Metabolomics 2 Flashcards
Metabolomics Technologies
NMR
- mg/mL - µg/mL
- organic acids
- lipids
- amino acids
- nucleotides
Mass Spectrometry (LC/MS, GC/MS, CE/MS)
- µg/mL
- ng/mL
- nucleotides
- steroids
- eicosanoids
- neurotransmitters
CUSTOM
- ng/mL
- pg/mL
- neurotransmitters
- peptides
- trace elements
Mass Spectrometry
-> Advantages and Disadvantages
Advantages
* Highly sensitive (5 nM)
* Structural elucidation of unknown compounds (accurate mass, fragments)
* Large number of metabolites detected and quantified
* Automation requires massive quality control
* HT, 100 samples / day
Disadvantages
* Many different variants, data from different source not comparable
* Lack of standardisation
* Not as robust as NMR
* High level of QC needed for quantification
NMR
-> Advantages and Disadvantages
Advantages
* Simple sample preparation
* Robust automation, HT (50 samples a day)
* Highly reproducible
* Truly quantitative (reference method for NIST standards)
* Can detect any metabolites above 5 μM
* Structure elucidation of unknown compounds
* Lipids: Total trigycerides, cholesterol, phosphatidylcholines, sphingomyelins
* Inblood: HDL, LDL, VLDL subclasses
Disadvantages
* Limited sensitivity (5μM), limited number of metabolites (50-200)
* Complex data deconvolution
Technology and sensitivity
-> NMR
Metabolites
1. Small water soluble molecules
2. Lipoproteins
Sample type
Biofluids (urine, blood, CSF), tissue extracts, plant extracts
Sample volume
5 mm: 600 µL
3 mm: 180 µL
1.7 mm: 35 µL
Run-time
10-30 min
Detection limit
5 µM
No. Metabolites
Blood: 40, 100
lipoproteins, glycoproteins
Urine: ca 100
Technology and sensitivity
-> GC-MS
Metabolites
- mainly water-soluble molecules
Sample Type
- biofluids, tissue extracts, plant extracts, bacterial, food
Sample volume
- 30-50 µL
Run-time
- 30-60 min
Detection limit
- 100 nM
No. metabolites
- 150 - 200 from any matrix requires sample prep
Technology and sensitivity
-> LC-MS
Metabolites
- biofluids, cell extracts
Sample Type
- mainly biofluids
Sample volume
- 10 µL
Run-time
- 1-2 h for 96 samples
Detection limit
- 5 nM
No. metabolites
- 2000-3000
- 300-500 quantifiable
- Lipidomics: >3000
-> Software: XCMS Online
Literature-assisted identification
MS data -> feature annotation -> MS filtering -> AI-NLP search -> MS2 identification of short list -> cognitive analysis of metabolomics
Biological pathway disease activity
MS data -> metabolites -> pathways -> AI gene search -> role in disease -> cognitive analysis of metabolomics
Metabolite prioritization
MS data -> dysregulated features -> AI network search -> categorize knowns -> select unknowns -> test unknowns
Metabolome-level Disease comparison
AI search diseases and compounds -> metabolites -> compare diseases 1 and 2 -> not shared = biomarker -> shared = drug target -> MS validation
Metabolome-level disease comparisons for drug repurposing
Iterative filtering of literature-based chemical-disease similarity network for CKD and AMI. Red dot: Vitamine D.
Drugs predicted for the diseases, with vitamin D as the top-ranked drug compound for CKD and ranked 70th for AMI.
Categorization of shared metabolites by types of drug, endogenous metabolites, hormones and well-known actors.
MetaboAnalyst
A unified and flexible workflow that enables end-to-end analysis of NMR and LC-MS metabolomics data.
Raw LC/MS data (LC-MS spectra) -> data processing (peak picking), (peak annotation) -> data processing (data cleaning) -> data analysis (statistical analysis) (knowledge based analysis)
What does NMR observe?
- The NMR phenomenon is based of a property of the nucleus of some atoms termed the spin
- Spins behave somehow like positively charged particles rotating in a magnetic field
- The rotation in the magnetic field induces a magnetic moment, as a consequence particles align in the magnetic field
- The two possible orientations of rotation lead to two energy states related to alignment with or against the outside magnetic field
- Most NMR applications use spin-1/2 nuclei with exactly two energy states
1H -> Net spin: 1/2 -> gamma/MHzT-1 42.58 -> Abundance/% 99.98 %
15N -> Net spin: 1/2 -> gamma/MHzT-1 4.31 -> Abundance/% 0.37
13C -> Net spin: 1/2 -> gamma/MHzT-1 10.71 -> Abundance/% 1.108
The NMR phenomenon
Spinning charge -> a magnetic field.
-> magnetic moment (μ).
External magnetic field (B0)
-> two spin state, +1/2 and -1/2.
+1/2 state, lower energy, aligned with the external field
-1/2 state, higher energy, opposed to the external field.
Energy Difference between spin states is dependent on the external magnetic field strength.
The Resonance Condition
The energy of the spin depends on its state: E = μzB0 = γħmIB0
Two possible states for I = 1/2 nuclei: E1/2 = 1⁄2μħB0. E1/2 = -1⁄2γħB0
Energy difference: ΔE = γħB0
Resonance condition: ω0 =γB0
Larmor Frequency ω0 ⇔ precession frequency of the spins about the axis of the static magnetic Field B0
classical:
B0 causes a torque on the magnetic moment -> Larmor precession
The RF probe
-> contains several coils for different nuclei
-> probe must be tuned like a radio by adjusting the eigenfrequency in a capacitor parallel to the coil
Phase sensitive detection
The sign of the signal can only be determined if a phase sensitive FID is available!
NMR spectra: Relaxation
Longitudinal relaxation T1 = spin lattice relaxation = relaxation of z-magnetisation
Transverse relaxation T2 = spin spin relaxation = relaxation of xy-magnetisation proportional to line width
S = ∑ exp(iωit) exp(t/T2)
T2 = signal decay
The NMR Spectrum: Chemical Shifts
The magnetic field induces magnetisations in the electron cloud surrounding the nucleus
=> Shielding, i.e. the magnetic field at the site of the nucleus is influenced by the electron density surrounding the nucleus
=> a higher magnetic field is required to meet the resonance condition
Blocal=B0(1-s)
s = shielding constant
The ppm scale = 𝛿 = (𝜈 − 𝜈ref)/v0
Field independent
=> same values of δ for spectrometers of different field strengths
The NMR Spectrum: Chemical Shifts
Depending on their chemical environment, protons in a molecule are shielded by different amounts.
Sauerstoff an ein Kohlenstoff gebunden = more shielded, absorb at a higher field
Sauerstoff an ein Wasserstoff gebunden = less shielded, absorbs at a lower field
Chemical Shift reference
TMS = Tetramethylsilane
TMSP = Trimethylsilylpropanoic acid
- TMS or TMSP is added to the sample
- Since silicon is less electronegative than carbon, TMS protons are highly shielded. Signal defined as zero.
- Organic protons absorb downfield (to the left) of the TMS signal.
The NMR Spectrum: Chemical Shifts
- NMR can distinguish spin-1/2 atoms in molecules based on their resonance frequency
- NMR spectroscopists called this the chemical shift
- The chemical shift changes as a consequence of the surrounding electron density which is directly related
to the chemicals bonds - The chemical shift is therefore highly sensitive to neighboring atoms (shiedling and deshielding) and to the
type of chemical bonds (single, double, triple bond, aromatic structures).
The NMR Spectrum: Signal Intensity
- The signal intensity is proportional to the number of spins
- I.e.: Proton spectrum of CH3 has 3 x intensity of CH
The NMR Spectrum: Spin-spin coupling
Nucleus A causes a weak magnetic polarisation of the bonding electrons, transmitted through overlapping orbitals to nucleus X.
=> local magnetic field for X varies
Two equally probable states => lines have same intensity
Energy of coupling is field independent => coupling constant is field independent
The NMR Spectrum: Spin-spin interactions
N+1 rule:
If a signal is split by N equivalent protons, it is split into N + 1 peaks.
Values of coupling constants
- free rotation = 7 Hz
- cis = 10 Hz
- trans = 15 Hz
- geminal = 2 Hz
- ortho = 8 Hz
- meta = 2 Hz
- allylic = 6 Hz
Wüthrich’s Approach
COSY = connections through bonds
cross peaks connect pairs of spins
TOCSY = connections through bonds cross peaks connect series of covalently linked spins
NOESY = connections through space < 5Å
Typical types of 1D-NMR spectra used in metabolomics
- NOESY-1D:
- 1D spectrum with optimal water suppression
- CPMG
- 1D spectrum with removal of large molecules
- Diffusion-edited
- 1D spectrum with removal of small molecules
- J-resolved
- 2D spectrum with couplings in 2nd dimension
- After processing: 1D without couplings
JRED: J-resolved spectra tilted
NMR: Structural information
- each compound can have one or several chemical groups or chemical shifts (location on the X axis)
- for example butyric acid has 3 chemical shifts
- interactions with neighboring protons result in the splitting of NMR peaks
Multiplicity = number of neighbors +1 - the peak intensity distribution follows the pattern of numbers in Pascal’s triangle
Metabolite indentification: TOCSY of a cell lysate
Overlay of reconstructions of 1H−1H-TOCSY spectra from databases (orange) with the experimental 1H−1H TOCSY spectrum of E. coli cell lysate (black). (A) The reconstruction of the TOCSY spectrum (orange) is based on spin-system information from the 1H(13C)-TOCCATA database.
HSQC-TOCSY
HSQC-TOCSY resolves overlap which can make TOCSYs difficult to interpret.
TOCSY cross-peaks are resolved into the 13C dimension which allows much easier assignment.
SUMMIT MS/NMR
Structure of Unknown Metabolomic Mixture components by MS/NMR
* High-resolution MS yields the unique molecular formulas of the metabolites present in the lysate.
* From the total structural manifold belonging to these masses, the 2D 13C-1H HSQC spectrum is predicted for each structure.
* The 2D 13C-1H HSQC spectrum of the lysate is deconvoluted into chemical shifts of each metabolite by combining information from 2D NMR experiments.
* Comparison of the experimental 13C-1H HSQC chemical shifts of each metabolite with the predicted 13C-1H HSQC spectra for each of the manifold structures allows the unique identification of the metabolites
MetaboAnalyst
DATA INPUT
- compound name list
- metabolite concentrations
- concentration/peak table, spectra bins
- MS/NMR peak list
DATA PROCESSING (PROT 1)
Name mapping -> integrity check -> peak alignment
- data editor
- image options
- data normalization and transformation
- missing value estimation
- data filtering
- computing ratios
FUNCTIONAL MODULES
- exploratory statistical analysis (Statistical analysis, biomarker analysis, power analysis, time-series/two factor analysis)
- functional enrichment analysis (enrichment analysis, pathway analysis, MS peaks to pathways)
- data integration and systems biology (joint pathway analysis, biomarker meta-analysis, network explorer)
MetaboAnalyst
-> Outlier detection using heat map visualization
Outlier detection using heatmap visualization:
Samples are in columns and features are in rows.
The colors vary from deep blue to dark brown to indicate
data values that change from very low (cold) to extremely high (hot).
Note that most data points from Sample P080 exhibit very high values.
NMR metabolites of blood
Bestandteile in absteigender Größe
- VLDL (very low density lipoprotein) -> diffundieren am schlechtesten
- IDL (intermediate density lipoprotein)
- LDL (low density lipoprotein
- HDL (high density lipoprotein)
-> Cholesterol
-> triglyceride
LMWM = low molecular weight molecules
NMR can detect lipoprotein associated molecules
Lipoprotein transport system
- Initial transport of dietary fats
- Secondary transport of processed cholesterol particles for steroid hormone and membran synthesis
- Processing of free fatty acids
-CH2 peak nach links verschoben und am höchsten, da es davon sehr viel gibt
- CH3 peak weiter nach rechts verschoben
