Endocrine Abstracts

The advent of high throughput techniques and genome sequencing has brought about a new era in the availability of biological data. This has created a need for new approached for data integration and to interpret complex biological data sets. A cell cannot be considered as using a set of independent signalling pathways. Instead, it is now clear that signalling proteins are integrated into a complex network. The human brain cannot handle this complexity. At the same time, we need to take a more quantitative approach to the analysis of how such systems work. Many of the experimental techniques that we use are poorly quantitative and are not easily integrated together.

Systems biology seeks to solve some of these problems by applying multidisciplinary experimental and theoretical approaches to analyse and understand biological systems. Both the experimental and theoretical approaches need to be appropriate for the task. It is important to be able to analyse enough components in order to be able to understand the function of the whole system. Research scientists need to be trained to communicate with people from other disciplines. I will discuss how these hurdles may be overcome. My talk will use examples from analysis of the NF-κB system and prolactin gene expression.

Nuclear factor κB (NF-κB) regulates cellular stress responses and the immune response to infection. We used an integrated live cell imaging and mathematical approach to analyse this system. We found that NF-κB activation results in oscillations in nuclear NF-κB abundance. We also found that the timing of the oscillations regulates downstream gene expression. I will show how the use of modelling has made unexpected insights into how this system works. Finally, I will go on to discuss new approaches for the analysis of transcriptional variation in live cells.