Project development P2 (2012)

Improving throughput

Modern microscopy allows for the imaging of live cells for long periods of time. The microscope does however need human assistance to select the cells to be studied, a bottle neck that has hampered automation procedures. Micropilot, (WP3) is an open source software available at EMBL, that pro­vides a machine learning-based module to control microscope tasks released to network members already during the projects first period. During this second year the software encountered further functionalities that were implemented in different areas. For example, the new functionalities of Micropilot have been implemented to remote control a picoquant fluorescence correlation spectroscopy system on a Leica SP5 confocal microscope. Several tests in robustness and throughoutput showed high feasibility of the combined automated acquisition and processing/evaluation approach, yielding large amounts of data in a reproducibly unbiased way. Also during this second period, the CSMA method (cell spot microarray) for production of high density siRNA transfection microarrays was optimized for the analyses of genes affecting the malignant cell behavior in various breast and prostate cancer cell lines.

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. As a first step in this direction, a “Software requirements specification for image analysis platform” was put together already during the first period as a solid guideline for joint analysis platform.  The computational software’s developed (or improved) during this second year are: 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 with novel methods for unsupervised learning. The previously published image analysis pipeline based on R/Bioconductor package was adapted to a number of different biological systems. The WiSoft image analysis software that includes tools for processing, visualization and statistical evaluation of time-lapse movies was released to the consortium during this period with several improved features. The consortium also made serious progress in the integration of different software into common platform, thus CellH5, a universal platform-independent data format for high-content microscopy, has been specified and implemented into the CellCognition framework. The R.HDF5`s package also developed by members of our consortium provides the interface between HDF5 and R and is suited for the exchange of large and/or complex datasets between R and other software package, and for letting R applications work on datasets that are larger than the available RAM.

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 of three key R/Bioconductor packages:

(i) cellTHS2 for versatile data and metadata management, normalization, quality control and summarization of data from large genetic or compound screens,

(ii) EBImage for image analysis and quantitative feature extraction within the R statistical environment

(iii) imageHTS for the analysis of many-dimensional quantitative descriptors from microscopy images in high-throughput cell-based assays (

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 a Knowledge base of gene-oriented data relevant to mitosis and cell migration”. The knowledge base is named “Micycle” and contains 5,922 human proteins (together with their genes of reference) annotated in an integrated and structured ontology with 17,304 different ontological terms. Micycle integrates the dominant Cell Cycle and Cellular Migration Gene Ontology (GO), other ontologies and formal classification such as, the Cell Cycle Ontology (CCO), the Cell Phenotype Ontology (CPO) and the Cell Migration Consortium data.

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). Important refinements and conceptual progress have been made for the tool generation tasks in particular, a method for variable selection in datasets of image-based cellular features that provides a generic framework for dimension reduction that overcomes many limitations of other approaches, in particular it selects specific features rather than defining hard-to-interpret linear combinations, and it allows to separate variability due to noise and informative signal, basing the selection only on the latter.

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). Thus, a standardized nomenclature of the quantitative parameters extracted from cellular images has been established based on published literature and communication with bio-imaging experts. A reference implementation of an extensive set of parameters on image texture and contours has been established in the CellCognition Open Source software and disseminated to the public on the CellCognition webpage: The implementation of the Portable Systems Microscopy (PSM) format has progressed to the stage that IDEA Biomedical is using the format in its commercial products, including its image analysis software WiSoft.

A prototype database for systems microscopy data is being developed (WP9) that further will facilitate standardization efforts. By storing, organizing and providing access to data, the database will constitute a central resource to the network that will enable data sharing among the network partners and serve as a prototype for a long-term, production-scale systems microscopy public data base. We made significant progress in further developing the prototypes for a public database and a query interface. The prototype database contains now 10 datasets and it has been deployed to a stable production server. Additional functionalities have been added to the query interface and extensive work has been done to improve data visualization, particularly for the reagent and phenotype pages. A simple spreadsheet template based submission tool and an ontology-based annotation tool for annotating phenotypic descriptions have been developed and has been prepared for circulation to the consortium for usability testing.

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 completely controls the outcome. Therefore, systems microscopy is an essential approach to gain understanding of cell division and cell migration. 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 project period, the work packages established several tools, including software and model systems, for the quantitative analysis of cell division and cell migration. These tools were further improved and tuned for the needs of the consortium during the second period including the assay systems and computational tools. We finalised the steps to translate the findings of genes influencing mitosis and migration obtained from screening in WPs 1 and 2. Novel functions of cell cycle genes have been predicted and validated using RNAi screens and bioinformatics tools. Testing model prediction using cross-correlation spectroscopy is currently providing new insights on the interaction between important mitotic proteins and protein complexes. We have also mapped the effects of knockdown of 107 previously identified Drosophila proteins involved in cell cycle regulation on the overall gene expression pattern by expression profiling.

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 within this second period has been applied to prioritize both mitotic and migratory genes, derived from siRNA screen studies in WP1, WP2 and WP3. Thus, we initiated the analysis of clinically relevant mitotic/migratory genes (found to be linked with breast cancer in silico), using the breast cancer patient tissue microarrays. We also started to develop a translational bioinformatics analysis pipeline for prostate cancer cell lines/patient data. A novel clinically relevant gene, SPRK1, found in cell migration-related siRNA screens, was shown to be clinically relevant in breast cancer patients, as well as to be involved in metastasis in mouse model. Importantly, the invasive behavior of different breast cancer cell lines in 3D environment has been characterized, enabling the selection of the most invasive cell lines for metastasis studies.


The expected final results and impact

The area of systems microscopy is just emerging, but has already proven its impact in being able to powerfully combine systems biology with detailed visual analysis of cellular processes. This NoE aims to enable systems biology of complex cellular processes. This aim will be fulfilled by the development and provision of common technical and computational tools for systems microscopy, as well as experimental and theoretical resources to carry out systems experiments and model their results. A generic approach for next-generation systems biology will be offered to the research community.

The joint research programme will generate data and models that are expected to further our systems-level understanding of cell division and migration, both of which are crucially involved in the development and progression of cancer, thereby providing new avenues for the translation of basic research into applied research. Novel testing systems for drug sensitivities and gene dependencies in primary cultures of cancer patients will be developed, tests that are expected to help guide future cancer diagnosis and therapy choices thereby paving the way for personalized medicine for the benefit of European citizens.

New technologies are developed in an area with significant future potential for innovation in biology and medicine, including translation to industry. We believe that at the end of this program, we will have developed significant tools, including software, screening systems and more, for translational applications that will provide opportunity for industrial collaborations to promote the NoE science and technology, thus strengthening European competitiveness. The results obtained in this project on cell division and migration, particularly in relation to cancer, may highlight and illuminate numerous opportunities for translational research breakthroughs, and consequent industrial benefits such as novel drug targets, as well as mechanisms of drug action.  Furthermore, it is likely that systems microscopy will become an indispensable tool to monitor drug effects in cellular systems in vitro, thereby playing a crucial role towards the development of future diagnostic applications.  

We will execute a multidisciplinary training programme, providing European research institutions with well-trained scientists to further develop this emerging area. The training programs will create a large user base, as well as contribute to the creation of future experts in this field across Europe. The power of the technology, the dissemination of knowledge and infrastructure will together serve as guarantor for the durability of the systems microscopy strategy.

Seventh Framework Programme

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