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Lehnen M, Ebert BE, Blank LM. A comprehensive evaluation of constraining amino acid biosynthesis in compartmented models for metabolic flux analysis. Metab Eng Commun 2017; 5:34-44. [PMID: 29188182 PMCID: PMC5699530 DOI: 10.1016/j.meteno.2017.07.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2017] [Revised: 05/29/2017] [Accepted: 07/05/2017] [Indexed: 11/18/2022] Open
Abstract
Recent advances in the availability and applicability of genetic tools for non-conventional yeasts have raised high hopes regarding the industrial applications of such yeasts; however, quantitative physiological data on these yeasts, including intracellular flux distributions, are scarce and have rarely aided in the development of novel yeast applications. The compartmentation of eukaryotic cells adds to model complexity. Model constraints are ideally based on biochemical evidence, which is rarely available for non-conventional yeast and eukaryotic cells. A small-scale model for 13C-based metabolic flux analysis of central yeast carbon metabolism was developed that is universally valid and does not depend on localization information regarding amino acid anabolism. The variable compartmental origin of traced metabolites is a feature that allows application of the model to yeasts with uncertain genomic and transcriptional backgrounds. The presented test case includes the baker's yeast Saccharomyces cerevisiae and the methylotrophic yeast Hansenula polymorpha. Highly similar flux solutions were computed using either a model with undefined pathway localization or a model with constraints based on curated (S. cerevisiae) or computationally predicted (H. polymorpha) localization information, while false solutions were found with incorrect localization constraints. These results indicate a potentially adverse effect of universally assuming Saccharomyces-like constraints on amino acid biosynthesis for non-conventional yeasts and verify the validity of neglecting compartmentation constraints using a small-scale metabolic model. The model was specifically designed to investigate the intracellular metabolism of wild-type yeasts under various growth conditions but is also expected to be useful for computing fluxes of other eukaryotic cells. Compartmentation influences computed intracellular fluxes. Improper localization constraints potentially produce false flux solutions. Minimal compartmentation constraints result in high-quality flux computations.
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Key Words
- 13C-metabolic flux analysis
- ACCOA, acetyl-CoA
- Compartmented metabolism
- Eukaryotes
- GLY, glycine
- H. polymorpha
- ILE, isoleucine
- LEU, leucine
- MDV, mass distribution vector
- MFA, metabolic flux analysis
- Non-conventional yeast
- PYR, pyruvate
- S. cerevisiae
- SER, serine
- Sd, flux solution from a fully constrained model
- Sdmin, flux solution from a model with minimal constraints
- Sf, flux solution from an unconstrained model
- THR, threonine
- TP, TargetP 1.1
- WP, WoLF PSORT
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Affiliation(s)
- Mathias Lehnen
- iAMB - Institute of Applied Microbiology, ABBt - Aachen Biology and Biotechnology, RWTH Aachen University, Worringer Weg 1, D-52074 Aachen, Germany
| | - Birgitta E Ebert
- iAMB - Institute of Applied Microbiology, ABBt - Aachen Biology and Biotechnology, RWTH Aachen University, Worringer Weg 1, D-52074 Aachen, Germany
| | - Lars M Blank
- iAMB - Institute of Applied Microbiology, ABBt - Aachen Biology and Biotechnology, RWTH Aachen University, Worringer Weg 1, D-52074 Aachen, Germany
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Marzan LW, Barua R, Akter Y, Arifuzzaman M, Islam MR, Shimizu K. A single metabolite production by Escherichia coli BW25113 and its pflA.cra mutant cultivated under microaerobic conditions using glycerol or glucose as a carbon source. J Genet Eng Biotechnol 2017; 15:161-168. [PMID: 30647652 PMCID: PMC6296642 DOI: 10.1016/j.jgeb.2017.01.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2016] [Revised: 12/08/2016] [Accepted: 01/04/2017] [Indexed: 10/31/2022]
Abstract
Abundant, low prices and a highly reduced nature make glycerol to be an ideal feedstock for the production of reduced biochemicals and biofuels. Escherichia coli has been paid much attention as the platform of microbial cell factories due to its high growth rate (giving higher metabolite production rate) and the capability of utilizing a wide range of carbon sources. However, one of the drawbacks of using E. coli as a platform is its mixed metabolite formation under anaerobic conditions. In the present study, it was shown that ethanol could be exclusively produced from glycerol by the wild type E. coli, while d-lactic acid could be exclusively produced from glucose by pflA.cra mutant, where the glucose uptake rate could be increased by this mutant as compared to the wild type strain. It was also shown that the growth rate is significantly reduced in pflA.cra mutant for the case of using glycerol as a carbon source due to redox imbalance. The metabolic regulation mechanisms behind the fermentation characteristic were clarified to some extent.
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Key Words
- ATP, adenosine triphosphate
- AcCoA, acetyl-coenzyme A
- Biofuel
- DCW, dry cell weight
- DHA, dihydroxyacetone
- Escherichia coli
- Ethanol production
- GAPDH, -glyceraldehyde-3-phosphate dehydrogenase
- GDH, glutamate dehydrogenase
- Glucose
- Glycerol
- KH2PO4, potassium dihydrogen phosphate
- KOH, potassium hydroxide
- LB, Luria Bertani
- LDH, lactate dehydrogenase
- M9, type of minimal media
- MgSO4, magnesium sulfate
- NAD+, nicotinamide adenine dinucleotide
- NADH, reduced form of nicotinamide adenine dinucleotide
- Na2HPO4, sodium phosphate
- NaCl, sodium chloride
- NaOH, sodium hydroxide
- OAA, oxaloacetic Acid
- OD, optical density
- PEP, phosphoenol pyruvate
- PEP, phosphoenolpyruvic acid
- PTS, phospho-transferase system
- PYR, pyruvate
- Pfl, pyruvate formatelyase
- TCA, tri-carboxylic acid
- UV, ultra violet
- cAMP, cyclic adenosine monophosphate
- cAMP-Crp, cAMP receptor protein
- pflA.cra mutant
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Affiliation(s)
- Lolo Wal Marzan
- Department of Genetic Engineering and Biotechnology, Faculty of Biological Sciences, University of Chittagong, Chittagong - 4331, Bangladesh
| | - Rinty Barua
- Department of Genetic Engineering and Biotechnology, Faculty of Biological Sciences, University of Chittagong, Chittagong - 4331, Bangladesh
| | - Yasmin Akter
- Department of Genetic Engineering and Biotechnology, Faculty of Biological Sciences, University of Chittagong, Chittagong - 4331, Bangladesh
| | - Md. Arifuzzaman
- Department of Biochemistry and Biotechnology, University of Science and Technology Chittagong, Bangladesh
| | - Md. Rafiqul Islam
- Department of Genetic Engineering and Biotechnology, Faculty of Biological Sciences, University of Chittagong, Chittagong - 4331, Bangladesh
| | - Kazuyuki Shimizu
- Department of Bioscience & Bioinformatics, Kyushu Institute of Technology, Iizuka, Fukuoka 820-8502, Japan
- Institute of Advanced Bioscience, Keio University, Tsuruoka, Yamagata 997-0017, Japan
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Suarez-Mendez C, Hanemaaijer M, ten Pierick A, Wolters J, Heijnen J, Wahl S. Interaction of storage carbohydrates and other cyclic fluxes with central metabolism: A quantitative approach by non-stationary 13C metabolic flux analysis. Metab Eng Commun 2016; 3:52-63. [PMID: 29468113 PMCID: PMC5779734 DOI: 10.1016/j.meteno.2016.01.001] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2015] [Revised: 11/30/2015] [Accepted: 01/19/2016] [Indexed: 12/11/2022] Open
Abstract
13C labeling experiments in aerobic glucose limited cultures of Saccharomyces cerevisiae at four different growth rates (0.054; 0.101, 0.207, 0.307 h-1) are used for calculating fluxes that include intracellular cycles (e.g., storage carbohydrate cycles, exchange fluxes with amino acids), which are rearranged depending on the growth rate. At low growth rates the impact of the storage carbohydrate recycle is relatively more significant than at high growth rates due to a higher concentration of these materials in the cell (up to 560-fold) and higher fluxes relative to the glucose uptake rate (up to 16%). Experimental observations suggest that glucose can be exported to the extracellular space, and that its source is related to storage carbohydrates, most likely via the export and subsequent extracellular breakdown of trehalose. This hypothesis is strongly supported by 13C-labeling experimental data, measured extracellular trehalose, and the corresponding flux estimations.
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Key Words
- 2PG, 2-phosphoglycerate
- 3PG, 3-phosphoglycerate
- 6PG, 6-phospho gluconate
- ACO, aconitate hydratase
- AK, adenylate kinase
- ALA, alanine
- ASP, aspartate
- Amino acids
- CoA, coenzyme-A
- DHAP, dihydroxy acetone phosphate
- DO, dissolved oxygen
- E4P, erythrose-4-phosphate
- ENO, phosphopyruvate hydratase
- F6P, fructose-6-phosphate
- FBA, fructose-bisphosphate aldolase
- FBP, fructose-1,6-bis-phosphate
- FMH, fumarate hydratase
- FUM, fumarate
- Flux estimation
- G1P, glucose-1-phosphate
- G6P, glucose-6-phosphate
- G6PDH, glucose-6-phosphate dehydrogenase
- GAP, glyceraldehyde-3-phosphate
- GAPDH&PGK, glyceraldehyde-3-phosphate dehydrogenase+phosphoglycerate kinase
- GLN, glutamine
- GLU, glutamate
- GLY, glycine
- GPM, phosphoglycerate mutase
- Glycogen
- IDMS, Isotope dilution mass spectrometry
- Iso-Cit, isocitrate
- LEU, leucine
- LYS, lysine
- MAL, malate
- METH, methionine
- Non-stationary 13C labeling
- OAA, oxaloacetate
- OUR, Oxygen uptake rate
- PEP, phospho-enol-pyruvate
- PFK, 6-phosphofructokinase
- PGI, glucose-6-phosphate isomerase
- PGM, phosphoglucomutase
- PMI, mannose-6-phosphate isomerase
- PPP, pentose phosphate pathway
- PRO, proline
- PYK, pyruvate kinase
- PYR, pyruvate
- RPE, ribulose-phosphate 3-epimerase
- RPI, ribose-5-phosphate isomerase
- Rib5P, ribose-5-phosphate
- Ribu5P, ribulose-5-phosphate
- S7P, sedoheptulose-7-phosphate
- SER, serine
- SUC, succinate
- T6P, trehalose-6-phosphate
- TCA, tricarboxylic acid cycle.
- TPP, trehalose- phosphatase
- TPS, alpha,alpha-trehalose-phosphate synthase
- Trehalose
- UDP, uridine-5-diphosphate
- UDPG, UDP-glucose
- UTP, uridine-5-triphosphate
- X5P, xylulose-5-phosphate
- α-KG, oxoglutarate
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Affiliation(s)
- C.A. Suarez-Mendez
- Department of Biotechnology, Delft University of Technology, Julianalaan 67 – 2628 BC Delft, The Netherlands
- Kluyver Centre for Genomics of Industrial Fermentation, P.O. Box 5057, 2600 GA Delft, The Netherlands
| | - M. Hanemaaijer
- Department of Biotechnology, Delft University of Technology, Julianalaan 67 – 2628 BC Delft, The Netherlands
| | - Angela ten Pierick
- Department of Biotechnology, Delft University of Technology, Julianalaan 67 – 2628 BC Delft, The Netherlands
| | - J.C. Wolters
- Department of Analytical Biochemistry, University of Groningen, Antonius Deusinglaan 1, 9713 AV Groningen, The Netherlands
| | - J.J. Heijnen
- Department of Biotechnology, Delft University of Technology, Julianalaan 67 – 2628 BC Delft, The Netherlands
- Kluyver Centre for Genomics of Industrial Fermentation, P.O. Box 5057, 2600 GA Delft, The Netherlands
| | - S.A. Wahl
- Department of Biotechnology, Delft University of Technology, Julianalaan 67 – 2628 BC Delft, The Netherlands
- Kluyver Centre for Genomics of Industrial Fermentation, P.O. Box 5057, 2600 GA Delft, The Netherlands
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