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Poly-pathway model, a novel approach to simulate multiple metabolic states by reaction network-based model – Application to amino acid depletion in CHO cell culture. J Biotechnol 2017; 259:235-247. [DOI: 10.1016/j.jbiotec.2017.05.026] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2016] [Revised: 05/30/2017] [Accepted: 05/31/2017] [Indexed: 01/10/2023]
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Systematic engineering of TCA cycle for optimal production of a four-carbon platform chemical 4-hydroxybutyric acid in Escherichia coli. Metab Eng 2016; 38:264-273. [PMID: 27663752 DOI: 10.1016/j.ymben.2016.09.004] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2016] [Revised: 08/17/2016] [Accepted: 09/19/2016] [Indexed: 01/03/2023]
Abstract
To address climate change and environmental problems, it is becoming increasingly important to establish biorefineries for the production of chemicals from renewable non-food biomass. Here we report the development of Escherichia coli strains capable of overproducing a four-carbon platform chemical 4-hybroxybutyric acid (4-HB). Because 4-HB production is significantly affected by aeration level, genome-scale metabolic model-based engineering strategies were designed under aerobic and microaerobic conditions with emphasis on oxidative/reductive TCA branches and glyoxylate shunt. Several different metabolic engineering strategies were employed to develop strains suitable for fermentation both under aerobic and microaerobic conditions. It was found that microaerobic condition was more efficient than aerobic condition in achieving higher titer and productivity of 4-HB. The final engineered strain produced 103.4g/L of 4-HB by microaerobic fed-batch fermentation using glycerol. The aeration-dependent optimization strategy of TCA cycle will be useful for developing microbial strains producing other reduced derivative chemicals of TCA cycle intermediates.
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Wang Y, Li Q, Zheng P, Guo Y, Wang L, Zhang T, Sun J, Ma Y. Evolving the L-lysine high-producing strain of Escherichia coli using a newly developed high-throughput screening method. J Ind Microbiol Biotechnol 2016; 43:1227-35. [PMID: 27369765 PMCID: PMC4983297 DOI: 10.1007/s10295-016-1803-1] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2016] [Accepted: 06/22/2016] [Indexed: 12/30/2022]
Abstract
This study provided a new method which applied a selected L-lysine-inducible promoter for evolving lysine industrial strains of E. coli. According to the intracellular levels of the enhanced green fluorescent protein (EGFP) whose expression was controlled by the promoter, 186 strains were preliminarily selected using fluorescence-activated cell sorting from a 10-million-mutant library generated from a L-lysine high-producing E. coli strain. By subsequent multiple parameter evaluation of the 186 selected strains according to the concentration and the yield of lysine, the productivity per unit of cell in 96-deep-well blocks, two mutants MU-1 and MU-2 were obtained. They produced 136.51 ± 1.55 and 133.2 9 ± 1.42 g/L of lysine, respectively, in 5-L jars. Compared with the lysine concentration and the yield of the original strain, those of strain MU-1 improved by 21.00 and 9.05 %, respectively, and those of strain MU-2 improved by 18.14 and 10.41 %, respectively. The mutant selection and evaluation system newly established in our study should be useful for continuous improvement of the current E. coli strains in the lysine industry.
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Affiliation(s)
- Yan Wang
- College of Biotechnology, Tianjin University of Science and Technology, Tianjin, People's Republic of China.,Key Laboratory of Systems Microbial Biotechnology, Chinese Academy of Sciences, Tianjin, People's Republic of China.,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, People's Republic of China
| | - Qinggang Li
- Key Laboratory of Systems Microbial Biotechnology, Chinese Academy of Sciences, Tianjin, People's Republic of China.,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, People's Republic of China
| | - Ping Zheng
- Key Laboratory of Systems Microbial Biotechnology, Chinese Academy of Sciences, Tianjin, People's Republic of China. .,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, People's Republic of China.
| | - Yanmei Guo
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, People's Republic of China
| | - Lixian Wang
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, People's Republic of China
| | - Tongcun Zhang
- College of Biotechnology, Tianjin University of Science and Technology, Tianjin, People's Republic of China
| | - Jibin Sun
- Key Laboratory of Systems Microbial Biotechnology, Chinese Academy of Sciences, Tianjin, People's Republic of China. .,Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, People's Republic of China.
| | - Yanhe Ma
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, People's Republic of China
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Hagrot E, Oddsdóttir HÆ, Hosta JG, Jacobsen EW, Chotteau V. RETRACTED: Poly-pathway model, a novel approach to simulate multiple metabolic states by reaction network-based model – Application to amino acid depletion in CHO cell culture. J Biotechnol 2016; 228:37-49. [DOI: 10.1016/j.jbiotec.2016.03.015] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2015] [Revised: 03/03/2016] [Accepted: 03/09/2016] [Indexed: 12/20/2022]
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Yanagihara H, Wakaki H, Fujikoshi Y. A consistency property of the AIC for multivariate linear models when the dimension and the sample size are large. Electron J Stat 2015. [DOI: 10.1214/15-ejs1022] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Nishio Y, Ogishima S, Ichikawa M, Yamada Y, Usuda Y, Masuda T, Tanaka H. Analysis of L-glutamic acid fermentation by using a dynamic metabolic simulation model of Escherichia coli. BMC SYSTEMS BIOLOGY 2013; 7:92. [PMID: 24053676 PMCID: PMC3851129 DOI: 10.1186/1752-0509-7-92] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/27/2012] [Accepted: 09/13/2013] [Indexed: 01/17/2023]
Abstract
Background Understanding the process of amino acid fermentation as a comprehensive system is a challenging task. Previously, we developed a literature-based dynamic simulation model, which included transcriptional regulation, transcription, translation, and enzymatic reactions related to glycolysis, the pentose phosphate pathway, the tricarboxylic acid (TCA) cycle, and the anaplerotic pathway of Escherichia coli. During simulation, cell growth was defined such as to reproduce the experimental cell growth profile of fed-batch cultivation in jar fermenters. However, to confirm the biological appropriateness of our model, sensitivity analysis and experimental validation were required. Results We constructed an l-glutamic acid fermentation simulation model by removing sucAB, a gene encoding α-ketoglutarate dehydrogenase. We then performed systematic sensitivity analysis for l-glutamic acid production; the results of this process corresponded with previous experimental data regarding l-glutamic acid fermentation. Furthermore, it allowed us to predicted the possibility that accumulation of 3-phosphoglycerate in the cell would regulate the carbon flux into the TCA cycle and lead to an increase in the yield of l-glutamic acid via fermentation. We validated this hypothesis through a fermentation experiment involving a model l-glutamic acid-production strain, E. coli MG1655 ΔsucA in which the phosphoglycerate kinase gene had been amplified to cause accumulation of 3-phosphoglycerate. The observed increase in l-glutamic acid production verified the biologically meaningful predictive power of our dynamic metabolic simulation model. Conclusions In this study, dynamic simulation using a literature-based model was shown to be useful for elucidating the precise mechanisms involved in fermentation processes inside the cell. Further exhaustive sensitivity analysis will facilitate identification of novel factors involved in the metabolic regulation of amino acid fermentation.
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Affiliation(s)
- Yousuke Nishio
- Institute for Innovation, Ajinomoto Co, Inc,, Suzuki-cho 1-1, Kawasaki-ku, Kawasaki City, Kanagawa 210-8681, Japan.
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Ohno S, Furusawa C, Shimizu H. In silico screening of triple reaction knockout Escherichia coli strains for overproduction of useful metabolites. J Biosci Bioeng 2013; 115:221-8. [DOI: 10.1016/j.jbiosc.2012.09.004] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2012] [Revised: 09/03/2012] [Accepted: 09/05/2012] [Indexed: 01/20/2023]
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Bio-based production of the platform chemical 1,5-diaminopentane. Appl Microbiol Biotechnol 2011; 91:1287-96. [DOI: 10.1007/s00253-011-3457-2] [Citation(s) in RCA: 120] [Impact Index Per Article: 9.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2011] [Revised: 06/16/2011] [Accepted: 06/16/2011] [Indexed: 10/18/2022]
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Golomysova AN, Ivanov PS. Investigation of the anaerobic metabolism of Rhodobacter capsulatus by means of a flux model. Biophysics (Nagoya-shi) 2011. [DOI: 10.1134/s000635091101009x] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
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Likhoshvai VA, Khlebodarova TM, Ree MT, Kolchanov NA. Metabolic engineering in silico. APPL BIOCHEM MICRO+ 2010. [DOI: 10.1134/s0003683810070021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Carlson RP. Decomposition of complex microbial behaviors into resource-based stress responses. ACTA ACUST UNITED AC 2008; 25:90-7. [PMID: 19008248 DOI: 10.1093/bioinformatics/btn589] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
MOTIVATION Highly redundant metabolic networks and experimental data from cultures likely adapting simultaneously to multiple stresses can complicate the analysis of cellular behaviors. It is proposed that the explicit consideration of these factors is critical to understanding the competitive basis of microbial strategies. RESULTS Wide ranging, seemingly unrelated Escherichia coli physiological fluxes can be simply and accurately described as linear combinations of a few ecologically relevant stress adaptations. These strategies were identified by decomposing the central metabolism of E.coli into elementary modes (mathematically defined biochemical pathways) and assessing the resource investment cost-benefit properties for each pathway. The approach capitalizes on the inherent tradeoffs related to investing finite resources like nitrogen into different pathway enzymes when the pathways have varying metabolic efficiencies. The subset of ecologically competitive pathways represented 0.02% of the total permissible pathways. The biological relevance of the assembled strategies was tested against 10 000 randomly constructed pathway subsets. None of the randomly assembled collections were able to describe all of the considered experimental data as accurately as the cost-based subset. The results suggest these metabolic strategies are biologically significant. The current descriptions were compared with linear programming (LP)-based flux descriptions using the Euclidean distance metric. The current study's pathway subset described the experimental fluxes with better accuracy than the LP results without having to test multiple objective functions or constraints and while providing additional ecological insight into microbial behavior. The assembled pathways seem to represent a generalized set of strategies that can describe a wide range of microbial responses and hint at evolutionary processes where a handful of successful metabolic strategies are utilized simultaneously in different combinations to adapt to diverse conditions.
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Affiliation(s)
- Ross P Carlson
- Department of Chemical and Biological Engineering, Center for Biofilm Engineering and Thermal Biology Institute, Montana State University, Bozeman, MT 59717, USA.
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Llaneras F, Picó J. Stoichiometric modelling of cell metabolism. J Biosci Bioeng 2008; 105:1-11. [DOI: 10.1263/jbb.105.1] [Citation(s) in RCA: 95] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2007] [Accepted: 10/25/2007] [Indexed: 10/22/2022]
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Sahdev S, Khattar SK, Saini KS. Production of active eukaryotic proteins through bacterial expression systems: a review of the existing biotechnology strategies. Mol Cell Biochem 2007. [PMID: 17874175 DOI: 10.1007/s11010‐007‐9603‐6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Among the various expression systems employed for the over-production of proteins, bacteria still remains the favorite choice of a Protein Biochemist. However, even today, due to the lack of post-translational modification machinery in bacteria, recombinant eukaryotic protein production poses an immense challenge, which invariably leads to the production of biologically in-active protein in this host. A number of techniques are cited in the literature, which describe the conversion of inactive protein, expressed as an insoluble fraction, into a soluble and active form. Overall, we have divided these methods into three major groups: Group-I, where the factors influencing the formation of insoluble fraction are modified through a stringent control of the cellular milieu, thereby leading to the expression of recombinant protein as soluble moiety; Group-II, where protein is refolded from the inclusion bodies and thereby target protein modification is avoided; Group-III, where the target protein is engineered to achieve soluble expression through fusion protein technology. Even within the same family of proteins (e.g., tyrosine kinases), optimization of standard operating protocol (SOP) may still be required for each protein's over-production at a pilot-scale in Escherichia coli. However, once standardized, this procedure can be made amenable to the industrial production for that particular protein with minimum alterations.
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Affiliation(s)
- Sudhir Sahdev
- Department of Biotechnology & Bioinformatics, New Drug Discovery Research, Ranbaxy Research Laboratories-R&D-3, 20-Sector 18 Udyog Vihar, Gurgaon, India.
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Sahdev S, Khattar SK, Saini KS. Production of active eukaryotic proteins through bacterial expression systems: a review of the existing biotechnology strategies. Mol Cell Biochem 2007; 307:249-64. [PMID: 17874175 DOI: 10.1007/s11010-007-9603-6] [Citation(s) in RCA: 255] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2007] [Accepted: 08/27/2007] [Indexed: 12/13/2022]
Abstract
Among the various expression systems employed for the over-production of proteins, bacteria still remains the favorite choice of a Protein Biochemist. However, even today, due to the lack of post-translational modification machinery in bacteria, recombinant eukaryotic protein production poses an immense challenge, which invariably leads to the production of biologically in-active protein in this host. A number of techniques are cited in the literature, which describe the conversion of inactive protein, expressed as an insoluble fraction, into a soluble and active form. Overall, we have divided these methods into three major groups: Group-I, where the factors influencing the formation of insoluble fraction are modified through a stringent control of the cellular milieu, thereby leading to the expression of recombinant protein as soluble moiety; Group-II, where protein is refolded from the inclusion bodies and thereby target protein modification is avoided; Group-III, where the target protein is engineered to achieve soluble expression through fusion protein technology. Even within the same family of proteins (e.g., tyrosine kinases), optimization of standard operating protocol (SOP) may still be required for each protein's over-production at a pilot-scale in Escherichia coli. However, once standardized, this procedure can be made amenable to the industrial production for that particular protein with minimum alterations.
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Affiliation(s)
- Sudhir Sahdev
- Department of Biotechnology & Bioinformatics, New Drug Discovery Research, Ranbaxy Research Laboratories-R&D-3, 20-Sector 18 Udyog Vihar, Gurgaon, India.
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