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Determination of key enzymes for threonine synthesis through in vitro metabolic pathway analysis
BACKGROUND: The overexpression of key enzymes in a metabolic pathway is a frequently used genetic engineering strategy for strain improvement. Metabolic control analysis has been proposed to quantitatively determine key enzymes. However, the lack of quality data often makes it difficult to correctly...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4465468/ https://www.ncbi.nlm.nih.gov/pubmed/26070803 http://dx.doi.org/10.1186/s12934-015-0275-8 |
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author | Zhang, Yanfei Meng, Qinglong Ma, Hongwu Liu, Yongfei Cao, Guoqiang Zhang, Xiaoran Zheng, Ping Sun, Jibin Zhang, Dawei Jiang, Wenxia Ma, Yanhe |
author_facet | Zhang, Yanfei Meng, Qinglong Ma, Hongwu Liu, Yongfei Cao, Guoqiang Zhang, Xiaoran Zheng, Ping Sun, Jibin Zhang, Dawei Jiang, Wenxia Ma, Yanhe |
author_sort | Zhang, Yanfei |
collection | PubMed |
description | BACKGROUND: The overexpression of key enzymes in a metabolic pathway is a frequently used genetic engineering strategy for strain improvement. Metabolic control analysis has been proposed to quantitatively determine key enzymes. However, the lack of quality data often makes it difficult to correctly identify key enzymes through control analysis. Here, we proposed a method combining in vitro metabolic pathway analysis and proteomics measurement to find the key enzymes in threonine synthesis pathway. RESULTS: All enzymes in the threonine synthesis pathway were purified for the reconstruction and perturbation of the in vitro pathway. Label-free proteomics technology combined with APEX (absolute protein expression measurements) data analysis method were employed to determine the absolute enzyme concentrations in the crude enzyme extract obtained from a threonine production strain during the fastest threonine production period. The flux control coefficient of each enzyme in the pathway was then calculated by measuring the flux changes after titration of the corresponding enzyme. The isoenzyme LysC catalyzing the first step in the pathway has the largest flux control coefficient, and thus its concentration change has the biggest impact on pathway flux. To verify that the key enzyme identified through in vitro pathway analysis is also the key enzyme in vivo, we overexpressed LysC in the original threonine production strain. Fermentation results showed that the threonine concentration was increased 30% and the yield was increased 20%. CONCLUSIONS: In vitro metabolic pathways simulating in vivo cells can be built based on precise measurement of enzyme concentrations through proteomics technology and used for the determination of key enzymes through metabolic control analysis. This provides a new way to find gene overexpression targets for industrial strain improvement. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12934-015-0275-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4465468 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-44654682015-06-15 Determination of key enzymes for threonine synthesis through in vitro metabolic pathway analysis Zhang, Yanfei Meng, Qinglong Ma, Hongwu Liu, Yongfei Cao, Guoqiang Zhang, Xiaoran Zheng, Ping Sun, Jibin Zhang, Dawei Jiang, Wenxia Ma, Yanhe Microb Cell Fact Research BACKGROUND: The overexpression of key enzymes in a metabolic pathway is a frequently used genetic engineering strategy for strain improvement. Metabolic control analysis has been proposed to quantitatively determine key enzymes. However, the lack of quality data often makes it difficult to correctly identify key enzymes through control analysis. Here, we proposed a method combining in vitro metabolic pathway analysis and proteomics measurement to find the key enzymes in threonine synthesis pathway. RESULTS: All enzymes in the threonine synthesis pathway were purified for the reconstruction and perturbation of the in vitro pathway. Label-free proteomics technology combined with APEX (absolute protein expression measurements) data analysis method were employed to determine the absolute enzyme concentrations in the crude enzyme extract obtained from a threonine production strain during the fastest threonine production period. The flux control coefficient of each enzyme in the pathway was then calculated by measuring the flux changes after titration of the corresponding enzyme. The isoenzyme LysC catalyzing the first step in the pathway has the largest flux control coefficient, and thus its concentration change has the biggest impact on pathway flux. To verify that the key enzyme identified through in vitro pathway analysis is also the key enzyme in vivo, we overexpressed LysC in the original threonine production strain. Fermentation results showed that the threonine concentration was increased 30% and the yield was increased 20%. CONCLUSIONS: In vitro metabolic pathways simulating in vivo cells can be built based on precise measurement of enzyme concentrations through proteomics technology and used for the determination of key enzymes through metabolic control analysis. This provides a new way to find gene overexpression targets for industrial strain improvement. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12934-015-0275-8) contains supplementary material, which is available to authorized users. BioMed Central 2015-06-13 /pmc/articles/PMC4465468/ /pubmed/26070803 http://dx.doi.org/10.1186/s12934-015-0275-8 Text en © Zhang et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Zhang, Yanfei Meng, Qinglong Ma, Hongwu Liu, Yongfei Cao, Guoqiang Zhang, Xiaoran Zheng, Ping Sun, Jibin Zhang, Dawei Jiang, Wenxia Ma, Yanhe Determination of key enzymes for threonine synthesis through in vitro metabolic pathway analysis |
title | Determination of key enzymes for threonine synthesis through in vitro metabolic pathway analysis |
title_full | Determination of key enzymes for threonine synthesis through in vitro metabolic pathway analysis |
title_fullStr | Determination of key enzymes for threonine synthesis through in vitro metabolic pathway analysis |
title_full_unstemmed | Determination of key enzymes for threonine synthesis through in vitro metabolic pathway analysis |
title_short | Determination of key enzymes for threonine synthesis through in vitro metabolic pathway analysis |
title_sort | determination of key enzymes for threonine synthesis through in vitro metabolic pathway analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4465468/ https://www.ncbi.nlm.nih.gov/pubmed/26070803 http://dx.doi.org/10.1186/s12934-015-0275-8 |
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