each behavior. Ensure that the same abbreviation or annotation is used throughout the videos to use this feature. 
	NOTE: Elan 6.8 will provide the number of times a behavior occurs, the total duration of behaviors, and the mean time spent on each behavior.
	<ol>
		<li>Define grooming bouts as 2 s of uninterrupted grooming. Identify each behavior observed as follows. Define the parameters for anatomical regions prior to the conduction of the assay.
		<ol>
			<li>Anterior grooming: Identify grooming performed at the anterior region of the fly body as anterior grooming. 
			NOTE: This behavior will almost always involve a rubbing motion on an anterior part, like the head or proboscis, with the front two legs of the fly.</li>
			<li>Posterior grooming: Identify grooming performed at the anterior-posterior end of the fly body as posterior grooming. 
			NOTE: Additionally, wings were included in the posterior region for simplicity. This behavior will almost always involve a rubbing motion with the central and most posterior set of legs on the fly. A good indicator that posterior grooming is occurring will be that, at first glance, the fly may look as if it is missing its most posterior legs, as depicted in Figure 2D.</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Mueller, J. M., Zhang, N., Carlson, J. M., Simpson, J. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Variation+and+variability+in+Drosophila+grooming+behavior.">Variation and variability in Drosophila grooming behavior.</a> Front Behav Neurosci. 15, 769372 (2022).</li><li>Szebenyi, A. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Cleaning+behaviour+in+Drosophila+melanogaster.">Cleaning behaviour in Drosophila melanogaster.</a> Anim Behav. 17 (4), 641-651 (1969).</li><li>Seeds, A. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+suppression+hierarchy+among+competing+motor+programs+drives+sequential+grooming+in+Drosophila.">A suppression hierarchy among competing motor programs drives sequential grooming in Drosophila.</a> Elife. 3, e02951 (2014).</li><li>Ringo, J. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=How+do+flies+keep+clean?+Head+grooming+in+Drosophila.">How do flies keep clean? Head grooming in Drosophila.</a> J Ethol. 38, 167-172 (2020).</li><li>Feusner, J. D., Hembacher, E., Phillips, K. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+mouse+who+couldn't+stop+washing:+pathologic+grooming+in+animals+and+humans.">The mouse who couldn't stop washing: pathologic grooming in animals and humans.</a> CNS Spectr. 14 (9), 503-513 (2009).</li><li>Berridge, K. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sequential+super-stereotypy+of+an+instinctive+fixed+action+pattern+in+hyper-dopaminergic+mutant+mice:+a+model+of+obsessive+compulsive+disorder+and+Tourette's.">Sequential super-stereotypy of an instinctive fixed action pattern in hyper-dopaminergic mutant mice: a model of obsessive compulsive disorder and Tourette's.</a> BMC Biol. 3, 4 (2005).</li><li>Russo, A., Diantonio, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Wnd/DLK+is+a+critical+target+of+FMRP+responsible+for+neurodevelopmental+and+behavior+defects+in+the+Drosophila+model+of+Fragile+X+syndrome.">Wnd/DLK is a critical target of FMRP responsible for neurodevelopmental and behavior defects in the Drosophila model of Fragile X syndrome.</a> Cell Rep. 28, 2581-2593.e5 (2019).</li><li>Andrew, D. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Spontaneous+motor-behavior+abnormalities+in+two+Drosophila+models+of+neurodevelopmental+disorders.">Spontaneous motor-behavior abnormalities in two Drosophila models of neurodevelopmental disorders.</a> J Neurogenet. 35 (1), 1-22 (2021).</li><li>Tian, Y., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=GABA-+and+acetylcholine-related+gene+expression+in+blood+correlate+with+tic+severity+and+microarray+evidence+for+alternative+splicing+in+Tourette+syndrome:+a+pilot+study.">GABA- and acetylcholine-related gene expression in blood correlate with tic severity and microarray evidence for alternative splicing in Tourette syndrome: a pilot study.</a> Brain Res. 1381, 228-236 (2011).</li><li>Barradale, F., Sinha, K., Lebestky, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Quantification+of+Drosophila+grooming+behavior.">Quantification of Drosophila grooming behavior.</a> J Vis Exp. 125, e55231 (2017).</li><li>Morris, B. I., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=PiSpy:+an+affordable,+accessible,+and+flexible+imaging+platform+for+the+automated+observation+of+organismal+biology+and+behavior.">PiSpy: an affordable, accessible, and flexible imaging platform for the automated observation of organismal biology and behavior.</a> PLoS One. 17 (10), e0276652 (2022).</li><li>. ELAN (Version 6.8) [Computer software]. Nijmegen: Max Planck Institute for Psycholinguistics, The Language Archive Available from: <a target="_blank" href="https://archive.mpi.nl/tla/elan&amp;#34">https://archive.mpi.nl/tla/elan&amp;#34</a> (2024)</li><li>M&#252;ller, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Tourette's+syndrome:+clinical+features,+pathophysiology,+and+therapeutic+approaches.">Tourette's syndrome: clinical features, pathophysiology, and therapeutic approaches.</a> Dialogues Clin Neurosci. 9 (2), 161-171 (2007).</li><li>Southall, T. D., Elliott, D. A., Brand, A. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+GAL4+system:+a+versatile+toolkit+for+gene+expression+in+Drosophila.">The GAL4 system: a versatile toolkit for gene expression in Drosophila.</a> Cold Spring Harb Protoc. 2008, (2008).</li><li>Hatfield, T., Johnson, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Knockdown+of+the+GABARAP+ortholog+Atg8a+elicits+deficits+in+learning+and+promotes+obsessive+behaviors+in+Drosophila+melanogaster.">Knockdown of the GABARAP ortholog Atg8a elicits deficits in learning and promotes obsessive behaviors in Drosophila melanogaster.</a> MicroPubl Biol. 2024, (2024).</li><li>Bartholomew, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Impaired+climbing+and+flight+behaviour+in+Drosophila+melanogaster+following+carbon+dioxide+anaesthesia.">Impaired climbing and flight behaviour in Drosophila melanogaster following carbon dioxide anaesthesia.</a> Sci Rep. 5, 15298 (2015).</li><li>Sindhurakar, A., Butensky, S. D., Carmel, J. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+forelimb+tasks+for+rodents:+current+advantages+and+limitations,+and+future+promise.">Automated forelimb tasks for rodents: current advantages and limitations, and future promise.</a> Neurorehabil Neural Repair. 33 (7), 503-512 (2019).</li><li>Qiao, B., Li, C., Allen, V. W., Shirasu-Hiza, M., Syed, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+analysis+of+long-term+grooming+behavior+in+Drosophila+using+a+k-nearest+neighbors+classifier.">Automated analysis of long-term grooming behavior in Drosophila using a k-nearest neighbors classifier.</a> Elife. 7, e34497 (2018).</li></ol>

The authors have nothing to disclose.

Overall, this easily executable and cost-effective assay allows for robust characterization of Drosophila melanogaster grooming behavior. This technique gives insight into the frequency, time spent engaging in, and anatomical distribution of a large number of previously identified grooming behaviors. A good indicator that grooming will occur or is underway is changes in leg placement, specifically raising any of the 6 legs. Taking note specifically of behaviors after leg movement can assist in identifying grooming behavior. This assay allows for behavioral annotation ranging from general total grooming to stereotyped grooming behaviors specific to an anatomical region, such as those targeting the wings, head, or legs of the fly. Any of these can be included or ignored to fit the needs of a study. In the representative data provided here, we use obsessive grooming as a representative measure of obsessive/compulsive behaviors associated with neurodevelopmental conditions like Tourette Syndrome. Other data may also be collected, such as information on walking patterns, time spent sleeping, and frequency of falls within the dish.
Aside from the availability of a camera or the desired camera that would be purchased, the assay is cost-effective and utilizes tools often found within lab spaces. There can be additional adjustments made, especially in constructing observation chambers to fit study needs or available supplies.
It is vital to avoid using standard carbon dioxide anesthetic in conducting experiments, as this can significantly impact the behavior of the flies16. Instead, we suggest the use of cold anesthetic with a 30-min recovery time in which the flies are left undisturbed in the observational chambers. Ensure that all chambers are effectively covered by a slide to ensure that no flies escape. Additionally, all data should be collected on flies at the same stage of adult life (aim for 4-9 days) and should be recorded at the same time within the 12/12-h light/dark cycle, as fly activity varies throughout the day. Neutral lighting and the elimination of direct overhead lighting are also ideal for video collection, as they prevent glare on the slides that will limit the view of flies in some observation chambers. Conducting assays in the same space for each trial/replicate can additionally prevent variation based on environmental factors.
Given the higher degree of subjectivity that can be introduced to this kind of behavioral observation, making annotating research blind to the genotype/treatment of the flies is ideal in executing the assay. It is also important to note that manual annotation of videos can be time-consuming, especially if many individuals or different variables are being assessed. Allow for the thorough analysis of 12 biological replicates to take roughly 12-14 h. This may be changed based on how the footage is annotated specifically. This study utilizes Elan 6.8, given that it is free to use and allows for the sub-categorization of behaviors; however, other software may be used if they are capable of annotation.
With the rise in automated processes to evaluate Drosophila grooming, manual methods of grooming like the one presented remain important to utilize. Current methods of automation present various advantages, including decreased time spent on analysis and a lack of annotator bias. Despite this, there are limitations to this kind of method that can be mediated by the use of manual methods of grooming observation.
Primarily, establishing automated processes can prove difficult in some labs, especially those at smaller undergraduate institutions with limited budget or computational expertise. In labs without a member or collaborator with the computer science skill to set up or train automated software, these methods can be inaccessible. Available methods are often complex, both in the hardware and software required, making them difficult and expensive to adapt to the specific needs of the study17.
Additionally, having a method of manual annotation is vital for times when it is needed, and it can be used in conjunction with automated methods. Drosophila&#160;mutants may display atypical behaviors that could easily be mistaken for grooming if non-grooming motor behavior abnormalities are present. This may lead to misidentification of behaviors by either a manual annotator or a computer. While studies evaluating automated annotation of Drosophila flies found that it has high accuracy rates for identification of grooming behavior18, manual methods are still necessary for verification of automated annotation accuracy to limit error.
While automated methods of grooming annotation represent a great step forward in behavioral neuroscience, beginner researchers would need to dedicate significant time and effort to learning software methods. This method presents a more straightforward method for labs lacking the expertise and time needed to initiate the use of automated annotation.
During observation, it is key to keep in mind that abnormal grooming phenotypes may be due to factors beyond a researcher&#39;s intended manipulation. Injury during fly transfer may occur, or greater motor deficits may be present in selected mutants. These individuals may display abnormal grooming phenotypes and should be watched closely to prevent false positive data. In cases of injury, the fly should be excluded from the data set.
Despite this assay&#39;s strengths, certain limitations make this assay non-ideal for certain projects. The procedure requires significant time and attention from investigators, which can significantly expand the time needed in order to get results. For this reason, automated methods may be better suited for larger-scale experiments or in labs with the computational skills and resources to execute automated observation. This would also prevent bias introduced by subjective viewing by human researchers. However, this can also be limited by blinding researchers to the samples present in a video. The assay can easily be modified to fit a study&#39;s specific needs and requires little supplies or reagents. With the ability to produce strong and reproducible results without requiring significant resources, this method provides a straightforward way in which excessive grooming may be studied in the fruit fly.

Drosophila melanogaster is a well-established model organism in behavioral and neurobiological studies, providing insight into mechanisms driving analogous human behaviors. Self-grooming in this organism is a highly regulated and well-defined behavior, following stereotypical patterns that are easily distinguished from one another1. The separate grooming behaviors exhibited by the fly can generally be classified by anatomical region2, most easily being defined as posterior or anterior. Drosophila grooming will initially focus on the anterior region and subsequently transition to the posterior end3. Under typical conditions, flies exhibit grooming behaviors to maintain cleanliness (e.g., by removing dust) and occur in response to exposure to potentially harmful external stimuli like pathogenic microbes4.
Abnormalities in grooming behavior, specifically spontaneous obsessive grooming, have been used in various model systems as an indicator of obsessive and/or compulsive behavior. Translational findings observing obsessive grooming behaviors in organisms such as rodents, birds, and canines have given insight into conditions eliciting similar compulsive behavior in humans5. These include conditions such as trichotillomania, obsessive compulsive disorder, and Tourette Syndrome6. Excessive grooming behavior has also been used as a benchmark in evaluating behavioral phenotypes in models of similar neurodevelopmental conditions in Drosophila melanogaster. Obsessive grooming behaviors have been observed in fly models of Fragile-X Syndrome (FSX) and associated autism spectrum disorder (ASD). Excess spontaneous grooming occurs under mutations of dfmr1, the ortholog to the ASD and FSX associated gene FMR17. There is additionally a notable change in grooming distribution between posterior and anterior ends in these mutants8. These changes are interpreted as reflective of obsessive and compulsive body-focused behaviors displayed by some patients with these conditions. In using the grooming assay described here, we observed grooming behaviors in flies after an RNAi-mediated knockdown of the Drosophila gene Atg8a produced by commercially available GAL4 drivers and UAS-RNAi lines9.
This method involves the manual annotation of footage taken of flies for specific grooming behaviors. Previous studies aiming to evaluate grooming behavior, such as those using indirect methods like dyes, while effective at quantifying the efficacy of grooming, do not allow for measurement of grooming duration or frequency10. This assay, however, allows for quantification of Drosophila grooming frequency and duration, both generally and by anatomical region. The method detailed here presents some advantages over current automated methods, as it is easily modified and can be conducted by individuals lacking a computational background. With the equipment required easily available in most laboratories we present a cost-efficient manner to evaluate for the presence of an excessive self-grooming phenotype (see Table of Materials). This makes the method readily accessible to primarily undergraduate institutions and easily adaptable to training environments or teaching laboratories.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>16 GB Micro SD card</td>
			<td>Adafruit</td>
			<td>1294</td>
			<td>For use in introducing the OS</td>
		</tr>
		<tr>
			<td>Display</td>
			<td>Adafruit</td>
			<td>3578</td>
			<td>Any display able to be connected by HDMI or flex cable is sufficient</td>
		</tr>
		<tr>
			<td>Drosophila Atg8a-RNAi UAS line</td>
			<td>Bloomington Stock Center</td>
			<td>34340</td>
			<td>Line used in representative data</td>
		</tr>
		<tr>
			<td>Drosophila Ok6 Driver</td>
			<td>N/A</td>
			<td>N/A</td>
			<td>Line used in representative data</td>
		</tr>
		<tr>
			<td>Glass slides</td>
			<td>Fisher Scientific</td>
			<td>12-550-A3</td>
			<td>Keeps flies in containment</td>
		</tr>
		<tr>
			<td>Heatsinks</td>
			<td>Adafruit</td>
			<td></td>
			<td>Prevents overheating of the computer</td>
		</tr>
		<tr>
			<td>Lens</td>
			<td>Adafruit</td>
			<td>4563</td>
			<td>Used with HD camera only</td>
		</tr>
		<tr>
			<td>PiCamera</td>
			<td>Adafruit</td>
			<td>4561</td>
			<td>The HD version was used here but a standard camera can be used under budget constraints</td>
		</tr>
		<tr>
			<td>Raspberry pi 4</td>
			<td>Adafruit</td>
			<td>4292</td>
			<td>Computer PiSpy is run on</td>
		</tr>
		<tr>
			<td>Ribbion Cable</td>
			<td>Adafruit</td>
			<td>1648</td>
			<td>For use in connecting camera and display</td>
		</tr>
		<tr>
			<td>SB components Case</td>
			<td>Adafruit</td>
			<td>4301</td>
			<td>Protects the computer</td>
		</tr>
		<tr>
			<td>Spot Plate</td>
			<td>Fisher Scientific</td>
			<td>S99406</td>
			<td>Pyrex versions were already avaliable for our use but cell culture dishes or plastic spot plates are sufficient as well</td>
		</tr>
		<tr>
			<td>Tripod</td>
			<td>Best Buy</td>
			<td>6355959</td>
			<td>For suspension and positioning of camera, any apparatus capable of this is sufficient</td>
		</tr>
		<tr>
			<td>USB C Power Supply</td>
			<td>Adafruit</td>
			<td>1995</td>
			<td>Supplies power to the computer</td>
		</tr>
	</tbody>
</table>

quantification of drosophila melanogaster grooming behavior for evaluation of excessive grooming phenotypes

Observable changes in stereotyped grooming are applied translationally in model organisms. These changes are representative of pathologies that elicit similar deviations in human behavior; for example, excessive grooming acts as a proxy for obsessive and compulsive behaviors present in conditions like Tourette Syndrome or obsessive-compulsive disorder. The grooming assay presented allows for the evaluation of abnormal self-grooming phenotypes in Drosophila melanogaster. Flies are recorded for a period of 10 min, and these recordings are observed and annotated blind for previously defined grooming behaviors. Quantitative measures of both grooming bout frequency and the time spent engaging in self-grooming can be obtained by manually annotating the footage. The assay is relatively inexpensive, requires few materials not already available in laboratory environments, and is easily adaptable to fit the specific needs of any given study aiming to observe grooming. Additionally, the low level of skill needed to perform the assay, as compared to computer science-heavy automated methods, makes the protocol well-suited for small labs and students. We discuss in detail the steps required to perform this assay and its present limitations.

This assay produces quantitative data measuring the time and frequency of grooming behaviors from annotated footage. A representative image of the setup and how behaviors are defined is outlined in Figure 2. Given the subjectivity introduced by video analysis, all annotations of videos should be blinded to the researcher performing the analysis.
This method was used to evaluate the role the Drosophila gene Atg8a has in the development of grooming behavior. Atg8a is orthologous to the human gene GABARAP, which has displayed decreased expression in some Tourette Syndrome (TS) patients9. TS is a condition characterized by involuntary movements and vocalizations known as tics that are commonly comorbid with other conditions that elicit obsessive/compulsive behavior13. We aimed to understand how this decrease in expression could impact the development of this neurodevelopmental condition by utilizing the common behavioral marker for TS and other neurodevelopmental models, obsessive grooming. By comparing the frequency and time spent grooming between RNAi mediated knockdown mutants of Atg8a produced through the Gal4-UAS system14, and their respective UAS lines and Gal4 drivers acting as controls. Overall, we found that there was a significant general increase in grooming behavior for Atg8a knockdown mutants15.
In exploring the distribution of grooming behaviors, we aimed to evaluate how obsessive grooming in the model described here compares to previously published neurodevelopmental condition Drosophila models, such as those evaluating the Autism Spectrum Disorder gene dfmr1. Studies found that there was not only an increase in grooming frequency7 but also that preferential grooming at the posterior end was observed under mutation of the dfmr18. We found, however, that Atg8a mutants, while displaying an overall increase in grooming, do not exhibit significant changes in the distribution of these behaviors from their control group counterparts. This finding allows us to differentiate our TS-like model from the ASD-like model by behavioral phenotype.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/67708/67708fig01.jpg" /> 
Figure 1: Illustrated workflow of obsessive grooming assay <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/67708/67708fig01large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 2" class="xfigimg" src="/files/ftp_upload/67708/67708fig02.jpg" /> 
Figure 2: Representative images and results of the study. (A) Loaded wells with sample flies as they will appear in the Elan software. (B) Illustrated representation of anatomical distribution classifications made for representative data. (C) Each row in an annotated .mov file is representative of a single fly in a well. Highlighted is the fly, abbreviated FL1, which indicates that the fly is the first in the farthest left column. (D) Drosophila exhibiting posterior grooming behavior abbreviated as PG in Elan 6.8. (E) Drosophila exhibiting anterior grooming behavior abbreviated as ANT in Elan 6.8.&#160;(F) Atg8a knockdown mutant flies had an overall increase in the number of grooming bouts initiated compared to the Ok6-Gal4 driver line (p = 0.0068) and the UAS Atg8a RNAi line (p = 0.0011). There was, however, no significant difference in grooming distribution either posteriorly or anteriorly in mutant flies as compared to these controls. Statistical analysis involved a Brown-Forsythe and Welch two-way ANOVA test meeting a significance level of at least P &#60; 0.001, followed by a Dunnet&#39;s multiple comparisons test. All analyses were performed in Prism 10.&#160;(G) Overall, there was a significant increase in the time the Atg8a knockdown mutant flies spent engaging in grooming behaviors as compared to the Ok6-Gal4 driver line (p = 0.0005) and the UAS Atg8a RNAi line (p = 0.0004). There was, however, no significant difference in grooming distribution either posteriorly or anteriorly in mutant flies as compared to these controls. Statistical analysis involved a Brown-Forsythe and Welch two-way ANOVA test meeting a significance level of at least P &#60; 0.001, followed by a Dunnet&#39;s multiple comparisons test. All analyses were performed in Prism 10. Panels F and G were adapted with permission from Hatfield and Johnson15. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/67708/67708fig02large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

The method presented here involves the manual annotation of footage acquired of Drosophila melanogaster for specific grooming behaviors. It allows for quantification of both the number of grooming bouts and overall time spent grooming to evaluate for atypical self-grooming phenotypes.

Quantification of Drosophila melanogaster Grooming Behavior for Evaluation of Excessive Grooming Phenotypes

Observable changes in stereotyped grooming are applied translationally in model organisms. These changes are representative of pathologies that elicit ...

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Nanyang Technological University

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JoVE Journal

Neuroscience

300 Views.  Simmons University. The method presented here involves the manual annotation of footage acquired of Drosophila melanogaster for specific grooming behaviors. It allows for quantification of both the number of grooming bouts and overall time spent grooming to evaluate for atypical self-grooming phenotypes.

Video: Quantification of Drosophila melanogaster Grooming Behavior for Evaluation of Excessive Grooming Phenotypes

Single Sensillum Recordings in the Insects Drosophila melanogaster and Anopheles gambiae

The sense of smell is essential for insects to find foods, mates, predators, and oviposition sites3. Insect olfactory sensory neurons (OSNs) are enclosed in sensory hairs called sensilla, which cover the surface of olfactory organs. The surface of each sensillum is covered with tiny pores, through which odorants pass and dissolve in a fluid called sensillum lymph, which bathes the sensory dendrites of the OSNs housed in a given sensillum. The OSN dendrites express odorant receptor (OR) proteins, which in insects function as odor-gated ion channels4, 5. The interaction of odorants with ORs either increases or decreases the basal firing rate of the OSN. This neuronal activity in the form of action potentials embodies the first representation of the quality, intensity, and temporal characteristics of the odorant6, 7.
Given the easy access to these sensory hairs, it is possible to perform extracellular recordings from single OSNs by introducing a recording electrode into the sensillum lymph, while the reference electrode is placed in the lymph of the eye or body of the insect. In Drosophila, sensilla house between one and four OSNs, but each OSN typically displays a characteristic spike amplitude. Spike sorting techniques make it possible to assign spiking responses to individual OSNs. This single sensillum recording (SSR) technique monitors the difference in potential between the sensillum lymph and the reference electrode as electrical spikes that are generated by the receptor activity on OSNs1, 2, 8. Changes in the number of spikes in response to the odorant represent the cellular basis of odor coding in insects. Here, we describe the preparation method currently used in our lab to perform SSR on Drosophila melanogaster and Anopheles gambiae, and show representative traces induced by the odorants in a sensillum-specific manner.

Single Sensillum Recordings in the Insects Drosophila melanogaster and Anopheles gambiae

Electrophysiological responses of olfactory sensory neurons to odorants can be measured in insects using single sensillum recordings. In this video article we will demonstrate how to perform single sensillum recordings in the antennae of the vinegar fly (Drosophila melanogaster) and the maxillary palps of the malaria mosquito (Anopheles gambiae).

The sense of smell is essential for insects to find foods, mates, predators, and oviposition sites3. Insect olfactory sensory neurons (OSNs) are enclosed ...

Simultaneous Recording of Calcium Signals from Identified Neurons and Feeding Behavior of Drosophila melanogaster

To study neuronal networks in terms of their function in behavior, we must analyze how neurons operate when each behavioral pattern is generated. Thus, simultaneous recordings of neuronal activity and behavior are essential to correlate brain activity to behavior. For such behavioral analyses, the fruit fly, Drosophila melanogaster, allows us to incorporate genetically encoded calcium indicators such as GCaMP1, to monitor neuronal activity, and to use sophisticated genetic manipulations for optogenetic or thermogenetic techniques to specifically activate identified neurons2-5. Use of a thermogenetic technique has led us to find critical neurons for feeding behavior (Flood et al., under revision). As a main part of feeding behavior, a Drosophila adult extends its proboscis for feeding6 (proboscis extension response; PER), responding to a sweet stimulus from sensory cells on its proboscis or tarsi. Combining the protocol for PER7 with a calcium imaging technique8 using GCaMP3.01, 9, I have established an experimental system, where we can monitor activity of neurons in the feeding center &#x2013; the suboesophageal ganglion (SOG), simultaneously with behavioral observation of the proboscis. I have designed an apparatus ("Fly brain Live Imaging and Electrophysiology Stage": "FLIES") to accommodate a Drosophila adult, allowing its proboscis to freely move while its brain is exposed to the bath for Ca2+ imaging through a water immersion lens. The FLIES is also appropriate for many types of live experiments on fly brains such as electrophysiological recording or time lapse imaging of synaptic morphology. Because the results from live imaging can be directly correlated with the simultaneous PER behavior, this methodology can provide an excellent experimental system to study information processing of neuronal networks, and how this cellular activity is coupled to plastic processes and memory.

Simultaneous Recording of Calcium Signals from Identified Neurons and Feeding Behavior of Drosophila melanogaster

The fruit fly, Drosophila melanogaster, extends its proboscis for feeding, responding to a sugar stimulus from its proboscis or tarsus. I have combined observations of the proboscis extension response (PER) with a calcium imaging technique, allowing us to monitor the activity of neurons in the brain, simultaneously with behavioral observation.

To study neuronal networks in terms of their function in behavior, we must analyze how neurons operate when each behavioral pattern is generated.  Thus, ...

Optogenetic Stimulation of Escape Behavior in Drosophila melanogaster

A growing number of genetically encoded tools are becoming available that allow non-invasive manipulation of the neural activity of specific neurons in Drosophila melanogaster1. Chief among these are optogenetic tools, which enable the activation or silencing of specific neurons in the intact and freely moving animal using bright light. Channelrhodopsin (ChR2) is a light-activated cation channel that, when activated by blue light, causes depolarization of neurons that express it. ChR2 has been effective for identifying neurons critical for specific behaviors, such as CO2 avoidance, proboscis extension and giant-fiber mediated startle response2-4. However, as the intense light sources used to stimulate ChR2 also stimulate photoreceptors, these optogenetic techniques have not previously been used in the visual system. Here, we combine an optogenetic approach with a mutation that impairs phototransduction to demonstrate that activation of a cluster of loom-sensitive neurons in the fly's optic lobe, Foma-1 neurons, can drive an escape behavior used to avoid collision. We used a null allele of a critical component of the phototransduction cascade, phospholipase C-&beta;, encoded by the norpA gene, to render the flies blind and also use the Gal4-UAS transcriptional activator system to drive expression of ChR2 in the Foma-1 neurons. Individual flies are placed on a small platform surrounded by blue LEDs. When the LEDs are illuminated, the flies quickly take-off into flight, in a manner similar to visually driven loom-escape behavior. We believe that this technique can be easily adapted to examine other behaviors in freely moving flies.

Optogenetic Stimulation of Escape Behavior in Drosophila melanogaster

Genetically encoded optogenetic tools enable noninvasive manipulation of specific neurons in the Drosophila brain. Such tools can identify neurons whose activation is sufficient to elicit or suppress particular behaviors. Here we present a method for activating Channelrhodopsin2 that is expressed in targeted neurons in freely walking flies.

A  growing number of genetically encoded tools are becoming available that allow non-invasive  manipulation of the neural activity of specific neurons in ...

A Single-fly Assay for Foraging Behavior in Drosophila

For many animals, hunger promotes changes in the olfactory system in a manner that facilitates the search for appropriate food sources. In this video article, we describe an automated assay to measure the effect of hunger or satiety on olfactory dependent food search behavior in the adult fruit fly Drosophila melanogaster. In a light-tight box illuminated by red light that is invisible to fruit flies, a camera linked to custom data acquisition software monitors the position of six flies simultaneously. Each fly is confined to walk in individual arenas containing a food odor at the center. The testing arenas rest on a porous floor that functions to prevent odor accumulation. Latency to locate the odor source, a metric that reflects olfactory sensitivity under different physiological states, is determined by software analysis. Here, we discuss the critical mechanics of running this behavioral paradigm and cover specific issues regarding fly loading, odor contamination, assay temperature, data quality, and statistical analysis.

A Single-fly Assay for Foraging Behavior in Drosophila

In this video article, we describe an automated assay to measure the effect of hunger or satiety on olfactory dependent food search behavior in the adult fruit fly Drosophila melanogaster.

For many animals, hunger promotes changes in the olfactory system in a manner that facilitates the search for appropriate food sources. In this video ...

Straightforward Assay for Quantification of Social Avoidance in Drosophila melanogaster

Drosophila melanogaster is an emerging model to study different aspects of social interactions. For example, flies avoid areas previously occupied by stressed conspecifics due to an odorant released during stress known as the Drosophila stress odorant (dSO). Through the use of the T-maze apparatus, one can quantify the avoidance of the dSO by responder flies in a very affordable and robust assay. Conditions necessary to obtain a strong performance are presented here. A stressful experience is necessary for the flies to emit dSO, as well as enough emitter flies to cause a robust avoidance response to the presence of dSO. Genetic background, but not their group size, strongly altered the avoidance of the dSO by the responder flies. Canton-S and Elwood display a higher performance in avoiding the dSO than Oregon and Samarkand strains. This behavioral assay will allow identification of mechanisms underlying this social behavior, and the assessment of the influence of genes and environmental conditions on both emission and avoidance of the dSO. Such an assay can be included in batteries of simple diagnostic tests used to identify social deficiencies of mutants or environmental conditions of interest.

Straightforward Assay for Quantification of Social Avoidance in Drosophila melanogaster

Here, we present a protocol to quantify the avoidance of stressed individuals. This paradigm is powerful yet user-friendly and can be used to assess the influence of genes and environment on one kind of social interaction in Drosophila melanogaster.

Drosophila melanogaster is an emerging model to study different aspects of social interactions. For example, flies avoid areas previously occupied by ...

High-resolution Quantification of Odor-guided Behavior in Drosophila melanogaster Using the Flywalk Paradigm

In their natural environment, insects such as the vinegar fly Drosophila melanogaster are bombarded with a huge amount of chemically distinct odorants. To complicate matters even further, the odors detected by the insect nervous system usually are not single compounds but mixtures whose composition and concentration ratios vary. This leads to an almost infinite amount of different olfactory stimuli which have to be evaluated by the nervous system.
To understand which aspects of an odor stimulus determine its evaluation by the fly, it is therefore desirable to efficiently examine odor-guided behavior towards many odorants and odor mixtures. To directly correlate behavior to neuronal activity, behavior should be quantified in a comparable time frame and under identical stimulus conditions as in neurophysiological experiments. However, many currently used olfactory bioassays in Drosophila neuroethology are rather specialized either towards efficiency or towards resolution.
Flywalk, an automated odor delivery and tracking system, bridges the gap between efficiency and resolution. It allows the determination of exactly when an odor packet stimulated a freely walking fly, and to determine the animal&#180;s dynamic behavioral reaction.

High-resolution Quantification of Odor-guided Behavior in Drosophila melanogaster Using the Flywalk Paradigm

The automated tracking system Flywalk is used for high-resolution quantification of odor-guided behavior in Drosophila melanogaster.

In their natural environment, insects such as the vinegar fly Drosophila melanogaster are bombarded with a huge amount of chemically distinct odorants. To ...

Why Quantification Matters: Characterization of Phenotypes at the Drosophila Larval Neuromuscular Junction

Most studies on morphogenesis rely on qualitative descriptions of how anatomical traits are affected by the disruption of specific genes and genetic pathways. Quantitative descriptions are rarely performed, although genetic manipulations produce a range of phenotypic effects and variations are observed even among individuals within control groups.&#160;Emerging evidence shows that morphology, size and location of organelles play a previously underappreciated, yet fundamental role in cell function and survival. Here we provide step-by-step instructions for performing quantitative analyses of phenotypes at the Drosophila larval neuromuscular junction (NMJ). We use several reliable immuno-histochemical markers combined with bio-imaging techniques and morphometric analyses to examine the effects of genetic mutations on specific cellular processes. In particular, we focus on the quantitative analysis of phenotypes affecting morphology, size and position of nuclei within the striated muscles of Drosophila larvae. The Drosophila larval NMJ is a valuable experimental model to investigate the molecular mechanisms underlying the structure and the function of the neuromuscular system, both in health and disease. However, the methodologies we describe here can be extended to other systems as well.

Why Quantification Matters: Characterization of Phenotypes at the Drosophila Larval Neuromuscular Junction

Morphology, size and location of intracellular organelles are evolutionarily conserved and appear to directly affect their function. Understanding the molecular mechanisms underlying these processes has become an important goal of modern biology. Here we show how these studies can be facilitated by the application of quantitative techniques.

Most studies on morphogenesis rely on qualitative descriptions of how anatomical traits are affected by the disruption of specific genes and genetic ...

Foraging Path-length Protocol for Drosophila melanogaster Larvae

The Drosophila melanogaster larval path-length phenotype is an established measure used to study the genetic and environmental contributions to behavioral variation. The larval path-length assay was developed to measure individual differences in foraging behavior that were later linked to the foraging gene. Larval path-length is an easily scored trait that facilitates the collection of large sample sizes, at minimal cost, for genetic screens. Here we provide a detailed description of the current protocol for the larval path-length assay first used by Sokolowski. The protocol details how to reproducibly handle test animals, perform the behavioral assay and analyze the data. An example of how the assay can be used to measure behavioral plasticity in response to environmental change, by manipulating feeding environment prior to performing the assay, is also provided. Finally, appropriate test design as well as environmental factors that can modify larval path-length such as food quality, developmental age and day effects are discussed.

Foraging Path-length Protocol for Drosophila melanogaster Larvae

We provide a detailed protocol for a Drosophila melanogaster foraging path-length assay. We discuss the preparation and handling of test animals, how to perform the assay and analyze the data.

The Drosophila melanogaster larval path-length phenotype is an established measure used to study the genetic and environmental contributions to behavioral ...

A Simple Way to Measure Alterations in Reward-seeking Behavior Using Drosophila melanogaster

We describe a protocol for measuring ethanol self-administration in fruit flies (Drosophila melanogaster) as a proxy for changes in reward states. We demonstrate a simple way to tap into the fly reward system, modify experiences related to natural reward, and use voluntary ethanol consumption as a measure for changes in reward states. The approach serves as a relevant tool to study the neurons and genes that play a role in experience-mediated changes of internal state. The protocol is composed of two discrete parts: exposing the flies to rewarding and nonrewarding experiences, and assaying voluntary ethanol consumption as a measure of the motivation to obtain a drug reward. The two parts can be used independently to induce the modulation of experience as an initial step for further downstream assays or as an independent two-choice feeding assay, respectively. The protocol does not require a complicated setup and can therefore be applied in any laboratory with basic fly culture tools.

A Simple Way to Measure Alterations in Reward-seeking Behavior Using Drosophila melanogaster

We describe a protocol for inducing rewarding and nonrewarding experiences in fruit flies (Drosophila melanogaster) using voluntary ethanol consumption as a measure for changes in reward states.

We describe a protocol for measuring ethanol self-administration in fruit flies (Drosophila melanogaster) as a proxy for changes in reward states. We ...

Analyzing Synaptic Modulation of Drosophila melanogaster Photoreceptors after Exposure to Prolonged Light

The nervous system has the remarkable ability to adapt and respond to various stimuli. This neural adjustment is largely achieved through plasticity at the synaptic level. The Active Zone (AZ) is the region at the presynaptic membrane that mediates neurotransmitter release and is composed of a dense collection of scaffold proteins. AZs of Drosophila melanogaster (Drosophila) photoreceptors undergo molecular remodeling after prolonged exposure to natural ambient light. Thus the level of neuronal activity can rearrange the molecular composition of the AZ and contribute to the regulation of the functional output.
Starting from the light exposure set-up preparation to the immunohistochemistry, this protocol details how to quantify the number, the spatial distribution, and the delocalization level of synaptic molecules at AZs in Drosophila photoreceptors. Using image analysis software, clusters of the GFP-fused AZ component Bruchpilot were identified for each R8 photoreceptor (R8) axon terminal. Detected Bruchpilot spots were automatically assigned to individual R8 axons. To calculate the distribution of spot frequency along the axon, we implemented a customized software plugin. Each axon&#39;s start-point and end-point were manually defined and the position of each Bruchpilot spot was projected onto the connecting line between start and end-point. Besides the number of Bruchpilot clusters, we also quantified the delocalization level of Bruchpilot-GFP within the clusters. These measurements reflect in detail the spatially resolved synaptic dynamics in a single neuron under different environmental conditions to stimuli.

Analyzing Synaptic Modulation of Drosophila melanogaster Photoreceptors after Exposure to Prolonged Light

Here we show how to quantify the number and spatial distribution of synaptic active zones in Drosophila melanogaster&#160;photoreceptors, highlighted with a genetically encoded molecular marker, and their modulation after prolonged exposure to light.

The nervous system has the remarkable ability to adapt and respond to various stimuli. This neural adjustment is largely achieved through plasticity at ...

Quantification of Drosophila melanogaster Grooming Behavior for Evaluation of Excessive Grooming Phenotypes

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Single Sensillum Recordings in the Insects Drosophila melanogaster and Anopheles gambiae

Simultaneous Recording of Calcium Signals from Identified Neurons and Feeding Behavior of Drosophila melanogaster

Optogenetic Stimulation of Escape Behavior in Drosophila melanogaster

A Single-fly Assay for Foraging Behavior in Drosophila

Straightforward Assay for Quantification of Social Avoidance in Drosophila melanogaster

High-resolution Quantification of Odor-guided Behavior in Drosophila melanogaster Using the Flywalk Paradigm

Why Quantification Matters: Characterization of Phenotypes at the Drosophila Larval Neuromuscular Junction

Foraging Path-length Protocol for Drosophila melanogaster Larvae

A Simple Way to Measure Alterations in Reward-seeking Behavior Using Drosophila melanogaster

Analyzing Synaptic Modulation of Drosophila melanogaster Photoreceptors after Exposure to Prolonged Light