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Pretreatment Application of Ligninolytic Enzymes Faculty Sponsor: Dr. Christine Kelly

Pretreatment Application of Ligninolytic Enzymes Faculty Sponsor: Dr. Christine Kelly School of CBEE Group Members: Uranbileg Daalkhaijav , Faraz Ebrahimi , Juissepp Rodriguez . Introduction Emerging Demand for Ethanol and the Use of Biomass

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Pretreatment Application of Ligninolytic Enzymes Faculty Sponsor: Dr. Christine Kelly

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  1. Pretreatment Application of Ligninolytic Enzymes Faculty Sponsor: Dr. Christine Kelly School of CBEE Group Members: UranbilegDaalkhaijav, FarazEbrahimi, Juissepp Rodriguez • Introduction • Emerging Demand for Ethanol and the Use of Biomass • Increase in petroleum fuel prices are driving the demand for renewable fuels. Cellulosic ethanol from waste biomass such as switchgrass and woodchips can yield better net energy than using corn or sugar canes. • Producing Bioethanol • Biomass lignocellulose = lignin + cellulose + hemicellulose. • Separate cellulose from lignin in pretreatment stage of biomass processing • Methodology • Bioreactor Conditions: • 2 liter BioFlo 110 bioreactor was used • Inoculated reactor with Pichiapastoris. • Cell density of 1 – 6 g/L marks the start of fed-batch when hemin and trace salts are added. • Samples from the broth taken every 4 – 6 hours. Results and Analysis Objective 3: Effects of pure oxygen Objective 1: Off gas analyzer • Complete reaction analysis require substrate and metabolite balances on the reactor system. • Current method lacks exhaust gas monitoring making reaction analysis incomplete. • Off gas analyzer connected to reactor exhaust vent to measure the gas fractions in the exit gas. • Gas monitoring fills the major holes in our elemental balances and redistribution analysis. The process diagram of the MnP production experiment is seen in. The bioreactor is sparged air at constant rate while the pH is automatically regulated by addition of ammonium hydroxide. The reactor conditions are monitored using the integral bioreactor control system. Exit gas fractions are measured by the off-gas analyzer, and is read by the data logger. Glucose (media + feed) Glucose (in broth) Biomass (inoculate) Biomass (in broth) • 20% higher final cell density in reactor sparged with pure oxygen. • MnPactivity increase doesn’t always directly correspond with cell density increase. • Cellulose and hemicellulose (polysaccharides)  glucose/ xyloseferment to ethanol • Lignin separation is an expensive process as currently practiced • Lignin Degradation via Enzymes • Enzyme manganese peroxidase (MnP) can degrade lignin • MnP produced from white rot fungi grows slow so little MnP is made • MnP gene cloned into yeast P. pastoristo produce large amounts of MnP Objective 2: Elemental mass balance 2 liter BioFlo 110 bioreactor used for this study. Breakdown of lignocelluloses to isolate fermentable sugars to distill bioethanol. Carbon Dioxide (off – gas) • Sample Analysis: • Cell density was determined by optical density using spectrophotometer at 600 nm wavelength. • Enzymatic activity is measured from the oxidation of 2,6-dimethoxyphenol at 469 nm. The broth sample was spun down at 10,000 rpm for 3 minutes to separate the MnP containing supernatant from the cells. • Glucose concentration is determined using multiwell plate colorimetric analysis. Carbon • Carbon and oxygen input and output is not balanced due to missing byproducts, offset in the off gas analyzer, and method of approximating the cell density. EX-2000 Off-Gas CO2 /O2 Analyzer. rMnP and Byproducts (in broth) • Dissolved oxygen depletion to zero corresponds with biomass density decrease. Colorimetric assay in multiwell plate. Pichiapastoriscells budding Conclusion Overall Goal Improve characterization of bioreactor experiment producing recombinentMnP. Objectives Install and operate off gas analyzer. Perform carbon mass balance on the system. Examine the yield change with cultivation time. Examine effects of pure oxygen on MnP titer. • The data sensitivity to the instrumental offset and methods of measurement introduces greatest possibilities of errors. • The high cell density does not necessarily correlate with increased rMnP activity. • Need to characterize the error in the instruments. • Recommendations: • Recreate dry weight analysis to get a more accurate relationship between absorbance and cell density. • Try to keep the cell density at a specific level in order to optimize the rMnP output. • Biomass and carbon dioxide yield over the duration of the experiment is not constant. Diagram of carbon sources and sinks in fed-batch bioreactor process. Special thanks to Kelsey Yee, Dr. Kelly, Dr. Harding, Shamon Walker and Andy Brickman. Overall diagram of the MnP production process in 2 L bioreactor.

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