Talk presented at COMBIO in 2007 in Sydney.

1. Developing standards for
metabonomics as a clinical tool.
Agnieszka M. Lichanska, Shaffinaz Abd Rahman
and Horst J. Schirra
School of Dentistry and IMB, University of Queensland, Australia

2. Introduction

3. Genomics and proteomics tells you what
might happen, but metabolomics tells you
what actually did happen.
- Bill Lasley, University of California, Davis

4. Genomics
Transcriptomics
Proteomics
Metabolomics
Metabonomics
DNA
RNA
Protein
Metabolites
25,000 genes
100,000 mRNAs
1,000,000 proteins
2,500 metabolites
Metabonomics in context

5. Introduction
Metabonomics
•'The quantitative measurement of the dynamic multiparametric
metabolic response of living systems to pathophysiological stimuli or
genetic modification' (Nicholson et. al.)
•Use of statistical methods to detect changes in metabolites over
time or between groups.
Metabolomics
•The characterisation of all metabolites in a sample/organism.
… a lot of people use both terms interchangeably…

6. Metabolic changes
Genetic changes
(mutations)
Drugs, diet
Changes in metabolite
concentration
Blood Urine other biofluids
NMR, MS
spectra
Disease
Identification of
individual metabolites
Detailed analysis
Metabolic changes and their analysis
Metabolite
Database

7. Methods
• Bruker 500MHz spectrometer with sample
changer
• Urine from fasted male mice
– WT controls
– Mutant mice
– Age 2-12 months
• Samples frozen upon collection
• 1M Phosphate buffer
• TSP, D2O

8. Nuclear Magnetic Resonance (NMR) - based
metabonomics
• Advantages:
– Fully quantitative
– Non-destructive
– Minimal sample preparation
– High throughput
• What can be analyzed?
– Analysis of all types of biofluids (urine, plasma, saliva,
cerebrospinal fluid, sperm, synovial fluid, amniotic fluid)
– Solid samples (biopsies of organs and cell cultures)

9. Mouse studies - physiology of growth
hormone
WT 569 391 GHR -/-
Rowland, Lichanska et al 2005, MCB 25:66-77
Model - GHR KI mice

10. Mouse studies - physiology of growth
hormone
Schirra et al 2007, under review

11. Mouse studies - physiology of growth
hormone
Schirra et al 2007, under review

12. Clinical Applications

13. Applications
• Health management
– Non-invasive monitoring of asthma in children - University Hospital
Padua
• Drug intervention - evaluation of drug treatment
• Risk management - exposure to toxic substances
• Lifestyle/diet studies – Nestle (age, gender, smoking, alcohol,
menopause, sport, BMI)
• Nutritional applications - Nestle studies (chocolate, coffee)
• Diagnostics
– CARDIUM project - Varese Hospital
– Tumor markers - epithelial ovarian cancer (serum)
– Inborn metabolic disorders
– Meningitis diagnosis (cerebrospinal fluid)

14. Diagnosis of inborn errors of metabolism
Disorders of:
• carbohydrate metabolism
– E.g. glycogen storage disease
• amino acid metabolism
– E.g. phenylketonuria
• organic acid metabolism
- E.g. alcaptonuria
• fatty acid oxidation and
mitochondrial metabolism
• porphyrin metabolism
• purine or pyrimidine metabolism
– E.g. Lesch-Nyhan syndrome
• steroid metabolism
– E.g. congenital adrenal hyperplasia
• mitochondrial function
• peroxisomal function
– Zellweger syndrome
• Lysosomal storage disorders
– Gaucher's disease

15. Sample preparation study

16. Methods
• Bruker 500MHz spectrometer with sample
changer
• Urine from a healthy volunteer
– 1st urine of the day
– Collected midstream
• 1M Phosphate buffer
• TSP, D2O
• Na Azide
• Storage conditions variable

17. Study design
Untreated Centrifuged
First morning
urine
Room
Temp.
on ice / -20°C
1% Sodium Azide Ultra-Filtrated
(MWCO 10 kDa)
The samples were stored either at -20o
C or at RT and were measured on
day 0, 2 and 9.
Sterile filtration
0.2µm

18. Day 0
1% Sodium Azide
Ultra-Filtrated Centrifuged
Untreated
Blue Spectra – Room Temperature
Red Spectra – In Ice
• Spectra are identical, irrespective of treatments
• Ultra-filtrated samples had addition glycerol signals
Glycerol

19. Day 2
-20°C Untreated
RT Untreated
-20°C 1% Sodium Azide
RT 1% Sodium Azide
-20°C Centrifuged
RT Centrifuged Formate
Formate
Formate
Acetate
Ethanol
Acetate
Acetate
Ethanol
Ethanol

20. Comparison between treatments days 0-9
Day 0
Day 2
Day 9
Day 9
Day 2
Day 0
Centrifuged
Formate
Formate
Formate
Formate
Ethanol
Ethanol
Acetate
Acetate
Acetate
Acetate
Untreated

21. Sample analysis
SDS-PAGE
SF1
ULF1
ULF2
untreated2
ULF3
ULF4
SF1
SF2
untreated1
SF2
Urine sample
SDS-PAGE Microbiological
testing:
1. Microscopy
2. Growth on
basal media
(agar plates)
Stain with
Coomasie
Scoring for growth
on plates and
presence/absence of
yeast or bacteria by
microscopy

22. Summary
• Storing samples at RT caused them to have ageing effects
formed from microbial contamination in the samples
• Sterile filtration samples kept at -20 °C were the only
treatment that showed consistently no presence of those
metabolites
• Optimal method:
1. Sterile filter samples
2. add 1% sodium azide
3. Measure at Day 0
4. Store at -20°C
• Ethanol, acetate and formate signals should be excluded in
all statistical study as it was proven that elevated
concentrations of these metabolites were due to external
ageing reactions.

23. Metabolomics standards initiative (MSI,
http://msi-workgroups.sourceforge.net/ )
• Sample information
– Collection details (date, place, method, frequency)
– Extracts from tissues or solid state analysis - processing details
– Patient information (diet, drugs, infections, chronic diseases, etc)
– Volume collected, pH, osmolarity,
– Sample storage (temperature, additives)
– Sample processing details
• NMR/MS data acquisition
– QC procedures, used of internal standards,
– Instrument performance and maintenance logs has to be documented
– Acquisition protocol details - SOP establishment
– Instrument specifications
• Data analysis
– All data manipulations should be specified, MSI has a format for reporting
analysis
• Data format
– Exchangeable file format
– Raw data access for future re-analysis or reference

24. FDA and metabonomic studies
• Metabolomics data is currently being evaluated by the
voluntary genomics data submission (VGDS) group.
• Such data is likely to be included in FDA submissions to
support:
– A mechanism of a drug
– Metabolite/s are used biomarkers in evaluations
• Metabolic markers are seen as most relevant for
understanding the mechanism of action, defining the
safety of a compound, and for monitoring clinical
efficacy.
• A metabolomic report should include a number of
information mentioned before. The two important issues
are the selection of controls and the analysis methods
used to identify the biomarker/s

25. Acknowledgments
IMB
Dr. Horst J. Schirra
Cameron Anderson
Linda Kerr
Sheryl Maher
Jenny Rowland
Prof. Mike J. Waters
Prof. David J. Craik
Mater Children’s
Hospital
Prof. Francis Bowling
Teresa Munce
Dr. Gary Leong
Tony Huynh
School of Dentistry/IMB
Shaffinaz Abd Rahman
University of Ohio
Prof. John Kopchik
Queensland Smart
State Fellowship