ABSTRACT Lipids, indispensable yet structurally intricate biomolecules, serve as critical regulators of cellular function and disease progression. Conventional lipidomics, constrained by limited resolution for isomeric and low‐abundance species, has been transformed by ion mobility‐mass spectrometry (IM‐MS). This technology augments analytical power through enhanced orthogonal separation, collision cross‐section (CCS)‐based identification, and improved sensitivity. This review examines the transformative advances in IM‐MS‐driven lipidomics, focusing on three major pillars: (1) a critical evaluation of leading ion mobility spectrometry (IMS) platforms, emphasizing innovative instrument geometries and breakthroughs in resolving lipid isomers; (2) an exploration of lipid CCS databases and predictive frameworks, spotlighting computational modeling and machine learning strategies that synergize experimental data with molecular representations for high‐confidence lipid annotation; (3) emerging multi‐dimensional lipidomics workflows integrating CCS with liquid chromatography‐MS/MS to boost identification and depth, alongside mass spectrometry imaging for spatially resolved lipidomics. By unifying cutting‐edge instrumentation, computational advances, and biological insights, this review outlines a roadmap for leveraging IM‐MS to unravel lipidome complexity, catalyzing biomarker discovery and precision medicine innovation.
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AutonoMS: Automated Ion Mobility Metabolomic Fingerprinting
Automation is dramatically changing the nature of laboratory life science. Robotic lab hardware able to perform manual operations with greater speed, endurance, and reproducibility opens an avenue for faster scientific discovery with less time spent on laborious repetitive tasks. A major bottleneck remains in integrating cutting-edge laboratory equipment into automated workflows, notably specialized analytical equipment which is designed for human usage. Here we present AutonoMS, a platform for automatically running, processing, and analyzing high-throughput mass spectrometry experiments. AutonoMS is currently written around an ion mobility-mass spectrometry (IM-MS) platform and can be adapted to additional analytical instruments and data processing flows. AutonoMS enables automated software agent-controlled end-to-end measurement and analysis runs from experimental specification files that can be produced by human users or upstream software processes. We demonstrate the use and abilities of AutonoMS in a high-throughput flow-injection ion mobility configuration with 5 second sample analysis time, processing robotically-prepared chemical standards and cultured yeast samples in targeted and untargeted metabolomics applications. The platform exhibited consistency, reliability, and ease of use while eliminating the need for human intervention in the process of sample injection, data processing, and analysis. The platform paves the way towards a more fully automated mass spectrometry analysis and ultimately closed-loop laboratory workflows involving automated experimentation and analysis coupled to AI-driven experimentation utilizing cutting-edge analytical instrumentation. AutonoMS documentation is available at https://autonoms.readthedocs.io
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- Award ID(s):
- 2117782
- PAR ID:
- 10565476
- Publisher / Repository:
- American Society for Mass Spectrometry
- Date Published:
- Journal Name:
- Journal of the American Society for Mass Spectrometry
- Volume:
- 35
- Issue:
- 3
- ISSN:
- 1044-0305
- Page Range / eLocation ID:
- 542 to 550
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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