Research

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Synthetic Biology underpins advances in the bioeconomy

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{Oyarzun:2014:10.1021/sb400126a,
author = {Oyarzun, DA and Lugagne, J-B and Stan, G-B},
doi = {10.1021/sb400126a},
journal = {ACS Synthetic Biology},
pages = {116--125},
title = {Noise propagation in synthetic gene circuits for metabolic control},
url = {http://dx.doi.org/10.1021/sb400126a},
volume = {4},
year = {2014}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Dynamic control of enzyme expression can be an effective strategy to engineer robust metabolic pathways. It allows a synthetic pathway to self-regulate in response to changes in bioreactor conditions or the metabolic state of the host. The implementation of this regulatory strategy requires gene circuits that couple metabolic signals with the genetic machinery, which is known to be noisy and one of the main sources of cell-to-cell variability. One of the unexplored design aspects of these circuits is the propagation of biochemical noise between enzyme expression and pathway activity. In this article, we quantify the impact of a synthetic feedback circuit on the noise in a metabolic product in order to propose design criteria to reduce cell-to-cell variability. We consider a stochastic model of a catalytic reaction under negative feedback from the product to enzyme expression. On the basis of stochastic simulations and analysis, we show that, depending on the repression strength and promoter strength, transcriptional repression of enzyme expression can amplify or attenuate the noise in the number of product molecules. We obtain analytic estimates for the metabolic noise as a function of the model parameters and show that noise amplification/attenuation is a structural property of the model. We derive an analytic condition on the parameters that lead to attenuation of metabolic noise, suggesting that a higher promoter sensitivity enlarges the parameter design space. In the theoretical case of a switch-like promoter, our analysis reveals that the ability of the circuit to attenuate noise is subject to a trade-off between the repression strength and promoter strength.
AU  - Oyarzun,DA
AU  - Lugagne,J-B
AU  - Stan,G-B
DO  - 10.1021/sb400126a
EP  - 125
PY  - 2014///
SN  - 2161-5063
SP  - 116
TI  - Noise propagation in synthetic gene circuits for metabolic control
T2  - ACS Synthetic Biology
UR  - http://dx.doi.org/10.1021/sb400126a
UR  - http://hdl.handle.net/10044/1/27223
VL  - 4
ER  -
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