Lipidomics

Xianlin Han is a Professor in the Programs of Cardiovascular Metabolism and Integrative Metabolism at the Sanford Burnham Prebys Medical Discovery Institute. Prof. Han is one of the pioneers in lipidomics and the inventor of shotgun lipidomics. He has published over 180 peer-reviewed papers in journals and 16 invited book chapters with an H-index of 62. He holds 5 international patents. He is the associate editor of “Lipids”. Prof. Han serves as a member of the Editorial Board of numerous international journals including J. Lipid Res., Mol. Cell Biol. Lipids in Biochim. Biophys. Acta, Chem. Phys. Lipids, and Anal. Biochem.

• Foreword xixPreface xxiAbbreviations xxvPart I Introduction 11 Lipids and Lipidomics 31.1 Lipids, 31.1.1 Definition, 3€1.1.2 Classification, 41.1.2.1 Lipid MAPS Approach, 71.1.2.2 Building Block Approach, 101.2 Lipidomics, 131.2.1 Definition, 131.2.2 History of Lipidomics, 14References, 162 Mass Spectrometry for Lipidomics 212.1 Ionization Techniques, 212.1.1 Electrospray Ionization, 222.1.1.1 Principle of Electrospray Ionization, 222.1.1.2 Features of Electrospray Ionization for Lipid Analysis, 282.1.1.3 Advent of ESI for Lipid Analysis: Nano-ESI and Off-Axis Ion Inlets, 302.1.2 Matrix-Assisted Laser Desorption/Ionization, 302.2 Mass Analyzers, 322.2.1 Quadrupole, 322.2.2 Time of Flight, 332.2.3 Ion Trap, 352.3 Detector, 362.4 Tandem Mass Spectrometry Techniques, 372.4.1 Product-Ion Analysis, 372.4.2 Neutral-Loss Scan, 392.4.3 Precursor-Ion Scan, 392.4.4 Selected Reaction Monitoring, 392.4.5 Interweaving Tandem Mass Spectrometry Techniques, 402.5 Other Recent Advances in Mass Spectrometry for Lipid Analysis, 422.5.1 Ion-Mobility Mass Spectrometry, 432.5.2 Desorption Electrospray Ionization, 43References, 453 Mass Spectrometry-Based Lipidomics Approaches 533.1 Introduction, 533.2 Shotgun Lipidomics: Direct Infusion-Based Approaches, 543.2.1 Devices for Direct Infusion, 543.2.2 Features of Shotgun Lipidomics, 553.2.3 Shotgun Lipidomics Approaches, 563.2.3.1 Tandem Mass Spectrometry-Based Shotgun Lipidomics, 563.2.3.2 High Mass Accuracy-Based Shotgun Lipidomics, 563.2.3.3 Multidimensional MS-Based Shotgun Lipidomics, 573.2.4 Advantages and Drawbacks, 633.2.4.1 Tandem Mass Spectrometry-Based Shotgun Lipidomics, 633.2.4.2 High Mass Accuracy-Based Shotgun Lipidomics, 633.2.4.3 Multidimensional Mass Spectrometry-Based Shotgun Lipidomics, 643.3 LC-MS-Based Approaches, 653.3.1 General, 653.3.1.1 Selected Ion Monitoring for LC-MS, 663.3.1.2 Selected/Multiple Reaction Monitoring for LC-MS, 673.3.1.3 Data-Dependent Analysis after LC-MS, 673.3.2 LC-MS-Based Approaches for Lipidomics, 683.3.2.1 Normal-Phase LC-MS-Based Approaches, 683.3.2.2 Reversed-Phase LC-MS-Based Approaches, 693.3.2.3 Hydrophilic Interaction LC-MS-Based Approaches, 713.3.2.4 Other LC-MS-Based Approaches, 723.3.3 Advantages and Drawbacks, 723.3.4 Identification of Lipid Species after LC-MS, 733.4 MALDI-MS for Lipidomics, 743.4.1 General, 743.4.2 Analysis of Lipid Extracts, 743.4.3 Advantages and Drawbacks, 753.4.4 Recent Advances in MALDI-MS for Lipidomics, 763.4.4.1 Utilization of Novel Matrices, 763.4.4.2 (HP)TLC-MALDI-MS, 783.4.4.3 Matrix-Free Laser Desorption/IonizationApproaches, 78References, 794 Variables in Mass Spectrometry for Lipidomics 894.1 Introduction, 894.2 Variables in Lipid Extraction (i.e., Multiplex Extraction Conditions), 894.2.1 The pH Conditions of Lipid Extraction, 894.2.2 Solvent Polarity of Lipid Extraction, 904.2.3 Intrinsic Chemical Properties of Lipids, 904.3 Variables in the Infusion Solution, 914.3.1 Polarity, Composition, Ion Pairing, and Other Variations in the Infusion Solution, 914.3.2 Variations of the Levels or Composition of a Modifier in the Infusion Solution, 934.3.3 Lipid Concentration in the Infusion Solution, 974.4 Variables in Ionization, 984.4.1 Source Temperature, 984.4.2 Spray Voltage, 994.4.3 Injection/Eluent Flow Rate, 1004.5 Variables in Building-Block monitoring with MS/MS Scanning, 1024.5.1 Precursor-Ion Scanning of a Fragment Ion Whose m/z Serves as a Variable, 1024.5.2 Neutral-Loss Scanning of a Neutral Fragment Whose Mass Serves as a Variable, 1024.5.3 Fragments Associated with the Building Blocks are the Variables in Product-Ion MS Analysis, 1034.6 Variables in Collision, 1044.6.1 Collision Energy, 1044.6.2 Collision-Gas Pressure, 1044.6.3 Collision Gas Type, 1084.7 Variables in Separation, 1084.7.1 Charge Properties in Intrasource Separation, 1084.7.2 Elution Time in LC Separation, 1114.7.3 Matrix Properties in Selective Ionization by MALDI, 1124.7.4 Drift Time (or Collision Cross Section) in Ion-Mobility Separation, 1124.8 Conclusion, 114References, 1145 Bioinformatics in Lipidomics 1215.1 Introduction, 1215.2 Lipid Libraries and Databases, 1225.2.1 Lipid MAPS Structure Database, 1225.2.2 Building-Block Concept-Based Theoretical Databases, 1235.2.3 LipidBlast – in silico Tandem Mass Spectral Library, 1295.2.4 METLIN Database, 1305.2.5 Human Metabolome Database, 1315.2.6 LipidBank Database, 1315.3 Bioinformatics Tools in Automated Lipid Data Processing, 1325.3.1 LC-MS Spectral Processing, 1325.3.2 Biostatistical Analyses and Visualization, 1345.3.3 Annotation for Structure of Lipid Species, 1355.3.4 Software Packages for Common Data Processing, 1365.3.4.1 XCMS, 1365.3.4.2 MZmine 2, 1365.3.4.3 A Practical Approach for Determination of Mass Spectral Baselines, 1375.3.4.4 LipidView, 1375.3.4.5 LipidSearch, 1375.3.4.6 SimLipid, 1385.3.4.7 MultiQuant, 1395.3.4.8 Software Packages for Shotgun Lipidomics, 1395.4 Bioinformatics for Lipid Network/Pathway Analysis and Modeling, 1395.4.1 Reconstruction of Lipid Network/Pathway, 1395.4.2 Simulation of Lipidomics Data for Interpretation of Biosynthesis Pathways, 1405.4.3 Modeling of Spatial Distributions and Biophysical5.5 Integration of "Omics", 1435.5.1 Integration of Lipidomics with Other Omics, 1435.5.2 Lipidomics Guides Genomics Analysis, 144References, 145Part II Characterization of Lipids 1516 Introduction 1536.1 Structural Characterization for Lipid Identification, 1536.2 Pattern Recognition for Lipid Identification, 1576.2.1 Principles of Pattern Recognition, 1576.2.2 Examples, 1596.2.2.1 Choline Lysoglycerophospholipid, 1596.2.2.2 Sphingomyelin, 1616.2.2.3 Triacylglycerol, 1646.2.3 Summary, 169References, 1707 Fragmentation Patterns of Glycerophospholipids 1737.1 Introduction, 1737.2 Choline Glycerophospholipid, 1757.2.1 Positive Ion Mode, 1757.2.1.1 Protonated Species, 1757.2.1.2 Alkaline Adducts, 1757.2.2 Negative-Ion Mode, 1787.3 Ethanolamine Glycerophospholipid, 1807.3.1 Positive-Ion Mode, 1807.3.1.1 Protonated Species, 1807.3.1.2 Alkaline Adducts, 1807.3.2 Negative-Ion Mode, 1827.3.2.1 Deprotonated Species, 1827.3.2.2 Derivatized Species, 1837.4 Phosphatidylinositol and Phosphatidylinositides, 1847.4.1 Positive-Ion Mode, 1847.4.2 Negative-Ion Mode, 1847.5 Phosphatidylserine, 1857.5.1 Positive-Ion Mode, 1857.5.2 Negative-Ion Mode, 1867.6 Phosphatidylglycerol, 1867.6.1 Positive-Ion Mode, 1867.6.2 Negative-Ion Mode, 1867.7 Phosphatidic Acid, 1877.7.1 Positive-Ion Mode, 1877.7.2 Negative-Ion Mode, 1887.8 Cardiolipin, 1887.9 Lysoglycerophospholipids, 1907.9.1 Choline Lysoglycerophospholipids, 1907.9.2 Ethanolamine Lysoglycerophospholipids, 1917.9.3 Anionic Lysoglycerophospholipids, 1937.10 Other Glycerophospholipids, 1937.10.1 N-Acyl Phosphatidylethanolamine, 1937.10.2 N-Acyl Phosphatidylserine, 1947.10.3 Acyl Phosphatidylglycerol, 1947.10.4 Bis(monoacylglycero)phosphate, 1947.10.5 Cyclic Phosphatidic Acid, 196References, 1968 Fragmentation Patterns of Sphingolipids 2018.1 Introduction, 2018.2 Ceramide, 2028.2.1 Positive-Ion Mode, 2028.2.2 Negative-Ion Mode, 2038.3 Sphingomyelin, 2058.3.1 Positive-Ion Mode, 2058.3.2 Negative-Ion Mode, 2058.4 Cerebroside, 2058.4.1 Positive-Ion Mode, 2058.4.2 Negative-Ion Mode, 2078.5 Sulfatide, 2088.6 Oligoglycosylceramide and Gangliosides, 2088.7 Inositol Phosphorylceramide, 2108.8 Sphingolipid Metabolites, 2108.8.1 Sphingoid Bases, 2108.8.2 Sphingoid-1-Phosphate, 2128.8.3 Lysosphingomyelin, 2128.8.4 Psychosine, 213References, 2139 Fragmentation Patterns of Glycerolipids 2179.1 Introduction, 2179.2 Monoglyceride, 2189.3 Diglyceride, 2189.4 Triglyceride, 2229.5 Hexosyl Diacylglycerol, 2239.6 Other Glycolipids, 224References, 22610 Fragmentation Patterns of Fatty Acids and Modified Fatty Acids 22910.1 Introduction, 22910.2 Nonesterified Fatty Acid, 23010.2.1 Underivatized Nonesterified Fatty Acid, 23010.2.1.1 Positive-Ion Mode, 23010.2.1.2 Negative-Ion Mode, 23010.2.2 Derivatized Nonesterified Fatty Acid, 23310.2.2.1 Off-Line Derivatization, 23310.2.2.2 Online Derivatization (Ozonolysis), 23410.3 Modified Fatty Acid, 23410.4 Fatty Acidomics, 238References, 24111 Fragmentation Patterns of other Bioactive Lipid Metabolites 24311.1 Introduction, 24311.2 Acylcarnitine, 24411.3 Acyl CoA, 24511.4 Endocannabinoids, 24611.4.1 N-Acyl Ethanolamine, 24711.4.2 2-Acyl Glycerol, 24711.4.3 N-Acyl Amino Acid, 24711.5 4-Hydroxyalkenal, 24811.6 Chlorinated Lipids, 25111.7 Sterols and Oxysterols, 25111.8 Fatty Acid–Hydroxy Fatty Acids, 252References, 25312 Imaging Mass Spectrometry of Lipids 25912.1 Introduction, 25912.1.1 Samples Suitable for MS Imaging of Lipids, 26012.1.2 Sample Processing/Preparation, 26012.1.3 Matrix Application, 26112.1.3.1 Matrix Application, 26112.1.3.2 Matrix Application Methods, 26212.1.4 Data Processing, 26312.1.4.1 Biomap, 26312.1.4.2 FlexImaging, 26412.1.4.3 MALDI Imaging Team Imaging Computing System (MITICS), 26412.1.4.4 DataCube Explorer, 26412.1.4.5 imzML, 26412.2 MALDI-MS Imaging, 26412.3 Secondary-Ion Mass Spectrometry Imaging, 26712.4 DESI-MS Imaging, 26812.5 Ion-Mobility Imaging, 27012.6 Advantages and Drawbacks of Imaging Mass Spectrometry for Analysis of Lipids, 27012.6.1 Advantages, 27012.6.2 Limitations, 272References, 272Part III Quantification of Lipids in Lipidomics 28113 Sample Preparation 28313.1 Introduction, 28313.2 Sampling, Storage, and Related Concerns, 28413.2.1 Sampling, 28413.2.2 Sample Storage Prior to Extraction, 28613.2.3 Minimizing Autoxidation, 28713.3 Principles and Methods of Lipid Extraction, 28813.3.1 Principles of Lipid Extraction, 28913.3.2 Internal Standards, 29213.3.3 Lipid Extraction Methods, 29513.3.3.1 Folch Extraction, 29513.3.3.2 Bligh–Dyer Extraction, 29613.3.3.3 MTBE Extraction, 29713.3.3.4 BUME Extraction, 29813.3.3.5 Extraction of Plant Samples, 29813.3.3.6 Special Cases, 29813.3.4 Contaminants and Artifacts in Extraction, 29913.3.5 Storage of Lipid Extracts, 300References, 30014 Quantification of Individual Lipid Species in Lipidomics 30514.1 Introduction, 30514.2 Principles of Quantifying Lipid Species by Mass Spectrometry, 30814.3 Methods for Quantification in Lipidomics, 31214.3.1 Tandem Mass Spectrometry-Based Method, 31214.3.2 Two-Step Quantification Approach Used in MDMS-SL, 31714.3.3 Selected Ion Monitoring Method, 32114.3.4 Selected Reaction Monitoring Method, 32414.3.5 High Mass Accuracy Mass SpectrometryApproach, 327References, 32915 Factors Affecting Accurate Quantification of Lipids 33515.1 Introduction, 33515.2 Lipid Aggregation, 33615.3 Linear Dynamic Range of Quantification, 33715.4 Nuts and Bolts of Tandem Mass Spectrometry for Quantification of Lipids, 33915.5 Ion Suppression, 34115.6 Spectral Baseline, 34315.7 The Effects of Isotopes, 34415.8 Minimal Number of Internal Standards for Quantification, 34715.9 In-Source Fragmentation, 34915.10 Quality of Solvents, 35015.11 Miscellaneous in Quantitative Analysis of Lipids, 350References, 35016 Data Quality Control and Interpretation 35316.1 Introduction, 35316.2 Data Quality Control, 35416.3 Recognition of Lipid Metabolism Pathways for Data Interpretation, 35516.3.1 Sphingolipid Metabolic Pathway Network, 35616.3.2 Network of Glycerophospholipid Biosynthesis Pathways, 35616.3.3 Glycerolipid Metabolism, 35916.3.4 Interrelationship between Different Lipid Categories, 36016.4 Recognition of Lipid Functions for Data Interpretation, 36016.4.1 Lipids Serve as Cellular Membrane Components, 36016.4.2 Lipids Serve as Cellular Energy Storage Depots, 36316.4.3 Lipids Serve as Signaling Molecules, 36516.4.4 Lipids Play Other Cellular Roles, 36616.5 Recognizing the Complication of Sample Inhomogeneity and Cellular Compartments in Data Interpretation, 36816.6 Integration of "Omics" for Data Supporting, 369References, 370Part IV Applications of Lipidomics in Biomedical and Biological Research 37717 Lipidomics for Health and Disease 37917.1 Introduction, 37917.2 Diabetes and Obesity, 38017.3 Cardiovascular Diseases, 38217.4 Nonalcohol Fatty Liver Disease, 38317.5 Alzheimer’s disease, 38517.6 Psychosis, 38717.7 Cancer, 38817.8 Lipidomics in Nutrition, 39017.8.1 Lipidomics in Determination of the Effects of Specific Diets or Challenge Tests, 39117.8.2 Lipidomics to Control Food Quality, 392References, 39318 Plant Lipidomics 40518.1 Introduction, 40518.2 Characterization of Lipids Special to Plant Lipidome, 40618.2.1 Galactolipids, 40718.2.2 Sphingolipids, 40818.2.3 Sterols and Derivatives, 41018.2.4 Sulfolipids, 41018.2.5 Lipid A and Intermediates, 41118.3 Lipidomics for Plant Biology, 41118.3.1 Stress-Induced Changes of Plant Lipidomes, 41118.3.1.1 Lipid Alterations in Plants Induced by Temperature Changes, 41118.3.1.2 Wounding-Induced Alterations in Plastidic Lipids, 41518.3.1.3 Phosphorus Deficiency-Resulted Changes of Glycerophospholipids and Galactolipids, 41618.3.2 Changes of Plant Lipidomes during Development, 41618.3.2.1 Alterations in Lipids during Development of Cotton Fibers, 41618.3.2.2 Changes of Lipids during Potato Tuber Aging and Sprouting, 41718.3.3 Characterization of Gene Function by Lipidomics, 41718.3.3.1 Role of Fatty Acid Desaturases and DHAP Reductase in Systemic Acquired Resistance, 41718.3.3.2 Roles of Phospholipases in Response to Freezing, 41918.3.3.3 Role of PLDζ in Phosphorus Deficiency-Induced Lipid Changes, 41918.3.4 Lipidomics Facilitates Improvement of Genetically Modified Food Quality, 420References, 42119 Lipidomics on Yeast and Mycobacterium Tuberculosis 42719.1 Introduction, 42719.2 Yeast Lipidomics, 42819.2.1 Protocol for Analysis of Yeast Lipidomes by Mass Spectrometry, 42819.2.2 Quantitative Analysis of Yeast Lipidome, 43019.2.3 Comparative Lipidomics Studies on Different Yeast Strains, 43119.2.4 Lipidomics of Yeast for Lipid Biosynthesis and Function, 43219.2.5 Determining the Effects of Growth Conditions on Yeast Lipidomes, 43519.3 Mycobacterium Tuberculosis Lipidomics, 436References, 43820 Lipidomics on Cell Organelle and Subcellular Membranes 44320.1 Introduction, 44320.2 Golgi, 44420.3 Lipid Droplets, 44520.4 Lipid Rafts, 44720.5 Mitochondrion, 44920.6 Nucleus, 45220.7 Conclusion, 453References, 454Index 459