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LC-MS metabolomics shows a smart way to reduce sulfites in wine

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-1200 -1100 -1000 -900 -800 -700 -600 -500 -400 -300 -200 -100 0 100 200 300 400 500 600 700 800 900 1000 1100 1200 -600 -500 -400 -300 -200 -100 0 100 200 300 400 500 600 t[ 1 ] t[4]

Scores Comp[4] vs. Comp[1] colored by Variety

Chardonnay Grillo Inzolia Muller Pinot grigio QC Traminer Hotelling’s T2 Ellipse (95%) = (559.1; 1139) R2X[4] = 0.06998 R2X[1] = 0.2906

EZinf o 2 - nomacorc2_1QC (M3: PCA-X) - 2015-01-23 12: 22:22 (UTC+1)

3 x Grillo

5 x Pinot gris

1 x Inzolia

1 x Muller Thurgau

1 x Chardonnay

1 x Traminer

6 x varieties

12 x wines

N

2

O

2

2 x bottling conditions

(4+4)x12 = 96 bottles (+)

~8000 features

statistical noise

QC

(2)

LC-MS Wine Metabolomics:

workflow

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation Method adaptation MetaDB PCA QC samples OPLS-DAXCMS Metadata Visual control TargetLynx Statistics Targeted analysis Internal database External database MS/MS Randomi-zation

(3)

LC-MS Wine Metabolomics:

method

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation Method adaptation

(4)

LC-MS Wine Metabolomics:

markers

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation XCMS OPLS-DA Visual control TargetLynx Statistics Targeted analysis

false positives

false negatives

(tentative) bio-markers

(5)

LC-MS Wine Metabolomics:

markers

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation Visual control TargetLynx Statistics

1.

Check chromatogram

2.

Check MS spectra

3.

Peak integration

4.

QC variability Vs. p-values

C

T

QC

C

T

QC

(6)

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation

External databases

Sigma-Aldrich has ~

55K

commercial available

chemicals

Kegg contains

18K

metabolites

HMDB is based in ~

42K

metabolites

Plant metabolome is estimated to cover

200K

metabolites

PubChem ID contains more than

10M

entries

CAS contains over

90M

unique organic and

inorganic chemicals

(7)

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation

The great unknown

(8)

LC-MS Wine Metabolomics:

Hypothesis

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation

O

O

H

OH

O

O

H

O

H

O

O

O

O

O

H

O

H

O

2

N

2

O

2

(9)

LC-MS Wine Metabolomics:

Hypothesis

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation

glutathione

O

2

O

H

NH

NH

O

NH

2

O

S

O

O

O

H

O

H

NH

NH

O

NH

2

O

S

O

O

O

H

O

H

NH

NH

O

NH

2

O

SH

O

O

O

H

N

2

O

2

(10)

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation

O

2

, HSO

3

-O

H

NH

NH

O

NH

2

O

SH

O

O

O

H

O

H

NH

NH

O

NH

2

O

S

O

O

O

H

S

O

OH

O

LC-MS Wine Metabolomics:

Hypothesis

(11)

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation

LC-MS Wine Metabolomics:

Message

O H NH NH O NH2 O SH O O O H O H NH NH O NH2 O S O O O H S O OH O SO2 + H2O HSO3 -O H NH NH O NH2 O S O O O H O H NH NH O NH2 O S O O O H

O

2

(12)

LC-MS Wine Metabolomics:

Annotation

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation

Low O

2

(13)

LC-MS Wine Metabolomics:

Annotation

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation m/z 120 140 160 180 200 220 240 260 280 300 320 340 360 380 % 0 100

D006_Pinot_RP_neg 21 (14.263) Cm (17:32) 18: TOF MSMS 366.12ES-

765 142.0669 765 128.0501 35 204.0672 216 186.0524 148 143.0557 132 159.0161 20 205.0008 24 270.8094 19 247.8298 13 287.8287 17 366.1111 8 329.5197 2

MS/MS

N H OH O OH

162

hexose

N

H

O

O

OH

O

OH

OH

O

H

OH

(14)

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation

N

H

O

O

OH

O

OH

OH

O

H

OH

S

O

OH

O

O

2

, HSO

3

-High O

2

Low O

2

N

H

O

O

OH

O

OH

OH

O

H

OH

LC-MS Wine Metabolomics:

Annotation

(15)

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation

O

NH

NH

O

OH

O

H

S

S

O

O

OH

O

NH

NH

O

OH

O

H

SH

N

H

OH

S

O

O

OH

N

H

OH

O

2

, HSO

3

-

O

2

, HSO

3

-O

NH

2

S

OH

S

O

O

O

H

O

NH

2

S

H

OH

O

2

, HSO

3

(16)

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation

LO: Low O

2

HO: High O

2

(17)

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation

O

OH

OH

O

H

OH

OH

O

OH

OH

O

H

OH

OH

O

OH

OH

O

H

OH

OH

O

OH

OH

O

H

OH

OH

S

O

O

O

-O

2

, HSO

3

(18)

Experimental design Experiment LC-MS analysis Quality Control Markers detection Markers validation Markers identification Hypothesis generation

http://www.ebi.ac.uk/metabolights/MTBLS137

Franceschi et al. Frontiers 2014

indole-3-lactic glucoside

0 100 200 300 400 500 600 700 800

Germ any Italy

a re a Phoenix Re gent

N

H

O

O

OH

O

OH

OH

O

H

OH

(19)

N

H

O

O

OH

O

OH

OH

O

H

OH

Grape metabolome

Top 30 red grape cultivars

Top 30 white grape cultivars

271 entries

181 entries

(20)

Fulvio Mattivi

Daniele Perenzoni

Andrea Angeli

Maurizio Ugliano

Paolo Pangrazzi

(21)

Pinot noir

Naousa

Rapsani

Chardonnay

Malagouzia

Cabernet Sauvignon

Nemea

Riesling

Assyrtico

Gewurtztraminer

Mantinia

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