DeadEasy Mito-Glia: Automatic Counting of Mitotic Cells and Glial Cells in Drosophila

Abstract

Cell number changes during normal development, and in disease (e.g., neurodegeneration, cancer). Many genes affect cell number, thus functional genetic analysis frequently requires analysis of cell number alterations upon loss of function mutations or in gain of function experiments. Drosophila is a most powerful model organism to investigate the function of genes involved in development or disease in vivo. Image processing and pattern recognition techniques can be used to extract information from microscopy images to quantify automatically distinct cellular features, but these methods are still not very extended in this model organism. Thus cellular quantification is often carried out manually, which is laborious, tedious, error prone or humanly unfeasible. Here, we present DeadEasy Mito-Glia, an image processing method to count automatically the number of mitotic cells labelled with anti-phospho-histone H3 and of glial cells labelled with anti-Repo in Drosophila embryos. This programme belongs to the DeadEasy suite of which we have previously developed versions to count apoptotic cells and neuronal nuclei. Having separate programmes is paramount for accuracy. DeadEasy Mito-Glia is very easy to use, fast, objective and very accurate when counting dividing cells and glial cells labelled with a nuclear marker. Although this method has been validated for Drosophila embryos, we provide an interactive window for biologists to easily extend its application to other nuclear markers and other sample types. DeadEasy MitoGlia is freely available as an ImageJ plug-in, it increases the repertoire of tools for in vivo genetic analysis, and it will be of interest to a broad community of developmental, cancer and neuro-biologists.

A novel role for the 3′-5′ exoribonuclease Dis3L2 in controlling cell proliferation and tissue growth

“…The number of nuclei undergoing mitosis were counted using the ImageJ plugin DeadEasy MitoGlia 39 . All discs were stained with anti-Phosphohistone H3 as above under the same conditions.…”

Automatic cell counting in vivo in the larval nervous system of Drosophila

“…Our method differs from and surpasses our previously developed method DeadEasy MitoGlia, which could also identify Repo‐labelled cells, although only in the Drosophila embryo (Forero et al , 2010a). DeadEasy MitoGlia used a global threshold to binarize each image, which produced good results in embryos, in which signal intensity was very high and there was little fluorescence attenuation through the stack.…”

“…We have tested in larvae and adult brains our programmes developed for embryos, and they do not perform accurately. In particular, DeadEasy MitoGlia (Forero et al , 2010a), which was developed to count cells labelled with Repo or p‐Histone‐H3, is not robust in post‐embryonic tissues. DeadEasy MitoGlia employs a global threshold to binarize each image, which produced good results in embryos given high signal intensity and low attenuation through the stack.…”

Image Processing Methods for Automatic Cell Counting In Vivo or In Situ Using 3D Confocal Microscopy

“…These filters in general reduce the noise and the significant intensity heterogeneity typical of confocal images, without strongly affecting the signal provided by the stained cells. The median filter is one of the simplest methods and we found it provides good results (Forero et al, 2009(Forero et al, , 2010a. Many other median filter variations can also be employed, although they can require a more exhaustive and time-consuming calculation, and some parameters to be fixed (Mitra, 2001;Forero & Delgado, 2003).…”

“…Cell Profiler (Carpenter, 2006) enables combinations of image-processing methods that can be used to count cells, but it is not very user friendly for most biologists as it requires computation expertise. We have developed a range of publicly available methods that can count the number of dividing or dying cells, neurons or glia, in intact specimens of fruit-fly Drosophila embryos (Forero et al, 2009(Forero et al, , 2010a. Quantification is automatic, accurate, objective and fast, enabling reliable comparisons of multiple specimens of diverse genotypes.…”