Transcript Document

Canadian Bioinformatics Workshops
www.bioinformatics.ca
Module #: Title of Module
2
Module 1
David Wishart
Environmental Influence
The Pyramid of Life
Metabolomics
8000
Chemicals
Proteomics
7500 Enzymes
Genomics
25,000 Genes
What is Metabolomics?
• Genomics - A field of life science research that uses
High Throughput (HT) technologies to identify and/or
characterize all the genes in a given cell, tissue or
organism (i.e. the genome).
• Metabolomics - A field of life science research that
uses High Throughput (HT) technologies to identify
and/or characterize all the small molecules or
metabolites in a given cell, tissue or organism (i.e.
the metabolome).
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What is a Metabolite?
• Any organic molecule detectable in the body with a MW
< 1500 Da
• Includes peptides, oligonucleotides, sugars, nucelosides,
organic acids, ketones, aldehydes, amines, amino acids,
lipids, steroids, alkaloids, foods, food additives, toxins,
pollutants, drugs and drug metabolites
• Includes human & microbial products
• Concentration > detectable (1 pM)
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What is a Metabolome?
• The complete collection of small molecule
metabolites in a cell, organ, tissue or organism
• Includes endogenous and exogenous molecules as
well as transient or even theoretical molecules
• Defined by the detection technology
• Metabolome size is always ill-defined
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Different Metabolomes
All Mammals
8000
Chemicals
20,000
Chemicals
200,000
Chemicals
The Pyramid of Life
All Microbes
All Plants
Human Metabolomes
3100 (T3DB)
Toxins/Env. Chemicals
1000 (DrugBank)
Drug metabolites
30000 (FooDB)
Food additives/Phytochemicals
1450 (DrugBank)
8500 (HMDB)
M
Drugs
Endogenous metabolites
mM
M
nM
pM
fM
Theoretical Human Metabolomes
100,000 (Lipidome)
Lipids/Lipid derivatives
10,000 (Drug metabolome)
Secondary drug metabolites
100,000 (Food metabolome)
10,000 (Secondome)
M
mM
Secondary food metabolites
Secondary endogenous metabolites
M
nM
pM
fM
Why is Metabolomics Important?
Small Molecules Count…
• >95% of all diagnostic clinical assays test for small
molecules
• 89% of all known drugs are small molecules
• 50% of all drugs are derived from pre-existing
metabolites
• 30% of identified genetic disorders involve diseases of
small molecule metabolism
• Small molecules serve as cofactors and signaling
molecules to 1000’s of proteins
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Metabolites Are the Canaries of the
Genome
A single base change can lead to a 10,000X change in metabolite levels
Response
Metabolomics
Response
Proteomics
Response
Metabolomics is More Time Sensitive
Than Other “Omics”
Genomics
Time
Metabolism is “Understood”
The Metabolome is Connected to
all other “Omes”
8000
Chemicals
7500 Enzymes
25,000 Genes
The Pyramid of Life
The Metabolome is Connected to All
Other “Omes”
• Small molecules (i.e. AMP, CMP, GMP, TMP) are the primary
constituents of the genome & transcriptome
• Small molecules (i.e. the 20 amino acids) are the primary
constituents of the proteome
• Small molecules (i.e. lipids) give cells their shape, form,
integrity and structure
• Small molecules (sugars, lipids, AAs, ATP) are the source of all
cellular energy
• Small molecules serve as cofactors and signaling molecules for
both the proteome and the genome
• The genome & proteome largely evolved to catalyze the
chemistry of small molecules
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Metabolomics Enables Systems
Biology
Bioinformatics
Meta
bolomics
Cheminformatics
Proteomics
Genomics
Systems
Biology
Metabolomics Applications
• Toxicology Testing
• Genetic Disease Tests
• Clinical Trial Testing
• Nutritional Analysis
• Fermentation Monitoring
• Clinical Blood Analysis
• Food & Beverage Tests
• Clinical Urinalysis
• Nutraceutical Analysis
• Cholesterol Testing
• Drug Phenotyping
• Drug Compliance
• Water Quality Testing
• Transplant Monitoring
• Petrochemical Analysis
• MRS and CS imaging
Metabolomics Methods
Metabolomics Workflow
Biological or Tissue Samples
pp
m
7
6
5
4
3
Data Analysis
2
Extraction
Biofluids or Extracts
1
Chemical Analysis
Why Metabolomics is Difficult
Chemical Diversity
Metabolomics
2x105
Chemicals
Proteomics
20 Amino acids
Genomics
4 Bases
The Pyramid of Life
Metabolomics Technologies
•
•
•
•
•
•
•
•
•
UPLC, HPLC
CE/microfluidics
LC-MS
FT-MS
QqQ-MS
NMR spectroscopy
X-ray crystallography
GC-MS
LIF detection
Chromatography
Chromatography
• The separation of components in a mixture that
involves passing the mixture dissolved in a
"mobile phase" through a stationary phase, which
separates the analyte to be measured from other
molecules in the mixture based on differential
partitioning between the mobile and stationary
phases
• Column, thin layer, liquid, gas, affinity, ion
exchange, size exclusion, reverse phase, normal
phase, gravity, high pressure
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High Pressure (Performance) Liquid
Chromatography - HPLC
• Developed in 1970’s
• Uses high pressures (6000 psi) and smaller (5 m),
pressure-stable particles
• Allows compounds to be detected at ppt (parts per
trillion) level
• Allows separation of many types of polar and
nonpolar compounds
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HPLC Modalities
• Reversed phase – for separation of non-polar
molecules (non-polar stationary phase, polar mobile
phase)
• Normal phase – for separation of non-polar molecules
(polar stationary phase, non-polar/organic mobile
phase)
• HILIC – hydrophilic interaction liquid chromatography
for separation of polar molecules (polar stationary
phase, mixed polar/nonpolar mobile phase)
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HPLC Columns
Reverse Phase Column
HPLC Separation Efficiency
HPLC Schematic
Gradient HPLC Schematic
HPLC of a Biological Mixture
Gas Chromatography
Gas Chromatography
• Involves a sample being vaporized to a gas and
injected into a column
• Sample is transported through the column by an
inert gas mobile phase
• Column has a liquid or polymer stationary phase
that is adsorbed to the surface of a metal tube
• Columns are 1.5-10 m in length and 2-4 mm in
internal diameter
• Samples are usually derivatized with TMS to make
them volatile
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TMS Derivatization
Gas Chromatography
GC-Columns
Polysiloxane
Retention Time/Index
• Retention time (RT) is the time taken by an
analyte to pass through a column
• RT is affected by compound, column (dimensions
and stationary phase), flow rate, pressure, carrier,
temp.
• Comparing RT from a standard sample to an
unknown allows compound ID
• Retention index (RI) is the retention time
normalized to the retention times of adjacently
eluting n-alkanes
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Compound Identification and
Quantification
GC-MS Chromatogram of a Biological
Mixture
Mass Spectrometry
• Analytical method to measure the molecular or atomic
weight of samples
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Typical Mass Spectrometer
MS Principles
• Different compounds can be uniquely identified
by their mass
Butorphanol
L-dopa
N -CH2OH
Ethanol
COOH
HO
-CH2CH-NH2
CH3CH2OH
HO
HO
MW = 327.1
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MW = 197.2
MW = 46.1
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Mass Spectrometry
• For small organic molecules the MW can be
determined to within 1 ppm or 0.0001% which is
sufficiently accurate to confirm the molecular formula
from mass alone
• For large biomolecules the MW can be routinely
determined within an accuracy of 0.002% (i.e. within 1
Da for a 40 kD protein)
• Recall 1 dalton = 1 atomic mass unit (1 amu)
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Different Types of MS
• GC-MS - Gas Chromatography MS
– separates volatile compounds in gas column and ID’s by mass
• LC-MS - Liquid Chromatography MS
– separates delicate compounds in HPLC column and ID’s by mass
• MS-MS - Tandem Mass Spectrometry
– separates compound fragments by magnetic or electric fields
and ID’s by mass fragment patterns
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Masses in MS
• Monoisotopic mass is
the mass determined
using the masses of
the most abundant
isotopes
• Average mass is the
abundance weighted
mass of all isotopic
components
Isotopic Distributions
1H
= 99.9%
2H = 0.02%
12C
= 98.9%
13C = 1.1%
35Cl
= 68.1%
37Cl = 31.9%
Isotopic Distributions
1H
12C
= 99.9%
2H = 0.02%
= 98.9%
13C = 1.1%
100
32.1
6.6
2.1
m/z
0.06 0.00
35Cl
= 68.1%
37Cl = 31.9%
Mass Spec Principles
Sample
+
_
Ionizer
Mass Analyzer
Detector
Typical Mass Spectrum
aspirin
Typical Mass Spectrum
• Characterized by sharp, narrow peaks
• X-axis position indicates the m/z ratio of a given ion
(for singly charged ions this corresponds to the
mass of the ion)
• Height of peak indicates the relative abundance of a
given ion (not reliable for quantitation)
• Peak intensity indicates the ion’s ability to desorb or
“fly” (some fly better than others)
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Resolution & Resolving Power
• Width of peak indicates the resolution of the MS
instrument
• The better the resolution or resolving power, the
better the instrument and the better the mass
accuracy
DM
• Resolving power is defined as:
M
• M is the mass number of the observed mass (DM) is
the difference between two masses that can be
separated
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Resolution in MS
Low resolution Instrument
(Ion trap)
High resolution Instrument
(TOF)
2847
Resolution in MS
Resolution/Resolving Power
MW(mono) = 3482.7473
MW(ave) = 3484
Blue DM/M = 1000
Red DM/M = 3000
Green DM/M = 10000
Black DM/M = 30000
Mass Spectrometer Schematic
Turbo pumps
Diffusion pumps
Rough pumps
Rotary pumps
High Vacuum System
Inlet
Sample Plate
Target
HPLC
GC
Solids probe
Ion
Source
Mass
Analyzer
MALDI
ESI
IonSpray
API
LSIMS
EI/CI
TOF
Quadrupole
Ion Trap
Orbitrap
QTrap
Mag. Sector
FTMS
Detector
Microch plate
Electron Mult.
Hybrid Detec.
Data
System
PC’s
UNIX
Mac
Different Ionization Methods
• Electron Ionization (EI - Hard method)
– Small molecules, 1-1000 Daltons, structure
• Chemical Ionization (CI – Semi-hard)
– Small molecules, 1-1000 Daltons, simple spectra
• Electrospray Ionization (ESI - Soft)
– Small molecules, peptides, proteins, up to 200,000 Daltons
• Matrix Assisted Laser Desorption (MALDI-Soft)
– Smallish molecules, peptides, proteins, DNA, up to 500 kD
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Electron Impact Ionization
• Sample introduced into instrument by heating it
until it evaporates
• Gas phase sample is bombarded with electrons
coming from rhenium or tungsten filament
(energy = 70 eV)
• Molecule is “shattered” into fragments (70 eV >>
5 eV bonds)
• Fragments sent to mass analyzer
• Most commonly used in GC-MS
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EI Fragmentation of CH3OH
CH3OH
CH3OH+
CH3OH
CH2O=H+
CH3OH
+
CH2O=H+
+ H
CH3 + OH
CHO=H+ + H
Electron Impact MS of CH3OH
Molecular ion
EI Breaks up Molecules in Predictable Ways
Soft Ionization Methods
337 nm UV laser
Fluid (no salt)
+
_
Lecture 2.1
cyano-hydroxy
cinnamic acid
Gold tip needle
MALDI
ESI
63
Electrospray (Detail)
Electrospray (Detail)
Electrospray Ionization
• Sample dissolved in polar, volatile buffer (no salts)
and pumped through a stainless steel capillary (70
- 150 m) at a rate of 10-100 L/min
• Strong voltage (3-4 kV) applied at tip along with
flow of nebulizing gas causes the sample to
“nebulize” or aerosolize
• Aerosol is directed through regions of higher
vacuum until droplets evaporate to near atomic
size (still carrying charges)
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Electrospray Ionization
5%H2O/95%CH3CN
95%H2O/5%CH3CN
100 V
1000 V
3000 V
Electrospray Ionization
• Can be modified to “nanospray” system with flow
< 1 L/min
• Very sensitive technique, requires less than a
picomole of material
• Strongly affected by salts & detergents
• Positive ion mode measures (M + H)+ (add formic
acid to solvent)
• Negative ion mode measures (M - H)- (add
ammonia to solvent)
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Mass Spectrometer Schematic
Turbo pumps
Diffusion pumps
Rough pumps
Rotary pumps
High Vacuum System
Inlet
Sample Plate
Target
HPLC
GC
Solids probe
Ion
Source
Mass
Analyzer
MALDI
ESI
IonSpray
FAB
LSIMS
EI/CI
TOF
Quadrupole
Ion Trap
Mag. Sector
FTMS
Detector
Microch plate
Electron Mult.
Hybrid Detec.
Data
System
PC’s
UNIX
Mac
Different Types of Mass Analyzers
• Magnetic Sector Analyzer (MSA)
– High resolution, exact mass, original MA
• Quadrupole Analyzer (Q or Q*)
– Low (1 amu) resolution, fast, cheap
• Time-of-Flight Analyzer (TOF)
– No upper m/z limit, high throughput
• Ion Cyclotron Resonance (FT-ICR)
– Highest resolution, exact mass, costly
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MS Mass Accuracy
Type
Mass Accuracy
FT-ICR-MS
0.1 - 1 ppm
Orbitrap
0.5 - 1 ppm
Magnetic Sector
1 - 2 ppm
TOF-MS
3 - 5 ppm
Q-TOF
3 - 5 ppm
Triple Quad
3 - 5 ppm
Linear IonTrap
50-200 ppm
(10 ppm in Ultra-Zoom)
ppm  (
mexp - mcalc
)  1 E 6
mexp
Mass Chromatograms
• Standard “output” from an LC-MS or GC-MS experiment
• X-axis is retention time, Y-axis is signal intensity
• Total Ion Current (TIC) chromatogram is summed intensity
across the entire range of masses being detected at every point
in the analysis
• Base Peak chromatogram (BPC) is like a TIC but displays only the
most intense peak in each spectrum
• Extracted Ion chromatogram (EIC) contains one or more
analytes extracted from the TIC or BPC
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Mass Chromatograms of Biological
Mixtures
Tomato Extract
Arabidopsis Extract
NMR Spectroscopy
Explaining NMR
Principles of NMR
• Measures nuclear magnetism or changes in nuclear
magnetism in a molecule
• NMR spectroscopy measures the absorption of light
(radio waves) due to changes in nuclear spin orientation
• NMR only occurs when a sample is in a strong magnetic
field
• Different nuclei absorb at different energies
(frequencies)
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Protons (and other nucleons) Have
Spin
Spin up
Spin down
Each Spinning Proton is Like a
“Mini-Magnet”
S
N
N
S
Spin up
Spin down
Principles of NMR
N
N
S
S
Low Energy
High Energy
hn
hn
Bigger Magnets are Better
Increasing magnetic field strength
low frequency
high frequency
A Modern NMR Instrument
Radio Wave
Transceiver
NMR Magnet
NMR Magnet Cross-Section
Magnet Legs
An NMR Probe
NMR Sample & Probe Coil
1H
NMR Spectra Exhibit...
• Chemical Shifts (peaks at different frequencies or
ppm values)
• Splitting Patterns (from spin coupling)
• Different Peak Intensities (# 1H)
8.0
Module 1
7.0
6.0
5.0 4.0
3.0 2.0 1.0
0.0
bioinformatics.
Chemical Shifts
• Key to the utility of NMR in chemistry
• Different 1H in different molecules exhibit different
absorption frequencies
• Each compound can be defined by a unique pattern of
chemical shifts (a fingerprint)
• Chemical shifts are mostly affected by electronegativity
of neighbouring atoms, bonds or groups
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Characteristic Chemical Shifts
Assigning Simple NMR Spectra
TMS
Assigning Simple NMR Spectra
NMR Spectra Need “Fixin’”
Before
After
Baseline
correction
Shimming
Water
suppression
Referencing
Phasing
NMR Spectra Need “Fixin’”
• Chemical shift referencing (TMS, DSS)
– Calibrates/normalizes chemical shifts
• Shimming
– Fixes line shape to look Lorentzian
• Phasing
– Fixes line shape to look “absorptive”
• Water suppression/removal
– Removes large water signal
• Baseline correction
– Makes spectrum look flat – not wobbly
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NMR Spectrum of a Biological
Mixture
# Metabolites or Features detected (Log10)
Technology & Sensitivity
Unknowns
4
LC-MS or
DI-MS
3
GC-MS
TOF
2
NMR
1
Knowns
GC-MS
Quad
0
M
mM
M
nM
Sensitivity or LDL
pM
fM
Comparison
NMR (with cold
probe)
GC-MS
DI-MS
Techniques
Metabolites
Water-soluble
(amino acids,
organic acids,
sugars)
mainly watersoluble (some
hydrophobic)
Mainly
hydrophobic
(some watersoluble)
Types of samples
Biofluids, plant,
bacterial,
animal tissue
extracts, Food
Biofluids, plant,
Mainly biofluids
bacterial, animal
tissue extracts, Food
Sample Volume
100 µL (min)
30-50 µL (min)
10 µL
Comparison
NMR
GC-MS
DI-MS
Sample prep time
30 -120
min/20
samples
30 -120 min/20
samples
3-4 h for 96
samples
Run time
20 -90
min/sample
30-60 min/sample
7 min/sample
Data Analysis
30-60 min /
sample
30-60 min / sample
1-2 h for 96
samples
Limit of Detection
~ 5 µM
~ 100 nM
~ 5 nM
No. of metabolites
~ 20 - 50
~20 -50
~ 100-180
Overlapping
Metabolites
10-15
10-15
10-15
Cross-checking
10-30 %
10-30 %
10-30 %
What’s Possible
• NMR-based metabolomics (~50 metabolites
identified/quantified, M sensitivity)
• GC-MS based metabolomics (~70 metabolites
identified/quantified, <M sensitivity)
• DI-MS based metabolomics (160 metabolites
identified/quantified, nM sensitivity)
• LC-MS based metabolomics (300 metabolites
identified/quantified, nM sensitivity)
• Lipidomics (3000 lipids identified and semi-quantified, nM
sensitivity)
• Specialty phytochemical, nutrient, drug and pesticide analysis
(mostly HPLC, nM sensitivity)
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2 Routes to Metabolomics
ppm
7
6
5
4
Quantitative (Targeted)
Methods
3
2
Chemometric (Profiling)
Methods
25
TMAO
hippurate
allantoin creatinine taurine
1
PC2
20
creatinine
15
10
citrate
ANIT
5
hippurate
urea
2-oxoglutarate
water
succinate
fumarate
0
-5
-10
ppm
7
6
5
4
3
2
1
Control
-15
PAP
-20
-25
-30
PC1
-20
-10
0
10
Profiling (Untargeted)
Data Reduction
Data Collection
25
PC2
20
15
10
5
ANIT
0
-5
-10
-15
-20
-25
-30
Sample Prep
Metabolite Identification
Control
PAP
-20
-10
PC1
0
10
Quantitative (Targeted)
Sample Prep
25
PC2
20
Biological Interpretation
15
10
5
ANIT
0
-5
-10
-15
-20
-25
-30
Control
PAP
-20
-10
PC1
0
Data Reduction
Metabolite Identification & Quantification
10
From Spectra to Lists
Table 1 . List of 121 dansyl derivative standards
identified and quantified in a 5
7
6
5
4
3
2
1
-day pooled hu man urine sample
Retention
Time
(min)
Conc. in
Urine
(µM)
Dns -o-phospho -L-serine
Dns -o-phospho -L-tyrosine
0.92
0.95
<D.L. *
<D.L.
Dns -adnosine monophosphate
Dns-o-phosphoethanolamine
Dns-glucosamine
Dns -o-phospho -L-threonine
0.99
1.06
1.06
1.09
Dns -6-dimet hylamine purine
Dns-3-methyl -histidine
(in bold face)
by using fast LC -FTICR MS.
Retention
Time
(min)
Conc. in
Urine
(µM)
Dns-Ile
Dns-3-aminosalicylic acid
6.35
6.44
25
0.5
<D.L.
16
22
<D.L.
Dns-pipecolic acid
Dns-Leu
Dns-cystathionine
Dns-Leu -Pro
6.50
6.54
6.54
6.60
0.5
54
0.3
0.4
1.20
1.22
<D.L.
80
Dns-5-hydroxylysine
Dns-Cystine
6.65
6.73
1.6
160
Dns-taurine
Dns-carnosine
Dns-Arg
Dns-Asn
1.25
1.34
1.53
1.55
834
28
36
133
Dns-N-norleucine
Dns -5-hydroxydopamine
Dns-dimethylamine
Dns-5-HIAA
6.81
7.17
7.33
7.46
0.1
<D.L.
293
18
Dns-hypotaurine
Dns-homocarnosine
1.58
1.61
10
3.9
7.47
7.63
1.9
<D.L.
Dns -guanidine
Dns-Gln
Dns-allantoin
1.62
1.72
1.83
<D.L.
633
3.8
Dns-umbelliferone
Dns -2,3 -diaminoproprionic acid
Dns-L-ornithine
7.70
7.73
7.73
15
51
8.9
Dns-L-citrulline
Dns-1 (or 3 -)-methylhistamine
Dns-adenosine
Dns -methylguanidine
1.87
1.94
2.9
1.9
7.76
7.97
3.3
82
2.06
2.20
2.6
<D.L.
Dns-homocystine
Dns-acetaminophen
Dns-Phe-Phe
Dns-5-methyo xysalicylic acid
8.03
8.04
0.4
2.1
Dns-Ser
Dns-aspartic acid amide
2.24
2.44
511
26
Dns-Lys
Dns -aniline
8.16
8.17
184
<D.L.
Dns-4-hydroxy -proline
Dns-Glu
Dns-Asp
2.56
2.57
2.3
21
Dns-leu -Phe
Dns-His
8.22
8.35
0.3
1550
Dns-Thr
Dns -epinephrine
Dns-ethanolamine
2.60
3.03
3.05
3.11
90
157
<D.L.
471
Dns -4-thialysine
Dns -benzylamine
Dns-1-ephedrine
Dns-tryptamine
8.37
8.38
8.50
8.63
<D.L.
<D.L.
0.6
0.4
Dns-aminoadipic acid
Dns-Gly
Dns-Ala
3.17
3.43
3.88
70
2510
593
Dns -pyrydoxamine
Dns -2-methyl -benzylamine
Dns-5-hydroxytrptophan
8.94
9.24
9.25
<D.L.
<D.L.
0.12
Dns-aminolevulinic acid
Dns-r-amino -butyric acid
3.97
3.98
30
4.6
Dns-1,3 -diaminopropane
Dns-putrescine
9.44
9.60
0.23
0.5
Dns-p-amino -hippuric acid
Dns-5-hydro xymethyluricil
3.98
4.58
4.70
4.75
2.9
1.9
5.5
<D.L.
Dns-1,2 -diaminopropane
Dns-tyrosinamide
9.66
9.79
10.08
10.08
0.1
29
140
0.08
4.79
4.81
1.6
7.2
10.19
10.19
0.4
9.2
4.81
4.91
85
17
Dns-histamine
Dns-3-methoxy -tyr amine
Dns-Tyr
10.28
10.44
321
<D.L.
Compound
ppm
and the corresponding metabolites
Dns-tryptophanamide
Dns -isoguanine
Dns-5-aminopentanoic acid
Dns-sarcosine
Dns-3-amino -isobutyrate
Dns-2-aminobutyric acid
Compound
Dns-4-acetyamidophenol
Dns-procaine
Dns-dopamine
Dns-cadaverine
Dns -cysteamine
From Lists to Pathways
Table 1 . List of 121 dansyl derivative standards
identified and quantified in a 5
and the corresponding metabolites
-day pooled hu man urine sample
Retention
Time
(min)
Conc. in
Urine
(µM)
Dns -o-phospho -L-serine
Dns -o-phospho -L-tyrosine
0.92
0.95
<D.L. *
<D.L.
Dns -adnosine monophosphate
Dns-o-phosphoethanolamine
Dns-glucosamine
Dns -o-phospho -L-threonine
0.99
1.06
1.06
1.09
Dns -6-dimet hylamine purine
Dns-3-methyl -histidine
(in bold face)
by using fast LC -FTICR MS.
Retention
Time
(min)
Conc. in
Urine
(µM)
Dns-Ile
Dns-3-aminosalicylic acid
6.35
6.44
25
0.5
<D.L.
16
22
<D.L.
Dns-pipecolic acid
Dns-Leu
Dns-cystathionine
Dns-Leu -Pro
6.50
6.54
6.54
6.60
0.5
54
0.3
0.4
1.20
1.22
<D.L.
80
Dns-5-hydroxylysine
Dns-Cystine
6.65
6.73
1.6
160
Dns-taurine
Dns-carnosine
Dns-Arg
Dns-Asn
1.25
1.34
1.53
1.55
834
28
36
133
Dns-N-norleucine
Dns -5-hydroxydopamine
Dns-dimethylamine
Dns-5-HIAA
6.81
7.17
7.33
7.46
0.1
<D.L.
293
18
Dns-hypotaurine
Dns-homocarnosine
1.58
1.61
10
3.9
7.47
7.63
1.9
<D.L.
Dns -guanidine
Dns-Gln
Dns-allantoin
1.62
1.72
1.83
<D.L.
633
3.8
Dns-umbelliferone
Dns -2,3 -diaminoproprionic acid
Dns-L-ornithine
7.70
7.73
7.73
15
51
8.9
Dns-L-citrulline
Dns-1 (or 3 -)-methylhistamine
Dns-adenosine
Dns -methylguanidine
1.87
1.94
2.9
1.9
7.76
7.97
3.3
82
2.06
2.20
2.6
<D.L.
Dns-homocystine
Dns-acetaminophen
Dns-Phe-Phe
Dns-5-methyo xysalicylic acid
8.03
8.04
0.4
2.1
Dns-Ser
Dns-aspartic acid amide
2.24
2.44
511
26
Dns-Lys
Dns -aniline
8.16
8.17
184
<D.L.
Dns-4-hydroxy -proline
Dns-Glu
Dns-Asp
2.56
2.57
2.3
21
Dns-leu -Phe
Dns-His
8.22
8.35
0.3
1550
Dns-Thr
Dns -epinephrine
Dns-ethanolamine
2.60
3.03
3.05
3.11
90
157
<D.L.
471
Dns -4-thialysine
Dns -benzylamine
Dns-1-ephedrine
Dns-tryptamine
8.37
8.38
8.50
8.63
<D.L.
<D.L.
0.6
0.4
Dns-aminoadipic acid
Dns-Gly
Dns-Ala
3.17
3.43
3.88
70
2510
593
Dns -pyrydoxamine
Dns -2-methyl -benzylamine
Dns-5-hydroxytrptophan
8.94
9.24
9.25
<D.L.
<D.L.
0.12
Dns-aminolevulinic acid
Dns-r-amino -butyric acid
3.97
3.98
30
4.6
Dns-1,3 -diaminopropane
Dns-putrescine
9.44
9.60
0.23
0.5
Dns-p-amino -hippuric acid
Dns-5-hydro xymethyluricil
3.98
4.58
4.70
4.75
2.9
1.9
5.5
<D.L.
Dns-1,2 -diaminopropane
Dns-tyrosinamide
9.66
9.79
10.08
10.08
0.1
29
140
0.08
4.79
4.81
1.6
7.2
10.19
10.19
0.4
9.2
4.81
4.91
85
17
Dns-histamine
Dns-3-methoxy -tyr amine
Dns-Tyr
10.28
10.44
321
<D.L.
Compound
Dns-tryptophanamide
Dns -isoguanine
Dns-5-aminopentanoic acid
Dns-sarcosine
Dns-3-amino -isobutyrate
Dns-2-aminobutyric acid
Compound
Dns-4-acetyamidophenol
Dns-procaine
Dns-dopamine
Dns-cadaverine
Dns -cysteamine
From Pathways & Lists to Models
Table 1 . List of 121 dansyl derivative standards
identified and quantified in a 5
and the corresponding metabolites
-day pooled hu man urine sample
(in bold face)
by using fast LC -FTICR MS.
Retention
Time
(min)
Conc. in
Urine
(µM)
Retention
Time
(min)
Conc. in
Urine
(µM)
Dns -o-phospho -L-serine
Dns -o-phospho -L-tyrosine
0.92
0.95
<D.L. *
<D.L.
Dns-Ile
Dns-3-aminosalicylic acid
6.35
6.44
25
0.5
Dns -adnosine monophosphate
Dns-o-phosphoethanolamine
Dns-glucosamine
Dns -o-phospho -L-threonine
0.99
1.06
1.06
1.09
<D.L.
16
22
<D.L.
Dns-pipecolic acid
Dns-Leu
Dns-cystathionine
Dns-Leu -Pro
6.50
6.54
6.54
6.60
0.5
54
0.3
0.4
Dns -6-dimet hylamine purine
Dns-3-methyl -histidine
1.20
1.22
<D.L.
80
Dns-5-hydroxylysine
Dns-Cystine
6.65
6.73
1.6
160
Dns-taurine
Dns-carnosine
Dns-Arg
Dns-Asn
1.25
1.34
1.53
1.55
834
28
36
133
Dns-N-norleucine
Dns -5-hydroxydopamine
Dns-dimethylamine
Dns-5-HIAA
6.81
7.17
7.33
7.46
0.1
<D.L.
293
18
Dns-hypotaurine
Dns-homocarnosine
1.58
1.61
10
3.9
1.9
<D.L.
1.62
1.72
1.83
<D.L.
633
3.8
Dns-umbelliferone
Dns -2,3 -diaminoproprionic acid
Dns-L-ornithine
7.47
7.63
Dns -guanidine
Dns-Gln
Dns-allantoin
7.70
7.73
7.73
15
51
8.9
Dns-L-citrulline
Dns-1 (or 3 -)-methylhistamine
Dns-adenosine
Dns -methylguanidine
1.87
1.94
2.9
1.9
7.76
7.97
3.3
82
2.06
2.20
2.6
<D.L.
Dns-homocystine
Dns-acetaminophen
Dns-Phe-Phe
Dns-5-methyo xysalicylic acid
8.03
8.04
0.4
2.1
Dns-Ser
Dns-aspartic acid amide
2.24
2.44
511
26
Dns-Lys
Dns -aniline
8.16
8.17
184
<D.L.
Dns-4-hydroxy -proline
Dns-Glu
Dns-Asp
Compound
Compound
Dns-4-acetyamidophenol
Dns-procaine
2.56
2.57
2.3
21
Dns-leu -Phe
Dns-His
8.22
8.35
0.3
1550
Dns-Thr
Dns -epinephrine
Dns-ethanolamine
2.60
3.03
3.05
3.11
90
157
<D.L.
471
Dns -4-thialysine
Dns -benzylamine
Dns-1-ephedrine
Dns-tryptamine
8.37
8.38
8.50
8.63
<D.L.
<D.L.
0.6
0.4
Dns-aminoadipic acid
Dns-Gly
Dns-Ala
3.17
3.43
3.88
70
2510
593
Dns -pyrydoxamine
Dns -2-methyl -benzylamine
Dns-5-hydroxytrptophan
8.94
9.24
9.25
<D.L.
<D.L.
0.12
Dns-aminolevulinic acid
Dns-r-amino -butyric acid
3.97
3.98
30
4.6
Dns-1,3 -diaminopropane
Dns-putrescine
9.44
9.60
0.23
0.5
Dns-p-amino -hippuric acid
Dns-5-hydro xymethyluricil
3.98
4.58
4.70
4.75
2.9
1.9
5.5
<D.L.
Dns-1,2 -diaminopropane
Dns-tyrosinamide
9.66
9.79
10.08
10.08
0.1
29
140
0.08
4.79
4.81
1.6
7.2
4.81
4.91
85
17
Dns-histamine
Dns-3-methoxy -tyr amine
Dns-Tyr
Dns-tryptophanamide
Dns -isoguanine
Dns-5-aminopentanoic acid
Dns-sarcosine
Dns-3-amino -isobutyrate
Dns-2-aminobutyric acid
Dns-dopamine
Dns-cadaverine
Dns -cysteamine
10.19
10.19
0.4
9.2
10.28
10.44
321
<D.L.
Key Informatics Challenges in
Metabolomics
• Spectra -> Lists
–
–
–
–
–
Data integrity and quality
Data alignment and normalization
Data reduction and classification
Assessment of significance
Metabolite identification/quantification
• Lists -> Pathways
– Pathway mapping and identification
– Biological interpretation
Module 1
bioinformatics.