Metabolomics
PCB 5530
Antje Thamm & Tom Niehaus
Fall 2015
Learning Outcomes
Day 1 (Antje Thamm)
• Lecture
- Learn the basics of metabolomics
- Understand the limitations of metabolomics
- Things to consider when using metabolomics for your own research
Day 2 (Tom Niehaus)
• Activity 1: Identifying an unknown peak
• Activity 2: Analyzing a metabolomics dataset
Definitions and Background
Metabolome = the collection of all metabolites in a sample
• All low molecular weight (< 2000
Da) organic molecules in a sample
such as a leaf, fruit, seedling, serum,
urine, etc.
Sugars
Nucleosides
Organic acids
Ketones
Aldehydes
Amines
Amino acids
Small peptides
Fatty acids
Isoprenoids
Phenols
Alkaloids
Drugs and pesticides
Definitions and Background
Metabolomics = high-throughput analysis of metabolites
Metabolomics is the simultaneous measurement of the levels of a large
number of cellular metabolites (typically several hundred). Many of these
are not identified (i.e. are just peaks in a profile).
Not
hypothesis
driven
snapshot
Definitions and Background
Definitions and Background
Scope
Metabolomics
-measure many compounds
- relative measurements
Metabolic profiling
-measure a set of
related compounds
(e.g. phosphate esters)
Targeted analysis
-measure a specific compound
-absolute quantification is possible
Accuracy
Definitions and Background
History and Development
• Metabolic profiling is not new. Profiling for clinical detection of human disease using
urine samples has been carried out for Centuries.
This urine wheel was
published in 1506 by
Ullrich Pinder, in his book
Epiphanie Medicorum.
The wheel describes the
possible colors, smells
and tastes of urine, and
uses them to diagnose
disease.
Nicholson, J. K. & Lindon, J. C. Nature
455, 1054–1056 (2008).
Definitions and Background
History and Development
• Advanced chromatographic separation techniques were developed in the late
1960’s.
• Linus Pauling published “Quantitative Analysis of Urine Vapor and Breath by GasLiquid Partition Chromatography” in 1971
• Chuck Sweeley at MSU helped pioneer metabolic profiling using gas chromatography/
mass spectrometry (GC-MS)
• Plant metabolic biochemists (e.g. Lothar Willmitzer) were among other early
leaders in the field.
• Metabolomics is expanding to catch up with other multiparallel analytical
techniques (transcriptomics, proteomics) but remains less developed and less
accessible.
Definitions and Background
Plant Metabolome Size
• It is estimated that all plant species combined contain 90,000 - 200,000
compounds.
• Each individual plant species contains about 5,000 – 30,000 compounds.
e.g. ~ 5,000 in Arabidopsis
The plant metabolome is much larger than that of yeast, where there are far
fewer metabolites than genes or proteins (<600 metabolites vs. 6000 genes).
The size of the plant metabolome reflects the vast array of plant secondary
compounds. This makes metabolic profiling in plants much harder than in other
organisms.
Definitions and Background
The Power of Metabolomics
Silent Knockout Mutations.
• ~90% of Arabidopsis knockout mutations are silent – i.e. have no visible
phenotype
• no direct clues to gene function. (The search for some sort of visible
phenotype therefore often becomes desperate.)
• Similar in yeast, where up to 85% of genes are non-essential
• Even if there is no change in growth rate (visible phenotype; the sum of all
fluxes), pool sizes of metabolites may have changed  Can be measured by
metabolomics
Definitions and Background
The Power of Metabolomics
Example: Chloroplast 2010 project
(phenotype analysis of knockouts of
Arabidopsis genes encoding predicted
chloroplast proteins):
Various knockouts
showed normal
growth and color but
highly abnormal free
amino acid profiles,
e.g. At1g50770
(‘Aminotransferaselike’)
Definitions and Background
Limitations of metabolomics
• High biological variance in metabolite levels (i.e., high variation between
genetically identical plants grown in the same conditions)
• Unlike nucleic acids and proteins, metabolites have a vast range of chemical
structures and properties. Their molecular weights span two orders of magnitude
(20–2000 Da). Therefore no single extraction or analysis method works for all
metabolites. (Unlike DNA sequencing, microarrays, MS analysis of proteins – all
are general methods.)
• The concentrations of various metabolites can vary dramatically from mM to pM
• Metabolite pools can be very dynamic – may change within seconds
• Some metabolites are labile and won’t survive extraction and analysis
• Issues with chromatography, detection, and data analysis
• one gene can influence many metabolites; the concentration of one metabolite
can regulate expression of many genes
Metabolomics
Steps in metabolomics
sample preparation
sample extraction
chromatography
data analysis
detection
Sample Preparation
Growth/Sample Size
• Grow organisms (e.g. plants or bacteria) under identical conditions
• Randomize the treatment groups
(Make sure the effects you measure are due to the variable being tested,
not variables in experiment set up)
• number of replicates… depends on what you want to find
- Large differences = small replication needed
- Small differences = large replication needed
• In general, six replicates for each treatment are needed
(due to high biological variability)
Sample Preparation
Sample collection
• Uniform sample sizes (e.g. hole punches in leaves)
• Be consistent
- similar tissue
- time of day
• Quickly freeze sample in liquid nitrogen, store
samples at -80°C
• Fast-harvesting method for bacteria (~30 sec)
Sample Extraction
Choosing an extraction method
• No universal extraction method exists – always compromise
• Some solvents may degrade certain compounds
• It’s good to have some idea of what metabolites you want to extract
Chromatography
Introduction
• Invented in 1900 by Mikhail Tsvet (used to separate plant pigments)
• There are several types of chromatography, but all consist of a
stationary phase and a mobile phase. Compounds are separated
based on differential partitioning between the two phases.
• Types include:
- TLC (thin-layer chromatography)
- GC (gas chromatography)
Y
- LC (liquid chromatography)
GC and LC are routinely used in
metabolomics
Chromatography
Gas Chromatography
• GC = ‘good chromatography’
• optimized over several
decades, high reproducibility
• Identification of compounds
based on ‘conventional GC’
method
• Suitable for
• compounds with
sufficient volatility
• Thermostable compounds
Limitations:
- high temperatures can destroy labile compounds
- polar compounds cannot ‘fly’ on GC columns and must first be derivatized
by blocking reactive groups
Chromatography
Liquid Chromatography
• LC = ‘Lousy chromatography’
• fairly new, recent advances
• thousands of columns available
- normal phase
-ion exchange
- reverse phase
-HILIC
• infinite solvent systems possible
• low reproducibility
Advantages:
- compound can be collected after separation
- derivatization not necessary
- a separation protocol can be optimized for nearly any compound