Tabatabaei Anaraki Maryam, Bermel Wolfgang, Dutta Majumdar Rudraksha, Soong Ronald, Simpson Myrna, Monnette Martine, Simpson André J
Environmental NMR Center, Department of Physical and Environmental Sciences, University of Toronto Scarborough, Military Trial, Toronto, ON 1265, Canada.
Bruker BioSpin GmbH, Silberstreifen 4, 76287 Rheinstetten, Germany.
Metabolites. 2019 Jan 16;9(1):16. doi: 10.3390/metabo9010016.
Nuclear magnetic resonance (NMR) spectroscopy is a powerful tool for the non-targeted metabolomics of intact biofluids and even living organisms. However, spectral overlap can limit the information that can be obtained from 1D 1H NMR. For example, magnetic susceptibility broadening in living organisms prevents any metabolic information being extracted from solution-state 1D 1H NMR. Conversely, the additional spectral dispersion afforded by 2D 1H-13C NMR allows a wide range of metabolites to be assigned in-vivo in 13C enriched organisms, as well as a greater depth of information for biofluids in general. As such, 2D 1H-13C NMR is becoming more and more popular for routine metabolic screening of very complex samples. Despite this, there are only a very limited number of statistical software packages that can handle 2D NMR datasets for chemometric analysis. In comparison, a wide range of commercial and free tools are available for analysis of 1D NMR datasets. Overtime, it is likely more software solutions will evolve that can handle 2D NMR directly. In the meantime, this application note offers a simple alternative solution that converts 2D 1H-13C Heteronuclear Single Quantum Correlation (HSQC) data into a 1D "spikelet" format that preserves not only the 2D spectral information, but also the 2D dispersion. The approach allows 2D NMR data to be converted into a standard 1D Bruker format that can be read by software packages that can only handle 1D NMR data. This application note uses data from Daphnia magna (water fleas) in-vivo to demonstrate how to generate and interpret the converted 1D spikelet data from 2D datasets, including the code to perform the conversion on Bruker spectrometers.
核磁共振(NMR)光谱学是用于完整生物流体甚至活生物体非靶向代谢组学研究的强大工具。然而,光谱重叠会限制从一维¹H NMR中获取的信息。例如,活生物体中的磁化率展宽会阻止从溶液态一维¹H NMR中提取任何代谢信息。相反,二维¹H-¹³C NMR提供的额外光谱分散使得在¹³C富集的生物体中能够在体内鉴定多种代谢物,并且总体上能为生物流体提供更深入的信息。因此,二维¹H-¹³C NMR在对非常复杂的样品进行常规代谢筛选中越来越受欢迎。尽管如此,能够处理二维NMR数据集进行化学计量分析的统计软件包数量非常有限。相比之下,有各种各样的商业和免费工具可用于分析一维NMR数据集。随着时间的推移,可能会出现更多能够直接处理二维NMR的软件解决方案。与此同时,本应用笔记提供了一种简单的替代解决方案,可将二维¹H-¹³C异核单量子相关(HSQC)数据转换为一维“小尖峰”格式,该格式不仅保留了二维光谱信息,还保留了二维分散信息。该方法可将二维NMR数据转换为标准的一维布鲁克格式,以便只能处理一维NMR数据的软件包读取。本应用笔记使用来自大型溞(水蚤)体内的数据来演示如何从二维数据集中生成和解释转换后的一维小尖峰数据,包括在布鲁克光谱仪上执行转换的代码。