Direct Infusion Acoustic Droplet Ejection Mass Spectrometry: Enabling High-Throughput Shotgun Lipidomics
收藏NIAID Data Ecosystem2026-05-10 收录
下载链接:
https://figshare.com/articles/dataset/Direct_Infusion_Acoustic_Droplet_Ejection_Mass_Spectrometry_Enabling_High-Throughput_Shotgun_Lipidomics/31854132
下载链接
链接失效反馈官方服务:
资源简介:
High-throughput lipidomics
is increasingly important for large-scale
studies and clinical applications. While shotgun lipidomics enables
rapid analysis, it suffers from limitations such as carryover, ion
suppression, and limited structural specificity. Acoustic droplet
ejection mass spectrometry (ADE-MS) presents a novel approach, enabling
touchless nanoliter-scale sample introduction at high speed, precision,
and accuracy. Initially designed for single-droplet injection, ADE-MS
was adapted for direct infusion with stable signals. In this study,
we developed and benchmarked a scalable workflow based on ADE-MS/MS
with parallel reaction monitoring (PRM) on a ZenoTOF MS platform implemented
in a 384-well format. By optimizing solvent composition, droplet parameters,
and MS acquisition settings, the workflow enabled reproducible quantification
of over 1000 polar and nonpolar lipid species across 14 subclasses,
with low sample consumption and a total run time of approximately
five minutes per sample. Applying this method to NIST SRM 1950 plasma,
a total of 731 lipid species were quantified. The method demonstrated
robust analytical performance in terms of linearity, precision, reproducibility,
and recovery across 384-well microplates. Cross-platform comparison
with a validated hydrophilic interaction liquid chromatography (HILIC)-MS/MS
method using NIST SRM 1950 plasma demonstrated strong agreement (R2 > 0.80 for most subclasses) and substantially
higher throughput, achieving over 200 lipid identifications per minute
and a daily capacity exceeding 280 samples. The applicability of this
workflow was demonstrated by identifying 656 differential lipid features
associated with progressive lipidomic dysregulation across body mass
index categories.
创建时间:
2026-03-25



