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Integrating metabolomics into a systems biology framework to exploit metabolic complexity: strategies and applications in microorganisms

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Abstract

As an important functional genomic tool, metabolomics has been illustrated in detail in recent years, especially in plant science. However, the microbial category also has the potential to benefit from integration of metabolomics into system frameworks. In this article, we first examine the concepts and brief history of metabolomics. Next, we summarize metabolomic research processes and analytical platforms in strain improvements. The application cases of metabolomics in microorganisms answer what the metabolomics can do in strain improvements. The position of metabolomics in this systems biology framework and the real cases of integrating metabolomics into a system framework to explore the microbial metabolic complexity are also illustrated in this paper.

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References

  • Allen J, Davey HM, Broadhurst D, Heald JK, Rowland JJ, Oliver SG, Kell DB (2003) High-throughput characterisation of yeast mutants for functional genomics using metabolic footprinting. Nat Biotechnol 2:692

    Google Scholar 

  • Askenazi M, Driggers EM, Holtzman DA, Norman TC, Iverson S, Zimmer DP, Boers ME, Blomquist PR, Martinez EJ, Monreal AW, Feibelman TP, Mayorga ME, Maxon ME, Sykes K, Tobin JV, Cordero E, Salama SR, Trueheart J, Royer JC, Madden KT (2003) Integrating transcriptional and metabolite profiles to direct the engineering of lovastatin-producing fungal strains. Nat Biotechnol 21:150–156

    CAS  PubMed  Google Scholar 

  • Beckonert O, Bollard ME, Ebbels TMD, Keun HC, Antti H, Holmes E, Lindon JC, Nicholson JK (2003) NMR-based metabonomic toxicity classification: Hierarchical cluster analysis and k-nearest-neighbour approaches. Anal Chim Acta 490:3–15

    CAS  Google Scholar 

  • Bhattacharya M, Fuhrman L, Ingram A, Nickerson KW, Conway T (1995) Single-run separation and detection of multiple metabolic intermediates by anion-exchange high-performance liquid chromatography and application to cell pool extracts prepared from Escherichia coli. Anal Biochem 232:98–106

    CAS  PubMed  Google Scholar 

  • Buchholz A, Takors R, Wandrey C (2001) Quantification of intracellular metabolites in Escherichia coli K12 using liquid chromatographic-electrospray ionization tandem mass spectrometric techniques. Anal Biochem 295:129–137

    CAS  PubMed  Google Scholar 

  • Buchholz A, Hurlebaus J, Wandrey C, Takors R (2002) Metabolomics: quantification of intracellular metabolite dynamics. Biomol Eng 19:5–15

    CAS  PubMed  Google Scholar 

  • Buziol S, Bashir I, Baumeister A, ClaasenW, Noisommit-Rizzi N, Mailinger W, Reuss M (2002) New bioreactor-coupled rapid stopped-flow sampling technique for measurements of metabolite dynamics on a subsecond time scale. Biotechnol Bioeng 80:632–636

    CAS  PubMed  Google Scholar 

  • Castrillo JI, Hayes A, Mohammed S, Gaskell SJ, Oliver SG (2003) An optimized protocol for metabolome analysis in yeast using direct infusion electrospray mass spectrometry. Phytochemistry 62:929–937

    CAS  PubMed  Google Scholar 

  • Choi HK, Choi YH, Verberne M, Lefeber AWM, Erkelens C, Verpoorte R (2004) Metabolic fingerprinting of wild type and transgenic tobacco plants by 1H NMR and multivariate analysis technique. Phytochemistry 65:857–864

    CAS  PubMed  Google Scholar 

  • Dalluge JJ, Smith S, Sanchez-Riera F, McGuire C, Hobson R (2004) Potential of fermentation profiling via rapid measurement of amino acid metabolism by liquid chromatography–tandem mass spectrometry. J Chromatogr A 1043:3–7

    CAS  PubMed  Google Scholar 

  • Dandekar T, Moldenhauer F, Builk S, Bertram H, Schuster S (2003) A method for classifying metabolites in topological pathways analysis based on minimization of pathway number. Biosystems 70:255–270

    CAS  PubMed  Google Scholar 

  • de Koning W, van Dam K (1992) A method for the determination of changes of glycolytic metabolites in yeast on a subsecond time scale using extraction at neutral pH. Anal Biochem 204:118–123

    PubMed  Google Scholar 

  • de Nijs M, Larsen JS, Gams W, Rombouts FM, Wernars K, Thrane Ul, Notermans SHW (1997) Variations in random amplified polymorphic DNA patterns and secondary metabolite profiles within Fusarium species from cereals from various parts of the Netherlands. Food Microbiol 14:449–457

    Google Scholar 

  • Devantier R, Scheithauer B, Villas-Boas S, Pandersen S, Olsson L (2005) Metabolite profiling for analysis of yeast stress response during very high gravity ethanol fermentations. Biotechnol Bioeng 90:703–714

    CAS  PubMed  Google Scholar 

  • Dunn WB, Ellis DI (2005) Metabolomics: current analytical platforms and methodologies. Trends Analyt Chem 24:285–294

    CAS  Google Scholar 

  • Duran AL, Yang J, Wang LJ, Sumner LW (2003) Metabolomics spectral formatting, alignment and conversion tools (MSFACTs). Bioinformatics 19:2283–2293

    CAS  PubMed  Google Scholar 

  • Ellis DI, Broadhurst D, Kell DB, Rowland JJ, Goodacre R (2002) Rapid and quantitative detection of the microbial spoilage of meat by Fourier transform infrared spectroscopy and machine learning. Appl Environ Microbiol 68:2822–2828

    CAS  PubMed  PubMed Central  Google Scholar 

  • Elmroth I, Sundin P, Valeur A, Larsson L, Odham G (1992) Evaluation of chromatographic methods for the detection of bacterial contamination in biotechnical processes. J Microbiol Methods 15:215–228

    CAS  Google Scholar 

  • Even S, Lindley ND, Cocaign-Bousquet M (2003) Transcriptional, translational and metabolic regulation of glycolysis in Lactococcus lactis subsp. cremoris MG 1363 grown in continuous acidic cultures. Microbiology 149:1935–1944

    CAS  PubMed  Google Scholar 

  • Fell DA (2001) Beyond genomics. Trends Genet 17:680–682

    CAS  PubMed  Google Scholar 

  • Fiehn O (2001) Combining genomics, metabolome analysis and biochemical modeling to understand metabolic networks. Comp Funct Genomics 2:155–168

    CAS  PubMed  PubMed Central  Google Scholar 

  • Fiehn O (2002) Metabolomics—the link between genotypes and phenotypes. Plant Mol Biol 48:155–171

    CAS  PubMed  Google Scholar 

  • Fiehn O (2003) Metabolic networks of Cucurbita maximaphloem. Phytochemistry 62:875–886

    CAS  PubMed  Google Scholar 

  • Förster J, Gombert AK, Nielsen J (2002) A functional genomics approach using metabolomics and in silico pathway analysis. Biotechnol Bioeng 79:703–712

    PubMed  Google Scholar 

  • Gavaghan CL, Wilson ID, Nicholson JK (2002) Physiological variation in metabolic phenotyping and functional genomic studies: use of orthogonal signal correction and PLS-DA. FEBS Lett 530:191–196

    CAS  PubMed  Google Scholar 

  • Glanemann C, Loos A, Gorret N, Willis LB, O’Brien XM, Lessard PA, Sinskey AJ (2003) Disparity between changes in mRNA abundance and enzyme activity in Corynebacterium glutamicum: implications for DNA microarray analysis. Appl Microbiol Biotechnol 61:61–68

    CAS  PubMed  Google Scholar 

  • Gonzalez B, Francosis J, Renaud M (1997) A rapid and reliable method for metabolite extraction in yeast using boiling buffered ethanol. Yeast 13:1347–1355

    CAS  PubMed  Google Scholar 

  • Goodacre R, Timmins EM, Burton R, Kaderbhai N, Woodward AM, Kell DB, Rooney PJ (1998) Rapid identification of urinary tract infection bacteria using hyperspectral, whole organism fingerprinting and artificial neural networks. Microbiology 144:1157–1170

    CAS  PubMed  Google Scholar 

  • Goodacre R, Vaidyanathan S, Dunn WB, Harrigan GG, Kell DB (2004) Metabolomics by numbers: acquiring and understanding global metabolite data. Trends Biotechnol 22:245–252

    CAS  PubMed  Google Scholar 

  • Grivet JP, Delort AM, Portais JC (2003) NMR and microbiology: from physiology to metabolomics. Biochimie 85:823–840

    CAS  PubMed  Google Scholar 

  • Gygi SP, Rochon Y, Franza BR, Aebersold R (1999) Correlation between protein and mRNA abundance in yeast. Mol Cell Biol 19:1720–1730

    CAS  PubMed  PubMed Central  Google Scholar 

  • Hajjaj H, Blanc PJ, Goma G, Francois J (1998) Sampling techniques and comparative extraction procedures for quantitative determination of intra- and extracellular metabolites in filamentous fungi. FEMS Microbiol Lett 164:195–200

    CAS  Google Scholar 

  • Halket JM, Przyborowska A, Stein SE, Mallard WG, Down S, Chalmers RA (1999) Deconvolution gas chromatography/mass spectrometry of urinary organic acids—potential pattern recognition and automated identification of metabolic disorders. Rapid Commun Mass Spectrom 13:279–284

    CAS  PubMed  Google Scholar 

  • Hans MA, Heinzle E, Wittmann C (2001) Quantification of intracellular amino acids in batch cultures of Saccharomyces cerevisiae. Appl Microbiol Biotechnol 56:776–779

    CAS  PubMed  Google Scholar 

  • Hardy F, Fuell H (2003) Database, data modeling and schemas. In: Harrigan GG, Goodacre R (eds) Metabolic profiling: its role in biomarker discovery and gene function analysis. Kluwer, Boston

    Google Scholar 

  • Harrigan GG, Goodacre R (eds) (2003) Metabolic profiling: its role in biomarker discovery and gene function analysis. Kluwer, Boston

    Google Scholar 

  • Horning EC, Horning MG (1971) Human metabolic profiles obtained by GC and GC/MS. J Chromatogr Sci 9:129–140

    CAS  Google Scholar 

  • Jenkins H, Hardy N, Beckmann M, Draper J, Smith AR, Taylor J, Fiehn O, Goodacre R, Bino RJ, Hall R, Kopka J, Lane GA, Lange BM, Liu JR, Mendes P, Nikolau BJ, Oliver SG, Paton NW, Rhee S, Roessner-Tunali U, Saito K, Smedsgaard J, Sumner LW, Wang T, Walsh S, Wurtele ES, Kell DB (2004) A proposed framework for the description of plant metabolomics experiments and their results. Nat Biotechnol 22:1601–1606

    CAS  PubMed  Google Scholar 

  • Jensen NBS, Jokumsen KV, Villadsen J (1999) Determination of the phosporylated sugars of the Embden–Meyerhoff–Parnas pathway in Lactococcus lactis using a fast sampling technique and solid phase extraction. Biotechnol Bioeng 63:357–362

    Google Scholar 

  • Kaderbhai NN, Broadhurst DI, Ellis DI, Goodacre R, Kell DB (2003) Functional genomics via metabolic footprinting: monitoring metabolite secretion by Escherichia coli tryptophan metabolism mutants using FT-IR and direct injection electrospray mass spectrometry. Comp Funct Genomics 4:376–391

    CAS  PubMed  PubMed Central  Google Scholar 

  • Kell DB (2002) Metabolomics and machine learning: explanatory analysis of complex metabolome data using genetic programming to produce simple, robust rules. Mol Biol Rep 29:237–241

    CAS  PubMed  Google Scholar 

  • Kell DB, Darby RM, Draper J (2001) Genomic computing: explanatory analysis of plant expression profiling data using machine learning. Plant Physiol 126:943–951

    CAS  PubMed  PubMed Central  Google Scholar 

  • Krömer JO, Sorgenfrei O, Klopprogge K, Heinzle E, Wittmann C (2004) In-depth profiling of lysine-producing Corynebacterium glutamicum by combined analysis of the transcriptome, metabolome, and fluxome. J Bacteriol 186:1769–1784

    PubMed  PubMed Central  Google Scholar 

  • Krömer JO, Fritz M, Heinzle E, Wittmann C (2005) In vivo quantification of intracellular amino acids and intermediates of the methionine pathway in Corynebacterium glutamicum. Anal Biochem 340:171–173

    PubMed  Google Scholar 

  • Lafaye A, Labarre J, Tabet JC, Ezan E, Junot C (2005a) Liquid chromatography–mass spectrometry and 15N metabolic labeling for quantitative metabolic profiling. Anal Chem 77:2026–2033

    CAS  PubMed  Google Scholar 

  • Lafaye A, Junot C, Pereira Y, Lagniel G, Tabet JC, Ezan E, Labarre J (2005b) Combined proteome and metabolite-profiling analyses reveal surprising insights into yeast sulfur metabolism. J Biol Chem 280:24723–24730

    CAS  PubMed  Google Scholar 

  • Lange HC, Eman M, van Zuijlen G, Visser D, van Dam JC, Frank J, Teixeira de Mattos MJ, Heijnen JJ (2001) Improved rapid sampling for in vivo kinetics of intracellular metabolites in Saccharomyces cerevisiae. Biotechnol Bioeng 75:406–415

    CAS  PubMed  Google Scholar 

  • Lee PS, Shaw LB, Choe LH, Mehra A, Hatzimanikatis V, Lee KH (2003) Insights into the relation between mrna and protein expression patterns: II. Experimental observations in Escherichia coli. Biotechnol Bioeng 84:834–841

    CAS  PubMed  Google Scholar 

  • Lee SY, Lee DY, Kin TY (2005) Systems biotechnology for stain improvement. Trends Biotechnol 23:349–358

    CAS  PubMed  Google Scholar 

  • Letisse F, Lindley ND (2000) An intracellular metabolite quantification technique applicable to polysaccharide-producing bacteria. Biotechnol Lett 22:1673–1677

    CAS  Google Scholar 

  • Lim GB, Lee SY, Lee EK, Haam SJ, Kim WS (2002) Separation of astaxanthin from red yeast Phaffia rhodozyma by supercritical carbon dioxide extraction. Biochem Eng J 11:181–187

    CAS  Google Scholar 

  • Maharjan RP, Ferenci T (2003) Global metabolite analysis: the influence of extraction methodology on metabolome profiles of Escherichia coli. Anal Biochem 313:145–154

    PubMed  Google Scholar 

  • Mandal M, Boese B, Barrick JE, Winkler WC, Breaker RR (2003) Riboswitches control fundamental biochemical pathways in Bacillus subtilis and other bacteria. Cell 113:577–586

    CAS  PubMed  Google Scholar 

  • Markuszewski MJ, Britz-McKibbin P, Terabe S, Matsuda K, Nishioka T (2003) Determination of pyridine and adenine nucleotide metabolites in Bacillus subtilis cell extract by sweeping borate complexation capillary electrophoresis. J Chromatogr A 989:293–301

    CAS  PubMed  Google Scholar 

  • Martinez-Antonio A, Collado-Vides J (2003) Identifying global regulators in transcriptional regulatory networks in bacteria. Curr Opin Microbiol 6:482–489

    CAS  PubMed  Google Scholar 

  • Mashego MR, Wu L, Van Dam JC, Ras C, Vinke JL, Van Winden WA, Van Gulik WM, Heijnen JJ (2004) MIRACLE: mass isotopomer ratio analysis of U-13C-labeled extracts—a new method for accurate quantification of changes in concentrations of intracellular metabolites. Biotechnol Bioeng 85:620–628

    CAS  PubMed  Google Scholar 

  • Mashego MR, Jansen ML, Vinke JL, van Gulik WM, Heijnen JJ (2005) Changes in the metabolome of Saccharomyces cerevisiae associated with evolution in aerobic glucose-limited chemostats. FEMS Yeast Res 5:419–430

    CAS  PubMed  Google Scholar 

  • Nicholson JK, Wilson ID (2003) Understanding ‘global’ systems biology: Metabonomics and the continuum of metabolism. Nat Rev Drug Discov 2:668–676

    CAS  PubMed  Google Scholar 

  • Nicholson JK, Lindon JC, Holmes E (1999) ‘Metabonomics’: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29:1181–1189

    CAS  PubMed  Google Scholar 

  • Nielsen J, Oliver S (2005) The next wave in metabolome analysis. Trends Biotechnol 23:544–546

    CAS  PubMed  Google Scholar 

  • Nielsen KF, Smedsgaard J (2003) Fungal metabolite screening: database of 474 mycotoxins and fungal metabolites for dereplication by standardized liquid chromatography-UV-mass spectrometry methodology. J Chromatogr A 1002:111–136

    CAS  PubMed  Google Scholar 

  • Oldiges M, Takors R (2005) Applying metabolic profiling techniques for stimulus–response experiments: chances and pitfalls. Adv Biochem Eng Biotechnol 92:173–196

    CAS  PubMed  Google Scholar 

  • Oliver SG (2002) Functional genomics: lessons from yeast. Philos Trans R Soc Lond B Biol Sci 357:17–23

    CAS  PubMed  PubMed Central  Google Scholar 

  • Oliver SG, Winson MK, Kell DB, Baganz F (1998) Systematic functional analysis of the yeast genome. Trends Biotechnol 16:373–378

    CAS  PubMed  Google Scholar 

  • Panagiotou G, Villas-Boas SG, Christakopoulos P, Nielsen J, Olsson L (2005) Intracellular metabolite profiling of Fusarium oxysporum converting glucose to ethanol. J Biotechnol 115(4):425–434

    CAS  PubMed  Google Scholar 

  • Ott KH, Aranibar N, Singh B, Stockton GW (2003) Metabonomics classifies pathways affected by bioactive compounds. Artificial neural network classification of NMR spectra of plant extracts. Phytochemistry 62:971–985

    CAS  PubMed  Google Scholar 

  • Raamsdonk LM, Teusink B, Broadhurst D, Zhang N, Hayes A, Walsh MC, Berden JA, Brindle KM, Kell DB, Rowland JJ, Westerhoff HV, van Dam K, Oliver SG (2001) A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations. Nat Biotechnol 19:45–50

    CAS  PubMed  Google Scholar 

  • Roessner U, Luedemann A, Brust D, Fiehn O, Linke T, Willmitzer L, Fernie AR (2001) Metabolic profiling allows comprehensive phenotyping of genetically or environmentally modified plant systems. Plant Cell 13:11–29

    CAS  PubMed  PubMed Central  Google Scholar 

  • Ruijter GJG, Visser J (1996) Determination of intermediary metabolites in Aspergillus niger. J Microbiol Methods 25:295–302

    CAS  Google Scholar 

  • Schaefer U, Boos W, Takors R, Weuster-Botz D (1999) Automated sampling device for monitoring intracellular metabolite dynamics. Anal Biochem 270:88–96

    CAS  PubMed  Google Scholar 

  • Schauer N, Steinhauser D, Strelkov S, Schomburg D, Allison G, Moritz T, Lundgren K, Roessner-Tunali U, Forbes M, Willmitzer L (2005) GC-MS libraries for the rapid identification of metabolites in complex biological samples. FEBS Lett 579:1332–1337

    CAS  PubMed  Google Scholar 

  • Schmidt C (2004) Metabolomics takes its place as latest up-and-coming “omic” science. J Natl Cancer Inst 96:733–734

    Google Scholar 

  • Shurubor YI, Paolucci U, Krasnikov BF, Matson WR, Kristal BS (2005) Analytical precision, biological variation, and mathematical normalization in high data density metabolomics. Metabolomics 1:75–85

    CAS  Google Scholar 

  • Smedsgaard J (1997) Micro-scale extraction procedure for standardized screening of fungal metabolite production in cultures. J Chromatogr A 760:264–270

    CAS  PubMed  Google Scholar 

  • Smedsgaard J, Nielsen J (2005) Metabolite profiling of fungi and yeast: from phenotype to metabolome by MS and informatics. J Exp Bot 56(410):273–286

    CAS  PubMed  Google Scholar 

  • Smilde AK, Jansen JJ, Hoefsloot HC, Lamers RJ, van der Greef J, Timmerman MF (2005) ANOVA-simultaneous component analysis (ASCA): a new tool for analyzing designed metabolomics data. Bioinformatics 21:3043–3048

    CAS  PubMed  Google Scholar 

  • Smits HP, Cohen A, Buttler T, Nielsen J, Olsson L (1998) Cleanup and analysis of sugar phosphates in biological extracts by using solid-phase extraction and anion-exchange chromatography with pulsed amperometric detection. Anal Biochem 261:36–42

    CAS  PubMed  Google Scholar 

  • Soga T, Ueno Y, Naraoka H, Ohashi Y, Tomita M, Nishioka T (2002) Simultaneous determination of anionic intermediates for Bacillus subtilis metabolic pathways by capillary electrophoresis electrospray ionization mass spectrometry. Anal Chem 74:2233–2239

    CAS  PubMed  Google Scholar 

  • Soga T, Ohashi Y, Ueno Y, Naraoka H, Tomita M, Nishioka T (2003) Quantitative metabolome analysis using capillary electrophoresis mass spectrometry. J Proteome Res 2:488–494

    CAS  PubMed  Google Scholar 

  • Stein SE (1999) An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry. J Am Soc Mass Spectrom 10:770–781

    CAS  Google Scholar 

  • Stephanopoulos G, Apler H, Moxley J (2004) Exploiting biological complexity for strain improvement through systems biology. Nat Biotechnol 22:1261–1267

    CAS  PubMed  Google Scholar 

  • Streikov S, von Elstermann M, Schomburg D (2004) Comprehensive analysis of metabolites in Corynebacterium glutamicum by gas chromatography/mass spectrometry. Biol Chem 385:853–861

    Google Scholar 

  • Taylor J, King RD, Altmann T, Fiehn O (2002) Application of metabolomics to plant genotype discrimination using statistics and machine learning. Bioinformatics 18(Suppl 2):241–248

    Google Scholar 

  • Terabe S, Markuszewksi MJ, Inoue N, Otsuka K, Nishioka T (2001) Capillary electrophoretic techniques toward the metabolome analysis. Pure Appl Chem 73:1563–1572

    CAS  Google Scholar 

  • ter Kuile BH, Westerhoff HV (2001) Transcriptome meets metabolome: hierarchical and metabolic regulation of the glycolytic pathway. FEBS Lett 500:169–171

    PubMed  Google Scholar 

  • Theobald U, Mailinger W, Baltes M, Rizzi M, Reuss M (1997) In vivo analysis of metabolic dynamics in Saccharomyces cerevisiae: I. Experimental observations. Biotechnol Bioeng 55:305–316

    CAS  PubMed  Google Scholar 

  • Tweeddale H, Notley-McRobb L, Ferenci T (1998) Effect of slow growth on metabolism of Escherichia coli, as revealed by global metabolite pool (“Metabolome”) analysis. J Bacteriol 180:5109–5116

    CAS  PubMed  PubMed Central  Google Scholar 

  • Urbanczyk-Wochniak E, Luedemann A, Kopka J, Selbig J, Roessner-Tunali U, Willmitzer L, Fernie AR (2003). Parallel analysis of transcript and metabolic profiles: a new approach in systems biology. EMBO Rep 4:989–993

    CAS  PubMed  PubMed Central  Google Scholar 

  • Villas-Boas SG, Moxley JF, Kesson M, Stephanopoulos G, Nielsen J (2005) High-throughput metabolic state analysis: the missing link in integrated functional genomics of yeasts. Biochem J 388:669–677

    CAS  PubMed  PubMed Central  Google Scholar 

  • Visser D, van Zuylen GA, van Dam JC, Oudshoorn A, Eman MR, Ras C, van Gulik WM, Frank J, van Dedem GWK, Heijnen JJ (2002) Rapid sampling for analysis of in vivo kinetics using the BioScope: a system for continuous-pulse experiments. Biotechnol Bioeng 79:674–681

    CAS  PubMed  Google Scholar 

  • Wang W, Gao J, Chiao J, Zhao G, Jiang W (2004) A novel two-component system amrB–amkB involved in the regulation of central carbohydrate metabolism in rifamycin SV-producing Amycolatopsis mediterranei U32. Curr Microbiol 48:14–19

    CAS  PubMed  Google Scholar 

  • Werf MJ (2005) Towards replacing closed with open target selection approaches. Trends Biotechnol 23:11–16

    PubMed  Google Scholar 

  • Wilkinson SR, Young M, Goodacre R, Morris JG, Farrow JAE, Collins MD (1995) Phenotypic and genotypic differences between certain strains of Clostridium acetobutylicum. FEMS Microbiol Lett 125:199–204

    CAS  Google Scholar 

  • Wittmann C, Hans M, van Winden WA, Ras C, Heijnen JJ (2005) Dynamics of intracellular metabolites of glycolysis and TCA cycle during cell-cycle-related oscillation in Saccharomyces cerevisiae. Biotechnol Bioeng 89:839–847

    CAS  PubMed  Google Scholar 

  • Wu L, Mashego MR, van Dam JC, Proell AM, Vinke JL, Ras C, van Winden WA, van Gulik WM, Heijnen JJ (2005) Quantitative analysis of the microbial metabolome by isotope dilution mass spectrometry using uniformly 13C-labeled cell extracts as internal standards. Anal Biochem 336:164–171

    CAS  PubMed  Google Scholar 

  • Yang C, Hua Q, Baba T, Mori H, Shimizu K (2003) Analysis of Escherichia coli anaplerotic metabolism and its regulation mechanisms from the metabolic responses to altered dilution rates and phosphoenolpyruvate carboxykinase knockout. Biotechnol Bioeng 84:129–144

    PubMed  Google Scholar 

  • Zaldivar J, Borges A, Johansson B, Smits HP, Villas-Boas SG, Nielsen J, Olsson L (2002) Fermentation performance and intracellular metabolite patterns in laboratory and industrial xylose-fermenting Saccharomyces cerevisiae. Appl Microbiol Biotechnol 59:436–442

    CAS  PubMed  Google Scholar 

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Acknowledgements

The authors would like to thank National Nature Science Foundation of China (no.20536040) and State Key Development Program for Basic Research of China (no.2003CB716003) for financial support.

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Wang, Qz., Wu, Cy., Chen, T. et al. Integrating metabolomics into a systems biology framework to exploit metabolic complexity: strategies and applications in microorganisms. Appl Microbiol Biotechnol 70, 151–161 (2006). https://doi.org/10.1007/s00253-005-0277-2

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