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Anal Chem. 2016 Jun 7;88(11):5733-41. doi: 10.1021/acs.analchem.6b00021. Epub 2016 May 24.

Greazy: Open-Source Software for Automated Phospholipid Tandem Mass Spectrometry Identification.

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Department of Biomedical Informatics, Vanderbilt University , Nashville, Tennessee 37203, United States.
Department of Pathology, University of Michigan , Ann Arbor, Michigan 48109, United States.
Department of Biochemistry, UT Health Science Center at San Antonio , San Antonio, Texas 78229, United States.
Department of Microbiology, Immunology and Pathology, Colorado State University , Fort Collins, Colorado 80523, United States.
European Bioinformatics Institute (EBI) , Wellcome Trust Genome Campus, Hinxton, Cambridge, U.K. CB10 1SD.
Department of Dermatology, Medical University of Vienna , 1090 Vienna, Austria.


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 modeling 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 quadrupole-time-of-flight (Q-TOF). These findings substantiate the application of proteomics derived methods to the identification of lipids. The software is available from the ProteoWizard repository: .

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