Evaluating Software Tools for Lipid Identification from Ion Mobility Spectrometry-Mass Spectrometry Lipidomics Data

Holistic Comparison of the Lipidomes Simultaneously From 12 Panax Herbal Medicines By Ultra-High-Performance Supercritical Fluid Chromatography Coupled With Ion Mobility-Quadrupole Time-of-Flight Mass Spectrometry

Researches regarding quality control of ginseng focusing on the lipids are rare. Herein, ultra-high-performance supercritical fluid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (UHPSFC/IM-QTOF-MS) combined with untargeted metabolomic analysis was utilized to holistically characterize and compare the lipidomic difference among 12 Panax-derived herbal medicines. The established UHPSFC/IM-QTOF-MS method, using a Torus 1-AA column with CO2/CH3OH (modifier) as the mobile phase, well resolved the ginseng lipidome within 30 min. The lipid isomers and those easily co-eluted by conventional reversed-phase chromatography got separated, and integrated analyses of the positive-/negative-mode MS data and IM-derived collision cross section (CCS) greatly enhanced lipids identification. By the pattern recognition chemometric analysis of 90 batches of ginseng samples, the root ginseng samples showed significant differences in lipidome composition from those stem/leaf and flower samples. In contrast, red ginseng also contained lipids significantly different from the other root ginseng. Totally 82 potential differential lipids were discovered and identified based on the positive-mode data and 90 ones in the negative mode. Some of these lipid markers might be diagnostic for their authentication. Conclusively, we first report the lipidomic difference among 12 ginseng varieties, and the information obtained can lay foundation for the accurate identification of ginseng from the lipidome level.

Computational tools and algorithms for ion mobility spectrometry-mass spectrometry

Ion mobility spectrometry-mass spectrometry (IMS-MS or IM-MS) is a powerful analytical technique that combines the gas-phase separation capabilities of IM with the identification and quantification capabilities of MS. IM-MS can differentiate molecules with indistinguishable masses but different structures (e.g., isomers, isobars, molecular classes, and contaminant ions). The importance of this analytical technique is reflected by a staged increase in the number of applications for molecular characterization across a variety of fields, from different MS-based omics (proteomics, metabolomics, lipidomics, etc.) to the structural characterization of glycans, organic matter, proteins, and macromolecular complexes. With the increasing application of IM-MS there is a pressing need for effective and accessible computational tools. This article presents an overview of the most recent free and open-source software tools specifically tailored for the analysis and interpretation of data derived from IM-MS instrumentation. This review enumerates these tools and outlines their main algorithmic approaches, while highlighting representative applications across different fields. Finally, a discussion of current limitations and expectable improvements is presented.

LipiDex 2 Integrates MSn Tree-Based Fragmentation Methods and Quality Control Modules to Improve Discovery Lipidomics

As lipidomics experiments increase in scale and complexity, data processing tools must support workflows for new liquid chromatography-mass spectrometry (LC-MS) methods while simultaneously supporting quality controls to maximize the confidence in lipid identifications. LipiDex 2 improves lipidomics data processing algorithms from LipiDex 1 and introduces new tools for spectral matching and peak annotation functions, with improvements in speed and user-friendliness. In silico spectral library generation now supports tandem mass spectral (MSn) tree-based fragmentation methods, and the LipiDex 2 workflow fully integrates the fragmentation logic into the data processing steps to enable lipid identification at the appropriate level of structural resolution. Finally, LipiDex 2 features new modules for automated quality control checks that also allow users to visualize data quality in a data dashboard user interface.

ReTimeML: a retention time predictor that supports the LC-MS/MS analysis of sphingolipids

The analysis of ceramide (Cer) and sphingomyelin (SM) lipid species using liquid chromatography-tandem mass spectrometry (LC-MS/MS) continues to present challenges as their precursor mass and fragmentation can correspond to multiple molecular arrangements. To address this constraint, we developed ReTimeML, a freeware that automates the expected retention times (RTs) for Cer and SM lipid profiles from complex chromatograms. ReTimeML works on the principle that LC-MS/MS experiments have pre-determined RTs from internal standards, calibrators or quality controls used throughout the analysis. Employed as reference RTs, ReTimeML subsequently extrapolates the RTs of unknowns using its machine-learned regression library of mass-to-charge (m/z) versus RT profiles, which does not require model retraining for adaptability on different LC-MS/MS pipelines. We validated ReTimeML RT estimations for various Cer and SM structures across different biologicals, tissues and LC-MS/MS setups, exhibiting a mean variance between 0.23 and 2.43% compared to user annotations. ReTimeML also aided the disambiguation of SM identities from isobar distributions in paired serum-cerebrospinal fluid from healthy volunteers, allowing us to identify a series of non-canonical SMs associated between the two biofluids comprised of a polyunsaturated structure that confers increased stability against catabolic clearance.

The Interplay of Lipid Signaling in Musculoskeletal Cross Talk: Implications for Health and Disease

The intricate interplay between the muscle and bone tissues is a fundamental aspect of musculoskeletal physiology. Over the past decades, emerging research has highlighted the pivotal role of lipid signaling in mediating communication between these tissues. This chapter delves into the multifaceted mechanisms through which lipids, particularly phospholipids, sphingolipids, and eicosanoids, participate in orchestrating cellular responses and metabolic pathways in both muscle and bone. Additionally, we examine the clinical implications of disrupted lipid signaling in musculoskeletal disorders, offering insights into potential therapeutic avenues. This chapter aims to shed light on the complex lipid-driven interactions between the muscle and bone tissues, paving the way for a deeper understanding of musculoskeletal health and disease.