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Foreword xix Preface xxi Abbreviations xxv Part I Introduction 1 1 Lipids and Lipidomics 3 1.1 Lipids, 3 1.1.1 Definition, 3EUR 1.1.2 Classification, 4 1.1.2.1 Lipid MAPS Approach, 7 1.1.2.2 Building Block Approach, 10 1.2 Lipidomics, 13 1.2.1 Definition, 13 1.2.2 History of Lipidomics, 14 References, 16 2 Mass Spectrometry for Lipidomics 21 2.1 Ionization Techniques, 21 2.1.1 Electrospray Ionization, 22 2.1.1.1 Principle of Electrospray Ionization, 22 2.1.1.2 Features of Electrospray Ionization for Lipid Analysis, 28 2.1.1.3 Advent of ESI for Lipid Analysis: Nano-ESI and Off-Axis Ion Inlets, 30 2.1.2 Matrix-Assisted Laser Desorption/Ionization, 30 2.2 Mass Analyzers, 32 2.2.1 Quadrupole, 32 2.2.2 Time of Flight, 33 2.2.3 Ion Trap, 35 2.3 Detector, 36 2.4 Tandem Mass Spectrometry Techniques, 37 2.4.1 Product-Ion Analysis, 37 2.4.2 Neutral-Loss Scan, 39 2.4.3 Precursor-Ion Scan, 39 2.4.4 Selected Reaction Monitoring, 39 2.4.5 Interweaving Tandem Mass Spectrometry Techniques, 40 2.5 Other Recent Advances in Mass Spectrometry for Lipid Analysis, 42 2.5.1 Ion-Mobility Mass Spectrometry, 43 2.5.2 Desorption Electrospray Ionization, 43 References, 45 3 Mass Spectrometry-Based Lipidomics Approaches 53 3.1 Introduction, 53 3.2 Shotgun Lipidomics: Direct Infusion-Based Approaches, 54 3.2.1 Devices for Direct Infusion, 54 3.2.2 Features of Shotgun Lipidomics, 55 3.2.3 Shotgun Lipidomics Approaches, 56 3.2.3.1 Tandem Mass Spectrometry-Based Shotgun Lipidomics, 56 3.2.3.2 High Mass Accuracy-Based Shotgun Lipidomics, 56 3.2.3.3 Multidimensional MS-Based Shotgun Lipidomics, 57 3.2.4 Advantages and Drawbacks, 63 3.2.4.1 Tandem Mass Spectrometry-Based Shotgun Lipidomics, 63 3.2.4.2 High Mass Accuracy-Based Shotgun Lipidomics, 63 3.2.4.3 Multidimensional Mass Spectrometry-Based Shotgun Lipidomics, 64 3.3 LC-MS-Based Approaches, 65 3.3.1 General, 65 3.3.1.1 Selected Ion Monitoring for LC-MS, 66 3.3.1.2 Selected/Multiple Reaction Monitoring for LC-MS, 67 3.3.1.3 Data-Dependent Analysis after LC-MS, 67 3.3.2 LC-MS-Based Approaches for Lipidomics, 68 3.3.2.1 Normal-Phase LC-MS-Based Approaches, 68 3.3.2.2 Reversed-Phase LC-MS-Based Approaches, 69 3.3.2.3 Hydrophilic Interaction LC-MS-Based Approaches, 71 3.3.2.4 Other LC-MS-Based Approaches, 72 3.3.3 Advantages and Drawbacks, 72 3.3.4 Identification of Lipid Species after LC-MS, 73 3.4 MALDI-MS for Lipidomics, 74 3.4.1 General, 74 3.4.2 Analysis of Lipid Extracts, 74 3.4.3 Advantages and Drawbacks, 75 3.4.4 Recent Advances in MALDI-MS for Lipidomics, 76 3.4.4.1 Utilization of Novel Matrices, 76 3.4.4.2 (HP)TLC-MALDI-MS, 78 3.4.4.3 Matrix-Free Laser Desorption/Ionization Approaches, 78 References, 79 4 Variables in Mass Spectrometry for Lipidomics 89 4.1 Introduction, 89 4.2 Variables in Lipid Extraction (i.e., Multiplex Extraction Conditions), 89 4.2.1 The pH Conditions of Lipid Extraction, 89 4.2.2 Solvent Polarity of Lipid Extraction, 90 4.2.3 Intrinsic Chemical Properties of Lipids, 90 4.3 Variables in the Infusion Solution, 91 4.3.1 Polarity, Composition, Ion Pairing, and Other Variations in the Infusion Solution, 91 4.3.2 Variations of the Levels or Composition of a Modifier in the Infusion Solution, 93 4.3.3 Lipid Concentration in the Infusion Solution, 97 4.4 Variables in Ionization, 98 4.4.1 Source Temperature, 98 4.4.2 Spray Voltage, 99 4.4.3 Injection/Eluent Flow Rate, 100 4.5 Variables in Building-Block monitoring with MS/MS Scanning, 102 4.5.1 Precursor-Ion Scanning of a Fragment Ion Whose m/z Serves as a Variable, 102 4.5.2 Neutral-Loss Scanning of a Neutral Fragment Whose Mass Serves as a Variable, 102 4.5.3 Fragments Associated with the Building Blocks are the Variables in Product-Ion MS Analysis, 103 4.6 Variables in Collision, 104 4.6.1 Collision Energy, 104 4.6.2 Collision-Gas Pressure, 104 4.6.3 Collision Gas Type, 108 4.7 Variables in Separation, 108 4.7.1 Charge Properties in Intrasource Separation, 108 4.7.2 Elution Time in LC Separation, 111 4.7.3 Matrix Properties in Selective Ionization by MALDI, 112 4.7.4 Drift Time (or Collision Cross Section) in Ion-Mobility Separation, 112 4.8 Conclusion, 114 References, 114 5 Bioinformatics in Lipidomics 121 5.1 Introduction, 121 5.2 Lipid Libraries and Databases, 122 5.2.1 Lipid MAPS Structure Database, 122 5.2.2 Building-Block Concept-Based Theoretical Databases, 123 5.2.3 LipidBlast - in silico Tandem Mass Spectral Library, 129 5.2.4 METLIN Database, 130 5.2.5 Human Metabolome Database, 131 5.2.6 LipidBank Database, 131 5.3 Bioinformatics Tools in Automated Lipid Data Processing, 132 5.3.1 LC-MS Spectral Processing, 132 5.3.2 Biostatistical Analyses and Visualization, 134 5.3.3 Annotation for Structure of Lipid Species, 135 5.3.4 Software Packages for Common Data Processing, 136 5.3.4.1 XCMS, 136 5.3.4.2 MZmine 2, 136 5.3.4.3 A Practical Approach for Determination of Mass Spectral Baselines, 137 5.3.4.4 LipidView, 137 5.3.4.5 LipidSearch, 137 5.3.4.6 SimLipid, 138 5.3.4.7 MultiQuant, 139 5.3.4.8 Software Packages for Shotgun Lipidomics, 139 5.4 Bioinformatics for Lipid Network/Pathway Analysis and Modeling, 139 5.4.1 Reconstruction of Lipid Network/Pathway, 139 5.4.2 Simulation of Lipidomics Data for Interpretation of Biosynthesis Pathways, 140 5.4.3 Modeling of Spatial Distributions and Biophysical 5.5 Integration of "Omics", 143 5.5.1 Integration of Lipidomics with Other Omics, 143 5.5.2 Lipidomics Guides Genomics Analysis, 144 References, 145 Part II Characterization of Lipids 151 6 Introduction 153 6.1 Structural Characterization for Lipid Identification, 153 6.2 Pattern Recognition for Lipid Identification, 157 6.2.1 Principles of Pattern Recognition, 157 6.2.2 Examples, 159 6.2.2.1 Choline Lysoglycerophospholipid, 159 6.2.2.2 Sphingomyelin, 161 6.2.2.3 Triacylglycerol, 164 6.2.3 Summary, 169 References, 170 7 Fragmentation Patterns of Glycerophospholipids 173 7.1 Introduction, 173 7.2 Choline Glycerophospholipid, 175 7.2.1 Positive Ion Mode, 175 7.2.1.1 Protonated Species, 175 7.2.1.2 Alkaline Adducts, 175 7.2.2 Negative-Ion Mode, 178 7.3 Ethanolamine Glycerophospholipid, 180 7.3.1 Positive-Ion Mode, 180 7.3.1.1 Protonated Species, 180 7.3.1.2 Alkaline Adducts, 180 7.3.2 Negative-Ion Mode, 182 7.3.2.1 Deprotonated Species, 182 7.3.2.2 Derivatized Species, 183 7.4 Phosphatidylinositol and Phosphatidylinositides, 184 7.4.1 Positive-Ion Mode, 184 7.4.2 Negative-Ion Mode, 184 7.5 Phosphatidylserine, 185 7.5.1 Positive-Ion Mode, 185 7.5.2 Negative-Ion Mode, 186 7.6 Phosphatidylglycerol, 186 7.6.1 Positive-Ion Mode, 186 7.6.2 Negative-Ion Mode, 186 7.7 Phosphatidic Acid, 187 7.7.1 Positive-Ion Mode, 187 7.7.2 Negative-Ion Mode, 188 7.8 Cardiolipin, 188 7.9 Lysoglycerophospholipids, 190 7.9.1 Choline Lysoglycerophospholipids, 190 7.9.2 Ethanolamine Lysoglycerophospholipids, 191 7.9.3 Anionic Lysoglycerophospholipids, 193 7.10 Other Glycerophospholipids, 193 7.10.1 N-Acyl Phosphatidylethanolamine, 193 7.10.2 N-Acyl Phosphatidylserine, 194 7.10.3 Acyl Phosphatidylglycerol, 194 7.10.4 Bis(monoacylglycero)phosphate, 194 7.10.5 Cyclic Phosphatidic Acid, 196 References, 196 8 Fragmentation Patterns of Sphingolipids 201 8.1 Introduction, 201 8.2 Ceramide, 202 8.2.1 Positive-Ion Mode, 202 8.2.2 Negative-Ion Mode, 203 8.3 Sphingomyelin, 205 8.3.1 Positive-Ion Mode, 205 8.3.2 Negative-Ion Mode, 205 8.4 Cerebroside, 205 8.4.1 Positive-Ion Mode, 205 8.4.2 Negative-Ion Mode, 207 8.5 Sulfatide, 208 8.6 Oligoglycosylceramide and Gangliosides, 208 8.7 Inositol Phosphorylceramide, 210 8.8 Sphingolipid Metabolites, 210 8.8.1 Sphingoid Bases, 210 8.8.2 Sphingoid-1-Phosphate, 212 8.8.3 Lysosphingomyelin, 212 8.8.4 Psychosine, 213 References, 213 9 Fragmentation Patterns of Glycerolipids 217 9.1 Introduction, 217 9.2 Monoglyceride, 218 9.3 Diglyceride, 218 9.4 Triglyceride, 222 9.5 Hexosyl Diacylglycerol, 223 9.6 Other Glycolipids, 224 References, 226 10 Fragmentation Patterns of Fatty Acids and Modified Fatty Acids 229 10.1 Introduction, 229 10.2 Nonesterified Fatty Acid, 230 10.2.1 Underivatized Nonesterified Fatty Acid, 230 10.2.1.1 Positive-Ion Mode, 230 10.2.1.2 Negative-Ion Mode, 230 10.2.2 Derivatized Nonesterified Fatty Acid, 233 10.2.2.1 Off-Line Derivatization, 233 10.2.2.2 Online Derivatization (Ozonolysis), 234 10.3 Modified Fatty Acid, 234 10.4 Fatty Acidomics, 238 References, 241 11 Fragmentation Patterns of other Bioactive Lipid Metabolites 243 11.1 Introduction, 243 11.2 Acylcarnitine, 244 11.3 Acyl CoA, 245 11.4 Endocannabinoids, 246 11.4.1 N-Acyl Ethanolamine, 247 11.4.2 2-Acyl Glycerol, 247 11.4.3 N-Acyl Amino Acid, 247 11.5 4-Hydroxyalkenal, 248 11.6 Chlorinated Lipids, 251 11.7 Sterols and Oxysterols, 251 11.8 Fatty Acid-Hydroxy Fatty Acids, 252 References, 253 12 Imaging Mass Spectrometry of Lipids 259 12.1 Introduction, 259 12.1.1 Samples Suitable for MS Imaging of Lipids, 260 12.1.2 Sample Processing/Preparation, 260 12.1.3 Matrix Application, 261 12.1.3.1 Matrix Application, 261 12.1.3.2 Matrix Application Methods, 262 12.1.4 Data Processing, 263 12.1.4.1 Biomap, 263 12.1.4.2 FlexImaging, 264 12.1.4.3 MALDI Imaging Team Imaging Computing System (MITICS), 264 12.1.4.4 DataCube Explorer, 264 12.1.4.5 imzML, 264 12.2 MALDI-MS Imaging, 264 12.3 Secondary-Ion Mass Spectrometry Imaging, 267 12.4 DESI-MS Imaging, 268 12.5 Ion-Mobility Imaging, 270 12.6 Advantages and Drawbacks of Imaging Mass Spectrometry for Analysis of Lipids, 270 12.6.1 Advantages, 270 12.6.2 Limitations, 272 References, 272 Part III Quantification of Lipids in Lipidomics 281 13 Sample Preparation 283 13.1 Introduction, 283 13.2 Sampling, Storage, and Related Concerns, 284 13.2.1 Sampling, 284 13.2.2 Sample Storage Prior to Extraction, 286 13.2.3 Minimizing Autoxidation, 287 13.3 Principles and Methods of Lipid Extraction, 288 13.3.1 Principles of Lipid Extraction, 289 13.3.2 Internal Standards, 292 13.3.3 Lipid Extraction Methods, 295 13.3.3.1 Folch Extraction, 295 13.3.3.2 Bligh-Dyer Extraction, 296 13.3.3.3 MTBE Extraction, 297 13.3.3.4 BUME Extraction, 298 13.3.3.5 Extraction of Plant Samples, 298 13.3.3.6 Special Cases, 298 13.3.4 Contaminants and Artifacts in Extraction, 299 13.3.5 Storage of Lipid Extracts, 300 References, 300 14 Quantification of Individual Lipid Species in Lipidomics 305 14.1 Introduction, 305 14.2 Principles of Quantifying Lipid Species by Mass Spectrometry, 308 14.3 Methods for Quantification in Lipidomics, 312 14.3.1 Tandem Mass Spectrometry-Based Method, 312 14.3.2 Two-Step Quantification Approach Used in MDMS-SL, 317 14.3.3 Selected Ion Monitoring Method, 321 14.3.4 Selected Reaction Monitoring Method, 324 14.3.5 High Mass Accuracy Mass Spectrometry Approach, 327 References, 329 15 Factors Affecting Accurate Quantification of Lipids 335 15.1 Introduction, 335 15.2 Lipid Aggregation, 336 15.3 Linear Dynamic Range of Quantification, 337 15.4 Nuts and Bolts of Tandem Mass Spectrometry for Quantification of Lipids, 339 15.5 Ion Suppression, 341 15.6 Spectral Baseline, 343 15.7 The Effects of Isotopes, 344 15.8 Minimal Number of Internal Standards for Quantification, 347 15.9 In-Source Fragmentation, 349 15.10 Quality of Solvents, 350 15.11 Miscellaneous in Quantitative Analysis of Lipids, 350 References, 350 16 Data Quality Control and Interpretation 353 16.1 Introduction, 353 16.2 Data Quality Control, 354 16.3 Recognition of Lipid Metabolism Pathways for Data Interpretation, 355 16.3.1 Sphingolipid Metabolic Pathway Network, 356 16.3.2 Network of Glycerophospholipid Biosynthesis Pathways, 356 16.3.3 Glycerolipid Metabolism, 359 16.3.4 Interrelationship between Different Lipid Categories, 360 16.4 Recognition of Lipid Functions for Data Interpretation, 360 16.4.1 Lipids Serve as Cellular Membrane Components, 360 16.4.2 Lipids Serve as Cellular Energy Storage Depots, 363 16.4.3 Lipids Serve as Signaling Molecules, 365 16.4.4 Lipids Play Other Cellular Roles, 366 16.5 Recognizing the Complication of Sample Inhomogeneity and Cellular Compartments in Data Interpretation, 368 16.6 Integration of "Omics" for Data Supporting, 369 References, 370 Part IV Applications of Lipidomics in Biomedical and Biological Research 377 17 Lipidomics for Health and Disease 379 17.1 Introduction, 379 17.2 Diabetes and Obesity, 380 17.3 Cardiovascular Diseases, 382 17.4 Nonalcohol Fatty Liver Disease, 383 17.5 Alzheimer's disease, 385 17.6 Psychosis, 387 17.7 Cancer, 388 17.8 Lipidomics in Nutrition, 390 17.8.1 Lipidomics in Determination of the Effects of Specific Diets or Challenge Tests, 391 17.8.2 Lipidomics to Control Food Quality, 392 References, 393 18 Plant Lipidomics 405 18.1 Introduction, 405 18.2 Characterization of Lipids Special to Plant Lipidome, 406 18.2.1 Galactolipids, 407 18.2.2 Sphingolipids, 408 18.2.3 Sterols and Derivatives, 410 18.2.4 Sulfolipids, 410 18.2.5 Lipid A and Intermediates, 411 18.3 Lipidomics for Plant Biology, 411 18.3.1 Stress-Induced Changes of Plant Lipidomes, 411 18.3.1.1 Lipid Alterations in Plants Induced by Temperature Changes, 411 18.3.1.2 Wounding-Induced Alterations in Plastidic Lipids, 415 18.3.1.3 Phosphorus Deficiency-Resulted Changes of Glycerophospholipids and Galactolipids, 416 18.3.2 Changes of Plant Lipidomes during Development, 416 18.3.2.1 Alterations in Lipids during Development of Cotton Fibers, 416 18.3.2.2 Changes of Lipids during Potato Tuber Aging and Sprouting, 417 18.3.3 Characterization of Gene Function by Lipidomics, 417 18.3.3.1 Role of Fatty Acid Desaturases and DHAP Reductase in Systemic Acquired Resistance, 417 18.3.3.2 Roles of Phospholipases in Response to Freezing, 419 18.3.3.3 Role of PLD¿ in Phosphorus Deficiency-Induced Lipid Changes, 419 18.3.4 Lipidomics Facilitates Improvement of Genetically Modified Food Quality, 420 References, 421 19 Lipidomics on Yeast and Mycobacterium Tuberculosis 427 19.1 Introduction, 427 19.2 Yeast Lipidomics, 428 19.2.1 Protocol for Analysis of Yeast Lipidomes by Mass Spectrometry, 428 19.2.2 Quantitative Analysis of Yeast Lipidome, 430 19.2.3 Comparative Lipidomics Studies on Different Yeast Strains, 431 19.2.4 Lipidomics of Yeast for Lipid Biosynthesis and Function, 432 19.2.5 Determining the Effects of Growth Conditions on Yeast Lipidomes, 435 19.3 Mycobacterium Tuberculosis Lipidomics, 436 References, 438 20 Lipidomics on Cell Organelle and Subcellular Membranes 443 20.1 Introduction, 443 20.2 Golgi, 444 20.3 Lipid Droplets, 445 20.4 Lipid Rafts, 447 20.5 Mitochondrion, 449 20.6 Nucleus, 452 20.7 Conclusion, 453 References, 454 Index 459
It is well known that lipids play many essential roles in life [1]. They possess functions to
More and more lines of evidence support a rationale that lipids are associated with many human diseases (e.g., diabetes and obesity, atherosclerosis and stroke, cancer, psychiatric disorders, neurodegenerative diseases and neurological disorders, and infectious diseases) (see Chapter 17). Therefore, the research on lipids has become a unique new discipline called "lipidomics" nowadays.
The majority of lipids are composed of two components. One part is largely hydrophobic ("water-fearing"), meaning that it is not suitably soluble in polar solvents (e.g., water), while the other part is often polar or hydrophilic ("water-loving") and is readily soluble in polar solvents. Therefore, lipids are amphiphilic molecules (having both hydrophobic and hydrophilic portions). However, prominent exceptions are also present, including waxes, triacylglycerol (TAG), cholesterol, cholesteryl esters, all of which are predominantly hydrophobic except for their hydroxyl or carbonyl groups.
In general, lipids are defined as a group of organic compounds in living organisms, most of which are insoluble in water but soluble in nonpolar solvents. Based on this definition, any petroleum products obtained from fossil materials or synthetic organic compounds are excluded in the category of lipids. Indeed, lipids are one of the main constituents of biological cells and the major components of lipoproteins in serum. Lipids are often conjugated with carbohydrates, which are known as lipopolysaccharides.
The historical origins of the term "lipid" and its early definitions can be found elsewhere if the readers are interested [2]. The precise definition of lipids is difficult to give, as no satisfactory or widely accepted definition exists. Thus, many varying definitions about lipids can be found. For example, Merriam-Webster dictionary defines lipids as "any of various substances that are soluble in nonpolar organic solvents (such as hexane, chloroform, and ether), that with proteins and carbohydrates constitute the principal structural components of living cells, and that include fats, waxes, phospholipids, cerebrosides, and related and derived compounds." Wikipedia (http://en.wikipedia.org/wiki/Lipid) describes it as "Lipids may be broadly defined as hydrophobic or amphiphilic small molecules; the amphiphilic nature of some lipids allows them to form structures such as vesicles, liposomes, or membranes in an aqueous environment." General textbooks describe lipids as a group of naturally occurring compounds, which have in common a ready solubility in organic solvents such as chloroform, benzene, ethers, and alcohols. Unfortunately, such a definition is misleading because there are many compounds that are now widely accepted as lipids, which may be more soluble in water than in organic solvents (e.g., lysoglycerophospholipids, acyl CoA, gangliosides).
The most recent definition of lipids was provided by a group of lipid chemists who formed the consortium of lipid metabolites and pathways strategy (Lipid MAPS). They defined lipids based on the origin of the lipid structures as hydrophobic or amphipathic small molecules that may originate entirely or, in part, by carbanion-based condensations of thioesters (fatty acids, polyketides, etc.) and/or by carbocation-based condensations of isoprene units (prenols, sterols, etc.). In this book, this definition, its classification (see the following), and its recommended nomenclature are largely accepted.
With the different definitions, different kinds of lipid classification are frequently used in the field. For example, many lipid chemists simply classify lipids into polar and nonpolar lipids based on the overall hydrophobicity of the lipids. The nonpolar lipids include fatty acids and their derivatives (e.g., long-chain alcohols and waxes), glycerol-derived lipids (e.g., monoacylglycerols (MAG), diacylglycerols (DAG), TAG (i.e., fats or oils)), and steroids. These nonpolar lipids are generally soluble in very nonpolar solvents such as hexane, ether, and ester. The polar lipids usually contain a polar head group, such as phosphocholine in choline glycerophospholipids (PC) (see the following), and are usually soluble in relatively polar solvents, such as alcohol, and even water.
Based on the features of chromatographic separation, lipids are classified into simple and complex molecules [2]. "Simple lipids" are those that yield mostly two types of primary products per molecule upon hydrolysis (e.g., fatty acids and their derivatives, MAG); "complex lipids" yield three or more primary hydrolysis products per molecule (e.g., PC, TAG, DAG). These hydrolysis products include fatty acids, phosphoric acid, organic bases, carbohydrates, glycerol, and many more components.
According to the functions of cellular lipids, many biochemists also refer lipids to
A more detailed classification is achieved by grouping lipids based on their chemical properties. Individual lipid molecular species (each of which has a unique molecular structure) are commonly categorized into small groups, that is, lipid classes, based on their chemical structural similarities. For example, individual lipid molecular species that possess an identical polar head group (e.g., phosphocholine, phosphoethanolamine, or phosphoserine) linked to a common glycerol backbone are categorized into a specific lipid class (e.g., PC, ethanolamine glycerophospholipid (PE), serine glycerophospholipid (PS), respectively) (Figure 1.1).
Figure 1.1 Examples of glycerophospholipid classes. Different structures of the moiety X, which are connected to the phosphate and exemplified in the box, determine the individual classes of GPL as indicated with abbreviations that are commonly used in the literature and adapted by the Lipid MAPS consortium.
Among each individual lipid class, due to the presence of a unique linkage or another unique feature, these species are further classified into smaller groups, that is, the subclasses of the lipid class (Figure 1.2). For example, the oxygen atom of glycerol at sn-1 position (here sn means stereospecific numbering) is connected to a fatty acyl chain through an ester, ether, or vinyl ether bond in both glycerophospholipids (GPL) and glycerolipids. These different linkages define the subclasses of a GPL class (Figure 1.2a), which are called phosphatidyl-, plasmanyl-, and plasmenyl- according to the recommended nomenclature by International Union of Pure and Applied Chemistry (IUPAC), corresponding to the ester, alkyl ether, and vinyl ether linkage, respectively [3]. These subclasses are abbreviated as prefix "d," "a," and "p," respectively, throughout this book. To date, the plasmanyl and plasmenyl subclasses have only been identified in mammalian lipidomes for the classes of choline, ethanolamine, and serine glycerophospholipids (PC, PE, and PS, respectively) and may be present in the class of phosphatidic acid (PA) and cardiolipin (CL). However, these subclasses have been found in other lipid classes in other species [4]. These different linkages have also been found in DAG and TAG [5, 6]. The presence or absence of a double bond between C4 and C5 of sphingoid base (see the following) leads to the classification of the individual sphingolipid class into sphingolipid and dihydrosphingolipid subclasses (Figure 1.2b).
Figure 1.2 Example of lipid subclasses, which are classified based on the different linkages at a certain position or a unique structural feature of a lipid class. (a) The subclasses of phosphatidyl-, plasmanyl-, and plasmenyl- are present in GPL as a result of the different linkages (i.e., ester, ether, and vinyl ether) of a fatty acyl chain to the hydroxyl group at sn-1 position of glycerol. (b) The different core structures of sphingoid bases in the presence or absence of a double bond between C4 and C5 carbon atoms lead to the common subclasses of sphingolipids and dihydrosphingolipids. Other less common subclasses of sphingolipids are also present due to other structures of the sphingoid bases (see Figure 1.6).
Following are the two major classification systems defined based on chemical properties of lipids that are largely used in the book.
Based on their mission, the Lipid MAPS consortium has classified lipids into eight categories, including fatty acyls, glycerolipids, GPL, sphingolipids, sterol lipids, prenol lipids, saccharolipids, and polyketides [7]. Importantly, individual lipid molecular species in this...
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