Short Course on Compound-Specific Isotope Ratio Mass Spectrometry

Short Course on Compound-Specific Isotope Ratio Mass Spectrometry

O

H

C N

14th April 2003, School of Chemistry, University of Bristol

Organic Geochemistry Unit

SIMSUG Short Course on Compound-Specific Isotope Analysis Programme: 8:30 to 8:40

Welcome

Rich Pancost

8:40 to 8:50

Introduction to compound-specific isotope analysis Richard Evershed

8:50 to 9:10

Laboratory techniques in compound-specific isotope analysis Ian D. Bull

9:10 to 9:30

Derivatisation of compounds for compound-specific isotope analysis Bart van Dongen

9:30 to 9:55

Gas Chromatography-Isotope Ratio Mass Spectrometry (GC-IRMS) instrumentation Rich Pancost

9:55 to 10:15

Discussion and Questions

10:15 to 10:30

Coffee

10:30 to 10:50

Troubleshooting in GC-IRMS

Jim Carter

10:50 to 11:20

Data analysis in GC-IRMS

Hazel Mottram

11:20 to 11:55

CSIA for other isotopes

Andreas Hilkert

11:55 to 12:25

Case studies using compound-specific isotope analysis Zoë Crossman and Mark Copley

12:10 to 12:45

Discussion and Questions

12:45 to 1:30

Lunch and Further Discussion

8:40 to 8:50 Introduction to compound-specific isotope analysis Richard Evershed

An introduction to compound-specific stable isotope determinations by gas chromatography-isotope ratio mass spectrometry Richard P. Evershed

Definitions • Stable isotope ratio mass spectrometry (IRMS) Used to achieve high precision determinations of the variations in stable isotope composition:

Abundance ratio R = 13C/12C δ13C values have units of per mil (o/oo) Rstandard = 0.0112372 for PDB (but assigned value of 0o/oo)

• Stable isotopically labelled compounds have been determined for many years using conventional MS but cannot be used to determine high precision stable isotope ratios at natural abundance - only capable of determining variations in isotope compositions at the o/o level, ca. three orders of magnitude lower precision

The profusion (and confusion) of acronyms!

• Isotope ratio monitoring-GC/MS (IRM-GCMS; Matthews and Hayes, 1978) • GC-IRMS • GC-combustion-IRMS (GC-C-IRMS) • GC-thermal conversion-IRMS (GC-TC-IRMS) • Compound-specific isotope analysis (CSIA) • Etc, etc. • Beware!

Origin of gas chromatography-isotope ratio mass spectrometry • Gas chromatography-IRMS – Concept of linking GC with IRMS evolved during the 1970s and 1980s (Matthews and Hayes, 1978) – GC separates organic compounds – On-line reactor combusts compounds to CO2 (and N2) – IRMS determines relative abundance ratio of 13C/12C as CO2 (15N/14N as N2) – Apparently rather simple!

Research opportunities for exploiting carbon isotopes •

•

•

•

Differences in natural abundance due to isotopic fractionation in nature - Abiological vs biological processes - C3 and C4 photosynthesis - Biochemical pathways - Environmental influences on organisms Tracer methodologies; 13C replacing radiotracers - Enriched substrates, i.e. commercially enriched gases, chemically synthesised compounds, cultures Versitility and scope - Laboratory experiments - Human subjects - Field experiments Improvements in stable isotope MS technologies - Continuous flow instruments - Compound-specific approaches

Why compound-specific determinations rather than bulk? • Dictated by the nature of the research question not by fashion! • Compound-specific and bulk determinations complimentary • Advantages - Linking molecular structure-stable isotope compositionsource or process - Small sample sizes; only a few tens of nanograms of a single compound required for a determination - Complex materials or mixtures, e.g. living organisms composed of biochemical components of widely varying structures and origins - Isotopic information accessible at the biochemical building-block level,e.g. individual amino acids in a protein

Why compound-specific determinations rather than bulk? • Disadvantages - Individual analyses slow to perform (hours rather than minutes) - Loss of sample integrity during sample preparation - Technically more demanding; major manpower commitment - More expensive initially and higher consumable costs - Analytical precision lower than bulk approaches; no compound-specific equivalent to the dual inlet although improvements will come

Continuous-flow bulk and compound-specific approaches z

Bulk isotope ratio instruments

GC

Combustion

IRMS

- Large sample sizes, e.g. 10–3 g - Minimal sample preparation z

Compound–specific isotope ratio instruments

GC

Combustion

IRMS

- Very small sample sizes, e.g. 10–8 g - Complex sample preparation procedures - Requires knowledge of capillary GC, reactor systems and low dead-volume gas handling systems

Sample preparation 8:50 to 9:10 Laboratory techniques in compound-specific isotope analysis Ian D. Bull 9:10 to 9:30 Derivatisation of compounds for compound-specific isotope analysis Bart van Dongen

Laboratory Techniques in Compound Specific Stable Isotope Analysis

Ian D Bull

Sample •

Aim: To isolate a complex extract containing hundreds of compounds and separate it into discrete groupings of compound class amenable to GC analysis Raw sample

GC sample

An example analytical protocol Sample Total lipid extract

Biopolymer analysis

Chromatography Acid fraction

• •

Neutral fraction

Polar fraction

Lipids are extracted from the sample matrix and separated by chromatography prior to analysis Biopolymers need to be isolated from the lipid extracted residue

Step 1 – Sample preparation

• • • •

Samples are freeze dried and crushed Freeze dried to remove water and increase the effectiveness of solvent penetrating the sample matrix Crushed in liquid nitrogen to provide a greater surface area and a homogenous sample Inorganic complications, e.g. S – remove with activated Cu turnings

•

• •

Glassware – needs to be ‘clean’ • furnaced • solvent extracted – solvent bottles Plasticisers You!

Relative Intensity

Contamination

cholesterol

HO

10

15

20 Time (min)

25

30

• Contamination may be more dominant than the compounds of interest • Co-elution of contaminants with compounds of interest • Contaminent may be the same as the compounds of interest

Step 2 - Extraction

•

Aim: To extract lipids from the sample matrix whilst maintaining sample extract integrity and project viability

• • •

Soxhlet Ultrasonication Bligh-Dyer – normal – acidified Liquid/liquid extraction Autoextraction

• •

Factors to consider before extraction

• • • •

What am I actually interested in? Stability of compounds of interest Type of matrix being extracted Sample size - limiting factor – small samples need high residue recovery rate

• • • • •

Soils, sediments - Soxhlet Small samples - ultrasonication Bacterial cultures, tissue - Bligh-Dyer Aqueous solutions - liquid/liquid extraction Proprietary autoextraction instruments – high sample throughput

Soxhlet extraction • • •

•

Pre-extracted cellulose thimble Continuous extraction for 16-24h Enables solvent to be recycled approximately 100 times during 24 h cycle Rigourous extraction but not suitable for light or heat sensitive compounds, e.g. ergosterol

HO

•

ergosterol

Large solvent volumes

Ultrasonication • •

•

• • •

Sample agitated ultrasonically to assist solvent penetration Normally performed with centrifuge tube or vial containing sample and solvent immersed in ultrasonic bath Sonication applied for 15 min and solvent removed and repeated several times with fresh solvent, solvent fractions combined Faster than Soxhlet extraction – large sample throughput Less rigorous extraction Good for very small samples

Bligh-Dyer

•

• • • •

Monophasic solvent system – buffered water, chloroform, methanol – acidifed Bligh-Dyer using acidified water Specifically designed for the extraction of fresh biological tissues (breaks cell membranes) Carried out in an ultrasonic bath Simultaneous, efficient extraction of both hydrophobic (lipids) and other hydrophilic cell components High sample throughput

Bligh , E.G. and W.J. Dyer (1959) Canadian Journal of Biochemistry and Physiology 37: 911-917

Total Lipid Extract •

Lipid extraction yields the Total Lipid Extract (TLE) – contains hundreds of observable compounds High temperature GC chromatogram of the TLE of oak leaf litter

Step 3 - Separation of lipid extracts

•

Carried out by chromatography using the principles – Stationary phase (silica, aluminium oxide) and mobile phase (solvent) – Different molecules have different affinities for the two phases hence move through column or along plate at different rates – Depends on size and/or functional groups – Specialised stationary phases can exhibit an ionic affinity for specific functional groups

Column Chromatography Solvents added in sequence Glass ‘column’ Sample

Fraction 1: hydrocarbons

Sorbent

Fraction 2: TAGs, wax esters Fraction 3: sterols, triterpenols, alcohols

Glass frit Stopcock

Fraction 1 Hexane

Least polar

Fraction 2 DCM

Elutropic series Increasing polarity

Fraction 3 DCM/methanol

Most polar

Step 3 - Separation of lipid extracts

•

Carried out by chromatography using the principles – Stationary phase (silica, aluminium oxide) and mobile phase (solvent) – Different molecules have different affinities for the two phases hence move through column or along plate at different rates – Depends on size and/or functional groups – Specialised stationary phases can exhibit an ionic affinity for specific functional groups

Solid phase extraction

Treatment of non GC-IRMS amenable lipids •

• •

Wax esters, steryl esters, triacylglycerols, phospholipids are all examples of compounds that are non GC-IRMS amenable yet are present in the samples and can yield important information Using phospholipids as an example Aliquot of the PLFA fraction taken and saponified to generate GC-IRMS amenable compounds, i.e. fatty acids

O

O O

O O O

- OH, 0.01 M -O

O

R

OR'

R

OR' OH

- OH H

+

O

- OR' R

O-

workup O OH

P OO-

Step 5 - Biopolymer analysis

•

Carbohydrates – acid hydrolysis of the lipid extracted residue HO

O

HO

O

O O

HO

O

HO

O

OH

OH

CH2OH

CH2OH

CH2OH

CH2OH

O

OH

n = 1-10000

72% H2SO4, RT, 1 h 1 M H2SO4, 100oC, 2.5 h

e.g. H

OH H

H

H HO OH

O OH

CH2OH H

glucose

O

O OH

Step 5 - Biopolymer analysis O

•

Proteins

e.g.

Gly

OH NH2

O OH

Phe

NH2 O 6 M HCl, 100oC, 24 h

Ser

OH

HO NH2

O

Pro

OH NH S

Met •

Still not ideal but we are getting there!

O OH NH2

Our example analytical protocol revisted Sample Total lipid extract

Biopolymer analysis

Chromatography

Proteins

Acid fraction

Neutral fraction

Polar fraction

n-alkanoic acids

Hydrocarbons wax esters n-alkanols sterols, triterpenols

PLFAs

Carbohydrates

Summary •

• • • • • • • •

Identify you target compounds before proceeding with any form of sample preparation - well constructed hypotheses Design extraction and separation procedures around the compounds of interest Be aware of limitations conferred by the remit of the investigation Acquire the necessary infrastructure Maintain an analytical environment Be paranoid about contamination – blank runs Use suitable standards to verify your analytical procedure and where appropriate act as internal references for quantitative work Never use the whole of your sample – mistakes will be made! The methods shown are not prescriptive – experiment!

Derivatisation of compounds for compound-specific isotope analysis Bart van Dongen

Analytical protocol Sample Residue analysis

Total lipid extract Chromatography Acid fraction n-alkanoic acids

Amino acids

Neutral fraction

Polar fraction

Hydrocarbons wax esters n-alkanols sterols triterpenols

PLFAs

Measurement possible?

Derivatisation GC-IRMS

Carbohydrates

Talk outline • Introduction • Why do we need derivatisation? • Conditions • What are the general factors that affect derivatisation reactions? • Different compound classes: • Fatty acids • Alcohols • Monosaccharides • Amino acids

n-Alkanes 31

Relative intensity

n-Alkanes obtained from a soil 29

27

33

25

21 23

Retention time No functional groups No derivatisation needed

GC-run of mixture of compounds

Relative intensity

n-Alkane

Sterols

Fatty acids

Retention time

Derivatisation • Compounds that are too involatile, because of functional groups, to analyse using GC can be chemically modified • Derivatised (i.e. functional groups blocked by apolar groups) • Examples of functional groups:

-Carboxylic acids -Hydroxy -Amino

• Examples of derivatisation reactions:

-Esterification -Silylation -Acetylation

• Many derivatisation reaction possible • Which to choose?

Requirements • Isotope effect (KIE= lightK/heavyK) • Addition of as little carbon as possible • Relatively fast reaction • Good separation of compounds possible • No interference with by-products • Stable end-products

Isotope effect in derivatisation Derivatisation reaction Carbon atoms target molecule involved

No carbon atoms involved No isotope effect

Isotope effect Conversion 100%

Method usable

Carbon atoms derivatisation molecule involved

Yes

Isotope effect Conversion not 100% Reproducible? No Method not usable

Addition of carbon by derivatisation

• Derivatisation results in the addition of carbon atoms, with different δ13C values (compared to the original carbon atoms) •Correction need to be made for every added carbon

nderivised compoundδ13Cderivitised compound-nderivative groupδ13Cderivative groupa δ13Ccompound = ncompound n = the number of carbon atoms

a Rieley,

1994

Uncertainty due to added carbona

Uncertainty in δ-value

2.4

n=3

n=5 • Increase in uncertainty with increasing addition of derivative carbon

1.2 n=10

• Effect larger if number of original carbon atoms is smaller

n=20 n=30 0

1

10

20

Carbon number added n = the number of original carbon atoms a after

Rieley, 1994

Fatty acids • Diazomethane method Bond broken O R

O

C H2N2 OH

+ N2

R

OMe

• Fast, Irreversible reaction • Isotope effect is on the carbon of the diazomethane • Added in excess quantity • Non-reproducable isotope effect

• Method not usable

Fatty acids • BF3, MeOH derivatization -

O

O R

OH

BF3 MeOH

R

Bond broken BF3

+

OH2 OMe

O R

OMe

• Isotope effect is on the carbon of the fatty acid • Conversion 100% • No isotope effect • Method usable

Fatty acids, GC-run standard mixture Fatty acids; derivatised

Relative intensity

Old situation

Retention time

Alcohols • Silylation using BSTFA (N,O-bis(trimethylsilyl)trifluoroacetamide) and pyridine

Pyridine R

OH

CF3

R

NSi(CH3)3

OSi(CH3)3

OSi(CH3)3

• No carbon atoms involved in reaction • Usable method • Disadvantage: products are stable but only for a relative short time

Alcohols, chromatogram Alcohols in a forest soil Relative intensity

24

28

26 22

30

23

25

27

32 29

31 Retention time

Monosaccharides O

O

OH

OH OH

HO

6

OH

OH

OH

OH

5

OH

Glucose

Ribose

• Main problems: Relatively large number of protection groups needed Relatively small number of original carbon atoms (usually 4 to 6) • How to minimize the addition of carbon?

(Silylation would add 12 to 18 carbon atoms)

Alditol acetate methoda O

OH

OH

OH

OH

NaBH4

OH

Bond broken

OAc

O

OAc

O O

OAc

OH

OH

OH

OH

OAc

OH

OH

OAc

Pyridine

OAc

• Isotope effect on the carbon of the reagent • Fractionation effect seems constantb • Method usable but correction factor needed Disadvantages: Still a large number of carbon atoms added (8-12) Actually measuring alditols; loss of information a After

Gunner et al., 1961; b Macko et al 1998; Docherty et al., 2001

Loss of structural information • Two hexoses, two pentoses etc. may lead to the same alditol O OH HO HO

HO

HO

OH

OH

OH

OH

OH

OH

OH

OH

Arabinose

O

Arabitol

Lyxose

• One hexose, pentose etc. may lead to two alditols OH

OH

O

OH

HO

HO OH

OH

OH

OH

OH Fructose

OH Glucitol

OH HO +

HO OH OH OH Mannitol

Methyl boroacetylation of monosaccharidesa HO HO

O OH

OH

+

HO O

HO

OH

Bonds broken OH 1)Methyl boroacetylation 2)Silylation

OH Si O

O

O

O

B Total 5

+

O O

B

O B

O O

• Addition of relatively small number of carbon atoms (2-5) • Measuring monosaccharides, not alditols • Isotope effect is on carbon atoms of monosaccharidesb • Reaction quantitative; No isotope effect a After Reinhold et al., 1974; b van Dongen et al., 2001

OO B

Total 2

GC-IRMS of a monosaccharide mixture

glucose

arabinose

Relative intensity

xylose

mannose

Relative retention time

Amino acids COOH H2N

Main problems:

H

• Two different groups which needs protection • Small number of own carbon atoms

R

2 (Glycine) to 11 (Tryptophan) COOH H2N

H

COOH H2N

H

H Glycine

N H Tryptophan

Amino acids, derivatisation OH

O

1) iso-propanol/HCl

Bond broken H 2N

H

2)

O

O

H N

O

R

Bond broken Isotope effect: Step 1;

OCH(CH3)2

O

H R

F3C

O

CF3

CF3

On carbon atom of amino acida Conversion 100%; method usable

Step 2;

On carbon atom of reagent Fractionation effect seems constantb Method usable but correction factor needed

aRieley

1994; bDocherty et al. 2001

Amino acids, GC-run

Relative retention time

Glu Phe

Pro Hyp

Leu Ile

Val

Thr

Ser

Ala Gly

Relative intensity

Asp

I.S.

Amino acids in a standard mixture

Amino acids, point to think about Total 5

OCH(CH3)2

O H N

O

H R

CF3

?

• Relatively large number of carbon atoms added (at least 5)

• A reaction with an isotope effect, although can be corrected for • HF can be formed, causing problems when measuring isotopes

Summary

• Derivatisation methods are available which make it possible to determine the δ13C values of the majority of functionalised compounds.

• However always bear in mind that: 1) derivatisation can cause an isotope effect 2) corrections are needed for the added carbon

GC-IRMS instrumentation and analysis 9:30 to 9:55 Gas Chromatography-Isotope Ratio Mass Spectrometry (GC-IRMS) instrumentation Rich Pancost 10:30 to 10:50 Troubleshooting in GC-IRMS Jim Carter

10:50 to 11:20 Data analysis in GC-IRMS Hazel Mottram 11:20 to 11:55 CSIA for other isotopes Andreas Hilkert

Gas Chromatography-Isotope Ratio Mass Spectrometry (GC-IRMS) instrumentation Rich Pancost

GC-IRMS Instrumentation

Gas Chromatograph Separates individual compounds, allowing discrete isotopic compositions to be determined Combustion/Reduction Interface Converts eluting compounds into CO2 for analysis Continuous Flow Instrument Allows the delivery of sample CO2 to an isotope ratio mass spectrometer via a He stream

The GC-IRMS ThermoFinniganMAT design

The Gas Chromatograph For further ref: http://gc.discussing.info/ Injector Column

Backflush valves

The GC Injector

• Ideally, want on-column injection • Makes best use of limited sample size • Minimizes problems associated with isotopic fractionation

A split/splitless injector

An on-column injector

The GC Column

Polyimide Coating Fused Silica Stationary Phase

Expanded view of capillary tubing

The GC Column The importance of investing in good separation

Differences amongst columns: Stationary phase Length Diameter 15 m

30 m

60 m

The Backflush System: Necessary for the removal of solvent • The small quantities of solvent used during injection represent a large amount of organic material introduced to the GC/C/IRMS system • Excess carbon will: • Saturate the oxidizing power of the combustion furnace • Saturate the NafionTM tubing with water • Introduce excess carbon to the source, which is quite bad for the filament • Use of chlorinated solvents is particularly problematic • Generate HCl in combustion furnace, could corrode downstream components

Straight v. Backflush Configuration

The Backflush System

Combustion furnace

O2

He

The Combustion Furnace • Converts organic compounds into CO2 and H2O • Contains an oxidizing metal (CuO or ZnO) and typically a catalyst (Pt) 4 CuO 2 NiO

ThermofinniganMAT design

2 Cu2O + O2 2 Ni + O2

• Configuration dictates operating temperature • CuO: 825-850°C (cannot operate at higher temperatures due to thermal decomposition of CuO) • NiO: 1150°C (can operate at lower temperatures but need supplemental O2) • Operation with supplemental O2 ideal for maximizing combustion but quickly exhausts downstream reduction furnace • Hybrid reactors favoured by many

• Key: avoid loss of chromatographic resolution • must allow laminar flow and/or • convert organic matter fully to CO2 rapidly

The Combustion Furnace

0 24 m m 0 32 m m

(240 mm long)

Note: heated zone is 260 mm, bracketing wires Capillary from GC (slides ~1.5 cm into end of reactor)

He

Furnace must extend at least 3 cm out of heated zone

Oxidation of the Combustion Furnace • To maintain oxidizing capacity of the furnace, it must periodically be oxidized • NOTE: CuO thermally degrades at 850°C; thus, the furnace must be oxidized even if the system is not in use • Immediately after oxidation, thermal desorption results in high amounts of O2 being released through system • This is bad for reduction furnace and filament • Oxidation schemes • Briefly (10-20 sec at end of each run) • Every other day (overnight) • Weekly (overnight)

Depends on usage, metals and temperature

Oxidation of the Combustion Furnace

• Oxidation must be done in backflush mode • Insures flow through reactor • Insures no flow into reduction furnace and MS

The Reduction Reactor

• Purpose: • Nitrous oxides are converted to N2 • Excess O2 is removed from analyte stream • Reactor material and components largely the same as combustion furnace • 3 Cu wires • Operated at 650°C

The Water Trap

• Water generated during combustion is a problem! • Can protonate CO2 in MS source resulting in elevated m/z 45 signals • Can be removed with a cryogenic trap OR • Can be removed by passing analyte stream through a selectively permeable membrane (NafionTM) with a dry He counterflow

The Open Split

• Adaptation for GC-IRMS that is analogous to adaptations for any continuous flow interface He

• Capillary to MS has an inner diameter of 0.1 mm • Insures that delivery of He stream to MS is 0.5 ml/min • Thus, typically 1/4 of the analyte is delivered to the MS

Analyte

Reference Gas Inlet Reference

To MS

He

Allows introduction of reference gas in a line parallel to the analyte (i.e. two columns deliver He and CO2 to MS)

Troubleshooting (Tricks and Tips) Jim Carter with special reference to: ThermoFinnigan GCC I-III GC-IRMS interface

Three things to consider

Combustion Reactor Gas Chromatograph (organic compound)

Interface (H2, N2, CO, CO2)

Axiom There is no substitute for good chromatography

The gas measured must correspond to a single compound Good Gaussian peak shape improves precision

Don’t assume … The software will not “separate” your peaks

Minor components will affect your result

GC basics (avoiding fractionation)

INJECTOR Splitless, on-column or PTV injection Constant flow rate = constant split ratio

COLUMN 0.32mm id / thick film 0.32mm id / thin film 0.25mm id

high sample loading improved chromatography improved split ratio

Tools of the trade

Hewlett Packard Flowcalc 2.05 www.chem.agilent.com /cag/servup/usersoft/main.html Digital flow meter

Tube reamers

Maximise your chromatography

• • • •

Eliminate the usual chromatographic problems Cold spots Dead volumes Active sites

Cold Spots

Reduce thermal mass

Remove metal

Dead Volumes

ZDV fitting GC column

Oxidation reactor

Remove coating Drill through

Dead Volumes

Bleed capillary 100µl / min helium

Dead Volumes

1% oxygen helium

Active Sites

GC column

System Checks

• • • • • • •

Know how your instrument performs when its working! Don’t wait until it breaks! Know - Flow rates - BF ON / BF OFF Know - Chromatographic “dead time” (to) Know - m/z 40 signal - BF ON / BF OFF (flow and leaks) Know - m/z 18 signal – BF OFF (water in ion source) Know - Standard ON/OFF test (standard deviation)

The Argon Test

• • • •

Monitor m/z 40 Inject 1µl of air RT = column t0 + interface t0 (10-15 sec) Tailing = dead volume, blockage or leak

The Hexane Test • • • • •

Monitor m/z 44 GC oven at ca. 100oC Inject 1µl of hexane vapour RT = approx. RT for argon Tailing = cold spots or poor combustion

NB should resolve hexane isomers

What can possibly go wrong? (1) Poor chromatography

Did RT change? (argon test) No

Yes

Check m/z 40

Check Injector (septum/liner) OK Check Ox. Reactor

Up

Check for leak

Check “T” piece

Down

Blockage (check flows)

Check Ox. reactor

What can possibly go wrong? (2) It’s the wrong numbers • • •

δ13C values are consistently enriched δ13C values are consistently depleted δ13C values are unstable

Is chromatography OK? No

Yes

As before

Which way did the δ value move? Up

Down N compounds?

Check m/z 18 High Check source heater OK Check Nafion

Yes Check Red. reactor

No Is m/z 40 OK? Yes Check Ox. Reactor (hexane test)

Isotope values are unstable As before

No

Is chromatography OK? Yes

Check for leaks No Check BF valve

Up

Is m/z 40 OK? Yes Is m/z 18 OK? Yes Standard ON/OFF test Poor Clean Ion Source

Summary • Chromatography first and foremost • Know your system when its working • Have the right tools available • Fault find systematically (check/change one thing at a time) • If all else fails: rebuild the interface start at the water trap – GC column capillaries “go wrong” as do fittings change one thing at a time “Once upon a time in Indiana …..”

Data Analysis and Interpretation Hazel Mottram

Axiom You cannot get reliable isotope data without good chromatography!

What is measured?

•

•

Unlike a conventional organic mass spectrometer, in which a range of ions are measured, in isotope ratio mass spectrometry we only measure a few ions For δ13C analyses, three ions are measured: – m/z 44 – m/z 45 – m/z 46

•

These correspond to the different isotopomers of CO2: – – –

•

12C16O16O

(m/z 44) 13C16O16O and 12C17O16O (m/z 45) 12C16O18O (m/z 46)

A reference gas is used in the same manner as in routine isotopic analysis to allow measurement of isotope ratios relative to a standard

What a run looks like!

What a run looks like!

Variation across peak

After Ricci et al (1994)

Peak integration - Automated

After Ricci et al (1994)

Manual integration •

Must integrate the whole peak in both m/z 44 and 45/44 traces – otherwise will get incorrect representation of isotope ratio

9

²

²

Manual integration • •

Must integrate the whole peak in both m/z 44 and 45/44 traces – otherwise will get incorrect representation of isotope ratio Peak area important – instrument is only linear over a certain range

Manual integration • • •

Must integrate the whole peak in both m/z 44 and 45/44 traces – otherwise will get incorrect representation of isotope ratio Peak area important – instrument is only linear over a certain range Peak shape important – unusual peak shapes (particularly in 45/44 trace) can indicate coelutions

Lichtfouse et al (1991)

The Background

• •

It is crucial to have appropriate background as the software calculates δ13C values from deviations from this Can be done automatically – On the basis of immediately preceding and subsequent data points as described previously – Or using dynamic background (develops a background from entire analysis, smoothing data) – Caution must be used! Especially for peaks eluting near a sudden shift in the baseline (i.e. when the instrument shifts out of backflush) – Or manually (be sure to inspect both m/z 44 and ratio trace!)

Sample analysis: Routine analysis with minor derivatisation (Note: different labs have significantly different protocols)

•

Compounds with minimal co-elution and over 0.3 V amplitude: – Samples should be run twice – Samples should be run with co-injected standards which have been measured off-line • Approximately same abundance • Same compound class if possible

– If duplicate runs are reproducible within 0.6 ‰ and standards are within ~0.5 ‰ of known values then no further runs are necessary

•

Compounds with 0.1 - 0.3 V amplitudes and minimal co-elution: – The analytical precision of the instrument decreases at this range (Merritt and Hayes, 1994) – Samples should be run in triplicate – Values should be reported with errors of ± 1.0 ‰

•

Values from compounds with amplitudes < 0.1 V should never be used!

Sample analysis: Coelutions

• • •

Ideally co-elution should be avoided using further clean up steps or a different column Where this is not possible, co-eluting peaks can be integrated together using the integration software For small overlaps, the co-eluting peaks can be integrated separately: – Maximum co-elution of 25% – A minimum estimate of analytical error can be gained by running a sample in different concentrations – Newer users should probably avoid trying to interpret co-elutions as this is a very tricky area

•

For a description of the errors arising from co-elution, see Ricci et al (1994)

Sample analysis: Compounds requiring extensive derivatisation

•

• • •

Compounds such as amino acids and monosaccharides require more extensive derivatisation, involving addition of numerous carbons and often involving a reproducible kinetic isotope effect These are both sources of error which must be accounted for Kinetic isotope effect must be calculated for each compound under each set of conditions More replicates needed to minimise error

Correction for derivatising groups

•

With no kinetic isotope effect, e.g. methylation of a fatty acid, this is a simple mass balance equation:

RCO2H

BF3/MeOH

RCO2Me

ncdδ13Ccd = ncδ13Cc + ndδ13Cd where

n is number of moles of carbon c refers to compound of interest d refers to the derivative group fd refers to the derivatised fatty acid (Rieley, 1994)

Correction for derivatising groups

• • •

Measure value of derivatising compound offline e.g. BF3/methanol Adjust value obtained for compound of interest accordingly Example: A value of –28.14 ‰ is obtained from the GC/C/IRMS analysis of C18:0 FAME The BF3/MeOH is measured offline and found to have a value of -40.15 ‰ What is the -corrected δ13C value for the fatty acid?

ncdδ13Ccd = ncδ13Cc + ndδ13Cd δ13Cc =

1 (ncdδ13Ccd - ndδ13Cd) nc

= 1/18 {(19 x –28.14) – (1 x –40.15)} = -27.47

Correction for derivatising groups

•

•

Where it is not possible to measure the value of the derivatising carbon offline (e.g. where reagents are obtained in numerous small batches) an alternative approach can be taken The derivatised and underivatised compound are analysed and the contribution of the derivatising reagent ncdδ13Ccd = ncδ13Cc + ndδ13Cd δ13Cd

•

=

1 (ncdδ13Ccd - ncδ13Cc) nd

This should be repeated for each compound of interest

Derivatisation: BSTFA for alcohols δ13Cd •

= 1 (ncdδ13Ccd - ncδ13Cc) nd

The contribution of the BSTFA to the overall δ13C value is normally measured using a standard alcohol with known δ13C value OH OH

HO

myo-inositol HO

OH OH

•

The advantage of using myo-inositol is that it has a large number of hydroxy groups – Therefore a large quantity of derivative carbon is added and there is less error in calculating its contribution

Correction for derivatising groups

• •

Where there is a kinetic isotope effect, δ13Cd cannot be directly determined The kinetic isotope effect for each compound can be quantified according to Rieley (1994): KIE = 1 + ∆ncd / 1000x where

•

ncd is the difference between the measured isotope value and that predicted from mass balance equations x is the number of groups available for derivatisation

Where the KIE is constant for a set of conditions, correction factors can be calculated − δ13C values of underivatised and derivatised compound are used to calculate the effective stable isotope composition of the derivatising carbons

Errors where there is no KIE

BF3/MeOH (IRMS) ± 0.1 ‰ Calculation errors propagate

FAME of interest (GC/C/IRMS) ± 0.3 ‰

δ13C of FAME of interest ±? 2

n  2  nc + n d   + σ 2d  d   σ c2 = σ cd  nc   nc 

2

σc2 = 0.32 × (19/18)2 + 0.12 × (1/18)2 σc2 = 0.100 σc = 0.32 ‰

Docherty et al (2001)

Errors where a KIE is present Underivatised sugar (IRMS) ± 0.1 ‰

Correction factor δcorr ± ?

Calculation errors propagate

Derivatised sugar (GC/C/IRMS) ± 0.3 ‰ 2

2

n   n + nd  2  nc + n d   + σ cd   σ = σ  s  + σ 2sd  s  nc   nc   nc  2 c

2

2 s

σc2 = 0.12 × 5 2 + 0.32 × 5+102 + 0.32 × 5+10 2 5 5 5 2 σc = 1.63 σc = 1.3 ‰

Derivatised sugar analyte (GC/C/IRMS) ± 0.3 ‰

Calculation errors propagate

δ13C of sugar of interest ±?

Docherty et al (2001)

Analysis of highly labelled compounds

• • •

How is the analysis of a sample containing highly labelled compounds different from analysis at natural abundance? Are the δ13C values of other compounds in that analysis affected? To investigate potential carryover: – FAME mixture containing 5 components at natural abundance analysed x 5 – Earlier eluting labelled compound added to mixture and analysed again

Within run carryover: 16:0* + natural abundance fame mix (1:1)

Within run carryover 16:0* + natural abundance fame mix (1:1)

16:1

17:0

17:1

18:0

-14 -16 -18

13

δ C (‰)

-20 -22 -24 -26 -28 -30 -32

after 16:0* FAME std

18:1

18:2

Within run carryover 16:0* + natural abundance fame mix (2:1)

16:1

17:0

17:1

18:0

-14 -16

13

δ C (‰)

-18 -20 -22 -24 -26 -28 -30 -32

after 16:0* FAME std

18:1

18:2

Within run carryover

Summary

• •

Good isotope data requires good chromatography Care must be taken during data analysis to ensure 1. Peak amplitudes are within range of instrumental linearity 2. Data is only collected from peaks with minimal coelution 3. Backgrounds are selected with care

• •

Corrections must be made for atoms added during derivatisation Errors must be accounted for – This is particularly important when dealing with kinetic isotope effect

•

When analysing highly enriched compounds: – Highly enriched components within a chromatographic run may adversely affect the δ13C values of closely eluting compounds

The Way to N, H, O by irm-GC/MS

Andreas Hilkert ThermoFinnigan MAT GmbH, Bremen

δ15N by irm-GC/MS

Introduced in 1992

Why 15N analysis ? -30

Carbon Isotope Ratio, δ 13CPDB [‰]

Drugs -31

-32

Source: CO2, Air

Heroin

-33

PlantMetabolism

-34

Cocaine

-35

Source: N2, Soil

Plant Metabolism

-36 -14

-12

-10

-8

-6

-4 15

Nitrogen Isotope Ratio, δ Nair [‰]

3

-2

0

Advantages + Nitrogen specific detection + All carbon of sample matrix is removed + All carbon of column bleed is removed + Free choice of derivatives + Derivatization groups without Nitrogen + No isotope dilution + No isotope fractionation + No intramolecular 15N tracer dilution e.g. 1-13C-Leucine vs. 15N-Leucine

4

N-selective irm-GC/MS Trace

Ref. gas

Ref. gas

Ref. gas

Comparison of FID trace and m/z 29 trace

N, O – tBDMS Amino Acid Derivatives 5

Challenges + Low abundance of 15N (ion statistics) + Low abundance in AA (sample amount) + N2 background (signal/background) + leak tightness of GC/C system + purity of Helium carrier gas + 100 % N2 yield

(ox / red efficiency)

+ Interfering masses (m/z 28, 29, 30) + CO (combustion efficiency) + CO+ from CO2+ (CO2 trap efficiency)

6

Comparison of δ15N and δ13C Determination H 15

N

R

H

Accumulated Effect on

13

C

H

C O O H

13

Element content Atoms per gas molecule 15N, 13C abundance Ionization efficiency rel. to CO2

Intensities of - in relation to m/z 45 (13C) - m/z 45 set to 100 % N

C

60 %

2 (in N2) 0.732 % ca. 70 %

1 (in CO2) 1.08 % 100 %

m/z 29 (15N) 8.33 % (e.g. 5% N, 60% C) 4.17 % 2.82 % 1.98 %

Theoretical required sample amount for δ15N 50 x higher than for δ13C if same precision as for δ13C is required

7

Challenges The Effect of CO contamination CO

Ratio 29/28 1.08 / 1 29

N2 0.732/ 1

28

δCON2 = (1.08/0.732 -1)*1000 = + 475 ‰

8

Combustion and Reduction Organic Compound 100 % Combustion Reduction

CO2, N2, H2O, NOx

Water Removal

CO2, N2, H2O CO2, N2

CO2 Removal

100 % N2 9

Combustion and Reduction 100 % N2 at 100 % Combustion

10

Combustion Requirements for δ15N • Complete Oxidation of C to CO2 • N2 Production optimized – High Temperature (980 °C) – Pyrolytic aspects

• NOx Production minimized – No Excess of O2 – Indicator mass m/z 30 (NO) -NHx -CHx

11

Ox Ox

N2 CO

Ox Red Ox

NOx

CO2

Combustion Efficiency

0

12

Sample Cleanup • Water Removal • CO2 Removal

13

δ15N Applications O-iPropyl, N-Pivaloyl Amino Acid Derivatives

Data taken from C. Metges

14

Sample Size

1.5 nmol N2 on col.

15

Boosting the Limits

16

Recipe for δ15N irm-GC/MS

17

Injector

splitless

Retention Gap

3m deactivated fused silica

Capillary Column

50 m, 0.32 mm i.d., 0.5 µm filmthickness, e.g. Ultra 2, DB5, ...

Column Connectors

glass deactivated (e.g. Restek) or metal / Vespel (e.g. Valco)

Oxidation Reactor

980 °C, restricted re-oxidation

Reduction Reactor

650 °C

CO2-Trap

cryogenic trap

Movable Open Split

release of trapped CO2

Sample

< 1.5 nmol N2 on column, < 600 ng AA derivative o.c.

δ2H by irm-GC/MS

Introduced in 1998

Why δ2H irm-GC/MS ? relatively D depleted clay minerals musts wine water natural gas marine oils non marine oils C3 ethanol

C4 ethanol C3 plants GISP

SLAP

-400 19

-300

-200

C4 plants SMOW

-100

0

100 ‰

Hydrogen Isotope Ratios Schematic Fractionation in the Atmospheric Water Cycle

-94 ‰ Vapor

-110 ‰ Vapor -14 ‰ Rain

OCEAN δD = 0 ‰

20

-126 ‰ Vapor -30 ‰ Rain

CONTINENT

We know where you eat ! 13

An orphan's tail: variations of δ O and δ D in a single elephant hair

-50

δΟ

-55

12 -60 -65

δD

10

-70 -75

9

-80 -85

8

-90 7

TC/EA-DELTA+XL ANALYST: H. Avak 6/23/2000 samples 200-600 µg

-95

6

-100 0

50

100

150 Length (mm)

21

200

250

δDSMOW (‰)

δ18 OSMOW (‰)

11

Comparison of δ2H and δ13C Determination

H

H 13

C

H 13

H

C

O

H

Accumulated Effect on Intensities of - in relation to m/z 45 (13C) - m/z 45 set to 100 %

H

e.g. Ethanol

Element content Atoms per gas molecule 2H, 13C abundance Ionization efficiency rel. to CO2

H

C

m/z 3 (DH)

13 %

50 %

2 (in H2) 0.03 % ca. 10 %

1 (in CO2) 1.08 % 100 %

300 % (e.g. 6 H, 2 C) 150 % 4.16 % 0.42 %

Theoretical required sample amount for δD 240 x higher than for δ13C if same precision as for δ13C is required

22

Low Energy Helium Ions Under continuous flow conditions 4He is about 107 times more abundant than HD

Due to collisions He ions with less energy than 3 kV would fall into the m/z 3 cup

magnet

m/z 4

m/z 3 (HD) m/z 2 (H2) ion source

23

universal triple collector for N2, CO, O2,CO2, SO2

Contribution of He+ Ions at m/z 3

300

10 He abundance at m/z 3 [V]

without retardation lens with retardation lens He abundance at m/z 3 [V

250

200

150

8 6 4 2 0 0

100

0.02

0.04

0.06

0.08

0.1

He flow [ml/min]

50

0 0

0.1

0.2

0.3

He flow [ml/min]

24

0.4

0.5

The production of low energy He ions is related to the He flow into the ion source

Energy Filter - Retardation Lens HD Collector - Rejection of 4He+ ions by a retardation lens entrance slit 4

Ion Kinetic Energy [kV]

HD

retardation lens

ground ~Vacc 3

HD+ ∆E>400 V

4

0

25

+

He+

He+

secondary electron suppressor

-100 V

Faraday cup

ground

1012 Ω

Energy Filter Complete absence of 4He at m/z 3 cup with Energy Filter

26 E 0998 032 PO

H3+ Factor H3+ Factor (K) = 6.01 ppm / nA

[H33++] = [H22]22 • K

30 V (nA)

227 mV (pA) 61 µV (fA) 0.31 µV H33++ (0.5 %) 27

m/z 3

12 mV (pA) 5.4 mV H33++ (45 %)

H3+ Factor – Linearity 6 y = 0.2x [‰ / V] at H3+ 6.010621

5

δD [‰]

4

30 V (nA)

3 0.05 ppm

2 1

y = -0.01x [‰ / V] at H3+ 6.06773

227 mV (pA)

0 -1 -2 0

5000

10000

15000

20000

Intensity [mV]

28

25000

30000

35000

Requirements to δ2H irm-GC/MS ¾ Quantitative Conversion ƒ Empty reactor tube at ≥ 1400 °C ¾ GC Performance ƒ Inner diameter of recommended GC columns: 0.25 mm ¾ Sensitivity ƒ GC flow: 0.8 – 1.0 ml/min Ì Optimal linear velocity ƒ High He flow into IRMS: 0.4 ml/min Ì Optimal open-split ratio ¾ Precision and Stability ƒ Long-term stability of the H3+ factor ¾ Linearity

29

High Temperature Conversion

y

Cn Hx Oy

GC/TC

x/2

>1400 °C n-y

30

CO

C

δ2H

H2

irm GC/MS

HD

H2

0.015 % 99.985 %

High Temperature Conversion High Temperature Conversion Interface

31

High Temperature Conversion Production of methane and hydrogen from propane as a function of temperature 10

hydrogen

9 8

Signal (V)

7 6

propane

5 4

1440 °C

3 2

methane

1 0 600

800

1000

1200

1400

Temperature (°C)

Chart according to T. Burgoyne et al., Anal. Chem. 1998, 70, 5136-5141 32

Transfer into the Reactor • Metal Connector / Ceramic Reactor – “Standard” F.S. i.d. = 0.25 mm i.d. = 0.32 mm

GC oven < 320 °C

Al2O3

Heater Heater 1450 940 °C°C

critical volume

nowires wires

• Metal Connector / Ceramic Reactor – “Optimized” F.S. i.d. = 0.32 mm

i.d. = 0.5 mm

GC oven < 320 °C

33

Al2O3

Heater Heater 1450 940 °C°C

ca. 0.5 cm polyimide are burnt off

nowires wires

δD of Free Steroids (underivatized) O

HO

HO

H

No.

O

Etiocholanolone

1 2 3 4 5 6 7 8 Mean-value: Std-deviation:

H

Androsterone

H22 Intensity Intensity (mV) (mV) H

6000 6000 5000 5000

Etiocholanolone Etiocholanolone

4000 4000

Androsterone Androsterone

3000 3000

mass mass 22

2000 2000

mass mass 33

1000 1000 00 820 820

840 840

860 860

880 880

900 900

Time Time (s) (s)

34

920 920

940 940

960 960

δ D/HSMOW [‰]

δ D/HSMOW [‰]

-227.08 -225.79 -225.84 -226.00 -228.90 -225.24 -224.98 -225.61 -226.18 1.26

-332.54 -332.27 -332.44 -332.56 -337.86 -332.94 -331.20 -333.47 -333.16 2.00

Metabolic Studies enriched 0.32 0.30 0.28 0.26 0.24 0.22 0.20 0.18

D/H ratio trace

δ2H of Natural and Enriched

natural

3.50

C16:0 C17:0

3.00

Fatty Acid Methyl Esters

m/z 2 trace [V]

2.50 2.00 1.50

C18:1

1.00 0.50 800

900

Time [sec]

35

1000

1100

1200

FAME

Sample 1

Sample 2

Methyl Palmitate

200 ng

200 ng

C16:0

- 313.6 ‰ ± 5.6 ‰

- 321.8 ‰ ± 3.1 ‰

Methyl Heptadecanoate

200 ng

200 ng

C17:0

- 302.4 ‰ ± 2.7 ‰

- 303.4 ‰ ± 2.7 ‰

Methyl Oleate

40 ng

20 ng

C18:1

21305 ‰ ± 191 ‰

21602 ‰ ± 94 ‰

δ18O by irm-GC/MS

Introduced in 1996

Why δ18O irm-GC/MS? 20 0

Honey

-20

Meteoric Water Line

SMOW

(‰)

-40

δD

Mexico

18

δD = 8δ O + 10

-60

Argentina

Chile

Guatemala

-80

USA

-100

18

δD= 7.35δ O - 254

-120 -140

Canada

H. Avak, MAT Application Lab TC/EA-ConFlo II-delta+XL

-160 -20

0

20 18

δ O SMO W (‰)

37

40

Comparison of δ18O and δ13C Determination Accumulated Effect Intensities of - in relation to m/z 45 (13C) - m/z 45 set to 100 % O

C

Element content

10-50 %

>60 %

Atoms per gas molecule 18O, 13C abundance in M+ Ionization efficiency rel. to CO2

1 (in CO) 0.204 % ca. 70 %

1 (in CO2) 1.08 % 100 %

m/z 30 (CO) 16.66 % (10% O, 60% C) 16.66 % 3.15 % 2.20 %

Theoretical required sample amount for δ18O 45 x higher than for δ13C if same precision as for δ13C is required

38

GC/TC Requirements on δ18O Analysis ¾Capillary Reactor Design ƒ Keep the GC resolution: No peak broadening ¾No Contact to Al2O3 ƒ Inert reactor design ƒ Avoiding of any exchange of oxygen ¾Surplus of Carbon in the Reactor ƒ Conditioning of the reactor ƒ Catalyst: • Principally suitable: Ni (mp 1455 °C) , Pt (mp 1769 °C) • Unsuitable: Fe, Co ¾Quantitative High Temperature Conversion ƒ Reactor temperature: > 1250 °C ¾No Memory Effects 39

Challenges Factors influencing the δ18O Determination

40

-

Backgrounds - N2, O2, CO2, H2O (leaks, He quality) - Column Bleed

-

Derivatization - Isotope Dilution - O - Exchange

-

Compounds containing N - N2 contamination on CO masses

High Temperature Conversion Interface

1250 °C

in standby Capillary reactor design ¾ Pt shielded ¾ No contact to Al2O3 ¾ Inert tube ¾ H2/He make-up gas ¾ Surplus of carbon (conditioning)

41

δ18O Analysis of Vanillin Direct after installation of a new reactor

26

δ1818 OO(‰) (‰)

24 22 20 18

Conditioning (6 Runs)

Average:

24.52 ‰

n:

26

Std. Dev:

0.23 ‰

Specification: 0.80 ‰

16 1

4

7

10

13

16

19

22

Number of Injection Operator: Peter Weigel 42

25

28

31

GC-IRMS Methodology Short Backflush Time = better GC/TC conditions

43

IRMS: Interface: GC: Column: Flow: Injector:

Delta plus XL GC/C&TC HP 6890 Ultra 1, 25 m x 0.32 mm, df= 0.52 µm 1.2 ml/min, Constant Flow 220 ˚C, Split/Splitless

Backflush off

CO Ref. gas

Backflush on

Solvent Peak

CO Ref. gas

CO Ref. gas

18O δδ18 O of of flavor flavor compounds compounds

GC/TC - TC/EA – Cross Calibration δ 18OSMOW [‰ ]

GC/TC

18O δδ18 O of of

flavor flavor compounds compounds

No. 1 2 3 4 5 6 7 8 9 10 Mean-value: Std-deviation:

Vanillin 9.09 9.11 9.17 8.52 9.21 9.24 9.19 9.34 9.20 8.88 9.10 0.23

β− Ionone 17.49 17.47 17.77 18.03 17.73 17.89 17.61 17.92 17.23 17.97 17.71 0.26

Frambinone 14.02 13.97 14.20 14.15 14.19 14.08 14.12 14.37 14.34 14.28 14.17 0.13

9.30 0.04

15.90 0.07

14.12 0.13

TC/EA Mean-value: Std-deviation:

¾

Short Backflush Time

¾ 44

¾

Inert reaction tube at 1250 °C

Low and constant He flow

Isotope Fingerprinting of Tequila -11.0

δ13C:

13 δ CSMOW (‰) Ethanol

GC-C/TC DELTA+XL Analyst: Dr. D. Juchelka Headspace sampling 4/2000

-11.5

100 %Tequila

Sugar Cane -12.0

Enzymatic Fractionation of Isotope -12.5 Ratios 0

Mixed

5

10

18 δ OSMOW (‰) Ethanol

45

δ18O:

15

Physical Fractionation of Isotope Ratios

References for Compound-Specific Isotope Analysis

Preparatory Chemistry Abidi, S. L. (2001). "Chromatographic analysis of plant sterols in foods and vegetable oils." Journal of Chromatography A 935(1-2): 173-201. Bligh , E.G. and W.J. Dyer (1959) "A Rapid Method of Total Lipid Extraction and Purification." Canadian Journal of Biochemistry and Physiology 37: 911-917 Christie, W. W. (1976) Lipids Analysis. Pergamon Press, New York. Manirakiza, P. et al (2001) "Comparative Study on Total Lipid Determination using Soxhlet, Roese-Gottlieb, Bligh & Dyer and Modified Bligh & Dyer Extraction Methods." Journal of Food Composition and Analysis 14, 93-100 Myher, J. J. and A. Kuksis (1995). "General Strategies in Chromatographic Analysis of Lipids." Journal of Chromatography B-Biomedical Applications 671(1-2): 3-33. Randall, R.C. et al (1991). “Evaluation of Selected Lipid Methods for Normalizing Pollutant Bioaccumulation.” Environment Toxicology and Chemistry 10: 1431-1436 Ruizgutierrez, V. and L. J. R. Barron (1995). "Methods for the Analysis of Triacylglycerols." Journal of Chromatography BBiomedical Applications 671(1-2): 133-168. Smedes, F. (1999). "Determination of total lipid using non-chlorinated solvents." Analyst 124(11): 1711-1718. Smedes, F. and T. K. Askland (1999). "Revisiting the development of the Bligh and Dyer total lipid determination method." Marine Pollution Bulletin 38(3): 193-201. Touchstone, J. C. (1995). "Thin-Layer Chromatographic Procedures for Lipid Separation." Journal of Chromatography BBiomedical Applications 671(1-2): 169-195. GC-IRMS Instrumentation and Data Analysis Barrie A., Bricout J., and Koziet J. (1984) Gas-Chromatography - Stable Isotope Ratio Analysis at Natural Abundance Levels. Biomedical Mass Spectrometry 11(11), 583-588. Becchi M., Aguilera R., Farizon Y., Flament M. M., Casabianca H., and James P. (1994) Gas-Chromatography Combustion Isotope Ratio Mass-Spectrometry Analysis of Urinary Steroids to Detect Misuse of Testosterone in Sport. Rapid Communications in Mass Spectrometry 8(4), 304-308. Bernreuther A., Koziet J., Brunerie P., Krammer G., Christoph N., and Schreier P. (1990) Chirospecific Capillary GasChromatography (Hrgc) and Online Hrgc-Isotope Ratio Mass-Spectrometry of Gamma-Decalactone from Various Sources. Zeitschrift Fur Lebensmittel-Untersuchung Und-Forschung 191(4-5), 299-301. Brand W. A. (1996) High precision isotope ratio monitoring techniques in mass spectrometry. Journal of Mass Spectrometry 31(3), 225-235. Brand W. A., Tegtmeyer A. R., and Hilkert A. (1994) Compound-Specific Isotope Analysis - Extending toward N-15 N-14 and O-18 O-16. Organic Geochemistry 21(6-7), 585-594. Burgoyne T. W. and Hayes J. M. (1998) Quantitative production of H-2 by pyrolysis of gas chromatographic effluents. Analytical Chemistry 70(24), 5136-5141. Caimi R. J. and Brenna J. T. (1993) High-Precision Liquid Chromatography-Combustion Isotope Ratio Mass-Spectrometry. Analytical Chemistry 65(23), 3497-3500. Caimi R. J. and Brenna J. T. (1995) High-Sensitivity Liquid-Chromatography Combustion Isotope Ratio MassSpectrometry of Fat-Soluble Vitamins. Journal of Mass Spectrometry 30(3), 466-472. Docherty, G., Jones. V. and Evershed R.P. (2001) Practical and theoretical considerations in the gas chromatography/combustion/isotope ratio mass spectrometry δ13c analysis of small polyfunctional compounds. Rapid Commuications in Mass Spectrometry 15, 730-738. Ellis L. and Fincannon A. L. (1998) Analytical improvements in irm-GC/MS analyses: Advanced techniques in tube furnace design and sample preparation. Organic Geochemistry 29(5-7), 1101-1117. Engel M. H., Macko S. A., and Silfer J. A. (1990) Carbon Isotope Composition of Individual Amino-Acids in the Murchison Meteorite. Nature 348(6296), 47-49. Evershed R. P., Arnot K. I., Collister J., Eglinton G., and Charters S. (1994) Application of Isotope Ratio Monitoring GasChromatography Mass-Spectrometry to the Analysis of Organic Residues of Archaeological Origin. Analyst 119(5), 909-914. Fantle M.S., Dittel, A.I., Schwalm S.M., Epifanio, C.E. and Fogel, M.L. (1999) A food web analysis of the juvenile blue crab, Callinectus sapidus, using stable isotopes in whole animals and individual amino acids. Oecologia 120, 416426. Gaschnitz R., Krooss B. M., Gerling P., Faber E., and Littke R. (2001) On-line pyrolysis-GC-IRMS: isotope fractionation of thermally generated gases from coals. Fuel 80(15), 2139-2153. Guo Z. K., Luke A. H., Lee W. P., and Schoeller D. (1993) Compound-Specific Carbon-Isotope Ratio Determination of Enriched Cholesterol. Analytical Chemistry 65(15), 1954-1959.

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Physiology of isotope fractionation in algae and cyanobacteria. In: Lajtha, K. and Michener, B. (Eds.), Stable Isotopes in Ecology, Blackwell Scientific Publications, Oxford, UK, 187-221. Grice K., Schaeffer P., Schwark L. and Maxwell J.R. (1997) Changes in palaeoenvironmental conditions during deposition of the Permian Kupferschiefer (Lower Rhine Basin, N.W. Germany) from variations in isotopic compositions of biomarker components. Org Geochem 26 677-690.

Grice, K., Schouten, S., Nissenbaum, A., Charrach, J., Sinninghe Damsté, J. S., 1998. Isotopically heavy carbon in the C21 to C25 regular isoprenoids in halite-rich deposits from the Sdom Formation, Dead Sea Basin, Israel. Org. Geochem. 28, 349-359. Hartgers W. A., Sinninghe Damste J. S., Requejo A. G., Allan J., Hayes J. M., and de Leeuw J. W. (1994) Evidence for only minor contributions from bacteria to sedimentary organic carbon, Nature 369, 224-227. Hayes, J.M., Takigiku, R., Ocampo, R., Callot, H.J., Albrecht, P., 1987. Isotopic compositions and probable origins of organic molecules of the Eocene Messel shale. Nature 329, 48-51. Hayes J. M., Popp B. N., Takigiku R., and Johnson M. W. (1989) An isotopic study of biogeochemical relationships between carbonates and organic carbon in the Greenhorn Formation. Geochimica et Cosmochimica Acta 53, 29612972. Hayes J. M., Freeman K. H., Popp B. N., and Hoham C. 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van Kaam-Peters, H. M. E., Schouten, S., Koster, J. and Sinninghe Damsté, J. S. 1998: Controls on the molecular and carbon isotopic composition of organic matter deposited in a Kimmeridgian euxinic shelf sea: Evidence for preservation of carbohydrates through sulfurisation. Geochimica Cosmochimica Acta 62, 3259-3283.

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