The first part presents slides that had been

on the handout for March 28;

We will go through these fast!

I will deposit the modified version on the web later.

Ionization techniques for GCIonization techniques for GC

• Electron Impact (EI) (-/+)

library searchable spectra, fragmentation, most versatile

• Chemical Ionisation (CI+/-)molecular weight information

• Desorption Chemical Ionisation (DCI)

thermally labile compounds, molecular weight information

• Field Ionisation (FI) / Field Desorption

soft ionisation, molecular weight information, reduced background

Ionisation MethodsIonisation Methods

EElectronlectron I Impactmpact

• Ionisation via bombardment of the sample with a

stream of high energy electrons

• Impact of the high energy electrons

with the vaporised sample molecules causes ejection of

(multiple) electrons from the analyte

and a radical cation M+• is formed

M + e- M+• + 2e-

Best combined with an upstream separation device, e.g., liquid chromatography or capillary electrophoresis

Analyzers for MS/MS - Triple QuadrupoleAnalyzers for MS/MS - Triple Quadrupole

collision cell

Q2Q1

Time Of Flight

For GC or LC

The time needed for an accelerated ion to transverse a field-free drift zone is directly related to the mass of an ion / peptide. The longer the flight path the better the resolution.

Field free drift region

Ionisation of peptides

Detection of ions

Ion acceleration by high voltage

Mass analyzersMass analyzers

2D GC-ToFMS2D GC-ToFMS

Tandem MS (MS/MS)Tandem MS (MS/MS)

MS/MS instruments select a single ion from a spectrum obtained by MS1

58.2134.6

178.8

121.2

This ion is fragmented by collision with an inert gas

58.2134.6178.8121.2

daughter ion scan

The mass of the secondary fragment ions is measured by MS2. For peptides, the amino acid sequence is deduced from the mass differences of the ions

primary scan

Tandem Mass SpectrometryTandem Mass Spectrometry

RT: 0.01 - 80.02

5 10 15 20 253 035 40 45 50 55 60 65 70 75 80Time (min)

0

10

20

30

40

50

60

70

80

90

100

Relati

ve Ab

undanc

e

13891991

1409 21491615 1621

14112147

161119951655

15931387

21551435 19872001 21771445 1661

19372205

1779 21352017

1313 22071307 23291105 17071095

2331

NL:1.52E8

Base Peak F: + c Full ms [ 300.00 - 2000.00]

S#: 1708 RT: 54.47 AV: 1 NL: 5.27E6T: + c d Full ms2 638.00 [ 165.00 - 1925.00]

200 400 600 800 1000 1200 1400 1600 1800 2000

m/z

0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

Rel

ativ

e A

bund

ance

850.3

687.3

588.1

851.4425.0

949.4

326.0524.9

589.2

1048.6397.1226.9

1049.6489.1

629.0

Scan 1708

LCLC

S#: 1707 RT: 54.44 AV: 1 NL: 2.41E7F: + c Full ms [ 300.00 - 2000.00]

200 400 600 800 1000 1200 1400 1600 1800 2000

m/z

0

5

10

15

20

25

30

35

40

45

50

55

60

65

70

75

80

85

90

95

100

Rel

ativ

e Ab

unda

nce

638.0

801.0

638.9

1173.8872.3 1275.3

687.6944.7 1884.51742.1122.0783.3 1048.3 1413.9 1617.7

Scan 1707

MS1MS1

MS/MSMS/MSIon

Source

MS-1collision

cell MS-2

Analyzers: Quadrupole Analyzers: Quadrupole vs.vs. ToF ToF

Elemental Composition ReportMass Calc. Mass mDa ppm Formula29.0027 29.0027 0.0 -1.4 C H O 29.0140 -11.3 -388.7 H N2 29.0265 -23.8 -822.3 C H3 N 29.0391 -36.4 -1255.9 C2 H5

accurate mass

by ToF

ToF

- high resolution

- better peak separation

Quadrupole

- poor resolution

ToF:ToF: resolves co-eluting compounds resolves co-eluting compounds

Peak finding software

- mass spectral deconvolution

(further resolves coeluting and/or low abundant

analytes)

Linear dynamic range: 104-106

2D GC-MS

2D GC- separates coeluting peaks in 2nd dimension

1D GC- Analytes Coelute in

complex samples

Spectral comparison with librariesSpectral comparison with libraries

chromatogram

Mass-spectrum

Library hits

Selected peak

Spectral match

NIST, Wiley

Comparison of EI and FI spectraComparison of EI and FI spectra

60 80 100 120 140 160 180 200 220 240 260 280 300m/z0

100

%

0

100

%

74.04

55.05

87.05

75.04

298.29255.23143.11

129.09101.06

199.17

185.16157.12 213.19 241.22267.27

269.25299.29

298.29

299.30

300.31

EI+EI+

FI+FI+Methyl StearateMethyl Stearate

Fragmentation

Intact ion

56

56

56

43

12

13

31

det

ecti

ve w

ork

CH3(CH2)16COOCH3

GC/MS – a routine technology - ChallengesChallenges

(1) Automation of sample preparation, wet chemistry, data processing after

an increasing number of data is obtained,

(2) Extension of the analytical scope – e.g., combined analyses of a sample

using multiple platforms,

(3) Combined analyses with proteome and transcriptome studies

(4) Profiling trace compounds, or signaling molecules in the presence of (very) abundant ‘bulk’ metabolites,

(5) Increasing accuracy in multi-parallel metabolite quantification

(6) Combining metabolite and flux analyses

(7) Establishing quantitative repeatability, arrive with an unambiguous nomenclature,

(8) Comparability between analytical platforms, and of work done by different labs.

(a) Typical ES- mass spectrum for polar extract green tomato (L. esculentum) fruit. Major identifiable peaks: 179 (hexose sugars, [M)H])), 191 (citric/iso-citric acid, [M)H])), 215 (hexose sugars, [M+Cl])), 237 (HEPES buffer, [M)H])), 475 (HEPES buffer, [2M)H])).

(b) Typical ES+ mass spectrum for polar extract of green tomato (L. esculentum) fruit. Major identifiable peaks: 147 (glutamic acid, [M+H]+),203 (hexose sugars [M+Na]+), 219 (hexose sugars, [M+K]+), 239 (HEPES buffer, [M+H]+), 261 (HEPES buffer, [M+Na]+), 277 (HEPES buffer, [M+K]+).

Dunn et al. (2005) Evaluation of automated electrospray-TOF MS for metabolic fingerprinting of the plant metabolome. Metabolomics 1, 137.

Some metabolites are very abundant – how to quantify, and how to analyze low abundance

Quantification Relationship between concentration of metabolite standard added to a plant extract and molecular ion intensity.

(b) ES+; open circle - alanine, open diamond - proline, closed triangle - GABA, closed diamond - aspartate, closed square - leucine.

(a) ES-; open circle - pyruvate, open triangle - oxalate, closed circle - fumarate, open triangle - oxalate, closed square - malate, open diamond - ascorbate.

Analytical and Biological Variations

Considerabledifferences in amountsbetween individual plants!

Considerable analytical variation!

Considerablevariation even within a singleorgan (e.g., tip and base of leaf)!

Considerable variation over time (diurnal, developmental)!

Lycopersicon esculentum - white fill; L. pennellii - grey fill;

1 malic acid, 2 citric acid, 3 GABA, 4 C4 sugars, 5 hexoses, 6 pyruvic acid, 7 fumaric acid, 8 ascorbic acid, 9 valine, 10 leucine/isoleucine, 11 asparagine, 12 glutamine, 13 tyrosine.

For clarity, the responses for 3–8 are increased by a factor of 10, andthose for 9–13 increased by a factor of 50. Values are ion intensity (cps), calculations employed the summed ion intensity for 180 scans and arepresented as the means of three replicate extracts ± standard deviation.

Peak intensity for 13 selected metabolite ions measured in each of three fruit extracts of two tomato species

Technologies for metabolome analysis. General strategies for metabolome analysis. CE, capillary electrophoresis; DIESI, direct-infusion

ESI, which can be linked to Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS); NMR, nuclear magnetic resonance; RI, refractive index detection; UV, ultraviolet detection.

Goodacre et al (2004) Trends Biotech. 22, 245.

(b) Example of an FT-IR spectrum of a biofluid. In this experiment, 10 ml of rat urine was dried and analysed on a Bruker IFS66 instrument between 400 and 600 cm21, with 4 cm21 resolution and 256 co-adds.

(c) Capillary gas chromatography–time-of-flight–mass spectrometry (GC-TOF-MS) analysis of human serum. In a 15 min run, 722 peaks could be discriminated.

Types of database for metabolomics

• Databases storing detailed metabolite profiles, including raw dataand detailed metadata (i.e. data about the data) [73].

• Single species-based databases that will store ‘relatively’ simplemetabolite profiles [73].

• Databases storing complex metabolite profile data from manyspecies in many different physiological states [73].

• Databases listing all known metabolites for each biologicalspecies.With suitable metadata, these databases could be extendedto contain temporal and spatial information.

• Databases such as KEGG [74], compiling established biochemicalfacts.

• Databases that integrate genome and metabolome data with anability to model metabolic fluxes [75,76].

References in Goodacre et al. (2004)

73. Mendes, P. (2002) Emerging bioinformatics for the metabolome. Brief. Bioinform. 3, 134–145

74. Kanehisa, M. et al. (2002) The KEGG databases at GenomeNet.Nucleic Acids Res. 30, 42–46

75. Famili, I. et al. (2003) Saccharomyces cerevisiae phenotypes can bepredicted by using constraint-based analysis of a genome-

scale reconstructed metabolic network. Proc. Natl. Acad. Sci. U. S. A. 100, 13134–13139

76. Fo¨rster, J. et al. (2003) Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network. Genome Res. 13, 244–253

Deposited on web - April 3

Metabolomics of volatile signals in Metabolomics of volatile signals in

Inter-species (and Inter-kingdom) Inter-species (and Inter-kingdom)

Communication. Communication.

Plant Volatiles – Chemical Defense Mechanisms Plant Volatiles – Chemical Defense Mechanisms

Symbiotic, antibiotic,

and defense

relationships

Acacias –

sugar compositionadjusted to

desired ant species

Heil et al. (2005) Postsecretory hydrolysis of nectar sucrose and specialization in ant/plant mutualism. Science 308 (5721)

Plants provide sugars for which particular ant species have no catabolic enzyme.

predator’sPlant predator

predator

PlantPlant

--

HerbivoreHerbivore

--

parasiticparasiticInsectInsect

““Tri-trophic” InteractionsTri-trophic” Interactions

Schnee et al. (2006) The products of a single maizesesquiterpene synthase form a volatile defensesignal that attracts natural enemies of maize herbivores. PNAS 103, 1129

““Tri-trophic” InteractionsTri-trophic” Interactions

maize, cotton, etc.

e.g. Spodoptera littoralis

parasitic wasps

feeding damage

forced regurgitating

JA biosynthesis – abbreviated JA biosynthesis – abbreviated

VOC – volatileorganic compounds

From plant signaling to insect response via

Farmer & Ryan (early 90s) – volatile signals from plant to plant

Jasmonates Terpenes

Plants respond to caterpillar feeding Plants respond to caterpillar feeding Turlings TCJ, Loughrin JH, McCall PJ, Rose USR,

Lewis WJ, Tumlinson JH (1992) How caterpillar-damaged plants protect themselves by attracting parasitic wasps. PNAS 92, 4169.

Healthy, undamaged maize seedlings

6 hours after start of caterpillar feeding

IS1,2 – internal standards

Some peak IDs (LC-MS): 1,2,3 – 3-hexenal; 2-hexenal; 3-hexenol5- linalool; 9 – β-farnesene; 10 - nerolidol

C6

C10

C15

10

9

5

1

C15

jasmone

indole

Feeding on Feeding on cottoncotton

1st day

3rd day

linalool

pinene

farnesene

• Change in composition & amount over time of attack.• Signaling compounds (or degradation products)

are present at low levels only.

Emitted compounds by Emitted compounds by cottoncotton

Start - 2 p.m.5 caterpillars on 6w-old cotton

A – LOX products from cotton

B – constitutive cotton volatiles

C – induced compounds in cotton

Emissions by infected corn over time Emissions by infected corn over time

LOX-products from maize

Induced complexcompounds

Leaves scratched, then addedcaterpillar regurgitate

Recognition – timing, composition and nature of compounds

Signals in Signals in caterpillar “spit”caterpillar “spit”

induce induce plantplant

biodefensebiodefenseWMDWMD

by recruiting by recruiting allied forcesallied forces

Based onBased on

Isoprene &Isoprene &

Isoprenoid metabolismIsoprenoid metabolism

acetoacetyl-CoA + acetyl-CoA > HMG-CoA > mevalonate >>>> isopentenyl-PP

C4 + C2 > C6 > C5 + CO 2

Isoprene

Isopentenyl-PP

Dimethylallyl-PP

Geranyl-PP

C5 C5

C20 - Geranyl-geranyl-PPC20 - Geranyl-geranyl-PP

C15 – farnesyl-PPC15 – farnesyl-PP

C25 – Sesterterpines > abundant, non-volatileC25 – Sesterterpines > abundant, non-volatile C30 - Triterpenes > steroid source structure, abundant, non-volatileC30 - Triterpenes > steroid source structure, abundant, non-volatile

C40 - Carotenes > carotenoid source structure, abundant, non-volatileC40 - Carotenes > carotenoid source structure, abundant, non-volatile

6β-acetoxy-24-methyl- 12, 24-dioxoscalaran-25-al

(pacific sponge)

Sesquiterpene type – Sesquiterpene type – phytol (retinol, retinal)phytol (retinol, retinal)

Cyclic sesq.(cadinene)

Induction of sesquiterpene synthasesInduction of sesquiterpene synthases

Wasps fly straight to damaged leaf from downwind, not to a wounded leaf, but to wounded leaves treated with regurgitated midgut sap of insect.

maizemaize

bergamotene

farnesene

sesquiphellandrene

Gene to ProductGene to Product

maizemaize

What happens when the gene is expressed in What happens when the gene is expressed in ArabidopsisArabidopsis ? ?

A single transgene/ protein generates the entire spectrum!

… … but will the wasps know?but will the wasps know?

Let the wasps chose! Let the wasps chose!

Wt and transformed Wt and transformed ArabidopsisArabidopsis – wasps in central compartment – wasps in central compartment

wt

tr

P < 0.01

• naïve wasps

• trained on Arabidopsis

• trained on maize

Side result – wasps must learn by

trial & error, i.e.,there are other cues;signals that connect

wasp & caterpillar

One could use the contraption for other experimentsOne could use the contraption for other experiments

WesternCorn rootworm

- Diobroticav. virgifera

-parasitic

nematodes

A major problem in US agriculture – is there a natural biodefense strategy (i.e., no chemicals)?

Metabolomicsto the

Rescue!

One could use the contraption for other experimentsOne could use the contraption for other experiments Maize

WesternCorn rootworm

Nematode

Trimorphic interaction involving a entomopathogenic nematode

Rasmann et al. (2005)Nature 434, 731.

trap

Experiments similar to the waspExperiments similar to the wasppredation experimentpredation experiment

• Identification of attractant

• Why is US maize not protected

• Does it work in the field

• Isoprenoids in the soil?

2 – β-caryophyllene

Attraction to / by authentic Attraction to / by authentic

ββ-caryophyllene-caryophyllene

OlfactometerOlfactometer arms spiked with arms spiked with

authentic authentic ββ-caryophyllne-caryophyllne

Absence of β-Car.

in some (mostly US)

maize lines

Reproductive success and Reproductive success and ββ-caryophyllene-caryophyllene

Pactol – low amountsGraf – high amounts

healthy

fungal infections

nematode presence

All six containers receivedAll six containers receivedthe same number of nematodesthe same number of nematodes

Added β-caryo.

Emergence of adults is reduced Emergence of adults is reduced

when nematodes are attractedwhen nematodes are attracted

ββ-caryophylline diffuses readily (at least in and out of sand)-caryophylline diffuses readily (at least in and out of sand)

A - Detection in a column of wet sand 10 cm from release point

B – detection in air space above a column of sand

(note the scale)

Sesquiterpene hydrocarbons in maizeSesquiterpene hydrocarbons in maize

A – leaf inducible, B – ubiquitous; C – root specific

Terpene synthases in maize Terpene synthases in maize

• Heterologous expression• GC-MS with isotopic tracers• GC-MS of different lines

• Mutational analysis

Sesquiterpene spectrum as affected by mutational analysis of the gene