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Research

Biological systems - including the simplest cells - exhibit a broad range of functions to thrive in their environment. Research in the Imperial College Centre for Synthetic Biology is focused on the possibility of engineering the underlying biochemical processes to solve many of the challenges facing society, from healthcare to sustainable energy. In particular, we model, analyse, design and build biological and biochemical systems in living cells and/or in cell extracts, both exploring and enhancing the engineering potential of biology.

As part of our research we develop novel methods to accelerate the celebrated Design-Build-Test-Learn synthetic biology cycle. As such research in the Centre for Synthetic Biology highly multi- and interdisciplinary covering computational modelling and machine learning approaches; automated platform development and genetic circuit engineering ; multi-cellular and multi-organismal interactions, including gene drive and genome engineering; metabolic engineering; in vitro/cell-free synthetic biology; engineered phages and directed evolution; and biomimetics, biomaterials and biological engineering.

Publications

Citation

BibTex format

@article{Kelly:2018:nar/gky828,
author = {Kelly, CL and Harris, AWK and Steel, H and Hancock, EJ and Heap, JT and Papachristodoulou, A},
doi = {nar/gky828},
journal = {Nucleic Acids Research},
pages = {9875--9889},
title = {Synthetic negative feedback circuits using engineered small RNAs},
url = {http://dx.doi.org/10.1093/nar/gky828},
volume = {46},
year = {2018}
}

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RIS format (EndNote, RefMan)

TY - JOUR
AB - Negative feedback is known to enable biological and man-made systems to perform reliably in the face of uncertainties and disturbances. To date, synthetic biological feedback circuits have primarily relied upon protein-based, transcriptional regulation to control circuit output. Small RNAs (sRNAs) are non-coding RNA molecules that can inhibit translation of target messenger RNAs (mRNAs). In this work, we modelled, built and validated two synthetic negative feedback circuits that use rationally-designed sRNAs for the first time. The first circuit builds upon the well characterised tet-based autorepressor, incorporating an externally-inducible sRNA to tune the effective feedback strength. This allows more precise fine-tuning of the circuit output in contrast to the sigmoidal, steep input-output response of the autorepressor alone. In the second circuit, the output is a transcription factor that induces expression of an sRNA, which inhibits translation of the mRNA encoding the output, creating direct, closed-loop, negative feedback. Analysis of the noise profiles of both circuits showed that the use of sRNAs did not result in large increases in noise. Stochastic and deterministic modelling of both circuits agreed well with experimental data. Finally, simulations using fitted parameters allowed dynamic attributes of each circuit such as response time and disturbance rejection to be investigated.
AU - Kelly,CL
AU - Harris,AWK
AU - Steel,H
AU - Hancock,EJ
AU - Heap,JT
AU - Papachristodoulou,A
DO - nar/gky828
EP - 9889
PY - 2018///
SN - 0305-1048
SP - 9875
TI - Synthetic negative feedback circuits using engineered small RNAs
T2 - Nucleic Acids Research
UR - http://dx.doi.org/10.1093/nar/gky828
UR - https://www.ncbi.nlm.nih.gov/pubmed/30212900
UR - http://hdl.handle.net/10044/1/64510
VL - 46
ER -