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Espoo, Finland

Agency: Cordis | Branch: FP7 | Program: CP-IP | Phase: HEALTH-2007-2.1.2-2 | Award Amount: 14.64M | Year: 2008

T-cell activation, whether induced by pathogens or auto-antigens, is a complex process relying on multiple layers of tightly controlled intracellular signalling modules that form an intricate network. Defects in this network can cause severe and chronic disorders such as autoimmune diseases. Although 5% of the population suffer from these diseases, only a few therapeutic treatments are available. To a large extent this is attributed to the lack of systems-level insights, which would provide concepts of how to modulate T-cell activation. The SYBILLA project groups 14 partners from 9 different EU countries, including 3 SMEs. Through a multidisciplinary effort it aims to understand at the systems level, how T-cells discriminate foreign from auto-antigens. Towards this goal, a transgenic mouse system will be used as a tractable physiological model. Data will be validated in human T-cells and a humanised mouse model for multiple sclerosis. SYBILLA will develop technological and mathematical tools to generate and integrate high-density quantitative data describing T-cell activation. Proteomics, transcriptomics, metabolomics, imaging and multiplexed biochemical techniques will be applied to obtain holistic maps of T-cell signalling networks and to achieve a quantitative understanding of the network and its regulation in response to different inputs. Building upon our existing network model, constant iterations will be used to develop more robust dynamic models to describe the networks response to perturbations. This will culminate in the generation of a Virtual T-Cell, allowing computer simulation to refine the predictability of physiological and pathophysiological reactions. SYBILLAs impact on EU biopharmaceutical competitiveness will be enormous through identification of new pharmacologic targets, optimised prediction of immunomodulatory drug efficacy, discovery of new concerted biomarkers and improvement of personalised medication for treating autoimmune diseases.

Tohmola N.,University of Helsinki | Ahtinen J.,Medicel Oy | Pitkanen J.-P.,Medicel Oy | Pitkanen J.-P.,VTT Technical Research Center of Finland | And 6 more authors.
Biotechnology and Bioprocess Engineering | Year: 2011

We constructed a bioprocess environment enabling automatic sampling from a bioreactor combined with a compact on-line high performance liquid chromatography (HPLC) unit. This setup allowed us to measure extracellular glucose, ethanol, glycerol, and acetate concentrations automatically at 5 min intervals during the cultivation. This environment also provides mechanical measurement of the optical density (OD) of cells and enables us to collect and store (-35°C) samples for further off-line analyses. Among the available devices, the performance of the sampling-analysis unit is by far the best with regard to speed and number of analytes. Both the sampling and analysis phases are easily controlled by software; thus, providing a unique environment to perform various bioprocess activity tasks, whether they would be cell line screening or optimisation of conditions for growth and productivity. Complex research set-ups can be created and continuous automated measurements empower long-term cultivations with a time series. We provide evidence for the applicability of this environment by performing three comparable batch cultivations with Saccharomyces cerevisiae yeast and show that both the on-line sampling and analysis modes produce reliable data for further use in the monitoring and controlling of bioprocesses. On-line data provided new insight into the dynamics of the diauxic shift during aerobic glucose batch cultivation. When cell growth and carbon dioxide production ceased for the first time during the diauxic shift, acetate accumulation and consumption of the remaining glucose below 0.15 g/L continued to occur for 1 h. At the same time, glycerol and ethanol began to be consumed. Samples were also collected during cultivation for later analysis of intracellular metabolites and to collect more valuable information about metabolism. © 2011 The Korean Society for Biotechnology and Bioengineering and Springer-Verlag Berlin Heidelberg. Source

A Europe-wide consortium of experimental biologists, biomathematicians, biostatisticians, computer scientists and clinical scientists will team up to approach cell death pathways in health and disease, placing particular emphasis on cancer and AIDS. The consortium will create a unique database integrating existing and accumulating knowledge on lethal signal transduction pathways leading to apoptosis or non-apoptotic (necrotic, autophagic, mitotic) cell death, perform data mining to integrate system-wide analyses on cell death (genome, epigenome, transcriptome, proteome, lipidome data), and use high-throughput methods (omics, CHiP-chip and genome-wide siRNA screens) for the experimental exploration of death pathways in human cell lines in vitro and in relevant disease models (in vitro in human cells and in vivo in mice and Drosophila). In addition, the consortium will establish mathematical models of lethal pathways to devise algorithms that predict apoptosis susceptibility and resistance, obtain data (genome, transcriptome, proteome, lipidome) on clinical samples (cancer cell lines, cancer tissues, serum, and blood samples) and perform biostatistical analyses on them in order to demonstrate the contribution of apoptotic process in human cancers and AIDS. Then, the consortium will integrate the knowledge into mathematical models for the optimal interpretation of clinical data, aiming at optimal diagnostic and prognostic performance as well as at the identification of possible therapeutic targets for the treatment of cancer and AIDS.

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