jonasoh / auttoflux

Pipeline for high-throughput analysis of RFP/GFP ratios in vacuoles

Tandem tag assay

The Tandem Tag (TT) assay is a widespread approach for quantifying autophagic activity in living cells. Here, we provide a semi-automated high-throughput TT assay optimized for measuring autophagic activity in Arabidopsis thaliana roots, and designated ImageJ macros and R scripts that facilitate analysis.

The detailed protocol for the TT assay can be found here.

This assay was developed for the study published in Dauphinee et al., 2019.

The assay includes high-throughput analysis of confocal laser scanning microscopy (CLSM) micrographs using the designated AuTToFlux pipeline. The pipeline consists of the following steps:

1. Image processing using ImageJ macro:

• convert images from different microscopy manufacturers into a common format (ImageProcessor.ijm).
• if needed, fine tune the tresholding parameters to best match the image quality (CalibrateThreshold.ijm).
• identify the vacuoles and calculate the fluorescence intensity ratios for the reporter proteins (FluorescenceIntensity.ijm).

2. Analyzing the obtained quantitative data using R scripts for different types of comparisons, and generating statistics:

• autophagic activity as a function of time (Flux-vs-Time.R).
• comparison of autophagic activity in control vs reporter lines (Control-vs-Reporter.R).

Here you can find demo files and also instruction videos to test the assay prior to performing analysis of your own data.

• ImageProcessor.ijm can be tested on both folders with demo files, while following instructions provided in the video 2.
• CalibrateThreshold.ijm can be tested on files in the Flux-vs-Time_demoFile folder. Please note that you will need to process the folder with ImageProcessor.ijm first. The three images used for treshold calibration in video 3 were:
  • Reporter_0.5uM.AZD_seedling1_image1
  • Reporter_Vehicle_seedling8_image3
  • Reporter_Vehicle_seedling9_image1
• FluorescenceIntensity.ijm can be tested on both folders with demo files following the instructions in video 4. Please note that you will need to process folders with ImageProcessor.ijm first.
• Flux-vs-Time.R can be tested using the Flux-vs-Time_demoFile folder, containing the micrographs utilized in video 5. The folder includes confocal micrographs of TT reporter line seedlings exposed to 0.5µM AZD or a Vehicle (1% DMSO) treatment. Treatments were applied at 2018-03-20 9:00 and seedlings were scanned at three timepoints.
• Flux-vs-Control.R can be tested using Control-vs-Reporter_demoFile folder as demonstrated in the video 6. The folder includes micrographs of TT Reporter and Control line seedlings treated with either 0.5 µM AZD or a Vehicle (1% DMSO).

Figure 1. TT assay workflow diagram

auttoflux's Issues

GFP-> mWasabi

Oy Jonas,

Could you please rename the GFP stuff in the FluorescenceIntensity macro

in the line 49:
// save the gfp channel and close the others -> // save the green channel and close the others

in the line 53:

saveAs("Tiff", name + ".gfp.tif"); -> saveAs("Tiff", name + ".mWasabi.tif");

tack!

A

number of rows in the CalibrateTreshold

Oy Jonas,

I've just checked how to get rid of the extra empty rows on the Montage result

The quick fix is to change the Line 71:
run("Make Montage...", "columns=14 scale=0.25 border=10 label");

to:
run("Make Montage...", "columns=14 rows=3 scale=0.25 border=10 label");

This would work if users processes 3 images, as we suggest.

A more jobbigt but elegant fix would be to count the number of images in the folder opened for threshold processing and then set this as the number of the rows in the Line 71. This would be more mmm...foolproof

could you please take a look when you have time?

tack!

a.