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11/30/2007
1
Applications of Molecular Applications of Molecular Biotechnology:Biotechnology:Ethanol Production from Cellulosic BiomassEthanol Production from Cellulosic Biomass
David R. ShonnardDavid R. ShonnardDepartment of Chemical Engineering Department of Chemical Engineering
CM4710 Biochemical ProcessesCM4710 Biochemical ProcessesNovember 30, November 30, 20072007
Presentation OverviewPresentation Overview
nn Ethanol from Ethanol from LignocellulosicLignocellulosic Biomass and its Potential to Biomass and its Potential to Displace Petroleum in the Displace Petroleum in the USAUSA
nn Research Needs in Forest Resources, Bioconversion Research Needs in Forest Resources, Bioconversion Processing, Engines, and Decision AnalysisProcessing, Engines, and Decision Analysis
nn Dilute Dilute Acid Pretreatment of Tree Species from the Upper Acid Pretreatment of Tree Species from the Upper Midwest RegionMidwest Region
nn Enzymatic Hydrolysis of Pretreated Woody BiomassEnzymatic Hydrolysis of Pretreated Woody Biomass
nn Genetic Engineering of E. coli for ethanol production from Genetic Engineering of E. coli for ethanol production from woody biomasswoody biomass
11/30/2007
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Managing the Carbon Cycle:Managing the Carbon Cycle:A Sustainable Energy ChallengeA Sustainable Energy Challenge
From http://www.bom.gov.au/info/climate/change/gallery/index.shtml
Combustion of Fossil Fuels acts as a Carbon PumpCombustion of Fossil Fuels acts as a Carbon Pump
COCO22 and Temperature in the and Temperature in the Northern Hemisphere are RisingNorthern Hemisphere are Rising
National Geographic, September 2004, pg 20, National Geographic Society, Washington, D.C.
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WoodWood--toto--Wheels (W2W) ConceptWheels (W2W) ConceptResearch Thematic AreasResearch Thematic Areas
Woody Biomass Resource Research
CO2
Bio-Processing ResearchPhoto: Glacial Lakes Energy
Vehicle Systems Research
SustainabilityAssessments /
Decision-Making
But, How Much Biomass is Available on But, How Much Biomass is Available on an Annual Basis in the USA?an Annual Basis in the USA?
Biomass as Feedstock for a Bioenergy and Bioproducts Industry: Technical Feasibility of a Billion ton Annual Supply: DOE/GO-102995-2135, April 2005.
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Forest Forest Biomass Biomass SourcesSources
Biomass as Feedstock for a Bioenergy and Bioproducts Industry: Technical Feasibility of a Billion ton Annual Supply: DOE/GO-102995-2135, April 2005.
AgricultureAgricultureBiomass Biomass SourcesSources Biomass as Feedstock for a Bioenergy and Bioproducts Industry: Technical
Feasibility of a Billion ton Annual Supply: DOE/GO-102995-2135, April 2005.
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How Much Petroleum is Used �.How Much Petroleum is Used �.Biomass as Feedstock for a Bioenergy and Bioproducts Industry: Technical Feasibility of a Billion ton Annual Supply: DOE/GO-102995-2135, April 2005.
.. and for What Purpose?.. and for What Purpose?Wang, Michael; Center for Transportation Research, Argonne National Laboratory
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How Much Gasoline Could be Replaced with How Much Gasoline Could be Replaced with Ethanol From 1B tons Ethanol From 1B tons LignocelluloseLignocellulose??
{ 1B tons biomass x 70{ 1B tons biomass x 70--100 gal Ethanol/ton biomass x 100 gal Ethanol/ton biomass x
.75 gal gasoline/gal Ethanol x 1.75 gal gasoline/gal Ethanol x 1--2 (efficiency of automobiles)} / 2 (efficiency of automobiles)} /
140B gal gasoline demand140B gal gasoline demand = 37.5= 37.5--75%75%
….displace 37.5-75% of current U.S. gasoline demand
0.0
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RFG Corn EtOH Cell. EtOH
Btu
/btu
Are There Energy Benefits of Fuel Ethanol? Are There Energy Benefits of Fuel Ethanol? Fossil Energy and Petroleum UseFossil Energy and Petroleum Use
Energy in fuel
Energy for producing fuel
Uncertainty Range
Energy Use for Each Btu of Fuel Used
Wang, Michael; Center for Transportation Research, Argonne National Laboratory
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Changes in Greenhouse Gas Emissions Changes in Greenhouse Gas Emissions per Mile Driven (Relative to GVs)per Mile Driven (Relative to GVs)
-90%
-80%
-70%
-60%
-50%
-40%
-30%
-20%
-10%
0%
CO
2
GH
G
CO
2
GH
G
CO
2
GH
G
CO
2
GH
G
E85 FFV: Corn EtOH E85 FFV: Cell. EtOH E10 GV: Corn EtOH E10 GV: Cell. EtOH
Cha
nges
Rel
ativ
e to
GV
sWang, Michael; Center for Transportation Research, Argonne National Laboratory
Forest ResourcesForest ResourcesBiotechnology/Genetic Biotechnology/Genetic
engineeringengineering
Forest policy and Forest policy and managementmanagement
Carbon cyclingCarbon cycling
BioBio--processingprocessingEnzyme improvementEnzyme improvement
Pilot plant operationsPilot plant operations
Metabolic engineeringMetabolic engineering
Vehicle/EnginesVehicle/EnginesEngine researchEngine research
Engine tests w/emissionsEngine tests w/emissions
Hybrid vehicle designHybrid vehicle design
Vehicle dynamometerVehicle dynamometer
Michigan Tech�s Qualifications
Assessment/DecisionsAssessment/DecisionsTechnology evaluationTechnology evaluation
Logistics and facilitiesLogistics and facilities
LifeLife--cycle, environmental, ancycle, environmental, an
d policy assessmentsd policy assessments
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Microarray Gene Expression Analysis
Metabolite Profiling&
Chemical Fingerprinting
Our expertise:Micropropagation
Gene transformationMolecular biochemistry
Whole-genome microarrayand metabolite profiling
Research areas:Wood formation
Defense & fitnessNatural variations
Carbon sequestration
Forest Functional Genomics & Forest Functional Genomics & BiotechnologyBiotechnology
Cellulosic Cellulosic Biomass Biomass StructureStructure
Breaking the Biological Barriers to Cellulosic Ethanol: A Joint Research Agenda: DOE/SC 0095, June 2006.
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Composition of Woody BiomassComposition of Woody Biomass
Beguin, P., J.P. Aubert. 1994. �The biological Degradation of Cellulose�. FEMS Microbiology Reviews. 13:25-58
1. Cellulose2. Hemicellulose3. Lignin
Composition of Dry Cellulosic BiomassComposition of Dry Cellulosic Biomass
Cellulose(35-50%)
Dry Cellolosic Biomass
Hemicellulose(20-35%)
Glucose6-C sugars
Lignin(12-20%)
XyloseArabanoseMannoseGalactose(5-C sugars)
hydrolysishydrolysis
no hydrolysis
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Thermochemical ConversionsThermochemical Conversions�� Optimize Optimize biomassbiomass--toto--sugar sugar
reactionsreactions�� Reduce byproduct reactionsReduce byproduct reactions�� Evaluate timber species� mixtures Evaluate timber species� mixtures �� IncreaseIncrease biodiesel yieldsbiodiesel yields
Integrated Bioprocess FacilityIntegrated Bioprocess Facility�� IntegrateIntegrate fermentation and fermentation and
purification to increase fuel yields purification to increase fuel yields �� Test Test monitoring devices and monitoring devices and
process control schemesprocess control schemes�� MinimizeMinimize energy consumption and energy consumption and
waste generationwaste generation
Biochemical ConversionsBiochemical Conversions�� Develop/test highDevelop/test high--activity activity
cellulasescellulases for tree species mixturesfor tree species mixtures�� Optimize cellulose hydrolysis using Optimize cellulose hydrolysis using
peptidomimeticspeptidomimetics�� Improve fermentations for Improve fermentations for high high
yieldsyields of ethanol / other bioof ethanol / other bio--based based materialsmaterials
�� Use metabolic flux analysis to Use metabolic flux analysis to guide guide strain improvementstrain improvement
Product PurificationProduct Purification�� BoostBoost yields by coupling membrane yields by coupling membrane
separation with fermentation separation with fermentation �� ConserveConserve water by recovering and water by recovering and
recycling reactantsrecycling reactants
BioBio--processing Initiatives: processing Initiatives:
NREL Process to Convert NREL Process to Convert LignocellulosicLignocellulosic Biomass to EthanolBiomass to Ethanol
Saccharification is enzymatic hydrolysis of pretreated cellulose yielding Glucose using cellulase from Trichoderma reesei
Charles E. Wyman, “Biomass Ethanol: Technical Progress, Opportunities, and Commercial Challenges”, Annu. Rev. Energy Environ.,1999, 24: 189-226.
1 – 3 mm
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Pretreatment of Woody Biomass Pretreatment of Woody Biomass
nn Goals: Goals: Prepare cellulose fraction for enzymatic hydrolysisPrepare cellulose fraction for enzymatic hydrolysisnn Convert crystalline Convert crystalline cellulose cellulose to amorphousto amorphousnn Remove some lignin from the cell wallRemove some lignin from the cell wallnn Increase accessibility or enzymes to celluloseIncrease accessibility or enzymes to cellulosenn Convert Convert hemicellulosehemicellulose fraction of the wood to sugarsfraction of the wood to sugars
nn Dilute acid hydrolysis resultsDilute acid hydrolysis results
Dilute Acid PretreatmentDilute Acid Pretreatment
0.25-1.0%Diluted H2SO4
Minimal Degradation Product
Shu C. Yat, 2006
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Goals of Pretreatment ResearchGoals of Pretreatment Research
nn Investigate Mixture EffectsInvestigate Mixture EffectsMixtures of timber species plus Mixtures of timber species plus switchgrassswitchgrassHypothesisHypothesis: no synergistic or antagonistic effects due to : no synergistic or antagonistic effects due to use of mixturesuse of mixtures
nn Model pretreatment reactionsModel pretreatment reactionsDevelop kinetic parameters from single species Develop kinetic parameters from single species exptsexpts..Predict Predict monomericmonomeric sugar concentrations for single species sugar concentrations for single species and mixtures and compare with experimental yieldsand mixtures and compare with experimental yields
nn Small scale pretreatments using �mini� reactor Small scale pretreatments using �mini� reactor systemsystem
Analyze small scale (< 1/100x) samples of biomassAnalyze small scale (< 1/100x) samples of biomass
Experimental Strategy for Pretreatment Experimental Strategy for Pretreatment of 50:50 Biomass Mixturesof 50:50 Biomass Mixtures
SWITCHGRASS
ASPEN RED MAPLE
BALSAM BASSWOOD
1
2
3 6
5
4
8
7
10
9
Duplicates for each experiment were performed.
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13
Methods: Reactor ExperimentsMethods: Reactor Experiments
nn Initial reactor temp. setpoint = 400Initial reactor temp. setpoint = 400ooCC
nn Initial temperature = Room TemperatureInitial temperature = Room Temperature
nn Initial pressure = 15 psiInitial pressure = 15 psi
nn Agitator speed = 50 rpmAgitator speed = 50 rpm
nn Record pressure and temperature readingsRecord pressure and temperature readings
nn Collect samples during experiment for HPLC analysisCollect samples during experiment for HPLC analysis
nn AspenAspennn BalsamBalsamnn BasswoodBasswoodnn Red MapleRed Maplenn SwitchgrassSwitchgrass
Shu C. Yat, 2006
Experimental Results Experimental Results -- ReproducibilityReproducibility
0
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0 20 40 60 80
Tem
pera
ture
('C
)
Time (min)
Time Temperature Profile
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10/12/2007
10/18/2007
10/23/2007
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Results Results �� Obtained by HPLC DetectionObtained by HPLC Detection
!"#$%&'%(&)'""*++(&,-.,-&/01234$&'50(&67(4+87"0"&4$"382"9&:6$&$1#$40/$%2'8&('2'&;+4&'88&;0<$&"3='4"&'%(&;34;34'8>&26$&/'0%&($=4'('20+%+(352>&'4$&"6+*%&0%&260"+29&?'2'&0"&;+4&"'/#80%=&20/$&#$40+(9
0
2
4
6
8
10
45 65 85 105
Co
nce
ntr
atio
n (
g/L
)
Time (min)
Xylose MonomerXylan Oligomer
@'""*++(&'%(&4$(&/'#8$&,-.,-&/01234$&'50(&67(4+87"0"&178+"$&/+%+/$4&'%(&+80=+/$4&;+4/'20+%&'%(&($=4'('20+%&264+3=6+32&26$&"'/#80%=&20/$&#$40+(9
0
2
4
6
8
45 65 85 105
Co
nce
ntr
atio
n (g
/L)
T ime (min)
Glucose
Xylose
Galactose
Arabinose
Mannose
Furfural
Biomass MixturesBiomass Mixtures
0
1
2
3
4
5
6
7
8
9
45 65 85 105 125
Con
cent
ratio
n (g
/L)
Time (min)
Xylose Formation and Degradation
Red Maple
Balsam
Red Maple/Balsam Mix1
Red Maple/Balsam Mix2
Expermiental results for red maple and balsam single species experiments compared with red maple/balsam 50/50 mixture results.
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Modeling Modeling XyloseXylose Reaction KineticsReaction Kinetics
XyloseXylose Kinetic Model Formation Kinetic Model Formation
•• Some studies assume that the Some studies assume that the hemicellulosehemicellulose contains two types of contains two types of xylanxylan, a , a fast reacting fraction and a slow reacting fraction. One example of a kinetic fast reacting fraction and a slow reacting fraction. One example of a kinetic model assuming this relationship is shown in [1].model assuming this relationship is shown in [1].
•• Other studies assume there is an intermediate Other studies assume there is an intermediate xylanxylan oligomeroligomer formation step formation step that is necessary for kinetic that is necessary for kinetic modellingmodelling. An example of this approach is shown . An example of this approach is shown in [2].in [2].
f
s
kFast Reacting Xylan
kSlow Reacting Xylan
Hemicellulose →
→
2kXylose Degradation Byproducts→A0%&80B30(CA178'%C
!"#
1
2
kFast Reacting Xylan
kSlow Reacting Xylan
Hemicellulose →
→
3 4k kO X D→ →
D6$4$&E&0"&"+83)8$&178'%&+80=+/$4>&F&0"&F78+"$>&'%(&?&0"&($=4'('20+%&)7#4+(352"
!$#
GHI&J"2$=68'80'%>&!9>&K'"60/+2+>&!9L9>&M$%"N$>&O9O9>&P$%%$4>&Q9K9&HRRS9&Q+($80%=&'%(&E#20/0T'20+%&+;&26$&?0832$UV38;3405U!50(&P4$24$'2/$%2&+;&W+4%&V2+<$4>&P+#8'4&'%(&V*0256=4'""9&@0+4$"+345$&:$56%+8+=7>&,R>&HXRUHYZ9GXI&W6$%>&[9>&\$$>&]9]9>&:+4=$2>&[9&HRRZ9&^0%$205&'%(&Q+($80%=&_%<$"20='20+%&+%&:*+UV2'=$&&[$<$4"$UM8+*&[$'52+4&'"&!##80$(&2+&?0832$U!50(&P4$24$'2/$%2&+;&!=40538234'8&[$"0(3$"9&!##80$(&@0+56$/0"247&'%(&@0+2$56%+8+=79&,S.,`>&HYYUHaZ9
3030
11/30/2007
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•A third kinetic modeling approach simplifies the above models and utilizes a pseudo first order rate constant. Experimental data in these studies suggest that the biphasic nature of the substrates is negligible. This approach is shown in [3].
•An improved application of the kinetic model in equation [3]was used in this work to determine the kinetic parameters for pure biomass pretreatment which takes into account the simultaneous mechanisms of xylose production and degradation and is shown in [4].
!%#
( )( )( )
1 1 21 1
1
2 1
12(0.88) 2
12
i i i ii
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∆ ∆ + ⋅ + ⋅ − = ∆+
1 2( ) ( ) ( )k kHemicellulose H Xylose X Degradation Products D→ →
D6$4$&K&4$;$4"&2+&26$&6$/05$8838+"$&;4'520+%&+;&26$&)0+/'"">&N&4$;$4&2+&4'2$&5+%"2'%2">&b2&4$;$4"&2+&26$&20/$&"2$#>&'%(&F&4$;$4"&2+&178+"$&5+%5$%24'20+%
!&#
GYI&]'2>&V9W9>&@$4=$4>&!9>&V6+%%'4(>&?9[9&X--S9&^0%$205&W6'4'52$40T'20+%&;+4&?0832$&V38;3405&!50(&K7(4+87"0"&+;&:0/)$4&c'40$20$" '%(&V*0256=4'""9&@0+4$"+345$&:$56%+8+=79&_%&P4$""9
XyloseXylose Kinetic Model Formation (cont.) Kinetic Model Formation (cont.)
:6$&/'""&)'8'%5$"&3"$(&2+&($40<$&+34&/+($8&$1#4$""0+%&'4$d
and ;+4&26$&)4$'N(+*%&+;&
6$/05$8838+"$&'%(&26$&;+4/'20+%&+;&178+"$&*6$4$& 0"&26$&($=4'('20+%&+;&178+"$9AK&4$;$4"&2+&26$&6$/05$8838+"$&;4'520+%&+;&26$&)0+/'"">&N&4$;$4&2+&4'2$&5+%"2'%2"&A!446$%03"C>&F&4$;$4"&2+&178+"$&5+%5$%24'20+%>&'%(&-9``&0"&26$&4'20+&+;&26$&6$/05$8838+"$&/+8$538'4&*$0=62&#$4&"3='4&3%02&2+&26$&/+8$538'4&*$0=62&+;&178+"$9C&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&&
*6$4$&
Basis of Our Kinetic ModelBasis of Our Kinetic Model
nn ^0%$205&P'4'/$2$4"&A#4$^0%$205&P'4'/$2$4"&A#4$UU$1#+%$%20'8&;'52+4"&!$1#+%$%20'8&;'52+4"&!+H+H e&!e&!+X+X>&&'%(&'520<'20+%&>&&'%(&'520<'20+%&$%$4=0$"&J$%$4=0$"&JHH e&Je&JXXC&5'%&)$&5'8538'2$(9&A[&0"&26$&='"&5+%"2'%2>&:&0"&C&5'%&)$&5'8538'2$(9&A[&0"&26$&='"&5+%"2'%2>&:&0"&2$/#$4'234$>&W&0"&'50(&5+%5$%24'20+%&A*fC&'%(&/&0"&'50(&5+%5$%24'20+%&2$/#$4'234$>&W&0"&'50(&5+%5$%24'20+%&A*fC&'%(&/&0"&'50(&5+%5$%24'20+%&$1#+%$%29C$1#+%$%29C
nn !&%3/$405'8&/+($8&;+4&26$&;+4/'20+%&+;&!&%3/$405'8&/+($8&;+4&26$&;+4/'20+%&+;&F78+"$F78+"$ 0"&($<$8+#$(&)7&'(g3"20%=&26$&0"&($<$8+#$(&)7&'(g3"20%=&26$&N0%$205&#'4'/$2$4"N0%$205&#'4'/$2$4"
1
dHk H
dt= − 1
20.88
k HdXk X
dt= −
2
dXk X
dt= −
/E RTk Ae−= moA A C=
11/30/2007
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Single Species Single Species XyloseXylose Formation and Formation and Degradation ModelsDegradation Models
A B C
D ESingle species kinetic models and experimental data for xylose formation and degradation of: (A)Switchgrass (B) Balsam (C) Red Maple (D) Aspen and (E) Basswood. For all species: (♦) experimental data and (!) model data.
Single Species and Mixtures Data and Single Species and Mixtures Data and Mixtures Kinetic Model Predictions for Mixtures Kinetic Model Predictions for
XyloseXylose Formation and DegradationFormation and Degradation
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Co
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/L)
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/L)
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F
Figure 2: Single species and mixture experimental data plotted with mixture model prediction for xylose formation and degradation of (A)Basswood/Red Maple Mixture (B)Basswood/Switchgrass (C)Aspen/Balsam (D)Balsam/Switchgrass (E)Aspen/Basswood and (F)Red Maple/Switchgrass. For A-F: ■ experimental data mixture 1, ▲experimental data mixture 2, ▬ (thick line) model mixture 1, ! (thin line) model mixture 2. Single species experimental data: (A) * Aspen, ● Balsam (B) * Basswood, ● Switchgrass (C) * Balsam, ● Switchgrass (D) * Basswood, ● Red Maple (E) * Aspen, ● Basswood and (F) * Red Maple, ● Switchgrass.
11/30/2007
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Single Species Theoretical YieldsSingle Species Theoretical Yields
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Mixtures Theoretical YieldsMixtures Theoretical Yields
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Mixtures ResultsMixtures Results
•The hypothesis that mixtures of the five biomass species should have no net effect on the individual species kinetics has held true.
•The kinetics of these individual species as generated by the new kinetic model are in excellent agreement with experimental data and can be used to accurately predict xylose concentrations obtained from mixtures of the biomass species.
•Mixtures of the five species studied can be pretreated simultaneously and maximum sugar yields, which are comparable to individual species yields, will still be obtained when the optimum temperature is reached.
Small Scale PretreatmentSmall Scale Pretreatment
nn System of mini reactors System of mini reactors SwagelockSwagelock SteelSteelAllows for greater than 100% reaction volume Allows for greater than 100% reaction volume decreasedecrease
nn Enzymatic hydrolysis can also be done on Enzymatic hydrolysis can also be done on small scalesmall scale
nn Forestry WorkForestry Work3 Wild Type Poplar Controls and 5 modified 3 Wild Type Poplar Controls and 5 modified Poplar samples (big leaf)Poplar samples (big leaf)Less than 4 grams total of each sampleLess than 4 grams total of each sample
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Similarities and Differences Similarities and Differences in Reaction Setupin Reaction Setup
nn Setup still allows for temperature controlSetup still allows for temperature controlnn Only one sugar sampleOnly one sugar samplenn Normal heat up with rapid coolingNormal heat up with rapid coolingnn Identified 170Identified 170°°C as optimum C as optimum
temperaturetemperaturenn Not enough liquid volume to study Not enough liquid volume to study
oligomersoligomers
Forestry Work ResultsForestry Work Results
'
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Future and Ongoing WorkFuture and Ongoing Work
nn Future work needs to be done to further study the Future work needs to be done to further study the oligomericoligomeric trends as well as the feasibility of converting trends as well as the feasibility of converting the the oligomersoligomers into monomers.into monomers.
nn Modeling Alternative Conditions of Reactor Operation Modeling Alternative Conditions of Reactor Operation --Different reactor configurations will be investigated in Different reactor configurations will be investigated in order to optimize process by maximizing products and order to optimize process by maximizing products and minimizing byproductsminimizing byproducts
CSTR: CSTR: Continuous Stirred Tank ReactorContinuous Stirred Tank Reactor
PFR: PFR: Plug Flow ReactorPlug Flow Reactor
nn Small scale enzymatic hydrolysis of hybrid poplarSmall scale enzymatic hydrolysis of hybrid poplar
Future and Ongoing Work (cont.)Future and Ongoing Work (cont.)
nn HeterologousHeterologous Expression and Mutagenesis of Cellulose Expression and Mutagenesis of Cellulose HydrolasesHydrolases for Improved Performancefor Improved Performance
nn Characterization of Improved Characterization of Improved CellulaseCellulase Enzymes for Cellulose Enzymes for Cellulose HydrolysisHydrolysis
nn Life cycle assessmentLife cycle assessment
nn Advanced imaging technology, including Scanning Electron Advanced imaging technology, including Scanning Electron Microscopy (SEM) and optical microscopy, of untreated, Microscopy (SEM) and optical microscopy, of untreated, pretreated, and pretreated, and enzymaticallyenzymatically hydrolyzed biomass samples to hydrolyzed biomass samples to view structural changes with fluorescent tagsview structural changes with fluorescent tags
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Scanning Electron MicroscopyScanning Electron Microscopy
SEM Image of Aspen prior to pretreatment
SEM Image of Aspen after pretreatment
Enzymatic Hydrolysis of Cellulose to Enzymatic Hydrolysis of Cellulose to Yield Glucose for FermentationYield Glucose for Fermentation
nn IntroductionIntroductionnn Technological issuesTechnological issues
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Building Blocks of CelluloseBuilding Blocks of Cellulose
ββββ-1,4 bonds
Difficult to hydrolyze
180 rotated
Repeat unit is cellobiose
100 � 14,000 glucose units
More easily hydrolyzed
Difficult to hydrolyze
Beguin, P., J.P. Aubert. 1994. �The biological Degradation of Cellulose�. FEMS Microbiology Reviews. 13:25-58
Hydrogen bondingbetween glucose unitsin adjacent chains
Beguin, P., J.P. Aubert. 1994. �The biological Degradation of Cellulose�. FEMS Microbiology Reviews. 13:25-58
Adsorption of cellulase componentsonto cellulose
Sequence of EventsSequence of Events
Endogluconases hydrolyze amorphous regions of celluloseyielding broken ended chains
Cellobiohydrolases attack the chainsfrom the non-reducing end yielding Cellobiose (2 glucose units)
ββββ-glucosidases break cellobiose into glucose units
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Components of Components of CellulasesCellulases
nn CBH CBH �� Cellobiohydrolases: Cellobiohydrolases: II attacks the nonattacks the non--reducing ends, reducing ends, IIIIattacks the the reducing ends of chainsattacks the the reducing ends of chains
nn EG EG �� endoglucanases: hydrolyze amorphous regionsendoglucanases: hydrolyze amorphous regionsnn ββ--glucosidases: split cellobiose to glucoseglucosidases: split cellobiose to glucosenn CBD CBD �� CelluloseCellulose--binding Domainbinding Domain
Valjamae, P. �The Kinetics of Cellulose Enzymatic Hydrolysis � Implications of the Synergism Between Enzymes�. ACTA Universitatis Upsaliensis. Uppsala. 2002
CellobiohydrolasesCellobiohydrolases
Valjamae, P. �The Kinetics of Cellulose Enzymatic Hydrolysis � Implications of the Synergism Between Enzymes�. ACTA Universitatis Upsaliensis. Uppsala. Sweden. 2002
Cellulose binding domain (CBD)
Tether portion
Active site
Crystalline cellulose
Cellobiose
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Observed rate of Cellulose HydrolysisObserved rate of Cellulose Hydrolysis
Valjamae, P. �The Kinetics of Cellulose Enzymatic Hydrolysis � Implications of the Synergism Between Enzymes�. ACTA Universitatis Upsaliensis. Uppsala. Sweden. 2002
Hypotheses1. Consumption of
easily hydrolysable components
2. Inhibition by reaction product cellobiose
3. Inactivation of cellulase
Rate decreases over time
Surface ErosionSurface ErosionModelModel
Valjamae, P. �The Kinetics of Cellulose Enzymatic Hydrolysis � Implications of the Synergism Between Enzymes�. ACTA Universitatis Upsaliensis. Uppsala. Sweden. 2002
1. Processivity of the CBH is hindered by the surface erosion pattern due to the strong binding of the CBD.
2. Mechanisms 2 and 3 from the previous slide are not important, as shown in the referenced work below.
Cellobiohydrolase (CBH)
Confronting other CBH
CBH confronts erosion features
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Enzyme Engineering of Enzyme Engineering of CellulaseCellulaseEnzymes for Enzymes for EEnhanced Activitynhanced Activity
nn Clone genes for Clone genes for cellulasescellulases into a suitable host cellinto a suitable host cellnn Perform random mutagenesis of on these genes Perform random mutagenesis of on these genes
using errorusing error--prone Polymerase Chain Reaction prone Polymerase Chain Reaction (PCR)(PCR)
nn Screen for enhanced activityScreen for enhanced activitynn Characterize �mutant� Characterize �mutant� cellulasescellulases for activity and for activity and
stabilitystabilitynn Sequence Sequence cellulasescellulases to determine the sites of to determine the sites of
mutationsmutationsnn MichaelMichael--BrodeurBrodeur Campbell and Jill Jensen (PhD Campbell and Jill Jensen (PhD
candidates)candidates)
Genetic Engineering of E. coli for Ethanol Genetic Engineering of E. coli for Ethanol Production from Woody BiomassProduction from Woody Biomass
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Process to Convert Cellulosic Biomass to Process to Convert Cellulosic Biomass to EthanolEthanol
1 –3 mm
0.8% H2SO4160ºC10 min
TrichodermareeseiFermentation
Genetically-engineered E. coli
Saccharification is enzymatic hydrolysis of pretreated cellulose yielding Glucose using cellulase from Trichoderma reesei
Charles E. Wymen, “Biomass Ethanol: Technical Progress, Opportunities, and Commercial Challenges”, Annu. Rev. Energy Environ.,1999, 24: 189-226.
History of Costs for Ethanol ProductionHistory of Costs for Ethanol Production
Sequential enzymatic hydrolysis then fermentation
Improved fungal strain for cellulaseproduction
Improved cellulase (150L) produced by Genencore
Charles E. Wymen, “Biomass Ethanol: Technical Progress, Opportunities, and Commercial Challenges”, Annu. Rev. Energy Environ.,1999, 24: 189-226.
Simultaneous Saccharification-Fermentation process
More efficient cellulase
Fermentation of 6C and 5C sugars using a single microorganism
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The cellulase responsible for enzymatic hydrolysis of pretreated cellulosic biomass is strongly inhibited by hydrolysis products: glucose and short cellulose chains. One way to overcome cellulase inhibition is to ferment the glucose to ethanol as soon as it appears in solution. SSF combines enzymatic hydrolysis with ethanol fermentation to keep the concentration of glucose low. The accumulation of ethanol in the fermenter does not inhibit cellulase as much as high concentrations of glucose, so SSF is a good strategy for increasing the overall rate of cellulose to ethanol conversion. It is important to keep the rate limiting step in mind. In SSF the ethanol production rate is controlled by the cellulase hydrolysis rate not the glucose fermentation, so steps to increase the rate of hydrolysis will lower the cost of ethanol production via SSF. The US Department of Energy, National Renewable Energy Laboratory (NREL) is funding Genercor International, Inc. to develop low cost cellulases that will reduce the cost of cellulose breakdown by a factor of 10.
Simultaneous Simultaneous SaccharificationSaccharification + + Fermentation (SSF)Fermentation (SSF)
The Challenge of Fermenting all Sugars in The Challenge of Fermenting all Sugars in BiomassBiomass
Saccharomyces cervisiae
Zymomonas mobilis
Ferment glucose to ethanolUtilize 6C sugars onlyTolerant to ethanol
Can these microorganisms be genetically engineered to utilize 5C sugars?
Escherichia coli
Can not ferment glucose to ethanolCan utilize 6C and 5C sugars
Is it easier to genetically engineer E. coli to ferment ethanol?
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GlycolysisGlycolysis: : EmbdenEmbden--MeyerhofMeyerhof--ParnasParnas(EMP) (EMP) PathwayPathway
�Principles of Biochemistry�Lehninger, Worth
This pathway is representative of a human muscle cell or E. coli
The end product is not ethanol
Is it Easier to Genetically Engineer This Is it Easier to Genetically Engineer This Pathway into Pathway into E. coliE. coli, or, or
Two genes are needed. One for pyruvatedecarboxylase and another for alcohol dehydrogenase. These enzymes working together in the cell will divert Pyruvate away from other fermentation products to ethanol. This would convert E. coli into an ethanol-producing microorganism, where before it was not! �Principles of Biochemistry�, Lehninger,
Worth
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Is it Easier to Genetically Engineer This Is it Easier to Genetically Engineer This Pathway into Pathway into S. cerviciaeS. cerviciae or or Z. mobilisZ. mobilis? ?
This is the Pentose Phosphate pathway in E. coli. This pathway is obviously more complicated, containing many more enzyme-catalyzed reactions than the two-step pathway on the previous slide. The pathway for other 5C sugars (arabanose, mannose, galactose) would be similar.
3 Xyloses would enter here
To Glycolysisand ethanol
ethanol
�Bioprocess Engineering: Basic ConceptsShuler and Kargi, Prentice Hall, 2002
Genetic Engineering of Ethanol Production Genetic Engineering of Ethanol Production in in E. coliE. coli
A plasmid for Pyruvatedecarboxylase (pdc)
Ingram, Conway, Clark, Sewell, and Preston, �Genetic engineering of ethanol production in E. coli�, App. Environ. Microbio., 1987, 53(10), 2420-2425.
A plasmid for Alcoholdehydrogenase (adh)
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Ethanol Ethanol Production Production in Sealed in Sealed Cultures Cultures of of E. coliE. coli TC4TC4
Ingram, Conway, Clark, Sewell, and Preston,�Genetic engineering of ethanol production in E. coli�,App. Environ. Microbio., 1987, 53(10), 2420-2425.
High Performance Liquid Chromatography Profiles
G = glucoseS = succinateL = lactic acidA = acetic acidU = unknownE = ethanol
Plasmid-free TC4 TC4withpLOI295
TC4withpLOI284
TC4withpLOI276
Questions?Questions?
Midwestern land cover (USFS North Central Research Station image)