Apport de l’analyse métabolomique à la recherche biomédicale · Laboratoire d’Etude du...
Transcript of Apport de l’analyse métabolomique à la recherche biomédicale · Laboratoire d’Etude du...
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Christophe Junot
CEA/Laboratoire d’Etude du Métabolisme des Médicaments
CEA-Saclay (iBiTec-S)
Apport de l’analyse métabolomique
à la recherche biomédicale
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Les approches globales «omiques»
Les gènes
Le génome
génomique
polymorphisme
Les ARN messagers
Le transcriptome
transcritomique
Les métabolites
Le métabolome
métabolomique
Les protéines
Le protéome
protéomique
GENOTYPE PHENOTYPE
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Métabolites et métabolome
D:\439010\...\ara 0uM CdCl2 n1.1 12/07/02 15:50:20
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CdCl2 n1.1Alimentation / Boisson
Pathologie
Environnement :
xénobiotiques
(polluants,
médicaments…)
Flore intestinale
Métabolisme «central»
Métabolites primaires Métabolites secondaires Xénobiotiques
Empreinte métabolique
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Déroulement d’une analyse métabolomique
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-4000 -3000 -2000 -1000 0 1000 2000 3000 4000
t[2]O
t[1]P
Data Tri 22-5 NVol Q=1.M13 (OPLS), M1-par
t[Comp. 1]/t[Comp. 2]
Colored according to Obs ID (Primary)
R2X[1] = 0.279651 R2X[2] = 0.313673
Ellipse: Hotelling T2 (0.95)
G1
G3
SIMCA-P 11 - 11/06/2008 10:05:39
TEMOINS MALADES
PREPARATION DES
ECHANTILONS
ACQUISITION DES EMPREINTES TRAITEMENT DES DONNEES
IDENTIFICATION DES BIOMARQUEURS CONFIRMATION ET
QUANTIFICATION
ECH.
VA
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BL
ES
(RT
-MA
SS
ES
)
EXTRACTION
DILUTION…
URINE30DIL4_CID20_endogènes #68 RT: 1.22 AV: 1 NL: 4.17E5F: FTMS + p ESI Full ms2 [email protected] [50.00-800.00]
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116.07041
173.09190
127.08652
155.0813680.4945870.06497
169.6742686.06400184.8621861.03990 102.71753 143.04167
-H2O
[M+H]+ -HCOOH
-C2H3ON
BASES DES DONNEES, MS/MS …
DETECTION AUTOMATIQUE
DES SIGNAUX
DETECTION AUTOMATIQUE
DES SIGNAUX
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Metabolites occur at a wide concentration
range
(Adapted from Sumner L.W. et al., 2003)
mM
Concentration
range
µM
nM
pM
Glucose
Citric acid
Amino-acids
Hormones
Neurotransmitters
Prostanoids
NMR
GC/MS
LC/MS
LC/Fluo
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Acquisition des empreintes métaboliques
Empreinte métabolique D:\439010\...\ara 0uM CdCl2 n1.1 12/07/02 15:50:20
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100,00-1000,00]
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CdCl2 n1.1
RMN GC-EI-MS - Simple, non invasif
- Rapide
- Applicable à des biomatériaux
intacts et aux grandes séries
Mais :
- Sensibilité limitée
- Difficulté d’identification de
composés inconnus
- Sensible
- Reproductible
- Bibliothèques de spectres de
masse
Mais :
- Modification chimique requise
pour les composés non volatils
- Composés non
thermosensibles
LC-API-MS - Accès à la masse moléculaire
(identification)
- Analyse des molécules
thermolabiles
- sensible
Mais:
peu reproductible
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
La spectrométrie de masse:
détecter et identifier des molécules par mesure
de leur masse
Source Analyseur(s) Détecteur Traitement du signal
Production d’ions en phase gazeuse
Séparation des ions selon leur rapport m/z
Conversion d’un courant ionique en courant électrique
080805-03 #7-29 RT: 0.10-0.46 AV: 23 NL: 1.91E7T: FTMS + p ESI Full ms [80.00-800.00]
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m/z
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288.2531
179.1068
147.1126114.0912
135.0910
159.0676119.0831
234.0970167.0830196.6413
183.0779
265.1116227.1752 244.2270
281.0650
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Ionisation à pression atmosphérique et analyseurs
à haute résolution
Résolution en masse
C10H15O4 (0.1 ppm)
Databases
Précision en masse
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
nM
µM
pM
Metabolome
1-10 10-100 100-500
Targeted
metabolites
Metabolic pathways
Chemical families
Number of analyzed compounds
High
Resolution MS
Triple quadrupole
instruments
(MRM mode)
Relative quantification
Absolute quantification
D:\439010\...\ara 0uM CdCl2 n1.1 12/07/02 15:50:20
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CdCl2 n1.1
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Few thousands of
variables…
…Few hundreds of
metabolites ??
Annotation of peak lists is required
to help for metabolite identification
D:\439010\...\ara 0uM CdCl2 n1.1 12/07/02 15:50:20
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CdCl2 n1.1
Samples
Va
ria
ble
s (
Rt-
ma
ss
)
?
?
?
?
?
?
?
?
?
D:\439010\...\ara 0uM CdCl2 n1.1 12/07/02 15:50:20
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1,63E7
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100,00-1000,00]
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D:\439010\...\ara 0uM CdCl2 n1.1 12/07/02 15:50:20
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CdCl2 n1.1
Chemical and biochemical databases: KEGG (www.genome.jp/kegg),
Metlin (www.metlin.scripps.edu), HMDB (www.hmdb.ca)
spectral databases
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
var mzmed rtmed mziT nom annotation
331 94.1035879 41.2395458 93.0963079
164 75.091789 41.4078375 74.084509
1,3-Propanediamine METLIN 3216 109-76-2@1,3-
Diaminopropane HMDB HMDB00002 109-76-2@1,3-
Diaminopropane KEGG C00986 109-76-2@ [(M+H)-(NH3)-(C4H6)]+ spermidine
121 72.0808764 41.4121375 71.0735964 3-Buten-1-amine KEGG C12244 IND@ [(M+H)-(NH3)-(C3H7N)]+ spermidine
401 102.115188 41.4677549 101.107908
595 129.139029 41.4682607 128.131749 [(M+H)-(NH3)]+ spermidine
404 102.616829 41.5832821 101.609549
152 74.0879546 41.5832821 73.0806746 [(M+2H)]2+ (13C) spermidine
34 58.0649479 41.6414273 57.0576679 Cyclopropylamine KEGG C14150 765-30-0@ [(M+H)-(NH3)-(C4H6)-(NH3)]+ spermidine
327 93.6019358 41.9281549 92.5946558
775 149.03607 42.3813985 148.02879
144 73.586346 42.3914349 72.579066 [(M+2H)]2+ spermidine
494 113.115813 42.7321078 112.108533 [(M+H)-2(NH3)]+ (13C) spermidine
834 159.368708 42.7372617 158.361428
884 164.864699 42.7393498 163.857419
81 65.072954 42.8461541 64.065674
848 161.719771 43.2554375 160.712491
762 147.169448 43.2633375 146.162168 [M+H]+ (13C)spermidine
485 112.112241 43.3123549 111.104961 [(M+H)-2(NH3)]+ spermidine
870 162.444745 43.3125665 161.437465
872 162.672941 43.3140799 161.665661
871 162.582679 43.6324198 161.575399
235 85.0888656 43.6602673 84.0815856 1-Methylpyrrolinium KEGG C06178 IND@
866 162.299377 43.661028 161.292097
858 162.081633 43.6615902 161.074353
371 97.9689677 43.6634508 96.9616877
756 146.165593 43.6718352 145.158313
Spermidine METLIN 254 124-20-9@Spermidine HMDB
HMDB01257 124-20-9@Spermidine KEGG C00315 124-20-
9@ [M+H]+ spermidine
857 162.050661 43.7169657 161.043381
679 133.561403 43.7169657 132.554123
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Formal identification of metabolites often requires several
complementary analytical tools
Mass spectrometry NMR spectroscopy
To discriminate between isomers
C:\Documents and Settings\...\MTA-CID1 12/02/2007 18:17:20 5 ug/ml
eau/MeCM, HCOOH 0.1%, col 15%
MTA-CID1 #1 RT: 0.01 AV: 1 NL: 3.22E7
T: + p Full ms2 [email protected] [50.00-300.00]
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136.0
297.9
163.1145.1
97.1 119.261.1 238.4178.493.875.1 208.2 280.1256.9221.2159.6 191.5
m/z Molecular mass
061017-CIDPB-PT-UPLC #2447-2474 RT: 44.30-44.76 AV: 10 NL: 2.60E7F: FTMS - c ESI d Full ms2 [email protected] [ 55.00-260.00]
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247.0721
204.0667
161.0612
176.0720
218.0333
133.0664
191.3928137.0212100.6693 229.144685.4235 165.784260.9031 77.0776 214.9476126.9277 149.5655114.1821
198.8961
179.1933
257.4338
242.8735
220.7238
x100 x20 x20
MS/MS, MSn
Structural information
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Identification of pantothenic acid in rat urine RT: 0.00 - 60.00 SM: 7G
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10016.69
22.57
5.40 23.4015.67 30.84 53.6845.0239.26
16.52
18.35 31.12 44.1234.74 56.093.19 6.65
16.53
22.54 23.365.01 15.62 38.84 43.29 52.83
NL: 1.03E7
Base Peak m/z= 220.10669-220.12871 F: FTMS + c ESI Full ms [75.00-1000.00] MS 070829-pos-05-urines
NL: 2.43E7
Base Peak m/z= 220.10669-220.12871 F: FTMS + c ESI Full ms [75.00-1000.00] MS 070829-POS-04-melstd
NL: 2.17E7
Base Peak m/z= 220.10669-220.12871 F: FTMS + c ESI Full ms [75.00-1000.00] MS 070829-pos-06-urinesurch
U
STD
US
50 100 150 200
m/z
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184.09719
142.08651156.10193
116.0342790.05494
201.8544672.04433
184.09723
142.08658156.10229
116.0344290.05491
201.8620672.04417
NL: 1.76E6
070829-pos-05-urines#817-877 RT: 16.67-16.75 AV: 3 F: FTMS + c ESI d w Full ms2 [email protected] [50.00-235.00]
NL: 3.70E6
070829-POS-04-melstd#793-844 RT: 16.10-16.73 AV: 17 F: FTMS + c ESI d w Full ms2 [email protected] [50.00-235.00]
x5
U
STD
MS²
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Characterization of unknown metabolites using MSn
Proposed by CAS Proposed (MSn, H/D)
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100139.11337
87.04586
155.10819113.06150
201.11358
71.05096101.06151 165.09146
196.98576
139.11337
201.11352157.1237874.02549 111.08214 194.63205
125.26109
139.11240
112.98559
201.1121168.99611 157.1227385.80583 119.15112
NL: 1.43E6
070829-urinepbpd_070829152643#1167-1206 RT: 21.82-21.88 AV: 3 F: FTMS - c ESI d w Full ms2 [email protected] [50.00-215.00]
NL: 2.12E6
070829-urinepbpd_070829152643#1487-1534 RT: 26.41-26.50 AV: 3 F: FTMS - c ESI d w Full ms2 [email protected] [50.00-215.00]
NL: 5.41E5
070829-mel10standards#697-723 RT: 26.86-27.02 AV: 4 F: FTMS - c ESI d w Full ms2 [email protected] [50.00-215.00]
(Werner E. et al., 2008), Collaboration Pr. J.-C. Tabet, UPMC
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Quantitative metabolite profiling for large
scale studies
Normalized metabolic profiles Absolute quantification of metabolites
A/A
ISConcentration
Molarity unit
Samples Biological
matrix
Internal
standards (ISs)Calibrants
Calibration curve
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
GC/MS ESI/MS LC/MS MALDI-TOF
NMR
1960 2010 2000 1990 1980 1970
Imaging MS
In situ analyses
Metabolomics
Metabonomics: The metabolic response
of living systems to physiopathological
stimuli via multivariate statistical
analysis of biological NMR spectra. (Nicholson et al., 1999)
Intermap study (NMR)
4630 participants (Holmes E., Nature, 2008)
«Metabolome Wide Association Studies» (Holmes E., Cell, 2008)
(Gieger C, Plos Genetics, 2008)
Sarcosine as a biomarker of
aggressive prostate cancers (Skreekumar, Nature 2009)
Microbiome interaction
Chronobiology, epigenetics
Biomarker discovery (cohort size<100)
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Glu-Phe
×
× ×
×
×
× ×
×
×
×
×
× ×
×
Glutamate
CSF metabotype of a Dihydropteridine
reductase (DHPR) deficient patient Autosomal recessive genetic disorder.
Hyperphenylalaninemia due to tetrahydrobiopterine
deficiency (malfunctioning Tyr and Trp
hydroxylases)
no change
not detected ×
increased concentrations
Phenylalanine metabolism
Tryptophan
metabolism
Medication
Miscellaneous
(Coll. Dr. F. Sedel, G.H. Pitié-Salpétrière)
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
1018_55
1043_31
1047_127
1048_95
1050_71
1052_46
1057.A
_88
1057.B
_133
1058_107
1061_32
1067_74
469
XC
96
LM
8
1073_29
1199_121
1074_80
1086_114
1087_27
1113_28
1114_50
1124_67
1134_43
1135_131
1136_39
1138_89
1140_68
1142_125
1148_77
1157_79
1161_90
1166_117
sugar acid N-acetylneuraminic acid 0.9 0.5 1.0 0.5 1.1 1.4 0.3 1.0 1.2 1.0 0.9 5.9 7.7 7.8 4.4 5.0 1.5 0.8 0.6 1.2 0.5 0.8 0.9 0.7 1.2 0.7 0.8 0.7 1.2 0.7 0.8 1.2
Deoxyribose 0.6 0.4 0.5 0.5 0.6 1.5 0.3 10.2 1.0 0.8 0.7 9.1 6.3 8.1 4.0 5.0 0.9 0.7 0.5 1.0 0.4 0.7 0.5 0.7 1.7 0.5 0.6 0.7 1.3 0.5 0.5 0.7
Pentose 1.4 0.7 0.6 0.4 0.6 3.9 0.3 1.1 1.7 1.0 0.9 8.3 2.2 1.1 4.1 2.0 3.0 0.7 0.6 2.1 1.0 1.0 0.6 0.6 1.2 0.5 0.6 0.8 1.2 0.7 0.6 0.7
Mannitol or isomers 0.9 0.6 1.1 0.4 0.8 1.8 0.6 1.3 1.1 0.8 0.7 2.2 4.4 3.3 2.5 8.1 1.3 0.8 0.6 0.9 0.6 1.0 0.6 0.7 1.0 0.5 0.4 1.5 1.7 0.6 0.6 1.3
Threonic acid 0.8 1.1 0.7 0.6 0.9 2.5 0.5 1.1 1.3 1.0 0.8 1.2 1.9 1.6 3.3 3.3 1.1 0.7 1.0 1.7 0.8 0.8 0.7 0.6 1.0 0.5 0.9 1.1 1.2 1.4 0.6 1.1
Quinic acid 3.4 0.3 0.6 0.0 0.0 4.7 0.0 0.9 5.0 1.6 0.8 4.8 4.0 1.5 2.3 3.2 5.3 1.1 0.4 9.3 2.3 3.1 0.1 1.1 0.3 0.0 0.6 1.2 0.7 0.0 1.1 0.0
nucleoside derivative Succinyladenosine 0.8 0.6 0.7 0.5 0.8 1.7 0.4 1.3 1.2 1.0 1.1 8.0 3.9 6.2 4.1 2.3 1.5 0.9 0.7 1.3 0.6 1.0 0.7 0.8 1.2 0.8 0.9 0.7 1.4 0.6 0.6 1.3
Proline Betaine 0.7 0.5 2.5 0.5 0.8 2.1 0.4 1.7 3.0 2.3 0.1 0.1 5.7 0.1 4.1 0.8 0.1 0.9 1.9 4.3 0.6 1.0 0.9 0.2 0.9 0.1 2.3 0.8 0.7 3.2 0.3 2.1
Glutamic acid0.6 0.5 0.9 0.5 0.9 1.5 0.4 1.2 1.1 0.8 0.8
3.60.7
3.42.3 2.8 1.8 0.9 0.8 1.2 0.7 0.9 0.7 0.8 1.1 0.8 0.9 0.7 1.2 0.8 0.9 1.1
Aminoadipic acid0.8 0.6 0.8 0.6 0.9 1.4 0.4 1.1 1.2 0.8 0.8
2.21.8
3.22.6 2.9 1.7 0.9 0.8 1.2 0.7 0.9 0.7 0.9 1.2 0.6 1.0 0.8 1.5 0.7 0.8 1.1
N-acetyl-L-glutamic acid 0.5 0.5 0.7 0.5 1.0 1.4 1.0 2.8 1.2 0.8 0.8 48.6 0.6 11.9 0.7 2.0 0.8 1.2 1.4 1.0 0.4 0.9 0.7 1.6 1.3 1.3 0.8 0.4 0.8 1.3 1.3 1.2
N-Acetyl-D-allo-isoleucine0.6 0.5 1.0 0.7 1.0 1.5 0.5 1.4 1.2 1.0 1.1
2.8 1.3 2.31.2 2.0 1.7 0.9 1.2 1.2 0.6 0.7 0.7 1.0 1.1 0.8 0.8 0.8 1.1 0.9 1.0 1.4
Pyrimidine derivated Dihydroorotic acid 0.9 0.7 0.8 0.4 0.9 2.2 0.4 1.3 0.9 0.8 1.0 1.6 5.5 2.7 2.2 5.0 1.3 0.5 0.7 1.1 0.8 1.0 0.7 0.5 1.4 0.6 0.7 1.1 1.4 0.5 0.6 1.3
Acetyl-carnitine 1.8 0.7 0.6 1.1 0.5 0.9 0.6 0.9 2.7 1.0 1.5 1.2 2.1 1.5 2.0 1.1 1.5 1.0 0.4 1.5 1.2 0.9 0.6 1.5 0.9 0.9 0.3 0.7 1.5 0.8 0.8 0.8
Propionyl-carnitine 1.9 0.5 0.5 1.0 0.5 1.6 0.8 0.8 2.3 1.3 1.5 0.8 3.7 1.2 2.1 0.8 0.8 1.0 0.7 1.3 1.2 0.8 0.6 1.9 0.8 1.0 0.2 0.4 1.8 1.1 0.9 0.9
Butyryl-carnitine 0.9 0.5 0.5 0.7 0.8 1.6 0.6 0.6 1.4 1.6 1.5 1.0 3.3 1.3 2.2 1.3 0.6 0.8 0.8 1.2 1.1 0.9 0.6 1.2 1.0 0.9 0.3 0.6 1.6 0.7 0.9 1.1
Methylbutyroyl-carnitine 1.3 0.4 0.6 0.9 0.8 1.9 0.5 0.9 1.5 1.4 1.3 1.0 2.5 1.1 2.4 0.7 0.7 0.8 1.0 1.3 0.9 0.7 0.6 1.1 0.8 0.9 0.3 0.4 1.7 0.9 0.8 1.0
Glycochenodeoxycholic acid4.4 0.1 1.0 0.2 0.2 2.6 0.6 0.1 1.0 0.9 0.0
0.0 11.0 0.0
11.1 6.7 7.4 0.3 0.0 0.6 2.8 1.3 0.0 1.2 1.3 0.1 0.0 0.0 0.6 0.1 0.7 0.2
Glycocholic acid 1.7 0.0 1.0 0.2 0.2 5.5 0.1 0.0 0.6 0.6 0.00.0 16.0 0.0
9.6 4.8 6.2 0.1 0.4 0.4 1.9 2.2 0.1 0.5 1.8 0.2 0.5 0.0 0.2 0.2 1.2 0.9
Bile acids
Patients with unexplained encephalopathy
Carbohydrates
Hydroxy acids
Aminoacid and derivatives
Acylcarnitines
CAFSA
Kearns-Sayre syndrome
Values are fold changes
related to control value
value >mean+2SD
Mean+SD<value <mean+2SD
(Coll. Dr. F. Sedel, G.H. Pitié-Salpétrière)
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Faciliter l’échange
des données
Identification des métabolites
Informatique et
bioinformatique
Améliorer et
standardiser la détection
des métabolites Traitement des données
Visualisation des données
Formats d’échange des données
Annotation des données
Bases de données spectrales
Le futur?
Le profilage métabolique à haut débit pour
l’épidémiologie et la médecine personnalisée
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Le futur?
Le profilage métabolique pour l’anatomo-pathologie?
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Remerciements CEA/LEMM Jean-François Heilier
Alexandra Lafaye
Céline Ducruix
Erwan Werner
Geoffrey Madalinski
Emmanuel Godat
Jérôme Cotton
Ying Xu
Aurélie Roux
Eric Ezan
Benoit Colsch
Samia Boudah
CEA/iRCM Paul-Henri Roméo
Dhouha Darghouth
Bérengère Koehl
Marie-Françoise Olivier
G.H. Pitié-Salpétrière Frédéric Sedel
Maria del Mar Amador
Fanny Mochel
Foudil Lamari
Laboratoire de Chimie
Structurale Organique et
Biologique (Paris 6, CNRS) Jean-Claude Tabet
Denis Lesage
Sandra Alves
Groupe de Chimie Analytique de Paris
Sud,EA 4041 (Université Paris 11) Pierre Chaminade
CEA/DRT/LIST/DETECS Olivier Gal, Antoine Souloumiac,
Etienne Thévenot, Jean-Pierre Both
CEA/Programme Transversal de
Technologies pour la santé Jacques Grassi, Pierre-Noël Lirsac,
Bruno Corman
CEA/iBiTec Jean Labarre, Franck et Corinne
Chauvat, Michel Toledano
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
(2008)
Polymorphism in the FADS1 (fatty acid delta 5 desaturase) gene
«Genetically determined metabotypes» Quantitative measurement of363
metabolites in 284 human serum samples
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Dendrogram from hierarchical cluster analysis
Samesample, twoexperiments
Thimainetransporter and
glucose transporter deficiencies Leukodystrophies
Same patient, two samples
(2009 and 2011)
Myoclonicataxia
MitochondriopathiesPsychiatricdisorders
Cerebellar ataxia
Same sample, twoexperiments
(Coll. Dr. F. Sedel, G.H. Pitié-Salpétrière)
Laboratoire d’Etude du Métabolisme des Médicaments, DSV/iBiTec-S/SPI
Sample preparation
Sophisticated sample preparation improves detection sensitivity
at the expense of metabolome coverage
Solid phase
extraction
Liquid-liquid
extraction Solvent/acid
precipitation
To clean-up samples and/or to concentrate metabolites
Sample preparation depends on the kind of biological medium investigated and
on the kind of metabolites detected.
Cell extracts, tissue extracts, biofluids
Quenching issue