Modeling isotopomer distributions in biochemical networks using isotopomer mapping matrices

Schmidt, Karsten; Carlsen, Morten; Nielsen, Jens; Villadsen, John

doi:10.1002/(sici)1097-0290(19970920)55:6<831::aid-bit2>3.0.co;2-h

Cited by 291 publications

(159 citation statements)

References 18 publications

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“…In practice, isotope labelling in metabolic balancing is often performed by growing a culture on 13 Cglucose and making time-dependent measurements of the flux of incorporated 13 C by NMR or (less frequently) MS (Szyperski, 1998). If NMR fine structures of 13 C-enriched metabolic intermediates are studied, the analysis of the position of the incorporated 13 C atoms enables mathematical modelling of the contribution of different pathways to the metabolic cycles (Schmidt et al, 1997;Klapa et al, 1999;Parket al, 1999). All these authors emphasized that NMR analyses proved to be more powerful compared to MSbased approaches, since it is much more difficult (and sometimes impossible) to obtain positional information of the incorporated 13 C atoms from interpretation of mass spectral fragmentation.…”

Section: Modelling Based On Metabolic Flux Measurementsmentioning

confidence: 99%

Metabolomics — the link between genotypes and phenotypes

Fiehn

2002

Functional Genomics

1,608

1,337

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Metabolites are the end products of cellular regulatory processes, and their levels can be regarded as the ultimate response of biological systems to genetic or environmental changes. In parallel to the terms 'transcriptome' and 'proteome', the set of metabolites synthesized by a biological system constitute its 'metabolome'. Yet, unlike other functional genomics approaches, the unbiased simultaneous identification and quantification of plant metabolomes has been largely neglected. Until recently, most analyses were restricted to profiling selected classes of compounds, or to fingerprinting metabolic changes without sufficient analytical resolution to determine metabolite levels and identities individually. As a prerequisite for metabolomic analysis, careful consideration of the methods employed for tissue extraction, sample preparation, data acquisition, and data mining must be taken. In this review, the differences among metabolite target analysis, metabolite profiling, and metabolic fingerprinting are clarified, and terms are defined. Current approaches are examined, and potential applications are summarized with a special emphasis on data mining and mathematical modelling of metabolism.

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Section: Modelling Based On Metabolic Flux Measurementsmentioning

confidence: 99%

Metabolomics — the link between genotypes and phenotypes

Fiehn

2002

Functional Genomics

1,608

1,337

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“…In actual enzymatic reaction systems, isotope abundances in products would be changed when compared to that of the substrate, as different carbon isotopes ( 12 C, 13 C) are associated with different catalytic efficiency. [23] This is referred to as the biological isotope fractionation effect, which would make the prediction of isotopomer equations [26,27] deviating from reality. A key feature of the carbon isotope fractionation by a particular enzyme is the fractionation associate with just the carbon bondmaking or -breaking step.…”

Section: Modelmentioning

confidence: 99%

Increasing the accuracy of mass isotopomer analysis through calibration curves constructed using biologically synthesized compounds

Shen

Xiong

et al. 2009

J. Mass Spectrom.

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Mass isotopomer analysis is an important technique to measure the production and flow of metabolites in living cells, tissues, and organisms. This technique depends on accurate quantifications of different mass isotopomers using mass spectrometry. Constructing calibration curves using standard samples is the most universal approach to convert raw mass spectrometry measurements into quantitative distributions of mass isotopomers. Calibration curve approach has been, however, of very limited use in comprehensive analyses of biological systems, mainly suffering from the lack of extensive range of standard samples with accurately known isotopic enrichment. Here, we present a biological method capable of synthesizing specifically labeled amino acids. These amino acids have well-determined and estimable mass isotopomer distributions and thus can serve as standard samples. In this method, the bacterium strain Methylobacterium salsuginis sp. nov. was cultivated with partially 13 C-labeled methanol as the only carbon source to produce 13 C-enriched compounds. We show that the mass isotopomer distributions of the various biosynthesized amino acids are well determined and can be reasonably estimated based on proposed binomial approximation if the labeling state of the biomass reached an isotopic steady state. The interference of intramolecular inhomogeneity of 13 C isotope abundances caused by biological isotope fractionation was eliminated by estimating average 13 C isotope abundance. Further, the predictions are tested experimentally by mass spectrometry (MS) spectra of the labeled glycine, alanine, and aspartic acid. Most of the error in mass spectrometry measurements was less than 0.74 mol% in the test case, significantly reduced as compared with uncalibrated results, and this error is expected to be less than 0.4 mol% in real experiment as revealed by theoretical analysis.

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“…Similar to metabolite balancing, balances can be set up around all isotopomers of a particular metabolite. Schmidt et al (Schmidt et al, 1997) described an elegant method for automatically generating the complete set of isotopomer balances using a matrix based method. More recently, Wiechert et al (Wiechert et al, 1999) introduced the concept of cumulative isotopomers (cumomers) and provided an efficient procedure for solving isotopomer models.…”

Section: Metabolic Flux Analysismentioning

confidence: 99%

Elementary metabolite units (EMU): A novel framework for modeling isotopic distributions

Antoniewicz¹,

Kelleher²,

Stephanopoulos³

2007

Metabolic Engineering

504

571

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Metabolic Flux Analysis (MFA) has emerged as a tool of great significance for metabolic engineering and mammalian physiology. An important limitation of MFA, as carried out via stable isotope labeling and GC/MS and NMR measurements, is the large number of isotopomer or cumomer equations that need to be solved, especially when multiple isotopic tracers are used for the labeling of the system. This restriction reduces the ability of MFA to fully utilize the power of multiple isotopic tracers in elucidating the physiology of realistic situations comprising complex bioreaction networks.Here, we present a novel framework for the modeling of isotopic labeling systems that significantly reduces the number of system variables without any loss of information. The elementary metabolite unit (EMU) framework is based on a highly efficient decomposition method that identifies the minimum amount of information needed to simulate isotopic labeling within a reaction network using the knowledge of atomic transitions occurring in the network reactions. The functional units generated by the decomposition algorithm, called elementary metabolite units, form the new basis for generating system equations that describe the relationship between fluxes and stable isotope measurements. Isotopomer abundances simulated using the EMU framework are identical to those obtained using the isotopomer and cumomer methods, however, require significantly less computation time. For a typical 13 C-labeling system the total number of equations that needs to be solved is reduced by one order-of-magnitude (100s EMUs vs. 1000s isotopomers). As such, the EMU framework is most efficient for the analysis of labeling by multiple isotopic tracers. For example, analysis of the gluconeogenesis pathway with 2 H, 13 C, and 18 O tracers requires only 354 EMUs, compared to more than 2 million isotopomers.

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Modeling isotopomer distributions in biochemical networks using isotopomer mapping matrices

Cited by 291 publications

References 18 publications

Metabolomics — the link between genotypes and phenotypes

Metabolomics — the link between genotypes and phenotypes

Increasing the accuracy of mass isotopomer analysis through calibration curves constructed using biologically synthesized compounds

Elementary metabolite units (EMU): A novel framework for modeling isotopic distributions

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