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Workflow for fast lipid tissue screening using LESA-FT-ICR-MS

机译:使用Lesa-FT-ICR-MS进行快速脂肪组织筛选的工作流程

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摘要

Lipid screening of biological substrates is an important step during biomarker detection and identification. In this work, a fast workflow is described capable of rapid screening for lipid components from biological tissues at ambient pressure based on liquid microjunction extraction in tandem with nano-electrospray ionization (nESI) with ultra-high resolution mass spectrometry, i.e., liquid extraction surface analysis (LESA) coupled to Fourier-transform ion cyclotron resonance (tandem) mass spectrometry (LESA-FT-ICR-MS/MS). Lipid profiles are presented for thin tissue sections of mouse brain (MB) and liver (ML) samples, analyzed in both positive and negative mode by data-dependent acquisition (DDA) tandem FT-ICR-MS/MS. Candidate assignments were based on fragmentation patterns using mostly SimLipid software and accurate mass using mostly the LipidMaps database (average sub-ppm mass error). A typical, single point surface analysis (< 1 mm spatial sampling resolution) lasted less than 15 minutes and resulted in the assignment of (unique and mulitple) lipid identifications of 190 (MB) and 590 (ML) m/z values. Despite the biological complexity, this led to unique identifications of distinct lipid molecules (sub-ppm mass error) from 38 different lipid classes, corresponding to 10-30% of the lipid m/z identifications.
机译:生物基质的脂质筛选是生物标志物检测和鉴定期间的重要步骤。在这项工作中,描述了一种快速的工作流程,能够快速筛选来自基于液体微型萃取(NESI)的液体微型萃取,即用超高分辨率质谱,即液体提取表面在环境压力下从生物组织中从生物组织中快速筛选脂质组分。耦合到傅里叶变换离子回旋谐振(串联)质谱(LESA-FT-ICR-MS / MS)的分析(LESA)。脂质曲线用于小鼠脑(MB)和肝脏(M1)样品的薄组织切片,通过数据依赖性采集(DDA)串联FT-ICR-MS / MS分析。候选分配基于使用大多数SimliPID软件和准确的碎屑的碎片模式,并且使用大多数是LipidMaps数据库(平均子PPM质量错误)。典型的单点表面分析(<1mm空间采样分辨率)持续不到15分钟,导致(唯一和多种)的脂质识别190(MB)和590(mL)M / Z值的分配。尽管存在生物复杂性,但这导致了来自38种不同脂质类别的不同脂质分子(亚ppm质量误差)的独特鉴定,相当于脂质M / Z鉴定的10-30%。

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