Gas Chromatography-Mass Spectrometry
Dr Erica ZarateAuckland Science Analytical Services - Mass Spectrometry
12 June 2015
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
GC-MS available
Agilent
Thermo
• 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
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
Fragmentation pattern
Chromatogram
Spectrum
Identification
Sample
Library
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).
• 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
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
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
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)
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
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
Metabolomics methods
TMS (~300 compounds)
MCF (~100 compounds)
Same sample extract, different derivatisation method (mussel gill tissue)
Metabolomics methods
QFAMEs (~60 compounds)
MCF (~100 compounds)
Same sample, different extraction and derivatisation method (human plasma)
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
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
Data matrix
Samples
Compounds
Data analysis
Help with data analysis:• Silas Villas Boas and Morgan Han (Metabolomics Lab)• Katya Ruggiero and Kevin Chang (Statistics Consulting
Centre)
Current UoA research
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