This repository contains all data that is used to run all the code found on https://gitlab.com/davidtadres/electrotaxis_publication to create all figures presented in the paper titled ‘Sensation of electric fields in Drosophila melanogaster’

Description of the Data and file structure

Folder ‘Behavior’ contains all behavioral data, folder ‘Ca_imaging_data’ contains all data related to calcium imaging, folder ‘simulation’ contains all data related to simulations and folder ‘IHC’ contains all immunohistochemistry images.

We recommend to use this repository in the following order:

1. Identify the figure in the manuscript one wants to re-plot (e.g. Figure 1F)
2. download the repository containing all code using the files found here.
3. Follow the Readme of the repository to point the code to the data from datadryad
4. In the folder ‘eletrotaxis_publication’ find the jupyter notebook with the desired figure name (“Fig1_multi_animal_assay.ipynb”).
5. Open the jupyter notebook and run the script. This should produce the unedited plot that was used for that figure.

Below is detailed information about each file type found in this repository.

Folder ‘Behavior’ contains exclusively data collected with PiVR (https://doi.org/10.1371/journal.pbio.3000712, www.PiVR.org). Data in the folders ‘pulse_experiment’ and ‘switch’ are single animal experiments. Navigation indeces were calculated by first running the following script: ‘electrotaxis_publication/Behavior_analysis/single_animal_assay/Calculate_Navigation_Index.py’ Data in the folder ‘static’ were multi animal experiments. After digitization of the animal position, scripts in ‘electrotaxis_publication/Behavior_analysis/multi_animal_assay’ were run to calculate the preference index. Please read the methods in the manuscript ‘Sensation of electric fields in Drosophila melanogaster’ for more information.

The structure of the ‘Behavior’ folder is as follows:

• Behavior
  • type of experiment (e.g. ‘pulse_experiment’ or ‘static’).
    We first focus on ‘pulse_experiment’ and ‘switch’ as those were single animal experiments
    • genotype (sometimes this is 2 folders deep, e.g. ‘Gr66a/MS193xMS581’ as a number of controls were run for each genotype).
      • some folders contain quality control and other files:
        • ‘CentroidSpeed.png’ is calculated in file
          ‘Calculate_Navigation_Index.py’. Similar to the tail speed
          shown in the figures. Less precise (tail indicates speed better)
          but more robust (centroid position is generally more correct than
          tail position before Head/Tail correction).
        • ‘median_nav_index.npy’ is calculated in file
          ‘Calculate_Navigation_Index.py’. It is the raw median Navigation Index
          at each timepoint.
        • ‘Navigation Index.png’ is calculated in file
          ‘Calculate_Navigation_Index.py’. It’s a plot of ‘median_nav_index.npy’.
        • ‘mean_corrected_nav_index.npy’ is calculated in file
          ‘Calculate_Navigation_Index.py’. It is the mean corrected
          (meaning it takes into account the polarity of the e-field)
          Navigation Index per experiment.
        • ‘voltages.npy’ is calculated in file
          ‘Calculate_Navigation_Index.py’. These are the voltages correctly
          aligned between experiments.
        • individual experiments (e.g. ‘2023.06.14_16-40-17_pulse exp’)
          Each experimental folder contains a set of files which are the
          standard output of PiVR as explained here:
          https://pivr.readthedocs.io/en/latest/output.html#tracking.
          • DATE_TIME_data.csv” contains the following columns
            1. The frame (=image) number into the experiment
            2. The time in seconds since the experiment started
            3. The X (column) coordinate of the Centroid
            4. The Y (row) coordinate of the Centroid
            5. The X (column) coordinate of the head
            6. The Y (row) coordinate of the head
            7. The X (column) coordinate of the tail
            8. The Y (row) coordinate of the tail
            9. The X (column) coordinate of the midpoint
            10. The Y (row) coordinate of the midpoint
            11. The Y-min (row) coordinate of the bounding box (If
                missing see ‘bounding_boxes.npy below)
            12. The Y-max (row) coordinate of the bounding box (If
                missing see ‘bounding_boxes.npy below)
            13. The X-min (row) coordinate of the bounding box (If
                missing see ‘bounding_boxes.npy below)
            14. The X-max (row) coordinate of the bounding box (If
                missing see ‘bounding_boxes.npy below)
            15. The local threshold used to extract the binary image
                during tracking (Missing in older experiments)
            16. the presented stimulus

            In addition there are two more columns which are special to
            the ‘PiVR electrotaxis’ version:

            1. The ‘measured_voltage’ during the relevant frame. Usually
               empty as the voltmeter was left unplugged for experiments as
               it introduced another electrical connectivity between the anode
               and the cathode, potentially lowering the electric field.
            2. The ‘measured_generic_value’ are the readings of a
               Yocto-milliVolt-Rx in parallel to the electric circuit with
               a shunting resistor of 5.1 Ohm.
          • Background.tiff:
            1. Contains the reconstructed background image.
          • “*.csv”, for example ‘10Hz_90Vswitch.csv’ or ‘10Hz_pulse_protocol.csv’
            is the stimulus file PiVR used to present the electric field stimuli
            during that particular experiment.
          • “experiment_settings.json” is a json file and contains a
            lot of useful experimental information:
            1. Camera Shutter Speed [us]: Shutter speed in microseconds
            2. Exp. Group: The string that was entered by the user
               during the experiment
            3. Experiment Date and Time: exactly that
            4. Framerate: The frequency at which PiVR tracked the animal
            5. Model Organism: While tracking, PiVR used the parameters
               of this animal to optimize tracking. See here for how to
               modify this parameter.
            6. PiVR info (recording): version number, git branch and
               git hash of the PiVR software that was used to record the
               experiment.
            7. PiVR info (tracking): version number, git branch and
               git hash of the PiVR software that was used to track the
               experiment. If online tracking is being done, this is
               identical to the info above.
            8. Pixel per mm: For PiVR to be able to track the animal,
               it needs to know how many pixels indicate one mm. This has
               been set by the user as described here.
            9. Recording time: The time in seconds that PiVR was
               tracking the animal
            10. Resolution: The camera resolution in pixels that PiVR
                used while tracking.
            11. Time delay due to Animal Detection[s]: For the
                autodetection the animal must move. The time it took between
                pressing start and successful animal detection is saved
                here.
            12. Virtual Reality arena name: If no virtual arena was
                presented, it will say None
            13. backlight 2 channel: If Backlight 2 has been defined
                (as described here) the chosen GPIO (e.g. 18) and the
                maximal PWM frequency (e.g. 40000) is saved as a [list].
            14. backlight channel: If Backlight 1 has been defined
                the chosen GPIO (e.g. 18) and the maximal PWM frequency
                (e.g. 40000) is saved as a [list]. This would normally be
                defined as [18, 40000].
            15. output channel 1: If Channel 1 has been defined
                the chosen GPIO (e.g. 17) and the maximal PWM frequency
                (e.g. 40000) is saved as a [list].
            16. output channel 2: If Channel 2 has been defined
                the chosen GPIO (e.g. 27) and the maximal PWM frequency
                (e.g. 40000) is saved as a [list].
            17. output channel 3: If Channel 3 has been defined
                the chosen GPIO (e.g. 13) and the maximal PWM frequency
                (e.g. 40000) is saved as a [list].
            18. output channel 4: If Channel 4 has been defined
                the chosen GPIO (e.g. 13) and the maximal PWM frequency
                (e.g. 40000) is saved as a [list].
          • “first_frame_data.json” is a json file and contains information
            that collected during animal detection.
            1. bounding box col max: The X_max value of the bounding box
               of the animal detected in the first frame during animal detection.
            2. bounding box col min: The X_min value of the bounding box
               of the animal detected in the first frame during animal detection.
            3. bounding box row max: The Y_min value of the bounding box
               of the animal detected in the first frame during animal detection.
            4. bounding box row min: The Y_max value of the bounding box
               of the animal detected in the first frame during animal detection.
            5. centroid col: The X value of the centroid of the animal
               detected in the first frame during animal detection.
            6. centroid row: The Y value of the centroid of the animal
               detected in the first frame during animal detection.
            7. filled area: The filled area in pixels of the blob defined
               as the animal in the first frame during animal detection
          • “sm_raw.npy” is a numpy file containing the small image of
            the the tracked animal. This file comes in shape
            [“y size”, “x size”, # of frames] with “y size” == “x size”.
          • “sm_thresh.npy” is a numpy file containing the binarized
            small image of the the tracked animal. This file comes in shape
            [“y size”, “x size”, # of frames] with “y size” == “x size”.
          • “sm_skeletons.npy” is a numpy file containing the skeleton
            of the tracked animal. This file comes in shape
            [“y size”, “x size”, # of frames] with “y size” == “x size”.
          • “undistort_matrices.npz” contains the undistort files used
            to correct for lens distortion of the image by the opencv
            function cv2.undistortPoints. See
            https://pivr.readthedocs.io/en/latest/manual_software.html#undistort-options
            for more information.
          • “Overview of tracking.png” shows the trajectory of the
            animal using the coordinates saved in “DATE_TIME_data.csv”.
          • Some folders contain additional files. This is because instead
            of real-time tracking, a video was recorded and tracking was
            done post-hoc:
        • “IDENTIFIER_Video.h264” is the video that was recorded during
          the experiment.
  • Next, we look at the ‘static’ folder:
    • genotype (sometimes this is 2 folders deep, e.g. ‘Gr66a/MS193xMS581’
      as a number of controls with each genotype were run).
      • Individual experiments (e.g. 2023.02.06_14-59-54_MS478xMS478_pos90V)
        Each experimental folder contains a set of files which are the
        standard output of PiVR multianimal tracker output as explained here:
        https://pivr.readthedocs.io/en/latest/tools.html#multi-animal-tracking
        in addition to analysis files described here:
        • “DATE_TIME_stimulation.csv” was written by PiVR during the video recording:
          and contains the following columns:
          1. The frame (=image) number into the experiment
          2. The time in seconds since the experiment started. Note that due to a (now fixed)
             bug in the PiVR software, the time must be divided by 1000000 to get the time in
             seconds.
          3. The stimulus provided by Channel 1 (the only one relevant for the data here).
          4. The stimulus provided by Channel 2 (not used in this study)
          5. The stimulus provided by Channel 3 (not used in this study)
          6. The stimulus provided by Channel 4 (not used in this study)
          7. The ‘measured_voltage’ during the relevant frame. Usually
             empty as the voltmeter was left unplugged for experiments as
             it introduced another electrical connectivity between the anode
             and the cathode, potentially lowering the electric field.
          8. The ‘measured_generic_value’ are the readings of a
             Yocto-milliVolt-Rx in parallel to the electric circuit with
             a shunting resistor of 5.1 Ohm.
        • “Background.npy” is the mean image created during tracking.
        • ‘defined_mideline.json’ is created by script
          Behavior_analysis/multi_animal_assay/3_cathode_attraction_folders.py with
          user input.
        • “experiment_settings.json” is a json file and contains a
          lot of useful experimental information:
          1. Camera Shutter Speed [us]: Shutter speed in microseconds
          2. Exp. Group: The string that was entered by the user
             during the experiment
          3. Experiment Date and Time: exactly that
          4. Framerate: The frequency at which PiVR tracked the animal
          5. Model Organism: While tracking, PiVR used the parameters
             of this animal to optimize tracking. See here for how to
             modify this parameter.
          6. PiVR info (recording): version number, git branch and
             git hash of the PiVR software that was used to record the
             experiment.
          7. PiVR info (tracking): version number, git branch and
             git hash of the PiVR software that was used to track the
             experiment. If online tracking is being done, this is
             identical to the info above.
          8. Pixel per mm: For PiVR to be able to track the animal,
             it needs to know how many pixels indicate one mm. This has
             been set by the user as described here.
          9. Recording time: The time in seconds that PiVR was
             tracking the animal
          10. Resolution: The camera resolution in pixels that PiVR
              used while tracking.
          11. backlight 2 channel: If Backlight 2 has been defined
              (as described here) the chosen GPIO (e.g. 18) and the
              maximal PWM frequency (e.g. 40000) is saved as a [list].
          12. backlight channel: If Backlight 1 has been defined
              the chosen GPIO (e.g. 18) and the maximal PWM frequency
              (e.g. 40000) is saved as a [list]. This would normally be
              defined as [18, 40000].
              13. output channel 1: If Channel 1 has been defined
              the chosen GPIO (e.g. 17) and the maximal PWM frequency
              (e.g. 40000) is saved as a [list].
          13. output channel 2: If Channel 2 has been defined
              the chosen GPIO (e.g. 27) and the maximal PWM frequency
              (e.g. 40000) is saved as a [list].
          14. output channel 3: If Channel 3 has been defined
              the chosen GPIO (e.g. 13) and the maximal PWM frequency
              (e.g. 40000) is saved as a [list].
          15. output channel 4: If Channel 4 has been defined
              the chosen GPIO (e.g. 13) and the maximal PWM frequency
              (e.g. 40000) is saved as a [list].
      • “stimulation_used.csv” was the stimulus file used to present the e-field stimulus
        during the video recording.
      • “Video.h264” is created during the video recording.
      • “Video_undistorted.avi” is the undistorted version of the “Video.h264”
        done by PiVR (https://pivr.readthedocs.io/en/latest/tools.html#undistort-video)
        which was used for further analysis.
      • “XY_postion.csv” are the x/y positions of larvae as tracked by the PiVR
        Multi Animal Tracker.
      • “interpolated_XY_position.csv” is calculated in script
        Behavior_analysis/multi_animal_assay/2.5_handling_missing_animals.py
        which takes care of “lost animals”. These are used to calculate the FractionOnCathodeSide.npy
        below
      • “FractionOnCathodeSide.npy” is calculated in script
        Behavior_analysis/multi_animal_assay/3_cathode_attraction_folders.py
        and contains the fraction of animals on the cathode side over time.

The structure of the ‘Ca_imaging_data’ folder is as follows:

• genotype + stimulus (e.g. Gr66a_5V_step or NP2728_15s_5V)
  • individiual experiments (e.g. 20221220_17-00-31_1V_2s_step) which
    contains the imaging data, the stimulus information and analysis.
    • The “*.tiff” file is the imaging file (x,y,t) containing the raw imaging data
      collected at the microscope.
    • The “*_AI_measurements.npy” were created during recording by the
      “calcium_imaging/hyperscope_GUI.py” script. It contains the measured voltage provided
      during the experiment.
    • “signal_ROI.npy” contains coordinates of the user defined ROI created with
      “calcium_imaging/calc_dF_F.py” script.
    • “DATE_TIME_delta_F_over_F_ROIX.csv” is the output of the “calcium_imaging/calc_dF_F.py”
      script. It contains the following columns:
      1. “Time [s]” indicates time in the experiment per second.
      2. “Stimulation AO1 [V]” is the measured voltage on AI1 (anterior <-> posterior e-field).
      3. “Stimulation AO3 [V]” is the measured voltage on AI3 (lateral e-field).
      4. “dF/F no 1” is the dF/F of the ROI indicated in the filename.
    • “DATE_TIME__stepdF_over_F.png” is a visualization of the data
      “DATE_TIME_delta_F_over_F_ROIX.csv”.

The structure of the “simulations” folder:

• e_fields_PB
  • “*V_axial_E_field.txt” contains COMSOL simulation. The first row
    is the position in meters, the second the electric field strength in V/m.
    See name for simulation parameters (e.g. 8mm agarose height, 90V applied voltage
    difference.)
• PB_measurements_and_simulations
  • “Electrotaxis_agarose_gel_and_PB_conductivities_hot_cool_100uM_to_40mM_data.txt”
    contains conductivity measurements for hot and cool PB, Agarose made with PB and
    theoretical conducitivty measurements.
  • “Gel_electrophoresis_estimated_Temp_rise_vs_PB_concentration_mM.txt” first column
    contains PB concentration (in mM) and second columns contains
    estimated temperature rise (see Methods).
  • “Gel_electrophoresis_Normalized_E_field(V per m)_vs_PB_concentration_mM.txt”, first
    column contains PB concentration (in mM), second contains normalize e-field above the
    agarose (see Methods).

The structure of the “IHC” folder is as follows:

• Figure 4A
  • Raw image files “.lif” and adjusted image shown in figure as “.jpg”. These images show NP2729-Gal4, tsh-Gal80 expression pattern in the anterior part of the animal.
• Figure 5A
  • Raw image files “.tif” and adjusted image shown in figure as “.jpg”. These images show Gr66a-Gal4 and Gr33a-Gal4 expression pattern in the anterior part of the animal.
• Figure S6A
  • Raw image files “.tif” and adjusted image shown in figure as “.jpg”. These images show NP2729-Gal4 expression pattern in the brain.
• Figure S6B
  • Raw image files “.tif” and adjusted image shown in figure as “.jpg”. These images show NP2729-Gal4, tsh-Gal80 expression pattern in the brain.
• Figure S7D
  • Raw image files “.tif” and adjusted image shown in figure as “.jpg”. These images show Gr66a-Gal4 expression pattern in the anterior part of the animal.
• Figure S7E
  • Raw image files “.tif” and adjusted image shown in figure as “.jpg”. These images show Gr66a-lexA expression pattern in the anterior part of the animal.
• Figure S7F
  • Raw image files “.tif” and adjusted image shown in figure as “.jpg”. These images show Gr66a-lexA and Gr66a-Gal4 expression pattern in the anterior part of the animal.
• Figure S7G
  • Raw image files “.tif” and adjusted image shown in figure as “.jpg”. These images show Gr66a-lexA and Gr33a-Gal4 expression pattern in the anterior part of the animal.
• Figure S7H
  • Raw image files “.tif” and adjusted image shown in figure as “.jpg”. These images show Gr66a-lexA and NP2729-Gal4, tsh-Gal80 expression pattern in the anterior part of the animal.