LipidSearch Software

Accurate lipid identification

Relative quantitation and accurate identification of lipids from biological samples requires sophisticated software with a comprehensive database. Thermo Scientific LipidSearch software provides automated identification of lipids and integrates an entire dataset into a concise report showing statistical differences between sample groups.

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Key benefits

Automated lipid identification	Comprehensive database coverage
Unique peak detection algorithms are customized for LC-data dependent MS/MS including combining the information from CID/HCD fragmentations and MS²/MS³ spectra using the Thermo Scientific Orbitrap IQ-X and Tribrid mass spectrometers. Product ion search and annotation alignment algorithms are optimized for untargeted lipid identification.	The LipidSearch software database contains molecular lipid species (96 sub-classes) and their predicted fragment ions and provides the most complete coverage of different sample types including cells, human plasma, insect larvae, plants, seed oils, tissue and yeast.

Related content

Poster: Software Utilizing Positive and Negative Ion MS² / MS³ HCD and CID Spectra for Improved MSⁿ Lipid Identification
Poster: High Throughput Lipid Identification and Quantification Using a Directed HRAM LC-MS-MS Approach on a Modified Quadrupole-Orbitrap Mass Spectrometer
Poster: LipidSearch 5.0: A New Software for Processing Data from Direct Infusion and LC-MS High Resolution Mass Spectrometry Based Lipidomics Workflows
Poster: Higher Resolution LC-MS and MS-MS Analysis of Lipid Extracts Using Benchtop Orbitrap-based Mass Spectrometers and LipidSearch Software
Poster: A New Lipid Software Workflow for Processing Orbitrap-based Global Lipidomics Data in Translational and Systems Biology Research
Poster: Robust and Sensitive LC-MS/MS Based Plasma Lipid Profiling on a Q Exactive HF-X Mass Spectrometer

References

R Taguchi, et al.,Precise and global identification of phospholipid molecular species by an Orbitrap mass spectrometer and automated search engine LipidSearch, J. Chrom. A, 2010, 1217, 4229–4239. doi: 10.1016/j.chroma.2010.04.034
T Yamada, et al.,Development of a lipid profiling system using reverse-phase liquid chromatography coupled to high-resolution mass spectrometry with rapid polarity switching and an automated lipid identification software, J. Chrom. A, 2013, 1292, 211-218. doi: 10.1016/j.chroma.2013.01.078
M B Trevino, et al., Perilipin 5 Regulates Islet Lipid Metabolism and Insulin Secretion in a cAMP-Dependent Manner: Implication of Its Role in the Postprandial Insulin Secretion, Diabetes, 2015; 64:1299–1310. doi: 10.2337/db14-0559
F G Tafesse, et al., (2015) Disruption of Sphingolipid Biosynthesis Blocks Phagocytosis of Candida albicans, PLoS Pathog 11(10): e1005188. doi: 10.2337/db14-0559
R Almeida, et al., Comprehensive Lipidome Analysis by Shotgun Lipidomics on a Hybrid Quadrupole-Orbitrap-Linear Ion Trap Mass Spectrometer, J. Am. Soc. Mass Spectrom. (2014). doi: 10.1007/s13361-014-1013-x
S B Breitkopf, et al., Triomics Analysis of Imatinib-Treated Myeloma Cells Connects Kinase Inhibition to RNA Processing and Decreased Lipid Biosynthesis,Anal. Chem. 2015, 87, 21, 10995-11006. doi: 10.1021/acs.analchem.5b03040
M Narvaez-Rivas, et al.Comprehensive untargeted lipidomic analysis using core-shell C30 particle column and high field orbitrap mass spectrometer, J Chrom. A (2016). doi: 10.1016/j.chroma.2016.02.054
S B Breitkopf, et al., A relative quantitative positive/negative ion switching method for untargeted lipidomics via high resolution LC-MS/MS from any biological source, Metabolomics (2017) 13: 30. doi: 10.1007/s11306-016-1157-8

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