« Forum für Lebensmittelsicherheit»

Waldbronn 30/31 Januar 2013

Spezifische, quantitative und

metabolomische Analysentecniken für

Marine Biotoxine mit dem

Agilent Q-ToF 6540

Philipp Hess1

Thomas Glauner2, Bernhard Wüst2,

Manoëlla Sibat1, Florence Mondeguer1, Zita Zendong1

1 Laboratoire Phycotoxines IFREMER – 44300 Nantes - France

2 Agilent Technologies R&D - 76337 Waldbronn - Germany

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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

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

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Biodiversity = Chemodiversity

Unknown toxins France 2003 – 2008

(as detected per mouse bioassay for lipophilic toxins)

27 % of unexplained mouse bioassays

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

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1- Full scan analysis:

Okadaic acid

Example of full scan power MS Mass Hunter software to evaluate molecular and pseudo-molecular ion clusters.

Development of fast quantitative method for marine biotoxins

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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)

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Calibration curves

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Quantitative rapid method (full scan)

Certified standards

Six calibration levels

R2 > 0,98

Matrix effects remain to be evaluated…

Agilent suite of software

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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

PCDL Manager - module

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458 ion is specific to

PnTX-G and does

not exist for SPXs

Using LC-HRMS

for definitive

confirmation of

identity:

Example of

isobaric PnTX-G

and SPX-B & 13-

dm SPX-D

Database development – literature search…

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Toxin family Toxin group Abbreviation

Number

Compound Molecular structure

ASP Domoic acid DA 9 9

DSP

Okadaic acid &

dinophysistoxins OA+DTXs 65 10

Azaspiracids AZAs 30 /

Pectenotoxins PTXs 16 4

Yessotoxins YTXs 31 /

Cyanobacteria Oscillatoxins n/a 9 /

Cyclic imines

(FAT)

Gymnodimines GYMs 4 4

Spirolides SPXs 11 11

Pinnatoxins and Pteriatoxins PnTXs+PterTX

s 12 12

PSP Saxitoxins STXs 18 18

Tetrodotoxins TTXs 18 /

NSP

Palytoxins PLTXs 8 1

Brevetoxins PbTXs (BTX) 16 /

Pacific Ciguatoxins P-CTXs 27 /

Caribbean Ciguatoxins C-CTXs 2 /

LC-MS/MS spectra are reputed to be non-

reproducible 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

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Database development – entering spectra…

Agilent work-flow for non-targeted analysis

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Sample Prep

Fingerprints(LC/HRMS)

Data retreatment

Statistical analyses

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1000’s ions Biomarkers ?

m/z

rt

intensités

133.07 133.08 133.09 133.10

m/z

0

10

20

30

40

50

60

70

80

90

100

110

Re

lative

Ab

un

da

nce

133.08020

133.07378

133.09665

133.08236

NL:9.69E2

C 4 H10 O2 N3: C 4 H10 O2 N3

p (gss, s /p:40) Chrg 1R: 20.0 PPM @FWHM

NL:1.11E6

281008023#93 RT: 2.46 AV: 1 SB: 1782 3.11-49.81 , 0.01-2.31 T: + c ESI Full ms [50.00-800.00]

Structure elucidation

MSn

Also:

Fingerprints

Footprints

Crosstalk

Metabolomics Approach:

Examples of algal metabolomes:

Alexandrium ostenfeldii

7,232 min 13,19 Didesmethyl-SPX-C (M+H)+ = 692,4520

Examples of algal metabolomes:

Karenia selliformis

6,48 min Gymnodimine A (M+H)+ = 508,3433

Examples of algal metabolomes:

Prorocentrum lima

11,38 min OA (M+H)+ = 805,4733 12,71 min DTX1 (M+H)+ = 819,4901

Examples of algal metabolomes:

Pseudo-nitzschia

5,49 min DA (M+H)+ 312,1445

Azadinium spinosum

Comparative metabolomes:

77 features only in A. obesum, 59 features only in A. spinosum, and 95 common features !

AZA1-methyl ester (M+H)+ 856.5201

AZA? (M+H)+ 716.4748

AZA2 (M+H)+ 856.5224 AZA1 (M+H)+ 842.5068

Azadinium obesum

From metabolomes to chemotaxonomy:

From metabolomes to chemotaxonomy:

Comparative metabolomes of algal fingerprints and algal footprints

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SPATT A. spinosum vs A. obesum

147 features in SPATT vs. 196 features in A. spinosum

Acetone extract of A. spinosum vs A. obesum

Pilot-scale culture of V. rugosum

Batch 1 2 3 4 5 6 7 8 9 10 Total

Mass of pellet (g) 26 19 16 13 16 28 28 58 56 29 289g

Masse PnTX G (µg) 614 442 303 237 259 411 276 140 246 181 3mg

Culture conditions L1 L1 L1* L1 L1 L1* L1 L1 L1 L1

Duration of culture (d) 41 33 29 39 25 47 37** 63 56 43

Metabolome of Vulcanodinium rugosum

- bioguided fractionation

Fractions

Chemical analysis Evaluation of biological activity

Data analysis

(comparison to large natural product libraries2)

-Triple quad

-Q-ToF -Cytotoxicity KB cells

-Fly larvae

-bacteria

Vulcanodinium

rugosum Crude extract

Biological Screening

and

Metabolomics: Dereplication1,2

Fractioning

(1) Kristian F. Nielsen et al. J Nat. Prod. (2011) 74, p2338-2348

(2) http://www.chem.canterbury.ac.nz/marinlit/marinlit.shtml

Fractionation of sample for polar lipids

Scheme of extraction and purification of PnTX-G

CRUDE (A)

(2050 mg)

DCM fraction (B) (442 mg; 22% of A)

Aqueous phase

Hexane phase Aq. MeOH fraction (C)

(168 mg; 8% of A)

SiO2-F2 (73 mg; 43 % of C)

SiO2-F3 (39 mg; 23 % of C)

PnTX G

Crude extr.

DCM-fract.

Aq. MeOH

Evaluation of the activity of algal extracts

using cytotoxicity assay

0

20

40

60

80

100

F1bP3 F2bP3 F3bP3 F4bP3 F5bP3

Masse fractions (%)

Masse PnTX G (%)

Dereplication: database screening results for SiO2 F3 Vulcanodinium EB DCMMeOHaq SiO2 F3

Pinnatoxin-G

Dereplication: SiO2 F2:

Screen against MarinLit

(database by Bunt & Munro

with > 30 000 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 5.68 402.2278 99.4 -0.82

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…

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 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

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

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Jean-François de Troy « The oyster lunch » 1735 (originally decorating the dining room in Versailles), Musée Condé,

Chantilly, France

Thanks for your attention !!

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