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Identification of Microorganisms for The IDENTIFICATION OF MICROORGANISMS FOR THE BIOREMEDIATION OF NITRATE AND MANGANESE IN MINNESOTA WATER A THESIS SUBMITTED TO THE FACULTY OF THE UNIVERSITY OF MINNESOTA BY EMILY ANDERSON IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE Satoshi Ishii AUGUST, 2018 © Emily Anderson 2018 ACKNOWLEDGEMENTS This work was supported by Minnesota Department of Agriculture (Project No. 108837), the Minnesota’s Discovery, Research and InnoVation Economy (MnDRIVE) initiative of the University of Minnesota, and the USDA North Central Region Sustainable Agriculture Research and Education (NCR-SARE) Graduate Student Grant Program. Additionally, I would like to thank my advisor, Satoshi Ishii, for taking me on as his first student and for his support and guidance throughout my degree program. I would also like to thank my committee members, Dr. Mike Sadowsky and Dr. Carl Rosen, as well as Dr. Gary Feyereisen for their time and advice towards achieving my degree. I am also grateful to the Ishii lab members for their support over the last two years, especially Jeonghwan Jang and Qian Zhang who have always been more than willing to help. I have enjoyed field and lab days in Willmar with the “woodchip team” (Ping Wang, Jeonghwan Jang, Ehsan Ghane, Ed Dorsey, Scott Schumacher, Todd Schumacher, Allie Arsenault, Hao Wang, Amanda Tersteeg) and others that were willing to volunteer with us (Nouf Aldossari, Stacy Nordstrom and Persephone Ma). For the manganese bioremediation project, I am grateful for the advice and encouragement from Dr. Cara Santelli and for the help from members of her lab. Luke Feeley had an important part in the manganese bioreactor establishment and maintenance as did Kimberly Hernandez and I am thankful for their contributions. i ABSTRACT Bioremediation is a way to safely and cost-effectively remove contaminants using living organisms. In this thesis, microorganisms capable of remediating two pollutants, nitrate and manganese, were identified using culture-dependent and –independent approaches. Nitrate in agricultural wastewater can lead to algal blooms and eutrophication. Edge-of-field woodchip bioreactors are a promising approach to prevent nitrate in wastewater from reaching surface waters by utilizing microbial denitrification to remove nitrate from the system. However, woodchip bioreactors experience low efficiency under cold temperatures, so one strategy to enhance bioreactors in the early spring involves bioaugmentation, or inoculating the bioreactors with cold-adapted denitrifying microorganisms. In order to identify a cold-adapted denitrifier for bioaugmentation, microorganisms were isolated from field woodchip bioreactors and subjected to denitrification testing under cold temperatures, measuring nitrate, nitrite, ammonium, nitrous oxide and dinitrogen gas, as well as whole genome sequencing to identify the presence of genes involved in denitrification and other important microbial processes. Based off of these results, two strains, Microvirgula sp. BE2.4 and Cellulomonas sp. WB94 were recommended for bioaugmentation. In part two, manganese was addressed. High levels of manganese in drinking water can cause health problems, and common treatment methods require cost-intensive chemicals, conditions and maintenance. In this study, a novel algae bioreactor was established to remove manganese from water. In this bioreactor, the algae provided fixed carbon for manganese-oxidizing microorganisms that oxidized the dissolved manganese, precipitating it out of solution. Using a culture-dependent approach, manganese-oxidizing bacteria and fungi were isolated from an environmental sample, including known ii oxidizers Bosea, Pseudomonas, Plectosphaerella and Phoma and some not previously known to oxidize manganese such as Aeromonas, Skermanella, Ensifer and Aspergillus. A culture-independent approach was also employed to determine how abundant the isolated manganese-oxidizing bacteria are in an actively oxidizing environmental sample. Using nitrate and manganese as examples, this thesis identified useful microorganisms involved in remediation and demonstrated how microorganisms can be utilized to effectively remove pollutants from the environment. iii Table of Contents List of Figures ......................................................................................................................v List of Tables .................................................................................................................... vii 1. Introduction ......................................................................................................................1 1-1. General introduction to bioremediation ............................................................1 1-2: Introduction to nitrate pollution........................................................................3 1-3: Introduction to manganese pollution ................................................................8 1-4: Structure of this thesis ....................................................................................12 2. Cold-Adapted Denitrifying Bacteria in Woodchip Bioreactors.....................................17 3. Comparison of the denitrifying microbial communities between four woodchip bioreactors in Minnesota ....................................................................................................49 4. Genomes of four nitrate-reducing bacteria isolated from woodchip bioreactors in Minnesota ...........................................................................................................................74 5. Algae Bioreactor to Remove Manganese from Groundwater ........................................95 6. Conclusion ..................................................................................................................120 6-1 Bioremediation of nitrogen ............................................................................120 6-2 Manganese-oxidation in the algae bioreactor ................................................122 Bibliography ....................................................................................................................124 iv List of Figures Figure 1-1 Eh-pH diagram showing the relationship between manganese 9 oxides. Figure 2-1 N2O production from the microcosms supplemented with 29 nitrate (i.e., treatments WINA and WIN) during 48-h incubation. Figure 2-2 Rarefaction curve generated based on the 16S rRNA (gene) 32 sequences obtained in this study. Total sequence reads were normalized to 28,609 and 21,530 reads per library for DNA and cDNA samples, respectively. Figure 2-3 Principal coordinate analysis (PCoA) plots showing β diversity 35 between microbial communities for (A) DNA and (B) cDNA samples. Figure 2-4 Heatmaps showing relative abundance of sequence reads in 37 operational taxonomic units (OTUs) for (A) DNA and (B) cDNA samples. Figure 2-5 Relative abundance (%) of Cellulomonas rRNA in the 39 sequencing libraries. Figure 2-6 Phylogenetic tree generated based on the deduced NirK 42 sequences using the maximum likelihood method. Figure 2-7 Transcription level of Cellulomonas nirK in the woodchip 43 microcosms. Transcription levels were normalized by the amount of the 16S rRNA. Figure 3-1 Photos of biofilm clogging woodchip bioreactors: a) biofilm 53 inside the woodchip sampling port. b) biofilm accumulation at the inlet pipe and acetate injection site. Figure 3-2 The composition of nitrate-reducing bacteria isolated from 4 59 bioreactors at the genus level. 15 Figure 3-3 Concentration of N2-N per cell measured over time for each 64 of the seven potential denitrifiers (a-g). Note that the concentrations vary between samples. 46 Figure 3-4 Concentration of N2O-N per cell measured over time for 67 each of the seven potential denitrifiers (a-g). Note that the concentrations vary between samples. v Figure 4-1 Phylogenetic tree based on NirS sequences using MEGA 85 7.0.26 and neighbor joining method (1,000 replications). Figure 4-2 Phylogenetic tree based on NosZ sequences using MEGA 86 7.0.26 and neighbor joining method (1,000 replications). Figure 5-1 Photos taken of Onneto Yuno-taki falls at time of sampling, 98 August 2016. Figure 5-2 Diagram of the continuous flow bioreactor with compartments 100 A, B, C and D. Medium enters via the influent valve in compartment A and flows through compartments B, C and D. The effluent valve is located in compartment D. Figure 5-3 Dissolved manganese concentration in the batch bioreactor 105 measured over time. Figure 5-4 Dissolved manganese concentration in the continuous flow 105 bioreactor measured across each compartment. Figure 5-5 Composition of manganese-oxidizing bacteria isolated from 106 Yuno-taki falls at the genus level. Class or phylum is also given. Figure 5-6 Principal coordinates analysis (PCoA) analysis plots based on 110 weighted UniFrac distance measurements comparing: a) DNA and cDNA in the Yuno-taki waterfall samples; b) DNA samples from compartments B, C and D in the continuous flow bioreactor; and c) all bioreactor DNA samples and Yuno-taki waterfall DNA samples. Figure 5-7 Relative abundance of bacteria (>1%) of the waterfall DNA 114 and cDNA samples at the genus level. Figure 5-8 Relative abundance of bacteria (>1%) of the bioreactor DNA 115 samples at the genus level. Figure S5-1 The concentration of sulfate in the influent and in 119 compartment D of the manganese-oxidizing bioreactor, sampled daily. vi List of Tables Table 2-1 Composition of the synthetic agricultural wastewater.
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