Parasite coat

Tools to analyze the fluorescence recovery of parasite coat protein from 3D timelapse microscopy image sequences.

Content

• ParasiteCoatRecovery.ijm : an ImageJ macro segmenting the parasite and measuring the fluorescence recovery. It also includes the estimation of the model.
• Analyze Results.ipynb : a jupyter notebook for analyzing the output of the macro.
• data: folder with example data

System requirements

The analysis of the data requires the installation of two components and should take less than 15min.

• For running the analysis macro please install:
  • Fiji (https://fiji.sc/) v1.54f
  • MorpholibJ (https://github.com/ijpb/MorphoLibJ) can be installed by activating the IJPB-plugins update site.
  • Download the macro and open it in Fiji.
• Dependencies for running the notebook can be installed using for example on macOS, Linux, or Git Bash on Window: bash # install micromamba "${SHELL}" <(curl -L micro.mamba.pm/install.sh) # reload the shell ${SHELL} # create an environment micromamba -qy create -f environment.yml # activate the environment micromamba activate parasite-coat # start the notebook jupyter lab "Analyze Results.csv"

Installation

Download the code and example data or clone the repository.

Demo

Sample images are included in this repository.

1. Open the file ParasiteCoatRecovery.ijm in Fiji and press run. Select the csv file as input and press OK (~15 second per image). This will produce for each input file:
   • *-mask.tif
   • *-profile.csv
2. The open the notebook and run all the cells (~ a minute to run). This will produce figures as pdf files:
   • heatmap.pdf
   • histogram of recovery times.pdf
   • intensity for all parasite.pdf
   • intensity parasite 1.pdf
   • intensity parasite 2.pdf

Instruction for use

1. Parasite need to be selected in the original image sequence, cropped and saved as individual TIFF files with pixel calibration and time interval present in the metadata (Image>Properties menu in ImageJ).
2. A list of the images is saved in a csv file with the following information: |Filename| Start time [min]| First frame| |--------|-----------------|------------| | .tif | 30 | 10 |
3. Open the macro in Fiji and press run, select the csv file as input and press run. The macro generates a profile.csv file for each image, a summary.csv file for the dataset and a config.yml file.
4. Open the notebook and set the config file to the config.yml file generated by the macro.