OPTIMAL MICROFLUIDIC · INNATE IMMUNE SIGNALLING: OPTIMAL MICROFLUIDICS PROTOCOLS, PREDICTION AND CONTROL

INNATE IMMUNE SIGNALLING: OPTIMAL MICROFLUIDICS PROTOCOLS, PREDICTION AND CONTROL

The ability to summarise observations using explanatory and predictive theories is one of the greatest strengths of science. Theories, of more or less formal character, attempt to link observations together into some reproducible patterns. Systems biology uses integrative modelling to develop a more complete understanding of mechanisms that trigger and coordinate events within living cells. The relevance of this discipline arises from the need not only to explain cellular systems but also to predict and control their behaviour. The success of the approach relies heavily on the quality of the biological data. Unfortunately, the complexity of biochemical systems causes informative experimentation to be a time consuming and expensive task. As a result, the currently available data report on biological systems measured only in a limited number of, not necessarily most informative, experimental conditions. The major aim of the project was to investigate the possibility of using mathematically designed experiments to better understand signalling pathways of the immune system, and, eventually, to provide insight how cellular responses can be controlled by biochemical interventions. We have taken a two-pronged approach to address this objective. Primarily we have been developing a theoretical methodology to understand biochemical signal transduction processes. Secondly, we have experimentally examined cellular responses of two of the major pathways of the immune system: the NF-kB and the JAK-STAT pathways. We have obtained a set of results that, we believe, constitute a tangible contribution to our understanding how cells generate distinct responses from complex biochemical stimuli, and hence, how distinct responses could be induced by biochemical interventions. Our deliverables can be broadly divided into (i) methods that can quantify to what extend a single stimulus can control behaviour of an individual cell; and (ii) insight obtained using these methods in specific biochemical scenarios. Perhaps most interestingly, we have provided a rationale why a single stimulus usually has a rather limited effect on responses of individual cells. The relevance of our results in a broader socio-economic context results from the need of novel pharmacological strategies to control cellular response in living organisms. Conventional identification of therapeutic targets has been influenced by the concept of distinct signalling pathways that link signals with specific cellular responses. Within this framework, molecular specificity of therapeutic agents correlates well with their functional or phenotypic specificity. In practice, however, clinical outcomes for many drugs with high molecular specificity have been different than originally hoped for, if not disappointing. Therefore, the design of pharmacological interventions aimed to induce specific cellular responses may require more sophisticated strategies, even when compounds when high molecular specificity are at hand. In particular, it is necessary to understand how information about complex mixture of extracellular stimuli is processed and translated into distinct cellular responses. Our work contributed to this ambition by developing mathematical tools that allow us to quantitatively analyse complex signalling processes and provide a rationale how outcomes of signalling could be effectively controlled. Deliverables of the project are being made available to the research community in form of scientific publications and open source software packages. A list of these is maintained on the website of our laboratory http://sysbiosig.org.

Data: CORDIS, © European Union