LipidFinder: A computational workflow for discovery of lipids identifies eicosanoid-phosphoinositides in platelets

LipidFinder: A computational workflow for discovery of lipids identifies eicosanoid-phosphoinositides in platelets
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DOI：
10.1172/jci.insight.91634
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发表时间：
2017-04-06
期刊：
JCI INSIGHT
影响因子：
8
通讯作者：
O'Donnell, Valerie B.
O'Donnell, Valerie B.
中科院分区：
医学1区
文献类型：
--
作者：
O'Connor, Anne;Brasher, Christopher J.;O'Donnell, Valerie B.

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从血浆、细胞或组织生成的脂质组学数据集的准确和高质量的管理对于细胞生物学研究和个性化医学的生物标志物发现变得至关重要。然而，一个主要的挑战在于从大的质谱文件（> 60 K特征）中去除否则被错误地解释为真实的脂质的伪影，同时保留数据集中的真实离子。这需要强大的信息学工具;然而，可用的工作流程尚未专门针对脂质组学，特别是发现研究。我们设计了一个开源的Python工作流Lipidogram。包括一个算法，根据用户自己的数据优化分析，并根据在线数据库筛选输出，并将其归类为LIPID MAPS类。使用来自人类血小板的数据，Lipidomics优于三种广泛使用的代谢组学软件包。我们展示了由凝血酶激活的血小板产生的三个12-羟基二十碳四烯酸磷酸肌醇（16：0/，18：1/，18：0/12-HETE-PI）的家族，表明人类细胞中类二十烷酸和磷酸肌醇途径之间的串扰。该软件可在GitHub上获得（https：//github.com/cjbrasher/Lipidhub），并附有完整的用户指南。
Accurate and high-quality curation of lipidomic datasets generated from plasma, cells, or tissues is becoming essential for cell biology investigations and biomarker discovery for personalized medicine. However, a major challenge lies in removing artifacts otherwise mistakenly interpreted as real lipids from large mass spectrometry files (> 60 K features), while retaining genuine ions in the dataset. This requires powerful informatics tools; however, available workflows have not been tailored specifically for lipidomics, particularly discovery research. We designed LipidFinder, an open-source Python workflow. An algorithm is included that optimizes analysis based on users ' own data, and outputs are screened against online databases and categorized into LIPID MAPS classes. LipidFinder outperformed three widely used metabolomics packages using data from human platelets. We show a family of three 12-hydroxyeicosatetraenoic acid phosphoinositides (16:0/, 18:1/, 18:0/12-HETE-PI) generated by thrombin-activated platelets, indicating crosstalk between eicosanoid and phosphoinositide pathways in human cells. The software is available on GitHub (https://github.com/cjbrasher/LipidFinder), with full userguides.