Dynamics and Function of the NF-kB Signalling System

A major challenge in biology is to understand how cells recognize external signals and give appropriate responses. Now that the sequence of the human genome is complete, it is important to assign functions to each gene and to identify the corresponding proteins that control key cellular functions. White and colleagues pioneered the development of microscopy-based methods for the visualization and timelapse measurement of biological processes in single living cells. We have used natural light-emitting proteins from fireflies, jelly fish and fluorescent corals. Synthesis (expression) of these proteins causes mammalian cells to become luminescent (light emitting in the dark) or fluorescent (change the colour of light). By placing the gene that codes for a luminescent protein next to a promoter that controls a gene of interest, we can use luminescence from living cells as a way of measuring when the gene of interest is normally switched on and off. Fluorescent proteins have also been used to genetically label proteins of interest, so that the movement of the protein can be visualized in a living cell. White and colleagues previously used timelapse fluorescence and luminescence microscopy coupled to computer simulations to investigate cell decision making. We discovered that a set of important signalling proteins, called NF-kappaB, move repeatedly into and out of the nucleus of the cell, suggesting that cells may use proteins as timers to encode complex messages (like Morse Code). This was a surprise since the original NF-kappaB protein, p65, was discovered 20 years ago and was thought to act as a simple switch that moves into the nucleus once to activate genes. Only timelapse measurements in single living cells were able to see this. The NF-kappaB system is widely recognised as crucial to the control of important cellular processes including both cell division and cell death. It is implicated as being involved in a variety of diseases, such as cancer and inflammatory disease. We will now develop a substantial systems biology project to study all of the components of this complex system. While the previous work has provided major insights, we now need a far broader range of integrated experimental tools to study it. Also the use of mathematical models to make computer predictions will be critical to help us to visualize how this system works. We will make accurate measurements of the (much larger) set of proteins that are involved in NF-kappaB signalling and the genes that are controlled by these signals. The (very experienced) project team includes bioinformaticians, cell biologists, computer scientists, mathematicians, molecular biologists, microscopists and protein chemists. The project will be managed in a structured and organized way, so that the mathematical modelling can be used to predict and design the biological experiments. A central team of experimental officers will be responsible for coordinating the experiments, data and model storage and communication of information between team members. We will study the numbers of molecules of each of the NF-kappaB proteins in the cell, their stability, chemical states and interactions with each other and with other proteins. We will also study in detail which genes that they bind to and control. We will also aim to understand how single protein molecules acting at single genes can act to control decisions of cell life and death. This multidisciplinary approach is essential in order to understand this complex system. A further aim of the project is to provide training for post-docs and students. In this respect, we will benefit from sponsorship of training courses and symposia by the instrumentation companies Carl Zeiss, Hamamatsu Photonics, Coherent and Nano Imaging Devices. The project will also benefit from ongoing collaborations with Genetix and AstraZeneca

We will develop an integrated systems biology programme to analyse the dynamic and physiological function of the NF-kappaB signalling system. We previously applied iterative real-time imaging and mathematical modelling approaches to show that the NF-kappaB system is oscillatory and uses delayed negative feedback to direct nuclear to cytoplasmic cycling of transcription factor(s) that regulate gene expression. Our recent work has made clear how little is currently understood about even the core parts of the NF-kappaB system and only included a small subset of the NF-?B proteins and feedback loops. We will develop and apply a set of quantitative experimental tools coupled to an intensive theoretical analysis to properly analyse the dynamic function of the system. A key question is how cells achieve appropriate cell fate decisions in response to time-varying signals. Our team includes the expertise to measure and simulate the important processes involved in the core NF-?B network and is supported by leading technology companies.. The experimental work (involving network perturbations) will integrate dynamic cell and single molecule imaging, quantitative proteomics (for measurement of absolute protein and phosphoprotein levels and rates of turnover), chromatin immunoprecipitation (ChIP) analysis (for the dynamics of NF-kappaB binding to target promoters) and RT-PCR and DNA microarray analysis (for measurement of endogenous gene expression). The theoretical work will develop: 1) new data analysis tools to interpret and direct experimental strategy, 2) deterministic and 3) stochastic mathematical models of the system. The computer simulations will develop new experimentally testable hypotheses. Our goal is complete understanding of this complex and non-linear system. We will determine how the set of complex feedback loops controls NF-kappaB dynamics and controls downstream gene expression in the nucleus and how it operates at the single molecule/gene level.