Introduction to Metabolomics Introduction to Metabolomics Thomas M. O’Connell, Ph.D. UNC Metabolomics Laboratory • Definitions of Metabolomics • Analytical Instrumentation – Nuclear Magnetic Resonance – Mass Spectrometry • Multivariate statistical Analysis – Principal Component Analysis • Applications to Toxicology
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Introduction to Metabolomics Thomas M. O’Connell, Ph.D. UNC Metabolomics Laboratory Definitions of Metabolomics Analytical Instrumentation –Nuclear Magnetic.
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Introduction to MetabolomicsIntroduction to Metabolomics
Thomas M. O’Connell, Ph.D. UNC Metabolomics Laboratory
• Definitions of Metabolomics
• Analytical Instrumentation– Nuclear Magnetic Resonance– Mass Spectrometry
• Multivariate statistical Analysis– Principal Component Analysis
• Applications to Toxicology
From Genotype to PhenotypeFrom Genotype to Phenotype
GENOMEGENOMETRANSCRIPTOMETRANSCRIPTOME
PROTEOMEPROTEOME METABOLOMEMETABOLOME
Mostly unknown Mostly known
Dettmer et al., MS Reviews, 26, 51, 2007
Metabolomics is the Most Closely Metabolomics is the Most Closely Related to PhenotypeRelated to Phenotype
Studying the Whole MetabolomeStudying the Whole Metabolome
CH2OP
CHOH
CH2O-
3-phosphoglyceric
acid dehydrogenase
CH2OP
CO
CH2O-
Focused analysis of a single metabolic pathwayFocused analysis of a single metabolic pathway
Unbiased analysis of the entire metabolomeUnbiased analysis of the entire metabolome
Identification of BiosignaturesIdentification of Biosignatures
Nature Rev Drug Disc, 1, 153, (2002)
Some DefinitionsSome Definitions
Typical Size Range of MetabolitesTypical Size Range of Metabolites
Douglas B. Kell, Curr Opin Microbiol. 7, 296, 2004
Development of NMR and MS in MetabolomicsDevelopment of NMR and MS in Metabolomics
PubMed references for title/abstract search on “metabolomics OR metabonomics” with NMR or MS
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# o
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itle
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Metabolomics
Metabolomics & MS
Metabolomics & NMR
Main Analytical Approaches to MetabolomicsMain Analytical Approaches to Metabolomics
MS
Chromatography
LC/MS
GC/MS
CE/MS
NMR
LC/NMR
Off-linehyphenation
NMR
LC/UV
GC/MS
LC/MS
M (10-6)
nM (10-9)
pM (10-12)
fM (10-15)
Range of Tools Required to Cover the Entire MetabolomeRange of Tools Required to Cover the Entire Metabolome
Adapted from Sumner, LW, et al., Phytochem, 62, 817,2003
Inlet
Ionization
Mass Analyzer
Mass Sorting (filtering)
Ion Detector
Detection
Ion Source
• Solid• Liquid• Vapor
Detect ionsForm ions
(charged molecules)Sort Ions by Mass (m/z)
1330 1340 1350
100
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50
25
0
Mass Spectrum
Acquiring a Mass SpectrumAcquiring a Mass Spectrum
All compounds must be ionized, but ionization efficiency is variable with different compounds
High voltage applied to metal sheath (~4 kV)
Sample Inlet Nozzle(Lower Voltage)
Charged droplets
++
++++
++
++++
++
++++ +++
+++ +++
+++ +
++
+
+
+
+
+++
+++
+++
MH+
MH3+
MH2+
Pressure = 1 atmInner tube diam. = 100 um
Sample in solution
N2
N2 gas
Partialvacuum
Electrospray ionization:
Ion Sources make ions from sample molecules
Typical MS SpectraTypical MS Spectra
Features of GC/MS MetabolomicsFeatures of GC/MS Metabolomics• Useful for volatiles or compounds that can be derivatized to volatile
compounds (derivatization often required)• Ideal for long chain compounds e.g. FFA, acyl carnitines, etc• More stable and reproducible than LC/MS• Most advanced metabolomics libraries• Standards are typically required for positive identification• Inexpensive technology
Experiment
Library match
• Chromatography can be tailored to specific chemical classes• Various MS analyzers can be coupled e.g. triple quad, TOF, ion trap each with it’s own
advantages in speed, resolution and sensitivity.• Very high mass accuracy available with TOF instruments (< 2ppm)• Variable ionization efficiencies and matrix suppression leads to poor quantitation w/out
standards• Excellent for targetted metabolomics, more challenging for global “unbiased” profiling• Q-TOF can acquire high res data + MS/MS for fragmentation analyses• Libraries are available but suffer from inconsistent retention times in the LC front end.
Features of LC/MS MetabolomicsFeatures of LC/MS Metabolomics
The NMR PhenomenonThe NMR Phenomenon(Hydrogen nuclei act like little magnets)(Hydrogen nuclei act like little magnets)
Hydrogen nuclei out and about Hydrogen nuclei in a magnetic field
RF
pulse
Aligned with the big magnetic field
Precessionbased on magnetic
environment& detection
Excited statetransverse to the field
The NMR ExperimentThe NMR Experiment
detector
The Chemical ShiftThe Chemical Shift
Different hydrogen atoms (gray) are in unique Different hydrogen atoms (gray) are in unique chemicalchemical and and magneticmagnetic environments environments
This results in different precession frequencies and This results in different precession frequencies and distinct spectral features.distinct spectral features.
If you want to live longest what should you drink?
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Principal Component Number
Cu
mu
lati
ve V
aria
nce
Cap
ture
d (
%)
Eigenvalues for Wine
Capture the Variance w/ Fewer Variables (factors)
-4 -3 -2 -1 0 1 2-2.5
-2
-1.5
-1
-0.5
0
0.5
1
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2
2.5
Scores on PC 1 (46.03%)
Sco
res
on
PC
2 (
32.1
1%)
France
Italy
Switz
Austra Brit
U.S.A.
Russia
Czech
Japan
Mexico
Samples/Scores Plot of Wine
Which Countries are Most Similar?
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Loadings on PC 1 (46.03%)
Lo
adin
gs
on
PC
2 (
32.1
1%)
Liquor
Wine
Beer
LifeEx HeartD
Variables/Loadings Plot for Wine
How are the Variables Correlated?
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-2
-1.5
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Scores on PC 1 (46.03%)
Sco
res
on
PC
2 (
32.1
1%)
France
Italy
Switz
Austra Brit
U.S.A.
Russia
Czech
Japan
Mexico
Samples/Scores Plot of Wine
-0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
Loadings on PC 1 (46.03%)
Lo
adin
gs
on
PC
2 (
32.1
1%)
Liquor
Wine
Beer
LifeEx HeartD
Variables/Loadings Plot for Wine
Trends in the Scores Plot are Explained by the Trends in the Scores Plot are Explained by the Corresponding Variables in the Loadings PlotCorresponding Variables in the Loadings Plot
““Binning” the NMR SpectrumBinning” the NMR Spectrum
Quantitative Fitting with NMR DatabaseQuantitative Fitting with NMR Database
Tools to Identify BiomarkersTools to Identify Biomarkers
Set of 1D1H spectra
2D spectra1H & 13C
NMRDatabase
1H & 13CPrediction
KEGG Analysis
MetaboliteID
The Human Metabolome DatabaseThe Human Metabolome Database
http://www.metabolomics.ca/
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Metabolite ID with 2D DatasetsMetabolite ID with 2D Datasets11H-H-11H or H or 11H-H-1313C correlation spectra on selected samplesC correlation spectra on selected samples
1 = terminal methyl groups of low density (LDL) and very low density lipoproteins (VLDL). 2 = valine. 3 = leucine. 4 = 3-hydroxybutyrate. 5 = lactate. 6 = methylene protons of LDL and VLDL. 7 = alanine. 8 = methylene protons of C3 of VLDL lipoproteins. 9 = allylic methylenes of lipoproteins. 10 = acetate. 11 = N-acetylated glyoproteins. 12 = methylene protons of C2 of VLDL. 13 = methylene protons between olefinic groups of lipoproteins. 14 = albumin lysyl methylene groups. 15 = phospholipid choline headgroups. 16 = taurine. 17 = glucose. 18 = glycerol. 19 = amino acid Ca protons. 20 = choline. 21 = methylene groups of phosphatidylethanolamines.
Mapping to Pathway DatabasesMapping to Pathway Databases
Targeted MetabolomicsTargeted Metabolomics
Perform quantitative fitting on all critical metabolites and use this data for statistical analysis
Serum Metabolomics Analysis from Binned DataSerum Metabolomics Analysis from Binned Data
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t[2]
t[1]
tmoc_101_a.M4 (PCA-X)t[Comp. 1]/t[Comp. 2]Colored according to classes in M4
2 week APAP phar metab- 100 scaled.M8 (OPLS), OPLSDA- Day 5-6, 1.5 > ALT > 2.0CoeffCS[Last comp.](responder (<1.5, >2))
SIMCA-P+ 11.5 - 7/18/2007 3:46:31 PM
Pathway AnalysisStatistical analysis Metabolite ID
The Overall The Overall MetabolomicsMetabolomics Process Process
The COMET ProjectCOnsortium on MEtabonomic Toxicology
Formed to investigate the utility of metabonomic approaches to the toxicological assessment of drug candidates
Use NMR based methods to categorize the pathologic effects caused by substances with toxic effects
Initially composed of Imperial College, UK and 6 big Pharma companies (BSM, Eli Lilly, Hoffman La Roche, NovoNordisk, Pfizer and Pharmacia.
J. Proteome Research, 6, 4407, 2007
Advantages of Metabolomics to Toxicology
Metabolomic profiling of biofluids is non-invasive and systemic
Compare with transcriptomics or much proteomics which comes from specific tissues – in a tox study which tissue do you look at?
Repeated sampling allow for temporal data which can help define fast & slow responders
Picking a single timepoint can be difficult; e.g. acetaminophen toxicity takes several days to develop?
Biochemical changes can be detected even w/out histopathological changes – can detect perturbations with sub-toxic doses
Flowchart of analyses used to develop models for classifying
compounds according to toxicity
Sampling Protocol
Urine collected
0-88-24
824487296
120144168
Pre Dose
Dosing
½ euthanized at 48 hrs
½ euthanized a 168 hrs
Similarity Matrix to Identify Compounds with Similar/Related Mechanisms of Toxicity
7 replicates of hydrazine
Acetaminophen studiesSingle dose & repeat dose
Drugs with endocrine disrupting effects
Drugs causing tubular necrosis
Papillary toxins
Correlates the metabolic profiles of the different treatments
J. Proteome Res. 6, 513, 2007
Monitoring the Metabolome and Determining Monitoring the Metabolome and Determining MetabotypesMetabotypes
Metabotype: the probabalistic, multiparametric description of an organism in a given physiological state based on the analysis of its cell types, biofluids or tissues
What is Pharmaco-Metabolomics?What is Pharmaco-Metabolomics?
The prediction of the outcome of a drug or The prediction of the outcome of a drug or xenobiotic intervention in an individual xenobiotic intervention in an individual based on a mathematical model of pre-based on a mathematical model of pre-