کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
1177060 961937 2009 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Numerical bias estimation for mass spectrometric mass isotopomer analysis
موضوعات مرتبط
مهندسی و علوم پایه شیمی شیمی آنالیزی یا شیمی تجزیه
پیش نمایش صفحه اول مقاله
Numerical bias estimation for mass spectrometric mass isotopomer analysis
چکیده انگلیسی

Mass spectrometric (MS) isotopomer analysis has become a standard tool for investigating biological systems using stable isotopes. In particular, metabolic flux analysis uses mass isotopomers of metabolic products typically formed from 13C-labeled substrates to quantitate intracellular pathway fluxes. In the current work, we describe a model-driven method of numerical bias estimation regarding MS isotopomer analysis. Correct bias estimation is crucial for measuring statistical qualities of measurements and obtaining reliable fluxes. The model we developed for bias estimation corrects a priori unknown systematic errors unique for each individual mass isotopomer peak. For validation, we carried out both computational simulations and experimental measurements. From stochastic simulations, it was observed that carbon mass isotopomer distributions and measurement noise can be determined much more precisely only if signals are corrected for possible systematic errors. By removing the estimated background signals, the residuals resulting from experimental measurement and model expectation became consistent with normality, experimental variability was reduced, and data consistency was improved. The method is useful for obtaining systematic error-free data from 13C tracer experiments and can also be extended to other stable isotopes. As a result, the reliability of metabolic fluxes that are typically computed from mass isotopomer measurements is increased.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Analytical Biochemistry - Volume 388, Issue 2, 15 May 2009, Pages 192–203
نویسندگان
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