Skip to main content Skip to navigation

Engineering metabolic pathways for optimal performance within host and biotechnological constraints.

Primary Supervisor: Dr Alexander Darlington, School of Engineering

Secondary supervisor: Variable dependent upon student interests, see below.

PhD project title: Engineering metabolic pathways for optimal performance within host and biotechnological constraints

University of Registration: University of Warwick

Project outline:

Research. Synthetic biology and microbial biotechnology offer sustainable routes to the manufacturer of commodity and high value chemicals from agricultural by-products instead of petrochemical feedstocks. However, at present the production of industrial strains is a time intensive and expensive process requiring multiple rounds of experimentation and redesign. A key cause of this is our difficulty in predicting the impact of the novel pathways on the host metabolism and wider physiology. Pathway enzyme production utilises the host gene expression machinery and drains host nucleotide and amino acid pools, while engineered pathways drain key metabolites from central carbon metabolism (as well as nucleotides and amino acids). These interactions perturb the host’s homeostasis, resulting in changes to resource supply which do not benefit either pathway performance or host growth. In addition to these internal constraints, these microbial ‘cell factories’ are subjected to industrial constraints including environmental heterogeneity, fermentation strategy, and cost.  

Our group aims to tackle these roadblocks to industrialization of synthetic biology by developing quantitative mathematical models that can inform and guide the engineering of biological systems. We develop models which combine metabolism, gene expression and microbial growth to understand how these multiple dynamic constraints emerge over the course of population growth during industrial production processes and how they impact the function of engineered gene circuits and pathways. We are working with academic and industrial partners to extend these modelling frameworks beyond the lab workhorse E. coli into industrially relevant strains to optimise real world bioprocesses. Within this framework we embed real world industrially relevant metabolic pathways and use mathematical techniques to identify key bottlenecks which limit their performance. Using this knowledge, we design control strategies which dynamically balance growth and production to improve efficiency and yield of these pathways. Our group works closely with experimental colleagues to validate model predictions in vivo and implement the new design strategies we identify. We anticipate all students will spend significant time undertaking experimental work in a partner lab to generate data to refine their computational models and to validate the design strategies they uncovered during their research.

Collaborators. Projects in our lab are highly flexible with aims that can be tailored to the student’s interest. The student will be co-supervised by experimental colleagues in the School of Life Sciences or Department of Chemistry at the University of Warwick. We have specific collaborations with the labs on the following projects:

  • Controlling secondary metabolism in Streptomyces with Dr Chris Corre.
  • Optimising metabolic pathways in yeast with Dr Fabrizio Alberti.
  • Genetic control systems in yeast with Prof. John McCarthy.

Students will be hosted by their experimental co-supervisor to enable validation of their theoretical findings. Students can also benefit from our links with industrial partners, such as Ingenza Ltd., who will provide commercial insights and feedback throughout the project. Depending on the specific project there is scope for students to visit the labs of our industrial partners for short placements.

Training. Students will receive a comprehensive interdisciplinary training needed for modern biological research including (i) mathematical modelling, (ii) programming, (iii) molecular biology and (iv) metabolic analysis. We also encourage students to take advantage of industrial links and participate in Warwick Innovations courses on university-industry partnerships.

Contact. Students should contact Dr Alexander Darlington (a.darlington.1 (at) as soon as possible to discuss their research interests and develop the scope of the specific project. Ideally entitle the email “MIBTP prospective student” so that it is not missed.

Key references.

Example work. Darlington, A. P. S. et al. (2018) ‘Dynamic allocation of orthogonal ribosomes facilitates uncoupling of co-expressed genes’, Nature Communications, 9, e695. doi: 10.1038/s41467-018-02898-6.

Background review on host constraints. Grunberg, T. W. and Del Vecchio, D. (2020) ‘Modular Analysis and Design of Biological Circuits’, Current Opinion in Biotechnology. 63, pp. 41–47. doi: 10.1016/j.copbio.2019.11.015.

Background review on overcoming host constraints. Boo, A., Ellis, T. and Stan, G.-B. (2019) ‘Host-Aware Synthetic Biology’, Current Opinion in Systems Biology. 14, pp. 66-73. doi: 10.1016/J.COISB.2019.03.001.

Background review on metabolic control. Hartline, C. J. et al. (2020) ‘Dynamic control in metabolic engineering: Theories, tools, and applications’, Metabolic Engineering, 63, pp. 126-140. doi: 10.1016/j.ymben.2020.08.015.

BBSRC Strategic Research Priority: Renewable Resources and Clean Growth: Industrial Biotechnology & Understanding the Rules of Life: Microbiology & Systems Biology

    Techniques that will be undertaken during the project:

    • Mathematical skills. Dynamical modelling, flux balance analysis, optimisation, other techniques as needed from Systems and Control Engineering.
    • Programming languages. Python, MATLAB (with initial and advanced training provided).
    • Molecular biology techniques (including Gibson assembly).
    • Enzymatic assays, High performance liquid chromatography.
    • Advanced techniques (dependent upon final collaborations): Streptomyces molecular biology, RNA-seq analysis, High throughput DNA assembly.

    Contact: Dr Alexander Darlington, University of Warwick