Exploratory Wine Study Using SIEVE 2.0

Michael Athanas, Ph.D. VAST SCIENTIFIC

B R I M S Biomarker Research Initiative in Mass Spectrometry

Mary Lopez Director

David Sarracino Manager, Biomarker Workflows

Bryan Krastins Leader Biomarker Translational Center

Amol Prakash Assoc. Director Informatics Center of Excellence

Michael Athanas Assoc. Director Informatics Center of Excellence

Jennifer Sutton Informatics Center of Excellence Project Manager

brims.center

SIEVE 2.0 New Features

• Component Elucidator Algorithm

• 64 bit • Enhanced multi-threading • Interoperability with Protein

Center • New hierarchal component

view • Dynamic framing • PerfectPair wizard • Integrated raw file explorer • Enhanced frame target

handling • Much more….

Beta release now available

2008 Wildfires and Wine

• Over 2790 individual wild fires • Weather conditions:

– 3 years of below normal rainfall – Lightning

• Poor air quality

13 Data Samples # Blend Location

1 zinfandel Lake10 petite sirah Lake13 zinfandel Lake36 cabernet sauvignon Mendocino37 petite sirah Mendocino2 cabernet franc Napa3 cabernet franc Napa

20 petite verdot Napa21 cabernet franc Sonoma25 cabernet sauvignon Sonoma33 merlot Sonoma35 merlot Sonoma44 cabernet sauvignon Sonoma

http://g.co/maps/nwjf Small and diverse samples

Sample Processing

13 samples direct LC injection

LC/MS using Thermo Q-Exactive Open Accela 1250 Triplicate measurements interspersed by single matrix blank measurements

Data analysis with SIEVE 2.0

Statistically rigorous automated label-free LC/MS differential analysis platform

Applied to: peptide, protein, small molecule data

State 1 Raw file

State 2 raw file

State … raw file

Workflow

Align Detect Identify

Reports: •Components •Identification •Relative Quantitation •Statistical Analysis •Trend information

SIEVE Analysis Platform

SIEVE WORKFLOW Align Detect Identify

1. Full scan spectra are typically acquired at 1Hz to 100Hz with high mass accuracy (<5ppm).

Data File 1 Reference

Data File 2

SIEVE Workflow – Alignment 1

Intensity

Intensity

M/Z

M/Z

SIEVE Workflow – Alignment 2

Intensity

Intensity

M/Z

M/Z

1. Full scan spectra are typically acquired at 1Hz to 20Hz with high mass accuracy (<5ppm).

2. The spectra are binned.

Data File 1 Reference

Data File 2

X

SIEVE Workflow – Alignment 3

1. Full scan spectra are typically acquired at 1Hz to 20Hz with high mass accuracy (<5ppm).

2. The spectra are binned.

3. A dot product correlation is calculated between each pair of spectra

Data File 1 Reference

Data File 2

Scan

# d

ata

file

2

Scan # data file 1

SIEVE Workflow – Alignment 4

Scan-to-scan correlation:

Red High Green Low

•An overlapping tile is constructed from the next region starting from the middle of the optimal path.

SIEVE Workflow – Alignment 5

•An overlapping tile is constructed from the next region starting from the middle of the optimal path. •The full plane is tiled and a final alignment score is calculated.

Overlapping measurements are averaged

SIEVE Workflow – Alignment 6

Unaligned basepeaks

SIEVE Workflow – Alignment 7

Wine

Aligned basepeaks

Alignment scores

SIEVE Workflow – Alignment 8

Wine

Sample - Solvent blank = Analyte signals

Background Subtraction

Adducts, fragments and multimers

[M+H]+ [M+Na]+ [M+K]+ 524.3703, z=1, I=4.2E+08, 100% 546.3517, z=1, I=1.0E+08, 24.6% 562.3232, z=1, I=1.1E+06, 0.3%

A+1

Isotopic peaks

525.3730, I=1.2E+08, 28.9%

527.3784, I=3.0E+06, 0.7%

528.3811, I=3.9E+05, 0.1%

A+2 526.3756, I=2.3E+07, 5.5%

A+3 A+4

547.3535, I=2.9E+07, 27.8%

548.3577, I=5.6E+06, 5.4%

549.3595, I=9.0E+05, 0.9%

A+1 A+2

A+3

Isotopic peaks

21.9816

37.9554

Component Detection

Constituents are represented by base component

Component Efficiency

9 out of the 10 compounds were identified using default settings

Spiked standards in

Frame / Feature Frame: a well defined rectangular region in the M/Z versus Retention Time plane.

L-Epicatechin MW = 290.0790

L-Epicatechin

L-Epicatechin MW = 290.0790

# Blend Location

1 zinfandel Lake10 petite sirah Lake13 zinfandel Lake36 cabernet sauvignon Mendocino37 petite sirah Mendocino2 cabernet franc Napa3 cabernet franc Napa

20 petite verdot Napa21 cabernet franc Sonoma25 cabernet sauvignon Sonoma33 merlot Sonoma35 merlot Sonoma44 cabernet sauvignon Sonoma

Dynamic Framing

Protein ratio = 1.155

SIEVE 1.3 SP2

SIEVE 2.0

Protein ratio = 8.456

LFTGHPETLEK

VEADIAGHGQEVLIR

Myoglobin

Reference: ABRF 2007 Study Jennifer Sutton @ Thermo

SIEVE 2.0

Complementary Signal Detection Algorithms Basepeak Framing Component Extraction

Peak detection

Fully unbiased based upon signal intensity, MS/MS, or Frame Targets

Automated peak shape on full scan

Pattern Recognition Isotope clusters Charge state +

adduct + isotope induction

Performance Fast Faster

Signal to noise Many noise frames – use Frames Filter

Only identified components

Background subtraction

Use Frame Targets to build background list

Completely automated

Application Proteomics, Small Molecule

Small Molecule Only

Identification PD 1.x, Mascot, built in SEQUEST, DBLookup

ChemSpider, DBLookup, (Mass Frontier coming soon)

SIEVE Frames vs. Components

0

50

100

150

200

250

0 2 4 6 8 10 12 14 16 18

Fram

e ID

Component

7 5 6

25

9 16

26

5 14

21

34

19 4

6 6 3 5 13

17 Components were identified from 224 frames. Shown in this plot are how the frames were grouped into the different components.

Accurate Mass Identification

Mass accuracy 2.9 ppm

using 445.12 background ion

www.vastsci.com/rawmeat

Local database

chemspider web service

Component MW

List of candidates

Identification Results

• 1224 components

• 255 identified components

• Flavonoid accurate mass database

MolWt Expression Name290.079 L-Epicatechin306.074 Epigallocatechin

314.01 D-glycoside of vanillin380.1254 Vellokaempferol 3-5-dimethyl ether382.1047 Velloquercetin 4 -methyl ether426.0945 Epigallocatechin 3-O-(4-hydroxybenzoate)436.1153 Epigallocatechin 3-O-cinnamate450.0793 Quercetin 4 -galactoside468.1051 Epigallocatechin 3-O-caffeate

472.1 Epigallocatechin 3-O-(3-O-methylgallate)477.1266 Isorhamnetin 7-alpha-D-Glucosamine;Quercetin 3 -methyl ether 7-alpha-D-Glucosam478.0742 Quercetin 7-glucuronide486.1157 Epigallocatechin 3-O-(3-5-di-O-methylgallate)494.0691 Myricetin 3-glucuronide504.1626 6-Hydroxykaempferol 3-5-7-4 -tetramethyl ether 6-rhamnoside;6-[(6-Deoxy-alpha-L-516.1262 Kaempferol 3-(3 -4 -diacetylrhamnoside)552.1474 6-Hydroxymyricetin 3-6-3 -5 -tetramethyl ether 7-glucoside562.2045 Caohuoside D;8-(3 -Hydroxy-3 -methylbutyl)kaempferol 4 -methyl ether 7-glucoside580.1423 Quercetin 3-xylosyl-(1-&gt;2)-rhamnoside

600.111 Quercetin 3-(2 -galloylrhamnoside)610.1317 Quercetin 3-(3 -p-coumarylglucoside)610.1528 Rutin;3-3 -4 -5-7-Pentahydroxyflavone 3-rutinoside;3-Rutinosylquercetin;Birutan;Qu 636.1474 Kaempferol 3-(4 -acetyl-6 -p-coumarylglucoside)

640.127 Quercetin 3-glucuronide-7-glucoside640.1634 Tamarixetin 3-glucosyl-(1-&gt;2)-galactoside;Quercetin 4 -methyl ether 3-glucosyl-(1

662.163 Kaempferol 3-(2 -3 -diacetyl-4 -p-coumarylrhamnoside668.1583 Euphorbianin;Quercetin 3-(6 -acetylglucosyl)-(1-&gt;3)-galactoside;3-[[3-O-(6-O-Ace724.1787 Platanoside;Kaempferol 3-(2 -3 -di-(E)-p-coumaroylrhamnoside);3-[[6-Deoxy-2-3-bi756.1685 Quercetin 3-(3 -6 -di-p-coumarylglucoside)770.1841 Kaempferol 3-(3 -p-coumaryl-6 -ferulylglucoside)772.1845 Quercetin 3-O-beta-(6 -O-E-p-coumaroylglucoside)-7-O-beta-glucoside

….

http://metabolomics.jp

Cluster Wine Flavonoids

Clustering based upon signal intensity profile

Flavonoid database

Absolute Quantitation Calibration Curve Method

Dilution series at four concentrations (.02, .04, .2,.4) mg/ml in 10% methanol

LC/MS using Thermo Q-Exactive

Data analysis with SIEVE 2.0

Epicatechin Catechin Orientin Luteolin

Ellagic Acid Quercetagetin

Chrysin Genistein

Rhamnetin Tamarixetin

Standards

Linear Regression

Observed value in Zinfandel from Lake (16ug/ml)

Linear Regression

Observed value in Cabernet Sauvignon from Mendocino (74ug/ml)

Absolute Quantitation

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

mg/

ml

Quercetagetin

L-Epicatechin

Contaminant Response

MolWt FORMULA NAME209.9406 C7H5Cl3O 2,4,6-Trichloroanisole150.0681 C9H10O2 2-Methoxy-4-vinylphenol (4-Vinylguaiacol)168.1514 C11H20O 2-Methylisoborneol122.0732 C8H10O 4- ethylphenol152.0837 C9H12O2 4-ethylguaiacol 138.0681 C8H10O2 4-methylguaiacol108.0575 C7H8O Cresol164.0837 C10H12O2 Eugenol96.02113 C5H4O2 Furfural182.1671 C12H22O Geosmin124.0524 C7H8O2 Guaiacol286.1053 C13H18O7 ß-D-glycoside of Guaiacol

314.01 C14H18O8 ß-D-glycoside of vanillin154.063 C8H10O3 Syringol

Possible smoke related contaminants

Contaminant Response

0.0000

0.0050

0.0100

0.0150

0.0200

0.0250

0.0300

0.0350

0.0400

0.0450

0.0500

2-Methoxy-4-vinylphenol (4-Vinylguaiacol)

4- ethylphenol

Eugenol

Furfural

Syringol

D-glycoside of Guaiacol

D-glycoside of vanillin

Summary Deep appreciation for superior expert laboratory craftsmanship to:

Mark Dreyer, Applications Specialist, ThermoFisher Thomas Collins, Ph.D, Senior Manager Research and Development, Treasury Wine Estates

For more information: michael@vastscientific.com http://sieve.vastscientific.com http://vastscientific.com/rawmeat

Team SEIVE

Mary Lopez Amy Zumwalt Jennifer Sutton Mark Sanders David Peakes Gouri Vadali Michael Athanas