Streamlined identification of strain engineering targets for bioprocess improvement using metabolic pathway enrichment analysis

被引:2
|
作者
Cortada-Garcia, Joan [1 ]
Daly, Ronan [2 ]
Arnold, S. Alison [3 ]
Burgess, Karl [1 ]
机构
[1] Univ Edinburgh, Inst Quantitat Biol Biochem & Biotechnol, Sch Biol Sci, Edinburgh EH8 9AB, Scotland
[2] Univ Glasgow, Glasgow Poly, Inst Infect Immun & Inflammat, Glasgow City G61 1QH, Scotland
[3] Ingenza Ltd, Roslin Innovat Ctr, Roslin EH25 9RG, Scotland
来源
SCIENTIFIC REPORTS | 2023年 / 13卷 / 01期
基金
英国生物技术与生命科学研究理事会;
关键词
RECOMBINANT PROTEIN-PRODUCTION; SUCCINATE PRODUCTION; 1-BUTANOL PRODUCTION; ACCUMULATION; PLATFORM; CULTURES; REVEALS; GLUCOSE; CELLS; ACID;
D O I
10.1038/s41598-023-39661-x
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Metabolomics is a powerful tool for the identification of genetic targets for bioprocess optimisation. However, in most cases, only the biosynthetic pathway directed to product formation is analysed, limiting the identification of these targets. Some studies have used untargeted metabolomics, allowing a more unbiased approach, but data interpretation using multivariate analysis is usually not straightforward and requires time and effort. Here we show, for the first time, the application of metabolic pathway enrichment analysis using untargeted and targeted metabolomics data to identify genetic targets for bioprocess improvement in a more streamlined way. The analysis of an Escherichia coli succinate production bioprocess with this methodology revealed three significantly modulated pathways during the product formation phase: the pentose phosphate pathway, pantothenate and CoA biosynthesis and ascorbate and aldarate metabolism. From these, the two former pathways are consistent with previous efforts to improve succinate production in Escherichia coli. Furthermore, to the best of our knowledge, ascorbate and aldarate metabolism is a newly identified target that has so far never been explored for improving succinate production in this microorganism. This methodology therefore represents a powerful tool for the streamlined identification of strain engineering targets that can accelerate bioprocess optimisation.
引用
收藏
页数:13
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