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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{Senthivel:2016:10.1038/srep39178,
author = {Senthivel, V and Sturrock, M and Piedrafita, G and Isalan, M},
doi = {10.1038/srep39178},
journal = {Scientific Reports},
title = {Identifying ultrasensitive HGF dose-response functions in a 3D mammalian system for synthetic morphogenesis},
url = {http://dx.doi.org/10.1038/srep39178},
volume = {6},
year = {2016}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - Nonlinearresponses to signalsarewidespread natural phenomenathat affect various cellular processes. Nonlinearitycan bea desirable characteristic for engineering living organismsbecause it can lead to more switch-like responses, similar to those underlying the wiring inelectronics. Steeperfunctions are described as ultrasensitive, and can be applied in synthetic biologyby using various techniquesincludingreceptor decoys, multiple co-operative binding sites, and sequentialpositive feedbacks. Here, we explore the inherent non-linearity of a biological signaling system to identify functions that can potentially be exploited using cell genome engineering.For this,we performed genome-wide transcription profilingto identify genes with ultrasensitiveresponse functionsto Hepatocyte Growth Factor (HGF). Weidentified3,527genesthat react to increasing concentrations of HGF, in Madin-Darby canine kidney (MDCK) cells,grown as cystsin 3D collagen cell culture. By fitting a generic Hill function to the dose-responsesof these genes we obtained ameasure of the ultrasensitivityofHGF-responsive genes, identifying a subset with higher apparent Hill coefficients (e.g. MMP1, TIMP1,SNORD75, SNORD86 andERRFI1). The regulatory regions of these genes are potential candidates for future engineering of synthetic mammalian gene circuits requiring nonlinear responses to HGF signalling.
AU - Senthivel,V
AU - Sturrock,M
AU - Piedrafita,G
AU - Isalan,M
DO - 10.1038/srep39178
PY - 2016///
SN - 2045-2322
TI - Identifying ultrasensitive HGF dose-response functions in a 3D mammalian system for synthetic morphogenesis
T2 - Scientific Reports
UR - http://dx.doi.org/10.1038/srep39178
UR - http://hdl.handle.net/10044/1/42705
VL - 6
ER -