Deconvolution of chemical mixtures with high complexity by NMR consensus trace clustering.
Deconvolution of chemical mixtures with high complexity by NMR consensus trace clustering.
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DOI：
10.1021/ac201464y
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发表时间：
2011-10-01
影响因子：
7.4
通讯作者：
Brueschweiler, Rafael
中科院分区：
文献类型：
--
作者：
Bingol, Kerem;Brueschweiler, Rafael
在化学、生物学和分子医学的许多领域中，复杂溶液状态混合物中分析物的鉴定和定量是关键步骤。核磁共振（NMR）是一个独特的工具，为这一目的提供了丰富的原子细节信息，而不需要大量的样品分馏。我们提出了三种新的多维NMR为基础的方法，是面向高复杂性的混合物在天然13 C丰度的分析，包括代谢组学中遇到的。所有三种方法的共同点是提取1D一致性光谱迹线或2D一致性平面，然后进行聚类的概念，这显著提高了识别受强光谱重叠影响的混合物组分的能力。该方法被证明为协方差1H-1H TOCSY和13 C-1H HSQC-TOCSY光谱和三秩相关光谱构建的13 C-1H HSQC和13 C-1H HSQC-TOCSY光谱对。所有的方法都是在应用于大肠杆菌提取物之前，首先对8种化合物代谢物模型混合物进行验证。coli细胞裂解液。
Identification and quantification of analytes in complex solution-state mixtures are critical procedures in many areas of Chemistry, Biology, and molecular Medicine. Nuclear magnetic resonance (NMR) is a unique tool for this purpose providing a wealth of atomic-detail information without requiring extensive fractionation of the samples. We present three new multidimensional-NMR based approaches that are geared toward the analysis of mixtures with high complexity at natural 13C abundance, including ones encountered in metabolomics. Common to all three approaches is the concept of the extraction of 1D consensus spectral traces or 2D consensus planes followed by clustering, which significantly improves the capability to identify mixture components that are affected by strong spectral overlap. The methods are demonstrated for covariance 1H-1H TOCSY and 13C-1H HSQC-TOCSY spectra and triple-rank correlation spectra constructed from pairs of 13C-1H HSQC and 13C-1H HSQC-TOCSY spectra. All methods are first demonstrated for an 8 compound metabolite model mixture before being applied to an extract from E. coli cell lysate.
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通过二维外推时间零（1）H-（13）C HSQC（HSQC（0））同时定量和鉴定代谢物混合物中的单个化学物质。
影响因子：
15
作者：
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通讯作者：
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影响因子：
2.2
作者：
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通讯作者：
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影响因子：
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作者：
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通讯作者：
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影响因子：
7.4
作者：
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通讯作者：
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影响因子：
2.7
作者：
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通讯作者：
Brueschweiler, Rafael