Content | |
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Description | Lipidomics |
Contact | |
Primary citation | PMID 17584797 |
Release date | 2003 |
Access | |
Website | www.lipidmaps.org |
LIPID MAPS (Lipid Metabolites and Pathways Strategy) is a web portal designed to be a gateway to Lipidomics resources. The resource has spearheaded a classification of biological lipids, dividing them into eight general categories. [1] LIPID MAPS provides standardised methodologies for mass spectrometry analysis of lipids, e.g. [2] [3] [4]
LIPID MAPS has been cited as evidence of a growing appreciation of the study of lipid metabolism [5] and the rapid development and standardisation of the lipidomics field [6] [7]
Key LIPID MAPS resources include:
Tools available from LIPID MAPS enable scientists to identify likely lipids in their samples from mass spectrometry data, a common method to analyse lipids in biological specimens. In particular, LipidFinder [10] enables analysis of MS data. Tutorials and educational material on lipids are also available at the site. [11]
In January 2020, LIPID MAPS became an ELIXIR service. [12] and in 2024 a core data resource. In addition, it joined Global Biodata Coalition as a core biodata resource. [13]
LIPID MAPS was founded in 2003 with NIH funding. [14] LIPID MAPS was previously funded by a multi-institutional grant from Wellcome, and is now funded under an MRC Partnership award, held jointly by University of Cardiff led by Prof Valerie O'Donnell, the Babraham Institute, UCSD and Swansea University, and The University of Edinburgh. Wakelam's obituary describes LIPID MAPS as unifying the field of lipidomics. [15]
LIPID MAPS is sponsored by Cayman Chemical and Avanti Polar lipids
In molecular biology, post-translational modification (PTM) is the covalent process of changing proteins following protein biosynthesis. PTMs may involve enzymes or occur spontaneously. Proteins are created by ribosomes, which translate mRNA into polypeptide chains, which may then change to form the mature protein product. PTMs are important components in cell signalling, as for example when prohormones are converted to hormones.
Lipidomics is the large-scale study of pathways and networks of cellular lipids in biological systems. 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 other major classes of biological molecules. Lipidomics is a relatively recent research field that has been driven by rapid advances in technologies such as mass spectrometry (MS), nuclear magnetic resonance (NMR) spectroscopy, fluorescence spectroscopy, dual polarisation interferometry and computational methods, coupled with the recognition of the role of lipids in many metabolic diseases such as obesity, atherosclerosis, stroke, hypertension and diabetes. This rapidly expanding field complements the huge progress made in genomics and proteomics, all of which constitute the family of systems biology.
Metabolomics is the scientific study of chemical processes involving metabolites, the small molecule substrates, intermediates, and products of cell metabolism. Specifically, metabolomics is the "systematic study of the unique chemical fingerprints that specific cellular processes leave behind", the study of their small-molecule metabolite profiles. The metabolome represents the complete set of metabolites in a biological cell, tissue, organ, or organism, which are the end products of cellular processes. Messenger RNA (mRNA), gene expression data, and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell, and thus, metabolomics provides a direct "functional readout of the physiological state" of an organism. There are indeed quantifiable correlations between the metabolome and the other cellular ensembles, which can be used to predict metabolite abundances in biological samples from, for example mRNA abundances. One of the ultimate challenges of systems biology is to integrate metabolomics with all other -omics information to provide a better understanding of cellular biology.
The metabolome refers to the complete set of small-molecule chemicals found within a biological sample. The biological sample can be a cell, a cellular organelle, an organ, a tissue, a tissue extract, a biofluid or an entire organism. The small molecule chemicals found in a given metabolome may include both endogenous metabolites that are naturally produced by an organism as well as exogenous chemicals that are not naturally produced by an organism.
BRENDA is the world's most comprehensive online database for functional, biochemical and molecular biological data on enzymes, metabolites and metabolic pathways. It contains data on the properties, function and significance of all enzymes classified by the Enzyme Commission of the International Union of Biochemistry and Molecular Biology (IUBMB). As ELIXIR Core Data Resource and Global Core Biodata Resource, BRENDA is considered a data resource of critical importance to the international life sciences research community. The database compiles a representative overview of enzymes and metabolites using current research data from primary scientific literature and thus serves the purpose of facilitating information retrieval for researchers. BRENDA is subject to the terms of the Creative Commons license, is accessible worldwide and can be used free of charge. As one of the digital resources of the Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures, BRENDA is part of the integrated biodata infrastructure DSMZ Digital Diversity.
The Protein Information Resource (PIR), located at Georgetown University Medical Center, is an integrated public bioinformatics resource to support genomic and proteomic research, and scientific studies. It contains protein sequences databases
The DrugBank database is a comprehensive, freely accessible, online database containing information on drugs and drug targets created and maintained by the University of Alberta and The Metabolomics Innovation Centre located in Alberta, Canada. As both a bioinformatics and a cheminformatics resource, DrugBank combines detailed drug data with comprehensive drug target information. DrugBank has used content from Wikipedia; Wikipedia also often links to Drugbank, posing potential circular reporting issues.
The Biological General Repository for Interaction Datasets (BioGRID) is a curated biological database of protein-protein interactions, genetic interactions, chemical interactions, and post-translational modifications created in 2003 (originally referred to as simply the General Repository for Interaction Datasets by Mike Tyers, Bobby-Joe Breitkreutz, and Chris Stark at the Lunenfeld-Tanenbaum Research Institute at Mount Sinai Hospital. It strives to provide a comprehensive curated resource for all major model organism species while attempting to remove redundancy to create a single mapping of data. Users of The BioGRID can search for their protein, chemical or publication of interest and retrieve annotation, as well as curated data as reported, by the primary literature and compiled by in house large-scale curation efforts. The BioGRID is hosted in Toronto, Ontario, Canada and Dallas, Texas, United States and is partnered with the Saccharomyces Genome Database, FlyBase, WormBase, PomBase, and the Alliance of Genome Resources. The BioGRID is funded by the NIH and CIHR. BioGRID is an observer member of the International Molecular Exchange Consortium.
Expasy is an online bioinformatics resource operated by the SIB Swiss Institute of Bioinformatics. It is an extensible and integrative portal which provides access to over 160 databases and software tools and supports a range of life science and clinical research areas, from genomics, proteomics and structural biology, to evolution and phylogeny, systems biology and medical chemistry. The individual resources are hosted in a decentralized way by different groups of the SIB Swiss Institute of Bioinformatics and partner institutions.
The lipidome refers to the totality of lipids in cells. Lipids are one of the four major molecular components of biological organisms, along with proteins, sugars and nucleic acids. Lipidome is a term coined in the context of omics in modern biology, within the field of lipidomics. It can be studied using mass spectrometry and bioinformatics as well as traditional lab-based methods. The lipidome of a cell can be subdivided into the membrane-lipidome and mediator-lipidome.
The Pathogen-Host Interactions database (PHI-base) is a biological database that contains manually curated information on genes experimentally proven to affect the outcome of pathogen-host interactions. The database has been maintained by researchers at Rothamsted Research and external collaborators since 2005. PHI-base has been part of the UK node of ELIXIR, the European life-science infrastructure for biological information, since 2016.
Rfam is a database containing information about non-coding RNA (ncRNA) families and other structured RNA elements. It is an annotated, open access database originally developed at the Wellcome Trust Sanger Institute in collaboration with Janelia Farm, and currently hosted at the European Bioinformatics Institute. Rfam is designed to be similar to the Pfam database for annotating protein families.
PDBsum is a database that provides an overview of the contents of each 3D macromolecular structure deposited in the Protein Data Bank (PDB).
The Human Metabolome Database (HMDB) is a comprehensive, high-quality, freely accessible, online database of small molecule metabolites found in the human body. It has been created by the Human Metabolome Project funded by Genome Canada and is one of the first dedicated metabolomics databases. The HMDB facilitates human metabolomics research, including the identification and characterization of human metabolites using NMR spectroscopy, GC-MS spectrometry and LC/MS spectrometry. To aid in this discovery process, the HMDB contains three kinds of data: 1) chemical data, 2) clinical data, and 3) molecular biology/biochemistry data (Fig. 1–3). The chemical data includes 41,514 metabolite structures with detailed descriptions along with nearly 10,000 NMR, GC-MS and LC/MS spectra.
The European Nucleotide Archive (ENA) is a repository providing free and unrestricted access to annotated DNA and RNA sequences. It also stores complementary information such as experimental procedures, details of sequence assembly and other metadata related to sequencing projects. The archive is composed of three main databases: the Sequence Read Archive, the Trace Archive and the EMBL Nucleotide Sequence Database. The ENA is produced and maintained by the European Bioinformatics Institute and is a member of the International Nucleotide Sequence Database Collaboration (INSDC) along with the DNA Data Bank of Japan and GenBank.
BacDive is the worldwide largest database for standardized bacterial and archaeal strain-level information.
Carbohydrate Structure Database (CSDB) is a free curated database and service platform in glycoinformatics, launched in 2005 by a group of Russian scientists from N.D. Zelinsky Institute of Organic Chemistry, Russian Academy of Sciences. CSDB stores published structural, taxonomical, bibliographic and NMR-spectroscopic data on natural carbohydrates and carbohydrate-related molecules.
Markus R. Wenk is a Swiss biochemist and academic. He is Dean of the College of Health and Life Sciences at Hamad Bin Khalifa University.
Valerie B. O'Donnell OBE, FMedSci, MAE, FLSW, is an Irish biochemist. She is a member of the Academy of Europe.