Greazy: Open-Source Software for Automated Phospholipid Tandem Mass Spectrometry Identification.
Greazy: Open-Source Software for Automated Phospholipid Tandem Mass Spectrometry Identification.
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DOI：
10.1021/acs.analchem.6b00021
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发表时间：
2016-06-07
影响因子：
7.4
通讯作者：
Tabb DL
中科院分区：
文献类型：
--
作者：
Kochen MA;Chambers MC;Holman JD;Nesvizhskii AI;Weintraub ST;Belisle JT;Islam MN;Griss J;Tabb DL
从高通量技术产生的数据中识别脂质对于阐明脂质在细胞功能和疾病中所起的作用至关重要。用于从串联质谱仪(MS/MS)谱中识别脂类的软件工具已经开发出来，但它们通常很昂贵，或者缺乏蛋白质组学对应物的复杂性。我们已经开发了Greazy，这是一种用于从MS/MS光谱中自动识别磷脂的开源工具，它使用的方法与为蛋白质组学开发的方法类似。根据用户提供的参数，Greazy建立了磷脂搜索空间和相关的理论MS/MS光谱。使用基于超几何分布的峰值分数和利用驻留在匹配峰中的总离子强度的百分比的强度分数，针对具有相似前体质量的搜索空间脂类对实验光谱进行评分。LipidLama组件通过混合建模和密度估计对结果进行过滤。我们根据NIST 2014新陈代谢组学文库评估Greazy的表现，观察到在搜索多个脂质类别时的高准确性。我们将Greazy/LipidLama与商业脂质鉴定软件LipidSearch进行了比较，结果表明，这两个平台在鉴定的光谱集上有很大差异，但在两者鉴定的光谱上表现出很好的一致性。最后，我们用不同的工具演示了Greazy/LipidLama的实用性。我们搜索了用Orbitrap获得的肺泡2型上皮细胞的复制数据和通过Q-TOF产生的人血清复制的数据。这些发现证实了蛋白质组学衍生方法在脂类鉴定中的应用。该软件可从ProteoWizard存储库中获得：[http://tiny.cc/bumbershoot-vc12-bin64].
Lipid identification from data produced with high-throughput technologies is essential to the elucidation of the roles played by lipids in cellular function and disease. Software tools for identifying lipids from tandem mass (MS/MS) spectra have been developed, but they are often costly or lack the sophistication of their proteomics counterparts. We have developed Greazy, an open source tool for the automated identification of phospholipids from MS/MS spectra, that utilizes methods similar to those developed for proteomics. From user-supplied parameters, Greazy builds a phospholipid search space and associated theoretical MS/MS spectra. Experimental spectra are scored against search space lipids with similar precursor masses using a peak score based on the hypergeometric distribution and an intensity score utilizing the percentage of total ion intensity residing in matching peaks. The LipidLama component filters the results via mixture modelling and density estimation. We assess Greazy’s performance against the NIST 2014 metabolomics library, observing high accuracy in a search of multiple lipid classes. We compare Greazy/LipidLama against the commercial lipid identification software LipidSearch and show that the two platforms differ considerably in the sets of identified spectra while showing good agreement on those spectra identified by both. Lastly, we demonstrate the utility of Greazy/LipidLama with different instruments. We searched data from replicates of alveolar type 2 epithelial cells obtained with an Orbitrap and from human serum replicates generated on a Q-TOF. These findings substantiate the application of proteomics derived methods to the identification of lipids. The software is available from the ProteoWizard repository: [http://tiny.cc/bumbershoot-vc12-bin64].