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SOFAST-HMQC:代谢组学的高效工具。

SOFAST-HMQC-an efficient tool for metabolomics.

机构信息

Department of Systems Pharmacology and Systems and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, 421 Curie Blvd., Philadelphia, PA, 19104-6160, USA.

Indian Institute of Science, CV Raman Rd., Bangalore, Karnataka, 560012, India.

出版信息

Anal Bioanal Chem. 2017 Nov;409(29):6731-6738. doi: 10.1007/s00216-017-0676-0. Epub 2017 Oct 13.

Abstract

Nuclear magnetic resonance (NMR)-based metabolomics relies mostly on 1D NMR; however, the technique is limited by overlap of the signals from the metabolites. In order to circumvent this problem, 2D H-C correlation spectroscopy techniques are often used. However owing to poorer natural abundance and gyromagnetic ratio of C, the acquisition time for 2D H-C heteronuclear single quantum coherence spectroscopy (HSQC) is long. This makes it almost impossible to be used in high throughput study. We have reported the application of selective optimized flip angle short transient (SOFAST) technique coupled to heteronuclear multiple quantum correlation (HMQC) along with nonlinear sampling (NUS) in urine and serum samples. This technique takes sevenfold less experimental time than the conventional H-C HSQC experiment with retention of almost all molecular information. Hence, this can be used for high throughput study. Graphical abstract SOFAST-HMQC is a two-dimensional NMR technique that significantly decreases experimental time without loss of information. This technique is applied in complex biofluid samples that are used for high throughput metabolomics studies and shows promise of better information recovery than conventional two-dimensional NMR technique in shorter time.

摘要

基于核磁共振(NMR)的代谢组学主要依赖于 1D NMR;然而,该技术受到代谢物信号重叠的限制。为了规避这个问题,通常使用 2D H-C 相关光谱技术。然而,由于 C 的天然丰度和磁旋比较差,二维 H-C 异核单量子相干光谱(HSQC)的采集时间较长。这使得它几乎不可能用于高通量研究。我们已经报道了选择性优化翻转角短瞬(SOFAST)技术与异核多量子相关(HMQC)结合非线性采样(NUS)在尿液和血清样本中的应用。该技术比传统的 H-C HSQC 实验节省了七倍的实验时间,同时保留了几乎所有的分子信息。因此,它可以用于高通量研究。

图谱摘要 SOFAST-HMQC 是一种二维 NMR 技术,可在不损失信息的情况下显著缩短实验时间。该技术应用于复杂的生物流体样本中,用于高通量代谢组学研究,并有望在更短的时间内比传统的二维 NMR 技术获得更好的信息恢复。

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