2. 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.

3. Ionization 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

4. Ionisation Methods Electron Impact 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 -

5. Best combined with an upstream separation device, e.g., liquid chromatography or capillary electrophoresis Analyzers for MS/MS - Triple Quadrupole collision cell Q2 Q1

6. 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 analyzers

7. 2D GC-ToFMS

8. Tandem MS (MS/MS) MS/MS instruments select a single ion from a spectrum obtained by MS1 58.2 134.6 178.8 121.2 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

9. Tandem Mass Spectrometry Scan 1708 LC Scan 1707 MS1 MS/MS Ion Source MS-1 collision cell MS-2

10. Analyzers: Quadrupole vs. ToF Elemental Composition Report Mass Calc. Mass mDa ppm Formula 29.0027 29.0027 0.0 -1.4 C H O 29.0140 -11.3 -388.7 H N 2 29.0265 -23.8 -822.3 C H 3 N 29.0391 -36.4 -1255.9 C 2 H 5 accurate mass by ToF ToF - high resolution - better peak separation Quadrupole - poor resolution

11. ToF: resolves co-eluting compounds

12. Peak finding software - mass spectral deconvolution (further resolves coeluting and/or low abundant analytes) Linear dynamic range: 10 4 -10 6 2D GC-MS

13. 2D GC - separates coeluting peaks in 2 nd dimension 1D GC - Analytes Coelute in complex samples

14. Spectral comparison with libraries chromatogram Mass-spectrum Library hits Selected peak Spectral match NIST, Wiley

15. Comparison of EI and FI spectra EI+ FI+ Methyl Stearate Fragmentation Intact ion 56 43 12 13 31 detective work CH3(CH2)16COOCH3

16. Challenges GC/MS – a routine technology - Challenges (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.

17. (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

18. QuantificationRelationship 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.

19. Analytical and Biological Variations Considerable differences in amounts between individual plants! Considerable analytical variation! Considerable variation even within a single organ (e.g., tip and base of leaf)! Considerable variation over time (diurnal, developmental)!

20. 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, and those for 9–13 increased by a factor of 50. Values are ion intensity (cps), calculations employed the summed ion intensity for 180 scans and are presented 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

21. 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.

22. (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.

23. (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.

24. Types of database for metabolomics Databases storing detailed metabolite profiles, including raw data and detailed metadata (i.e. data about the data) [73]. Single species-based databases that will store ‘relatively’ simple metabolite profiles [73]. Databases storing complex metabolite profile data from many species in many different physiological states [73]. Databases listing all known metabolites for each biological species.With suitable metadata, these databases could be extended to contain temporal and spatial information. Databases such as KEGG [74], compiling established biochemical facts. Databases that integrate genome and metabolome data with an ability to model metabolic fluxes [75,76]. References in Goodacre et al. (2004)

25. 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 be predicted by using constraint-based analysis of a genome- scalereconstructed 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

26. Deposited on web - April 3 Metabolomics of volatile signals in Inter-species (and Inter-kingdom) Communication.

27. Plant Volatiles – Chemical Defense Mechanisms Symbiotic, antibiotic, and defense relationships Acacias – sugar composition adjusted 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.

28. predator’s Plant predator predator Plant-Herbivore-parasiticInsect “Tri-trophic” Interactions

29. Schnee et al. (2006) The products of a single maize sesquiterpene synthase form a volatile defense signal that attracts natural enemies of maize herbivores. PNAS 103, 1129 “Tri-trophic” Interactions maize, cotton, etc. e.g. Spodoptera littoralis parasitic wasps feeding damage forced regurgitating

30. JA biosynthesis – abbreviated VOC – volatile organic compounds From plant signaling to insect response via Farmer & Ryan (early 90s) – volatile signals from plant to plant Jasmonates Terpenes

31. 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-hexenol 5- linalool; 9 – β-farnesene; 10 - nerolidol C6 C10 C15 10 9 5 1 C15

32. jasmone indole Feeding on cotton 1 st day 3 rd day linalool pinene farnesene Change in composition & amount over time of attack. Signaling compounds (or degradation products) are present at low levels only.

33. Emitted compounds by cotton Start - 2 p.m. 5 caterpillars on 6w-old cotton A – LOX products from cotton B – constitutive cotton volatiles C – induced compounds in cotton

34. Emissions by infected corn over time LOX-products from maize Induced complex compounds Leaves scratched, then added caterpillar regurgitate Recognition – timing, composition and nature of compounds

35. Signals in caterpillar “spit” induceplantbiodefenseWMD by recruiting allied forces Based on Isoprene & Isoprenoid metabolism acetoacetyl-CoA + acetyl-CoA > HMG-CoA > mevalonate >>>> isopentenyl-PP C4 + C2 > C6 > C5 + CO 2

36. Isoprene Isopentenyl-PP Dimethylallyl-PP Geranyl-PP C5

37. C20 - Geranyl-geranyl-PP C15 – farnesyl-PP C25 – Sesterterpines > abundant, non-volatile C30 - Triterpenes > steroid source structure, abundant, non-volatile C40 - Carotenes > carotenoid source structure, abundant, non-volatile 6β-acetoxy-24-methyl- 12, 24-dioxoscalaran-25-al (pacific sponge) Sesquiterpene type – phytol (retinol, retinal) Cyclic sesq. (cadinene)

38. Induction 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. maize

39. bergamotene farnesene sesquiphellandrene Gene to Product maize

40. What happens when the gene is expressed in Arabidopsis ? A single transgene/ protein generates the entire spectrum! … but will the wasps know?

41. Let the wasps chose!

42. Wt and transformed Arabidopsis – 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

43. One could use the contraption for other experiments Western Corn rootworm - Diobrotica v. virgifera - parasitic nematodes A major problem in US agriculture – is there a natural biodefense strategy (i.e., no chemicals)? Metabolomics to the Rescue!

44. One could use the contraption for other experiments Maize Western Corn rootworm Nematode Trimorphic interaction involving a entomopathogenic nematode Rasmann et al. (2005) Nature 434, 731. trap

45. Experiments similar to the wasp predation experiment Identification of attractant Why is US maize not protected Does it work in the field Isoprenoids in the soil? 2 – β-caryophyllene

46. Attraction to / by authentic β-caryophyllene Olfactometer arms spiked with authentic β-caryophyllne

47. Absence of β-Car. in some (mostly US) maize lines

48. Reproductive success and β-caryophyllene Pactol – low amounts Graf – high amounts healthy fungal infections nematode presence All six containers received the same number of nematodes

49. Added β-caryo. Emergence of adults is reduced when nematodes are attracted

50. β-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)

51. Sesquiterpene hydrocarbons in maize A – leaf inducible, B – ubiquitous; C – root specific

52. 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