Transcript Lecture 1 - Edward Dennis - University of California San Diego

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.
B.
C.
D.
LIPID MAPS Initiative in Lipidomics
Human Plasma Lipidome
Eicosadomics of Macrophages
Genomics and Proteomics Integration
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”
Dennis (2009) Lipidomics Joins the
Omics Evolution, PNAS, 106, 2089.
5
all the fats: >10
~40,000 in LM database
Number of
Citations
Increases in Omics Citations 1985-2009
Wenk MR (2010) Lipidomics:
New Tools and Applications.
Cell, 143, 888-895.
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
Sphingolipids
Fatty Acyls
Glycerolipids
Glycerophospholipids
Prenols
Lipid categories and Species in the
Human Plasma *SRM
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
588
7411
449.9
Lipid Category
Total
*SRM = standard reference material
J Lipid Res 51, 3299-3305 (2010)
SRM: Prostaglandins, Isoprostanes
3.0
2.5
pmol/ml
2.0
1.5
1.0
0.5
0.0
SRM: Sterols
8
7
nmol/ml
6
5
4
3
2
1
0
Cholesterol
3.8 umol/ml
SRM: Cholesteryl Esters
2500
nmol/ml
2000
1500
1000
500
0
0
32:1
34:0
34:1
34:1p
34:2
34:2p
36:0
36:1
36:2
36:2e/36:1p
36:3
36:3e/36:2p
36:4
36:4e/36:3p
36:5
36:5e/36:4p
38:1
38:2
38:3
38:4
38:5
38:5e/38:4p
38:6
38:6e/38:5p
40:1
40:4
40:5
40:5e
40:6
40:6e
40:7
40:7e
42:1
42:5
42:5p
42:6
42:6p
42:7
nmol/ml
SRM: Phosphatidylethanolamines
60
50
40
30
20
10
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)
LIPID MAPS
NIGMS Large Scale Collaborative Grant
“Glue Grant” [NIH U54 GM 69338]
Mouse Macrophage:
Environmental Agonist:
HPLC/Mass Spectrometer:
Synthesis/Characterize:
Bioinformatics:
Website:
RAW cell line & primary cell
initially LPS, then oxidized LDL
identify known & new, quantify
new lipids, MS quantitative standards
informatics and lipid networks
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
a “divide-and-conquer” strategy
medium
sonicate
homogenate
category specific
internal standards
(deuterated, odd-chain carbon)
extraction
category optimized
(liq-liq, SPE)
extract
category specific
GC
LC
(GC, NP-HPLC, RP-HPLC, chiral, specialty)
mass spectrometer
Harkewicz & Dennis, “Applications of mass
spectrometry to lipids and membranes”
Ann Rev Biochem, 80: 301-325 (2011)
(variables)
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
Lipid A
Glycophospholipid
Kdo
Dennis et al (2010)
J. Biol. Chem, 51, 39976-85
Phospholipase A2 (PLA2) Function in
Arachidonic Acid Release
PLA2
AA
FA
PX
HO
FA
PX
Arachidonic Acid
Aspirin
NSAID
Cyclooxygenase
Prostaglandins
Lipoxygenase
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
LC-MS/MS
Isolate Media &
Solid Phase Extraction
(Eicosanoids)
Cellular Eicosanoid Metabolism
Buczynski, Dumlao, Dennis (2009) JLR, 50, 1015-38
Cellular Eicosanoid Metabolism
COX
CYP(EET)
CYP(ω)
12-LOX
5-LOX
15-LOX
Buczynski, Dumlao, Dennis (2009) JLR, 50, 1015-38
Cellular eicosanoid metabolism
CYP(w)
COX
CYP(EET)
15-LOX
12-LOX
Buczynski, Dumlao, Dennis, 2009, JLR, 50: 1015-38
5-LOX
Cellular eicosanoid metabolism
COX
KLA / RAW Macrophage: Time-course
Eicosanoid
(ng / 1x106 cells)
80
AA
60
3
40
2
20
1
0
0
0.5
Eicosanoid
(ng / 1x106 cells)
4
11-HETE
0.4
0.3
0.2
PGF2a
60
PGJ2
50
15
PGE2
250
12
200
9
150
6
100
3
50
0
0
60
15D PGD2
50
40
40
30
30
20
20
0.1
10
10
0.0
0
0
0.5
0.5
0.5
PGD2
80
15D PGJ2
60
40
20
0
Eicosanoid
(ng / 1x106 cells)
0
5-HETE
LTC4
11t LTC4
4
8 12 16 20 24
Time (hr)
0.4
0.4
0.4
Extracellular
0.3
0.3
0.3
Intracellular
0.2
0.2
0.2
0.1
0.1
0.1
0.0
0.0
0.0
0
4
8 12 16 20 24
Time (hr)
0
4
8 12 16 20 24
Time (hr)
PGD2 + metabolites
(Extracellular)
0
4
8 12 16 20 24
Time (hr)
Buczynski et al (2007)
JBC, 282, 22834
Fluxomics: KLA / RAW Macrophage Time-course
Gupta, Maurya, Stephens, Dennis, Subramaniam (2009) Biophys J, 96, 4542
Prediction of Eicosanoid Fluxes in
TLR4-Primed/Purinergic-Stimulated BMDM
COX pathway
LO pathway
www.lipidmaps.org
Kihara et al, (2014) Biophys J, 106, 966-975
Good fit!
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
Fold Increase
PGI2
PGE2
PGD2
TxB2
Fold Decrease
Not detected
COX-2 Metabolites and Transcripts
PGE2/PGD2 vs PGES/PGDS Transcripts
Proportionality of Eicosanoids and Transcripts
RPM
TGEM
J. Leukocyte
Biology, 90,
563-574 (2011)
BMDM
RAW
Directed Proteomics on Enzymes of
Eicosanoid Biosynthesis
FPR1
FPR2
THIKA
DHB4
NLTP
ECHP
PROSTAGLANDIN
CATABOLIC
PATHWAYS
PE2R1
GPR44
PE2R2
PPARD
PE2R3
PD2R
ACOX1
PPARA
PTGR2
PE2R4
ACOX2
PPARG
PF2R
PI2R
PTGIS
CYCLOOXYGENASE
PATHWAY
THAS
PTGDS
CBR1
PTGD2
CAO93
PTGR1
ACOX3
HYES
PTGES
TA2R
PGES2
PGH2
CP4AA
CP4FE
Q8QZW
4
CP254
CP4CA
CP255
Q924D
1
Q6IEF7
CP4F3
B0G0Y
1
CP2BJ
CP238
CP239
CP240
CP2CT
CP2J5
CP4AE
CY250
PA24A
CP237
PGH1
TEBP
CP1B1
Arachidonic
Acid
PA2G5
PA2GA
AL5AP
PA2GX
LOX5
GGT1
LTC4S
GGT5
MGST3
LKHA4
DPEP1
DPEP2
5-LIPOXYGENASE
PATHWAY
A2RST1
LX12B
CYTOCHROM P450
AHR
LX12L
LOX12
CBR1
LX15B
LOXE3
PGDH
RECEPTORS
CLTR2
LT4R1
CLTR1
LX12E
LT4R2
12-LIPOXYGENASE
PATHWAY
15-LIPOXYGENASE
PATHWAY
ENZYMES
Sabido, Quehenberger
Dennis, Aebersold
(2012)
Mol Cell Proteomics 11:
M111.014746
Protein Abundance after KLA Stimulation
Eicosanoid Genes to Proteins to Metabolites
Genes Proteins
Eico
Eicosanoid 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]
LIPID MAPS
TM