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利用代谢途径富集分析简化生物工艺改进的菌株工程目标的鉴定。

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

机构信息

Institute of Quantitative Biology, Biochemistry and Biotechnology, School of Biological Sciences, University of Edinburgh, Edinburgh, EH8 9AB, UK.

Institute of Infection, Immunity and Inflammation, Glasgow Polyomics, University of Glasgow, Glasgow, G61 1QH, UK.

出版信息

Sci Rep. 2023 Aug 10;13(1):12990. doi: 10.1038/s41598-023-39661-x.

DOI:10.1038/s41598-023-39661-x
PMID:37563133
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10415327/
Abstract

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.

摘要

代谢组学是鉴定生物过程优化遗传靶标的有力工具。然而,在大多数情况下,仅分析针对产物形成的生物合成途径,限制了这些靶标的鉴定。一些研究使用非靶向代谢组学,允许采用更无偏的方法,但使用多元分析进行数据分析通常并不简单,需要时间和精力。在这里,我们首次展示了使用非靶向和靶向代谢组学数据进行代谢途径富集分析的应用,以更精简的方式鉴定生物过程改进的遗传靶标。使用这种方法分析大肠杆菌琥珀酸生产生物过程,在产物形成阶段发现了三个明显调节的途径:戊糖磷酸途径、泛酸和辅酶 A 生物合成以及抗坏血酸和醛酸盐代谢。其中,前两个途径与之前提高大肠杆菌琥珀酸产量的努力是一致的。此外,据我们所知,抗坏血酸和醛酸盐代谢是一个新发现的靶标,迄今为止,在这种微生物中,从未有人探索过通过该途径来提高琥珀酸产量。因此,该方法代表了一种强大的工具,可用于精简鉴定菌株工程靶标,从而加速生物过程优化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f746/10415327/50cdcc4a0632/41598_2023_39661_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f746/10415327/cbc0d6ba4416/41598_2023_39661_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f746/10415327/6973f559d292/41598_2023_39661_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f746/10415327/d216dd68ec62/41598_2023_39661_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f746/10415327/a9077f1d6c2f/41598_2023_39661_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f746/10415327/50cdcc4a0632/41598_2023_39661_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f746/10415327/cbc0d6ba4416/41598_2023_39661_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f746/10415327/6973f559d292/41598_2023_39661_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f746/10415327/d216dd68ec62/41598_2023_39661_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f746/10415327/a9077f1d6c2f/41598_2023_39661_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f746/10415327/50cdcc4a0632/41598_2023_39661_Fig5_HTML.jpg

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