鈥淎dd to Subtract鈥? A Simple Method to Remove Complex Background Signals from the 1H Nuclear Magnetic Resonance Spectra of Mixtures

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• 作者：Tao Ye ; Cheng Zheng ; Shucha Zhang ; G. A. Nagana Gowda ; Olga Vitek ; Daniel Raftery
• 刊名：Analytical Chemistry
• 出版年：2012
• 出版时间：January 17, 2012
• 年：2012
• 卷：84
• 期：2
• 页码：994-1002
• 全文大小：433K
• 年卷期：v.84,no.2(January 17, 2012)
• ISSN：1520-6882

文摘

Because of its highly reproducible and quantitative nature and minimal requirements for sample preparation or separation, ¹H nuclear magnetic resonance (NMR) spectroscopy is widely used for profiling small-molecule metabolites in biofluids. However ¹H NMR spectra contain many overlapped peaks. In particular, blood serum/plasma and diabetic urine samples contain high concentrations of glucose, which produce strong peaks between 3.2 ppm and 4.0 ppm. Signals from most metabolites in this region are overwhelmed by the glucose background signals and become invisible. We propose a simple 鈥淎dd to Subtract鈥?background subtraction method and show that it can reduce the glucose signals by 98% to allow retrieval of the hidden information. This procedure includes adding a small drop of concentrated glucose solution to the sample in the NMR tube, mixing, waiting for an equilibration time, and acquisition of a second spectrum. The glucose-free spectra are then generated by spectral subtraction using Bruker Topspin software. Subsequent multivariate statistical analysis can then be used to identify biomarker candidate signals for distinguishing different types of biological samples. The principle of this approach is generally applicable for all quantitative spectral data and should find utility in a variety of NMR-based mixture analyses as well as in metabolite profiling.