Identification and Quantification of cellular lipids

Lipidomics is the large-scale study of pathways and networks of cellular lipids in biological systems[1][2][3] The word “lipidome” is used to describe the complete lipid profile within a cell, tissue, organism, or ecosystem and is a subset of the “metabolome” Which also includes the three other major classes of biological molecules: proteins/amino-acids, sugars, and nucleic acids. Lipidomics research involves the identification and quantification of the thousands of cellular lipid molecular species and their interactions with other lipids, proteins, and other metabolites.

Investigators in lipidomics examine the structures, functions, interactions, and dynamics of cellular lipids and the changes that occur during perturbation of the system. To date, the main limitations for LC-MS-based untargeted lipidomics reside in the lack of adequate computational and cheminformatics tools that are able to support the analysis of several thousands of species from biological samples, enabling data mining and automating lipid identification and external prediction processes.

Chemist putting vial with a sample into autosampler of HPLC system. High performance liquid chromatography at chemical laboratory. Developing of pharmaceuticals or vaccine. Biochemistry analysis

To address these issues, we developed Lipostar, novel vendor-neutral high-throughput software that effectively supports both targeted and untargeted LC-MS lipidomics, implementing data acquisition, user-friendly multivariate analysis (to be used for model generation and new sample predictions), and advanced lipid identification protocols that can work with or without the support of preformed lipid databases. Moreover, Lipostar integrates the lipidomic processes with a full metabolite identification (MetID) procedure, essential in drug safety applications and in translational studies. Case studies demonstrating a number of Lipostar features are also presented. 


  1. Wenk MR (July 2005). “The emerging field of lipidomics”. Nat Rev Drug Discov. 4 (7): 594–610. doi:10.1038/nrd1776PMID 16052242S2CID 83931214. 
  2. ^ Watson AD (October 2006). “Thematic review series: systems biology approaches to metabolic and cardiovascular disorders. Lipidomics: a global approach to lipid analysis in biological systems”. J. Lipid Res. 47 (10): 2101–11. doi:10.1194/jlr.R600022-JLR200PMID 16902246. 
  3. ^ “Lipidomics”. The Lipid Chronicles. 2011-12-15. Retrieved 2012-01-08. 
  • Guiding the choice of informatics software and tools for lipidomics research applications
    • February 2023. Zhixu Ni Michele WölkGeoff JukesKarla Mendivelso EspinosaRobert AhrendsLucila AimoJorge Alvarez-JarretaSimon AndrewsRobert AndrewsAlan BridgeGeremy C ClairMatthew J ConroyEoin FahyCaroline GaudLaura GoracciJürgen HartlerNils HoffmannDominik KopczyinkiAnsgar KorfAndrea F Lopez-ClavijoAdnan MalikJacobo Miranda AckermanMartijn R MolenaarClaire O’DonovanTomáš PluskalAndrej ShevchenkoDenise SlenterGary SiuzdakMartina KutmonHiroshi TsugawaEgon L WillighagenJianguo XiaValerie B O’DonnellMaria Fedorova
  • Retinoic acid-induced 1 gene haploinsufficiency alters lipid metabolism and causes autophagy defects in Smith-Magenis syndrome
    • November 2022. Elisa Maria TurcoAngela Maria Giada GiovenaleLaura SirenoMartina MazzoniAlessandra CammareriCaterina MarchiorettiLaura GoracciAlessandra Di VeroliElena MarchesanDaniel D’AndreaAntonella FalconieriBarbara TorresLaura BernardiniMaria Chiara MagnificoAlessio PaoneSerena Rinaldo, Matteo Della MonicaStefano D’ArrigoDiana PostorivoAnna Maria NardoneGiuseppe ZampinoRoberta OnesimoChiara LeoniFederico CaicciDomenico RaimondoElena BindaLaura TrobianiAntonella De JacoAda Maria TataDaniela FerrariFrancesca CutruzzolàGianluigi MazzoccoliElena ZivianiMaria PennutoAngelo Luigi VescoviJessica Rosati 



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