Combinatorial Systems Biology of ROS-Regulated Interleukin-1 Gene Expression
Lead Research Organisation:
University of Manchester
Department Name: Chemistry
Abstract
Inflammation is our bodies' response to stresses, and also helps us to heal and repair. The process of inflammation involves the coordinated actions of a large number of molecules or mediators. A molecule called interleukin-1beta, or IL-1beta for short, is key in causing inflammation. The pathways or cascade of events that result in the production of IL-1beta are complicated. Our goal is to elucidate these pathways of IL-1beta production. It is common knowledge that free radicals are, in general, harmful, and their production leads to a process called oxidative stress. So when high levels of free radicals are produced in parts of the body that are particularly sensitive such as the brain, it can be damaging to our tissues and our health. However, there is some information that shows they are important for inflammatory processes. They are also thought to be involved in the production of IL-1beta. A variety of free radicals can be produced, we know that iron ions (especially a 'free' form of iron, Fe++) can trigger the production of a particularly damaging one known as the hydroxyl radical. Molecules known as iron chelators can bind to iron and stop this from happening, while so-called antioxidants such as vitamin E can mop them up. Like any biological pathway, the process of IL-1beta production is very complicated and depends upon many factors. Due to this complexity we would normally study factors in isolation. However, biological systems are typically considerably more than the sum of their parts, and in preliminary experiments we have shown that while Vitamin E or an iron chelator ALONE do comparatively little, IN COMBINATION they have a huge effect in inhibiting the production of IL-1beta. We shall therefore construct a mathematical model of this system. The advantage of this is that we can very easily vary the rates of reactions, alone or combined, within a computer and see which combinations of changes have the greatest effect. In parallel we shall perform experimental measurements of the production of the various substances of main interest and the effect on this of these combinations. The result will be a quantitative understanding not only of the whole system but of WHY we both anticipate and find that we need to manipulate multiple steps in a biological pathway to have substantial effects on it.
Technical Summary
IL-1beta is a key mediator of inflammation, but the pathways that result in its production are complex; the aim of this proposal is to describe them quantitatively. Due to this complexity we would traditionally study factors in isolation. However, biological systems are typically considerably more than the sum of their parts, and in preliminary experiments we have shown that while Vitamin E or an iron chelator ALONE do comparatively little, IN COMBINATION they have a huge effect in inhibiting the production of IL-1beta. We shall therefore construct a mathematical model of this system. The advantage of this is that we can very easily vary the rates of reactions in silicio, alone or combined, and see which combinations of changes have the greatest effect. In parallel we shall perform experimental measurements of the production of the various substances of main interest and the effect on this of these combinations. To overcome the combinatorial explosion of factors involved we shall develop multi-objective evolutionary algorithms to optimise the cocktails of substances added. The result of this interdisicplinary project, combining both 'wet' and 'dry' strands in an iterative manner, will be a quantitative understanding not only of the whole system but of WHY we both anticipate and find that we need to manipulate multiple steps in a biological pathway in order to have substantial effects on it.
Publications

Challenger J
(2012)
Multi-compartment linear noise approximation
in Journal of Statistical Mechanics: Theory and Experiment



Kell DB
(2012)
Scientific discovery as a combinatorial optimisation problem: how best to navigate the landscape of possible experiments?
in BioEssays : news and reviews in molecular, cellular and developmental biology

Li P
(2010)
Systematic integration of experimental data and models in systems biology.
in BMC bioinformatics

Pahle J
(2012)
Biochemical fluctuations, optimisation and the linear noise approximation.
in BMC systems biology

Patel Y
(2011)
Predicting the points of interaction of small molecules in the NF-?B pathway.
in BMC systems biology

Rowe W
(2010)
Predictive models for population performance on real biological fitness landscapes.
in Bioinformatics (Oxford, England)

Small BG
(2011)
Efficient discovery of anti-inflammatory small-molecule combinations using evolutionary computing.
in Nature chemical biology
Description | We developed a computer based method to produce a cocktail of potential drugs to make a mixture that was more effective together than the drugs alone in reducing inflammation. |
Exploitation Route | This strategy could be adopted by researchers using primary cell culture or whole animal experiments and thus could potentially have a massive effect on reducing the numbers of animals used for an experiment. |
Sectors | Agriculture, Food and Drink,Chemicals,Digital/Communication/Information Technologies (including Software),Healthcare,Pharmaceuticals and Medical Biotechnology |
Description | No social or economic impact at this stage, only academic. |
Title | Evolutionary algorithm |
Description | We developed a multi-objective evolutionary algorithm for the generation and optimisation of cocktails of drugs. This is a generic tool applicable to all areas of biological research. |
Type Of Material | Technology assay or reagent |
Provided To Others? | No |
Impact | Use of the EA greatly reduced the numbers of experiments we needed to perform to optimise drug cocktails. |