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用于绘制木质素解聚产物混合物中谱系联系的二维质量缺陷矩阵图。

Two-dimensional mass defect matrix plots for mapping genealogical links in mixtures of lignin depolymerisation products.

作者信息

Qi Yulin, Hempelmann Rolf, Volmer Dietrich A

机构信息

Institute of Bioanalytical Chemistry, Saarland University, Campus B2.2, 66123, Saarbrücken, Germany.

Institute of Physical Chemistry, Saarland University, Campus B 22, 66123, Saarbrücken, Germany.

出版信息

Anal Bioanal Chem. 2016 Jul;408(18):4835-43. doi: 10.1007/s00216-016-9598-5. Epub 2016 May 14.

Abstract

Lignin is the second most abundant natural biopolymer, and lignin wastes are therefore potentially significant sources for renewable chemicals such as fuel compounds, as alternatives to fossil fuels. Waste valorisation of lignin is currently limited to a few applications such as in the pulp industry, however, because of the lack of effective extraction and characterisation methods for the chemically highly complex mixtures after decomposition. Here, we have implemented high resolution mass spectrometry and developed two-dimensional mass defect matrix plots as a data visualisation tool, similar to the Kendrick mass defect plots implemented in fields such as petroleomics. These 2D matrix plots greatly simplified the highly convoluted lignin mass spectral data acquired from Fourier transform ion cyclotron resonance (FTICR)-mass spectrometry, and the derived metrics provided confident peak assignments and strongly improved structural mapping of lignin decomposition product series from the various linkages within the lignin polymer after electrochemical decomposition. Graphical Abstract 2D mass defect matrix plot for a lignin sample after decomposition.

摘要

木质素是第二丰富的天然生物聚合物,因此木质素废料有可能成为可再生化学品(如燃料化合物)的重要来源,以替代化石燃料。然而,由于缺乏对分解后化学性质高度复杂的混合物进行有效提取和表征的方法,目前木质素的废料增值仅限于少数应用,如在纸浆工业中。在此,我们采用了高分辨率质谱法,并开发了二维质量缺陷矩阵图作为数据可视化工具,类似于石油组学等领域中使用的肯德里克质量缺陷图。这些二维矩阵图极大地简化了从傅里叶变换离子回旋共振(FTICR)质谱仪获取的高度复杂的木质素质谱数据,并且所得到的指标提供了可靠的峰归属,并显著改进了电化学分解后木质素聚合物内各种键合产生的木质素分解产物系列的结构映射。图形摘要 分解后木质素样品的二维质量缺陷矩阵图。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8c1f/4914518/0bf11210263b/216_2016_9598_Figd_HTML.jpg

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