Collection of structures and annotations of biologically relevant lipids that contains unique lipid structures. Structures of lipids from : LIPID MAPS Consortium's core laboratories and partners; lipids identified by LIPID MAPS experiments; biologically relevant lipids manually curated from LIPID BANK, LIPIDAT, Lipid Library, Cyberlipids, ChEBI and other public sources; novel lipids submitted to peer-reviewed journals; and computationally generated structures for appropriate classes. All the lipid structures adhere to the structure drawing rules proposed by the LIPID MAPS consortium. A number of structure viewing options are offered: gif image (default), Chemdraw (requires Chemdraw ActiveX/Plugin), MarvinView (Java applet) and JMol (Java applet). All lipids have been classified using the LIPID MAPS Lipid Classification System. Each lipid structure has been assigned a LIPID MAPS ID (LM_ID) which reflects its position in the classification hierarchy. In addition to a classification-based retrieval of lipids, users can search using either text-based or structure-based search options.

This repository contains the LIPID MAPS® Structure Database (LMSD) formatted for use in MetFrag (and other workflows).

LIPID MAPS® Lipidomics Gateway is a free, comprehensive website for researchers interested in lipid biology. Use https://www.lipidmaps.org to stay abreast of developments each month from across the field, and explore the rich information collections, tools and resources from the LIPID Metabolites And Pathways Strategy (LIPID MAPS®) Consortium.

The workflow used to create this file (by B. Talavera Andújar) can be found here: https://gitlab.lcsb.uni.lu/eci/simple-utilities/sdf2csv

Reference: LMSD: LIPID MAPS® structure database, Sud M., Fahy E., Cotter D., Brown A., Dennis E., Glass C., Murphy R., Raetz C., Russell D., and Subramaniam S., Nucleic Acids Research, 2006, DOI: 10.1093/nar/gkl838

The LIPID MAPS Lipid Classification System is comprised of eight lipid categories, each with its own subclassification hierarchy. All lipids in the LIPID MAPS Structure Database (LMSD) have been classified using this system and have been assigned LIPID MAPS ID's which reflects their position in the classification hierarchy.

Analysis of oxylipins by liquid chromatography mass spectrometry (LC/MS) is challenging because of the small mass range occupied by this diverse lipid class, the presence of numerous structural isomers, and their low abundance in biological samples. Although highly sensitive LC/MS/MS methods are commonly used, further separation is achievable by using drift tube ion mobility coupled with high-resolution mass spectrometry (DTIM-MS). Herein, we present a combined analytical and computational method for the identification of oxylipins and fatty acids. We use a reversed-phase LC/DTIM-MS workflow able to profile and quantify (based on chromatographic peak area) the oxylipin and fatty acid content of biological samples while simultaneously acquiring full scan and product ion spectra. The information regarding accurate mass, collision-cross-section values in nitrogen (DTCCSN2), and retention times of the species found are compared to an internal library of lipid standards as well as the LIPID MAPS Structure Database by using specifically developed processing tools. Features detected within the DTCCSN2 and m/z ranges of the analyzed standards are flagged as oxylipin-like species, which can be further characterized using drift-time alignment of product and precursor ions distinctive of DTIM-MS. This not only helps identification by reducing the number of annotations from LIPID MAPS but also guides discovery studies of potentially novel species. Testing the methodology on Salmonella enterica serovar Typhimurium-infected murine bone-marrow-derived macrophages and thrombin activated human platelets yields results in agreement with literature. This workflow has also annotated features as potentially novel oxylipins, confirming its ability in providing further insights into lipid analysis of biological samples.

A lipidome is the set of lipids in a given organism, cell or cell compartment and this set reflects the organism’s synthetic pathways and interactions with its environment. Recently, lipidomes of biological model organisms and cell lines were published and the number of functional studies of lipids is increasing. In this study we propose a homology metric that can quantify systematic differences in the composition of a lipidome. Algorithms were developed to 1. consistently convert lipids structure into SMILES, 2. determine structural similarity between molecular species and 3. describe a lipidome in a chemical space model. We tested lipid structure conversion and structure similarity metrics, in detail, using sets of isomeric ceramide molecules and chemically related phosphatidylinositols. Template-based SMILES showed the best properties for representing lipid-specific structural diversity. We also show that sequence analysis algorithms are best suited to calculate distances between such template-based SMILES and we adjudged the Levenshtein distance as best choice for quantifying structural changes. When all lipid molecules of the LIPIDMAPS structure database were mapped in chemical space, they automatically formed clusters corresponding to conventional chemical families. Accordingly, we mapped a pair of lipidomes into the same chemical space and determined the degree of overlap by calculating the Hausdorff distance. We named this metric the ‘Lipidome jUXtaposition (LUX) score’. First, we tested this approach for estimating the lipidome similarity on four yeast strains with known genetic alteration in fatty acid synthesis. We show that the LUX score reflects the genetic relationship and growth temperature better than conventional methods although the score is based solely on lipid structures. Next, we applied this metric to high-throughput data of larval tissue lipidomes of Drosophila. This showed that the LUX score is sufficient to cluster tissues and determine the impact of nutritional changes in an unbiased manner, despite the limited information on the underlying structural diversity of each lipidome. This study is the first effort to define a lipidome homology metric based on structures that will enrich functional association of lipids in a similar manner to measures used in genetics. Finally, we discuss the significance of the LUX score to perform comparative lipidome studies across species borders.

Percentage of lipids by lipid category on a molar basis in the plasma of Quaker parrots (Myiopsitta monachus) as determined by targeted lipidomics panels.

A database which contains structures and annotations of biologically relevant metabolites from public repositories such as LIPID MAPS, ChEBI, HMDB, PubChem, and KEGG. Users can search for molecular structure based on substructure, text, or mass.

Plasma concentration (μM) of non-lipid or lipid-like metabolites and organic acids important in fatty acid metabolic pathways in six Quaker parrots (Myiopsitta monachus) determined by mass spectrometry.

Lipids were separated by a C18 reverse phase column, using an Ascentis® Express 90 Å C18 HPLC column (15 cm x 2.1 mm; 2.7 μm, Supelco®) inserted into an HPLC system (Ultimate 3000 Dionex, Thermo Fisher Scientific, Bremen, Germany) with an autosampler coupled online to a Q-Exactive™ Hybrid Quadrupole-Orbitrap™ Mass Spectrometer (Thermo Fisher Scientific, Bremen, Germany). A volume of 5 μL of each sample mixture was injected into the HPLC column, at a flow rate of 260 μL/min. The temperature of the column oven was maintained at 50 °C. Elution started with 32% of mobile phase B, and the gradient used was: 45% B (1.5 min), 52% B (4 min), 58% B (5 min), 66% B (8 min), 70% B (11 min), 85% B (14 min), 97% B (18 min, maintained for 7 min), and 32% B (25.01 min, followed by a re-equilibration period of 8 min prior next injection).The Q-Exactive™ orbitrap mass spectrometer with a heated electrospray ionization source was operated in the positive mode (electrospray voltage of 3.0 kV) and negative mode (electrospray voltage of -2.7 kV). The sheath gas flow was 35 U, the auxiliary gas was 3 U, the capillary temperature was 320 °C, the S-lenses RF was 50 U and the probe`s temperature was 300 °C. Full scans MS spectra were acquired both in positive and negative modes in an m/z range of 300-1600, with a resolution of 70.000, automatic gain control (AGC) target of 3x10E6 and maximum injection time of 100 ms. For tandem MS (MS/MS) experiments, a top-10 data-dependent method was used. The top 10 most abundant precursor ions in full MS were selected to be fragmented in the collision cell HCD, with the dynamic exclusion of 30 s and an intensity threshold of 8x10E4. The MS/MS spectra were obtained with a resolution of 17,500; an AGC target of 1x10E5; an isolation window of 1 m/z; and a maximum injection time of 100 ms. A stepped normalized collision energy™ scheme was used and ranged between 25 and 30 eV for the positive ion mode and between 20, 24 and 28 for the negative ion mode. The MS/MS spectra obtained were those combining the information obtained with the different collision energies applied to each ionization mode. Data acquisition was carried out using the Xcalibur data system (V3.3, Thermo Fisher Scientific, USA).PC, LPC and SM were analysed in the LC-MS spectra in the positive ion mode, as [M+H]+ ions. The presence of the fragment ion at m/z 184, corresponding to the phosphocholine polar head group, in the MS/MS of [M+H]+ ions allows identifying PL molecular species belonging to the PC, LPC and SM classes, which were further differentiated by the characteristic retention times. The identification of PC, LPC and SM classes was confirmed in the LC-MS spectra in the negative ion mode, as formate adducts ([M+HCOO]- ions). MS/MS spectra of [M+HCOO]- ions of these three PL classes should display the typical fragment ion at m/z 168 (phosphocholine polar head group minus a methyl moiety). Carboxylate anions of fatty acyl chains can also be seen for PC and LPC. PE and LPE classes were analysed in negative ion mode ([M−H]- ions). The fragment ion at m/z 140 (phosphoethanolamine polar head group) and the carboxylate anions of fatty acyl chains can be found in the MS/MS data from negative ion mode. PI and PS species were analysed in negative ion mode, as [M−H]- ions. The presence of the fragment ion at m/z 241, corresponding to the phosphoinositol polar head group, in the MS/MS of [M-H]- ions, allows the identification of PI molecular species. PS species were identified in the MS/MS of [M-H]- ions by the neutral loss of -87Da from the molecular ion. The identification of the remaining lipid species belonging to the classes of carnitines (CAR), ceramides (Cer), cholesteryl esters (CE, fragment ion at m/z 369), diacylglycerols (DG) and triacylglycerols (TG), was made in LC-MS spectra in the positive ion mode, as [M+H]+ ions (CAR and Cer), [M+NH4]+ ions (CE) and [M+NH4]+ ions (DG and TG) respectively. LC-MS data were processed using the Lipostar software (Molecular Discovery Ltd., version 2.1.1 x64). This software was used for raw data import, peak detection, and identification. Lipid assignment and identification was made against a database created from LIPID MAPS structure database (version December 2022), that was then fragmented using the DM Manager Module in Lipostar, according to Lipostar fragmentation rules. The raw files were imported directly and aligned using the settings according to Lange et al. Briefly, automatic peak picking was performed with SDA smoothing level set to high and minimum S/N ratio 3. Automatic isotope clustering settings were set to 7 ppm with an RT tolerance of 0.2 min. The MS/MS filter was applied to keep only features with MS/MS spectra for identification. Lipid identification was made according to the following parameters: 5 ppm precursor ion mass tolerance and 10 ppm product ion mass tolerance. The automatic approval was performed to keep structures with a quality of 2-4 stars. The lists with the identified and approved species results were exported and we used MZmine software (v2.42) to perform relative quantification.Relative quantification was performed by exporting the peak area values to a computer spreadsheet. For data normalization, the peak areas of the extracted ion chromatograms (XIC) of the lipid precursor ions of each class were divided by the peak areas of the internal standards selected for the class. Missing values were replaced by 1/5 of the minimum positive values detected in the data set. Univariate and multivariate statistical analyses were performed using R version 3.5.1 in Rstudio version 1.1.4. The data sets were then normalized to the internal standard, generalized log2, and EigenMS. Principal component analysis (PCA) was performed using the R libraries FactoMineR and factoextra. Heatmaps were created using the R package heatmap using “Euclidean” as the clustering distance and “ward.D” as the clustering method. The normality of the data was tested with the Shapiro−Wilk test. To test the significance of the differences between conditions, we used either the ANOVA or Kruskal−Wallis test, followed by Tukey’s or Dunn’s test, respectively, using the R package Rstatix. A p-value < 0.05 was considered an indicator of statistical significance. All graphics and boxplots were created using the R package ggplot2.

In this study, we used clownfish Amphiprion ocellaris as a model organism to study reef fish mechanisms of thermal adaptation and determine how high temperature affects different lipid aspects in fish. We exposed juvenile fish to two different experimental conditions, implemented over 28 days: average tropical water temperatures (26 ˚C, control) or average warm pool temperatures (30 ˚C). We then performed several analyses on fish muscle and liver tissues: i) total lipid content (%), ii) lipid peroxides, iii) fatty acid profiles, iv) lipid metabolic pathways and v) body condition. Raw data from these analyses were compiled and included in three datasheets: one for the fatty acid masses/concentration datasets, the second for body condition (length and weight) dataset and the third for fatty acid enrichment dataset based on LMSD – Lipid Maps Structure Database; KEGG – Kyoto Encyclopedia of Genes and Genomes; and HMBD – Human Metabolome Database. Statistical analyses and conclusions from the study can be found in Madeira et al. 2021 entitled "Conserved fatty acid profiles and lipid metabolic pathways in a tropical reef fish exposed to ocean warming – an adaptation mechanism of tolerant species?", published in STOTEN, https://doi.org/10.1016/j.scitotenv.2021.146738

Plasma free hydroxy fatty acid concentration (μM) in six Quaker parrots (Myiopsitta monachus) determined by mass spectrometry.

This dataset contains the European data of MICROBIS, a database of marine microbial biota. AccConID=21 AccConstrDescription=This license lets others distribute, remix, tweak, and build upon your work, even commercially, as long as they credit you for the original creation. This is the most accommodating of licenses offered. Recommended for maximum dissemination and use of licensed materials. AccConstrDisplay=This dataset is licensed under a Creative Commons Attribution 4.0 International License. AccConstrEN=Attribution (CC BY) AccessConstraint=Attribution (CC BY) Acronym=None added_date=2009-05-29 12:11:29.413000 BrackishFlag=1 CDate=2009-06-09 cdm_data_type=Other CheckedFlag=1 Citation=Neal, P. R., Patterson, D.J. MICROBIS. 1 Jan. 2005, Version 1 (European data). Comments=None ContactEmail=None Conventions=COARDS, CF-1.6, ACDD-1.3 CurrencyDate=None DasID=1980 DasOrigin=Data collection DasType=Data DasTypeID=1 DateLastModified={'date': '2025-08-22 01:33:40.264606', 'timezone_type': 1, 'timezone': '+02:00'} DescrCompFlag=0 DescrTransFlag=0 Easternmost_Easting=-25.0 EmbargoDate=None EngAbstract=This dataset contains the European data of MICROBIS, a database of marine microbial biota. EngDescr=This dataset contains the European data of MICROBIS.

The MICROBIS database serves legacy, lipidomic, and pyrosequencing data and associated contextual data collected as part of the ICoMM (International Census of Marine Microbes) Census of Marine Life Ocean Realm Project. Legacy data include geospatial and environmental data collected from environmental sequencing surveys prior to the initiation of the ICoMM effort. MICROBIS links to lipid structures (via Lipid Maps) and a mass spectrometry library that contains lipid data derived from microbes from modern and ancient environments. FreshFlag=1 geospatial_lat_max=60.9 geospatial_lat_min=50.4 geospatial_lat_units=degrees_north geospatial_lon_max=-25.0 geospatial_lon_min=-38.53 geospatial_lon_units=degrees_east infoUrl=None InputNotes=None institution=WHOI License=https://creativecommons.org/licenses/by/4.0/ Lineage=Prior to publication data undergo quality control checked which are described in https://github.com/EMODnet/EMODnetBiocheck?tab=readme-ov-file#understanding-the-output MarineFlag=1 modified_sync=2021-02-05 00:00:00 Northernmost_Northing=60.9 OrigAbstract=None OrigDescr=None OrigDescrLang=English OrigDescrLangNL=Engels OrigLangCode=en OrigLangCodeExtended=eng OrigLangID=15 OrigTitle=None OrigTitleLang=English OrigTitleLangCode=en OrigTitleLangID=15 OrigTitleLangNL=Engels Progress=Completed PublicFlag=1 ReleaseDate=May 29 2009 12:00AM ReleaseDate0=2009-05-29 RevisionDate=None SizeReference=24 261 distribution records sourceUrl=(local files) Southernmost_Northing=50.4 standard_name_vocabulary=CF Standard Name Table v70 StandardTitle=MICROBIS Database (version 1) - European data StatusID=1 subsetVariables=ScientificName,YearCollected,MonthCollected,DayCollected,aphia_id TerrestrialFlag=1 time_coverage_end=2003-05-28T01:00:00Z time_coverage_start=2002-09-16T01:00:00Z UDate=2025-03-26 VersionDate=None VersionDay=None VersionMonth=5 VersionName=1 VersionYear=2009 VlizCoreFlag=1 Westernmost_Easting=-38.53

Plasma simple glycosphingolipids (cerebrosides and globosides) concentration (μM) in six Quaker parrots (Myiopsitta monachus) determined by mass spectrometry.

Plasma ceramide phosphocholines (sphingomyelins) concentration (μM) in six Quaker parrots (Myiopsitta monachus) determined by mass spectrometry.

Plasma dihydroceramides concentration (μM) in six Quaker parrots (Myiopsitta monachus) determined by mass spectrometry.

Plasma monoacylglycerophosphocholines (lysophosphatidylcholines) and monoalkylglycerophosphocholines concentration (μM) in six Quaker parrots (Myiopsitta monachus) determined by mass spectrometry.

Plasma bile acids concentration (μM) in six Quaker parrots (Myiopsitta monachus) determined by mass spectrometry.

Plasma diacylglycerols concentration (μM) in six Quaker parrots (Myiopsitta monachus) determined by mass spectrometry.

Plasma triacylglycerols concentration (μM) in six Quaker parrots (Myiopsitta monachus) determined by mass spectrometry.

Plasma alkylacylglycerophosphocholines concentration (μM) in six Quaker parrots (Myiopsitta monachus) determined by mass spectrometry.