1
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Zhang R, Chen B, Zhang H, Tu L, Luan T. Stable isotope-based metabolic flux analysis: A robust tool for revealing toxicity pathways of emerging contaminants. Trends Analyt Chem 2023. [DOI: 10.1016/j.trac.2022.116909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
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2
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de Oliveira RD, Novello V, da Silva LF, Gomez JGC, Le Roux GAC. Glucose metabolism in Pseudomonas aeruginosa is cyclic when producing Polyhydroxyalkanoates and Rhamnolipids. J Biotechnol 2021; 342:54-63. [PMID: 34687809 DOI: 10.1016/j.jbiotec.2021.10.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 10/11/2021] [Accepted: 10/14/2021] [Indexed: 10/20/2022]
Abstract
Pseudomonas aeruginosa is an important chassis for production of polyhydroxyalkanoates (PHA) and rhamnolipids (RHL). Advances in the understanding of the biosynthesis metabolism of these biocompounds are crucial for increasing yield. 13C-Metabolic Flux Ratio Analysis (13C-MFA) is a technique to estimate in vivo metabolic fluxes ratios. PHA and RHL are essentially non-growth associated products of biotechnological interest and both contain hydroxyalkanoates (HAs), whose labeling patterns could be accessed by GC-MS. In this study, to reveal the relative contributions of the Entner-Doudoroff (ED) pathway and the non-oxidative Pentose Phosphate (PP) pathway to PHA and RHL production, 13C-MFA was performed in Pseudomonas aeruginosa LFM634 when supplied with labeled glucose. This bacterial strain lacks both functional EMP and the oxidative PP branch. Labeling patterns in HAs were measured. Experiments with [U-13C] glucose indicated a low flux though PP pathway. An optimal design of labeling experiment showed that [6-13C] glucose would be the best substrate to enable an estimation of the ED flux with high accuracy. Results of experiments performed with this isotope indicated that about two-thirds of glyceraldehyde 3-phosphate is recycled through a cyclic ED architecture, suggesting that P. aeruginosa utilizes that cycle to regulate the NADPH/Acetyl-CoA ratio for PHA and RHL biosynthesis.
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Affiliation(s)
| | - Vânia Novello
- Department of Microbiology, Institute of Biomedical Sciences, University of São Paulo, Brazil
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3
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Wiechert W, Nöh K. Quantitative Metabolic Flux Analysis Based on Isotope Labeling. Metab Eng 2021. [DOI: 10.1002/9783527823468.ch3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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4
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Beyß M, Parra-Peña VD, Ramirez-Malule H, Nöh K. Robustifying Experimental Tracer Design for 13C-Metabolic Flux Analysis. Front Bioeng Biotechnol 2021; 9:685323. [PMID: 34239861 PMCID: PMC8258161 DOI: 10.3389/fbioe.2021.685323] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 05/19/2021] [Indexed: 11/25/2022] Open
Abstract
13C metabolic flux analysis (MFA) has become an indispensable tool to measure metabolic reaction rates (fluxes) in living organisms, having an increasingly diverse range of applications. Here, the choice of the13C labeled tracer composition makes the difference between an information-rich experiment and an experiment with only limited insights. To improve the chances for an informative labeling experiment, optimal experimental design approaches have been devised for13C-MFA, all relying on some a priori knowledge about the actual fluxes. If such prior knowledge is unavailable, e.g., for research organisms and producer strains, existing methods are left with a chicken-and-egg problem. In this work, we present a general computational method, termed robustified experimental design (R-ED), to guide the decision making about suitable tracer choices when prior knowledge about the fluxes is lacking. Instead of focusing on one mixture, optimal for specific flux values, we pursue a sampling based approach and introduce a new design criterion, which characterizes the extent to which mixtures are informative in view of all possible flux values. The R-ED workflow enables the exploration of suitable tracer mixtures and provides full flexibility to trade off information and cost metrics. The potential of the R-ED workflow is showcased by applying the approach to the industrially relevant antibiotic producer Streptomyces clavuligerus, where we suggest informative, yet economic labeling strategies.
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Affiliation(s)
- Martin Beyß
- Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, Jülich, Germany.,Computational Systems Biotechnology (AVT.CSB), RWTH Aachen University, Aachen, Germany
| | | | | | - Katharina Nöh
- Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, Jülich, Germany
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5
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Introducing Parameter Clustering to the OED Procedure for Model Calibration of a Synthetic Inducible Promoter in S. cerevisiae. Processes (Basel) 2021. [DOI: 10.3390/pr9061053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
In recent years, synthetic gene circuits for adding new cell features have become one of the most powerful tools in biological and pharmaceutical research and development. However, because of the inherent non-linearity and noisy experimental data, the experiment-based model calibration of these synthetic parts is perceived as a laborious and time-consuming procedure. Although the optimal experimental design (OED) based on the Fisher information matrix (FIM) has been proved to be an effective means to improve the calibration efficiency, the required calculation increases dramatically with the model size (parameter number). To reduce the OED complexity without losing the calibration accuracy, this paper proposes two OED approaches with different parameter clustering methods and validates the accuracy of calibrated models with in-silico experiments. A model of an inducible synthetic promoter in S. cerevisiae is adopted for bench-marking. The comparison with the traditional off-line OED approach suggests that the OED approaches with both of the clustering methods significantly reduce the complexity of OED problems (for at least 49.0%), while slightly improving the calibration accuracy (11.8% and 19.6% lower estimation error in average for FIM-based and sensitivity-based approaches). This study implicates that for calibrating non-linear models of biological pathways, cluster-based OED could be a beneficial approach to improve the efficiency of optimal experimental design.
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6
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Otero-Muras I, Carbonell P. Automated engineering of synthetic metabolic pathways for efficient biomanufacturing. Metab Eng 2020; 63:61-80. [PMID: 33316374 DOI: 10.1016/j.ymben.2020.11.012] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Revised: 11/15/2020] [Accepted: 11/20/2020] [Indexed: 12/19/2022]
Abstract
Metabolic engineering involves the engineering and optimization of processes from single-cell to fermentation in order to increase production of valuable chemicals for health, food, energy, materials and others. A systems approach to metabolic engineering has gained traction in recent years thanks to advances in strain engineering, leading to an accelerated scaling from rapid prototyping to industrial production. Metabolic engineering is nowadays on track towards a truly manufacturing technology, with reduced times from conception to production enabled by automated protocols for DNA assembly of metabolic pathways in engineered producer strains. In this review, we discuss how the success of the metabolic engineering pipeline often relies on retrobiosynthetic protocols able to identify promising production routes and dynamic regulation strategies through automated biodesign algorithms, which are subsequently assembled as embedded integrated genetic circuits in the host strain. Those approaches are orchestrated by an experimental design strategy that provides optimal scheduling planning of the DNA assembly, rapid prototyping and, ultimately, brings forward an accelerated Design-Build-Test-Learn cycle and the overall optimization of the biomanufacturing process. Achieving such a vision will address the increasingly compelling demand in our society for delivering valuable biomolecules in an affordable, inclusive and sustainable bioeconomy.
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Affiliation(s)
- Irene Otero-Muras
- BioProcess Engineering Group, IIM-CSIC, Spanish National Research Council, Vigo, 36208, Spain.
| | - Pablo Carbonell
- Institute of Industrial Control Systems and Computing (ai2), Universitat Politècnica de València, 46022, Spain.
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7
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Optimal experiment design under parametric uncertainty: A comparison of a sensitivities based approach versus a polynomial chaos based stochastic approach. Chem Eng Sci 2020. [DOI: 10.1016/j.ces.2020.115651] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
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8
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Tsolis KC, Hamed MB, Simoens K, Koepff J, Busche T, Rückert C, Oldiges M, Kalinowski J, Anné J, Kormanec J, Bernaerts K, Karamanou S, Economou A. Secretome Dynamics in a Gram-Positive Bacterial Model. Mol Cell Proteomics 2019; 18:423-436. [PMID: 30498012 PMCID: PMC6398212 DOI: 10.1074/mcp.ra118.000899] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Revised: 11/21/2018] [Indexed: 12/11/2022] Open
Abstract
Protein secretion is a central biological process in all organisms. Most studies dissecting bacterial secretion mechanisms have focused on Gram-negative cell envelopes such as that of Escherichia coli However, proteomics analyses in Gram negatives is hampered by their outer membrane. Here we studied protein secretion in the Gram-positive bacterium Streptomyces lividans TK24, in which most of the secretome is released in the growth medium. We monitored changes of the secretome as a function of growth phase and medium. We determined distinct protein classes of "house-keeping" secreted proteins that do not change their appearance or abundance in the various media and growth phases. These comprise mainly enzymes involved in cell wall maintenance and basic transport. In addition, we detected significant abundance and content changes to a sub-set of the proteome, as a function of growth in the different media. These did not depend on the media being minimal or rich. Transcriptional regulation but not changes in export machinery components can explain some of these changes. However, additional downstream mechanisms must be important for selective secretome funneling. These observations lay the foundations of using S. lividans as a model organism to study how metabolism is linked to optimal secretion and help develop rational optimization of heterologous protein production.
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Affiliation(s)
- Konstantinos C Tsolis
- From the ‡KU Leuven, Rega Institute, Dpt of Microbiology and Immunology, Herestraat 49, B-3000 Leuven, Belgium
| | - Mohamed Belal Hamed
- From the ‡KU Leuven, Rega Institute, Dpt of Microbiology and Immunology, Herestraat 49, B-3000 Leuven, Belgium
- ‡‡Molecular Biology Dpt, National Research Centre, Dokki, Giza, Egypt
| | - Kenneth Simoens
- §KU Leuven, Bio- & chemical systems Technology, Reactor Engineering and Safety Section, Department of Chemical Engineering, Celestijnenlaan 200F, 3001 Leuven, Belgium
| | - Joachim Koepff
- ¶Forschungszentrum Jülich GmbH, Institute of Bio- and Geosciences, IBG-1: Biotechnology, Leo-Brandt-Straβe, 52428, Jülich, Germany
| | - Tobias Busche
- ‖Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany
- **Institute for Biology-Microbiology, Freie Universität Berlin, Berlin, Germany
| | - Christian Rückert
- ‖Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany
| | - Marco Oldiges
- ¶Forschungszentrum Jülich GmbH, Institute of Bio- and Geosciences, IBG-1: Biotechnology, Leo-Brandt-Straβe, 52428, Jülich, Germany
| | - Jörn Kalinowski
- ‖Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany
| | - Jozef Anné
- From the ‡KU Leuven, Rega Institute, Dpt of Microbiology and Immunology, Herestraat 49, B-3000 Leuven, Belgium
| | - Jan Kormanec
- §§Institute of Molecular Biology, Slovak Academy of Sciences, Dubravska cesta 21, 84551 Bratislava, Slovakia
| | - Kristel Bernaerts
- §KU Leuven, Bio- & chemical systems Technology, Reactor Engineering and Safety Section, Department of Chemical Engineering, Celestijnenlaan 200F, 3001 Leuven, Belgium
| | - Spyridoula Karamanou
- From the ‡KU Leuven, Rega Institute, Dpt of Microbiology and Immunology, Herestraat 49, B-3000 Leuven, Belgium
| | - Anastassios Economou
- From the ‡KU Leuven, Rega Institute, Dpt of Microbiology and Immunology, Herestraat 49, B-3000 Leuven, Belgium;
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9
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Daniels W, Bouvin J, Busche T, Rückert C, Simoens K, Karamanou S, Van Mellaert L, Friðjónsson ÓH, Nicolai B, Economou A, Kalinowski J, Anné J, Bernaerts K. Transcriptomic and fluxomic changes in Streptomyces lividans producing heterologous protein. Microb Cell Fact 2018; 17:198. [PMID: 30577858 PMCID: PMC6302529 DOI: 10.1186/s12934-018-1040-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2018] [Accepted: 11/26/2018] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND The Gram-positive Streptomyces lividans TK24 is an attractive host for heterologous protein production because of its high capability to secrete proteins-which favors correct folding and facilitates downstream processing-as well as its acceptance of methylated DNA and its low endogeneous protease activity. However, current inconsistencies in protein yields urge for a deeper understanding of the burden of heterologous protein production on the cell. In the current study, transcriptomics and [Formula: see text]-based fluxomics were exploited to uncover gene expression and metabolic flux changes associated with heterologous protein production. The Rhodothermus marinus thermostable cellulase A (CelA)-previously shown to be successfully overexpressed in S. lividans-was taken as an example protein. RESULTS RNA-seq and [Formula: see text]-based metabolic flux analysis were performed on a CelA-producing and an empty-plasmid strain under the same conditions. Differential gene expression, followed by cluster analysis based on co-expression and co-localization, identified transcriptomic responses related to secretion-induced stress and DNA damage. Furthermore, the OsdR regulon (previously associated with hypoxia, oxidative stress, intercellular signaling, and morphological development) was consistently upregulated in the CelA-producing strain and exhibited co-expression with isoenzymes from the pentose phosphate pathway linked to secondary metabolism. Increased expression of these isoenzymes matches to increased fluxes in the pentose phosphate pathway. Additionally, flux maps of the central carbon metabolism show increased flux through the tricarboxylic acid cycle in the CelA-producing strain. Redirection of fluxes in the CelA-producing strain leads to higher production of NADPH, which can only partly be attributed to increased secretion. CONCLUSIONS Transcriptomic and fluxomic changes uncover potential new leads for targeted strain improvement strategies which may ease the secretion stress and metabolic burden associated with heterologous protein synthesis and secretion, and may help create a more consistently performing S. lividans strain. Yet, links to secondary metabolism and redox balancing should be further investigated to fully understand the S. lividans metabolome under heterologous protein production.
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Affiliation(s)
- Wouter Daniels
- Department of Chemical Engineering, Bio- and Chemical Systems Technology, Reactor Engineering and Safety Section, KU Leuven, Celestijnenlaan 200F, box 2424, 3001, Leuven, Belgium
| | - Jeroen Bouvin
- Department of Chemical Engineering, Bio- and Chemical Systems Technology, Reactor Engineering and Safety Section, KU Leuven, Celestijnenlaan 200F, box 2424, 3001, Leuven, Belgium
| | - Tobias Busche
- Center for Biotechnology (CeBiTec), Bielefeld University, Universitätsstraße 27, 33615, Bielefeld, Germany
| | - Christian Rückert
- Center for Biotechnology (CeBiTec), Bielefeld University, Universitätsstraße 27, 33615, Bielefeld, Germany
| | - Kenneth Simoens
- Department of Chemical Engineering, Bio- and Chemical Systems Technology, Reactor Engineering and Safety Section, KU Leuven, Celestijnenlaan 200F, box 2424, 3001, Leuven, Belgium
| | - Spyridoula Karamanou
- Department of Microbiology and Immunology, Laboratory of Molecular Bacteriology, KU Leuven, Herestraat 49, box 1037, 3000, Leuven, Belgium
| | - Lieve Van Mellaert
- Department of Microbiology and Immunology, Laboratory of Molecular Bacteriology, KU Leuven, Herestraat 49, box 1037, 3000, Leuven, Belgium
| | | | - Bart Nicolai
- Division of Mechatronics, Biostatistics and Sensors (MeBioS), Department of Biosystems (BIOSYST), KU Leuven, Willem de Croylaan 42, 3001, Leuven, Belgium
| | - Anastassios Economou
- Department of Microbiology and Immunology, Laboratory of Molecular Bacteriology, KU Leuven, Herestraat 49, box 1037, 3000, Leuven, Belgium
| | - Jörn Kalinowski
- Center for Biotechnology (CeBiTec), Bielefeld University, Universitätsstraße 27, 33615, Bielefeld, Germany
| | - Jozef Anné
- Department of Microbiology and Immunology, Laboratory of Molecular Bacteriology, KU Leuven, Herestraat 49, box 1037, 3000, Leuven, Belgium
| | - Kristel Bernaerts
- Department of Chemical Engineering, Bio- and Chemical Systems Technology, Reactor Engineering and Safety Section, KU Leuven, Celestijnenlaan 200F, box 2424, 3001, Leuven, Belgium.
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10
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Nöh K, Niedenführ S, Beyß M, Wiechert W. A Pareto approach to resolve the conflict between information gain and experimental costs: Multiple-criteria design of carbon labeling experiments. PLoS Comput Biol 2018; 14:e1006533. [PMID: 30379837 PMCID: PMC6209137 DOI: 10.1371/journal.pcbi.1006533] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Accepted: 09/27/2018] [Indexed: 01/23/2023] Open
Abstract
Science revolves around the best way of conducting an experiment to obtain insightful results. Experiments with maximal information content can be found by computational experimental design (ED) strategies that identify optimal conditions under which to perform the experiment. Several criteria have been proposed to measure the information content, each emphasizing different aspects of the design goal, i.e., reduction of uncertainty. Where experiments are complex or expensive, second sight is at the budget governing the achievable amount of information. In this context, the design objectives cost and information gain are often incommensurable, though dependent. By casting the ED task into a multiple-criteria optimization problem, a set of trade-off designs is derived that approximates the Pareto-frontier which is instrumental for exploring preferable designs. In this work, we present a computational methodology for multiple-criteria ED of information-rich experiments that accounts for virtually any set of design criteria. The methodology is implemented for the case of 13C metabolic flux analysis (MFA), which is arguably the most expensive type among the ‘omics’ technologies, featuring dozens of design parameters (tracer composition, analytical platform, measurement selection etc.). Supported by an innovative visualization scheme, we demonstrate with two realistic showcases that the use of multiple criteria reveals deep insights into the conflicting interplay between information carriers and cost factors that are not amendable to single-objective ED. For instance, tandem mass spectrometry turns out as best-in-class with respect to information gain, while it delivers this information quality cheaper than the other, routinely applied analytical technologies. Therewith, our Pareto approach to ED offers the investigator great flexibilities in the conception phase of a study to balance costs and benefits. Designing experiments is obligatory in the biosciences to valorize their scientific outcome. When the experiments are expensive, unfortunately, in practice often the costs emerge to be showstoppers. In this situation the question arises: How to get the most out of the experiment for your invest in terms of time and money? We approach this question by formulating the design task as a multiple-criteria optimization problem. Its solution produces a set of Pareto-optimal design proposals that feature the trade-off between information gain, as measured by different metrics, and the costs. Then, exploration of the design proposals allows us to make the best decision on information-economic experiments under given circumstances. Implemented in the field of isotope-based metabolic flux analysis, practical application of the Pareto approach provides detailed insight into the tight interplay of plenty of information carriers and cost factors. Supported by an innovative tailored visual representation scheme, the investigator is enabled to explore the options before conducting the experiment. With a practical showcase at hand, our computational study highlights the benefits of incorporating multiple information criteria apart from the costs, balancing the shortcomings of conventional single-objective experimental design strategies.
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Affiliation(s)
- Katharina Nöh
- Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, Jülich, Germany
- * E-mail:
| | - Sebastian Niedenführ
- Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Martin Beyß
- Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, Jülich, Germany
| | - Wolfgang Wiechert
- Institute of Bio- and Geosciences, IBG-1: Biotechnology, Forschungszentrum Jülich GmbH, Jülich, Germany
- Computational Systems Biotechnology, RWTH Aachen University, Aachen, Germany
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11
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Uncertainty in optimal experiment design: comparing an online versus offline approaches. ACTA ACUST UNITED AC 2018. [DOI: 10.1016/j.ifacol.2018.04.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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12
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Dai Z, Locasale JW. Understanding metabolism with flux analysis: From theory to application. Metab Eng 2017; 43:94-102. [PMID: 27667771 PMCID: PMC5362364 DOI: 10.1016/j.ymben.2016.09.005] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2016] [Revised: 09/06/2016] [Accepted: 09/19/2016] [Indexed: 12/27/2022]
Abstract
Quantitative and qualitative knowledge of metabolic rates (i.e. fluxes) over a metabolic network and in specific cellular compartments gives insights into the regulation of metabolism and helps to understand the contribution of metabolic alterations to pathology. In this review we introduce methodology to resolve metabolic fluxes from stable isotope labeling and relevant techniques in model development, model simplification, flux uncertainty analysis and experimental design that together is termed metabolic flux analysis. Finally we discuss applications using metabolic flux analysis to elucidate mechanisms pertinent to tumor cell metabolism. We hope that this review gives the readers a brief introduction of how flux analysis is conducted, how technical issues related to it are addressed, and how its application has contributed to our knowledge of tumor cell metabolism.
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Affiliation(s)
- Ziwei Dai
- Department of Pharmacology and Cancer Biology, Duke University School of Medicine, Durham, NC 27710, USA
| | - Jason W Locasale
- Department of Pharmacology and Cancer Biology, Duke University School of Medicine, Durham, NC 27710, USA.
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Theorell A, Leweke S, Wiechert W, Nöh K. To be certain about the uncertainty: Bayesian statistics for 13 C metabolic flux analysis. Biotechnol Bioeng 2017; 114:2668-2684. [PMID: 28695999 DOI: 10.1002/bit.26379] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2017] [Accepted: 07/02/2017] [Indexed: 12/18/2022]
Abstract
13 C Metabolic Fluxes Analysis (13 C MFA) remains to be the most powerful approach to determine intracellular metabolic reaction rates. Decisions on strain engineering and experimentation heavily rely upon the certainty with which these fluxes are estimated. For uncertainty quantification, the vast majority of 13 C MFA studies relies on confidence intervals from the paradigm of Frequentist statistics. However, it is well known that the confidence intervals for a given experimental outcome are not uniquely defined. As a result, confidence intervals produced by different methods can be different, but nevertheless equally valid. This is of high relevance to 13 C MFA, since practitioners regularly use three different approximate approaches for calculating confidence intervals. By means of a computational study with a realistic model of the central carbon metabolism of E. coli, we provide strong evidence that confidence intervals used in the field depend strongly on the technique with which they were calculated and, thus, their use leads to misinterpretation of the flux uncertainty. In order to provide a better alternative to confidence intervals in 13 C MFA, we demonstrate that credible intervals from the paradigm of Bayesian statistics give more reliable flux uncertainty quantifications which can be readily computed with high accuracy using Markov chain Monte Carlo. In addition, the widely applied chi-square test, as a means of testing whether the model reproduces the data, is examined closer.
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Affiliation(s)
- Axel Theorell
- Forschungszentrum Jülich GmbH, Institute of Bio- und Geosciences, IBG-1: Biotechnology, Jülich, Germany
| | - Samuel Leweke
- Forschungszentrum Jülich GmbH, Institute of Bio- und Geosciences, IBG-1: Biotechnology, Jülich, Germany
| | - Wolfgang Wiechert
- Forschungszentrum Jülich GmbH, Institute of Bio- und Geosciences, IBG-1: Biotechnology, Jülich, Germany.,Computational Systems Biotechnology (AVT.CSB), RWTH Aachen University, Aachen, Germany
| | - Katharina Nöh
- Forschungszentrum Jülich GmbH, Institute of Bio- und Geosciences, IBG-1: Biotechnology, Jülich, Germany
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