The Synthetic Biology theme aims to use knowledge-based design to modify living systems, to develop new processes and products based upon sustainable systems informed by successful naturally occurring processes, and to deliver new products and sustainable real-world solutions to current and future problems.
Our research focusses upon three key areas of activity:
Technologies for gene therapy
In Technologies for Gene Therapy (TGT), we will focus on pre-clinical and technological development and applicable model systems both for the treatment of disease and as a tool to investigate genotoxicity and solid tumor generation. We have consistent performance in funding in this area and a strong published research output. In addition there is expressed interest from other members of Biosciences and an opportunity to expand existing disease models with the building of the new animal facility. To be a major player in this area, we need to build on our current staff base and associated infrastructure in the area of Gene Therapy Vectors. It is envisaged that there will be substantial overlaps and synergies with the potential research thrusts of the Division of Biosciences in the areas of Chromosome damage, repair and other processes that are important to Ageing Studies and cancer.
Some diseases and disorders happen because certain genes work incorrectly or no longer work at all. We are designing therapeutic interventions for human diseases and disorders by developing the technologies to correct defective genes in order to cure and treat disease. Our current areas of interest in Technologies for Gene Therapy are in the areas of:
The greatest area of opportunity is Microbial BioEngineering; Europe is the world-leading producer of enzymes and is heading the implementation of industrial biotechnology for fine chemicals. Biotechnologies and the bio-based economy are, therefore, very high on the national and international funding agendas. We continue to build on our unique work and platform technology developments at Brunel and our recent success with EU funding in this area. We will further invest in expertise and infrastructure in the areas of bacterial bioengineering and in fermentation biology and translational biotechnology in order to scale up the activities of the Theme to larger scale pre-industrial activities that will bridge the ‘translational readiness level’ (TRL) gap of TRL3 to 5 required to link our work to industrial partners and SMEs.
The most exploitable and engineerable organisms are bacteria. So we want to harness the capacity and diversity of bacteria to create totally white technologies; those which cause no harm. Our research uses integrated genomics strategies to direct bacterial engineering for a number of translational applications.
Our current areas of greatest effort in the area of Microbial BioEngineering are in the areas of:
- The use of under-used and waste biomaterials from biomass and biodiesel manufacture
- The generation of products currently derived from petrochemicals from natural non-polluting sources
- The generation of bacteria to increase the performance (and hence longevity and reduce use) of cement
- The generation of bacteria optimized for the production of clean proteins
- The identification of new processes for the degradation of persistent environmental pollutants, including pollutants of water
- Using resources developed for synthetic biology to investigate ways to address antibiotic resistance in medically important bacteria
We are exploring other areas, and are open to developing new lines of research that will make the best use of the strain and widely applicable tools for strain assessment and development, especially when they are directed at projects that have sustainability as part of what they seek to achieve.
Computer Sciences, Statistics and Maths
The Computer Sciences and Math’s cluster aims to address practical analytical, modelling, and other computational problems related to synthetic biology as well as other biological science-related data and problems for the rest of the Research Themes, Institutes, and the wider University. Aspects involve data analysis, biological system simulation, analysis of large scale and time-series data, data integration, databases, information mining, ontologies for lab research, and development of new informatics tools.
Computational, mathematical and statistical approaches play vital roles in the design and analysis stages of the synthetic biology workflow. This is illustrated in the figure below, where desired behaviour is encoded as a functional phenotype and described by a mathematical model which acts as a blueprint or design template to guide the construction of the physical biological system. These models need to be analysed using advanced mathematical and computational techniques for internal consistency and coherence, as well as checking that they properly capture the properties of the desired target behaviour. Moreover, the actual behaviour of the implemented biosystems needs to be checked against the desired behaviour as expressed by the design templates, and against the desired target behaviour. As with any engineering process, the workflow is best conceived of as a set of cycles, representing refinement of the design and the implementation