Centre for Systems Biology, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
Magn Reson Chem. 2009 Dec;47 Suppl 1:S86-95. doi: 10.1002/mrc.2501.
NMR spectroscopy remains one of the primary analytical approaches in metabolomics. Although 1D (1)H NMR spectroscopy is versatile, highly reproducible and currently the most widely used technique in NMR metabolomics, analysis of complex biological samples typically yields highly congested spectra with severely overlapping signals making unambiguous metabolite identification and quantification almost impossible. Consequently there is a growing use of 2D NMR methods, in particular (1)H J-resolved (JRES) spectroscopy, which spreads the high signal density into a second dimension. One potentially powerful method to deconvolute these JRES spectra, facilitating metabolite quantification, is via line-shape fitting. However, the mathematical functions describing the JRES NMR line-shape, in particular after applying apodisation functions and JRES specific processing, including tilting and symmetrisation, remain uncharacterised. Furthermore, possible quantitation errors arising from processing JRES spectra have not been evaluated, nor have the potentially adverse quantitative effects of overlapping dispersive tails of closely spaced signals in the 2D spectrum. Here we address these issues and evaluate the suitability of the JRES experiment for accurate complex mixture analysis. Specifically, we have examined changes in NMR line-shape and signal intensity after application of different apodisation functions (SINE and SEM) and JRES specific processing (tilting and symmetrising), comparing simulated and experimental data. We also report a significant quantitation error of up to 33%, dependent upon apodisation, due to overlap of the dispersive tails of closely spaced resonances. Finally, we have validated the use of these mathematical line-shape functions for metabolite quantitation of 2D JRES spectra, by comparison to corresponding 1D NMR datasets, using both gravimetrically-prepared chemically defined mixtures as well as biological tissue extracts.
NMR 光谱仍然是代谢组学中主要的分析方法之一。尽管 1D（1）H NMR 光谱具有多功能性、高度重现性，并且是目前代谢组学中应用最广泛的技术，但分析复杂的生物样本通常会产生高度拥挤的光谱，信号严重重叠，使得明确鉴定和定量代谢物几乎不可能。因此，二维 NMR 方法（特别是 1H J 分辨（JRES）光谱）的使用越来越多，它将高信号密度扩展到第二个维度。一种潜在的强大方法是通过谱线形状拟合来分解这些 JRES 光谱，从而促进代谢物定量。然而，描述 JRES NMR 谱线形状的数学函数，特别是在应用窗函数和 JRES 特定处理（包括倾斜和对称化）之后，仍然没有特征。此外，尚未评估处理 JRES 光谱可能产生的定量误差，也未评估二维谱中紧密间隔信号的弥散尾部重叠对定量的潜在不利影响。在这里，我们解决了这些问题，并评估了 JRES 实验在准确分析复杂混合物方面的适用性。具体来说，我们研究了不同窗函数（SINE 和 SEM）和 JRES 特定处理（倾斜和对称化）应用后 NMR 谱线形状和信号强度的变化，比较了模拟和实验数据。我们还报告了高达 33%的显著定量误差，这取决于窗函数，这是由于紧密间隔共振的弥散尾部重叠所致。最后，我们通过与相应的 1D NMR 数据集进行比较，使用重量法制备的化学定义混合物以及生物组织提取物，验证了这些数学谱线形状函数在 2D JRES 光谱代谢物定量中的应用。
