Laboratory of Natural Compounds Chemistry and Bioanalytics, Core Facility Center "Arktika", M.V. Lomonosov Northern (Arctic) Federal University, Northern Dvina Emb. 17, 163002, Arkhangelsk, Russia.
Anal Bioanal Chem. 2023 Jul;415(17):3525-3534. doi: 10.1007/s00216-023-04742-3. Epub 2023 May 24.
Lignin is the second most abundant biopolymer in nature and a promising renewable feedstock for the production of aromatic compounds, composite materials, sorbents, etc. Being a complex mixture of oligomeric molecules with an irregular structure, natural lignin is an extremely difficult object to study. Its molecular level characterization requires advanced analytical techniques among which atmospheric pressure photoionization Orbitrap mass spectrometry holds a promising place. In the present study, Kendrick mass defect (KMD) analysis was proposed to facilitate the visualization and interpretation of Orbitrap mass spectra of the biopolymer on an example of Siberian pine dioxane lignin preparation. The use of the typical guaiacylpropane structure CHO as a Kendrick base unit made it possible to effectively identify oligomer series with different polymerization degrees and structurally related compounds, as well as to reliably determine the elemental compositions and structures of oligomers with high molecular weights (> 1 kDa). For the first time, KMD analysis was applied to the interpretation of the complex tandem mass spectra of lignin oligomers, rapid discrimination of the product ion series, and the establishment of the main collision-induced dissociation pathways. It was demonstrated that especially promising was the use of KMD filtering in the study of broadband fragmentation tandem mass spectra, which allows for the structural characterization of all oligomers with a particular degree of polymerization.
木质素是自然界中第二丰富的生物聚合物,是生产芳香族化合物、复合材料、吸附剂等的有前途的可再生原料。作为一种具有不规则结构的低聚物分子的复杂混合物,天然木质素是一个极难研究的对象。其分子水平的表征需要先进的分析技术,其中常压光电离轨道阱质谱法具有广阔的应用前景。在本研究中,提出了 Kendrick 质量亏损 (KMD) 分析,以促进西伯利亚松二氧六环木质素制备的生物聚合物的轨道阱质谱可视化和解释。使用典型的愈创木基丙烷结构 CHO 作为 Kendrick 基准单元,使得能够有效地识别具有不同聚合度的低聚物系列和结构相关的化合物,以及可靠地确定具有高分子量 (>1 kDa) 的低聚物的元素组成和结构。首次将 KMD 分析应用于木质素低聚物复杂串联质谱的解释,快速区分产物离子系列,并建立主要的碰撞诱导解离途径。结果表明,KMD 过滤在宽带碎裂串联质谱研究中具有广阔的应用前景,它允许对特定聚合度的所有低聚物进行结构表征。