Establishing the Use of Pseudomonas Spp. As Biocontrol Agents of Fungal and Nematode

Home , Pantoea agglomerans, Pseudomonas, Pseudomonas aureofaciens, Pseudomonas chlororaphis, Pseudomonas protegens, Pseudomonas rhodesiae

Establishing the use of Pseudomonas spp. as biocontrol agents of fungal and nematode

pathogens

Dissertation

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the

Graduate School of the Ohio State University

Rebecca B. Kimmelfield, B.S.

Graduate Program in Translational Plant Sciences

The Ohio State University

2020

Dissertation Committee:

Associate Professor Christopher G. Taylor, Advisor

Professor Michelle Jones, Member

Professor Sally Miller, Member

Associate Professor Joshua Blakeslee, Member

Associate Professor Stephanie Strand, Member

Copyrighted By Rebecca B. Kimmelfield 2020

Abstract The use of microbial inoculants to control plant disease is an increasingly used method in agriculture to mitigate damage caused by phytopathogens across a variety of systems. Best management practices to control many plant diseases can include use of multiple types of control measures in which biocontrol is one of a suite of tools used. One bacteria genus commonly investigated as biocontrol agents is Pseudomonas. These bacteria are known to be capable of promoting plant growth and reducing damage caused by disease though a variety of modes of action including nutrient competition and niche exclusion, secretion of antibiotic compounds including phenazines, DAPG, and pyoluteorin, and production of volatile organic compounds

(VOCs). The primary focus of this dissertation, broadly, is the use of microorganisms

(specifically Pseudomonas spp.) as biocontrol agents. Studies performed using these bacteria, both physically and conceptually, ranged from basic science, to small-scale microplot field trials, to applied market research.

The focus of Chapters 2 and 3 of this work was investigating the role of VOCs in the biocontrol of nematodes (Caenorhabditis elegans) and fungi (Fusarium oxysporum) under in vitro conditions. The first objective of this work was to investigate how bacterial VOCs affected the growth and activity of other microorganisms, and determine what bioactive VOCs are produced by the bacteria. In shared-air indirect exposure assays using a diverse group of 20 bacteria (19 strains of Pseudomonas representing seven species and one of Pantoea agglomerans) we established that a majority the of the bacteria tested produced VOCs inhibitory

ii to both C. elegans and F. oxysporum while other strains were only effective in inhibiting C. elegans. We performed VOC profiling using proton transfer reaction time-of-flight mass- spectrometry (PTR-ToF-MS) to compare differences in volatile production between the bioactive and non-bioactive strains. Hydrogen cyanide (HCN) and organosulfur compounds were associated with F. oxysporum inhibition, while only HCN was correlated with C. elegans inhibition. These findings generally confirmed our knowledge of antagonistic bacterial VOCs, as members of these categories of compounds have been shown to be antagonistic toward microorganisms. The second objective of this dissertation was to build off this knowledge, in which we sought to determine whether manipulation of the bacteria growth medium could selectively enhance production of specific VOCs. To test this, in vitro assays and VOC profiling were performed with three strains of Pseudomonas (P. chlororaphis, P. rhodesiae, P. protegens) on three media (minimal medium± glycine or L-methionine). These amino acids were selected because they are precursors to HCN (glycine) and methanethiol (methionine), two compounds highly produced by the inhibitory bacteria in the first objective. HCN is a VOC with well- established control potential, and methanethiol is the precursor to multiple organosulfur compounds, some of which have control potential. The addition of each amino acid affected bacterial VOCs to different extents. L-methionine could effectively prime the system. Bacteria grown on minimal media supplemented with L-methionine produced more organosulfur compounds and had greater bioactivity in bioassays compared to bacteria growth on minimal media. Of the three strains, the P. rhodesiae was enhanced by L-methionine to the greatest extent. In both in vitro agar-based and soil-based assays, P. rhodesiae inhibitory behavior against

F. oxysporum was increased with the addition of L-methionine. We also found that addition of only L-methionine to a soil system was sufficient to prime the native microorganism population

iii to produce inhibitory VOCs against F. oxysporum. The addition of glycine to the system promoted an increase in bacterial hydrogen cyanide but varied in increased efficacy against microorganisms; for the strains that produced hydrogen cyanide, the VOCs produced by bacteria grown on minimal medium±glycine had no differences in F. oxysporum inhibition; however, an increase was seen in C. elegans inhibition. Results from this study indicate that VOCs can contribute to the control potential of pseudomonads, and the compounds produced by the bacteria can be manipulated though the inputs added to the growth matrix.

The third objective of this work was to investigate the potential for Pseudomonas,

Bacillus, and Pantoea strains to control soybean cyst nematode (SCN) in the greenhouse and microplot (small-scale field trial) settings. These experiments move the biocontrol research from basic (in vitro laboratory assays) to more applied. In total, eight strains (six Pseudomonas spp., one Bacillus sp., and one Pantoea agglomerans) were used in these trials. Bacteria were tested using multiple formulations including individual strains and consortia of bacteria, and soil drench and seed treatments. In the microplot trials, nematode control efficacy investigated two parameters: end of season SCN egg counts and soybean yield. The results of the studies were varied. Efficacy of individual treatments was inconsistent from trial to trial. There were no treatments that either caused significantly lower SCN egg densities or significantly higher yield in all microplot experiments, however select treatments showed potential in at least one experiment.

Finally, the last objective of this work was to investigate the current environment for biocontrol research and product development within the industry. This project, presented in

Chapter 5, explored the potential for increased collaborations between university researchers and the microbial bioproducts industry. Companies are continuing to explore new actives for

iv bioproducts, and professors continue to research potential beneficial microorganism and natural products. We interviewed professors from the state of Ohio who research in the fields of microorganism and natural products and learned while many professors want to commercialize their research, not all have gone through the necessary steps required to do so. We also interviewed companies that develop microbial inoculants, specifically individuals involved in research and development, and discovered that many companies obtain microorganisms and natural products from external sources. Companies and university faculty also collaborate in research projects. The results from this project indicated that there is no uniform method of collaborating between university and industry, but there is potential to streamline the process. In this way, bioproducts research could be done to meet the needs and wants of both the industry developing the products and university researchers performing the basic science.

The results obtained in each chapter, from the basic science presented in Chapters 2 and 3 to the market research project in Chapter 5, present evidence that there is potential for

Pseudomonas as biocontrol agents. The VOCs produced by the bacteria have significant inhibitory activity against F. oxysporum and C. elegans. While we saw varied efficacy of the bacteria against SCN, future studies can continue to explore the mode of action of these bacteria and determine whether there is applicability in other field and greenhouse systems. With sufficient in vitro and mode of action studies, paired with applied greenhouse and field trials, our best candidates can be further explored to determine whether they have potential from a commercial perspective.

This work is dedicated to the memory of my Grandma Sue Krolikowski. Thank you for being my most vocal cheerleader though all my studies. You have inspired me to continue on my quest of being a lifelong learner.

Acknowledgements

I am truly grateful for the tremendous support—both professionally and personally—that

I have received from countless individuals over my time in this program. I would first like to thank my advisor, Dr. Chris Taylor, for his support and guidance over the past six years. Chris has encouraged me, in the best possible way, to forge my own path and tackle scientific queries as an independent, critical thinker. I am also grateful for the rest of my scientific advisory committee, both current and past members. Thank you for your patience and sharing of scientific knowledge over the years.

The bulk of the research presented within this dissertation succeeded because I had many great people helping me along the way. The success of the science truly took a village. There are multiple people in particular I would like to thank. Department of Plant Pathology members Dr.

Xiao-Yuan Tao, Rachel Kaufman, Dr. Anna Testen and Therese Miller for helping train me to work with the microorganisms and field work and Wanderson Bucker Moraes for his help and patience with statistics; Dr. Shauna Brummet was an invaluable mentor for the entrepreneurial study presented in Chapter 5; Multiple interns—Heather, Jack, Justin—both helped with the experiments and helped me develop leadership skills. Thank you to current and recent members of the Taylor Lab: Dr. Tim Frey, Cecilia Chagas de Freitas, Leslie Taylor, and Edwin D. Navarro

Monserrat, and many others for helping me with lab work and reasoning though questions, as well as providing me with friendship, emotional support, and endless laughter over the years.

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Multiple studies presented here were done at the International Laboratory for Plant

Neurobiology (LINV). Thank you to all members of the LINV, specifically Drs. Stefano

Mancuso, Cosimo Taiti and Diego Comparini, for being fantastic collaborators on the volatile organic compounds experiments. You made me welcome during my time spent in your lab, and I gained a tremendous amount knowledge working with you.

Finally, I’d like to give a huge thank you to my friends and family. My parents have been nothing but supportive of me in every adventure and challenge, and that means the world. To

Michael, Abby, Alison, Emily, Norman, Nathan, Brian, Francesca, Joe, Edwin, Cecilia, Tim, Ali, and many others, I have endless appreciation for your love and friendship, it’s helped me celebrate the highs, and survive the lows.

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Vita

2013...... B.S. Environmental Science, The Ohio State University

2013 to present .... Graduate Fellow (Translational Plant Sciences Graduate Program) or Graduate Research Associate (Department of Plant Pathology), The Ohio State University

Publications

Cocuron, J. C., Koubaa, M., Kimmelfield, R., Ross, Z., & Alonso, A. P. (2019). A combined metabolomics and fluxomics analysis identifies steps limiting oil synthesis in maize embryos. Plant Physiology, 181(3), 961–975. https://doi.org/10.1104/PP.19.00920

Fields of Study

Major Field: Translational Plant Sciences

Table of Contents

Abstract ...... ii Dedication ...... vi Acknowledgements ...... vii Vita ...... ix Table of Contents ...... x List of Tables ...... xiii List of Figures ...... xv Chapter 1 Literature Review ...... 1 1.1 Introduction to Biocontrol...... 2 1.2 Ohio Agriculture ...... 2 1.3 Pathogens Affecting Ohio Crops ...... 3 1.3.1 Soybean diseases ...... 3 1.3.2 Tomato diseases ...... 7 1.4 Management Strategies for Controlling Pathogens ...... 8 1.4.1 Soybean cyst nematode management strategies ...... 8 1.4.2 Fusarium oxysporum management strategies ...... 15 1.5 Pseudomonas ...... 17 1.5.1 Pathogenic Pseudomonas...... 18 1.5.2 Beneficial Pseudomonas ...... 19 1.6 Commercial Pseudomonas-Based Products ...... 31 1.7 Objectives ...... 32 Chapter 2: Determination of the Volatile Compounds Produced by Pseudomonas spp. Strains and Establishing Their Role in Biocontrol...... 49 2.1 Abstract ...... 50 2.2 Introduction ...... 51 2.3 Materials and Methods ...... 55 2.3.1 Microorganism maintenance ...... 55 2.3.2 Pseudomonas mode of action assays ...... 56 2.3.3 Pseudomonas single strain VOC measurement ...... 58 2.3.4 HCN measurement ...... 59 2.3.5 F. oxysporum inhibition using HCN ...... 60 2.3.6 Data analysis and statistics ...... 61 2.4 Results ...... 63 2.4.1 In vitro bioassays ...... 63 2.4.2 PTR-ToF-MS and HCN quantification ...... 65 2.4.3 Correlation between in vitro assays and volatile compounds ...... 68 2.5 Discussion ...... 69 2.6 Conclusions and Future Directions ...... 78

Chapter 3: Identifying the Potential to Prime Pseudomonas spp. for Volatile Organic Compound Production Though Manipulation of the Culture Medium ...... 109 3.1 Abstract ...... 110 3.2 Introduction ...... 111 3.3 Materials and Methods ...... 114 3.3.1 Microorganism maintenance ...... 114 3.3.2 In vitro volatile inhibition assays ...... 115 3.3.3 Pseudomonas volatile organic compound (VOC) quantification ...... 117 3.3.4 Pseudomonas genome mining for methanethiol and hydrogen cyanide synthesis genes ...... 118 3.3.5 Fusarium inhibition with organosulfur VOCs ...... 119 3.3.6 Data analysis ...... 120 3.4 Results ...... 121 3.4.1 In vitro VOC inhibition assays ...... 121 3.4.2 Inhibition of F. oxysporum by volatiles produced by Pseudomonas grown on soil...... 122 3.4.3 VOC production by Pseudomonas ...... 123 3.4.4 Correlation of F. oxysporum inhibition with volatile production ...... 126 3.4.5 Presence of genes involved in methanethiol and hydrogen cyanide production ...... 126 3.4.6 F. oxysporum 289 inhibition by DMS and DMDS ...... 127 3.5 Discussion ...... 127 3.6 Conclusions and Future Directions ...... 133 Chapter 4: Evaluation of Bacterial Treatments as Biocontrol Agents of Soybean Cyst Nematode in Microplot and Greenhouse Trials ...... 155 4.1 Abstract ...... 156 4.2 Introduction ...... 156 4.3 Materials and Methods ...... 160 4.3.1 Plant material ...... 160 4.3.2 Nematode inoculum preparation-microplots ...... 160 4.3.3 Bacteria preparation-microplots ...... 161 4.3.4 Microplot setup and yield measurements ...... 163 4.3.5 Determination of SCN infestation of microplots ...... 164 4.3.6 SCN greenhouse assay ...... 165 4.3.7 Data analysis ...... 165 4.4 Results ...... 166 4.4.1 2017 microplot study ...... 167 4.4.2 2018 microplot study ...... 167 4.4.3 SCN greenhouse assays ...... 170 4.5 Discussion ...... 170 4.6 Conclusions and Future Directions ...... 176 Chapter 5: Market Research on the Development of a Platform for Streamlined University-Industry Collaboration in the Field of Microorganisms and Natural Products ...... 201 5.1 Key Takeaways ...... 202 5.2 Introduction and Project Rationale ...... 202 5.3 Methodology ...... 206

5.4 Results and Discussion ...... 207 5.4.1 Interview summary ...... 208 5.4.2 Business model canvas and business model: Hypotheses validation ...... 212 5.5 Conclusions and Future Directions ...... 213 Chapter 6: Perspectives ...... 231 References ...... 236 Appendix A1: Volatile Organic Compounds Quantified in the Headspace of Pseudomonas spp. and Pantoea agglomerans ...... 261 Appendix A2: Root Exudate Profile of 10-day Old Glycine max ‘Lee’ Seedlings ...... 272 A2.1 Materials and Methods ...... 273 A2.1.1 Plant material ...... 273 A2.1.2 Experimental setup and quantification: Root exudates ...... 273 A2.2 Results ...... 274

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List of Tables

Table 1.1. Representative list of commercially available Pseudomonas-based bioproducts in the United States ...... 48 Table 2.1. Pseudomonas strain information ...... 99 Table 2.2. Pearson’s correlation coefficients for the volatile compounds most positively correlated with fungal inhibition ...... 100 Table 2.3. Inhibition of F. oxysporum 289 by HCN ...... 101 Supplemental Table S2.1. Organosulfur compounds produced by Pseudomonas spp. and Pantoea agglomerans strains ...... 107 Table 3.1. Pearson’s correlation coefficients for VOCs correlated with F. oxysporum 289 inhibition ...... 149 Table 3.2. Genome search for the presence of genes coding for enzymes involved in methanethiol and hydrogen cyanide biosynthesis...... 150 Table 3.3. Inhibition of F. oxysporum 289 by DMDS and DMS ...... 151 Supplemental Table S3.1 Protein sequences used in tblastn search for presence of organosulfur compound and hydrogen cyanide synthesis genes in three Pseudomonas strains ...... 152 Supplemental Table S3.2. Organosulfur compounds produced by Pseudomonas spp. on M9 minimal medium±amino acids ...... 153 Table 4.1. Bacteria strains used in microplot and greenhouse experiments ...... 189 Table 4.2. Bacteria treatments used in 2017 microplot study ...... 190 Table 4.3. Bacteria treatments used in 2018 microplot study ...... 191 Table 4.4. 2017 microplot summary ...... 192 Table 4.5. 2018 microplot summary ...... 193 Table 4.6. Statistical differences between 2017 SCN microplot treatments-75,000 egg inoculum ...... 195 Table 4.7. Statistical differences between 2018 SCN microplot treatments-50,000 egg inoculum ...... 197 Table 4.8. Statistical differences between 2018 SCN microplot treatments-5,000 egg inoculum...... 199 Table 5.1 Ratio of gross licensing income to total research expenditures for Big Ten universities in 2017 ...... 224 Table 5.2 Federal budget information for the National Science Foundation and US Department of Agriculture from FY2016-FY2021...... 225 Table 5.3. Questions asked in I-CORPS@Ohio interviews ...... 226

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Table 5.4. Industry collaborations with universities and/or private research contract companies ...... 228 Table 5.5. Company sourcing for microorganisms and natural products ...... 229 Table 5.6. Responses from technology commercialization officers, other university administration, and similar organization interview segments ...... 230 Table A1.1. Compounds identified with PTR-ToF-MS analysis ...... 263 Table A2.1. Amino acid external standard ...... 277 Table A2.2. Amount of 24 amino acids in root exudates of Glycine max ‘Lee’ seedlings ...... 278 Table A2.3. Proportion of 24 amino acids in root exudates of Glycine max ‘Lee’ seedlings .....279

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List of Figures

Figure 2.1. Top agar growth inhibition of F. oxysporum 289 by Pseudomonas spp. and Pantoea agglomerans strains ...... 86 Figure 2.2. Dual plating growth inhibition of F. oxysporum 289 by Pseudomonas spp. and Pantoea agglomerans strains ...... 87 Figure 2.3. Indirect volatile exposure inhibition of F. oxysporum isolates 289 (A) and 197 (B) with Pseudomonas spp. and Pantoea agglomerans strains ...... 88 Figure 2.4. Indirect volatile exposure inhibition of F. oxysporum isolates 289 (A) and 197 (B) by Pseudomonas sp. and Pantoea agglomerans ...... 90 Figure 2.5. Volatile activity against C. elegans by Pseudomonas spp. and Pantoea agglomerans ...... 92 Figure 2.6. Heat map showing the average intensities (ppbv) of 20 strains of Pseudomonas spp. and Pantoea agglomerans...... 93 Figure 2.7. Cyanide and sulfur-containing compounds produced by the Pseudomonas spp. and Pantoea agglomerans...... 94 Figure 2.8. Hydrogen cyanide quantification by Pseudomonas spp. and Pantoea agglomerans + strains using either A) PTR-ToF-MS (H2CN , m/z 28.018) or B) a colorimetric semi-quantitative assay ...... 95 Figure 2.9. Signal intensity of organosulfur compounds produced by 20 Pseudomonas spp. and Pantoea agglomerans strains...... 96 Figure 2.10. Principal component analysis (PCA) biplots of 20 Pseudomonas and Pantoea strains and LB controls ...... 97 Supplemental Figure S2.1. In vitro inhibition assay setup ...... 102 Supplemental Figure S2.2. Variable reductive principal component analysis (PCA) of the volatile profiles produced by Pseudomonas spp. and Pantoea agglomerans strains ...... 103 Figure 3.1. Pathways of (A) hydrogen cyanide (HCN) and (B) organosulfur compounds biosynthesis ...... 140 Figure 3.2. Indirect volatile exposure inhibition of F. oxysporum 289 by Pseudomonas spp. grown on minimal medium with and without supplementation of amino acids ...... 141 Figure 3.3. Indirect volatile exposure inhibition of C. elegans by Pseudomonas spp. grown on LB or minimal medium with and without supplementation of amino acids ...... 142 Figure 3.4. Indirect volatile exposure inhibition of F. oxysporum 289 by P. rhodesiae 88A6 grown on topsoil supplemented with L-methionine ...... 143 Figure 3.5 Heat map showing the average intensities (ppbv) of the volatile profile of Pseudomonas spp. strains grown on media with different amino acid compositions ...... 144

Figure 3.6. Principal component analysis (PCA) score plot of Pseudomonas spp. grown on minimal media with and without supplementation of amino acids ...... 145 Figure 3.7. Cyanide and sulfur-containing VOCs compared to the total amount of volatile organic compounds produced by each treatment ...... 146 + Figure 3.8. Hydrogen cyanide (CH2N , m/z 28.018) produced by Pseudomonas spp. strains grown on media with different amino acid compositions ...... 147 Figure 3.9. Organosulfur compounds produced by Pseudomonas spp. strains grown on media with different amino acid compositions ...... 148 Figure 4.1 SCN hatch rate and fecundity assay for a collection of Pseudomonas spp. strains ...182 Figure 4.2 Microplot setup ...... 183 Figure 4.3 Correlation between eggs/100 cubic-centimeters soil and soybean yield in microplot trials...... 184 Figure 4.4 Yield comparison between egg load in 2018 microplot study ...... 186 Figure 4.5 Box and whisker plots of SCN greenhouse assays ...... 187 Figure 5.1 Total research expenditures versus industry research expenditures ...... 217 Figure 5.2 Research expenditures versus gross licensing income ...... 218 Figure 5.3. Business model initially proposed by MO-NP@OSU ...... 219 Figure 5.4. Business model canvas (BMC) for I-CORPS@Ohio Project ...... 220 Figure 5.5. Proposed business model for MO-NP@OSU ...... 223 Figure A2.1. Setup of root exudate experiment ...... 276

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Chapter 1: Literature Review

1.1 Introduction to Biocontrol

Biocontrol was described by DeBach and Rosen (1991) as “the utilization of natural enemies to reduce the damage caused by noxious organisms to tolerable levels.” An early record of biocontrol in the United States dates to 1888, with use of beneficial vedalia beetles (Rodolia cardinalis) to control cottony-cushion scale (Icerya purchase) in California citrus, and has been used ever since (DeBach & Rosen,1991). Biocontrol of pests and pathogens can be achieved with beneficial insects, nematodes, fungi, viruses and bacteria. This is a relevant area of study because the demand for biocontrol products has grown in recent years, and the trend is forecasted to continue. In the United States, sales of biological products is predicted to increase from 750 million USD in 2015 to 3 billion USD in 2025 (Dunham, 2017). The purpose of this work seeks to investigate the potential for the bacteria Pseudomonas spp. to act as biological control agents of relevant Ohio plant pathogens, namely Heterodera glycines (soybean cyst nematode, SCN) and Fusarium oxysporum. This literature review will explore each facet of the biological control system, namely the plant, pathogen, and biological control agent, with emphasis on pathogen and biocontrol agent mode of action.

1.2 Ohio Agriculture

Ohio has the 16th largest agriculture economy in the United States, responsible for 2.4% of the nationwide commodity sales receipts in 2018 (USDA-ERS, n.d). In 2019, Ohio had over

77,000 individual farms with approximately 13.5 million acres of land used in agriculture; over 8 million acres were planted with crops (USDA-NASS, n.d. a). In 2015 agriculture production contributed to 0.63% of Ohio’s gross state product (3.9 billion USD), and accounted for over

83,000 jobs in the state. Many additional jobs and revenue also came downstream from

2 agriculture and food processing (DiCarolis et al, 2017). In 2018 the top five crops produced within the state (according to state receipts) were soybean (Glycine max), corn (Zea mays), wheat

(Triticum spp.), hay and tomatoes (Solanum lycopersicum); Ohio production of these crops made up respectively 6.5%, 4.2%, 1.8%, 1.6%, and 2.8% of the nationwide totals. (USDA-ERS, n.d).

With such a large portion of the state economy (in both jobs and GSP) dependent on agriculture, it is important to maximize crop production as efficiently as possible. As such, the focus of this chapter is to investigate the use of control agents to mitigate plant pathogens. Emphasis will be put on describing soybean cyst nematode (SCN), the primary pathogen of the state’s most widely grown crop, soybean, as well as Fusarium oxysporum, which can infect multiple crops in Ohio.

Both SCN and F. oxysporum are used in biocontrol experiments in subsequent chapters of this dissertation.

1.3 Pathogens Affecting Ohio Crops

1.3.1 Soybean diseases

There are many phytopathogens, including fungi, oomycetes, bacteria, viruses, and nematodes that are causal agents for diseases that can negatively affect soybean yield. These pathogens can attack the aboveground portion of the plant, or dwell in the soil and affect the root system. Soybean pathogens in Ohio resulted in estimates of 2.75 billion dollars (USD) lost between 2010 and 2014; the only states that had estimated losses higher than Ohio were Illinois and Minnesota (Allen et al, 2017). Three pathogens that cause some of the highest soybean yield loss in Ohio are Phytophthora sojae, Fusarium spp., and SCN (Wrather & Koenning, 2006).

Phytophthora sojae has been found widely around the state of Ohio (Dorrance et al,

2003). It is a pathogen responsible for stem and root rot and affects plants at every stage of

3 development (Martin & Dorrance, 2019). Between 2003 and 2005, disease caused by P. sojae resulted in an estimated loss of 1.45 million metric tons (MT) of soybeans in Ohio, and 3.93 million MT across 28 US states (all of the soybean producing states in the United States), as compared to estimated yield in a healthy soybean production system (Wrather & Koenning,

2006). A second common soybean pathogen is Fusarium spp, and although multiple species can infect soybeans, F. graminearum was the most virulent species among a collection of Ohio isolates (Broders et al, 2007). In Ohio multiple Fusarium diseases have caused substantial economic damage due to soybean loss. Fusarium spp. is a causal agent of soybean root rot, and between 2003 and 2005 had estimated yield loss of over 55,000 MT in Ohio, and over 0.53 million MT across 28 US states; over the same timeframe sudden death syndrome (causal agent

F. virguliforme) accounted for losses of 58,000 MT Ohio and nearly 2 million MT across 28 states. The damage caused annually by Phytophthora was more consistent than damage caused by the Fusarium pathogens, which has fluctuated more over the years (Allen et al, 2017; Wrather

& Koenning 2006).

Finally, SCN is among the most economically devastating pathogens of soybean in the

United States soybean growing region, including Ohio (Wrather & Koenning, 2006). SCN was used in microplot studies in Chapter 4 of this work, and as such more information will be detailed for this pathogen than other soybean pathogens. It is newly known to Ohio, first found in

1987 (Reidel & Golden, 1988). SCN is a root parasitic nematode which feeds on plant host roots, ultimately taking nutrients from the host plant, subsequently resulting in reduced plant yield.

SCN infestation in fields can be asymptomatic. Susceptible and resistant soybean cultivars planted in the same infested field grew visually similar, although yield was higher in resistant cultivars (Young 1996). Damage due to SCN has increased immensely in recent years. Between

2003 and 2005, SCN damage resulted in an estimated yield loss of 0.92 million MT in Ohio and

8.3 million MT lost in 28 US states (Wrather & Koenning 2006). Approximately one decade later, between 2010 and 2014, SCN damage resulted in an estimated 16.8 million MT lost across

28 US states and Ontario, Canada (Allen et al, 2017). SCN presence in soybean growing states has increased in recent years. In Ohio, SCN has been found in over 80% of counties and was newly detected in three Ohio counties between 2014 and 2017 (SCN in Ohio, n.d, Tylka &

Marett 2017). At the national scale, SCN detection has increased from North Carolina in 1954 to a majority of soybean growing counties in the US (Tylka & Marett 2017; USDA-NASS, n.d. b).

Soybean cyst nematode lifecycle

SCN is a sedentary obligate biotroph parasitic nematode, meaning the nematode needs a living plant host to grow on and reproduce. The reproductive cycle of SCN is as short as 3 weeks under ideal conditions (Niblack, 2005). This short cycle means single fields can experience multiple SCN generations though a growing season; small initial nematode populations may grow large over the course of a few months. There are multiple crop hosts of SCN including soybean (Glycine max, namesake of this disease), dry beans (Phaseolus vulgaris, including pinto and kidney beans), and select weed hosts including purple deadnettle (Lamium purpureum) and field pennycress (Thlaspi arvense) (Abawi & Jacobsen 1984; Poromarto & Nelson

2009;Venkatesh et al, 2000). Under proper conditions including temperature (approximately 25-

36ºC), adequate moisture, cation concentrations and presence of a host, eggs are stimulated, undergo their first molt, hatch into second-stage juveniles (J2s) and begin migrating towards the host root (Niblack, 2005; Tefft et al, 1982). The presence of a host root is important as the roots exude compounds important in stimulating hatching, including glycinoeclepin A, produced by

5 common bean, and other uncharacterized compounds produced by soybean (Masamune et al,

1984; Okada, 1971; Schmitt & Riggs, 1991; Tefft et al, 1982).The importance of host root exudates is further demonstrated as hatch rates in the exudates of non-hosts were significantly lower than in the exudates of soybean or a water control (Medina, 2016; Schmitt & Riggs, 1991).

Once arriving at the plant, the J2 penetrates the root using a needle-like stylet and secretes a number of enzymes to degrade the cell wall. Smant et al (1998) first reported on the isolation of β-1,4-endoglucanases (cellulases) from H. glycines juveniles’ esophageal glands.

Since then, additional genes have been discovered in the genome of SCN that are expressed in the esophageal glands of J2s and encode for enzymatic proteins involved in cell wall degradation and are important to SCN’s ability to parasitize the host plant (Gao et al, 2003). Wang et al

(1999) demonstrated that one esophageal β-1,4-endoglucanase, HG-ENG-2, is secreted though the nematode stylet into root tissue while another, HG-ENG-1 is not secreted into the root. When secreted, these enzymes can break down the plant cell wall so the nematode can enter the plant root. Once in the root at the feeding site, the nematode secretes additional effector proteins to induce the plant to create a multi-nucleated syncytium (feeding site) (Bohlmann and Sobczak,

2014; Mejias et al 2019). In an infected plant, cell wall breakdown at the feeding site occurs within days of infection, a true syncytium forms after a week, and individual cells are no longer distinguishable at 15 days after infection (Gipson et al, 1971). At the syncytium, the J2 becomes sedentary and loses its somatic musculature, and undergoes two additional molts, J3 and J4, before reaching the adult stage (male or female). SCN is an obligately sexual parasite, and the male adults regain their somatic musculature and leave the root to fertilize the females, which remain adhered to the syncytium (Niblack, 2005). SCN undergoes epidermal proliferation

(number and ploidy of cells) after infection, and the adult female nematode is more saccate-

6 shaped than the juveniles and males (Thapa et al, 2019). After fertilization, female SCN produce hundreds of eggs, and finally die, leaving a protective cyst surrounding the eggs. The females also deposit eggs unprotected external from the cyst in a gelatinous matrix (Niblack, 2005; Sipes et al, 1992). Protected within the cyst, SCN eggs can remain viable for multiple years in the soil.

SCN-cyst infested soil stored indoors had viable eggs for at least 7 years that could hatch out and infect soybean plants (Inagaki & Tsutumi, 1971). It is imperative to control for SCN because the nematode is both so economically destructive and persistent in the soil.

1.3.2 Tomato diseases

Many foliar and soilborne pathogens can affect tomatoes grown in high tunnels and the field. Within the state of Ohio, soilborne diseases affecting tomato crops include Verticillium wilt (Verticillium dahlia), corky root rot (Pyrenochaeta lycopersici), root knot nematode

(Meloidogyne spp.) and Fusarium wilt (Fusarium oxysporum f. sp. lycopersici) (Testen & Miller,

2017a). In high tunnels, pathogens can form disease complexes and contribute to reduced health of the plant (Testen & Miller, 2018). Fusarium oxysporum was used in in vitro assays in

Chapters 2 and 3 of this work, and as such more information will be detailed about this pathogen than other tomato pathogens. Multiple subspecies of F. oxysporum have demonstrated a damaging effect on tomato yield. Tomato yield in field trials inoculated with a consortium of pathogens (Sclerotinia rolfsii, Pythium ultimum, Rhizoctonia solani, F. oxysporum f.sp. lycopersici (FOL)) was significantly lower compared to uninoculated plants (Mao et al, 1998). In greenhouse assays, tomatoes inoculated with F. oxysporum f.sp. radicis-lycopersici (FORL, causal agent Fusarium crown and root rot) had substantial plant death and a threefold reduction of tomato yield in plants as compared to uninoculated plants (Lafontaine & Benhamou, 1995).

Both FOL (causal agent Fusarium wilt) and FORL can be introduced to a system via infected transplants or though infected equipment. The fungi can survive for multiple cropping seasons in infected soil due to the production of chlamydospores. Both pathogens are found widely where tomatoes are grown (Davis & Paulus, 2014; Correll & Jones, 2014).

There are multiple management strategies used for controlling these soilborne plant pathogens. Control strategies are diverse and include one or a combination of genetic, cultural, chemical and biological practices. Some of the management strategies are described in the following sections.

1.4 Management Strategies for Controlling Pathogens

1.4.1 Soybean cyst nematode management strategies

Discussed here are some methods for controlling SCN: genetic resistance, crop rotation, chemical control, and biological control.

SCN management: Genetics (resistance)

The primary strategy used to control SCN is use of resistant soybean cultivars. Trials across the state of Iowa demonstrated that within the same SCN-infested environment, resistant cultivars can have significantly higher yield compared to a susceptible cultivar (Tylka et al,

2019). In the United States, genetics has been used to prevent SCN infection in soybeans since the nematode was first detected in North Carolina. Field testing in 1957 demonstrated that of the soybean lines tested, only 0.28% were highly resistant to SCN (Ross & Brim, 1957). Over the next few decades, further studies revealed that SCN populations have variable infection ability.

That is, individual populations could reproduce on some resistant soybean lines but not on

8 others, which indicates the presence of multiple resistance genes within the soybean genome

(Anand & Brar, 1983; Golden et al, 1970). Quantitative trait locus (QTL) mapping in 16 studies on crosses between a susceptible and resistant line of soybean has identified two common gene loci involved in resistance: rhg1 and Rhg4 (Concibido et al, 2004). The genes (type and copy number) involved in resistance vary among SCN-resistant soybean lines. For example, in both plant introduction (PI) 437654 and Peking the rhg1 allele interacts with the Rhg4 allele to achieve resistance against SCN, while in PI88788 only the rhg1 allele is responsible for resistance (Brucker et al, 2005; Yu et al, 2016). Yu et al (2016) also demonstrated the importance of increased Rhg1 copy number in resistance against multiple SCN populations.

Many soybean accessions have demonstrated resistance to SCN, however few of these lines have been used in the field as sources of genetic resistance in commercial varieties (Arelli et al, 2000; Rao Arelli et al, 1997; Tylka & Mullaney, 2019). SCN resistant cultivar PI88788 contributes to the genetic resistance of over 95% of commercially sold SCN-resistant varieties in the northern and central United States (Maturity Groups (MGs) 0, I, II, and III). Accessions

Peking and PI737654 also contribute resistance to commercial varieties in MGs 0, I, II, and III, however to a much lesser extent than PI88788 (Tylka and Mullaney 2019). Ohio is in MG zones

II, III, and IV (Stowe & Dunphy, 2017). Soybeans planted in southern Ohio (MG IV) may be different SCN-resistant cultivars than those grown in Northern Ohio (MGs II and III). Careful consideration must be used for determining which SCN-resistant cultivars to plant. There is variability in the effectiveness of resistant cultivars to control SCN reproduction and increase yield, even when cultivars have the same genetic source of resistance (Tylka et al, 2019).

Soil samples from around the United States have contained populations of nematodes able to grow at elevated levels (>10% of susceptible control) on PI88788, which indicates that

9 nematode populations are overcoming soybean genetic resistance (scncoalition.com, n.d.).

Samples in Ohio have also contained nematodes able to grow at elevated levels on Peking. At this time, no Ohio soil samples has contained nematodes capable of growing on PI437654 at elevated levels (Therese Miller & Christopher Taylor, unpublished). Because these soils contain nematodes adapted to reproducing on the most commonly used genetic source of SCN-resistance in soybean, additional methods of nematode management must also be utilized.

SCN management: Cultural (crop rotation)

Crop rotation with SCN non-hosts is an effective strategy to reduce nematode impact.

Over 20 crops are suggested for use in rotation with soybean as poor- or non-hosts of SCN

(Niblack & Tylka, n.d) Trials have demonstrated that planting corn (non-host) in an infested field increased soybean yield in the subsequent season compared to treatments with continuous soybean (Porter et al, 2001; Sasser & Uzzell, 1990). The number of SCN eggs in soil decreased over time when growing corn in a field previously planted with soybean, but when soybeans were planted in an SCN-infested field after multiple seasons of corn, SCN populations rebounded (Porter et al, 2001). Rotations using bahiagrass and velvetbean, a leguminous cover crop, were also effective at reducing SCN and increasing soybean yield, as compared to a continuous soybean planting, however neither of these crops is widely grown in most of the soybean growing region of the United States (Hancock et al, 2017; Weaver et al, 1993; Weaver et al, 1998; USDA-NASS, n.d. b, UDSA-NRCS, n.d.). Niblack (2005) and Niblack and Tylka

(n.d) also suggest rotating different SCN-resistant cultivars. In this approach, the nematodes present may have to overcome multiple sources of resistance which may slow their adaptability to growing on soybean.

SCN non-hosts produce compounds which may contribute to nematode control. In greenhouse experiments, a variety of plant residues, including clover and ryegrass, were incorporated into soil and decreased nematode numbers after 8 weeks (Riga et al, 2001). This suggests the residues contain nematocidal compounds. Additionally, plant root exudates

(including clover, ryegrass, and corn) have been shown to alter (both increasing and decreasing) the hatching rate of SCN eggs as compared to either soybean or water controls (Medina, 2016;

Riga et al, 2001). Much is unknown about the individual bioactive compounds within plant residues and root exudates. The importance of selecting the proper non-host, cover crop, host, and rotation length suggests that careful planning must be used to establish the best crop rotation strategy.

SCN management: Chemical (synthetic nematicides and fumigants)

Chemical nematicides and less targeted fumigants have been sold for decades, however, they are not the optimal strategy for SCN control. Through the years multiple active ingredients in nematicides and fumigants including 1,2-Dibromo-3-chloropropane (DBCP), methyl bromide, and aldicarb have been banned or limited by the EPA and/or individual states due to their serious human health and environmental consequences (Osteen, 2003; Tomasko, 2018; USEPA, 2000;

USEPA, 2010). The nematicides and fumigants that are currently on the market have had varying levels of success in SCN control, both in terms of increasing yield and reducing nematode numbers in the soil. According to the Soybean Cyst Nematode Management Guide, while nematicides are available, they are rarely recommended for use (Niblack & Tylka, n.d)

De Bruin and Pedersen (2008) conducted field trials using the fumigant Telone® C-35

(Corteva AgriScience; 1,3-dichloropropene and chloropicrin) in combination with resistant and

11 susceptible soybean cultivars. Telone® did not affect all cultivars equally, contributing to significant yield increases in the susceptible cultivar and only one of the resistant cultivars. In both field and microplot testing of seed treatments Avicta® (Syngenta Corporation; Abamectin) and Aeris® (Bayer CropScience; Imidacloprid+Thiodicarb) on both SCN-resistant and - susceptible cultivars, there were no significant differences in yield (Frye, 2009). Additional field trials have demonstrated the minimal effect of Avicta® on both SCN-susceptible and -resistant cultivars (Ahmed et al 2018, Yabwalo et al, 2019). Finally, BASF recently introduced a new product, ILeVO® (Fluopyram), to control SCN. Greenhouse and laboratory trials have demonstrated that ILeVO® significantly reduced nematode reproduction on susceptible cultivars, and both seed and radicle exudates of nematicide treated susceptible seed significantly reduced egg hatching (Beeman & Tylka, 2018). Field efficacy of ILeVO® is varied (Ahmed et al, 2018;

Yabwalo et al, 2019). While nematicides and fumigants may be a useful strategy to mitigate yield loss, selection of cultivar is important. SCN-susceptible seed grown on a field treated with

Telone® had significantly increased yield than non-treated plots, however the yields of all SCN- resistant cultivars were significantly higher than the susceptible cultivar in fumigated soil (De

Bruin & Pedersen, 2008). Alternatively, ILeVO® treated SCN-susceptible seed resulted in yields significantly higher than the untreated control, and comparable to all treatments of the SCN- resistant cultivar (Yabwalo et al, 2019).

SCN management: Biological control

Multiple biological products are sold commercially to control SCN. The bio-nematicides available in the United States are bacteria based or derived. Bacterial-based products sold specifically to target soybean cyst nematode include Clariva® (Syngenta Corporation, active

12 microbe Pasteruia nishizawae Pn1), Poncho®/VOTiVO® (BASF, active microbe Bacillus firmus

I-1582), Aveo® EZ (Valent Biosciences, active microbe B. amyloliquefaciens PTA 4838), and

BioST® Nematicide 100 (Albaugh LLC, Burkholderia rinojensis A396). The aforementioned products all use whole (living or dead) microorganisms in their formulations. N-Hibit® (Plant

Health Care) is a bioproduct that uses bacteria derived Harpin αβ proteins. Genetically engineered Escherichia coli produces the protein, which is harvested and purified in the production formulation process (USEPA-OPP, n.d.). Like chemical nematicides, the efficacy of biological nematicides is varied. Multiple studies demonstrated that Clariva® neither produces significant yield increases nor nematode end-of-season-population decreases (Ahmed et al 2018;

Musil et al, 2015; Yabwalo et al, 2019). Alternatively, in a series of small-scale field experiments with Clariva®, Bissonnette et al (2018) saw yield increases in some plots but not others. Poncho®/ VOTiVO® studies had variability in egg reduction and yield increase, and efficacy can vary by study (Ahmed et al, 2018; Chilvers et al, 2012; Musil et al, 2015) In 2007 field trials with SCN-susceptible and -resistant seed treated with N-Hibit® (Plant Health Care, harpin protein) there was no significant effect on end of season SCN egg density. Of all seed treatments a significant yield increase was seen only in two of the treated SCN-susceptible seed plots as compared to the untreated control (Tylka & Marrett, 2008). Finally, Aveo® EZ had no effect on nematode populations, but had varied effects on yield in 2017 and 2018 field trials

(Tylka, 2019). To the best of my knowledge, there is no publicly available trial data on BioST® against SCN. The commercial biological products have different modes of action. P. nishizawae

Pn1, the active ingredient in Clariva® Complete is an obligate parasite of the nematode, and prevents SCN infection by directly infecting SCN juveniles, which subsequently alters the ability of the nematode to infect the soybean roots (Syngenta, 2013). Alternatively, B. firmus I-1582

(Poncho®/VoTiVO®) and B. amyloiquefaciens PTA 4838 (Aveo® EZ) colonize the plant roots and prevent infection by acting as physical barriers of entry to the juvenile SCN (BASF, n. d.;

Valent Biosciences, n.d.). Burkholderia rinojensis A396 (BioST®), in contrast to the other microorganisms, is applied as a dead microbe, and the modes of action is though enzymes and toxins in the growth medium (Albaugh, n.d.). The Harpin αβ protein in N-Hibit® induces systemic acquired resistance in treated plants, rather than directly targeting the pathogen

(USEPA-OPP, n.d).

Substantial effort has been expended into discovering additional “novel” microbes for use in SCN control. Marrone BioInnovations, Inc. submitted product registration with the EPA in

2013 for MBI-302, a formulation containing Flavobacterium sp. strain H492 (Marrone Bio

Innovations, 2013). While MBI-302 is not yet a commercially available product, isolates within this genus can reduce SCN activity. Two isolates of Flavobacterium johnsoniae showed activity against nematodes in greenhouse trials (Tian et al, 2000). Additional studies have investigated the potential for additional bacteria (including Bacillus and Burkholderia) as SCN biocontrol agents (Kloepper et al, 1992; Xiang et al, 2017). Fungi have also been investigated as biocontrol agents. Multiple studies demonstrated the ability of a collection of fungi isolated from soil across the Mid-South United States to parasitize SCN at multiple life stages in vitro and in greenhouse assays (Kim & Riggs 1991; Timper et al, 1999). Despite the potential of this fungal collection, a commercial product was not developed. At present there are no commercial, fungal-based biological nematicide for Soybean Cyst Nematode.

Finally, our lab has a collection of Pseudomonas spp. strains with demonstrated nematode activity against SCN in greenhouse trials, reducing cyst numbers compared to the

14 control (Aly, 2009; Xiao-Yuan Tao and Christopher Taylor, unpublished). The collection of bacterial strains used by Aly (2009) was used in many of the studies presented in future chapters.

1.4.2 Fusarium oxysporum management strategies

Genetics, soil disinfestation, biocontrol and best cultural practices are among strategies used to control diseases caused by Fusarium oxysporum. According to the Midwest Vegetable

Production Guide for Commercial Growers 2020 there are no fungicides recommended for control of Fusarium wilt of tomato (Egel, 2020). Metam sodium has been recommended as a fumigant for managing Fusarium crown and root rot of tomato, especially when combined with solarization, however efficacy of this compound is varied and could depend upon the method of application (Davis & Paulus 2014; McGovern et al, 1998). There are a limited number of fungicides recommended for control of Fusarium wilt and other Fusarium diseases in other crops, however additional methods of control are commonly suggested and will be discussed in the subsequent paragraphs (Egel, 2020).

F. oxysporum management: Genetics (resistance)

Grafting and resistant tomato cultivars are two commonly used methods to control the pathogen in a variety of crops (Egel, 2020). Many commercial tomato varieties (both seed and rootstock used for grafting) have resistance to a multitude of diseases including both Fusarium wilt and Fusarium crown rot (McGrath, n.d.). In a field trial where heirloom tomato scions were grafted to F. oxysporum f.sp. lycopersici resistant rootstock, disease incidence was significantly reduced in the plants with resistant rootstock, however significant increases in yield varied between field sites (Rivard & Louws, 2008). On the other hand, compared to the control plants

15 watermelon scion grafted with F. oxysporum f. sp. niveum race 2 resistant rootstocks grown in a severely infested field had significantly lower disease incidence and a significantly higher proportion of marketable-sized fruit (Keinath & Hassel, 2014). While grafting may be an effective tool, the economic benefit of resistant rootstock can depend on high enough disease pressure (and as it relates to yield not lost due to disease), particularly due to the high cost of grafted plants verses non-grafted (Rivard et al, 2010).

F. oxysporum management: Anaerobic soil disinfestation

Anaerobic soil disinfestation (ASD) has also been shown to control Fusarium oxysporum spp. In this strategy, organic amendments are first applied to soil infested with a phytopathogen, then the soil is saturated and covered to induce anaerobic conditions, and a subsequent decline in the pathogen population will occur (Testen & Miller, 2017b). One of the first reported accounts of ASD described control of F. oxysporum f. sp. asparagi (causal agent of crown and root rot of asparagus) added to soil amended with broccoli or grass clippings and covered in plastic. A similar level of control was not achieved with only the vegetal matter or plastic (Blok et al 2000).

F. oxysporum f. sp. lycopersici viability was reduced when soil containing the inoculum was watered with ethanol and stored in an airtight box as compared to the water- and non- treated soil

(Momma et al, 2010).

F. oxysporum management: Biological control

Biological control is another management strategy for disease caused by Fusarium.

Multiple biofungicides including Mycostop® (AgBio, active microbe Streptomyces K61),

Prestop® (AgBio, active microbe Gliocladium catenulatum J1446) and RootShield® (BioWorks,

16 active microbe Trichoderma harzianum T-22) are registered for activity against a number of fungal and oomycete pathogens including Fusarium. In greenhouse trials with F. oxysporum f. sp. radicis-cucumerinum (causal agent root and stem rot of cucumber) and the three

® aforementioned biological pesticides, only cucumber seedlings inoculated with Prestop had significantly lower disease incidence than plants inoculated with only the pathogen (Rose et al,

2003). Addition of RootShield® or SoilGard® (Certis USA, active microbe Trichoderma virens

GL-21) at sufficient rates to the potting media significantly reduced Fusarium wilt in F. oxysporum inoculated tomatoes (Larkin & Fravel, 1998). Many additional studies have investigated the potential of additional microorganisms (including Pseudomonas) to control both

Fusarium wilt and Fusarium crown and root rot (Larkin & Fravel, 1998; Mao et al, 1998;

McGovern, 2015; Rezzonico et al, 2007).

1.5 Pseudomonas

Pseudomonas is a diverse genus of gram-negative bacteria belonging to the λ- proteobacteria family. According to the List of Prokaryotic Names With Standing in

Nomenclature database, as of April 2020 there are over 300 species listed as Pseudomonas

(Parte, 2018). The number of species in this list is fluid, as species continue to be discovered and species reclassification occurs. Phylogenetic analysis of 141 strains has revealed Pseudomonas to be primarily divided into two distinct lineages, “P. fluorescens” and “P. aeruginosa.” (Mulet et al, 2012). Individual species within the genus cluster into phylogenetically distinct groups and sub-groups based on the 16S rDNA and housekeeping genes sequences. All of the Pseudomonas strains worked with in subsequent chapters of this dissertation are part of the Pseudomonas fluorescens group, but represent multiple subgroups based on species designation. Likewise,

17 most (if not all) of the plant pathogenic and biocontrol species described in this dissertation are part of the Pseudomonas fluorescens lineage (Anzai et al, 2000; Mulet et al, 2012).

Pseudomonads are found in a variety of environments, including soil, water, plants, and animals and occupy a variety of ecological niches.

1.5.1 Pathogenic Pseudomonas

Some species of Pseudomonas are pathogenic, including P. aeruginosa and P. syringae, which respectively infect humans and plants. Between 2011-2014, P. aeruginosa was the 6th most prevalent pathogen cause of healthcare associated infections in the United States, accounting for 7.3% (29,636 of a reported 365,490 pathogen infections) as reported to the CDC.

P. aeruginosa was found in a variety of infection types including surgical site infections, ventilator-associated pneumonias and catheter-associated urinary tract infections (Weiner et al,

2016). Additionally, individuals with cystic fibrosis (CF) are particularly susceptible to P. aeruginosa infection. In 2016, out of 29,497 patients in the United States with CF, over 46% tested positive for P. aeruginosa (Cystic Fibrosis Foundation, 2016). Epithelial cells from cystic fibrosis patients were conducive for bacteria growth, while cells from healthy individuals had bactericidal activity (Smith et al, 1996).

In 2012 plant bacteriologists associated with Molecular Plant Pathology voted P. syringae (all pathovars) to be the most important bacterial plant pathogen, taking both scientific and economic impact into consideration (Mansfield et al, 2012). The P. syringae group has over

60 pathovar types of P. syringae and other plant pathogenic Pseudomonas species (Baltrus et al,

2017). These bacteria primarily cause symptoms in the aboveground portion of the plant, including leaf spot, bacterial blight, bacterial canker, and galls, but can also affect the root

18 portion. Disease symptoms vary by host plant and pathovar type. (Höfte & De Vos, 2007). P. syringae can cause significant monetary loss in crops. An outbreak beginning in 2010 of P. syringae pv actinidiae (Psa) on kiwifruit had devastating effects on the New Zealand economy.

In 2012 it was estimated that Psa would cost the economy between 2012-2017 310-410 million

(NZD), with thousands of jobs lost and reduced fruit production (Greer & Saunders, 2012).

1.5.2 Beneficial Pseudomonas

Multiple strains of Pseudomonas have demonstrated beneficial activity through disease control or plant growth promotion. As of 2018 nine Pseudomonas strains were registered as biopesticide active ingredients with the United States Environmental Protection Agency, and many more strains have been investigated as biological control agents (USEPA, 2018). Burr et al

(1978) identified P. fluorescens and P. putida strains which were both antagonistic towards

Erwinia carotovora pv. carotovora in in vitro assays and increased yield of inoculated potatoes as compared to uninoculated controls in field trials. A collection of Pseudomonas strains isolated from water, soil and plants have exhibited biocontrol activity in in vitro assays against several bacterial and fungal phytopathogens including Fusarium graminearum, F. solani, Pythium irregulare, P. cryptoirregulare, Rhizoctonia solani, Ralstonia solanacearum, Botrytis cinera, and Sclerotinia sclerotiorum (Aly, 2009; Martin, 2017; Mavrodi et al, 2012; McSpadden

Gardener et al, 2005; Raudales et al, 2009; South et al, 2020; Subedi et al, 2019). The

Pseudomonas strains mentioned here were also tested in subsequent chapters of this dissertation.

Multiple pseudomonads have been reported to affect plant parasitic nematode activity. For example, Pseudomonas fluorescens F113 both increased the hatch rate and decrease juvenile motility of Globodera rostochiensis (Cronin et al, 1997). Both root knot nematode (Meloidogyne

19 javanica) and soil fungal pathogens were inhibited with the addition of P. aeruginosa IE-6S+ and

P. fluorescens CHA0 (Siddiqui & Shaukat, 2002; Siddiqui et al, 2006).

In addition to beneficial results achieved though adding bacteria into the system, disease control also occurs though antagonistic activity by native Pseudomonas populations in the rhizosphere. Some soils contain native microorganisms that suppress pathogen activity though general or specific mechanisms. Pseudomonas present in suppressive soil contributes to the control of take all disease (TAD) (causal agent Gaeumannomyces graminis var. tritici) in wheat through the production of various antifungal metabolites. Higher levels of beneficial pseudomonads indicated soil less conducive to TAD (Weller et al, 2002).

Pseudomonads, both singular strains and in suppressive soils, use one or a combination of mechanisms to control plant disease and promote plant growth. Within each mode of action, the plant pathogen is controlled by biocontrol agents either through antagonism or induction of systemic resistance in the plant. Some important mechanisms used by Pseudomonas in biocontrol will be described here. The collection of Pseudomonas strains used in the subsequent chapters of this work (Chapters 2, 3, and 4) may use one or multiple of the mechanisms described here in their bioactivity against phytopathogens. Full genome sequencing and analysis on the collection of bacteria has indicated the presence of genes coding for siderophores, secretion systems, and antimicrobial compounds (Xiao-Yuan Tao & Christopher Taylor, unpublished data).

Pseudomonas biocontrol: Siderophores and competition

Antagonistic pseudomonads can control phytopathogens though competition for nutrients and root space in the soil. Iron is an essential nutrient required by many living organisms but is

20 predominantly present in the soil in its non-bioavailable, insoluble form. Microorganisms, including Pseudomonas, produce siderophores, metal-chelating agents, to solubilize iron in the soil (Andrews et al, 2003). Removing essential nutrients from the soil can be an effective competition strategy. Pseudomonads can produce multiple siderophores including pyoverdine, which is widespread across many species, pyochelin, and quinolobactin (Budzikiewicz, 1997;

Cox et al, 1981; Mossialos et al, 2000). In environments with low iron availability, siderophore- producing Pseudomonas were antagonistic towards fungal and bacterial phytopathogens, while the antagonism was lost in the presence of high bioavailable iron. (Duijff et al, 1994; Kloepper et al, 1980a; Xu & Gross, 1985). A siderophore-producing P. putida strain was able to control fusarium wilt in carnation while a siderophore-lacking mutant was unable to, indicating that within certain bacteria siderophores may be involved in disease control (Duijff et al, 1994).

Siderophores can also contribute to the effectiveness of suppressive soil; soil originally conducive to either fusarium wilt or TAD became suppressive though the addition of

Pseudomonas or purified siderophores, and suppressive soil became conducive to disease with the addition of Fe3+ (Kloepper et al, 1980b).

In addition to suppressing disease, siderophore-producing bacteria can also promote plant growth and yield. In low Fe3+ soil, both siderophore-producing Pseudomonas B10 and pure siderophore inoculated on potatoes significantly enhanced plant growth, while the effect was lost in high Fe3+ soil (Kloepper et al, 1980a). Similarly, in greenhouse and field trials, potato seed tubers treated with siderophore-producing Pseudomonas putida WCS358 had significantly higher root weights and yields than the non-inoculated and WCS358-siderophore mutant treatments (Bakker et al, 1988).

Siderophores produced by other microorganisms can affect the bioactivity of those produced by the biocontrol agent. Pseudomonas strains were unable to antagonize siderophore producing Escherichia coli K-12 AN194 but were active against siderophore-lacking E. coli K-

12 AN193. (Kloepper et al, 1980a). Alternatively, in greenhouse assays siderophore-producing

Pseudomonas putida A12 was active against pathogenic, siderophore-producing fusaria (Scher &

Baker, 1982). These examples indicate bioactivity can depend on a number of factors, including the ability of competing microorganism to also produce siderophores.

Another competition strategy used by Pseudomonas is niche exclusion. Beneficial bacteria can outcompete the pathogen if both organisms occupy the same niche in the rhizosphere. Confocal laser microscope analysis revealed that beneficial P. chlororaphis

PCL1391 and P. fluorescens WCS365, and pathogenic F. oxysporum f. sp. radicis-lycopersici all colonized tomato- root cellular junctions. When the pseudomonads were present fungal colonization of the root cells was inhibited (Bolwerk et al, 2003). Similarly, P. fluorescens

PCL1751 treated tomato seeds had significantly lower disease as compared to the non-treated control when planted into F. oxysporum f. sp. radicis-lycopersici infested soil. PCL1751 neither induced systemic resistance (in contrast, WCS365 induced resistance) in inoculated tomato plants nor was bioactive in vitro, which indicates the bacteria may compete with the fungus through niche exclusion (Kamilova et al, 2005).

Pseudomonas biocontrol: Secretion systems

There are six known secretions systems used by gram-negative bacteria. Pseudomonads may contain one or multiple secretions systems which can directly antagonize other microorganisms. Described here are type three (T3) and type six (T6) secretion systems (SS),

22 which have been shown to play a role in the ability of Pseudomonas to control phytopathogen activity.

Pseudomonas biocontrol: Type three secretion systems

T3SS was first characterized in many gram-negative animal- and plant- pathogenic bacteria as a mechanism of protein transport from the pathogen to the host organism (Hueck,

1998). While there are at least seven characterized families of T3SS across all plant and animal associated bacteria, three types of T3SS are known to be utilized by Pseudomonas: Hrp/Hrc-1, -3

(hypersensitive response and pathogenicity; requires respectively presence of hrp/hrc1 and hrp/hrc2 gene clusters), and SPI-1 (Salmonella pathogenicity island; requires presence of inv/mxi/spa-like gene cluster). The structure of the T3SS gene clusters is not conserved across all

Pseudomonas species and strains (Egan et al, 2014; Loper et al, 2012; Tampakaki et al, 2010). In plant pathogenic bacteria including Erwinia spp., Ralstonia solanacearum, and P. syringae the

T3SS is involved in inducing hypersensitive response (HR), programmed cell death of infected cells in resistant plants, and causing disease in susceptible plants (Hueck, 1998; Tampakaki et al,

2010). Bacteria that have these gene clusters can produce a multitude of proteins which play a role in bacteria pathogenicity. Harpin and harpin-like proteins are well characterized effector proteins that play a role in Pseudomonas phytopathogenicity via T3SS Hrp/Hrc (Tampakaki et al, 2010). Wei et al (1992) originally isolated harpin (hrpN) from E. amylovora Ea321. When either pure bacteria culture or isolated proteins were infiltrated into tobacco (non-host of E. amylovora) leaves HR was induced; this activity was lost upon mutation of the hrpN gene (Wei et al, 1992). Since the original discovery of harpin in Erwinia, additional harpins produced by P.

23 syringae (HrpZ (HrpZ1), HrpW (HrpW1), HopAK1) have been identified as elicitors of HR in tobacco (Charkowski et al, 1998; He et al, 1993; Kvitko et al, 2007).

Beneficial Pseudomonas strains across multiple species also contain the genes coding for

T3SS. In a comparative genomic analysis, Loper et al (2012) identified the presence of gene clusters rsp/rsc (rhizosphere-expressed secretion protein and rsp- conserved), similar to the hrp/hrc gene clusters of Hrp1 of phytopathogenic Pseudomonas, in six known biocontrol strains across three species (P. fluorescens, P. brassicacearum, P. synxantha). Additionally, one of these strains also contained similarity to a SPI-1 family T3SS gene of Salmonella enterica (Loper et al,

2012). There is evidence for the importance of T3SS in P. fluorescens SBW25, one of the isolates studied in Loper et al (2012), for rhizosphere colonization. On inoculated sugar beet root tips, wild-type SBW25 were significantly better colonizers than select rsp mutants (Jackson et al,

2005). This indicates the T3SS may play a role in niche exclusion in a system where a pathogen is present. The T3SS can also play a role in phytopathogen control. Rezzonico et al (2005) demonstrated plant growth promotion of Pythium ultimum infected-cucumber seedlings inoculated with P. fluorescens KD as compared to its hrcV mutant and the untreated control.

Neither P. fluorescens SBW25 nor KD were able to elicit the traditional T3SS HR in inoculated plants, further demonstrating that the role of the T3SS varies between pathogenic and beneficial bacteria (Preston et al, 2001; Rezzonico et al 2004).

Pseudomonas biocontrol: Type six secretion systems

T6SS is present across multiple classes of gram-negative bacteria including alpha- proteobacteria, beta-proteobacteria, and gamma-proteobacteria. It plays a role in multiple bacterial functions including the interbacterial competition, host manipulation, and biofilm

24 formation. Many Pseudomonas strains (including human pathogenic, plant pathogenic and non- pathogenic strains), contain gene sequences encoding for the secretion systems, although differences occur both in T6SS copy number and type (genetic structure and secreted proteins) among different species and strains (Bernal et al, 2017; Bernal et al, 2018; Filloux et al, 2008).

Within the Pseudomonas genus, multiple gene clusters code for T6SS proteins. P. aeruginosa contains three T6SS gene loci (Hcp (Haemolysin A co-regulated protein) Secretion Island (HSI)-

I, -II, -III). The HSI loci contain genes coding for both secreted (Hcp and VgrG) and non- secreted proteins (Filloux et al, 2008; Lesic et al, 2009; Mougous et al 2006). The T6SS loci play a role in P. aeruginosa virulence in animal and plant systems. Deletion of both the HSI-II and -

III clusters in P. aeruginosa PA14 both significantly decreased the mortality rate of mice infected with the bacteria and lowered the amount of bacteria colonizing inoculated Arabidopsis thaliana plants as compare to the controls (Lesic et al, 2009).

The T6SS can also play a role in beneficial plant bacteria controlling phytopathogenic bacteria. Wild type P. fluorescens MFE01, capable of secreting Hcp- and VgrG-like proteins, was able to inhibit both Pectobacterium atrosepticum growth in vitro in co-culture assays and soft-rot on potato tubers inoculated with P. atrosepticum, while treatment with the Δhcp2 mutant was comparable to the controls (Decoin et al, 2014). P. putida KT2440 has three main T6SS clusters (KI, -II, -III) as well as hcp and vgr “orphan” clusters. When subjected to competition assays with Xanthomonas campestris, Nicotiana benthamiana leaves treated with KT2440 had less leaf tissue necrosis and X. campestris colonization as compared to the control and

KT2440ΔT3SS triple mutant. KT2440 has 10 potential T6SS effector proteins, all of which may play a role in bioactivity against prey bacteria (Bernal et al, 2017).

Pseudomonas biocontrol: Antimicrobial secondary metabolites

Pseudomonads can produce numerous secondary metabolites that demonstrate antagonistic activity against competing organisms. Many bacteria produce more than one antibiotic and bioactivity can be due to a combination of metabolites. Many of the antimicrobial compounds (including secreted, volatile, and siderophores) produced by Pseudomonas (both antagonistic and beneficial strains) are controlled by presence of the GacA/GacS (global activator of antibiotic and cyanide synthesis) system (Heeb & Haas, 2001). For example, unlike their wildtype, gacA mutants of P. fluorescens CHA0 produced negligible to no 2,4- diacetylphloroglucinol (DAPG), pyoluteorin, and hydrogen cyanide (HCN) (Laville et al, 1992).

Likewise, Gac mutants of additional Pseudomonas strains were unable to produce select volatile compounds (including HCN, organosulfur compounds, and 2R, 3R-butanediol) (Han et al, 2006;

Ossowicki et al, 2017). Bacterial production of certain metabolites can be associated. For example, Rezzonico et al (2007) found that over 98% of DAPG producers also produced HCN; however, the inverse was not true: many HCN producers did not produce DAPG. Genetic analysis of the Pseudomonas collection used in this work revealed this same association of

DAPG and HCN (Xiao-Yuan Tao & Christopher Taylor, unpublished) (Table 2.1). Described below are some examples of antimicrobial secondary metabolites, including both non-volatile and volatile compounds.

Pseudomonas biocontrol: Non-volatile antimicrobials

Beneficial pseudomonads can produce numerous antimicrobial metabolites including, but not limited to, DAPG, phenazines, and pyrrolnitrin. Weller et al (2002) proposed that within a wheat monoculture system, soil suppressiveness increases with the increasing abundance of

DAPG producing bacteria. P. fluorescens CHA0, a known DAPG producer, has shown inhibitory activity against several pathogens. Wildtype CHA0 was able to inhibit both F. oxysporum and G. graminis var. tritici in vitro while inhibition was not seen with the DAPG- deficient mutant (Keel et al, 1992). Disease severity in tobacco plants inoculated with both

Thielaviopsis basicola and CHA0 was reduced, while mutants were comparable to the controls

(Keel et al, 1992; Laville et al, 1992). Similarly, tomato plants co-inoculated with Clavibacter michiganensis subsp. michiganensis and Pseudomonas sp. LBUM300 had better disease control than plants co-inoculated with the pathogen and a LBUM300 DAPG-minus mutant (Lanteigne et al, 2012). Genotypic variation of the phlD (DAPG marker) gene occurs across Pseudomonas, which leads to varied biocontrol activity of individual bacteria. In vitro inhibition assays against

Pythium using Pseudomonas strains representative of four phlD genotypes had mixed results, dependent on the nutrient composition of the media used (McSpadden Gardener et al, 2005).

Synthetic DAPG inhibited the growth of multiple fungal and bacterial pathogens and reduced potato cyst nematode (Globodera rostochiensis) juvenile mobility (Cronin et al, 1997; Keel et al

1992).

Pseudomonads can also produce multiple phenazines (e.g. pyocyanin and phenazine-1- carboxylic acid), some of which have known biocontrol potential. The efficacy of the compounds in the control of microorganisms can be dependent on multiple factors including pH and quorum sensing of the beneficial bacteria (Cezairliyan et al, 2013; Chin-a-Wong et al 1998;

Wood & Pierson, 1996). Phenazine producing pseudomonads (wild type or mutants) were able to significantly inhibit C. elegans in vitro and reduce symptoms of multiple fungal diseases in planta as compared to their PCA-deficient mutants (Arseneault et al, 2013; Cezairliyan et al,

2013; Chin-A-Woeng et al, 1998; Thomashow & Weller, 1988). Additionally, pyocyanin

27 producer P. aeruginosa 7NSK2 controlled foliar phytopathogens through induction of systemic resistance in inoculated plants while the pyocyanin-mutants were comparable to the control treatments (Audenaert et al, 2002; De Vleesschauwer et al, 2006). The activities of individual phenazines have been investigated for antagonistic activity towards microorganisms both in vitro and in planta (Cezairliyan et al, 2013; Chin-A-Wong et al, 1998; De Vleesschauwer et al, 2006;

Gurusiddaiah et al, 1986)

Pyrrolnitrin also plays a role in the biocontrol potential of pseudomonads. Originally isolated from a Pseudomonas and characterized by Arima et al (1964), the antibiotic showed activity against multiple human bacterial pathogens. In addition, pyrrolnitrin is effective in vitro or in planta against multiple fungal phytopathogens (Howell & Stipanovic, 1979; Pfender et al,

1993) Studies have also investigated the biocontrol potential of P. fluorescens strains capable of producing pyrrolnitrin. Fungal pathogen (Sclerotinia homoeocarpa and Pyrenophora tritici- repentis) growth was inhibited with addition of P. fluorescens Pf-5 to inoculum containing the fungus as compared to the negative controls and pyrrolnitrin-deficient mutants (Pfender et al,

1993; Rodriguez & Pfender, 1997). Damping off (causal agent R. solani) was also significantly reduced by treating seeds with P. fluorescens strains BL915 or PF-5 before planting in inoculated soil as compared to the control (Hill et al, 1994; Howell & Stipanovic 1979). Insertion of pyrrolnitrin biosynthesis genes into Pseudomonas strains that were both unable to produce the antibiotic and were not inhibitory against R. solani in vitro enabled them to antagonize the pathogen in vitro and produce a measurable amount of pyrrolnitrin (Hill et al, 1994).

Pseudomonas biocontrol: Volatile antimicrobials

Many pseudomonads, representative of both pathogenic and beneficial bacteria, spread across the genus can produce volatile organic compounds (VOCs) with antagonistic activity

28 against a wide diversity of pathogens. Some well characterized antimicrobial volatiles include

HCN, organosulfur compounds, and hydrocarbons. HCN was fully inhibitory to nematodes (C. elegans) and fungus (Puccinia recondita f. sp. tritici and Septoria tritici) (Flaishman et al, 1996;

Gallagher and Manoil 2001). In vitro volatile assays with HCN-producing pseudomonads demonstrated antagonistic activity against multiple plant pathogens (Ahl et al, 1986; Hunziker et al. 2015; Ossowicki et al, 2017). Multiple studies determined cyanide production and control against black root rot (causal agent Thielaviopsis basicola) in tobacco were substantially higher in P. protegens (formerly P. fluorescens) CHA0 than multiple HCN-deficient mutants (anr, gacA and hcn) while the complemented mutants had restored activity to varying extents (Laville et al,

1998; Laville et al, 1992; Voisard et al, 1989). HCN-producing Pseudomonas strains have also been investigated against nematode species. C. elegans and Meloidogyne javanica were inhibited to varying extents by HCN-producing pseudomonads as compared to their cyanide-mutant strains (Gallagher & Manoil, 2001; Siddiqui et al, 2006). Addition of amino acids including glycine (direct precursor to HCN) and threonine to the media enhanced cyanide production of pseudomonads (Aly, 2009; Castric, 1977; Gross & Loper, 2009; Kang et al, 2018).

Pseudomonads can also produce a variety of organosulfur compounds, some of which have demonstrated antimicrobial activity. Organosulfur volatiles produced by bacteria are originally derived from methionine converted into methanethiol, which is subsequently converted into more complex molecules including sulfides and thioesters (Carrión et al, 2015;

Yvon & Rijnen, 2001). One well studied organosulfur compound is dimethyl disulfide (DMDS), which is currently sold commercially as an alternative to the fumigant methyl bromide (Paladin®,

Arkema Inc, France) (USEPA, 2012). When applied to soil in field trials as a synthetic fumigant

(rate 300-600 liters/ha), DMDS decreased disease caused by Meloidogyne spp. and F. oxysporum

29 f. sp. radices-lycopersici (Gómez-Tenorio et al, 2018; Leocata et al, 2014). Multiple

Pseudomonas strains capable of inhibiting fungal pathogens in vitro produced organosulfur compounds including dimethyl sulfide (DMS), DMDS, dimethyl trisulfide (DMTS), and S-

Methyl methanethiosulfonate (MMTS), as measured in the headspace of cultures using GC-MS.

Some studies reported that DMDS was one of the most abundant VOCs quantified in the headspace (Briard et al, 2016; De Vrieze et al, 2015; Hunziker et al, 2015; Ossowicki et al, 2017;

Zhou et al, 2014). Activity of organosulfur compounds can vary against specific organisms. Pure

DMDS and/or DMTS inhibited select bacterial, fungal, and oomycete pathogens to varying extents when exposed indirectly to the microorganism (Briard et al, 2016; De Vrieze et al, 2015;

Ossowicki et al, 2017; Zhou et al, 2014). DMTS and MMTS were more effective at inhibiting P. infestans mycelial growth and spore production/germination than DMDS (De Vrieze et al, 2015).

Not every organosulfur compound is inhibitory, and inhibition may be environment dependent.

Both P. aeruginosa volatiles and DMS stimulated the growth of the human pathogen Aspergillus fumigatus. Additionally, both DMS and DMDS stimulated the growth of A. fumigatus when the fungus was grown on a sulfur-depleted medium (Briard et al, 2018).

Hydrocarbons are another class of VOCs commonly produced by Pseudomonas. 1- undecene (C11H22) was a highly abundant compound in the volatile profile of multiple strains

(De Vrieze et al, 2015; Hunziker et al, 2015; Lo Cantore et al, 2015; Ossowicki et al, 2017; Zhou et al, 2014). Control activity due to 1-undecene was dose dependent. Growth of fungi and oomycetes was lowered to when exposed to 1-undecene at high enough levels, however significance and degree of inhibition varied between both the organisms and chemical concentration (De Vrieze et al, 2015; Hunziker et al, 2015; Lo Cantore et al 2015; Zhou et al,

2014).

Not all volatiles produced by Pseudomonas are involved in direct antagonism of a competing microorganism. 2R, 3R-Butanediol provides multiple benefits to inoculated plants. It can promote plant growth, yield, and ISR, as evidenced in both tobacco seedlings inoculated with Pectobacterium carotovorum (causal agent of soft rot) and pepper plants planted in soil naturally infested with multiple pathogenic viruses (Han et al, 2006; Kong et al, 2018). Drought symptoms in Arabidopsis thaliana were alleviated in plants inoculated with 2R, 3R-butanediol as compared the control (Cho et al, 2008). 2R, 3R-Butanediol producer Pseudomonas chlororaphis

O6 both induced resistance to P. carotovorum in tobacco and alleviated drought symptoms in A. thaliana as compared to its gacS- mutant and controls. While the gacS complemented mutant restored activity (either partial or full), it is possible that the effect was due to a combination of factors including 2R, 3R-butanediol, as the GacA/GacS complex regulates many genes (Cho et al, 2008; Han et al, 2006).

Chapters 2 and 3 of this dissertation will focus on identifying the volatile profile of

Pseudomonas strains, their impact on plant pathogens, and determining whether the bacteria can be primed for the production of specific volatile compounds.

1.6 Commercial Pseudomonas-based products

Multiple Pseudomonas strains have been formulated for sale in the United States as either biopesticides or biostimulants. Microbial biopesticides are products that are microbe based, and specific in their target organisms. Per USEPA rules, despite them being considered less toxic and quicker to breakdown than conventional pesticides, sufficient data and product registration is still required for biopesticides to be made commercially available (USEPA, n.d.). Biostimulants on the other hand do not have a set definition or regulatory requirements in the United States but are

31 intended to enhance plant health though a variety of mechanisms (du Jardin, 2015). As of April

2020, the USEPA is working on framework for biostimulants, but no decisions are available on the topic (Dunn, 2019). A representative list of commercially sold Pseudomonas products in the

United States is found in Table 1.1. While the biopesticides listed in Table 1.1 contain only

Pseudomonas strains as the active ingredient, the biostimulants include the pseudomonad as part of a consortium.

Worldwide, companies are continuing to develop new microorganism-based products

(biopesticide and biostimulant). Chapter 4 of this dissertation will describe a collaboration with a biologicals company to determine the potential of Pseudomonas strains to control SCN; Chapter

5 will describe university-company relationships in regard to product discovery and development.

1.7 Objectives

The overarching goal of this dissertation is investigating the potential for Pseudomonas as biocontrol agents. To accomplish this, this work is divided into four primary objectives:

1) To determine the global volatile profile of a diverse collection of Pseudomonas strains

and identify the biocontrol potential of the bacterial volatiles.

2) To determine whether manipulation of the growth medium can enhance production of

specific VOCs and bioactivity of the bacteria.

3) To assess the potential of Pseudomonas to control SCN in the greenhouse and microplot

settings. This objective was conducted in collaboration with 3Bar Biologics Inc.

(Columbus, OH, USA).

4) To investigate the potential for increased industry-university collaborations in the fields

of microorganisms and natural product discovery and development. This objective was

completed as part of the I-CORPS@Ohio training program.

References

Abawi, G. S., & Jacobsen, B. J. (1984). Effect of initial inoculum densities of Heterodera glycines on growth of soybean and kidney bean and their efficiency as hosts under greenhouse conditions. Phytopathology, 74, 1470–1474. Ahl, P., Voisard, C., & Défago, G. (1986). Iron bound‐siderophores, cyanic acid, and antibiotics involved in suppression of Thielaviopsis basicola by a Pseudomonas fluorescens strain. Journal of Phytopathology, 116(2), 121–134. https://doi.org/10.1111/j.1439- 0434.1986.tb00903.x Ahmed, S. M., Byrd-Masers, L., & Mehl, H. L. (2018). Evaluation of nematicide seed treatments for control of soybean cyst nematode (SCN) in soybean in Virginia, 2017. Plant Disease Management Reports, 12, N003. Albaugh. n.d. BIOST® Nematicide 100. https://www.albaughllc.com/webres/File/North- America/Seed-Treatment/BioST%20Nematicide.pdf Allen, T. W., Bradley, C. A., Sisson, A. J., Byamukama, E., Chilvers, M. I., Coker, C. M., … Wrather, J. A. (2017). Soybean yield loss estimates due to diseases in the United States and Ontario, Canada, from 2010 to 2014. Plant Health Progress, 18(1), 19–27. https://doi.org/10.1094/PHP-RS-16-0066 Aly, H. (2009). Role of Pseudomonas produced hydrogen cyanide in biological control of plant- parasitic nematodes. University of Missouri-St. Louis [Dissertation]. https://irl.umsl.edu/cgi/viewcontent.cgi?article=1385&context=dissertation Anand, S. C., & Brar, G. S. (1983). Response of soybean lines to differentially selected cultures of soybean cyst nematode Heterodera glycines Ichinohe. Journal of Nematology, 15(1), 120– 123. Andrews, S. C., Robinson, A. K., & Rodríguez-Quiñones, F. (2003). Bacterial iron homeostasis. FEMS Microbiology Reviews, 27(2–3), 215–237. https://doi.org/10.1016/S0168- 6445(03)00055-X Anzai, Y., Kim, H., Park, J., Wakabayashi, H., & Oyaizu, H. (2000). Phylogenetic affiliation of the pseudomonads based on 16S rRNA sequence. International Journal of Systematic and Evolutionary Microbiology, 50(4), 1563–1589. https://doi.org/10.1099/00207713-50-4-1563 Arelli, P. R., Sleper, D. A., Yue, P., & Wilcox, J. A. (2000). Soybean reaction to races 1 and 2 of Heterodera glycines. Crop Science, 40(3), 824-826. https://doi.org/10.2135/cropsci2000.403824x Arima, K., Imanaka, H., Kousaka, M., Fukuda, A., & Tamura, G. (1964). Pyrrolnitrin, a new antibiotic substance, produced by Pseudomonas. Agricultural and Biological Chemistry, 28(8), 575–576. https://doi.org/10.1080/00021369.1964.10858275 Arseneault, T., Goyer, C., & Filion, M. (2013). Phenazine production by Pseudomonas sp. LBUM223 contributes to the biological control of potato common scab. Phytopathology, 103(10), 995–1000. https://doi.org/10.1094/PHYTO-01-13-0022-R Audenaert, K., Pattery, T., Cornelis, P., & Höfte, M. (2002). Induction of systemic resistance to Botrytis cinerea in tomato by Pseudomonas aeruginosa 7NSK2: Role of salicylic acid, pyochelin, and pyocyanin. Molecular Plant-Microbe Interactions, 15(11), 1147–1156. https://doi.org/10.1094/MPMI.2002.15.11.1147 Bakker, P. A. H. M., Schippers, B., & Weisbeek, P. J. (1988). Siderophore production by plant growth-promoting Pseudomonas spp. Journal of Plant Nutrition, 11(6–11), 925–933. https://doi.org/10.1080/01904168809363857

Baltrus, D. A., McCann, H. C., & Guttman, D. S. (2017). Evolution, genomics and epidemiology of Pseudomonas syringae: Challenges in bacterial molecular plant pathology. Molecular Plant Pathology, 18(1), 152–168. https://doi.org/10.1111/mpp.12506 BASF. n.d. Poncho® Votivo® seed treatment. https://agriculture.basf.us/crop- protection/products/poncho-votivo.html Beeman, A. Q., & Tylka, G. L. (2018). Assessing the effects of ILeVO and VOTiVO seed treatments on reproduction, hatching, motility, and root penetration of the soybean cyst nematode, Heterodera glycines. Plant Disease, 102(1), 107–113. https://doi.org/10.1094/PDIS-04-17-0585-RE Bernal, P., Allsopp, L. P., Filloux, A., & Llamas, M. A. (2017). The Pseudomonas putida T6SS is a plant warden against phytopathogens. ISME Journal, 11, 972–987. https://doi.org/10.1038/ismej.2016.169 Bernal, P., Llamas, M. A., & Filloux, A. (2018). Type VI secretion systems in plant-associated bacteria. Environmental Microbiology, 20(1), 1–15. https://doi.org/10.1111/1462-2920.13956 Bissonnette, K. M., Marett, C. C., Mullaney, M. P., Gebhart, G. D., Kyveryga, P., Mueller, T. A., & Tylka, G. L. (2018). Effects of Clariva Complete Beans seed treatment on Heterodera glycines reproduction and soybean yield in Iowa. Plant Health Progress, 19(1), 1–8. https://doi.org/10.1094/PHP-08-17-0043-RS Blok, W. J., Lamers, J. G., Termorshuizen, A. J., & Bollen, G. J. (2000). Control of soilborne plant pathogens by incorporating fresh organic amendments followed by tarping. Phytopathology, 90(3), 253–259. https://doi.org/10.1094/PHYTO.2000.90.3.253 Bohlmann, H., & Sobczak, M. (2014). The plant cell wall in the feeding sites of cyst nematodes. Frontiers in Plant Science, 5(89). https://doi.org/10.3389/fpls.2014.00089 Bolwerk, A., Lagopodi, A. L., Wijfjes, A. H. M., Lamers, G. E. M., Chin-A-Woeng, T. F. C., Lugtenberg, B. J. J., & Bloemberg, G. V. (2003). Interactions in the tomato rhizosphere of two Pseudomonas biocontrol strains with the phytopathogenic fungus Fusarium oxysporum f. sp. radicis-lycopersici. Molecular Plant-Microbe Interactions, 16(11), 983–993. https://doi.org/10.1094/MPMI.2003.16.11.983 Briard, B., Heddergott, C., & Latgé, J. P. (2016). Volatile compounds emitted by Pseudomonas aeruginosa stimulate growth of the fungal pathogen Aspergillus fumigatus. MBio, 7(2), e00219-16. https://doi.org/10.1128/mBio.00219-16 Broders, K. D., Lipps, P. E., Paul, P. A., & Dorrance, A. E. (2007). Evaluation of Fusarium graminearum associated with corn and soybean seed and seedling disease in Ohio. Plant Disease, 91(9), 1155–1160. https://doi.org/10.1094/PDIS-91-9-1155 Brucker, E., Carlson, S., Wright, E., Niblack, T., & Diers, B. (2005). Rhg1 alleles from soybean PI 437654 and PI 88788 respond differentially to isolates of Heterodera glycines in the greenhouse. Theoretical and Applied Genetics, 111, 44–49. https://doi.org/10.1007/s00122- 005-1970-3 Budzikiewicz, H. (1997). Siderophores of fluorescent pseudomonads. Zeitschrift Fur NaturforschungC- A Journal of Biosciences, 52(11–12), 713–720. https://doi.org/10.1515/znc-1997-11-1201 Burr, T. J., Schroth, M. N., & Suslow, T. (1978). Increased potato yields by treatment of seedpieces with specific strains of Pseudomonas fluorescens and P. putida. Phytopathology, 68(9), 1377–1383. https://doi.org/10.1094/phyto-68-1377

Carrión, O., Curson, A. R. J., Kumaresan, D., Fu, Y., Lang, A. S., Mercadé, E., & Todd, J. D. (2015). A novel pathway producing dimethylsulphide in bacteria is widespread in soil environments. Nature Communications, 6(6579). https://doi.org/10.1038/ncomms7579 Castric, P. A. (1977). Glycine metabolism by Pseudomonas aeruginosa: Hydrogen cyanide biosynthesis. Journal of Bacteriology, 130(2), 826–831. https://doi.org/10.1128/jb.130.2.826- 831.1977 Cezairliyan, B., Vinayavekhin, N., Grenfell-Lee, D., Yuen, G. J., Saghatelian, A., & Ausubel, F. M. (2013). Identification of Pseudomonas aeruginosa phenazines that kill Caenorhabditis elegans. PLoS Pathogens, 9(1), e1003101. https://doi.org/10.1371/journal.ppat.1003101 Charkowski, A. O., Alfano, J. R., Preston, G., Yuan, J., He, S. Y., & Collmer, A. (1998). The Pseudomonas syringae pv. tomato HrpW protein has domains similar to harpins and pectate lyases and can elicit the plant hypersensitive response and bind to pectate. Journal of Bacteriology, 180(19), 5211–5217. https://doi.org/10.1128/jb.180.19.5211-5217.1998 Chilvers, M. I., Warner, F. W., Jacobs, J. L., & Wang, J. (2012). Efficacy of nematicide and fungicide seed treatments for soybean cyst nematode and soybean sudden death syndrome on soybeans in Michigan, 2011. Plant Disease Management Reports, 6(ST003). Chin-A-Woeng, T. F. C., Bloemberg, G. V., Van Der Bij, A. J., Van Der Drift, K. M. G. M., Schripsema, J., Kroon, B., … Lugtenberg, B. J. J. (1998). Biocontrol by phenazine-1- carboxamide-producing Pseudomonas chlororaphis PCL1391 of tomato root rot caused by Fusarium oxysporum f. sp. radicis-lycopersici. Molecular Plant-Microbe Interactions, 11(11), 1069–1077. https://doi.org/10.1094/MPMI.1998.11.11.1069 Cho, S. M., Kang, B. R., Han, S. H., Anderson, A. J., Park, J.-Y., Lee, Y.-H., … Kim, Y. C. (2008). 2R,3R-butanediol, a bacterial volatile produced by Pseudomonas chlororaphis O6, is involved in induction of systemic tolerance to drought in Arabidopsis thaliana. Molecular Plant-Microbe Interactions, 21(8), 1067–1075. https://doi.org/10.1094/MPMI-21-8-1067 Concibido, V. C., Diers, B. W., & Arelli, P. R. (2004). A decade of QTL mapping for cyst nematode resistance in soybean. Crop Science, 44(4), 1121–1131. https://doi.org/10.2135/cropsci2004.1121 Cox, C. D., Rinehart, K. L., Moore, M. L., & Cook, J. C. (1981). Pyochelin: Novel structure of an iron-chelating growth promoter for Pseudomonas aeruginosa. Proceedings of the National Academy of Sciences of the United States of America, 78(7), 4256–4260. https://doi.org/10.1073/pnas.78.7.4256 Correll, J., & Jones, J. P. (2014). Fusarium wilt. In J. B Jones, T. A. Zitter, T. M. Momol, & S. A. Miller (Eds). Compendium of tomato diseases and pests, Second edition (pp. 28-29). https://doi.org/10.1094/9780890544341.002 Cronin, D., Moënne-Loccoz, Y., Fenton, A., Dunne, C., Dowling, D. N., & O’Gara, F. (1997). Role of 2,4-diacetylphloroglucinol in the interactions of the biocontrol pseudomonad strain F113 with the potato cyst nematode Globodera rostochiensis. Applied and Environmental Microbiology, 63(4), 1357–1361. https://doi.org/10.1128/aem.63.4.1357-1361.1997 Cystic Fibrosis Foundation. (2016). Annual data report 2016: Cystic Fibrosis Foundation patient registry. https://www.cff.org/research/researcher-resources/patient-registry/2016- patient-registry-annual-data-report.pdf Davis, R. M., & Paulus, A. O. (2014). Fusarium crown and root rot. In J. B Jones, T. A. Zitter, T. M. Momol, & S. A. Miller (Eds). Compendium of tomato diseases and pests, Second edition (pp. 25-27). https://doi.org/10.1094/9780890544341.002

DeBach, P., & Rosen, D. (1991). Biological control by natural enemies, Second edition. Cambridge University Press. De Bruin, J. L., & Pedersen, P. (2008). Soybean cultivar and planting date response to soil fumigation. Agronomy Journal, 100(4), 965–970. https://doi.org/10.2134/agronj2007.0116 Decoin, V., Barbey, C., Bergeau, D., Latour, X., Feuilloley, M. G. J., Orange, N., & Merieau, A. (2014). A type VI secretion system is involved in Pseudomonas fluorescens bacterial competition. PLoS ONE, 9(2). https://doi.org/10.1371/journal.pone.0089411 Dunn, A. D. (2019) Pesticides; draft guidance for pesticide registrants on plant regulator label claims, including plant biostimulants; notice of availability. Federal Register, 84(59):11538- 11540. https://www.govinfo.gov/content/pkg/FR-2019-03-27/pdf/2019-05879.pdf De Vleesschauwer, D., Cornelis, P., & Höfte, M. (2006). Redox-active pyocyanin secreted by Pseudomonas aeruginosa 7NSK2 triggers systemic resistance to Magnaporthe grisea but enhances Rhizoctonia solani susceptibility in rice. Molecular Plant-Microbe Interactions, 19(12), 1406–1419. https://doi.org/10.1094/MPMI-19-1406 De Vrieze, M., Pandey, P., Bucheli, T. D., Varadarajan, A. R., Ahrens, C. H., Weisskopf, L., & Bailly, A. (2015). Volatile organic compounds from native potato-associated Pseudomonas as potential anti-oomycete agents. Frontiers in Microbiology, 6(1295). https://doi.org/10.3389/fmicb.2015.01295 DiCarolis, J., Haab, T., Plakias, Z., Sheldon, I., Sohngen, B., & Trinoskey, K. (2017). The economic contribution of agricultural and food production to the Ohio economy. The Ohio State University-College of Food, Agricultural, and Environmental Sciences. https://aede.osu.edu/sites/aede/files/publication_files/The%20Economic%20Contribution%2 0of%20Agricultural%20and%20Food%20Production%20to%20the%20Ohio%20Economy_ FINAL%20Nov%2028%202017.pdf Dorrance, A. E., McClure, S. A., & DeSilva, A. (2003). Pathogenic diversity of Phytophthora sojae in Ohio soybean fields. Plant Disease, 87(2), 139–146. https://doi.org/10.1094/PDIS.2003.87.2.139 Duijff, B. J., Bakker, P. A. H. M., & Schippers, B. (1994). Suppression of Fusarium wilt of carnation by Pseudomonas putida WCS358 at different levels of disease incidence and iron availability. Biocontrol Science and Technology, 4(3), 279–288. https://doi.org/10.1080/09583159409355336 du Jardin, P. (2015). Plant biostimulants: Definition, concept, main categories and regulation. Scientia Horticulturae, 196, 3–14. https://doi.org/10.1016/j.scienta.2015.09.021 Dunham, M. (2017). Biological control global market overview. http://wrir4.ucdavis.edu/events/2017_SLR_Meeting/Presentations/GeneralPresentations/1 Trimmer - Global Biocontrol Market 2017.pdf Egan, F., Barret, M., & O’Gara, F. (2014). The SPI-1-like type III secretion system: More roles than you think. Frontiers in Plant Science, 5(34). https://doi.org/10.3389/fpls.2014.00034 Egel, D. (2020). Midwest vegetable production guide for commercial growers 2020. https://mwveguide.org/uploads/pdfs/ID-56-web-2020.pdf Filloux, A., Hachani, A., & Bleves, S. (2008). The bacterial type VI secretion machine: Yet another player for protein transport across membranes. Microbiology, 154(6), 1570–1583. https://doi.org/10.1099/mic.0.2008/016840-0 Flaishman, M. A., Eyal, Z., Zilberstein, A., Voisard, C., & Haas, D. (1996). Suppression of Septoria tritici blotch and leaf rust of wheat by recombinant cyanide-producing strains of Pseudomonas putida. Molecular Plant-Microbe Interactions, 9(7), 642–645.

Frye, J. W. (2009). Efficacy of novel nematicide seed treatments for the control of Heterodera glycines in soybean production. North Carolina State University. [Thesis]. https://repository.lib.ncsu.edu/bitstream/handle/1840.16/46/etd.pdf?sequence=1&isAllowed= y Gallagher, L. A., & Manoil, C. (2001). Pseudomonas aeruginosa PAO1 kills Caenorhabditis elegans by cyanide poisoning. Journal of Bacteriology, 183(21), 6207–6214. https://doi.org/10.1128/JB.183.21.6207 Gao, B., Allen, R., Maier, T., Davis, E. L., Baum, T. J., & Hussey, R. S. (2003). The parasitome of the phytonematode Heterodera glycines. Molecular Plant-Microbe Interactions, 16(8), 720–726. https://doi.org/10.1094/MPMI.2003.16.8.720 Gipson, I., Kim, K. S., & Riggs, R. D. (1971). An ultrastructural study of syncytium development in soybean roots infected with Heterodera glycines. Phytopathology, 61, 347– 353. https://doi.org/10.1094/phyto-61-347 Golden, A. M., Epps, J. M., Riggs, R. D., Duclos, L. A., Fox, J. A., & Bernard, R. L. (1970). Terminology and identity of infraspecific forms of the soybean cyst nematode (Heterodera glycines). Plant Disease Reporter, 54(7), 544–546. Gómez-Tenorio, M. A., Tello, J. C., Zanón, M. J., & de Cara, M. (2018). Soil disinfestation with dimethyl disulfide (DMDS) to control Meloidogyne and Fusarium oxysporum f. sp. radicis- lycopersici in a tomato greenhouse. Crop Protection, 112, 133–140. https://doi.org/10.1016/j.cropro.2018.05.023 Greer, G., & Saunders, C. (2012). The costs of Psa-V to the New Zealand kiwifruit industry and the wider community (Research Report Number 327). Lincoln University-Agribusiness and Economics Research Unit. https://researcharchive.lincoln.ac.nz/bitstream/handle/10182/5448/aeru_rr_327.pdf?sequence =1&isAllowed=y Gross, H., & Loper, J. E. (2009). Genomics of secondary metabolite production by Pseudomonas spp. Natural Product Reports, 26(11), 1408–1446. https://doi.org/10.1039/b817075b Gurusiddaiah, S., Weller, D. M., Sarkar, A., & Cook, R. J. (1986). Characterization of an antibiotic produced by a strain of Pseudomonas fluorescens inhibitory to Gaeumannomyces graminis var. tritici and Pythium spp. Antimicrobial Agents and Chemotherapy, 29(3), 488– 495. https://doi.org/10.1128/AAC.29.3.488 Han, S. H., Lee, S. J., Moon, J. H., Park, K. H., Yang, K. Y., Cho, B. H., … Kim, Y. C. (2006). GacS-dependent production of 2R, 3R-butanediol by Pseudomonas chlororaphis O6 is a major determinant for eliciting systemic resistance against Erwinia carotovora but not against Pseudomonas syringae pv. tabaci in tobacco. Molecular Plant-Microbe Interactions, 19(8), 924–930. https://doi.org/10.1094/MPMI-19-0924 Hancock, D. W., Lacy, R. C., Stewart, R. L., Tubbs, R. S., Kichler, J., Green, T. W., & Hicks, R. (2017). The management and use of bahiagrass (UGA Cooperative Extension Bulletin 1362). The University of Georgia Cooperative Extension. https://secure.caes.uga.edu/extension/publications/files/pdf/B%201362_4.PDF He, S. Y., Huang, H. C., & Collmer, A. (1993). Pseudomonas syringae pv. syringae harpinPss: A protein that is secreted via the hrp pathway and elicits the hypersensitive response in plants. Cell, 73(7), 1255–1266. https://doi.org/10.1016/0092-8674(93)90354-S Heeb, S., & Haas, D. (2001). Regulatory roles of the GacS / GacA two-component system in plant-associated and other gram-negative bacteria. Molecular Plant-Microbe Interactions, 14(12), 1351–1363. https://doi.org/10.1094/MPMI.2001.14.12.1351

Hill, D. S., Stein, J. I., Torkewitz, N. R., Morse, A. M., Howell, C. R., Pachlatko, J. P., … Ligon, J. M. (1994). Cloning of genes involved in the synthesis of pyrrolnitrin from Pseudomonas fluorescens and role of pyrrolnitrin synthesis in biological control of plant disease. Applied and Environmental Microbiology, 60(1), 78–85. https://doi.org/10.1128/aem.60.1.78-85.1994 Höfte M., De Vos P. (2007) Plant pathogenic Pseudomonas species. In: Gnanamanickam S.S. (Ed.) Plant-associated bacteria (pp 507-533). Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-4538-7_14 Howell, C. R., & Stipanovic, R. D. (1979). Control of Rhizoctonia solani on cotton seedlings with Pseudomonas fluorescens and with an antibiotic produced by the bacterium by the soil tube method described previously. Phytopathology, 69(5), 480–482. Hueck, C. J. (1998). Type III protein secretion systems in bacterial pathogens of animals and plants. Microbiology and Molecular Biology Reviews, 62(2), 379–433. https://doi.org/10.1128/mmbr.62.2.379-433.1998 Hunziker, L., Bönisch, D., Groenhagen, U., Bailly, A., Schulz, S., & Weisskopf, L. (2015). Pseudomonas strains naturally associated with potato plants produce volatiles with high potential for inhibition of Phytophthora infestans. Applied and Environmental Microbiology, 81(3), 821–830. https://doi.org/10.1128/AEM.02999-14 Inagaki, H., & Tsutsumi, M. (1971). Survival of the soybean cyst nematode, Heterodera glycines Ichinohe (Tylenchida: Heteroderidae) under certain storing conditions. Applied Entomology and Zoology, 6(4), 156–162. Jackson, R. W., Preston, G. M., & Rainey, P. B. (2005). Genetic characterization of Pseudomonas fluorescens SBW25 rsp gene expression in the phytosphere and in vitro. Journal of Bacteriology, 187(24), 8477–8488. https://doi.org/10.1128/JB.187.24.8477- 8488.2005 Kamilova, F., Validov, S., Azarova, T., Mulders, I., & Lugtenberg, B. (2005). Enrichment for enhanced competitive plant root tip colonizers selects for a new class of biocontrol bacteria. Environmental Microbiology, 7(11), 1809–1817. https://doi.org/10.1111/j.1462- 2920.2005.00889.x Kang, B. R., Anderson, A. J., & Kim, Y. C. (2018). Hydrogen cyanide produced by Pseudomonas chlororaphis O6 exhibits nematicidal activity against Meloidogyne hapla. Plant Pathology Journal, 34(1), 35–43. https://doi.org/10.5423/PPJ.OA.06.2017.0115 Keel, C., Schnider, U., Maurhofer, M., Voisard, C., Laville, J., Burger, U., … Defago, G. (1992). Suppression of root diseases by Pseudomonas fluorescens CHA0: Importance of the bacterial secondary metabolite 2,4-diacetylphloroglucinol. Molecular Plant-Microbe Interactions, 5(1), 4–13. https://doi.org/10.1094/MPMI-5-004 Keinath, A. P., & Hassell, R. L. (2014). Suppression of Fusarium wilt caused by Fusarium oxysporum f. sp. niveum race 2 on grafted triploid watermelon. Plant Disease, 98(10), 1326– 1332. https://doi.org/10.1094/PDIS-01-14-0005-RE Kim, D. G., & Riggs, R. D. (1991). Characteristics and efficacy of a sterile hyphomycete (ARF18), a new biocontrol agent for Heterodera glycines and other nematodes. Journal of Nematology, 23(3), 275–282. Kloepper, J. W., Leong, J., Teintze, M., & Schroth, M. N. (1980a). Enhanced plant growth by siderophores produced by plant growth-promoting rhizobacteria. Nature, 286, 885–886. Kloepper, J. W., Leong, J., Teintze, M., & Schroth, M. N. (1980b). Pseudomonas siderophores: A mechanism explaining disease-suppressive soils. Current Microbiology, 4(5), 317–320. https://doi.org/10.1007/BF02602840

Kloepper, J. W., Rodríguez-Kábana, R., McInroy, J. A., & Young, R. W. (1992). Rhizosphere bacteria antagonistic to soybean cyst (Heterodera glycines) and root-knot (Meloidogyne incognita) nematodes: Identification by fatty acid analysis and frequency of biological control activity. Plant and Soil, 139, 75–84. https://doi.org/10.1007/BF00012844 Kong, H. G., Shin, T. S., Kim, T. H., & Ryu, C. M. (2018). Stereoisomers of the bacterial volatile compound 2,3-butanediol differently elicit systemic defense responses of pepper against multiple viruses in the field. Frontiers in Plant Science, 9(90). https://doi.org/10.3389/fpls.2018.00090 Kvitko, B. H., Ramos, A. R., Morello, J. E., Oh, H. S., & Collmer, A. (2007). Identification of harpins in Pseudomonas syringae pv. tomato DC3000, which are functionally similar to HrpK1 in promoting translocation of type III secretion system effectors. Journal of Bacteriology, 189(22), 8059–8072. https://doi.org/10.1128/JB.01146-07 Lafontaine, P. J., & Benhamou, N. (1996). Chitosan treatment: An emerging strategy for enhancing resistance of greenhouse tomato plants to infection by Fusarium oxysporum f.sp. radicis-lycopersici. Biocontrol Science and Technology, 6(1), 111–124. https://doi.org/10.1080/09583159650039575 Lanteigne, C., Gadkar, V. J., Wallon, T., Novinscak, A., & Filion, M. (2012). Production of DAPG and HCN by Pseudomonas sp. LBUM300 contributes to the biological control of bacterial canker of tomato. Phytopathology, 102(10), 967–973. https://doi.org/10.1094/PHYTO-11-11-0312 Larkin, R. P., & Fravel, D. R. (1998). Efficacy of various fungal and bacterial biocontrol organisms for control of Fusarium wilt of tomato. Plant Disease, 82(9), 1022–1028. https://doi.org/10.1094/PDIS.1998.82.9.1022 Laville, J., Voisard, C., Keel, C., Maurhofer, M., Défago, G., & Haas, D. (1992). Global control in Pseudomonas fluorescens mediating antibiotic synthesis and suppression of black root rot of tobacco. Proceedings of the National Academy of Sciences of the United States of America, 89(5), 1562–1566. https://doi.org/10.1073/pnas.89.5.1562 Laville, J., Blumer, C., Von Schroetter, C., Gaia, V., Défago, G., Keel, C., & Haas, D. (1998). Characterization of the hcnABC gene cluster encoding hydrogen cyanide synthase and anaerobic regulation by ANR in the strictly aerobic biocontrol agent Pseudomonas fluorescens CHA0. Journal of Bacteriology, 180(12), 3187–3196. Leocata, S., Pirruccio, G., Myrta, A., Medico, E., & Greco, N. (2014). Dimethyl disulfide (DMDS): A new soil fumigant to control root-knot nematodes, Meloidogyne spp., in protected crops in Sicily, Italy. Acta Horticulturae, 1044, 415–420. https://doi.org/10.17660/ActaHortic.2014.1044.57 Lesic, B., Starkey, M., He, J., Hazan, R., & Rahme, L. G. (2009). Quorum sensing differentially regulates Pseudomonas aeruginosa type VI secretion locus I and homologous loci II and III, which are required for pathogenesis. Microbiology, 155(9), 2845–2855. https://doi.org/10.1099/mic.0.029082-0 Loper, J. E., Hassan, K. A., Mavrodi, D. V., Davis, E. W., Lim, C. K., Shaffer, B. T., … Paulsen, I. T. (2012). Comparative genomics of plant-associated Pseudomonas spp.: Insights into diversity and inheritance of traits involved in multitrophic interactions. PLoS Genetics, 8(7). https://doi.org/10.1371/journal.pgen.1002784 Mansfield, J., Genin, S., Magori, S., Citovsky, V., Sriariyanum, M., Ronald, P., … Foster, G. D. (2012). Top 10 plant pathogenic bacteria in molecular plant pathology. Molecular Plant Pathology, 13(6), 614–629. https://doi.org/10.1111/j.1364-3703.2012.00804.x

Mao, W., Lewis, J. A., Lumsden, R. D., & Hebbar, K. P. (1998). Biocontrol of selected soilborne diseases of tomato and pepper plants. Crop Protection, 17(6), 535–542. https://doi.org/10.1016/S0261-2194(98)00055-6 Marrone Bio Innovations (2013). Marrone Bio Innovations submits biological nematicide for EPA registration. [Press Release]. https://www.prnewswire.com/news-releases/marrone-bioinnovations-submits-biological-nematicide-for-epa-registration-236575921.html Martin, D. (2017). Investigation of the biocontrol activity in vitro and in planta of different Pseudomonas species against important crown, stem, foliar and root pathogens of ornamental crops. The Ohio State University. [Thesis]. https://etd.ohiolink.edu/!etd.send_file?accession=osu1503063395390704&disposition=inline Martin, D., & Dorrance, A. E. (2019). Phytophthora damping off and root rot of soybean. Ohio State University-College of Food, Agricultural, and Environmental Sciences. https://ohioline.osu.edu/factsheet/plpath-soy-04 Masamune, T., Anetai, M., Takasugi, M., & Katsui, N. (1982). Isolation of a natural hatching stimulus, glycinoeclepin A, for the soybean cyst nematode. Nature, 297, 495–496. https://doi.org/10.1038/297495a0 Mavrodi, O. V., Walter, N., Elateek, S., Taylor, C. G., & Okubara, P. A. (2012). Suppression of Rhizoctonia and Pythium root rot of wheat by new strains of Pseudomonas. Biological Control, 62(2), 93–102. https://doi.org/10.1016/j.biocontrol.2012.03.013 McGovern, R. J. (2015). Management of tomato diseases caused by Fusarium oxysporum. Crop Protection, 73, 78–92. https://doi.org/10.1016/j.cropro.2015.02.021 McGovern, R. J., Vavrina, C. S., Noling, J. W., Datnoff, L. A., & Yonce, H. D. (1998). Evaluation of application methods of metam sodium for management of Fusarium crown and root rot in tomato in southwest Florida. Plant Disease, 82(8), 919–923. https://doi.org/10.1094/PDIS.1998.82.8.919 McGrath, M. n.d. Vegetable MD online. Cornell University Department of Plant Pathology. http://vegetablemdonline.ppath.cornell.edu/Tables/TableList.htm McSpadden Gardener, B. B., Gutierrez, L. J., Joshi, R., Edema, R., & Lutton, E. (2005). Distribution and biocontrol potential of phlD+ pseudomonads in corn and soybean fields. Phytopathology, 95(6), 715–724. https://doi.org/10.1094/PHYTO-95-0715 Medina, R. M. (2017). Investigation of maize root exudates on Heterodera glycines populations under direct and indirect exposure. The Ohio State University [Thesis]. https://etd.ohiolink.edu/pg_10?0::NO:10:P10_ACCESSION_NUM:osu1482499805741097 Mejias, J., Truong, N. M., Abad, P., Favery, B., & Quentin, M. (2019). Plant proteins and processes targeted by parasitic nematode effectors. Frontiers in Plant Science, 10(970). https://doi.org/10.3389/fpls.2019.00970 Momma, N., Momma, M., & Kobara, Y. (2010). Biological soil disinfestation using ethanol: Effect on Fusarium oxysporum f. sp. lycopersici and soil microorganisms. Journal of General Plant Pathology, 76(5), 336–344. https://doi.org/10.1007/s10327-010-0252-3 Mougous, J. D., Cuff, M. E., Raunser, S., Shen, A., Zhou, M., Gifford, C. A., … Mekalanos, J. J. (2006). A virulence locus of Pseudomonas aeruginosa encodes a protein secretion apparatus. Science, 312(5779), 1526–1530. DOI: 10.1126/science.1128393 Mossialos, D., Meyer, J. M., Budzikiewicz, H., Wolff, U., Koedam, N., Baysse, C., … Cornelis, P. (2000). Quinolobactin, a new siderophore of Pseudomonas fluorescens ATCC 17400, the production of which is repressed by the cognate pyoverdine. Applied and Environmental Microbiology, 66(2), 487–492. https://doi.org/10.1128/AEM.66.2.487-492.2000

Mulet, M., Gomila, M., Scotta, C., Sánchez, D., Lalucat, J., & García-Valdés, E. (2012). Concordance between whole-cell matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry and multilocus sequence analysis approaches in species discrimination within the genus Pseudomonas. Systematic and Applied Microbiology, 35(7), 455–464. https://doi.org/10.1016/j.syapm.2012.08.007 Musil, K. M., Arneson, N. J., & Giesler, L. J. (2015). Evaluation of biological soybean seed treatments on yield and soybean cyst nematode populations, 2014. Plant Disease Management Reports, 9, N016. Niblack, T. L. (2005). Soybean cyst nematode management reconsidered. Plant Disease, 89(10), 1020–1026. DOI: 10.1094/PD-89-1020 Niblack, T. L., & Tylka, G. L. (Eds.). (n.d.). Soybean cyst nematode management guide, Fifth edition. Plant Health Initiative, North Central Soybean Research Program. https://www.ncsrp.com/pdf_doc/SCN_Management.pdf Okada, T. (1971). The hatching responses of the soybean cyst nematode, Heterodera glycines Ichinohe (Tylenchida: Heteroderidae). Applied Entomology and Zoology, 6(2), 91–93. https://doi.org/10.1303/aez.6.91 Ossowicki, A., Jafra, S., & Garbeva, P. (2017). The antimicrobial volatile power of the rhizospheric isolate Pseudomonas donghuensis P482. PLoS ONE, 12(3), e0174362. https://doi.org/10.1371/journal.pone.0174362 Osteen, C. (2003). Methyl bromide phaseout proceeds: Users request exemptions. Amber Waves. https://www.ers.usda.gov/amber-waves/2003/april/methyl-bromide-phaseout-proceeds/ Parte, A. C. (2018). LPSN - List of prokaryotic names with standing in nomenclature (Bacterio.net), 20 years on. International Journal of Systematic and Evolutionary Microbiology, 68(6), 1825–1829. https://doi.org/10.1099/ijsem.0.002786 Pfender, W. F., Kraus, J., & Loper, J. E. (1993). A genomic region from Pseudomonas fluorescens Pf-5 Required for pyrrolnitrin production and inhibition of Pyrenophora tritici- repentis in wheat straw. Phytopathology, 83(11), 1223–1228. Poromarto, S. H., & Nelson, B. D. (2009). Reproduction of soybean cyst nematode on dry bean cultivars adapted to North Dakota and northern Minnesota. Plant Disease, 93(5), 507–511. https://doi.org/10.1094/PDIS-93-5-0507 Porter, P. M., Chen, S. Y., Reese, C. D., & Klossner, L. D. (2001). Population response of soybean cyst nematode to long term corn-soybean cropping sequences in Minnesota. Agronomy Journal, 93(3), 619–626. https://doi.org/10.2134/agronj2001.933619x Preston, G. M., Bertrand, N., & Rainey, P. B. (2001). Type III secretion in plant growth- promoting Pseudomonas fluorescens SBW25. Molecular Microbiology, 41(5), 999–1014. https://doi.org/10.1046/j.1365-2958.2001.02560.x Rao Arelli, A. P., Wilcox, J. A., Myers Jr, O., & Gibson, P. T. (1997). Soybean germplasm resistant to races 1 and 2 of Heterodera glycines. Crop Science, 37(4), 1367-1369. https://doi.org/10.2135/cropsci1997.0011183X003700040055x Raudales, R. E., Stone, E., & McSpadden Gardener, B. B. (2009). Seed treatment with 2,4- diacetylphloroglucinol-producing pseudomonads improves crop health in low-pH soils by altering patterns of nutrient uptake. Phytopathology, 99(5), 506–511. https://doi.org/10.1094/PHYTO-99-5-0506 Reidel, R. M., & Golden, A. M. (1988). First report of Heterodera glycines on soybean in Ohio. Plant Disease, 72(4), 363.

Rezzonico, F., Binder, C., Défago, G., & Moënne-Loccoz, Y. (2005). The type III secretion system of biocontrol Pseudomonas fluorescens KD targets the phytopathogenic chromista Pythium ultimum and promotes cucumber protection. Molecular Plant-Microbe Interactions, 18(9), 991–1001. https://doi.org/10.1094/MPMI-18-0991 Rezzonico, F., Défago, G., & Moënne-Loccoz, Y. (2004). Comparison of ATPase-encoding type III secretion system hrcN genes in biocontrol fluorescent pseudomonads and in phytopathogenic proteobacteria. Applied and Environmental Microbiology, 70(9), 5119– 5131. https://doi.org/10.1128/AEM.70.9.5119-5131.2004 Rezzonico, F., Zala, M., Keel, C., Duffy, B., Moënne-Loccoz, Y., & Défago, G. (2007). Is the ability of biocontrol fluorescent pseudomonads to produce the antifungal metabolite 2,4- diacetylphloroglucinol really synonymous with higher plant protection? New Phytologist, 173, 861–872. https://doi.org/10.1111/j.1469-8137.2006.01955.x Riga, E., Welacky, T., Potter, J., Anderson, T., Topp, E., & Tenuta, A. (2001). The impact of plant residues on the soybean cyst nematode, Heterodera glycines. Canadian Journal of Plant Pathology, 23, 168–173. https://doi.org/10.1080/07060660109506926 Rivard, C. L., & Louws, F. J. (2008). Grafting to manage soilborne diseases in heirloom tomato production. HortScience, 43(7), 2104–2111. https://doi.org/10.21273/hortsci.43.7.2104 Rivard, C. L., Sydorovych, O., O’Connell, S., Peet, M. M., & Louws, F. J. (2010). An economic analysis of two grafted tomato transplant production systems in the United States. HortTechnology, 20(4), 794–803. https://doi.org/10.21273/horttech.20.4.794 Rodriguez, F., & Pfender, W. F. (1997). Antibiosis and antagonism of Sclerotinia homoeocarpa and Drechslera poae by Pseudomonas fluorescens Pf-5 in vitro and in planta. Phytopathology, 87(6), 614–621. https://doi.org/10.1094/PHYTO.1997.87.6.614 Rose, S., Parker, M., & Punja, Z. K. (2003). Efficacy of biological and chemical treatments for control of Fusarium root and stem rot on greenhouse cucumber. Plant Disease, 87(12), 1462– 1470. https://doi.org/10.1094/PDIS.2003.87.12.1462 Ross, J. P., & Brim, C. A. (1957). Resistance of soybeans to the soybean cyst nematode as determined by a double-row method. Plant Disease Reporter, 41(11), 923–924. Sasser, J. N., & Uzzell Jr, G. (1991). Control of the soybean cyst nematode by crop rotation in combination with a nematicide. Journal of Nematology, 23(3), 344–347. http://www.ncbi.nlm.nih.gov/pubmed/19283137%0Ahttp://www.pubmedcentral.nih.gov/arti clerender.fcgi?artid=PMC2619170 Scher, F. M., & Baker, R. (1982). Effect of Pseudomonas putida and a synthetic iron chelator on induction of soil suppressiveness to Fusarium wilt pathogens. Phytopathology, 72, 1567– 1573. https://doi.org/10.1094/phyto-77-1567 Schmitt, D. P., & Riggs, R. D. (1991). Influence of selected plant species on hatching of eggs and development of juveniles of Heterodera glycines. Journal of Nematology, 23(1), 1–6. Scncoalition.com. n.d, SCN reproduction on PI 88788. https://www.thescncoalition.com/application/files/7815/8154/4360/2200-002- 20_SCN_Reproduction_Map_Feb12.pdf Siddiqui, I. A., & Shaukat, S. S. (2002). Mixtures of plant disease suppressive bacteria enhance biological control of multiple tomato pathogens. Biology and Fertility of Soils, 36(4), 260– 268. https://doi.org/10.1007/s00374-002-0509-x Siddiqui, I. A., Shaukat, S. S., Sheikh, I. H., & Khan, A. (2006). Role of cyanide production by Pseudomonas fluorescens CHA0 in the suppression of root-knot nematode, Meloidogyne

javanica in tomato. World Journal of Microbiology and Biotechnology, 22(6), 641–650. https://doi.org/10.1007/s11274-005-9084-2 Sipes, B. S., Schmitt, D. P., & Barker, K. R. (1992). Fertility of three parasitic biotypes of Heterodera glycines. Phytopathology, 82(10), 999–1001. https://doi.org/10.1094/phyto-82- 999 Smant, G., Stokkermans, J. P. W. G., Yan, Y., De Boer, J. M., Baum, T. J., Wang, X., … Bakker, J. (1998). Endogenous cellulases in animals: Isolation of β-1,4-endoglucanase genes from two species of plant-parasitic cyst nematodes. Proceedings of the National Academy of Sciences of the United States of America, 95(9), 4906–4911. https://doi.org/10.1073/pnas.95.9.4906 Smith, J. J., Travis, S. M., Greenberg, E. P., & Welsh, M. J. (1996). Cystic fibrosis airway epithelia fail to kill bacteria because of abnormal airway surface fluid. Cell, 85(2), 229–236. https://doi.org/10.1016/S0092-8674(00)81099-5 South, K. A., Peduto Hand, F., & Jones, M. L. (2020). Beneficial bacteria identified for the control of Botrytis cinerea in petunia greenhouse production. Plant Disease, 104(6), 1801- 1810. https://doi.org/10.1094/pdis-10-19-2276-re Soybean cyst nematode in Ohio (n.d.) https://u.osu.edu/ohscn/ Stowe, K. D., & Dunphy, J. (2017). The soybean plant. In North Carolina Soybean production guide (AG-385). North Carolina State Extension. https://content.ces.ncsu.edu/north-carolina- soybean-production-guide/the-soybean-plant Syngenta. (2013). ClarivaTM Complete Beans-technical overview. http://www.syngentaebiz.com/productsystem/ImageHandler.ashx?ImID=76f635de-c7b3- 4aba-b579-2e54079231f7&fTy=0&t=0 Subedi, N., Taylor, C. G., Paul, P. A., & Miller, S. A. (2019). Combining partial host resistance with bacterial biocontrol agents improves outcomes for tomatoes infected with Ralstonia pseudosolanacearum. Crop Protection, 104776. https://doi.org/10.1016/j.cropro.2019.03.024 Tampakaki, A. P., Skandalis, N., Gazi, A. D., Bastaki, M. N., Panagiotis F., S., Charova, S. N., … Panopoulos, N. J. (2010). Playing the “harp”: Evolution of our understanding of hrp/hrc Genes. Annual Review of Phytopathology, 48(1), 347–370. https://doi.org/10.1146/annurev- phyto-073009-114407 Tefft, P. M., Rende, J. F., & Bone, L. W. (1982). Factors influencing egg hatching of the soybean cyst nematode Heterodera glycines race 3. Proceedings of the Helminthological Society of Washington, 49(2), 258–265. Testen, A., & Miller, S. (2017a). Getting to the root of the matter: Soilborne diseases of tomato. Ohio Veggie Disease News, The Ohio State University-College of Food, Agriculture, and Environmental Sciences. https://u.osu.edu/miller.769/2017/09/09/getting-to-the-root-of-the- matter-soilborne-diseases-of-tomato/ Testen, A. L., & Miller, S. A. (2017b). Anaerobic soil disinfestation for management of soilborne diseases in midwestern vegetable production. Ohio State University Extension. https://cpb-us-w2.wpmucdn.com/u.osu.edu/dist/8/3691/files/2017/10/ASD-Factsheet-OSU- 2017-2melc4d.pdf Testen, A., & Miller, S. (2018). Soilborne diseases in tomato high tunnels: An emerging threat. Poster presented at Ohio State University. CFAES Annual Research Conference. https://kb.osu.edu/bitstream/handle/1811/86197/CFAES_ARC_2018_Testen.pdf?sequence=1 &isAllowed=y

Thapa, S., Gates, M. K., Reuter-Carlson, U., Androwski, R. J., & Schroeder, N. E. (2019). Convergent evolution of saccate body shapes in nematodes through distinct developmental mechanisms. EvoDevo, 10(5). https://doi.org/10.1186/s13227-019-0118-5 Thomashow, L. S., & Weller, D. M. (1988). Role of a phenazine antibiotic from Pseudomonas fluorescens in biological control of Gaeumannomyces graminis var. tritici. Journal of Bacteriology, 170(8), 3499–3508. https://doi.org/10.1128/jb.170.8.3499-3508.1988 Tian, H., Riggs, R. D., & Crippen, D. L. (2000). Control of soybean cyst nematode by chitinolytic bacteria with chitin substrate. Journal of Nematology, 32(4), 370–376. Timper, P., Riggs, R. D., & Crippen, D. L. (1999). Parasitism of sedentary stages of Heterodera glycines by isolates of a sterile nematophagous fungus. Phytopathology, 89(12), 1193–1199. https://doi.org/10.1094/PHYTO.1999.89.12.1193 Tomasko, S. (2018). All aldicarb use now banned in Wisconsin. University of Wisconsin Pesticide Applicator Training Program-Division of Extension. https://fyi.extension.wisc.edu/pat/2018/11/10/014_nov_art06/ Tylka, G. L. (2019). Effects of seed treatments on population densities of soybean cyst nematode and soybean yields in Iowa. In Proceedings of the 2019 Wisconsin Agribusiness Classic (pp. 35–36). https://www.agclassic.org/proceedings/2019proceedings.pdf Tylka, G. L., Gebhart, G. D., Marett, C. C., and Mullaney, M. P. (2019) Evaluation of soybean varieties resistant to soybean cyst nematode in Iowa—2019 (IPM 52). Extension and Outreach Publications. https://lib.dr.iastate.edu/extension_pubs/99/ Tylka, G., & Marrett, C. (2008). Field testing of N-HibitTM seed treatment in Iowa. ICM News, Iowa State University Extension and Outreach. https://crops.extension.iastate.edu/cropnews/2008/05/field-testing-n-hibit%E2%84%A2- seed-treatment-iowa Tylka, G. L., & Marett, C. C. (2017). Known distribution of the soybean cyst nematode, Heterodera glycines, in the United States and Canada, 1954 to 2017. Plant Health Progress, 18(3), 167–168. https://doi.org/10.1094/PHP-05-17-0031-BR Tylka, G. L., & Mullaney, M. P. (2019). Soybean cyst nematode-resistant soybean varieties for Iowa (PM 1649). Extension and Outreach Publications. https://store.extension.iastate.edu/product/5154 United States Department of Agriculture-Economic Research Service. (n.d). Farm income and wealth statistics. https://data.ers.usda.gov/reports.aspx?ID=17844 United States Department of Agriculture-National Agricultural Statistics Service. (n.d. a). 2019 state agriculture overview-Ohio. https://www.nass.usda.gov/Quick_Stats/Ag_Overview/stateOverview.php?state=OHIO United States Department of Agriculture-National Agricultural Statistic Service (n.d. b). Soybeans 2019 planted acres by county for selected states. https://www.nass.usda.gov/Charts_and_Maps/graphics/SB-PL-RGBChor.pdf United States Department of Agriculture-Natural Resources Conservation Service. (n.d.). Mucuna pruriens (L.) DC. velvet bean. https://plants.usda.gov/core/profile?symbol=MUPR United States Environmental Protection Agency. (n.d.). What are biopesticides? https://www.epa.gov/ingredients-used-pesticide-products/what-are-biopesticides United States Environmental Protection Agency. (2000). 1,2-Dibromo-3-chloropropane (DBCP) (96-12-8). https://www.epa.gov/sites/production/files/2016-09/documents/1-2-dibromo-3- chloropropane.pdf

United State Environmental Protection Agency. (2010). Bayer agrees to terminate all uses of aldicarb. [Press Release]. https://archive.epa.gov/epapages/newsroom_archive/newsreleases/29f9dddede97caa8852577 8200590c93.html United States Environmental Protection Agency (2018). Biopesticide active ingredients. https://www.epa.gov/ingredients-used-pesticide-products/biopesticide-active-ingredients United States Environmental Protection Agency. (2012). Methyl bromide alternatives. https://www.epa.gov/sites/production/files/2015- 07/documents/alternatives_for_specific_commodities_0.pdf United States Environmental Protection Agency-Office of Pesticide Programs. (n.d.) Harpin αβ protein (006506). (Fact Sheet). https://www3.epa.gov/pesticides/chem_search/reg_actions/registration/fs_PC-006506_30- Jan-02.pdf Valent Biosciences. (n.d.) Aveo EZ®. https://www.valentbiosciences.com/soilhealth/products/aveo-ez/ Venkatesh, R., Harrison, S. K., & Riedel, R. M. (2000). Weed hosts of soybean cyst nematode (Heterodera glycines) in Ohio. Weed Technology, 14(1), 156–160. https://doi.org/10.1614/0890-037X(2000)014[0156:WHOSCN]2.0.CO;2 Voisard, C., Keel, C., Haas, D., & Dèfago, G. (1989). Cyanide production by Pseudomonas fluorescens helps suppress black root rot of tobacco under gnotobiotic conditions. The EMBO Journal, 8(2), 351–358. https://doi.org/10.1002/j.1460-2075.1989.tb03384.x Wang, X., Meyers, D., Yan, Y., Baum, T., Smant, G., Hussey, R., & Davis, E. (1999). In planta localization of a β-1,4-endoglucanase secreted by Heterodera glycines. Molecular Plant- Microbe Interactions, 12(1), 64–67. https://doi.org/10.1094/MPMI.1999.12.1.64 Wei, Z., Laby, R. J., Zumoff, C. H., Bauer, D. W., He, S. Y., Colimer, A., & Beer, S. V. (1992). Harpin, elicitor of the hypersensitive response produced by the plant pathogen Erwinia amylovora. Science, 257(5066), 85–88. DOI: 10.1126/science.1621099 Weiner, L. M., Webb, A. K., Limbago, B., Dudeck, M. A., Patel, J., Kallen, A. J., … Sievert, D. M. (2016). Antimicrobial-resistant pathogens associated with healthcare-associated infections: Summary of data reported to the National Healthcare Safety Network at the Centers for Disease Control and Prevention, 2011-2014. Infection Control and Hospital Epidemiology, 37(11), 1288–1301. https://doi.org/10.1017/ice.2016.174 Weaver, D. B., Rodríguez-Kábana, R., & Carden, E. L. (1993). Velvetbean in rotation with soybean for management of Heterodera glycines and Meloidogyne arenaria. Journal of Nematology, 25(4 Supp.), 809–813. Weaver, D. B., Rodríguez-Kábana, R., & Carden, E. L. (1998). Velvetbean and bahiagrass as rotation crops for management of Meloidogyne spp. and Heterodera glycines in soybean. Journal of Nematology, 30(4 SUPPL), 563–568. Weller, D. M., Raaijmakers, J. M., Gardener, B. B. M., & Thomashow, L. S. (2002). Microbial populations responsible for specific soil suppressiveness to plant pathogens. Annual Review of Phytopathology, 40, 309–348. https://doi.org/10.1146/annurev.phyto.40.030402.110010 Wood, D. W., & Pierson, L. S. (1996). The phzI gene of Pseudomonas aureofaciens 30-84 is responsible for the production of a diffusible signal required for phenazine antibiotic production. Gene, 168, 49–53. https://doi.org/10.1016/0378-1119(95)00754-7 Wrather, J. A., & Koenning, S. R. (2006). Estimates of disease effects on soybean yields in the United States 2003 to 2005. Journal of Nematology, 38(2), 173–180.

Xiang, N., Lawrence, K. S., Kloepper, J. W., Donald, P. A., & McInroy, J. A. (2017). Biological control of Heterodera glycines by spore-forming plant growth-promoting rhizobacteria (PGPR) on soybean. PLoS ONE, 12(7). https://doi.org/10.1371/journal.pone.0181201 Xu, G.-W., & Gross, D. C. (1986). Selection of fluorescent pseudomonads antagonistic to Erwinia carotovora and suppressive of potato seed piece decay. Phytopathology, 76, 414– 422. https://doi.org/10.1094/phyto-76-414 Yabwalo, D., Tande, C., & Byamukama, E. (2019). 2018 field plot summaries for soybeans: Plant disease and fungicide trials. South Dakota State University Extension. https://extension.sdstate.edu/sites/default/files/2019-02/P-00081.pdf Young, L. D. (1996). Yield loss in soybean caused by Heterodera glycines. Journal of Nematology, 28(4 SUPPL.), 604–607. Yu, N., Lee, T. G., Rosa, D. P., Hudson, M., & Diers, B. W. (2016). Impact of Rhg1 copy number, type, and interaction with Rhg4 on resistance to Heterodera glycines in soybean. Theoretical and Applied Genetics, 129(12), 2403–2412. https://doi.org/10.1007/s00122-016- 2779-y Yvon, M., & Rijnen, L. (2001). Cheese flavour formation by amino acid catabolism. International Dairy Journal, 11(4–7), 185–201. https://doi.org/10.1016/S0958- 6946(01)00049-8 Zhou, J. Y., Zhao, X. Y., & Dai, C. C. (2014). Antagonistic mechanisms of endophytic Pseudomonas fluorescens against Athelia rolfsii. Journal of Applied Microbiology, 117(4), 1144–1158. https://doi.org/10.1111/jam.12586

Table 1.1. Representative list of commercially available Pseudomonas-based bioproducts in the United States. The target pathogens and crops may not be a comprehensive, but rather representative list of the bioproduct targets. For the most up to date information on each product, visit the manufacturers’ websites.

Chapter 2

Determination of the Volatile Compounds Produced by Pseudomonas spp. Strains and

Establishing Their Role in Biocontrol

2.1 Abstract

Biocontrol is has become an increasingly relied upon strategy in the control of certain phytopathogens. Bacteria as biocontrol agents can utilize multiple modes of action against competing microorganisms, including direct antagonism, secretion of antibiotics, and/or production of volatile organic compounds (VOCs). The study presented here investigated these three modes of action using Pseudomonas (19 strains representing eight different species) and

Pantoea agglomerans (one strain) against the fungal pathogen Fusarium oxysporum. We further characterized VOC action against the bacterial feeding nematode, Caenorhabditis elegans. We were particularly interested in the antagonistic volatiles and determined the global profile of each bacterium utilizing proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS).

PTR-ToF-MS is a system that has been extensively used in the quantification and identification of volatiles in systems ranging from bacteria to fungi to fruit, however to the best of our knowledge this is the first study using this analytical system with Pseudomonas. We quantified

39 VOCs produced by Pseudomonas, Pantoea, and the controls, ranging in size from m/z (mass- to-charge ratio) 27.023 to 153.120 that were produced at levels >1ppbv. Six compounds were significantly correlated with inhibition of F. oxysporum, five of which were putatively identified as cyanides and organosulfurs. We found that production of hydrogen cyanide was required for bacterial VOCs to inhibit F. oxysporum, and in multiple strains cyanide was the dominantly measured compound; in contrast pseudomonads that did not produce any measurable cyanide were also able to inhibit the reproduction of C. elegans over a weeklong experiment. Of the nine bacteria species investigated, volatiles produced by P. fluorescens and P. protegens were the most effective in reducing growth or reproduction of F. oxysporum and C. elegans. Our findings demonstrated that the volatile profiles of bacteria are complex and can contribute to

50 microorganism inhibition. This work has laid the groundwork for future, more in-depth studies of bacterial volatile profiles and their role in microorganismal inhibition.

2.2 Introduction

Synthetic pesticides can be linked to negative human health and environmental downstream effects in addition to reduced crop yield and increased pest resistance, accounting for billions of dollars of lost economic value (Pimentel & Burgess, 2014). Biologicals are increasingly used to suppress plant diseases and pests (i.e. biocontrol) in agriculture as a substitute for or supplement to synthetic pesticides. Over the past few decades both the European

Commission and the United States Environmental Protection Agency (USEPA) have promoted biocontrol as a key part of integrated pest management programs. This is due in part to bioproducts’ reduced toxicity and increased target specificity as compared to some chemical pesticides. Additionally, use of biocontrol agents can provide help in preventing the buildup of target pest/pathogen resistance to commercially used pesticides (Chandler et al, 2011; Leahy et al, 2014). As the demand for organic food increases, the use of biocontrol products is also expected to rise to replace the use of synthetic chemical pesticides. To be labelled as organic by the US Department of Agriculture (USDA), synthetic chemicals may not be used on plants while non-synthetic substances (including biological products) may be applied, save for certain exceptions (National Organic Program, 2020). According to the market research company

DunhamTrimmer LLC, the value of the worldwide biocontrol industry will be as high as 11 billion USD by 2025, increasing over 100-fold from 1993 (Dunham, 2017). Many organisms, macro- and micro-, are used in biocontrol. Bacteria are commonly used biocontrol agents.

Bacillus spp. were the first microbial biopesticide active ingredients, registered with the USEPA

51 in 1971. Since then, dozens more strains representing multiple genera have been added to the list

(USEPA, 2018). One such widely studied bacterial genus for biocontrol potential is

Pseudomonas. There are currently three Pseudomonas strains that have been registered with the

USEPA and formulated into biopesticides to control bacterial and fungal diseases. Additional pseudomonads have been developed into biostimulants, which are beneficial to plants, but do not have marketed pesticide activity (Table 1.1).

Multiple species of Pseudomonas have demonstrated biocontrol activity. The bacteria show antagonistic activity towards a wide spectrum of pathogens under a variety of conditions

(Haas & Defago, 2005). Bioactivity from Pseudomonas is due to several modes of action including inducing systemic plant resistance (ISR), competitive niche exclusion and antibiotic production. Pseudomonads are capable of secreting multiple antibiotic compounds effective against competing microorganisms including 2,4-diacetyl phloroglucinol (DAPG), phenazine-1- carboxolyic acid (PCA), pyoluteorin, and pyrrolnitrin (Bolwerk et al, 2003, Haas & Defago,

2005, Van Loon & Bakker, 2008). These bacteria can also produce low molecular weight volatile organic compounds (VOCs), some of which have biocontrol potential. Unlike other compounds, VOCs are of particular interest because the source organism does not need to be in direct contact with the target plant or pathogen to have the desired effect.

Pseudomonads are capable of releasing VOCs representing multiple classes of compounds including alcohols, cyanides, hydrocarbons, and organosulfur compounds (Effmert et al, 2012). Some strains antagonize competing organisms using VOCs, as demonstrated with shared-air in vitro assays. VOCs including hydrogen cyanide (HCN), dimethyl disulfide

(DMDS), dimethyl sulfide (DMS) and undecene, can have antagonistic activity to varying extents against microorganisms including nematodes, fungi, and oomycetes (Briard et al, 2016;

De Vrieze et al, 2015; Gallagher & Manoil 2001; Hunziker et al, 2015; Lo Cantore et al, 2015,

Ossowicki et al, 2017). Bacterial volatiles also play a role in promoting induced systemic resistance (ISR) in plants. Both pure 2R,3R-butanediol and Pseudomonas chlororaphis O6, which is capable of producing 2, 3-butanediol, induced systemic resistance in inoculated tobacco plants challenged with Pectobacterium carotovorum (Han et al, 2006).

It is imperative to choose the correct technique of volatile analysis. For example, Bean et al (2012) and Zhu et al (2010) analyzed the VOCs of the same Pseudomonas strain utilizing different methodology and quantified different volatiles for the strain. A commonly used method of global volatile profiling across Pseudomonas species is gas chromatography-mass spectrometry (GC-MS), or other iterations (solid phase microextraction GC-MS; GC-Qtime-of- flight-MS; closed-loop-striping analysis-GC-MS (Briard et al, 2016; Cellini et al, 2016; De

Vrieze et al, 2015; Hunziker et al, 2015; Labows et al, 1980; Lo Cantore et al, 2015; Ossowicki et al, 2017 ). One drawback when using these analytical techniques is the difficulty to measure

HCN. In the aforementioned examples, if HCN was measured, the authors used complementary experiments to the GC-MS. Alternatively, cyanide was quantified in blood samples analyzed with GC-MS and SPME GC-MS, which indicates to us that HCN could be quantified in bacteria samples using GC-MS/SPME GC-MS under the proper experimental and analytical conditions

(Calafat & Stanfill 2002; Frison et al, 2006). Two other mass spectrometry methods, selected ion flow tube mass spectrometry (SIFT-MS) and 2 dimensional GC-MS (GCxGC-time-of-flight

(ToF)-MS) have been used to identify the volatile compounds, including HCN, produced by P. aeruginosa (Bean et al, 2012; Carrol et al, 2005; Shestivska et al, 2011). Two-dimensional GC has greater sensitivity than 1-dimensional GC and allows substances to be separated by polarity as well as volatility, which can account for peak differentiation (Phillips & Xu, 1995). To the

53 best of our knowledge, SIFT-MS and GCxGC-ToF-MS technology have not been applied to other species of Pseudomonas. A newer method of volatile analysis is proton transfer reaction- mass spectrometry (PTR-MS). In this technique, the VOCs are protonated, and compound identification is done based on the protonated mass value. PTR-MS is sensitive (limit of detection at the parts-per-trillion scale) and capable of measuring very small compounds. One drawback of PTR-MS is low mass resolution, which results in an inability to differentiate isobaric compounds. This drawback led to the development of PTR-time of flight-MS (PTR-

ToF-MS) (Jordan et al, 2009; Yuan et al, 2017). The VOC profiles of multiple biological systems, including, fungi, bacteria, yeast, and fruit inoculated with bacteria have been investigated utilizing this system (Cellini et al, 2015; Infantino et al, 2017; Khomenko et al,

2017; Kuppusami et al, 2014; Vita et al, 2015). HCN can be detected using PTR-ToF-MS

(Moussa et al, 2016). We are not aware of any studies applying PTR-ToF-MS to determine the volatile profile of Pseudomonas strains, making this technique novel to our system.

The aims of this study were threefold. First, the biocontrol potential of 19 Pseudomonas strains representative of eight species and one Pantoea agglomerans strain, was investigated in vitro using nematode (C. elegans) and fungal (Fusarium oxysporum) systems to elucidate potential modes of action. Additionally, the global volatile profiles of the bacteria were analyzed using PTR-ToF-MS to determine which compounds are produced by the bacteria. Similarities and differences within the strains were investigated to identify patterns in volatile production between the species. Finally, in vitro assays were performed using hydrogen cyanide against F. oxysporum to determine the inhibitory activity of the individual compound.

2.3 Materials and Methods

2.3.1 Microorganism maintenance

Bacteria: The 20 Pseudomonas spp. and Pantoea agglomerans strains used in this study were collected by the Taylor and Brian McSpadden Gardener (Ohio State) laboratories from river water, soil, and plant samples from across the United States. The origin and species of each strain are shown in Table 2.1. Species designation for the Pseudomonas strains is based off an analysis of 10 housekeeping genes (Loper et al, 2012; Xiao-Yuan Tao & Christopher Taylor, unpublished). Pantoea agglomerans MBSA-3BB1 was identified using 16S sequencing and deposited in GenBank (Molecular Cell Imaging Center (MCIC), Ohio State University, Ohio-

USA). Strains sourced from the Taylor lab were initially screened for in vitro activity against

Caenorhabditis elegans. This collection has previously been tested for biocontrol activity against phytopathogens including bacteria, fungi, and nematodes (Aly, 2009; Martin, 2017; Mavrodi et al, 2012; South et al, 2020; Subedi et al, 2019). Genome mining was performed on the strains to search for the presence of biocontrol-related gene clusters (including, but not limited to HCN,

DAPG, and phenazines) (Xiao-Yuan Tao and Chris Taylor, unpublished). Bacteria were stored in the long term as glycerol stocks at -80°C, and cultures were maintained on Luria-Bertani (LB) agar plates (1L: 10g tryptone, 5g yeast extract, 10g NaCl, 15g agar). In each assay, overnight culture (16 to 18-hour growth, Pseudomonas spp. and Pantoea agglomerans: 28-30°C, ~200-

225RPM, E. coli 37°C, ~200-250RPM) in 5±0.5ml LB liquid media was used.

Fungi: Fusarium oxysporum isolates from Ohio tomato high tunnels were obtained from

Dr. Sally Miller (The Ohio State University). In the experiments presented here, two isolates were used, F. oxysporum 289 and 197, taken from diseased tomato roots in high tunnels in Ohio.

Fungi were cultured on ½ potato dextrose agar (PDA) (1L: 19.5g DifcoTM Potato Dextrose Agar,

7.5g agar). In the in vitro assays, six to eight-day-old old mycelial plugs (size 3 cork borer,

5/6mm inner/outer diameter) were used. Unless otherwise noted, fungal experiments were performed on ½ PDA plates (100mm) containing 20±0.5ml. The identity of the isolates was confirmed using ITS sequencing (MCIC, Ohio State University).

Nematodes: C. elegans were maintained on Nematode Growth Media (NGM) plates seeded with Escherichia coli OP50 as a food source. C. elegans were synchronized so that L1 stage juveniles were used in the in vitro assays. Eggs were harvested from adult nematodes using reagent recipes and a modified protocol from Stiernagle (2006). Briefly, under sterile conditions

C. elegans were washed from plates into a 15ml-tube using S Basal or M9 media and settled on ice. The supernatant was removed and an alkaline bleach solution (500µl 10N NaOH + 750µl commercial bleach + 5.75ml S. Basal or M9 medium) was added to the tube. After gently inverting the tube to mix, the worms sat in the bleach solution for 7-10 minutes, after which the tube was centrifuged at 750RPM (4ºC) for 5 minutes. The supernatant was removed, and eggs were transferred to a 50ml centrifuge tube with 15ml of S Basal or M9 media. The nematodes were washed 3 times in 15ml using the same centrifuge settings. Finally, harvested eggs were kept at 15°C. Eggs hatched after 24-hours and were viable for up to a few weeks after harvest.

Recipes for media used for C. elegans experiments are described in Stiernagle (2006).

2.3.2 Pseudomonas mode of action assays

Growth inhibition assays were performed in vitro to elucidate the mode of action of the bacteria. Bioactivity of each strain was tested against F. oxysporum 289 utilizing top agar, dual plating, and VOC exposure assays. F. oxysporum 197 and C. elegans were also used in the VOC exposure assays. An individual plate was considered an experimental unit. LB was used in each

56 assay as the negative control. In the C. elegans volatile assays, E. coli OP50 was also used as a negative control. Three or four experimental units were used per treatment in each fungal experiment. Five experimental units were used per treatment in each C. elegans experiment. All plates used in the experiments were sealed with at least three layers of parafilm and kept on the laboratory bench at ambient temperature and light conditions. Total fungal growth area was assessed after a one-week period, which included thicker “inner growth” and thinner “outer growth” mycelium (Supplemental Figure 1.1). In the fungal inhibition assays, total growth (full area of thin and thick hyphal growth) was measured. The proportion of “thin” and “thick” mycelial growth varied from plate to plate. Every bacterium was tested in two independent assays. Supplemental Figure 1.1 shows the experimental setup for each assay type.

Top agar assay: The top agar assay was used to determine activity associated with direct bacteria-fungal contact, metabolites in the supernatant, and volatile compounds produced by the bacteria. For each bacteria strain, 500µl of undiluted overnight culture was added to cooled, liquified 50ml of ½ PDA (0.75% agar). 10ml of the top agar bacteria suspension was pipetted on a 100mm plastic plate containing 15±0.5ml ½ PDA. A fungal plug was placed in the center of the plate on top of the solidified top agar.

Dual plating assay: The dual plating assay was used to determine activity due to compounds secreted into the growth medium and volatile compounds produced by the bacteria.

A fungal plug was placed in the center of a ½ PDA plate. A sterile inoculating loop was dipped into liquid bacterial culture and streaked three centimeters to the left and right of the plug, running the length of the plate.

VOC exposure assay: The VOC exposure assay was used to determine activity due to volatile compounds produce by the bacteria. The Pseudomonas VOC assays were done with both

F. oxysporum 289 and 197 and C. elegans. In the fungal assays, 100µl of overnight

Pseudomonas culture was spread on 100mm plastic plates containing 20±0.5ml LB agar. A fungal plug was placed in the center of a ½ PDA plate. The ½ PDA plates were inverted on top of the LBA plates and sealed with parafilm.

In the C. elegans assays, 30µl of overnight Pseudomonas or E. coli OP50 culture was spread on a 35mm plastic plate containing 3±0.3mL LB agar. Approximately 10-25 L1 stage C. elegans were added to 35mm plastic plates containing 3±0.3mL NGM and a freshly spread lawn of 30µl E. coli OP50. The NGM plates were inverted and placed on top of the LB plates and sealed with parafilm.

2.3.3 Pseudomonas single strain VOC measurement

+ Pseudomonas volatiles were measured by PTR-ToF-MS using H3O as reagent ions.

These experiments were conducted at the LINV (International Laboratory of Plant

Neurobiology) of the University of Florence (Tuscany-Italy). Overnight bacteria culture (50µl) was spread on a 60mm glass plate containing 10±0.2ml LB agar. Plates were sealed with parafilm and bacteria were grown at 28ºC for about 24 hours, at which point a bacteria lawn covered the plate. After the overnight growth period, the lid was removed, and the bottom half of each plate was placed in a 750 cubic-centimeter glass jar which was lidded and sealed with

TEROSON® RB IX (Rubix Group), an inert putty. Subsequently, each glass jar was flushed with zero air for 120 seconds through two Teflon tubes placed on the lid, after which the tubes were sealed with the putty and the samples were incubated for 20 minutes (Zero air generator, Peak

Scientific Instruments, USA). Bacteria had either two or three biological replicates. With the exception of three bacteria (P. brassicacearum 37D10, P. poae 36C8, P. chlororaphis 14D6),

58 three biological replicates of each strain were used for analysis. Those three strains had poor growth from one experimental run which were removed from analysis. With the exception of one bacterium (P. frederiksbergensis39A2), all bacteria had each biological replicate run on separate days. Two of the 39A2 replicates were run on one day. Bacteria growth varied from day to day, which may account for differences within the replicates. LB agar plates were used as negative controls, two in each experimental run. Additionally, clean air was flushed though the machine between all sample measurements, and to verify no contaminating volatiles were in the system, empty glass jars were run at the beginning of each experimental run as a negative control.

After incubation the headspace sampling was carried out for 120 seconds (with a flow rate of 50 standard cubic centimeters per minute), which corresponds to 120 mass spectra

(acquiring 1 spectrum per second). The last 100 seconds were used for analysis. Values for each compound were corrected to the blank headspace values. Moreover, as reported by Taiti et al,

(2019) to avoid different experimental conditions, all the samples were analyzed in an air- conditioned room, with a constant temperature of 25°C ± 1°C. For all sample analysis the PTR parameters were set as follows: a mass spectrum comprised between m/z 1 and m/z 250, pressure

2.3 mbar, drift voltage 600V, temperature of 100°C, extraction voltage at the end of the pipe

(Udx) 35 V and corresponding to an E/N value of 134 Td (Td, 1 Td = 10−17 cm2/V s). As reported previously by Pang (2015), the E/N value that is used gives a good balance between excessive water cluster formation and product ion fragmentation.

2.3.4 HCN measurement

HCN production was measured for each Pseudomonas isolate using a protocol modified from Carterson et al (2004). Bacteria (40µl, OD600 0.45-0.55) were spread onto plastic 35mm

59 plates containing approximately 4ml LB agar. Each plate was placed on top of a second 35mm plate containing 1ml 4M NaOH and sealed with at least three layers of parafilm. Once sealed, the bacteria were incubated at 28-30°C for approximately 24 hours. During this period, the 4M

NaOH absorbed HCN produced by the bacteria. After the incubation period the 4M NaOH was diluted to 0.09M and HCN was quantified using a 96-well plate spectrophotometer. A 1:1 o- dinitrobenzene in 2-methoxyethanol:p-nitrobenzaldehyde in 2-methoxyethanol solution was used to quantify bacterial cyanide. Seventy microliters of the 1:1 solution was added to 21μl of each sample. After a 30-minute incubation at room temperature the OD600 was measured. Samples were quantified relative to a potassium cyanide standard curve (1-20μM in 0.09M NaOH).

Additional dilutions were made with 0.09M NaOH if needed. Every strain was quantified in at least triplicate.

2.3.5 F. oxysporum inhibition using HCN

The inhibitory activity of HCN was tested against F. oxysporum 289. The experimental setup was similar to the Pseudomonas-Fusarium volatile assay. A stock solution KCN was prepared by dissolving 0.30g in 10ml 0.09M NaOH. The KCN was further diluted in 0.09M

NaOH and 823µl KCN was combined with an equivalent volume of 0.2N HCl to achieve final concentrations of 6.25, 12.5, 25, 50, 100, and 200 KCN parts per million (ppm) per plate. The plates were sealed with at least three layers of parafilm and gently rocked to combine the NaOH and HCl solutions to release HCN gas. The KCN quantities correspond to final concentrations of

2.59, 5.19, 10.37, 20.75, 41.49, 82.99 HCN ppm per plate if all cyanide in the solution was converted to HCN. The area of fungal growth was assessed after one week. Three experimental

60 units were used per treatment in each experiment. The cyanide fungal inhibition assay was performed twice.

2.3.6 Data analysis and statistics

The spectra calibration of “time of flight” was performed off-line after dead time

+ + correction and was based on three points (m/z = 29.997 (NO ), m/z = 59.049 (C3H7O ) and m/z

+ = 137.132 (C10H17 )). Data were recorded with the software “TOF-DAQ” (Tofwerk AG,

Switzerland), and were analyzed using a “PTR-MS viewer”.

The raw data was converted on the basis of primary ion signal from cps to ppbv. Volatile compounds with <0.25ppbv and other interfering ions, were filtered following the procedure used by Taiti et al (2017). In this manner, were detected a total of 55 compounds using a threshold of 0.25ppbv; however, for downstream analysis we removed all compounds that were below 1ppbv in every replicate across all treatments (39 remaining compounds) (Supplemental

Table A1). Compounds that were not present at quantities >1ppbv in every replicate of at least one bacterium or LB control were not included in any analysis. After removing volatile compounds <1ppbv, one-way ANOVA (α=0.05) was performed for the remaining compounds to identify compounds that were significantly different between the bacteria and LB control. Thirty- three compounds were significantly different between the treatments. Compounds that were not different between the 20 bacteria and LB control were further removed from the data set.

A heat map showing the abundances of individual compounds was prepared on log(n+1) transformed data in Microsoft Excel. The average values for each bacterium and LB control are used in the heat map. Variable reduction principal component analysis (PCA) was performed on the volatile profiles of the bacteria and LB controls. In this method, only compounds that

61 accounted for the most variation in the data set were used in the final PCA (Supplemental Figure

S2.2). Before PCA, the dataset was preprocessed using log(n+1) transformation followed by mean centering. Data preprocessing using transformation and scaling is commonly used in metabolite studies (van den Berg, 2006). All bacteria treatments and controls are used in the

PCA. PCA was performing using JMP from SAS.

VOCs were assigned a tentative identification utilizing data available from previous

PTR-MS, PTR-ToF-MS, and additional methods of mass spectrometry analysis studies. Where available we tentatively identified compounds based on previously reported fragmentation patterns (Buhr et al, 2002; Gueneron et al, 2015; Maleknia et al, 2007; Mochalski et al, 2014;

Perraud et al, 2016)

Fungal mycelial growth in in vitro assays was measured using ImageJ

(https://imagej.nih.gov/ij/). Data were tested for normality and homogeneity of variances using the Shapiro-Wilk and Levene’s test. A majority of the treatments were normally distributed; however, the variances were not equal across treatments. The in vitro fungal data were subject to analysis with the parametric Welch’s ANOVA (confidence interval 95%, α= 0.05) with post-hoc

Games-Howell test. The in vitro C. elegans data were subject to analysis with the nonparametric

Kruskal-Wallis test followed by a post-hoc Dunn’s multiple comparisons test (α=0.05).

Correlations between the in vitro volatile assays and individual volatile compounds were conducted using Pearson’s correlation coefficient analysis. Average % inhibition of each F. oxysporum isolate and average C. elegans ratings were used in the correlation analysis. All

ANOVA, correlation coefficient calculations, and nonparametric statistics presented in this study were performed using Minitab (Minitab LLC, Pennsylvania, USA) or SPSS (IBM, New York,

USA).

2.4 Results

2.4.1 In vitro bioassays

Every strain of bacteria tested inhibited the growth of Fusarium oxysporum 289 in vitro.

In the top agar inhibition assay, all bacteria significantly inhibited F. oxysporum 289 by over

65% (Figure 2.1). The nine most effective strains were those which caused over 95% reduction of growth of Fusarium in the top agar as compared to the LB control. These strains had limited to no growth past the fungal plug. The nine bacteria were spread across four Pseudomonas species (P. protegens, P. brassicacearum, P. chlororaphis, and P. poae). Further insight into mode of action was obtained from the dual plating and indirect volatile exposure assays.

In the dual plating assay only two strains (P. fluorescens 24D3 and 89F1) did not significantly inhibit growth of F. oxysporum 289 as compared to the control (Figure 2.2). The magnitude of inhibition varied between bacteria. Some strains caused fungal growth to stop upon making contact with the bacteria, however this still resulted in significant growth inhibition as compared to the controls (Supplemental Figure S2.1). Nine strains inhibited F. oxysporum 289 by over 50% compared to the LB control. There was complete overlap of the nine top strains in both the dual plating and top agar assays.

The species best at inhibiting growth of F. oxysporum in our volatile bioassays were P. fluorescens and P. protegens (Figures 2.3 and 2.4). Not every bacterium produced volatiles capable of significantly inhibiting the growth of F. oxysporum 289 (Figure 2.3A). Five of the 20 strains tested did not significantly inhibit growth of the fungus. The effects of volatiles varied among the remaining 15 bacteria. The volatiles produced by five strains (P. protegens and P. fluorescens), inhibited growth of the fungus by over 50% as compared to the control. Of the top five strains with volatile activity only one, P. fluorescens 36F3, was not a top treatment in the top

63 agar and dual plating assays. We also performed the indirect exposure inhibition assays on two other microorganisms, F. oxysporum 197 and the bacterial-feeding nematode C. elegans. Seven bacteria strains in the P. fluorescens and P. protegens species significantly suppressed the growth of F. oxysporum 197, however fungal suppression was less with this isolate than with F. oxysporum 289 (Figure 2.3B).

Due to the short reproductive cycle of the nematode, the number of C. elegans at the end of a 7-day period was recorded on a scale of 0 to 4, where zero represents no living nematodes, and four represents over 200 C. elegans adults and juveniles. In the final nematode counts only living nematodes were counted. A rating of four indicates that the nematodes were able to grow and reproduce over the duration of the experiment. With one exception, plates with a rating of zero contained only dead juvenile nematodes. The LB and E. coli OP50 negative controls had average ratings of 4 and 3.7, respectively. Volatiles of multiple strains inhibited the nematodes.

Seventeen of the strains significantly inhibited C. elegans compared to the LB and E. coli OP50 negative controls (Figure 2.5). Six bacteria (P. chlororaphis, P. fluorescens, and P. protegens) produced volatiles that resulted in complete nematode lethality. An additional seven strains (P. brassicacearum, P. chlororaphis, P. fluorescens, P. frederiksbergensis, P. poae, P. protegens) had average ratings of 0

2.4.2 PTR-ToF-MS and HCN quantification

In the 20 Pseudomonas spp. and Pantoea agglomerans strains and LB controls, 39 compounds were quantified at abundances >1ppbv using PTR-ToF-MS, ranging in m/z from

27.023 to 153.120. Of these, 33 were significantly different (α= 0.05) between the bacteria and controls. In general, the lower molecular weight compounds were more abundant than the higher ones. Compounds were putatively identified based on their protonated masses, from which chemical formulas could be determined. All compounds present in every replicate of at least one bacterium or the LB control above 1pppv are included in Table A1.1. Through the remainder of this text, m/z will be referred to as their theoretical (calculated mass), rather than the experimentally measured mass unless we were unable to assign a chemical formula to a compound. Categories of compounds putatively identified included hydrocarbons (alkyl fragments), alcohols, ketones, organosulfurs and cyanides. Differences in the abundance of each compound >1ppbv is shown in a heat map in Figure 2.6. Bacteria are separated by species designation in the heat map to best allow for pattern differentiation. Within the heat map, cells that are red are most abundant and cells that are black are not present in the samples. All strains and the LB controls had complex VOC profiles. There were multiple compounds quantified in which average values in the LB were higher than all the average values of every bacteria strains

(m/z 27.023, 30.046, 45.033, 47.049, 77.042, 79.054, and 97.028). As indicated in the heat map,

+ m/z 28.018 (H2CN ) was the most abundant compound in some of the bacteria but was not present in others. HCN production varied based on species. Additional differences occur in the heat map for individual bacterial strains and compounds; however, no clear patterns are viewed except for Pantoea agglomerans MBSA-3BB1 standing out from the Pseudomonas spp. strains.

Bacteria growth varied from day to day, which may account for differences within treatments.

Some bacteria had replicates where the lawn did not cover the entire plate which may have contributed to differences in overall volatile quantification.

Many strains produced substantial amounts of two classes of compounds: cyanides and organosulfurs. Figure 2.7 shows the abundance of HCN and organosulfur compounds as compared to the remaining compounds. Abundance of compounds varies among the strains.

Figure 2.8 shows hydrogen cyanide (HCN) production by each strain. Hydrogen cyanide quantification is shown using both a colorimetric assay and the PTR-ToF-MS quantification

+ (H2CN , m/z 28.018) to compare the results of each assay. Cyanide production varied between the strains. Of the 16 strains that emitted measurable hydrogen cyanide, average levels ranged from 25 to 1569 ppbv. No strains in the P. poae or P. rhodesiae species produced measurable amounts of cyanide. The LB control did not produce measurable cyanide in either assay. While the amount of cyanide produced was not comparable between the PTR-ToF-MS and colorimetric assay results, the same trend in HCN production among the strains was seen in both assays except for Pantoea agglomerans MBSA-3BB1. With this strain, a small amount of hydrogen cyanide was measured with PTR-ToF-MS and none with the spectrophotometer. Due to variation in the cyanide standard curve between experimental runs, the colorimetric assay is considered semiquantitative rather than quantitative.

Figure 2.9 and Supplemental Table S2.1 shows sulfur containing compounds produced by each strain and the LB control. In general, the most abundant organosulfur compound

+ produced by the bacteria was m/z 49.011 (CH5S , methanethiol/ DMDS fragment). Within this study, we were interested in volatiles with biocontrol potential, and consequently one organosulfur compound we were most interested in was DMDS and associated fragments.

Synthetically produced DMDS is sold commercially as a soil fumigant to control soilborne plant

66 pathogens, nematodes, and weeds of a variety of crops (Arkema, 2016). Seven of the 21 bacterial

+ strain produced DMDS (C2H7S2 , m/z 94.998) average levels at over 1ppbv. The top two DMDS producing strains were P. protegens strains 1B1 and Darke (average 12.1 and 8.6 ppbv,

+ respectively). All bacteria and the controls produced levels of CH3S2 (DMDS-fragment, m/z

+ 78.967) at levels greater than 1ppbv. 1B1 and Darke were also the top CH3S2 producers

(average 124.9 and 96.7, respectively). For both m/z 94.998 and 78.967, 1B1 and Darke produced approximately 1-2 log fold more than the other bacteria. An additional compound of

+ interest was methyl thiocyanate (C2H4NS , m/z 74.006), which was produced at levels >1ppbv by

19 strains. Methyl thiocyanate was the most abundant organosulfur compound produced by P. protegens strains 15G2 and 38G2. The highest producer of methyl thiocyanate was P. protegens

+ 1B1 (158.0 ppbv). Finally, nine strains produced S-methyl thioacetate (C3H7OS , m/z 91.021) at quantities >1 ppbv. The highest S-methyl thioacetate producer was P. fluorescens 24D3

+ (6.9ppbv). One organosulfur compound, m/z 77.042 (C3H9S ), was only present >1ppbv in the

LB control, which may indicate it could have been used as a nutrient source by the bacteria to generate other organosulfur compounds.

Volatile compounds >1ppbv were log transformed and mean centered and analyzed using principal component analysis, shown in Figure 2.10. The data set was reduced a set of eight compounds responsible for 75.5% the variation within the bacteria and LB controls. The bacteria did not separate into discrete groups on the PCA, rather separated along a gradient. Supplemental

Figure S2.2 demonstrates the importance of reductive PCA to reduce the complexity of correlations between variables. The eight variables used in the PCA are cyanide or sulfur containing compounds or compound fragments (m/z 28.018, 46.995, 49.011, 63.026, 74.006,

78.967, 91.021, 94.998). All variables except m/z 63.026 highly influenced PC1. All cyanide and

67 organosulfur compounds >1ppbv were included in the PCA except for m/z 77.042, which was not selected for the reductive PCA. When the bacteria are colored by species, rather than isolate designation, separation into groups is seen for some species but others are more spread across the

PCA, indicating differences in VOC production among strains within the same species

(Supplemental Figure S2.2).

2.4.3 Correlation between in vitro assays and volatile compounds

We were interested in correlations between the volatiles produced by the bacteria and microorganism inhibitory activity. The inhibitory activity of the bacteria and controls was placed on the PCA using eight cyanide and sulfur containing compounds and fragments, coloring individual samples according to fungal inhibition (Figure 2.10 B, C). Fungal inhibition by the strains is observed along the gradient. Pearson’s correlation coefficient was determined for 33 volatile compounds (>1ppbv and significance with ANOVA, α=0.05) against inhibition of both

F. oxysporum 289 and 197. Four VOCs were positively correlated with inhibition of both fungal isolates, and two additional compounds were positively correlated with F. oxysporum 197 inhibition only (Table 2.2). Five of the compounds correlated with inhibition are organosulfur and/or cyanide containing compounds and fragments. We tested the activity of pure HCN against

F. oxysporum 289. At HCN concentrations of 20.75ppm or greater (50ppm KCN or greater) growth of the fungus was inhibited (Table 2.3). In these assays we only measured the area of thick hyphal growth, because there was no growth in the inhibitory concentrations. The only

+ VOC significantly correlated with inhibition of C. elegans was H2CN (Pearson’s Correlation

Coefficient -0.692, p-value 0.001). Additional compounds were significantly associated with higher amounts of nematodes (data not shown).

2.5 Discussion

Within the rhizosphere, a biocontrol agent may not be in direct contact with the soilborne pathogen it is controlling, and as such multiple modes of action could be contributing to bioactivity. Our study focused on multiple modes of action to explore control activity of fungal

(F. oxysporum) and nematode (C. elegans) systems by beneficial bacteria. The bioactivity mechanisms tested in the top agar assay were direct contact, secreted antibiotic and volatile compounds; dual plating assay were secreted antibiotic and volatile compounds; and shared-air inhibition assay only investigated activity though volatile compounds produced by the bacteria.

The best candidates in the top agar and dual plating inhibition assays of F. oxysporum 289 belonged to the P. protegens, P. brassicacearum, P. chlororaphis, and P. poae species (Figures

2.1 and 2.2). Except for P. poae 29G9, genome mining indicated the presence of three antibiotic gene clusters (Table 2.1: DAPG, pyrrolnitrin, and phenazine) that could play a role in fungal antagonism in the top strains. These gene clusters were only present in the most bioactive bacteria, although not every bioactive strain contained all three antibiotic gene clusters. DAPG, pyrrolnitrin, and phenazines are diffusible secondary metabolites, meaning the compounds can be secreted by the bacteria and move through the growth media (in vitro) or soil to affect the pathogen (Haas & Defago, 2005). Just as the presence of antibiotics genes is inconsistent within our collection, some well-characterized Pseudomonas strains capable of biocontrol have varied potential to produce these antibiotic compounds (Loper et al, 2012). Every P. protegens strain as well as the most active P. brassicacearum strains contain the DAPG gene cluster. DAPG is a secondary metabolite produced by Pseudomonas that can play a role in antibiosis of multiple classes of pathogens including fungi, oomycetes, and bacteria (Keel et al, 1992; Levy et al, 1992;

Rezzonico et al 2007). Soils suppressive to take all disease of wheat (causal agent

Gaeumannomyces graminis var. tritici) contain higher levels of pseudomonads with the DAPG gene phlD in the rhizosphere and/or root tissue (de Souza et al, 2002; Raaijmakers & Weller,

1998). Some of our bioactive P. chlororaphis and P. protegens strains also contain genes for pyrrolnitrin, an antibiotic that can be produced by Pseudomonas sp. and Pantoea agglomerans which has demonstrated activity against multiple microorganisms (Arima et al, 1964; Chernin et al, 1996; Howell & Stipanovic, 1979; Tripathi & Gottlieb, 1969). P. fluorescens Pf-5 mutants unable to produce pyrrolnitrin were less effective against fungal pathogens in vitro and in planta than the wildtype isolate (Rodriguez & Pfender, 1997). The two most bioactive P. chlororaphis strains contain the gene cluster for phenazine production. Phenazines purified from Burkholderia cepacia have shown activity against Rhizoctonia solani in vitro (Cartwright et al, 1995).

Phenazine mutant- Pseudomonas isolates were not as effective in controlling disease caused by

Fusarium oxysporum f. sp. radicis-lycopersici in planta as compared to the wildtype isolate

(Chin-A-Woeng et al, 1998). Additionally, two of our P. protegens strains also contain the gene cluster for pyoluteorin, an antibiotic compound with demonstrated oomycete (fungal-like microorganism) control activity (Howell & Stipanovic, 1980). Because it does not contain the gene clusters for any of the abovementioned antibiotics it is not clear to us what is contributing to the biocontrol activity of P. poae 29G9, and further exploration may be warranted.

The best bacteria in the shared-air indirect exposure assays of F. oxysporum isolates 289 and 197 belonged to the P. fluorescens and P. protegens species. The VOCs produced by the top

Pseudomonas strains inhibited mycelial growth by over 50% in F. oxysporum 289 and over 30% in F. oxysporum 197 as compared to the control. This indicates that the control capabilities of bacteria might differ against microorganisms of the same species, which has implications for identifying biocontrol agents with a broader spectrum of control activity. When strains were

70 pooled together and inhibition activity was determined at the species level, P. fluorescens and P. protegens were significantly better at inhibiting Fusarium mycelial growth than the other species. Strains from P. chlororaphis, P. frederiksbergensis, and P. brassicacearum also inhibited F. oxysporum 289 mycelial growth (Figures 2.3 and 2.4). It is also important to note that P. protegens and P. fluorescens both had four strains used for testing while the other species had fewer strains. It is possible that greater inhibition at the species level might have been seen if the other species had more strains used in the assays. Our results contrasted with the results of

Hunziker et al (2015), who screened a collection of bacteria representing species including P. fluorescens, P. protegens, and P. frederiksbergensis against F. oxysporum in shared-air experiments. Although the volatiles produced by some of their bacteria caused significant reduction, Hunziker et al (2015) saw substantially less inhibition of F. oxysporum mycelia

(<12%) than our top candidates (>50% reduction as compared to the control). While our results indicated patterns of inhibition among the species, the differences between our results and

Hunziker et al (2015) indicate the necessity to test more strains within the species presented here in this study, with additional isolates of F. oxysporum representative of multiple formae, to gain a more comprehensive picture of fungal volatile inhibitory activity at the species level.

Every strain that significantly inhibited growth of F. oxysporum 289 contains the hcnABC gene cluster (Figure 2.3A, Table 2.1). Through a colorimetric semi-quantitative assay, we determined that all these strains produced a measurable amount of hydrogen cyanide (Figure

2.8B), a volatile compound produced by many pseudomonads capable of biocontrol of fungi and nematodes. Pseudomonas mutants with reduced (either substantially or completely) HCN production were less effective in pathogen control in vitro or in planta (Ahl et al, 1986;

Flaishman et al, 1996; Gallagher & Manoil, 2001; Hunziker et al, 2015; Laville et al, 1998;

Ossowicki et al, 2017). Additionally, pure HCN and NaCN were effective against C. elegans and multiple fungal pathogens (Ahl et al, 1986; Flaishman et al, 1996; Gallagher & Manoil, 2001).

HCN was fully inhibitory to F. oxysporum 289 in vitro at concentrations 20.75ppm and greater

(Table 2.3). The level of fungal inhibition due to bacterial volatiles varied between F. oxysporum

289 and 197. Unlike for F. oxysporum 289, not every cyanide producer was capable of significantly inhibiting F. oxysporum 197. Some strains with relatively high cyanide production were not did not significantly inhibit growth of F. oxysporum 197 (Figures 2.3B, 2.8). Likewise, not every cyanide producer significantly inhibited the growth and reproduction of C. elegans

(Figures 2.5 and 2.8). Due to the differences in biocontrol capabilities among the different bacteria we were interested in seeing if any additional volatile compounds may play a role in biocontrol of nematodes and fungi. Differences in the bacteria volatilomes were determined using PTR-ToF-MS.

As seen in Figure 2.6, the volatile profile of the control and bacteria is complex, and there is large variation in the abundance of individual compounds. Cyanide production using PTR-

ToF-MS resulted in a similar pattern of production among the bacteria as the colorimetric assay

(Figure 2.8). The PTR-ToF-MS and colorimetric assay results were compared against previous qualitative and quantitative cyanide quantification done in the Taylor Laboratory in which some, but not all, of the strains matched with results presented in this study (Aly, 2009). Ultimately the previous quantification methods were different, based on color change of filter paper (qualitative, rating scale of zero to three) or micro-ion probe (quantitative). Results of those two methods did not always match in relative magnitude, and it is possible sensitivity of the quantification methods may play a role in the differing results. The similarity in measurement of hydrogen cyanide between the colorimetric assay and PTR-ToF-MS boosts our confidence in using the

PTR-ToF-MS to verify volatile production in our bacteria. Between these four cyanide quantifications tested in current and previous experiments, it is clear the method of volatile quantification is imperative for the most correct and informative data.

Of the 39 compounds quantified at intensities <1 ppbv, we identified eight, all cyanides and sulfur-containing compounds, that contributed to 75.5% of the variation between the bacteria and controls (Figure 2.10). There was variation in both total quantity and abundance (% total

VOC) of these compounds between the bacteria and LB controls (Figure 2.7). Strains ranged from having cyanides and organosulfur compounds comprise 3.1% (Pantoea agglomerans) to over 70% (P. fluorescens and P. protegens) of the total VOCs produced. When the PCA was colored based on fungal inhibition activity of each strain, we saw that the bacteria and controls separated along a gradient. Strains that caused limited to no inhibition of fungal growth were

+ generally in the upper left quadrant of the PCA, opposite the vectors for m/z 28.018 (H2CN ,

+ + hydrogen cyanide), 74.006 (C2H4NS . methyl thiocyanate), and 91.021 (C3H7OS , S-methyl thioacetate) (Figure 2.10 B, C). Correlation analysis indicated that these three compounds, in

+ + addition to m/z 46.995 (CH3S , methanethiol/DMS fragment), 49.011 (CH5S , methanethiol/DMDS fragment), and 51.010 (unknown fragment) may contribute to fungal inhibition (Table 2.2). Because HCN has already been discussed, we will explore the possible involvement of these additional volatiles in fungal inhibition.

Methyl thiocyanate (m/z 74.006), produced by 11 of our bacteria (P. brassicacearum, P. chlororaphis, P. fluorescens, and P. protegens) at >10ppbv, is an organosulfur cyanide compound that has been quantified in multiple Pseudomonas genera (Bean et al, 2012;

Ossowicki et al, 2017). It is lethal and/or paralytic to root-knot nematode in vitro and can act as a repellant to P. aeruginosa (Aissani et al, 2015; Ohga et al, 1993). Within our collection, the

73 strains that produced volatiles significantly inhibitory to F. oxysporum 289 produced higher quantities of methyl thiocyanate than the non-inhibitory strains. Top methyl thiocyanate producing strains also inhibited F. oxysporum 197 mycelial growth in volatile indirect exposure assays (Figures 2.3 and 2.9, Supplemental Table S2.1). Methyl isothiocyanate, isomer to methyl thiocyanate, is a fumigant (non-soil) registered with the EPA that is currently under review for registration as a pesticide, however it is not known to be produced by pseudomonads (Reaves,

2019). S-methyl thioacetate (m/z 91.021), produced by nine of our strains (P. brassicacearum, P. chlororaphis, P. fluorescens, and P. protegens) at >1ppbv has been previously quantified in other pseudomonads and shown to significantly inhibit Rhizoctonia solani hyphal growth in vitro

(Ossowicki et al, 2017). All strains that produced S-methyl thioacetate at average levels >1ppbv significantly inhibited F. oxysporum 289 mycelial growth in indirect exposure assays; however, the second highest producer (P. brassicacearum 93G8) was unable to significantly inhibit growth of F. oxysporum 197. Of the seven bacteria with significant VOC activity against of F. oxysporum 197, only four produced S-methyl thioacetate >1ppbv.

+ Other VOCs including m/z 46.995 (CH3S , methanethiol/DMS fragment) and 49.011

+ (CH5S , methanethiol/DMDS) fragments) were also correlated with F. oxysporum inhibition

(m/z 46.995 both F. oxysporum 289 and 197; m/z 49.011 F. oxysporum 197 only), however there is less evidence that these compounds are involved in microorganism control (Table 2.2).

Methanethiol, widely produced by multiple Pseudomonas species, is the precursor to other organosulfur compounds including DMDS and DMS, and thioesters (Drotar et al, 1987; Lo

Cantore et al, 2015; Thorn et al, 2011; Carrol et al, 2005; Yvon & Rijnen 2001). Lo Cantore et al

(2015) saw that pure methanethiol and DMDS were significantly inhibitory to fungal isolates in vitro, although the inhibition occurred at lower concentration of DMDS than methanethiol.

Alternatively, the growth of human pathogen Aspergillus in vitro was significantly stimulated by

DMS (on both sulfur-containing and -deficient media) and DMDS (on sulfur-deficient medium)

(Briard et al, 2018). Ultimately production of these compounds was varied among our bacteria.

The top producers of both m/z 46.995 (>30ppbv) and 49.011 (>100ppbv) belong to strains of P. chlororaphis, P. fluorescens, and P. protegens, however multiple strains not inhibitory to either

F. oxysporum 289 or 197 produced relatively high amounts of these compounds (Figures 2.3,

+ + 2.9, Supplemental Table S2.1). The masses representing only DMDS (CH3S2 and C2H7S2 ; m/z

94.998 and 78.967) varied among the bacteria but were not correlated with fungal inhibition. The top DMDS/DMDS fragment producers, P. protegens strains 1B1 and Darke, were inhibitory to both Fusarium isolates, however not all strains that were relatively high producers of these compounds were inhibitory to F. oxysporum (P. poae and P. rhodesiae) (Figures 2.3 and 2.9,

Supplemental Table S2.1). The possible effects that DMDS may have on Fusarium inhibition will be discussed further in Chapter 3.

Dimethyl disulfide may play a role in the inhibitory activity of the four non-cyanogenic strains that significantly inhibited C. elegans (limited growth and reproduction rather than full lethality). P. poae 29G9 and P. rhodesiae 88A6 and 90F12-1 were in the top producers of m/z

94.998 and 78.967 (DMDS and its associated fragment). P. poae 36C8, also inhibitory to C. elegans, produced the greatest amount of DMS (C2H7S+, m/z 63.026), however as mentioned above, DMS is not known as a biocontrol agent (Figures 2.5 and 2.9, Supplemental Table S2.1).

Differences in inhibition between the two Fusarium isolates indicates that volatiles may affect isolates from the same species to different extents. Correlation analysis was performed between bacteria volatiles quantified after 20 minutes of volatile collection by approximately 24 hour-old plates and fungal inhibition after a weeklong assay. It is possible volatile production,

75 both in number of compounds and abundance of individual compounds is not consistent over the full week. Studies involving the volatilome of yeast and fungus over a time-course saw that quantification of individual compounds could vary over the course of the experiment (Azzollini et al, 2018; Khomenko et al, 2017). Therefore, the correlation of volatile production with fungal inhibition might be different if the volatile profiling was done at a different time point. It is also important to consider possible turnover of compounds over the course of the weeklong in vitro assay. Additionally, it is unclear to us what role volatiles produced by the fungi or nematodes may have on the bacteria in the in vitro assays. The volatile profile produced by the bacteria in the presence of other organisms may differ from the bacteria grown alone, as previously demonstrated in individual and co-culturing experiments of bacteria and fungi (Azzollini et al,

2018; Garbeva et al 2014a).

One downfall of using PTR-ToF-MS to identify bacterial volatiles is the difficulty to accurately measure the abundance of certain compounds present in the headspace. Fragmentation of hydrocarbons, alcohols, esters, aldehydes, and ketones results in many m/z associated with multiple compounds (Aprea et al, 2007; Buhr et al, 2002; Gueneron et al, 2015; Maleknia et al.

2007). Within our data set, multiple compounds are associated with groups of fragments, but a precise compound identification cannot be given due to there being multiple possible identities of the fragments. In other instances the mass and chemical formula fit certain compound

+ identities, however they did not fit within the parameters of our system; for example C2H6 (m/z

30.046) is the chemical formula for isotopic ethylene but we identified it is an acetyl fragment because it was produced at highest levels in the controls, which should not be producers of ethylene. Larger compounds including hydrocarbons, ketones, aldehydes were not specifically measured in our data, however some of the mass fragments may have been associated with them

(Table A1.1). These categories of compounds are ubiquitously present in the VOC profile of

Pseudomonas and certain ones have demonstrated control activity against phytopathogens. Other studies have determined multiple compounds (ketones and alkenes) including 2-docecanone, 1- undecene, 2-heptanone, and 2-undecanone can inhibit the growth of fungal and oomycete phytopathogens to varying extents in vitro (De Vrieze et al, 2015; Guevara-Avendaño et al,

2019; Hunziker et al, 2015). m/z 51.010 (chemical formula unknown) is correlated with inhibition of F. oxysporum 197; while some of the strains capable of significantly inhibiting F. oxysporum 197 mycelial growth produced measurable amounts of this compound, other high producers did not significantly impact fungal growth. We were not able to tentatively identify this compound, but it is possible it came from a larger, bioactive compound. Due to fragmentation of larger molecules, we may have missed some compounds with bioactive potential in our analysis. As seen in Appendix A1, some fragments were not significantly different between the controls and bacteria, which indicates the volatile was LB derived and likely does not play a role in biocontrol activity. Future studies with PTR-ToF-MS may need to be performed to investigate fragmentation patterns for larger compounds the bacteria may be producing, so we have a more comprehensive idea of what VOCs bacteria from the genera

Pseudomonas and Pantoea produce.

It is likely that more than one mode of action is responsible for the inhibitory activity of a given bacteria. Multiple studies have demonstrated the Pseudomonas mutants lacking the ability to produce a specific antibiotic/volatile compound (or produced the compound in negligible amounts) could inhibit growth of tested organisms in vitro or control disease in plants. Within these studies, control with the mutants was comparatively worse than with the wildtype isolate, which indicates more than one mode of action responsible for pathogen control (Chin-A-Woeng

77 et al, 1998; Hunziker et al, 2015; Keel et al, 2002; Rodriguez & Pfender, 1997). Many of our strains that were active under direct and indirect contact F. oxysporum 289 inhibition assays contain the ability to secrete multiple antibiotic diffusible and volatile compounds. Therefore, organismal control could be achieved through a single- or combination of- modes of action.

2.6 Conclusions and Future Directions

Overall, the most effective bacteria species in inhibiting F. oxysporum and C. elegans were P. fluorescens and P. protegens. The extent of control capabilities varied between individual strains. Within the framework of our analysis, we identified that cyanides and organosulfur compounds could play a role in controlling our target microorganisms. We have identified some future directions to be taken with the project: 1) the mode of action assays should be repeated using un-sealed systems so that the activity of the bacteria can be established when trapped volatiles are not a component of the system; 2) volatile profiling experiments should be repeated over a longer time frame, and with co-culturing of the fungus and nematodes to gain the most accurate representation of how Pseudomonas spp. and Pantoea agglomerans volatiles affect F. oxysporum and C. elegans; 3) volatile profiling should be done with a second method of volatile analysis to complement PTR-ToF-MS, so that all possible volatile organic compounds with biocontrol potential are identified; 4) if possible, mutants with the inability to produce specific compounds should be generated of our most bioactive bacteria to further elucidate the role a specific mode of action has on the overall inhibitory activity of the isolate.

We acknowledge Drs. Cosimo Taiti and Diego Comparini (LINV, Sesto Fiorentino, Tuscany-

Italy) for their assistance in performing and analyzing the data from the PTR-ToF-MS

78 experiments, Edwin Daniel Navarro Monserrat for help with the in vitro assays, and the

Translational Plant Sciences Graduate Program for funding the PTR-ToF-MS experiments

References

Ahl, P., Voisard, C., & Défago, G. (1986). Iron bound‐siderophores, cyanic acid, and antibiotics involved in suppression of Thielaviopsis basicola by a Pseudomonas fluorescens strain. Journal of Phytopathology, 116(2), 121–134. https://doi.org/10.1111/j.1439- 0434.1986.tb00903.x Aissani, N., Urgeghe, P. P., Oplos, C., Saba, M., Tocco, G., Petretto, G. L., … Caboni, P. (2015). Nematicidal activity of the volatilome of Eruca sativa on Meloidogyne incognita. Journal of Agricultural and Food Chemistry, 63(27), 6120–6125. https://doi.org/10.1021/acs.jafc.5b02425 Aly, H. (2009). Role of Pseudomonas produced hydrogen cyanide in biological control of plant- parasitic nematodes. University of Missouri-St. Louis [Dissertation] https://irl.umsl.edu/dissertation/384 Aprea, E., Biasioli, F., Märk, T. D., & Gasperi, F. (2007). PTR-MS study of esters in water and water/ethanol solutions: Fragmentation patterns and partition coefficients. International Journal of Mass Spectrometry, 262(1–2), 114–121. https://doi.org/10.1016/j.ijms.2006.10.016 Arima, K., Imanaka, H., Kousaka, M., Fukuda, A., & Tamura, G. (1964). Pyrrolnitrin, a new antibiotic substance, produced by Pseudomonas. Agricultural and Biological Chemistry, 28(8), 575–576. https://doi.org/10.1080/00021369.1964.10858275 Arkema. (2016). PALADIN. https://www3.epa.gov/pesticides/chem_search/ppls/055050-00004- 20160502.pdf Azzollini, A., Boggia, L., Boccard, J., Sgorbini, B., Lecoultre, N., Allard, P. M., … Wolfender, J. L. (2018). Dynamics of metabolite induction in fungal co-cultures by metabolomics at both volatile and non-volatile levels. Frontiers in Microbiology, 9(72). https://doi.org/10.3389/fmicb.2018.00072 Bean, H. D., Dimandja, J. M. D., & Hill, J. E. (2012). Bacterial volatile discovery using solid phase microextraction and comprehensive two-dimensional gas chromatography-time-of- flight mass spectrometry. Journal of Chromatography B, 901, 41–46. https://doi.org/10.1016/j.jchromb.2012.05.038 Bolwerk, A., Lagopodi, A. L., Wijfjes, A. H. M., Lamers, G. E. M., Chin-A-Woeng, T. F. C., Lugtenberg, B. J. J., & Bloemberg, G. V. (2003). Interactions in the tomato rhizosphere of two Pseudomonas biocontrol strains with the phytopathogenic fungus Fusarium oxysporum f. sp. radicis-lycopersici. Molecular Plant-Microbe Interactions, 16(11), 983–993. https://doi.org/10.1094/MPMI.2003.16.11.983 Briard, B., Heddergott, C., & Latgé, J. P. (2016). Volatile compounds emitted by Pseudomonas aeruginosa stimulate growth of the fungal pathogen Aspergillus fumigatus. Mbio, 7(2), 1–5. https://doi.org/10.1128/mBio.00219-16 Buhr, K., Van Ruth, S., & Delahunty, C. (2002). Analysis of volatile flavour compounds by proton transfer reaction-mass spectrometry: Fragmentation patterns and discrimination between isobaric and isomeric compounds. International Journal of Mass Spectrometry, 221(1), 1–7. https://doi.org/10.1016/S1387-3806(02)00896-5 Calafat, A. M., & Stanfill, S. B. (2002). Rapid quantitation of cyanide in whole blood by automated headspace gas chromatography. Journal of Chromatography B, 772(1), 131–137. https://doi.org/10.1016/S1570-0232(02)00067-3

Carrol, W., Lenney, W., Wang, T., Španěl, P., Alcock, A., & Smith, D. (2005). Detection of volatile compounds emitted by Pseudomonas aeruginosa using selected ion flow tube mass spectrometry. Pediatric Pulmonology, 39(5), 452–456. https://doi.org/10.1002/ppul.20170 Carterson, A. J., Jackson, D. W., Frisk, A., Lizewski, S. E., Jupiter, R., Simpson, K., … Hassett, D. J. (2004). The transcriptional regulator AlgR controls cyanide production in Pseudomonas aeruginosa. Journal of Bacteriology, 186(20), 6837–6844. https://doi.org/10.1128/JB.186.20.6837 Cartwright, D. K., Chilton, W. S., & Benson, D. M. (1995). Pyrrolnitrin and phenazine production by Pseudomonas cepacia, strain 5.5B, a biocontrol agent of Rhizoctonia solani. Applied Microbial Biotechnology, 43, 211–216. https://doi.org/10.1007/BF00172814 Cellini, A., Biondi, E., Buriani, G., Farneti, B., Rodriguez-Estrada, M. T., Braschi, I., … Spinelli, F. (2016). Characterization of volatile organic compounds emitted by kiwifruit plants infected with Pseudomonas syringae pv. actinidiae and their effects on host defences. Trees, 30(3), 795–806. https://doi.org/10.1007/s00468-015-1321-1 Chandler, D., Bailey, A. S., Mark Tatchell, G., Davidson, G., Greaves, J., & Grant, W. P. (2011). The development, regulation and use of biopesticides for integrated pest management. Philosophical Transactions of the Royal Society B, 366(1573), 1987–1998. https://doi.org/10.1098/rstb.2010.0390 Chernin, L., Brandis, A., Ismailov, Z., & Chet, I. (1996). Pyrrolnitrin production by an Enterobacter agglomerans strain with a broad spectrum of antagonistic activity towards fungal and bacterial phytopathogens. Current Microbiology, 32(4), 208–212. https://doi.org/10.1007/s002849900037 Chin-A-Woeng, T. F. C., Bloemberg, G. V., Van Der Bij, A. J., Van Der Drift, K. M. G. M., Schripsema, J., Kroon, B., … Lugtenberg, B. J. J. (1998). Biocontrol by phenazine-1- carboxamide-producing Pseudomonas chlororaphis PCL1391 of tomato root rot caused by Fusarium oxysporum f. sp. radicis-lycopersici. Molecular Plant-Microbe Interactions, 11(11), 1069–1077. https://doi.org/10.1094/MPMI.1998.11.11.1069 de Souza, J. T., Weller, D. M., & Raaijmakers, J. M. (2003). Frequency, diversity, and activity of 2,4-diacetylphloroglucinol-producing fluorescent Pseudomonas spp. in Dutch take-all decline soils. Phytopathology, 93(1), 54–63. https://doi.org/10.1094/PHYTO.2003.93.1.54 De Vrieze, M., Pandey, P., Bucheli, T. D., Varadarajan, A. R., Ahrens, C. H., Weisskopf, L., & Bailly, A. (2015). Volatile organic compounds from native potato-associated Pseudomonas as potential anti-oomycete agents. Frontiers in Microbiology, 6(1295). https://doi.org/10.3389/fmicb.2015.01295 Drotar, A., Burton, G. A., Tavernier, J. E., & Fall, R. (1987). Widespread occurrence of bacterial thiol methyltransferases and the biogenic emission of methylated sulfur gases. Applied and Environmental Microbiology, 53(7), 1626–1631. Dunham, M. (2017). Biological control global market overview. http://wrir4.ucdavis.edu/events/2017_SLR_Meeting/Presentations/GeneralPresentations/1 Trimmer - Global Biocontrol Market 2017.pdf Effmert, U., Kalderás, J., Warnke, R., & Piechulla, B. (2012). Volatile Mediated Interactions Between Bacteria and Fungi in the Soil. Journal of Chemical Ecology, 38(6), 665–703. https://doi.org/10.1007/s10886-012-0135-5 Frison, G., Zancanaro, F., Favretto, D., & Ferrara, S. D. (2006). An improved method for cyanide determination in blood using solid-phase microextraction and gas

chromatography/mass spectrometry. Rapid Communications in Mass Spectrometry, 20(19), 2932–2938. https://doi.org/10.1002/rcm.2689 Gallagher, L. A., & Manoil, C. (2001). Pseudomonas aeruginosa PAO1 kills Caenorhabditis elegans by cyanide poisoning. Journal of Bacteriology, 183(21), 6207–6214. https://doi.org/10.1128/JB.183.21.6207 Garbeva, P., Hordijk, C., Gerards, S., & De Boer, W. (2014a). Volatile-mediated interactions between phylogenetically different soil bacteria. Frontiers in Microbiology, 5(289). https://doi.org/10.3389/fmicb.2014.00289 Gueneron, M., Erickson, M. H., Vanderschelden, G. S., & Jobson, B. T. (2015). PTR-MS fragmentation patterns of gasoline hydrocarbons. International Journal of Mass Spectrometry, 379, 97–109. https://doi.org/10.1016/j.ijms.2015.01.001 Guevara-Avendaño, E., Bejarano-Bolívar, A. A., Kiel-Martínez, A. L., Ramírez-Vázquez, M., Méndez-Bravo, A., von Wobeser, E. A., … Reverchon, F. (2019). Avocado rhizobacteria emit volatile organic compounds with antifungal activity against Fusarium solani, Fusarium sp. associated with Kuroshio shot hole borer, and Colletotrichum gloeosporioides. Microbiological Research, 219, 74–83. https://doi.org/10.1016/j.micres.2018.11.009 Flaishman, M. A., Eyal, Z., Zilberstein, A., Voisard, C., & Haas, D. (1996). Suppression of Septoria tritici Blotch and Leaf Rust of Wheat by Recombinant Cyanide-Producing Strains of Pseudomonas putida. Molecular Plant-Microbe Interactions, 9(7), 642–645. Haas, D., & Défago, G. (2005). Biological control of soil-borne pathogens by fluorescent pseudomonads. Nature Reviews Microbiology, 3(4), 307–319. https://doi.org/10.1038/nrmicro1129 Han, S. H., Lee, S. J., Moon, J. H., Park, K. H., Yang, K. Y., Cho, B. H., … Kim, Y. C. (2006). GacS-dependent production of 2R, 3R-butanediol by Pseudomonas chlororaphis O6 is a major determinant for eliciting systemic resistance against Erwinia carotovora but not against Pseudomonas syringae pv. tabaci in tobacco. Molecular Plant-Microbe Interactions, 19(8), 924–930. https://doi.org/10.1094/MPMI-19-0924 Howell, C. R., & Stipanovic, R. D. (1979). Control of Rhizoctonia solani on cotton seedlings with Pseudomonas fluorescens and with an antibiotic produced by the bacterium by the soil tube method described previously. Phytopathology, 69(5), 480–482. Howell, C. R., & Stipanovic, R. D. (1980). Suppression of Pythium ultimum -Induced damping- off of cotton seedlings by Pseudomonas fluorescens and its antibiotic, pyoluteorin. Phytopathology, 70(8), 712. https://doi.org/10.1094/Phyto-70-712 Hunziker, L., Bönisch, D., Groenhagen, U., Bailly, A., Schulz, S., & Weisskopf, L. (2015). Pseudomonas strains naturally associated with potato plants produce volatiles with high potential for inhibition of Phytophthora infestans. Applied and Environmental Microbiology, 81(3), 821–830. https://doi.org/10.1128/AEM.02999-14 Infantino, A., Costa, C., Aragona, M., Reverberi, M., Taiti, C., & Mancuso, S. (2017). Identification of different Fusarium spp. through mVOCS profiling by means of proton- transfer-reaction time-of-flight (PTR-TOF-MS) analysis. Journal of Plant Pathology, 99(3), 663–669. https://doi.org/10.4454/jpp.v99i3.3953 Jordan, A., Haidacher, S., Hanel, G., Hartungen, E., Märk, L., Seehauser, H., … Märk, T. D. (2009). A high resolution and high sensitivity proton-transfer-reaction time-of-flight mass spectrometer (PTR-TOF-MS). International Journal of Mass Spectrometry, 286(2–3), 122– 128. https://doi.org/10.1016/j.ijms.2009.07.005

Keel, C., Schnider, U., Maurhofer, M., Voisard, C., Laville, J., Burger, U., … Defago, G. (1992). Suppression of root diseases by Pseudomonas fluorescens CHA0: Importance of the bacterial secondary metabolite 2,4-diacetylphloroglucinol. Molecular Plant-Microbe Interactions, 5(1), 4. https://doi.org/10.1094/MPMI-5-004 Khomenko, I., Stefanini, I., Cappellin, L., Cappelletti, V., Franceschi, P., Cavalieri, D., … Biasioli, F. (2017). Non-invasive real time monitoring of yeast volatilome by PTR-ToF-MS. Metabolomics, 13(10), 1–13. https://doi.org/10.1007/s11306-017-1259-y Kuppusami, S., Clokie, M. R. J., Panayi, T., Ellis, A. M., & Monks, P. S. (2015). Metabolite profiling of Clostridium difficile ribotypes using small molecular weight volatile organic compounds. Metabolomics, 11(2), 251–260. https://doi.org/10.1007/s11306-014-0692-4 Labows, J. N., McGinley, K. J., Webster, G. F., & Leyden, J. J. (1980). Headspace analysis of volatile metabolites of Pseudomonas aeruginosa and related species by gas chromatography- mass spectrometry. Journal of Clinical Microbiology, 12(4), 521–526. Laville, J., Blumer, C., Von Schroetter, C., Gaia, V., Défago, G., Keel, C., & Haas, D. (1998). Characterization of the hcnABC gene cluster encoding hydrogen cyanide synthase and anaerobic regulation by ANR in the strictly aerobic biocontrol agent Pseudomonas fluorescens CHA0. Journal of Bacteriology, 180(12), 3187–3196. Leahy, J., Mendelsohn, M., Kough, J., Jones, R., & Berckes, N. (2014). Biopesticide oversight and registration at the U.S. Environmental Protection Agency. In A. D. Gross, J. R. Coats, S. O. Duke, & J. N. Seiber (Eds.), Biopesticides: State of the art and future opportunities: ACS Symposium Series 1172 (pp 3–18). https://doi.org/10.1021/bk-2014-1172.ch001 Levy, E., Gough, F. J., Berlin, K. D., Guiana, P. W., & Smith, J. T. (1992). Inhibition of Septoria tritici and other phytopathogenic fungi and bacteria by Pseudomonas fluorescens and its antibiotics. Plant Pathology, 41(3), 335–341. https://doi.org/10.1111/j.1365- 3059.1992.tb02355.x Lo Cantore, P., Giorgio, A., & Iacobellis, N. S. (2015). Bioactivity of volatile organic compounds produced by Pseudomonas tolaasii. Frontiers in Microbiology, 6(1082). https://doi.org/10.3389/fmicb.2015.01082 Loper, J. E., Hassan, K. A., Mavrodi, D. V., Davis, E. W., Lim, C. K., Shaffer, B. T., … Paulsen, I. T. (2012). Comparative genomics of plant-associated Pseudomonas spp.: Insights into diversity and inheritance of traits involved in multitrophic interactions. PloS Genetics, 8(7). https://doi.org/10.1371/journal.pgen.1002784 Maleknia, S. D., Bell, T. L., & Adams, M. A. (2007). PTR-MS analysis of reference and plant- emitted volatile organic compounds. International Journal of Mass Spectrometry, 262(3), 203–210. https://doi.org/10.1016/j.ijms.2006.11.010 Martin, D. (2017). Investigation of the biocontrol activity in vitro and in planta of different Pseudomonas species against important crown, stem, foliar and root pathogens of ornamental crops. The Ohio State University [Thesis]. https://etd.ohiolink.edu/!etd.send_file?accession=osu1503063395390704&disposition=inline Mavrodi, O. V., Walter, N., Elateek, S., Taylor, C. G., & Okubara, P. A. (2012). Suppression of Rhizoctonia and Pythium root rot of wheat by new strains of Pseudomonas. Biological Control, 62(2), 93–102. https://doi.org/10.1016/j.biocontrol.2012.03.013 Mochalski, P., Unterkofler, K., Španěl, P., Smith, D., & Amann, A. (2014). Product ion distributions for the reactions of NO+ with some physiologically significant volatile organosulfur and organoselenium compounds obtained using a selective reagent ionization

time-of-flight mass spectrometer. Rapid Communications in Mass Spectrometry, 28(15), 1683–1690. https://doi.org/10.1002/rcm.6947 Moussa, S. G., Leithead, A., Li, S. M., Chan, T. W., Wentzell, J. J. B., Stroud, C., … Liggio, J. (2016). Emissions of hydrogen cyanide from on-road gasoline and diesel vehicles. Atmospheric Environment, 131, 185–195. https://doi.org/10.1016/j.atmosenv.2016.01.050 National Organic Program. (2020). 7 Code of Federal Regulations §205. https://www.ecfr.gov/cgi-bin/text- idx?SID=f8c63e05a49f815dc02a2a511584c15a&mc=true&node=pt7.3.205&rgn=div5 Ohga, T., Masduki, A., Kato, J., & Ohtake, H. (1993). Chemotaxis away from thiocyanic and isothiocyanic esters in Pseudomonas aeruginosa. FEMS Microbiology Letters, 113(1), 63– 66. https://doi.org/10.1111/j.1574-6968.1993.tb06488.x Ossowicki, A., Jafra, S., & Garbeva, P. (2017). The antimicrobial volatile power of the rhizospheric isolate Pseudomonas donghuensis P482. PloS ONE, 12(3), 1–13. https://doi.org/10.1371/journal.pone.0174362 Pang, X. (2015). Biogenic volatile organic compound analyses by PTR-TOF-MS: Calibration, humidity effect and reduced electric field dependency. Journal of Environmental Sciences, 32, 196–206. https://doi.org/10.1016/j.jes.2015.01.013 Perraud, V., Meinardi, S., Blake, D. R., & Finlayson-Pitts, B. J. (2016). Challenges associated with the sampling and analysis of organosulfur compounds in air using real-time PTR-ToF- MS and offline GC-FID. Atmospheric Measurement Techniques, 9(3), 1325–1340. https://doi.org/10.5194/amt-9-1325-2016 Pimentel, David, & Burgess, M. (2014). Environmental and economic costs of the application of pesticides primarily in the United States. In D. Pimentel & R. Peshin (Eds.), Integrated pest management:(pp. 47–71). https://doi.org/10.1007/978-94-007-7796-5 Phillips, J. B., & Xu, J. (1995). Comprehensive multi-dimensional gas chromatography. Journal of Chromatography A, 703(1–2), 327–334. https://doi.org/10.1016/0021-9673(95)00297-Z Raaijmakers, J. M., & Weller, D. M. (1998). Natural plant protection by 2,4- diacetylphloroglucinol-producing Pseudomonas spp. in Take-all decline soils. Molecular Plant-Microbe Interactions, 11(2), 144–152. https://doi.org/10.1094/MPMI.1998.11.2.144 Reaves, M. (2019). Pesticide registration review; proposed interim decisions for several pesticides; notice of availability. Federal Register, 84(222), 63650–63652. https://www.regulations.gov/document?D=EPA-HQ-OPP-2013-0242-0034 Rezzonico, F., Zala, M., Keel, C., Duffy, B., Moënne-Loccoz, Y., & Défago, G. (2007). Is the ability of biocontrol fluorescent pseudomonads to produce the antifungal metabolite 2,4- diacetylphloroglucinol really synonymous with higher plant protection? New Phytologist, 173, 861–872. https://doi.org/10.1111/j.1469-8137.2006.01955.x Rodriguez, F., & Pfender, W. F. (1997). Antibiosis and antagonism of Sclerotinia homoeocarpa and Drechslera poae by Pseudomonas fluorescens Pf-5 in vitro and in planta. Phytopathology, 87(6), 614–621. https://doi.org/10.1094/PHYTO.1997.87.6.614 Shestivska, V., Nemec, A., Dřevínek, P., Sovová, K., Dryahina, K., & Spaněl, P. (2011). Quantification of methyl thiocyanate in the headspace of Pseudomonas aeruginosa cultures and in the breath of cystic fibrosis patients by selected ion flow tube mass spectrometry. Rapid Communications in Mass Spectrometry, 25(17), 2459–2467. https://doi.org/10.1002/rcm.5146

South, K. A., Peduto Hand, F., & Jones, M. L. (2020). Beneficial bacteria identified for the control of Botrytis cinerea in petunia greenhouse production. Plant Disease, 104(6), 1801- 1810. https://doi.org/10.1094/pdis-10-19-2276-re Stiernagle, T. (2006). Maintenance of C. elegans. In WormBook: The online review of C. elegans biology, The C. elegans Research Community & Wormbook (Eds.), https://doi.org/10.1895/wormbook.1.101.1 Subedi, N., Taylor, C. G., Paul, P. A., & Miller, S. A. (2019). Combining partial host resistance with bacterial biocontrol agents improves outcomes for tomatoes infected with Ralstonia pseudosolanacearum. Crop Protection, 135(2020),104776. https://doi.org/10.1016/j.cropro.2019.03.024 Taiti, C., Marone, E., Lanza, M., Azzarello, E., Masi, E., Pandolfi, C., … Mancuso, S. (2017). Nashi or Williams pear fruits? Use of volatile organic compounds, physicochemical parameters, and sensory evaluation to understand the consumer’s preference. European Food Research and Technology, 243, 1917–1931. https://doi.org/10.1007/s00217-017-2898-y Taiti, C., Pandolfi, C., Caparrotta, S., Dei, M., Giordani, E., Mancuso, S., & Nencetti, V. (2019). Fruit aroma and sensorial characteristics of traditional and innovative Japanese plum (Prunus salicina Lindl.) cultivars grown in Italy. European Food Research and Technology, 245(12), 2655–2668. https://doi.org/10.1007/s00217-019-03377-y Thorn, R. M. S., Reynolds, D. M., & Greenman, J. (2011). Multivariate analysis of bacterial volatile compound profiles for discrimination between selected species and strains in vitro. Journal of Microbiological Methods, 84(2), 258–264. https://doi.org/10.1016/j.mimet.2010.12.001 Tripathi, R. K., & Gottlieb, D. (1969). Mechanism of action of the antifungal antibiotic pyrrolnitrin. Journal of Bacteriology, 100(1), 310–318. United States Environmental Protection Agency. (2018). Biopesticide active ingredients. https://www.epa.gov/ingredients-used-pesticide-products/biopesticide-active-ingredients van den Berg, R. A., Hoefsloot, H. C. J., Westerhuis, J. A., Smilde, A. K., & van der Werf, M. J. (2006). Centering, scaling, and transformations: Improving the biological information content of metabolomics data. BMC Genomics, 7(142). https://doi.org/10.1186/1471-2164-7- 142 Van Loon, L. C., & Bakker, P. A. H. M. (2006). Induced systemic resistance as a mechanism of disease suppression by rhizobacteria. In Z. A. Siddiqui (Ed.). PGPR: Biocontrol and biofertilization (pp. 39–66). Springer, Dordrecht. https://doi.org/10.1007/1-4020-4152-7_2 Vita, F., Taiti, C., Pompeiano, A., Bazihizina, N., Lucarotti, V., Mancuso, S., & Alpi, A. (2015). Volatile organic compounds in truffle (Tuber magnatum Pico): comparison of samples from different regions of Italy and from different seasons. Scientific Reports, 5, 12629. https://doi.org/10.1038/srep12629 Yuan, B., Koss, A. R., Warneke, C., Coggon, M., Sekimoto, K., & De Gouw, J. A. (2017). Proton-transfer-reaction mass spectrometry: Applications in atmospheric sciences. Chemical Reviews, 117(21), 13187–13229. https://doi.org/10.1021/acs.chemrev.7b00325 Yvon, M., & Rijnen, L. (2001). Cheese flavour formation by amino acid catabolism. International Dairy Journal, 11(4–7), 185–201. https://doi.org/10.1016/S0958- 6946(01)00049-8 Zhu, J., Bean, H. D., Kuo, Y. M., & Hill, J. E. (2010). Fast detection of volatile organic compounds from bacterial cultures by secondary electrospray ionization-mass spectrometry. Journal of Clinical Microbiology, 48(12), 4426–4431. https://doi.org/10.1128/JCM.00392-10

Figure 2.1. Top agar growth inhibition of F. oxysporum 289 by Pseudomonas spp. and Pantoea agglomerans strains. Inhibition of the fungus by a bacterium was assessed after a week of direct exposure. Values are presented as a proportion of growth as compared to the LB control. Each bacterium was tested in two independent assays, and the results of all assays were combined. n= 8 for each bacterium and 20 for the LB control. Data shown are mean± standard error. Bacteria are organized by species designation: P. br, P. brassicacearum; P. chl, P. chlororaphis; P. f, P. fluorescens; P. fr, P. frederiksbergensis; P. po, P. poae; P. pr, P. protegens; P. rho, P. rhodesiae; Pa. ag, Pantoea agglomerans. Due to large differences in standard deviation between the treatments, significant differences were determined using the Welch’s ANOVA for unequal variances followed by a post-hoc Game’s Howell Test (α 0.05). All treatments significantly inhibited growth of the fungus compared to the control (p<0.05).

Figure 2.2. Dual plating growth inhibition of F. oxysporum 289 by Pseudomonas spp. and Pantoea agglomerans strains. Inhibition of the fungus by a bacterium was assessed after a week of indirect exposure. Values presented are percentage of growth as compared to the LB control. Each bacterium was tested in two independent assays, and the results of all assays were combined. n= 8 for each bacterium and 20 for the LB control. Data shown are mean± standard error. Bacteria are organized by species designation: P. br, P. brassicacearum; P. chl, P. chlororaphis; P. f, P. fluorescens; P. fr, P. frederiksbergensis; P. po, P. poae; P. pr, P. protegens; P. rho, P. rhodesiae; Pa. ag, Pantoea agglomerans. Due to large differences in standard deviation between the treatments, significant differences were determined using the Welch’s ANOVA for unequal variances followed by a post-hoc Game’s Howell Test (α 0.05). Only treatments that are not significantly different from the control are shown and indicated with (A) (p<0.05).

Figure 2.3. Indirect volatile exposure inhibition of F. oxysporum isolates 289 (A) and 197 (B) with Pseudomonas spp. and Pantoea agglomerans strains. Inhibition of the fungus by a bacterium was assessed after a week of indirect exposure. Fusarium was exposed to the volatiles produced by each bacterium in a closed system. To account for differences between experiments, data presented are percentage of growth compared to the LB control. Growth was recorded as percentage of the petri plate area. Each bacterium was tested in two independent assays, and the results of all assays were combined. n= 7-8 for each bacterium and 16 for the LB control. Data shown are mean± standard error. Bacteria are organized by species designation: P. br, P. brassicacearum; P. chl, P. chlororaphis; P. f, P. fluorescens; P. fr, P. frederiksbergensis; P. po, P. poae; P. pr, P. protegens; P. rho, P. rhodesiae; Pa. ag, Pantoea agglomerans. Due to large differences in standard deviation between the treatments, significant differences were determined using the Welch’s ANOVA for unequal variances followed by a post-hoc Game’s Howell Test (α 0.05). Only treatments that are not significantly different from the control are shown and indicated with (A) (p<0.05).

(Figure 2.3 continued).

(Figure 2.3 Continued).

Figure 2.4. Indirect volatile exposure inhibition of F. oxysporum isolates 289 (A) and 197 (B) by Pseudomonas sp. and Pantoea agglomerans. Inhibition of the fungus by a bacterium was assessed after a week of indirect exposure. Fusarium was exposed to the volatiles produced by each bacterium in a closed system. Values presented are percentage of growth as compared to the LB control. Bacteria representing a species were pooled together. Each bacterium was tested in two independent assays. n= 8-32 for each bacteria species and 16 for the LB control. Data shown are mean± standard error. Significance between all treatments was determined using Welch’s ANOVA for unequal variances followed by a post-hoc Games-Howell test. Treatments with the same letter are not significantly different from each other (α=0.05).

(Figure 2.4 Continued).

Figure 2.5. Volatile activity against C. elegans by Pseudomonas spp. and Pantoea agglomerans. A rating scale of 0-4 was used to determine the nematicidal activity of bacterial volatiles against C. elegans: 0= 0 living C. elegans; 1= 1-20 living; 2= 21-100 living; 3= 101-200 living; and 4= greater than 200 living nematodes after a week-long indirect exposure assay. Bacteria are organized by species designation: P. br, P. brassicacearum; P. chl, P. chlororaphis; P. f, P. fluorescens; P. fr, P. frederiksbergensis; P. po, P. poae; P. pr, P. protegens; P. rho, P. rhodesiae; Pa. ag, Pantoea agglomerans. Each bacterium was tested in 2 separate experiments and combined. n= 9-10 per Pseudomonas and Pantoea strain, n=20 for the control treatments. Mean± standard error is shown. Significance between the treatments and controls was determined using the Kruskal-Wallis test followed by a post-hoc Dunn’s multiple comparisons test (α=0.05). Treatments not significantly different from LB control are marked with (*) and treatments not significantly different from the OP50 control are marked with (^) (p<0.05)

m/z 27.023 28.018 30.046 31.018 33.033 39.023 41.039 43.018 43.054 45.033 46.995 47.049 49.011 51.011 53.039 55.054 57.033 57.07 59.049 61.028 63.026 65.039 67.054 69.07 71.049 71.086 73.065 74.006 75.044 77.042 78.967 79.054 81.07 83.086 87.08 91.021 94.998 97.028 153.127 LB Control Wood3 P. br 93G8 37D10 14D6 P. chl 48G9 14B11 36F3 24D3 P. f 36G2-1 89F1 P. fr 39A2 29G9 P. po 36C8 15G2 38G2 P. pr 1B1 Darke 88A6 P. rho 90F12-1 Pa. ag MBSA-3BB1

log(n+1) Scale 0 3.5

Figure 2.6. Heat map showing the average intensities (ppbv) of 20 strains of Pseudomonas spp. and Pantoea agglomerans. Compounds at quantities >1 ppbv in every replicate of at least one bacterium or the LB control are included (39 compounds). Bacteria are organized by species designation: P. br, P. brassicacearum; P. chl, P. chlororaphis; P. f, P. fluorescens; P. fr, P. frederiksbergensis; P. po, P. poae; P. pr, P. protegens; P. rho, P. rhodesiae; Pa. ag, Pantoea agglomerans. n=2 or 3 for each bacterium and 6 for the LB control. Average values are displayed. Before averaging treatments, log(n+1) transformation was performed on the data set. This transformation was taken to better visualize differences due to the high range in abundance among compounds.

Figure 2.7. Cyanide and sulfur-containing compounds produced by the Pseudomonas spp. and Pantoea agglomerans. A) compounds are shown as ppbv, B) compounds are shown as % total volatiles produced by a bacterium or LB control. Compounds at quantities >1 ppbv in every replicate of at least one bacterium or the control (39 total) are included. Bacteria are organized by species designation: P. br, P. brassicacearum; P. chl, P. chlororaphis; P. f, P. fluorescens; P. fr, P. frederiksbergensis; P. po, P. poae; P. pr, P. protegens; P. rho, P. rhodesiae; Pa. ag, Pantoea agglomerans. n=2 or 3 for each bacterium and 6 for the LB control. Shown are the averages± standard deviation.

Figure 2.8. Hydrogen cyanide quantification by Pseudomonas spp. and Pantoea agglomerans strains + using either A) PTR-ToF-MS (H2CN , m/z 28.018) or B) a colorimetric semi-quantitative assay. Bacteria are organized by species designation: P. br, P. brassicacearum; P. chl, P. chlororaphis; P. f, P. fluorescens; P. fr, P. frederiksbergensis; P. po, P. poae; P. pr, P. protegens; P. rho, P. rhodesiae; Pa. ag, Pantoea agglomerans. Some of the strains as well as the LB controls (not included) do not produce a measurable amount of hydrogen cyanide. B) In the colorimetric assay LB samples were comparable to the blanks. Apart from 37D10 all cyanide producers were quantified in two independent assays and the results combined. Non-cyanide producers and 37D10 were quantified in one assay. n=2 or 3 (PTR-of-MS) and 3 or 6 (colorimetric assay). Shown are the averages ± standard deviation. cc= cubic centimeter.

Figure 2.9. Signal intensity of organosulfur compounds produced by 20 Pseudomonas spp. and Pantoea agglomerans strains. Compounds included were present at levels >1ppbv in every replicate of at least one bacterium or control. Bacteria are organized by species designation: P. br, P. brassicacearum; P. chl, P. chlororaphis; P. f, P. fluorescens; P. fr, P. frederiksbergensis; P. po, P. poae; P. pr, P. protegens; P. rho, P. rhodesiae; Pa. ag, Pantoea agglomerans. The LB controls produce a measurable about of organosulfur compounds and are also included in the figure. Each point is the average of n=2 or 3 biological replicates for each bacterium and n=6 control replicates. Averages values are shown, and average±standard deviation are included in Supplemental Table S21. Putative chemical + + formula and identity of the masses are m/z 46.995 (CH3S ); m/z 49.011 (CH5S , methanethiol/ DMDS + + + fragment); m/z 63.026 (C2H7S , DMS); m/z 74.006 (C2H4NS , methyl thiocyanate); m/z 77.042 (C3H9S , S- + + containing fragment); m/z 78.967 (CH3S2 , DMDS fragment); m/z 91.025 (C3H7OS , S-methyl thioacetate); + m/z 94.998 (C2H7S2 , DMDS).

Figure 2.10. Principal component analysis (PCA) biplots of 20 Pseudomonas and Pantoea strains and LB controls. Eight variables (m/z 28.018, 46.995, 49.011, 63.026, 74.006, 78.967, 91.021, 94.998) were used to construct the PCA. The first two Eigenvalues account for 75.5% of the variability within the data set. A) shows each bacterium and control colored differently to identify patterns among the bacteria; B) shows data points colored according to F. oxysporum 289 growth inhibition; C) shows data points colored according to F. oxysporum 197 growth inhibition. Inhibition indicates (100-% growth compared to LB controls). Volatile data were log(n+1) transformed and mean centered before performing the PCA. Each replicate for every treatment is shown as a point. n=2 or 3 for each bacterium or 6 for the LB control.

(Figure 2.10 Continued).

Table 2.1. Pseudomonas strain information. Included is species designation, source of collection, and potential for antimicrobial compound production based on presence of antibiotic gene clusters within the genome.

Antimicrobial Metabolite Strain Species a Source Potentialb Wood3 P. brassicacearum Ohio soil DAPG, HCN 93G8c P. brassicacearum Missouri soil DAPG, HCN 37D10 P. brassicacearum Wyoming soil HCN 14D6 P. chlororaphis Mississippi River HCN 48G9 P. chlororaphis Wisconsin soil HCN, PRN, PHZ 14B11 P. chlororaphis Missouri River HCN, PRN, PHZ 36F3 P. fluorescens Wyoming soil HCN 24D3 P. fluorescens Missouri Botanical Garden HCN herbarium collection 36G2-1 P. fluorescens Wyoming soil HCN 89F1 P. fluorescens Missouri soil HCN 39A2 P. frederiksbergensis Wyoming soil HCN 29G9 P. poae Missouri Botanical Garden herbarium collection 36C8 P. poae Wyoming soil 15G2 P. protegens Missouri River DAPG, HCN 38G2 P. protegens Wyoming soil DAPG, HCN 1B1 P. protegens Mississippi River DAPG, HCN, PRN, PLT DARKE P. protegens Ohio Soil DAPG, HCN, PRN, PLT 88A6 P. rhodesiae Missouri soil 90F12-1 P. rhodesiae Missouri soil MBSA-3BB1 Pantoea agglomerans unknown unknown aSamples from the herbarium collection were collected from the rhizosphere of frozen/dried plant tissue. bDAPG: 2,3-diacetylphloroglucinol; HCN: hydrogen cyanide; PRN: pyrrolnitrin; PHZ: phenazine; PLT: pyoluteorin. cGenome analysis done on clonally identical 93F8.

Table 2.2. Pearson’s correlation coefficients for the volatile compounds most positively correlated with fungal inhibition. The peak intensities (ppbv) were averaged and correlated with the average F. oxysporum 289 and 197 indirect exposure inhibition of each bacterium and the LB control. Average inhibition values were determined relative to the LB control. N.S indicates a compound was not significant for inhibition of the fungal isolates. aProtonated chemical formula was determined based on m/z

F. oxysporum 289 F. oxysporum 197 Protonated Chemical Pearson’s Pearson’s m/z a Tentative Identification p- p- Formula Correlation Correlation value value Coefficient Coefficient + 28.018 H2CN Hydrogen Cyanide 0.872 0.000 0.869 0.000 Methanethiol/DMS + 46.995 CH3S Fragment 0.533 0.013 0.679 0.001 Methanethiol/DMDS + 49.011 CH5S Fragment N.S. N.S. 0.551 0.010 51.010 Unknown Unknown Compound N.S. N.S. 0.545 0.011 + 74.006 C2H4NS Methyl thiocyanate 0.582 0.006 0.717 0.000 + 91.021 C3H7OS S-methyl thioacetate 0.475 0.030 0.533 0.013

100

Table 2.3. Inhibition of F. oxysporum 289 by HCN. The lethal dose of HCN to Fusarium was determined though indirect exposure assays. The concentrations in the table assume that the KCN was fully converted to HCN. Each treatment was tested in 2 independent assays and the results combined. n=6 for each treatment. NG indicates no growth and the only area determined was the area of the fungal plug.

0.09M Treatment Blank 2.59 ppm 5.19 ppm 10.37 ppm 20.75 ppm 41.49 ppm 82.99 ppm NaOH Average % Plate Area 67.83 65.24 54.44 47.55 7.04 NG NG NG Standard Deviation % 3.57 2.08 4.47 4.65 10.53 ------Plate Area

101

Supplemental Figure S2.1. In vitro inhibition assay setup. The top left image of a plate shows thicker inner growth (indicated with red dotted line) and total growth (indicated with black dotted line). The total hyphal growth area was used in measurements.

102

A) PCA with 55 compounds measured with PTR-ToF-MS. The first two Principal Components account for 42.4% of the variation in the data set when all compounds measured with PTR-ToF-MS are used.

Supplemental Figure S2.2. Variable reductive principal component analysis (PCA) of the volatile profiles produced by Pseudomonas spp. and Pantoea agglomerans strains. PTR-ToF-MS peak intensity data (ppbv) were preprocessed using a log(n+1) transformation followed by mean centering of the data. Multiple iterations of the PCA were performed, using multiple selection methods to select variables to use in the analysis. In this way, we were able to select variables accounting for the most variance in the data. Variable reduction was selected using multiple factors including peak abundance (ppbv), significance of the compound (ANOVA, α=0.05), variable weights within the PCA loading matrix, and targeted compounds of interest. A-F display the PCA score plots of the 21 bacteria and control treatments under multiple variable reductive selection guidelines and visualization methods. The specific selection parameters for each plot can be found above each plot.