This work was supported in part by a scholarship from the Behavioural and Cognitive Neuroscience Program of the University of Groningen and a graduate scholarship from the Consejo Nacional de Ciencia y Tecnolog&#237;a (CONACyT) from Mexico, granted to Andrea Soto-Padilla, and a grant from the John Templeton Foundation for the study of time awarded to Hedderik van Rijn and Jean-Christophe Billeter. We are also thankful to Peter Gerrit Bosma for his participation in developing the FlySteps tracker.
Scripts TemperaturePhases,FlySteps, and FlyStepAnalysis can be found as supplementary information and in the following temporary and publicly available link: 
https://dataverse.nl/privateurl.xhtml?token=c70159ad-4d92-443d-8946-974140d2cb78

1. Preparation of Fly Food Medium
<ol>
	<li>Pour 1 L of tap water into a 2 L glass beaker and add a magnetic stir bar. Put the beaker on a magnetic hot plate at 300 &#176;C until boiling temperature is reached.</li>
	<li>Stir at 500 rounds/min and add the following: 10 g of agar, 30 g of glucose, 15 g of sucrose, 15 g of cornmeal, 10 g of wheat germ, 10 g of soy flour, 30 g of molasses, and 35 g of active dry yeast.</li>
	<li>When the mix foams vigorously, turn down the hot plate temperature to 120 &#176;C while continuing stirring.</li>
	<li>Turn the hot plate temperature further down to 30 &#176;C after 10 min and continue stirring until the mix cools to 48 &#176;C. Measure the temperature by inserting a thermometer directly into the food without touching the walls of the beaker.</li>
	<li>Dissolve 2 g of p-hydroxy-benzoic acid methyl ester into 10 mL of 96% ethanol and add it to the mix, together with 5 mL of 1 M propionic acid. Continue stirring for 3 min.</li>
	<li>Turn the hot plate off and pour 45 mL of food into the rearing bottles and 6.5 mL of food into the collection vials.</li>
</ol>
2. Preparation of Flies
<ol>
	<li>Place 20 male and 20 female flies in the rearing bottles containing 45 mL of fly food medium. Transfer the flies to new bottles after 3 to 4 days by tapping them down and then tapping them into the fresh bottles. Discard the flies after three changes.
	<ol>
		<li>Place the bottles inside the incubator under 12-h light/12-h dark cycles with a constant temperature of 25 &#176;C. 
		NOTE: A new generation of flies will eclose after ten days.</li>
	</ol>
	</li>
	<li>Anesthetize newly eclosed flies on carbon dioxide pads for a maximum of 4 min and collect them in 2.5 x 9.5 cm fly rearing vials with 6.5 mL of fly food medium using a paintbrush.
	<ol>
		<li>Collect only virgin flies and separate them by sex into groups of 20 flies per rearing vial.</li>
		<li>Place the vials inside incubators for 5-7 days, changing the flies to new vials every 2-3 days and on the days before experiments.</li>
	</ol>
	</li>
</ol>
3. Frame of Lights
<ol>
	<li>Make a wooden frame of 10 cm length, 4 cm width, 4 cm height, and 0.5 cm thick.</li>
	<li>On each of the short edges, create a border of 4 cm length, 4 cm height, and 1.5 cm width towards the inside area of the wooden frame. Leave the internal face of the border open.</li>
	<li>Drill two holes of 0.5 cm diameter at the intersection of one of the long edges of the wooden frame and at each of the borders at the short edges.</li>
	<li>Place 10 cm of a warm white LED strip inside each of the borders on the short edges. Peel the back of the LED strip to immediately glue it in place. 
	NOTE: For experiments in which illumination needs to be eliminated, the warm white LED strip can be substituted for infrared LED strips.</li>
	<li>Connect one end of the LED strip in one of the borders to the switching power supply and its other end to the LED strip on the opposite border.</li>
	<li>Turn the switching power supply on to verify that both LED strips turn on.</li>
	<li>Cover the open side of each border with a white piece of paper.</li>
	<li>Glue another piece of paper to each of the internal phases of the long edges.</li>
</ol>
4. Temperature-Controlled Arena
<ol>
	<li>Turn on the temperature-controlled arena (Figure 1A and 1C). Ensure that the fan starts running and the aluminum ring starts warming up.</li>
	<li>Use a USB cable to connect the temperature-controlled arena to the control computer running the TemperaturePhases script with the temperature sequences.</li>
	<li>Open the TemperaturePhases script in the control computer and verify that the temperature sequence is properly set up (Video 1).
	<ol>
		<li>Check that the duration of each experimental phase is set to 60 s by verifying that &#34;par.StimulusDur&#34; is equal to 60 s.</li>
		<li>Check that the 1) number equal to&#160;desired number of phases, 2) iterative ON/OFF set-up of the indicative red light emitting diodes (LEDs), 3) 2 &#176;C temperature increase per phase, and 4) 16 &#176;C as the starting temperature are all correct under the &#34;Start the experimental block&#34; section. 
		NOTE: Allow the flies to acclimate to the Fly Arena for 7 min at 16 &#176;C to avoid an artificial increase of speed during the first experimental phases (Figure 2).</li>
		<li>Run the TemperaturePhases script. The software will initialize for 5 seconds as determined in &#34;arena.Wait&#34; and then stop.&#160;</li>
		<li>Press the spacebar of the keyboard to begin running the experimental phases once a fly has been blown into the Fly Arena (step 5.3). 
		NOTE: The TemperaturePhases is the current script controlling the box; however, it is possible to create other custom scripts to use this device that adjust to the requirements of different experiments.</li>
	</ol>
	</li>
	<li>Connect the camera on top of the arena to the recording computer using the camera&#39;s USB cable.</li>
	<li>Open the video recording program (see Table of Materials) in the recording computer by selecting &#34;File | New Movie Recording&#34;. A screen showing the image from the camera will open.
	<ol>
		<li>Ensure that the camera image captures all edges of the arena and the indicative red LEDs.</li>
		<li>Start recording by pressing the red button in the middle of the screen&#39;s bottom edge showing the camera image once the frame of lights is set around the arena (step 5.4). 
		NOTE: Small changes in lighting can affect accuracy of the tracking. It is recommended to keep the illumination of the temperature-controlled arena constant by fixing the location of the apparatus.</li>
	</ol>
	</li>
</ol>
5. Temperature Behavioral Experiments
<ol>
	<li>Prepare the Fly Arena (Figure 1C).
	<ol>
		<li>Place a strand of white conductive tape on the top of the copper tiles, ensuring all edges are covered.</li>
		<li>Place the heated aluminum ring around the copper tiles. The edge of the ring fits perfectly around the copper tiles so it is always placed in the same location.</li>
		<li>Clean the glass cover with a clean tissue and place it on the top of the aluminum ring, leaving a gap through which a fly can be blown in. 
		NOTE: Before the experiments, coat the glass cover with the siliconizing agent to create a slippery surface. Apply the siliconizing agent for 24 h and rinse it with water before use.</li>
	</ol>
	</li>
	<li>Run the TemperaturePhases script (step 4.3.3) and open the video recording program (step 4.5).</li>
	<li>Blow the fly from a rearing vial (step 2.2.2) into the Fly Arena (e.g., 1 male fly in Figure 3).
	<ol>
		<li>Take a vial of flies from the incubator, tap it twice to force them to go to the bottom, trap one fly with a mouth aspirator, and close the vial and put it back into the incubator.</li>
		<li>Place the fly in the arena through the gap that has been left between the glass cover and aluminum ring (step 5.1.3).</li>
		<li>Close the gap between the glass cover and aluminum ring by pushing the glass cover until it reaches the edge of the aluminum ring as soon as the fly is introduced to the Fly Arena.</li>
	</ol>
	</li>
	<li>Place the frame of lights around the arena to ensure symmetric illumination.
	<ol>
		<li>Mark the location (e.g., using a permanent marker) of the frame of lights around the Fly Arena (Figure 1C) to ensure that the frame is always placed in the same location.</li>
	</ol>
	</li>
	<li>Start recording with the video recording program (step 4.5.2) and press the spacebar on the keyboard of the control computer to begin running the experimental phases (step 4.3.4).</li>
	<li>After all experimental phases are done, save the video in .mp4 or .avi format and remove the fly from the Fly Arena with the mouth aspirator. 
	NOTE: The end of the experimental phases can be determined by both indicative red LEDs being turned off or by the TemperaturePhases script stopping.
	<ol>
		<li>Stop the video recording by pressing the stop button in the middle of the screen&#39;s bottom edge in the recording program. Press &#34;File | Save as&#34; to save the video.</li>
	</ol>
	</li>
</ol>
6. Video Tracking and Data Analysis
<ol>
	<li>Use the FlySteps tracking software (Video 2) to track the videos.
	<ol>
		<li>Open the &#34;configuration_file.ini&#34; inside the &#34;FlyTracker&#34; folder.</li>
		<li>Set the location of the videos in &#34;video_folder&#34; and the names of the videos in &#34;video_files&#34;.</li>
		<li>Specify the borders of the Fly Arena in &#34;arena_settings&#34; based on (x, y) pixel coordinates of multiple points at the edge of the arena.</li>
		<li>Specify the location of the indicative red LEDs in &#34;led_settings&#34; based on (x, y) pixel coordinates of the location of the center of the LEDs.</li>
		<li>Check the location of the borders of the Fly Arena by setting &#34;debug&#34; to &#34;true&#34; in &#34;arena_settings&#34;, clicking &#34;Save&#34;, and running the script in the terminal.A screen capture of the video will appear with a blue square formed by the coordinates inputted in &#34;arena_settings&#34;. 
		NOTE: This square surrounds the area to be tracked.</li>
		<li>Change &#34;debug&#34; in &#34;arena_settings&#34; to &#34;false&#34;, click &#34;Save&#34;, and run the screen in the terminal once more. 
		NOTE: This will start the tracking process. 
		NOTE: Flies can walk out of the tracking area onto the heated aluminum ring. This happens during the first seconds of an experiment, after which flies stop touching the heated ring and remain inside the tracking area. 
		NOTE: Videos can be tracked with other tracking software according to the experimenter&#39;s preferences.</li>
	</ol>
	</li>
	<li>Use the (x,y) location of each fly provided by the tracking software to calculate the measure of interest for the temperature performance. Custom scripts (e.g., FlyStepsAnalysis in Supplementary) can be used.</li>
	<li>Compare the temperature performance curves of different fly groups using repeated measurements (RM) analysis of variance (ANOVA) and post-hoc multiple comparisons using statistical software (see Table of Materials).</li>
</ol>

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The authors declare that they have no competing financial interests.

Here we have presented an automated temperature-controlled arena (Figure 1) that produces precise temperature changes in time and space. This method allows exposure of individual Drosophila not only to pre-programmed gradual increases of temperature (Figure 2 and Figure 3), but also to dynamic temperature challenges in which each tile of the fly arena was heated independently to a different temperature (Figure 4 and Figure 5).
The temperature-controlled arena uses an innovative approach to the heating process. Instead of producing temperature changes in the tiles through thermoelectric Peltier heating elements used in traditional methods, the temperature-controlled arena uses current to warm up a copper mass with the copper tiles, and flies are placed at the top. The copper mass is constantly cooled down by a heat sink block connected to a fan. Peltier-like elements are used to maintain the desired temperature of the copper mass once it has been warmed up. Because these elements are not the main temperature generators, they suffer less stress, which extends their life span and permits faster temperature changes. A programmable circuit that receives feedback from temperature sensors under each of the copper tile, which can also activate the low voltage power supply, coordinates the heating mechanism. Researchers can specify when and where temperature changes occur and determine the intensity and direction of such changes. Furthermore, coupling the method with specialized tracking software, such as FlySteps, permits analysis of all aspects relating to Drosophila&#39;s movement, such as the overall speed at certain temperatures or time spent in certain locations (Figure 2, Figure 3, Figure 4, Figure 5). Nevertheless, all results must consider characteristics inherent to fly behavior that might affect their locomotion. For example, if flies are not allowed to explore the arena and settle before changing the temperature, speed measurements might be artificially high (Figure 2). Flies can also leave odorants that affect subsequent flies; hence, the glass cover must be cleaned, and tape covering the tiles must be changed between subjects. Given that locomotion declines as flies age26, it is important that flies are standardized for age to avoid variation in results. In our arena, flies have also shown centrophobism, preferring edges over the middle area. Experimenters must control for this by changing the location of comfortable areas to prevent overestimating site preference.
The current characteristics of the arena and requirements of the tracking process could limit some experimental procedures. For example, the close environment of the arena does not include access points through which odours could be introduced, which prevents studies in which this stimulus is important. Similarly, the FlyStepts tracker necessitates videos with uniform backgrounds, which limits the possibility of adding food or other items to the fly&#39;s environment. The arena could be adapted to include a connection to a gas valve, and software developments exist that may allow for more objects to be present. Future projects may take advantage of these possibilities to adapt the temperature-controlled arena to specific experimental needs.
Finally, we have shown in the results that different species of Drosophila perform differently as temperature increases (Figure 3) and that temperature mutants do not respond in the same way as controls (Figure 5). This shows that this new method may be used to explore Drosophila&#39;s thermal behavior and how it is affected by natural selection and functional characteristics. Finally, it illustrates that our method may help further understanding of thermal adaptation and speciation as well as the interactions of temperature receptors with other stimuli in future studies.

Temperature is a constant environmental factor that affects how organisms function and behave1. Differences in latitude and altitude lead to differences in the type of climates organism are exposed to, which results in evolutionary selection for their responses to temperature2,3. Organisms respond to different temperatures through morphological, physiological, and behavioral adaptations that maximize performance under their particular environments4. For instance, in the fruit fly Drosophila melanogaster, populations from different regions have different temperature preferences, body sizes, developmental times, longevity, fecundity, and walking performance at different temperatures2,5,6,7. The diversity observed between flies of different origins is explained in part by genetic variation and plastic gene expression8,9. Similarly, Drosophila species from different areas distribute differently among temperature gradients and show differences in resistance to extreme heat and cold tests10,11,12.
Drosophila has also recently become the model of choice to understand the genetic and neural basis of temperature perception13,14,15,16,17. Broadly, adult flies perceive temperature through cold and hot peripheral temperature sensors in the antennae and through temperature sensors in the brain13,14,15,16,17,18,19,20. The periphery receptors for hot temperatures express Gr28b.d16 or Pyrexia21, while the periphery cold receptors are characterized by Brivido14. In the brain, temperature is processed by neurons expressing TrpA115. Behavioral studies on mutants of these pathways are improving our understanding of how temperature is processed and give insights into mechanisms that vary among populations of Drosophila from different regions.
Here we describe a temperature-controlled arena that produces fast and precise temperature changes. Investigators can pre-program these changes, which allows for standardized and repeatable temperature manipulations without human intervention. Flies are recorded and tracked with specialized software to determine their position and speed at different phases of an experiment. The main measurement presented in this protocol is the walking speed at different temperatures, because it is an ecologically relevant index of physiological performance that can identify individual thermal adaptability5. Together with temperature receptor mutants, this technique can help reveal the mechanisms of thermal adaptation at cellular and biochemical levels.

<table><tbody><tr><td>Arduino Due</td><td>Arduino</td><td>A000062</td><td>Software RUG</td></tr><tr><td>Electronics Board</td><td>Ruijsink Dynamic Engineering</td><td>FF-Main-02-2014</td><td></td></tr><tr><td>Power supply Boost</td><td>XP-Power 48. V 65 W</td><td>ECS65US48</td><td>Set to 53 Volt</td></tr><tr><td>Power supply Tile Heating</td><td>XP-Power 15. V 80 W</td><td>VFT80US15</td><td></td></tr><tr><td>Power supply Cooling</td><td>XP-Power 15. V 130 W</td><td>ECS130U515</td><td></td></tr><tr><td>Peltier elements</td><td>Marlow Industries</td><td>RC12-4</td><td>2 Elements, controlled DC feed</td></tr><tr><td>Heat sink</td><td>Fisher Technik</td><td>LA 9/150-230V</td><td>Decoupled for vibration</td></tr><tr><td>Temperature sensors</td><td>Measurement Specialties</td><td>MCD_10K3MCD1</td><td>Micro Thermistor Probe</td></tr><tr><td>Copper block/tiles</td><td>Ruijsink Dynamic Engineering</td><td>FF-CB-01-2014</td><td></td></tr><tr><td>Auminum ring</td><td>Ruijsink Dynamic Engineering</td><td>FF-RoF-02-2015</td><td></td></tr><tr><td>Tesa 4104 white tape 25 x 66 mm</td><td>RS Components</td><td>111-2300&amp;nbsp;</td><td>White conductive tape</td></tr><tr><td>Red LEDs</td><td>Lucky Ligt</td><td>ll-583vc2c-v1-4da</td><td>Wavelength between 625 nm, 20 mAmp and 6 V</td></tr><tr><td>Warm white LED strip</td><td>Ledstripkoning</td><td>HQ-3528-SMD</td><td>60 LEDs per meter</td></tr><tr><td>Switch Power Supply</td><td>Generic</td><td>T-36-12</td><td></td></tr><tr><td>Logitech c920</td><td>Logitech Europe S.A</td><td>PN960-001055</td><td></td></tr><tr><td>QuickTime Player</td><td>Apple Computer</td><td></td><td>Recording program</td></tr><tr><td>Tracking analysis software</td><td>R</td><td></td><td>Packages: pacman</td></tr><tr><td>Tracking analysis software</td><td>MATLAB</td><td></td><td></td></tr><tr><td>Thermal Imaging</td><td>FLIR T400sc</td><td></td><td></td></tr><tr><td>Graphs and Statisticts Software</td><td>Graph Pad Prism</td><td></td><td></td></tr><tr><td>Sigmacote</td><td>Sigma-Aldrich</td><td>SL2-100ML</td><td>Siliconising agent</td></tr><tr><td>Fly rearing bottles</td><td>Flystuff</td><td>32-130</td><td>6oz Drosophila stock bottle</td></tr><tr><td>Flypad</td><td>Flystuff</td><td>59-114</td><td></td></tr><tr><td>Fly rearing vials</td><td>Dominique Dutscher</td><td>789008</td><td>Drosophila tubes narrow 25x95 mm</td></tr><tr><td>Incubator</td><td>Sanyo</td><td>MIR-154</td><td></td></tr><tr><td>Magnetic hot plate</td><td>Heidolph</td><td>505-20000-00</td><td>MR Hei-Standard</td></tr><tr><td>Agar</td><td>Caldic Ingredients B.V.</td><td>010001.26.0</td><td></td></tr><tr><td>Glucose</td><td>Gezond&amp;amp;wel</td><td>1019155</td><td>Dextrose/Druivensuiker</td></tr><tr><td>Sucrose</td><td>Van Gilse</td><td></td><td>Granulated sugar</td></tr><tr><td>Cornmeal</td><td>Flystuff</td><td>62-100</td><td></td></tr><tr><td>Wheat germ</td><td>Gezond&amp;amp;wel</td><td>1017683</td><td></td></tr><tr><td>Soy flour</td><td>Flystuff</td><td>62-115</td><td></td></tr><tr><td>Molasses</td><td>Flystuff</td><td>62-117</td><td></td></tr><tr><td>Active dry yeast</td><td>Red Star</td><td></td><td></td></tr><tr><td>Tegosept</td><td>Flystuff</td><td>20-258</td><td>100%</td></tr></tbody></table>

an automated method to determine the performance of drosophila in response to temperature changes in space and time

Temperature is a ubiquitous environmental factor that affects how species distribute and behave. Different species of Drosophila fruit flies have specific responses to changing temperatures according to their physiological tolerance and adaptability. Drosophila flies also possess a temperature sensing system that has become fundamental to understanding the neural basis of temperature processing in ectotherms. We present here a temperature-controlled arena that permits fast and precise temperature changes with temporal and spatial control to explore the response of individual flies to changing temperatures. Individual flies are placed in the arena and exposed to pre-programmed temperature challenges, such as uniform gradual increases in temperature to determine reaction norms or spatially distributed temperatures at the same time to determine preferences. Individuals are automatically tracked, allowing the quantification of speed or location preference. This method can be used to rapidly quantify the response over a large range of temperatures to determine temperature performance curves in Drosophila or other insects of similar size. In addition, it can be used for genetic studies to quantify temperature preferences and reactions of mutants or wild-type flies. This method can help uncover the basis of thermal speciation and adaptation, as well as the neural mechanisms behind temperature processing.

The temperature-controlled arena (Figure 1A) consists of three copper tiles whose temperature can be individually controlled through a programmable circuit. Each copper tile possesses a temperature sensor that gives feedback to the programmable circuit. The circuit activates a power supply to increase the temperature of each tile. Passive thermoelectric elements act as constant heating elements to maintain the desired temperature, while a heat sink cooled by a fan provides constant cooling. The magnitude of temperature change determines the speed of the process in a non-linear manner. An increase of 2 &#176;C requires only 0.1 s, and an increase of 18 &#176;C requires 4 s. A screen connected to the programmable circuit (Figure 1C) informs the user of the temperature measured by the temperature sensors in each of the tiles. The copper tiles are surrounded by an aluminum ring constantly heated to 50 &#176;C (Figure 1B and 1C) by semiconductors around the periphery. This ring forms the edges of the Fly Arena (Figure 1C), the area in which flies are to be placed. The Fly Arena is covered by a siliconized glass cover (Figure 1A and 1C), which provides a 3 mm high space which ensures that flies can walk but not fly. Next to the Fly Arena are two red LEDs (Figure 1C) that can be programmed to mark different experimental phases. For example, for the results shown in Figure 2A, each LED is associated with a different temperature, while in Figure 2B, each LED indicates 60 s. The FlySteps software can register when each of the indicative LEDs is on, and the researcher can then use this information to automatically determine the experimental phases based on temperature or time.
The temperature-controlled arena can be used to compare the behavioral response of flies from different genetic backgrounds to dynamic temperature changes. For example, flies from different species can be exposed to gradually increasing temperatures (Figure 3) to compare differences in thermal performance. The speed of all species increases as temperature increases until reaching a point of maximum performance, after which it decayed and perished. However, each species has a particular response curve with specific maximum response speeds and thermal tolerances. Previous reports have shown that Drosophila from different species differ among developmental timing, longevity, fecundity, body dimensions, sexual communication, and temperature tolerance3,6,7,8,22. Thus, our description of species-specific locomotion in a temperature gradient adds to this body of work.
The temperature-controlled arena can also be used to explore the response to conditioning experiments based on temperature. The simplest form of this approach is an operant conditioning paradigm in which flies are trained to prefer one side of the arena over the other, by warming up the side that will be avoided23,24,25. We exposed individual flies to 40 &#176;C in the middle and one of the side tiles, while leaving the other side tile at a comfortable 22 &#176;C (Figure 4). Wild-type flies quickly stopped moving along the arena and remained in the comfortable location. In contrast, the classic memory mutant Dunce kept exploring the arena and spent less time than controls in the comfortable location. The differences between performance of the wild-type flies and Dunce mutants became larger when all tiles were set to 22 &#176;C and comparisons were made between the treatment groups. Dunce mutants also showed greater differences between training and test phases in comparison to the wild-type flies (Figure 4). These results suggest an effect of memory on remaining in the comfortable location.
Combinations of temperature and location are also useful to understand the function of different temperature receptors during dynamic temperature changes. We exposed individual D. melanogaster Gr28b.d and TrpA1GAL4 mutants to increasing temperatures (2 &#176;C increase every 60 s) while providing a comfortable location at 22 &#176;C (Figure 5). The comfortable location shifted from left to right, and vice versa, per iteration. Results show that the periphery temperature receptor Gr28b.d mutants behave as the control, as they spend more time in the comfortable location as temperature increases. However, brain temperature receptor TrpA1GAL4 mutants are not affected by increasing temperatures and do not change their locations in the arena. The increases and decrease in the curve of TrpA1GAL4 mutants show the effect in flies that were already sitting in the comfortable location before it became comfortable and remained there during that phase. The consistency of peaks and valleys of the curve of TrpA1GAL4 suggest that these flies remained still for most of the experiment; hence, they were constantly counted when their location was the one considered comfortable. This conclusion was confirmed by visual inspection of the recorded videos. These results support previous physiological reports suggesting that periphery perception of fast and large changes does not depend on Gr28b.d17 and that flies possess a main central mechanism to sense temperature based on TrpA114,21.
<img alt="Figure 1" class="xfigimg" src="/files/ftp_upload/58350/58350fig1.jpg" /> 
Figure 1: Diagram of temperature controlled-arena. (A) A lateral view of the temperature-controlled arena. A programmable circuit connects a power supply and temperature sensors to heating elements under copper tiles to control their temperature. Tiles are constantly cooled down through a heat sink connected to a fan. A heated aluminum ring over which a glass cover rests surrounds the tiles. (B) Thermal imaging showing the tiles set at 24 &#176;C (top) and side tiles at 24 &#176;C with a middle tile at 30 &#176;C (bottom). (C) A top view of the arena. A camera records the copper tiles, aluminum ring, and red LEDs, then automatically determines experimental phases. A screen in the corner of the box, not recorded by the camera, displays the current tile temperature. (D) Ring of light: two warm white LED strips inside a wooden box covered in white paper ensure constant and symmetric illumination of the whole arena. <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58350/58350fig1large.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/58350/58350fig2.jpg" /> 
Figure 2: Flies must acclimate to the arena before starting the temperature protocol. (A) Single male flies were introduced to the arena and allowed to explore at a constant 16 &#176;C for 1 min, after which the temperature started increasing. (B) Single flies exposed to 16 &#176;C, 20 &#176;C, or 24 &#176;C (no group differences; two-way ANOVA F (2,570) = 4.156, p = 0.162) have a higher locomotion at the beginning of the experiment than after 5 min (two-way RM ANOVA F (9,570) = 7.803, p &#60; 0.0001). Data are mean and standard error of the mean (&#177; SEM) of 20 virgin female flies 5 to 7 days old tested over multiple days. Asterisk indicates significant difference among groups (****p &#60; 0.0001; Tukey&#39;s multiple comparison test, p = 0.05). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58350/58350fig2large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 3" class="xfigimg" src="/files/ftp_upload/58350/58350fig3.jpg" /> 
Figure 3: Locomotion of 5 Drosophila species exposed to gradually increasing temperatures. Individual male flies from temperate (blue), tropical (red), and cosmopolitan (brown) Drosophila species were exposed to an increasing temperature gradient (2 &#176;C every 60 s) between 16 and 46 &#176;C. The first 7 min were constantly at 22 &#176;C to allow flies to explore the arena. Species were significantly different (two-way RM ANOVA F(4,70) = 28.46, p &#60; 0.001). (a) D. melanogaster (brown; filled circles) was faster when introduced to the arena. (b) D. yakuba (red; empty squares) was faster as temperature increased. (c) D. suzukii (brown; filled square) was slower than the other cosmopolitan flies at its maximum performance point. (d) D. simulans (brown; empty circles) was in decay at the maximum point of D. melanogaster. Each point represents the mean (&#177; SEM) of 15 male flies 5 to 7 days old tested over several days. Significance indicated by symbols (&#9830; = difference from all, p &#60; 0.0001; &#8224;= difference from all except D. melanogaster, p &#60; 0.0001; &#8226; = difference from D. melanogaster, p &#60; 0.01; &#162; = difference from D. melanogaster, p &#60; 0.001; **** = difference between named groups, p &#60; 0.0001; Tukey&#39;s multiple comparison test, p = 0.05). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58350/58350fig3large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 4" class="xfigimg" src="/files/ftp_upload/58350/58350fig4.jpg" /> 
Figure 4: The temperature-controlled arena can be used for operant conditioning. D. melanogaster Canton-S strain (wild-type; black border) and dnc1 (Dunce; red border) mutants were trained to prefer a lateral tile at 22 &#176;C after warming the middle and opposite lateral tiles to 40 &#176;C for 4 min (training, no pattern). Memory of the heated areas is then tested by setting all tiles to 22 &#176;C (test; grid pattern). Flies were conditioned to prefer tiles on the left in half of the experiments, then tiles on the right in the other half. The percentage of total time inside the tile at 22 &#176;C during training and testing was measured to compare performances. Groups were significantly different (one-way ANOVA F(3,76) = 23.23, p &#60; 0.0001), with Dunce performing worse than wild-type overall. Data are mean (&#177; SEM) of 20 virgin female flies 5 to 7 days old tested over several days. Asterisks indicate significance difference among groups (****p &#62; 0.0001; ***p &#62; 0.001; **p &#62; 0.01; Tukey&#39;s multiple comparison test, p = 0.05) <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58350/58350fig4large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>
<img alt="Figure 5" class="xfigimg" src="/files/ftp_upload/58350/58350fig5.jpg" /> 
Figure 5: Response of temperature mutants to increasing temperature when a comfortable location is provided. Temperature mutants Gr28b.d (green; squares) respond as controls (w1118, black; circles) by increasing the percentage of time in the comfortable area as temperature increases (two-way RM ANOVA F (1,38) = 0.5107, p = 0.479). TrpA1GAL4 mutants (yellow; triangles) are different from controls (w1118, black), as they do not increase the time in the comfortable area as temperature increases (two-way RM ANOVA F (1,38) = 1.670, p = 0.019). Data are mean (&#177; SEM) of 20 male flies 5 to 7 days old tested over several days. TrpA1GAL4 is significantly different from Gr28b.d and the control (p &#60; 0.05; Tukey&#39;s multiple comparison test, p = 0.05). <a href="https://www-jove-com.remotexs.ntu.edu.sg/files/ftp_upload/58350/58350fig5large.jpg" target="_blank">Please click here to view a larger version of this figure.</a>

Watch this Scientific Journal Video about An Automated Method to Determine the Performance of Drosophila in Response to Temperature Changes in Space and Time at JoVE.com

An Automated Method to Determine the Performance of Drosophila in Response to Temperature Changes in Space and Time

Here we present a protocol to automatically determine the locomotor performance of Drosophila at changing temperatures using a programmable temperature-controlled arena that produces fast and accurate temperature changes in time and space.

An Automated Method to Determine the Performance of Drosophila in Response to Temperature Changes in Space and Time

Temperature is a ubiquitous environmental factor that affects how species distribute and behave. Different species of Drosophila fruit flies have specific ...

an-automated-method-to-determine-performance-drosophila-response-to

Nanyang Technological University

Research

JoVE Journal

Behavior

6.4K Views.  University of Groningen. Deze methode kan ons helpen bij het beantwoorden van belangrijke vragen over de reactie van vliegen op temperatuurveranderingen, zoals verschillen tussen genotypen, de interactie met andere zintuiglijke signalen, of de functie van verschillende temperatuurreceptoren. Het belangrijkste voordeel van deze techniek is dat het zorgt voor meerdere snelle en nauwkeurige temperatuurveranderingen die tijd en ruimte en op een geautomatiseerde manier regelen. Begin met het plaatsen van 20 mannelijke en ...

Video: An Automated Method to Determine the Performance of Drosophila in Response to Temperature Changes in Space and Time

Assaying Locomotor Activity to Study Circadian Rhythms and Sleep Parameters in Drosophila

Most life forms exhibit daily rhythms in cellular, physiological and behavioral phenomena that are driven by endogenous circadian (&equiv;24 hr) pacemakers or clocks. Malfunctions in the human circadian system are associated with numerous diseases or disorders. Much progress towards our understanding of the mechanisms underlying circadian rhythms has emerged from genetic screens whereby an easily measured behavioral rhythm is used as a read-out of clock function. Studies using Drosophila have made seminal contributions to our understanding of the cellular and biochemical bases underlying circadian rhythms. The standard circadian behavioral read-out measured in Drosophila is locomotor activity. In general, the monitoring system involves specially designed devices that can measure the locomotor movement of Drosophila. These devices are housed in environmentally controlled incubators located in a darkroom and are based on using the interruption of a beam of infrared light to record the locomotor activity of individual flies contained inside small tubes. When measured over many days, Drosophila exhibit daily cycles of activity and inactivity, a behavioral rhythm that is governed by the animal's endogenous circadian system. The overall procedure has been simplified with the advent of commercially available locomotor activity monitoring devices and the development of software programs for data analysis. We use the system from Trikinetics Inc., which is the procedure described here and is currently the most popular system used worldwide. More recently, the same monitoring devices have been used to study sleep behavior in Drosophila. Because the daily wake-sleep cycles of many flies can be measured simultaneously and only 1 to 2 weeks worth of continuous locomotor activity data is usually sufficient, this system is ideal for large-scale screens to identify Drosophila manifesting altered circadian or sleep properties.

Assaying Locomotor Activity to Study Circadian Rhythms and Sleep Parameters in Drosophila

We describe procedures for recording daily locomotor activity rhythms of Drosophila and subsequent data analysis. Locomotor activity rhythms are a reliable behavioral output of animal circadian clocks and are used as the standard readout of clock function when studying circadian mutants or examining how the environment regulates the circadian system.

Most life forms exhibit daily rhythms in cellular, physiological and behavioral phenomena that are driven by endogenous circadian (&equiv;24 hr) ...

Neuroscience

Quantitative Measurement of the Immune Response and Sleep in Drosophila

A complex interaction between the immune response and host behavior has been described in a wide range of species. Excess sleep, in particular, is known to occur as a response to infection in mammals 1 and has also recently been described in Drosophila melanogaster2. It is generally accepted that sleep is beneficial to the host during an infection and that it is important for the maintenance of a robust immune system3,4. However, experimental evidence that supports this hypothesis is limited4, and the function of excess sleep during an immune response remains unclear. We have used a multidisciplinary approach to address this complex problem, and have conducted studies in the simple genetic model system, the fruitfly Drosophila melanogaster. We use a standard assay for measuring locomotor behavior and sleep in flies, and demonstrate how this assay is used to measure behavior in flies infected with a pathogenic strain of bacteria. This assay is also useful for monitoring the duration of survival in individual flies during an infection. Additional measures of immune function include the ability of flies to clear an infection and the activation of NF&kappa;B, a key transcription factor that is central to the innate immune response in Drosophila. Both survival outcome and bacterial clearance during infection together are indicators of resistance and tolerance to infection. Resistance refers to the ability of flies to clear an infection, while tolerance is defined as the ability of the host to limit damage from an infection and thereby survive despite high levels of pathogen within the system5. Real-time monitoring of NF&kappa;B activity during infection provides insight into a molecular mechanism of survival during infection. The use of Drosophila in these straightforward assays facilitates the genetic and molecular analyses of sleep and the immune response and how these two complex systems are reciprocally influenced.

Quantitative Measurement of the Immune Response and Sleep in Drosophila

To understand a link between the immune response and behavior, we describe a method to measure locomotor behavior in Drosophila during bacterial infection as well as the ability of flies to mount an immune response by monitoring survival, bacterial load, and real-time activity of a key regulator of innate immunity, NF&kappa;B.

A complex interaction between the immune response and  host behavior has been described in a wide range of species. Excess sleep, in  particular, is known ...

Immunology and Infection

Determination of the Spontaneous Locomotor Activity in Drosophila melanogaster

Drosophila melanogaster has been used as an excellent model organism to study environmental and genetic manipulations that affect behavior. One such behavior is spontaneous locomotor activity. Here we describe our protocol that utilizes Drosophila population monitors and a tracking system that allows continuous monitoring of the spontaneous locomotor activity of flies for several days at a time. This method is simple, reliable, and objective and can be used to examine the effects of aging, sex, changes in caloric content of food, addition of drugs, or genetic manipulations that mimic human diseases.

Determination of the Spontaneous Locomotor Activity in Drosophila melanogaster

Drosophila melanogaster are useful in studying genetic or environmental manipulations that affect behaviors such as spontaneous locomotor activity.&#160; Here we describe a protocol that utilizes monitors with infrared beams and data analysis software to quantify spontaneous locomotor activity.&#160;

Drosophila melanogaster has been used as an excellent model organism to study environmental and genetic manipulations that affect behavior. One such ...

High-Throughput Heat Tolerance Measurement in Drosophila Using DAM2 Systems

Heat Tolerance Assays Using the Drosophila Activity Monitor System: A Guide to an Executable Application for Data Analysis

The study of heat tolerance in&#8239;Drosophila melanogaster has been of particular interest to researchers for decades, with a common approach to assessing heat tolerance being to monitor the time to knockdown (TKD) after exposure to an elevated temperature. Classically, flies are housed in individual vials and placed inside a heated water bath. TKD is then monitored manually by researchers. While very well-established, there remain problems of subjectivity and consistent application of a tangible definition of cessation of all movement, including muscular spasms, when implementing these manual assays. We have developed a high-throughput method for automating heat tolerance assays using the TriKinetics Drosophila Activity Monitors (DAM2). To accompany the DAM2 system, we have written a program and created an easy-use executable to automatically read the last time of movement from the activity data generated. This script then writes to a .csv file the time to heat paralysis (TKD) for each fly. Our data show that this automated DAM2 method is consistent and reliable. Meanwhile, activity profiles created from the activity count data are of interest. These activity profiles can be compiled and have the potential to expand heat tolerance assays to include the relatively unstudied behavioral components of heat tolerance. This protocol will describe in detail how to use the DAM2 system and the HoTDAM! software to estimate heat tolerance in D. melanogaster.

This report describes a method for measuring adult Drosophila melanogaster time to knockdown using a Drosophila Activity Monitor (DAM2) in response to an air conduction heat stressor within an incubator chamber. The DAM2 measures activity by recording individual fly movements as they cross an infrared beam. Data analysis is facilitated by a novel executable file created by the authors.

The study of heat tolerance in&#8239;Drosophila melanogaster has been of particular interest to researchers for decades, with a common approach to ...

A Temperature Gradient Assay to Determine Thermal Preferences of Drosophila Larvae

Many animals, including the fruit fly, Drosophila melanogaster, are capable of discriminating minute differences in&#160;environmental temperature, which enables them to seek out their preferred thermal landscape. To define the temperature preferences of larvae over a defined linear range, we developed an assay using a temperature gradient. To establish a single-directional gradient, two aluminum blocks are connected to independent water baths, each of which controls the temperature of individual blocks. The two blocks set the lower and upper limits of the gradient. The temperature gradient is established by placing an agarose-coated aluminum plate over the two water-controlled blocks so that the plate spans the distance between them. The ends of the aluminum plate that is set on the top of the water blocks defines the minimum and maximum temperatures, and the regions in-between the two blocks form a linear temperature gradient. The gradient assay can be applied to&#160;larvae of different ages and can be used to identify mutants that exhibit phenotypes, such as those with mutations affecting genes encoding TRP channels and opsins, which are required for temperature discrimination.

A Temperature Gradient Assay to Determine Thermal Preferences of Drosophila Larvae

Here, we present a protocol to determine the preferred environmental temperature of Drosophila larvae using a continuous thermal gradient.

Many animals, including the fruit fly, Drosophila melanogaster, are capable of discriminating minute differences in&#160;environmental temperature, which ...

Design and Analysis of Temperature Preference Behavior and its Circadian Rhythm in Drosophila

The circadian clock regulates many aspects of life, including sleep, locomotor activity, and body temperature (BTR) rhythms1,2. We recently identified a novel Drosophila circadian output, called the temperature preference rhythm (TPR), in which the preferred temperature in flies rises during the day and falls during the night 3. Surprisingly, the TPR and locomotor activity are controlled through distinct circadian neurons3. Drosophila locomotor activity is a well&#160;known circadian behavioral output and has provided strong contributions to the discovery of many conserved mammalian circadian clock genes and mechanisms4. Therefore, understanding TPR will lead to the identification of hitherto unknown molecular and cellular circadian mechanisms. Here, we describe how to perform and analyze the TPR assay. This technique not only allows for dissecting the molecular and neural mechanisms of TPR, but also provides new insights into the fundamental mechanisms of the brain functions that integrate different environmental signals and regulate animal behaviors. Furthermore, our recently published data suggest that the fly TPR shares features with the mammalian BTR3. Drosophila are ectotherms, in which the body temperature is typically behaviorally regulated. Therefore, TPR is a strategy used to generate a rhythmic body temperature in these flies5-8. We believe that further exploration of Drosophila TPR will facilitate the characterization of the mechanisms underlying body temperature control in animals.

Design and Analysis of Temperature Preference Behavior and its Circadian Rhythm in Drosophila

We recently identified a novel Drosophila circadian output, temperature preference rhythm (TPR), in which the preferred temperature in flies rises during the day and falls during the night. TPR is regulated independently from another circadian output, locomotor activity. Here&#160;we describe the design and analysis of TPR in Drosophila.

The circadian clock regulates many aspects of life, including sleep, locomotor activity, and body temperature (BTR) rhythms1,2. We recently identified a ...

Biology

An Improved Method for Accurate and Rapid Measurement of Flight Performance in Drosophila

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An Improved Method for Accurate and Rapid Measurement of Flight Performance in Drosophila

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Drosophila has proven to be a useful model system for analysis of behavior, including flight. The initial flight tester involved dropping flies into an ...

Measurement of Larval Activity in the Drosophila Activity Monitor

Drosophila larvae are used in many behavioral studies, yet a simple device for measuring basic parameters of larval activity has not been available. This protocol repurposes an instrument often used to measure adult activity, the TriKinetics Drosophila activity monitor (MB5 Multi-Beam Activity Monitor) to study larval activity. The instrument can monitor the movements of animals in 16 individual 8 cm glass assay tubes, using 17 infrared detection beams per tube. Logging software automatically saves data to a computer, recording parameters such as number of moves, times sensors were triggered, and animals&#8217; positions within the tubes. The data can then be analyzed to represent overall locomotion and/or position preference as well as other measurements. All data are easily accessible and compatible with basic graphing and data manipulation software. This protocol will discuss how to use the apparatus, how to operate the software and how to run a larval activity assay from start to finish.

Measurement of Larval Activity in the Drosophila Activity Monitor

This report describes a method for measuring Drosophila larval activity using the TriKinetics Drosophila Activity Monitor. The device employs infrared beams to detect movements of up to 16 individual animals. Data can be analyzed to represent motion parameters including rates and the positions of the animals within the assay chambers.

Drosophila larvae are used in many behavioral studies, yet a simple device for measuring basic parameters of larval activity has not been available. This ...

High-Throughput Assays of Critical Thermal Limits in Insects

Upper and lower thermal limits of plants and animals are important predictors of their performance, survival, and geographic distributions, and are essential for predicting responses to climate change. This work describes two high-throughput protocols for measuring insect thermal limits: one for assessing critical thermal minima (CTmin), and the other for assessing heat knock down time (KDT) in response to a static heat stressor. In the CTmin assay, individuals are placed in an acrylic-jacketed column, subjected to a decreasing temperature ramp, and counted as they fall from their perches using an infrared sensor. In the heat KDT assay, individuals are contained in a 96 well plate, placed in an incubator set to a stressful, hot temperature, and video recorded to determine the time at which they can no longer remain upright and move. These protocols offer advantages over commonly used techniques. Both assays are low cost and can be completed relatively quickly (~2 h). The CTmin assay reduces experimenter error and can measure a large number of individuals at once. The heat KDT protocol generates a video record of each assay and thus removes experimenter bias and the need to continuously monitor individuals in real time.

Thermal limits can predict the environments organisms tolerate, which is valuable information in the face of rapid climate change. Described here are high-throughput protocols to assess critical thermal minima and heat knockdown time in insects. Both protocols maximize the throughput and minimize the cost of the assays.

Upper and lower thermal limits of plants and animals are important predictors of their performance, survival, and geographic distributions, and are ...

Temperature Gradient Assay: A Method to Test Temperature Preference in Drosophila Larvae

Source: Liu, J., et al. <a href="https://www-jove-com.remotexs.ntu.edu.sg/video/57963/" target="_blank">A Temperature Gradient Assay to Determine Thermal Preferences of Drosophila Larvae</a>. J. Vis. Exp. (2018).
Drosophila fruit flies can distinguish small changes in temperature and therefore select environments with favorable thermal conditions. This video describes a behavioral assay that tests the temperature preference of Drosophila larvae on a linear thermal gradient.

Source: Liu, J., et al. A Temperature Gradient Assay to Determine Thermal Preferences of Drosophila Larvae. J. Vis. Exp. (2018).
Drosophila fruit flies ...

An Automated Method to Determine the Performance of Drosophila in Response to Temperature Changes in Space and Time

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