GCaMP-tdt_Analysis

Code for analyzing baseline activity by normalizing GCaMP fluorescence to tdtomato signal.

Preparing your images

Samples were nervous systems expressing GAL4>opGCaMP6s,tdttomato. All samples were dissected quickly in Drosophila saline, then mounted in a petri dish with ~ 4 ml of the same saline. Images were acquired on a Zeiss LSM 710 micrscope in the Cellular Imaging Core at BCH using a Mai Tai 2-photon laser and a W Plan-Apochromat 20x/1.0 DIC VIS (IR) M27 75 mm objective. The laser was set to 960 nm such that both GCaMP and tdtomato would be excited by the laser and their fluorescence could be captured in a single image. Within the Zen black software the following settings were used:

• 512 x 512 pixels
• speed = 7
• avg = 1
• 8 bit
• zoom = 1.0* but this can be easily changed depending on your sample
• slices were 3 um thick and enough slices were taken to cover the entire region of interest, as seen via the tdtomato channel
• laser = 960 nm
• laser power = 12.0
• gain (for both green and red channels) = 750

Blinding images with the batchblind2.m script

This script automatically blinds the LSM files. This step can be omitted if you do not want to blind your results.

To use this script:

• Save all your images for an experiement in a single folder with no other images.
• Run the script.
• Select the folder containing those images.
• This script will create a new folder within the original that contains the blinded images.
• It will also save the key as key.mat file.
• To unblind the images, load the key.mat file in matlab. Open the key cell found in the workspace.

Converting LSM files to Tiffs with the PrepforGCaMPtdt_.jim macro

This macro takes a z-stack saved as an LSM file, computes the max intensity projection of the stack for both channels, then saves results for each channel separately as two tiffs.

To install the macro as a plugin in Fiji:

• Save the macro in your Fiji>Fiji.app>plugins>macros folder.
• Restart Fiji
• It should appear in the Plugins>macros dropdown menu

Using the macro

• Run the macro.
• It will first ask you to choose the source directory - select the folder containing the blinded images.
• It will then ask you to choose the output directory - select the folder where you want the prepared images to save.
• Channel 1 is assumed to be green/GCaMP while channel 2 is assumed to be red/tdtomato and the tiffs will be saved as name_green.tiff and name_red.tiff, respectively.
• When the macro is done you should see 2x the images in the output directory.

Use BatchNormalizedIntensity.m to obtain normalized intensity

This code will prompt you to select the folder containing the blinded tiffs. It will then pull up each image twice: the first time you select the ROI, the second time you select the background. It performs a background subtraction on both channels then divides to get the normalized intensity. All information is stored in the myData.mat file, the last column of which is the normalized intensity.