[Progress in applications of ambient ionization mass spectrometry for lipids identification]

Lipids are indispensable components of living organisms and play pivotal roles in cell-membrane fluidity, energy provision, and neurotransmitter transmission and transport. Lipids can act as potential biomarkers of diseases given their abilities to indicate cell-growth status. For example, the lipid-metabolism processes of cancer cells are distinct from those of normal cells owing to their rapid proliferation and adaptation to ever-changing biological environments. As a result, the ability to rapidly detect, identify, and monitor lipid components is critical for tracking life-related processes and may enhance cancer diagnosis and treatment efficacy. Mass spectrometry (MS) is regarded to be among the most efficient methods for directly obtaining molecular-structural information, and is distinctly advantageous for identifying lipids. Recent years have witnessed the emergence of ambient mass spectrometry (AMS), which enables direct analyte sampling and ionization without the need for sample preprocessing. These characteristics endow AMS with special advantages for identifying and monitoring lipids. Furthermore, the ongoing development of soft ionization technologies has led to the widespread use of AMS for the detection of complex and diverse lipid molecules. Electrospray ionization (ESI) is a gentle ionization method that can be used to detect medium-to-high-polarity compounds and provide detailed chemical information for lipids by producing a fine mist of charged droplets from a liquid sample. Consequently, a series of ESI-based ionization methods have been developed for fabricating different AMS systems capable of rapidly detecting lipids in a simple manner. For example, desorption electrospray ionization (DESI) is among the most extensively employed ambient ionization techniques, and has been used to detect a wide range of samples, including solids, liquids, and gases. DESI involves spraying a charged solvent onto the surface of a sample, after which the solvent is desorbed, the analyte is ionized, and the generated ions are transferred to the detector of the mass spectrometer via a gas plume. DESI can easily and precisely regulate the sampling space, thereby offering a highly effective approach for the in-situ detection of lipids from tissue samples. Additionally, single-cell lipid analysis is limited by small cell volumes, complex cellular matrices, and minimal absolute amounts of analyte. Common detection methods for single cells include flow cytometry and fluorescence microscopy, both of which require fluorescent labeling to detect specific target molecules, which limits detection selectivity and reproducibility to some extent. ESI-based single-cell mass spectrometry has emerged as a more-effective method for detecting cellular lipids owing to advantages that include high sensitivity, low sample consumption, high throughput, and multiple-detection capabilities. Moreover, lipid chemical diversity poses a significant challenge for determining structural details. Therefore, AMS-based lipid detection has been augmented with a series of chemical-treatment methods that provide more-comprehensive structural information for lipids. For example, diverse gas-phase dissociation techniques have been used to discriminate between lipid C=C-bond isomers and their sn-positions. Strategies that involve chemically modifying specific target C=C bonds prior to MS detection have also been employed. For example, the Paternò-Büchi (P-B) photochemical reaction oxidizes C=C bonds in unsaturated lipids to form oxetane structures, C=C bonds can be epoxidized to form the corresponding oxaziridines, the N-H aziridination reaction converts C=C bonds into aziridines, and the ¹ΔO₂ ene reaction adds an OOH group to a C=C bond. In this review, we discuss various environmental ionization techniques for lipid AMS developed over the past five years, with an emphasis on typical chemical strategies used to analyze lipid fine structures. Obtaining a high-coverage, high-sensitivity lipid-detection platform based on AMS remains challenging and requires further in-depth studies despite significant improvements in lipid MS-based detection techniques.