Statistical reconciliation of the elemental and molecular biomass composition of Saccharomyces cerevisiae
Statistical reconciliation of the elemental and molecular biomass composition of Saccharomyces cerevisiae
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DOI：
10.1002/bit.10054
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发表时间：
2001-11-05
影响因子：
3.8
通讯作者：
Heijnen, JJ
中科院分区：
文献类型：
--
作者：
Lange, HC;Heijnen, JJ
一个系统的数学程序能够检测测量中存在的严重误差，并通过使用最大似然原理协调连接的数据集，应用于酵母的生物量组成数据。分析了在葡萄糖限制条件下在恒温器中培养的酿酒酵母的生物量组成，分析了其元素组成和分子组成。两种描述最初在元素组成、分子量和还原度方面产生了相互矛盾的结果。应用基于元素平衡和平等关系的统计调和方法，获得一致的生物量组成。同时，在对账过程中，数据集的误差幅度显著减小。在统计分析的基础上，发现在生物量成分列表中包含约4%的水对于充分描述干生物量和匹配两组测量值至关重要。生物量的调和碳含量与分子分析结果相差4%。该方法通过提供基于所有可用数据的最佳估计，提高了其元素和分子生物量组成数据的准确性，从而为代谢通量分析和黑箱建模方法提供了改进和一致的基础。(C) 2001 John Wiley & Sons Inc。
A systematic mathematical procedure capable of detecting the presence of a gross error in the measurements and of reconciling connected data sets by using the maximum likelihood principle is applied to the biomass composition data of yeast. The biomass composition of Saccharomyces cerevisiae grown in a chemostat under glucose limitation was analyzed for its elemental and for its molecular composition. Both descriptions initially resulted in conflicting results concerning the elemental composition, molecular weight, and degrees of reduction. The application of the statistical reconciliation method, based on elemental balances and equality relations, is used to obtain a consistent biomass composition. Simultaneously, the error margins of the data sets are significantly reduced in the reconciliation process. On the basis of statistical analysis it was found that inclusion of about 4% water in the list of biomass constituents is essential to adequately describe the dry biomass and match both set of measurements. The reconciled carbon content of the biomass varied 4% from the ones obtained from the molecular analysis. The proposed method increases the accuracy of biomass composition data of its elements and its molecules by providing a best estimate based on all available data and thus provides an improved and consistent basis for metabolic flux analysis as well as black box modeling approaches. (C) 2001 John Wiley & Sons Inc.