1 ) ( 1000
DNA mrna Gene-ome Transcript-ome Protein-ome Metabolite-ome Gene-omics Transcript -omics Protein -omics Metabolite -omics Title/abstract: metabolomics/metabolome Source: PubMed 1600 1400? 1200 1000 800 600 400 200 0 00 01 02 03 04 05 06 07 08 09 10 11 12 13 2013 9
CE-MS GC/MS LC-MS FT-ICRMS NMR ( ) ( ) DNA CE-MS
CE(LC)-TOFMS 200 160 60 CE-TOF MS 1m CE ) ( MS MS CE HMT 3 TOF
CE-TOF MS (CE) CE EOF MS EOF CE( ) MS( ) - - - - N N N N N N N N N N EOF 300 C(Z)E 2011/6/266/30 @Cairns CC CE-TOFMS T Takebe et al., Nature, 2013, 499(7459):481- Vascularized and functional human liver from an ipsc- S Yoshimoto et al., Nature, 2013, 499(7456):97- -induced gut microbial metabolite promotes liver cancer through senescence secretome N Ternette et al., Cell Rep., 2013, 3(3):689- aconitase by succination in fumarate hydratase H Miwa et al., Oncol. Rep. 2013, 29(5);2053- perturbation provoked by 2- Y Mitsuishi et al., Cancer Cell. 2012, 22(1);66- JM Fusin et al., Cell Rep. 2012, 1(4);341- A. Hirayama et al., Cancer Res. 2009, 69(11):4918-25. metabolome profiling of colon and stomach cancer microenvironment by capillary electrophoresis time-of- Ishii et al., Science. 2007, 316(5824): 593- Multiple Highthroughput analyses monitor the response of E. coli to perturbations
Facebook/Twitter http://humanmetabolome.com/rd/researchlist https://www.facebook.com/tarometabolo https://twitter.com/me_taro
2 A. B. C.
& ( ) & ( ) ( ) t (MS/MS NMR) HMT & ( ) & & ( ) t
& ( ) & & ( ) t HMT in vitro () in vivo ( ) I () II () III () ( ) /
2.A
QqQMS N 2 Q1 m/z Q2 Q1 Q3 m/z cgmp 20 nmol/l AMP dgmp m/z 346 152 m/z 346 Intensity S/N 356 S/N 2.5 m/z 348 136 m/z 348 152 Intensity HMT FEASIBILITY Select candidate BMs in smallscale study DISCOVERY Identify candidate BMs QUALIFICATION Confirm differential abundance of candidates VERIFICATION Begin to assess specificity of candidates VALIDATION Establish sensitivity and specificity CLINICAL ASSAY DEVELOPMENT Assay optimization CNS Major Depression Influenza-associated encephalopathy Fibromyalgia RENAL Diabetic nephropathy HEPATIC Non-alcoholic steatohepatitis GASTRO ENTERIC Colorectal cancer The process flow is depicted based on the perspective by Rifai, Gillette, and Carr (Nat. Biotech. 24:971, 2006)
MDD 31 7 34 37.8 (20-63) 49.4 (27-78) 38.9 (20-70) 15, 16 2, 5 14, 20 BMI CES-D (Score) 21.8 (16.6-30.4) 23.7 (18.7-33.3) 22.9 (18.6-31.2) 7.7 (0-17) 21.6 (13-34) 31.6 (8-50) EDTA-treated blood (5 ml) collected by vacuum blood tubes Plasma (1 ml) prepared within 2 h and stored at 80 C Metabolites extracted by solvent-extraction method (H 2 O:MeOH:CHCl 3 ) Metabolites in the aqueous layer (50 μl) analyzed by CE-TOFMS Plasma metabolome included 538 (193 annotated) metabolites Metabolite levels compared by Wilcoxon rank-sum test. O Not Significant N O P O Ethanolamine phosphate (EAP) IUPAC: 2-aminoethyl dihydrogen phosphate Molecular formula: C 2 H 8 NO 4 P Exact mass: 141.019097 O EAP (μm) P = 4.6 x 10-8 Reduction (57%) in median value No significant difference b/w AD & Ctrl (n=34) (n=7) (n=31) Significant difference in EAP between the control and MDD subjects (Wilcoxon rank-sum test: P < 0.0001 after Bonferroni correction) but no significant difference between the control and adjustment disorder subjects. * Defined in Rubin A: Statistics for evidence-based practice and evaluation, Brooks/Cole Pub Co., 2009.
(n=27)
2.B 4 (2009) CE-MSLC-MS 2000 2001 2004 2005 2006 2007
CE&LC-TOFMS 2004 2005 2006 2007 2001 2000 CE-TOFMS 161 LC-TOFM 49 2008 2007 2006 2005 2004 2003 2002 R 2 =0.991 PCR 2001 2000 1999 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 0.7 0.6 0.5 0.4 0.3 0.2 1 st Adipic acid 2 nd Malvidin-3-glucoside 0.1 0
(MLF) () CO 2 MLF 2000 2001 2004 2005 2006 2007 Pyruvic acid, Glycolic acid, 2-Hydroxypentanoic acid, Oxypurinol, Glyceric acid, Mevalonic acid, etc. Pro, Malonic acid, 5-Amino-4-oxovaleric acid, etc.
vs β
2.C MELAS: mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke-like episodes
DCA treatment Pyr treatment PDH kinase inhibited No effect on [NADH/NAD] Pyr Lac enhanced PDH activated?? G3P 1,3BPG stagnated [Lac/Pyr] & [NADH/NAD] balanced No change in TCA Glycolysis stagnated G3P1,3BPG enhanced Bypassed TCA cycle enhanced No change in Oxi. Phos. ATP remained low Glycolysis enhanced ATP increased ATP remained low ATP increased Pyr treatment changes NADH-NAD turnover, glycolysis, and TCA cycle fluxes, thereby improving the energy state in 2SD cells.
NCI-60 NCI-60 http://dtp.nci.nih.gov/branches/btb/characterizationnci60.html The NCI-60 cell lines include the following cell lines (tissue of origin is shown in bold): Lung: NCI-H23, NCI-H522, A549-ATCC, EKVX, NCI-H226, NCI-H332M, H460, H0P62, HOP92 Colon: HT29, HCC-2998, HCT116, SW620, COLO205, HCT15, KM12 Breast: MCF7, MCF7ADRr, MDAMB231, HS578T, MDAMB435, MDN, BT549, T47D Ovarian: OVCAR3, OVCAR4, OVCAR5, OVCAR8, IGROV1, SKOV3 Leukemia: CCRFCEM, K562, MOLT4, HL60, RPMI8266, SR Renal: UO31, SN12C, A498, CAKI1, RXF393, 7860, ACHN, TK10 Melanoma: LOXIMVI, MALME3M, SKMEL2, SKMEL5, SKMEL28, M14, UACC62, UACC257 Prostate: PC3, DU145 CNS: SNB19, SNB75, U251, SF268, SF295, SM539
ATP EC
Published in 2012 by Wiley Prof. Thomas Seyfried @ Boston College J Biol Chem. 2006 Jun 16;281(24):16768-76. Differential metabolomics reveals ophthalmic acid as an oxidative stress biomarker indicating hepatic glutathione consumption. Soga T, et al. PMID: 16608839 Nature. 2009 Feb 12;457(7231):910-4. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Sreekumar A, et al. PMID: 19212411 Nature. 2013 Jul 4;499(7456):97-101. Obesity-induced gut microbial metabolite promotes liver cancer through senescence secretome. Yoshimoto S, et al. PMID: 23803760 Metabolomics. 2013 Apr;9(2):444-453. Metabolomic profiling of lung and prostate tumor tissues by capillary electrophoresis time-of-flight mass spectrometry. Kami K, et al. PMID: 23543897 Proc Natl Acad Sci U S A. 2012 Feb 14;109(7):2625-9. The human circadian metabolome. Dallmann R. et al. PMID: 22308371 Oncol Rep. 2013 May;29(5):2053-7. Leukemia cells demonstrate a different metabolic perturbation provoked by 2-deoxyglucose. Miwa H, et al. PMID: 23440281 Mitochondrion. 2012 Nov;12(6):644-53. Metabolomic profiling rationalized pyruvate efficacy in cybrid cells harboring MELAS mitochondrial DNA mutations. Kami K, et al. PMID: 22884939 Science. 2012 May 25;336(6084):1040-4 Metabolite profiling identifies a key role for glycine in rapid cancer cell proliferation. Jain M, et al. PMID: 22628656 Science. 2012 May 25;336(6084):990-1. Cancer. Systems biology, metabolomics, and cancer metabolism. Tomita M, et al. PMID: 22628644 Nutr Metab (Lond). 2010 Jan 27;7:7. Cancer as a metabolic disease. Seyfried TN, et al. PMID: 20181022 Proc Natl Acad Sci U S A. 2009 Jun 16;106(24):9890-5. Measurement of internal body time by blood metabolomics. Minami Y, et al. PMID: 19487679
3
1 3 n=1 3 10 n=3 n=5 10 20 n=20 n=50 n=20 BMI EDTA ph EDTA NaF HMT EDTA Na K
Creatinine () (12) (18) A B C D E (24) Proline () (12) (18) A B C D E (24)
DNA OD HC H HS WHHL
LDL WHHL (BM) BM CE-TOFMS m/z R.S.D. EOF ( ) EOF m/z 156 Migration Time (MT) min 169 154 128 50 100 150
Pathway PCA Clustering 1 Screening Validation Construction Ratio 1 PCA 2 3 2 3 2 Screening I. (p value) Welch p 1 )
2 Screening II. Ratio 10 Uric acid N,N-Dimethylglycine Betaine 3-Hydroxy-3-methylglutaric acid ADP-ribose Ophthalmic acid 0.1 Frontier ( 2-fold) X : vs Y : vs RelativeArea > 0.1 0.01~0.1 < 0.01 10 size) n (pool Citrulline Xanthosine Cys Gluthathione 0.1 3 Screening III.!?
Screening III. 4 Hyperlipidemic (H/HC) BR CM LI WB PL Amino acids Heat Map Amino acid metabolism Clustering Choline catabolism Purine & pyrimidine Glycolysis & Pentose-P TCA cycle Organic acid Fatty acid / Lipid Coenzyme metabolism Short peptide Other 5 Metabolic changes observed in Liver Pathway / TCA Energy charge HOT SPOTS
6 Human Metabolome Data Base WikiGenes KEGG, Ecocyc HMT MeTaBoard ( ) 1 Lipoprotein (LDL) THF
2 3 Pentose-phosphate 10-formyl THF Gly, Glu, Asp
statin HMG-CoA cholesterol HDL VLDL IDL LDL / oxldl
4 HMT -80-80 -80
HMT Advanced Scan Basic Scan C-SCOPE Dual Scan CE-TOFMS 900 116 1200 (Basic Scan ) ( ) * 200 ~ 250 200 ~ 400 100 ~ 150 200 ~ 250 150 ~ 250 50 ~ 80 90 ~ 90 ~ 180 ~ 200 250 ~ 300 200 ~ 300 (3 ) 30 2 2 * ** 2013 10 12 95 ( 20% ) 2013 12 27 ( ) 2013 12 27