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Computational Discovery of Phenotype Related Biochemical Processes for Engineering University of South Florida Scholar Commons Graduate Theses and Dissertations Graduate School 2011 Computational Discovery of Phenotype Related Biochemical Processes for Engineering Andrea M. Rocha University of South Florida, [email protected] Follow this and additional works at: https://scholarcommons.usf.edu/etd Part of the American Studies Commons, Biology Commons, and the Environmental Engineering Commons Scholar Commons Citation Rocha, Andrea M., "Computational Discovery of Phenotype Related Biochemical Processes for Engineering" (2011). Graduate Theses and Dissertations. https://scholarcommons.usf.edu/etd/3315 This Dissertation is brought to you for free and open access by the Graduate School at Scholar Commons. It has been accepted for inclusion in Graduate Theses and Dissertations by an authorized administrator of Scholar Commons. For more information, please contact [email protected]. Computational Discovery of Phenotype Related Biochemical Processes for Engineering Bacterial Biohydrogen by Andrea M. Rocha A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Civil & Environmental Engineering College of Engineering University of South Florida Major Professor: James R. Mihelcic, Ph.D. Nagiza Samatova, Ph.D. Daniel Yeh, Ph.D. Shekhar Bhansali, Ph.D. Kathleen Scott, Ph.D. Date of Approval: April 28, 2011 Keywords: Bioenergy, Dark Fermentation, Metabolic Processes, Systems Biology, Clostridium acetobutylicum Copyright © 2011, Andrea M. Rocha DEDICATION I would like to dedicate this dissertation to my loving family. Throughout my graduate studies, they supported me, encouraged me to follow my dream, and provided me with unending support. ACKNOWLEDGEMENTS There are many people I would like to thank for their contribution to my dissertation. First and foremost, I would like to thank Dr. James Mihelcic and Dr. Nagiza Samatova for their guidance, support, and encouragement in completing this work. I would also like to thank my committee members, Dr. Daniel Yeh, Dr. Kathleen Scott, and Dr. Shekhar Bhansali for their time and assistance with my project. I also want to thank my research group and collaborators from North Carolina State University for their help and assistance with this work. Specifically, I would thank Matt Schmidt, William Hendrix, Kanchana Padmanabhan, Kevin Wilson, Wenbin Chen, and Katie Shpanskaya. In addition, I would like to say thank you to my family and friends who have supported me during my doctoral studies. I would like to give a special ‗thank you‘ to my parents and sister for their unending love and support throughout the years. I would like to thank Mr. Bernard Batson for his support and assistance throughout my time at USF. Last, I would like to thank Debbie McCoy and her staff for providing me the opportunity to participate in the RAMS programs at Oak Ridge National Lab. Support for this work has been funded by the NSF Bridge to the Doctorate Fellowship, USF Delores Auzenne Diverse Student Success Fellowship, Alfred P. Sloan Fellowship, GEM Fellowship, State of Florida 21st Century World Class Scholar Program, and Oak Ridge National Laboratory (ORNL) Research Alliance in Math & Science (RAMS) internship program. TABLE OF CONTENTS LIST OF TABLES ...............................................................................................................v LIST OF FIGURES ......................................................................................................... viii ABSTRACT .........................................................................................................................x CHAPTER 1: INTRODUCTION ........................................................................................1 1.1 Problem Statement and Motivation .............................................................1 1.2 Systems Biology to Enhance Understanding of Biohydrogen Production ....................................................................................................3 1.3 Metabolic Engineering for Hydrogen Production........................................6 1.4 Objective and Proposed Research Approach ...............................................7 1.5 Development of Statistical Analysis Techniques for Identification of Phenotype-Related Genes (Chapter 3) ....................................................9 1.5.1 Impact ............................................................................................12 1.6 Identification of Phenotype-Specific Metabolic Pathways (Chapter 4) ................................................................................................................13 1.6.1 Impact ............................................................................................15 1.7 Identification of Functional Network Associations for Specific Phenotypes (Chapter 5) ..............................................................................16 1.7.1 Impact ............................................................................................18 CHAPTER 2: IDENTIFICATION OF IDEAL MICROBIAL PHENOTYPES FOR BIOLOGICAL HYDROGEN PRODUCTION FROM WASTEWATER AND WASTE MATERIALS .......................................20 2.1 Biohydrogen Production as a Renewable Energy Resource ......................20 2.2 Microorganisms Capable of Hydrogen Production ...................................21 2.3 Biological Methods for Hydrogen Production ...........................................24 2.3.1 Bio-Photolysis ................................................................................24 2.3.2 Light Fermentation.........................................................................25 2.3.3 Dark Fermentation .........................................................................27 2.4 Wastewater and Waste Materials as Biomass ............................................29 2.5 Current Application and Studies Using Wastewaters From Various Sources .......................................................................................................32 2.6 Current Challenges to Hydrogen Production in Wastewater Treatment ...................................................................................................32 2.6.1 Microbial Composition for Hydrogen Production .........................34 2.6.2 Biological Challenges: Impacts on Hydrogen Production .............35 2.6.3 Operational Parameters: Temperature, HRT, Partial Pressure ..........................................................................................39 i 2.7 Phenotypes for Dark Fermentative Hydrogen Production in Wastewater Treatment Facilities................................................................43 CHAPTER 3: IDENTIFICATION OF PHENOTYPE-RELATED GENES: AN INTEGRATED APPROACH TO CATALOGING GENES IMPORTANT FOR HYDROGEN PRODUCERS ...................................47 3.1 Motivation ..................................................................................................47 3.2 Aims and Contributions of Research .........................................................49 3.3 Results ........................................................................................................51 3.3.1 Validation of Methodology Using Known Aerobic and Anaerobic Organisms.....................................................................52 3.3.1.1 Enzymes Predicted by NIBBS for Validation Experiment ......................................................................53 3.3.2 Hydrogen Related Enzymes ...........................................................54 3.3.2.1 Hydrogen-Related Enzymes ...........................................55 3.3.3 Phenotype-Related Enzymes: Acid-Tolerant .................................59 3.3.3.1 Acid-Tolerant Enzymes Predicted by NIBBS ................59 3.4 Discussion ..................................................................................................62 3.4.1 Additional Applications for NIBBS Algorithm .............................64 3.4.2 Limitation on Acid-Tolerant Results .............................................64 3.5 Approach ....................................................................................................65 3.5.1 Genotype Phylogenetic Profiling Using Student‘s T-Test ............66 3.5.2 NIBBS Algorithm: High Throughput Comparative Analysis of Multiple Genome-Scale Metabolic Networks ............67 CHAPTER 4: IDENTIFICATION OF PHENOTYPE-SPECIFIC METABOLIC PATHWAYS: APPLICATION TO HYDROGEN PRODUCTION ........69 4.1 Motivation ..................................................................................................69 4.2 Research Aims and Contribution ...............................................................71 4.3 Results ........................................................................................................73 4.3.1 High Throughput Analysis of Phenotype Related Pathways: NIBBS Algorithm ..........................................................................73 4.3.1.1 TCA versus rTCA Pathway ............................................73 4.3.1.2 Pathways Related to Dark Fermentative Hydrogen Production .......................................................................76 4.3.1.2.1 Fatty Acid Biosynthesis ...................................77 4.3.1.2.2 Purine Metabolism ...........................................79 4.3.1.2.3 Arginine and Proline Metabolism ....................80 4.3.1.2.4 Cysteine and Methionine Metabolism .............81 4.3.2 Acid-Tolerant Pathways.................................................................82
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