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California Wine LC/MS Analysis with SIEVE

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California Wine LC/MS Analysis with SIEVE Exploratory Wine Study Using SIEVE 2.0 Michael Athanas, Ph.D. VAST SCIENTIFIC BRIMS Biomarker Research Initiative in Mass Spectrometry Amol Prakash Assoc. Director Bryan Krastins brims.center Informatics Center of Excellence Leader Biomarker Translational Center Jennifer Sutton David Sarracino Informatics Center of Excellence Michael Athanas Project Manager Manager, Biomarker Workflows Assoc. Director Informatics Center of Excellence Mary Lopez Director 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 Lake 10 petite sirah Lake 13 zinfandel Lake 36 cabernet sauvignon Mendocino 37 petite sirah Mendocino 2 cabernet franc Napa 3 cabernet franc Napa 20 petite verdot Napa 21 cabernet franc Sonoma 25 cabernet sauvignon Sonoma 33 merlot Sonoma 35 merlot Sonoma 44 cabernet sauvignon Sonoma http://g.co/maps/nwjf Small and diverse samples Sample Processing 13 samples LC/MS using Thermo Data analysis with Q-Exactive SIEVE 2.0 direct LC injection Open Accela 1250 Triplicate measurements interspersed by single matrix blank measurements SIEVE Analysis Platform Statistically rigorous automated label-free LC/MS differential analysis platform State 1 Reports: Raw file •Components Workflow •Identification State 2 •Relative Quantitation raw file Align Detect •Statistical Analysis Identify •Trend information State … raw file Applied to: peptide, protein, small molecule data Align Detect Identify SIEVE WORKFLOW SIEVE Workflow – Alignment 1 1. Full scan spectra are typically Data File 1 acquired at 1Hz to Reference 100Hz with high mass accuracy (<5ppm). Intensity M/Z Data File 2 Intensity M/Z SIEVE Workflow – Alignment 2 1. Full scan spectra are typically Data File 1 acquired at 1Hz to Reference 20Hz with high mass accuracy (<5ppm). Intensity 2. The spectra are binned. M/Z Data File 2 Intensity M/Z SIEVE Workflow – Alignment 3 1. Full scan spectra are typically Data File 1 acquired at 1Hz to Reference 20Hz with high mass accuracy (<5ppm). 2. The spectra are binned. X 3. A dot product correlation is calculated between each pair of spectra Data File 2 SIEVE Workflow – Alignment 4 Scan # data file 1 Scan-to-scan correlation: Red High Green Low file 2 data data Scan # Scan SIEVE Workflow – Alignment 5 •An overlapping tile is constructed from the next region starting from the middle of the optimal path. SIEVE Workflow – Alignment 6 •An overlapping tile is constructed from the next region starting from the middle of the optimal path. Overlapping measurements •The full plane is tiled and a final are averaged alignment score is calculated. SIEVE Workflow – Alignment 7 Unaligned basepeaks Wine SIEVE Workflow – Alignment 8 Aligned basepeaks Wine Alignment scores Background Subtraction Sample - Solvent blank = Analyte signals Component Detection Adducts, fragments and multimers 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% [M+H]+ [M+Na]+ [M+K]+ 21.9816 37.9554 Isotopic peaks A+1 525.3730, I=1.2E+08, 28.9% Isotopic peaks A+2 526.3756, I=2.3E+07, 5.5% 527.3784, I=3.0E+06, 0.7% 547.3535, I=2.9E+07, 27.8% A+3 A+1 A+4 528.3811, I=3.9E+05, 0.1% A+2 548.3577, I=5.6E+06, 5.4% A+3 549.3595, I=9.0E+05, 0.9% Constituents are represented by base component Component Efficiency Spiked standards in 9 out of the 10 compounds were identified using default settings Frame / Feature Frame: a well defined rectangular region in the M/Z versus Retention Time plane. L-Epicatechin MW = 290.0790 L-Epicatechin # Blend Location 1 zinfandel Lake 10 petite sirah Lake 13 zinfandel Lake 36 cabernet sauvignon Mendocino 37 petite sirah Mendocino 2 cabernet franc Napa 3 cabernet franc Napa 20 petite verdot Napa 21 cabernet franc Sonoma 25 cabernet sauvignon Sonoma 33 merlot Sonoma 35 merlot Sonoma 44 cabernet sauvignon Sonoma L-Epicatechin MW = 290.0790 Dynamic Framing Myoglobin Protein ratio = 8.456 Protein ratio = 1.155 SIEVE 2.0 SIEVE 1.3 SP2 VEADIAGHGQEVLIR LFTGHPETLEK SIEVE 2.0 Reference: ABRF 2007 Study Jennifer Sutton @ Thermo Complementary Signal Detection Algorithms Basepeak Framing Component Extraction Fully unbiased based Automated peak upon signal intensity, shape on full scan Peak detection MS/MS, or Frame Targets Isotope clusters Charge state + Pattern Recognition adduct + isotope induction Performance Fast Faster Many noise frames – Only identified Signal to noise use Frames Filter components Background Use Frame Targets to Completely subtraction build background list automated Proteomics, Small Small Molecule Only Application Molecule PD 1.x, Mascot, built in ChemSpider, Identification SEQUEST, DBLookup DBLookup, (Mass Frontier coming soon) SIEVE Frames vs. Components 250 13 3 5 200 6 6 4 19 34 150 21 Frame ID 14 100 5 26 16 50 9 25 5 6 7 0 0 2 4 6 8 10 12 14 16 18 Component 17 Components were identified from 224 frames. Shown in this plot are how the frames were grouped into the different components. Accurate Mass Identification Component MW Mass accuracy chemspider Local web service 2.9 ppm database using 445.12 background ion List of candidates www.vastsci.com/rawmeat Identification Results MolWt Expression Name 290.079 L-Epicatechin 306.074 Epigallocatechin • 1224 314.01 D-glycoside of vanillin 380.1254 Vellokaempferol 3-5-dimethyl ether components 382.1047 Velloquercetin 4 -methyl ether • 255 identified 426.0945 Epigallocatechin 3-O-(4-hydroxybenzoate) 436.1153 Epigallocatechin 3-O-cinnamate components 450.0793 Quercetin 4 -galactoside 468.1051 Epigallocatechin 3-O-caffeate 472.1 Epigallocatechin 3-O-(3-O-methylgallate) • Flavonoid 477.1266 Isorhamnetin 7-alpha-D-Glucosamine;Quercetin 3 -methyl ether 7-alpha-D-Glucosam accurate mass 478.0742 Quercetin 7-glucuronide 486.1157 Epigallocatechin 3-O-(3-5-di-O-methylgallate) database 494.0691 Myricetin 3-glucuronide 504.1626 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-glucoside 562.2045 Caohuoside D;8-(3 -Hydroxy-3 -methylbutyl)kaempferol 4 -methyl ether 7-glucoside 580.1423 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-glucoside 640.1634 Tamarixetin 3-glucosyl-(1-&gt;2)-galactoside;Quercetin 4 -methyl ether 3-glucosyl-(1 662.163 Kaempferol 3-(2 -3 -diacetyl-4 -p-coumarylrhamnoside 668.1583 Euphorbianin;Quercetin 3-(6 -acetylglucosyl)-(1-&gt;3)-galactoside;3-[[3-O-(6-O-Ace 724.1787 Platanoside;Kaempferol 3-(2 -3 -di-(E)-p-coumaroylrhamnoside);3-[[6-Deoxy-2-3-bi http://metabolomics.jp 756.1685 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 …. Cluster Wine Flavonoids Clustering based upon signal intensity profile Flavonoid database Absolute Quantitation Calibration Curve Method Standards Epicatechin Catechin Orientin Luteolin Ellagic Acid Quercetagetin Chrysin Genistein Dilution series at LC/MS using Thermo Data analysis with Rhamnetin four concentrations Q-Exactive SIEVE 2.0 Tamarixetin (.02, .04, .2,.4) mg/ml in 10% methanol Linear Regression Observed value in Zinfandel from Lake (16ug/ml) Linear Regression Observed value in Cabernet Sauvignon from Mendocino (74ug/ml) Absolute Quantitation 0.08 0.07 0.06 0.05 0.04 mg/ml Quercetagetin 0.03 L-Epicatechin 0.02 0.01 0 Contaminant Response Possible smoke related contaminants MolWt FORMULA NAME 209.9406 C7H5Cl3O 2,4,6-Trichloroanisole 150.0681 C9H10O2 2-Methoxy-4-vinylphenol (4-Vinylguaiacol) 168.1514 C11H20O 2-Methylisoborneol 122.0732 C8H10O 4- ethylphenol 152.0837 C9H12O2 4-ethylguaiacol 138.0681 C8H10O2 4-methylguaiacol 108.0575 C7H8O Cresol 164.0837 C10H12O2 Eugenol 96.02113 C5H4O2 Furfural 182.1671 C12H22O Geosmin 124.0524 C7H8O2 Guaiacol 286.1053 C13H18O7 ß-D-glycoside of Guaiacol 314.01 C14H18O8 ß-D-glycoside of vanillin 154.063 C8H10O3 Syringol Contaminant Response 0.0500 0.0450 0.0400 2-Methoxy-4-vinylphenol (4- 0.0350 Vinylguaiacol) 4- ethylphenol 0.0300 0.0250 Eugenol 0.0200 Furfural 0.0150 Syringol 0.0100 D-glycoside of Guaiacol 0.0050 D-glycoside of vanillin 0.0000 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: Team SEIVE [email protected] Mary Lopez Amy Zumwalt http://sieve.vastscientific.com Jennifer Sutton Mark Sanders http://vastscientific.com/rawmeat David Peakes Gouri Vadali Michael Athanas .
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