Automated Lipid A Structure Assignment from Hierarchical Tandem Mass Spectrometry Data

作者：Ting Ying S; Shaffer Scott A; Jones Jace W; Ng Wailap V; Ernst Robert K; Goodlett David R^*

来源：Journal of the American Society for Mass Spectrometry, 2011, 22(5): 856-866.

DOI：10.1007/s13361-010-0055-y

• HiTMS
• Hierarchical
• Multi-stage
• Mass spectrometry
• High-throughput
• Lipid A
• Lipidomic
• Algorithm
• Automated
• Structural
• Cross-correlation

Infusion-based electrospray ionization (ESI) coupled to multiple-stage tandem mass spectrometry (MS(n)) is a standard methodology for investigating lipid A structural diversity (Shaffer et al. J. Am. Soc. Mass. Spectrom. 18(6), 1080-1092, 2007). Annotation of these MSn spectra, however, has remained a manual, expert-driven process. In order to keep up with the data acquisition rates of modern instruments, we devised a computational method to annotate lipid A MSn spectra rapidly and automatically, which we refer to as hierarchical tandem mass spectrometry (HiTMS) algorithm. As a first-pass tool, HiTMS aids expert interpretation of lipid AMS(n) data by providing the analyst with a set of candidate structures that may then be confirmed or rejected. HiTMS deciphers the signature ions (e. g., A-, Y-, and Z-type ions) and neutral losses of MSn spectra using a species-specific library based on general prior structural knowledge of the given lipid A species under investigation. Candidates are selected by calculating the correlation between theoretical and acquired MSn spectra. At a false discovery rate of less than 0.01, HiTMS correctly assigned 85% of the structures in a library of 133 manually annotated Francisella tularensis subspecies novicida lipid A structures. Additionally, HiTMS correctly assigned 85% of the structures in a smaller library of lipid A species from Yersinia pestis demonstrating that it may be used across species.

• 出版日期2011-5