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Molecular analysis of honey bee foraging ecology Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Rodney Trey Richardson Graduate Program in Entomology The Ohio State University 2018 Dissertation Committee Professor Reed Johnson, Advisor Professor Mary Gardiner Professor John Christman Professor Roman Lanno 1 Copyrighted by Rodney Trey Richardson 2018 2 Abstract While numerous factors currently impact the health of honey bees and other pollinating Hymenoptera, poor floral resource availability due to habitat loss and land conversion is thought to be important. This issue is particularly salient in the upper Midwest, a location which harbors approximately 60 percent of the US honey bee colonies each summer for honey production. This region has experienced a dramatic expansion in the area devoted to crop production over the past decade. Consequently, understanding how changes to landscape composition affect the diversity, quality and quantity of available floral resources has become an important research goal. Here, I developed molecular methods for the identification of bee-collected pollen by adapting and improving upon the existing amplicon sequencing infrastructure used for microbial community ecology. In thoroughly benchmarking our procedures, I show that a simple and cost-effective three-step PCR-based library preparation protocol in combination with Metaxa2-based hierarchical classification yields an accurate and highly quantitative pollen metabarcoding approach when applied across multiple plant markers. In Chapter 1, I conducted one of the first ever proof-of-concept studies applying amplicon sequencing, or metabarcoding, to the identification of bee-collected pollen. In this work, we used rudimentary laboratory and bioinformatic methods to apply the method to a single nuclear marker, ITS2. In doing so, we found the method to be highly ii inaccurate with respect to quantitative inference of the relative abundances of different plant taxa represented within our sample. Thus, in Chapter 2 I used the same methods and turned my attention to two alternative chloroplast markers, matK and rbcL, in addition to ITS2. In this study, I found that the chloroplast markers were more useful for quantification of pollen abundance relative to ITS2. With an improved understanding of the behavior of different plant markers, I began optimizing the bioinformatic and laboratory methods used for pollen metabarcoding. In Chapter 3, I conducted in silico cross-validation analyses using three prominent hierarchical amplicon sequence classifiers. Testing the classifiers on data from all five commonly used plant barcoding markers, I found wide variance in the accuracy and sensitivity of the classifiers evaluated, suggesting that the choice of classifier and the optimization of classification procedures is an important area for future methods development. In Chapter 4, I expand on evaluating hierarchical sequence classifiers with finer granularity and apply cross-validation analysis to the Metaxa2 hierarchical DNA sequence classifier. Further, I discuss and implement my perspective upon best practices for reference database curation. These curation procedures are designed for the purposes of hierarchical classification specifically. In Chapter 5, I apply pollen metabarcoding in combination with waggle dance interpretation to investigate the spatial and taxonomic foraging patterns of honey bees in central Ohio agroecosystems. After modifying existing PCR-based library preparation protocols, we applied our methods to target four plant barcode markers, trnL, trnH, rbcL and ITS2, for 32 samples collected across the month of May 2015 from four corn and iii soybean-dominated agroecosystems. Our results indicated that the vast majority of colony nutrition provided by pollen during this time was provided by three major plant taxa, woody Rosaceae trees, Salix and Trifolium. Inference of spatial foraging patterns through waggle dance analysis revealed a significant preference for wood lots and tree lines relative to herbaceous, residential and crop landcover types. Having worked to optimize and validate molecular methods for pollen analysis, investigations into how floral resource availability mediates honey bee health can be more feasibly conducted at large scales. It is my hope that this approach proves useful for quantifying and maximizing the pollinator floral resource value of managed lands. iv Dedication To my family - past, present and future. v Acknowledgments Upon applying to graduate school, I was an un-exceptional student and I largely owe my opportunities to an advisor who took a chance on me when others would not. Thank you, Reed. John Christman, Johan Bengtsson-Palme, Douglas Sponsler, Chia Hua-Lin, Mary Gardiner, Roman Lanno, Karen Goodell and Megan Ballinger provided valuable guidance and collaborative engagement throughout my doctoral research. For friendship and lively discussions, scientific or otherwise, I thank Drew Spacht, Brent Nowinski, Ben Green, Chris Riley, Natalia Riusech, Molly Dieterich Mabin, Alice Vossbrink and Yvan Delgado. For all the colleagues of whom I’ve had the privilege to work alongside through the long and often seemingly futile scientific process, I thank Juan Pillajo, Hailey Curtis, Emma Matcham, Garret Cherry, Tyler Eaton, Katie Turo, Alyssa Wheeler, Luke Hearon, Karissa Smith and Sreelakshmi Suresh. I hope that your experience in the lab will be a valuable asset to your future efforts. This work was funded by numerous sources, foremost among them being the Costco-Project Apis m. Honey Bee Biology Fellowship. Funding was also provided by the North American Pollinator Protection Campaign, Pollinator Partnership, OARDC SEEDS grant program and The Ohio State Beekeepers Association. vi To all my family, I am grateful for your support throughout the years. Since my interest in science is largely derived from my love of nature, I am deeply indebted to my parents, Jo and Rodney, and my step parents, Phyllis and Bob, for frequently exposing me to the harsh outdoors from an early age. To my sister, Casey, thanks for encouraging a questioning mind from an early age. Last but certainly not least, thanks to my wife, Sandra, who has provided an endless supply of smiles, hugs and cheer after many a failed experiment. This work is very much a product of her support. vii Vita 2013................................................................B.S. Biochemistry, Indiana University 2013 to present ...............................................Graduate Research Associate, Department of Entomology, The Ohio State University Publications Richardson, RT, HR Curtis, EG Matcham, C-H Lin, S Suresh, DB Sponsler, L Hearon & RM Johnson. In Press. Quantitative multi-locus metabarcoding and waggle dance interpretation reveal honey bee spring foraging patterns in Midwest agroecosystems. Molecular Ecology (bioRxiv preprint: http://dx.doi.org/10.1101/418590) Bengtsson-Palme, J, RT Richardson, M Meola, et al. 2018. Metaxa2 Database Builder: enabling taxonomic identification from metagenomic or metabarcoding data using any genetic marker. Bioinformatics, bty482 Richardson, RT, MN Ballinger, F Qian, JW Christman & RM Johnson. 2018. Morphological and functional characterization of hemocyte communities spanning the honey bee, Apis mellifera, lifecycle. Apidologie, 49: 397-410 Richardson, RT, J Bengtsson-Palme & RM Johnson. 2017. Evaluating and optimizing the performance of software commonly used for the taxonomic classification of DNA metabarcoding sequence data. Molecular Ecology Resources, 17: 760-769 Bell, KL, N de Vere, A Keller, RT Richardson, A Gous, KS Burgess & BJ Brosi. 2016. Pollen DNA barcoding: Current applications and future prospects. Genome, 59: 1- 12 Richardson, RT, C-H Lin, JQ Quijia, NS Riusech, K Goodell & RM Johnson. 2015. Rank-based characterization of pollen assemblages collected by honey bees using a multi-locus metabarcoding approach. Applications in Plant Sciences, 3(11): 1500043 viii Richardson, RT, C-H Lin, JO Quijia, DB Sponsler, K Goodell & RM Johnson. 2015. Application of ITS2 metabarcoding to determine the provenance of pollen collected by honey bees in a field-crop dominated agroecosystem. Applications in Plant Sciences, 3(1): 1400066 Fields of Study Major Field: Entomology ix Table of Contents Abstract ............................................................................................................................... ii Dedication ........................................................................................................................... v Acknowledgments.............................................................................................................. vi Vita ................................................................................................................................... viii Table of Contents ................................................................................................................ x List of Tables ................................................................................................................... xiv List of Figures .................................................................................................................. xvi Chapter 1. Application of ITS2 Metabarcoding to Determine the Provenance of Pollen Collected by Honey Bees in an Agroecosystem ................................................................
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