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«Forum für Lebensmittelsicherheit» Waldbronn 30/31 Januar 2013 Spezifische, quantitative und metabolomische Analysentecniken für Marine Biotoxine mit dem Agilent Q-ToF 6540 Philipp Hess 1 Thomas

1 «Forum für Lebensmittelsicherheit» Waldbronn 30/31 Januar 2013 Spezifische, quantitative und metabolomische Analysentecniken für Marine Biotoxine mit dem Agilent Q-ToF 6540 Philipp Hess 1 Thomas Glauner 2, Bernhard Wüst 2, Manoëlla Sibat 1, Florence Mondeguer 1, Zita Zendong 1 1 Laboratoire Phycotoxines IFREMER Nantes - France 2 Agilent Technologies R&D Waldbronn - Germany

Cooperation agreement started in late 2011 based on: Agilent loan of Q-ToF 6540 Agilent providing technical expertise Ifremer providing staff time and scientific expertise on marine biotoxins Main

2 Cooperation agreement started in late 2011 based on: Agilent loan of Q-ToF 6540 Agilent providing technical expertise Ifremer providing staff time and scientific expertise on marine biotoxins Main objectives of the research project: Development of a rapid, quantitative method of detection for marine biotoxins Development and validation of a work-flow for screening and metabolite ID Development and validation of a database and library for marine biotoxins Agilent Europe: John Lee Agilent Germany: Thomas Glauner Bernd Wüst Agilent France: Jean-Luc Desvallée Maxime Grives Gwenolé Guillou 2

3 Content Context Development of a quantitative, rapid method for marine biotoxins using full scan Q-ToF mass spectrometry Full scan techniques Chromatographic developments Development of a database and library for marine biotoxins Databases (collection of molecular formulae) Libraries (database plus structures, spectra and metadata) Home-made versus commercially available tools Metabolomic techniques in chemotaxonomy and the elucidation of unknowns (dereplication) Metabolome of a sample Metabolomes of micro-algae (indivudual, comparative, chemotaxonomy) Standardisation of work-flow Linking dereplication work-flow to miniaturised bioassays Conclusion 3

4 Biodiversity = Chemodiversity

Unknown toxins France 2003 2008 (as detected per mouse

5 Unknown toxins France (as detected per mouse bioassay for lipophilic toxins) 27 % of unexplained mouse bioassays

6 European or global perspective: Europe is a single market, hence all toxins encountered in Europe must be monitored Europe imports shellfish from a wide variety of third countries, hence an even larger, virtually global range of toxins must be taken into account for imports (AU, NZ, JP, KO, Thailand, Vietnam, Jamaica, CA, Chile, Peru, Uruguay, Greenland, Morocco, Tunisia and Turkey) Legislative change from mouse bioassay for lipophilic toxins to targeted LC-MS/MS methods as reference requires increased vigilance 6

7 1- Full scan analysis: Example of full scan power MS Mass Hunter software to evaluate molecular and pseudo-molecular ion clusters. Okadaic acid 7

6µm (Phenomenex) Poroshell 120 EC-C18 100*2.1mm 2.

8 Development of fast quantitative method for marine biotoxins Fast LC-MS/MS method tested on: Kinetex C18 100*2.1mm 2.6µm (Phenomenex) Poroshell 120 EC-C18 100*2.1mm 2.7µm (Agilent) Zorbax Extend-C18 50*2.1mm 1.8 µm (Agilent) Zorbax SB C8 50*2.1mm 1.8µm (Agilent) 8

9 9

10 Calibration curves Quantitative rapid method (full scan) Certified standards Six calibration levels R2 > 0,98 Matrix effects remain to be evaluated 10

11 Agilent suite of software PCDL Manager - module Database in construction (currently 275 compounds) All major phycotoxins in Europe Structures created in ChemDraw and then inserted into the PCDL library as.mol-files 11

12 Using LC-HRMS for definitive confirmation of identity: Example of isobaric PnTX-G and SPX-B & 13- dm SPX-D 458 ion is specific to PnTX-G and does not exist for SPXs 12

13 Database development literature search Toxin family Toxin group Abbreviation Compound Number Molecular structure ASP Domoic acid DA 9 9 DSP Okadaic acid & dinophysistoxins OA+DTXs Azaspiracids AZAs 30 / Pectenotoxins PTXs 16 4 Yessotoxins YTXs 31 / Cyanobacteria Oscillatoxins n/a 9 / Cyclic imines (FAT) PSP NSP Gymnodimines GYMs 4 4 Spirolides SPXs Pinnatoxins and Pteriatoxins PnTXs+PterTX s Saxitoxins STXs Tetrodotoxins TTXs 18 / Palytoxins PLTXs 8 1 Brevetoxins PbTXs (BTX) 16 / Pacific Ciguatoxins P-CTXs 27 / Caribbean Ciguatoxins C-CTXs 2 / 13

14 Database development entering spectra LC-MS/MS spectra are reputed to be nonreproducible between instruments of different manufacturers This can be overcome to some extent by acquiring spectra at low, medium and high collision energies We are working with Agilent to establish whether a simple mass indicator can be used to set increasing CEs as a standard approach 14

15 Agilent work-flow for non-targeted analysis 15

Relative Abundance 110 100 90 80 70 60 50 40 30 20

81, 0.01-2.31 T: + c ESI Full ms [50.00-800.

16 Relative Abundance m/z NL: 9.69E2 C 4 H10 O 2 N3: C 4 H10 O 2 N3 p (gss, s /p:40) Chrg 1 R: 20.0 NL: 1.11E #93 RT: 2.46 AV: 1 SB: , T: + c ESI Full ms [ ] Metabolomics Approach: MS n Structure elucidation 1000 s ions Biomarkers? Data retreatment Statistical analyses Fingerprints(LC/ HRMS) Sample Prep intensités rt Also: Fingerprints m/z Footprints Crosstalk 16

17 Examples of algal metabolomes: Alexandrium ostenfeldii 7,232 min 13,19 Didesmethyl-SPX-C (M+H) + = 692,4520

18 Examples of algal metabolomes: Karenia selliformis 6,48 min Gymnodimine A (M+H) + = 508,3433

19 Examples of algal metabolomes: Prorocentrum lima 11,38 min OA (M+H) + = 805, ,71 min DTX1 (M+H) + = 819,4901

20 Examples of algal metabolomes: Pseudo-nitzschia 5,49 min DA (M+H) + 312,1445

Comparative metabolomes: Azadinium obesum AZA1 (M+H) + 842.

4748 Azadinium spinosum AZA1-methyl ester (M+H) + 856.

21 Comparative metabolomes: Azadinium obesum AZA1 (M+H) AZA2 (M+H) AZA? (M+H) Azadinium spinosum AZA1-methyl ester (M+H) features only in A. obesum, 59 features only in A. spinosum, and 95 common features!

23 From metabolomes to chemotaxonomy:

24 From metabolomes to chemotaxonomy:

25 Comparative metabolomes of algal fingerprints and algal footprints Acetone extract of A. spinosum vs A. obesum SPATT A. spinosum vs A. obesum 147 features in SPATT vs. 196 features in A. spinosum 25

16 28 28 58 56 29 289g Masse PnTX G (µg) 614 442 303 237 259 411 276 140

26 Pilot-scale culture of V. rugosum Batch Total Mass of pellet (g) g Masse PnTX G (µg) mg Culture conditions L1 L1 L1* L1 L1 L1* L1 L1 L1 L1 Duration of culture (d) **

$Metabolome of Vulcanodinium rugosum - bioguided fractionation Vulcanodinium$ Metabolomics: Dereplication 1,2 Chemical analysis -Triple quad -Q-ToF Evaluation

Metabolomics: Dereplication 1,2 Chemical analysis -Triple quad -Q-ToF Evaluation

analysis (comparison to large natural product libraries 2 ) (1) Kristian F.

27 Metabolome of Vulcanodinium rugosum - bioguided fractionation Vulcanodinium rugosum Crude extract Fractioning Fractions Biological Screening and Metabolomics: Dereplication 1,2 Chemical analysis -Triple quad -Q-ToF Evaluation of biological activity -Cytotoxicity KB cells -Fly larvae -bacteria Data analysis (comparison to large natural product libraries 2 ) (1) Kristian F. Nielsen et al. J Nat. Prod. (2011) 74, p (2)

$purification of PnTX-G CRUDE (A) (2050 mg) PnTX G Crude extr. DCM-fract.$ $DCM fraction (B) (442 mg; 22% of A) Aqueous phase Aq. MeOH Hexane phase Aq.$

28 Fractionation of sample for polar lipids Scheme of extraction and purification of PnTX-G CRUDE (A) (2050 mg) PnTX G Crude extr. DCM-fract. DCM fraction (B) (442 mg; 22% of A) Aqueous phase Aq. MeOH Hexane phase Aq. MeOH fraction (C) (168 mg; 8% of A) SiO 2 -F2 (73 mg; 43 % of C) SiO 2 -F3 (39 mg; 23 % of C)

$80 60 40 Masse fractions (%) Masse$

29 Evaluation of the activity of algal extracts using cytotoxicity assay Masse fractions (%) Masse PnTX G (%) 20 0 F1bP3 F2bP3 F3bP3 F4bP3 F5bP3

30 Dereplication: database screening results for SiO 2 F3 Vulcanodinium EB DCM MeOHaq SiO2 F3 Pinnatoxin-G

around 15 min per 10 min of full scan data) Name RT m/z

31 Dereplication: SiO 2 F2: Screen against MarinLit (database by Bunt & Munro with > cpds (this process takes around 15 min per 10 min of full scan data) Name RT m/z Score (DB) Diff (DB, ppm) Nakijiquinone A

32 Interestingly Out of the 144 compounds present in these two fractions, we were able to identify 45 compounds applying a filter of 5 ppm, or 36 compounds when applying a filter of 2 ppm, and 22 compounds at < 1 ppm About 100 unknowns to follow up on Several present that had been initially identified from sponges: nakijiquinone, petrosaspongiolide, plakinic acid and sarcotin We expect to be able to clarify the biological origin and biogeography of many natural products

33 Conclusions Developed rapid & quantitative method for marine biotoxins using full scan techniques Linear over appropriate range Allows for quantitation of all regulated (EU) lipophilic toxins in < 9 min Developed a database and library for marine biotoxins Ca. 275 compounds entered (ca. 90 structures added) Demonstrated capability of rapid screening against large-scale commercial databases Developed work-flow for assessing finger- and footprints of microalgae Exemplified how to use MP in comparative work Make a basis for chemotaxonomy of microalgae Used dereplication in conjunction with bioscreening

34 Thanks for your attention!! Jean-François de Troy «The oyster lunch» 1735 (originally decorating the dining room in Versailles), Musée Condé, Chantilly, France 34

35 ni PinnTx ni Nakijikinone ne sont des marqueurs discriminants de l axenisation de la souche Si avec le traitement anti bactérien 72>65, 7 composés supplémentaires s ajoutent donc pas utile d axéniser

WEBINAR. Target quantitation and metabolomic studies of marine biotoxins in algae and shellfish using QTOF technology

WEBINAR. Target quantitation and metabolomic studies of marine biotoxins in algae and shellfish using QTOF technology WEBINAR Target quantitation and metabolomic studies of marine biotoxins in algae and shellfish using QTOF technology Philipp Hess 1 Thomas Glauner 2, Bernhard Wüst 2, Manoëlla Sibat 1, Florence Mondeguer