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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{Borkowski:2018:10.1038/s41467-018-03970-x,
author = {Borkowski, O and Bricio, C and Murgiano, M and Rothschild-Mancinelli, B and Stan, G and Ellis, T},
doi = {10.1038/s41467-018-03970-x},
journal = {Nature Communications},
pages = {1--11},
title = {Cell-free prediction of protein expression costs for growing cells},
url = {http://dx.doi.org/10.1038/s41467-018-03970-x},
volume = {9},
year = {2018}
}

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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Translating heterologous proteins places significant burden on host cells, consuming expression resources leading to slower cell growth and productivity. Yet predicting the cost of protein production for any given gene is a major challenge, as multiple processes and factors combine to determine translation efficiency. To enable prediction of the cost of gene expression in bacteria, we describe here a standard cell-free lysate assay that provides a relative measure of resource consumption when a protein coding sequence is expressed. These lysate measurements can then be used with a computational model of translation to predict the in vivo burden placed on growing E. coli cells for a variety of proteins of different functions and lengths. Using this approach, we can predict the burden of expressing multigene operons of different designs and differentiate between the fraction of burden related to gene expression compared to action of a metabolic pathway.
AU  - Borkowski,O
AU  - Bricio,C
AU  - Murgiano,M
AU  - Rothschild-Mancinelli,B
AU  - Stan,G
AU  - Ellis,T
DO  - 10.1038/s41467-018-03970-x
EP  - 11
PY  - 2018///
SN  - 2041-1723
SP  - 1
TI  - Cell-free prediction of protein expression costs for growing cells
T2  - Nature Communications
UR  - http://dx.doi.org/10.1038/s41467-018-03970-x
UR  - https://www.nature.com/articles/s41467-018-03970-x
UR  - http://hdl.handle.net/10044/1/58614
VL  - 9
ER  -