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Semi-automated liquid chromatography–mass spectrometric imaging platform for enhanced detection and improved data analysis of complex peptides

机译:半自动液相色谱-质谱光谱成像平台用于增强检测和改进复杂肽的数据分析

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摘要

A semi-automated analytical platform featuring the coupling of monolithic reversed-phase liquid chromatography (RPLC) to matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI MSI) has been developed and evaluated. This is the first time that LC separation is readily coupled to MS imaging detection for the analysis of complex peptide mixtures both qualitatively and quantitatively. Methacrylate-based monolithic column with C12 functional groups is fabricated for fast RPLC separation. The LC flow and matrix flow are collected on a commercially available MALDI plate which is mechanically controlled and analyzed with MALDI MSI subsequently. Both tryptic peptides digested from bovine serum albumin (BSA) and endogenous neuropeptides extracted from the blue crab Callinectes sapidus are analyzed with this novel LC–MSI platform. Compared with regular offline LC fractionation coupled with MALDI MS detection, LC–MSI exhibits significantly increased MS signal intensity due to retaining of temporal resolution from separation dimension via continuous sampling, which results in increased number of peptides detected and accurate quantitation. In addition, imaging signals enable improved data analysis based on either mass-to-charge ratio or retention time, which is extremely beneficial for the analysis of complex analytes. These findings have demonstrated the potential of employing LC–MSI platform for enhanced proteomics and peptidomics studies.
机译:已开发并评估了一个半自动化分析平台,该平台具有整体式反相液相色谱(RPLC)与基质辅助激光解吸/电离质谱成像(MALDI MSI)的耦合功能。这是首次将LC分离轻松与MS成像检测结合使用,以进行定性和定量分析复杂的肽混合物。制备具有C12官能团的基于甲基丙烯酸酯的整体柱,以实现快速RPLC分离。 LC流量和基质流量收集在市售的MALDI板上,然后对其进行机械控制并使用MALDI MSI进行分析。使用这种新型LC-MSI平台分析了从牛血清白蛋白(BSA)消化的胰蛋白酶肽和从蓝蟹Callinectes sapidus提取的内源性神经肽。与常规离线LC分离结合MALDI MS检测相比,LC-MSI的质谱信号强度显着提高,这是由于通过连续采样保留了分离尺寸的时间分辨率,从而导致检测到的肽数量增加和准确定量。此外,成像信号还可以基于质荷比或保留时间改善数据分析,这对于分析复杂的分析物极为有利。这些发现证明了使用LC–MSI平台进行增强的蛋白质组学和肽组学研究的潜力。

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