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Fundamental Studies of Separation Science Principles and Metrics
Instrumentation and Sensor Development
Data Analysis – Chemometrics – Software
Methodology Design and Optimization
Advances in Separation Science Knowledge and Technology:
10 nm
Synovec Research Group
Robert E. Synovec U. Washington, Chemistry
………from high-speed analysis of simple mixtures to the analysis of complex samples
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• Discovery-stage fundamental studies
• Real-time analytical technology
• Process optimization and control
Our research focus:
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• Metabolomics
- Food quality and safety - Bacteria - Yeast - Mice - Human disease profiling - Primates, related to human health
• Fuel characterization (Bio and Fossil)
• High Speed GC-on-a-chip
• On-line, Real-time Chromatographic Retention Time Alignment
• Chemometric Software Development
Current research projects:
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Metabolomics
“Metabolomics is the study of the small molecules that are an integral facet of cell biology, where the metabolites found in a given sample are inextricably connected to protein expression as manifested by gene regulation.”
“Metabolomics is emerging as possibly the most important of the “-omics” fields, providing complementary information in relation to the genomics and proteomics fields.”
…at the Discovery Stage ofthe process analysis effort….
Need to learn what to control !
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- Up in derepressed cells
- Up in repressed cells
Gene Expression
- Up in repressed cells
- Up in derepressed cells
Metabolite Concentration
Yeast cell studies with different growth conditions
Validation Study Analytical Goal:
Measure metabolite concentration ratio, in different growth conditions i.e., the [DR] / [R], to link control of gene expression to metabolic changes that occur in response to glucose limitation.
Glycerol
Glycerol-3-P Glyceraldehyde-3-P
Glucose-6-P
Dihydroxy-acetone-P
Pyruvate
L-Lactate
AcetaldehydeEthanol
Acetate Acetyl-CoA
Propionate
Propionyl-CoA
2-methyl-citrate
2-methyl-isocitrate
Threonine
Isocitrate
Formate
2H
CO2
2H
2H
2H
2H2H
2H
Oxaloacetate
Phosphoenol-pyruvate
Citrate
-KetoglutarateSuccinyl-CoA
Succinate
Fumarate
Malate
2H
2H
2H
Glyoxylate
ADH1
ADH2
GUT119
GUT27.8
FDH135
ALD4,68.6, 3.4
CYB28.1
PDC5,-2.6
ACH15.2
-2.1
LSC2
FUM1
PYK1
PYC1,2
PDA1,2etc.
2H2H
PGI1
2H
TPI1-2.0?
ACS143
,2
GPM1
PGK1
TDH1,2,3
PFK1,2
FBA1
CIT350
KGD1,2LPD1
IDH1,2
IDP221
ICL128
SDH3,43.1, 3.0
,1,2
ENO1,2-2.4, -2.1
ACO13.2
ACO13.2or
Pyruvate
ICL221
MLS111
BAT1-5.0
,2
128
1,6
92
6.9
ACS143
,215
2.2
PDH143
5.8, 4.7, 50
PathwaysFructose- 1,6-P
Young, Elton T., et.al. J Biol. Chem. (2003), 278, 26146-26158.
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Comprehensive Two-Dimensional Gas Chromatography (GC x GC)
Column 1 Time, seconds
Co
lum
n 2
Tim
e,
seco
nd
s
FID
Sig
nal
15 Component Mixture: REAL-TIME separation into different chemical classes!
Column 1 (Non-Polar)–10-m x 320-m i.d. –0.25-m poly(5% diphenyl/ 95% dimethyl siloxane)
–35C initial, 120C/min program, 25.5 psi H2
Column 2 (Polar)–2-m x 250-m i.d. –0.2-m cyanopropyl polysiloxane
–100C, 25.0 psi H2
15 20 25 30 35 40 45
0.3
0.4
0.5
0.6
Column 1 Time, Seconds
Co
lum
n 2
Tim
e,
Se
co
nd
s
Alcohols
Ketones
Alkyl Benzenes
Alkanes
15 20 25 30 35 40 45
0.3
0.4
0.5
0.6
Column 1 Time, Seconds
Co
lum
n 2
Tim
e,
Se
co
nd
s
Alcohols
Ketones
Alkyl Benzenes
Alkanes
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Comprehensive Two-Dimensional Gas Chromatography with Time-of-Flight Mass
Spectral Detection (GC x GC - TOFMS)
• Complete mass spectra peak identification
• Fast 500 spectra / second Peak widths on column two ~ 50 ms
• Adds another selective dimension 3rd - order technique, benefit by using chemometric software
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Time 1, minutes
Time 1, minutes
Time 1, minutes
Time 2, seconds
Time 2, seconds
Time 2, seconds
Ion
Co
un
tsIo
n C
ou
nts
Ion
Co
un
ts
Extracted Ion Chromatograms
m/z 217
m/z 128
m/z 73
m/z
Time 1 Tim
e 2
Data Cube
3rd Order Data• column 1 retention time • column 2 retention time • full mass spectrum at each point
We analyze the RAW data!
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Typical data, yeast grown in glucose conditions
GC x GC –TOFMS of Repressed Yeast Cell Extract, m/z = 73, Metabolites have been derivatized: m/z = TMS group is a “selective” channel
•Over 590 peaks at this m/z alone - Complex !•Many data runs…a huge amount of data to process !
ISSUES:
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Repressed Yeast Sample: subsection shows excellent chromatographic separation efficiency in two dimensions !
m/z 73
But not all of the 590+ peaks are important……..need high-throughput data reduction !
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Chemometric data analysis tools: utilize 3rd order data structure
(1) Discover sample-class distinguishing locations in 2D separation space – Data reduction by a 3D Fisher ratio method, Signal ratio method
(2) Targeted metabolite analysis: 3D mathematical resolution, confirmed mass spectral identification and quantification – PARAFAC GUI ….state-of-the-art software tools to apply powerful Linear Algebra concepts
Discovery-Based Approach:Discovery-Based Approach: comprehensively explore the comprehensively explore the data using chemometric classification/data reduction data using chemometric classification/data reduction methods to methods to “discover” “discover” the sample-distinguishing metabolitesthe sample-distinguishing metabolites
From high throughput data reduction and analysis to valuable information !
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TCA Cycle
R- glucose DR- ethanol
Glucose
Ethanol Acetyl CoA
glycolysis
Study Protein Function with Metabolomics (Snf1 mutant study)
• Study this mutant strain at metabolome level• Wild type (R & DR)• Mutant (R & DR)
• In the absence of specific proteins (Snf1 Protein Complex) cells are unable to switch from using glucose to ethanol
~ 160 metabolites analyzed
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TCA Cycle
Glucose
Ethanol Acetyl CoA
glycolysis
Study Protein Function with Metabolomics (Snf1 mutant study)
XX
ΔSnf1 cannot
complete the shift
• Study this mutant strain at metabolome level• Wild type (R & DR)• Mutant (R & DR)
• In the absence of specific proteins (Snf1 Protein Complex) cells are unable to switch from using glucose to ethanol
~ 160 metabolites analyzedR- glucose DR- ethanol
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0
0.00002
0.00004
0.00006
0.00008
0.0001
0.00012
0.5 2 4 6Time (hours)
No
rmal
ized
(T
IC)
PA
RA
FA
C v
olu
me
Fumarate
• TCA Cycle is active in DR conditions• Snf1 protein complex needed to make shift from R
to DR conditions
TCA Cycle
Glucose
Ethanol Acetyl CoA
glycolysis
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Cacao Beans and the Chocolate Industry
Organic, Fair Trade, Bean-to-BarChocolate Factory, Seattle, WA
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Differences can be IdentifiedDifferences can be Identified
UNMOLDED
MOLDED
UnmoldedMolded
Analyte 3
0
1E7
2E7
3E7
4E7
5E7
6E7
1 2 3 4 5 6 7 8 9 10
Pea
k A
rea
Bean Number
Analyte 4
1 2 3 4 5 6 7 8 9 100
5.0E5
1.0E6
1.5E6
2.0E6
2.5E6
Bean Number
Others analytes are elevated in Molded Samples:
Some analytes are elevated in Unmolded Samples:
Pea
k A
rea
Analyte 1
0
2.0E7
4.0E7
6.0E7
8.0E7
1.0E8
1.2E8
1.4E8
1.6E8
1.8E8
1 2 3 4 5 6 7 8 9 10Bean Number
Analyte 2
0
5.0E6
1.0E7
1.5E7
2.0E7
2.5E7
3.0E7
1 2 3 4 5 6 7 8 9 10Bean Number
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Separation conditions must be fully optimized
Fully Integrated Micro-GC:•Injection
•Separation•Detection
Minimal Dead VolumesPotential for Large
Dead Volumes
Standard GC:•Injection
•Separation•Detection
Miniaturization of Instrument Components
GC-on-a-chip:Instrumentation Challenges of High-Speed GC
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• 50 sq. micron channels x 30 cm
• 30 sec CNT growth time
• Integrated thin film resistive heating:
5 nm Ti 100 nm Pt
Microfabricated GC-on-a ChipMicrofabricated GC-on-a Chip
Reid, V.R., Stadermann, M., Bakajin, O., Synovec, R.E. Talanta, 2009, 77, 1420-1425.
1 μm
SEM image Back of Chip
HydrogenCarrier
Gas
Commercial GC Injector
Diaphragm Valve Injection
Voltage/Grounding
Leads
VariableAC Power
Supply(0 -120 V)
V1 V2
HydrogenCarrier
Gas
Commercial GC Injector
Diaphragm Valve Injection
Voltage/Grounding
Leads
VariableAC Power
Supply(0 -120 V)
Vent FID
V
DeactivatedSilica Capillary
Leads
HydrogenCarrier
Gas
Commercial GC Injector
Diaphragm Valve Injection
Microfabricated SWCNT Column 30 cm, 50 μm x 50 μm
Voltage/Grounding
Leads
VariableAC Power
Supply(0 -120 V)
FID
V
DeactivatedSilica Capillary
Leads
FID
V
Top of Chip
with Carbon Nanotube (CNT) Stationary Phase and High-Speed Resistive Heating with Carbon Nanotube (CNT) Stationary Phase and High-Speed Resistive Heating collaboration with Lawrence Livermore National Lab (LLNL)collaboration with Lawrence Livermore National Lab (LLNL)
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Solution to General Elution Problem: Rapid Temperature Solution to General Elution Problem: Rapid Temperature Programming via Resistive Heating ~ 1500 °C/minProgramming via Resistive Heating ~ 1500 °C/min
(Hexane, Octane, Nonane, Decane and Undecane)Ti = 50 ºC, H2 carrier gas at 10 psi, 15 ms injection pulse
Application of 36 V yields 1560 ºC/min
0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 2.40
0.2
0.4
0.6
0.8
1
1.2
Time, seconds
FID
Sig
nal,
volts
50 °C 115 °C
C11
C6
C8C9
C10
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Recently Joined:
Angie MadridMahmoud Al-Shaer Ryan WilsonTom Dearing (post doc)
Pictured:
Rachel Mohler (PhD)Chris SieglerVanessa Reid (PhD)Jeremy NadeauLiz HumstonNate Watson (MS)Matthew VanWingerden (UG) Jamin Hoggard (PhD, post doc)Thomas Skov (PhD, R. Bro)
Synovec Research Group
Funding and Support: NIH, WTC, Theo Chocolate, LECO, PNNL, LECO, LLNL, CPAC and various sponsors
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After Today’s Webinar• Please go to the CPAC
web site (www.cpac.washington.edu) for the program and registration details of the CPAC Spring Meeting, May 4-7, 2009
• We would like you to respond to a short questionnaire regarding the topics of this webinar – please provide your e-mail address to [email protected]