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

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

Wavefront sensing for three-component three-dimensional flow velocimetry in microfluidics

We present the application of wavefront sensing to three-component, three-dimensional micro particle tracking velocimetry (lPTV). The technique is based upon examining the defocus of the wavefront scattered by a tracer particle and from such information establishing the 3-D tracer location. The imaging system incorporates a cylindrical lens acting as an anamorphic element that creates different magnifications in the two orthogonal axes. A single anamorphic image is obtained from each tracer, which contains sufficient information to reconstruct the wavefront defocus and uniquely identify the tracer’s axial position. A mathematical model of the optical system is developed and shows that the lateral and depth performance of the sensor can be largely independently varied across a wide range. Hence, 3-D image resolution can be achieved from a single viewpoint, using simple and inexpensive optics and applied to a wide variety of microfluidic or biological systems. Our initial results show that an uncertainty in depth of 0.18 µm was achieved over a 20 µm range. The technique was employed to measure the 3-D velocity field of micron-sized fluorescent tracers in a flow within a micro channel, and an uncertainty of 2.8 µm was obtained in the axial direction over a range of 500 µm. The experimental results were in agreement with the expected fluid flow when compared to the corresponding CFD model. Thus, wavefront sensing proved to be an effective approach to obtain quantitative measurements of three component three-dimensional flows in microfluidic devices