Project Development P3 (2013)

Improving throughput

Fluorescence microscopy provides an ideal tool to study complex biological processes with high spatiotemporal resolution. The microscope does however need human support to select the cells to be studied, a bottle neck that has hampered automation procedures. The open source software, Micropilot, (WP3) developed at EMBL at the beginning of the project, pro­vides a machine learning-based module to control microscope tasks that is continually updated with new functionalities to enrich its implementation in different areas. An important core resource for microscopy and high-throughput screening was the generation of a collection of more than 100 human tissue culture cell lines that stably express combinations of different fluorescent markers for plasma membrane, cytoskeleton elements, endomembrane systems, nuclear envelope etc. as well as biosensors to probe for enzymatic activities. The work on high-throughput screening platform development continued with the development of an automated fluid delivery system that utilizes microfluidic imaging chambers for high-throughput correlated and multimodal microscopy. New automated workflow for FCS/FCCS acquisition and analysis was established on two microscopes to increase throughput. Also during this third period, the CSMA method (cell spot microarray) for production of high density siRNA transfection microarrays started the development of a new microarray format using acoustic nano-dispersing technology for siRNA transfection reagent, varied microenvironments and cell transfer to improve efficiency and cost-effectiveness.

Maximizing content

Available high-throughput image analysis software offer efficient algorithms for analysis of single time-point assays while the existing tools for the analysis of cellular dynamics in multi-dimensional large-scale imaging are very limited. To enable systems biology analyses of the cell division and cell migration, the network started to develop image analysis tools (WP4) aimed at increasing the data content that can be extracted in parallel through microscopy. The computational software’s further developed during this third year are for example the CellCognition software - an analysis module designed to combine object detection and supervised machine learning for classification of morphologies with time-resolved analysis by single-cell tracking was extended additional learning module for semi-supervised learning. The open source standard format CellH5 for high content screening data has been developed to integrate multiple software packages into a unified workflow. Software interfaces have been developed for the widely used programming languages “R” and “Python”. The WiSoft image analysis software that includes tools for processing, visualization and statistical evaluation of time-lapse movies has been further developed during the third year with a special tool build into the software that supports integration of new analysis and statistical modules into the platform. The custom developed image analysis software PAD was extended with a Matlab based software platform that automatically combines metadata information with pixel data information and enables retrieval of multiple scales of information that can be further combined into datasets for multiscale statistical analysis.

Data processing, modeling and query

The large, multi-dimensional image-based data sets that are generated from systems microscopy studies pose high demands on the tools used for statistical analysis. Network members have continued to improve software (WP5) that performs primary statistical analysis of complex data along with quality assessment and significance analysis.

Thus, we have continued the development and refinement of three key R/Bioconductor packages: cellTHS2, for versatile data and metadata management, normalization, quality control, EBImage for image analysis and quantitative feature extraction within the R statistical environment and imageHTS for the analysis of many-dimensional quantitative descriptors from microscopy images in high-throughput cell-based assays. In addition, several other statistical tools were developed for analysis of cell dynamics, cell migration and cell polarity. We have publically released tutorial documents with case studies demonstrating best practices for statistical data analysis and image processing of systems microscopy experiments.

A tremendous amount of information exist in the literature, in bioinformatics databases and in published experimental datasets on the function of gene products in cell division and migration. To optimally leverage this knowledge for experiments done within the consortium and beyond, we created (during P1 and P2) a Knowledge Base (KB) of gene-oriented data relevant to mitosis and cell migration” named “Micycle”. To this end, two Knowledge Bases (KBs) about Cell Cycle (CC) and Cellular Migration (CM), both of them classified by the dominant ontology Gene Ontology (GO), were created and in addition to the GO ontology other ontological resources were included in the KBs, such as: Cell Cycle Ontology (CCO), Cell Phenotype Ontology (CPO) and Cell Migration Consortium (CMC). Based on this former work we have developed a web tool, which has been added to the extanded Micycle web-page, for modelling specific human sub-interactomes for any list of genes required by the user, based on experimental and predicted protein-protein interaction (PPIs) networks. This new web resource is now available through the KBs web-page to all the partners in the consortium (

Data derived from a number of different experimental set-ups have been used to commence bold modeling projects that will ultimately serve to describe the dynamic processes of cell migration and division. Close collaboration between experimental and modeling partners, which are actively exchanging modelling methodology and know-how, has generated extremely promising results (WP6). We have achieved significant results in the work focusing on modelling drug–domain networks to explore the role of protein domains as drug targets and to explain drug polypharmacology in terms of the interactions between drugs and protein domains. Important refinements and conceptual progress have been made for population-level and cell-level modelling with several papers exemplifying our conceptual approach.

Standardization measures

Systems biology aims to produce comprehensive models of biological systems, requiring integration of multiple experimental techniques, analytical methods and modeling approaches. A central task for this NoE is therefore the development of standards that enable exchange, interoperability and integration of data from different laboratories (WP8). Through the third year, we have maintained the rhdf5 package that provides interface between the R/Bioconductor software tools and the HDF5 file format.

Database Development

A prototype database for systems microscopy data has been developed within the framework of WP9 to facilitate standardization efforts toward a common platform for data sharing. The prototype database “Cellular Phenotype Database” (CPD) for systems microscopy data has been launched during the third year and its running on a production server CPD is a gene-centered, non-relational database and contains data from two model organism, Homo sapiens and Drosophila Melanogaster. All phenotypes associated with the datasets loaded in CPD have been mapped to the Cellular Microscopy Phenotype Ontology ( and the mappings are in the CPD production instance.

The biological systems

The characteristics of cancer biology and its clinical consequences render a strong case for studying cell division and migration at the systems level. Cell division and cell migration are dynamic processes, in which the dramatic spatiotemporal dynamics of cells, sub-cellular machineries and molecules dictates the outcome. The molecular complexity of these biological processes and their deregulation in cancer cells need to be addressed by powerful imaging tools and combined with systems-scale perturbation experiments. The study of cell division and cell migration form the basis for the activities in WP1 and WP2 respectively.

In the first and second project period the work on WP1 and WP2 focused on establishing, improving and tuning the tools for the quantitative analysis of cell division and cell migration as well as starting the RNAi screens for mitosis and cell migration. During the third project period, the tertiary RNAi screen to validate regulators of mitotic chromosome condensation has been completed and genes involved in collective migration were identified and validated. To model and predict function of mitotic genes, a new method was developed for systematically detecting directionality of genetic interaction of RNAi perturbations in cycling cells. Furthermore, we developed a fully automated 3D localization algorithm to enable testing of model predictions by systematic localization measurements and we further developed fluorescence cross-correlation spectroscopy method to enable testing of model predictions by systematic interaction measurements. We have also mapped down the effects of knockdown of specific genes on metastasis and initiated the work on the impact of tissue stiffness on breast cancer malignancy.

The consortium is also dedicated to leverage the powerful systems microscopy tools developed within the project in specific translational applications, such as exploration and diagnosis of the dependency of cancer on specific targets, or reactivity towards specific drugs (WP7). The translational bioinformatic analysis pipeline, developed during the second period has been applied during the third project period for the analysis and validation of top mitotic and migratory genes. To enable the image and data sharing in the network, we have also established a pipeline for displaying and sharing cell microarray/plate based screen images to collaborators (Webmicroscope,

Training the next generation

The network was pleased to welcome a high number of junior participants to its second Annual Consortium meeting, many of them presenting their work either by giving an oral presentation or presenting a poster. During the third project period, the three courses supported by the NoE were organized and attended by both NoE external and NoE associated participants, thus providing training opportunities in systems microscopy methodology. In training the next generation of scientists, both events contributed to the durability objective of the training work package (WP10).  A large number of postdocs and students have further been enrolled within the NoE and started their training by research, which constitutes the main training method applied in this NoE.


Structures for internal as well as external communication (WP11) that have been set up during P1 were followed up during second and third period: the project website (both internal and external) was updated continuously, a brochure (reaching both the scientific community as well as the general public) was produced, the partners were disseminating the project extensively at conferences, meetings, public lectures, by publications and other means (TV interviews). In addition, the management office actively disseminated the consortium at several conferences and workshops.

Seventh Framework Programme

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