Morrison Lindsay J, Parker W Ryan, Holden Dustin D, Henderson Jeremy C, Boll Joseph M, Trent M Stephen, Brodbelt Jennifer S
Department of Chemistry, University of Texas , Austin, Texas 78712, United States.
Department of Infectious Diseases, University of Georgia , Athens, Georgia 30602, United States.
Anal Chem. 2016 Feb 2;88(3):1812-20. doi: 10.1021/acs.analchem.5b04098. Epub 2016 Jan 15.
The lipid A domain of the endotoxic lipopolysaccharide layer of Gram-negative bacteria is comprised of a diglucosamine backbone to which a variable number of variable length fatty acyl chains are anchored. Traditional characterization of these tails and their linkages by nuclear magnetic resonance (NMR) or mass spectrometry is time-consuming and necessitates databases of pre-existing structures for structural assignment. Here, we introduce an automated de novo approach for characterization of lipid A structures that is completely database-independent. A hierarchical decision-tree MS(n) method is used in conjunction with a hybrid activation technique, UVPDCID, to acquire characteristic fragmentation patterns of lipid A variants from a number of Gram-negative bacteria. Structural assignments are derived from integration of key features from three to five spectra and automated interpretation is achieved in minutes without the need for pre-existing information or candidate structures. The utility of this strategy is demonstrated for a mixture of lipid A structures from an enzymatically modified E. coli lipid A variant. A total of 27 lipid A structures were discovered, many of which were isomeric, showcasing the need for a rapid de novo approach to lipid A characterization.
革兰氏阴性菌内毒素脂多糖层的脂质A结构域由一个二葡糖胺主链组成,其上锚定有数量可变、长度可变的脂肪酰链。通过核磁共振(NMR)或质谱对这些尾部及其连接进行传统表征既耗时,又需要已有的结构数据库来进行结构归属。在此,我们介绍一种用于脂质A结构表征的完全独立于数据库的自动化从头分析方法。一种分层决策树MS(n)方法与一种混合激活技术UVPDCID结合使用,以获取来自多种革兰氏阴性菌的脂质A变体的特征性裂解模式。结构归属源自三到五个光谱的关键特征整合,无需预先存在的信息或候选结构,数分钟内即可实现自动解读。该策略的实用性在一种经酶修饰的大肠杆菌脂质A变体的脂质A结构混合物中得到了证明。总共发现了27种脂质A结构,其中许多是异构体,这表明需要一种快速的从头分析方法来进行脂质A表征。