Four-Way Olfactometer Assay: A Method to Assess Odorant-Cued Responses in Drosophila

This protocol is an excerpt from Lin et al., Olfactory Behaviors Assayed by Computer Tracking Of Drosophila in a Four-quadrant Olfactometer, J. Vis. Exp. (2016).

1. Behavioral Responses to Attractive and Repellent Odorants

1. Switch on the temperature controller and set it to 25 °C.
2. Connect the odorant chambers (control and test odorants) by inserting the tubing to the outlet of odorant chamber and to the push-to-connect fitting on the behavior box.
3. Check the flow rate in each quadrant by using the airflow meter to make sure that the control and odorant airstreams are equal to 100 ml/min.
4. Clean the PTFE fly arena and the glass plates with 70% ethanol 2-3 times and allow them to fully air dry (~3-4 min).
5. Affix the glass plates to the arena with clamps.
6. Transfer flies without CO₂ anesthesia into the arena through the hole in one of the glass plates. After the transfer, place a circular mesh on the hole to prevent flies from escaping.
   NOTE: CO₂ anesthesia has been shown to affect Drosophila behavior and should not be used within 24 hr of a behavioral experiment.
7. Place the arena with flies into the light-tight chamber, connect the four control air streams by connecting the tubing attached to the push-to-connect fitting on the behavior box to the arena corners, close the door of the chamber and wait 10-15 min to let the flies acclimatize to the new environment. If possible, switch the lights off in the room where the experiments are performed, to avoid possible minimal light leak that may bias the experimental outcome.
8. Run a 5-10 min control experiment, in which flies are exposed to 4 control air streams.
9. Analyze the data immediately (see Data analysis section below) to make sure that the flies are distributed uniformly in the arena, and the Attraction Index is close to 0. This step is essential, as it verifies that there are no uncontrolled sources of preference or avoidance within the arena (e.g. light leaking from the outside, uneven temperature distribution, uneven arena, odor contamination, etc.). If the flies are distributed unequally or their locomotor activity is low, discard the flies, clean the arena again (Step 1.4) and use a new batch of flies to repeat the experiment.
10. Connect the test odorant chamber to the setup by switching on the 3-way valves or re-plugging the connector tubes.
11. Run test experiment for 5-10 min and analyze the data as discussed in section 2 below (Figure 1). Recordings longer than 20 min can result in data files that may be difficult to computationally process. If longer experimental recordings are desired, rapidly stop and re-start the tracking program. This results in a ~10 sec gap between experimental recordings.
12. Discard flies.
13. Clean arena and glass plates with 70% ethanol (Step 1.4) and replace connector tubes within the light-tight enclosure. To expedite experiments, a new clean arena can be used, and the dirty arena cleaned while performing experimental runs.
14. Run another experiment with a new batch of flies, if required. If several experiments are run on the same day, take extreme care to ensure that no odorant is left in the system from a previous test run. This is normally not a problem with low concentrations of odorants or with CO₂, but for highly concentrated stimuli up to a 24 hr gap between experimental runs may be needed. In addition, all tubing after the flow-tubes can be replaced if odorant contamination is suspected during control experiments. Always leave the dry air on between the experiments to continuously flush the system.

2. Data Analysis

NOTE: The suggested fly tracking acquisition software (detailed in Materials), tracks flies in real time during acquisition, and saves the time stamp and coordinates of all detected flies in *.dat format. We have developed a custom-made Matlab routine to convert the data into a Matlab format, and to analyze the data. Code examples are provided in Supplementary Materials, but details of implementation will depend on the software used for data acquisition.

1. Load the raw data. Create a spatial mask that follows the contours of the arena and apply the mask to the raw data to remove all data points that fall outside of the arena as they represent noise (Figure 2A, Supplementary Code MaskSpatialFiltering.m, Score.m, DrawCircularMask.m).
2. Remove all data points that move at a speed below 0.163 cm/s for longer than 3s, as this data is likely to be noise or generated by non-moving flies (Figure 2B, Supplementary Code TemporalFiltering.m).
3. Visualize remaining data points by plotting them out all at once or as single trajectories (Figure 1, Supplementary Code SingleTrajectoryViewer.m).
   NOTE: The location of odor boundaries in the four-field likely depends on a number of factors, such as the characteristics of each odorant and the airflow rates being used. For example, highly volatile odorants will likely fill the odor quadrant more fully than less volatile odorants. Thus, it is likely that each odorant may exhibit slightly different odor boundaries. The use of a photoionization detector to measure odor boundaries can be problematic as it uses a vacuum to sample air from a particular spot, and so disrupts the odorant concentration at that spot. Nonetheless, odor boundaries can be quickly estimated based on fly behavioral data. For example, an odor boundary based on cumulated fly tracks in response to different odors can be clearly observed in Figure 1C and 1D.
4. Calculate an attraction index to determine whether control experiments generate no preference response, and also to access the response to an odorant (or optogenetic) stimulus. To calculate an Attraction Index (AI), use the last 5 min of a control or test recording. To obtain a measure of attraction that falls between +1 (absolute attraction) and -1 (absolute repulsion), the following formula is used to calculate the AI:
   
   where N_test is the number of data points in the test quadrant, N_control is the average number of data points in the three control quadrants. This measure is intuitive as no preference would be indicated by near-zero values. However, it does not correctly indicate the proportion of the total number of flies that are located in the odorant quadrant. To obtain this measure, a Percentage Index (PI) may be used:
   
   where N_test is the number of data points in the test quadrant, and N_total is the total number of data points in all four quadrants. This formula provides a measure that falls between 0 and 1, with 0.25 corresponding to no behavioral preference (Figure 1E and 2C, Supplementary Code AttractionIndex.m).
5. Run 5-10 repeats of each experimental condition, using a new group of flies for each repeat. Compare the attraction indexes between conditions or against controls by using the Kolmogorov-Smirnov non-parametric test (Figure 1F, kstest2 function in Matlab).