Metabolomics

Mark Haid

Helmholtz Zentrum München IEG/GAC

München, 2016-10-12

Prof. J. Adamski (Head of GAC)

Dr. Cornelia Prehn (Head of Metabolomics

Platform)

Metabolomics portfolio @GAC

Coming soon: >50 Eicosanoids

Biocrates p150 / p180

(163/186 metabolites) 10 µL plasma/serum (3 µL blood – DBS)

25-50 mg tissue 10 µL urine

Stero17 (17 steroids)

250 µL serum Steroids „in-house“

50 µL plasma/ serum

100 µL plasma/serum 20-50 mg tissue

Bile Acids (12 metabolites)

non-targeted (500-600 metabolites)

150 µL plasma/serum 25-50 mg tissue

150 µL urine

Metformin „in-house“

(cell culture/plasma)

Coming Soon ABSciex Lipidizer Platform

Source: ABSciex

~ 1000 Lipids in a single run (100 µl) Position of fatty acids in lipid can be determined

Which matrices/species? (p150/p180)

● Plasma, serum

● Urine, feces

● Tissue

● Lung lavage

● Atherosclerotic plaques

● Cell culture samples

● Mitochondria

● DBS

Human

Mouse

Rat

Hamster

Sheep

Bovine

Porcine

Zebrafish

Tadpole

Metabolomics • The systematic identification and quantification of all

the metabolic products of a cell, tissue, organ, or organism under varying conditions

• Sum of all products of metabolism of an organism (~104-105) – „small molecules“

• Metabolite levels integrate information from both endogenous (genetic) and exogenous (nutrition, medication, environment) origins.

Applications/aims:

● Characterisation of human diseases via animal models

● Population studies – also for GWAS (Genome-Wide Association Studies)

● early diagnosis of diseases

● Mechanistical studies

● early detection of drug effects/ side effects (development/treatment)

● pathway analysis

● MulitOmics

● Personalised Medicine

GC-MS (gas chromatography-mass spectrometry) Medium throughput (derivatisation), good quantification, highly-standardised, hydrophobic molecules, central metabolism LC-MS (liquid chromatography-mass spectrometry) Broad spectrum of metabolites, good sensitivity, very high throughput, matrix effects NMR (nuclear magnetic resonance) High reproducibility, absolute quantification, less sensitive, medium to high throughput ELISA, RIA (antibody based assays) Very sensitive, cross-reactivity problems, low throughput

Analytical Methods in Metabolomics

Multivariate Data Analysis

- high-dimensional data sets

- Principal Component Analysis (PCA) overview on data set, outlier detection

- (O)PLS-Discriminance Analysis Separation of ≥ 2 groups

- Support Vector Machines non-parametric, can deal with non linear data

- Random Forest Analysis Tree based method (non-parametric)

- Multivariate methods with intrinsic feature selection:

- Lasso

- Elastic Net

- Parameter Optimization:

- Cross-validation

- Bootstrapping

Recommended Websites

http://metabolomicssociety.org/resources/metabolomics-databases

Targeted vs. Non-targeted Metabolomics

Patti, Nature Reviews MolCellBio, 2012

High sensitivity

Correction of matrix effects

Absolute quantification

Good comparability between different study cohorts

11 11

Metabolome coverage: non-targeted Metabolon (Durham, USA)

Targeted vs. Non-targeted Metabolomics

Patti, Nature Reviews MolCellBio, 2012

The systematic identification and quantification of all the metabolic products of a cell, tissue, organ, or organism under varying conditions

Only semi-quantitative, identification can be tedious, comparability

Targeted vs. Non-targeted Metabolomics

Comparison targeted vs- non-targeted Metabolomics

• Twins UK Study (1001 twins)

• Biocrates p150 (160 metabolites)

• Metabolon (488 metabolites)

• overlap: 43 metabolites

• mean correlation coefficient: 0.44

Yet, PLoS one, 2016

Tissue: high-throughput sample preparation

Extraction and quantification pipeline

Extraction solvents

Targeted Metabolomics of Dried Blood Spots

• minimal invasive • easy to perform • low sample volume

• easy shipment, storage, handling

• sample stability • whole blood marker

Workflow human

apply blood to Whatman filter paper (80 µL) – dry for 4 h punch out 3-mm disks AbsoluteIDQTM p180 kit

reproducible application

Zukunft S, Sorgenfrei M, Prehn C, Möller G, Adamski J. Targeted metabolomics of dried blood spot extracts. Chromatographia 76, 1295-1305 (2013)

apply 3 µL blood to directly to 3-mm filter paper discs

Why DBS?

option for mouse

Pre-analytics

• Talk to metabolomics expert BEFORE the experiment (study design, SOPs...)

• very stringent conditions

• Control and mutants have to be of same age & have to be exposed to same

condition

• 15 mice per phenotype & gender (minimum 10 mice) for statistical power needed

• Decay of samples

• Chill samples during work-up (enzymes)

• Storage at -80 °C

• Avoid freeze-thaw cycles

Errors in the pre-analytics are the digits before the decimal point!

Errors in the wet lab analytics are the digits behind the decimal point!

Effect of Anaesthesia and Euthanasia on Metabolome

• Male C57BL/6J mice, age 20 weeks

• n = 8 mice per method

• 6 different methods of anaesthesia/euthanasia

• Cervical dislocation (CD)

• CO2 Overdose (CO2-OD)

• Isoflurane Overdose (Iso-OD)

• CO2

• Isoflurane Continuous (Iso-Cont)

• Ketamine (Ket)

• Pentobarbital (Pent)

• Collection of all tissues was complete within 3 min

• Target- and non-targeted Metabolomics

Overmyer, PLoS One, 2015

Effect of Anaesthesia and Euthanasia on Metabolome – Non-targeted Metabolomics

Overmyer, PLoS One, 2015

• Anaesthesia methods similar

• CO2 and Isoflurane-OD similar

• Clustering is tissue specific

• Ketamine higher 95% CI

red = CD green = CO2 light blue = Iso-OD dark blue = Iso-Cont purple = Ketamine orange = Pentobarbital

Effect of Anaesthesia and Euthanasia on Metabolome – Non-targeted Metabolomics

Overmyer, PLoS One, 2015

• PLS-DA-VIP

• metabolites with large contribution

on class separation

• heterogeneous for each tissue

• no clear tissue specific trend

Effect of Anaesthesia and Euthanasia on Metabolome – Targeted Metabolomics

• 112 metabolites

• peak areas compared to cervical dislocation

• clear distinction between euthanasia &

anaesthesia

• In euthanized mice:

• Glycolysis: ↑ switch to anaerobic glycolysis (lactate)

• TCA cycle: ↓ except ↑ Succinate & AcCoA

• Nucleotides: ↓ heart & liver

• Nucleosides: ↑ breakdown of nucleotides

Lactate

blue = lower yellow = higher

Response of metabolome to cease of

blood circulation is rapid (< 1min)!

always same preparation sequence!

Collect organs under anaesthesia!

Short-term Stability of Metabolites

Anton, PLoS One, 2015 Breier, PLoS One, 2014

Kamlage, Clin. Chem., 2014

• Variance between person is larger that influence of storage condition

• Samples should be chilled on ice as soon as possible

• Phospholipase A2, COX2, Proteolysis

Long-term Stability of Metabolites at -80 °C

Haid et al., in preparation

Pooled plasma sample repeatedly measured over 5 years

~ 10 % change of metabolite concentrations after 5 years at -80 °C

Interindividual Variation of Metabolite Concentrations n the Context of Challenges and Sample Types

Krug et al., FASEB, 2012

Challenges:

• 24 h Fasting

• Standard Liquid Diet (SLD)

• Oral Glucose Tolerance Test (OGTT)

• Physical Activity Test (PAT)

• Oral Lipid Tolerance Test (OLTT)

• Cold Stress (STRESS)

Individuals react differently to challenges, but metabolite profile returns to stable levels

• 40 % (58 %) of the individuals could uniquely be identified based on metabotype conservation index after 7 years!

• 95 % of individuals were among 30 % ranks

Long-term Stability of Metabolite Concentrations of Human Plasma Samples

Yousri et al., Metabolomics, 2014

Metabotypes:

• Conservation index=1 52 % of population

• Conservation index [0.83,1] 43 % of population

• Conservation index [0, 0.83] 5 % of population

Gender Age BMI

Circle size = variance

Summary

• targeted metabolomics: absolute quantification of a selected set of metabolites

• non-targeted metabolomics: hypothesis-free, fold-changes

• careful study design (talk to people with experience with metabolomics analyses)

• garbage in garbage out

• organ preparation

• be rapid, always prepare in the same organ sequence

• anaesthesia methods recommended

• snap freezing of organs!

• sample quality:

• keep samples on ice

• sample storage at -80°C or liquid nitrogen recommended

• avoid freeze-thaw cycles

Acknowledgements Genome Analyis Center (HMGU)

• Prof. Dr. Jerzy Adamski

• Dr. Cornelia Prehn

• Dr. Anna Artati

• Caroline Muschet

• Katharina Faschinger

• Maria Kugler

• Andrea Nefzger

• Silke Becker

• Dr. Torben Friedrich (†)

Institute of Bioinformatics & Systems Biology (HMGU)

• Dr. Gabi Kastenmüller

• Dr. Werner Römisch-Margl

Institute of Computational Biology (HMGU)

• Dr. Jan Krumsiek

Research Unit Molecular Biology (HMGU)

• Dr. Christian Gieger

• Dr. Harald Grallert

• Dr. Rui Wang-Sattler

• Dr. Simone Wahl

• Dr. Michaela Breier

Weill Cornell Medical College (Quatar)

• Prof. Dr. Karsten Suhre

• Noha Yousri

• Dr. Ana Halama

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