| In recent years, the concept and theory of systems biology have been undergoing a major development in accordance with its wide application in various areas. The core of this newly established discipline is the information integration across different "omes". Among these omes, the fluxome has played an increasingly important role in linking omes of different level.Investigation of fluxome gives birth to the fluxomics which aims at quantitatively analyzing the direction and quantity of metabolic flux. Insights acquired from fluxomics would be of significant biological importance for depicting the physiological characteristic of cell as well as assessing the influence of the genetic and environmental manipulations on cell.The primary technique for fluxomics is metabolic flux analysis, which consists of stoichiometry metabolic flux analysis and 13C metabolic flux analysis (13C MFA). 13C MFA has been the research hotspot of metabolic engineering internationally due to its accuracy and applicability. However, there is no domestic doctorate thesis concerning about 13C metabolic flux analysis.This PhD thesis consists of two parts. The first part details the fundamental principle of 13C MFA and the implementation of its experimental platform. The second part describes a method to improve the measurement accuracy of 13C mass isotopomer analysis.Chapter 1 illustrates the fundamental principle of 13C MFA.The first part of chapter 1 describes the fundamental principle of 13C MFA.13C MFA introduces partial 13C labeling in cultivation substrate.13C will distribute among intermediates and metabolites and results in different isotopomer distribution. Starting from the concept of isotopomer, the mass balance relationship could be extended as isotopomers balance relationship which relates the metabolic flux with the isotopomer distribution of intermediates and metabolites. Isotopomers balance relationship is a complicated square equation of multiple variables. Based on these equations, the metabolic flux quantity could be deduced from the measured isotopomer information through evolution algorithm based parameter optimization. Afterwards, we could construct the theoretical measurement space and quantify the confidence interval of estimated flux value by Monte Carlo sampling.Chapter 2 focuses on the introduction and implementation of experimental technique for 13C MFA.The first part of chapter 2 describes experimental techniques which are necessary for 13C MFA.The 13C labeling technique is the basis for 13C MFA. To estimate the intracellular metabolic flux value, information of isotopomer distribution as well as the information of the metabolites efflux must be obtained. The information of specific isotopomers can be acquired through NMR measurements. J-resolved HSQC could be used to analyze the isotopomers containing directly connected carbon-carbon bond. The mass isotopomer distribution could be quantified by MS measurement. The metabolites efflux is the other kind of information necessary for 13C MFA. Efflux value of some certain metabolites could be determined by analysis of the accumulated amount and the cellular composition of biomass. Besides, quantitatively analyzing the residual concentration could determine efflux value of other intermediates and metabolites. At the last stage, the objectivity for parameter optimization and confidence interval estimation method are presented.The second part of chapter 2 is exhaustive experimental protocol of 13C MFA in continuous cultivation. That is the first implementation of 13C MFA platform in USTC.Chapter 2 describes the second part of our work that is the improvement of measurement accuracy of 13C mass isotopomer analysis hence the flux accuracy of 13C MFA. The first part of chapter 2 introduces concisely the principle and process of MS measurement. Then the basic structural and functional units of MS instrument are discussed. These units includes samples introduction, ionization source, mass separation and signal detection. Additionally, the derivatization methods, especially the TMBDMS-derivatization for GC-MS, are illustrated detailedly. Then a mathematical framework, correction matrix, is described to address the mass shift effect introduced by heavy isotopes in nonskeleton carbon.The second part of chapter 2 firstly describes in particular the basic assumption for 13C mass isotopomer analysis by MS measurement. Then we re-state this assumption in a mathematical framework. Based upon this mathematical frame, we can easily classify and depict the previous methods of improving the MS measurement accuracy. These methods utilize linear extrapolation, nonlinear relationship or theoretical correction. These methods indeed produce accurate results than simple measurement. However, they have a shared shortcoming that they are instrument specificThe second part describes how to increase the accuracy of mass iotopomer analysis through calibration curves constructed using biologically synthesized compounds. Using the compounds with known isotopomer distribution as the standard sample one could plot calibration curve for any instrument. Thus, the correction method relying on calibration curve would be a general method that is universally applicable to MS measurements. The bacterium strain Methylobacterium salsuginis sp. nov. is cultivated with partially 13C labeled methanol as the only carbon source to produce 13C enriched compounds. The resulting product isotopomers obey binomial distribution. We introduces a new variable to replace the mass isotopomer distribution as optimization objectivity in order to circumvent the calibration for MID. Moreover, posterior measurement of average 13C abundance minimized the interference of intramolecular inhomogeneity of 13C isotope abundances caused by biological isotope fractionation.The third part deals with the experimental implementation of the theory raised in the second part. This includes experimental protocol, numeric modeling, results and discussion. The absolute uncertainty after correction by calibration curve has decreased to 0.9mol%, remarkably reduced compared to the uncalibrated results. If the average 13C abundance is measured by gas chromatography-combustion-isotope ratio mass spectrometry, the expected error would decrease to 0.4mol%.Ground on this 13C MFA platform, Rui Bin and I performed a global investigation of central carbon metabolism in response to superoxide stress in E.coli. Please refer to Rui Bin's PhD thesis for detailed description.Besides, we had performed an investigation titled "serial metabolic flux analysis revealed a dose-dependent response of E.coli metabolism to oxidative stress".
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