Apoptosis Quantification in Tissue: Development of a Semi-Automatic Protocol and Assessment of Critical Steps of Image Processing

Biomolecules. 2021 Oct 15;11(10):1523. doi: 10.3390/biom11101523.

Abstract

Apoptosis is associated with numerous phenotypical characteristics, and is thus studied with many tools. In this study, we compared two broadly used apoptotic assays: TUNEL and staining with an antibody targeting the activated form of an effector caspase. To compare them, we developed a protocol based on commonly used tools such as image filtering, z-projection, and thresholding. Even though it is commonly used in image-processing protocols, thresholding remains a recurring problem. Here, we analyzed the impact of processing parameters and readout choice on the accuracy of apoptotic signal quantification. Our results show that TUNEL is quite robust, even if image processing parameters may not always allow to detect subtle differences of the apoptotic rate. On the contrary, images from anti-cleaved caspase staining are more sensitive to handle and necessitate being processed more carefully. We then developed an open-source Fiji macro automatizing most steps of the image processing and quantification protocol. It is noteworthy that the field of application of this macro is wider than apoptosis and it can be used to treat and quantify other kind of images.

Keywords: Drosophila; TUNEL; apoptosis; caspase; image processing; signal quantification; thresholding.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Apoptosis / genetics*
  • Caspases, Effector / chemistry
  • Caspases, Effector / genetics*
  • Humans
  • Image Processing, Computer-Assisted*
  • In Situ Nick-End Labeling / methods*
  • Tissue Distribution / genetics

Substances

  • Caspases, Effector