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UNDERSTANDING THE DOSE RESPONSE OF CELLULASE
ENZYME COCKTAILS UNDER VARIABLE TEMPERATURE, pH AND
IONIC LIQUID CONDITIONS
Davis Hu1, Vimalier Reyes-Oritz2, Kenneth Sale2, Steve Singer2, Blake Simmons2
1Maryville College, Maryville, TN 37804 · 2Lawrence Berkeley National Laboratory
ABSTRACT
ACKNOWLEDGMENTS
This work was supported and made possible by the Center of Science and
Engineering Education at Lawrence Berkeley National Laboratory, U.S.
Department of Energy, Office of Science, and The Joint BioEnergy Institute. I would
like to thank my wonderful supporting mentors Vimalier Reyes-Oritz and Kenneth
Sale. I would also like to thank my safety work lead supervisor Steve Singer. Lastly,
I would also like to thank Vice President Blake Simmons who made my internship
possible by his wise selection of me for my participation in this program. This work
conducted by the Joint BioEnergy Institute was supported by the Office of Science,
Office of Biological and Environmental Research, of the U. S. Department of
Energy under Contract No. DE-AC02-05CH11231.
BACKGROUND
RESEARCH QUESTION
HOW CELLULASES WORK
EXPERIMENTAL/DATA FIGURES
MATERIALS/METHODS
Production of biofuels from sugars in lignocellulosic biomass is a promising
alternative to liquid fossil fuels, but there are barriers to overcome to maximize
production of fuels from these resources. Due to its composition of a complex
array of cellulose, hemicellulose and ligin polymers, lignocellulosic biomass is
extremely recalcitrant to degradation to glucose. The experiment proposed
consists of finding a mixture of enzymes that maximize the release of glucose at
an optimized temperature and pH and to study the dose response of the enzyme
mixture. Initial experiments were run on the individual enzymes over a range of
temperatures and pH to determine their optimal enzymatic conditions. This set of
enzymes was then mixed in various ratios to determine the combination of
cellulases that maximize glucose yields from ionic liquid pretreated switchgrass.
With these preliminary results, we will be able to seek future development of
inexpensive cellulosic biofuels at high yield production which would limit the
dependence on fossil based fuels which causes many significant adverse effects
to the environment and society.
INSTRUMENTAL ANALYSIS
• A major proportion (~85% in US) of energy
consumed is derived from oil, coal and natural gas.
• Concerns over depleting oil reserves and global
warming are fueling the development of alternative
sources of liquid transportation fuels to meet
increasing demands for generations and beyond.
• Lignocellulosic biomass is a potential feedstock for
renewable transportation fuels.
• Mixtures of enzymes compatible with the biomass
pretreatment process are required for production of
fermentable sugars.
• Thermophilic and Ionic Liquid Tolerant Enzymes
• Endo-Cellulase (Endo) – Cel_9A & Cel_5A
• Cellobiohydralase (CBH) – Csac
• β-Glucoside (BG) – βG
• Reaction Conditions
• Temperature – 50°C-80°C – Thermophilic to prevent contamination
and increase rate of reaction
• Ionic Liquid Content – 0%-20% Concentration
• Enzyme Load – 20 mg of enzyme/g of glucon
• Materials and Supplies
• Enzymes – E. Coli  Grow  Lysate  Purify  Buffer Exchange –
3-4 Days
• Substrate – Weigh into analytical 1.7 mL tubes
• Characterization Equipment
• High Performance Liquid Chromatography (HPLC)
• 2950 Biochemistry Analyzer (YSI)
• SpectraMax M2 Instrument for Dinitrosalycylic Acid Colorimetric
Assay
• Preparation and Running a DNS assay for Temperature Variance with enzymes Cel_9A and
Cel_5A AND for Temperature and pH Variance with enzymes Endo-cellulase,
Cellobiohydrase and β-Glucosidase
• Preparation and Running a DNS assay for an Enzyme Cocktail Solution
Figure 6. Typical wet-lab space at the Joint BioEnergy Institute
Figure 1. Cellulases work synergistically to catalyze the conversion
of cellulose to glucose by catalyzing the cleavage of the β(1-4)
bonds between the glucose units.
Figure 7. YSI 2950 Biochemistry Analyzer Instrument
Description/Diagram.
Figure 8. DNS colorimetric progression from yellow to red as a function
of increasing temperature.
Figure 9. SpectraMax M2 Instrument.
Figure 10. Schematic Diagram of a Spectrophotometer in SpectraMax M2.
0.340 0.345
0.000
0.050
0.100
0.150
0.200
0.250
0.300
0.350
0.400
35 45 55 65 75 85 95
Absorbance
Temperature(°C)
Temperature Profiles of Enzymes Cel_9A & Cel_5A
Cel_9A
Cel_5A
0.000
0.050
0.100
0.150
0.200
0.250
0.300
0.350
0.400
0.450
0.500
25 35 45 55 65 75 85
Absorbance
Temperature(°C)
Temperature Profiles of Enzymes ENDO, CBH and βG at pH 5,
6, 7
ENDO pH 5
ENDO pH 6
ENDO pH 7
CBH pH 5
CBH pH 6
CBH pH 7
βG pH 5
βG pH 6
βG pH 7
DISCUSSION/CONCLUSION
• Cel_9A had maximum activity 65°C and Cel_5A had maximum
activity at 85°C.
• The optimal (Temperature, pH) for each enzyme tested was (40 °C, 5)
for the endocellulase, (45°C, 5) for the cellobiohydralse and (75 °C,
7) for the β-glucosidase.
• Glucose yields increase steadily as a function of total enzyme dose.
- With ionic liquid pretreated switch grass (ILSG) as the substrate,
glucose yields increase rapidly between 100 and 400 nM befoe
beginning to level off.
- To the contrary, glucose yields from avicel reached a plateau at
200 nM and no further increase was observed even at a higher
enzyme doses.
- The approximate 3X greater glucose yields produced from ILSG
are likely due it having a higher content of amorphous cellulose
compared to the highly crystalline avicel substrate.
• The study could be extended to producing an optimized multi-
component enzyme mixture that maximizes glucose yields at a specific
temperature and pH.
Figure 3. Example of the colorimetric DNS cellulase assay.
Figure 4. Veriti 96 Thermal Cycler Heater for heating enzyme samples.
What is the proportion of each enzyme in a
mixture of enzymes that maximizes release
of glucose? What is the optimal enzyme
dose and the optimal temperature and pH
for the saccharification reaction?
Figure 5. Eppendorf Thermomixer Apparatus for heating and mixing of
enzyme/substrate samples
Figure 2. Schematic diagram example of enzymes Cel_9A and Cel_5A
arrangement in 96-well plate along with specified temperatures.
-0.1
0.1
0.3
0.5
0.7
0.9
1.1
0 25 50 100 200 400
Absorbance
Enzyme Concentration [nM]
Absorbance vs Enzyme Concentration of ILSG and Avicel
ILSG IL-Avicel
0
1
2
3
4
5
6
7
8
0 50 100 150 200 250 300 350 400 450
GlucoseConcentration(nM)
Enzyme Concentration (nM)
Glucose vs. Enzyme Concentration of ILSG and Avicel
GC ILSG
GC Avicel
Crystal
structure of a
b-glucosidase
Crystal
structure of an
endoglucanas
e
Crystal
structure
of a CBH
Plants Enzymes Microbes
feedstock
engineering
enzyme
engineering
fuels synthesis
pretreatment
LIGNOCELLULOSIC
BIOFUELS

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Research Poster Hu, Davis SULI Summer 2013

  • 1. UNDERSTANDING THE DOSE RESPONSE OF CELLULASE ENZYME COCKTAILS UNDER VARIABLE TEMPERATURE, pH AND IONIC LIQUID CONDITIONS Davis Hu1, Vimalier Reyes-Oritz2, Kenneth Sale2, Steve Singer2, Blake Simmons2 1Maryville College, Maryville, TN 37804 · 2Lawrence Berkeley National Laboratory ABSTRACT ACKNOWLEDGMENTS This work was supported and made possible by the Center of Science and Engineering Education at Lawrence Berkeley National Laboratory, U.S. Department of Energy, Office of Science, and The Joint BioEnergy Institute. I would like to thank my wonderful supporting mentors Vimalier Reyes-Oritz and Kenneth Sale. I would also like to thank my safety work lead supervisor Steve Singer. Lastly, I would also like to thank Vice President Blake Simmons who made my internship possible by his wise selection of me for my participation in this program. This work conducted by the Joint BioEnergy Institute was supported by the Office of Science, Office of Biological and Environmental Research, of the U. S. Department of Energy under Contract No. DE-AC02-05CH11231. BACKGROUND RESEARCH QUESTION HOW CELLULASES WORK EXPERIMENTAL/DATA FIGURES MATERIALS/METHODS Production of biofuels from sugars in lignocellulosic biomass is a promising alternative to liquid fossil fuels, but there are barriers to overcome to maximize production of fuels from these resources. Due to its composition of a complex array of cellulose, hemicellulose and ligin polymers, lignocellulosic biomass is extremely recalcitrant to degradation to glucose. The experiment proposed consists of finding a mixture of enzymes that maximize the release of glucose at an optimized temperature and pH and to study the dose response of the enzyme mixture. Initial experiments were run on the individual enzymes over a range of temperatures and pH to determine their optimal enzymatic conditions. This set of enzymes was then mixed in various ratios to determine the combination of cellulases that maximize glucose yields from ionic liquid pretreated switchgrass. With these preliminary results, we will be able to seek future development of inexpensive cellulosic biofuels at high yield production which would limit the dependence on fossil based fuels which causes many significant adverse effects to the environment and society. INSTRUMENTAL ANALYSIS • A major proportion (~85% in US) of energy consumed is derived from oil, coal and natural gas. • Concerns over depleting oil reserves and global warming are fueling the development of alternative sources of liquid transportation fuels to meet increasing demands for generations and beyond. • Lignocellulosic biomass is a potential feedstock for renewable transportation fuels. • Mixtures of enzymes compatible with the biomass pretreatment process are required for production of fermentable sugars. • Thermophilic and Ionic Liquid Tolerant Enzymes • Endo-Cellulase (Endo) – Cel_9A & Cel_5A • Cellobiohydralase (CBH) – Csac • β-Glucoside (BG) – βG • Reaction Conditions • Temperature – 50°C-80°C – Thermophilic to prevent contamination and increase rate of reaction • Ionic Liquid Content – 0%-20% Concentration • Enzyme Load – 20 mg of enzyme/g of glucon • Materials and Supplies • Enzymes – E. Coli  Grow  Lysate  Purify  Buffer Exchange – 3-4 Days • Substrate – Weigh into analytical 1.7 mL tubes • Characterization Equipment • High Performance Liquid Chromatography (HPLC) • 2950 Biochemistry Analyzer (YSI) • SpectraMax M2 Instrument for Dinitrosalycylic Acid Colorimetric Assay • Preparation and Running a DNS assay for Temperature Variance with enzymes Cel_9A and Cel_5A AND for Temperature and pH Variance with enzymes Endo-cellulase, Cellobiohydrase and β-Glucosidase • Preparation and Running a DNS assay for an Enzyme Cocktail Solution Figure 6. Typical wet-lab space at the Joint BioEnergy Institute Figure 1. Cellulases work synergistically to catalyze the conversion of cellulose to glucose by catalyzing the cleavage of the β(1-4) bonds between the glucose units. Figure 7. YSI 2950 Biochemistry Analyzer Instrument Description/Diagram. Figure 8. DNS colorimetric progression from yellow to red as a function of increasing temperature. Figure 9. SpectraMax M2 Instrument. Figure 10. Schematic Diagram of a Spectrophotometer in SpectraMax M2. 0.340 0.345 0.000 0.050 0.100 0.150 0.200 0.250 0.300 0.350 0.400 35 45 55 65 75 85 95 Absorbance Temperature(°C) Temperature Profiles of Enzymes Cel_9A & Cel_5A Cel_9A Cel_5A 0.000 0.050 0.100 0.150 0.200 0.250 0.300 0.350 0.400 0.450 0.500 25 35 45 55 65 75 85 Absorbance Temperature(°C) Temperature Profiles of Enzymes ENDO, CBH and βG at pH 5, 6, 7 ENDO pH 5 ENDO pH 6 ENDO pH 7 CBH pH 5 CBH pH 6 CBH pH 7 βG pH 5 βG pH 6 βG pH 7 DISCUSSION/CONCLUSION • Cel_9A had maximum activity 65°C and Cel_5A had maximum activity at 85°C. • The optimal (Temperature, pH) for each enzyme tested was (40 °C, 5) for the endocellulase, (45°C, 5) for the cellobiohydralse and (75 °C, 7) for the β-glucosidase. • Glucose yields increase steadily as a function of total enzyme dose. - With ionic liquid pretreated switch grass (ILSG) as the substrate, glucose yields increase rapidly between 100 and 400 nM befoe beginning to level off. - To the contrary, glucose yields from avicel reached a plateau at 200 nM and no further increase was observed even at a higher enzyme doses. - The approximate 3X greater glucose yields produced from ILSG are likely due it having a higher content of amorphous cellulose compared to the highly crystalline avicel substrate. • The study could be extended to producing an optimized multi- component enzyme mixture that maximizes glucose yields at a specific temperature and pH. Figure 3. Example of the colorimetric DNS cellulase assay. Figure 4. Veriti 96 Thermal Cycler Heater for heating enzyme samples. What is the proportion of each enzyme in a mixture of enzymes that maximizes release of glucose? What is the optimal enzyme dose and the optimal temperature and pH for the saccharification reaction? Figure 5. Eppendorf Thermomixer Apparatus for heating and mixing of enzyme/substrate samples Figure 2. Schematic diagram example of enzymes Cel_9A and Cel_5A arrangement in 96-well plate along with specified temperatures. -0.1 0.1 0.3 0.5 0.7 0.9 1.1 0 25 50 100 200 400 Absorbance Enzyme Concentration [nM] Absorbance vs Enzyme Concentration of ILSG and Avicel ILSG IL-Avicel 0 1 2 3 4 5 6 7 8 0 50 100 150 200 250 300 350 400 450 GlucoseConcentration(nM) Enzyme Concentration (nM) Glucose vs. Enzyme Concentration of ILSG and Avicel GC ILSG GC Avicel Crystal structure of a b-glucosidase Crystal structure of an endoglucanas e Crystal structure of a CBH Plants Enzymes Microbes feedstock engineering enzyme engineering fuels synthesis pretreatment LIGNOCELLULOSIC BIOFUELS