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Gas Chromatography-Mass Spectrometry
Dr Erica ZarateAuckland Science Analytical Services - Mass Spectrometry
12 June 2015
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Gas chromatography -Mass Spectrometry
• Robust• More reproducible than LC-MS• Can be fully automated
– high throughput• Cheaper than other mass spec
techniques – $22 per sample if you do
prep and analysis (we provide training)
– $42/sample if we do it for you
– Full pricing on iLabImage: Gerstel
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GC-MS available
Agilent
Thermo
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• Samples are carried in a gas, not a liquid– Helium, hydrogen, nitrogen, argon, or a combination of these
• Compounds are carried and separated in a column– Typically capillary and 30– 100m for metabolomics work
• Separation is achieved by:– column heating
– sample interaction with the stationery phase inside the column
– Many different columns for different applications
How it works
~ 1 hour per
sample
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Elution and Ionisation
• Compounds arrive separated at the end of the column• They are ionised by electron bombardment and fragment• Fragments are conveyed to detector electromagnetically• The detector amplifies the fragment signal
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Fragmentation pattern
Chromatogram
Spectrum
Identification
Sample
Library
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Sample Introduction
• Samples must be injected VOLATILE– They might already be volatile (eg: essential oils)
– If not, they can be made volatile (extraction into volatile solvent, derivatisation, pyrolysis).
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• Humans: Plasma, Serum, Urine, Saliva, Sweat, Mucus, Lymph, Milk, Hair, Faeces, Tissue, Amniotic fluid
Extraction
• Marine animals: sea urchins, sea cucumbers, corals, mussels
Anything you can think of we can probably develop an extraction method for.
• Sample size limitations:− 300uL liquids− 200mg fresh tissue
Samples can be:• Liquid• Solid• Swab samples
• Honey, Yeast, Bacteria, Wine, Juices, Fungi, Growth Media, Fruits and Veggies, Feathers, Fish oil
Examples
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Metabolomics methods
• Screening methods (discovery – hypothesis generation)
− quick
− provide relative abundance
− only trends can be compared with published literature
− good for finding possible biomarkers
− Show response to treatment (eg:mode of action – new drugs)
− Eg. MCF and TMS methods
• Targeted methods (hypothesis testing)− take time
− cost more
− provide absolute concentrations
− data easily compared with published literature
− required for validating biomarkers
− Eg: our Q-FAMEs method, isotopically labelled internal standards
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Derivatisation
• Trimethylsilylation– Good universal method– Most derivatives in NIST library– But derivatives not stable
• Methylchloroformate derivatisation– Good for amino acids and fatty acids– But several derivatives formed– Limited to in-house library– Stable derivatives
• Direct transesterification– Fast– Good for fatty acids– Stable derivatives
Derivatisation is a chemical reaction that makes non-volatile compounds volatile
TMS
MCF
QFAMEs
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What compounds can be detected?
• GC-MS is best for small molecules: ie: 0 - 800 amu
• We have in-house mass spectral libraries (reference standards)
• We can screen for unknowns using the NIST mass spectral library (>300,000 compounds)
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10-Heptadecenoic acid 3-Hydroxypropionic acid beta-Citryl-L-glutamic acid Glutamine Methionine Putrescine
10-Pentadecenoic acid3-Methyl-2-oxopentanoic acid beta-Methylamino-alanine Glutaric acid Myristic acid Pyroglutamic acid
11,14,17-Eicosatrienoic acid 3-Oxoadipic acid Butylated hydroxytoluene Glutathione Myristoleic acid Pyruvic acid
11,14-Eicosadienoic 4-Aminobenzoic acidbishomo-gamma-Linolenic acid Glyceric acid N-Acetylcysteine Quinic acid
13,16-Docosadienoic acid4-Aminobutyric acid (GABA) Caffeine Glycerol N-Acetylglutamic acid S-Adenosylhomocysteine
1-Aminocyclopropane-1-carboxylic acid 4-Hydroxycinnamic acid cis-4-Hydroxyproline Glycine NADP_NADPH S-Adenosylmethionine
1-Phenylethanol4-Hydroxyphenylacetic acid cis-Aconitic acid Glyoxylic acid N-alpha-Acetyllysine Salicylic acid
2,3-Butanediol 4-Hydroxyphenylethanol cis-Vaccenic acid Gondoic acid Nervonic acid Sebacic acid
2,4-Diaminobutyric acid4-Methyl-2-oxopentanoic acid Citraconic acid Heneicosanoic acid Nicotinamide Serine
2,6-Diaminopimelic acid 5-Hydroxy-L-lysine Citramalic acid Heptadecane Nicotinic acid Sinapic acid
2-Aminoadipic acid5-Hydroxymethyl-2-furaldehyde Citric acid Hexanoic acid Nonacosane Stearic acid
2-Aminophenylacetic acid 5-Methyltryptophan Creatinine Hippuric acid Nonadecanoic acid Suberic acid
2-Hydroxybutyric acid5-Oxotetrahydrofuran-2-carboxylic acid Cystathionine Histidine Norvaline Succinic acid
2-Hydroxycinnamic acid 9-Heptadecenoic acid Cysteine Homocysteine O-Acetylserine Syringic acid2-Hydroxyisobutyric acid Adipic acid Dibutyl phthalate Indole-3-butyric acid Octanoic acid Tartaric acid2-Isopropylmalic acid Adrenic acid Decanoic acid Isocitric acid Oleic acid Thiamine2-Methyloctadecanoic acid Alanine Docosahexaenoic acid Isoleucine Ornithine Threonine2-Oxoadipic acid alpha-Linolenic acid Dodecane Itaconic acid Oxalic acid trans-4-Hydroxyproline2-Oxobutyric acid Anthranilic acid Dodecanoic acid Lactic acid Oxaloacetic acid trans-Cinnamic acid2-Oxoglutaric acid Arachidic acid Docosapentaenoic acid Leucine Palmitic acid Tricosane
2-Oxovaleric acid Arachidonic acidEthylenediaminetetraacetic acid Levulinic acid Palmitoleic acid Tricosanoic acid
2-Phosphoenolpyruvic acid Asparagine Eicosapentaenoic acid Lignoceric acid para-Toluic acid Tridecane2-Phosphoglyceric acid Aspartic acid Erucic acid Linoleic acid Pentadecane Tridecanoic acid3,5-Diiodo-L-tyrosine Azelaic acid Ferulic acid Lysine Pentadecanoic acid Tryptophan3-Hydroxybenzoic acid Behenic acid Fumaric acid Malic acid Phenethyl acetate Tyrosine3-Hydroxydecanoic acid Benzoic acid gamma-Linolenic acid Malonic acid Phenylalanine Undecanoic acid3-Hydroxyoctanoic acid beta-Alanine Glutamic acid Margaric acid Pimelic acid Valine
Proline Vanillic acid
MCF Amino acids, fatty acids and organic acids
In-house libraries
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Fatty acidsHexanoic acid (C6_0) 9,12-trans-Octadecadienoic acid (E,E) C18:2(n-6t)Octanoic acid (C8_0) 7-trans-Nonadecenoic acid, (7E)- C19:1(n-12t)Decanoic acid (C10_0) 10-trans-Nonadecenoic acid, (10E)- (C19_1n-10t)Undecanoic acid (C11_0) 9,12-cis-Octadecadienoic acid (Z,Z) (C18_2n-6c)Dodecanoic acid (C12_0) Eicosanoic acid (C20_0)
Tridecanoic acid (C13_0)6,9,12-cis-Octadecatrienoic acid, (6Z,9Z,12Z)- (C18_3n-6c)
Tetradecanoic acid (C14_0) 11-trans-Eicosenoic acid, (11E)- C20:1(n-9t)
9-trans-Tetradecenoic acid (C14_1n-5t)9,12,15-cis-Octadecatrienoic acid, (9Z,12Z,15Z)- C18:3(n-3c)
9-cis-Tetradecenoic acid (C14_1n-5c) 11-cis-Eicosenoic acid, (11Z)- C20:1(n-9c)Pentadecanoic acid (C15_0) Heneicosanoic acid (C21_0)10-trans-Pentadecenoic acid (C15_1n-5t) 11,14-cis-Eicosadienoic C20:2(n-6c)10-cis-Pentadecenoic acid (C15_1n-5c) Docosanoic acid (C22_0)
Hexadecanoic acid (C16_0)8,11,14-cis-Eicosatrienoic acid, (8Z,11Z,14Z)-C20:3(n-6c)
9-trans-Hexadecenoic acid (C16_1n-7t) 13-trans-Docosenoic acid, (13E)- (C22_1n-9t)9-cis-Hexadecenoic acid (C16_1n-7c) 11,14,17-cis-Eicosatrienoic acid C20:3(n-3c)Heptadecanoic acid (C17_0) 13-cis-Docosenoic acid, (13Z)- (C22_1n-9c)10-trans-Heptadecenoic acid, (10E) (C17_1n-7t) 5,8,11,14-cis-Eicosatetraenoic acid (C20_4n-6c)10-cis-Heptadecenoic acid, (10Z)- (C17_1n-7c) Tricosanoic acid (C23_0)Octadecanoic acid (C18_0) 13,16-cis-Docosadienoic acid (C22_2n-6c)
6-trans-Octadecenoic acid, (E)- C18:1(n-12t)5,8,11,14,17-cis-Eicosapentaenoic acid, (5Z,8Z,11Z,14Z,17Z)- C20:5(n-3)
9-trans-Octadecenoic acid, (9E)- C18:1(n-9t) Tetracosanoic acid (C24_0)11-trans-Octadecenoic acid, (E)- C18:1(n-7t) 15-cis-Tetracosenoic acid, (15Z)-(C24_1n-9c)
6-cis-Octadecenoic acid, (Z)- C18:1(n-12c)7,10,13,16-cis-Docosatetraenoic acid, (7Z,10Z,13Z,16Z)- C22:4(n-6c)
9-cis-Octadecenoic acid (9Z)- (C18_1n-9c)4,7,10,13,16-cis-Docosapentaenoic acid, (4Z,7Z,10Z,13Z,16Z) C22:5(n-6c)
11-cis-Octadecenoic acid, (Z)- C18:1(n-7c)7,10,13,16,19-cis-Docosapentaenoic acid, (7Z,10Z,13Z,16Z,19Z)-C22:5(n-3c)
Nonadecanoic acid (C19_0)4,7,10,13,16,19-cis-Docosahexaenoic acid, (4Z,7Z,10Z,13Z,16Z,19Z) C22:6(n-3c)
ducitol
fructose
myoinositol
glucose
glycerol
mannitol
sorbitol
fucitol
ribitol
galactose
mannose
rhamnose
sorbose
arabinose
ribose
trehalose
xylose
lactose
maltose
QFAMEs
TMS
In-house libraries
Sugars
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Metabolomics methods
TMS (~300 compounds)
MCF (~100 compounds)
Same sample extract, different derivatisation method (mussel gill tissue)
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Metabolomics methods
QFAMEs (~60 compounds)
MCF (~100 compounds)
Same sample, different extraction and derivatisation method (human plasma)
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Automated Data Processing
Both in GUI-R developed by Morgan Han
Metab (Aggio)
lower false positive, higher missing values
MSOmics (Han)
higher false positive, fewer zero values
They use R – XCMS package
Two options
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Data processing
Figure: Morgan Han
• Big data – eg. 1000 samples each with 10-20MB datafile
• Need to be processed batchwise so that a data matrix is generated, enabling sample comparison for each compound
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Data matrix
Samples
Compounds
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Data analysis
Help with data analysis:• Silas Villas Boas and Morgan Han (Metabolomics Lab)• Katya Ruggiero and Kevin Chang (Statistics Consulting
Centre)
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Current UoA research