Principal Supervisor name and department: Dr Daniel Hebenstreit, School of Life Sciences

Where will the student be based? School of Life Sciences, Warwick

PhD project title:
Synthetic biology: designing reliable and predictable gene circuits in mammalian cells

Project description:

Synthetic biology holds great promise for many diverse fields, including energy and food production and the enhancement of human health. A major aim of synthetic biology is it to construct artificial gene circuits that function reliably and that can be tailored to different applications. Currently this is not possible due to fluctuations and random variations on the molecular level. Systems based on more than four or five regulatory interactions usually become unpredictable.

In this project, we will use genome editing in order to rewire signaling pathways in a mammalian cell line. We will restrict variations in the general states of the cells [1, 2] in order to design more complex synthetic gene circuits that are robust and predictable.

The project will initially involve transient transfections of the HEK293 cell line to ectopically express factors and explore their suitability for our project. The results will be evaluated using a combination of single-molecule RNA-FISH [3], flow cytometry, and next generation sequencing. In later project stages, CRISPR/Cas9 technology [4] will be employed to re-engineer the cell lines to yield stable systems with controllable synthetic components.

References:

1.  Paulsson, J., Physics of Life Reviews, 2005. 2(2): p. 157-175.

2.  Swain, P.S., M.B. Elowitz, and E.D. Siggia, Proc Natl Acad Sci U S A, 2002. 99(20): p. 12795-800.

3. Raj, A., et al., Nat Methods, 2008. 5(10): p. 877-9.

4. Ran, F.A., et al., Nat Protoc, 2013. 8(11): p. 2281-308.

Contact details for application enquiries:

Daniel Hebenstreit

Assistant Professor

School of Life Sciences

University of Warwick

Gibbet Hill Campus

Coventry CV4 7AL, UK

Phone: +44 (0)24 76 574457

E-mail:

Keywords:

Synthetic biology, systems biology, gene expression, transcription, stochastic kinetics, biological noise, genome editing, mammalian cells