PROTEOMICS OF OBESITY

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Genomics on Obesity Toulouse 7-8 June 2007
PROTEOMICS OF OBESITY
Jennifer RIEUSSET (jennifer .rieusset_at_univ-lyon1.f
r)
UMR INSERM 870 / INRA 1235 Régulations
métaboliques, nutrition et diabètes Hubert
VIDAL Lyon
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CONTENTS
Slide

• What is proteomics ? 3 - 8
• Why do it ? 9 - 10
• How is it done ? 11 - 24
• Application of proteomics to obesity 25 49
• Acknowledgements 50
• Abbreviations used 51

Genomics on Obesity, Toulouse, 7-8 June 2007
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OVERVIEW

• What is proteomics ?
• Why do it ?
• How is it done ?
• Application of proteomics to obesity

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DEFINITIONS

• PROTEOME

 The analysis of the entire PROTEin complement
expressed by a genOME, or by a cell or tissue
type.  Wasinger VC et al. Electrophoresis 16
(1995)

• PROTEOMICS

Study of the proteins expressed by a genome in a
biological sample (organism, organ, biological
fluids), at a given point in time, in a given
situation.
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Dynamics and protein concentration range
Functional Proteins
DNA
mRNA
Proteins
Genome
Transcriptome
Proteome
Post-translational modifications
Transcription
Translation
Human 30 000 genes 300 000 transcripts
3 000 000 proteins
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Diverse properties of proteins
Proteomics is a particularly rich source of
biological information

• complex
• dynamic
• PTMs

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Complexity of proteomes
Same genome
Different proteomes
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Applications of proteomics

• Systematic proteome description
• Functional proteomics
• Differential analysis (biological markers)
• Cell map proteomics (organelles)
• protein/protein or protein/drug interactions
• Post-translational modifications

Multiprotein complexes affinity purification
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OVERVIEW

• What is proteomics ?
• Why do it ?
• How is it done ?
• Application of proteomics to obesity

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Why do proteomics ?

• mRNA expression analysis does not always
  reflect the expression level
• of proteins
• Biological samples such as CSF, serum, urine
  etc. are not suitable for
• mRNA expression analysis
• It focuses on gene products the active agents
  in cells/tissues/organisms
• Analyse the modifications of proteins that are
  not apparent from DNA
• sequence (i.e. post-translational modifications)
• Analyse the location of proteins

Genomics on Obesity, Toulouse, 7-8 June 2007
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OVERVIEW

• What is proteomic ?
• Why do it ?
• How is it done ?
• Application of proteomics to obesity

Genomics on Obesity, Toulouse, 7-8 June 2007
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Proteomics workflow

• Sample preparation
• Protein separation
• Protein detection
• Protein identification
• Validation and functional analysis

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Sample preparation
Conditions sufficiently denaturing to solubilize
a maximum of proteins, to dissociate all the
complexes, to maintain them in solution and avoid
all chemical modifications of protein subunits.

• Sample preparation
• Protein separation
• Protein detection
• Protein identification
• Validation and functional
• analysis

chaotrope Agents
Reducing Agents
DTT (65 mM) Dithiothreitol DTE ( 65 mM)
Dithioerythreitol TBP (2mM) Tributyl phosphine
Urea (5-8M) Thiourea (2M)
Non ionic Detergents
Ampholytes
CHAPS (2-4) SB 3-10 (2) ASB-14 (1) SDS lt0,25
IPG buffer pH 3-10 0,5-2
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Sample preparation

• Lysis procedure
• Protease inhibitors
• Removal of interfering substances
• Nucleic acids
• lipids
• salts
• insoluble materials
• Precipitation
• Fractionation
• subcellular
• differential

• Sample preparation
• Protein separation
• Protein detection
• Protein identification
• Validation and functional
• analysis

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Protein separation

• Gel-based proteomics
• 1D or 2D electrophoresis
• Mass spectrometry driven proteomics
• Chromatography
• ICAT
• Protein arrays

• Sample preparation
• Protein separation
• Protein detection
• Protein identification
• Validation and functional
• analysis

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2D electrophoresis
The most widely used technical approach

• 1D separation based on the pI of proteins
• 2D separation based on the molecular weight
• of proteins
• Several visualization/detection possibilities

gt Up to 10 000 protein spots/gel
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First dimension IPG strip
IPG Immobolized pH gradients Copolymerisation of
the pH gradient with the acrylamide matrix on a
plastic film

• Size
• Width 3mm
• Depth 5mm
• Length 7, 11, 13, 18 et 24 cm

Best resolution and reproducibility

• pH scale
• large 7 pH units (3-10, 3-10NL)
• narrow 3-4 pH units (3-7, 4-7, 6-9, 6-11)
• micro 1 pH unit (3,5-4,5, 4-5, 4,5-5,5, 5-6,
  5,5-6,5)

Large scale
Narrow scale Increase loading capacities and
resolution of proteins
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First dimension Isoelectric focusing (IEF)
IPGphor (Amersham)

• Programming
• Voltage (0-10000V, step-n-hold, gradient)
• 50 µA/strip
• Vh
• temperature 15-20C

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Equilibration
Tris-HCl 50 mM pH 8,8, Urée 6M, Glycérol 30, SDS
2 DTT 125 mM during10 min iodoacétamide
125 mM during 10 min
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SDS-PAGE
Criterion cell and precast gels (BioRad)
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Protein detection

• Sample preparation
• Protein separation
• Protein detection
• Protein identification
• Validation and functional
• analysis

Sensibility 100 ng 200 pg 1 ng 250 pg 1pg
Linearity low low high high high
Methods Comassie blue Silver Nitrate Fluorescen
ce Fluorescent labelling Radiolabelling
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Protein detection
Imagescanner (Amersham)

• Sample preparation
• Protein separation
• Protein detection
• Protein identification
• Validation and functional
• analysis

Image Master 2D Platinum (Amersham)
Proteins are automatically detected, background
is corrected, spot density is quantified and
spots are matched between up to 100 gels
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Protein identification

• Sample preparation
• Protein separation
• Protein detection
• Protein identification
• Validation and functional
• analysis

• MS identification of proteins after quantitative
  analysis
• by 2DE
• Peptide mass fingerprinting (MALDI MS)
• Sequence based identification (MS/MS)
• Identification and quantitation using MS
• Labelling samples for quantitative analysis
• Identification of post-translational
  modifications

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Validation

• Validation
• by Western-blot
• by ELISA
• by activity measurements
• Functional analysis
• Overexpression
• siRNA

• Sample preparation
• Protein separation
• Protein detection
• Protein identification
• Validation and functional
• analysis

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OVERVIEW

• What is proteomics ?
• Why do it ?
• How is it done ?
• Application of proteomics to obesity

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OBESITY
Glucose homeostasis requires the
coordinated actions of various organs
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Proteomics of obesity
Schmid GM, Converset V, Walter N, Sennitt MV,
Leung KY, Byers H, Ward M, Hochstrasser DF,
Cawthorne MA, Sanchez JC. Effect of high-fat
diet on the expression of proteins in muscle,
adipose tissues, and liver of C57BL/6 mice.
Proteomics. 42270-82, 2004. Sanchez JC,
Converset V, Nolan A, Schmid G, Wang S, Heller M,
Sennitt MV, Hochstrasser DF, Cawthorne MA. Effect
of rosiglitazone on the differential expression
of obesity and insulin resistance associated
proteins in lep/lep mice. Proteomics. 31500-20,
2003. Budde P, Schulte I, Appel A, Neitz S,
Kellmann M, Tammen H, Hess R, Rose Peptidomics
biomarker discovery in mouse models of obesity
and type 2 diabetes. Comb Chem High Throughput
Screen. 8775-81, 2005. Hittel DS, Hathout Y,
Hoffman EP, Houmard JA. Proteome analysis of
skeletal muscle from obese and morbidly obese
women. Diabetes. 541283-8, 2005. DeLany JP,
Floyd ZE, Zvonic S, Smith A, Gravois A, Reiners
E, Wu X, Kilroy G, Lefevre M, Gimble JM.
Proteomic analysis of primary cultures of human
adipose-derived stem cells modulation by
Adipogenesis. Mol Cell Proteomics. 4731-40,
2005. Xu A, Wang Y, Xu JY, Stejskal D, Tam S,
Zhang J, Wat NM, Wong WK, Lam KS. Adipocyte fatty
acid-binding protein is a plasma biomarker
closely associated with obesity and metabolic
syndrome. Clin Chem. 52405-13, 2006.
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Proteomics of obesity
Hittel DS et al. Proteome analysis of skeletal
muscle from obese and morbidly obese women.
Diabetes. 541283-8, 2005.
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OBESITY
Chronic elevation of NEFAs inhibits insulin
action in skeletal muscle
Insulin
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OBESITY
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Mitochondrial dysfunction
Potential mechanism by which mitochondrial
dysfunction induces insulin resistance in
skeletal muscle
Lowell BB et al. (2005) Science 307, 384-387.
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Skeletal muscle
- 4 of muscle mass - Variation with function of
muscles, type of fibers, physical activity and
age. - 2 populations of mitochondria
Subsarcolemmal mitochondria
Intermyofibrillar mitochondria
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Mitochondrial proteome
Human genome 30 000-40 000 genes
Mitochondria 1500 proteins
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Mitochondrial dysfunction
Stockage TG
Fatty acids
Fatty acids
Signaling
-
Acyl-CoA
Glucose
Glucose
ß-oxydation
Altered mitochondrial structure, biogenesis and
function in skeletal muscle of HFD mice
PGC-1a
Target gene
nucleus
CO2
O2
Identify differentially expressed proteins in
skeletal muscle of SD and HFD-fed mice (after 4
and 16 weeks of diet)
2D gels of mitochondrial proteins
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Sample preparation
2 times of diet (4 and 16 weeks)
10
pI 3
6 SD mice
6 HFD mice
Gastrocnemius muscle
10
pI 3
Purification of mitochondria
7M Urea, 2M thiourea, 1 ASB14, 2mM TBP, 0.2
IPG buffer, BB
Protein solubilization
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2D electrophoresis
6 mt samples SD 6 mt samples HFD
10
pI 3
1 mt sample SD 1 mt sample HFD
Strip pH 3-10NL 20 µg mt proteins Active
rehydration (50V) Focalisation 22 250 V.h.
6 strip SD 6 strip HFD
IEF
SDS-PAGE gels 8-16 Silver nitrate staining
6 2D gels SD 6 2D gels HFD
pI 3
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Data analysis

• Format
• Resolution (dpi)
• depth (8-16 bit)
• Artefacts

Image acquisition (300 dpi)
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Image analysis ImageMaster 2D Platinum
Identification by LC-MS/MS
Proteomic platform of Rhônes-Alpes Region Jerome
Garin, CEA Grenoble
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Data analysis

• Visualizing and calibrating gels
• Detecting spots
• (intensity, volume)
• Matching spots
• Verification of match
• Intra-class analysis
• Statistical tests
• Kolmogorov, Wilcoxon, T-test

Image acquisition (300 dpi)
10
Image analysis ImageMaster 2D Platinum
Identification by LC-MS/MS
Proteomic platform of Rhônes-Alpes Region Jerome
Garin, CEA Grenoble
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Data analysis
Molecules
IonisationMALDI, ESI,
Image acquisition (300 dpi)
Analyser TOF, Q, B, IT
m/z
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Detection
Image analysis ImageMaster 2D Platinum
Identification by LC-MS/MS
Spectrum
Proteomic platform of Rhônes-Alpes Region Jerome
Garin, CEA Grenoble
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Analyse of mRNA and protein expression levels
mRNAProt (46)
mRNA?Prot (54)
PTMs ?
mRNA Real-time RT-PCR Protein 2D electrophoresis
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PROTEOMIC APPROACH
2D Electrophoresis
ProteomLab PF 2D
1st dimensionHPLCSeparation based on pI 2nd
dimensionHPLCSeparation based on hydrophobicity
1st dimensionIsoelectric focalisation Separation
based on pI 2nd dimension SDS-PAGE gel
Separation based on molecular weight
Identification of proteins by mass
spectrometry (Proteomic plateform of Rhône-Alpes
Region - JéromeGarin, CEA, Grenoble)
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2D electrophoresis
330 matched proteins on 12 gels
18 dysregulated proteins (17 up, 1 down)
A
D
B
C
E
F
STZ
STZ
STZINS
STZINS
4324 4333 4329 4370 4367
4390 4432
4405
4348
4062 4123 4133 4129
4182 4168
4271 5307 4378
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PROTEOMLAB PF2D
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PF2D 32KARA
B
A
Gradient (pH8-4)
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PF2D ProteoVue
Hydrophobicity profile of the proteins with pI
4.96-5.2
pH
Washing
A
pH Gradient
B
Hydrophobicity
Temps de rétention (min)
Wells
10
B
9
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
A
27
Fractions
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PF2D DeltaVue
Hydrophobicity profile for the proteins with pI
6. 32-6.6
Hydrophobicity profile for the proteins with pI
6. 32-6.6
pI
Hydrophobicité
STZ
STZ INS
STZ INS
Differential
STZ
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Sample preparation
1 mg mt proteins
Mitochondria purification from gastrocnemius
muscle
STZ INS
6 mice/group n2
49 mitochondrial proteins are regulated by
insulin treatment 43 and 6
Identification by mass spectrometry
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Strategy for identification of proteins
Purification
PF2D (no MS/MS)
Elution
Differential analysis
Excision of bands
1D gel and silver nitrate staining
MALDI-TOF
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Limits of each proteomic approach
2D-E
2D-LC

• time consuming
• reproductibility
• staining
• proteins of high MW
• hydrophobic proteins
• low quantity proteins

• higher number of proteins
• quantity of sample (1-5 mg)
• columns/buffers
• differential analysis
• mass spectrometry
• several proteins in a fraction

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Acknowledgements
CEA Grenoble Jérome Garin
UMR INSERM U449/INRA U1235 Jennifer
Rieusset Charlotte Bonnard Hubert Vidal
IFR 62 Laennec Simone Peyrol Annabelle Bouchardon
CRNH RA Martine Laville
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Abbreviations used(not otherwise explained in
slides or notes)
ADN DNA
ARN RNA
ASB Aminosulphobetaine (detergent)
CHAPS 3-(3-cholamido propyl) dimethyl ammonio-1-propanesulphonate (detergent)
COX Cytochrome C oxidase
CSF Cerebrospinal fluid
ELISA Enzyme-linked immunosorbent assay
GTT Glucose tolerance test
HFD High fat diet
HPRT Hypoxanthine/guanine phosphoribosyl transferase (a housekeeping gene)
ICAT Isotope-coded affinity tagging
IPG (buffer) Immobilized pH gradient
LC Liquid chromatography
MALDI-TOF Matrix assisted laser desorption/ionization time of flight (mass spectrometry)
MS Mass spectrometry
mt Mitochondria(l)
PGC (-1a, etc) Peroxisome-proliferator-activated receptor-gamma co-activator
PTM Post-translational modification (of proteins)
SB Sulphobetaine (detergent)
SD Standard diet
SDS-PAGE Sodium dodecyl sulfate polyacrylamide gel electrophoresis
siRNA Small interfering RNA
STZ Streptozotocin