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

DeadEasy Caspase: Automatic Counting of Apoptotic Cells in Drosophila

Development, cancer, neurodegenerative and demyelinating diseases, injury, and stem cell manipulations are characterised by alterations in cell number. Research into development, disease, and the effects of drugs require cell number counts. These are generally indirect estimates, because counting cells in an animal or organ is paradoxically difficult, as well as being tedious and unmanageable. Drosophila is a powerful model organism used to investigate the genetic bases of development and disease. There are Drosophila models for multiple neurodegenerative diseases, characterised by an increase in cell death. However, a fast, reliable, and accurate way to count the number of dying cells in vivo is not available. Here, we present a method based on image filtering and mathematical morphology techniques, to count automatically the number of dying cells in intact fruit-fly embryos. We call the resulting programme DeadEasy Caspase. It has been validated for Drosophila and we present examples of its power to address biological questions. Quantification is automatic, accurate, objective, and very fast. DeadEasy Caspase will be freely available as an ImageJ plug-in, and it can be modified for use in other sample types. It is of interest to the Drosophila and wider biomedical communities. DeadEasy Caspase is a powerful tool for the analysis of cell survival and cell death in development and in disease, such as neurodegenerative diseases and ageing. Combined with the power of Drosophila genetics, DeadEasy expands the tools that enable the use of Drosophila to analyse gene function, model disease and test drugs in the intact nervous system and whole animal.This work was funded by Wellcome Trust Equipment Grant 073228 and EMBO YIP to AH, and by BBSRC and MRC studentships to JAP and ARL.Peer reviewe

Role of DaPKC in the organization of the Follicular Epithelium of the Drosophila egg chamber

Resumen del póster presentado al 52nd Annual Drosophila Research Conference, celebrado en San Diego, California (US) del 30 de marzo al 3 de abril de 2011.Disruption of apico-basal cell polarity induces changes in cell fate, differentiation, proliferation and migration. The follicular epithelium of the Drosophila egg chamber is a very good system to address whether and how disruption of the proper function of different polarity determinants may lead to misregulation of different signalling pathways, and whether these alterations are the basis of the aberrant modifications of tissue growth and organization associated to the polarity mutants. To tackle these questions, we have focused in investigating the role of the apical determinant DaPKC, using the follicular epithelium as a model system. Our data suggest that DaPKC plays a key role in organizing epithelial structure, not only by regulation of general cell architecture features, but also through the modulation of different signalling pathways. Loss of function as well as gain of function analyses of DaPKC suggest that this kinase is required for regulation of endocytic processes in the follicular epithelium and hence, for the proper function of key signalling pathways such as Notch.Peer Reviewe

Implicacion de la vía de Hippo en el sobrecrecimiento de los epitelios de Drosophila melanogaster asociado a la desregulación de los niveles de DaPKC

Resumen del póster presentado al XXXVI Congreso de la Sociedad Española de Bioquímica y Biología Molecular celebrado en Madrid del 3 al 6 de septiembre de 2013.El establecimiento y mantenimiento de la polaridad celular ápico-basal depende de la distribución asimétrica de moléculas, orgánulos celulares y componentes del citoesqueleto. Las células epiteliales de Drosophila y vertebrados comparten, a pesar de sus diferencias estructurales, la mayoría de las proteínas implicadas en la regulación de la polaridad. Entre ellas se encuentra la proteína quinasa DaPKC, perteneciente al complejo apical Par3/Bazooka, la cual fosforila a diversos determinantes de polaridad. Así, nuestro grupo ha demostrado fosforilación de Crumbs por DaPKC. La sobreexpresión de una forma dirigida a la membrana, constitutivamente activa de DaPKC (DaPKCCAAX), durante el desarrollo larvario causa sobrecrecimientos en los discos imaginales. Este sobrecrecimiento depende de la función quinasa de DaPKC ya que la sobreexpresión conjunta de DaPKCCAAXy una isoforma de DaPKCCAAX sin actividad quinasa, que funciona como dominante negativo, rescata el fenotipo mutante. Durante la última década se ha avanzado mucho en la comprensión de la vía de Hippo que controla el crecimiento de los órganos controlando proliferación y muerte celular, y cuyo funcionamiento está en parte regulado por la polaridad ápico-basal en las células epiteliales. Nos preguntamos si el sobrecrecimiento asociado a la sobreexpresión de DaPKCCAAXpodría estar mediado a través de la vía de Hippo. Para investigarlo, estamos analizando si la expresión de genes diana de la vía de Hippo se encuentra alterada al sobreexpresar DaPKCCAAX, estamos llevando a cabo experimentos de interacción génica entreDaPKC y componentes de la vía de Hippo y experimentos bioquímicos para determinar si DaPKC fosforila a alguna proteína de la vía de Hippo.Peer Reviewe

Image processing algorithm.

<p>Digrammatic representation of the different image processing steps.</p

Validation of DeadEasy MitoGlia in identifying mitotic and glia cells.

<p>Validation of DeadEasy MitoGlia in identifying mitotic and glia cells.</p

Examples of applications of DeadEasy MitoGlia to address biological questions.

<p>(A) Automatic quantification of mitotic pH3 positive cells in vivo in wild-type and <i>pros^J013</i> null mutants, showing that proliferation increases in the mutants throughout embryogenesis. (B) Automatic quantification of Repo positive glia in wild-type and <i>cycE^AR95</i> mutant embryos, showing a decrease in glial number when cell division is compromised. Only a subset of dorsal glia are counted here. Numbers within bars indicate sample sizes. Error bars are s.e.m.</p

Image processing steps.

<p>(A) Images showing the image processing steps starting from the raw image and finishing in the result, which corresponds to the identified objects (cells). (B) Histogram of a typical pH3 stained image. (C) Higher magnification examples to show, as in (A), the different processing steps. This example shows the power of the programme to separate cells that in some slices may appear to be joined. (D) Example of a faintly stained sample that DeadEasy MitoGlia cannot process and must be discarded.</p

Cell division and glia in the embryonic VNC.

<p>(A) Diagram showing an embryo (left) and a cross-section view of the ventral nerve cord (VNC, right). The red box indicates an example of a region of interest (ROI) comprising the VNC and excluding the epidermis; any ROI of choice can be used. (B) Characteristic embryonic VNCs labelled with the mitotic marker pH3 and the glial marker Repo. (C) Higher magnification views of details from specimens in (B) to show the properties of the images. (D) Interactive window to enable users to change the parameters to apply the programme to other markers or sample types.</p

Parameters than can be modified and effects on performance.

<p>Parameters than can be modified and effects on performance.</p