The Experts below are selected from a list of 105 Experts worldwide ranked by ideXlab platform
Christian R H Raetz - One of the best experts on this subject based on the ideXlab platform.
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Crystal structure of LpxK, the 4′-kinase of lipid A biosynthesis and atypical P-loop kinase functioning at the membrane interface
Proceedings of the National Academy of Sciences of the United States of America, 2012Co-Authors: Ryan P. Emptage, Kelly D. Daughtry, Charles W. Pemble, Christian R H RaetzAbstract:In Gram-negative bacteria, the hydrophobic anchor of the outer membrane lipopolysaccharide is lipid A, a Saccharolipid that plays key roles in both viability and pathogenicity of these organisms. The tetraacyldisaccharide 4′-kinase (LpxK) of the diverse P-loop–containing nucleoside triphosphate hydrolase superfamily catalyzes the sixth step in the biosynthetic pathway of lipid A, and is the only known P-loop kinase to act upon a lipid substrate at the membrane. Here, we report the crystal structures of apo- and ADP/Mg2+-bound forms of Aquifex aeolicus LpxK to a resolution of 1.9 A and 2.2 A, respectively. LpxK consists of two α/β/α sandwich domains connected by a two-stranded β-sheet linker. The N-terminal domain, which has most structural homology to other family members, is responsible for catalysis at the P-loop and positioning of the disaccharide-1-phosphate substrate for phosphoryl transfer on the inner membrane. The smaller C-terminal domain, a substructure unique to LpxK, helps bind the nucleotide substrate and Mg2+ cation using a 25° hinge motion about its base. Activity was severely reduced in alanine point mutants of conserved residues D138 and D139, which are not directly involved in ADP or Mg2+ binding in our structures, indicating possible roles in phosphoryl acceptor positioning or catalysis. Combined structural and kinetic studies have led to an increased understanding of the enzymatic mechanism of LpxK and provided the framework for structure-based antimicrobial design.
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LpxI: A Novel PhosphoSaccharolipid Hydrolase
Biophysical Journal, 2012Co-Authors: Louis E. Metzger, Christian R H Raetz, John K. Lee, Janet Finer-moore, Robert M. StroudAbstract:Gram-negative bacteria possess an asymmetric outer membrane in which the inner leaflet is composed primarily of phospholipids, while the outer leaflet contains mainly lipopolysaccharide (LPS). LPS forms a structural barrier that protects Gram-negative bacteria from antibiotics and other environmental stressors. LPS is anchored to the outer membrane by lipid A, a unique glucosamine-based Saccharolipid. Lipid A biosynthesis is required for bacterial viability and pathogenesis. While most lipid A biosynthetic genes are present in a single copy, one gene, lpxH, encoding a membrane-associated specific UDP-diacylglucosamine hydrolase, is absent in ∼30% of Gram-negative bacteria. We hypothesized that a transformational analogue of lpxH must exist in these organisms. We identified this gene, designated lpxI, in Caulobacter crescentus, and confirmed its ability to cover for a deficiency of lpxH in Eschserichia coli. LpxI lacks homology to any other known enzyme. We over-expressed LpxI, purified it, and obtained protein crystals. We solved the X-ray crystal structure of this peripheral membrane enzyme using a single-wavelength anomalous dispersion (SAD) dataset collected on Se-Met derivatized protein. The structural data reveal two domains, each having a novel fold. Unexpectedly, “apo” LpxI co-purified and co-crystallized stoichiometrically with its product, diacylglucosamine-1-phosphate (lipid X), the Saccharolipid precursor of lipid A. We then identified and determined the 2.5 A X-ray crystal structure of an inactive point mutant of Caulobacter crescentus LpxI, which co-purified in a stoichiometric ratio with its substrate, UDP-2,3-diacyglucosamine. The conformation of substrate-liganded LpxI differs significantly from the product -liganded wild-type enzyme. Taken together with analytical unltracentrifugation data, this observation suggests that large-scale domain re-arrangement occurs during LpxI substrate binding and/or catalysis. These data provide an interesting example of lipid-protein interaction, and set the stage for additional structural and mechanistic work.
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Discovery of new biosynthetic pathways: the lipid A story.
Journal of Lipid Research, 2009Co-Authors: Christian R H Raetz, Ziqiang Guan, Brian O. Ingram, David A. Six, Feng Song, Xiaoyuan Wang, Jinshi ZhaoAbstract:The outer monolayer of the outer membrane of Gram-negative bacteria consists of the lipid A component of lipopolysaccharide (LPS), a glucosamine-based Saccharolipid that is assembled on the inner surface of the inner membrane. The first six enzymes of the lipid A pathway are required for bacterial growth and are excellent targets for the development of new antibiotics. Following assembly, the ABC transporter MsbA flips nascent LPS to the periplasmic side of the inner membrane, whereupon additional transport proteins direct it to the outer surface of the outer membrane. Depending on the bacterium, various covalent modifications of the lipid A moiety may occur during the transit of LPS to the outer membrane. These extra-cytoplasmic modification enzymes are therefore useful as reporters for monitoring LPS trafficking. Because of its conserved structure in diverse Gram-negative pathogens, lipid A is recognized as foreign by the TLR4/MD2 receptor of the mammalian innate immune system, resulting in rapid macrophage activation and robust cytokine production.
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a comprehensive classification system for lipids
European Journal of Lipid Science and Technology, 2005Co-Authors: Eoin Fahy, Alfred H. Merrill, Christopher K Glass, David W. Russell, Shankar Subramaniam, Yousuke Seyama, Robert C. Murphy, Christian R H Raetz, Alex H Brown, Walter ShawAbstract:Lipids are produced, transported, and recognized by the concerted actions of numerous enzymes, binding proteins, and receptors. A comprehensive analysis of lipid molecules, “lipidomics,” in the context of genomics and proteomics is crucial to understanding cellular physiology and pathology; consequently, lipid biology has become a major research target of the postgenomic revolution and systems biology. To facilitate international communication about lipids, a comprehensive classification of lipids with a common platform that is compatible with informatics requirements has been developed to deal with the massive amounts of data that will be generated by our lipid community. As an initial step in this development, we divide lipids into eight categories (fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, sterol lipids, prenol lipids, Saccharolipids, and polyketides) containing distinct classes and subclasses of molecules, devise a common manner of representing the chemical structures of individual lipids and their derivatives, and provide a 12 digit identifier for each unique lipid molecule. The lipid classification scheme is chemically based and driven by the distinct hydrophobic and hydrophilic elements that compose the lipid. This structured vocabulary will facilitate the systematization of lipid biology and enable the cataloging of lipids and their properties in a way that is compatible with other macromolecular databases.[Reprinted with copyright permission from the Journal of Lipid Research. 2005. 46: 839–861.]
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A comprehensive classification system for lipids
Journal of Lipid Research, 2005Co-Authors: Edward Fahy, Alfred H. Merrill, H. Alex Brown, Christopher K Glass, David W. Russell, Shankar Subramaniam, Yousuke Seyama, Robert C. Murphy, Christian R H Raetz, Walter ShawAbstract:Lipids are produced, transported, and recognized by the concerted actions of numerous enzymes, binding proteins, and receptors. A comprehensive analysis of lipid molecules, "lipidomics," in the context of genomics and proteomics is crucial to understanding cellular physiology and pathology; consequently, lipid biology has become a major research target of the postgenomic revolution and systems biology. To facilitate international communication about lipids, a comprehensive classification of lipids with a common platform that is compatible with informatics requirements has been developed to deal with the massive amounts of data that will be generated by our lipid community. As an initial step in this development, we divide lipids into eight categories (fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, sterol lipids, prenol lipids, Saccharolipids, and polyketides) containing distinct classes and subclasses of molecules, devise a common manner of representing the chemical structures of individual lipids and their derivatives, and provide a 12 digit identifier for each unique lipid molecule. The lipid classification scheme is chemically based and driven by the distinct hydrophobic and hydrophilic elements that compose the lipid. This structured vocabulary will facilitate the systematization of lipid biology and enable the cataloging of lipids and their properties in a way that is compatible with other macromolecular databases.
Xianyang Chen - One of the best experts on this subject based on the ideXlab platform.
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Identification of the lipid biomarkers from plasma in idiopathic pulmonary fibrosis by Lipidomics.
BMC pulmonary medicine, 2017Co-Authors: Feng Yan, Wenjun Wang, Zhensong Wen, Rui Wang, Wenling Luo, Xianyang ChenAbstract:Idiopathic pulmonary fibrosis (IPF) is an irreversible interstitial pulmonary disease featured by high mortality, chronic and progressive course, and poor prognosis with unclear etiology. Currently, more studies have been focusing on identifying biomarkers to predict the progression of IPF, such as genes, proteins, and lipids. Lipids comprise diverse classes of molecules and play a critical role in cellular energy storage, structure, and signaling. The role of lipids in respiratory diseases, including cystic fibrosis, asthma and chronic obstructive pulmonary disease (COPD) has been investigated intensely in the recent years. The human serum lipid profiles in IPF patients however, have not been thoroughly understood and it will be very helpful if there are available molecular biomarkers, which can be used to monitor the disease progression or provide prognostic information for IPF disease. In this study, we performed the ultraperformance liquid chromatography coupled with quadrupole time of flight mass spectrometry (UPLC-QTOF/MS) to detect the lipid variation and identify biomarker in plasma of IPF patients. The plasma were from 22 IPF patients before received treatment and 18 controls. A total of 507 individual blood lipid species were determined with lipidomics from the 40 plasma samples including 20 types of fatty acid, 159 types of glycerolipids, 221 types of glycerophospholipids, 47 types of sphingolipids, 46 types of sterol lipids, 7 types of prenol lipids, 3 types of Saccharolipids, and 4 types of polyketides. By comparing the variations in the lipid metabolite levels in IPF patients, a total of 62 unique lipids were identified by statistical analysis including 24 kinds of glycerophoslipids, 30 kinds of glycerolipids, 3 kinds of sterol lipids, 4 kinds of sphingolipids and 1 kind of fatty acids. Finally, 6 out of 62 discriminating lipids were selected as the potential biomarkers, which are able to differentiate between IPF disease and controls with ROC analysis. Our results provided vital information regarding lipid metabolism in IPF patients and more importantly, a few potentially promising biomarkers were firstly identified which may have a predictive role in monitoring and diagnosing IPF disease.
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Potential plasma lipid biomarkers in early-stage breast cancer
Biotechnology Letters, 2017Co-Authors: Nan Jiang, Chengping Yan, Guofen Zhang, Lijie Pan, Yan Weng, Xianyang Chen, Wenjun Wang, Liwei Zhang, Guoshan YangAbstract:ObjectiveTo find new biomarkers for early diagnosis of breast cancer.Results847 lipid species were identified from 78 plasma samples (37 breast cancer samples and 41 healthy controls) by ultra HPLC coupled with quadrupole time-of-flight tandem mass spectrometry. These include 321 glycerophospholipids (GPs), 265 glycerolipids (GLs), 91 sphingolipids (SPs), 77 fatty acyls (FAs), 68 sterol lipids (STs), 18 prenol lipids (PRs), 6 polyketides (PKs), and 1 Saccharolipid (SL). Separation was observed from an orthogonal signal correction Partial Least Square Discrimination Analysis model. Based on this analysis, six differentiating lipids were identified: PC (20:2/20:5), PC (22:0/24:1), TG (12:0/14:1), and DG (18:1/18:2) had high levels, whereas PE (15:0/19:1) and N-palmitoyl proline had low levels in the breast cancer samples compared with the healthy controls. Furthermore, significant differences in metabolites were found among some clinical characteristics.ConclusionsOur results reveal that six specific lipids could serve as potential biomarkers for early diagnosis of breast cancer.
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Potential plasma lipid biomarkers in early-stage breast cancer
Biotechnology letters, 2017Co-Authors: Nan Jiang, Chengping Yan, Guofen Zhang, Lijie Pan, Yan Weng, Xianyang Chen, Wenjun Wang, Liwei Zhang, Guoshan YangAbstract:To find new biomarkers for early diagnosis of breast cancer. 847 lipid species were identified from 78 plasma samples (37 breast cancer samples and 41 healthy controls) by ultra HPLC coupled with quadrupole time-of-flight tandem mass spectrometry. These include 321 glycerophospholipids (GPs), 265 glycerolipids (GLs), 91 sphingolipids (SPs), 77 fatty acyls (FAs), 68 sterol lipids (STs), 18 prenol lipids (PRs), 6 polyketides (PKs), and 1 Saccharolipid (SL). Separation was observed from an orthogonal signal correction Partial Least Square Discrimination Analysis model. Based on this analysis, six differentiating lipids were identified: PC (20:2/20:5), PC (22:0/24:1), TG (12:0/14:1), and DG (18:1/18:2) had high levels, whereas PE (15:0/19:1) and N-palmitoyl proline had low levels in the breast cancer samples compared with the healthy controls. Furthermore, significant differences in metabolites were found among some clinical characteristics. Our results reveal that six specific lipids could serve as potential biomarkers for early diagnosis of breast cancer.
Wenjun Wang - One of the best experts on this subject based on the ideXlab platform.
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Identification of the lipid biomarkers from plasma in idiopathic pulmonary fibrosis by Lipidomics.
BMC pulmonary medicine, 2017Co-Authors: Feng Yan, Wenjun Wang, Zhensong Wen, Rui Wang, Wenling Luo, Xianyang ChenAbstract:Idiopathic pulmonary fibrosis (IPF) is an irreversible interstitial pulmonary disease featured by high mortality, chronic and progressive course, and poor prognosis with unclear etiology. Currently, more studies have been focusing on identifying biomarkers to predict the progression of IPF, such as genes, proteins, and lipids. Lipids comprise diverse classes of molecules and play a critical role in cellular energy storage, structure, and signaling. The role of lipids in respiratory diseases, including cystic fibrosis, asthma and chronic obstructive pulmonary disease (COPD) has been investigated intensely in the recent years. The human serum lipid profiles in IPF patients however, have not been thoroughly understood and it will be very helpful if there are available molecular biomarkers, which can be used to monitor the disease progression or provide prognostic information for IPF disease. In this study, we performed the ultraperformance liquid chromatography coupled with quadrupole time of flight mass spectrometry (UPLC-QTOF/MS) to detect the lipid variation and identify biomarker in plasma of IPF patients. The plasma were from 22 IPF patients before received treatment and 18 controls. A total of 507 individual blood lipid species were determined with lipidomics from the 40 plasma samples including 20 types of fatty acid, 159 types of glycerolipids, 221 types of glycerophospholipids, 47 types of sphingolipids, 46 types of sterol lipids, 7 types of prenol lipids, 3 types of Saccharolipids, and 4 types of polyketides. By comparing the variations in the lipid metabolite levels in IPF patients, a total of 62 unique lipids were identified by statistical analysis including 24 kinds of glycerophoslipids, 30 kinds of glycerolipids, 3 kinds of sterol lipids, 4 kinds of sphingolipids and 1 kind of fatty acids. Finally, 6 out of 62 discriminating lipids were selected as the potential biomarkers, which are able to differentiate between IPF disease and controls with ROC analysis. Our results provided vital information regarding lipid metabolism in IPF patients and more importantly, a few potentially promising biomarkers were firstly identified which may have a predictive role in monitoring and diagnosing IPF disease.
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Potential plasma lipid biomarkers in early-stage breast cancer
Biotechnology Letters, 2017Co-Authors: Nan Jiang, Chengping Yan, Guofen Zhang, Lijie Pan, Yan Weng, Xianyang Chen, Wenjun Wang, Liwei Zhang, Guoshan YangAbstract:ObjectiveTo find new biomarkers for early diagnosis of breast cancer.Results847 lipid species were identified from 78 plasma samples (37 breast cancer samples and 41 healthy controls) by ultra HPLC coupled with quadrupole time-of-flight tandem mass spectrometry. These include 321 glycerophospholipids (GPs), 265 glycerolipids (GLs), 91 sphingolipids (SPs), 77 fatty acyls (FAs), 68 sterol lipids (STs), 18 prenol lipids (PRs), 6 polyketides (PKs), and 1 Saccharolipid (SL). Separation was observed from an orthogonal signal correction Partial Least Square Discrimination Analysis model. Based on this analysis, six differentiating lipids were identified: PC (20:2/20:5), PC (22:0/24:1), TG (12:0/14:1), and DG (18:1/18:2) had high levels, whereas PE (15:0/19:1) and N-palmitoyl proline had low levels in the breast cancer samples compared with the healthy controls. Furthermore, significant differences in metabolites were found among some clinical characteristics.ConclusionsOur results reveal that six specific lipids could serve as potential biomarkers for early diagnosis of breast cancer.
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Potential plasma lipid biomarkers in early-stage breast cancer
Biotechnology letters, 2017Co-Authors: Nan Jiang, Chengping Yan, Guofen Zhang, Lijie Pan, Yan Weng, Xianyang Chen, Wenjun Wang, Liwei Zhang, Guoshan YangAbstract:To find new biomarkers for early diagnosis of breast cancer. 847 lipid species were identified from 78 plasma samples (37 breast cancer samples and 41 healthy controls) by ultra HPLC coupled with quadrupole time-of-flight tandem mass spectrometry. These include 321 glycerophospholipids (GPs), 265 glycerolipids (GLs), 91 sphingolipids (SPs), 77 fatty acyls (FAs), 68 sterol lipids (STs), 18 prenol lipids (PRs), 6 polyketides (PKs), and 1 Saccharolipid (SL). Separation was observed from an orthogonal signal correction Partial Least Square Discrimination Analysis model. Based on this analysis, six differentiating lipids were identified: PC (20:2/20:5), PC (22:0/24:1), TG (12:0/14:1), and DG (18:1/18:2) had high levels, whereas PE (15:0/19:1) and N-palmitoyl proline had low levels in the breast cancer samples compared with the healthy controls. Furthermore, significant differences in metabolites were found among some clinical characteristics. Our results reveal that six specific lipids could serve as potential biomarkers for early diagnosis of breast cancer.
Daniel Kahne - One of the best experts on this subject based on the ideXlab platform.
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On the essentiality of lipopolysaccharide to Gram-negative bacteria.
Current Opinion in Microbiology, 2013Co-Authors: Ge Zhang, Timothy C Meredith, Daniel KahneAbstract:Lipopolysaccharide is a highly acylated Saccharolipid located on the outer leaflet of the outer membrane of Gram-negative bacteria. Lipopolysaccharide is critical to maintaining the barrier function preventing the passive diffusion of hydrophobic solutes such as antibiotics and detergents into the cell. Lipopolysaccharide has been considered an essential component for outer membrane biogenesis and cell viability based on pioneering studies in the model Gram-negative organisms Escherichia coli and Salmonella. With the isolation of lipopolysaccharide-null mutants in Neisseria meningitidis, Moraxella catarrhalis, and most recently in Acinetobacter baumannii, it has become increasingly apparent that lipopolysaccharide is not an essential outer membrane building block in all organisms. We suggest the accumulation of toxic intermediates, misassembly of essential outer membrane porins, and outer membrane stress response pathways that are activated by mislocalized lipopolysaccharide may collectively contribute to the observed strain-dependent essentiality of lipopolysaccharide.
Shankar Subramaniam - One of the best experts on this subject based on the ideXlab platform.
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Bioinformatics and Systems Biology of the Lipidome
Chemical reviews, 2011Co-Authors: Shankar Subramaniam, Eoin Fahy, Shakti Gupta, Manish Sud, Robert W. Byrnes, Dawn Cotter, Ashok Reddy Dinasarapu, Mano Ram MauryaAbstract:Lipids play an important role in physiology and pathophysiology of living systems. Until a few decades ago, the number of lipid molecules that were chemically characterized was a few hundred at most and were catalogued in monographs and compendia.1 Since the advent of the era of the genome and the proteome, there has been increasing recognition that other macromolecules like lipids and polysaccharides in living systems display considerable structural diversity and systematic efforts are underway to identify, characterize and catalog these molecules. With mass spectrometric techniques coming of age, several thousand distinct molecular species have been identified from living species and the roles of several of these are beginning to be characterized.2 Unlike genes and proteins, whose defined alphabets provide the framework for ontologies and classification at the sequence level, lipids and polysaccharides have been characterized for the large part by popular names, with no foundations for systematic classification. The past two decades have witnessed two major advances in lipid biology. In the first, mass spectrometry has enabled the identification of thousands of lipid molecular species from cells and tissues and this has pointed to the important need for developing a systematic ontology that can rationally name and catalog the molecules. Second, the ability to investigate the functional roles of lipid molecules through systematic phenotypic studies has led to the identification of lipids as extremely important players in physiology and pathophysiology of living species.3 In combination with proteins and nucleic acids, lipids are integrally involved in biochemical networks that lead to phenotypes such as homeostasis, differentiation, and death of cells and tissues. Any approach to systems characterization of living systems, of necessity, has to include lipids along with other macromolecules and all complex cellular pathways involving lipid molecular species. Systems biology now extends in its scope to identify biosynthetic and metabolic lipid networks, cellular signaling networks that explicitly include lipid molecules and transcriptional and epigenetic networks where lipids play an integral role.4 Several large scale projects to characterize lipids and their functional roles have been initiated as exemplified by the LIPID MAPS5 effort. The LIPID MAPS is an exemplar systems biology project that measures cell-wide lipid changes in an attempt to reconstruct biochemical pathways associated with lipid processing and signaling. The cell-wide measurements of components of these pathways include mass spectrometric measurements of lipid changes in response to stimulus in mammalian cells, changes in transcription profiles in response to stimulus and in select cases proteomic changes in response to stimulus. Figure 1 shows a schematic of the LIPID MAPS experiments related to different lipid categories/pathways and the subsequent processing of the experimental data generated. Network reconstruction efforts rely on organization, analysis and integration of these data and this requires a strong bioinformatics and systems biology effort. The former has to include development of a systematic and universal classification and nomenclature system, design and development of lipid and lipid-gene, lipid-protein databases with appropriate functional annotations, and efficient query and analysis systems that can be broadly useful to the biology research community. The latter has to include methods for analysis of large scale lipid measurements in cells, reconstruction of lipid metabolic and biosynthetic pathways, and quantitative models of lipid fluxes in cells under varied perturbations. In this review, we will provide a comprehensive summary of extant developments in lipid bioinformatics and systems biology and discuss the outlook for the future integration of lipidomics into cellular and organismic biology. The sections that follow are delineated into the informatics approaches specific to lipid biology followed by an overview and exemplar approach to analysis of large scale lipidomic data towards a systems description of mammalian cells. Figure 1 Overview of the process of performing a quantitative lipid analysis of macrophage cell sample (in this example, a time-course experiment using bone marrow derived macrophages). Extraction methods, LC/GC purification methods, MS acquisition strategies ... 2. Classification, Ontology, Nomenclature and Structure Representation of Lipid Molecules The first step towards classification of lipids is the establishment of an ontology that is extensible, flexible and scalable. One must be able to classify, name and represent these molecules in a logical manner which is amenable to data basing and computational manipulation. Lipids have been loosely defined as biological substances that are generally hydrophobic in nature and in many cases soluble in organic solvents.6 These chemical features are present in a broad range of molecules such as fatty acids, phospholipids, sterols, sphingolipids, terpenes and others. In view of the fact that lipids comprise an extremely heterogeneous collection of molecules from a structural and functional standpoint, it is not surprising that there are significant differences with regard to the scope and organization of current classification schemes. 2.1. Classification, Ontology and Nomenclature In order to address the lack of a consistent classification and nomenclature methodology for lipids, LIPID MAPS consortium members have developed a comprehensive classification system for lipids.7 The consortium has taken a more chemistry-based approach and defines lipids as hydrophobic or amphipathic small molecules that may originate entirely or in part by carbanion based condensations of thioesters (such as fatty acids and polyketides) and/or by carbocation based condensations of isoprene units (such as prenols and sterols). Figure 2 shows the mechanisms of lipid biosynthesis.8 Based on this classification system, lipids have been divided into eight categories: Fatty acyls, Glycerolipids, Glycerophospholipids, Sphingolipids, Sterol lipids, Prenol lipids, Saccharolipids, and Polyketides. Each category is further divided into classes and subclasses. Additionally, following the existing rules and recommendations proposed by the International Union of Biochemistry and Applied Chemists and the International Union of Biochemistry and Molecular Biology (IUPAC-IUBMB) commission on Biochemical Nomenclature, a consistent nomenclature scheme has also been developed to provide systematic names for various classes and subclasses of lipids.7 Figure 2 Mechanisms of lipid biosynthesis. Biosynthesis of ketoacyl- and isoprene-containing lipids proceeds by carbanion and carbocation-mediated chain extension, respectively.8 All lipids in the LIPID MAPS Structure Database (LMSD) are classified and annotated using this comprehensive classification and nomenclature system developed by the LIPID MAPS consortium.
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a comprehensive classification system for lipids
European Journal of Lipid Science and Technology, 2005Co-Authors: Eoin Fahy, Alfred H. Merrill, Christopher K Glass, David W. Russell, Shankar Subramaniam, Yousuke Seyama, Robert C. Murphy, Christian R H Raetz, Alex H Brown, Walter ShawAbstract:Lipids are produced, transported, and recognized by the concerted actions of numerous enzymes, binding proteins, and receptors. A comprehensive analysis of lipid molecules, “lipidomics,” in the context of genomics and proteomics is crucial to understanding cellular physiology and pathology; consequently, lipid biology has become a major research target of the postgenomic revolution and systems biology. To facilitate international communication about lipids, a comprehensive classification of lipids with a common platform that is compatible with informatics requirements has been developed to deal with the massive amounts of data that will be generated by our lipid community. As an initial step in this development, we divide lipids into eight categories (fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, sterol lipids, prenol lipids, Saccharolipids, and polyketides) containing distinct classes and subclasses of molecules, devise a common manner of representing the chemical structures of individual lipids and their derivatives, and provide a 12 digit identifier for each unique lipid molecule. The lipid classification scheme is chemically based and driven by the distinct hydrophobic and hydrophilic elements that compose the lipid. This structured vocabulary will facilitate the systematization of lipid biology and enable the cataloging of lipids and their properties in a way that is compatible with other macromolecular databases.[Reprinted with copyright permission from the Journal of Lipid Research. 2005. 46: 839–861.]
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A comprehensive classification system for lipids
Journal of Lipid Research, 2005Co-Authors: Edward Fahy, Alfred H. Merrill, H. Alex Brown, Christopher K Glass, David W. Russell, Shankar Subramaniam, Yousuke Seyama, Robert C. Murphy, Christian R H Raetz, Walter ShawAbstract:Lipids are produced, transported, and recognized by the concerted actions of numerous enzymes, binding proteins, and receptors. A comprehensive analysis of lipid molecules, "lipidomics," in the context of genomics and proteomics is crucial to understanding cellular physiology and pathology; consequently, lipid biology has become a major research target of the postgenomic revolution and systems biology. To facilitate international communication about lipids, a comprehensive classification of lipids with a common platform that is compatible with informatics requirements has been developed to deal with the massive amounts of data that will be generated by our lipid community. As an initial step in this development, we divide lipids into eight categories (fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, sterol lipids, prenol lipids, Saccharolipids, and polyketides) containing distinct classes and subclasses of molecules, devise a common manner of representing the chemical structures of individual lipids and their derivatives, and provide a 12 digit identifier for each unique lipid molecule. The lipid classification scheme is chemically based and driven by the distinct hydrophobic and hydrophilic elements that compose the lipid. This structured vocabulary will facilitate the systematization of lipid biology and enable the cataloging of lipids and their properties in a way that is compatible with other macromolecular databases.
