Swedish NMR Centre at the University of Gothenburg, P.O. Box 465, SE-405 30 Gothenburg, Sweden.
Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, P.O. Box 459, SE-405 30 Gothenburg, Sweden.
Anal Chem. 2024 Aug 13;96(32):13078-13085. doi: 10.1021/acs.analchem.4c01532. Epub 2024 Jul 31.
Urine is an equally attractive biofluid for metabolomics analysis, as it is a challenging matrix analytically. Accurate urine metabolite concentration estimates by Nuclear Magnetic Resonance (NMR) are hampered by pH and ionic strength differences between samples, resulting in large peak shift variability. Here we show that calculating the spectra of original samples from mixtures of samples using linear algebra reduces the shift problems and makes various error estimates possible. Since the use of two-dimensional (2D) NMR to confirm metabolite annotations is effectively impossible to employ on every sample of large sample sets, stabilization of metabolite peak positions increases the confidence in identifying metabolites, avoiding the pitfall of oranges-to-apples comparisons.
尿液也是代谢组学分析中一种极具吸引力的生物流体，因为它在分析上是一种具有挑战性的基质。核磁共振（NMR）对尿液代谢物浓度的准确估计受到样品之间 pH 值和离子强度差异的阻碍，导致峰位移动的巨大变异性。在这里，我们表明，使用线性代数从样品混合物中计算原始样品的光谱可以减少峰位移问题，并使各种误差估计成为可能。由于二维（2D）NMR 用于确认代谢物注释的方法在大型样本集中的每个样本上实际上都无法采用，因此稳定代谢物峰位可以提高鉴定代谢物的可信度，避免将橘化为苹果的比较陷阱。
