BIOM 209/CHEM 210/PHARM 209 Lipid Cell Signaling

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Presentation transcript:

BIOM 209/CHEM 210/PHARM 209 Lipid Cell Signaling Genomics, Proteomics and Metabolomics January 5, 2016 Professor Edward A. Dennis Department of Chemistry and Biochemistry Department of Pharmacology, School of Medicine University of California, San Diego Copyright/attribution notice: You are free to copy, distribute, adapt and transmit this tutorial or individual slides (without alteration) for academic, non-profit and non-commercial purposes. Attribution: Edward A. Dennis (2010) “LIPID MAPS Lipid Metabolomics Tutorial” www.lipidmaps.org E.A. DENNIS 2016 ©

OMICS OVERVIEW: GENOMICS/PROTEOMICS/METABOLOMICS OF LIPID METABOLISM AND CELL SIGNALING AND IMPLICATIONS FOR HUMAN DISEASE PROFILING AND BIOMARKER DISCOVERY A. LIPID MAPS Initiative in Lipidomics B. Human Plasma Lipidome C. Eicosadomics of Macrophages D. Genomics and Proteomics Integration

Lipid Metabolites And Pathways Strategy GENOMICS (TRANSCRIPTOMICS) LIPID MAPS Lipid Metabolites And Pathways Strategy GENOMICS (TRANSCRIPTOMICS) 4 base side chains ~25,000 coding genes PROTEOMICS 20 amino acid side chains ~30,000 in databases METABOLOMICS nucleic acids, amino acids, sugars and fats: >105 ~42,000 in databases “LIPIDOMICS” all the fats: >105 ~40,000 in LM database Dennis (2009) Lipidomics Joins the Omics Evolution, PNAS, 106, 2089.

Increases in Omics Citations 1985-2009 Number of Citations Wenk MR (2010) Lipidomics: New Tools and Applications. Cell, 143, 888-895. Year

Lipidomics Publications 2002-2015

Human Plasma Lipidomics NIST collected (pooled) fasting plasma from 100 individuals 50% female and 50% male; age 40-50 15% of the total taken from individuals of Hispanic origin

Human Plasma Metabolites (mg/dL) Lipids Nucleic Acids Amino Acids Sugars

Human Plasma Lipid Categories (M) Sterol Lipids Fatty Acyls Sphingolipids Glycerolipids Prenols Glycerophospholipids

Lipid categories and Species in the Human Plasma *SRM Lipid Category Number of Species Sum (nmol/ml) Sum (mg/dl) Fatty Acyls 107 214 5.8 Glycerolipids 74 1110 93.7 Glycerophospholipids 160 2590 200 Sphingolipids 204 318 23.7 Sterol Lipids 35 3174 123 Prenol Lipids 8 5 3.7 Total 588 7411 449.9 J Lipid Res 51, 3299-3305 (2010) *SRM = standard reference material

SRM: Prostaglandins, Isoprostanes

SRM: Sterols

SRM: Cholesteryl Esters

SRM: Phosphatidylethanolamines

Human Plasma Lipid Diversity J Lipid Res, 51, 3299-3305 (2010)

Plasma Lipids in the Metabolic Syndrome Quehenberger & Dennis, New Eng. J. Medicine, 365, 1812-23 (2011)

Implications of Lipidomics for the Future of Clinical Medicine Identification of metabolites in human plasma and other tissues for diagnostic purposes Discovery of novel metabolites as biomarkers for disease states Quantitation of metabolites which permit dynamic monitoring of disease pathophysiology over time Evaluation of the efficacy of pharmacotherapeutic agents targeted to specific diseases which affect lipid metabolic pathways (statins)

NIGMS Large Scale Collaborative Grant LIPID MAPS NIGMS Large Scale Collaborative Grant “Glue Grant” [NIH U54 GM 69338] Mouse Macrophage: RAW cell line & primary cell Environmental Agonist: initially LPS, then oxidized LDL HPLC/Mass Spectrometer: identify known & new, quantify Synthesis/Characterize: new lipids, MS quantitative standards Bioinformatics: informatics and lipid networks Website: LIPID MAPS -- Nature Lipidomics Gateway, http://www.lipidmaps.org LIPID MAPS TM

“CLASS”: Comprehensive Lipidomics Analysis using Separation Simplification cells or tissues probe cells tissues medium a “divide-and-conquer” strategy sonicate homogenate category specific internal standards (deuterated, odd-chain carbon) category optimized extraction (liq-liq, SPE) extract category specific GC LC (GC, NP-HPLC, RP-HPLC, chiral, specialty) mass spectrometer (variables) Harkewicz & Dennis, “Applications of mass spectrometry to lipids and membranes” Ann Rev Biochem, 80: 301-325 (2011) 1. Mass spectrometer types 2. Ionization mode 3. Additives (for ionization) 4. Mass spectrometer monitoring modes

Kdo2-Lipid A (KLA, LPS subspecies) A specific agonist of TLR-4 on RAW 264.7 macrophages Raetz et al., 2006, J. Lipid Res. 47: 1097 Nuclei – DAPI Mitochondria – MitoTracker Red O-Specific chain Polysaccharide Core Kdo Glycophospholipid Lipid A 19

Dennis et al (2010) J. Biol. Chem, 51, 39976-85

Phospholipase A2 (PLA2) Function in Arachidonic Acid Release AA PX FA HO PX FA Arachidonic Acid Cyclooxygenase Lipoxygenase Aspirin NSAID Prostaglandins Leukotrienes Dennis et al (2011) Chem Rev, 111, 6130-85

Eicosanoid Signaling Pathways in RAW264.7 Macrophage ATP ATP LPS (KLA) Numerous eicosanoid metabolites Buczynski et. al. (2007) JBC, 282, 22834

Basic Macrophage Experimental Scheme Eicosanoid enzyme mRNA & protein Macrophages ± Kdo2 Lipid A (TLR4) ± 2 mM ATP (P2X7) Solid Phase Extraction & LC-MS/MS Isolate Media & Solid Phase Extraction (Eicosanoids) LC-MS/MS

Cellular Eicosanoid Metabolism Buczynski, Dumlao, Dennis (2009) JLR, 50, 1015-38 24

Cellular Eicosanoid Metabolism COX CYP(ω) 5-LOX 15-LOX CYP(EET) 12-LOX Buczynski, Dumlao, Dennis (2009) JLR, 50, 1015-38

Cellular eicosanoid metabolism CYP(w) COX 5-LOX CYP(EET) 15-LOX 12-LOX Buczynski, Dumlao, Dennis, 2009, JLR, 50: 1015-38

Cellular eicosanoid metabolism COX

KLA / RAW Macrophage: Time-course Extracellular Intracellular PGD2 + metabolites (Extracellular) Buczynski et al (2007) JBC, 282, 22834

Fluxomics: KLA / RAW Macrophage Time-course Gupta, Maurya, Stephens, Dennis, Subramaniam (2009) Biophys J, 96, 4542

Good fit! Prediction of Eicosanoid Fluxes in TLR4-Primed/Purinergic-Stimulated BMDM COX pathway LO pathway www.lipidmaps.org This is a result of prediction of eicosanoid profile in KLA-primed ATP-stimulated BMDM cells. For most time points, the difference between the simulated and experimental data under treatment and control conditions was within the standard error of the mean. Good fit! Kihara et al, (2014) Biophys J, 106, 966-975

Macrophage Phenotypes Resident Peritoneal (RPM) Thioglycolate-Elicited Peritoneal (TGEM) Sterile Inflammation Bone Marrow-Derived (BMDM) RAW264.7 Cell Line (RAW) Tumor M-CSF Ab-MuLV

Eicosanoid Changes by Phenotype 8 Hr PGI2 PGE2 Fold Increase PGD2 TxB2 104 Eicosanoids analyzed Fold Decrease Not detected

COX-2 Metabolites and Transcripts

PGE2/PGD2 vs PGES/PGDS Transcripts

Proportionality of Eicosanoids and Transcripts RPM TGEM BMDM RAW J. Leukocyte Biology, 90, 563-574 (2011)

Directed Proteomics on Enzymes of Eicosanoid Biosynthesis Sabido, Quehenberger Dennis, Aebersold (2012) Mol Cell Proteomics 11: M111.014746

Protein Abundance after KLA Stimulation

Eicosanoid Genes to Proteins to Metabolites Quehenberger & Dennis, New Eng. J. Medicine, 365, 1812-23 (2011)

THE NEED FOR “METABOLOMICS” “Premiums in the shape of sensational discoveries may be hoped for, but cannot be assured even to the greatest genius. But what has to penetrate, relative to this question, more completely into the consciousness of pathologists, is this, that to understand zymoses, to be able to counteract them by rational, as distinguished from empirical or accidentally discovered means, is only possible by the aid of a complete knowledge of the chemical constitution of all the tissues, organs and juices of the body, and of all their possible products.” Johann Ludwig Wilhelm Thudichum (1829-1901) A Treatise on the Chemical Constitution of the Brain (1884) Quoted from [Joseph Needham (1971) The Chemistry of Life, Cambridge Univ Press p. 199] “Premiums in the shape of sensational discoveries may be hoped for, but cannot be assured even to the greatest genuis. But what has to penetrate, relative to this question, more completely into the consciousness of pathologists, is this, that to understand zymoses, to be able to conteract them by rational, as distinguished from empirical or accidentally discovered means, is only possible by the aid of a complete knowledge of the chemical constitution of all the tissues, organs and juices of the body, and of all their possible products. LIPID MAPS TM