In this section
@article{Lv:2022:10.1016/j.copbio.2022.102724,
author = {Lv, X and Hueso-Gil, A and Bi, X and Wu, Y and Liu, Y and Liu, L and Ledesma, Amaro R},
doi = {10.1016/j.copbio.2022.102724},
journal = {Current Opinion in Biotechnology},
title = {New synthetic biology tools for metabolic control},
url = {http://dx.doi.org/10.1016/j.copbio.2022.102724},
volume = {76},
year = {2022}
}
TY - JOUR
AB - In industrial bioprocesses, microbial metabolism dictates the product yields, and therefore, our capacity to control it has an enormous potential to help us move towards a bio-based economy. The rapid development of multiomics data has accelerated our systematic understanding of complex metabolic regulatory mechanisms, which allow us to develop tools to manipulate them. In the last few years, machine learning-based metabolic modeling, Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) derived synthetic biology tools, and synthetic genetic circuits have been widely used to control the metabolism of microorganisms, manipulate gene expression, and build synthetic pathways for bioproduction. This review describes the latest developments for metabolic control, and focuses on the trends and challenges of metabolic engineering strategies.
AU - Lv,X
AU - Hueso-Gil,A
AU - Bi,X
AU - Wu,Y
AU - Liu,Y
AU - Liu,L
AU - Ledesma,Amaro R
DO - 10.1016/j.copbio.2022.102724
PY - 2022///
SN - 0958-1669
TI - New synthetic biology tools for metabolic control
T2 - Current Opinion in Biotechnology
UR - http://dx.doi.org/10.1016/j.copbio.2022.102724
UR - https://www.ncbi.nlm.nih.gov/pubmed/35489308
UR - http://hdl.handle.net/10044/1/96640
VL - 76
ER -
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