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{Wu:2020:nar/gkz1123,
author = {Wu, Y and Chen, T and Liu, Y and Tian, R and Lv, X and Li, J and Du, G and Chen, J and Ledesma-Amaro, R and Liu, L},
doi = {nar/gkz1123},
journal = {Nucleic Acids Research},
pages = {996--1009},
title = {Design of a programmable biosensor-CRISPRi genetic circuits for dynamic and autonomous dual-control of metabolic flux in Bacillus subtilis},
url = {http://dx.doi.org/10.1093/nar/gkz1123},
volume = {48},
year = {2020}
}

Download

RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Dynamic regulation is an effective strategy for fine-tuning metabolic pathways in order to maximize target product synthesis. However, achieving dynamic and autonomous up- and down-regulation of the metabolic modules of interest simultaneously, still remains a great challenge. In this work, we created an autonomous dual-control (ADC) system, by combining CRISPRi-based NOT gates with novel biosensors of a key metabolite in the pathway of interest. By sensing the levels of the intermediate glucosamine-6-phosphate (GlcN6P) and self-adjusting the expression levels of the target genes accordingly with the GlcN6P biosensor and ADC system enabled feedback circuits, the metabolic flux towards the production of the high value nutraceutical N-acetylglucosamine (GlcNAc) could be balanced and optimized in Bacillus subtilis. As a result, the GlcNAc titer in a 15-l fed-batch bioreactor increased from 59.9 g/l to 97.1 g/l with acetoin production and 81.7 g/l to 131.6 g/l without acetoin production, indicating the robustness and stability of the synthetic circuits in a large bioreactor system. Remarkably, this self-regulatory methodology does not require any external level of control such as the use of inducer molecules or switching fermentation/environmental conditions. Moreover, the proposed programmable genetic circuits may be expanded to engineer other microbial cells and metabolic pathways.
AU  - Wu,Y
AU  - Chen,T
AU  - Liu,Y
AU  - Tian,R
AU  - Lv,X
AU  - Li,J
AU  - Du,G
AU  - Chen,J
AU  - Ledesma-Amaro,R
AU  - Liu,L
DO  - nar/gkz1123
EP  - 1009
PY  - 2020///
SN  - 0305-1048
SP  - 996
TI  - Design of a programmable biosensor-CRISPRi genetic circuits for dynamic and autonomous dual-control of metabolic flux in Bacillus subtilis
T2  - Nucleic Acids Research
UR  - http://dx.doi.org/10.1093/nar/gkz1123
UR  - https://www.ncbi.nlm.nih.gov/pubmed/31799627
UR  - http://hdl.handle.net/10044/1/75692
VL  - 48
ER  -