In this section

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{Mannan:2017:10.1021/acssynbio.7b00172,
author = {Mannan, AA and Liu, D and Zhang, F and Oyarzun, DA},
doi = {10.1021/acssynbio.7b00172},
journal = {ACS Synthetic Biology},
pages = {1851--1859},
title = {Fundamental design principles for transcription-factor-based metabolite biosensors},
url = {http://dx.doi.org/10.1021/acssynbio.7b00172},
volume = {6},
year = {2017}
}

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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Metabolite biosensors are central to current efforts toward precision engineering of metabolism. Although most research has focused on building new biosensors, their tunability remains poorly understood and is fundamental for their broad applicability. Here we asked how genetic modifications shape the dose–response curve of biosensors based on metabolite-responsive transcription factors. Using the lac system in Escherichia coli as a model system, we built promoter libraries with variable operator sites that reveal interdependencies between biosensor dynamic range and response threshold. We developed a phenomenological theory to quantify such design constraints in biosensors with various architectures and tunable parameters. Our theory reveals a maximal achievable dynamic range and exposes tunable parameters for orthogonal control of dynamic range and response threshold. Our work sheds light on fundamental limits of synthetic biology designs and provides quantitative guidelines for biosensor design in applications such as dynamic pathway control, strain optimization, and real-time monitoring of metabolism.
AU  - Mannan,AA
AU  - Liu,D
AU  - Zhang,F
AU  - Oyarzun,DA
DO  - 10.1021/acssynbio.7b00172
EP  - 1859
PY  - 2017///
SN  - 2161-5063
SP  - 1851
TI  - Fundamental design principles for transcription-factor-based metabolite biosensors
T2  - ACS Synthetic Biology
UR  - http://dx.doi.org/10.1021/acssynbio.7b00172
UR  - http://hdl.handle.net/10044/1/50318
VL  - 6
ER  -