Lipid Annotator: Towards Accurate Annotation in Non-Targeted Liquid Chromatography High-Resolution Tandem Mass Spectrometry (LC-HRMS/MS) Lipidomics Using a Rapid and User-Friendly Software

Abstract

Lipidomics has great promise in various applications; however, a major bottleneck in lipidomics is the accurate and comprehensive annotation of high-resolution tandem mass spectral data. While the number of available lipidomics software has drastically increased over the past five years, the reduction of false positives and the realization of obtaining structurally accurate annotations remains a significant challenge. We introduce Lipid Annotator, which is a user-friendly software for lipidomic analysis of data collected by liquid chromatography high-resolution tandem mass spectrometry (LC-HRMS/MS). We validate annotation accuracy against lipid standards and other lipidomics software. Lipid Annotator was integrated into a workflow applying an iterative exclusion MS/MS acquisition strategy to National Institute of Standards and Technology (NIST) SRM 1950 Metabolites in Frozen Human Plasma using reverse phase LC-HRMS/MS. Lipid Annotator, LipidMatch, and MS-DIAL produced consensus annotations at the level of lipid class for 98% and 96% of features detected in positive and negative mode, respectively. Lipid Annotator provides percentages of fatty acyl constituent species and employs scoring algorithms based on probability theory, which is less subjective than the tolerance and weighted match scores commonly used by available software. Lipid Annotator enables analysis of large sample cohorts and improves data-processing throughput as compared to previous lipidomics software.

A Novel Solid Phase Extraction Sample Preparation Method for Lipidomic Analysis of Human Plasma Using Liquid Chromatography/Mass Spectrometry

“…LC-HRMS/MS data from the pooled sample were annotated to specific lipids using HRMS/MS in silico spectral matching with the MassHunter Lipid Annotator 1.0 software (Agilent Technologies). This software uses an algorithm that combines probability density, Bayesian scoring, and a non-negative least square fit to search a theoretical lipid library [ 35 ]. Positive and negative mode datasets were treated separately throughout data analysis.…”

New software tools, databases, and resources in metabolomics: updates from 2020

“…Lipid Annotator, is a standalone software for lipidomic analysis of data collected by HR LC–MS/MS (Koelmel et al 2020 ). Lipid Annotator algorithm, intended for lipid annotation based on in-silico libraries, consists of five general steps: feature finding, association of MS/MS scans with features, annotation of possible lipids for each feature, calculation of the percent abundance of each fatty acyl constituent under a single chromatographic peak in the case of mixed spectra, and filtration of final annotated features.…”

Recurrent Topics in Mass Spectrometry-Based Metabolomics and Lipidomics—Standardization, Coverage, and Throughput

“… 176 The application of Bayesian statistics presents an interesting and promising direction and may overcome some limitations of hand-crafted rule sets. 177 Excellent community-based resources provide guidelines (see ILS, LSI 92 ) on criteria and characteristic fragments for MS/MS annotation. The LIPID MAPS 178 and LSI website list continuously update information on manual inspection of MS/MS data reporting on obligatory fragment ions for unambiguous annotation of lipids.…”