metabolomic studies pn seabukthorn leaves … filemetabolomic studies pn seabukthorn leaves ......

Titlu slideDepartment of Agrifood Chemistry and Biochemistry

University of Agricultural Sciences and Veterinary MedicineCluj-Napoca, Romania

METABOLOMIC STUDIES PN SEABUKTHORN LEAVES AND FRUITS –

TOWARDS RAPID FINGERPRINT OF BIOLOGICAL AND GEOGRAPHICAL ORIGIN

Carmen SOCACIU & col.Department of Chemistry & Biochemistry,

Univ. Agr. Sciences & Vet. Med., Cluj-Napoca, ROMANIA



OutlineI. Metabonomics in postgenomic era: fingerprint of phytochemicals vs quantitation of metabolites - NETWORK

II. Phytochemicals as indicators of seabuckthorn (SB) composition ( leaves vs. fruits)III. Analytical steps and advanced techniques -BIOMARKERS

IV. Case studies: determination of biological and geographical origin by metabolomic analysis + chemometrics

V. Impact of metabolomics studies

Conf.SB Potsdam 3 Dec.2010



Metabolomics = systematic study of chemical fingerprint to realize a metabolite profiling ( small molecules) in a specific matrix ( plant, food)

Metabonomics = quantitative measurements to identify a specific metabolic response ( by key-molecules, e.g. phytochemicals)

METABOLOME = complement of all metabolites expressed in a cell, tissue or organism


Organic + Analytical Chemistry

Biochemistry

FOOD

Metabolomics: An INTEGRATED Tool for Studying SYSTEMS BIOLOGY

Metabolites = end products of gene expression and enzymatic activities Metabolomics – reflect the activity of a certain NETWORKcomplementary method to the large-scale gene transcript analysis (transcriptomics) and proteins fingerprint (proteomics) explain and identify the differences between sets of organisms (e.g. differences in genotypes) CHEMOTAXONOMYelucidate environmental factors that influence biomolecules fingeprint

GENOTYPE + ENVIRONMENT PHENOTYPE

MetabolomeTranscriptomics

PrimaryProteomics Secondary

(small molecules)

METABOLITES

Conf.SB Potsdam 3 Dec.2010Conf.SB Potsdam 3 Dec.2010

CHEMOMETRICS




Chemistry

IsolationPurificationStructureElucidation

Individuals

Applied BIO-Chemistry

• Direct measurement of a physical property (e.g. color)•Selective solubilization from a complex matrix•Group identification and quantification ( spectrometry)•Fingerprint of a certain group (comparisons)•Individual characterization (MS, NMR)

IT

Advanced Statistics

High performance

Equipments

Plant metabolome ProcessingWHAT WE NEED

Fingerprint

http://www.flickr.com/photos/ghonet/27421952/�

Widely used methods for plant metabolite analysis:

GC /MS and LC/MS (Sumner, Mendes & Dixon (2003) and Dunn & Ellis (2005).

LC/PDA/MS (Huhman & Sumner, 2002),

Capillary electrophoresis/mass spectrometry (CE/MS (Soga et al., 2003; Sato et al., 2004)

Fourier Transformed IR Spectroscopy (Socaciu, 2009)Fourier-transform ion-cyclotron mass spectrometry (FT/MS) (Tohge et

al., 2005)

Nuclear magnetic resonance (NMR) (Ward et al., 2003; Wiklund et al., 2005)




1. Carotenoids & chlorophylls2. Vitamins C and E3. Unsaturated -fatty acids4. Phytosterols5. Polyphenols- flavonoids,

antocyanins, phenolic acids,tannins

Plant secondary metabolites (more than 10000 molecules known yet…)

Attraction/defence moleculesAntioxidant/antibiotic actionBeneficial for plant, animal & human health.

Functionality-dependent on solubility, stability, bioavailability &redox potential


II. Phytochemicals as indicators of seabuckthorn (SB) composition ( leaves vs. fruits)-BIOMARKERS

AIMS – specific localization and stability of biomolecules related to their solubility

9

Lipophilic Hydrophilic

Comparative composition of H.r. ssp. carpaticavarieties from România and Germany (Hergo, Leikora)

Determination of metabolic profiles of carotenoids- polyphenols by HPLC-PDA, LC-MS, GC-MS, FTIR UV-Vis spectrometry

III. Analytical steps and advanced techniquesNEED FOR COMPLEMENTARY

METHODS/TECHNIQUES/KNOWLEDGE





0,00E+00

5,00E-01

1,00E+00

1,50E+00

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200 300 400 500 600

Wavelength (nm )

Ab

so

rban

ce

455

260

0

1

0.2

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200 750400 600

Abs

Wavelength [nm]

phenolics

carotenoidsChl

1st step = UV- VIs analysis ( for both LE and HE)

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Wavelength (nm)

Abs

orba

nce

(A.U

.)

Sm SBm SJmLE – hexane HE- methanol-water

flavonoids

Biomarkers group identificationQuantitative evaluation




2nd STEP- advanced methods HPLC-PDA or LC-MS

BERRY Profiling

20 40 60

0

10000

20000

Abso

rption

units

Retention time ( min)

280 450 535Seabuckthorn fruits

ether extr.

Carotenoid esters

10 20 30 40

0

20

40

60

Abso

rptio

n un

its

Retention time (min)

Seabuckthorn fruitsPhenolics

LE HE

340 nm





Profiling and quantitation of LE - carotenoids

0 10 20 30 40 50

0

200000

400000

A.U

.

Time (min)

Serbanesti

Sf Gheorghe

Ovidiu

SBB carotenoid fingerprint at 450 nm

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250000

300000

350000

A.U.

Time (min)

Carotenoid fingerprint at 450 nm, Serbanesti variety

SBB

SBL

Lutein

β carotene Carotenoid esters

Fingerprint and quantitative evaluation – discrimination of variety and geographical env.

BERRIES





Profiling and quantitation of LE - carotenoids

Fingerprint and quantitative evaluation – discrimination of variety and geographical env.

LEAVES

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Time (min)

Serbanesti

Sf Gheorghe

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SBL carotenoid fingerprint at 450 nm

Lutein β caroteneChlorophylls

0 10 20 30

0

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A.U

.

Time (min)

Chlorophylls fingerprint at 660 nm, Serbanesti variety

SBB

SBL

3 diff. varieties of leaves Chlorophyl ( leves vs berry) at Serbanesti variety




2bd STEP- advanced methods HPLC-PDA or LC-MS

Profiling and quantitation of HE - phenolics

5 10 15 20 250

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Time (min)

SBB

SBL

Flavonol Glycosides fingerprint at 340 nm, Serbanesti variety

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Time(min)

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Sf Gheorghe

Ovidiu

SBB Flavonol glycosides fingeprint at 340 nm

Leaves vs fruits for 1 variety3 diff. varieties of berries

IGR

IG

IG

Peack

tR (min) UV (nm) [M+H]+ m/z MS2 MS3 Structure Assignment

1 7.59 227,269, 350 627(100) 465(100), 303(24) 303(100) Q di glucoside

2 8.29 227, 351 733 (100) 611(20), 449(100), 303(35) 303 (100) Q sopho-rhamno

3 8.64 227, 350 641(100) 479(100), 317(20) 317(100) I diglucoside

4 8.77 227, 350 787(100) 641(38), 479(100), 317(36) 317(100) I diglucoside rhamnoside

5 9.14 227, 353 787(100) 625(22), 463(100), 317(54) 317(100) I sophoroside rhamnoside

6 9.77 227, 340 611(100) 465(2), 449(100), 303(27) 303(100) Q glucoside rhamnoside

7 10.74 227, 351 625(100) 479(7), 463(100), 317(28) 317(100) I glucoside rhamnoside

8 10.98 228, 254, 354 625(100) 463(92), 479(13), 317(100) 317(100) I glucoside rhamnoside

9 11.48 227, 254, 353 465 303(100) 257(100), 304(78), 229(68), 165(52), 286(45)

Q hexoside

10 12.31 226,352 625(100) 479(32), 463(3), 317(100) 302(100), 285(43), 317(14), 257(13)

I glucoside -rhamnoside

11 12.54 227,254,354 625(100) 479(19), 463(3) ,317(100) 302(100), 285(35), 314(14), 257(10)

I glucoside -rhamnoside

12 12.96 228, 254, 353 479(100) 317(100) 302(100), 285(40), 317(13), 153(4)

I glucoside

13 16.28 226,253,370 303(100) 257(100), 229(76), 303(59), 285(57), 165(55), 137(17), 153(15)

229(100) Q

14 17.04 226, 254, 370 463(100) 317(100) 302(100), 285(45), 257(10), 153(7)

I rhamnoside

15 18.08 226, 257, 354, 378

709(100) 574(100), 317(33) 317(100) I-acyl- glucoside-rhamnoside

16 19.51 226, 254, 370 317(100) 302(100), 285(45), 317(17), 257(12), 153(5)

274(100), 285(32), 153(25), 302(2)

I

ESI MS fragmentation pattern for I 3 glucoside 7 rhamnoside (IGR)

10 #1485 RT: 11.13 AV: 1 NL: 2.42E5T: ITMS + c ESI d Full ms2 [email protected] [160.00-640.00]

200 250 300 350 400 450 500 550 600m/z

0

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Rel

ativ

e A

bund

ance

463.32

317.20

479.21359.23 607.17302.25 443.18 575.88257.23221.12

10 #1483 RT: 11.11 AV: 1 NL: 2.53E5T: ITMS + c ESI d Full ms3 [email protected] [email protected] [115.00-475.00]

150 200 250 300 350 400 450m/z

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Rel

ativ

e A

bund

ance

317.13

445.23359.30146.95 403.41

10 #1484 RT: 11.12 AV: 1 NL: 6.32E5F: ITMS + c ESI Full ms [280.00-1000.00]

300 400 500 600 700 800 900 1000m/z

0

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Rel

ativ

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bund

ance

625.27

503.31388.33331.32 548.34 771.31647.22 949.16496.38 910.05

[M+H-C6H12O6 ]+

[M+H-C6H12O6 – C6H12O5]+

Major biomarker for leaves

[ ]

300 400 500 600 700 800 900 1000m/z

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Re

lativ

e A

bu

nd

an

ce

479.31

973.94871.35595.39501.31307.97 956.94391.45 738.03 819.35636.79

150 200 250 300 350 400 450m/z

0

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Re

lativ

e A

bu

nd

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317.22

461.31359.23 413.23145.02 225.33 292.69185.25

100 150 200 250 300m/z

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lativ

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bu

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302.20

285.18

317.21257.20139.10 165.07 243.21229.19201.17111.0495.06

ESI MS fragmentation pattern for Isorhamnetin glucoside (IG)

[M+H]+ [M+H-C6H12O6 ]+

Collaboration USAMV Cluj-Napoca & Wageningen University, NL ( Pop R.)

Fragmentation fingerprint

Individual identification of berries, together with IGH ( ratio 1-1.5)




2bd STEP- advanced methods HPLC-PDA or LC-MS

Profiling and quantitation of HE-phenolics

5 10 15 20

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2200000

A.U

.

Time(min)

Serbanesti

Sf Gheorghe

Ovidiu

SBB Flavonol glycosides fingeprint at 340 nm

3 diff. varieties of berries

IGR IG IG

5 10 15 200

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A.U.

Time (min)

Serbanesti

Sf Gheorghe

Ovidiu

SBL Flavonol glycosides fingerprint at 340nm

3 diff. varieties of leaves

-4000

6000

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Retention Time [min]

A.U

.

450

280

Carotenoid esters

10 20 30 400

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Absorp

tion u

nits


Seabuckthorn juicePhenolics

10 20 30 40

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Abso

rptio

n unit

s


Seabuckthorn fruitsPhenolics


Juice OIL280 nm

CASE STUDY – SEABUCKTHORN PRODUCTS




3rd Step- FTIR Spectrometric Fingerprint

Carotenoids – 965, 1367 and 1450 cm-1

Chlorophylls –1587and 1725 cm-1

Phenolics – 694-849 cm-1

Lypophilic component fingerprint2800-2900 and 1000-1500 cm-1

Hydrophilic components–1030-1200 cm-1

Degradation of lipids – look at 3300-3500 cm-1

Rapid, non-destructive, need validation

0

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Wavelength (cm-1)

Ab

so

rba

nc

e (

A.U

.)

SBm SBj lutein

1

24

3

6

5

7

Identification 1720-1734 cm-1 (1), 1620-1695 cm-1 (2), 1516-1550 cm-1 (3), 1238-1396 cm-1 (4), 1132-1134 cm-1 (5), 1024-1029 cm-1 (6), 961-964 cm-1(7).


Glucosides

Polyene chain

Esters

Esters

FT(ATR)MIR fingerprint regions of SB fruitFT(ATR)MIR fingerprint of SB juices (raw vs clear)

1

6

5




0

500

1000

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Seabuckthorn Aronia Black currant Bilberries

Total

polyp

heno

ls co

ntent

(mg/1

00g D

M)

0

20

40

60

80

100

120

140

Total

carot

enoid

conte

nt (m

g/100

g DM)

CASE STUDIES SEABUCKTHORN-ARONIA_BLACK CURRANT_BILBERRIES

800100012001400160018002000240028003200360040001/cm

-0

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1

Abs

Coacaze Acizi Fenolici evaporat Afine Acizi Fenolici evaporat

Aronia Acizi Fenolici evaporatCatina Serbanesti Acizi Fenolici evaporat

Catina Serbanesti Acizi Fenolici evaporat

800100012001400160018002000240028003200360040001/cm

-0

0.15

0.3

0.45

0.6

0.75

0.9

1.05

1.2

Abs

R1 SERBANESTI evapAfine carotenoide evaporat

Aronia carotenoide evaporatCoacaze carotenoide evaporat

Coacaze carotenoide evaporat

FTIR comparative fingerprint – SB, Bilberry, Aronia, Black currant

HYDROPHILIC EXTRACT

LYPOPHILIC EXTRACT

Polyene chains

H2O and carbohydrates

Esters

Carbohydrates

Carbohydrates

Phenolics

Polyene chains




4th STEP = Statistical correlations = CHEMOMETRY

Profiling and quantitation = INTEGRATION of DATA

HPLC + FTIR ( PLS analysis) + PCA to see correlations

recognize biological / geographical origin

Technological impact on food quality and safety

Consequences

METABOLOMIC ANALYSIS CONCEPT =

COUPLING ANALYTICS + CHEMOMETRY

The analytical data are pre-processed and used for multivariate analysis

The differences between samples are used to identify metabolites and make biological interpretation.

C = Chromographic profilesP =peaksS = spectral profiles.Conf.SB Potsdam 3 Dec.2010



Preprocessing by MetalignGenemathsSIMCAMathlabInfometrix: Pirouette 4.0

Cluster analysis PCA and PLS Analysis

Pattern recognition

Chemometrics


Comp.1

Com

p.2

-0.6 -0.4 -0.2 0.0 0.2 0.4

-0.6

-0.4

-0.2

0.0

0.2

0.4

M2/S1M2/S2

M4/S1

M4/S2M3/S1M3/S2

M5/S1

M5/S2

M1/S1

M1/S2

-30000 -20000 -10000 0 10000 20000

-300

00-2

0000

-100

000

1000

020

000

p1p2p3

p4

p5

p6p7

p8

Comp.1

Com

p.2

-0.6 -0.4 -0.2 0.0 0.2 0.4 0.6

-0.6

-0.4

-0.2

0.0

0.2

0.4

0.6

M2/S1

M2/S2

M4/S1

M4/S1

M3/S1

M3/S2

M5/S1

M5/S2

M1/S1

M1/S2

-20 -10 0 10 20

-20

-10

010

20

chlorogeniccaffeic rosmarinic

Name Code Beta-carotene/zeaxanthin esters ratio

Chlorogenic Acid (1)(mg/g)

Rosmarinic Acid (4)(mg/g)

SB Transylvania RO Cluj M2/S1 0.9 0 21.66

SB Transylvania RO Cluj M2/S2 1.02 1.42 35.34

SB SouthWest RO Timisoara M4/S1 1.05 0 23.92

SB South West RO Timisoara M4/S2 0.8 1.24 39.44

SB Germany (Hergo) M3/S1 1.4 0 7.58

SB Germany (Leikora) M3/S2 1.32 1.42 18.45

SB North East RO M5/S1 1.2 0 29.08

SB North East RO M5/S2 1.83 1.83 21.49

SB Danube Delta RO M1/S1 0.7 0 24.56

SB Danube Delta RO M1/S2 0.9 1.40 20.52

Biological origin is stronger in SB

variability than the geographical

origin

PHENOLICS

CAROTENOIDS

G

B B

B

For bioactive molecules



We are able to identify different, specific biomarkers realizing the berry vs leave fingerprint, discrimination of biological and geographical origin

The technological progress in development of new instruments (LC-MS, GC-MS, TOF/MS, FTIR, etc) allows the identification and quantification of each marker (1) as well the plant/food fingerprint/profile (2).

Combinations of different, complementary analytical techniques completed with chemometric analysis are required for comprehensive metabolomic studies.

Specific predictions can be established for routine analysis, cheaper and easy to perform

Experimental conclusions




Establishment of quality standards based on major biomarkers ( carotenoids, phenolics, vit. C) with antioxidant potential

Evaluation of technological flow, from raw material to intermediates and final products

Authenticity of products and their traceability (origin) Safety aspects ( PCH, pesticides) Use of rapid methods ( FTIR) which are in good

correlation with validated , expensive methods (HPLC, GC)

Specific predictions can be established for routine analysis, cheaper and easy to perform for many samples

IMPACT OF METABOLOMIC STUDIES




First Metabolomics program in Romania

Carmen SOCACIU - coordinator

Floricuta RANGA – UV-Vis, HPLC, and LC-MS (plants)

Florinela FETEA – FTIR (plants and food)Adela PINTEA & Andrea BUNEA- HPLC-

PDA (carotenoids and in vitro effects)Raluca PARLOG: LC-MS and TOF (food

metabolomics)Monica TRIF, PhD – FTIR and NMR

(functional oils)Loredana LEOPOLD: FTIR and Raman

spectroscopyFrancisc DULF, PhD : GC-FID and GC-MS

(phytosterols)Constantin BELE and Cristian Matea :GC-

FID (fatty acids)

MeT-RO : A major initiative to establish the Centre for Plant and Food Metabolomic AnalysisMetabolomics Society Reseaux Metabolomics and Fluxonomics –FranceMetaboP- EU Project META-PHOR

http://www.flickr.com/photos/ghonet/27421952/�

FOOD COLORANTS: Structural and Functional Properties

CRC Press, Taylor & Francis, 2008

Series editor: T. SikorskiEditor: Carmen Socaciu (USAMV Cluj, RO)

Contributors: Amiot-Carlin M-J.&coll. (INSERM,Marseille,FR) Caris Veyrat C.(INRA Avignon, FR)Diehl H.(Uni Bremen, DE)Dufosse L.(Uni La Reunion, FR)During A. (Res. Beltsville, USA)Lanfer Marquez U.M. ( Sao Paolo, BR)Luning P. (UR Wageningen, NL)Mercadante A. and coll. (Uni. Campinas, BR)Otles S.(Uni Izmir, TK)Pintea A. (USAMV Cluj, RO)Socaciu C (USAMV Cluj, RO)Stintzing F.and R.Carle (Uni Hohenheim, DE)Wuerzel E.and coll.( Lehman Coll, NY,USA)

More about pigments ….

Department of Chemistry & Biochemistry www.usamvcluj.ro/cercetarewww.biochim.usamvcluj.ro

http://www.usamvcluj.ro/cercetare�

TRADITIONand MODERNITY

metabolomic studies pn seabukthorn leaves … filemetabolomic studies pn seabukthorn leaves ......

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