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Moore JC, Ramos I, Van Dien S. OUP accepted manuscript. J Ind Microbiol Biotechnol 2022; 49:6520437. [PMID: 35108392 PMCID: PMC9118995 DOI: 10.1093/jimb/kuab088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 12/20/2021] [Indexed: 11/13/2022]
Abstract
Optimization of metabolism to maximize production of bio-based chemicals must consistently balance cellular resources for biocatalyst growth and desired compound synthesis. This mini-review discusses synthetic biology strategies for dynamically controlling expression of genes to enable dual-phase fermentations in which growth and production are separated into dedicated phases. Emphasis is placed on practical examples which can be reliably scaled to commercial production with the current state of technology. Recent case studies are presented, and recommendations are provided for environmental signals and genetic control circuits.
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Affiliation(s)
| | - Itzel Ramos
- BP Biosciences Center, San Diego, CA 92121, USA
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Burk MJ, Van Dien S. Biotechnology for Chemical Production: Challenges and Opportunities. Trends Biotechnol 2016; 34:187-190. [DOI: 10.1016/j.tibtech.2015.10.007] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2015] [Revised: 10/08/2015] [Accepted: 10/22/2015] [Indexed: 01/19/2023]
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Andreozzi S, Chakrabarti A, Soh KC, Burgard A, Yang TH, Van Dien S, Miskovic L, Hatzimanikatis V. Identification of metabolic engineering targets for the enhancement of 1,4-butanediol production in recombinant E. coli using large-scale kinetic models. Metab Eng 2016; 35:148-159. [PMID: 26855240 DOI: 10.1016/j.ymben.2016.01.009] [Citation(s) in RCA: 59] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2015] [Revised: 12/16/2015] [Accepted: 01/29/2016] [Indexed: 11/24/2022]
Abstract
Rational metabolic engineering methods are increasingly employed in designing the commercially viable processes for the production of chemicals relevant to pharmaceutical, biotechnology, and food and beverage industries. With the growing availability of omics data and of methodologies capable to integrate the available data into models, mathematical modeling and computational analysis are becoming important in designing recombinant cellular organisms and optimizing cell performance with respect to desired criteria. In this contribution, we used the computational framework ORACLE (Optimization and Risk Analysis of Complex Living Entities) to analyze the physiology of recombinant Escherichia coli producing 1,4-butanediol (BDO) and to identify potential strategies for improved production of BDO. The framework allowed us to integrate data across multiple levels and to construct a population of large-scale kinetic models despite the lack of available information about kinetic properties of every enzyme in the metabolic pathways. We analyzed these models and we found that the enzymes that primarily control the fluxes leading to BDO production are part of central glycolysis, the lower branch of tricarboxylic acid (TCA) cycle and the novel BDO production route. Interestingly, among the enzymes between the glucose uptake and the BDO pathway, the enzymes belonging to the lower branch of TCA cycle have been identified as the most important for improving BDO production and yield. We also quantified the effects of changes of the target enzymes on other intracellular states like energy charge, cofactor levels, redox state, cellular growth, and byproduct formation. Independent earlier experiments on this strain confirmed that the computationally obtained conclusions are consistent with the experimentally tested designs, and the findings of the present studies can provide guidance for future work on strain improvement. Overall, these studies demonstrate the potential and effectiveness of ORACLE for the accelerated design of microbial cell factories.
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Affiliation(s)
- Stefano Andreozzi
- Laboratory of Computational Systems Biotechnology (LCSB), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
| | - Anirikh Chakrabarti
- Laboratory of Computational Systems Biotechnology (LCSB), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
| | - Keng Cher Soh
- Laboratory of Computational Systems Biotechnology (LCSB), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
| | | | | | | | - Ljubisa Miskovic
- Laboratory of Computational Systems Biotechnology (LCSB), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland
| | - Vassily Hatzimanikatis
- Laboratory of Computational Systems Biotechnology (LCSB), Swiss Federal Institute of Technology (EPFL), CH-1015 Lausanne, Switzerland; Swiss Institute of Bioinformatics, CH-1015 Lausanne, Switzerland.
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Van Dien S. From the first drop to the first truckload: commercialization of microbial processes for renewable chemicals. Curr Opin Biotechnol 2013; 24:1061-8. [PMID: 23537815 DOI: 10.1016/j.copbio.2013.03.002] [Citation(s) in RCA: 111] [Impact Index Per Article: 10.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2012] [Revised: 02/27/2013] [Accepted: 03/05/2013] [Indexed: 01/24/2023]
Abstract
Fermentation of carbohydrate substrates by microorganisms represents an attractive route for the manufacture of industrial chemicals from renewable resources. The technology to manipulate metabolism of bacteria and yeast, including the introduction of heterologous chemical pathways, has accelerated research in this field. However, the public literature contains very few examples of strains achieving the production metrics required for commercialization. This article presents the challenges in reaching commercial titer, yield, and productivity targets, along with other necessary strain and process characteristics. It then reviews various methods in systems biology, synthetic biology, enzyme engineering, and fermentation engineering which can be applied to strain improvement, and presents a strategy for using these tools to overcome the major hurdles on the path to commercialization.
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Affiliation(s)
- Stephen Van Dien
- Genomatica, Inc., 10520 Wateridge Circle, San Diego, CA 92121, United States.
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Yim H, Haselbeck R, Niu W, Pujol-Baxley C, Burgard A, Boldt J, Khandurina J, Trawick JD, Osterhout RE, Stephen R, Estadilla J, Teisan S, Schreyer HB, Andrae S, Yang TH, Lee SY, Burk MJ, Van Dien S. Metabolic engineering of Escherichia coli for direct production of 1,4-butanediol. Nat Chem Biol 2011; 7:445-52. [PMID: 21602812 DOI: 10.1038/nchembio.580] [Citation(s) in RCA: 710] [Impact Index Per Article: 54.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2010] [Accepted: 04/01/2011] [Indexed: 12/25/2022]
Abstract
1,4-Butanediol (BDO) is an important commodity chemical used to manufacture over 2.5 million tons annually of valuable polymers, and it is currently produced exclusively through feedstocks derived from oil and natural gas. Herein we report what are to our knowledge the first direct biocatalytic routes to BDO from renewable carbohydrate feedstocks, leading to a strain of Escherichia coli capable of producing 18 g l(-1) of this highly reduced, non-natural chemical. A pathway-identification algorithm elucidated multiple pathways for the biosynthesis of BDO from common metabolic intermediates. Guided by a genome-scale metabolic model, we engineered the E. coli host to enhance anaerobic operation of the oxidative tricarboxylic acid cycle, thereby generating reducing power to drive the BDO pathway. The organism produced BDO from glucose, xylose, sucrose and biomass-derived mixed sugar streams. This work demonstrates a systems-based metabolic engineering approach to strain design and development that can enable new bioprocesses for commodity chemicals that are not naturally produced by living cells.
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Affiliation(s)
- Harry Yim
- Genomatica, Inc., San Diego, California, USA
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Suthers PF, Burgard AP, Dasika MS, Nowroozi F, Van Dien S, Keasling JD, Maranas CD. Metabolic flux elucidation for large-scale models using 13C labeled isotopes. Metab Eng 2007; 9:387-405. [PMID: 17632026 PMCID: PMC2121621 DOI: 10.1016/j.ymben.2007.05.005] [Citation(s) in RCA: 72] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2006] [Revised: 04/23/2007] [Accepted: 05/23/2007] [Indexed: 10/23/2022]
Abstract
A key consideration in metabolic engineering is the determination of fluxes of the metabolites within the cell. This determination provides an unambiguous description of metabolism before and/or after engineering interventions. Here, we present a computational framework that combines a constraint-based modeling framework with isotopic label tracing on a large scale. When cells are fed a growth substrate with certain carbon positions labeled with (13)C, the distribution of this label in the intracellular metabolites can be calculated based on the known biochemistry of the participating pathways. Most labeling studies focus on skeletal representations of central metabolism and ignore many flux routes that could contribute to the observed isotopic labeling patterns. In contrast, our approach investigates the importance of carrying out isotopic labeling studies using a more comprehensive reaction network consisting of 350 fluxes and 184 metabolites in Escherichia coli including global metabolite balances on cofactors such as ATP, NADH, and NADPH. The proposed procedure is demonstrated on an E. coli strain engineered to produce amorphadiene, a precursor to the antimalarial drug artemisinin. The cells were grown in continuous culture on glucose containing 20% [U-(13)C]glucose; the measurements are made using GC-MS performed on 13 amino acids extracted from the cells. We identify flux distributions for which the calculated labeling patterns agree well with the measurements alluding to the accuracy of the network reconstruction. Furthermore, we explore the robustness of the flux calculations to variability in the experimental MS measurements, as well as highlight the key experimental measurements necessary for flux determination. Finally, we discuss the effect of reducing the model, as well as shed light onto the customization of the developed computational framework to other systems.
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Affiliation(s)
- Patrick F. Suthers
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802
| | | | - Madhukar S. Dasika
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802
| | - Farnaz Nowroozi
- Department of Chemical Engineering, University of California - Berkeley, Gilman Hall, Berkeley, CA 94720-1462
| | - Stephen Van Dien
- Genomatica, Inc, 5405 Morehouse Drive, Suite 210, San Diego, CA 92121
| | - Jay D. Keasling
- Department of Chemical Engineering, University of California - Berkeley, Gilman Hall, Berkeley, CA 94720-1462
| | - Costas D. Maranas
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802
- *Corresponding author Fax: 814-865-7846, e-mail address:
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Iwatani S, Van Dien S, Shimbo K, Kubota K, Kageyama N, Iwahata D, Miyano H, Hirayama K, Usuda Y, Shimizu K, Matsui K. Determination of metabolic flux changes during fed-batch cultivation from measurements of intracellular amino acids by LC-MS/MS. J Biotechnol 2006; 128:93-111. [PMID: 17055605 DOI: 10.1016/j.jbiotec.2006.09.004] [Citation(s) in RCA: 70] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2006] [Revised: 08/16/2006] [Accepted: 09/08/2006] [Indexed: 12/01/2022]
Abstract
Metabolic flux analysis using (13)C-labeled substrates is a well-developed method for investigating cellular behavior in steady-state culture condition. To extend its application, in particular to typical industrial conditions, such as batch and fed-batch cultivations, a novel method of (13)C metabolic flux analysis is proposed. An isotopomer balancing model was developed to elucidate flux distributions in the central metabolism and all amino acids synthetic pathways. A lysine-producing strain of Escherichia coli was cultivated by fed-batch mode in a growth medium containing yeast extract. Mass distribution data was derived from both intracellular free amino acids and proteinogenic amino acids measured by LC-MS/MS, and a correction parameter for the protein turnover effect on the mass distributions of intracellular amino acids was introduced. Metabolic flux distributions were determined in both exponential and stationary phases. Using this new approach, a culture phase-dependent metabolic shift was detected in the fed-batch culture. The approach presented here has great potential for investigating cellular behavior in industrial processes, independent of cultivation modes, metabolic phase and growth medium.
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Affiliation(s)
- Shintaro Iwatani
- Systems Biology Group, Institute of Life Sciences, Ajinomoto Co., Inc., Kawasaki 210-8681, Japan.
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