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
• Discovery-stage fundamental studies
• Real-time analytical technology
• Process optimization and control
Our research focus:
• 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:
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 !
- 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.
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
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
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!
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:
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 !
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 !
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
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
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
Cacao Beans and the Chocolate Industry
Organic, Fair Trade, Bean-to-BarChocolate Factory, Seattle, WA
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
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
• 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)
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
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
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]