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