UVliPiD: A UVPD-Based Hierarchical Approach for De Novo Characterization of Lipid A Structures
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 (...
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Published in | Analytical chemistry (Washington) Vol. 88; no. 3; pp. 1812 - 1820 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
American Chemical Society
02.02.2016
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Subjects | |
Online Access | Get full text |
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Summary: | 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. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0003-2700 1520-6882 |
DOI: | 10.1021/acs.analchem.5b04098 |