Systems engineering tools for next generation engineering biology

Research Group Activity

Bioengineering, Engineering biology and biotechnology

Project Description

BACKGROUND. Synthetic biology is a young discipline at the interface of complex systems and biotechnology which aims to efficiently engineer new functions into living cells (great online intro video at https://youtu.be/H_CLySMFP38). These small artificial genetic networks can be used to integrate external stimuli and guide microbial behaviour with numerous potential applications in a range of sectors including healthcare, the chemicals industry and environmental remediation (Good introductory review at https://www.nature.com/articles/nmeth.2926). However, at present the production of such engineered microbes is a time intensive and expensive process requiring multiple rounds of experimentation and redesign. Our group aims to tackle key roadblocks to industrialization of engineering biology by developing quantitative modelling frameworks to inform and guide the engineering of biological systems. Projects within the group are highly flexible and can be tailored to suit the student’s specific interests and experience. Example projects include: (1) TESTING MICROBIAL CONSORTIA CONTORL STRATEGIES. In this project, we will model the division of a biotechnological process between different organisms in complex communities called microbial consortia. In such consortia each individual strain carries out one part of the pathway with the whole pathway only functioning and producing the compound of interest when all members of the community are present. We will investigate how production and/or growth rates should be designed to allow stable production over industrially relevant time periods. We will explore how introducing communication between the strains and/or feedback control strategies can improve the robustness of microbial communities. (2) DESIGNING GENETIC CONTROLLERS FOR BIOMANUFACTURING. In this project, we will apply control and systems engineering tools to design control systems to improve the performance of synthetic gene circuits and biotechnological pathways. We will develop mathematical models of key medical or industrial circuits or pathways. We will explore how circuit or pathway performance can be improved by the incorporation of feedback control. These control systems can be realised as either experimentally implementable chemical reactions in living cells or in silico approaches where an external computer carries out the control action. We will explore how to design these control systems, exploring potential trade-offs between different performance metrics, and identifying designs with optimal performance and good robustness to parametric uncertainty. Prospective students are encouraged to contact Dr Alexander Darlington (a.darlington.1@warwick.ac.uk) to discuss further opportunities and their interests.

Student Level

Open to both undergraduate and postgraduate students

Location

This project can be completed remotely.

Skills you can learn from this project

These projects will utilise MATLAB to create and solve dynamical models to answer biological questions. They are ideal for those who want to improve their understanding of dynamical systems or those considering taking Biomedical Systems Modelling and Computational Synthetic and Systems Biology � in the fourth year. Depending on project choice, students will also gain an enhanced understanding of control theory and/or multi-objective optimisation.

Required Skills

Students will have skills in ordinary differential equation modelling and an interest developing their control and/or optimisation skills. They will need to be comfortable working in a programming language of their choice, ideally MATLAB. Students without either of these are welcome to select the project but will be expected to carry out self-directed study before the project starts. Recommended reading and support will be given to facilitate this.

If you wish to apply for this project, fill in the form below including uploading your CV and personal statement, explaining why you want to do this particular internship project. Attachments must be in PDF format.

Project Team

Alexander Darlington