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Studying Methanotrophic Bacterial Diversity in Ohio Soils Using High-Throughput Sequence Analysis DISSERTATION Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Aditi Sengupta Graduate Program in Environment and Natural Resources The Ohio State University 2015 Dissertation Committee: Dr. Warren A. Dick, Advisor Dr. Richard P. Dick Dr. Brian H. Lower Dr. Renukaradhya Gourapura Copyrighted by Aditi Sengupta 2015 i ABSTRACT The net flux of methane (CH4), a biogenic greenhouses gas, into the atmosphere is dependent on feedbacks that exist between the atmosphere and the soil. Aerobic methanotrophic bacteria in soil oxidize CH4 and use it as their sole source of carbon and energy, thereby allowing soils to serve as the only know biological sink of atmospheric methane. However, a clear understanding of the diversity and community composition of these bacteria, as affected by land-use and land-management practices is lacking. The objective of this study was to characterize the diversity of methanotrophs in two contrasting soils in Ohio using the sequencing-by-synthesis technique. In addition to location, the effect of rotation, tillage, and management of soils under grass and forest areas on methanotrophic community was also studied. Several molecular-based high-throughput sequencing techniques were employed. Following a pilot pyrosequencing study, Illumina’s sequencing-by-synthesis approach was used to generate millions of sequences targeting the methanotrophic bacteria. A combination of four primer sets targeting the whole community 16S rRNA, the 16S rRNA gene region of Type I and Type II methanotrophs, and the functional pmoA gene (a ii subunit of the particulate methane monooxygenase gene) were used. Software packages including Mothur, QIIME (Quantitative Insights Into Microbial Ecology), and R were used to study community diversity and abundance in soils under no-till continuous corn, no-till corn-soybean, plow-till continuous-corn, plow-till corn-soybean, grass, and forest. A variety of methanotrophic bacterial operational taxonomic units (OTUs) were identified across different land-uses and management, representing diverse genera of methanotrophs. On average, 2% of sequences represented methantrophs OTUs in the 16S rRNA datasets, while the pmoA dataset was compared to a reference database which classified all the sequences as methanotrophic OTUs. Community diversity estimators showed that a combination of community richness and evenness contributed to the methanotrophic diversity. In addition to commonly reported methanotrophic genera, this study also noted the presence of Verrucomicrobial methanotrophic OTUs, non- methanotrophic methylotroph OTUs, and OTUs representing Upland Soil Clusters. For most datasets, no-till soils had higher diversity than plow-till soils. The community composition of both agricultural practices were distinctly different from forest and grass areas. Due to the fact that forest soils were undisturbed, the highest number of different species was generally recovered from these soils. Among the variables analyzed, location was dominant, followed by tillage and rotation. The pmoA dataset showed that even over a long period of time (>50 years), soil methanotrophy function was governed by soil type. It can be concluded that despite soil disturbance, the iii inherent functioning of microbes in these soils is possibly more impacted by soil type, that is a reflection of its geographical location, followed by land-use. This dissertation adds to knowledge of land-use and land-management practices that can be employed on a long-term basis to increase biological fixation of CH4 gas. On a broader level, this study of methanotrophic diversity in soils has the potential to help develop climate change mitigation strategies with respect to globally shifting soils to become increasingly active as CH4 sinks. iv This dissertation is dedicated to my parents Vaswati and Arunabha Sengupta, and to my brother Anirban and sister-in-law Ruchika, for their unconditional love, support, and encouragement. v ACKNOWLEDGMENTS This has been an exhilarating journey full of challenges, excitement, highs, and lows. Through it all, I have had the support of a number of people. To begin with, I want to thank my advisor, Dr. Warren A. Dick for believing in me. His support has been unwavering, as has been his guidance. He taught me to aim high and step out of my comfort zone. His approach towards science and life is inspiring, and for which I will forever be grateful. I want to thank Dr. Richard P. Dick for allowing me to work in his lab during the initial days of my research and for his support over these years. I am thankful to Dr. Brian H. Lower for being my mentor when I sought him out and for his encouraging words. I am grateful to Dr. Renukaradhya Gourapura for his motivation and support as I tried to get my experiments going. A majority of this research work was conducted at the Molecular and Cellular Imaging Center (MCIC) at OARDC. I want to convey my gratitude to Jody Whittier, Dr. Asela Wijeratene, Saranga Wijeratne, Maria Elena Hernandes Gonzales, and Fiorella Cisneros Carter for providing assistance in sequencing and bioinformatics. I also want to thank Dr. Liming Chen, Dr. Dave Kost and Clayton Dygert for helping me in sampling. The administrative staff in SENR provided me with all the support I needed during this time. A special thank you to Amy Schmidt for being my mother in Columbus vi when I first came. I also want to thank Beverly Winner in Wooster and Annie Bingman in Columbus for all their help. Lastly, the journey would not have been half as enjoyable if not for my friends and colleagues at Ohio State. I am blessed to have Pranay Ranjan, Dr. Kshipra Chandrashekhar, and Dr. Kuhuk Sharma stand by me during the brightest and the darkest hours. My heartfelt thank you to Joshua Kendall and Janani Hariharan for walking together with me as we all ventured into the world of bioinformatics. I want to thank Dr. Taniya Roy Chowdhury and Dr. Jaideep Banerjee for being my family, Jennifer Tvyergak for being my first friend in Columbus, and Jennifer Harrison for her timely reassurances. I also want to acknowledge the present and past members of the lab, especially Maninder Kaur Walia, Nghia Nguyen, Brittany Campbell, and Samer Al- Saffar for their motivation and encouragement. Funding Source Funding for this study was provided by the USDA-NIFA, Award No. 2011-68002-30190 “Cropping Systems Coordinated Agricultural Project (CAP): Climate Change, Mitigation, and Adaptation in Corn-based Cropping Systems”. vii VITA 2005................................................................Bharatiya Vidya Bhavan, New Delhi 2008................................................................B.S. Biochemistry, University of Delhi 2010................................................................M.S. Environmental Studies, TERI University 2010 to present ..............................................Graduate Research Associate, School of Environment and Natural Resources, The Ohio State University PUBLICATIONS Sengupta, A. & Dick, W.A., Bacterial community diversity in soil under two tillage practices as determined by pyrosequencing, Microbial Ecology, May 2015. DOI: 10.1007/s00248-015-0609-4 Dick, W.A., Thavamani, B., Conley, S., Blaisdell, R. & Sengupta, A., Prediction of β- glucosidase and β-glucosaminidase activities, soil organic C, and amino sugar N in a diverse population of soils using near infrared reflectance spectroscopy, Soil Biology and viii Biochemistry, Volume 56, issue (January, 2013), p. 99-104. ISSN: 0038-0717. DOI: 10.1016/j.soilbio.2012.04.003. FIELD OF STUDY Major Field: Environment and Natural Resources Specialization: Soil Science ix TABLE OF CONTENTS Abstract ............................................................................................................................... ii Acknowledgments.............................................................................................................. vi Vita ........................................................................................................................ ……..viii Publications ............................................................................................................ ……..viii Field of Study ..................................................................................................................... ix Table of Contents ................................................................................................................ x List of Tables ................................................................................................................... xiv List of Figures .................................................................................................................. xvi CHAPTER 1: INTRODUCTION ...................................................................................... 1 1. Rationale and Significance .......................................................................................... 2 2. Hypothesis ................................................................................................................... 4 3. Objectives .................................................................................................................... 4 4. Data Analysis and Statistics ........................................................................................ 5 x 5. Means
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