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Lipostar

Lipostar 2 is a comprehensive, vendor-neutral software for LC-MS/MS-based lipidomics (DDA and DIA), which includes a large number of features including: raw data import and peak detection, identification, quantification, statistical analysis, trend analysis and biopathways analysis.

Lipostar 2 finds application in untargeted and semi-targeted lipidomics, including stable isotope labelling experiments. Within a Lipostar session, different modes of lipidomics analysis can be combined to increase knowledge and obtain a more comprehensive analysis of lipid profiles.

Key Features

• The DB Manager module that enables the generation of databases of fragmented lipids by applying fragmentation rules provided by the software or by importing experimental MS/MS data
• A flexible lipid identification approach that includes:
  1. a spectral matching approach
  2. high-throughput bottom-up approach, based on class-specific fragment recognition
  3. high-throughput identification of oxidized species.
• A gap-filler algorithm to reduce missing values
• Various plots to visualize and refine identification results
• Various multivariate statistical analysis tools
• Lipid pathways

Enhancements in Lipostar 2

Data Processing

• More instruments supported. Now Lipostar 2 reads the most common file formats:
  • Agilent Q-Tof(*.d): AutoMS and full scan at multiple energies of collision (All Ions).
  • Waters (*.raw): MSe, HDMSe, DDA, and MSMS, SONAR
  • Thermo-Fisher (*.RAW): Ion-Trap and Orbitrap, Exactive, Q-Exactive, DDA and AIF
  • ABSCiex *.wiff file format.
  • Bruker (*.d): QTof, FT-ICR, TIMS-TOF data dependent scan.
  • Shimadzu (*.lcd): QTof
• Data processing can be run in the background.

Data Analysis

• Trend analysis for global lipid profiling

Identification

• New fragmentation rules for automatic lipid identification
• Lipid database generation from in-house data
• Improved adduct and in source fragmentation clustering
• Customized adducts support
• Transfer of identification results to submatrices
• Kendrick mass defect plot
• Use of Waters CCS values for identification scores

Quantification

• New handling of adduct information

Lipid pathways

• Updated and new biopathways maps available (metabolism & disease)

Cross-talk with other software

• Connection to LipidLynxX for lipid annotation
• connection to LPPTiger for in depth identification of oxidized species

Tutorials

• 14 updated and new tutorials are available

References

• Goracci L; Tortorella S; Tiberi P; Pellegrino RM; Di Veroli A; Valeri A; Cruciani G,
  Lipostar, a Comprehensive Platform-Neutral Cheminformatics Tool for Lipidomics.
  Anal. Chem., 2017, 89 (11), pp 6257–6264
• Capece D,  D'Andrea D,  Begalli F,  Goracci L, et al.
  Enhanced triacylglycerol catabolism by Carboxylesterase 1 promotes aggressive colorectal carcinoma.
  J Clin Invest. 2021;131(11):e137845
• Terao M, Goracci L, Celestini V, Kurosaki M, et al.
  Role of mitochondria and cardiolipins in growth inhibition of breast cancer cells by retinoic acid.
  J Exp Clin Cancer Res 38, 436 (2019). Erratum in: J Exp Clin Cancer Res. 2019 Dec 18;38(1):496. PMID: 31665044; PMCID: PMC6821005.
• Goracci L, Valeri A, Sciabola S, Aleo MD, et al.
  A Novel Lipidomics-Based Approach to Evaluating the Risk of Clinical Hepatotoxicity Potential of Drugs in 3D Human Microtissues.
  Chem Res Toxicoly 2020 Jan 21;33(1):258-270. Epub 2019 Dec 24. PMID: 31820940.
• Ni Z, Goracci L, Cruciani G, Fedorova M.
  Computational solutions in redox lipidomics - Current strategies and future perspectives.
  Free Radic Biol Med. 2019 Nov 20;144:110-123. Epub 2019 Apr 26. PMID: 31035005.
• La Barbera G, Antonelli M, Cavaliere C, Cruciani G, et al.
  Delving into the Polar Lipidome by Optimized Chromatographic Separation, High-Resolution Mass Spectrometry, and Comprehensive Identification with Lipostar: Microalgae as Case Study.
  Anal Chem. 2018 Oct 16;90(20):12230-12238. Epub 2018 Sep 24. PMID: 30204416.
• Torquato P, Giusepponi D, Alisi A, Galarini R, et al.
  Nutritional and lipidomics biomarkers of docosahexaenoic acid-based multivitamin therapy in pediatric NASH.
  Sci Rep. 2019 Feb 14;9(1):2045. PMID: 30765737; PMCID: PMC6375912.
• Camera E, Ludovici M, Tortorella S, Sinagra JL et al.
  Use of lipidomics to investigate sebum dysfunction in juvenile acne.
  J Lipid Res. 2016 Jun;57(6):1051-8. Epub 2016 Apr 27. PMID: 27127078; PMCID: PMC4878189.

Try out Lipostar

Want to evaluate or know more about Lipostar? Please refer to Molecular Discovery