Automated Lipid A Structure Assignment from Hierarchical Tandem Mass Spectrometry Data

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 MS ⁿ 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 MS ⁿ 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 A MS 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 MS ⁿ 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 MS ⁿ 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.