Pseudomonas Entomophila 23S, a PGPR with Potential for Control of Bacterial

Pseudomonas entomophila 23S, a PGPR with potential for control of bacterial

canker disease in tomato (Solanum lycopersicum L.) against Clavibacter

michiganensis subsp. michiganensis

Yoko Takishita

Department of Plant Science

Faculty of Agricultural and Environmental Sciences

Macdonald Campus of McGill University

21111 Lakeshore Road, Stainte-Anne-de-Bellevue, Quebec H9X 3V9

May 2018

A thesis submitted to McGill University in partial fulfillment of the requiremnets of the degree

of DOCTOR of PHLOSOPHY

Table of Contents

Acknowledgements ...... v Abstract ...... x Résumé ...... xiii List of Tables ...... xvi List of Figures ...... xvii List of Appendices ...... xix Preface ...... xx Contributions of Authors ...... xx Contributions to knowledge ...... xxi Chapter 1 Introduction ...... 1 1.1. Introduction ...... 1 1.2. Objectives of this thesis ...... 4 Chapter 2 Literature review ...... 6 2.1. Tomato ...... 6 2.2. Tomato bacterial canker ...... 8 2.3. Clavibacter michiganensis subsp. michiganensis ...... 11 2.4. Pathogenicity of Cmm ...... 12 2.5. Plant defense responses to the pathogen...... 14 2.6. Induced systemic resistance (ISR) elicited by plant-growth-promoting-rhizobacteria (PGPR)...... 17 2.7. Molecular response of tomato plants to Cmm ...... 19 2.8. Control of bacterial canker ...... 22 2.9. Work in our laboratory ...... 25 Connecting text ...... 29 Chapter 3 Characterization of rhizobacterium Pseudomonas entomophila 23S having antagonistic activity against Clavibacter michiganensis subsp. michiganensis - a bacterial canker causing pathogen in tomato ...... 30 3.1. Abstract ...... 31 3.2. Introduction ...... 32 3.3. Materials and Methods ...... 34 3.4. Results ...... 42

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3.5 Discussion ...... 47 3.6 Conclusions ...... 58 3.7 Acknowledgements ...... 59 Connecting text ...... 77 Chapter 4 Isolation of antimicrobial compounds produced by Pseudomonas entomophila 23S against Clavibacter michiganensis subsp. michiganensis, a pathogen of tomato causing bacterial canker ...... 78 4.1. Abstract ...... 79 4.2. Introduction ...... 80 4.3. Materials and Methods ...... 82 4.4. Results ...... 89 4.5. Discussion ...... 93 4.6. Conclusions ...... 98 4.7. Acknowledgements ...... 99 Connecting text ...... 113 Chapter 5 The biocontrol rhizobacterium Pseudomonas entomophila 23S induces systemic resistance in tomato (Solanum lycopersicum L.), against bacterial canker Clavibacter michiganensis subsps. michiganensis ...... 114 5.1. Abstract ...... 115 5.2. Introduction ...... 116 5.3. Materials and Methods ...... 119 5.4. Results ...... 123 5.5. Discussion ...... 126 5.6. Conclusions ...... 131 5.7. Acknowledgements ...... 132 Chapter 6 Summary, discussion, conclusions and future research ...... 140 6.1. Summary of Results...... 140 6.2. General Discussion ...... 142 6.3. General Conclusions ...... 144 6.4. Future research directions ...... 144 Chapter 7 References ...... 146 Appendix: Supplemental information for Chapter 3 proteomics ...... 173

Acknowledgements

Although my undergraduate major was in agricultural sciences, my master’s research was on ecology, rather close to geography. When I started the PhD in McGill in 2012, my knowledge of plant science and my relevant laboratory skills were only at the undergraduate level, and most of them I had somewhat forgotten. A number of people have supported me and given me help during my PhD. Starting as such an immature scientist, I am completing this PhD project today.

This accomplishment would not be possible without the support of these generous, kind and wonderful people.

I cannot thank enough my supervisor Professor Donald Smith. Whenever I encountered hardships during my research, his constant positive attitude made me calm and relaxed, and often made me laugh, and I was able to carry on. His broad knowledge and experience taught me many lessons during my research, and he guided me to the right direction. Don cared not only about my research, but also my life here, in every matter. From this point of view, I am also grateful to his wife, Margareta. As I was away from my family, they understood my situation and supported me mentally and physically. Even with his hectic schedule, Don made himself available for calls, even during the weekends or late at night, whenever I had a problem. I met Don for the first time when I was taking his course during my undergraduate studies. Even a few years after this, he remembered me and invited me to join his laboratory for a PhD. I heartily appreciate being given this opportunity, allowing me to learn as a person.

I am deeply grateful to my co-supervisor Jean-Benoit Charron, who has given me valuable advice throughout the project. Whenever I had new ideas, questions, and challenges about my

v research, he listened to me. He was constructive and his suggestions were always to the point. He showed himself as a model for me regarding how to become a good scientist and professor.

I am very thankful to Guy Rimmer and Ian Ritchie for substantial technical support throughout my experiments. Although I was sometimes demanding, they continuously provided support around growth chamber and greenhouse use, even during the weekends.

My sincere gratitude also goes to Jim Fyles, my committee member. Although we did not have much time to talk, his opinions during my committee meetings provided me with new insights, and definitely contributed to the development of my research.

I would like to thank very much Lekha Sleno, and Leanne Ohlund from UQAM. As our laboratory HPLC was not able to purify my extracts completely, their participation was significant in discovering the novel compounds revealed during this project. Lekha and Leanne were both on maternity leaves during parts of the project, but they constantly provided help and spent time on the compound analysis and writing of that part of this thesis.

I am grateful to the team at IRCM, especially Denis Faubert and Marguerite Boulos, who handled my proteomic samples and conducted the proteomic analysis.

I wish to greatly thank Hélène Lalande, from the Natural Resource Science Department, for analyzing my plant tissue. Even in the face of my sometimes hasty requests, she was always willing to take her time and worked for me meticulously.

I am thankful to members of Department of Plant Science, many of whom I cannot, due to space limitations, name here. During my time here, I got to know a lot of people in the department; they always provided kind support to me whenever I needed it.

I am very grateful to all the members of my laboratory. I thank Alfred Soulemanov for teaching me about compound isolation and the use of HPLC. He was always helpful when I needed things in the lab, especially specific chemicals and information on equipment use. Thanks to his presence, I was able to enjoy working on Saturdays, when nobody else was in the lab. I thank

Sowmya Subramanian for her valuable suggestions. She has given me the benefit of her experience and knowledge through many discussions of my work, often forgetting the time because the conversations became so engrossing. She also contributed to my proteomic study, which was a new and challenging field for me. I was able to learn thanks to her thorough teaching approach. I thank Selvakumari Arunachalam for teaching me about compound extraction, when I had just joined the lab and was a bit overwhelmed and unsure where and how to start. She also supported me attitudinally, constantly providing cheering and positive words.

I thank Timothy Schwinghamer, Rachel Backer, Franziska Srocke, Gayathri Ilangumaran, Di

Fan, Jack Lamont, Olivia Harley and Werda Saeed for their kind help throughout my PhD. They are not only my best colleagues, but also my best friends. I enjoyed talking with them, and they always made me smile, whenever I was stuck and feeling discouraged during my PhD. At times they also provided help with my experiments, giving a hand when extensive labor was required and providing me with constructive suggestions. Werda was my trusted research assistant,

vii running the elemental analyzer for the plant tissue analysis, and watering growth chamber plants when I was away.

I am very grateful to Keomany Ker, Pratyusha Chennupati, Emily Ricci, and Tomona Morita, who had previously been working in our laboratory but have now left McGill. Keo provided much help in getting me ready for the comprehensive exam and also provided many helpful ideas regarding experiments. I learned many of laboratory techniques and skills from Pratyusha and Emily, and their hard-working attitudes always impressed and motivated me. Tomona

Morita, the only Japanese colleague I had, was a research assistant but for me was often more of a counselor, giving me strength to never give up.

I thank Dana Praslickova and Xiaomin Zhou for consideration and support during my PhD. Dana not only helped me with paperwork, but gave me valuable advice on my experiments as she has expertise in molecular work. Xiaomin was always amiable and encouraged me in my research and my life.

I am grateful to members of Prof. Jean-Benoit Charron‘s laboratory. I greatly thank Alexandre

Martel for teaching me about qPCR. Expertise for the gene expression study was something I had very much wanted to learn. Without his hands-on teaching, I would not have been able to learn the techniques so quickly and successfully. I also thank Boris, Gabriel and Jordan for their kind support whenever I was having difficulties in the molecular work.

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I would like to thank Sharon Rutherfold, my former landlord as well as a biology teacher at John

Abbot College. When I was living in her house, she was very caring in every matter and also gave me her thoughts whenever we discuss my experiments. Even after I moved out of her house, she always encouraged me and expressed interest in my progress with the PhD and also provided support around my overall wellbeing.

And last, but not least, I would like to give a big thanks to my family: my dad Toru, my mom

Junko, my sister Tomoko, and my brother Keishi. Thank you very much for allowing me to come to Canada. Their unending support, for almost 6 years, provided me courage and mental and physical strength to complete this PhD. Unfortunately, they were not able to visit during my

PhD; but, I am excited to share my success with them when I go home.

Abstract

Bacterial canker disease, caused by Clavibacter michiganensis subsp. michiganensis (Cmm) is one of the most destructive diseases of tomato. The disease can cause substantial crop losses and has become a serious concern for both field and greenhouse tomato production. Existing control strategies, such as seed treatment and chemical control, have shown only limited efficacy in controlling this disease. Thus, effective control strategies need to be developed. A bacterial strain that shows antagonistic activity against Cmm in vitro was isolated from the rhizosphere of soybean. This PhD project investigated the potential of this newly isolated anti-Cmm strain for control of bacterial canker and plant growth promotion in tomato. The work was broken into three sets of experiments, or studies. The goal of the first study was to characterize the anti-Cmm bacterium. The results showed that this strain is a strain of Pseudomonas entomophila. The strain, now designated 23S, was able to solubilize phosphorus, to produce siderophores, hydrogen cyanide, and indole acetic acid, to resist against several common antibiotics, and to inhibit the growth of other plant pathogens: Pseudomonas syryingae DC 3000 (bacterial speck),

Botrytis cinerea (gray mold), and Sclerotinia minor (lettuce drop disease). An in planta assay indicated that application of the P. entomophila 23S promoted the growth of tomato seedlings.

The bacterial exo-proteomic study revealed that P. entomophila 23S was under stress conditions when interacting directly with Cmm, as it secreted stress-related proteins such as chaperons, peptidases, ABC-transporters and elongation factors. The study demonstrated that P. entomophila 23S has significant potential as a plant growth promoting rhizobacterium (PGPR).

The goal of the second study was to isolate and characterize the anti-Cmm compounds produced by P. entomophila 23S. After butanol extraction, solid-phase-extraction (SPE), and purification by high-pressure-liquid-chromatography (HPLC), two anti-Cmm compounds were isolated. The

LC/MS spectra suggested that their molecular formulas were C15H17N2O and C16H19N2O and that the two compounds had a quinoline ring and differed in terms of a methyl group within the side chain. Analysis by nuclear magnetic resonance (NMR) spectroscopy was unable to resolve the complete structure and this remains the subject of future study. In addition, the effects of different growth media on the compound production were evaluated, and showed that the production of anti-Cmm compounds was largest with the nutrient broth media where P. entomophila 23S growth was slowest. This study provided new information around the two novel anti-Cmm compounds.

The goal of the third study was to investigate whether P. entomophila 23S could alleviate the severity of bacterial canker through induced systemic resistance (ISR), and to study the gene expression of PR1a, PI2, ACO, which are markers for salycilic acid (SA), jasmonic acid (JA) and, ethylene (ET), respectively. Under growth chamber conditions, two-week-old tomato plants were treated with P. entomophila 23S by soil drench and after 3, 5, and 7 days, were inoculated with Cmm, and grown for a further 3 weeks for the evaluation. The results showed that at 5 days: the disease progress was significantly delayed; the weights of dry shoots and roots, and the level of carbon, nitrogen and phosphorus in the leaf tissue were significantly higher; and, the Cmm population in the stem was significantly lower for plants treated with P. entomophila 23S. Real- time quantitative PCR (qPCR) analysis indicated that treatment with P. entomophila 23S alone increased transcript abundance of PR1a in tomato plants while no change was detected for PI2 and ACO. When the plants were treated with P. entomophila 23S and inoculated with Cmm, transcripts of PR1a and ACO were accumulated, and these responses were faster and stronger than for plants inoculated with Cmm but not treated with P. entomophila 23S. The study

xi indicated that P. entomophila 23S could induce ISR, where SA played roles in related signaling pathways.

Overall, this project demonstrated a meaningful potential for the newly isolated rhizobacterium

P. entomophila 23S to be used in tomato production.

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Résumé

Maladie bactérienne du chancre causée par Clavibacter michiganensis subsp. michiganensis

(Cmm) est l'une des maladies les plus destructrices de la tomate. La maladie peut causer d'importantes pertes des récoltes et elle est devenue une préoccupation sérieuse pour la production des tomates de plein champ et de serre. Les stratégies de la lutte existantes contre cette maladie, telles que le traitement des semences et le contrôle chimique, n'ont montré qu'une efficacité limitée. Cela veut dire que des stratégies de contrôle efficaces doivent être développées. Une souche bactérienne ayant montré une activité antagoniste contre Cmm in vitro a été isolée de la rhizosphère du soja.

Ce projet du doctorat visait à étudier le potentiel de cette souche anti-Cmm nouvellement isolée pour le contrôle du chancre bactérien et la promotion de la croissance des tomates. Le travail a

été divisé en trois séries d'expériences ou d'études. Le but de la première étude était de caractériser la bactérie anti-Cmm. Les résultats ont montré que cette souche est une souche de

Pseudomonas entomophila. La souche, maintenant nommée 23S, était capable de solubiliser le phosphore, de produire des sidérophores, du cyanure d'hydrogène et de l'acide indole acétique, de résister à plusieurs antibiotiques courants et d'inhiber la croissance d'autres pathogènes végétaux: Pseudomonas syryingae DC 3000 (tache bactérien) , Botrytis cinerea (moisissure grise) et Sclerotinia minor (maladie de laitue). Le test sur la plante a indiqué que l'application de

P. entomophila 23S favorisait la croissance des plantules de tomate. L'étude protéomique a révélé que P. entomophila 23S était soumis à des conditions de stress lorsqu'il interagissait directement avec Cmm, car il sécrétait des protéines liées au stress comme les chaperons, les peptidases, les transporteurs ABC et les facteurs d'élongation. L'étude a démontré que P. entomophila 23S possède un potentiel important en tant que bactérie favorisant la croissance des

xiii plantes (PGPR).

Le but de la seconde étude était d'isoler et de caractériser les composés anti-Cmm produits par P. entomophila 23S. Après extraction au butanol, extraction en phase solide (SPE) et purification par chromatographie liquide haute performance (HPLC), deux composés anti-Cmm ont été isolés. Les spectres LC / MS ont suggéré que leurs formules moléculaires étaient C15H17N2O et

C16H19N2O et que les deux composés avaient un cycle quinoléine et différaient en termes d'un groupe méthyle dans la chaîne latérale. L'analyse par spectroscopie de résonance magnétique nucléaire (RMN) n'a pas réussi à résoudre la structure complète et cela reste l'objet de futures

études. En outre, les effets de différents milieux de croissance sur la production de composés ont

été évalués, et ont montré que la production des composés anti-Cmm était la plus importante avec les milieux de bouillon nutritif où la croissance de P. entomophila 23S était la plus lente.

Cette étude a fourni des nouvelles informations sur les deux nouveaux composés anti-Cmm.

La troisième étude visait à déterminer si le P. entomophila 23S pouvait atténuer la sévérité du chancre bactérien par la résistance systémique induite (RSI) et étudier l'expression génique de

PR1a, PI2, ACO, qui sont des marqueurs de l'acide salicylique (AS), l'acide jasmonique (AJ) et l'éthylène (ET), respectivement. Dans les conditions de la chambre de croissance, des plants de tomate âgés de deux semaines ont été traités avec P. entomophila 23S par bassinage du sol et après 3, 5 et 7 jours, ont été inoculés avec Cmm et cultivés pendant 3 semaines supplémentaires pour l'évaluation. Les résultats obtenues après 5 jours ont montré que l'évolution de la maladie

était significativement retardée; le poids des pousses sèches et des racines, et les niveaux de carbone, d'azote et de phosphore dans le tissu foliaire étaient significativement plus élevés; et, la population Cmm dans la tige était significativement plus faible pour les plantes traitées avec le P. entomophila 23S. L'analyse quantitative en temps réel de la PCR (qPCR) a indiqué que le

xiv traitement avec le P. entomophila 23S seul augmentait l'abondance des transcrits de PR1a chez les plants de tomate alors qu'aucun changement n'était détecté pour PI2 et ACO. Lorsque les plantes ont été traitées avec P. entomophila 23S et inoculées avec Cmm, les transcrits de PR1a et

ACO ont été accumulés, et ces réponses ont été plus rapides et plus fortes que pour les plantes inoculées avec Cmm mais non traitées avec P. entomophila 23S. L'étude a indiqué que le P. entomophila 23S pourrait induire ISR, où SA a joué un rôle dans les voies de signalisation connexes. Dans l'ensemble, ce projet a démontré l'existence d'un potentiel significatif de la souche nouvellement isolée de la rhizobacterie P. entomophila 23S pour utiliser dans la production de tomates.

List of Tables Table 3.1 Shoot and root dry weights; root length, volume, diameter and surface area of tomato seedlings from control and P. entomophila 23S treatments ...... 60 Table 3.2 Total number of P. entomophila 23S proteins identified at 95 % protein probability and total spectra at 95 % peptide probability, with a minimum of two peptides: P. entomophila 23S was grown in NB media with and without Cmm ...... 61 Table 3.3 Protein grouping between categories, significant in contrasts based on Fisher’s Exact Test (p < 0.05): P. entomophila 23S was grown in NB media with and without Cmm ...... 62 Table 3.4 Pseudomonas entomophila 23S proteins, for which levels increased significantly when grown with Cmm. (Twenty proteins with greatest fold change) ...... 63 Table 3.5 Pseudomonas entomophila 23S proteins, for which level decreased significantly when grown with Cmm. (Twenty proteins with smallest fold change) ...... 64 Table 3.6 Total number of Cmm proteins identified at 95 % protein probability and total spectra at 95% peptide probability, with two minimum peptides: Cmm was grown in NB media with and without P. entomophila 23S ...... 65 Table 3.7 Protein grouping among categories, significant in contrasts based on Fisher’s Exact Test (p < 0.05): Cmm was grown in NB media with and without P. entomophila 23S ...... 66 Table 3.8 Cmm proteins, for which levels increased significantly when grown with P. entomophila 23S ...... 67 Table 3.9 Cmm proteins, for which level decreased significantly when grown with P. entomophila 23S (Twenty proteins with smallest fold change) ...... 68 Table 4.1 Anti-Cmm activity of SPE fractions ...... 100 Table 4.2 Predominant product ions seen in MS/MS spectrum of m/z 241 compound, showing elemental formulae for each confirmed by accurate mass data, and corresponding neutral losses ...... 101 Table 4.3 Predominant product ions seen in MS/MS spectrum of m/z 255 compound, showing elemental formulae for each confirmed by accurate mass data, and corresponding neutral losses ...... 102 Table 5.1 List of primers and sequences used for the gene expression study ...... 133 Table 5.2 Pseudomonas entomophila 23S treatment, 5-day prior to Cmm inoculation, reduced the Cmm population in the stem ...... 134

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List of Figures

Figure 2.1 Typical symptoms of tomato bacterial canker: a) stem discoloration, b) dead tomato plants, and c) stem canker...... 26 Figure 2.2 Disease cycle of Clavibacter michiganensis subsp. michiganensis ...... 27 Figure 3.1 Neighbor-joining tree constructed based on 16S rRNA sequencing of the anti-Cmm bacterium (inquiry = P. entomophila 23S) ...... 69 Figure 3.2 Antagonistic activity of P. entomophila 23S against other plant pathogens: (a) Pseudomonas syringe pv. tomato DC3000; (b) Botrytis cinerea; and, (c) Sclerotinia minor...... 70 Figure 3.3 Phosphorus solubilization assay of P. entomophila 23S ...... 71 Figure 3.4 Siderophore production assay of P. entomophila 23S on a chrome azurol S (CAS) agar plate ...... 72 Figure 3.5 Hydrogen cyanide (HCN) production of P. entomophila 23S ...... 73 Figure 3.6 Effects of antibiotics on the growth of the P. entomophila 23S ...... 74 Figure 3.7 Tomato seedlings and roots from control and P. entomophila 23S treatment...... 75 Figure 3.8 Population size (cells) for P. entomophila 23S and Cmm ...... 76 Figure 4.1 Anti-Cmm activity of butanol extract from the P. entomophila 23S culture ...... 103 Figure 4.2 Effects of 50, 60, 70 and 80 % SPE fractions on Cmm growth ...... 104 Figure 4.3 Extracted ion chromatograms from SPE fractions from P. entomophila 23S, Pseudomonas sp. KJ, and NB media for the two compounds of interest m/z 241, and 255, as protonated molecules (MH+): (A) 60 %, (B) 70 %, (C) 80 % SPE fraction ...... 105 Figure 4.4 High resolution MS/MS spectra for compounds found at m/z 241(a) and 255 (b)...... 106 Figure 4.5 Representative HPLC-UV chromatograms (at 265 nm) from semi-preparative purifications of SPE fractions (A) 60 % extract showing 3 fractions collected and (B) 70 % extract showing two fractions collected ...... 107 Figure 4.6 Representative high resolution extracted ion chromatograms (left) and mass spectra (right) from two fractions F1(a) and F2 (b) from 70 % SPE sample, collected by semi-preparative HPLC purification ...... 108 Figure 4.7 Anti-Cmm activities of HPLC fractions 1 and fraction 2 collected from 60 and 70 % SPE fractions...... 109 Figure 4.8 Anti-Cmm activity of butanol extracts prepared from different media...... 110

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Figure 4.9 Growth of P. entomophila 23S grown in different media...... 111 Figure 4.10 Overlaid extracted ion chromatograms of two biologically-active molecules in butanol extracts from P. entomophila 23S cultured in four different culture media...... 112 Figure 5.1 Pseudomonas entomophila 23S treatment, 5 days prior to Cmm inoculation, delayed progress of bacterial canker ...... 135 Figure 5.2 Pseudomonas entomophila 23S treatment, 5 days prior to Cmm inoculation, increased weights of shoots and roots ...... 136 Figure 5.3 Pseudomonas entomophila 23S treatment, 5 days prior to Cmm inoculation, improved nutrient levels of leaf tissue ...... 137 Figure 5.4 Pseudomonas entomophila 23S treatment induced an increase in the transcript level of PR1a ...... 138 Figure 5.5 Pseudomonas entomophila 23S treatment, 5 days prior to Cmm inoculation, induced faster and greater response in transcript levels of PR1a and ACO ...... 139

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List of Appendices

Appendix 1 Functional classification of GO distribution for P. entomophila 23S proteins grown in NB media with and without Cmm: a) Cellular component; b) Main Enzyme classes; c) Molecular function, and; d) Biological function ...... 173 Appendix 2 Functional classification of GO distribution for Cmm proteins grown in NB media with/without P. entomophila 23S: a) Cellular component; b) Main Enzyme classes; c) Molecular function, and; d) Biological function ...... 175 Appendix 3 Pseudomonas entomophila 23S proteins (not shown in the paper), for which level increased when grown with Cmm ...... 177 Appendix 4 Pseudomonas entomophila 23S proteins (not shown in the paper), for which level decreased when grown with Cmm ...... 178 Appendix 5 Pseudomonas entomophila 23Sproteins, for which level did not change when grown with Cmm ...... 185 Appendix 6 Cmm proteins (not shown in the paper), for which level decreased when grown with P. entomophila 23S ...... 186 Appendix 7 Cmm protein, for which level did not change when grown with P. entomophila 23S 209 Appendix 8 Nutrient composition of nutrient broth (NB), Kind’s B (KB), Luria Broth (LB) and Tryptic Soy Broth (TSB) ...... 210

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Preface

Contributions of Authors

Chapter 3

Yoko Takishita wrote the manuscript, and conducted and analyzed all the laboratory assays. For the proteomic experiment, LC/MS-MS assays was conducted at Institut de recherches cliniques de Montréal (IRCM), Quebec. Sowmya Subramanian contributed to analysis on the proteomic data. Donald Smith guided and supervised the overall study.

Chapter 4

Yoko Takishita conducted the laboratory work and wrote the manuscript, except for the section on compound identification, which was written by Dr. Sleno Lekha, a professor of chemistry at the University of Quebec at Montreal (UQAM). The HPLC and LC/MS-MS analyses were performed by Lekha Sleno’s laboratory at UQAM. Leanne Ohlund assisted with the LC/MS work, and Dr. Alexandre Arnold conducted NMR assessment. Donald Smith guided and supervised the overall study.

Chapter 5

Yoko Takishita wrote the manuscript, conducted the growth chamber experiments, gene expression studies, and analysis of the data. Jean-Benoit Charron and Donald Smith guided and supervised the overall study.

Contributions to knowledge

This PhD project contributed to knowledge in the following ways:

1. Characterization of an isolated anti-Cmm bacterium, a strain of Pseudomonas entomophila

(23S), revealed potential for the bacterium, not only as a biocontrol agent, but also as a

biofertilizer agent with general plant-growth-promoting properties.

2. Isolation and identification of anti-Cmm compounds contributed to the discovery of new

chemical compounds that inhibit the growth of Cmm, and possibly mitigate the tomato

bacterial canker disease that can be caused by this pathogen.

3. Evaluating the effects of P. entomophila strain 23S on tomato revealed its ability to induce

systemic resistance (ISR) and its effectiveness in controlling tomato bacterial canker disease.

4. Gene expression study of plants treated with P. entomophila 23S with and without Cmm

infection revealed pathways possibly involved for the induction of ISR by the this bacterium

5. The project created the potential for development of biopesticide products that contains the

bacterium or/and the anti-Cmm compounds it produces, to control bacterial canker disease

for the tomato production industry.

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Chapter 1 Introduction

1.1. Introduction

Plant diseases are challenging problems for global food production. They cause substantial reductions in crop yields, representing 10-16 % of the global harvest losses, at a total value of more than $200 billion each year (Oerke, 2006). Growing world population and changing diets will increase global food demand into the foreseeable future (Oerke and Dehne, 2004). Global food production must increase 50 % by 2050 to meet the projected demand of the world population (Chakraborty and Newton, 2011). This will not be achieved if yield losses from diseases remain at current levels (Oerke and Dehne, 2004) or even further increases under climate change conditions (Juroszek and Von Tiedemann, 2011).

Heavy use of synthetic agrochemicals is not a sustainable option. Plant disease control has relied mainly on synthetic chemicals as exemplified by a 15–20-fold increase in the amount of pesticides used worldwide over the last 50 years (Oerke, 2006). However, increasing public awareness of environmental and health issues associated with synthetic chemicals is causing a shift toward more sustainable crop management practices that rely less on these synthetic chemicals (Chandler et al., 2008). The European Union, USA and other countries have undertaken regulatory changes that reduced the number of registered active ingredients to those certainly unavoidable, more selective, less toxic and with lower negative environmental impact

(Montesinos, 2007). At the same time, many plant pathogens have evolved resistance to long- used chemical control measures (Lucas et al., 2011). As a result, some plant diseases of economic importance have become more difficult to control, due to the lack of effective compounds (Montesinos, 2007; Bailey, 2010).

Use of plant growth promoting rhizobacteria (PGPR) offers an ecological, and effective alternative to synthetic chemical treatments for managing plant disease problems. Microbes are associated with every part of plants, forming phytomicrobiomes (Smith et al., 2015). The rhizomicrobiome, located in and around the roots, or rhizosphere (Lundberg et al., 2012; Kishi et al., 2017) is the most populous and active of all those associated with higher plants (Quiza et al.,

2015). The PGPR members of this rhizomicrobiome are rhizosphere free-living bacteria that colonize plant roots and have beneficial effects on plant growth (Kloepper and Schroth, 1978;

Kloepper et al., 1989; Bouizgarne, 2013). Disease mitigation is one of these effects. Some PGPR serve as biocontrol agents because of their abilities to produce antimicrobial compounds against pathogens or/and to induce systemic resistance in plants, thus protecting the plants from the pathogens and alleviating the disease damages. In fact, pathogen-suppressing microorganisms, such as PGPR with biocontrol abilities, or their produced bioactive compounds, have been sold as biopesticides, and they have been increasingly researched, with markets expanding rapidly today (Ojiambo and Scherm, 2006). Such biopesticide products have the advantages of greater biodegradation, higher selectivity and non-target biological safety (Wang et al., 2011).

Resistance to these products, in target organisms, is not easily developed, unlike in many cases of their chemical counterparts (Mnif and Ghribi, 2015). Microorganism-based biological control is an important tool for managing disease problems in crop agriculture and achieving sustainable crop production.

Plant diseases are major constraints in tomato production. Especially, bacterial canker, caused by

Clavibacter michiganensis subsp. michiganensis (Cmm), which is one of the most destructive

2 diseases of tomato (Gleason et al., 1993; de León et al., 2011). The disease is reported in most tomato production in the world and causes substantial losses (Chang et al., 1992a). Despite the seriousness, no control methods are to be completely effective. As no Cmm-resistant cultivars are commercially available, current control primarily relies on the use of pathogen-free certified seeds and transplants, good hygiene, disinfection of all tools, and crop rotations (Xu et al., 2015).

Effective control methods for bacterial canker are urgently needed.

In an effort to search for effective control strategies for tomato bacterial canker, our laboratory isolated a strain of rhizobacterium that inhibited the growth of Cmm in vitro; the isolation procedures followed those described in Jung et al. (2014). The use of this isolated strain and the compound(s) it produces, is a novel mechanism for effective control of tomato bacterial canker.

The objective of this PhD project was to investigate the potential of an isolated anti-Cmm microbial strain (P. entomophila 23S) for control of bacterial canker and plant growth promotion in tomato. Three specific goals were set. The first goal was characterizing the isolated anti-Cmm strain. After confirming a potential for biocontrol as well as plant-growth promoting abilities of this anti-Cmm rhiozbacterium, the second goal was isolating and identifying the anti-Cmm compound(s) produced by this stain. Finally, the third goal was determining whether the application of P. entomophila 23S could induce systemic resistance in tomato plants, and studying its efficacy in the control bacterial canker.

1.2. Objectives of this thesis

This PhD project was divided into three studies. The first study was focused on characterizing the isolated strain showing antagonistic activity towards Cmm in vitro. The strain was first identified using 16S rRNA sequencing, and the characteristics that are important as a PGPR were investigated. These characteristics were abilities to: 1) solubilize phosphorous, 2) produce siderophores, hydrogen cyanide, and indole acetic acid, 3) resist against common antibiotics, and

4) inhibit the growth of other plant pathogens. In addition, plant assays were conducted to examine the growth-promoting effects of P. entomophila 23S application in tomato seedlings.

Lastly, bacterial exo-proteomics were explored by comparing the secreted proteins produced by

P. entomophila 23S when it is grown in presence and absence of Cmm.

The second study was focused on isolating and identifying the anti-Cmm compounds produced by P. entomophila 23S. The isolation and purification were achieved by solvent extraction, solid phase extraction and high-performance-liquid-chromatography, and liquid chromatography- tandem-mass-spectrometry, used for the final attempt at identification of the isolated compound.

Anti-Cmm activity was regularly checked by agar-disk diffusion assay during the isolation work.

As part of the isolation work, extracts were prepared when P. entomophila 23S was grown in different media; these extracts were evaluated for the anti-Cmm activity in order to help understand the conditions required for anti-Cmm compound production by P. entomophila 23S.

The third study aimed at determining whether the application of P. entomophila 23S could induce systemic resistance (ISR) in tomato plants, and studying the control efficacy for bacterial canker mitigation. Under controlled environment conditions (growth chamber), tomato plants

4 were treated with P. entomophila 23S, followed by Cmm inoculation, with different time- intervals between the dates of the anti-Cmm strain application and Cmm inoculation, in order to determine the time-interval that gave the most effective control of bacterial canker. Moreover, expression of the defense-related genes, specifically markers for threes hormones, salicylic acid, jasmonic acid and ethylene were analyzed in tomato plants treated with P. entomophila 23S and with and without Cmm inoculation, in order to help understand the ISR signaling pathways.

Chapter 2 Literature review

2.1. Tomato

Tomato (Solanum lycopersicum L.) is a dicotyledonous plant belonging to the family

Solanaceae. It originated from the Andean region of South America; tomato was first domesticated and used for food in Mexico (Labate et al., 2007; Blancard, 2012). The time of the domestication remains uncertain (Labate et al., 2007). At the time of Spanish conquest, during the 15th century, tomato was introduced to Europe. The Spanish introduced tomato to the

Philippines, from which it spread to the rest of Asia and throughout the world (Bai and Lindhout,

2007). Since the early 1870s, large scale breeding for economic traits has taken place in Europe and United States (Labate et al., 2007).

Cultivated tomato is a diploid, self-pollinating perennial herb (Girish and Umesha, 2005). It has compound leaves, fleshy fruits, and sympodial shoot branching (Ranjan et al., 2012).

Development can be either determinate or indeterminate, depending on cultivars. In general, it takes 3.5-4 months for tomato to grow: 6-8 weeks from seed sowing to blossoming and 7-8 weeks from blossoming to ripened fruit with seed formation (Blancard, 2012). The genome sequencing of tomato was completed in 2012 (The Tomato Genome Consortium, 2012). It revealed that the tomato genome sequences were approximately 900 Mbp in size and contain

34,727 protein-encoding genes aligned to the twelve chromosomes (Sato and Tabata, 2016).

Large germplasm collections consisting of numerous accessions of landraces of tomato and its wild relatives have contributed to development of modern cultivated tomato varieties (Ranjan et al., 2012).

Tomato is an important vegetable, consumed throughout the world. It is often called a functional food because of its high nutritional value (Canene-Adams et al., 2005). Especially, it is an essential source of lycopene, β-carotene, phenolic compounds, vitamin C, vitamin E, folic acid, and potassium (Luthria et al., 2006). In 2016, 177 million t of tomato was grown on about 4.7 million ha globally (FAO, 2017). Eaten either as fresh fruits or processed forms (e.g. ketchup, juice, canned, etc.), tomato has gained popularity especially during the last half-century (Preedy and Watson, 2008).

In Canada, tomato is produced both in field and greenhouses. The field area under tomato production was 5499 ha in 2015, with total production of 401,858 t while the total area under greenhouse tomatoes was 5,530,341 m2, with a total production of 266,845 t (Statistics Canada,

2016). Sixty percent of Canada’s production is for export, virtually all to the United States (Cook and Calvin, 2005).

In Canada, greenhouse tomato production has expanded significantly, with an almost tenfold increase from 1990 to 2010. Today, Canada is the largest producer of greenhouse tomatoes in

North America. Ontario is the biggest greenhouse tomato producer followed by British Columbia and Quebec (UC Davis, 2005; Statistics Canada, 2016). Through the use of artificial lighting systems, tomato is made available year-round in some provinces, such as in Quebec (Agriculture and Agri-Food Canada, 2006).

2.2. Tomato bacterial canker

Tomato plants are prone to bacterial diseases, for example: bacterial speck caused by

Psedomonas syringae pv. tomato, bacterial spot caused by Xanthomonas spp., bacteria wilt caused by Ralstonia solanacarum, and bacterial canker caused by Clavibacter michiganensis subsp. michiganensis (Davis et al., 1984; Labate et al., 2007; Blancard, 2012). Among these, bacterial canker is considered to be one of the most destructive bacterial diseases for tomato

(Gleason et al., 1993; de León et al., 2011).

Tomato plants affected by bacterial canker exhibit a variety of symptoms (Figure 2.1). Entry of the pathogen through trichomes, wounds or natural openings such as stomata and hydathodes

(Sharabani et al., 2013) leads to local infection, and initial symptoms are typically marginal necrosis of leaflets, which appear dried and curl upward. Generally, localized leaf symptoms can be seen within 3-5 days after the pathogen inoculation (Basu, 1966). The necrotic margin gradually widens leading to wilting of all leaves. Eventually, canker develops on the stems, which may generate small white blister-like spots (de León et al., 2011). Infected stems may show discoloration developed from internal necrosis (Sen et al., 2015). If the infection occurs at a late stage of plant development, the plants may survive and still produce fruits; however, these infected plants fail to fully develop the fruits, which are stunted, malformed and often ridged

(Utkhede and Koch, 2004). Fruits of the infected plants may develop distinctive raised white spots that later become dark-colored in the center with white halos – generally known as “bird’s- eye” lesions (Fatmi et al., 1991), and seeds could be contaminated with Cmm (Gleason et al.,

1993). Seed contamination could also occur through external fruit lesions of the exocarp (Tancos et al., 2013). The pathogen can infect the plants systemically through the vascular tissue of the

8 whole plant, leading to severe wilting. In systemic infections, the pathogen invades the xylem via wounds of roots or stem and spreads from xylem to nearby phloem and parenchyma cells where lysogenous cavities develop (EPPO/CABI, 1997). Systemic symptoms may take up to 80 days to appear (Strider, 1969). At early stages, the wilt is observed on unilateral leaves with eventual development of light yellow to brown streaks along diseased stems and on the underside of petioles. Infected plants wither, collapse and die early. Occasionally, localized infections progress into vascular bundles and lead to systemic symptoms (Gleason et al., 1993).

Environmental conditions, as well as plant age, inoculum concentration and cultivars, influence the severity of the disease. Warm temperature (23-28 °C) and high relative humidity (>80 %) maximize pathogen survival and disease development (Basu, 1966). Symptom development may be less severe at cooler temperatures and in older plants (Chang et al., 1992a). Typical greenhouse environments, which are warm, humid, with frequent overhead irrigation and closely spaced seedlings, favor the pathogen growth and disease development (Hausbeck et al., 2000).

Tomato bacterial canker occurs through several different infection routes (Kawaguchi et al.,

2010). Infected soils (Strider et al., 1967), seeds (Xu et al., 2010), transplants (Xu et al., 2010;

Chang et al., 1991), tomato debris in soils (Fatmi and Schaad, 2002), leaf-surface populations on alternative host plants and on non-host plants (Chang et al., 1992b), and operating tools and equipment (Yogev et al., 2009) are known as primary sources of the pathogen inoculum. In particular, infected seeds have been considered the major inoculum source leading to outbreaks and dissemination of Cmm infection (Tsiantos, 1987). A low transmission rate (~ 0.01% = a single infected seed in a seed lot of 10,000) from seed to seedlings can cause serious epidemics in fields, under favorable condition (Chang et al., 1991; Gitaitis et al., 1991). Inocula from the

9 primary sources can spread the infection to nearby healthy plants (Sharabani et al., 2013) via worker’s fingers and tools during tying, pruning, clipping, spraying and harvesting (Ark, 1944;

Gleason et al., 1993). Because tomato plants are handled many times during their growth, a few diseased plants can lead to a high level of secondary infection (Chang et al., 1992a).

Furthermore, latent infection and symptomless seedlings have been commonly reported, and in such cases outbreak could remain unnoticed for some time, hindering early control measures

(Chang et al., 1991; Gitaitis et al., 1991; Werner et al., 2002; Tancos et al., 2013). The disease cycle of Cmm is described in Figure 2.2.

Tomato bacterial canker has caused serious damage to both greenhouse and field tomato production worldwide. The disease was first reported in tomatoes grown in a greenhouse in

Michigan, USA in 1909 (Smith, 1914). At present, it can be found everywhere tomatoes are gown (Gleason et al., 1993; Menzies and Jarvis, 1994; Sen et al., 2015). In the last decade, many new outbreaks have been reported in many Asian countries (e.g. Japan), Europe (e.g. Italy), and

North and South America (e.g. US, Canada, Mexico, Guatemala), some of them occurring in the areas where Cmm had not been previously reported (de León et al., 2011; Xu et al., 2012).

Although the disease outbreak is sporadic, it can cause substantial economic losses. Yield losses as high as 50-80 % have occurred in the US, Canada and Kenya (Chang et al., 1992a). For example, 46 % (Chang et al., 1992a) to 93 % (Dhanvantari, 1989) yield losses were observed under experimental conditions. An outbreak caused economic losses of as much as $300,000 for one grower in a single year in processing tomato production in Michigan (Hausbeck et al., 2000).

2.3. Clavibacter michiganensis subsp. michiganensis

Clavibacter michiganensis subspecies are plant-pathogenic actinomycetes. Nine subspecies have been discovered (Nandi et al., 2018), among which five subspecies were well-known:

Clavibacter michiganensis subsp. sepedonicus (Cms), which causes ring rot in potato (Solanum tuberosum); Clavibacter michiganensis subsp. insidiosus, which causes wilting and stunting in alfalfa (Medicago sativa); Clavibacter michiganensis subsp. nebraskensis (Cmn), which causes wilt and blight of maize (Zea mays); Clavibacter michiganensis subsp. tessellarius (Cmt), which causes leaf freckles and leaf spot in wheat (Triticum aestivum); and Clavibacter michiganensis subsp. michiganensis (Cmm), which causes bacterial canker in tomato (Solanum lycopersicum)

(Eichenlaub and Gartemann, 2011).

The causal agent of tomato bacterial canker is Clavibacter michiganensis subsp. michiganensis

(Davis et al., 1984), commonly abbreviated as Cmm. Cmm is a slow-growing, gram-positive, nonmotile, nonspore-forming, aerobic, curbed, rod-shaped bacterium (Eichenlaub and

Gartemann, 2011). When grown in a culture media, it develops shining, mucoid, circular, yellow colonies with entire margins (Hayward and Waterston, 1964). Tomato is a primary host for Cmm although pepper (Capsicum annuum), bell pepper (Capsicum sativum) and eggplant (Solanum melongena) have been also reported to be naturally infected with Cmm in field (Yim et al.,

2012). As a pathogen, Cmm is mainly biotrophic and moderately necrotrophic (Garteman et al.,

2008). Cmm survives in soil for only relatively short periods of time (Eichenlaub et al., 2006); however, in association with plant debris, Cmm can survive in soil for 2-3 years (Gleason et al.,

1993; Fatmi and Schaard, 2002). Cmm is capable of multiplying and surviving both epiphytically on leaf surfaces (Chang et al., 1991; Sharabani et al., 2013) and endophytically within plant

11 tissue (Eichenlaub et al., 2006). Cmm can colonize tomato xylem both acropetally and basipetally, as shown by bioluminescent (Xu et al., 2010) and green fluorescent protein (GFP)- labeled Cmm (Chalupowicz et al., 2012). Inside the xylem, Cmm forms biofilm-like structures composed of large bacterial aggregates (Chalupowicz et al., 2012). Endophytic populations of

108 CFU g-1 of plant tissue can induce disease symptoms (Garteman et al., 2003).

2.4. Pathogenicity of Cmm

The genome sequencing for Cmm NCPPB382 (wild-strain; Cmm382) was completed in 2008

(Gartemann et al., 2008), an important step for understanding the molecular mechanisms of pathogenesis of Cmm. The genome size of Cmm382 is 3.3 M bp with 3,080 putative protein- encoding sequences. Major pathogenesis determinants in Cmm are plasmid-borne CelA and Pat-

1, and a chromosomal pathogenicity island (PAI).

Cmm 382 possesses two circular conjugative plasmids, pCM1 (27.4kb) and pCM2 (70kb). pCM1 carries the gene for CelA, a secreted cellulase with endo-β-1,4-glucanase activity (Jahr et al.,

2000), while pCM2 carries the gene for Pat-1, a putative serine protease (Dreier et al., 1997).

CelA and Pat-A are known to affect wilting symptoms but not the colonization to the host

(Eichenlaub et al., 2006). Loss of either of these two plasmids reduces virulence, whereas simultaneous loss of both plasmids results in a non-virulent endophytic strain (Cmm100) that can colonize tomato stems but does not cause any disease symptoms (Meletzus et al., 1993;

Gartemann et al., 2003). In addition to CelA, Cmm produces other extracellular cell wall degrading-enzymes (e.g., xylanase, pectate lyases, and polygalacturonase), which are thought to

12 be involved in degradation of cell walls in xylem vessels and thus responsible for impairment of water transport and consequent wilting (Gartemann et al., 2008).

Chromosomally encoded genes are critical for pathogenicity, especially for colonization and evasion or suppression of plant defense reactions (Eichenlaub and Gartemann, 2011). A single circular chromosome of Cmm is characterized by high G+C content (72.6%). A pathogenicity island (PAI; 129 kb) is located on a lower G+C content (65.5 %) region near the chromosomal origin of replication, also known as the chp/tomA region (Chalupowicz et al., 2012; Gartemann et al., 2008). The chp subregion harbors several genes encoding serine proteases as well as a few extracellular enzymes (two pectate lyases and a β-N-acetylglucosaminidase). The tomA subregion carries the tomA gene encoding a tomatinase, which deglycosylates and detoxifies the antifungal/antibacterial saponin α-tomatine produced by tomato plants. In addition, the tomA region contains numerous genes encoding glycosidases, putative sugar transporters, and regulators that may be involved in the utilization of plant-derived nutrients (Eichenlaub and

Gartemann, 2011; Flügel et al., 2012). Cmm27, a mutant lacking chp/tomA PAI, colonized the tomato xylem at a considerably lower population number than the wild type did and the lower population was not sufficient to induce disease symptoms even when virulence factors like CelA were present (Gartemann et al., 2008; Chalupowicz et al., 2010), implying that chp/tomA is essential for increased colonization, which is a prerequisite for inducing the disease in tomato plants (Gartemann et al., 2011). As for the tomato response, the expression of chitinase class II and pathogenesis-related protein-5 isoform, which were associated with defense response to pathogens, were significantly higher in Cmm27-inoculated plants than in the wild-type strain or

Cmm100, suggesting that chp/tomA PAI might be involved in suppression of tomato basal defenses (Chalupowicz et al., 2010).

Secretion of effectors into the apoplast and/or cytoplasm of the host are critical for phytopathogen suppression of host basal defense (Jones and Dangl, 2006). A proteomic study suggested that suspected virulence factors such as various serine proteases carry a signal peptide for secretion (Savidor et al., 2011). A recent study indicated that the ChpG, gene encoding putative serine proteases, was secreted into the apoplast of the plant leaves, and could be an elicitor of hyper-responsive reaction (HR) (Lu et al., 2015). For most gram-negative pathogenic bacteria, the type III secretion system (T3SS) is responsible for delivering the bacterial effectors.

However, Cmm lacks T3SS, and no genes encoding effector proteins resembling those in gram- negative pathogenic bacteria have been identified (Eichenlaub and Gartemann, 2011).

2.5. Plant defense responses to the pathogen

Plants possess layers of defense mechanisms against invading pathogens. Once pathogens enter plant tissues, microbial elicitor pathogen-associated molecular patterns (PAMPs), are detected by receptor proteins, plant pattern recognition receptors (PRRs). In addition to PAMPs, plants also respond to endogenous molecules from damaged cells called danger-associated molecular patterns (DAMPs). The perception of PAMPs/DAMPs by PRRs activates an immune response in plants, known as PAMP-triggered immunity (PTI). PTI induces multiple events such as: extracellular alkalization; stomatal closure; production of reactive oxygen species (ROS) known as oxidative burst; activation of mitogen activated protein kinases (MAPK) that induces many defense-related genes; hormone biosynthesis and, deposition of callose in the cell wall (Nicaise

14 et al., 2009; Segonzac and Zipfel, 2011). PTI contributes to a nonspecific resistance, which is a broad-spectrum resistance sufficient to block the majority of hostile microbes (Jones and Dangl,

2006; Boller and He, 2009; Lipka et al., 2005).

Virulent pathogens, however, are capable of suppressing PTI through deployment of effectors.

Effectors are molecules delivered into host cells by a pathogen (Göhre and Robatzek, 2008).

Effector delivery systems differ among pathogens. Bacteria possess secretion systems recognized as types I through VII. Among these, type II secretion system (T2SS), type III secretion system

(T3SS), and type IV secretion system (T4SS) are well known effector delivery systems related to pathogenesis and virulence. Effectors are important for pathogen virulence and promote penetration into host tissues, persistence inside the host, access to nutrients, proliferation, and growth (Göhre and Robatzek, 2008), and results in effector-triggered susceptibility (ETS) in plants. ETS reduces the plant’s immune response to basal levels of resistance, which cannot protect the plant against pathogens, but restricts its level of virulence (Ahmad et al., 2010).

As a counter move, plants have evolved effector recognition receptors (also called R proteins) to detect pathogen effectors, activating the immune response, called effector-triggered immunity

(ETI). Activated immune responses in ETI are qualitatively stronger and faster than those in PTI.

ETI often involves a vigorous type of defense reaction known as hypersensitive response (HR), characterized by rapid apoptotic cell death and local necrosis (Martin et al., 2003, Nimchuk et al., 2003), which can block virulent pathogens at relatively early stages of infection (Ahmad et al., 2010). Yet, the downstream immune responses of the PTI and ETI pathways are similar, including oxidative burst, hormonal changes, and transcriptional reprogramming (Tsuda and

Katagiri, 2010). Downstream responses to PTI and ETI involve accumulation of defense

15 hormones, such as salicyclic acid (SA), ethylene (ET) and jasmonic acid (JA), which play important roles in inducing systemic resistance in plants.

Two types of systemic resistance exist in plants: systemic acquired resistance (SAR) and induced systemic resistance (ISR), which are differentiated based on the nature of their elicitors and regulatory pathways involved (Choudhary et al., 2007). SAR is typically activated upon localized pathogen infection and triggers defense responses in the distal uninfected plant tissues to prime the plants against subsequent pathogen attack (Hammond-Kosack and Parker, 2003).

SAR signaling involves SA, resulting in the expression of a set of SAR-specific genes encoding for what are mostly known as pathogenesis-related proteins (PRs) with antimicrobial properties, such as chitinase and glucanase (Durrant and Dong, 2004; Pieterse et al., 2009). Mutants defective in SA signaling cannot activate the PRs genes and induce SAR upon pathogen infection (Durrant and Dong, 2004), indicating the critical role of SA in SAR activation. Another type of systemic resistance, ISR, is activated upon colonization of plant roots by beneficial microorganisms such as plant growth promoting bacteria (PGPR) and mycorrhizal fungi (Van

Loon et al., 1998; Pozo and Azcon-Aguilar, 2007). ISR establishes a primed state by inducing more rapid defense-response upon pathogen attack (Valenzuela-Soto et al., 2010). Unlike SAR,

ISR does not involve the accumulation of SA, but instead, its signaling depends on JA and ET

(Pieterse et al., 2009). While enhanced defense capacity by SAR is associated with the accumulation of PRs (Van Loon, 2007), ISR-mediated defense response does not necessarily involve accumulation of PRs (Wang et al., 2009). ISR results in the expression of defense-related genes that are JA- and ET-responsive (Choudhary et al., 2007). Both SAR and ISR are effective against broad ranges of pathogens (Van Loon et al., 1998; Durrant and Dong, 2004), and the

16 ranges partially overlap (Van Oosten et al., 2008). SAR is predominantly effective against biotrophic pathogens, whereas ISR is predominantly effective against necrotrophic pathogens that are sensitive to JA- and ET-dependent defenses (Ton et al., 2002).

2.6. Induced systemic resistance (ISR) elicited by plant-growth-promoting- rhizobacteria (PGPR)

ISR is an important trait for biocontrol abilities of PGPR: certain PGPR can trigger ISR in plants and make them less susceptible to subsequent infection by pathogen, thereby contributing the disease alleviation.

Molecular determinants that are responsible for ISR elicitation include sub-structures possessed by and/or compounds produced by the PGPR. To recognize PGPR, pattern recognition receptors

(PRRs) at plant roots detect microbe-associated molecular patterns (MAMPs; a term used for microbes in general, as opposed to PAMPs for pathogens), common microbial compounds, such as bacterial flagellin or fungal chitin (Boller and Felix, 2009; Zipfel, 2009; Pieterse et al., 2014a).

MAMPs of beneficial microbes and from pathogens are speculated to be recognized in a similar manner; how plants discriminate beneficial microbes and pathogens has not been fully understood (Henry et al., 2012). Among the MAMPS, flagellin, lipopolysaccharides, and peptidoglycan fragments were identified ISR elicitors (Mariutto and Ongena et al., 2015). In addition, compounds that are produced and secreted by PGPR, iron-regulated metabolites, salicylic acid, antibiotics, serves as a elicitor of ISR, together with or without the MAMPs

(Pieterse et al., 2014a; Mariutto and Ongena et al., 2015).

Downstream of the molecular recognition of PGPR, a cascade of signaling events takes place in plants, and plant hormones play a critical role. Typically, the signaling of the PGPR-induced ISR is thought to be dependent on (JA)/(ET), and differentiated from pathogen-induced-SAR in which signaling involves SA (Pieterse and Van Wees, 2015). Although their signaling pathways differ, both SAR and ISR require a regulatory protein nonexpressor of PR genes1 (NPR1)

(Pieterse et al., 1998) but its role must be different since SAR activation leads to activation of pathogensis-related (PR) genes, SA-responsive genes, while ISR activation does not (Pieterse et al., 2014b). MYB72, a transcription factor gene, is also implicated as being significant for onset of ISR in arabidopsis (Verhagen et al., 2004). However, increasing evidence suggests that signaling pathways differ depending on the type of PGPR, pathogens and host plants. ISR- inducing PGPR that use the SA-pathway, and not the JA/ET pathway, were reported in past studies (Maurhofer et al., 1994; De Meyer and Höfte, 1997; Maurhofer et al., 1998; Audenaert et al., 2002; Barriuso et al., 2008; van de Mortel et al., 2012). For example, in a study by Jiang et al. (2015), Bacillus cereus AR156 induced ISR in arabidopsis against Pseudomonas syringae

DC3000, simultaneously activating SA- and JA/ET-dependent signaling pathways, as well as

NPR1. In this system, the expression of MYB72 was not affected, and the other two transcription factors, WRK11 and WRKY70, were identified as key regulators of the ISR. As other plant hormones, such as gibberellins (Navarro et al., 2008), auxins (Kazan and Manners, 2009), cytokinins (Giron et al., 2013), and brassinosteroids (Nakashita et al., 2003) have also been demonstrated to function as modulators of the plant immune signaling network, hormone crosstalk is believed to exist, providing plants with capacity to finely tune immune responses for their growth and protection (Pieterse et al., 2014b).

ISR-induced plants are primed for future pathogen attack. Root colonization of PGPR does not always lead to major changes in defense-related genes of aboveground plant tissue (Pozo et al.,

2008; Van Wees et al., 2008; Verhagen et al., 2004; Wang et al., 2005; Pieterse et al., 2014a).

Up-regulation of defense-related genes occurs upon pathogen attack, and the response is faster and/or stronger in ISR-induced plants than non-induced plants (Van Wees et al., 1999). This phenomenon is called “priming” and is characterized by potentiated activation of cellular defenses upon pathogen or insect attack (Conrath et al., 2006; Frost et al., 2008). Such responses include oxidative burst (Iriti et al., 2003), cell-wall reinforcement (Benhamou and Bélanger,

1998;Van der Ent et al., 2009), and production of secondary metabolites (Yedidia et al., 2003; van de Mortel et al., 2012; Balmer et al., 2015), each of which contributes to augmentation of a plant’s defense capacity. Priming has been observed for a number of PGPR, and is thus regarded as a basis of the ISR-enhanced defensed capacity (Pieterse et al., 2014a). Activation of inducible defense presents a major fitness cost that can affect plant growth and reproduction (Heil, 2002).

In priming, the defense and its signal transduction are not activated before pathogen attack, and thus it does not confer major fitness costs under pathogen-free conditions (van Hulten et al.,

2006). Studies of the costs and benefits of priming indicated that benefits of induced resistance through priming outweigh the costs under disease pressure (van Hulten et al., 2006; Vos et al.,

2013; Walters et al., 2008)

2.7. Molecular response of tomato plants to Cmm

Relatively little is known about host plant responses to Cmm infection at a molecular level

(Eichenlaub and Gartemann, 2011; Balaji et al., 2011).

Upon Cmm infection, tomato plants display basal defense responses. Early studies indicated that

Cmm-infected tomato leaves accumulate phenolics (e.g. chlorogenic acid, cinnamic acid), tomatine (Beimen et al., 1992) and cell-wall strengthening proteins (hydroxyproline rich glycoproteins; Benhamou, 1991), which might play a protective role in the pathogen infection.

Yet, tomato plants infected with Cmm inevitably develop disease and thus, defense reactions are either too weak or too late to prevent the disease caused by the pathogen (Eichenlaub and

Gartemann, 2011). More recently, microarray analysis was conducted to study gene expression in Cmm-infected tomato plants (Balaji et al., 2008). The study showed that 122 out of 9,254 tomato genes were differentially expressed in Cmm-infected plants as compared with mock- infected plants. These genes were assigned to defense-related genes, production and scavenging of free oxygen radicals, enhancement of protein turnover and hormone synthesis, suggesting

Cmm activated the typical basal defense response in tomato plants.

Ethylene probably plays a critical role in induction of disease symptoms in tomato. Microarray analysis by Balaji et al. (2008) showed that Cmm infection induced the S1ACO1 gene, which encodes 1-aminocyclopropane-1-carboxylic acid oxidase (ACO). ACO is an enzyme that catalyzes the conversion of 1-aminocyclopropane-1-carboxylate (ACC) to ethylene, the final step of ethylene synthesis (Broekaert et al., 2006). Balaji, et al. (2008) further tested the disease’s development in tomato mutants, Never ripe which are impaired in ethylene perception; Cmm- infected mutants exhibited significant delay in appearance of wilt symptoms as compared with the wild-type plants, without altering expression of defense-related genes, reducing bacterial population, or decreasing ethylene synthesis.

The importance of ethylene in disease symptom development was also revealed by proteomic analysis on Cmm382-infected tomato plants (Savidor et al., 2011). This study of the tomato proteome during Cmm382 infection was characterized by the induction of proteins related to signal transduction (e.g. mitogen activated protein kinase 3, phospholipase D), pathogenesis- related (PR) proteins (e.g. 1,3-β-glucosidase), and other defense-related proteins (e.g. lipoxygenase-1 (LOX1)), suggesting that the plant sensed the invading pathogen and mounted a basal defense response. On the other hand, several proteins, typically associated with defense, including class III peroxidases and serine protein kinase, were reduced in abundance and thus, these proteins might be potential targets of active Cmm suppression. Correlated with transcriptional changes detected by microarray analysis (Balaji et al., 2008), ACO was induced in Cmm 322-infected plants. In contrast, ACO was not induced in response to Cmm100

(endophytic strain lacking two plasmids) and remained at similar levels to those observed in the mock-infected plants. Other than ACO, regulation patterns in Cmm100-infected plants were similar to those seen in Cmm322-infected plants (i.e. up-regulation of PR proteins and LOX1 and down-regulation of class III peroxidase), indicating that Cmm100 was recognized by the tomato plants, which triggered basal defense responses. Reduced ethylene production may be related to the lack of symptoms in Cmm100-infected plants.

Most recent studies discovered tomato proteins, which play a role in disease progress. Using

Nicotiana benthamiana-Cmm compatible interaction and virus-induced gene silencing, 6 genes, for which suppression led to more disease susceptibility and plant Cmm population, were identified (Balaji et al., 2011). These genes are encoding N. benthamiana homologs of: 1) ubiquitin activating enzyme; 2) snakin-2; 3) extensin-like protein; 4) divinyl ether synthase; 5) 3-

21 hydroxy-3-methylglutaryl-coenzyme A reductase 2, and; 6) Pto-like kinase. In a further study, the genes for snaking-2 and extension-like protein were over-expressed in tomato plants (Balaji and Smart, 2012). Snaling-2 is a cysteine-rich peptide, isolated from Solanum tuberosum cv.

Desireé that has been shown to have broad-spectrum antimicrobial activity in vitro (Segura et al.,

1999; Berrocal et al., 2002; Balaji and Smart, 2012). Extensin-like protein is a major cell-wall hydroxylproline-rich glycoprotein and has been shown to play a role in plant response to pathogen attack and wounding (Bowles, 1990; Balaji and Smart, 2012). These transgenic plants showed enhanced tolerance to Cmm, with delayed disease progress and smaller plant Cmm populations.

2.8. Control of bacterial canker

No methods have been found to be completely effective for bacterial canker disease control in tomato (Gleason et al., 1993; de León et al., 2011). Currently, no commercial cultivars resistant to Cmm are available (Eichenlaub et al., 2006; Balaji et al., 2011). Therefore, current control measures rely on the use of pathogen-free certified seed and transplants, good hygiene in the greenhouses, and disinfection of tools (Menzies and Jarvis, 1994; Xu et al., 2015). As a seed treatment, soaking with hot water for 30 minutes (Fatmi et al., 1991) and hydrochloric acid

(Dhanvantari, 1989) may partially control Cmm. The use of hot water, however, could reduce seed viability (Fatmi et al., 1991). Rotation away from tomato for three to five years is another option to remove Cmm from the soil, but it is not popular among producers due to required capital investments (Eichenlaub and Gartemann, 2011). Alternatively, soil treatments such as the use of formaldehyde and solarization (Antoniou et al., 1995; Shlevin et al., 2004) are often

22 practiced; however, the results are inconsistent due to recontamination from surrounding areas

(Eichenlaub and Gartemann, 2011).

Chemical control of Cmm relies on the use of antibiotics or copper containing compounds. In a study by Hausbeck et al. (2000), applications of copper hydroxide, copper hydropxide/mancozeb and streptomycin/copper hydroxide to tomato seedling in the greenhouse prevented development of severe canker symptoms and yield loss. However, the use of antibiotics or copper compounds is considered to be only partially effective (de León et al., 2008; Sen et al., 2015) and has raised concerns over safety, environmental problems, and evolution of resistance. The use of bacteriophage-encoded endolysins that specifically lyse Cmm (Wittmann et al., 2010) has been proposed as a new approach to control Cmm, although it has not yet been widely implemented

(Eichenlaub and Gartemann, 2011).

Interest in biological control of Cmm is growing as an alternative to chemical controls. PGPR having antagonistic activities towards Cmm have been isolated and studied (Aksoy et al., 2017;

Lanteigne et al., 2012; Amkraz et al., 2010, Deng et al., 2015; Romero et al., 2003; Boudyach et al., 2001). Although not all of these studies investigated the mechanisms of the biocontrol in detail, the major mechanism is most likely to have been the anti-Cmm activities of the PGPR as inoculated Cmm and the PGPR were directly in contact. The biocontrol mechanism of

Pseudomonas spp. LBUM330 was explained by the production of 2,4- diacetylphloroglucinol

(DAPG) and hydrogen cyanide (HCN) (Lanteigne et al., 2012). DAPG and HCN are well known antimicrobial metabolites produced by Pseudomonas species and have been largely studied and characterized (Haas and Keel, 2003). In Cmm-infected tomato plants, occurrence of the disease

23 was significantly reduced by treatment with the strain LBUM330, but not with its mutant strains of DAPG (LBUM300phlD-) and HCN (LBUM300hcnC-), suggesting that simultaneous

DAPG/HCN production by Pseudomonas sp. LBUM300 was involved in its control mechanism.

For another species, Pseudomonas putida (CKPp9) (Aksoy et al., 2017) provoked ISR. This ISR was accompanied by induction of significant amounts of phenolic compounds, which contributed to the disease reduction.

Apart from PGPR, various biocontrol agents were studied for efficacy of Cmm control. Plant activators such as propolis (Basim et al., 2006), resinous exudates (Modak et al., 2004), rhizome extracts (Özdemir and Erincik, 2015) and essential oils (Daferera et al., 2003; Kizil et al., 2005;

Kotan et al., 2013) have shown in vitro efficacy. Utkhede and Koch (2004) showed that treatments with bacteria-based commercial products, Quadra 136 and Quadra 137 (B. subtilis),

RootShield® (Trichoderma harzianum), S33 (Rhodosporidum diobovatum), as well as lysozyme, vermicompost tea, applied as a spray prevented the disease incidence under greenhouse. Yogev et al., (2009) reported that compost based on tomato or pepper residues combined with cattle or chicken manure reduced canker disease between 79-100 % following both natural infection and intentional inoculation. Anti-Cmm activities were observed from the extracts of red imported fire ants, piperidine and piperideine alkaroids, and spray treatments with piperidine alkkaloids reduced symptom development in tomato seedlings in the greenhouse (Li et al., 2013). Barda et al. (2015) showed that extracellular metabolites secreted by Pseudozyma aphidis, yeast-like fungi is inhibitory to Cmm in vitro, and the application of Pseudozyma aphidis on tomato plants in a greenhouse significantly reduced the incidence of disease. They also demonstrated that the control mechanism was systemic, and involved the SA pathway.

2.9. Work in our laboratory

Our laboratory has been working to develop PGPR-based technologies for agriculture. As a part of our work on finding new PGPR (Jung et al., 2014), we isolated a rhizobacteria that inhibited the growth of Cmm in vitro (Figure 2.3).

Figure 2.1 Typical symptoms of tomato bacterial canker: a) stem discoloration, b) dead tomato plants, and c) stem canker. (Taken from Sen et al. (2015))

Figure 2.2 Disease cycle of Clavibacter michiganensis subsp. michiganensis (modified from Eichenlaub et al. (2006) and de León et al. (2011))

Figure 2.3. Anti-Cmm activity of newly isolated bacterium One hundred µL of Cmm culture was spread on Nutrient Broth Yeast Extract (NBYE) agar. A sterile filter-paper-disk (6 mm diameter) was placed on the agar surface. Five µL of the newly isolated bacterium culture (on the right), and Nutrient Broth (on the left) were applied on the respective disks. The plate was sealed with parafilm and incubated at 28 °C for 2 days. Zone of inhibition = 5 mm

Connecting text

Anti-Cmm activity of the newly isolated bacterial strain in vitro suggested the potential of this strain to be used as a biocontrol agent and/or plant growth promoting rhizobacterium (PGPR).

Therefore, I decided to study this bacterial strain, first by identifying what it is and testing the traits that are relevant as a PGPR, in order to explore its potential.

Chapter 3 Characterization of rhizobacterium Pseudomonas entomophila

23S having antagonistic activity against Clavibacter michiganensis subsp. michiganensis - a bacterial canker causing pathogen in tomato

Authors: Yoko Takishita1, Sowmyalakshmi Subramanian1, Donald L. Smith1

Affiliations:

1Department of Plant Science, McGill University, Macdonald Campus, 21,111 Lakeshore Road,

Sainte-Anne-de-Bellevue, Quebec, Canada, H9X 3V9

3.1. Abstract

Plant growth promoting rhizobacteria (PGPR) are free-living bacteria that colonize plant roots, impart beneficial effects on plant growth and play important roles in achieving sustainable crop production. For this study, we have isolated a rhizospheric bacterium that shows antagonistic activity against Clavibacter michiganensis subsp. michiganensis (Cmm), which causes bacterial canker disease in tomato. This newly isolated anti-Cmm bacterium was characterized to explore its potential for use in greenhouse and field tomato production. The bacterium has been identified as a strain of Pseudomonas entomophila by 16S rRNA sequencing. This strain, designated P. entomophila 23S, is able to solubilize inorganic phosphate, and to produce indole acetic acid, siderophore and hydrogen cyanide. The strain is resistant to several antibiotics and also inhibited the growth of other plant pathogens such as Pseudomonas syringe DC3000

(bacterial speck), Botrytis cinerea (gray mold) and Sclerotinia minor (lettuce drop). A plant assay indicated that P. entomophila 23S could promote tomato seedling growth in the absence of

Cmm. A comparative exo-proteomic study showed that when P. entomophila 23S is grown with

Cmm, it secretes stress-related proteins, chaperons, peptidases, ABC-transporters and elongation factors. The results of our study demonstrated that the newly isolated strain P. entomophila 23S has a meaningful potential to be used as a multi-functional PGPR in plant growth promotion, including through reduction of plant pathogen pressures, in this case Cmm.

3.2. Introduction

Plant growth promoting rhizobacteria (PGPR) are rhizosphere free-living bacteria that colonize plant roots and have beneficial effects on plant growth (Kloepper and Schroth, 1978; Kloepper et al., 1989; Bouizgarne, 2013). Agronomically, PGPR effects are of particular interest (Gray and

Smith, 2005). The use of PGPR can replace chemical fertilizers, pesticides and other supplements. PGPR play important roles in achieving sustainable crop production

(Bhattacharyya and Jha, 2012). To date, diverse bacteria have been identifies as PGPR; examples being, members of the genera of Azospirillum, Pseudomonas, Acetobacter, Burkholderia,

Bacillus, Paenibacillus, and some members of the Enterobacteriaceae (Reddy, 2014), among which Pseudomonas and Bacillus are predominant (Podile and Kishore, 2007).

Impacts, actions and mechanisms of PGPR have been extensively studied and reviewed

(Lugtenberg and Kamilova, 2009; Dutta and Podile, 2010; Pieterse et al., 2014a; Beneduzi et al.,

2012; Jha and Saraf, 2015). PGPR can enhance plant growth by various mechanisms. One direct mechanism is the provision of nutrients to plants. A well characterized example of PGPR that provides nitrogen is rhizobia, which form a symbiosis with legume plants (Gray and Smith,

2005). Some PGPR are phosphate solubilizers and provide phosphorus, another essential macronutrient for plant growth. Others may produce iron-chelating siderophores and make iron available to the plants. Several PGPR are reported to produce hormones, such as indole acetic acid (IAA), gibberellic acid and cytokinin, which alter root architecture and support plant development (Bhattacharyya and Jha, 2012; Dodd et al., 2010; Idris et al., 2007). Indirect mechanisms of PGPR action involve protection of plants from phytopathogens (reviewed in

Siddiqui, 2005; Beneduzi et al., 2012). Many PGPR are capable of synthesizing antimicrobial compounds, for instance, secondary metabolites such as hydrogen cyanide (HCN) and 2,4- disacetylphloroglucinol (DAPG). Bacteriocins and lipopeptide biosurfactants, which are quite proteinaceous, also inhibit the growth of certain phytopathogens and have been reported to account for biocontrol activity of PGPR (de Bruijn et al., 2007; Raaijmakers et al., 2010). For the

PGPR, such a trait may be important for their survival in competitive rhizospheric environments

(Haas and Keel, 2003). Another indirect mechanism of PGPR is induced systemic resistance

(ISR), where the PGPR colonization enhances defensive capacity of the entire plant and establishes primed state against subsequent pathogen attack (Valenzuela-Soto et al., 2010).

Clavibacter michiganensis subsp. michiganensis, abbreviated as Cmm, is a gram-positive bacterium that causes bacterial canker, one of the most destructive diseases in tomato (Glesason et al., 1993; de León et al., 2011). Cmm invades the plants through wounds and natural openings such as stomata and hydathodes after which they move to the xylem and multiplies rapidly

(Carlton et al., 1998; Gartemann et al., 2003; Sharabani et al., 2013). Initial symptoms appear as marginal leaf necrosis, which widens and leads to wilting of all leaves while canker develops on the stem, and the whole plants can be stunted, severely wilted and dead (de León et al., 2011).

The disease is reported in most tomato production in the world and causes substantial crop losses both in the greenhouses and in the field (Chang et al., 1992a; Kawaguchi and Tanina, 2014).

A new strain of rhizobacterium that inhibited the growth of Cmm in vitro was isolated in our laboratory. The objective of this study was to characterize this newly isolated stain of anti-Cmm bacterium to explore the potential for its use in agriculture. The new isolate was first identified

33 and studied for important traits as PGPR, such as abilities to solubilize phosphorous; siderphore,

IAA, and HCN production; resistances to antibiotics; antagonistic activities against phytopathogens, other than Cmm; and effects on tomato seedlings. In addition, a bacterial exo- protomic study was conducted. Not only after host cell contact in planta, Cmm was shown to secrete virulence factors, Pat-1 and CelA into minimal media and xylem mimicking medium

(Hiery et al., 2015). Given the anti-Cmm activity of the isolated strain, studying proteomic changes during interaction between the two bacteria, in comparison with solitary growth of each, may help understand the anti-Cmm strain and its antagonistic nature against Cmm.

3.3. Materials and Methods

3.3.1. Bacterial growth condition

The anti-Cmm strain was grown in Nutrient Broth (NB, Difco; 8 g/L) media at 28 °C, with shaking at 100 rpm. Cmm strain 930 (Cmm) was provided by Agriculture, Pecheries et

Alimentation, Quebec. Cmm was grown in NB media at 28 °C, with shaking at 150 rpm.

3.3.2. Identification of anti-Cmm bacterium by 16S rRNA sequencing

Sanger sequencing was conducted for the 16S rRNA region of the anti-Cmm strain at the McGill

University Genome Québec Innovation Center, using universal primers 27F (5’-

AGRGTTYGATYMTGGCTCAG-3’) and 1064R (5’-CGACRRCCATGCANCACCT-3’).

Samples were diluted in water (1/10) and 1 µL of the dilution was used for the PCR with the Fast

HotStart enzyme (Kapa Biosystems). Purified PCR products were subjected to Sanger sequencing, which used Big Dye Terminator V3.1 (Applied Biosystems) (initial denaturation

96°C for 1 min, followed by 25 cycles of 96 °C for 10 sec, 50°C for 5 sec, and 60°C for 4 min,

34 and held at 4°C). The sequencing reactions were read on a 3730xl DNA Analyzer (Applied

Biosystems). The results were compared with published 16S rRNA sequences by using a Basic

Local Alignment Search Tool (NCBI) using Nucleotide Blast (blastn) with 16S ribosomal RNA sequences (Bacteria and Archaea) database. The sequence from the anti-Cmm strain and those from closely related species were aligned with ClustalW Multiple Alignment, and the phylogenetic analysis was performed by using MEGA 6 software (Tamura et al., 2013). The phylogenetic tree was constructed with maximum likelihood method. The phylogeny was evaluated with 1000 bootstrap replications.

3.3.3. Antagonistic activity against other plant pathogen

Antagonistic activity of the anti-Cmm stain were assessed against three plant pathogens,

Pseudomonas syringae pv. tomato DC3000 (provided by Dr. Diane Cuppels, AAFC, London),

Botrytis cinerea and Sclerotinia minor (provided by Dr. Alan Watson, McGill university).

Pseudomonas syringe was grown in Kings B media or 2 days. One hundred µL of P. syringae pv. tomato DC3000 culture was spread on each Kings B agar plate. For B. cinerea and S. minor, a disk of fungal culture were placed on the center of Potato dextrose agar plate (39 g L-1). A sterile filter-paper disk, with 10 µL of the anti-Cmm strain culture was spotted on the disk and placed in the center of each pathogen inoculated plate, and the plates was sealed with parafilm and incubated for at least 2 days at 28 °C to observe development of inhibition zones.

3.3.4. Phosphorus solubilization assay

Pikovskaya medium (PVK; per L distilled H2O: Glucose 10 g, Ca3(PO4)2 5 g, (NH4)2SO4 0.5 g,

NaCl 0.2 g , MgSO4•7H2O 0.1 g, KCl 0.2 g, yeast extract 0.5 g, MnSO4•H2O 0.002 g,

FeSO4•7H2O 0.002 g, Agar 15 g) (Pikoviskaya, 1948) and National Botanical Research

Institute’s phosphate growth medium (NBRIP; per L distilled H2O: Glucose 10 g, Ca3(PO4)2 5 g,

MgSO4•7H2O 0.25 g, KCl 0.2 g, (NH4)2SO4 0.1 g, Agar 15 g) (Nautiyal, 1999) were used to determine if the anti-Cmm strain had phosphorus solubilization ability. The two types of plates were used to corroborate the results since the PVK plate could sometime give variable results

(Nautiyal, 1999). A sterile filter-paper-disk (6-mm-diameter) was placed on the agar plates, and

10 µL of 2-day culture of anti-Cmm bacterium was spotted on the filter paper disk. For the control, the same volume of nutrient broth media was used. The plates were incubated for at least

2 days to observe halo formation. The quantitative assay was also performed following the Fiske and Subbarow method (Fiske and Subbarow, 1925). The anti-Cmm bacterium was grown in the

NBRIP media (the above recipe excluding the agar; Nautiyal, 1999) for 2 days at 28 °C, with shaking at 100 rpm. The NBRIP broth was used because it was shown to be more efficient than

PVK broth (Nautiyal, 1999). The culture was then filter-sterilized (0.22 um, mixed cellulose ester filter, Millipore Corp.), centrifuged at 12,000 rpm for 3 min, and the supernatant was mixed with Barton reagent followed by spectrophotometric measurement at 430 nm (Ultrospec 4050

Pro UV/Visible Spectrophotometer, LKN). The values were computed with reference to a standard curve generated with potassium dihydrogen orthophosphate.

3.3.5. Siderophore production assay

To determine if our anti-Cmm strain produce siderophores, a chrome azurol S (CAS) assay was conducted based on the methods by Alexander and Zuberer (1991). Anti-Cmm strain was grown in M9 minimum media (per L of distilled H2O: M9 salts (5X) 200 mL, glucose (20 %, w/v) 20 mL, MgSO4 (1M) 2 mL, CaCl2 (1M) 100 µL) for 2 days at 28 °C, at 100 rpm, and 10 µL of this

36 culture was spotted on a sterile filter paper disk, which was placed on a CAS agar plate. M9 minimum media was used as the control. The plate was sealed with parafilm and incubated for at least 2 days at 28 °C. A color change of the CAS agar, from blue to orange, indicated the production of siderophores. To quantitatively assess the siderophore production, the anti-Cmm strain was grown in M9 minimum medium as described above. The culture was then centrifuged and filter-sterilized (0.22 um, mixed cellulose ester, Millipore Corp.). The supernatant was treated with CAS assay solution and the optical density at 630 nm was measured (Alexander and

Zuberer, 1991; Schwyn and Neilands, 1987). Percent siderophore production was calculated by using the following formula:

% siderophore production = (Ar-As)/Ar × 100

Where, Ar represents the absorbance of reference (CAS assay solution plus growth medium) at

630 nm and As represents the sample (CAS assay solution plus bacterial supernatant) at 630 nm

(Ghosh et al., 2015).

3.3.6. Hydrogen cyanide (HCN) production

Since glycine is a precursor of HCN and needed for its production (Knowles, 1976; Askeland and Morrison, 1983; Schippers et al., 1991), the anti-Cmm strain was grown in Kings B medium

(per L of distilled H2O: proteose peptone No.3 20 g, glycerol 10 mL, K2HPO4 1.5 g, MgSO4 1.5 g), in which glycerin serves as a precursor molecule. The production of HCN was assessed by using the method described in Nandhini et al. (2012), with slight modification. One hundred µL of the anti-Cmm strain was spread over on a Kings B agar plate, and on underside of the lid of the petriplate, a filter paper soaked in alkaline picrate solution (2 % sodium carbonate in 0.5 %

37 picric acid solution, w/v) was placed. The plate was incubated for at least 2 days at 28 °C, and the color was observed. A color change from yellow to orange indicated production of HCN.

3.3.7. Indole acetic acid (IAA) production

To determine whether the anti-Cmm strain would produce IAA, the strain was first grown in 25 mL of NB medium with 0.5 g L-1 and 1.0 g L-1 of DL-tryptophan (TM 7425 Sigma), which served as a precursor of IAA, for 5 days at 28 °C, with shaking at 100 rpm, and the culture was then centrifuged to remove all cells. The supernatant was mixed with Salkowski reagent (0.5M

FeCl2•6H2O in 12 M H2SO4), incubated for 45 min., and the optical density at 525 nm was measured. The values were computed with reference to a standard curve of IAA (Gordon and

Weber, 1951; Deaker et al., 2011).

3.3.8. Resistance to antibiotics

Antibiotic resistance of the anti-Cmm bacterium was studied for eight antibiotics: 1) ampicillin,

2) chloramphenicol, 3) kanamycin, 4) rifampicin, 5) gentamycin, 6) penicillin, 7) streptomycin, and 8) tetracycline, based on the broth microdilution method, as described by Wiegand et al.

(2008). The antibiotic concentrations ranged from 0.5 to 256 µg mL-1. Briefly, the anti-Cmm bacterial culture (adjusted for 5×105 cfu mL-1 in NB media) was mixed with each concentration of antibiotics prepared in a 96-well plate. The anti-Cmm strain, in the NB medium without any antibiotics, served as a growth control while the NB medium without antibiotics or the anti-Cmm strain served as a sterile control. The plate was incubated with agitation at 28 °C for 20 h while the optical density at 600 nm was measured every 2 h with a Gen5TM Biotek microplate reader

(Biotek Inc.). The data were analyzed by SAS package program version 9.4 (SAS institute Inc.,

Cary, NC, USA) using the proc-mixed model, with time-points and concentrations as fixed effects. Tukey’s test was applied for multiple comparisons for the least square means when there is a significant treatment effect at the 95 % confidence level (p < 0.05). The minimum inhibition concentration (MIC) was defined as the lowest concentration where the bacterial growth was significantly different from the growth control samples.

3.3.9. Plant assay

A plant assay was conducted to study the effect of anti-Cmm strain on tomato seedlings. Tomato seeds (Bush Beefsteak 351; Stroke Seeds Inc. Thorold, ON, Canada) were surface-sterilized by soaking with 3 % (v/v) hypochlorite solution for 3 minutes, washing thoroughly with water, and drying overnight. The seeds were sown in pots (7.5 mm diameter; 2 seeds pot-1) filled with a mix of sand and turface (5:5). The pots were washed with bleach, and a mix of sand and turface was autoclaved prior to use. The seedlings were thinned to leave 1 plant pot-1 after emergence. After

7 days from the day of seeding, 50 mL suspension of the anti-Cmm strain (10-8 cfu mL-1 in 10 mM MgSO4) was applied to each pot as a soil drench. For the control treatment, 50 mL of 10 mM MgSO4 was applied to each pot. The seedlings were grown in a growth chamber with a

14/10 h photoperiod and a 25/23 °C day/night temperature. Sterilized water was applied as needed. After 3 and 7 days from the date of anti-Cmm bacterial treatment (10 and 14-day-old seedlings), the population of the anti-Cmm bacteria around the roots was enumerated. For this, the seedling was pulled up from the soil, shaken to remove the soil as much as possible, and the root cut from the plant. The root was then ground with a mortar and pestle in 500 µL of 10 mM

MgSO4. The solution was centrifuged (10,000 rpm, 1 min) to remove the debris, and 100 µL of its serial dilution was plated on Pseudomonas Isolation Agar plates (PIA; Difco). The plates

39 were incubated overnight at 28 °C, after which the number of colonies formed was counted.

After 11 days from the date of anti-Cmm bacterial treatment (18-day-old seedlings), the whole plants were harvested. The shoots were dried in an incubator for 2 days at 60 °C and shoot dry weight was determined. The roots were first scanned (Modified Epson Expression 10000XL,

Regent Instruments Inc., Quebec, Canada) at 400 dots per inch (dpi) resolution and then, images were analyzed by using WinRhizo software (Reagent Instuments Inc.) to study the morphological features and later used for determination of root dry weight. There were 5 biological replicates per treatment and each time point for the population study, and there were 7 biological replicates for the dry weight study. The experiment was conducted twice. A student’s t-test was applied to determine significant differences between control and bacterial treatments.

3.3.10. Proteomic study

To examine the secreted proteins, three-day culture (108 cfu mL-1) of the anti-Cmm strain in

Nutrient broth (NB) was centrifuged at 4 ºC, at 10,000 rpm (15,180 g; SLA-1500) on a Sorvall

Biofuge Pico (Mandel Scientific, Guelph, ON, Canada) for 10 minutes, to separate the bacterial supernatant from the bacterial cells. Total proteins were extracted from the supernatant using trichloroacetic acid (TCA; T9151, Sigma Aldrich) precipitation. One hundred % (w/v) TCA was added to the bacterial supernatant to a final concentration of 25 %. The solution was mixed, kept at -20 ºC for one hour, and placed on an orbital shaker at -4 ºC, with shaking at 90 rpm (MBI,

Montreal Biotech Inc., Canada) overnight, to allow for protein precipitation. It was then centrifuged at 4 ºC, with shaking at 10,000 rpm for 10 minutes, and the supernatant was discarded to obtain a protein pellet. The protein pellet was washed several times with ice-cold acetone, air-dried under a laminar hood and dissolved in 8 M urea (U4883, Sigma Aldrich). The

40 protein concentration was determined by the Lowry assay (Lowry et al., 1951) using bovine serum albumin as the standard. For comparison, the proteins produced by the anti- Cmm strain, in the presence of Cmm, were also studied. For this, the culture of the anti-Cmm strain and Cmm were mixed (each containing 108 cfu mL-1) and incubated for 3 days at 28 °C, with shaking at

100 rpm. The protein extraction was conducted as described above.

Protein profiling analysis was performed by liquid chromatography tandem mass spectrometry

(LC-MS/MS) at the Institut de Recherches Cliniques de Montreal (IRCM) in Montreal. Ten μg of the protein sample dissolved in 20 μL of 2 M urea was sent for analysis. The protein extracts were digested with trypsin and analyzed by LC-MS/MS equipped with LTQ-Velos Orbitrap

(Thermo Fisher, MA, USA). Subsequent analysis for the protein identification was performed as described by Subramanian et al. (2016). The obtained mass spectra datasets were searched against a Pseudomonas entomophila database for the anti-Cmm bacterium and against

Clavibacter michiganensis database for the Cmm, respectively, using Mascot software (Matrix

Science, London, UK). The Mascot search was performed with a fragment ion mass tolerance of

0.60 Da, a parent ion tolerance of 15 ppm, carbamidomethyl of cysteine as a fixed modification, and oxidation of methionine as a variable modification. Scaffold software (version Scaffold

4.8.3, Proteome Software Inc., Portland, OR) was used to validate the MS/MS based peptides and protein identification. Peptide identifications were accepted if they could be established at greater than 95 % probability, as specified by the Peptide Prophet algorithm (Keller et al., 2002).

Protein identifications was be accepted if they could be established at greater than 95 % probability assigned by the Protein Prophet algorithm (Nesvizhskii et al., 2003) and contained at least 2 identified peptides. Scaffold was also used for quantification of the protein based on

41 spectra count values. The spectral count values were normalized, and an analysis of variance

(ANOVA) test was performed to detect differential abundance among the treatments at the 95 % confidence level (p < 0.05). The FASTA file generated was analyzed by Blast2GO-Pro Version

4.1 for the functional annotation and analysis of the protein sequences, while enzyme code (EC),

KEGG maps and InterPro motifs were queried directly using the InterProScan web service.

3.3.11. Number of colony forming units of each bacteria during interaction

To understand the population number of each bacterium during the interaction, colony forming units (cfu) of each bacterium was enumerated. The anti-Cmm strain and Cmm was grown individually for the first 3 days as described above. For each day, the serial dilutions of the bacterial culture was plated on Nutrient Broth Yeast Extract (NBYE; per L distilled H2O: 8.0 g nutrient broth, 2.0 g yeast extract, 2.0 g K2HPO4, 0.5 g KH2PO4, 5.0 g Glucose, 0.25 g

MgSO4•H2O and 15 g agar) agar plates. After three days, the two bacteria were mixed, each containing 108 cfu mL-1, as done for the proteomics, and grown together for another 3 days. For each day, the serial dilutions of the mixture were plated on Pseudomonas isolation agar plates

(Difco # 292710) and Cmm-selective plates (Ftayeh et al., 2011) to enumerate cfu of anti-Cmm strain and Cmm, respectively.

3.4. Results

3.4.1. Anti–Cmm bacterium is identified as a strain of Pseudomonas entomophila

A blast search of 16S rRNA sequences indicated that the anti-Cmm bacterium was most similar to Pseudomonas entomophila L48 (Accesssion number: NR_102854), with highest scoring match with 99% identity (Figure 3.1). We designated our strain Pseudomonas entomophila 23S.

3.4.2. P. entomophila 23S showed antagonistic activity against other plant pathogens

Antagonistic activity of P. entomophila 23S against three plant pathogens, Pseudomonas syringe pv. tomato DC 3000, Botrytis cinerea and Sclerotinia minor were assessed. Pseudomonas entomophila 23S inhibited the growth of all the three pathogens as indicated by inhibition zones around the disk (Figure 3.2a; the size of the inhibition zone by the P. syringe was 4 mm).

Pseudomonas entomophila 23S inhibited the growth of Botrytis cinerea (Figure 3.2b) and

Sclerotinia minor (Figure 3.2c), and the zone of inhibition was asymmetric.

3.4.3. Pseudomonas entomophila 23S solubilized inorganic phosphorus

Pikovskaya (PVK) and National Botanical Research Institute’s phosphate growth medium

(NBRIP) were used to determine whether P. entomophila 23S had phosphorus solubilization ability. In both PVK and NBRIP plates, the P. entomophila 23S inoculation resulted in a halo around the disk (Figure 3.3; approximately 1 mL added to each plate). The broth assay showed that P. entomophila 23S solubilized 5.84 µg mL-1 (± 0.85) of inorganic phosphorus.

3.4.4. Pseudomonas entomophila 23S produced siderophores

In the siderophore assay, P. entomophila 23S changed the blue color of the chrome azurol S

(CAS) plate to orange (Figure 3.4; size of halo was 4 mm). The quantitative assay showed that its production is 50.7 % (± 3.38).

3.4.5. Pseudomonas entomophila 23S produced hydrogen cyanide (HCN)

For the hydrogen cyanide assay, the negative control plate, where media had been applied, was bright yellow (Figure 3.5a) whereas the positive control plate, where HCN-positive bacterium had been applied, was blight orange (Figure 3.5c). Pseudomonas entomophila 23S containing plate was neither this bright yellow nor bright orange, but rather light orange color (Figure 3.5b).

3.4.6. Pseudomonas entomophila 23S moderately produced indole acetic acid (IAA)

To study whether P. entomophila 23S would produce IAA, two concentrations of tryptophan, 0.5 g mL-1 and 1.0 g L-1, were used as a precursor. The quantitative assay indicated that the anti-

Cmm strain produced 1.96 µg IAA mL-1 (± 0.09) at 0.5 M tryptophan and 2.72 µg IAA mL-1 (±

0.07) at 1.0 g L-1 tryptophan.

3.4.7. Pseudomonas entomophila 23S showed resistance against several common antibiotics

Antibiotic resistance of P. entomophila 23S was studied for eight antibiotics: ampicillin (Figure

3.6a); chloramphenicol (Figure 3.6b); kanamycin (Figure 3.6c); rifampicin (Figure 3.6d); gentamycin (Figure 3.6e); penicillin (Figure 3.6f); streptomycin (Figure 3.6g); and, tetracycline

(Figure 3.6h). The antibiotic concentrations ranged from 0.5 to 256 µg mL-1. For seven antibiotics, excluding penicillin, the minimum inhibitory concentration was 1 µg mL-1: the bacterial growth at all the concentrations differed significantly from control growth. For penicillin, the MIC was 256 µg mL-1 (Figrue 3.6f). For five of the seven antibiotics (ampicillin, chloramphenicol, rifampicin, streptomycin and tetracycline), growth was affected in a concentration dependent manner (Figure 3.6a, b, d, g, h). No growth was observed: at the concentrations of 256 and 512 µg mL-1 for ampicillin and chloramphenicol; at concentrations of

16 to 512 µg mL-1 for rifampicin; at concentrations of 64 to 512 µg mL-1 for the streptomycin; and, at concentrations of 8 to 512 µg mL-1 for the tetracycline. For kanamycin and gentamycin, no growth was observed at any of the concentrations tested (Figure 3.6c, e).

3.4.8. Pseudomonas entomophila 23S promoted growth of tomato seedlings

Pseudomonas entomophila 23S was applied as a soil drench and its effect on the growth was examined for tomato seedlings. As Figure 3.7 shows, P. entomophila 23S treated seedlings were visually bigger, and the dry weights of their shoots and roots were significantly higher

(approximately 47 % increase) than those of control seedlings. Roots of P. entomophila 23S treated seedlings appeared finer and longer than the roots of control seedlings. Based on the root scanning analysis, root length, volume, and surface area from the P. entomophila 23S treated seedlings were significantly greater than those of control seedlings (Table 3.1).

To assess the root colonization ability, P. entomophila 23S (50 mL of suspension with 108 cfu mL-1 root-1) was applied to tomato seedlings as a soil drench, and after 3 days and 7 days, the viable number of P. entomophila 23S cells around the root was enumerated. The number of bacteria was, 105.08 (± 0.12) and 105.49 (± 0.14) colony forming units per seedling after 3 days and

7 days, respectively.

3.4.9. Pseudomonas entomophila 23S proteins decreased, with changes in proteomic profile after, Cmm interaction

Secreted proteins of P. entomophila 23S were studied by comparing two conditions: when it was grown in the NB media (Pe) and when it was grown in the NB media with Cmm (PeC). The total number of proteins was decreased under PeC compared with Pe: the total number of proteins

45 identified at 95 % probability was 369 and 142 for Pe and PeC, respectively (Table 3.2). Thirty- six proteins were increased in their levels under PeC as compared with Pe (Table 3.3). Among these, the ATP-dependent chaperone ClpB, elongation factor G, endopeptidase La, shikimate dehydrogenase, iron ABC transporter substrate-binding protein, and 30S ribosomal protein S1 were detected only for PeC (Table 3.4). Chaperones, which are involved in protein folding, and

ABC transporters, which are involved in transport of ions and amino acids, and peptidases involved in proteolysis, were frequently detected. Other up-regulated proteins detected, for example, those related with carbon metabolism (e.g. phosphoglycerate kinase, malate dehydrogenase), chemotaxis (e.g chemotaxis protein CheW), RNA metabolism (e.g. nucleoside diphosphate kinase, ribonuclease) and porin (e.g. outer membrane protein assembly factor

BamC) (Appendix 3).

One hundred eighty four proteins were decreased in level under PeC, as compared with Pe

(Table 3.3). The proteins produced only under Pe included, for example, those related to proteolysis (e.g. aminopeptidase N), protein translation (e.g. isoleucine-tRNA ligase), secretion of virulence factors (e.g. cluster of type IC secretion protein RhS, adeC/adeK/oprM family multidrug efflux complex outer membrane factor), nitrogen metabolism (e.g. NADP-glutamate dehydrogenase, nitrite reductase) (Table 3.5 and Appendix 4).

At the same time, secreted proteomics of Cmm was also analyzed under two conditions; it was grown alone in the NB media (Cm) and it was grown in the NB media with P. entomophila 23S

(CmP). Similar to the P. entomophila 23S proteome, the total number of Cmm proteins was decreased under CmP compared with Cm: the total number of proteins identified at 95 %

46 probability was 405 and 27 for Cm and CmP, respectively (Table 3.6). The levels of only four proteins were increased under CmP, as compared with Cm (Table 3.7); these are histidine triad nucleotide-binding protein, DUF 188 domain containing protein, thioredoxin, and DNA starvation/stationary phase protection protein (Table 3.8). Levels of 97 proteins were decreased in CmP as compared with Cm (Table 3.7). The proteins produced only under Cm included, for example, various transporters (e.g. sugar/peptide ABC transporter substrate-binding proteins), those related to carbon metabolism (e.g. glucoside hydrolase family 68 protein), proteolysis (e.g. serine protease), protein folding (molecular chaperon DnaK), and translational elongation (e.g. elongation factor G) (Table 3.9 and Appendix 6).

3.4.10. Pseudomonas entomophila 23S population is static while Cmm population decreased during their interaction

Along with the exo-proteomics, the colony forming units of each bacterium were affected. After the two bacteria was mixed, the number of P. entomophila 23S became static while the number of Cmm decreased and no Cmm colony was detected at day 6, which was 3 days after the two bacteria were mixed (Figure 3.8).

3.5 Discussion

Previously, our laboratory isolated a bacterium that inhibited the growth of Cmm in vitro. In the current study, this anti-Cmm bacterium was characterized to explore the potential for its use in agriculture. Based on the 16S rRNA sequences, our anti-Cmm bacterial stain was closest to bacterial strain Pseudomonas entomophila L48. Among bacteria used for biocontrol of plant diseases, the genus Pseudomonas is one of the most studied and deployed bacteria (Weller, 2007;

Haas and Défago, 2005). Pseudomonas entomophila L48 was initially isolated from fruit fly

(Drosophila melanogaster) because it was highly pathogenic to Drosophila larvae and adults

(Vodovar et al., 2005; Vallet-Gely et al., 2010). The bacterium was shown to protect cucumber from the root disease caused by Pythium ultimum; (Vallet-Gely et al., 2010). Yet, it has generally known as an entomopathogenic bacterium and used for studying host-pathogen interactions

(Vodovar et al., 2005; Liehl et al., 2006; Vallet-Gely et al., 2010) and development of biocontrol agents against insect pests (Dieppois et al., 2015). This is the first report that the species P. entomophila possesses antagonistic activity against Cmm. A whole genome sequencing would be needed for this bacterial strain to determine the identification at the strain level.

The results showed that P. entomophila 23S inhibited the growth of Pseudomonas syringae pv. tomato DC 3000, Botrytis cinerea, and Sclerotinia minor in vitro. Pseudomonas syringae pv. tomato DC3000 causes bacterial speck disease of tomato (Solanum lycopersicum) and

Arabidopsis thaliana (Whalen et al., 1991). Botrytis cinerea is the pathogen of grey mould disease in over 200 crops (Williamson et al., 2007). Sclerotinia minor causes basal drop disease in lettuce and other vegetables (e.g. celery, sunflower, etc.; El-Tarabily et al., 2000; Budge and

Whipps, 1991). Antifungal acitivity of P. entomophila 23S exhibited for B. cinerea and S. minor may not be as strong as the antibacterial activity exhibited for P. syringae since the zones of inhibition for the fungi were asymmetric, and the fungi were slowly growing back from the center. The antagonistic activity of P. entomophila 23S suggest the possibility of controlling the diseases caused by these three pathogens. It would be of interest to test whether P. entomophila

23S has antagonistic activity against other pathogens.

Phosphorus is a limiting nutrient for plant growth and development in most soils (Pant et al.,

2015; Marschner, 1995; Raghotahama, 1999; Lynch, 2011). Our results indicated that P. entomophila 23S could solubilize insoluble phosphorus; however, the amount was low as compared to other phosphorus-solubilzing PGPR (Rahi et al., 2010). Since our assay was conduced in vitro, an in planta study could reveal the biofertilizer potential of P. entomophila

23S in terms of phosphorus.

Pseudomonas entomophila 23S was identified as a siderophore-producer. The strain also produced moderate levels of hydrogen cyanide (HCN). Siderophore production is one of the major biocontrol mechanisms in suppression of root diseases by rhizobacteria (O’Sullivan and

O’Gara, 1992; Schippers et al., 1987). Siderophores are low-molecular-weight iron chelaters, which strongly bind to ferric iron, which thereby facilitates iron acquisition for siderophore- producing bacteria, especially under iron-limited conditions. Thus, siderophore-producing bacteria outcompete pathogens by rendering iron unavailable (Shanmugaiah et al., 2015). Several

Pseudomonas spp. have been reported to be producers of siderophores (Leong, 1986; de Weger et al., 1986; Loper and Henkels, 1999). For the P. entomophila L48 strain, its genome contains genes clusters encoding proteins required for pyoverdine siderophore biosynthesis and uptake

(Dieppois et al., 2015). HCN is a volatile, antibiotic, secondary metabolite (Haas and Keel,

2003). HCN production is a common trait among rhizospheric Pseudomonas species (Schippers et al., 1991), and has been shown to contribute to disease suppression by biocontrol bacteria

(Voisard et al., 1989; Defago and Haas, 1990; Haas and Keel, 2003). An HCN-producing strain of Pseudomonas spp. LBUM330 was shown to inhibit Cmm (Lanteigne et al., 2012). Production

49 of HCN may partly explain the antagonistic activity of P. entomophila 23S towards Cmm observed in this study.

Eighty percent of rhizospheric bacteria have been suggested to be IAA producers (Patten and

Glick, 1996), and P. entomophila 23S was found to be one of them. IAA production depends on the concentration of tryptophan (Idris et al., 2007), which is present in plant root exudates (Patten and Glick, 1996). Our results agree with this, as the amount of IAA produced by P. entomophila

23S was higher when the bacterium was grown at higher concentrations of tryptophan. The effect of bacteria-produced IAA on plants is a function of its concentration as well as sensitivity of the roots (Spaepen et al., 2007). IAA-producing ability of P. entomophila 23S further adds to the potential for this bacterium as a plant-growth-promoting bacterium.

Pseudomonas entomophila 23S showed varying degrees of resistance to ampicillin, chloramphenicol, rifampicin, penicillin, streptomycin and tetracycline, while it did not grow at all in the presence of kanamycin and gentamycin. A high proportion of rhizospheric bacteria has been reported to be intrinsically resistant to antibiotics (Gilbert et al., 1993). PGPR with resistance against multiple antibiotics have ecological advantages with regard to survival in the rhizosphere (Döbereiner and Baldani, 1979; De Brito et al., 1995). In fact, a range of antibiotics is produced by soil microbes and thus, are present in natural soils; for example, chloramphenicol, kanamycin, streptomycin, and tetracycline were originally derived from Streptomyces species, while penicillin is originally derived from a fungus (Alexander, 1977; Yasmin et al., 2010). The result implies that P. entomophila 23S has resistance to at least some antibiotics and may have high competitiveness when used as an inoculum in field.

The plant assay demonstrated that P. entomophila 23S promotes the growth of the tomato seedlings. The energy stored in the seeds is usually sufficient for their emergence but, nutrients must be provided to promote further growth of the seedlings. In this experiment, the substrate used was a mix of sand and turface, which did not contain essential nutrients such as N, K and P, and the seedlings were receiving water only. Therefore, the substrate was not the source of nutrients for seedlings, as well as for P. entomophila 23S. However, P. entomophila 23S could utilize the nutrients from exudates secreted by roots. Root exudates contain compounds such as organic acids, sugars, and amino acids, and are known to be easily utilized by rhizospheric microorganisms (Kamilova et al., 2006; Rovira, 1969; Vancura and Hovadik, 1965). Organic acids, specifically citric acid, are the most abundant reduced carbon source in the tomato root exudates (Kamilova et al., 2006; Lugtenberg et al., 2001) and represent a major class of utilizable carbon (de Weert et al., 2007; Lugtenberg et al., 2001). Our earlier results suggested that P. entomophila 23S could solubilize phosphorus and produce siderophores, HCN, and IAA.

Among these traits, the production of HCN was probably not significant in the seedling growth promotion exhibited by the P. entomophila 23S treatment because HCN is more involved in biocontrol ability and there was no meaningful pathogen pressure on the seedlings. Root exudates contain tryptophan, a precursor of IAA, and many rhizobacteria are known to convert the root exudate tryptophan to IAA (Frankenberger and Muhammad, 1995). This might explain the enhanced root development of the plants treated with P. entomophila 23S. Enhanced root growth leads to subsequent effects on improving water and nutrient intake, further helping the growth of the seedlings.

Pseudomonas entomophila 23S was also shown to be a good colonizer of tomato roots. The result implies that P. entomophila 23S can colonize the roots and establish in good numbers within 3 days. The populations found in this study are similar to those reported for earlier PGPR studies of tomato seedling root colonization (Lugtenberg et al., 1999; Yan et al., 2003). We also tried to isolate P. entomophila 23S from inside the root tissue by sterilizing the root surface, but we were not able to do so (data not shown). Hence, P. entomophila 23S seems to reside only on the root surface (rhizoplane) and in the soil around the root (rhizosphere), not the inside the root, and exerts effects of plant growth promotion.

The exo-proteomic study provided further knowledge regarding characteristics of P. entomophila

23S, specifically as relates to interaction with Cmm. From an agar-disk diffusion assay, P. entomophila 23S was found to inhibit the growth of Cmm. However, the exo-proteomic results showed that co-culturing of Cmm and P. entomophila 23S decreased the total number of proteins for both. Still, this decrease was more dramatic for Cmm than for P. entomophila 23S, implying that Cmm was substantially affected by P. entomophila 23S. Cmm must have been dying during the interaction with P. entomophila 23S. This was confirmed by our colony forming units (cfu) enumulation study as the number of cfu for Cmm decreased dramatically after mixing with P. entomophila 23S, while the number of cfu for P. entomophila 23S was static. Unsurprisingly, only four upregulated proteins were detected for the Cmm exo-proteome. Among them, histidine triad nucleotide-binding protein (Hints), which has an enzymatic hydrolase activity, was only detected in the context of P. entomophila 23S interaction and thus, is worthy of note. However, the function of this protein is not fully understood despite that fact that these proteins are conserved from bacteria to humans (Brenner et al., 1999). Human Hints have been studied and

52 were thought to be tumor suppressors (Li et al., 2006). Recently, involvement in D-alanine metabolism was suggested in Escherichia coli (Bardaweel et al., 2011). Roles in stress response have been reported for thioredoxin and DNA starvation/stationary phase protection proteins, which in our study, showed slight upregulation due to interaction with P. entomophila 23S

(Kumar et al., 2004; Antipov et al., 2017). Overall, Cmm proteome changes confirm that the bacterium is suppressed by P. entomophila 23S.

Although we focused our exo-proteomics on proteins produced by the bacteria and released into the external environment, most of the detected Cmm proteins must have included cellular proteins because Cmm was dying because of its interaction with P. entomophila 23S and the cells were likely to have been lysed. It is possible that the analyzed P. entomophila 23S secreted proteome might also contain some cellular proteins, since it was entering into the stationary phase, and some of the bacterial cells could have been undergoing lysis.

As opposed to Cmm, which was dying during the interaction with P. entomophila 23S, P. entomophila 23S was attempting to adapt. A distinctive feature of P. entomophila 23S proteome under these conditions was the induction of molecular chaperons. The results showed that the bacterium secreted ATP-dependent ClpB exclusively during interaction with Cmm, and other chaperons (e.g. molecular chaperone GroEL) were also found to be upregulated. In contrast, molecular chaperons were not detected in Cmm proteomes under any investigated condition.

Molecular chaperons, also known as heat-shock or stress proteins (hsps) interact with and aid in the folding or/and assembly of other proteins (Hendrick and Hartl, 1993; Kim et al., 2013).

Proteins that have been denatured or otherwise damaged by cellular stresses are subjected to

53 refolding by chaperons, and degraded by proteases or the proteosome to prevent deleterious effects to cells (Ling and Söll, 2010). Chaperons play an important role in protein quality control during the periods of cellular stresses, and a specific family of chaperons, heat shock proteins, are only induced under the conditions of stress (Kim et al., 2013). Our observation suggests that

Cmm served as a stress factor, and P. entomophila 23S must have been affected by Cmm while trying to adapt to the changing circumstances. Moreover, the two bacteria must compete for limiting resources, such as nutrients. During the interaction with Cmm, P. entomophila 23S might have also been stressed though resource competition.

The proteins that underwent fold change increases also included many peptidases (e.g. endopeptidase La) and elongation factors (e.g. Elongation factor G). Along with chaperons, peptidase could be playing a role in proteolysis for degradation of damaged proteins under stress conditions. Elongation factor, which functions in translational elongation, is also suggested to act as a chaperon towards unfolded and denatured proteins (Kudlicki et al., 1997; Caldas et al.,

2000). Several types of ABC transporters for amino acids and ions (e.g. methionine ABC transporter substrate-binding protein, iron ABC transporter substrate-binding protein) were upregulated during the interaction with Cmm, and might be an indication that P. entomophila

23S was attempting to take up scarce nutrient from the external environment for survival

(Shimizu, 2014). Similar observations were also reported when bacteria were under conditions of nutrient starvation and/or of high density (Al Dahouk et al., 2013; Wick et al., 2001; Eymann et al., 2002; Yoon et al., 2003). Proteomic studies on cultivation of more than one bacterium exist, but most of them were for cooperative relationships. For antagonistic relationships, our results were similar to those by Zhang et al. (2014) in that up-regulated proteins of the antagonistic

54 bacterium, during the interaction with pathogenic fungi, included molecular chaperons and elongation factors.

Downregulation of a number of P. entomophila 23S proteins during the Cmm interaction could be due to a strategy to save energy. The observation that a number of proteins were downregulated and its population were static suggest that the bacterium was not actively growing. The induction of chaperons, as well as of other stress-related proteins, as discussed above, implies that the bacterium was struggling to remain functional by focusing metabolism that was vital for their survival and shutting down other accessory activities. Among the downregulated proteins, almost half of them were found not produced at all during the interaction with Cmm. Regarding carbon metabolism, one distinctive feature were the detections of pyruvate decarboxylase, which is related to fermentation (Van Zyl et al., 2014), nitrite reductase and formate dehydrogenase, both of which are related to denitrification (Tosques et al.,

1997; Einsle, 2011). The processes that these enzymes are involved in typically occur under anaerobic conditions, as alternative pathways to aerobic respiration, to produce energy. Retaining these aspects of metabolisms seems insignificant during the condition of stress encountred in this case. Instead, P. entomophila 23S concentrated on reduced carbon for energy production through aerobic respiration, which is more energy-efficient, as long as conditions are aerobic. In support of this, the P. entomophila 23S proteomic data showed fold increases in phosphoglycerate kinase, which is involved in glycolysis, and malate dehydrogenase, which is involved in the citric acid (TCA) cycle (Minic, 2015).

As for nitrogen metabolism, down-regulation of many proteins related with synthesis of amino acids (e.g. NADP-glutamate dehydrogenase, threonine ammonia-lyse, dihydroxy-acid dehydratase) indicates reduced need for specific metabolic activities. Yet, this could be another way to increase energy efficiency. For example, NADP-glutamate dehydrogenase, which catalyzes the reversible conversion of glutamate to 2-oxoglutarate, was not being produced during the Cmm interaction. This enzyme links amino acid and carbon metabolisms since the 2- oxoglutarate can be used in the TCA cycle for energy generation (Owen et al., 2002; Sharkey et al., 2013). The observation that many peptidases were downregulated seems contradictory, given the fact that many peptidases were also upregulated during the Cmm interaction, as described above. However, most of the peptidases that were not produced during the Cmm interaction (e.g. aminopeptidase N) were the type of peptidases that acted on single amino acids. They were different from the peptidases that were found to be upregulated during the Cmm interaction (e.g. endopeptidase La), as these acted on long polypeptides for breakdown of unfolded proteins

(Chandu and Nandi, 2003). This might imply that while cells were coping with damaged proteins, they were recycling the amino acids for maintaining essential aspects of metabolism.

Another distinctive feature of the P. entomophila 23S proteome was detection of many proteins related with purine and pyrimidine metabolism in both upregulated and downregulated protein lists. For instance, nucleoside-diphosphate kinase, which catalyzes the reversible transfer of phosphates from nucleoside triphosphates to nucleoside diphosphates (Levit et al., 2002), was only produced during the Cmm interaction. Xanthine dehydrogenase and dihydropyrimidinase, which are involved in purine and pyrimidine metabolism (Xi et al., 2000), respectively, were not produced during the Cmm interaction. Correspondingly, distribution of functional categorization

56 of spectra for molecular functions also indicated that many of them were related with nucleotide metabolism (See Appendix 1). Purine and pyrimidine participate in many essential biochemical processes. They are substrates for nucleic acid synthesis, precursors for the synthesis of coenzymes (e.g. NAD), and important for energy transfer functions (as ATP and GTP) (Nagar et al., 2016; Moffatt and Ashihara, 2002). They also play a critical role as cell signaling molecules during stress by allowing cells to recognize the changing environments and adapt to them

(Hengge, 2009; Weber et al., 2006; Nagar et al., 2016). Synthesis of purine and pyrimidines occurs de novo from small molecules and through salvage pathways from intermediates generated during their degradation; de novo synthesis is known to be more energy-consuming than salvage pathways (Nyhan, 2005). Several studies reported proteins for the purine and pyrimidine synthesis were downregulated under nutrient starvation and other stresses (Soufi et al., 2010; Otto et al., 2010; Eymann et al., 2002). Yoon et al. (2003) reported similar results under high cell density but also noted increases in proteins involved in salvage pathways. For some bacteria, purine and pyrimidine synthesis was required for virulence (Samant et al., 2008) or colonization (Vogel-Scheel et al., 2010). Detection of many proteins related to purine and pyrimidine metabolism may suggest that P. entomophila 23S was adapting to the presence of

Cmm. At the same time, salvage pathways may be enhanced to save the energy.

Our proteomic work did not suggest proteins explaining the antagonistic activity of P. entomophila 23S towards Cmm. Type IV secretion protein RhS, outer membrane autotransporter barrel domain-containing proteins, and TolC family proteins are outer membrane proteins, and for other bacteria, they are used for secretion of virulence factors (Russell et al., 2014;

Henderson and Nataro, 2001; Sharff et al., 2001). For P. entomophila 23S, many of such proteins

57 were downregulated, some of them were not produced at all during the Cmm interaction.

Pseudomonas entomophila 23S might have turned off the production of these proteins under nutrient starvation, due to competition with Cmm, as protein secretion is an energy-consuming process. For example, a study showed that production of Type IV secretion protein was growth- dependent and that it was largely produced when the bacterium was growing actively during the exponential stage and declined during the stationary phase (Huang et al., 2017). Alternatively, the anti-Cmm activity of P. entomophila 23S towards Cmm may be based on a mechanism that does not rely on these secretion mechanisms.

3.6 Conclusions

In this study, we have investigated a novel bacterial strain that showed antagonistic activity towards Cmm. The identified strain, Pseudomonas entomophila 23S, could solubilize inorganic phosphate, produce indole acetic acid, siderophore and hydrogen cyanide. Plant assay confirmed that P. entomophila 23S could promote growth of tomato seedlings. Whether this promoting activity occurs only with tomatoes or for other crop plants would be interesting as it could increase the potential utility of this bacterium in agriculture. The strain inhibited the growth of three other plant pathogens, Pseudomonas syringe pv. tomato DC3000, Botrytis cinerea and

Sclerotinia minor, suggesting that P. entomophila 23S have potential for biocontrol use for not only tomato bacterial canker against Cmm, but also for the diseases that are caused by these pathogens. In vivo study would be needed to test the effectiveness of the strain for control of diseases in other plants. The exo-proteomic study demonstrated that P. entomophila 23S, although superior to Cmm, was affected by the presence of this pathogen, secreting stress-related proteins such as chaperons, peptidases, and ABC-transporters, and elongation factors for protein

58 quality control. Moreover, changes in purine and pyrimidine metabolisms, and carbon and nitrogen metabolisms were implicated in efficient generation of energy as part of adaptation to stress. Further study could target these proteins to further investigate their role in the antagonisitic acitivty of P. entomophila 23S against Cmm. For some bacteria, proteinaceous compounds, such as bacteriocins are responsible for their antimicrobial activities (Gray et al.,

2006). The exo-proteomic study did not give further information regarding anti-Cmm compounds or anti-Cmm activity of P. entomophila 23S. Isolation of the anti-Cmm compounds, or genomic studies on P. entomophila 23S could be future research, expanding our knowledge around anti-

Cmm compounds produced by P. entomophila 23S, and being useful for improving Cmm control technology.

3.7 Acknowledgements

The authors would like to acknowledge Ministère de l'Agriculture, des Pêcheries et de l'Alimentation du Québec (MAPAQ), the Natural Sciences and Engineering Research Council

(NSERC) of Canada, and BioFuelNet for supporting the project. The McGill University and Génome Québec Innovation Centre, Montreal for performing 16S rRNA sequencing and

LC-MS/MS service provided by Institut de recherches cliniques de Montréal (IRCM) for label free proteomic analysis were highly appreciated.

Table 3.1 Shoot and root dry weights; root length, volume, diameter and surface area of tomato seedlings from control and P. entomophila 23S treatment Control P. entomophila 23S

Dry shoot weight (mg) 8.81 ± 0.58 13.0 ± 0.78 *

Dry root weight (mg) 4.91 ± 0.48 7.18 ± 0.70 *

Root length (cm) 92.14 ± 5.83 123.18 ± 8.91 *

Root volume (mm3) 72.40 ± 4.59 97.27 ± 6.01 *

Root diameter (mm) 0.32 ± 0.0054 0.32 ± 0.0032

Root surface area (cm2) 9.13 ± 0.55 12.26 ± 0.82 *

Data represented as mean ± standard error (n=15). An asterisk indicates significant difference from the control after the student’s t-test (p < 0.05).

Table 3.2 Total number of P. entomophila 23S proteins identified at 95 % protein probability and total spectra at 95 % peptide probability, with a minimum of two peptides: P. entomophila 23S was grown in NB media with and without Cmm Bacterial Pe 1 Pe 2 Pe 3 PeC 1 PeC 2 PeC 3 supernatant

Proteins 342 384 382 143 113 170

Spectra 9906 11855 11990 2483 1784 2808

(Pe = P. entomophila 23S, PeC = P. entomophila 23S was grown with Cmm (n=3))

Table 3.3 Protein grouping between categories, significant in contrasts based on Fisher’s Exact Test (p < 0.05): P. entomophila 23S was grown in NB media with and without Cmm Increased Total proteins 36

(fold change more than 1) Known proteins (P. entomophila) 31

(Family: Pseudomonas) 4

Hypothetical proteins 1

Decreased Total proteins 184

(fold change less than 1) Known proteins (P. entomophila) 163

(Family: Pseudomonas) 10

Hypothetical proteins 11

Unchanged Total proteins 5

(fold change equal to 1) Known proteins (P. entomophila) 2

(Family: Pseudomonas) 2

Hypothetical proteins 1

(Analyzed by Scaffold software)

Table 3.4 Pseudomonas entomophila 23S proteins, for which levels increased significantly when grown with Cmm. (Twenty proteins with greatest fold change)

Identified proteinsa NCBI Accession Molecular Peb PeCc Fold Fisher’s Functiond weight change exact Test (kDa) (P-value) ATP-dependent WP_011535712.1 95 0 32 INF < 0.00010 - Protein metabolic process chaperone ClpB - Protein processing - Response to heat Transporter WP_008095172.1 8 0 21 INF < 0.00010 Transport [Pseudomonas] elongation factor G WP_011534610.1 78 0 19 INF < 0.00010 Translational elongation endopeptidase La WP_011533116.1 89 0 12 INF < 0.00010 - Protein catabolic process - Proteolysis shikimate WP_044487548.1 29 0 10 INF < 0.00010 - Oxidation-reduction process dehydrogenase - Shikimate metabolic process iron ABC WP_011536289.1 37 0 8 INF < 0.00010 NA transporter substrate-binding protein 30S ribosomal WP_011532776.1 61 0 6 INF < 0.00010 Translation protein S1 phosphoglycerate WP_011536016.1 40 2 15 7.5 < 0.00010 Glycolytic process kinase nucleoside- WP_011532343.1 15 2 12 6 < 0.00010 - UTP biosynthetic process diphosphate kinase - CTP biosynthetic process [Pseudomonas] - GTP biosynthetic process - Nucleoside diphosphate phosphorylation ribonuclease WP_011532999.1 18 3 12 4 < 0.00010 Regulation of RNA metabolic process molecular WP_011535514.1 57 30 115 3.8 < 0.00010 - Protein refolding chaperone GroEL - Protein folding methionine ABC WP_011531630.1 29 7 22 3.1 < 0.00010 NA transporter substrate-binding protein copper chaperone WP_011535894.1 17 6 18 3 < 0.00010 NA PCu(A)C peptidase WP_044487760.1 47 3 9 3 < 0.00010 NA polyamine ABC WP_011536452.1 41 4 12 3 < 0.00010 Polyamine transport transporter substrate-binding protein outer membrane WP_011535131.1 41 2 6 3 0.00082 NA protein assembly factor BamC malate WP_011531748.1 45 10 27 2.7 < 0.00010 Oxidation-reduction process dehydrogenase membrane WP_011536164.1 36 3 8 2.7 0.00014 Proteolysis dipeptidase [Pseudomonas] chemotaxis protein WP_011534880.1 18 22 58 2.6 < 0.00010 - Chemotaxis CheW - Signal transduction glycine/betaine WP_011532740.1 31 23 57 2.5 < 0.00010 Transport ABC transporter substrate-binding protein a : identified as proteins of P. entomophila L48, except for those with [Pseudomonas], which indicates proteins from family of Pseudomonas b: Pe = P. entomophila is grown in NB media c: PeC = P. entomophila is grown with Cmm d: biological function assigned by Uni-Prot, NA = not available

Table 3.5 Pseudomonas entomophila 23S proteins, for which level decreased significantly when grown with Cmm. (Twenty proteins with smallest fold change)

Identified proteinsa NCBI Accession Molecular Peb PeCc Fold Fisher’s Functiond weight change exact Test (kDa) (P-value)

aminopeptidase N WP_011532972.1 99 164 0 0 < 0.00010 Proteolysis isoleucine--tRNA WP_011535726.1 106 128 0 0 < 0.00010 - Isoleucyl-tRNA aminoacylation ligase - tRNA aminoacylation for protein translation hydrolase WP_011532191.1 23 100 0 0 < 0.00010 Metabolic process Cluster of type IV WP_011531922.1 [4] 176 92 0 0 < 0.00010 Self-proteolysis secretion protein (WP_011531922.1) Rhs

malate synthase G WP_011536115.1 79 88 0 0 < 0.00010 Glyoxylate cycle nitrite reductase, WP_011536210.1 41 79 0 0 < 0.00010 - Nitrogen compound metabolic copper-containing process - Oxidation-reduction process dihydrolipoyl WP_011534948.1 48 78 0 0 < 0.00010 - Oxidation-reduction process dehydrogenase - Cell redox homeostasis xanthine WP_011533017.1 88 74 0 0 < 0.00010 Oxidation-reduction process dehydrogenase molybdopterin binding subunit guanine deaminase WP_011533015.1 48 73 0 0 < 0.00010 Guanine catabolic process glutathione- WP_011533508.1 49 61 0 0 < 0.00010 - Glutathione metabolic process disulfide reductase - Oxidation-reduction process - Cell redox homeostasis pyruvate WP_044487944.1 60 57 0 0 < 0.00010 NA decarboxylase formate WP_011531941.1 92 53 0 0 < 0.00010 - Oxidation-reduction process dehydrogenase-N - Cellular respiration subunit alpha dihydrolipoyl WP_044488604.1 49 52 0 0 < 0.00010 - Cell redox homeostasis dehydrogenase - Oxidation-reduction process NADP-specific WP_044487662.1 49 51 0 0 < 0.00010 - Cellular amino acid metabolic glutamate process dehydrogenase - Oxidation-reduction process dihydropyrimidinas WP_011534398.1 53 50 0 0 < 0.00010 NA e adeC/adeK/oprM WP_011535418.1 53 49 0 0 < 0.00010 Transport family multidrug efflux complex outer membrane factor xanthine WP_011533018.1 53 48 0 0 < 0.00010 Oxidation-reduction process dehydrogenase small subunit TolC family protein WP_011532102.1 55 47 0 0 < 0.00010 Transport NAD(P)/FAD- WP_011531818.1 62 45 0 0 < 0.00010 Oxidation-reduction process dependent oxidoreductase outer membrane WP_011534185.1 109 44 0 0 0.00012 Proteolysis autotransporter barrel domain- containing protein a : identified as proteins of P. entomophila L48, except for those with [Pseudomonas], which indicates proteins from family of Pseudomonas b: Pe = P. entomophila is grown in NB media c: PeC = P. entomophila is grown with Cmm d: biological function assigned by Uni-Prot, NA = not available

Table 3.6 Total number of Cmm proteins identified at 95 % protein probability and total spectra at 95% peptide probability, with two minimum peptides: Cmm was grown in NB media with and without P. entomophila 23S Bacterial Cm 1 Cm 2 Cm 3 CmP 1 CmP 2 CmP 3 supernatant Proteins 378 359 478 28 28 26 Spectra 9669 8439 8709 329 366 312

(Cm = Cmm is grown in NB media, CmP = Cmm is grown with P. entomophila 23S (n = 3))

Table 3.7 Protein grouping among categories, significant in contrasts based on Fisher’s Exact Test (p < 0.05): Cmm was grown in NB media with and without P. entomophila 23S Increased Total proteins 4

(fold change more than 1) Known proteins (C. michiganensis) 3

(Family: Clavibacter) 1

Decreased Total proteins 97

(fold change less than 1) Known proteins (C. michiganensis) 69

(Family: Clavibacter) 10

Hypothetical proteins 18

unchanged Total proteins 1

(fold change equal to 1) Known proteins (Family: Clavibacter) 1

(Analyzed by Scaffold software)

Table 3.8 Cmm proteins, for which levels increased significantly when grown with P. entomophila 23S

Identified proteinsa NCBI Accession Molecular Cmb CmPc Fold Fisher’s Functiond weight (kDa) chang exact Test e (P-value)

histidine triad WP_012038254.1 12 0 5 INF < 0.00010 NA nucleotide-binding (+3) protein

DUF2188 domain- WP_011931210.1 8 4 52 13 < 0.00010 NA containing protein

thioredoxin WP_012039655.1 12 18 30 1.7 < 0.00010 - Glycerol ether [Clavibacter] metabolic process - Cell redox homeostasis DNA WP_079534702.1 21 4 6 1.5 < 0.00010 - Cellular iron ion starvation/stationary homeostasis phase protection - Oxidation-reduction protein process - Response to stress a : identified as proteins of Clavibacter michiganensis, except for those with [Clavibacter], which indicates proteins from family of Clavibacter b: Cm = C. michiganensis subsp. michiganensis is grown in NB media c: CmP = C. michiganensis subsp. michiganensis is grown with P. entomophila d: biological function assigned by Uni-Prot, NA = not available

Table 3.9 Cmm proteins, for which level decreased significantly when grown with P. entomophila 23S (Twenty proteins with smallest fold change)

Identified proteinsa NCBI Accession Molecular Cmb CmPc Fold Fisher’s Functiond weight (kDa) change exact Test (P-value)

hypothetical protein WP_043560339.1 28 852 0 0 < 0.00010 NA (+4) sugar ABC WP_011931571.1 45 752 0 0 < 0.00010 NA transporter substrate- binding protein sugar ABC WP_012037564.1 39 532 0 0 < 0.00010 NA transporter substrate- (+1) binding protein peptide ABC WP_012037484.1 59 486 0 0 < 0.00010 Transmembrane transporter substrate- transport binding protein glycoside hydrolase WP_087198335.1 56 332 0 0 < 0.00010 Carbohydrate family 68 protein utilization Cluster of WP_086507566.1 81 305 0 0 < 0.00010 NA hypothetical protein [3] (WP_086507566.1) putative extracellular WP_011931147.1 33 294 0 0 < 0.00010 NA serine protease hypothetical protein WP_079533702.1 63 265 0 0 < 0.00010 NA (+1) glycosyl hydrolase WP_087198062.1 55 264 0 0 < 0.00010 Carbohydrate metabolic family 5 process sugar ABC WP_012039472.1 47 257 0 0 < 0.00010 Transport transporter substrate- (+1) binding protein nuclease WP_094114344.1 74 244 0 0 < 0.00010 NA serine protease WP_011931204.1 30 244 0 0 < 0.00010 Proteolysis ABC transporter WP_012038693.1 32 216 0 0 0.00017 NA substrate-binding protein isocitrate WP_012039226.1 45 216 0 0 0.00017 - Metabolic process dehydrogenase - Oxidation-reduction (NADP(+)) process hypothetical protein WP_011931558.1 44 212 0 0 0.0002 NA hypothetical protein WP_086515896.1 27 206 0 0 0.00025 NA molecular chaperone WP_011931370.1 67 203 0 0 0.00029 Protein folding DnaK elongation factor G WP_086506550.1 77 199 0 0 0.00034 Translational elongation penicillin-binding WP_079532147.1 79 180 0 0 0.00072 NA protein (+4) 2-oxoglutarate WP_079532746.1 140 169 0 0 0.0011 - Metabolic process dehydrogenase E1 (+1) - Ttricarboxylic acid component cycle - Oxidation-reduction process a : identified as proteins of Clavibacter michiganensis, except for those with [Clavibacter], which indicates proteins from family of Clavibacter b: Cm = C. michiganensis subsp. michiganensis is grown in NB media c: CmP = C. michiganensis subsp. michiganensis is grown with P. entomophila: d: biological function assigned by Uni-Prot, NA = not available

Figure 3.1 Neighbor-joining tree constructed based on 16S rRNA sequencing of the anti-Cmm bacterium (inquiry = P. entomophila 23S)

Figure 3.2 Antagonistic activity of P. entomophila 23S against other plant pathogens: (a) Pseudomonas syringe pv. tomato DC3000; (b) Botrytis cinerea; and, (c) Sclerotinia minor. (a) One hundred µL of P. syringae pv. tomato DC3000 culture was spread on King’s B plate, and 5 µL of NB media (on the left), of P. entomophila 23S was placed on each desk. (b), (c) Pathogen fungal culture was placed on the center of PDA, and 5 µL of NB media (on the left), of P. entomophila 23S was placed on each desk.

Figure 3.3 Phosphorus solubilization assay of P. entomophila 23S (a) On a PVK agar plate - 10 µL of NB media (top center), and of P. entomophila 23S culture (left and right), and of positive control bacterium (bottom center) were placed on each disk (b) On a PBRIP agar plate – 10 µL NB media (left), and of P. entomophila 23S culture (right) were placed on each disk.

Figure 3.4 Siderophore production assay of P. entomophila 23S on a chrome azurol S (CAS) agar plate On a CAS plate, 10 µL of NB media (on the left), and P. entomophila 23S culture (on the right) were placed on each disk.

Figure 3.5 Hydrogen cyanide (HCN) production of P. entomophila 23S (a) Kings B media, (b) P. entomophila 23S, and (c) a positive control bacterium on King’s B

Figure 3.6 Effects of antibiotics on the growth of the P. entomophila 23S (a) ampicillin, (b) chloramphenicol, (c) kanamycin, (d) rifampicin, (e) gentamycin, (f) penicillin, (g) streptomycin, and (h) tetracycline.

Figure 3.7 Tomato seedlings and roots from control and P. entomophila 23S treatment Seedlings from control (a, b, and c) and from P. entomophila 23S treatment (d, e, and f), and roots from control (g, h, and i) and from P. entomophila 23S treatment (j, k and l).

Figure 3.8 Population size (cells) for P. entomophila 23S and Cmm Psudomonas entomophila 23S and Cmm was grown individually for the first 3 days (Day 1 -3), 108 cfu mL-1 of each culture mixed, and grown together for another 3 days (Days 4-6).

Connecting text

The results of Study 1 suggested that Pseudomonas entomophila 23S has substantial potential as a plant growth promoting rhizobacterium (PGPR). Next, we focused on the anti-Cmm activity of

P. entomophila 23S. Effective control strategies for tomato bacterial canker caused by Cmm have been lacking. Since P. entomophila 23S showed anti-Cmm activity in vitro, we attempted to isolate the anti-Cmm compound(s) produced by this bacterium. Biocontrol agents used for plant disease control may consist of pathogen-suppresing microbes, but could also be biologically produced compounds that inhibit the growth of plant pathogens. Because the survival abilities of the bacteria is not a concern, use of the active compound(s) could also constitute an effective biocontrol agent for plant disease.

Chapter 4 Isolation of antimicrobial compounds produced by

Pseudomonas entomophila 23S against Clavibacter michiganensis subsp. michiganensis, a pathogen of tomato causing bacterial canker

Authors: Yoko Takishita1, Leanne Ohlund2, Alexandre Arnold2, Lekha Sleno2, Donald L.

Smith1

Affiliations:

1 Department of Plant Science, McGill University, Macdonald Campus, 21,111 Lakeshore Road,

Sainte-Anne-de-Bellevue, Quebec, Canada, H9X 3V9

2 Département de Chimie, Université du Québec à Montréal CB4010, Case postale 8888, succursale Centre-ville Montréal, Quebec, Canada H3C 3P8

4.1. Abstract

Biopesticides, which consist of antagonistic microorganisms, or the bioactive compounds they produce, offer attractive alternatives to synthetic agrochemicals as a means to reduce plant diseases in crop production systems. Previously, we isolated a rhizobacterial strain Pseudomonas entomophila 23S that inhibited the growth of the bacterial phytopathogen Clavibacter michiganensis subsp. michiganensis (Cmm) in vitro. Cmm causes tomato bacterial canker disease, which results in serious damage to the tomato production industry due to lack of effective management strategies. The objective of this study was to purify and characterize an anti-Cmm compound(s) produced by P. entomophila 23S. Initially, crude extract was obtained by butanol extraction, then fractionated by solid-phase-extraction (SPE), purified by high-pressure- liquid-chromatography (HPLC), and characterized by liquid chromatography coupled to high- resolution tandem mass spectrometry (LC-HRMS/MS). We were able to isolate two anti-Cmm compounds. From the LC/MS spectra, we had predicted that each of these contained a quinoline ring and differed by a methyl group. The analysis by nuclear magnetic resonance (NMR) spectroscopy was not successful in resolving the complete structure and this remains a subject of future study. In addition, study of anti-Cmm activity of extracts prepared following growth of P. entomophila 23S in different media indicated that the P. entomophila 23S produced the anti-

Cmm compounds in greater amounts when it was grown in the nutrient broth medium, where bacterial growth was slowest. The NB medium may possess a distinct feature that is triggering P. entomophila 23S to higher production of the anti-Cmm compounds.

4.2. Introduction

Plant diseases caused by viruses, bacteria and fungi are responsible for significant crop losses.

Current control measures rely largely on the application of chemical pesticides (Agrio, 2005).

However, chemical pesticides have detrimental effects on human and environmental health

(Gillor and Ghazaryan, 2007). Their widespread use has also resulted in development of resistance to control mechanisms by the pests (Mnif and Ghribi, 2015). Because of these concerns, many pesticides are no longer available or are being targeted for removal from the marketplace (Strobel et al., 2004). Therefore, eco-friendly alternatives are urgently needed to control crop pests and diseases.

Microorganism-based biological control offers an effective alternative to synthetic chemical treatment of plant diseases. Biopesticides, which consist of antagonistic microorganisms, or the bioactive compounds they produce, have been increasingly researched, and their markets are growing rapidly (Ojiambo and Scherm, 2006). Most biopesticides have the advantages of more rapid and complete biodegradation, higher selectivity and non-target biological safety (Wang et al., 2011). Resistance to biopesticides in target organisms is not easily developed, in contrast to the general case for their chemical counterparts (Mnif and Ghribi, 2015).

Pseudomonas, non-spore-forming, gram-negative, rod-shaped bacteria, are capable of synthesizing various antimicrobial compounds. Pseudomonas species are ubiquitous in the rhizosphere and suppressive soils, and because they are easy to isolate, culture and manipulate genetically, these bacteria have great potential as biocontrol agents (Whipps, 1997; Raajimakers et al., 2010). Numerous studies have been conducted on this genus and its antibiotic production

(reviewed in Haas and Keel, 2003). Pyoluteorin, phenazine derivatives, such as phenazine-1- carboxylic acid, 2,4-diacetylephloroglucinol, pyrrolnitrin, pyoluteorin, hydrogen cyanide, pyocyanine, rhamnolipids, and protein-type compounds such as oomycin A, cepaciamide A, ecomycins, and lipopeptides are reported to be produced by various Pseudomonas species

(Santoyo et al., 2012; Raajimakers et al., 2010; Wang et al., 2011). In fact, Pseudomonas is one of the major biocontrol agents currently used for managing plant diseases (Haas and Keel, 2003).

A rhizobacterial strain, Pseudomonas entomophila 23S, which inhibited the growth of the plant pathogen Clavibacter michiganensis subsp. michiganensis (Cmm) in vitro was previously isolated in our laboratory. Cmm is a gram-positive bacterium and a causal agent of bacterial canker, one of the most destructive diseases in tomato (Glesason et al., 1993; León et al., 2011).

Through wounds and natural openings such as stomata and hydathodes, Cmm enters the plants and moves to the xylem where it multiplies rapidly (Carlton et al., 1998; Gartemann et al., 2003;

Sharabani et al., 2013). Infected plants initially exhibit marginal necrosis of leaflets, which gradually widens and leads to wilting of all leaves, while canker develops on the stem (de León et al., 2011). The whole plant can be stunted, severely wilted and, ultimately, killed. Infected fruits are malformed, and/or develop distinctive raised dark-spots – generally known as “bird’s- eye” lesions (Fatmi et al., 1991). The disease has been reported in most tomato production systems in the world and causes substantial crop losses (Chang et al., 1992a; Kawaguchi and

Tanina, 2014).

Despite the seriousness, no control methods have been found to be completely effective for tomato bacterial canker disease. No Cmm-resistant cultivars are commercially available, and

81 current control primarily relies on the use of pathogen-free certified seeds and transplants, good hygiene, disinfection of all tools, and crop rotations (Xu et al., 2015). Use of antibiotics or copper containing compounds have shown only limited efficacy (Hausbeck et al., 2000; Miller and Ivey, 2005). Efforts are ongoing to find effective methods for management of this disease.

Several studies have identified bacteria, fungi, plant extracts, and insect extracts that possess anti-Cmm activity and/or showed effective disease control in tomato plants. Strains of

Pseudomonas (Aksoy et al., 2017; Lanteigne et al., 2012; Amkraz et al., 2010), and Pseudozyma aphidis yeast-type fungi (Barda et al., 2015), extracts from plants (Kotan et al., 2013; Özdemir and Erincik, 2015) and insects (Li et al., 2013) show promise. Non-biological anti-Cmm compounds were also identified and studied by screening existing chemical libraries, synthetic peptides (Choi et al., 2014), and 12 small molecules (Xu et al., 2015).

In this study, we report the purification and characterization of novel anti-Cmm compounds produced by Pseudomonas entomophila 23S. Initially, the crude extract was first obtained by butanol extraction, then fractioned by solid-phase-extraction (SPE), purified by high- performance-liquid-chromatography (HPLC), and characterized by liquid chromatography coupled to high-resolution tandem mass spectrometry (LC-HRMS/MS).

4.3. Materials and Methods

4.3.1. Bacterial growth conditions

Pseudomonas entomophila 23S, was originally isolated by members of our laboratory, from a soybean field in Quebec (Jung et al., 2014). It was grown in Nutrient Broth (Difco; 8 g L-1) medium at 28 °C, 100 rpm. Clavibacter michiganensis subsp. michiganensis strain 930 (Cmm)

82 was provided by Agriculture, Pêcheries et Alimentation, Quebec. Cmm was grown at 28 °C, 150 rpm. Both bacteria were maintained as glycerol stocks at -80 °C.

4.3.2. Butanol extraction of bacterial culture

Pseudomonas entomophila 23S was prepared in 2 L of broth cultures, in 4 L flasks shaken at 100 rpm, for 5 days, to reach stationary phase, with a total of 16 L of bacterial culture, following the methods described in Soulemanov et al. (2002). Eight hundred mL of 1-butanol were then added to each 2 L of bacterial culture, shaken occasionally and left overnight to allow for complete phase partitioning. The upper butanol layers were collected from all the flasks and combined; the butanol was then evaporated using a rotary evaporator (90 rpm, 50 °C). The dried material remaining after the evaporation was resuspended in 30 mL of 10 % acetonitrile (ACN/H2O, v/v).

The extract was then centrifuged at 4 °C and 18,000 rpm for 30 minutes to remove large particles, and the supernatant was then filtered through a 0.22-um pore size syringe membrane

(Mixed Cellulose Ester; Millipore Corp.). The filtered extract was evaluated for anti-Cmm activity through an agar-well diffusion assay, as described below.

4.3.3. Agar-well diffusion assay

The agar-well diffusion assay followed the general methods of Pitkin and Martin-Mazuelos

(2007). One hundred μL of Cmm culture was spread onto a Nutrient Broth Yeast Extract (NBYE; per L distilled H2O: 8.0 g nutrient broth, 2.0 g yeast extract, 2.0 g K2HPO4, 0.5 g KH2PO4, 5.0 g

Glucose, 0.25 g MgSO4•H2O and 15 g agar) agar plate. Wells with a diameter of 6 mm were made in the plate agar with a cork borer, and 80 µL of the sample extracted from P. entomophila culture was loaded into each well, except the control, which was loaded with 10 % acetonitrile

83 solution. The petri plates were sealed with parafilm and incubated for at least 48 h at 28 °C. The zone of inhibition was measured (mm) as the straight-line distance from the edge of the well to the edge of the zone of inhibition.

4.3.4. Solid phase extraction

The butanol extract obtained from the above procedures and showing anti-Cmm activity in vitro, were subjected to solid phase extraction. The butanol extract (30 mL) was first diluted to 100 mL with 10 % acetonitrile, and then loaded onto Extract-CleanTM C18 10000 mg (75 mL)-1 SPE cartridges (Alltech, USA) with 25 mL column-1 (using a total of 4 columns). As an eluent, acetonitrile was applied at increasing concentrations: starting from 0 % at 50 mL, then 20, 30,

40, 50, 60, and 70 % each at 25 mL, and lastly 80 % at 50 mL per column. The eluate (fractions) were collected and tested for anti-Cmm activity by the agar-well diffusion assay, as described above.

For the 50, 60, 70, and 80 % fractions, minimum inhibitory concentrations (MIC) were determined. Fractions were lyophilized and resuspended in 50 % acetonitrile. Ten concentrations

(1.0, 2.0, 4.0, 8.0, 16, 32, 64, 128, 256, and 512 µg mL-1) were prepared in a 96-well plate according to the microdilution method established by Wiegand et al. (2008). The initial Cmm culture was adjusted to 5 ×105 cfu mL-1 in NB medium. The Cmm in the NB medium without any fractions served as a control, while the NB media without fractions and the Cmm served as a sterile control. The plate was incubated at 28 °C for 2 days using a Gen5TM Biotek microplate reader (Biotek Inc.). The plate was agitated through double-orbital shaking, and the optical density, at 600 nm, was measured every 6 h. The data were analyzed with the SAS package

84 program version 9.4 (SAS institute Inc., Cary, NC, USA) using the proc-mixed model, with time-points and concentrations as fixed effects and well-plates as a random effect. Tukey’s test was applied for multiple comparisons with least square means when there was a significant treatment effect at the 95 % confidence level (p < 0.05). The MIC was defined as the lowest concentration at which the Cmm growth was significantly different from the growth medium control samples.

4.3.5. Antagonistic activity of SPE fractions against other bacteria

SPE fractions were also tested against other plant-associated bacteria: Bradyrhizobium japonicum USDA110, Bacillus thuringiensis NEB17, and Pseudomonas syringae pv. tomato

DC3000. Bradyrhizobium japonicum USDA110 was grown in Yeast Extract Mannitol medium

(per L of distilled H2O: 10 g mannitol, 1 g yeast extract, 0.2 g MgSO4, 0.1 g NaCl, 0.5 g

K2HPO4), B. thuringiensis NEB17, and P. syringae pv. tomato DC3000 were grown in King’s B media (per L of distilled H2O: 20 g, proteose peptone No.3, 10 mL glycerol, 1.5 g K2HPO4, 1.5 g

MgSO4). For each bacterium, antagonistic activity was tested for by agar-well diffusion assay as described above.

4.3.6. Comparisons of SPE fractions from different strains

Active SPE fractions were analyzed by HPLC, but to determine the active peaks, the SPE fractions were also prepared from the NB media without P. entomophila 23S, and from another strain of Pseudomonas sp. (accession number KJ534477, hereafter, referred as Pseudomonas sp.

KJ), for comparison of their anti-Cmm activities. Pseudomonas sp. KJ is a PGPR of tomato plants, but results of 16s rRNA analysis did not allow identification to the species level (Ricci,

2015). Our P. entomophila 23S and Pseudomonas sp. KJ belong to the same genus, but

Pseudomonas sp. KJ is a different strain from the P. entomophila 23S, as the colony characteristics are clearly and substantially different between the two. This strain, as well as its butanol extracts, do not inhibit the growth of Cmm. Preparation of the SPE fractions and anti-

Cmm agar-well diffusion assays from each fraction were conducted as described above.

4.3.7. LC-HRMS/MS analysis of SPE fractions, and butanol extracts

LC-MS/MS analysis was performed on a Shimadzu Nexera UHPLC (Shimadzu, Kyoto, Japan) coupled to a high resolution Sciex Triple TOF 5600 (quadrupole time-of-flight, QqTOF) system

(SCIEX, Concord, ON, Canada). Samples were injected onto an Aeris PEPTIDE XB-C18 100 ×

2.1 mm column, with solid core 1.7 μm particles (100 Å) (Phenomenex, Torrance, CA) using a

Nexera UHPLC system with water (A) and ACN (B), both containing 0.1 % formic acid, at a flow rate of 300 μL min-1 (40 °C). The gradient started at 30 % B, was held for 1 min, and was then linearly increased to 70 % B over 10 min, to 85 % B at 12 min, and held for 3 min before column re-equilibration at 30 % B. MS and MS/MS spectra were collected in positive ion mode using a DuoSpray ion source at 5 kV source voltage, 450 °C source temperature, and 50 psi

GS1/GS2 gas flows, with a declustering potential of 80 V. The instrument performed a survey

TOF-MS acquisition from m/z 80−1000 (150 ms accumulation time), followed by MS/MS on precursor ions from m/z 241.135 and 255.1505. Each MS/MS acquisition had an accumulation time of 150 ms and used three collision energy settings of 15, 30, and 50 V. The total cycle time was 0.95 s. High-resolution MS/MS spectra were analyzed using PeakView software (version

2.1) to determine tentative structural information.

4.3.8. HPLC semi-preparative purification

Purification of extracts was conducted on a semi-preparative scale (5 mL min-1) Agilent 1260

Infinity HPLC system (Agilent Technologies, Santa Clara, CA) with UV detection at 254 nm

(see results for more information of fractions purified). Samples were concentrated by drying under nitrogen until approximately half of original volume remained. Concentrated samples were centrifuged (5 min, 14,000 rpm) and the supernatants were transferred to vials. An Agilent

Pursuit XRs C18 column (5 μm, 250 x 10 mm) was employed at a flow rate of 5 mL min-1.

Mobile phases A and B were water and acetonitrile, both containing 0.1 % formic acid, respectively. The gradient started at 30 % B, which was held for 1 minute after sample injection.

Mobile phase B was then increased to 70 % from 1 to 4 minutes and then to 85 % for 4 to 14 minutes. Subsequently, the column was washed at 95 % B from 14.5 to 16 minutes, prior to re- equilibration at 30 % B. Sample injection volume was 900 μL. Fractions collected were re-tested by LC-MS and then subjected to biological testing to confirm activity.

4.3.9. LC-UV-MS analysis of HPLC purified fractions

LC-UV-MS analysis was conducted on an Agilent 1200 HPLC coupled to an Agilent 6210 ESI-

TOF mass spectrometer. Samples were injected onto an Eclipse Plus C18 50 x 3 mm column, with porous 1.8 μm particles (Agilent Technologies, Santa Clara, CA) with water (A) and ACN

(B), both containing 0.1 % formic acid, at a flow rate of 400 μL min-1. The gradient started at 30

% B, was held for 1 min, and was then linearly increased to 50 % B over 4 min, to 75 % B at 11 min, to 95 % at 11.5 min and held for 2.5 minutes before column re-equilibration. The UV detector was set to 254 nm and MS spectra were collected in positive ion mode from m/z 100-

1000. High-resolution MS spectra were internally calibrated for accurate mass measurements.

4.3.10. NMR characterization of purified fractions

NMR spectra were acquired on a Bruker Avance III-HD using a double-resonance 5 mm BBFO probe. Samples were dissolved in methanol-d4 and 1H spectra recorded at room temperature using a 30 degree pulse, 2 s recycle delay and 32 scans.

4.3.11. Effects of media on anti-Cmm activity of butanol extracts

Butanol extracts were also prepared from three additional media (other than NB): 1) King’s B

(KB); 2) Luria Broth (LB); and 3) Tryptic Soy Broth (TSB). Preparation of KB, LB and TSB were prepared as follows: for KB, per L of distilled H2O - proteose peptone No.3 20 g, glycerol

10 mL, K2HPO4 1.5 g, MgSO4 1.5 g; for LB, per L of distilled H2O - tryptone 10 g, NaCl 10 g, yeast extract 5 g; and for TSB, per L of distilled H2O - tryptic soy broth 30 g. Pseudomonas entomophila 23S was grown in each medium, extracted with butanol as described above, and the four extracts were tested for anti-Cmm activity.

In addition, the effect of each medium on the growth rate of P. entomophila 23S was studied in a

96-well plate. The initial culture was adjusted to 5×105 cfu mL-1 in each medium and 100 μL was applied to each well. Each medium, without the culture, served as a sterile control. The plate was incubated at 28 °C for 2 days using the Gen5TM Biotek microplate reader. The plate was double- orbital shaken, and the optical density at 600 nm was measured every 2 h. The data was analyzed with the SAS package program version 9.4 (SAS institute Inc., Cary, NC, USA) using the proc- mixed model, with time-points and concentrations as fixed effects. Tukey’s test was applied for

88 multiple comparison of the least square means when there was a significant treatment effect at the 95 % confidence level (p < 0.05).

4.4. Results

4.4.1. Butanol exacts from P. entomophila 23S culture showed anti-Cmm activity

The butanol extract obtained from our anti-Cmm bacterial culture was tested for anti-Cmm activity with a disk-diffusion assay on NBY plates (Figure 4.1), resulting in the inhibition of

Cmm growth as indicated by zone of inhibition (10 mm).

4.4.2. The 50, 60, 70 and 80 % fractions from solid phase extraction (SPE) showed anti-

Cmm activities

The butanol extract above was subjected to solid phase extraction (SPE), using 10 to 80 % ACN as eluent and each fraction was assessed for anti-Cmm activity. The disk-diffusion assay showed that among the eight fractions, the 50, 60, 70 and 80 % SPE fractions inhibited the growth of

Cmm as indicated by the zone of inhibition (Table 4.1).

In addition, effects of the 50, 60, 70 and 80 % SPE fractions on Cmm-growth were investigated at various concentrations, using spectrophotometry (Figure 4.2). For the 50 % SPE fraction, the minimum inhibitory concentration (MIC) was 256 µg mL-1 (Figure 4.2a). The Cmm growth showed initial effects at 30 h when the concentration was 512 µg mL-1. Growth of Cmm occurred at higher concentrations, but it was slower than the growth observed at the lower concentrations.

The MIC for the 60 % SPE fraction was 128 µg mL-1 (Figure 4.2b). Cmm growth was first affected at 24 h when the concentrations were 256 and 512 µg mL-1. Growth was minimal at 256

89 and 512 µg mL-1. For the 70 % SPE fraction, the MIC was 128 µg mL-1 (Figure 4.2c). Cmm growth was initially affected at 24 h at 256 and 512 µg mL-1. Like the 50 % SPE fraction, growth occurred at slower rates at the higher concentrations than at the lower concentrations. The MIC was 32 µg mL-1 for the 80 % SPE fraction (Figure 4.2d). Cmm growth was first affected at 18 h when the concentrations were 128, 256 and 512 µg mL-1. As with the 60 % SPE fraction, growth was minimal at 256 and 512 µg mL-1.

4.4.3. Fraction of SPE 80 % showed antagonistic activity against B. thuringinensis NEB17 and P. syringae pv. tomato DC3000.

SPE fractions were also tested against other plant-associated bacteria. For Bradyrhizobium japonicum USDA110, no fraction showed antagonistic activity. For Bacillus thuringiensis

NEB17, 80 % SPE fraction showed antagonistic activity, and the zone of inhibition was 3 mm.

For Pseudomonas syringae pv. tomato DC3000, the 80 % SPE fraction showed antagonistic activity, and the zone of inhibition was 3 mm.

4.4.4. Putative two anti-Cmm compounds were identified

SPE fractions prepared from NB medium only, from P. entomophila 23S grown in NB, and from

Pseudomonas sp. strain KJ grown in NB were tested for anti-Cmm activity through the agar-well diffusion assay. Anti-Cmm activities were not detected for any fractions prepared from the NB media only, or from the Pseudomonas sp. strain KJ grown in NB as compared to inhibition zones of 20, 14 and 11 mm for 60, 70 and 80 % fractions, respectively, from P. entomophila 23S.

These SPE extracts were then analyzed by LC-MS/MS to determine which compounds could potentially be responsible for the anti-Cmm activity. Two peaks of interest were found and are shown in Figure 4.3, where extracted ion chromatograms are overlaid for the three samples (NB media control, and the two strains grown in NB) for the 60, 70 and 80 % fractions. The peaks corresponded to protonated molecules having mass-to-charge ratios (m/z) of 241 and 255. The accurate masses measured for these two ions were 241.1341 and 255.1499, corresponding to protonated ions of C15H16N2O (2.4 ppm) and C16H18N2O (2.9 ppm), respectively. Figure 4.4 shows the high-resolution MS/MS spectra for these two peaks. From this data, we were able to confirm formulae for fragment ions (Tables 4.2 and 4.3) and hence start elucidating some structural features of these compounds. It is apparent that the two compounds are structurally very similar, with only one methyl group difference between them. By studying the fragmentation pathways, we have tentatively found that these compounds contain either an indole or quinoline ring system as well as a side chain, where the mentioned extra methyl group is present in the case of the ion at m/z 255.

4.4.5. Both anti-Cmm compounds have anti-Cmm activity when purified

Two of the most active SPE fractions (60 and 70 %) were subjected to HPLC purification to better characterize the putative anti-Cmm compounds. From the 60 % SPE fraction, three fractions were collected and two fractions were collected from the 70 % SPE fraction. Figure 4.5 shows representative HPLC traces from this purification showing the fractionation windows collected. The fractions were evaluated for purity by LC-UV-TOF-MS (see Methods) and five out of six were found to contain only one peak of interest in the UV and total ion chromatogram traces. Fraction 3 from the 60 % sample and Fraction 1 from the 70 % sample contained a

91 protonated molecule at m/z 241.1348 and Fraction 2 from the 70 % sample showed a protonated molecule at m/z 255.1490 (Figure 4.6).

After 85 HPLC injections, each fraction was pooled (~200 mL), concentrated 50x under nitrogen at 40 °C and then submitted for LC-MS/MS and NMR analysis, as well as testing for anti-Cmm activity (Figure 4.7).

4.4.6. Tentative structure of the compounds were deduced by NMR analysis

NMR analysis of HPLC purified fractions supported the quinoline ring part of structure, but could not yield a confirmed complete structure, likely due to interferences or low sensitivity of analyzed fractions. The side chain seems likely to contain a terminal isopropyl group for the compound at m/z 241, and as mentioned previously with an extra methyl for the compound at m/z 255. Unfortunately, the MS/MS and NMR data were not able to confirm a complete structure for these biologically active compounds.

4.4.7. Production of anti-Cmm compounds was enhanced under NB medium, where P. entomophila 23S grew slowest

Butanol extracts were prepared when the anti-Cmm bacterium was grown in various media,

King’s B (KB), Luria broth (LB), and tryptic soy broth (TSB). Only the butanol extracts made from NB-grown culture showed anti-Cmm activity and the butanol extracts from KB, LB, and

TSB-grown cultures did not manifest any anti-Cmm activity (Figure 4.8).

To investigate whether differences in the anti-Cmm activity of butanol extracts prepared from different media were due to the number of cells, growth of P. entomophila 23S was compared when it was in NB, LB, LB and TSB (Figure 4.9). Statistical analysis detected effects of media, time, and their interaction (media x time). At 8 h, the growth of P. entomophila 23S began to differ at a statistically detectable level; the optical density (OD600) was significantly higher for the TSB than other media. At the same time, the value for NB was significantly lower than those of other media. This trend continued to develop during the 20 h growth period. For KB and LB, the OD values were similar, except at the 10 and 12 h points, when the values for KB became greater than those of LB.

In addition, the butanol extracts prepared from each medium were analyzed by HPLC and checked for the presence of the active compounds, which were identified as having molecular weights of 240 and 254 Da, from the previous HPLC/LC-MS analyses. As shown by the overlaid extracted ion chromatograms from LC-MS analysis (Figure 4.10), peaks for protonated ions at both m/z 241 and 255 were present for the all four media. However, the peak intensities for the

NB-prepared butanol extracts were comparably higher than those for KB, LB, TSB-prepared butanol extracts.

4.5. Discussion

Butanol extracts, prepared from cultures of P. entomophila 23S clearly showed anti-Cmm activity, implying that the solvent extraction was effiective. Solid phase extraction (SPE) was also effective since 50, 60, 70 and 80 % fractions possessed anti-Cmm activity. Results from the agar-disk diffusion assay suggested superior anti-Cmm activities for the 60, 70, 80 % fractions

93 than the 50 % fraction. In particular, the 80 % fraction produced the lowest MIC, suggesting that the more hydrophobic fractions have stronger inhibitory effects toward Cmm. This could be due to the presence of several active materials and/or greater concentrations of such material(s). For all the four SPE fractions, the 512 and 256 µg mL-1 concentrations stopped or significantly slowed Cmm growth for all fractions, implying that the anti-Cmm compounds contained in the fractions had cidal and/or static effects depending on the concentrations. On the contrary, at low concentrations the fractions slightly enhanced the growth of Cmm. In addition to the anti-Cmm compounds, some growth-promoting compounds might have been present in the fractions, and at the low concentrations growth-promoting effects of the fractions are greater than the growth- inhibiting effects, resulting in enhanced Cmm growth.

Beyond Cmm, SPE fractions showed antagonistic activity against several plant-associated microbes. Bacillus thuringiensis NEB17 is a gram-positive, spore-forming endophytic bacterial strain isolated from soybean root tissues (Bai et al., 2002), and known to produce a bacteriocin that has plant growth promoting effects (Lee et al., 2009). Cmm is a gram-positive bacterium, and the antagonistic activity of the SPE fractions were different for the two, gram-positive bacteria: only the 80 % fraction inhibited the growth of B. thuringiensis NEB17, while the 60,

70, and 80 % fractions inhibited the growth of Cmm. A gram-negative bacterium, Pseudomonas syringae pv. tomato DC3000, which is a pathogen causing bacterial speck in tomato and

Arabidopsis thaliana (Whalen et al., 1991), was affected by the 80 % fraction only. Since SPE cannot separate the compounds completely, the compounds that inhibited the growth of B. thuringiensis and P. syringae pv. tomato DC3000 in the 80 % fraction might also have been present in other fractions, especially in the 70 % fraction, which was closest to the 80 % fraction

94 in activity; yet, its concentration might have been too low for the B. thuringiensis NEB17and P. syringae pv. tomato DC3000 to be affected in the disk-diffusion assay. Alternatively, these bacteria may have resistance mechanisms to detoxify the active compounds that affect Cmm. On the contrary, none of the SPE fractions showed antagonistic activity against the other gram- negative bacteria Bradyrhizobium japonicum UDSA110, suggesting that the antagonistic activity of the SPE fractions are not dependent on the gram-status of the evaluated bacteria. B. japonicum

UDSA110 is a gram-negative rhizobia originally isolated from soybean nodules and used for scientific studies regarding symbiotic nitrogen fixation (Kaneko et al., 2002). Since our P. entomophila 23S was originally isolated from a soybean field, one could also speculate that the anti-Cmm bacterium might not inhibit the B. japonicum UDSA110 growth because B. japonicum

UDSA110 supplies nitrogen to soybean plants, and therefore, the presence of B. japonicum

UDSA110, which contributes to the vigour of soybean plants, is beneficial to P. entomophila

23S.

As a result of the purification and analysis efforts, two anti-Cmm compounds were isolated in this study. We were not able to confirm the complete structures of these compounds. However, the data suggest that they have molecular formulas of C15H17N2O and C16H19N2O. They differ by one methyl group, and both have a quinoline ring as the largest part of the structure. A number of quinoline-based antibiotics currently exist, for example quinolone itself; these are largely used in human medical applications (Musiol et al., 2010; O’Donnell et al., 2010). In a previous study by

Xu et al. (2015) 12 anti-Cmm compounds were identified by screening a chemical library of yeast-active molecules; these compounds had piperidines, benzimidazoles, phenols, phenoxy isopropanolamines, or pyrrolidones as base structures. Quinoline seems not to have been

95 previously studied or/and reported on regarding antagonistic activities towards Cmm. Based on the molecular formula, searches were conducted in Chemspider (http://www.chemspider.com/), and 93 matches and 120 matches were found for the C15H17N2O and C16H19N2O compounds, respectively. None of them seems to be related with and/or relevant as biocontrol agents. The two compounds we isolated seem to be novel, at least as anti-Cmm compounds.

Type of growth medium influences the production of anti-Cmm compounds by P. entomophila

23S. This suggested that anti-Cmm activities of the butanol extracts prepared from different media are not due to cell numbers, but due to concentrations of the active compounds. The NB medium resulted in the greatest anti-Cmm compound production, while P. entomophila 23S grew slowest in this medium, implying that this medium has distinctive characteristics that are enhancing production of the anti-Cmm compounds by this strain. The production of antibiotics is often affected by nutrient status of the growth environment for the organisms producing them.

Nutrient deficiency is known to trigger the production of antibiotics for species of Streptomyces

(Rigali et al., 2008), Bacillus (Inaoka et al., 2003), Pseudomonas aeruginosa (Macfarlane et al.,

1999), and many other bacteria (Poole et al., 2012a; 2012b). Under stressful conditions some microorganisms switch on specific secondary metabolisms as a strategy to remain competitive and survive in their environment (Vining, 1990; Haas and Keel, 2003). A well-known example is

“stringent response”, which is mediated by the second messenger guanosine 5’-diphosphate-3’- diphosphate or ppGpp (St-Onge et al., 2015). In this response, nutrient deficiency, most notably amino acid deprivation, activates pathways required for stress resistance (Potrykus and Cashel,

2008; Dalebroux and Swanson, 2012; Poole, 2014), including sporulation in Bacillus and

Streptomyces (Ochi et al., 1981; Chakraburtty and Bibb, 1997), and quorum sensing for biofilm

96 formation in Pseudomonas aeruginosa (Van Delden et al., 2001). In an attempt to determine differences among the four media compared in this study, we calculated the nutrient composition of each medium (Appendix 8), using the available information provide by the company producing each medium

(https://www.bdbiosciences.com/documents/bionutrients_tech_manual.pdf). We found that the amounts of nutrients seem to be lower for NB as compared to other media. For example, the amount of nitrogen in NB is less than half of that in the other media. The less-rich nutrient composition of NB might act as a stress, or at least a growth limiting factor, for P. entomophila

23S, triggering greater production of anti-Cmm compounds. Among the four media, P. entomophila 23S grew best in TSB. The main difference between TSB and the other media is that TSB contains soybean meal, a plant component. Pseudomonas entomophila 23S was originally isolated from the rhizosphere of soybean. Thus, TSB may have been more favorable for growth of this bacterial strain than the other medium. Alternatively, specific elements may be present in the NB medium, and these elements may be inducing this strain to produce anti-Cmm compounds at higher levels. Further study is needed to understand what characteristics NB medium possesses, and other media do not possess, that enhance the production of anti-Cmm compounds by this strain. Since the active compounds are present at low concentrations in KB,

LB, and TSB butanol extracts, these extracts might also show anti-Cmm activities if they were concentrated, for instance by freeze-drying, to increase the concentrations of active compounds.

4.6. Conclusions

In this study, we isolated two compounds that inhibited the growth of Cmm from the novel bacterium P. entomophila 23S. Although their full structures were not confirmed, the data indicated that these compounds, with a molecular formulae of C15H17N2O and C16H19N2O, differ by one methyl group, and that both have a quinoline ring as the main component of structure.

Further research is required to elucidate the full structure of these compounds. These appear to be novel compounds with regard to inhibition of Cmm growth. Given the seriousness of Cmm- caused bacterial canker and lack of very effective control methods, these compounds would be of great potential as new biocontrol agents for the disease. Determining the effectiveness of the compounds for treating tomato bacterial canker is important. During the studies reported here, we had noted that P. entomophila 23S was producing more than one anti-Cmm compound, and we were able to isolate two of these. Research on these compounds may provide novel biocontrol agents for tomato bacterial canker. Comparing the anti-Cmm activities of the butanol extracts prepared from the growth media in which P. entomophila 23S grew, we found that the strain produced the anti-Cmm compounds in greater amounts when grown in the NB medium, where the strain grew slowest. The potential future subjects include further research to investigate factors that induce P. entomophila 23S to produce the anti-Cmm compounds, the mechanisms of inhibitory action of those compounds, and identification of the genes or proteins involved in the production of the anti-Cmm compounds. The knowledge generated could improve the production of the compounds and aid in finding new biocontrol agents for tomato bacterial canker.

4.7. Acknowledgements

We would like to acknowledge Ministère de l'Agriculture, des Pêcheries et de l'Alimentation du

Québec (MAPAQ), Natural Sciences and Engineering Research Council (NSERC) of Canada, and BioFuelNet for supporting the project. We also thank Dr. Alfred Souleimanov (McGill

University) for valuable advice during the extraction procedures.

Table 4.1 Anti-Cmm activity of SPE fractions % Zone of acetonitrile inhibition

(in (mm) fractions)

10 n/a

20 n/a

30 n/a

40 n/a

50 4

60 20

70 14

80 11

(n/a represents no inhibition)

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Table 4.2 Predominant product ions seen in MS/MS spectrum of m/z 241 compound, showing elemental formulae for each confirmed by accurate mass data, and corresponding neutral losses m/z ion m/z ppm neutral loss calculated formula

+ 57.0697 57.0699 C4H9 -3.9 C11H8N2O

+ 85.0640 85.0648 C5H9O -9.0 C10H8N2

+ 130.0649 130.0651 C9H8N -1.9 C6H9NO

+ 142.0644 142.0651 C10H8N -5.0 C5H9NO

+ 157.0758 157.0760 C10H9N2 -1.4 C5H8O

+ 169.0757 169.0760 C11H9N2 -1.6 C4H8O

+* 198.0788 198.0788 C12H10N2O -0.3 C3H7*

+ 241.1341 241.1335 C15H17N2O 2.4 (* denotes radical species)

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Table 4.3 Predominant product ions seen in MS/MS spectrum of m/z 255 compound, showing elemental formulae for each confirmed by accurate mass data, and corresponding neutral losses m/z ion m/z ppm neutral loss calculated formula

+ 71.0853 71.0855 C5H11 -3.0 C11H8N2O

+ 99.0799 99.0804 C6H11O -5.3 C10H8N2

+ 130.0651 130.0651 C9H8N -0.3 C7H11NO

+ 142.0649 142.0651 C10H8N -1.3 C6H11NO

+ 157.0761 157.0760 C10H9N2 0.3 C6H10O

+ 169.0774 169.0760 C11H9N2 8.4 C5H10O

+* 198.0782 198.0788 C12H10N2O -2.8 C4H9*

+ 255.1499 255.1492 C16H19N2O 2.9 (* denotes radical species)

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Figure 4.1 Anti-Cmm activity of butanol extract from the P. entomophila 23S culture Cmm culture (100 μL) was spread on a Nutrient Broth Yeast Extract (NBYE) agar plate, and wells (6 mm diameter) were made in the agar with a cork borer: 80 μL of 10 % acetonitrile (left), and 80 μL of butanol extract (right) was added into the well. The plate was incubated at 28 °C for 3 days.

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Figure 4.2 Effects of 50, 60, 70 and 80 % SPE fractions on Cmm growth. Fractions collected by SPE were freeze-dried, and resuspended in acetonitrile, from: 50 % fraction (a); 60 % fraction (b); 70 % fraction (c); and, 80 % fraction (d).

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Figure 4.3 Extracted ion chromatograms from SPE fractions from P. entomophila 23S, Pseudomonas sp. KJ, and NB media for the two compounds of interest m/z 241, and 255, as protonated molecules (MH+): (a) 60 %, (b) 70 %, (c) 80 % SPE fraction. 23S = P. entomophila 23S, KJ = Pseudomonas sp. KJ, NB = NB media

105

Figure 4.4 High resolution MS/MS spectra for compounds found at m/z 241(a) and 255 (b).

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Figure 4.5 Representative HPLC-UV chromatograms (at 265 nm) from semi-preparative purifications of SPE fractions (a) 60 % extract showing 3 fractions collected and (b) 70 % extract showing two fractions collected. All fractions were analyzed for purity and mass determination by high resolution LC-UV-TOF- MS.

107

Figure 4.6 Representative high resolution extracted ion chromatograms (left) and mass spectra (right) from two fractions F1(a) and F2 (b) from 70 % SPE sample, collected by semi-preparative HPLC purification. F1 contains a purified species giving MH+ at m/z 241.1348 and F2 yields a molecule with MH+ measured at m/z 255.1490. The total ion chromatograms and UV traces (at 254 nm) showed no other peaks present in these purified fractions.

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Figure 4.7 Anti-Cmm activities of HPLC fractions 1 and fraction 2 collected from 60 and 70 % SPE fractions. Cmm culture (100 μL) was spread on a Nutrient Broth Yeast Extract (NBYE) agar plate, and wells (6 mm diameter) were made in the agar with a cork borer: (a) 60 % fraction 1, (b) 60 % fraction 2, (c) 60 % fraction 3, (d) 70 % fraction 1, (e) 70 % fraction 2, and (f) 50 % acetonitrile (control). Eighty μL of fraction was added into the well. The plate was incubated at 28 °C for 3 days.

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Figure 4.8 Anti-Cmm activity of butanol extracts prepared from different media. Cmm culture (100 μL) was spread on Nutrient Broth Yeast Extract (NBYE) agar plates, and wells (6 mm diameter) were made with a cork borer. 80 μL of the butanol extracts prepared form each medium were added to the wells: a) nutrient broth; b) King’s B; c) luria broth; and d) tryptic soy broth. The plate was incubated at 28 °C for 3 days.

110

Figure 4.9 Growth of P. entomophila 23S grown in different media. Pseudomonas entomophila 23S was grown in NB, KB, LB, and TSB and the optical density (OD) at 600 nm was measured every 2 h for 20 h.: NB = nutrient broth; KB = King’s B; LB = luria broth; and, TSB = tryptic soy broth.

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Figure 4.10 Overlaid extracted ion chromatograms of two biologically-active molecules in butanol extracts from P. entomophila 23S cultured in four different culture media. NB = nutrient broth; KB = King’s B; LB = luria broth; and, TSB = tryptic soy broth.

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Connecting text

The results of Study 2 confirmed that our P. entomophila 23S produced compounds that inhibit the growth of Cmm. We also isolated the compounds and partially identified their chemical structures. We next decided to focus on induced systemic resistance (ISR) as part of the anti- pathogen effect. In addition to direct antimicrobial activity, biocontrol abilities of plant growth promoting rhizobacteria (PGPR) can be attributed to ISR. Not all PGPR possess ISR-inducing ability. I attempted to determine if P. entomophila 23S could trigger ISR and mitigate tomato bacterial canker disease in tomato plants infected by Cmm. In addition, the existing literature suggests that the signaling pathways of ISR vary among the PGPR, plants and pathogens involved. Therefore, I also decided to conduct a gene expression study to elucidate the role of plant hormones, specifically salicylic acid, jasmonic acid, and ethylene, in ISR provoked by the

P. entomophila 23S.

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Chapter 5 The biocontrol rhizobacterium Pseudomonas entomophila

23S induces systemic resistance in tomato (Solanum lycopersicum L.), against bacterial canker Clavibacter michiganensis subsps. michiganensis

Authors: Yoko Takishita1, Jean-Benoit Charron1, Donald L. Smith1

Affiliations:

Department of Plant Science, McGill University, Macdonald Campus, 21,111 Lakeshore Road,

Sainte-Anne-de-Bellevue, Quebec, Canada, H9X 3V9

This manuscript is submitted to Frontiers of Microbiology and being reviewed for publication.

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5.1. Abstract

Tomato bacterial canker disease, caused by Clavibacter michiganensis subsp. michiganensis

(Cmm) is a destructive disease and has been a serious concern for tomato industries worldwide.

Previously, a rhizosphere isolated strain of Pseudomonas entomophila (23S) was shown to inhibit the growth of Cmm in vitro. The potential of treating tomato plants with P. entomophila

23S to reduce the severity of tomato bacterial canker by inducing systemic resistance (ISR) was investigated using well characterized marker genes such as PR1a [salicylic acid (SA)], PI2

[jasmonic acid (JA)], and ACO [ethylene (ET)]. Two-week-old tomato plants were treated with

P. entomophila 23S by soil drench, and Cmm was inoculated into the stem by needle injection on

3, 5, or 7 days post drench. The results indicate that treatment of tomato plants with P. entomophila 23S 5 days before inoculation with Cmm significantly delayed the progression of the disease. Three weeks from the date of Cmm inoculation P. entomophila 23S treated plants had significantly higher dry shoot and root weight, higher levels of carbon, nitrogen, phosphorus and potassium in the leaf tissue, and the size of the Cmm population in the stem was significantly lower for the plants treated with P. entomophila 23S. Real-time quantitative PCR (qPCR) analysis showed that treatment with P. entomophila 23S alone was found to trigger a significant increase in the level of PR1a transcripts in tomato plants. When the plants were treated with P. entomophila 23S and inoculated with Cmm, the level of PR1a and ACO transcripts were increased, and this response was faster and greater than in plants inoculated with Cmm but not treated with P. entomophila 23S. Overall, the results suggest that P. entomophila 23S induced

ISR and the involvement of SA signaling pathways for ISR induced by P. entomophila 23S.

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5.2. Introduction

Bacterial canker disease, caused by Clavibacter michiganensis subsp. michiganensis (Cmm) is one of the most destructive diseases in tomato (Gleason et al., 1993; de León et al., 2011). It has been reported in both greenhouse and field tomato production worldwide, and has caused substantial crop losses (Chang et al., 1992a; Hausbeck et al., 2000; de León et al., 2011). Once plants are infected by Cmm, initial marginal leaf necrosis symptoms widen, leading to wilting of all leaves while canker develops on the stem; the whole plants can be stunted and severely wilted leading to death (de León et al., 2011). Cmm inoculum can originate from infected soils, seeds, transplants, tomato debris in soil, and operating tools and equipment. The bacteria can enter the plants through wounds and natural openings such as stomata and hydathodes after which they move to the xylem and multiply rapidly (Carlton et al., 1998; Gartemann et al., 2003; Sharabani et al., 2013). Production practices such as tying, pruning, clipping, spraying and harvesting can cause a high level of secondary infection spread to nearby healthy plants via workers’ fingers and tools (Ark, 1994; Gleason et al., 1993). Despite the seriousness of this disease, no control methods have been found to be completely effective. As no Cmm-resistant cultivars are commercially available, current control primarily relies on the use of pathogen-free certified seeds and transplants, good hygiene, disinfection of all tools, and crop rotations (Xu et al., 2015).

Hence an effective control method for bacterial canker is urgently needed.

Use of plant growth-promoting rhizobacteria (PGPR) as biocontrol agents offers an ecological means to manage disease problems in agriculture. PGPR are rhizosphere free-living bacteria that colonize plant roots and have beneficial effects on plant growth (Kloepper and Schroth, 1978;

Kloepper et al., 1989; Bouizgarne, 2013). The biocontrol ability of PGPR can be attributed to

116 two general mechanisms: direct antagonism against pathogens or induction of systemic resistance throughout the plant. Production of antimicrobial compounds, such as antibiotic metabolites, for instance bacteriocin, has been observed from many PGPR, and their inhibitory actions against pathogens contribute to reduction of plant diseases (Subramanian and Smith,

2015). In addition to direct suppressive effects on the pathogens, PGPR can trigger systemic resistance throughout the plant. PGPR-mediated induced systemic resistance (ISR) is often achieved by priming (Pieterse et al., 2014a). Priming is characterized as potentiated activation of defense responses, which are subsequently induced upon pathogen attack, resulting in enhanced plant defense capacity (Conrath et al., 2006).

Although many ISR-inducing PGPR have been discovered, signaling and activation mechanisms of the ISR are not completely understood. The involvement of three plant hormones, salicylic acid (SA), jasmonic acid (JA), and ethylene (ET) have been well documented. Conventionally,

PGPR-mediated ISR is known to be dependent on JA and ET signaling; it is an SA-independent process and does not lead to induction of PR proteins. On the other hand, SA is believed to be involved in systemic acquired resistance (SAR), which is induced by pathogen attack and follows induction of PR proteins (Van Loon and Bakker, 2005; Van wees et al., 2008; Pieterse et al., 2014a). As more research on ISR has been conducted, however, evidence of SA-dependent

ISR has been observed for some PGPR (Tjamos et al., 2005; Conn et al., 2008; Niu et al., 2012;

De Meyer et al., 1999; Schuhegger et al., 2006; Rudrappa et al., 2008).

Regarding tomato bacterial canker, several PGPR having antagonistic activity towards Cmm have been isolated and studied (Amkraz et al., 2010; Lanteigne et al., 2012; Deng et al., 2015;

117

Aksoy et al., 2017). Among them, the induction of ISR was only reported for Pseudomonas putida (CKPp9) (Aksoy et al., 2017). This ISR was accompanied by induction of significant amounts of phenolic compounds, which contributed to the disease reduction.

A rhizosphere bacterial strain of Pseudomonas entomophila 23S that possesses antagonistic activity towards Cmm in vitro was isolated in our laboratory. This strain has now been confirmed to produce several compounds that inhibit the growth of Cmm, and we have been able to isolate and partially identify two of these anti-Cmm compounds. A root drench treatment of this strain was also found to improve the growth of tomato seedlings.

The objectives of this study are to determine: 1) whether P. entomophila 23S induces ISR; 2) whether treatment with P. entomophila 23S reduces the severity of tomato bacterial canker; and

3) whether treatment with P. entomophila 23S causes changes in the transcript levels of defense- related genes, specifically PR1a, PI2 and ACO. PR1a codes for a pathogenesis-related protein, and has been used as a marker gene for salicylic acid resistance induction (Park et al., 2001;

Block et al., 2005; Niu et al., 2012; Martínez-Medina et al., 2013). PI2 codes for a proteinase inhibitor and is induced by wounding and jasmonic acid (JA; Peña-Cortés et al., 1995; Peiffer et al., 2009; Niu et al., 2012; Martínez-Medina et al., 2013). ACO is a gene coding for 1- aminocyclopropane-1-carboxylix acid (ACC) oxidase, the level of which is related to ethylene

(ET) production since ACO is an enzyme that converts ACC into ethylene (Stearns and Glick,

2003; Yim et al., 2014). Investigating the transcript levels of these three genes could help to determine the possible involvement of SA, JA and/or ET, and to understand ISR signaling pathways specific to this biotic stress.

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5.3. Materials and Methods

5.3.1. Bacterial growth conditions

The anti-Cmm bacterium under investigation, Pseudomonas entomophila 23S, was grown in

Nutrient Broth (NB, Difco; 8 g L-1) media at 28 °C, at 100 rpm. Clavibacter michiganensis subsp. michiganensis strain 930 (Cmm) was provided by Agriculture, Pecheries et Alimentation,

Quebec. Cmm was grown in NB media at 28 °C, at 150 rpm. Both bacteria were maintained as a glycerol stock in -80 °C.

5.3.2. Plant growth conditions

Tomato seeds (Bush Beefsteak 351; Stroke Seeds Inc. Thorold, ON, Canada) were surface- sterilized by soaking with 3 % (v/v) hypochlorite solution for 3 minutes, washing thoroughly with water, and drying overnight. The seeds were sown in pots (13 mm diameter) filled with agromix (G10). The plants were grown in a plant growth chamber under the following conditions: 16/8 h of photoperiod, 25/20 °C of day/night temperature, and 65 % of relative humidity; they were watered daily, and when needed, half-strength Hoagland solution was provided (Hoagland and Arnon, 1950; PlantMedia #30630037-5).

5.3.3. Effects of P. entomophila 23S on bacterial canker

Tomato plants were grown under growth chamber conditions as described above. The experiment was organized following a factorial design with two levels of P. entomophila 23S treatments (+ and -), and two levels of Cmm inoculation (+ and -). Treatments consisted of: 1)

Cont = without P. entomophila 23S treatment, and without Cmm inoculation (negative control);

2) Ps = treated with P. entomophila 23S; 3) Cm = without P. entomophila 23S treatment, and

119 inoculated with Cmm; and, 4) P+C = treated with P. entomophila 23S, and inoculated with

Cmm. Two weeks after sowing, the plants were treated with P. entomophila 23S. Each plant received 100 mL of the P. entomophila 23S cells suspended in 10 mM MgSO4 (approximately

8 -1 10 cfu mL ) for Ps and P+C treatments and 100 mL of 10 mM MgSO4 for Cont and Cm treatments. The Cmm inoculation was conducted on one of the fours days: 1, 3, 5 and 7 days after the date of P. entomophila 23S treatment (corresponding to 15, 17, 19, and 21 day-old

8 -1 plants). Ten µL of Cmm cells suspended in 10 mM MgSO4 (approximately 10 cfu mL ) for Cm

8 -1 and P+C, or 10 µL of 10 mM MgSO4 (approximately 10 cfu mL ) was inoculated by injecting into the main stem, where the cotyledon emerged, in each plant using a syringe (31 gauge needle,

Thermo Scientific #3170513). Three weeks after the Cmm inoculation, the plants were harvested, and leaf area, above and belowground dry weight were measured. For each plant, a stem piece

(approximately 1 cm) was sampled from 2-cm above the Cmm inoculation site in order to evaluate the Cmm population (number of cells per gram of tissue). The stem piece was weighed and ground with 1 mL of 10 mM MgSO4 using mortar and pestle. The extract was centrifuged at

10,000 rpm for one minute, and ten-fold serial dilutions of the supernatant were plated on Cmm- selective agar plates (Ftayeh et al., 2011). The number of Cmm colonies were enumerated 3-4 days after incubation at 28 °C. Dried aboveground tissues were ground to fine powder with mortar and pestle and used to analyze carbon (C), nitrogen (N), phosphorus (P) and potassium

(K) contents. An elemental analyzer (Model NC2500; CE Instruments, Milan, Italy) was used for the C and N analysis. For the P and K analysis, a flow injection analyzer and atomic absorption spectrophotometer were used, respectively (Parkinson and Allen, 1975). First, the tissues were digested in sulfuric acid and peroxide with the addition of catalysts (lithium and selenium) at 340

°C for approximately 3 h. The content was diluted to 100 mL and used for the flow injection

120 analyzer. Phosphorus was measured colorimetrically at 880 nm after being complexed with ammonium molybdate (Lachat Instruments QuickChem Method 13-115-01-1-B, 6645 West Mill

Road, Milwaukee, WI 53218 USA). Potassium was read on a 10-fold diluted subsample (from the same diluted sample used for the P analysis) by emission on a Varian 220FS (now part of

Agilent) atomic absorption spectrophotometer. Seven plants were sampled for each inoculation time (1, 3, 5, and 7 days) per treatment, and the experiment was repeated twice.

5.3.4. Effects of P. entomophila 23S on defense-related genes of tomato plants

Tomato plants were grown as described in the “Plant Growth Conditions” section above. Two weeks after sowing, the plants were treated with P. entomophila with the cells, suspended in 10

8 -1 mM MgSO4 (approximately 10 cfu mL ), and applied as a soil drench. For control plants, 100 mL of 10 mM MgSO4 was applied to a plant in the same manner. At 1, 3, 5, and 7 days after the date of P. entomophila 23S application, the shoot was harvested (biomass pooled for each four plants), flash-frozen with liquid nitrogen, and stored in -80 °C for subsequent real-time quantitative PCR (qPCR) analysis. The experiment was conducted three times with independent biological replicates.

5.3.5. Effects P. entomophila 23S on defense-related genes of tomato plants infected with bacterial canker

Tomato plants were grown in the same manner as described in the “Effects of P. entomophila

23S on bacterial canker” section, above. At two weeks from sowing, the appropriate plants were treated with P. entomophila, and after 5 days, 10 µL of Cmm cells suspended in 10 mM MgSO4

8 -1 8 (approximately 10 cfu mL ) for Cm and P+C, or 10 µL of 10 mM MgSO4 (approximately 10

121 cfu mL-1) were inoculated into each plant by injecting into the main stem, where the cotyledon emerged, with a syringe (31 gauge needle, Thermo Scientific #3170513). At 1, 3, 5, and 7 days after Cmm inoculation, the shoot was harvested (pooled from four plants), flash-frozen with liquid nitrogen, and stored in -80 °C for subsequent real-time qPCR analysis. The experiment was conducted three times with independent biological replicates.

5.3.6. Quantitative real-time PCR (qPCR) analysis

Total RNA from tomato leaves was extracted using TRIzol Reagent (Thermo Fisher Scientific catalog#: 15596026), and the RNAs were treated with DNase I (AmbionTM DNaseI, Thermo

Fisher Scientific catalog#: AM2222) according to the manufacturer’s instructions. The integrity of the extracted RNA was checked on agarose gel electrophoresis, and its purity and concentration were assessed by a ND-1000 spectrophotometer (NanoDrop). Complementary

DNA (cDNA) was synthesized using an iScript Advanced cDNA Synthesis Kit (Biorad, catalog#: 1725037), following the manufacturer’s instructions. The cDNA was diluted to 400 ng

µL-1 and stored in -20 °C for qPCR. The gene-specific primers used are listed in Table 5.1. The qPCR was conducted on a CFX Connect Real Time System (BioRad) with Green-2-Go qPCR

Mastermix (Biobasic, catalog#: QPCR004-S), using the cycling program of: 95 °C for 10 minutes for the enzyme activation step, 95 °C for 15 seconds for the initial denaturation step, 60

°C for 60 seconds for annealing and extension, repeated for 40 cycles (PR1: 52 °C; PI2: 56 °C;

ACO: 52 °C: GAPDH: 56.4 °C). Each plate consisted of three technical replicates from the three independent biological replicates. The Ct value obtained was normalized against the housekeeping gene GAPDH, and the relative gene expression (fold change) was calculated using

2− ΔΔCT method (Livak and Schmittgen, 2001).

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5.4. Results

5.4.1. Pseudomonas entomophila 23S alleviated bacterial canker by ISR

The effects of P. entomophila 23S on the disease progress were studied for tomato plants infected with Cmm when the interval period between P. entomophila 23S application and Cmm inoculation dates were 3, 5, and 7 days (Figure 5.1a, b, c). The disease progression of the Cm and

P+C treatment were similar. The leaves started to wilt from 6 days post-Cmm inoculation. The percentage of wilted leaves increased over time for the treatment in which the Cmm inoculation was 3-days after P. entomophila 23S application, and reached more than 80 % at 21 days post-

Cmm inoculation (Figure 5.1a). When the interval was 5 days, Cm treatment resulted in a disease progression similar to the Cm treatment for the 3-day interval. However, the disease progression for the P+C treatment was slower, and the percentage of wilted leaves was about 60 % at 21 days post-Cmm inoculation (Figure 5.1b). When the interval was 7 days, the disease progression was slower than the disease progression at 3- and 5-day intervals. The percentage of wilted leaves was also smaller at 21 days post-Cmm inoculation, less than 60 % of the Cm treatment

(Figure 5.1c). At day 21, most plants were dead or stunted for the 3- and 5-day intervals (Figure

5.1a, b), while for the 7-day interval, the plants looked weak but not as damaged as those at 3- and 5- day intervals (Figure 1c). In addition, the 7-day interval treatments of the Cm and P+C treatment resulted in a similar disease progression (Figure 5.1c). There were no disease symptoms observed for the Cont and Ps treatments at any time.

The dry weights of shoots and roots were measured for the tomato plants that were treated with

P. entomophila 23S and infected with Cmm when the interval period between P. entomophila

23S application and Cmm inoculation dates were 3, 5, and 7 days (Figure 5.2a, b). The shoot dry

123 weights of the Cont and Ps treatments were not significantly different for any of the intervals

(Figure 5.2a). When the interval was 3 and 5 days, the shoot dry weights of the Cont and Ps treatments were significantly different from those of the Cm and P+C treatments while they were not significantly different when the interval was 7 days. When the interval was 3 and 7 days, the shoot dry weights of the Cm and P+C treatments were not significantly different. Between the

Cm and P+C treatments, the shoot dry weight was significantly different for the 5-day interval, although it was not significantly different for the 3-day and 7-day intervals. Similar trends were found for the root dry weight (Figure 5.2b).

At the harvest (21 days post-Cmm inoculation), a 1-cm- length stem piece above the inoculation site was taken and used for counting Cmm colony forming units (cfu) (Table 5.2). The number of cfu for the P+C were significantly lower than that for the Cm treatment when the interval was 5 days, while no difference was detected when the intervals were 3 and 7 days.

Nutrient levels of shoots, specifically nitrogen (N), phosphorus (P), potassium (K), and carbon

(C) were measured when tomato plants were treated with P. entomophila 23S and inoculated with Cmm after 3, 5, and 7 day intervals (Figure 5.3a, b, c, d). For all nutrients measured, the levels were not significantly different between the Cont and Ps treatments, and the Cm and P+C treatments at the 3 day time interval, and the levels of the Cm and P+C treatments were significantly lower than those of the Cont and Ps treatments. When the time interval was 5 days, the levels for all the nutrients of the P+C treatment were significantly higher than those of the

Cm treatment (Figure 5.3a, b, c, d). For the 7-day-interval, the levels of the Cm treatment tended

124 to be lower but overall, the levels for all the nutrients were not very different among the treatments (Figure 5.3a, b, c, d).

5.4.2. Pseudomonas entomophila 23S treatment increased the transcript level of PR1a

The transcript levels of PR1a, PI2, and ACO were studied in tomato plants 1, 3, 5, and 7 days after soil drench treatment with P. entomophila 23S (Figure 5.4a, b, c). The transcript levels of

PR1a, a marker gene of salicylic acid activity were higher for the P. entomophila 23S treatment that those of the control treatment at all the time points (Figure 5.4a). Its transcript abundance was greatest at day 3 (10 fold), then diminished at days 5 (4 fold) and 7 (5 fold). For PI2, a marker gene of jasmonic acid activity, and the ethylene marker gene ACO transcript, the transcript levels were not different between Control and P. entomophila 23S treatments at any of the time points (Figure 5.4b, c).

5.4.3. Treatment with P. entomophila 23S prior to Cmm inoculation caused faster and greater accumulation responses of PR1a and ACO transcripts

Transcript levels of PR1a, PI2, and ACO were also examined when tomato plants treated with P. entomophila 23S by soil drench and inoculation of Cmm into the main stem by needle injection 5 days later (Figure 5.5a, b, c). Day 5 was chosen because the previous physiological experiment, described above, indicated that the disease in severity was smallest when Cmm was inoculated after 5 days, rather than 3 or 7 days. The transcript level of PR1a was not different among treatments at day 1; however, at days 3 and 5, the P+C treatment resulted in significantly higher transcript levels (54 fold for day 3 and 58 fold for day 5) than other treatments (Figure 5.5a). At day 7, its transcript level was still higher (55 fold), and the transcript levels for the Ps and Cm

125 treatments were also as high as that of the P+C treatment (34 fold for the Ps and 75 fold for Cm treatment) (Figure 5.5a). The transcript levels of PI2 were relatively high at day 1 for all the treatments (87, 25, 48 and 68 fold for the Cont, Ps, Cm and P+C treatments, respectively) as compared with those at day 3, 5, 7 (Figure 5.5b). In addition, they were variable among biological replicates, resulting in large standard errors. No difference was detected among treatments at days 1, 3 and 5. At day 7, the transcript level of the Cm treatment (9 fold greater than the control) was significantly higher than other treatments. The transcript level of ACO gradually increased going from day 1 to day 7 (Figure 5.5c). For all the time points: the transcript level of the Cont treatment was the lowest; the level of the Ps and Cm treatments were similar to or slightly higher than those of the Cont treatment; and, no difference was detected between the Ps and Cm treatments. The P+C treatment was always the highest among the treatments (1.5, 1.75, 2.5, and 4.5 fold relative to the Cont, Ps, Cm and P+C treatments, respectively).

5.5. Discussion

Our results demonstrated that P. entomophila 23S triggered induced systemic resistance (ISR), which probably contributed to the reduction of bacterial canker severity by Cmm in tomato plants when Cmm was inoculated 5 days after the P. entomophila 23S application. In this study, P. entomophila 23S was applied before Cmm inoculation, and the two bacteria were spatially separated since P. entomophila 23S was applied as soil drench and Cmm was injected to the main stem by syringe needle. Stem samples taken from above the inoculation site only contained

Cmm, and not P. entomophila 23S (data not shown). Thus, direct contact between Cmm of the P. entomophila 23S was not likely to occur, and the bacterial canker reduction that was observed must have been a result of ISR effects. At the same time, since P. entomophila 23S is known to 126 produce anti-Cmm compounds in vitro, such anti-Cmm compounds, if produced by the strain when on the roots, and taken up by the plants, could be translocated and affect the growth of

Cmm that colonized the stem. The effects of such anti-Cmm compounds by P. entomophila 23S in plants needs further study.

In our experimental system, the age and/or size of the plants at the time of the Cmm-inoculation might have influenced the disease progression within plants. The date of visual symptom appearance, and the severity of bacterial canker are affected by temperature, plant age, inoculum concentration, and cultivar (Chang et al., 1992b). In young tomato plants, the disease symptoms caused by Cmm are known to appear earlier and they are more susceptible to infection than mature plants (Chang et al., 1992b; Sharabani et al., 2013). The age of the tomato plants in our study, were 17, 19 and 21 days at the time of Cmm-inoculation when the time-interval between the P. entomophila treatment 23S and Cmm inoculation was 3, 5 and 7 days, respectively.

Although these time gaps do not seem large, we visually observed that the plants at this stage grew quickly. Growth of the plants was relatively rapid at this time, probably because the tomato cultivar used was a fast-maturing variety. In fact, the results showed that leaf wilting began to appear earlier for the 3-day-interval as compared to the 7-day-interval.

Cmm can survive as an endophyte in tomato plants, but induction of disease symptoms requires a certain minimum population level, generally 108 cfu g-1 of plant tissue (Garteman et al., 2003).

Compared to this number, as well as to the reports from past studies (Balaji et al., 2008;

Sharabani et al., 2013), the Cmm population in the stem samples in our study was relatively small although leaf wilting was observed. This could be because the tomato plants used in our

127 study were younger than those used in other studies (17-21 days vs. 28 days). In fact, the analysis detected significant effects of time-interval on Cmm population in the stem samples, another indication that plant age had an influence on disease development.

The results showed that P. entomophila 23S increased the transcript level of the PR1a, but not of

PI2 and ACO, suggesting that the ISR induced by P. entomophila 23S may involve the salicylic acid (SA) pathway, rather than jasmonic acid (JA) or ethylene (ET). Although JA/ET are generally considered to be key hormone(s) for ISR response, which is mediated by non- pathogenic plant growth promoting bacteria (PGPR), different results have been reported from more recent studies (De Vleesschauwer and Höfte, 2009), and the ISR induced by the P. entomophila 23S seems to be associated with this newly discovered pattern. The signaling pathway for ISR seems species specific, that is specific to the rhizobacterium, and pathogen involved (Ryu et al., 2003; Conn et al., 2008; Djavaheri, 2007). Researchers agree that hormone crosstalk plays an important role in regulating ISR. Regarding SA-and JA/ET pathways, antagonistic interaction has been documented from many studies (Koornneef and Pieterse, 2008), and this might apply to our case, where P. entomophila 23S induced SA response but not JA and

ET. The antagonistic interaction between SA and JA may be the outcome of resource allocation, costs of induction, or a means for the plant to adaptively tailor its responses to different enemies and a target for manipulation by enemies (Thaler et al., 2012). Generally, SA-dependent defense response is said to be effective against biotrophic pathogens, while JA/ET-dependent defense response is effective against necrotrophic pathogens (Sorokan et al., 2013). In this respect, Cmm would be a suitable target for the SA-dependent ISR because Cmm is considered as a biotrophic pathogen (Eichenlaub and Gartemann, 2011). We cannot exclude the possibility that JA and ET

128 are involved in the ISR provoked by P. entomophila 23S. Mutant plants impaired in SA, JA, and

ET pathways could be utilized to confirm whether these hormones are required for ISR.

In our study, 5 days was the optimal interval between P. entomophila application and Cmm inoculation for alleviating bacterial canker. Past studies showed that several days are required for

ISR to develop and to deliver resistance against various phytopathogens (Babu et al., 2015). The strain-specific different best time interval between PGPR treatment and pathogen inoculation could be related to the population size of the PGPR. The protection by PGPR-mediated ISR is said to be apparent only when the roots were colonized by PGPR at a specific threshold population size (Raaijmakers et al., 1995). Also, Zhang et al. (2004) indicates “quorum sensing effects”, where a certain bacterial population density is essential to produce a signal molecule that is involved in provoking ISR.

Furthermore, the results demonstrated priming effect of the P. entomophila 23S treatment. Faster and/or greater defense-gene response - priming - has been observed for many ISR-inducing

PGPR (Pieterse et al., 2014a). The observed accumulation response of PR1a after Cmm inoculation was faster and quantitatively greater for plants pre-treated with P. entomophila 23S than plants without the pre-treatment. Since the P. entomophila 23S treatment alone also induces accumulation response of PR1a, the prior- P. entomophila 23S treatment probably prepares the plants for pathogen attack, by making this response faster and greater and enhancing the defense capacity of the plants. Priming may explain the disease reduction observed for the 5-day interval treatment in our study. To understand the effects of the P. entomophila 23S treatment for disease

129 reduction, studying the responses of other defense-related genes (e.g. other PR proteins, defense- related enzymes) and whether they also show priming effects would be helpful.

Faster and greater accumulation response was also observed for the ACO, but the situation may be different from the PR1, because the ACO transcript abundance was not affected by P. entomophila 23S treatment alone. From past studies, ethylene is known to play a critical role in bacterial canker of tomato. Plants with reduced ethylene production or impairment of ethylene perception have diminished disease severity (Balaji et al., 2008; Savidor et al., 2011), and thus host-derived ethylene is suggested to be a requirement for the disease development by Cmm. Our finding that the P. entomophila 23S treatment alone did not significantly affect ACO abundance but the same treatment did after Cmm inoculation supports past studies indicating that ethylene is involved Cmm infection. At the same time, the fact that the P. entomophila 23S treatment can make this response faster and greater, and quantitatively and alleviate the disease, suggests that

P. entomophila 23S might have modulated the role of ethylene. This, consequently, could influence disease development by Cmm and thus contribute to the disease reduction observed in our study.

The transcript level of PI2 showed different trend from that of PR1a or ACO, elevated on day 1, especially for the control treatment. The PI2 gene encodes a proteinase inhibitor that is activated by wounding and jasmonic acid (JA) (Farmer and Ryan, 1992). In this study, Cmm-inoculation was conducted by injecting the cultural suspension into the main stem with a syringe needle. The control treatment plants were also treated in the same manner, except that MgSO4 buffer was injected instead of Cmm culture. Therefore, even the control and P. entomophila 23S treated

130 plants were wounded to some degree, and this might explain why the transcript level of PI2 was high on day 1. The transcript level of PI2 decreased as the days progressed for all the treatments, but for Cmm inoculated plants, its level remained high at day 7. Treatment with P. entomophila

23S might have explained this; while the Cmm inoculated plants must combat Cmm invasion, the same plants were less affected by the effect of prior P. entomophila 23S treatment through ISR mechanism, requiring less proteinase inhibitors for their defense response.

5.6. Conclusions

This study demonstrated that P. entomophila 23S could induce ISR in tomato plants and reduce the severity of tomato bacterial canker disease that is caused by Cmm. The best time interval between the P. entomophila 23S treatment and Cmm inoculation, for reducing the severity of bacterial canker, was 5-days in our experimental system, which used drench application of P. entomophila, stem inoculation of Cmm, and young tomato plants. This interval, as well as the effectiveness of ISR, could change with different methods, timing of bacterial application and of pathogen inoculation, and plant age. Such information would be useful, especially for the commercial use of this bacterium. Our study also suggested that the ISR induction by P. entomophila 23S may involve SA in its signaling pathway. However, the possibility of JA and/or

ET involvement should not be discounted. Mutant plants with impaired hormonal pathways could be studied in the context of a Cmm infection to confirm their involvement. In addition, our results provided new insights on the role of ethylene in development of Cmm driven disease.

Further studies to elucidate the signaling pathways of P. entomophila 23S ISR would certainly add knowledge for understanding molecular mechanisms of ISR induced by PGPR, but it would provide useful information regarding the disease strategies taken by Cmm.

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5.7. Acknowledgements

We would like to acknowledge Ministère de l'Agriculture, des Pêcheries et de l'Alimentation du

Québec (MAPAQ), the Natural Sciences and Engineering Research Council (NSERC) of

Canada, and BioFuelNet for supporting the project. We are grateful for Hélène Lalande (McGill

University) for phosphorus and potassium analyses, and for Werda Saeed (McGill University) for carbon and nitrogen analyses of plant tissues. We thank Alex Martel (McGill University) for helping with real-time qPCR. We greatly appreciate Dr. Sowmyalakshmi Subramanian (McGill

University) for advice during the experiments and for editorial input into this paper.

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Table 5.1 List of primers and sequences used for the gene expression study ID Target gene Primer sequence (5 ' to 3') M69247 Pathogenesis related protein GTGGGATCGGATTGATATCCT (PR1a)1 CCTAAGCCACGATACCATGAA X94946 Proteinase inhibitor (PI2)2 AATTATCCATCATGGCTGTTCAC CCTTTTTGGATCAGATTCTCCTT AB013101 1-aminocyclopropane-1-carboxylix AAGATGGCACTAGGATGTCAATAG acid oxidase (ACO)3 TCCTCTTCTGTCTTCTCAATCAAC U97257 GAPDH4 CTGGTGCTGACTTCGTTGTTG GCTCTGGCTTGTATTCATTCTCG

1López-Ráez et al. (2010), Martínez-Medina et al. (2013); 2Song et al. (2015); 3Yim et al. (2014); 5Chalupowicz et al. (2010)

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Table 5.2 Pseudomonas entomophila 23S treatment, 5-day prior to Cmm inoculation, reduced the Cmm population in the stem Day 3 Day 5 Day 7

Cma 6.84 ± 0.17 6.57 ± 0.15 6.11 ± 0.06

P+Cb 7.19 ± 0.08 6.16 ± 0.16 * 6.21 ± 0.16

Two-week-old tomato plants were treated with P. entomophila 23S (or 10 mM MgSO4) by soil drench, and after 3, 5 or 7 days of Cmm (or 10 mM MgSO4) inoculation into the main stem by needle injection. After 3 weeks a 1-cm piece of stem (2 cm above the inoculation site) was sampled for enumeration of Cmm cells. The values represent the number of Cmm colony forming units (log10). a Cm = inoculated with Cmm b P+C = treated with P. entomophila 23S, and inoculated with Cmm *Asterisk indicates statistical significance between the Cm and P+C treatments based on the student’s t-test p <0.05.

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Figure 5.1 Pseudomonas entomophila 23S treatment, 5 days prior to Cmm inoculation, delayed progress of bacterial canker Two-week-old tomato plants were treated with P. entomophila 23S by soil drench, and after 3 days (A), 5 days (B) or 7 days (C), Cmm was inoculated in the main stem by needle injection. The number of wilted leaves was counted every 3 days for 3 weeks. Treatments are: Cont = control; Ps = treated with P. entomophila 23S; Cm = inoculated with Cmm; and, P +C = treated with P. entomophila 23S, and inoculated with Cmm. Cont and Ps treatments showed no disease symptom throughout the experiment.

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Figure 5.2 Pseudomonas entomophila 23S treatment, 5 days prior to Cmm inoculation, increased weights of shoots and roots

Two-week-old tomato plants were treated with P. entomophila 23S (or 10 mM MgSO4) by soil drench, and after 3, 5 or 7 days, Cmm (or 10 mM MgSO4) was inoculated into the main stem by needle injection. The plants were harvested after 3 weeks and sampled for: (a) weight of dry shoots and (b) weight of dry roots. Error bars indicates standard error of the mean. Different associated letters indicate statistical significance based on ANOVA followed by Tukey’s multiple comparison test. Treatments are: Cont = control; Ps = treated with P. entomophila 23S; Cm = inoculated with Cmm; and, P +C = treated with P. entomophila 23S, and inoculated with Cmm.

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Figure 5.3 Pseudomonas entomophila 23S treatment, 5 days prior to Cmm inoculation, improved nutrient levels of leaf tissue

Two-week-old tomato plants were treated with P. entomophila 23S (or 10 mM MgSO4) by soil drench, and after 3, 5 or 7 days, Cmm (or 10 mM MgSO4) was inoculated into the main stem by needle injection. The plants were harvested after 3 weeks. Different associated letters indicate statistical significance based on ANOVA followed by Tukey’s multiple comparison test. Treatments are: Cont = control; Ps = treated with P. entomophila 23S; Cm = inoculated with Cmm; and, P +C = treated with P. entomophila 23S, and inoculated with Cmm.

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Figure 5.4 Pseudomonas entomophila 23S treatment induced an increase in the transcript level of PR1a

Two-week old tomato plants were treated with P. entomophila 23S (Pse) or 10 mM MgSO4 (Control) and after 1, 3, 5 and 7 days, the shoots were harvested and used for RNA extraction and real-time qPCR. Error bars indicated standard error of the mean. Association with different letters indicates statistical significance based on ANOVA followed by Tukey’s multiple comparison test p <0.05.

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Figure 5.5 Pseudomonas entomophila 23S treatment, 5 days prior to Cmm inoculation, induced faster and greater response in transcript levels of PR1a and ACO

Two-week old tomato plants were treated with P. entomophila 23S (or 10 mM MgSO4) and after 5 days, Cmm (or 10 mM MgSO4) was inoculated into the stem by needle injection: Cont = control; Ps = treated with P. entomophila 23S; Cm = inoculated with Cmm; and, P+C = treated with P. entomophila 23S, and inoculated with Cmm. After 1, 3, 5 and 7 days, the shoots were harvested and used for RNA extraction, and real-time qPCR. Error bars indicated standard error of the mean. Association with different letters indicates statistical significance based on ANOVA followed by Bonferroni multiple comparison p<0.05.

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Chapter 6 Summary, discussion, conclusions and future research

Bacterial canker caused by Clavibacter michiganensis subsp. michiganensis (Cmm) is an important disease problem for tomato. The disease has spread worldwide, both in greenhouse and field-grown tomato. Although efforts have been made to improve control technologies for this disease, there is considerable need for further innovation. Industry partners have indicated that the pathogen is becoming more virulent and more difficult to control (oral communication with the tomato production company Savoura). The use of plant growth promoting rhizobacteria

(PGPR) has attracted attention in agriculture, as a means to reduce the use of agrochemicals, and to move towards more ecological and sustainable crop production. A strain of rhizobacterium that has antagonistic activity towards Cmm in vitro has been isolated in our laboratory. We have conducted this project to answer the following underlying questions:

1. What is the species of the isolated anti-Cmm bacterial strain (now known to be P.

entomophila 23S), and what are its general characteristics?

2. Does it show potential as a PGPR?

3. What are the anti-Cmm compounds that are produced by P. entomophila 23S?

4. Which growth conditions best support the anti-Cmm compound production?

5. Does P. entomophila 23S induce systemic resistance (ISR) in tomato plants infected with

Cmm? If so, which defense-related hormones (salicylic acid, jasmonic acid, and ethylene) are

relevant in the ISR it provokes?

6.1. Summary of Results

The first study in this thesis characterized the isolated anti-Cmm bacterial strain. The anti-Cmm bacterial strain was identified as a strain of Pseudomonas entomophila. We designated it as P.

140 entomophila 23S. The strain is able to solubilize inorganic phosphorus, to produce siderophores, hydrogen cyanide, and indole acetic acid. Pseudomonas entomophila 23S also showed resistance to several common antibiotics. The strain was also shown to directly promote the growth of tomato seedlings. A proteomic study indicated that during interactions with Cmm, P. entomophila 23S secreted stress-related proteins such as chaperons, peptidases, and ABC- transporters, and elongation factors.

The second study isolated two anti-Cmm compounds produced by P. entomophila 23S. The molecular formulae of these compounds were C15H17N2O and C16H19N2O. Although the full structures was not confirmed, analysis suggested that these two compounds differed by only one methyl group, and that both had a quinoline ring as the core structural element in the molecule.

The production of anti-Cmm compounds was greatest when the bacterium was grown in the nutrient broth medium, where the bacterial growth was slowest.

The third study demonstrated that P. entomophila 23S induced ISR in tomato plants that were infected with Cmm. The treatment of tomato plants with P.entomophila 5 days before Cmm infection alleviated the severity of bacterial canker. Treatment with P. entomophila 23S alone increased the transcript level of tomato gene PR1a, which was related to salicylic acid production, while no significant change was detected for PI2 and ACO, which were related to jasmonic acid and ethylene production, respectively. When the tomato plants were treated with

P. entomophila 23S, prior to Cmm inoculation, the PR1a and ACO transcripts were accumulated faster and to a greater degree than plants inoculated with only Cmm.

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6.2. General Discussion

The three studies conducted revealed unique characteristics of P. entomophila 23S, a newly isolated strain of rhizobacterium. Pseudomonas entomophila 23S was found to have porperties that could allow it to enhance plant growth. This is probably the consequence of a lengthy evolution between the bacterium and the plant that adapted the bacterium to assist in plant growth which, in turn, assisted the bacterium. Pseudomonasentomophila 23S was originally isolated from soybean roots, and thus is a member of the phytomicrobiome (Smith et al., 2015), specifically the rhizomicrobiome. Another interesting finding is that P. entomophila L48, which was isolated from fruit fly found to be most closely related with our strain, has entomocidal activity against fruit fly (Vodovar et al., 2005) as opposed to antibacterial activity, against Cmm, as is the case with P. entomophila 23S.

The three research studies included in the thesis suggested significant potential for the use of P. entomophila 23S in tomato production, especially in low-input or organic tomato production systems. The bacterium can be used as a biocontrol agent for bacterial canker, and also as a biofertilizer because of its abilities to solubilize phosphorus, as shown through the work presented here. The plant assay proved that it could promote the growth of tomato seedlings.

Given the seriousness of bacterial canker disease, using the P. entomophila 23S could become an important control mechanism, and one that does not involve potentially environmentally damaging agrochecmicals. It is also attractive because it is a very low-input and inexpensive input.

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When greenhouses become infected with Cmm the plants must be removed and the space must be decontaminated. The anti-Cmm compounds produced by P. entomophila 23S could be effective in this role. They could be applied alone, or possibly with live P. entomophila 23S cells, to make the greenhouse space pathogen-free.

The cost of producing the anti-Cmm compounds could be further reduced by improving industrial production methods. It seems that induction of stress in P. entomophila 23S could increase production level. Our study showed that the production of the anti-Cmm compounds was greater in nutrient broth media where P. entomophila 23S grows slowest, and the NB medium seems less rich than the other media evaluated. At the same time, according to the exo- proteomic study, P. entomophila was found to be under stress during direct interaction with

Cmm. It would be interesting to examine whether the production of anti-Cmm compounds is enhanced when P. entomophila 23S is grown in the presence of Cmm or in the presence of specific materials produced by Cmm that produce a stress response in P. entomophila 23S. If stress is a key to higher production of anti-Cmm higher temperatures might supply the correct level of stress and accelerate the production process increasing the levels of compound production and reducing the costs associated with fermentor time.

Genomic studies could also provide knowedlge that helps to improve the production of anti-

Cmm compounds. If the genome of P. entomophila 23S was sequenced and analyzed, the genes involved in the production of anti-Cmm compounds, related pathways, or enzymes might be predicted. This can open the door to genetic manuplation. For instance, the identified genes

143 could be cloned into industrial strains (e.g. Eschericia coli). One could also increase the expression of such genes. For future commercialization of the anti-Cmm compounds, the genetic approach may be useful.

6.3. General Conclusions

This project demonstrated that P. entomophila 23S is a PGPR. It possesses multiple characteristics ideal for such an organism: 1) It can promote growth of tomato seedlings, 2) It diminishes the severity of tomato bacterial canker by ISR; salicylic acid may be involved for its induction. Although further studies under greenhouse or field conditions, with mature plants, are essential, a potential use of this bacterium in tomato plants, for plant growth promotion and biocontrol of bacterial canker, was confirmed.

Two anti-Cmm compounds, produced by P. entomophila 23S, were isolated and their molecular structures were partially elucidated through this work. The amounts of these compounds was influenced by the medium in which P. entomophila 23S grew. The two isolated anti-Cmm compounds have not been previously reported and are believed to be novel concerning their anti-

Cmm activity.

6.4. Future research directions

As next steps, following aspects should be investigated:

1. P. entomophila 23S

– Whole genome sequencing for strain identification

2. Plant growth promotion by P. entomophila 23S application

144

– Observations carried to full tomato plant growth and fruit production

3. Control of bacterial canker by P. entomophila 23S

– Observations regarding effects on fruit production by fully grown tomato plants

– Study of different application methods and timing

4. Control of other diseases

– Study of the effects of P. entomophila 23S application on tomato plants for control of

bacterial speck, which is caused by Pseudomonas syringae pv. tomato DC 3000

5. ISR induction by P. entomophila 23S

– Determination whether P. entomophila 23S induces ISR in other crop plants

6. Signaling pathway of ISR induction

– Study of plant responses using mutants with impaired salicylic acid, jasmonic acid or

ethylene pathways, to confirm the possible involvement of each

– Perform microarray studies to provide a broader picture of this form of ISR regulation

7. Anti-Cmm compounds

– Determination of the complete structure of the isolated anti-Cmm compounds

– Study of the effects of the isolated anti-Cmm compounds on tomato plants

– Isolation of any other anti-Cmm compounds produced by P. entomophila 23S

– Genomic approach to increase the production of anti-Cmm compounds

– Factors to improve the production of anti-Cmm compounds

145

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Appendix: Supplemental information for Chapter 3 proteomics

* Pe = P. entomophila 23S is grown in NB media. PeC = P. entomophila 23S is grown in NB media with Cmm

173

* Pe = P. entomophila 23S is grown in NB media. PeC = P. entomophila 23S is grown in NB media with Cmm

174

Appendix 2 Functional classification of GO distribution for Cmm proteins grown in NB media with/without P. entomophila 23S: a) Cellular component; b) Main Enzyme classes; c) Molecular function, and; d) Biological function

* Cm = Cmm is grown in NB media. CmP = Cmm is grown in NB media with P. entomophila 23S

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* Cm = Cmm is grown in NB media. CmP = Cmm is grown in NB media with P. entomophila 23S

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Appendix 3 Pseudomonas entomophila 23S proteins (not shown in the paper), for which level increased when grown with Cmm

Molecular Fold Identified proteins NCBI Accession Pe PeC Fisher’s exact weight (kDa) change Test (P-value)

elongation factor G WP_011531886.1 79 11 26 2.4 < 0.00010 3-hydroxyisobutyrate WP_011532058.1 30 4 9 2.2 < 0.00010 dehydrogenase copper chaperone WP_011534515.1 17 6 13 2.2 < 0.00010 PCu(A)C beta-ketoacyl-[acyl- carrier-protein] WP_011534737.1 43 5 9 1.8 0.00021 synthase I molecular chaperone WP_011532126.1 69 11 18 1.6 < 0.00010 DnaK sulfate ABC transporter substrate- WP_011536264.1 37 32 50 1.6 < 0.00010 binding protein hypothetical protein WP_044488591.1 13 5 8 1.6 0.00075 5- (carboxyamino)imidaz WP_011536443.1 17 6 9 1.5 0.00045 ole ribonucleotide mutase dienelactone hydrolase WP_011532636.1 29 29 39 1.3 < 0.00010 family protein gamma-glutamyl- WP_011535848.1 46 3 4 1.3 0.026 phosphate reductase peptidoglycan-binding WP_011532948.1 94 7 9 1.3 0.00085 protein 50S ribosomal protein L7/L12 WP_011531883.1 13 24 29 1.2 < 0.00010 [Pseudomonas] isocitrate dehydrogenase WP_011533427.1 45 4 5 1.2 0.014 (NADP(+)) DNA starvation/stationary WP_011535164.1 18 33 35 1.1 < 0.00010 phase protection protein CoA transferase WP_011533669.1 25 7 8 1.1 0.0026 subunit A malate dehydrogenase WP_011533566.1 58 11 12 1.1 0.0003 (quinone) a: identified as proteins of P. entomophila L48, except for those with [Pseudomonas], which indicates proteins from family of Pseudomonas b: Pe = P. entomophila 23S is grown in NB media c: PeC = P. entomophila 23S is grown with Cmm

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Appendix 4 Pseudomonas entomophila 23S proteins (not shown in the paper), for which level decreased when grown with Cmm

Molecular Fold Fisher’s exact Identified proteinsa NCBI Accession weight Peb PeCc change Test (P-value) (kDa)

hypothetical protein WP_011534530.1 43 43 0 0 0.00014 molybdenum cofactor biosynthesis WP_011534840.1 19 40 0 0 0.00026 protein B pyridoxal phosphate- dependent WP_011535033.1 43 39 0 0 0.00032 aminotransferase DegT/DnrJ/EryC1/St rS family WP_011533678.1 46 38 0 0 0.0004 aminotransferase acyloxyacyl WP_011534057.1 18 36 0 0 0.0006 hydrolase LPS-assembly WP_011531842.1 107 35 0 0 0.00074 protein LptD multidrug RND WP_011535776.1 52 35 0 0 0.00074 transporter argininosuccinate WP_011536330.1 52 34 0 0 0.00091 lyase m18 family aminopeptidase WP_011532729.1 47 33 0 0 0.0011 [Pseudomonas entomophila] phosphomannomutas e/phosphoglucomutas WP_011536399.1 51 32 0 0 0.0014 e sugar phosphate WP_011533824.1 46 31 0 0 0.0017 isomerase/epimerase 3- phosphoserine/phosp WP_083789155.1 40 30 0 0 0.0021 hohydroxythreonine transaminase ribulose-phosphate 3- WP_011531853.1 24 30 0 0 0.0021 epimerase electron transfer flavoprotein- WP_044488267.1 61 29 0 0 0.0025 ubiquinone oxidoreductase UDP-N- acetylglucosamine 2- WP_011534125.1 43 27 0 0 0.0038 epimerase (non- hydrolyzing) LamB/YcsF family WP_044488343.1 28 26 0 0 0.0047 protein N-acetyltransferase WP_011532002.1 18 26 0 0 0.0047 acyl-CoA WP_011532866.1 89 25 0 0 0.0058 dehydrogenase choline ABC transporter substrate- WP_011536174.1 34 25 0 0 0.0058 binding protein

178

serine/threonine WP_011533495.1 51 23 0 0 0.0088 protein kinase carboxylating nicotinate-nucleotide WP_011532257.1 30 22 0 0 0.011 diphosphorylase 3-carboxymuconate WP_044487869.1 41 21 0 0 0.013 cyclase S49 family peptidase WP_011532881.1 36 21 0 0 0.013 2,3- bisphosphoglycerate- independent WP_011531800.1 55 20 0 0 0.016 phosphoglycerate mutase type II 3- dehydroquinate WP_011535870.1 16 20 0 0 0.016 dehydratase [Pseudomonas] Nif3-like dinuclear metal center WP_011535569.1 27 20 0 0 0.016 hexameric protein isoquinoline 1- oxidoreductase WP_011533399.1 80 20 0 0 0.016 subunit beta phosphogluconate WP_011535472.1 66 20 0 0 0.016 dehydratase threonine ammonia- WP_011536225.1 55 20 0 0 0.016 lyase, biosynthetic Zn-dependent WP_011536001.1 48 19 0 0 0.02 protease acetyl-CoA WP_011532033.1 46 18 0 0 0.025 acetyltransferase cytochrome c4 WP_011531534.1 21 18 0 0 0.025 NADP(H)-dependent WP_011535558.1 39 17 0 0 0.03 aldo-keto reductase amidase WP_011533246.1 60 17 0 0 0.03 long-chain fatty acid WP_011532688.1 45 17 0 0 0.03 transporter spermidine/putrescin e ABC transporter WP_011531850.1 38 17 0 0 0.03 substrate-binding protein sulfate ABC transporter substrate- WP_011531940.1 22 17 0 0 0.03 binding protein acyl-CoA WP_011532082.1 32 16 0 0 0.037 thioesterase II carboxymuconolacto ne decarboxylase WP_011534344.1 16 16 0 0 0.037 family protein dihydrodipicolinate synthase family WP_011533588.1 32 16 0 0 0.037 protein long-chain fatty acid WP_011532688.1 45 17 0 0 0.03 transporter glutamate synthase WP_011531757.1 162 16 0 0 0.037 large subunit glycosyl hydrolase WP_011533645.1 96 16 0 0 0.037 family 5 penicillin acylase WP_011536240.1 87 16 0 0 0.037 family protein

179

peptidase C69 WP_011536000.1 52 16 0 0 0.037 phage major tail WP_011535242.1 17 16 0 0 0.037 protein FAD-binding WP_011536230.1 51 15 0 0 0.046 oxidoreductase acyl-CoA WP_011536028.1 15 15 0 0 0.046 thioesterase formate dehydrogenase WP_011531942.1 35 15 0 0 0.046 subunit beta outer membrane autotransporter barrel WP_011534186.1 105 15 0 0 0.046 domain-containing protein

porin WP_011535463.1 50 15 0 0 0.046 Cluster of : type VI secretion system tube protein Hcp WP_011531920.1 [2] 19 521 3 0.006 < 0.00010 [Pseudomonas] (WP_011531920.1) oligopeptidase A WP_083789141.1 77 70 1 0.01 < 0.00010 ATP phosphoribosyltransf WP_011535944.1 43 55 1 0.02 0.00013 erase regulatory subunit NAD(P)/FAD- dependent WP_011532219.1 36 49 1 0.02 0.00042 oxidoreductase dihydroxy-acid WP_011531705.1 65 42 1 0.02 0.0015 dehydratase aspartate/tyrosine/aro matic WP_011532901.1 43 86 2 0.02 < 0.00010 aminotransferase dihydrodipicolinate synthase family WP_011535119.1 34 156 3 0.02 < 0.00010 protein glycine dehydrogenase WP_011535490.1 102 222 5 0.02 < 0.00010 (aminomethyl- transferring) hypothetical protein WP_011533683.1 254 164 4 0.02 < 0.00010 porphobilinogen WP_011536312.1 37 58 1 0.02 < 0.00010 synthase class II fumarate WP_011532758.1 49 40 1 0.03 0.0022 hydratase amidohydrolase WP_011532353.1 30 38 1 0.03 0.0032 glycine dehydrogenase WP_011536285.1 105 74 2 0.03 < 0.00010 (aminomethyl- transferring) serine hydroxymethyltransf WP_011532152.1 45 165 5 0.03 < 0.00010 erase NAD(P)H-dependent WP_011534674.1 20 69 3 0.04 0.00031 oxidoreductase ketohydroxyglutarate WP_011535458.1 24 67 3 0.04 0.00043 aldolase

180

heme iron utilization WP_011535516.1 27 47 2 0.04 0.003 protein alanine--glyoxylate aminotransferase WP_011533921.1 41 26 1 0.04 0.028 family protein beta- hydroxydecanoyl- WP_011534736.1 19 25 1 0.04 0.033 ACP dehydratase hypothetical protein WP_011532536.1 41 24 1 0.04 0.039 thioredoxin-disulfide WP_011532256.1 34 80 4 0.05 0.0002 reductase 6- carboxytetrahydropte WP_011533721.1 19 76 4 0.05 0.00038 rin synthase TonB-dependent WP_011533696.1 80 62 3 0.05 0.00099 siderophore receptor amino acid WP_011533578.1 52 62 3 0.05 0.00099 decarboxylase dihydroorotase WP_011536055.1 44 60 3 0.05 0.0014 type VI secretion system contractile WP_011531906.1 56 55 3 0.05 0.003 sheath large subunit dienelactone hydrolase family WP_011534741.1 26 42 2 0.05 0.007 protein ABC transporter substrate-binding WP_011536395.1 58 40 2 0.05 0.0097 protein pyridoxine 5'- WP_044488397.1 27 38 2 0.05 0.013 phosphate synthase isocitrate lyase WP_008096174.1 49 130 6 0.05 < 0.00010 [Pseudomonas] hypothetical protein WP_011535859.1 179 178 9 0.05 < 0.00010 tail protein WP_011535215.1 42 118 6 0.05 < 0.00010 type III PLP- WP_011532360.1 43 100 5 0.05 < 0.00010 dependent enzyme outer membrane WP_011531643.1 49 54 3 0.06 0.0036 porin, OprD family prolyl WP_011536083.1 37 49 3 0.06 0.0077 aminopeptidase acetyl-CoA C- WP_044488455.1 41 57 4 0.07 0.0069 acyltransferase ABC transporter substrate-binding WP_011532380.1 59 43 3 0.07 0.019 protein nucleoside hydrolase WP_011533201.1 36 43 3 0.07 0.019 N-acetyl-gamma- glutamyl-phosphate reductase WP_011531871.1 36 147 10 0.07 < 0.00010 [Pseudomonas entomophila] dihydroorotase WP_011532522.1 38 91 7 0.08 0.0011 aspartate aminotransferase WP_011532048.1 48 471 40 0.08 < 0.00010 family protein amidohydrolase WP_086009466.1 68 141 12 0.09 0.00014

181

ABC transporter substrate-binding WP_011533169.1 44 56 5 0.09 0.02 protein IMP dehydrogenase WP_011535448.1 52 288 27 0.09 < 0.00010 hypothetical protein WP_011533684.1 19 187 17 0.09 < 0.00010 homogentisate 1,2- WP_011535651.1 48 154 15 0.1 0.00033 dioxygenase aldehyde WP_011532006.1 55 183 20 0.1 0.00042 dehydrogenase ketol-acid WP_011535735.1 36 257 33 0.1 0.00055 reductoisomerase glutamate--ammonia WP_011531808.1 52 260 35 0.1 0.0011 ligase glycerol kinase WP_011532512.1 55 211 27 0.1 0.0016 TonB-dependent hemoglobin/transferri WP_011535476.1 95 150 18 0.1 0.0037 n/lactoferrin family receptor guanosine monophosphate WP_011533722.1 40 135 17 0.1 0.0091 reductase cytosol WP_011535497.1 52 115 14 0.1 0.012 aminopeptidase hypothetical protein WP_011533821.1 89 109 13 0.1 0.012 hypothetical protein WP_011532388.1 60 104 14 0.1 0.034 putative selenate ABC transporter WP_011532322.1 31 63 7 0.1 0.038 substrate-binding protein VOC family protein WP_011534119.1 17 85 11 0.1 0.042 1,02 hypothetical protein WP_011533685.1 37 128 0.1 < 0.00010 7.00 hypothetical protein WP_011532178.1 43 323 40 0.1 < 0.00010 nucleoside deaminase WP_044487849.1 45 410 44 0.1 < 0.00010 ornithine WP_011535483.1 38 500 69 0.1 < 0.00010 carbamoyltransferase porin WP_011533004.1 37 854 112 0.1 < 0.00010 dihydrolipoyl dehydrogenase WP_011534749.1 50 444 78 0.2 0.016 [Pseudomonas] ATP synthase WP_011536501.1 50 697 131 0.2 0.019 subunit beta serine 3- 3,53 WP_011532827.1 51 752 0.2 0.027 dehydrogenase 9.00 2,26 flagellin WP_011534918.1 30 350 0.2 < 0.00010 6.00 DUF1329 domain- WP_011532243.1 51 319 104 0.3 0.0013 containing protein peroxiredoxin WP_009684560.1 22 143 50 0.3 0.0075 [Pseudomonas] urocanate hydratase WP_011536088.1 61 565 156 0.3 0.021 outer membrane WP_011532299.1 444 170 65 0.4 0.00043 autotransporter branched-chain amino acid ABC WP_011532595.1 39 185 68 0.4 0.00076 transporter substrate- binding protein

182

transporter WP_011536352.1 15 78 35 0.4 0.0011 sulfate ABC transporter substrate- WP_011532926.1 37 98 40 0.4 0.002 binding protein superoxide dismutase WP_011532441.1 22 139 49 0.4 0.0072 amino acid ABC transporter substrate- WP_011535574.1 36 75 30 0.4 0.0084 binding protein [Pseudomonas] cystine transporter WP_011531636.1 29 57 24 0.4 0.011 subunit peroxiredoxin WP_011533509.1 21 77 30 0.4 0.011 ABC transporter substrate-binding WP_044488314.1 28 64 26 0.4 0.012 protein DUF541 domain- WP_011532384.1 26 70 27 0.4 0.017 containing protein DUF3108 domain- WP_011532661.1 26 58 22 0.4 0.033 containing protein ubiquinol- cytochrome c WP_011535557.1 21 58 22 0.4 0.033 reductase iron-sulfur subunit 1,22 hypothetical protein WP_011536029.1 19 432 0.4 < 0.00010 5.00 surface adhesion 1,21 WP_011531578.1 596 547 0.4 < 0.00010 protein 9.00 branched-chain amino acid WP_011533322.1 37 58 29 0.5 0.00076 aminotransferase choline ABC transporter substrate- WP_011536167.1 35 44 20 0.5 0.01 binding protein chitin-binding protein WP_011533765.1 24 129 70 0.5 < 0.00010 DUF4426 domain- WP_011531734.1 15 34 22 0.6 0.00025 containing protein hypothetical protein WP_011531496.1 8 25 14 0.6 0.0082 [Pseudomonas] Cluster of acyl-CoA dehydrogenase WP_011536103.1 [2] 65 16 10 0.6 0.014 (WP_011536103.1) amine oxidoreductase WP_011533348.1 69 16 9 0.6 0.031 histidine triad nucleotide-binding WP_011531867.1 13 56 35 0.6 < 0.00010 protein [Pseudomonas] nitrogen regulatory protein P-II 1 WP_002555808.1 12 54 35 0.6 < 0.00010 [Pseudomonas] MetQ/NlpA family WP_011531521.1 28 134 82 0.6 < 0.00010 lipoprotein RidA family protein WP_011536411.1 14 161 91 0.6 < 0.00010 alpha/beta hydrolase [Pseudomonas WP_011533984.1 30 137 77 0.6 < 0.00010 entomophila] flagellar hook protein WP_011534931.1 49 69 38 0.6 < 0.00010 FlgE PrkA family serine WP_011531835.1 74 23 17 0.7 0.00041 protein kinase 183

succinate dehydrogenase WP_011534753.1 64 14 10 0.7 0.0075 flavoprotein subunit elongation factor Tu WP_010951775.1 43 189 140 0.7 < 0.00010 [Pseudomonas] branched-chain amino acid ABC WP_011535927.1 40 189 139 0.7 < 0.00010 transporter substrate- binding protein cytochrome c5 WP_011536383.1 13 23 18 0.8 0.00017 phage major tail tube WP_011535214.1 18 20 15 0.8 0.00081 protein class II fumarate WP_011532408.1 48 9 7 0.8 0.018 hydratase 4-oxalocrotonate WP_011535780.1 7 38 30 0.8 < 0.00010 tautomerase DUF1842 domain- WP_011534071.1 21 67 54 0.8 < 0.00010 containing protein arginine deiminase WP_011535482.1 47 102 78 0.8 < 0.00010 glycine cleavage WP_011536286.1 13 27 21 0.8 < 0.00010 system protein H peptidyl-prolyl cis- WP_011532713.1 26 39 33 0.8 < 0.00010 trans isomerase peptidylprolyl WP_011531841.1 49 15 14 0.9 0.00027 isomerase SurA molecular chaperone GroES WP_003260750.1 10 10 9 0.9 0.004 [Pseudomonas] co-chaperone YbbN WP_011531961.1 32 7 6 0.9 0.021 polyamine ABC transporter substrate- WP_011536274.1 40 95 87 0.9 < 0.00010 binding protein [Pseudomonas] taurine ABC transporter substrate- WP_011531642.1 34 126 111 0.9 < 0.00010 binding protein thioredoxin TrxA WP_011536309.1 12 49 43 0.9 < 0.00010 a: identified as proteins of P. entomophila L48, except for those with [Pseudomonas], which indicates proteins from family of Pseudomonas b: Pe = P. entomophila 23S is grown in NB media c: PeC = P. entomophila 23S is grown with Cmm

184

Appendix 5 Pseudomonas entomophila 23Sproteins, for which level did not change when grown with Cmm

Fisher’s Molecular Fold Identified proteinsa NCBI Accession Peb PeCc exact Test weight (kDa) change (P-value)

amino acid ABC WP_011536193.1 28 162 167 1 < 0.00010 transporter hypothetical protein WP_003259780.1 9 69 69 1 < 0.00010 [Pseudomonas] cold-shock protein WP_011533204.1 8 7 7 1 0.0077 50S ribosomal protein L4 WP_008089819.1 22 6 6 1 0.014 [Pseudomonas] 50S ribosomal protein L3 WP_011531887.1 23 2 2 1 0.16 [Pseudomonas] a: identified as proteins of P. entomophila L48, except for those with [Pseudomonas], which indicates proteins from family of Pseudomonas b: Pe = P. entomophila 23S is grown in NB media c: PeC = P. entomophila 23S is grown with Cmm

185

Appendix 6 Cmm proteins (not shown in the paper), for which level decreased when grown with P. entomophila 23S

Molecular Fold Fisher’s Identified proteinsa NCBI Accession Cmb CmPc weight (kDa) change exact Test (P-value)

Efem/EfeO family WP_086506227.1 42 160 0 0 0.0016 lipoprotein (+1) sugar ABC transporter WP_086505785.1 47 146 0 0 0.0029 substrate-binding protein branched-chain amino acid ABC WP_012039255.1 transporter 44 136 0 0 0.0043 (+1) substrate-binding protein penicillin-binding WP_086505909.1 62 134 0 0 0.0046 protein 2 ATP synthase subunit beta WP_012037855.1 53 132 0 0 0.005 [Clavibacter] hypothetical protein WP_086506025.1 17 131 0 0 0.0052 hypothetical protein WP_079534396.1 32 131 0 0 0.0052 glycerol kinase WP_079533407.1 55 128 0 0 0.0059 WP_079531184.1 hypothetical protein 32 127 0 0 0.0061 (+1) WP_043561055.1 serine protease 121 125 0 0 0.0066 (+4) sugar ABC transporter WP_012039388.1 48 120 0 0 0.0081 substrate-binding DNA-directed RNA polymerase subunit WP_012039319.1 143 119 0 0 0.0084 beta' [Clavibacter] WP_079532056.1 hypothetical protein 46 117 0 0 0.0092 (+1) WP_087196584.1 serine protease 49 113 0 0 0.011 (+1) ribonucleoside- diphosphate WP_012039118.1 93 112 0 0 0.011 reductase subunit alpha BMP family ABC transporter WP_012037662.1 37 111 0 0 0.012 substrate-binding protein peptidyl-prolyl cis- WP_012038851.1 34 111 0 0 0.012 trans isomerase hypothetical protein WP_086507870.1 27 109 0 0 0.013 WP_086506263.1 hypothetical protein 34 108 0 0 0.013 (+1) WP_012039179.1 hypothetical protein 19 108 0 0 0.013 (+2)

186 hypothetical protein WP_011931197.1 27 108 0 0 0.013 WP_079531904.1 serine protease 31 107 0 0 0.014 (+1) sugar ABC transporter WP_086506863.1 35 106 0 0 0.014 substrate-binding protein D-alanyl-D-alanine carboxypeptidase/D WP_086505311.1 46 103 0 0 0.016 -alanyl-D-alanine- (+1) endopeptidase Cluster of peptidase WP_094113551.1 35 103 0 0 0.016 (WP_094113551.1) [3] 2-oxoglutarate dehydrogenase, E2 component, WP_079533166.1 49 102 0 0 0.017 dihydrolipoamide succinyltransferase polar amino acid ABC transporter WP_012039317.1 29 102 0 0 0.017 substrate-binding (+1) protein sugar ABC transporter WP_086506863.1 35 106 0 0 0.014 substrate-binding protein cytochrome c WP_012038529.1 34 100 0 0 0.018 oxidase subunit II DUF1775 domain- WP_011931836.1 26 99 0 0 0.019 containing protein WP_012038635.1 serine protease 33 94 0 0 0.023 (+3) WP_012038422.1 transketolase 75 93 0 0 0.024 (+3) glycine dehydrogenase WP_012038885.1 105 92 0 0 0.025 (aminomethyl- transferring) septum formation WP_079534978.1 38 87 0 0 0.031 initiator (+1) ABC transporter WP_011931305.1 substrate-binding 46 86 0 0 0.032 (+2) protein WP_012038081.1 hypothetical protein 63 86 0 0 0.032 (+2) hypothetical protein WP_011931192.1 18 84 0 0 0.034 Cluster of carboxypeptidase regulatory-like WP_086505225.1 77 83 0 0 0.036 domain-containing [2] protein (WP_086505225.1) peptidoglycan- WP_012038559.1 43 82 0 0 0.037 binding protein succinate--CoA WP_012039236.1 30 82 0 0 0.037 ligase subunit alpha (+1) hypothetical protein WP_086505215.1 20 81 0 0 0.039 6-phospho-beta- WP_011931568.1 48 80 0 0 0.04 glucosidase

187 serine protease WP_011931203.1 30 80 0 0 0.04 hypothetical protein WP_087198324.1 31 78 0 0 0.044 pyruvate dehydrogenase WP_012038309.1 (acetyl- 101 78 0 0 0.044 (+1) transferring), homodimeric type 50S ribosomal WP_012039303.1 31 76 0 0 0.048 protein L2 alpha/beta hydrolase WP_012038620.1 30 76 0 0 0.048 Cluster of pectate WP_086503556.1 lyase 29 76 0 0 0.048 [6] (WP_086503556.1) WP_079535052.1 hypothetical protein 45 74 0 0 0.051 (+2) sugar ABC transporter WP_012037477.1 33 74 0 0 0.051 substrate-binding protein serine/threonine- WP_011931234.1 61 71 0 0 0.058 protein kinase (+1) ABC transporter WP_012038000.1 substrate-binding 38 69 0 0 0.063 (+1) protein ADP-forming succinate--CoA WP_043584273.1 40 69 0 0 0.063 ligase subunit beta (+1) [Clavibacter] LytR family transcriptional WP_043560497.1 43 67 0 0 0.068 regulator aminopeptidase N WP_012038143.1 94 66 0 0 0.071 DNA-directed RNA WP_012039320.1 polymerase subunit 129 65 0 0 0.074 (+1) beta type 1 glutamine amidotransferase WP_012038747.1 20 65 0 0 0.074 [Clavibacter] carbohydrate- WP_012039127.1 48 65 0 0 0.074 binding protein (+1) serine/threonine WP_012038560.1 69 65 0 0 0.074 protein kinase (+2) 30S ribosomal WP_012038069.1 35 63 0 0 0.08 protein S2 glucose-6- WP_079533281.1 phosphate 55 63 0 0 0.08 (+1) isomerase proline racemase WP_087198333.1 36 63 0 0 0.08 Cluster of class A WP_086506576.1 beta-lactamase 33 61 0 0 0.087 [3] (WP_086506576.1) GDP-mannose 4,6- WP_012038287.1 39 60 0 0 0.09 dehydratase branched-chain amino acid ABC WP_012039251.1 49 60 0 0 0.09 transporter permease

188 succinate dehydrogenase WP_012037656.1 66 59 0 0 0.094 flavoprotein subunit hypothetical protein WP_011931202.1 30 57 0 0 0.1 peptidyl-prolyl cis- WP_012038378.1 34 57 0 0 0.1 trans isomerase (+1) polyribonucleotide WP_012038734.1 nucleotidyltransfera 80 57 0 0 0.1 (+1) se serine protease WP_011931271.1 31 57 0 0 0.1 carbohydrate kinase WP_086505815.1 35 56 0 0 0.11 hypothetical protein WP_012039172.1 32 56 0 0 0.11 phosphoglycerate WP_086507379.1 42 56 0 0 0.11 kinase sugar ABC WP_012039532.1 transporter ATP- 28 56 0 0 0.11 (+1) binding protein beta-N- acetylglucosaminida WP_011931268.1 63 54 0 0 0.11 se Cluster of WP_012038097.1 hypothetical protein 55 54 0 0 0.11 [3] (WP_012038097.1) pyruvate kinase [Clavibacter WP_012038446.1 51 54 0 0 0.11 michiganensis] phosphate ABC transporter WP_012039194.1 37 53 0 0 0.12 substrate-binding protein WP_079531359.1 hypothetical protein 19 51 0 0 0.13 (+1) WP_043560344.1 hypothetical protein 20 51 0 0 0.13 (+1) cystathionine beta- WP_012038522.1 27 49 0 0 0.14 lyase hypothetical protein WP_012038720.1 34 48 0 0 0.15 peptidoglycan WP_012039155.1 32 48 0 0 0.15 endopeptidase (+3) sugar ABC transporter WP_011931328.1 48 48 0 0 0.15 substrate-binding protein elongation factor Ts WP_012038070.1 29 47 0 0 0.15 6-phosphogluconate dehydrogenase WP_011931222.1 32 45 0 0 0.16 (decarboxylating) [Clavibacter] WP_011931828.1 hypothetical protein 28 45 0 0 0.16 (+1) hypothetical protein WP_050976328.1 11 45 0 0 0.16 lipase WP_086507444.1 30 45 0 0 0.16 WP_079532341.1 hypothetical protein 49 44 0 0 0.17 (+1) DUF4012 domain- WP_012037595.1 64 43 0 0 0.18 containing protein (+2)

189

Cluster of endo-1,4- WP_079533212.1 beta-xylanase A 47 43 0 0 0.18 [2] (WP_079533212.1) glycine/betaine ABC transporter WP_012038219.1 32 43 0 0 0.18 substrate-binding (+1) protein hypothetical protein WP_011931228.1 22 43 0 0 0.18 sugar ABC transporter WP_011931416.1 46 43 0 0 0.18 substrate-binding protein ABC transporter substrate-binding WP_012038796.1 49 42 0 0 0.19 protein TlpA family protein WP_043560937.1 21 42 0 0 0.19 disulfide reductase carbohydrate ABC transporter WP_087197888.1 45 42 0 0 0.19 substrate-binding protein phosphomannomuta WP_012037720.1 se/phosphoglucomu 50 42 0 0 0.19 (+1) tase NAD(P)-dependent WP_012037543.1 32 41 0 0 0.19 oxidoreductase (+1) glucose-6- phosphate WP_012038425.1 58 41 0 0 0.19 dehydrogenase peptidase M23 WP_079531650.1 43 41 0 0 0.19 LytR family WP_012037691.1 transcriptional 49 40 0 0 0.2 (+2) regulator cyclase WP_011931860.1 17 40 0 0 0.2 hypothetical protein WP_094113568.1 12 40 0 0 0.2 WP_043560526.1 hypothetical protein 14 40 0 0 0.2 (+2) DUF4012 domain- WP_086506445.1 67 39 0 0 0.21 containing protein (+1) TlpA family protein WP_011931789.1 21 39 0 0 0.21 disulfide reductase (+2) WP_043560410.1 hypothetical protein 24 39 0 0 0.21 (+1) hypothetical protein WP_012038075.1 24 39 0 0 0.21 50S ribosomal protein L9 WP_012039647.1 16 38 0 0 0.22 [Clavibacter] type IV secretion WP_011931185.1 119 38 0 0 0.22 protein Rhs ABC transporter WP_079532194.1 substrate-binding 44 37 0 0 0.23 (+1) protein Cluster of DUF305 domain-containing WP_086507858.1 24 37 0 0 0.23 protein [2] (WP_086507858.1) aldo/keto reductase WP_079534953.1 37 37 0 0 0.23 hypothetical protein WP_094117203.1 26 36 0 0 0.24

190

Cluster of peptide ABC transporter WP_086507289.1 substrate-binding 58 36 0 0 0.24 [3] protein (WP_086507289.1) ABC transporter substrate-binding WP_079533858.1 35 35 0 0 0.25 protein YceI family protein WP_012038014.1 23 35 0 0 0.25 WP_012038358.1 aldo/keto reductase 31 35 0 0 0.25 (+1) WP_012037889.1 hypothetical protein 38 35 0 0 0.25 (+3) Cluster of WP_012037835.1 hypothetical protein 21 35 0 0 0.25 [2] (WP_012037835.1) 30S ribosomal WP_012297764.1 23 34 0 0 0.26 protein S5 50S ribosomal WP_012039295.1 13 34 0 0 0.26 protein L24 (+1) Lsr2 family protein WP_012039150.1 13 34 0 0 0.26 30S ribosomal protein S3 WP_012039300.1 30 34 0 0 0.26 [Clavibacter] WP_012038799.1 beta-galactosidase 112 34 0 0 0.26 (+1) translation factor WP_012039149.1 29 34 0 0 0.26 Sua5 NAD(P)/FAD- dependent WP_087197940.1 53 33 0 0 0.27 oxidoreductase single-stranded DNA-binding WP_012039649.1 19 33 0 0 0.27 protein DUF2510 domain- WP_086506662.1 43 32 0 0 0.28 containing protein Cluster of peptidase WP_079534998.1 35 32 0 0 0.28 (WP_079534998.1) [3] ATP-dependent Clp protease proteolytic WP_012038150.1 21 31 0 0 0.29 subunit 30S ribosomal protein S8 WP_012039293.1 14 31 0 0 0.29 [Clavibacter] NAD-dependent succinate- WP_012037619.1 52 31 0 0 0.29 semialdehyde (+3) dehydrogenase Cluster of acetate-- WP_050976352.1 CoA ligase 71 31 0 0 0.29 [3] (WP_050976352.1) chorismate mutase AroQ, gamma WP_011931498.1 20 31 0 0 0.29 subclass Cluster of ABC transporter WP_079533852.1 substrate-binding 32 30 0 0 0.3 [2] protein (WP_079533852.1)

191

DUF3417 domain- WP_086507251.1 93 30 0 0 0.3 containing protein UPF0182 family WP_043561604.1 104 30 0 0 0.3 protein hypothetical protein WP_012038488.1 40 30 0 0 0.3 WP_012039120.1 hypothetical protein 15 30 0 0 0.3 (+3) 50S ribosomal WP_094113918.1 23 29 0 0 0.31 protein L3 LytR family WP_043560780.1 transcriptional 43 29 0 0 0.31 (+1) regulator 50S ribosomal protein L18 WP_012039291.1 13 29 0 0 0.31 [Clavibacter] : 50S ribosomal protein L22 WP_012039301.1 14 29 0 0 0.31 [Clavibacter] alpha-D-glucose phosphate-specific WP_086506907.1 58 29 0 0 0.31 phosphoglucomutas e endo-1,4-beta- WP_094117213.1 71 29 0 0 0.31 xylanase A penicillin-binding WP_011931236.1 50 29 0 0 0.31 protein 2 (+2) peptide ABC transporter WP_012038870.1 65 29 0 0 0.31 substrate-binding (+4) protein Cluster of 5-deoxy- glucuronate WP_012037462.1 33 28 0 0 0.33 isomerase [2] (WP_012037462.1) NAD(P)-dependent alcohol WP_087198182.1 37 28 0 0 0.33 dehydrogenase endoglucanase WP_012039381.1 48 28 0 0 0.33 phosphoglycerate WP_012037786.1 56 28 0 0 0.33 dehydrogenase Cluster of glutamine amidotransferase WP_043584374.1 27 27 0 0 0.34 [Clavibacter] [2] (WP_043584374.1) NADP-dependent WP_012038776.1 36 27 0 0 0.34 oxidoreductase (+1) beta-ketoacyl-[acyl- WP_012038304.1 carrier-protein] 43 27 0 0 0.34 (+1) synthase II WP_012038704.1 hypothetical protein 13 27 0 0 0.34 (+1) succinate dehydrogenase iron- WP_012037655.1 28 26 0 0 0.35 sulfur subunit [Clavibacter] Cluster of Xaa-Pro WP_086506144.1 aminopeptidase 52 26 0 0 0.35 [2] (WP_086506144.1) WP_012039451.1 hypothetical protein 22 26 0 0 0.35 (+2)

192 methylmalonate- semialdehyde WP_012037461.1 53 26 0 0 0.35 dehydrogenase (+2) (CoA acylating) cold-shock protein WP_012038298.1 7 25 0 0 0.37 [Clavibacter] peptidyl-prolyl cis- WP_012038460.1 trans isomerase 13 25 0 0 0.37 (+1) [Clavibacter] cell division protein WP_080580257.1 FtsQ [Clavibacter 27 25 0 0 0.37 (+2) michiganensis] methionine ABC transporter WP_012038973.1 32 25 0 0 0.37 substrate-binding protein phosphoserine WP_012039157.1 40 25 0 0 0.37 transaminase WP_012038173.1 ribonuclease E/G 109 25 0 0 0.37 (+4) Cluster of transcription WP_012037842.1 termination factor 88 25 0 0 0.37 [3] Rho (WP_012037842.1) trigger factor WP_012038149.1 [Clavibacter 53 25 0 0 0.37 (+1) michiganensis] 50S ribosomal WP_012038059.1 13 24 0 0 0.38 protein L19 (+1) ABC transporter substrate-binding WP_011931385.1 33 24 0 0 0.38 protein UTP--glucose-1- phosphate WP_012039135.1 33 24 0 0 0.38 uridylyltransferase [Clavibacter] acetyl-/propionyl- WP_012037677.1 CoA carboxylase 62 24 0 0 0.38 (+2) subunit alpha WP_012039592.1 hypothetical protein 45 24 0 0 0.38 (+2) purine-nucleoside WP_012037675.1 29 24 0 0 0.38 phosphorylase 50S ribosomal WP_012039299.1 15 23 0 0 0.4 protein L16 50S ribosomal WP_012038175.1 protein L21 11 23 0 0 0.4 (+1) [Clavibacter] cold-shock protein WP_012039167.1 8 23 0 0 0.4 [Clavibacter] ribonucleotide- diphosphate WP_012039117.1 38 23 0 0 0.4 reductase subunit beta [Clavibacter] acyltransferase WP_086503701.1 domain-containing 91 23 0 0 0.4 (+1) protein, partial WP_079533514.1 hypothetical protein 15 23 0 0 0.4 (+3)

193

WP_011931511.1 hypothetical protein 27 23 0 0 0.4 (+3) triose-phosphate WP_043560807.1 28 23 0 0 0.4 isomerase (+3) ABC transporter WP_011931905.1 42 22 0 0 0.41 permease (+2) 30S ribosomal protein S10 WP_012039307.1 12 22 0 0 0.41 [Clavibacter] gfo/Idh/MocA WP_011931254.1 family 38 22 0 0 0.41 (+4) oxidoreductase glycosyl transferase WP_012037707.1 75 22 0 0 0.41 translational WP_012038869.1 70 22 0 0 0.41 GTPase TypA ATP-dependent Clp WP_012037542.1 protease ATP- 92 21 0 0 0.43 (+1) binding subunit Cluster of DUF2207 domain-containing WP_087197387.1 63 21 0 0 0.43 protein [2] (WP_087197387.1) DUF3105 domain- WP_012037556.1 27 21 0 0 0.43 containing protein (+2) 30S ribosomal protein S4 WP_012038492.1 24 21 0 0 0.43 [Clavibacter] 50S ribosomal WP_012039288.1 protein L15 20 21 0 0 0.43 (+1) [Clavibacter] hypothetical protein WP_094113556.1 25 20 0 0 0.45 hypothetical protein WP_086505221.1 9 20 0 0 0.45 polygalacturonase WP_012039559.1 49 20 0 0 0.45 ribosomal subunit WP_012037739.1 25 20 0 0 0.45 interface protein valine--tRNA ligase WP_086505386.1 97 20 0 0 0.45 WP_012038940.1 hypothetical protein 75 19 0 0 0.47 (+3) WP_012037703.1 hypothetical protein 79 19 0 0 0.47 (+3) hypothetical protein WP_012037743.1 22 19 0 0 0.47 molybdate ABC transporter WP_012039033.1 26 19 0 0 0.47 substrate-binding (+3) protein multidrug ABC transporter ATP- WP_086507216.1 33 19 0 0 0.47 binding protein 50S ribosomal WP_012039272.1 20 18 0 0 0.49 protein L17 DUF4307 domain- WP_012038933.1 17 18 0 0 0.49 containing protein (+1) FAD-binding WP_086507519.1 46 18 0 0 0.49 protein Lsr2 family protein WP_011931186.1 13 18 0 0 0.49 Cluster of aldo/keto WP_079532443.1 reductase 37 18 0 0 0.49 [4] (WP_079532443.1)

194 hypothetical protein WP_094117136.1 239 18 0 0 0.49 proline--tRNA WP_079534492.1 64 18 0 0 0.49 ligase (+1) ubiquinol- WP_012038523.1 cytochrome c 40 18 0 0 0.49 (+1) reductase WP_012037567.1 xylose isomerase 44 18 0 0 0.49 (+2) 50S ribosomal WP_012039292.1 19 17 0 0 0.51 protein L6 (+1) class II fumarate WP_079534409.1 50 17 0 0 0.51 hydratase (+4) WP_011931686.1 hypothetical protein 31 17 0 0 0.51 (+2) hypothetical protein WP_080580209.1 19 17 0 0 0.51 ABC transporter WP_012037929.1 substrate-binding 40 16 0 0 0.53 (+2) protein Hsp20/alpha crystallin family WP_012038780.1 17 16 0 0 0.53 protein polyisoprenoid- binding protein WP_012038201.1 20 16 0 0 0.53 [Clavibacter] carboxypeptidase regulatory-like WP_079531338.1 62 16 0 0 0.53 domain-containing (+2) protein deferrochelatase/per WP_012038867.1 46 16 0 0 0.53 oxidase EfeB (+3) WP_012038868.1 hypothetical protein 17 16 0 0 0.53 (+5) hypothetical protein WP_012039168.1 20 16 0 0 0.53 1-pyrroline-5- WP_011931839.1 carboxylate 131 15 0 0 0.55 (+4) dehydrogenase 3-isopropylmalate WP_079532427.1 37 15 0 0 0.55 dehydrogenase DNA-binding WP_012039622.1 10 15 0 0 0.55 protein hypothetical protein WP_012038124.1 10 15 0 0 0.55 [Clavibacter] serine WP_043586123.1 hydroxymethyltrans 45 15 0 0 0.55 (+2) ferase [Clavibacter] RNA degradosome WP_012039192.1 polyphosphate 82 15 0 0 0.55 (+2) kinase WP_012039121.1 aldo/keto reductase 35 15 0 0 0.55 (+1) alpha/beta hydrolase WP_094117166.1 55 15 0 0 0.55 energy-dependent WP_012038137.1 translational throttle 62 15 0 0 0.55 (+1) protein EttA glucose-1- WP_012038407.1 phosphate 45 15 0 0 0.55 (+1) adenylyltransferase WP_011931611.1 hypothetical protein 20 15 0 0 0.55 (+3)

195

WP_012039585.1 hypothetical protein 24 15 0 0 0.55 (+1) malto- WP_012038116.1 oligosyltrehalose 66 15 0 0 0.55 (+2) trehalohydrolase threonine--tRNA WP_086507399.1 77 15 0 0 0.55 ligase NAD(P)H-quinone WP_012037676.1 50 14 0 0 0.57 dehydrogenase Cluster of YhgE/Pip domain-containing WP_011931891.1 70 14 0 0 0.57 protein [2] (WP_011931891.1) bifunctional phosphoribosylamin oimidazolecarboxa WP_012039233.1 mide 57 14 0 0 0.57 (+3) formyltransferase/I MP cyclohydrolase PurH glucose WP_079534233.1 41 14 0 0 0.57 dehydrogenase malto- WP_012038117.1 oligosyltrehalose 85 14 0 0 0.57 (+1) synthase Cluster of phosphoenolpyruvat WP_086507287.1 e carboxykinase 70 14 0 0 0.57 [3] (GTP) (WP_086507287.1) Cluster of sugar phosphate WP_011931253.1 isomerase/epimeras 29 14 0 0 0.57 [3] e (WP_011931253.1) 50S ribosomal protein L11 WP_012039476.1 15 13 0 0 0.59 [Clavibacter] 50S ribosomal protein L27 WP_012038176.1 9 13 0 0 0.59 [Clavibacter] arginine--tRNA WP_012037836.1 60 13 0 0 0.59 ligase argininosuccinate WP_012038683.1 45 13 0 0 0.59 synthase WP_012038531.1 dipeptidase 49 13 0 0 0.59 (+3) WP_012037716.1 glycosyl transferase 106 13 0 0 0.59 (+3) histidinol WP_079533420.1 45 13 0 0 0.59 dehydrogenase [ (+2) WP_079534136.1 hypothetical protein 19 13 0 0 0.59 (+1) WP_012038849.1 hypothetical protein 20 13 0 0 0.59 (+4) oxidoreductase WP_012038426.1 35 13 0 0 0.59 pyridoxal phosphate- WP_012039479.1 44 13 0 0 0.59 dependent (+3) aminotransferase

196

WP_012038355.1 sulfurtransferase 34 13 0 0 0.59 (+2) ABC transporter WP_043561713.1 ATP-binding 28 12 0 0 0.62 (+1) protein ABC transporter WP_079534281.1 36 12 0 0 0.62 permease 50S ribosomal protein L14 WP_012039296.1 13 12 0 0 0.62 [Clavibacter] glutamine--fructose- 6-phosphate transaminase WP_012039265.1 66 12 0 0 0.62 (isomerizing) [Clavibacter] adenylosuccinate WP_011931909.1 47 12 0 0 0.62 synthase aliphatic sulfonates ABC transporter WP_012038478.1 36 12 0 0 0.62 substrate-binding (+1) protein WP_043560306.1 hypothetical protein 8 12 0 0 0.62 (+1) Cluster of long- chain fatty acid-- WP_079535001.1 55 12 0 0 0.62 CoA ligase [5] (WP_079535001.1) WP_012039398.1 peptidase M23 40 12 0 0 0.62 (+2) WP_012038950.1 serine protease 43 12 0 0 0.62 (+5) threonine synthase [ WP_079532519.1 37 12 0 0 0.62 1,4-alpha-glucan- WP_094114522.1 95 11 0 0 0.64 branching protein 4-hydroxy- tetrahydrodipicolina WP_043560894.1 34 11 0 0 0.64 te synthase GuaB1 family IMP WP_012038009.1 dehydrogenase- 50 11 0 0 0.64 (+3) related protein LytR family transcriptional WP_086505971.1 42 11 0 0 0.64 regulator M23 family WP_087196300.1 27 11 0 0 0.64 peptidase, partial ribose-phosphate pyrophosphokinase WP_012038964.1 35 11 0 0 0.64 [Clavibacter] Cluster of SGNH/GDSL WP_012039202.1 hydrolase family 23 11 0 0 0.64 [3] protein (WP_012039202.1) UDP- galactopyranose WP_012037706.1 44 11 0 0 0.64 mutase [ aldo/keto reductase WP_012037544.1 36 11 0 0 0.64 alpha-N- WP_012039124.1 57 11 0 0 0.64 arabinofuranosidase (+1)

197

WP_011931348.1 class F sortase 22 11 0 0 0.64 (+1) class II fructose- bisphosphate WP_012038916.1 36 11 0 0 0.64 aldolase hypothetical protein WP_086507137.1 60 11 0 0 0.64 WP_012039229.1 hypothetical protein 17 11 0 0 0.64 (+2) ketoacyl-ACP WP_012038306.1 35 11 0 0 0.64 synthase III (+1) WP_012038051.1 serine protease 40 11 0 0 0.64 (+2) ABC transporter WP_079531983.1 ATP-binding 33 10 0 0 0.67 (+1) protein ATP synthase WP_012037854.1 33 10 0 0 0.67 subunit gamma (+1) ATP-dependent Clp protease proteolytic WP_012038151.1 25 10 0 0 0.67 subunit BMP family ABC transporter WP_079532256.1 37 10 0 0 0.67 substrate-binding (+2) protein 30S ribosomal protein S9 WP_012039268.1 17 10 0 0 0.67 [Clavibacter] GuaB3 family IMP dehydrogenase- WP_012039248.1 39 10 0 0 0.67 related protein [Clavibacter] carbohydrate ABC transporter WP_012037553.1 36 10 0 0 0.67 permease (+1) [Clavibacter] WP_012038240.1 amidohydrolase 44 10 0 0 0.67 (+2) chromosome WP_012037593.1 49 10 0 0 0.67 partitioning protein (+1) WP_012037915.1 hypothetical protein 48 10 0 0 0.67 (+4) iron-siderophore ABC transporter WP_079531351.1 36 10 0 0 0.67 substrate-binding (+2) protein serine hydrolase WP_094114313.1 71 10 0 0 0.67 succinate- WP_011931399.1 semialdehyde 49 10 0 0 0.67 (+1) dehydrogenase sugar ABC transporter WP_012039099.1 48 10 0 0 0.67 substrate-binding (+2) protein uroporphyrinogen WP_011931807.1 40 10 0 0 0.67 decarboxylase (+1) DUF839 domain- WP_012039537.1 74 9 0 0 0.7 containing protein DUF2993 domain- WP_043560708.1 29 9 0 0 0.7 containing protein [

198

DUF4245 domain- WP_012038921.1 25 9 0 0 0.7 containing protein (+1) alanine--tRNA WP_012038490.1 95 9 0 0 0.7 ligase (+3) WP_012038486.1 chorismate synthase 43 9 0 0 0.7 (+2) deoxycytidine WP_012039588.1 triphosphate 22 9 0 0 0.7 (+2) deaminase glycerol-3- phosphate WP_012038510.1 64 9 0 0 0.7 dehydrogenase/oxid (+2) ase WP_086507734.1 hypothetical protein 26 9 0 0 0.7 (+1) WP_012038091.1 hypothetical protein 47 9 0 0 0.7 (+5) WP_012037594.1 hypothetical protein 31 9 0 0 0.7 (+5) hypothetical protein WP_086507612.1 48 9 0 0 0.7 phosphogluconate dehydrogenase (NADP(+)- WP_012038962.1 52 9 0 0 0.7 dependent, decarboxylating) pyridine nucleotide- WP_012037494.1 disulfide 57 9 0 0 0.7 (+2) oxidoreductase 1-deoxy-D- WP_043560798.1 xylulose-5- 70 8 0 0 0.73 (+1) phosphate synthase 3-deoxy-7- phosphoheptulonate WP_012038561.1 50 8 0 0 0.73 synthase class II WP_012039139.1 ATPase AAA 135 8 0 0 0.73 (+4) DUF2207 domain- WP_086503569.1 76 8 0 0 0.73 containing protein DeoR/GlpR WP_011931569.1 transcriptional 26 8 0 0 0.73 (+1) regulator 30S ribosomal protein S6 WP_012039650.1 16 8 0 0 0.73 [Clavibacter] : 30S ribosomal protein S7 WP_012039311.1 17 8 0 0 0.73 [Clavibacter] hydroperoxide resistance protein WP_011931929.1 14 8 0 0 0.73 [Clavibacter] ROK family protein WP_012038319.1 29 8 0 0 0.73 TIGR04028 family ABC transporter WP_012038647.1 58 8 0 0 0.73 substrate-binding protein WP_012037581.1 acetate kinase 42 8 0 0 0.73 (+2) aquaporin family WP_012038517.1 25 8 0 0 0.73 protein (+1)

199 aspartate WP_012038853.1 aminotransferase 49 8 0 0 0.73 (+1) family protein aspartate ammonia- WP_012038765.1 53 8 0 0 0.73 lyase WP_011931232.1 class E sortase 28 8 0 0 0.73 (+1) cupin domain- WP_012038807.1 32 8 0 0 0.73 containing protein (+2) cystathionine WP_012037558.1 41 8 0 0 0.73 gamma-synthase WP_011931873.1 cysteine synthase A 33 8 0 0 0.73 (+4) cytochrome c WP_050976371.1 63 8 0 0 0.73 oxidase subunit I WP_012039403.1 hypothetical protein 25 8 0 0 0.73 (+3) hypothetical protein WP_086505130.1 25 8 0 0 0.73 leucyl WP_087198095.1 52 8 0 0 0.73 aminopeptidase methylmalonyl- WP_043560653.1 CoA 56 8 0 0 0.73 (+1) carboxyltransferase 4-hydroxy-3- methylbut-2-en-1-yl WP_043560923.1 40 7 0 0 0.76 diphosphate synthase 50S ribosomal WP_012039475.1 24 7 0 0 0.76 protein L1 ABC transporter WP_012037487.1 ATP-binding 31 7 0 0 0.76 (+1) protein DUF349 domain- WP_012038494.1 45 7 0 0 0.76 containing protein (+2) DUF4350 domain- WP_012037732.1 43 7 0 0 0.76 containing protein (+2) DivIVA domain- WP_012038539.1 24 7 0 0 0.76 containing protein (+2) 50S ribosomal WP_012039304.1 protein L23 11 7 0 0 0.76 (+1) [Clavibacter] DUF3117 domain- containing protein WP_012037866.1 6 7 0 0 0.76 [Clavibacter] metal-dependent transcriptional WP_012039156.1 25 7 0 0 0.76 regulator (+2) [Clavibacter] TonB-dependent WP_079531335.1 26 7 0 0 0.76 receptor (+2) YbhB/YbcL family Raf kinase WP_086506051.1 18 7 0 0 0.76 inhibitor-like protein YhgE/Pip domain- WP_012037766.1 63 7 0 0 0.76 containing protein (+3) branched-chain WP_043561571.1 amino acid 39 7 0 0 0.76 (+1) aminotransferase

200 diaminobutyrate--2- WP_050976326.1 oxoglutarate 47 7 0 0 0.76 (+2) transaminase WP_012038261.1 esterase 48 7 0 0 0.76 (+4) glutamine- WP_012039243.1 hydrolyzing GMP 56 7 0 0 0.76 (+2) synthase glycine cleavage WP_012038887.1 42 7 0 0 0.76 system protein T (+4) hypothetical protein WP_011931291.1 26 7 0 0 0.76 WP_012038905.1 hypothetical protein 15 7 0 0 0.76 (+2) WP_043561611.1 hypothetical protein 19 7 0 0 0.76 (+1) indole-3-glycerol- WP_012038452.1 27 7 0 0 0.76 phosphate synthase (+2) mannose-6- WP_012037713.1 phosphate 46 7 0 0 0.76 (+1) isomerase, class I WP_012037952.1 membrane protein 31 7 0 0 0.76 (+4) ornithine carbamoyltransferas WP_012038684.1 33 7 0 0 0.76 e phenylalanine-- WP_012038689.1 tRNA ligase subunit 88 7 0 0 0.76 (+5) beta response regulator WP_012299329.1 22 7 0 0 0.76 short chain WP_012038368.1 28 7 0 0 0.76 dehydrogenase tryptophan synthase WP_012038451.1 43 7 0 0 0.76 subunit beta 30S ribosomal WP_012039275.1 14 6 0 0 0.79 protein S13 DNA topoisomerase WP_012037613.1 I [Clavibacter 106 6 0 0 0.79 (+2) michiganensis] 50S ribosomal protein L28 WP_012039624.1 9 6 0 0 0.79 [Clavibacter] chromosome WP_012038568.1 partitioning ATPase 29 6 0 0 0.79 (+1) [Clavibacter] glutamine synthetase WP_012038322.1 50 6 0 0 0.79 [Clavibacter] NAD(P)-dependent WP_012039519.1 29 6 0 0 0.79 oxidoreductase (+1) NADP WP_012037821.1 23 6 0 0 0.79 oxidoreductase RNase J family beta-CASP WP_011931392.1 61 6 0 0 0.79 ribonuclease UMP kinase WP_012038071.1 25 6 0 0 0.79 acetolactate WP_012037780.1 synthase large 67 6 0 0 0.79 (+2) subunit WP_011931863.1 alkene reductase 38 6 0 0 0.79 (+1)

201 bifunctional hydroxymethylpyri midine WP_087197304.1 76 6 0 0 0.79 kinase/phosphometh ylpyrimidine kinase WP_012037911.1 cold-shock protein 64 6 0 0 0.79 (+2) glyceraldehyde 3- WP_011931541.1 36 6 0 0 0.79 phosphate reductase (+2) WP_011931702.1 hypothetical protein 70 6 0 0 0.79 (+3) WP_012037934.1 hypothetical protein 30 6 0 0 0.79 (+4) WP_012038553.1 hypothetical protein 23 6 0 0 0.79 (+1) WP_094113919.1 hypothetical protein 37 6 0 0 0.79 (+1) non-heme iron oxygenase WP_012038417.1 11 6 0 0 0.79 ferredoxin subunit phosphoribosylform WP_012037413.1 ylglycinamidine 84 6 0 0 0.79 (+4) synthase II Cluster of sugar WP_094114005.1 kinase 31 6 0 0 0.79 [2] (WP_094114005.1) Cluster of ubiquinol- cytochrome c WP_012038524.1 reductase 60 6 0 0 0.79 [3] cytochrome b subunit (WP_012038524.1) 1,4-dihydroxy-2- naphthoyl-CoA WP_011931796.1 33 5 0 0 0.82 synthase 4-hydroxy- WP_012038727.1 tetrahydrodipicolina 28 5 0 0 0.82 (+1) te reductase DUF885 domain- WP_012038441.1 62 5 0 0 0.82 containing protein (+2) acyl carrier protein WP_012038305.1 9 5 0 0 0.82 [Clavibacter] adenosine WP_012037669.1 40 5 0 0 0.82 deaminase (+2) WP_012037489.1 alpha/beta hydrolase 48 5 0 0 0.82 (+2) bifunctional N- acetylglucosamine- 1-phosphate WP_012038965.1 uridyltransferase/gl 54 5 0 0 0.82 (+2) ucosamine-1- phosphate acetyltransferase bifunctional WP_079532472.1 metallophosphatase/ 73 5 0 0 0.82 (+3) 5'-nucleotidase dienelactone WP_012037412.1 hydrolase family 28 5 0 0 0.82 (+1) protein

202 gfo/Idh/MocA family WP_086507888.1 42 5 0 0 0.82 oxidoreductase WP_012038563.1 glucokinase 33 5 0 0 0.82 (+2) hypothetical protein WP_086505626.1 8 5 0 0 0.82 molecular WP_012038252.1 40 5 0 0 0.82 chaperone DnaJ (+2) ornithine--oxo-acid WP_079533658.1 43 5 0 0 0.82 transaminase (+2) phosphoribosylform WP_012037443.1 ylglycinamidine 37 5 0 0 0.82 (+2) cyclo-ligase translation initiation WP_012038839.1 98 5 0 0 0.82 factor IF-2 (+1) 3-dehydroquinate WP_012038484.1 40 4 0 0 0.85 synthase 5-dehydro-2- WP_086507026.1 35 4 0 0 0.85 deoxygluconokinase (+1) DUF3416 domain- WP_079533741.1 73 4 0 0 0.85 containing protein (+4) DUF3459 domain- WP_012039212.1 57 4 0 0 0.85 containing protein (+2) Fe-S cluster WP_012038418.1 assembly protein 43 4 0 0 0.85 (+3) SufD L-arabinose WP_012037563.1 55 4 0 0 0.85 isomerase (+5) L-ribulose-5- phosphate 4- WP_012037562.1 25 4 0 0 0.85 epimerase Fe-S cluster assembly protein WP_012038419.1 53 4 0 0 0.85 SufB [Clavibacter] peptide-methionine (R)-S-oxide WP_012039170.1 15 4 0 0 0.85 reductase [Clavibacter] transcriptional regulator WP_012038571.1 17 4 0 0 0.85 [Clavibacter] NAD(P)-dependent WP_079533684.1 23 4 0 0 0.85 oxidoreductase NAD(P)-dependent WP_080580226.1 31 4 0 0 0.85 oxidoreductase NADPH:quinone WP_012038616.1 35 4 0 0 0.85 reductase (+3) WP_011931421.1 beta-galactosidase 69 4 0 0 0.85 (+3) WP_012037568.1 beta-glucosidase 55 4 0 0 0.85 (+4) bifunctional 1-(5- phosphoribosyl)-5- ((5- phosphoribosylamin o)methylideneamin WP_012038701.1 26 4 0 0 0.85 o)imidazole-4- carboxamide isomerase/phosphor ibosylanthranilate isomerase PriA 203

WP_012038922.1 carbonic anhydrase 23 4 0 0 0.85 (+1) WP_011931815.1 ferrochelatase 45 4 0 0 0.85 (+4) glycine--tRNA WP_012038268.1 52 4 0 0 0.85 ligase [ WP_012037831.1 hypothetical protein 34 4 0 0 0.85 (+1) hypothetical protein WP_012038136.1 16 4 0 0 0.85 hypothetical protein WP_050976267.1 22 4 0 0 0.85 hypothetical protein WP_012037822.1 27 4 0 0 0.85 WP_012038155.1 methylase 29 4 0 0 0.85 (+4) penicillin-binding WP_012039347.1 49 4 0 0 0.85 protein (+5) WP_012038154.1 peptidase M3 76 4 0 0 0.85 (+5) phospho-sugar WP_012037674.1 61 4 0 0 0.85 mutase (+1) pyridoxal 5'- WP_012038506.1 phosphate synthase 32 4 0 0 0.85 (+1) lyase subunit PdxS xylose ABC transporter ATP- WP_012037565.1 55 4 0 0 0.85 binding protein 2-methylcitrate WP_012039060.1 42 3 0 0 0.89 synthase 3-oxoacyl-ACP WP_012038788.1 31 3 0 0 0.89 reductase (+1) DNA gyrase subunit WP_011931226.1 98 3 0 0 0.89 A (+4) WP_012037788.1 MFS transporter 52 3 0 0 0.89 (+3) ABC transporter ATP-binding WP_012039254.1 27 3 0 0 0.89 protein [Clavibacter] sporulation protein WP_012038434.1 35 3 0 0 0.89 [Clavibacter] NAD(P)-dependent WP_011931670.1 22 3 0 0 0.89 oxidoreductase (+2) acyltransferase WP_012037408.1 81 3 0 0 0.89 alpha-ketoacid WP_043562076.1 dehydrogenase 35 3 0 0 0.89 (+1) subunit beta WP_012038617.1 amidohydrolase 55 3 0 0 0.89 (+5) WP_012039565.1 histidine kinase 62 3 0 0 0.89 (+1) malate:quinone WP_012037589.1 54 3 0 0 0.89 oxidoreductase mannitol-1- WP_012039278.1 phosphate 5- 41 3 0 0 0.89 (+2) dehydrogenase metallophosphatase WP_086505901.1 31 3 0 0 0.89 Cluster of peptidase WP_012039507.1 M13 73 3 0 0 0.89 [5] (WP_012039507.1)

204 phosphate WP_012037580.1 74 3 0 0 0.89 acetyltransferase (+3) protein translocase WP_012038498.1 36 3 0 0 0.89 subunit SecF (+1) pyridine nucleotide- WP_012037818.1 disulfide 49 3 0 0 0.89 (+2) oxidoreductase sugar ABC transporter WP_011931516.1 44 3 0 0 0.89 substrate-binding (+1) protein 3D-(3,5/4)- trihydroxycyclohex WP_012037463.1 ane-1,2-dione 68 2 0 0 0.92 (+1) acylhydrolase (decyclizing) 6- WP_011931824.1 phosphofructokinas 36 2 0 0 0.92 (+1) e ATP synthase WP_012037852.1 28 2 0 0 0.92 subunit delta (+1) DNA topoisomerase WP_050976329.1 (ATP-hydrolyzing) 74 2 0 0 0.92 (+3) subunit B DUF1684 domain- WP_012038819.1 27 2 0 0 0.92 containing protein (+2) glycosyltransferase family 2 protein WP_012039000.1 26 k 2 0 0 0.92 [Clavibacter] N-dimethylarginine WP_079531629.1 dimethylaminohydr 30 2 0 0 0.92 (+2) olase UDP-N- acetylmuramoyl-L- WP_012038548.1 55 2 0 0 0.92 alanine--D- (+5) glutamate ligase WP_012038285.1 acyltransferase 77 2 0 0 0.92 (+4) alpha-N- WP_011931530.1 56 2 0 0 0.92 arabinofuranosidase (+5) amidase WP_012037618.1 20 2 0 0 0.92 argininosuccinate WP_012038682.1 53 2 0 0 0.92 lyase (+3) asparaginase II WP_012038854.1 35 2 0 0 0.92 hydroxyethylthiazol WP_012038805.1 27 2 0 0 0.92 e kinase (+2) lipase WP_086507443.1 31 2 0 0 0.92 peptide-methionine WP_012038132.1 (S)-S-oxide 19 2 0 0 0.92 (+1) reductase sugar phosphate WP_012039459.1 isomerase/epimeras 39 2 0 0 0.92 (+3) e cellulase WP_011931144.1 78 177 1 0.0065 0.006 elongation factor Tu WP_012039309.1 43 237 2 0.004 0.008 WP_012037524.1 peptidase M23 45 224 2 0.0061 0.009 (+1) Cluster of WP_015488823.1 19 96 1 0.1 0.01 peptidylprolyl [2]

205 isomerase [Clavibacter] (WP_015488823.1) aconitate hydratase WP_086507342.1 101 105 1 0.076 0.01 AcnA Cluster of dihydroxy-acid WP_012037779.1 59 51 1 0.39 0.02 dehydratase [2] (WP_012037779.1) 50S ribosomal protein L4 WP_043584322.1 23 49 2 0.6 0.04 [Clavibacter] alanine WP_094114028.1 39 83 3 0.56 0.04 dehydrogenase ketol-acid WP_012037782.1 37 113 5 0.5 0.04 reductoisomerase (+1) hypothetical protein WP_012038363.1 17 655 30 0.29 0.05 serine protease WP_086505715.1 120 630 29 0.29 0.05 WP_012038629.1 hypothetical protein 34 254 15 0.11 0.06 (+1) WP_079533606.1 serine hydrolase 46 100 6 0.24 0.06 (+3) transaldolase WP_012038423.1 40 128 8 0.17 0.06 ATP synthase WP_012037853.1 59 130 9 0.097 0.07 subunit alpha Cluster of WP_079532591.1 hypothetical protein 117 42 3 0.26 0.07 [3] (WP_079532591.1) penicillin-binding protein [Clavibacter WP_079532157.1 88 441 33 0.0012 0.07 michiganensis] sugar ABC transporter 1,22 < WP_012039530.1 37 88 0.07 substrate-binding 6.00 0.00010 protein type I glutamate-- WP_012038324.1 53 102 7 0.14 0.07 ammonia ligase (+1) DSBA WP_012038144.1 23 24 2 0.27 0.08 oxidoreductase catalase WP_079531856.1 57 190 17 0.0034 0.09 ABC transporter ATP-binding WP_012039173.1 39 94 11 0.0028 0.1 protein 30S ribosomal protein S1 WP_012038440.1 53 86 12 0.00046 0.1 [Clavibacter] DNA-directed RNA polymerase subunit WP_012039273.1 36 53 6 0.028 0.1 alpha [Clavibacter] Cluster of PTS lactose transporter WP_012038190.1 69 10 1 0.36 0.1 subunit IIC [3] (WP_012038190.1) dihydrolipoyl < WP_012038330.1 48 107 15 0.1 dehydrogenase 0.00010 hypothetical protein WP_012037596.1 19 37 4 0.076 0.1 Cluster of WP_079532685.1 hypothetical protein 30 29 3 0.13 0.1 [3] [Clavibacter

206 michiganensis] (WP_079532685.1) peptide ABC transporter WP_012038274.1 58 58 7 0.014 0.1 substrate-binding protein serine/threonine WP_011931235.1 65 25 3 0.096 0.1 protein kinase (+2) 50S ribosomal WP_012039294.1 22 15 3 0.032 0.2 protein L5 DNA starvation/stationary WP_012038147.1 17 8 2 0.056 0.2 phase protection protein 50S ribosomal protein L7/L12 WP_012037546.1 13 39 6 0.0079 0.2 [Clavibacter] DNA-binding response regulator WP_012039163.1 26 6 1 0.24 0.2 [Clavibacter] co-chaperone < WP_012039257.1 11 117 20 0.2 GroES [Clavibacter] 0.00010 WP_011931509.1 YceI family protein 23 19 3 0.053 0.2 (+2) Cluster of aldehyde dehydrogenase WP_086507044.1 < 51 135 32 0.2 (NADP(+)) [2] 0.00010 (WP_086507044.1) Cluster of alpha- WP_086506834.1 < mannosidase 117 440 89 0.2 [2] 0.00010 (WP_086506834.1) carbohydrate ABC transporter < WP_012037551.1 48 374 70 0.2 substrate-binding 0.00010 protein WP_012038953.1 < enolase 45 135 22 0.2 (+1) 0.00010 Cluster of ferredoxin family WP_011931885.1 12 10 2 0.078 0.2 protein [2] (WP_011931885.1) < hypothetical protein WP_011931364.1 23 113 18 0.2 0.00010 < hypothetical protein WP_043560984.1 20 60 11 0.2 0.00010 WP_012038384.1 hypothetical protein 47 4 1 0.18 0.2 (+3) inorganic < pyrophosphatase WP_012037526.1 20 50 14 0.3 0.00010 [Clavibacter] nucleoside- diphosphate kinase WP_012038171.1 15 13 4 0.0037 0.3 [Clavibacter] glutathione- dependent WP_012039603.1 42 15 4 0.0057 0.3 formaldehyde (+2) dehydrogenase type I < glyceraldehyde-3- WP_012038432.1 36 98 42 0.4 0.00010 phosphate

207

dehydrogenase [Clavibacter] dihydrodipicolinate < synthase family WP_079531998.1 33 161 71 0.4 0.00010 protein molecular < WP_012039166.1 57 265 97 0.4 chaperone GroEL 0.00010 Cluster of peptide ABC transporter WP_087197142.1 < substrate-binding 66 300 117 0.4 [2] 0.00010 protein (WP_087197142.1) ATP-dependent WP_094114169.1 80 7 4 0.00062 0.6 chaperone ClpB mannose-1- phosphate WP_012037660.1 < 40 9 6 0.7 guanylyltransferase (+1) 0.00010 [Clavibacter] Cluster of CHRD domain-containing WP_011931347.1 < 24 31 28 0.9 protein [2] 0.00010 (WP_011931347.1) a: identified as proteins of Clavibacter michiganensis, except for those with [Clavibacter], which indicates proteins from family of Clavibacter b: Cm = Cmm is grown in NB media c: CmP = Cmm is grown with P. entomophila 23S

208

Appendix 7 Cmm protein, for which level did not change when grown with P. entomophila 23S

Fisher’s Molecular Fold Identified proteinsa NCBI Accession Cmb CmPc exact Test weight (kDa) change (P-value)

superoxide dismutase WP_012038433.1 23 29 30 1 < 0.00010 [Clavibacter] a: identified as proteins of Clavibacter michiganensis, except for those with [Clavibacter], which indicates proteins from family of Clavibacter b: Cm = Cmm is grown in NB media c: CmP = Cmm is grown with P. entomophila 23S

209

Appendix 8 Nutrient composition of nutrient broth (NB), Kind’s B (KB), Luria Broth (LB) and Tryptic Soy Broth (TSB)

210

211