In Planta Studies of the Corn Pathogen Pantoea Stewartii Subsp

In planta studies of the corn pathogen Pantoea stewartii subsp. stewartii and applications of a corn-based industrial byproduct

Holly Packard Bartholomew Dissertation submitted to the faculty of Virginia Polytechnic Institute and State University in partial fulfilment of the degree of Doctor in Philosophy In Biological Sciences

Ann M. Stevens; Committee Chair Roderick V. Jensen David L. Popham Boris A. Vinatzer

June 12, 2020 Blacksburg, VA, USA

Keywords: Pantoea stewartii, Stewart’s wilt, phytopathogen, transcription regulation, corn, ethanol production, Bacillus species, aquaculture

In planta studies of the corn pathogen Pantoea stewartii subsp.

stewartii and applications of a corn-based industrial byproduct

Holly Packard Bartholomew

ABSTRACT

Corn is a valuable agricultural commodity in the United States and in the world. The causal agent of Stewart’s wilt disease in corn, Pantoea stewartii subsp. stewartii, is a bacterial phytopathogen that is vectored into the plant by the corn flea beetle, Chaetocnema pulicaria.

After entering the apoplast of the leaf, the bacteria cause water soaking symptoms before traveling to the plant xylem to form a dense biofilm, thereby blocking water transport and inducing necrosis and wilt. This results in reduced crop yield and may even lead to death of the corn plant. To better understand the in planta requirements of this pathogen, a whole transcriptome study was performed via RNA-Seq to determine genes differentially expressed in the bacteria while inside the corn. It was found that nutrient transporters and stress response genes were upregulated specifically when the bacteria are in their host plant, suggesting a response to nutrient availability and host defense in the xylem. Further elucidation of the genes required for the P. stewartii in planta lifestyle was performed via a reverse genetics approach where in-frame gene deletions and the corresponding complementation strains were constructed for genes that had shown a fitness defect in corn based on a previously published Tn-Seq study: genes encoding seven transcription factors, nsrR, iscR, lrp, nac, DSJ_00125, DSJ_03645, and

DSJ_18135, as well as a hypothetical protein DSJ_21690. Investigation of the physiological role of these genes was performed using in planta virulence and competition assays for all strains. An in planta qRT-PCR analysis of bacterial gene transcription was also completed for the strains

with deletions in nsrR and iscR. In vitro assays were performed on all strains to determine their capsule production and motility phenotypes. Taken together, it was seen that iscR is important for colonization capabilities in planta, both NsrR and IscR act as regulators, and lrp is important for full disease capabilities, perhaps due to reduced capsule and motility phenotypes. These findings lay the groundwork for finding potential disease intervention strategies not only against

P. stewartii, but also other xylem-dwelling bacterial phytopathogens.

In addition to exploring ways to enhance crop yield, an additional research area was on repurposing a byproduct of corn ethanol production, syrup. It was hypothesized that this corn- based syrup could be utilized as a carbon source to grown bacteria. In turn, the resulting bacterial biomass could then be added as a fish feed supplement in aquaculture. Syrup was tested as a growth medium for individual soil bacterial isolates as well as a full mixed bacterial community consortium to determine which bacteria could grow most efficiently, both in rate and yield. It was found that the highest growth rate and yield was from Bacillus species, some of which may have probiotic benefits to fish.

Ultimately, the collective outcomes from these projects in basic research about a bacterial corn pathogen and applied research about beneficial microbes grown on a corn-based substrate are expected to improve scientific endeavors as well as agricultural practices.

In planta studies of the corn pathogen Pantoea stewartii subsp.

stewartii and applications of a corn-based industrial byproduct

Holly Packard Bartholomew

GENERAL AUDIENCE ABSTRACT

Corn is a top agricultural commodity in the United States, as a food for human consumption, a primary nutrient source used in animal feed, and a substrate consumed during biofuel production. These various corn-based industries are impacted by bacteria in multiple ways; in some cases, bacteria may cause disease that reduces crop yield, but other bacteria serve beneficial roles that enhance health. This dissertation research describes studies about the bacterium that causes Stewart’s wilt disease in corn, Panteoa stewartii subsp. stewartii. In an initial experiment, the genes that P. stewartii expresses at the highest levels when it grows inside the corn plant were identified. These genes were deduced to be important for the ability of the bacterium to live successfully in this environment. This work was followed up with a more specific approach that examined the role of certain genes that were predicted to be master regulators of the expression of other genes in the ability of the P. stewartii to colonize the plant and/or cause disease. By identifying key bacterial genes, disease intervention strategies to combat Stewart’s wilt and other similar bacterial plant pathogen diseases might become possible.

Protecting corn yields is important for ethanol production. The final study of this dissertation examined the ability of bacteria to grow on a byproduct of ethanol production called syrup. The goal was to then use the biomass of these beneficial microbes as a food source for animals being produced in aquaculture facilities. Among the species tested, the highest growth rate and yield was from Bacillus subtilis, a safe-to-eat bacterium that has known beneficial health properties

when consumed by fish. Overall, the research studies that were completed for this dissertation have the potential to improve agricultural practices by decreasing corn disease leading to increased corn yield and developing new downstream corn-based animal feed products.

ACKNOWLEDGEMENTS

First and foremost, I would like to thank Dr. Ann Stevens for mentoring me, first as an undergraduate and then later as a graduate student in her lab. Thank you for encouraging me to work hard and to think critically as a scientist. You have taught me to persevere and to be confident in my abilities. Most importantly, you have fostered my love of microbiology, of which I will forever be grateful.

Additional thanks to my committee members, Dr. Roderick V. Jensen, Dr. David L.

Popham, and Dr. Boris Vinatzer. It has been a pleasure meeting with you each semester to discuss the science and brainstorm ideas. Thank you for your welcome feedback and your perspectives that enabled these projects to move forward. I have appreciated your support and insights throughout this time, and your willingness to always give advice.

None of this would have been possible without the amazing people that have made up the

Stevens Lab. To those that came before me and trained me, Dr. Alison Kernell Burke and Dr.

An Duong, thank you for your patience and kindness as you gave me all of the tools I needed to succeed, both in and out of the lab. To Ian Hines and Guadalupe Reynoso, you have both contributed to the fun atmosphere of the lab and made experimental failures more bearable.

Graduate school definitely had some challenges, but working together with you all was absolutely not one of them. Finally, to the graduate microbiology group, I treasure the friendships I have built with you, and I am so grateful we were able to support each other throughout this process.

To my post baccalaureate trainee, Chastyn Smith, and my undergraduate research collaborators, Stephanie Williams, Zachary Taylor, Brandi Thomas, Chase Mullins, Madigan vi

Hawkins, and Katie Grant. Thank you for your enthusiasm toward the projects we worked on together, I could not have done this alone. I have enjoyed watching you all learn and thrive as students and scientists, and I look forward to seeing where each of you will go with your future endeavors. I am rooting for you all!

To my biggest cheerleaders, my parents. Thank you for getting excited when I would tell you about even the smallest of findings filled with way too much jargon. I am forever in awe of your optimism and unwavering support. You have taught me from the beginning to try my best, to reach for the stars, and to accept failure and frustration with a smile before pushing forward.

Everything I have done I attribute to you, and I am so glad I can finally tell you that I did it!

Finally, I would like to say thank you to my amazing husband Paul. You have been right here with me since we decided to take this Ph.D. journey together, and I cannot imagine it any other way. You have always been quick with a congratulations when something went right, and the shoulder to lean on when something went wrong. I am looking forward to celebrating our accomplishments together, and I cannot wait until it is your turn!

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TABLE OF CONTENTS Page Number Dissertation Title i Abstract ii General Audience Abstract iv Acknowledgements vi Table of Contents viii List of Figures xii List of Tables xiii Chapter One: Literature Review 1 Introduction 2 The genus Pantoea 3 The phytopathogen Pantoea stewartii subsp. stewartii 5 Stewart’s wilt disease 6 Corn Flea Beetle 7 Virulence Factors of P. stewartii 8 Type III Secretion System 8 Extracellular Polysaccharide 10 Surface Motility 11 Other Vascular Bacterial Pathogens 12 Xylella fastidiosa 12 Ralstonia solanacearum 14 Research Plan 16 References 18 Chapter Two: Analysis of the in planta Transcriptome Expressed by the Corn Pathogen Pantoea stewartii subsp. stewartii via RNA-Seq 28 Abstract 30 Introduction 31 Materials and Methods 33 Bacterial strains and media 33

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Growth of cells for RNA-Seq analysis 33 RNA purification and RNA-Seq 35 RNA-Seq data analysis 35 Cloning of coding regions of genes of interest for primer optimization 37 Quantitative reverse transcription PCR (qRT-PCR) 37 Gene ontology 38 Accession numbers 39 Results 39 Comparison of RNA-Seq data reveals genes important for in planta colonization and growth 39 Validation of the RNA-Seq via quantitative reverse transcription PCR 41 Gene ontology (GO) analysis demonstrates the importance of select groups of genes in planta 42 Discussion 43 References 50 Chapter Three: Elucidating the role of select transcription factors in Pantoea stewartii subsp. stewartii survival during xylem infection of corn 58 Abstract 60 Introduction 62 Methods 66 Strains and growth conditions 66 Gene selection criterion 67 Deletion and complementation strain construction 68 Xylem virulence assay 69 Competition assay 70 RNA extraction 71 Quantitative reverse-transcription polymerase chain reaction (qRT-PCR) 72 Capsule production phenotypic assay 72 Surface motility phenotypic assay 73

Results 73 The transcription factor IscR plays a role in P. stewartii colonization of corn 73 The transcription factor Lrp impacts P. stewartii disease severity 74 qRT-PCR reveals genes regulated by P. stewartii IscR and NsrR 75 Lrp is involved in both capsule production and surface motility of P. stewartii 76 Discussion 77 Acknowledgements 84 References 85 Chapter Four: Identification of soil bacteria capable of utilizing a corn ethanol fermentation byproduct 105 Abstract 107 Introduction 108 Materials and methods 110 The syrup growth substrate 110 Temporal community profiling of bacterial enrichment in anaerobic reactors 111 MiSeq data analysis 112 Pure culture strain isolation from enrichment cultures 113 Monoculture and binary-combination growth assays of microbial strains 114 Strain identification 115 Accession numbers 116 Results 117 Community profiling illustrates succession of enriched bacterial families 117 Monoculture growth revealed differences in growth yield between strains 118

Binary culture combinations showed no synergism 119 Pure-culture isolates from reactors were Bacillus species 120 Discussion 120 Acknowledgements 123 References 125 Chapter Five: Concluding Remarks 134 References 140 Appendix A: Chapter 2 Supplementary Information 141 Appendix B: Chapter 3 Supplementary Information 197 Appendix C: Chapter 4 Supplementary Information 203

LIST OF FIGURES Chapter One Page Number Figure 1.1 Simple schematic of the quorum-sensing system within P. stewartii 25 Figure 1.2 Examples of Stewart’s wilt symptom severity 26 Figure 1.3 (1) Simple model of a type III secretion system (T3SS) structure. (2) Example of plant-pathogen interaction regarding host immunity 27 Chapter Two Figure 2.1. Differential mRNA expression in planta 55 Figure 2.2. Relative gene expression from the RNA-Seq and qRT-PCR data 56 Figure 2.3. Gene Ontology analysis groupings for the list of regulated genes 57 Chapter Three Figure 3.1 Proposed regulatory targets of P. stewartii IscR and NsrR, key regulators in Fe-S cluster formation based on the Escherichia coli model 90 Figure 3.2 Competition assay for P. stewartii mutant strains lacking select transcription regulators 91 Figure 3.3 Virulence of P. stewartii nsrR, iscR, lrp, and nac mutant and complementation strain 92 Figure 3.4 Relative gene expression of select gene targets for IscR and NsrR using qRT-PCR 93 Figure 3.5 Capsule production by P. stewartii nsrR, iscR, nac, and lrp mutant and complementation strains. 94 Figure 3.6 Surface motility of P. stewartii nsrR, iscR, nac, and lrp mutant and complementation strains 95 Figure 3.7 Expanded predicted in planta regulatory network of P. stewartii 96 Chapter Four Figure 4.1. Bacterial community profile across anaerobic syrup enrichment cycles 133

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LIST OF TABLES Chapter Two Page Number Table 2.1. Genes from the RNA-Seq data comparing the in planta reads to the pre-inoculum in vitro liquid culture reads validated by qRT-PCR 53 Table 2.2. Genes from the RNA-Seq data comparing the in planta reads to the in vitro plate culture reads validated by qRT-PCR 54 Chapter Three Table 3.1. Strains used in this study 97 Table 3.2. Primers used for this study 99 Chapter Four Table 4.1. Estimated Number of Families and alpha diversity of the soil enrichment community 128 Table 4.2. Microbes used in this study 129 Table 4.3. Growth yields of monocultures on syrup from three production facilities 131

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CHAPTER ONE

Literature Review

Introduction

Agricultural industries are facing heavy challenges with the increase in demand to supply food and energy across the globe. The population in the United States alone has risen 6.3% over the last decade, and projections for the year 2050 show a dramatic need for crop yield increase

(Ray et al., 2013; USCB 2019). Innovative technologies and methods are being discovered and implemented to maximize crop output, and success has been seen in improving yield (Edgerton,

2009; Trivedi et al., 2017). One such area of relevant research is the study of microorganisms, as these can have numerous impacts on the food industry, including pathogenicity toward crops, synergism via microbial protection, nutrient conversion and acquisition, or through microbial cultivation and utilization (Savary et al., 2019; Trivedi et al., 2017; Bargués-Ribera & Gokhale,

2020; Leathers, 2003), as well as impact on the production of biofuels (Singh et al., 2001).

In the U.S., corn is the number one agricultural commodity, with ~ 37% of total acres in

2019 specifically utilized for corn cultivation (USDA FSA, 2020). Corn varieties are used for human and agriculture feed, and for biofuel production. In 2019, about 40% of the corn went toward feed and leftover corn residuals, while 36% was utilized for biofuels (USDA ERS,

2020b). Corn was the major crop for feed grains, contributing almost 96% of the total feed grain production in the U.S. (USDA ERS, 2020a).

Due to the multifaceted economic significance of corn, the purpose of this dissertation research was to examine microbes and their influence on the corn agricultural practices through

(1) studies of the corn pathogen Pantoea stewartii subsp. stewartii and (2) identification of beneficial bacteria capable of using a byproduct of corn-based ethanol production as a growth substrate.

The genus Pantoea

Pantoea is a genus composed of a number of species that are all Gram-negative, rod shaped, gamma-proteobacteria in the family Enterobacteriaceae. Pantoea species cause a variety of diseases within different host plants or animals, including humans. A few are even able to colonize both plants and animals, such as Pantoea agglomerans (formerly Erwinia herbicola). Some examples of plant diseases P. agglomerans causes are bacterial blight in eucalyptus (Brady et al., 2012), bulb rot and leaf blight in sweet onion (Edens et al., 2006), and seed and ball rot in cotton (Medrano, Esquivel, & Bell, 2007). In humans, P. agglomerans is a known source of bacteremia (Christakis et al., 2007) or pneumonia (Kursun et al., 2012).

Besides P. agglomerans, other species within the Pantoea genus are also harmful to crop yields, such as P. ananatis, which causes fruit rot of netted melon (Kido et al., 2008), leaf spot disease in corn (Pérez-y-Terrón et al., 2009), center rot of onion (Carr et al., 2010), and leaf blotch in

Sudangrass (Azad, Holmes, & Cooksey 2000).

There are also instances of mutualistic and commensal interactions between Pantoea sp. and their various hosts. P. agglomerans, for example, has a mutualistic relationship with an insect host, the blueberry maggot fly. For the bacteria, the fly provides a nutrient source and a habitat, whereas the bacteria in return are able to process nitrogen species within the gut of the fly, thereby assisting digestion (MacCollom, et al., 2009). Many Pantoea sp. have epiphytic

(surface associated) relationships with the host plant as part of their microbial flora. Among these are Pantoea cypripedii on orchids (Brady et al., 2010) or Pantoea eucalyptii on thistle

(Nadarasah & Stavrinides, 2014). Many epiphytes have developed distinguishing features in order to adapt to their host environment. For example, it is thought that the yellow pigment characteristic of the Pantoea sp., produced by carotenoids, enables them to better survive as

epiphytes. These carotenoids can protect the bacteria from harmful ultraviolet radiation due to exposure to sunlight on the plant surfaces (Mohammadi, Burbank, & Roper, 2012a). In some instances, the bacteria are even able to manipulate their host to their benefit, such as the release of indole-3-acetic acid by P. agglomerans to trigger the release of nutrients from the host leaves

(Brandl & Lindow, 1998).

Pantoea sp. can also be found in non-host environments. Pantoea dispersa is found in soil (Selvakumar et al., 2008) and P. agglomerans in drinking water (September et al., 2007).

Additionally, several Pantoea species have been found in rainwater and have been shown to posess ice nucleating activity (Failor et al., 2017). Although some Pantoea species are able to survive without a host, there are some that are only able to survive and transmit with the help of vector organisms. P. ananatis requires insects such as the cotton fleahopper (Bell et al., 2007),

P. agglomerans can use the wood-boring beetle (Delalibera, Handelsman, & Raffa, 2005), and

Pantoea stewartii subsp. indologenes the mosquito (Terenius et al., 2012) while Pantoea stewartii subsp. stewartii lies in the corn flea beetle (Correa et al., 2012).

Research to utilize Pantoea species as biocontrol agents has also been performed, as some species contain antibacterial or antifungal properties. Pantoea vagans and P. agglomerans have both been shown to antagonize the growth of Erwinia amylovora, the causal agent of blossom blight on apple and pear flowers, through the production of the antibacterial agent herbicolin (Kamber et al., 2012; Pusey et al., 2011). Additionally, black rot in sweet potato caused by the fungal pathogen Ceratocystis fimbriata, has been found to be inhibited by Pantoea dispersa, an endophyte of the sweet potato (Jiang et al., 2019).

The hosts, diseases, and impact for each species of Pantoea are distinctive. However, there are similarities between the species, from their capsule pigment to the type of secretion

systems used for pathogenesis. Type VI secretion systems (T6SS) are common in the genus.

Effector proteins from the T6SS locus, encoded by hcp and vgrG, are homologous to genes important for pathogenesis in many Pantoea species, including P. agglomerans, P. vagans, P. ananatis, and P. stewartii (De Maayer et al., 2011). In P. agglomerans, species-specific type III secretion effectors are used to form galls in the plant host (Nissan, et al., 2012). Use of type III secretion in P. stewartii is likewise important for causing damage to plant cells (see below).

Comparative genomics has the potential to reveal insights into the shared and distinctive functionality across the different species of Pantoea (De Maayer et al., 2017; Wang, Wang, &

Jing, 2017).

The phytopathogen Pantoea stewartii subsp. stewartii

Pantoea stewartii subsp. stewartii (previously Erwinia stewartii) causes the disease

Stewart’s wilt in corn. This phytopathogen targets sweet corn, popcorn, and some susceptible field corn plant varieties of maize (Roper, 2011). The bacteria have a distinct yellow mucoid colony appearance, which is due to the yellow pigmented capsule produced by the bacteria at high cell densities. This capsule production, along with other characteristics involved in virulence and survival, is regulated by the process of quorum sensing (QS) (Koutsoudis et al.,

2006). QS is bacterial cellular communication based upon population density. The QS master regulator, EsaR, binds to DNA targets at low cell density causing repression or activation (von

Bodman et al., 2003). When the acyl-homoserine lactone (AHL) signaling molecule produced by the P. stewartii EsaI synthase protein becomes abundant enough in the local environment at high cell densities, it complexes with EsaR. AHL binding inactivates the EsaR protein resulting in deactivation and derepression of the QS genes at high cell density (Figure 1.1) (Schu et al.,

2009). Thus, the capsule production required for biofilm formation in the xylem occurs

exclusively at high cell density due to deprepression of the RcsA regulatory protein. QS is also important for regulating other factors for P. stewartii survival, such as stress responses and surface motility (Ramachandran et al., 2014). Specifically, surface motility is impacted by the transcription factor LrhA, which is known to regulate genes encoding fimbria and biosurfactant production in P. stewartii (Kernell Burke et al., 2015; Duong & Stevens, 2017). Further elucidation of this system has shown that the downstream regulon of EsaR is interconnected between LrhA and the capsule-producing regulator RcsA, and that RcsA also plays a role in motility (Duong & Stevens, 2017). The temporal control afforded through quorum sensing is critical for the ability of P. stewartii to cause disease, as mutant strains either lacking quorum sensing or constitutively expressing high cell density functions both exhibit reduced symptoms in plant virulence assays (von Bodman, Majerczak, & Coplin, 1998).

Stewart’s wilt disease

Stewart’s wilt is the name of the disease caused by P. stewartii in maize. F. C. Stewart was the first to report the disease in 1897 in Long Island, NY, and he inspired the naming of both the species and disease (Roper, 2011). When the corn flea beetle vector (Chaetocnema pulicaria) feeds on the corn plant by scratching its surface, the bacteria are transferred into the leaf apoplast through fecal contamination of the wound. During the initial stages of infection within the apoplast, the bacteria induce water-soaking symptoms, resulting in leaf lesions. From there, the bacteria secrete an endoglucanase to break down pit membranes and enter the xylem

(Mohammadi, Burbank, & Roper, 2012b). Inside the xylem, the bacteria form a dense monoculture biofilm with copious amounts of the exopolysaccharide stewartan that results in water flow blockage leading to wilt, plant cell necrosis, and in the case of seedlings, death of the plant (Figure 1.2) (Bradshaw-Rouse et al., 1981). This bacterial lifestyle is enabled by the

accurately timed expression of the QS regulated genes involved in the initial surface motility and later-stage exopolysaccharide stewartan production (Koutsoudis et al., 2006).

Stewart’s wilt is a costly disease for United States agriculture. Although resistant corn hybrids have been bred, there are many areas that still utilize susceptible strains of sweet corn

(Freeman & Pataky, 2001). The mechanism behind cultivar resistance is not completely understood. Recent findings suggest an increase in the vascular defense response of resistant cultivars; vascular blockage may reduce systemic travel and colonization within the xylem

(Doblas-Ibáñez et al., 2019). Stewart’s wilt disease impacts more than the corn crop yield each year. Just over 12% of corn produced in the United States was exported in 2019 (USDA ERS,

2020b). Because the disease can be transmitted to seeds produced by an infected plant, the seeds are subjected to inspection prior to any shipment outside of the North America. This enables the restriction of P. stewartii to the United States where it is native to help to protect susceptible cultivars (Michener, Pataky, & White, 2002).

Corn Flea Beetle

Chaetocnema pulicaria, the corn flea beetle, is the insect vector for P. stewartii. This 1.8 mm black beetle is only endemic in North America where it overwinters in the soil of corn fields and feeds on young corn seedlings upon emerging in the spring. P. stewartii reside in the midgut of infested corn flea beetles (Correa et al., 2012). The adults lay eggs that hatch after six days before spending two weeks in the larval stage. After a pupal stage of another five days, they reach adulthood, where they are ready to mate and repeat the cycle. Due to this rapid timeline, multiple generations can pass before the end of the beetle’s mating season and impact the corn plants throughout the growing season (Esker, 2005). Temporal analysis has revealed that beetles

infested with P. stewartii are most prevalent in August, although they can be found throughout the year (Esker & Nutter, 2003).

The initial onset of Stewart’s wilt disease is when the corn is first planted, and the beetles have their first exposure to the seedlings. Since the corn plants are still immature when infected, this has the most detrimental impact to the crop yield in a season. As the second generation of beetles emerges, the next wave of P. stewartii infection occurs, with this new generation acquiring P. stewartii from the infected plants of the first wave and reinfecting the more mature corn population. Corn yield is not impacted as severely during this second wave, since most of the plant growth has already occurred (Pataky, 2003).

Virulence Factors of P. stewartii

Type III Secretion System

Many pathogenic bacteria utilize a type III secretion system (T3SS) as a common mechanism of virulence. This type of protein transport is composed of a complex system that spans the inner and outer membrane in Gram-negative bacteria like P. stewartii, and it utilizes

ATP and chaperonins to transfer proteins through the secretion system across three membranes into the interior of the host target cell (Figure 1.3) (Galán & Collmer, 1999). The secretion system has been equated to a syringe-needle-type structure, and the proteins that compose the needle penetrate the host cells permitting the transfer of small proteins called effectors. Effectors can disrupt a variety of processes within the plant, including host immunity, host cell membrane integrity, nutrient release, plant metabolism, and signalling pathways (Deslandes & Rivas, 2012;

Stavrinides, McCann, & Guttman, 2008).

In P. stewartii, there are two functioning T3SSs. One enables persistence and colonization within the corn flea beetle host (Correa et al., 2012). For the beetle specific T3SS,

the structure is that of the Inv-Mxi-Spa T3SS family, which is common among bacteria capable of colonizing animal hosts or vectors. P. stewartii transcribes these genes from the Pantoea secretion island 2 (PSI-2) on a megaplasmid (Duong, Stevens, & Jensen, 2017). The gene ospC1 encodes an effector protein that is thought to play a key role in beetle colonization (Correa et al.,

2012).

The second T3SS utilized by P. stewartii is expressed within the corn plant and is a Hrc-

Hrp 1 T3SS. These are common in phytopathogens due to the longer, more flexible structure of the injectisome pilus that enables the penetration of the thick plant cell wall (Troisfontaines &

Cornelis, 2005). Genes for the T3SS and related effectors are found on Pantoea secretion island

1 (PSI-1) on a second megaplasmid (Duong, Stevens, & Jensen, 2017). The hrp genes encoding the T3SS are regulated by a two-component system HrpX/Y that enables the downstream HrpL alternative sigma factor regulator to activate all hrp genes (Merighi et al., 2003). Once activated, this gene cluster is autoregulated at a rapid pace to heighten expression during infection

(Merighi, Majerczak, & Coplin, 2005). Interestingly, genotypes of Arabidopsis thaliana resistant to the pathogen Pseudomonas syringae produce less of certain metabolites that are required for the induction of the T3SS in the bacteria in a dose-dependent manner (Anderson et al., 2014). This could be a way that P. stewartii cells are able to recognize their host and determine which T3SS to express during plant infection versus insect vector colonization.

The Hrp system also regulates genes that are required for the water-soaking characteristic seen at the beginning of infection in the leaf apoplast after transmission from the corn flea beetle

(Merighi et al., 2003). Genes designated wts are found on the P. stewartii chromosome directly adjacent to the hrp cassette, and these genes, specifically wtsE, encode for an effector essential to the virulence of the bacteria. WtsE induces fluid buildup by disrupting the plant cell membranes,

resulting in the water-soaking symptom at the beginning of infection (Coplin & Cook, 1990).

Due to the ability of wts mutants to survive in planta, it is thought that these are necessary for damaging the host, but not necessarily for the viability of P. stewartii (Coplin et al., 1992).

Analysis of the corn plant response to the WtsE effector revealed a large change in expression of genes in the phenylpropanoid pathway. This pathway leads to numerous metabolites influencing

(1) lignin buildup of cell walls during the hypersensitive response, (2) production of salicylic acid, and (3) plant defense signaling. The addition of some of these metabolites back into the system restores the plant defense response in the presence of the effector, indicating the disruption of the phenylpropanoid pathway is a key factor in P. stewartii virulence (Asselin et al., 2015). Recently, it was also found that WtsE is required for systemic infection within the xylem during the later stages of disease progression (Doblas-Ibáñez, et al., 2019).

Extracellular Polysaccharide

One of the most important virulence factors utilized by P. stewartii is its extracellular polysaccharide (EPS) capsule or exuded slime production. In P. stewartii, this EPS is known as stewartan. It has been seen that stewartan is composed of glucose, galactose, and glucoronate

(Coplin & Cook, 1990). The EPS protects the bacteria from agglutinin produced by the corn host, enabling it to proliferate systemically throughout the xylem instead of only producing a localized infection (Bradshaw-Rouse et al., 1981). It is also thought to aid in water retention for help with intercellular growth (Coplin & Cook, 1990). Additionally, the EPS capsule enables increased adherence of the bacteria to the xylem and subsequent biofilm formation. It is this characteristic that enables the physical blockage of the water transport within the xylem, which causes wilt disease symptoms (Koutsoudis et al., 2006). EPS synthesis is controlled via the

master quorum sensing regulator EsaR, which derepresses rcsA at high cell densities, leading to the activation of capsule (cps) gene transcription by the RcsA/B complex (Minogue et al., 2005).

Surface Motility

For many years, P. stewartii was considered a nonmotile species. However, the bacterium’s capacity for movement has more recently been reexamined. This is because orthologues of various motility-related genes were found in the P. stewartii genome (Roper,

2011). Additionally, due to the ability of these bacteria to produce biofilm, which oftentimes requires some form of motility, it was determined that they produce multiple flagellar structures.

These flagella are required for swarming motility, but they do not permit swimming motility in broth culture. When imaged, the flagella were seen to be much thinner and more fragile than those in other bacteria. In planta, it was seen that this motility is essential in the production of the biofilm, for it helps with the initial stages of aggregation. Without flagella, the bacteria cannot properly spread throughout the host xylem. The production of EPS is also required for this motility to occur (Herrera et al., 2008), and recent work has shown that regulation of the EPS by RcsA is co-controlled by the surface motility-associated transcription factor LrhA (Duong &

Stevens, 2017).

In comparison to other phytopathogens, such as those listed in subsequent sections, P. stewartii has a relatively smaller arsenal of virulence factors it employs in planta. Besides the aforementioned T3SS, biofilm production, and motility, these bacteria also utilize an endoglucanase to break down plant tissue for systemic infection (Mohammadi, Burbank, &

Roper, 2012b). It has also been found that the pigment produced as part of the capsule impacts virulence (Mohammadi, Burbank & Roper, 2012a), siderophore production impacts motility

(Burbank, Mohammadi, & Roper, 2014) and an RTX toxin is thought to be involved in the early

water-soaking symptom (Roper et al., 2015). A recent study also found genes encoding outer membrane porin proteins and a Lon protease impact the in planta survival and virulence (Duong,

Jensen, & Stevens, 2018). A comparison to other known wilt-disease causing pathogens is warranted to determine variation in the scope of virulence factors utilized by each.

Other Vascular Bacterial Pathogens

Xylella fastidiosa

Besides bacteria within the genus Pantoea, other phytopathogens can cause disease via vascular colonization and targeting, including Xylella fastidiosa. X. fastidiosa causes disease in a variety of different plants, including grapevines, and many types of tree leaf scorches (i.e., plum), with detrimental effects to the yield and large economic impact (Chatterjee, Almeida, &

Lindow, 2008). Like Pantoea sp., X. fastidiosa is found in the United States, although it is geographically limited to more tropical and subtropical regions in the Americas (Hopkins &

Purcell, 2002). Another similarity to Pantoea sp. is the transmission of X. fastidiosa to hosts via insect vectors. While P. stewartii subsp. stewartii is transmitted via the corn flea beetle, X. fastidiosa has a variety of sharpshooter leafhopper species that vector the bacteria into the multitude of hosts targeted by the bacterium (Hopkins & Purcell, 2002). X. fastidiosa can be immediately transmitted by the vector hosts, but they are also able to persist within the insects for a prolonged period before transmission, similar to the relationship between P. stewartii and the corn flea beetle (Hill & Percell, 1995).

Once vectored into the plant, X. fastidiosa travels systemically within the xylem, via pit membrane disruption (Roper et al., 2007b). X. fastidiosa uses type IV pili for twitching motility to migrate throughout the xylem of the host plants (Meng et al., 2005). Like P. stewartii, X. fastidiosa occlude the xylem with a biofilm and prevent water transport, leading to stunted fruit

growth, leaf scorch, and sometimes wilting. When forming a biofilm, they employ short type I pili to help with adhesion, as well as other fimbrial adhesins that are temporally expressed to help with the initial adhesion (i.e., XadA1, PilA2, PilC) and later aggregation (i.e., XadA2) necessary for biofilm formation (Caserta et al., 2010). The biofilm itself is composed of an EPS similar to that produced by Xanthomonas sp. and this EPS, encoded by gum genes, is required for the maturation of the biofilm, although not for the initial attachment (Roper et al., 2007a).

Unlike P. stewartii, X. fastidiosa does not have genes to encode a T3SS, nor does it have any homologues for T3SS effector proteins. Instead, it encodes a variety of ABC transporters

(ATP binding cassette) that are of the type I secretion superfamily. Type I secretion systems in

Gram-negative bacteria involve an ABC transporter in the inner membrane, a membrane fusion protein (MFP) that crosses the inner membrane, spanning the periplasmic space to the outer membrane where an outer membrane factor, often the large porin protein (TolC), is used for secretion through the outer membrane (Sharff et al., 2001; Jones & George, 2004). Secretion of this type is involved in numerous functions, including efflux pumps to help with drug resistance

(Lubelski, Konings, & Driessen, 2007), hemolysin secretion, and nutrient uptake (Jones &

George, 2004). Although it has not yet been seen to play a role in X. fastidiosa effector or toxin secretion, studies have shown that the TolC protein is required for the growth, survival, and virulence within the xylem, indicating this could have a role in defense against plant immune responses (Chatterjee, Wistrom, & Lindow, 2008).

In addition to type I secretion, X. fastidiosa also utilizes type II secretion, which is a Sec- dependent system that produces a pseudopilus capable of functioning like a piston to export proteins from the periplasm across the peptidoglycan and outer membrane (Sandkvist, 2001).

Based upon the proteins exported, such as xylanases, xylosidases, β 1,4 endoglucanases, and a

polygalacturonase (encoded by pglA) it is suspected this system is mainly important in degradation of the pit membranes within the xylem. Like with the P. stewartii endoglucanase, it is thought this allows systemic spread of the bacteria (Mohammadi, Burbank, & Roper, 2012b).

Support for this comes from the loss of systemic spread and therefore pathogenicity in bacteria with a pglA deletion (Roper et al., 2007b).

Many phytopathogens, including both P. stewartii and X. fastidiosa, are capable of QS.

For X. fastidiosa, the signaling molecule is a diffusible signaling molecule (DSF) with a 12- methyl tetradecanoic acid structure (Colnaghi Simionato et al., 2007), as opposed to the AHL structure of the P. stewartii QS molecule. QS in X. fastidiosa is regulated by the RpfC protein and the DSF synthase RpfF. It has been seen that the master regulator negatively regulates the synthase gene expression, unlike the synthase in P. stewartii, which is independent of the master regulator (Minogue et al., 2002). In X. fastidiosa QS controls the expression of adhesins, motility, and virulence factors, like the aforementioned genes tolC and pglA (Chatterjee,

Wistrom, & Lindow, 2008).

Ralstonia solanacearum

Another important vascular pathogen is Ralstonia solanacearum. These Gram-negative bacteria are considered to be one of the most detrimental bacterial phytopathogens, in part due to their incredibly wide host range (Mansfield, et al., 2012). Over 250 different plant species are susceptible to R. solanacearum infection, including solanaceaous plants, such as potatoes. They do not have one specific geographic location, and can therefore hinder crop yield across the globe (Peeters et al., 2013). Infection with R. solanacearum can lead to diseases such as the potato brown rot or Moko disease of banana, with the most common disease being total plant wilt.

R. solanacearum is not vectored by an insect like P. stewartii. Rather, they enter the plant through cracks and splits where lateral roots emerge, as they can survive outside of the host within the soil. Once they enter the plant, they travel up through the xylem and create a biofilm using EPS to block water transport. R. solanacearum has a very large number of effector proteins in its arsenal, which could be due to its vast number of possible hosts. Unlike in most phytopathogens, R. solanacearum transcribes T3SS genes throughout infection, instead of just during the initial stages (Jacobs et al., 2012). This T3SS is in the same Hrc/Hrp family as the one used in planta by P. stewartii, and the genes for this and the effectors are directly regulated by the master regulatory protein HrpB, which is also suspected to control other virulence factors for R. solanacearum (Occhialini et al., 2005).

In addition to the EPS necessary for pathogenicity (Araud-Razou et al., 1998), R. solanacearum has a multitude of other virulence factors. Type II secretion plays an important role in R. solanacearum infection by releasing 30 cell wall-degrading enzymes and other secreted proteins that are required for colonization and virulence (Liu et al., 2005). For survival within the plant host, R. solanacearum utilizes oxidative stress genes, like the peroxidase Bcp, to survive against the harmful reactive oxygen species (ROS) that are created by the plant during infection (Flores-Cruz & Allen, 2009). These oxidative stress genes are regulated by OxyR, which is required for the survival of the pathogen within the plant (Flores-Cruz & Allen, 2011).

Multidrug efflux pumps have also been seen to be necessary in this harsh environment, such as the ones encoded by acrA and dinF (Brown, Swanson, & Allen, 2007). Due to the limited oxygen availability within the xylem, R. solanacearum uses a cbb3-type cytochrome c oxidase, which is utilized in microaerobic environments (Colburn-Clifford & Allen, 2010). However, as a facultative organism, R. solanacearum has the capability to utilize inorganic nitrogen species

as terminal electron acceptors under anaerobic conditions. Detoxification of reactive nitrogen species, like nitric oxide by HmpX, is also crucial in planta (Dalsing et al., 2015).

Iron sequestration is important in the nutrient poor xylem. R. solanacearum has numerous siderophores, such as staphyloferrin B, which is regulated by the transcriptional regulator PhcA (Bhatt & Denny, 2004). PhcA also regulates a large number of virulence factors, such as EPS, motility, type II and type III secretion, adhesion, and signal sensing (Genin &

Denny 2012). The unique signaling molecule 3-hydroxypolmytic acid methyl ester (3-OH

PAME), synthesized by the protein PhcB, is what controls the transcriptional activator PhcA.

Synthesis is constitutive, and phenotypic change occurs based on confinement of the bacteria

(such as within the plant xylem) (Schell, 2000). QS is also possible in this species using an AHL signaling molecule and the SolR/SolI regulator and signal synthase. However, not much is known on the genes regulated by this system, as mutants deficient in QS exhibit wild-type levels of virulence (Schell, 2000).

R. solanacearum is capable of multiple forms of motility. First, it uses flagella for swimming motility, and this is required for the initial stages of infection and colonization to occur (Tans-Kersten, Huang, & Allen, 2001). Once within the plant, the bacteria then utilize type IV pili for twitching motility and surface adhesion. These are important for the formation of the biofilm within the plant, leading to disease symptoms, as well as for initial attachment to the roots to begin invasion (Kang et al., 2002). Research Plan

In comparison to other wilt-causing pathogens, a great deal remains to be discovered about the full scope of virulence factors employed by P. stewartii . Prior to the work described in this dissertation, little was known about the full gene expression profiles (i.e., transcriptomes) 16

for plant pathogens in planta. Chapter Two presents findings from one of the first in planta

RNA-Seq studies and how the data generated was used to discover the genes most highly regulated by P. stewartii when it is living in the plant xylem. Chapter Three builds upon this initial work in an effort to understand the role of select transcription factors essential for P. stewartii survival when it grows in planta. The goal of these efforts was to identify possible targets for disease intervention strategies against P. stewartii to improve corn production.

Corn is an important agricultural commodity in the United State not only due to food security, but also for energy production needs. Corn ethanol production has developed as a major industry. In an attempt to make this process more economically profitable, Chapter Four describes efforts to use a byproduct of ethanol production, syrup, as a growth substrate for beneficial bacteria. These bacteria, in turn would have the potential to be repurposed for use as a feed additive for aquaculture grown animals, further contributing to human food security.

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Figure 1.1. Simple schematic of the quorum-sensing system within P. stewartii. At low cell density, EsaI is constitutively expressed to synthesize the AHL signal. The EsaR regulatory protein is bound to the promoter of target genes, which thereby blocks transcription of those genes if acting as a repressor, or enhances transcription as an activator. At high cell density, the

AHL enters the cell and complexes with EsaR, leading to the release of the promoter region, thereby enabling derepression or deactivation of those target genes, respectively.

Figure 1.2. Examples of Stewart’s wilt symptom severity. Scoring of symptom severity is based on 1 point increments, with (a) 0 = no symptoms, (b) 1 = few scattered lesions on one leaf,

(c) 2 = scattered water soaking symptoms on multiple leaves, (d) 3 = numerous lesions and slight wilting of one leaf, (e) 4 = one or more leaves is severely wilted, (f) 5 = One or less leaves still green, the rest completely wilted, and (g) a close up view of the leaf lesions.

1) 2)

Figure 1.3. (1) Simple model of a type III secretion system (T3SS) structure. Chaperonins shuttle the required proteins to the T3SS, where they are transferred across both membranes within the cell envelope of a Gram negative bacterium. The injectisome connects the bacterial and target host cells, and the effector proteins are transferred into the host cell. This process is driven with the use of an ATP-hydrolyzing protein at the base of the structure. In plant pathogens, the injectisome must be long enough to also penetrate through the cell wall. (2)

Example of plant-pathogen interaction regarding host immunity. The bacteria can have

PAMPs that are recognized by the host cell. This would initiate PAMP-triggered immunity

(PTI). Effectors secreted by the pathogen into the host cell are able to block PTI from taking place. In cases where the pathogen has effectors that are recognized by the host, effector- triggered immunity (ETI) can occur. PRR = Pattern Recognition Receptor, PAMP = Pathogen

Associated Molecular Pattern.

CHAPTER TWO

Analysis of the in planta Transcriptome Expressed by the Corn Pathogen Pantoea stewartii subsp. stewartii via RNA-Seq

Packard H, Kernell Burke A, Jensen RV, Stevens AM*. 2017. Analysis of the in planta transcriptome expressed by the corn pathogen Pantoea stewartii subsp. stewartii via RNA-Seq.

PeerJ 5:e3237 https://doi.org/10.7717/peerj.3237

*Corresponding author:

219 Life Sciences 1 (0910)

970 Washington St. SW

Virginia Tech

Blacksburg, VA 24061

Phone (540)-231-9378

FAX (540)-231-4043

Email: [email protected]

Keywords: Transcriptome analysis, Pantoea stewartii, Phytopathogen, Corn, RNA-Seq

Attributions

Holly Packard Bartholomew contributed to the experimentation and analysis for data in Figures

2.1, 2.2, 2.3 and Tables 2.1, 2.2, S2.1, S2.2, S2.3, S2.4, S2.5, S2.6, S2.7, S2.8, S2.9, and S2.10.

Dr. Ann M. Stevens was the lead principle investigator and Dr. Roderick V. Jensen was also a principle investigator on this project. Holly and Ann wrote the manuscript. Dr. Alison Kernell

Burke contributed to the experimentation for Figures 2.1 and 2.2, and Tables 2.1, 2.2, S2.1, S2.2,

S2.3, S2.4, S2.5, S2.6, S2.7, and S2.8.

Abstract

Pantoea stewartii subsp. stewartii is a bacterial phytopathogen that causes Stewart’s wilt disease in corn. It uses quorum sensing to regulate expression of some genes involved in virulence in a cell density-dependent manner as the bacterial population grows from small numbers at the initial infection site in the leaf apoplast to high cell numbers in the xylem where it forms a biofilm. There are also other genes important for pathogenesis not under quorum-sensing control such as a Type III secretion system. The purpose of this study was to compare gene expression during an in planta infection versus either a pre-inoculum in vitro liquid culture or an in vitro agar plate culture to identify genes specifically expressed in planta that may also be important for colonization and/or virulence. RNA was purified from each sample type to determine the transcriptome via RNA-Seq using Illumina sequencing of cDNA. Fold gene expression changes in the in planta data set in comparison to the two in vitro grown samples were determined and a list of the most differentially expressed genes was generated to elucidate genes important for plant association. Quantitative reverse transcription PCR (qRT-PCR) was used to validate expression patterns for a select subset of genes. Analysis of the transcriptome data via gene ontology revealed that bacterial transporters and systems important for oxidation reduction processes appear to play a critical role for P. stewartii as it colonizes and causes wilt disease in corn plants.

Introduction

Pantoea stewartii subsp. stewartii is a Gram-negative gamma-proteobacterium that causes Stewart’s wilt disease in corn plants. After P. stewartii enters the corn plant through wounds created during feeding by the corn flea beetle, Chaetocnema pulicaria, it first causes water-soaked lesions within the leaves of the plant. Once within the leaf apoplast, the bacteria travel to the xylem of the plant where they can then proliferate and form a biofilm containing the exopolysaccharide stewartan. Biofilm formation blocks water transport within the xylem leading to wilting and even death of seedlings (Bradshaw-Rouse et al., 1981). More specifically, the biofilm buildup leads to rupturing of the pit membrane between xylem cells, which normally prevents vascular pathogen passage, enabling the continued spread of the bacteria in a systemic manner while simultaneously inhibiting water transport (Choat, Cobb, & Jansen, 2008).

Although resistant corn hybrids have emerged in the last 50 years, there are still areas where partially and fully susceptible cultivars are grown (Freeman & Pataky, 2001). The disease is native to North America, but can be transmitted to the seeds from the infected parent plant, therefore thorough examination of the seeds must occur before exportation (Michener, Pataky, &

White, 2002).

The lifestyle of P. stewartii requires precise temporal control of colonization and virulence factor expression in the plant host. Quorum-sensing regulation is known to enable the transition from low bacterial density in the leaf apoplast to high bacterial density in the xylem.

This cell-cell communication occurs in response to the production of population density- dependent signals. The master quorum-sensing regulator, EsaR, is active at low cell density, but rendered inactive at high cell density in the presence of the acyl-homoserine lactone signal, 3-

oxo-C6-homoserine lactone (von Bodman, Majerczak, & Coplin, 1998). Thus one subset of genes in P. stewartii is activated or repressed at low cell density, but then these same genes will be deactivated or derepressed, respectively, at high cell density (Beck von Bodman & Farrand,

1995; Schu et al., 2009). Quorum sensing has been demonstrated to directly regulate genes important for exopolysaccharide production, adhesion/motility and stress response

(Ramachandran et al., 2014), including the second tier transcription factors RcsA and LrhA, whose regulons are important for virulence (Kernell Burke et al., 2015).

Other virulence factors in P. stewartii appear to be expressed independently of the quorum-sensing response. For example, hrp (hypersensitive response and pathogenicity) genes that encode for type III secretion system (T3SS) and effector proteins are also activated during infection (Frederick et al., 2001; Correa et al., 2012). The WtsE (water soaking) effector protein is regulated as part of the HrpL regulon (Merighi et al., 2003), and is responsible for disrupting the host cell membrane, leading to the buildup of fluids characteristic of the water-soaking symptom (Ham et al., 2006). In addition to water soaking, WtsE is also responsible for altering the metabolome within the plant, specifically inducing gene expression for the phenylpropanoid pathway (Asselin et al., 2015). Disrupting this pathway influences the ability of the plant to accumulate lignin during the hypersensitive response, produce salicylic acid, and maintain plant defense signaling, indicating this alteration is a key factor in P. stewartii success (Asselin et al.,

2015).

To better understand the interactions occurring between the corn plant and P. stewartii, and how this influences expression of genes required for pathogen survival within the host, an analysis of in planta bacterial gene expression was performed. It was hypothesized that comparing in planta transcriptome levels to those of the bacteria in a pre-inoculum in vitro liquid 32

culture (low cell density planktonic growth) or an in vitro agar plate culture (high cell density surface growth) would reveal genes required exclusively for host colonization and infection.

Genes of interest identified through studies of P. stewartii may serve as targets for disease intervention strategies and have implications for understanding other xylem-dwelling and/or wilt disease-causing bacterial phytopathogens.

Materials and Methods

Bacterial strains and media

Strains of P. stewartii and Escherichia coli that were used in this study are listed in Table

S2.1. Luria Bertani broth (LB; 10 g/L tryptone, 5 g/L NaCl, 5 g/L yeast extract) or 1.5% agar plates were used for all E. coli strains, while both LB and Rich Minimal medium (RM; 1X M9 salts, 2% casamino acids, 1 mM MgCl2, 0.4% glucose) were used for P. stewartii growth. E. coli strains were grown at 37°C and P. stewartii strains were grown at 30°C. Growth media were supplemented with nalidixic acid (30 µg/mL) or ampicillin (100 µg/mL) when required (Table

S2.1).

Growth of cells for RNA-Seq analysis

Three different conditions were used to grow duplicate samples of P. stewartii for RNA-

Seq analysis. First, a liquid culture of P. stewartii DC283 was grown overnight shaking at 30 ᵒC in LB medium supplemented with 30 µg/ml nalidixic acid. This was subcultured to an optical density (OD600) of 0.05 in 5 ml of the same medium and then grown to an OD600 of 0.2. The cells were pelleted by centrifugation (Eppendorf centrifuge 5424, rotor 5424R) for 1 min at

10,000 rpm and washed in phosphate buffered saline solution (PBS; 137 mM NaCl, 2.7 mM 33

KCl, 10 mM Na2HPO4 and 2 mM KH2PO4, pH 7.4) followed by a second centrifugation step.

RNA Protect Bacterial Reagent (Qiagen)(5 mL) was used to resuspend the pellet. After a brief vortex and 5 min incubation at room temperature, centrifugation was again performed and the pellet was stored at -20 ᵒC temporarily until RNA was extracted.

The second set of samples was comprised of agar-grown bacteria. A culture of P. stewartii DC283 was grown overnight shaking at 30 ᵒC in RM liquid medium supplemented with

30 µg/ml nalidixic acid. This was subcultured the following day to an optical density (OD600) of

0.05. A 100 µl volume of this was spread onto a RM medium 1.5% agar plate with 30 µg/ml nalidixic acid and then incubated at 30 ᵒC for 18 hours. The plate culture was harvested by using

5 mL of RNA Protect Bacterial Reagent to flood the plate, and then the cells were gently scraped and pipetted off of the plate and into a microcentrifuge tube. This sample was briefly vortexed, incubated at room temperature for 5 min, pelleted via centrifugation for 1 min at 10,000 rpm as described above and the pellet was stored at -20 ᵒC prior to RNA extraction.

Third, in planta bacterial samples were prepared. Zea mays ‘Jubilee’ corn seeds (HPS

Seed) were planted and grown for five days in a Percival Scientific plant chamber at 28 ᵒC, 80% humidity, 16 hour light and 8 hour dark cycles, and at least 200 mE m-2 s-1 light intensity in

Sunshine Mix #1 soil. On day four, P. stewartii DC283 was grown overnight in LB medium supplemented with 30 µg/ml nalidixic acid in 30 ᵒC. This was subcultured on day five to an

OD600 of 0.05, and then grown to an OD600 of 0.2. One mL of the culture was harvested, via centrifugation for 1 min at 10,000 rpm, and washed in PBS. Average-sized healthy seedlings were surface washed with 70% ethanol at the point of inoculation at the base of the stem, then scratched with a sterile syringe needle (one cm in length and one cm above the soil) deep enough to reach the plant xylem, and 5 µL of culture resuspended in PBS were pipetted into the scratch 34

area. The plants were grown for ten more days before harvesting. The plant stem and a razor blade were washed with ethanol, and then the stem was cut at the soil line and again at the top before leaf branching occurred. The stem was placed in RNA Protect Bacterial Reagent and a pipette was used to draw 1 mL up through the stalk to extract the biofilm. Samples, composed of material recovered from two stems, were then briefly vortexed, incubated at room temperature for 5 min, and bacterial cells were pelleted via centrifugation at 10,000 rpm for 1 min in an

Eppendorf centrifuge 4524. Pellets were stored at -20 ᵒC prior to RNA extraction.

RNA Purification and RNA-Seq

Frozen cell pellets were resuspended in 100 µl TE buffer (10 mM Tris-HCl, 1 mM

EDTA, pH 7.0) containing 15 mg/mL lysozyme and 30 mAU/mL of Proteinase K (Qiagen), as previously described (Ramachandran et al., 2014). After resuspension of the pellet, the miRNeasy kit (Qiagen) was used to extract total RNA per the recommended manufacturer’s protocol. Quality of RNA was determined at the Virginia Tech Biocomplexity Institute (VTBI) via the Agilent Bioanalyzer 2100, and a minimal RNA integrity number (RIN) of 7.0 was required for continued analysis. Ribosomal RNA (rRNA) was removed from the sample using a

RiboZero Bacteria kit (Illumina) and HiSeq 2500 100nt single-end read Illumina sequencing was performed at the University of Illinois Roy J. Carver Biotechnology Center.

RNA-Seq Data Analysis

Data preparation and analysis were performed based on a previously published protocol

(Kernell Burke et al., 2015). Briefly, the data was downloaded and unzipped into the Geneious software (version 8.3.1) to align to the coding sequences annotated in the WGS reference

sequence AHIE00000000.1 for Pantoea stewartii subsp. stewartii DC283 from NCBI. Thus, the small amount of plant sequences in the samples were eliminated from the analysis.

Normalization of individual read counts for genes to the total number of mapped sequence reads via reads per million (RPM) was performed in Microsoft Excel. Due to the high similarity of the many transposase sequences in the Pantoea genome, all transposases and IS66 family insertion sequences were excluded from the read normalization analysis. RPM expression values were then compared between each sample through ratios.

In addition, the Bioconductor software package “DESeq2” (Love, Anders and Huber, 2014) was used in R (3.2.4) to analyze the raw read counts with a more sophisticated gene expression normalization and error model to estimate the statistical significance of detected gene expression changes by calculating multiple testing adjusted p-values. The fold changes (DESeq Fold

Regulation) determined by this second method overlapped to a large extent with our Microsoft

Excel analysis for the genes with four-fold or greater change (Tables S2.2 and S2.3). The adjusted p-values (DESeq padj) for those gene selected for qRT-PCR validation were all less than 0.023.

Genes chosen from this dataset for qRT-PCR validation for the in planta culture and pre-inoculum in vitro liquid culture comparison were selected based upon previous standards

(Kernell Burke et al., 2015). These genes each had greater than 100 reads for at least one of the samples, there was at least a four-fold change in expression between the two sample types compared, and there was no more than a two-fold change between the two replicates for each sample type. From the list of genes that met the above criteria, ten genes were chosen for qRT-

PCR validation based upon their biological function. These same ten genes were used for validation for the in planta culture and in vitro plate culture comparison. Three of the genes fell 36

below the four-fold change in expression threshold, but were still included in this second analysis. Three control genes were selected based on stable housekeeping function, with at most a two-fold difference between the replicates, and less than a two-fold change between the sample types.

Cloning of Coding Regions of Genes of Interest for Primer

Optimization

The coding region of the genes selected for qRT-PCR validation of the RNA-Seq data were cloned into pGEM-T (Promega). PCR was performed with 1X ThermoPol Buffer, 200 µM dNTP, 1.25 units/ 50 µL of Taq Polymerase, 0.2 µM of each primer (Table S2.4), and P. stewartii DC283 chromosomal DNA template. Thermocycler settings per enzyme protocol (New

England Biolabs) were denaturation at 95°C for 30 seconds, annealing for 60 seconds at the appropriate temperature (Table S2.4), and extension at 68°C for 30 seconds, performed for 30 cycles. The final extension was 68°C for 5 min. The PCR products were visualized on a 1% agarose gel, and extracted using a Gel Extraction Kit (Qiagen). Fragments were modified by addition of dATP via Taq polymerase and a PCR Purification Kit (Qiagen) was used to remove additional dATPs. This PCR product was then ligated into the pGEM-T vector (Promega) and the resulting plasmid was transformed into E. coli Top 10 (Table S2.1). Plasmids containing the coding regions were screened via PCR and sequenced (VTBI) to confirm the construct.

Quantitative Reverse Transcription PCR (qRT-PCR)

The qRT-PCR primers for the genes of interest (Table S2.4) were designed by Primer

Express, version 3.0 (Life Technologies) to amplify approximately 100 bp segments from

regions with uniform coverage in the RNA-Seq reads as confirmed using Geneious software. For primer optimization (90-110% efficiency) and qRT-PCR (Applied Biosystems 7300 Real-Time

PCR System), the primers were all at 0.4 µM concentration, with the exception of CKS_3793

(0.6 µM), as this was optimized from a previous study (Kernell Burke et al., 2015). RNA for each sample type was harvested using the same methods as for the RNA-Seq following the miRNeasy kit protocol. Each sample had a RIN value of at least 7. Once extracted, the RNA was converted to cDNA using the ABI High Capacity cDNA Reverse Transcription kit (Thermo

Fisher Scientific). The Pfaffl method was used to determine the fold change differences between samples from the in planta culture and either the pre-inoculum in vitro liquid culture or in vitro plate culture.

Gene Ontology

Gene ontology (GO) analysis was performed using topGO software (Alexa &

Rahnenfuhrer, 2016) in R version 3.3.0 (Bioconductor). The genes from the RNA-Seq data that were four-fold or more differentially expressed between the in planta culture and pre-inoculum in vitro liquid culture were separated into genes that were upregulated or downregulated in planta. This was repeated for the in planta comparison with the in vitro plate culture. Fisher’s exact test was used for statistical analysis, specifically using the default “weight01” algorithm for processing the datasets (Alexa, Rahnenfuhrer, & Lengauer, 2006). Analysis focused on groups of genes enriched for the Biological Process (BP) gene ontologies. Gene groups with p-values of

0.01 or lower were considered significantly regulated within the dataset.

Accession numbers

The read data for the pairs of duplicate samples of the P. stewartii DC283 cells from the in planta culture, the pre-inoculum in vitro liquid culture, and the in vitro plate culture have been deposited in the NCBI Sequence Read Archive (SRA) with accession numbers, GSM2333085,

GSM2333086, GSM2333087, GSM2333088, GSM2333089, GSM2333090, respectively. An

Excel file summarizing the total read counts for each sample using the P. stewartii DC283 version 8 sequence annotations from NCBI was deposited into the NCBI Gene Expression

Omnibus (Edgar, Domrachev, & Lash, 2003) database (GEO Accession GSE87520).

Results

Comparison of RNA-Seq Data Reveals Genes Important for in planta Colonization and Growth

RNA-Seq was performed on wild-type P. stewartii DC283 RNA extracted, in duplicate, from an in planta infection culture, a pre-inoculum in vitro liquid culture, and an in vitro agar plate culture in order to determine genes differentially expressed during an in planta infection versus in vitro culture conditions. Raw RNA-Seq reads of 100 bp length yielded an average of between 32.7 and 39.2 million reads for the different samples. The normalized RPM counts for each data set were calculated, replicates were averaged, and the fold change of differential regulation between two different growth conditions was determined for each gene. Genes with four-fold or greater increased RPM expression levels in planta compared to the pre-inoculum liquid or in vitro plate cultures were considered upregulated, while those whose expression levels were decreased four-fold or more in planta were considered downregulated (Fig. 1). 39

There were 528 genes (roughly 10% of the genome) that had a minimum of four-fold differential RPM expression between the in planta set and the pre-inoculum in vitro liquid culture set (Table S2.2). The highest fold RPM change for an annotated gene was about a 53- fold higher in planta compared to the pre-inoculum liquid culture for gene CKS_3263, annotated as an HrpA family pilus protein. Comparing the in planta data set with the in vitro plate culture set yielded 530 differentially expressed genes (Table S2.3) with a minimum of four-fold differential RPM expression. The highest fold RPM for an annotated gene was almost 70-fold higher in planta compared to the in vitro plate culture for gene CKS_3355, annotated as a periplasmic-binding component of an ABC superfamily ribose transporter. Interestingly, there was a great deal of overlap between the most upregulated and downregulated genes between the in planta and pre-inoculum liquid culture comparison and the in planta and in vitro agar plate culture comparison. There were 357 genes found to be common in both comparisons, 308 upregulated and 49 downregulated (Table S2.5), indicating these genes are unique to plant colonization and infection. Results of a secondary analysis of the RNA-Seq data using DESeq2

(DESeq Fold Regulation) demonstrated that the DESeq results overlapped to a large degree with our Microsoft Excel RPM analysis for the genes with four-fold or greater change (Tables S2.2 and S2.3), and also provided impressive estimates of statistical significance. Only a relatively small number of additional new genes with four-fold or greater change were identified via

DESeq (Table S2.6), thus the RPM results was used for subsequent analysis.

Validation of the RNA-Seq via Quantitative Reverse Transcription

PCR

Ten genes that were regulated greater than four-fold via the RPM analysis (p-values

(DESeq padj) < 0.023) or were of particular physiological interest as described below, were chosen to use for qRT-PCR validation of the in planta versus the pre-inoculum liquid culture

RNA-Seq comparison (Table 2.1) and for the in planta versus the in vitro plate RNA-Seq comparison (Table 2.2) using a second independent set of RNA samples. Seven of these selected genes were differentially regulated four-fold or more in both comparisons. Three of the genes fell below the four-fold change in expression threshold in the in planta versus in vitro plate culture comparison, but they were still included in the qRT-PCR studies. Gene choice was also driven based in part upon putative annotated biological function. CKS_3263 and the CKS_4537 were chosen because of their relation to the T3SS regulon, which would indicate if they were required during late stage infection. Transcriptional regulators encoded by CKS_3570, associated with stress response or pathogenicity (Gallegos et al., 1997), CKS_2505, associated with cellular metabolism, pili formation, and suspected in helping with persistence (Deng, Wang,

& Xie, 2011), and hupA, associated with DNA binding and regulation (Kohno et al., 1990), were chosen for validation, as well as the rmf, which encodes a translational regulator seen to be activated during stationary phase in E. coli (Wada et al., 1990). Genes aceB and yeaG were chosen to look for metabolic changes that are in planta specific. CKS_3793 was chosen due to its normal function in microaerobic environments, hinting at the conditions within the plant xylem (Anraku & Gennis, 1987; Cotter et al., 1997). Finally, the bfr gene was chosen due to its role in iron acquisition during plant-pathogen interactions (Lawson et al., 2009). Control genes

recF, atpD, and gyrB (Tables 2.1 and 2.2) were chosen based upon their housekeeping functions and stable expression levels under all three growth conditions.

Although the absolute values for the RNA-Seq and qRT-PCR gene expression fold changes were not identical, the Pfaffl method for qRT-PCR analysis yielded similar trends for all genes chosen for expression validation from the RNA-Seq data (Figure 2.2, Tables S2.7 and

S2.8). Similar trends were found using all three of housekeeping control genes recF (Figure 2.2), gyrB, and atpD (Tables S2.7 and S2.8). Thus, all three of these genes have the capacity to serve as appropriate internal controls for future studies of the P. stewartii transcriptome. The overall

RNA-Seq dataset in this study was strongly supported based upon the qRT-PCR analysis, enabling further bioinformatics analysis of the full data set, specifically with regard to regulation of biological processes in planta.

Gene Ontology (GO) analysis demonstrates the importance of select groups of genes in planta

GO analysis was used to identify common patterns in the functions of differentially expressed genes identified through RNA-Seq as described above. The most significant biological processes driving major physiological responses in P. stewartii during late stage biofilm formation in the plant are shown in Figure 2.3. From the in planta vs. pre-inoculum liquid culture upregulated set of genes, GO analysis revealed six different groups of genes under the biological processes hierarchy with a p-value below 0.01 (Figure 2.3A and Table S2.9). The groups with the highest number of genes were involved in transport (with 61 genes), followed by the oxidation-reduction process (with 31 genes), and protein secretion (with eight genes). For the downregulated set of genes, eight different groups were given from the biological processes 42

hierarchy, and the group with the highest numbers of genes related to translation (with six genes)

(Figure 2.3A and Table S2.9).

From the in planta versus in vitro plate culture GO analysis nine biological process groups were identified with a p-value below 0.01 from the upregulated genes (Figure 2.3B and

Table S2.10). As with the in planta and pre-inoculum liquid culture comparison, transporters

(with 88 genes) and oxidation-reduction processes (with 33 genes) were the top two GO categories represented, with phosphoenolpyruvate-dependent sugar phosphatase system genes third on the list (12 genes). The downregulated genes from this comparison resulted in three groups of biological processes. All three groups in the downregulated set had the same number of genes (with two genes) downregulated in their categories (Figure 2.3B and Table S2.10). Thus genes associated with transporters and oxidation-reduction processes appear to play a vital role for P. stewartii in planta.

Discussion

There are a number of phytopathogens that preferentially colonize the xylem of target plants. However, to date, knowledge about the full set of genes required for plant colonization and virulence is limited. Previous studies aimed at analyzing the transcriptome of bacterial vascular pathogens have been performed in vitro (Kimbrel et al., 2011). Microarray technology was successfully used to analyze the in planta transcriptome of Ralstonia solanacearum and

Xanthomonas oryzae pv. oryzae (Soto-Suárez et al., 2010; Jacobs et al., 2012). Other work using dual-transcriptome RNA-Seq to simultaneously analyze the gene expression patterns of bacterial or fungal pathogens within their hosts have also been performed (Camilios-Neto et al., 2014).

However, the challenge of performing transcriptome-level protocols on in planta bacterial

samples remains a common deterrent due to difficulty extracting high quality bacterial mRNA in appropriate abundance. Here, RNA-Seq technology was used to analyze the full transcriptome of P. stewartii isolated as a monoculture grown within the xylem of a corn plant. A comparison of the in planta culture to either a pre-inoculum in vitro liquid culture or an in vitro agar plate culture revealed that ~10% of the genome exhibited greater than four-fold changes in gene expression (Figure 2.1). Many of these differentially expressed genes are likely required specifically during host infection. The RNA-Seq data was validated using qRT-PCR analysis of a select set of ten differentially expressed genes (Figure 2.2). This enabled confidence in a bioinformatic GO analysis that revealed gene expression associated with the biological processes of transport and oxidation/reduction groups are significantly upregulated in planta suggesting that these genes play a critical role in plant colonization and/or virulence (Figure 2.3).

In many plant-pathogen interactions, survival within the host depends upon the pathogen’s ability to adapt to its environment (Roper, 2011; Fatima & Senthil-Kumar, 2015).

Bacteria are known to have the ability to influence host metabolism and take advantage of the resulting nutrient availability (Guo et al., 2012). Previous work has shown that P. stewartii is able to alter metabolic pathways within the host corn plant, specifically the phenylpropanoid pathway (Asselin et al., 2015). Disruption of this pathway could cause an alteration of metabolites available for the bacteria to utilize. In the P. stewartii in planta culture, by far, the largest group of genes upregulated four-fold or greater included genes encoding transporters for amino acids (e.g. alanine, arginine, aspartate, glutamate, histidine, isoleucine, leucine, lysine, valine), sugars (e.g. arabinose, galactose, ribose, xylose), and other compounds (e.g. ammonium, magnesium, molybdate, sulfate, taurine) in comparison to either of the in vitro culture conditions. Some transcriptional regulators associated with these transporters were also

upregulated, including nac, involved in regulating genes associated with nitrogen assimilation and araC, important for arabinose catabolism. The observed regulatory patterns indicate the transporters are activated while in the host, indicating availability or preference of the transporter-associated molecules within the nutrient-limited xylem. Published work by others has shown that ABC-transporters and TonB dependent transporters are used by the bacteria to scavenge for plant derived carbohydrates in otherwise nutrient poor environments such as leaf surfaces, apoplast, and xylem niches (Blanvillain et al., 2007; Delmotte et al., 2009; Fatima &

Senthil-Kumar, 2015). Whether specific nutrients are normally available in the xylem or specifically produced in response to the bacterial infection remains to be determined for P. stewartii in planta.

The second largest group of annotated genes upregulated in planta corresponded to genes associated with oxidation reduction biological processes. This list included cytochrome d ubiquinol subunits (CKS_3793 and cytD (CKS_3794)). In E. coli, these subunits are involved in electron transport only when oxygen is very limited in the environment (Miller & Gennis, 1983;

Anraku & Gennis, 1987). This suggests the corn xylem and/or bacterial biofilm is an oxygen- limited environment for the bacteria, which supports previous conclusions from studies performed with other vascular pathogens (Pegg, 1985; Dalsing et al., 2015).

Annotated genes associated with fatty acid metabolism were also grouped into the oxidation reduction GO category. The fadJ gene (CKS_2016) encodes a protein primarily involved in anaerobic degradation of long and medium-chain fatty acids (Campbell, Morgan-

Kiss, & Cronan, 2003) and fadE (CKS_0306) is an acyl-coenzyme A dehydrogenase involved in the fatty-acid beta-oxidation (Campbell & Cronan, 2002). Most of the other genes involved in fatty acid metabolism were also upregulated in planta with the exception of fadD, fadH and 45

fadR, the latter of which encodes a regulator for the pathway. Interestingly, the glyoxylate cycle associated genes aceA and aceB (CKS_4658 and CKS_4657), encoding isocitrate lyase and malate synthase respectively, and the latter of which was used for qRT-PCR validation, were also expressed in planta. These results indicate the potential availability of long fatty acids as a carbon source for the bacteria while in the xylem, resulting in the use of beta-oxidation and the glyoxylate bypass pathways.

Annotated dehydrogenases involved in oxidation of a number of other potential carbon sources/metabolic intermediates, including aldehyde dehydrogenase (aldB), an altronate oxidoreductase involved in pentose-gluconate interconversion, succinate-semialdehyde dehydrogenase (gabD), glycerol dehydrogenase (gldA), myo-inositol dehydrogenase, and Zn- containing alcohol dehydrogenase, were also upregulated. The NAD(P) transhydrogenase alpha and beta subunits (encoded by pntA and pntB) involved in the transhydrogenation between

NAD(H) and NADP(H) was an upregulated function as well. Collectively, these findings suggest that the overall physiology of P. stewartii is being altered in planta so that the cells have a greater capacity to utilize alternative carbon sources and/or alter internal carbon flow to their advantage, permitting successful growth in the nutrient-limited xylem during late stage infection where the impact of stationary phase also likely plays an important role.

Within the oxidation reduction processes GO category were also a few annotated genes upregulated that are associated with environmental stresses on the bacteria. This included genes important for the oxidative stress response, sodC (CKS_3446), which encodes a superoxide dismutase and CKS_3597, encoding catalase. Additionally, hmp (CKS_1509) encodes the nitric oxide dioxygenase, which converts nitric oxide to nitrate. Nitric oxide is known to be used by plants as a signaling molecule during defense (Torres, Jones, & Dangl, 2006) and can also 46

produce reactive nitrogen species (RNS) when reacted with superoxide (Bellin et al., 2012).

During plant defense response, many plants are known to secrete reactive oxygen species as a way to combat pathogenic infection (O’Brien et al., 2012). The expression of these genes by P. stewartii could indicate a method of defense utilized by the phytopathogen against the plant immune response.

Virulence factors are also known to be important to successful plant infection by P. stewartii. It has long been known that one of the two P. stewartii T3SS is essential for the early stages of plant infection (Frederick et al., 2001; Roper, 2011) and the other is important for colonization of the corn flea beetle (Correa et al., 2012). The RNA-Seq studies have determined that genes encoding HrpA, HprB, HrpD, HrpF, HrpJ, HrpN, HrpO, and HrpT family proteins, as well as many other T3SS related genes, are highly expressed in planta (Tables S2.2 and S2.3).

This supports previous work showing the importance of T3SS in pathogenesis (Frederick et al.,

2001), but reveals their potential continued involvement in late-stage P. stewartii infection. Use of a T3SS throughout infection has been seen from an in planta analysis of R. solanacearum

(Jacobs et al., 2012), but this has not been demonstrated experimentally in P. stewartii (Merighi et al., 2006; Roper, 2011).

In conclusion, very little is known of the expression of genes required during in planta infection within vascular pathogens. Transcriptomic work enables large-scale analysis of patterns of gene expression within the bacteria during their interaction with the host. Analysis of changes in the P. stewartii in planta transcriptome has revealed some of the key groups of genes, such as nutrient transporters and metabolic oxidation reduction processes including associated regulators, expressed by the bacteria during colonization and growth in the xylem. These finding may also apply to other xylem-dwelling and wilt disease-causing phytopathogens. 47

Additional Information and Declarations

Competing Interests

The authors declare there are no competing interests.

Author Contributions

Holly Packard conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

Alison Kernell Burke conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, reviewed drafts of the paper.

Roderick V. Jensen conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, prepared figures and/or tables, reviewed drafts of the paper.

Ann M. Stevens conceived and designed the experiments, analyzed the data, contributed reagents/materials/analysis tools, wrote the paper, reviewed drafts of the paper.

Data Availability

The following information was supplied regarding data availability:

For accessing fastq read files (on the NCBI Sequence Read Archive (SRA) Database) and excel files (on NCBI Gene Expression Omnibus (GEO) Database), please use the accession numbers provided in the text. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?token=slefewsojdyrxwpacc=GSE87520.

Funding

This work was supported by the Life Sciences 1 Building Fund and Virginia Tech’s Open

Access Subvention Fund supported its publication. There was no additional external funding

received for this study. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

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Table 2.1. Genes from the RNA-Seq data comparing the in planta reads to the pre-inoculum in vitro liquid culture reads validated by qRT-PCRa.

DESeq DESeq Locus RPM Fold Fold padj Tag Gene Annotation Regulation Regulation CKS_3263 HrpA family pilus protein A 52.64 34.17 1.09E-85 CKS_3793 cytochrome d ubiquinol oxidase subunit I A 36.48 23.81 2.78E-59 CKS_4032 rmf ribosome modulation factor A 28.23 17.29 3.37E-21 CKS_1591 bfr bacterioferritin iron storage and detoxification protein A 27.19 17.89 1.27E-50 CKS_3570 AraC Family Transcriptional Regulator A 19.33 12.66 2.19E-33 CKS_4657 aceB malate synthase A A 15.20 9.76 2.40E-20 CKS_2714 yeaG serine-protein kinase A 8.22 5.66 1.38E-29 CKS_2505 AsnC family transcriptional regulator A 4.20 2.89 1.45E-09 HUD DNA-binding transcriptional regulator alpha CKS_0004 hupA subunit R 4.58 6.30 2.94E-30 CKS_4537 T3SS Effector protein R 18.27 23.86 8.75E-59 CKS_4346 recF gap repair protein control 1.29 0.90 5.99E-01 F1 sector of membrane-bound ATP synthase beta CKS_1206 atpD subunit control 1.14 0.62 2.51E-02 CKS_4345 gyrB DNA gyrase subunit B control 1.08 0.65 3.95E-02 aA = activated or R = repressed gene in planta

Table 2.2. Genes from the RNA-Seq data comparing the in planta reads to the in vitro plate culture reads validated by qRT-PCRa.

DESeq RPM Fold Fold DESeq Locus Tag Gene Annotation Regulation Regulation padj CKS_3263 HrpA family pilus protein A 58.52 41.81 3.36E-90 CKS_3570 AraC Family Transcriptional Regulator A 45.70 32.15 2.94E-52 CKS_3793 cytochrome d ubiquinol oxidase subunit I A 31.45 11.51 7.77E-05 CKS_4657 aceB malate synthase A A 15.65 11.35 1.23E-26 bacterioferritin iron storage and detoxification 14.97 CKS_1591 bfr protein A 10.99 1.79E-24 CKS_4032 rmf ribosome modulation factor A 3.70 b 2.84 5.81E-07 CKS_2714 yeaG serine-protein kinase A 3.16 b 2.42 2.80E-08 CKS_2505 AsnC family transcriptional regulator A 2.13 b 1.61 2.34E-02 HUD DNA-binding transcriptional regulator alpha CKS_0004 hupA subunit R 4.71 5.93 7.63E-19 CKS_4537 T3SS Effector protein R 36.62 44.52 1.97E-89 CKS_4346 recF gap repair protein control 1.07 0.82 2.77E-01 F1 sector of membrane-bound ATP synthase beta CKS_1206 atpD subunit control 1.73 1.34 1.74E-01 CKS_4345 gyrB DNA gyrase subunit B control 1.43 1.10 5.91E-01 aA= activated or R = repressed gene in planta culture. bGenes selected for in planta versus pre-inoculum liquid culture comparison (Table 2.1), but also included in this study.

Figure 2.1. Differential mRNA expression in planta. Whole transcriptome data (averaged normalized RPM) of the P. stewartii DC283 strain grown in planta versus the pre-inoculum in vitro liquid culture (A) or an in vitro plate culture (B). A gray filled circle is used to represent each gene. The green and red lines represent the four-fold expression ratio cutoff, where any points that fall outside of them are considered upregulated (green) or downregulated (red) in planta. Genes validated through qRT-PCR are represented as filled green (upregulated), red

(downregulated), or black (below the four-fold regulation parameter) circles.

Figure 2.2. Relative gene expression from the RNA-Seq and qRT-PCR data. Changes in expression of ten select genes were compared between the RNA-Seq RPM analysis (white) and qRT-PCR analysis (black). Results are shown for the in planta culture data and the pre-inoculum in vitro liquid culture data (A) or plate in vitro culture data (B). The fold activation (A1 and B1) or repression (A2 and B2) for the in planta data is represented on a logarithmic scale. RNA-Seq results are averages of two experimental samples and qRT-PCR data represent two experimental samples analyzed in triplicate. For both RNA-Seq and qRT-PCR, the error bars were estimated using the sample standard error of the fold-change across the two independent biological replicates. The recF gene was used as the reference for normalization of the qRT-PCR results.

Figure 2.3. Gene Ontology analysis groupings for the list of regulated genes. Groups created from genes differentially expressed through the RNA-Seq RPM data comparisons between the in planta and pre-inoculum in vitro liquid culture (A) or in vitro plate culture (B). Upregulated

(green) and downregulated (red) groups had a maximum p-value of 0.01 when using Fisher’s exact test in topGO.

CHAPTER THREE Elucidating the role of select transcription factors in

Pantoea stewartii subsp. stewartii survival during

xylem infection of corn

Holly Packard Bartholomew, Brandi J. Thomas1, Chase M. Mullins1, Chastyn Smith1, Guadalupe

Reynoso1, and Ann M. Stevens

1Alphabetical order by first name

Attributions

Holly Packard Bartholomew contributed to the experimentation and analysis for data in Figures

3.1, 3.2, 3.3, 3.4, 3.5, 3.6, 3.7, S3.1, S3.2, S3.3, S3.4 and Tables 3.1 and 3.2. Ann M. Stevens was the principle investigator and contributed to the experimentation presented in Figures 3.2,

3.3, S3.1, S3.2. Holly and Ann wrote the manuscript. Brandi J. Thomas, Chase M. Mullins,

Chastyn Smith, & Guadalupe Reynoso contributed to the experimentation presented in Figures

3.2, 3.3, S3.1, & S3.2, as well as strain construction in Table 3.1.

Abstract

The causal agent of Stewart’s wilt disease in corn, Pantoea stewartii subsp. stewartii, is a xylem-dwelling bacterial phytopathogen. A previous RNA-Seq study examined P. stewartii gene expression patterns during late-stage infection in the xylem, while a Tn-Seq study using a

P. stewartii mutant library revealed genes essential for colonization of the xylem. From these datasets, select P. stewartii transcription factors were chosen to further study their role in planta.

Among these are NsrR, IscR, Nac and Lrp, proteins that are hypothesized to be involved in regulating nitric oxide stress response, iron-sulfur cluster synthesis, nitrogen assimilation, and the leucine response, respectively. An additional three genes annotated as encoding transcription factors and a hypothetical protein, neither of which have been studied in other systems, were chosen to elucidate their function. Markerless gene deletion strains and the corresponding chromosomal complementation strains were constructed. Deletion and complementation strains were co-inoculated into corn plants to determine the ability of the mutant bacteria to survive in planta, and it was determined that IscR is important for P. stewartii colonization. Individual deletion strains were then used to infect corn seedlings to determine the roles of the deleted genes in virulence and the lrp deletion strain was found to cause significantly less disease. A qRT-PCR analysis was performed to screen for changes in gene expression in the P. stewartii wild type strain versus the mutant strains ∆nsrR and ∆iscR based on the hypothesized model of their regulons. NsrR represses hmp, encoding a flavohemoprotein, and activates lysP, the lysine- specific permease, while IscR represses cydA, a cytochrome c oxidase subunit. Capsule and motility in vitro assays suggest that Lrp may play a role in regulating these physiological outputs, pending additional strain analysis. Understanding the role of these transcription factors during

growth in the xylem will help to build a model of the regulatory network used by P. stewartii living in planta.

Introduction

The bacterial phytopathogen Pantoea stewartii subsp. stewartii causes Stewart’s wilt disease when it colonizes the leaves and xylem of corn. The corn flea beetle, Chaetocnema pulicaria, which is endemic to North America including the mid-Atlantic to Midwest regions of the United States (Pataky, 2004), serves as a vector for P. stewartii. The bacterium is enteric within the beetle, but it is transferred into the apoplast of the corn leaves during insect feeding.

Once inside the plant, the bacteria migrate to the xylem where they proliferate to form a dense biofilm, blocking water transport that leads to wilt during late-stage plant infection. Among the major virulence components of P. stewartii are the hrp-encoded type III secretion system and the effector WtsE important early during an infection, a cell wall degrading enzyme (CWDE) thought to be critical for dissemination of P. stewartii throughout the plant and in accessing plant nutrients, and the exopolysaccharide (EPS) produced by P. stewartii late in the infection that affords protection and enables biofilm formation in the xylem (Bradshaw-Rouse et al., 1981;

Coplin & Cook, 1990; Mohammadi, Burbank, & Roper, 2012b). Other known virulence factors include capsule pigment, surface motility and adhesins, siderophore production, an RTX toxin, oxidative stress regulation with OxyR and SoxR, outer membrane porins, and Lon protease

(Burbank, Mohammadi, & Roper, 2014; Burbank & Roper, 2014; Duong, Jensen, & Stevens,

2018; Kernell Burke et al., 2015; Mohammadi, Burbank, & Roper, 2012a; Roper et al., 2015).

Regulation of the bacterium’s transition from the apoplast to the xylem is in large part controlled by a quorum sensing (QS) system, where cell-cell signaling of high cell densities leads to a decrease in motility and an increase in capsule production (Koutsoudis et al., 2006).

Whereas regulation and transcriptional pathways within the model organism Escherichia coli has been heavily studied, less is known about other organisms and how their regulatory networks may vary from this system. In P. stewartii, regulation has been elucidated for the QS regulon (EsaR) and downstream regulators for capsule production (RcsA) and surface motility

(LrhA) (Duong & Stevens, 2017; Kernell Burke et al., 2015; Ramachandran et al., 2014).

Interestingly, the P. stewartii LrhA regulon was shown to be quite different from its homologue in E. coli, validating the importance of transcriptomic studies for non-model organisms (Kernell

Burke et al., 2015). Other previous studies in P. stewartii revealed regulation of the oxidative stress response through the transcription factors OxyR and SoxR (Burbank & Roper, 2014). To explore the regulation and requirements of P. stewartii in planta, an RNA-Seq study was used to compare the wild-type transcriptome to that of an in vitro culture (Packard et al., 2017). Genes essential for survival in planta were subsequently identified using a Tn-Seq approach (Duong,

Jensen, & Stevens, 2018).

Three P. stewartii genes, nsrR, iscR, and lrp, were chosen for further study primarily based on the Tn-Seq data, with in planta expression confirmed using RNA-Seq results. A fourth gene, nac, was chosen based on its upregulation in the transcriptome data and its potential connection to the other transcription factors as evidenced in the E. coli literature (Figure 3.1).

Finally, an additional four uncharacterized genes were chosen for further study based on the Tn-

Seq data, three were identified as transcriptional regulators and one as a hypothetical protein.

NsrR in E. coli is known to recognize nitric oxide (NO), a reactive nitrogen compound.

Utilized by both plants and bacteria, NO is a signalling molecule that controls a wide variety of physiological outputs. In plants, this includes responses to both biotic and abiotic stresses, as well as involvement in germination, root development, and bacterial symbiosis (Arasimowicz-

Jelonek & Floryszak-Wieczorek, 2014; Baudouin & Hancock, 2014; Bellin et al., 2013;

Delledonne et al., 1998; Mur et al., 2012; Romero-Puertes & Delledonne, 2003). During pathogen infiltration, plants use NO for the salicyclic acid (SA) and jasmonic acid (JA) hormone pathways, as well as induction of programmed cell death and the hypersensitive response (Mur et al., 2012). As NO is highly reactive and has a strong binding affinity toward many cellular compounds, a method of detoxification is critical for cellular function and homeostasis of plant- associated bacteria (Arasimowicz-Jelonek & Floryszak-Wieczorek, 2014). In addition to detoxification, there is evidence that bacteria also may sequester NO in order to interfere with the plant cell signaling as a means of combating the plant immune response.

Under NO stress in some enteric bacteria, such as E. coli, the transcriptional repressor

NsrR upon binding NO is released from the promoter regions of around 60 genes involved in detoxifying NO so that they can be transcribed (Filenko et al., 2007; Tucker, et al., 2010).

Among these genes are hmp, encoding a flavohemoprotein that has been shown to be involved in nitric oxide detoxification in multiple bacteria (Boccara, et al., 2005; Dalsing et al., 2015; Poole et al., 1996). Bioinformatics approaches have identified a conserved recognition motif for NsrR in both Gram-positive and Gram-negative bacteria, and microarray data has supported many of the predictions of putative binding sites in E. coli (Filenko et al, 2007; Partridge et al., 2009;

Rodionov et al., 2005). Among these targets are a number of genes also within the regulons of other global regulators of nitrogen and oxygen utilization genes (i.e., Fnr, NarP, and NarL;

Tucker et al., 2010). This suggests the importance of crosstalk between these regulators to closely coordinate expression of pathways that influence one another in E. coli. Structural data is conflicting but does imply that there may be multiple conformations of NsrR, specifically an

apo form, a [2Fe-2S] form, and a [4Fe-4S] form, and that each one could have different promoter sequence targets (Tucker et al., 2010).

IscR is a transcription repressor involved in iron metabolism and oxidative stress response in many bacteria, including E. coli (Runyen-Janecky, et al., 2008). Like NsrR, it is a

Rrf2-type transcriptional regulator and has been shown in vitro to bind NO, although it is suspected to bind at non-physiologically relevant concentrations (Pullan et al., 2007, Tucker et al., 2010). IscR in E. coli functions both without an iron sulfur cluster (apo-IscR) or with the addition of a [2Fe-2S] cluster (holo-IscR). Both forms of the protein are required under normal cellular conditions to balance the Fe-S cluster abundance in the bacterium. Holo-IscR can tightly bind the isc promoter as an autoregulatory repressor. However, under iron-limited conditions or in cases of oxidative stress, the apo-IscR will activate a second Fe-S biosynthesis pathway, encoded by the suf operon (Mettert & Kiley, 2014; Santos et al., 2015). Depending on the conformation, IscR has two different promoter binding sites in E. coli (Nesbit et al., 2009). The gene encoding IscR is required for virulence in several biofilm-producing organisms, including

Klebsiella pneumoniae and the plant pathogen Xanthomonas oryzae (Fuangthong, et al., 2015;

Wu et al., 2014). Additionally, the type III secrection system (T3SS) in Yersinia pseudotuberculosis has been shown to be influenced by IscR (Miller et al., 2014).

The Lrp transcriptional regulator is a global regulator originally named due to the role it plays in the leucine response of E. coli (Brinkman et al., 2003). However, recent studies have shown that Lrp may actually regulate almost half of all genes within E. coli either directly or indirectly under a variety of conditions, including numerous instances of leucine-independent

Lrp binding (Kroner, Wolfe, & Freddolino, 2018; Shimada et al., 2015). Among the identified direct targets are Nac (nitrogen assimilation control), LrhA (motility), SoxS (superoxide stress),

and ArgR (arginine biosynthesis), suggesting ties to a wide variety of physiological responses within the bacteria involved in stress, navigation, and metabolism.

The gene nac encodes a transcription factor for nitrogen assimilation in E. coli (Muse &

Bender, 1998). Previously, Nac has been shown to act as a repressor for the glutamate synthase operon. In addition, it has been shown to coordinate regulation with nitrogen regulatory protein

C, NtrC, for numerous transporters under nitrogen-limited conditions, enabling import of nitrogen-containing compounds (Zimmer et al., 2000). Connections to the asparagine biosynthesis pathway was also determined for E. coli (Poggio et al., 2002).

In this study, a reverse genetics approach was employed, using strains with in-frame chromosomal deletions in the genes encoding the seven transcription factors (NsrR, IscR, Nac,

Lrp, DSJ_00125, DSJ_03645, and DSJ_18135) and the one hypothetical protein (DSJ_21690). It was hypothesized that the genes selected impact the ability of P. stewartii to infect and survive within the corn host environment. The mutant strains and their corresponding complementation strains were tested through both in planta and in vitro assays to understand the role of these gene products during the bacterial life cycle in planta. Using the extensive literature available about the NsrR and IscR regulons in E. coli, we predicted the potential for similarities between the regulatory network of the two enteric bacteria (Figure 3.1), and explored this via in planta-based qRT-PCR transcriptional experiments.

Methods

Strains and Growth Conditions

E. coli and P. stewartii strains were grown at 37°C and 30°C, respectively, in LB (10 g/L tryptone, 5 g/L NaCl, 5 g/L yeast extract) broth or 1.5% agar plates. The growth medium was 66

supplemented with the appropriate antibiotics for each strain (see Table 3.1): ampicillin (Amp;

100 µg/mL), chloramphenicol (Cm; 35 µg/mL), gentamycin (Gm; 10 µg/mL), nalidixic acid

(Nal; 30 µg/mL), kanamycin (Kan; 50 µg/mL), and streptomycin (Str; 100 µg/mL).

Diaminopimelic acid (DAP) was supplemented in the growth medium for the E. coli RHO5 strain (200 µg/mL for broth and 400 µg/mL for agar plates).

Gene Selection Criterion

Eight genes were chosen for mutant strain construction, seven annotated as transcription factors and one hypothetical protein. Two annotated transcription factors, nsrR and iscR, were selected based upon being at least 10-fold reduced in the in planta sequencing reads from the Tn-

Seq study (Duong, Jensen, & Stevens, 2018), and for the network cross-talk seen between them in E. coli as described above. These results suggest these genes are important for bacterial fitness while inside of their plant host. The genes lrp and nac, although having missed the 10- fold reduced in planta read count in one of the biological replicates from the study, still showed lower reads in planta and were chosen based upon their connection to the nsrR and iscR regulons in E. coli (Figure 3.1). Each of the three uncharacterized transcription factors, as well as the hypothetical protein, showed a minimum 10-fold reduction from the Tn-Seq study as well.

Finally, all genes were confirmed to have transcript reads from a previous RNA-Seq study to ensure they were being actively transcribed in planta for WT P. stewartii (Packard et al., 2017).

Eighteen genes for qRT-PCR were selected based upon their homologues in E. coli, and how those genes could be functionally connected (Table 3.2). First, genes were selected using

BioCyc v.24 online software if they appeared to belong to the nsrR or iscR transcriptional networks, via either a direct or indirect link (e.g., nsrR, iscR, iscS, sufA, sufE, nrdA, nfuA, erpA,

hmp, lrp; Karp et al., 2019). Due to the previous work performed in P. stewartii with the QS regulon, including downstream regulons for RcsA and LrhA, additional genes from those studies

(e.g., esaR, lrhA, rcsA, lysP, osmY, cydA, argC) were selected to see if any connections could be confirmed between the different regulons, thereby broadening the understanding of the overall cellular regulatory network. Finally, another gene, bfr, associated with iron storage and previously utilized for qRT-PCR in P. stewartii was selected (Packard et al., 2015). Many of the selected qRT-PCR targets also had an upregulation in the WT P. stewartii from the RNA-Seq study (Packard et al., 2017), or were reduced in survival capabilities from the Tn-Seq study when mutated (Duong, Jensen, Stevens, 2018).

Deletion and Complementation Strain Construction

Two procedures were used for deletion construction, both of which have been described previously (Kernell Burke et al., 2015; Stice et al., 2020). Briefly, the genes nsrR, iscR, nac,

DSJ_03645 (03645), and DSJ_18135 (18135) underwent a markerless deletion construction using the Gateway plasmid transfer system (Life Technologies) with primers (Table 3.2), plasmids, and strains (Table 3.1) as previously described (Kernell Burke et al., 2015). The genes lrp, DSJ_00125 (00125), and DSJ_21690 (21690) underwent a deletion strategy from methods described by Stice et al., 2020 that was modified as described below. Overlap extension PCR products with attB sites for the up- and downstream regions of the genes of interest were added to the BP Clonase II Reaction directly with the suicide vector pR6KT2G. Overnight room temperature BP reactions were transformed into Eco MaH1 pir+ via calcium chloride transformation and LB Gm10 plates (1.5% agar) then colonies patched onto Gm10 and Cm35 plates. Patches with exclusive growth on Gm10 plates were grown overnight in liquid medium,

then plasmid constructs were extracted with a QIAprep spin Miniprep kit (Qiagen), digested via

XhoI to screen for the expected insertion size, and sent for Sanger sequencing (Fralin Life

Sciences Institute; FLSI). Each plasmid was then transformed into the conjugation strain E. coli

RHO5 on DAP Gm10 plates, PCR was used to screen for the expected insert size, and the plasmid was conjugated into DC283 via a 5 µL spot onto LB DAP. After incubating 24 hr at

30°C lid-up, each spot was resuspended in 1 mL LB medium, and spread 1X and 10X onto LB

Gm10 Nal30 plates. After 48 hrs at 30°C, colonies were patched onto LB Gm10 Nal30 for another

48 hrs at 30°C. Patches were grown overnight at 30°C in 3 parts 1M sucrose with 1 part LB,

-4 -6 30 subcultured to 0.05 OD600 and grown until OD600 0.5, plated at 10 -10 onto LB Nal and incubated 48 hrs for 30°C. Colonies were patched onto LB Gm10 Nal30 and LB Nal30 for 24 hrs at

30°C. Those that grew exclusively on LB Nal30 were screened via PCR to determine successful recombination, and amplified fragments of the expected size were sequenced for confirmation

(FLSI).

Complementation strain construction was performed as described previously (Choi et al.,

2005; Kernell Burke et al., 2015). The coding sequence and upstream region to encompass the promoter were inserted into a neutral region downstream of the gene glmS in the P. stewartii chromosome using the vector system pUC18R6K-mini-Tn7-cat with appropriate primers (Table

3.2).

Xylem Virulence Assay

Sweet corn seeds (Zea mays cv. Jubilee; 2B Seeds) were planted (day 0) in Promix B soil

(Premier Tech Horticulture, Rivière-du-Loup, Canada) and grown in a 30°C chamber (Conviron

CMP4030) with 16 hr light 8 hr dark cycles, ~200 µE m-2 s-1 light intensity. On day 5 of growth,

plants were inoculated with P. stewartii wild type (WT), deletion strain (∆), corresponding complementation strain (∆/+), or phosphate-buffered saline (PBS; 137 mM NaCl, 2.7 mM KCl,

10 mM Na2HPO4, and 2 mM KH2PO4, pH 7.4). As previously described (Kernell Burke et al.,

2015), bacterial strains were grown overnight at 30°C, then subcultured to an optical density at

600 nm (OD600) of 0.05 and grown until OD600 0.2, when they were washed with 1 mL of PBS twice at 2 min 10,000 rpm (rotor 5424R) before resuspension in 1 mL PBS. Fifteen plants per inoculum were surface disinfected with 70% ethanol (EtOH), scratched with a syringe needle on the stem above the soil line (1 cm), and 5 µL of washed cells were inoculated into the scratch.

Virulence was measured on a 0-5 scale after 10 days post-inoculation, with 0 = no symptoms, 1

= water-soaking lesions on one leaf, 2 = lesions on two or more leaves, 3 = wilting of one leaf, 4

= wilting of multiple leaves, and 5 = death of the seedling with no symptom-free leaves. A

Student’s t-test (p-value ≤ 0.01) was performed comparing the disease scores of the WT inoculated plants to the other strains to determine statistical significance.

Competition Assay

A modified protocol for a previously described competition assay was performed to find relative competition indices (RCI) via counting patched colonies instead of the previously used spread plate colony counting (Duong, Jensen, & Stevens, 2018). Plants were grown and bacterial cultures processed on day 5 as described in the virulence assay protocol. After resuspension of the washed cells in 1 mL of PBS, the deletion strain (NalR) was mixed with the corresponding complementation strain (NalRCmR) in a 1:1 ratio and used as the inoculum for six plants. The initial inoculum was serially diluted, spread plated on LB Nal30, and 100 colonies were replica patched onto Nal30 Cm35 then LB Nal30 to enumerate the complementation and deletion strains, respectively. Five days after inoculation, the stems were surface disinfected with 70

70% EtOH and sliced with a sterilized razor blade at the base of the stem and where the leaves emerge. The harvested stem was sliced into ~ 1 mm segments and shaken at 30°C for 1 hr in 10 mL of PBS. Each sample was serially diluted and spread on LB Nal30 agar plates, and 100 colonies patched from these onto Nal30 Cm35 then LB Nal30 as with the initial inoculum to enumerate the ratio of complementation and deletion strains that survived in planta. Both the initial inoculum and final harvested bacterial ratios were used to find the RCI as follows: RCI =

[deletion patches/complementation patchesoutput]/[deletion patches/complementation patchesinput].

RNA Extraction

Plants were inoculated as described above for the virulence assay, and in planta cell cultures were harvested on day 5 post inoculation as follows. Stems were surface disinfected with 70% EtOH and cut at the base and at the top before leaf formation. Each stem was placed in 1 mL of RNA Protect bacterial reagent, and the reagent pipetted to wash through the stalk to remove the bacteria. After a brief vortex, the cells incubated for 5 min at room temperature, then were centrifuged for 10,000 rpm for 1 min with cells from three stems combined to create one sample for further processing. Supernatant was removed before storing the pellet in -20°C. RNA extraction was performed using a modified protocol for the Qiagen miRNeasy Mini kit (Qiagen,

Germantown, MD) as previously described (Packard et al., 2017; Ramachandran et al., 2014).

RNA was stored at -80°C. Samples were sent to FLSI for quality analysis with the Agilent

Bioanalyzer, and samples with an RNA Integrity Number (RIN) of greater than 7 were converted to cDNA using the ABI High Capacity cDNA Reverse Transcription kit (Thermofisher

Scientific, Waltham, MA). All cDNA samples were stored at -20°C.

Quantitative Reverse-Transcriptase Polymerase Chain Reaction

(qRT-PCR)

Primers for the selected genes analyzed by qRT-PCR and for control template construction into pGEM-T (Promega) were designed using the P. stewartii DC283 reference sequence NZ_CP017581 on the National Center for Biotechnology Information (NCBI) site

(Table 3.2). IDT Oligo Analyzer online software (Integrated DNA Technologies) was used to determine the quality and annealing temperature of the chosen primers. Primers for qRT-PCR were designed to amplify ~100 bp fragments from the coding sequences of each gene chosen.

Each were optimized using the constructed plasmid templates containing the coding regions of each gene as a template. SYBR Green Master Mix (Applied Biosystems) was used per the manufacturer’s protocols with plasmid template diluted 1:10 from 0.1 ng to 0.0001 ng. Standard curve experiments were performed for primer optimization using the Applied Biosystems

StepOnePlus RT-PCR system until an efficiency range of 90-110% was achieved. Comparative

Ct experiments were performed with cDNA at a final concentration of 3.2 ng/µL. Ct values were exported into Microsoft Excel for fold change calculations using the Pfaffl method with an assumed 100% efficiency comparing the wild-type transcripts to the deletion and complementation strain transcripts (Pfaffl, 2001). Three biological replicates of each strain were analyzed with triplicate wells each, and the atpD housekeeping gene was chosen as the internal reference gene (Packard et al., 2017).

Capsule Production Phenotypic Assay

The ability of the strains to produce capsule was tested in duplicate as previously described (Kernell Burke et al., 2015). Briefly, strains were grown overnight in the appropriate

medium, subcultured to an OD600 of 0.05, and grown until they reached an OD600 of 0.2. A 2-cm cross streak of each strain was grown on CPG agar plates (0.1% casamino acids, 1% peptone,

1% glucose, 1.5% agar) and incubated at 30°C. After 48 hr of growth, strains were assessed qualitatively for capsule production levels and photographed with a Bio-Rad Gel Doc imager.

Surface Motility Phenotypic Assay

Each strain was tested in duplicate for surface motility capabilities as described by

Kernell Burke et al., 2015. Strains were grown overnight and used to inoculate fresh medium at an OD600 of 0.05. Each strain was grown to an OD600 of 0.5, then 5 µL of each strain was spotted onto LB quad-plates with 0.4% agar and supplemented with 0.4% glucose. Plates were incubated for 30 min at room temperature, then stored lid-up in a container with a lid during incubation at 30°C. Plates were photographed with a Bio-Rad Gel Doc imager 48 hours after inoculation to qualitatively assess motility capabilities. Results

The transcription factor IscR plays a role in P. stewartii colonization of corn

To assess the ability of each gene deletion strain to colonize the plant and to validate the original Tn-Seq study findings (Duong, Jensen, & Stevens, 2018), competition assays were performed. Each deletion mutant strain (NalR) was co-inoculated in a 1:1 ratio with the corresponding complementation strain (NalR/CmR), to serve functionally as the wild type strain but with a selectable antibiotic resistance gene and eliminating possible impacts from secondary site mutations. RCI were calculated for each pairing (Figure 3.2, Figure S3.1). A competition assay with ompC was used as a positive control due to the previously published finding that there 73

was a colonization requirement of that gene in planta (Duong, Jensen, & Stevens, 2018), and results showed an average RCI of 0.02, confirming that previous work. For the nsrR, nac, and lrp strain sets, each had an RCI close to 1 (Figure 3.2), suggesting no defect in colonization capabilities with these mutants. Similarly, DSJ_00125, DSJ_03645, DSJ_18135, and the hypothetical DSJ_21690 had RCI close to 1, also indicating no obvious colonization defect

(Figure S3.1). However, the iscR mutant set had an RCI of 0.3, showing a partial reduction in colonization capabilities of the deletion strain (Figure 3.2). This suggests that IscR contributes to the ability of P. stewartii to grow in planta.

The transcription factor Lrp impacts P. stewartii disease severity

The WT strain of P. stewartii was compared to each deletion and corresponding complement strain set in the ability to cause disease (Figure 3.3, Figure S3.2). Ten days post- inoculation, plants were scored from 0-5 on symptoms, with the WT strain producing an average score of 3.7. The negative control, PBS, showed an average virulence score of 0, while the positive control ∆rcsA, with an anticipated reduction in virulence (Kernell Burke, et al., 2015), had an average score of 0.64. The ∆nsrR, ∆iscR, and ∆nac strains were not statistically different than the WT strain with average virulence scores of 4.2, 4.0 and 3.7, respectively. The ∆lrp showed a partial reduction in average disease score at 2.9 that was statistically significantly lower compared to the WT strain (p ≤ 0.01). All complement strains had no statistical difference to the wild-type levels of disease symptoms. Deletion strains of the three transcription factors of unknown function and the hypothetical protein had no significant impact on P. stewartii virulence (Figure S3.2).

qRT-PCR reveals potential genes regulated by P. stewartii IscR and

NsrR

Since the first phenotypic effect associated with the known transcription factors was attributed to IscR, and due to the overlapping regulatory patterns between IscR and NsrR in E. coli, the decision was made to pursue a preliminary qRT-PCR analysis of the regulation patterns of select target genes for just these two transcription factors. Eighteen genes were chosen for qRT-PCR analysis based upon the annotated function of each in relation to the putative transcription factor regulon, both direct and indirect hypothesized target genes, and also genes available from previous studies that could have functional relatedness (Figure 3.1). In addition, a constitutive reference gene, atpD identified in a previous study (Packard et al., 2017) was included as an internal control. A two-fold differential expression level between the deletion and

WT strains was chosen as the cut-off value to identify the most highly regulated genes as previously reported (Ramachandran et al; 2014). The gene cydA (previously CKS_3793) had differential expression at levels 2.8-fold higher in the ∆iscR strain versus the WT strain (Figure

3.4). This suggests IscR may regulate this gene through repression under the in planta conditions tested here. Similarly, for the ∆nsrR strain transcripts compared to the WT strain, the gene hmp was 2.3-fold upregulated in the deletion strain, suggesting that NsrR serves as a repressor for hmp. Finally, the gene lysP was downregulated 2.4-fold in the ∆nsrR strain (Figure

3.4). To provide additional visual analysis of the data, expression levels of cydA, hmp, and lysP were graphed to compare WT levels to the mutant strains using the exact efficiencies obtained via primer optimization, and these trends were confirmed (Figure S3.3). Taken together, these results suggest both IscR and NsrR function as transcriptional regulators in planta, however these findings should be repeated for confirmation. Interestingly, no evidence for regulation was 75

seen for the other chosen genes (Figure 3.4), suggesting their expression was not impacted by the absence of iscR or nsrR.

Lrp is involved in both capsule production and surface motility of P. stewartii

Capsule production was tested for each of the P. stewartii deletion and complement strains in comparison to the WT strain and the ∆rcsA strain, which is known to have an obvious reduction in capsule producing capabilities (Duong & Stevens, 2017). For ∆nsrR, ∆iscR, and

∆nac, as well as the four unnamed gene deletion strains, there was no perceived phenotypic difference compared to the WT strain in capsule production (Figure 3.5, Figure S3.4). Of all the strains tested, the lrp deletion strain clearly mimicked the ∆rcsA strain in capsule-reduced phenotype (Figure 3.5). However, the complementation strain was unable to produce wild-type levels of capsule.

For the motility assays, the WT strain behaved as previously described, with either a unidirectional outward expansion or a symmetrical expansion from the point of inoculation

(Herrera et al., 2008; Kernell Burke et al., 2015). These plates were also inoculated with ∆lrhA, which has been shown to have a reduction in motility in P. stewartii (Kernell Burke et al., 2015).

The ∆lrp strain showed a mutant phenotype like that of ∆lrhA, as it was unable to migrate on the plate surface like the WT strain (Figure 3.5). Surprisingly, the ∆lrp/lrp+ was again unable to complement the phenotype. Besides the lrp strains, all other mutant strains tested had qualitative motility phenotypes that appeared to match the WT strain (Figure 3.6, Figure S3.5)

Discussion

A previous Tn-Seq study identified 486 genes that were essential for in planta survival of

P. stewartii and 27 of these genes were annotated transcription factors (Duong, Jensen, &

Stevens, 2018). In this study, genes encoding four transcription factors, three putative transcription factors, and one hypothetical protein were further investigated based on the Tn-Seq results and in conjunction with their demonstrated transcription in planta from a previous RNA-

Seq study (Packard et al., 2017), A combination of in planta and in vitro techniques were used in an effort to reveal additional components of the regulatory network used by P. stewartii in planta.

Competition assays were performed to confirm the initial findings from the Tn-Seq study, that the genes selected for analysis here were essential for in planta survival. Unfortunately, many of the mutant strains with in-frame deletions in the transcription factor genes did not show a reduction in the ability to colonize as hypothesized. However, there are a few potential explanations for the lack of a readily perceptible phenotype. It is possible the community structure impacted the results, since the 1:1 deletion to complement ratio with monocultures versus a ~1:4000 ratio of each mutant within the total Tn-Seq library pool may have resulted in competitive differences impacting the survival capabilities of the mutants. Additionally, the transposon insertions were large and disruptive, so it is possible there was a polar effect that was removed when the in-frame markerless deletion constructions were remade in this study. Based upon the E. coli literature, it appears nsrR and iscR could be in operons. It is possible small RNA genes in these regions could have been disrupted, however identification of these has not been investigated. Redundancy in the bacterial networks producing compensatory cross-talk could have masked the impact of individual transcription factor gene deletions on the bacterial fitness. 77

It should be noted, however, that the growth rates in vitro were not impacted by the deletion nor complementation manipulations in each strain compared to the WT strain (data not shown). For nac, this gene was not chosen based upon the Tn-Seq data, but rather an upregulation in planta from a previous RNA-Seq study, so lack of a survival phenotype was not unexpected. Finally, a lack of precise understanding about the temporal nature of gene regulation might have also impacted interpretation of the results across different studies (i.e., Tn-Seq versus competition assays).

In the case of the ∆iscR mutant, there was a noticeable reduction in its ability to colonize the host compared to the complementation strain. Additionally, the gene from our preliminary qRT-PCR experiment that appears to be repressed by IscR under in planta conditions, cydA, is annotated as a cytochrome d ubiquinol subunit. Expression of cydA was upregulated 36-fold in planta compared to in vitro cultures during late stage infection (Packard et al., 2017), which could be due to the microaerophilic environment of the xylem. IscR appears to repress expression of this gene, which may be important temporally as the bacterium is adapting to changing environmental conditions. The loss of the normal regulatory pattern of cydA may contribute to the inability of the ∆iscR strain to survive and colonize at wild-type levels in planta. Based upon what is known about the regulation of cydA in E. coli, direct regulation by

IscR seemed unlikely. The binding sites (type 1 and type 2) for the E. coli IscR were also not found upstream of cydA in P. stewartii (Nesbit et al., 2009). However, to confirm regulation of cydA by IscR, and to determine direct or indirect regulation, further experiments outside the scope of this study would need to be performed.

In K. pneumoniae IscR was shown to be involved in both capsule biosynthesis as well as iron acquisition (Wu et al., 2014). Previous studies in P. stewartii have shown that iron 78

acquisition influences motility of the organism, and loss of siderophore production (i.e., the iucA operon) reduces bacterial virulence in planta (Burbank, Mohammadi, & Roper, 2014). Recent work has also revealed a reduction in iron availability within the xylem sap during in planta colonization of P. stewartii, hypothesized as a plant defense response to the infection (Doblas-

Ibañez et al., 2019). Although a virulence phenotype was not evident in this study for ∆iscR, perhaps ties to the iron acquisition system in the reduced iron environment contributed to the reduction in colonization capabilities for ∆iscR. To determine the reason behind the observed phenotypes, and to understand the potential crosstalk with the other transcription factor networks such as for NsrR a complete RNA-Seq transcriptome-level exploration of the IscR regulon is warranted.

Despite no significant phenotypes for the ∆nsrR strain in the virulence or competition assays, expression level changes were seen for the gene hmp through the preliminary qRT-PCR experiment. In many systems, hmp encodes a flavohemoprotein, specifically nitric oxide dioxygenase. This is responsible for the detoxification of nitric oxide through conversion to nitrate, and has been seen to be repressed by NsrR in other bacteria like E. coli (Bodenmiller &

Spiro, 2006). Based upon our findings here, it appears NsrR also acts as a repressor for this hmp, supporting the hypothesized connection in our model (Fig 3.7). Additionally, the binding site for the E. coli NsrR was found upstream of hmp in P. stewartii, further supporting the possibility of direct regulation (Partridge et al., 2009). However, experimental validation of direct control needs to be completed. Since the influx of nitric oxide most likely occurred within the plant during infection, and this environment requires hmp for the bacterial survival, it could suggest a reason for not having a visible phenotype for neither the competition nor virulence assays, since

hmp is upregulated in the ∆nsrR strain. Overexpression of NsrR might produce a stronger phenotypic output than gene deletion.

Another gene found to be regulated more than two-fold by NsrR from the initial qRT-

PCR analysis is lysP. In this case, NsrR appears to act as an activator. In E. coli, LysP is a lysine-specific permease, enabling lysine to be transported across the cytoplasmic membrane

(Steffes et al., 1992). It has been shown that Lrp is a regulator for transcription of genes associated with lysine-limited conditions (Ruiz, Haneburger, & Jung, 2011). Therefore, although

NsrR was not found to regulate lrp in the current study, there appears to be a potential for downstream interconnected regulons for these two transcription factors. Additionally, lysP was found previously to be regulated in P. stewartii indirectly by the QS regulator EsaR using both

RNA-Seq and qRT-PCR methods (Ramachandran et al., 2014). However, the identified binding site for NsrR in E. coli was not found upstream of the lysP start site, suggesting regulation may be indirect (Partridge et al., 2009).

It has already been shown that the E. coli model system does not always align with what is seen in P. stewartii regarding regulatory networks. In E. coli, the transcription factor LrhA regulates flagellar synthesis, whereas in P. stewartii it does not (Duong & Stevens, 2017; Kernell

Burke et al., 2015; Lehnen et al., 2002). Therefore, although it was initially hypothesized that the annotated P. stewartii transcription factor homologues would have similarities in their regulon with that of the E. coli system, it was not unexpected that variation was seen between the two systems. For example, lrp did not have a large change in gene expression in the ∆nsrR mutant, despite this occurring in E. coli. This may mean there is no regulatory link between these two transcription factors in P. stewartii. Alternatively, transcription factors are often very tightly regulated due to the large influence they have on cellular function. It is possible the

phenotype was muted due to the regulation of lrp by other regulatory factors in the network. To understand if these two transcription factors are within the same regulatory network, one approach would be to perform an RNA-Seq experiment to determine the regulons of NsrR and

Lrp. Although we did not see evidence of lrp regulation by nsrR from the qRT-PCR, this experiment could validate that finding. More importantly, it could reveal downstream coordinated cross-talk between these two regulons, beyond what was found with lysP, through the limited qRT-PCR study.

For many of the genes in the qRT-PCR experiments, it was seen for both the nsrR and iscR strain sets that the complementation strain transcript levels did not always match that of the

WT. Complementation strain construction was performed by replacing the gene and an upstream region into the chromosome at a silent site downstream of glmS (Choi et al., 2005). However, there is a possibility that the cloned upstream promoter region in the complementation construct does not encompass all of the regulatory binding sites needed for appropriate gene control. For the nsrR transcript in the ∆nsrR/nsrR+ strain, there was a 2-fold increase in transcript that would support this theory. Although iscR expression in the ∆iscR/iscR+ strain did not reach a 2-fold threshold of differential expression, there was an increased trend at 1.4-fold higher than the WT.

Even small changes in the levels of the transcription factor have the potential to impact expression patterns of the downstream regulon such that they would be altered in comparison to the WT.

The ∆lrp mutant revealed a reduction in virulence of P. stewartii in planta and in both capsule production and motility in vitro. From previous studies in P. stewartii (Koutsoudis et al.,

2006; Minogue et al., 2005; Ramachandran et al., 2013; von Bodman, Majerczak , & Coplin,

1998), capsule and motility regulation are linked through the QS regulator EsaR and the

downstream regulators RcsA and LrhA, both of which are important for virulence. Additionally,

Lrp in E. coli has been shown to regulate lrhA (Kroner, Wolfe, & Freddolino, 2018; Shimada et al., 2015). Taken together, it seems lrp is required for virulence and may influence it through connections with capsule and motility. In addition, Lrp in E. coli also has connections to oxidative stress via regulation of soxS, and SoxRS regulation is also required for virulence in P. stewartii (Burbank & Roper, 2014; Kroner, Wolfe, & Freddolino, 2018). Therefore, future work understanding the Lrp regulon would be important to elucidating its role in P. stewartii during in planta infection. However, these potentially exciting findings are tempered by the inability of the lrp deletion strain to be complemented in two of three assays utilized. While the complementation strain appeared to restore statistically similar levels of virulence to the WT, for the qualitative capsule and motility assays, there seemed to be no recovery of the wild-type phenotype. As discussed above for the nsrR and iscR complementation strains, it may be altered regulation of the complemented gene that is an issue. Alternatively, there may be another genetic change at a secondary site(s) within the chromosome that is causing this phenotype. A previous study in P. stewartii showed there was chromosomal instability in a 66-kb region for a constructed complement strain; many transposon repeats are present within the genome that may result in these alterations (Duong, Stevens, & Jensen, 2017; Duong & Stevens 2017). Although this specific region was screened via PCR for each of the mutant strains and their complementation strains (data not shown), the additional transposon repeats within the genome may still provide potential for chromosomal variation. To determine the exact reason for the deletion phenotype and/or lack of complementation, additional experimentation will be necessary.

From the phenotypic findings of this study, the predicted in planta regulatory model for

P. stewartii has been updated (Figure 3.7). In addition to the connections found using the qRT-

PCR results, the network has been expanded to include hypothesized connections to the QS regulon. Previous work has shown a transcriptional regulation via RNA-Seq for EsaR and the gene sufE, however this result was never validated through qRT-PCR (Ramachandran et al.,

2014). Additional confirmation of EsaR regulating ompR could connect to a previously obtained phenotype for ompC (Duong, Jensen, & Stevens, 2018). It would be interesting to see how the regulon of the QS system interacts with the regulon of Lrp, as there are numerous predicted links suggesting cross-talk between these systems, including lysP, which appears to be regulated by

NsrR. Further, the preliminary phenotypic evidence from this study showed regulation of both motility and capsule by Lrp, which are also regulated by QS in P. stewartii.

An observation to note from this study is the potential for temporal gene regulation that could change phenotypic outputs. Although regulation by IscR or NsrR was not seen for many of the genes selected for the qRT-PCR study, it is still possible regulation could be found at a different point of the infection process. For all of the in planta assays performed in this study, the inoculation method does not mimic the very initial stages of infection within the apoplast.

Instead, inoculations are made directly into the stem of the plant. Thus, the use of alternative infection approaches, such as apoplast inoculations (Asselin et al., 2015), and temporal sampling could further elucidate the roles of these transcription factors throughout the P. stewartii lifestyle.

In conclusion, this study produced limited success in demonstrating that individual transcription factors play a role in the in planta survival of P. stewartii, especially with regard to nac and the transcription factors of unknown function. Therefore, their role in P. stewartii

physiology remains elusive. However, interesting phenotypes were found for a few of the transcription factors of predicted function (i.e., IscR, NsrR and Lrp) suggesting links to growth and virulence including capsule production and motility. This knowledge has permitted us to expand our knowledge of the regulatory network utilized by P. stewartii in planta. Acknowledgements

Special thanks to Dr. Brian Kvitko and Shaun P. Stice at the University of Georgia for sharing strains and protocols for deletion mutant construction. This work was supported by the Virginia

Tech Graduate Research Development Program (HPB), a Virginia Tech Graduate Student

Doctoral Assistantship (HPB), the Virginia Tech Biological Sciences Dean’s Discovery Fund, the Interdisciplinary Graduate Education Program funding through the Translational Plant

Sciences group, and Department of Biological Sciences (AMS). We would like to acknowledge

Ian Hines and Madigan Hawkins for their assistance with the competition assay patching protocols.

References

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Figure 3.1. Proposed regulatory targets of P. stewartii IscR and NsrR, key regulators in Fe-

S cluster formation based on the Escherichia coli model (Karp et al., 2019). Gene targets studied through qRT-PCR are displayed in black; other genes within the model are displayed in gray. Gene regulation is indicated by dashed lines for indirect or unknown regulation, solid lines for direct regulation, arrows for activation, and T-bars for repression.

0.1

0.01 Relative Competition Index Index (RCI) Competition Relative

0.001 ompC nsrR iscR lrp nac

Figure 3.2. Competition assay for P. stewartii mutant strains lacking select transcription regulators. Deletion (NalR) and complementation (NalR/CmR) strain sets of nsrR, iscR, lrp, and nac mutants, and the ompC positive control, were co-inoculated into the corn seedlings at a 1:1 ratio. The relative competition index (RCI) for each set was calculated as the ratio of deletion to complementation strains extracted five days post-inoculation over the ratio of deletion to complementation strains in the inoculum. N ≥ 6 per inoculum.

5 4.5 4 3.5 * 3 2.5 2

Disease Disease Score 1.5 1 * 0.5 * 0

Figure 3.3. Virulence of P. stewartii nsrR, iscR, lrp, and nac mutant and complementation strains. Average disease score for the following P. stewartii strains: wild type (WT; white),

∆rcsA as a positive control (gray), ∆nsrR, ∆nsrR/nsrR+ (orange), ∆iscR, ∆iscR/iscR+ (blue), ∆lrp,

+ + ∆lrp/lrp (green), ∆nac, and ∆nac/nac (yellow). PBS was used as a negative control. Scores were collected ten days post-inoculation from a minimum of 15 plants. An asterisk (*) represents a significant difference from the wild-type strain (p ≤ 0.01) using the Student’s T-

Test. Error bars were calculated using the standard error for each set.

A 10.00

1.00 Fold Regulation Fold

0.10

B 10.00

1.00 Fold Regulation Fold

0.10

Figure 3.4. Relative gene expression of select targets for IscR and NsrR regulation.

Transcripts from in planta grown WT P. stewartii were compared using qRT-PCR to in planta grown A) ∆iscR and B) ∆nsrR and strain transcripts. Fold derepression (> 1) or deactivation (<

1) for the deletion strain is represented on a logarithmic scale. Results are averaged from three experimental samples per strain analyzed in triplicate, and were normalized using the reference gene atpD. Error bars are represented as estimates of the sample standard error of the fold- change across the three biological replicates.

Figure 3.5. Capsule production by P. stewartii nsrR, iscR, nac, and lrp mutant and complementation strains. All photographs were taken at the same magnification after a 48 hr incubation in 30°C on CPG agar.

Figure 3.6. Surface motility of P. stewartii nsrR, iscR, nac, and lrp mutant and complementation strains. All photographs were taken at the same magnification after a 48 hr incubation in 30°C on LB medium (0.4% agar, 0.4% glucose).

Figure 3.7. Expanded predicted in planta regulatory network of P. stewartii. Gene regulation is indicated by dashed lines for indirect or unknown regulation, solid lines for direct regulation, arrows for activation, and T-bars for repression. Blue lines indicate predicted regulation based on previous E. coli studies (Karp et al., 2019), while red indicate known connections from P. stewartii studies (this study; Ramachandran et al., 2014).

Table 3.1. Strains used in this study

Strains Genotype and notes* References Pantoea stewartii strains (Dolph et al., DC283 Wild-type strain; Nalr 1988) Unmarked deletion of rcsA coding sequence from DC283; Duong & Stevens, ∆rcsA Nalr 2017 Unmarked deletion of lrhA coding sequence from DC283; Kernell Burke et ∆lrhA Nalr al., 2015 Unmarked deletion of both ompC coding sequence from Duong, Jensen, & ∆ompC DC283; Nalr Stevens, 2018) ∆ompC/ompC+ ∆ompC with chromosomal complementation of ompC and Duong, Jensen, & its promoter downstream of glmS; Nalr Cmr Stevens, 2018) Unmarked deletion of nsrR coding sequence from DC283; ∆nsrR This study Nalr ∆nsrR with chromosomal complementation of nsrR and its ∆nsrR/nsrR+ This study promoter downstream of glmS; Nalr Cmr Unmarked deletion of iscR coding sequence from DC283; ∆iscR This study Nalr ∆iscR with chromosomal complementation of iscR and its ∆iscR/iscR+ This study promoter downstream of glmS; Nalr Cmr Unmarked deletion of lrp coding sequence from DC283; ∆lrp This study Nalr ∆lrp with chromosomal complementation of lrp and its ∆lrp/lrp+ This study promoter downstream of glmS; Nalr Cmr Unmarked deletion of nac coding sequence from DC283; ∆nac This study Nalr ∆nac with chromosomal complementation of nac and its ∆nac/nac+ This study promoter downstream of glmS; Nalr Cmr Unmarked deletion of DSJ_00125 coding sequence from ∆DSJ_00125 This study DC283; Nalr ∆DSJ_00125/DSJ_00125+ with chromosomal ∆DSJ_00125/ complementation of DSJ_00125 and its promoter This study DSJ_00125+ downstream of glmS; Nalr Cmr Unmarked deletion of DSJ_03645 coding sequence from ∆DSJ_03645 This study DC283; Nalr ∆DSJ_03645/DSJ_03645+ with chromosomal ∆DSJ_03645/ complementation of DSJ_03645 and its promoter This study DSJ_03645+ downstream of glmS; Nalr Cmr

Unmarked deletion of DSJ_18135 coding sequence from ∆DSJ_18135 This study DC283; Nalr ∆DSJ_18135/DSJ_18135+ with chromosomal ∆DSJ_18135/ complementation of DSJ_18135 and its promoter This study DSJ_18135+ downstream of glmS; Nalr Cmr Unmarked deletion of DSJ_21690 coding sequence from ∆DSJ_21690 This study DC283; Nalr ∆DSJ_21690/DSJ_21690+ with chromosomal ∆DSJ_21690/ complementation of DSJ_21690 and its promoter This study DSJ_21690+ downstream of glmS; Nalr Cmr Escherichia coli strains F- endA1 glnV44 thi-1 recA1 relA1 gyrA96 deoR nupG DH5α λpir Φ80dlacZΔM15 Δ(lacZYA-argF)U169 hsdR17(rK- mK+) Kvitko et al., 2012 λpir

MaH1 attTn7 pir116 R6K replicon plasmids, DH5α derivative Kvitko et al., 2012 RHO5 F-, λpir+, thi-1, thr-1, leuB6, lacY1, tonA21, glnV44, recA, yfcU::Mu, Δasd::FRT, glvB::RP4-2-TcR::Mu, Kvitko et al., ΔaphA::FRT (KmS), attTn7::pir116 2012 DAP-dependent conjugation strain S17-1 λpir recA pro hsdR RP4-2-Tc::Mu-Km::Tn7 λpir Labes et al., 1990 Top 10 F- mcrA Δ(mrr-hsdRMS-mcrBC) Φ80dlacZΔM15 ΔlacX74 deoR recAI araD139 Δ(ara-leu)7697 galU galK rpsL (Strr) Grant et al., 1990 endA1 nupG Plasmids pAUC40 Suicide vector pKNG101::attR-ccdB-CmR; Cmr, Strr, sacB Carlier et al., 2009 pDONR201 Entry vector in the Gateway system, Knr Life Technologies pEVS104 Conjugative helper plasmid, tra trb; Knr Stabb & Ruby, 2002 pGEM-T Cloning vector, Ampr Promega pR6KT2G Gateway-derivative of pR6KT2, a Tn7 vector for chromosomal integration into the intergenic region Stice et al., 2020 downstream of glmS; sacB, gus, Cmr, Gmr pUC18R6K- Tn7 vector for chromosomal integration into the intergenic Choi et al., 2005 mini-Tn7-cat region downstream of glmS; Cmr, Ampr * Ampr, ampicillin resistance; Cmr, chloramphenicol resistance; Gmr, gentamycin resistance Knr, kanamacyin resistance; Nalr, nalidixic acid resistance; Strr, streptomycin resistance; DAP, diaminopimelic acid

Table 3.2. Primers used for this study1 Deletion construction Source NAC-UPF GTCGACAATACGTGTACGCCATCG Amplify 1 kb This study NAC-UPR AGTGGAATATAGGCGGCCGCTAA region GTTCATCTTGCCTCCG upstream of nac NAC-DNF GCGGCCGCCTATATTCCACTTTCT Amplify 1 kb This study GTTTATCCCTCTCAAGC region NAC-DNR GGATCCCTGATCGGCCAGAATACC downstream of nac NAC-1kbUPF-attB1 GGGGACAAGTTTGTACAAAAAAG Amplify 2 kb This study CAGGCTGTCGACAATACGTGTACG deletion CCATCG fragment of NAC-1kbDNR- GGGGACCACTTTGTACAAGAAAGC nac with attB2 TGGGTGGATCCCTGATCGGCCAGA flanking attB ATACC sites UP- NAC-F GCCTCATCCTCGGTGAAGATTGC Screen/sequen This study IN- NAC-F TGATGAATGCCGGTCAGGTGG ce mutants for DN- NAC-R GGACGCACAGAGAGGACAGC nac deletion NSRR-UPF GTCGACCGGTACCTATCCCTATGT Amplify 1 kb This study G region NSRR-UPR AGTGGAATATAGGCGGCCGCCCTC upstream of TGTAATACTGGTTAGTCTG nsrR NSRR-DNF GCGGCCGCCTATATTCCACTGAAA Amplify 1 kb This study TTGTATTGTCTGAACCGC region NSRR-DNR GGATCCATAGTGACTAACGGCAAC downstream TG of nsrR NSRR-1kbUPF- GGGGACAAGTTTGTACAAAAAAG Amplify 2 kb This study attB1 CAGGCTGTCGACCGGTACCTATCC deletion CTATGTG fragment of NSRR-1kbDNR- GGGGACCACTTTGTACAAGAAAGC nsrR with attB2 TGGGTGGATCCATAGTGACTAACG flanking attB GCAACTG sites UP- NSRR-F AGCCGATCTATGAAACCCAGCC Screen/sequen This study IN- NSRR-F GCCTTACATGATGCCGTGCAG ce mutants for DN- NSRR-R AGATCAAGACGTTCAGGCAGGG nsrR deletion ISCR-UPF GTCGACAAAGTGCCATTATCATGT Amplify 1 kb This study GG region ISCR -UPR AGTGGAATATAGGCGGCCGCACGT upstream of CCTTTGGATGTCAG iscR ISCR -DNF GCGGCCGCCTATATTCCACTGGAA Amplify 1 kb This study ATCAACGTTAACCTCC region ISCR -DNR GGATCCATCTCTTCTTCACGCACC downstream of iscR

ISCR -1kbUPF- GGGGACAAGTTTGTACAAAAAAG Amplify 2 kb This study attB1 CAGGCTGTCGACAAAGTGCCATTA deletion TCATGTGG fragment of ISCR -1kbDNR- GGGGACCACTTTGTACAAGAAAGC iscR with attB2 TGGGTGGATCCATCTCTTCTTCAC flanking attB GCACC sites UP- ISCR -F ACGACCTGGAGCGTTTCTACC Screen/sequen This study IN- ISCR -F GACCTGAGCGTCCGTATTAGCG ce of mutants for iscR DN- ISCR -R ACAGGCAGTTCAGCGAGATCG deletion LRP-UPF-attB1 GGGGACAAGTTTGTACAAAAAAG Amplify 1 kb This study CAGGCTGTCGACATGCATACGTTC region CATCAGC upstream of LRP-UPR TAACTCGAGTGCCTAGGTATGGTA lrp with attB CCTCCTGTCGAGATCCTTACC site LRP-DNF AGGTACCATACCTAGGCACTCGAG Amplify 1 kb This study TTAAGCAATCGTCTGGTGATC region LRP-DNR-attB2 GGGGACCACTTTGTACAAGAAAGC downstream TGGGTGGATCCAAGGTTAACCATG of lrp with ACCAGC attB site UP- LRP-F ACGGAAGGGACGGTTCTGC Screen/sequen This study IN- LRP-F CGTGCCTGATATGTCCGCTTACC ce of mutants for lrp DN- LRP-R ATGCCAGGGTTCATCGTGACG deletion DSJ_00125-UPF- GGGGACAAGTTTGTACAAAAAAG Amplify 1 kb This study attB1 CAGGCTGTCGACAAGATATTACTG region GCGCTGG upstream of DSJ_00125-UPR TAACTCGAGTGCCTAGGTATGGTA DSJ_00125 CCTCTAATAGTGGCGCGAGAAG with attB site DSJ_00125-DNF AGGTACCATACCTAGGCACTCGAG Amplify 1 kb This study TTATATTGAAGGCCACGATCATC region DSJ_00125-DNR- GGGGACCACTTTGTACAAGAAAGC downstream attB2 TGGGTGGATCCATATTCCGCAATC of DSJ_00125 AGCATG with attB site UP- DSJ_00125-F GTCGTCTACCCGATGAGCGC Screen/sequen This study IN- DSJ_00125-F GGGTTTGATGAGCTGGAGTGGG ce of mutants for DN- DSJ_00125-R ACCGCTGCTTTGACGTGCAC DSJ_00125 deletion DSJ_03645-UPF GTCGACCGATCATTTCATCATCTTC Amplify 1 kb This study AACC region DSJ_03645-UPR AGTGGAATATAGGCGGCCGCTTAG upstream of TTCAACCACGCGTG DSJ_03645 DSJ_03645-DNF GCGGCCGCCTATATTCCACTAATC Amplify 1 kb This study TGCTCTGTGATGTGC region

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DSJ_03645-DNR GGATCCAAGGCCACAAAGATGAT downstream CG of DSJ_03645 DSJ_03645- GGGGACAAGTTTGTACAAAAAAG Amplify 2 kb This study 1kbUPF-attB1 CAGGCTGTCGACCGATCATTTCAT deletion CATCTTCAACC fragment of DSJ_03645- GGGGACCACTTTGTACAAGAAAGC DSJ_03645 1kbDNR-attB2 TGGGTGGATCCAAGGCCACAAAG with flanking ATGATCG attB sites UP- DSJ_03645-F TAGCGCGCTAAAGTGTGTTCCTGC Screen/sequen This study CCTATTTGCCTTCGTACATGGTGC ce mutants for IN- DSJ_03645-F AGG DSJ_03645 DN- DSJ_03645-R TTCAGAGTCAGGTGCTTCCGACG deletion DSJ_18135-UPF GTCGACCCAGAATGATTAACACCA Amplify 1 kb This study TCCC region DSJ_18135-UPR AGTGGAATATAGGCGGCCGCGCTG upstream of GATGATTGTTGAGTCAT DSJ_18135 DSJ_18135-DNF GCGGCCGCCTATATTCCACTGGCT Amplify 1 kb This study CTGATTCGTGAAATTGG region DSJ_18135-DNR downstream GGATCCCGTCTGCATTTCTTCCACC of DSJ_18135 DSJ_18135- GGGGACAAGTTTGTACAAAAAAG Amplify 2 kb This study 1kbUPF-attB1 CAGGCTGTCGACCCAGAATGATTA deletion ACACCATCCC fragment of DSJ_18135- GGGGACCACTTTGTACAAGAAAGC DSJ_18135 1kbDNR-attB2 TGGGTGGATCCCGTCTGCATTTCTT with flanking CCAC attB sites UP- DSJ_18135-F GCCGAAACAATCCAGCTTCCG Screen/sequen This study IN- DSJ_18135-F CGCTCGATACGCTGTTTGGC ce mutants for DSJ_18135 DN- DSJ_18135-R CACGCGCCTTAATGCCGG deletion DSJ_21690- GGGGACAAGTTTGTACAAAAAAG Amplify 1 kb This study 1kbUPF-attB1 CAGGCTGTCGACAAATTCAGCTCT region CAGGGC upstream of DSJ_21690-UPR AGTGGAATATAGGCGGCCGCGGG DSJ_21690 TAGAGAGAATGCTTAAAGC with attB site DSJ_21690-DNF GCGGCCGCCTATATTCCACTTACA Amplify 1 kb This study ACGATGGCAACTATCAC region DSJ_21690- GGGGACCACTTTGTACAAGAAAGC downstream 1kbDNR-attB2 TGGGTGGATCCACTCTGTCATTAA of DSJ_21690 ATACGTCACC with attB site UP- DSJ_21690-F ACTGTTTACCTGCGGAACTGGG Screen/sequen This study IN- DSJ_21690-F TTAGTGGTGTCGCCGGTGC ce of mutants for DN- DSJ_21690-R CCTGCGCCTGTTGATTTGTTACCG DSJ_21690 deletion

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Chromosomal complementation construction GAGCTCAACAGGGTAGTAAACGTT Amplify This study C_NAC_F2_SacI TCGG promoter and coding region CTCGAGCTATAAACAGAACGCTGT of nac, and C_NAC_R1_XhoI GTTTAGC screen conjugants GAGCTCACCCATTCAGCGCGTAAT Amplify This study C_NSRR_F_SacI C promoter and coding region CTCGAGCTATTTGACATTACGGTT of nsrR, and C_NSRR_R1_XhoI CCTCC screen conjugants GAGCTCAAACGGCCCTGAATAGTT Amplify This study C_ISCR_F_SacI G promoter and coding region CTCGAGCTAGGAGAAGCAGAGGA of iscR, and C_ISCR_R_XhoI TTAGG screen conjugants GAGCTCGCGAATAACTTAGTCTGA Amplify This study C_LRP_F_SacI AC promoter and coding region CTCGAGCTATGGTCCTGTATGTAT of lrp, and C_LRP_R_XhoI TCAC screen conjugants GAGCTCTTATTGCGATTCGTCAGG Amplify This study C_00125_F_SacI C promoter and coding region of CTCGAGCTAGTAAGTGAAGGGAA C_00125_R_XhoI DSJ_00125, CAATCTG and screen conjugants GAGCTCTTGTTGTTTCCTCTCGCCA Amplify This study C_03645_F_SacI TGG promoter and coding region of CTCGAGCTATGTATTGCAACAATC C_03645_R_XhoI DSJ_03645, AGCGACC and screen conjugants GAGCTCGGTTCGATGTATTGAGAT Amplify This study C_18135_F_SacI GCG promoter and coding region of CTCGAGCTAACTCATCCTTCAACA C_18135_R_XhoI DSJ_18135, GCG and screen conjugants 102

GAGCTCAGCCTGATCGACCATAAA Amplify This study C_21690_F_SacI TTTCC promoter and coding region of CTCGAGCTATTATTTGTACAACTC C_21690_R_XhoI DSJ_21690, AGCGGTGG and screen conjugants qRT-PCR and plasmid construction RT-argC_F GTGGAGCAGGGCGCAAA Kernell Burke et AAATACCGTAAGGCTGCAGACTGA al., 2015 RT-argC_R (62°C) RT-atpD_F GGTGCGGGTGTGGGTAAAA Packard et al., 2017 GCTCAGCCGCAATGTTACG RT-atpD_R (64°C) RT-bfr_F TGATTACGTAAGCCGCGATATG Packard et al., 2017 CAGTCGATATGATGCTCCTCATCTT RT-bfr_R (60°C) RT-CKS_3793_F CCTTTGTGGGCCTGTTCTTTTT Kernell Burke et ACCGCCAGATGCTGCACTT al., 2015 RT-CKS_3793_R (64°C) CDSerpA_F ATGAAGTAGTAGCACTGCCGTTG This study CDSerpA_R AGATGCTGAAGGAAGACCCG RTerpA_F TGATTGCTGACGAAGATAACCCG This study RTerpA_R CATTTGATCGTCGAAGGTGAAACC (60°C) RTesaR_F GTCCGTGATCATTAAAGGCAACG This study RTesaR_R TGCTCGTTAAAATCAATCAGCAGC (62°C) CDShmp_F TGCCAAGACGATTCACATTGTG This study CDShmp_R CCTTATGCGGACCAAACACC RThmp_F ATTCGTCAGTACTCACTCACCAC This study RThmp_R GAATCTCATCGCCTGCTTTGG (62°C) CDSiscR_F ATGAGACTGACATCCAAAGGACG This study CDSiscR _R ACGTTGATTTCCTGTGCGC RTiscR_F GGTTGATGAATCTGTGGACGC This study RTiscR_R CTAATACGGACGCTCAGGTCAC (60°C) CDSiscS_F ACCGATTTACCTGGATTATGCCG This study CDSiscS_R TGACTTCATGAGTTCACGCAGG RTiscS_F AGATTGTCGGCATGGGTGAG This study RTiscS_R GCCACAGTTTGTCACGCAAC (60°C) RTlrhA_F GATGTACAGCAATATTCAGGGCG This study RTlrhA_R TGGGATAAACAGAGGTAACGCTG (62°C) CDSlrp_F TGAATTGCAGAAAGACGGTCGC This study CDSlrp_R TTTGATCACCAGACGATTGCTC RTlrp_F AACTCAACCCTCACTACCTGG 103

This study CGGCGTTAAATTGCTCAAACAC RTlrp_R (60°C) RT-lysP_F GCCGTTTGCCGGAGGTT Ramachan dran et al., CCTGGAAAGAAAAGCCGACAA 2014 RT-lysP_R (64°C) CDSnfuA_F AATTACTGATTCTGCCCAAGAGC This study CDSnfuA_R GGTGCTCAGTAATATCGCGC RTnfuA_F GGAAGACGCTGAAATTGACTTCG This study RTnfuA_R CGCATCGTCAGAAACCTTGC (60°C) CDSnrdA_F ATGAACCAAAGTCTGCTCGTTAC This study CDSnrdA_R TTTCGCAGCCATCATCCTG RTnrdA_F TTCTACAAGCACTTCCAGACGG This study RTnrdA_R TTCAGGACTAACAGGCTTTCCAC (60°C) CDSnsrR_F CGGAAGGCAGACTAACCAG This study CDSnsrR_R TCATTGAGTATTCATTGCCACCG RTnsrR_F TCGTGCTGGGTTTGTTGC This study RTnsrR_R GCAGGCGTGATAGAGCAC (60°C) RT-osmY_F CGAAAATCGACAGCTCAATGAAGA Ramachan dran et al., CCACCAGCGCCGCTTT 2014 RT-osmY_R (60°C) RT-rcsA_F AGCGGAAAATTAAAACGCACAAC Kernell Burke et CAGAGGTCACGTTATCGGTTAAGC al., 2015 RT-rcsA_R (60°C) CDSsufA_F ATGTCATCCGTGAATGCAGACTC This study CDSsufA_R GCAGGCGTGTTGAGCTTTAGG RTsufA_F GTCAAGGGCCTGCGTTTAG This study RTsufA_R CAATGTTGCGCCGTAGTAGG (60°C) CDSsufE_F CTTTAATCGTTGCGCTAACTGGG This study CDSsufE_R TTAGCTGAGGTTCTGAGCGG RTsufE_F TCAGGTGTGGATCAAGATGACC This study RTsufE_R GGTTGCAGGTTCTGATAAAGGC (60°C) 1All sequences 5’ to 3’. Coding DNA sequence primers (CDS) were for cloning into the pGEM-

T vector, while RT primers were for the qRT-PCR experiments. Annealing temperatures for qRT-PCR are listed within the parentheses.

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CHAPTER FOUR Identification of soil bacteria capable of utilizing a corn ethanol fermentation byproduct

Packard H, Taylor ZW, Williams SL, Guimarães PI, Toth J, Jensen RV, Senger RS, Kuhn DD,

Stevens AM*. 2019. Identification of soil bacteria capable of utilizing a corn ethanol fermentation byproduct. PLoS ONE 14(3): e0212685. https://doi.org/10.1371/journal.pone.0212685

*Corresponding author:

Email [email protected]

Keywords: anaerobic digestion, Bacillus, ethanol production, microbial biomass, MiSeq, thin stillage

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Attributions

Holly Packard Bartholomew contributed to the experimentation and analysis for data in Figures

4.1, S4.1, S4.2 and Tables 4.1, 4.2, 4.3, S4.1, S4.2. Ann M. Stevens was the lead principle investigator and Roderick V. Jensen, David D. Kuhn, and Ryan S. Senger were also principle investigators on the project. Holly and Ann wrote the manuscript. Zachary Taylor and Stephanie

Williams contributed to the experimentation presented in Figures S4.1 and S4.2, and Table 4.3.

Pedro Ivo Guimarães and Jackson Toth contributed to the experimentation presented in Figure

4.1. Zachary, Stephanie, Pedro, and Jackson contributed to the experimentation presented in

Table 4.2.

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Abstract

A commercial corn ethanol production byproduct (syrup) was used as a bacterial growth medium with the long-term aim to repurpose the resulting microbial biomass as a protein supplement in aquaculture feeds. Anaerobic batch reactors were used to enrich for soil bacteria metabolizing the syrup as the sole nutrient source over an eight-day period with the goal of obtaining pure cultures of facultative organisms from the reactors. Amplification of the V4 variable region of the 16S rRNA gene was performed using barcoded primers to track the succession of microbes enriched for during growth on the syrup. The resulting PCR products were sequenced using Illumina MiSeq protocols, analyzed via the program QIIME, and the alpha-diversity was calculated. Seven bacterial families were the most prevalent in the bioreactor community after eight days of enrichment: Clostridiaceae, Alicyclobacillaceae,

Ruminococcaceae, Burkholderiaceae, Bacillaceae, Veillonellaceae, and Enterobacteriaceae.

Pure culture isolates obtained from the reactors, and additional laboratory stock strains, capable of facultative growth, were grown aerobically in microtiter plates with the syrup substrate to monitor growth yield. Reactor isolates of interest were identified at a species level using the full

16S rRNA gene and other biomarkers. Bacillus species, commonly used as probiotics in aquaculture, showed the highest biomass yield of the monocultures examined. Binary combinations of monocultures yielded no apparent synergism between organisms, suggesting competition for nutrients instead of cooperative metabolite conversion.

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Introduction

Commercial-level ethanol production is a global industry that yielded roughly 27 billion gallons in 2017, around 16 billions of which were processed in the United States (Renewable

Fuels Association, 2017). Production of ethanol uses a starch-based biomass, with corn being the predominant source in U.S. production. Ethanol production commonly starts with milling of the corn, followed by cooking, liquification, and saccharification to allow yeast fermentation of the product, which is then distilled to separate ethanol from the stillage byproducts. The stillage is then centrifuged to separate the solid (wet distillers’ grains) from liquid (thin stillage) portions

(Singh et al., 2001). The thin stillage is concentrated through high temperature evaporation into condensed corn distillers solubles (CCDS), commonly termed syrup. This syrup is often used as an animal feed supplement when combined and dried with the wet distillers’ grains (Kingsly et al., 2010; Probst et al., 2013; Singh et al., 2001). Since the syrup contains organic carbon sources

(Kim et al., 2008), microbes have also been used to convert it into other desirable products, such as production of the complex polysaccharide pullulan by fungi (e.g. Aureobasidium sp.)

(Leathers 2003; Leathers & Gupta, 1994). However, the syrup remains an underutilized component of the ethanol production process. In this study, the syrup was used as a nutrient-rich medium for microbial biomass development, which, if successful, would improve the profitability of ethanol production by developing a possible new protein source for aquaculture feeds.

Large-scale cultivation of microbial biomass has been used in a variety of industrial practices, including production of agricultural probiotics (Balcázar et al., 2006), carotenoid production (Johnson & Schroeder 1996), human and agricultural food production (Boze, Moulin,

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& Galzy, 1995; Martin, 1994; Unibio, n.d.), and wastewater treatment (Boze, Moulin, & Galzy,

1995; Gupta & Mohapatra, 2003; Gutzeit et al., 2005; Narasimhulu & Pydi Setty, 2012). The aquaculture industry has a particular interest in culturing protein-rich bacterial biomass on wastewater/byproducts to replace fishmeal in aquaculture feeds. Fishmeal has traditionally served as the major protein source for many cultured species of fish and shellfish due to its high palatability and digestibility and its well-balanced essential amino acid profile (FAO, 2018).

However, fishmeal demand has increased along with the price (under $650/metric ton in 2003 to over $1,500/metric ton in 2018; Index Mundi, 2018), which is making alternative protein sources more lucrative to the aquaculture industry. Culturing microbial biomass on wastewater/byproducts has the added benefit of making use of these otherwise no- to low-value waste streams. It has been previously demonstrated that microbial biomass can be cultured while treating wastewater from fish farms and confectionary manufacturing plants and this biomass can be successfully used to replace fishmeal in feeds for shrimp grown in aquaculture (Kuhn, et al.,

2010; Kuhn et al., 2016). The goal of this study was to investigate the capacity for microbes to grow on a corn ethanol fermentation syrup substrate so that they might also be used as a protein supplement in aquaculture feeds. A bioreactor-grown soil enrichment community capable of metabolizing the syrup was first established and its community profile was characterized at a molecular level using 16S rRNA sequences. Then, defined monocultures were tested for their growth yields, and binary culture combinations were examined for possible synergistic effects within the community. Bacillus species, although not the dominant organism in the bioreactor, were the most productive pure culture isolates. These findings lay the groundwork for future application of the bacterial biomass in aquaculture.

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Materials and Methods

The syrup growth substrate

Syrup, a byproduct of ethanol production, was obtained for used as a growth substrate for bacteria. To examine how robust the bacterial growth would be across different lots of syrup, three separate batches were provided from three different Flint Hills Resources (FHR) ethanol production facilities with similar design and function. All three facilities are an ICM design for

100 million gallons per year plants (ICM, Inc., KS, USA). The syrups were removed at the same point in the ethanol production process, after oil separation and evaporation through the application of centrifugation and high temperature (~85ᵒC), respectively. Although three different commercial yeast strains were used, Bio-Ferm XR, TransFerm Yield+ (Lallemand

Biofuels and Distilled Spirits, GA, USA) and Ethanol Red (Fermentis, France), the CCDS produced were all similar in content with ~30-40% solids and ~60-70% water. The CCDS, known as syrup, were cooled prior to shipping overnight to Virginia Tech. Upon receipt, an aliquot of each syrup was streaked on to a rich medium, trypticase-soy agar (TSA; 17 g L-1 pancreatic digest of casein, 5 g L-1 sodium chloride, 3 g L-1 papaic digest of soybean, 2.5 g L-1 dipotassium phosphate, 2.5 g L-1 dextrose), to ensure that there were no microbial contaminants present prior to further analysis. Using aseptic technique, the contaminant-free lots of syrup were individually diluted 1:1 (volume/volume) with milliQ dH2O. Bottles (500 mL) of the diluted syrup were centrifuged (Avanti J-26 XP centrifuge with JA-10 rotor, Beckman Coulter, CA,

USA) for 30 min at 4,000 rpm and 4ᵒC to remove insoluble solids. The syrup was then filtered through autoclaved Sofwipe cheesecloth (American Fiber & Furnishing, Inc., MA, USA) to remove additional remaining solids from the syrup and the processed liquid syrup was stored at

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4ᵒC for short-term use or -20ᵒC for longer-term storage in sterile containers. This processed syrup had high water activity as it contained ~12-16% solids in ~84-88% water with the dominant solids/solutes comprised of ~27-34% glycerol, ~16-20% dextrin (DP4), ~9-11% maltose (DP2) with lesser amounts of maltotriose (DP3), glucose (DP1), and lactic acid detected across all three processed syrups used for further studies. Syrup 2 was used for all studies, while syrups 1 and 3 were examined in monoculture studies to test for organism robustness.

Temporal community profiling of bacterial enrichment in anaerobic reactors

Processed syrup 2 was added to 1 L digestor reactors at a 1:16 (volume/volume) dilution with milliQ dH2O. A soil sample was obtained, 13 inches below the surface, from a site adjacent to a local cornfield with likely exposure to residuals from corn plants (latitude: 37.211668; longitude: -80.436833). Aliquots of the soil sample were added to reactors at a 1:10 mass to volume ratio with the diluted and processed syrup to enrich the microbial community for organisms capable of using the syrup as their sole nutrient source. Nitrogen gas was sparged through the reactors for 5 min to create an anaerobic environment that would select against strict aerobes. Anaerobic digestion was performed at 37ºC over a four-day initial enrichment period without any adjustment to the pH. On the fourth day, the liquid top layer was removed from the denser solid and particulate materials (i.e. soil) and replaced with fresh processed syrup, and this second enrichment continued for another four days. In total, the microbial community was enriched over an eight-day period. Samples (10 mL) were collected via a sampling syringe and deposited into sterile conical tubes aerobically on day 0, day 1, and day 4 from the first portion of the enrichment cycle. After the addition of more syrup, samples were obtained on day 5 and

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day 8 from the second portion of the enrichment cycle, totaling five samples each from three separate reactors. DNA was extracted from these samples using the Qiagen DNeasy Powersoil

Kit (Qiagen, MD, USA) per the manufacturer’s protocol. PCR was performed in triplicate using

0.2 µM barcoded primers for the V4 variable region of the 16S rRNA gene as previously described (Table S4.1) (Caporaso et al., 2011), as well as 1X 5Prime HotMasterMix (Quantabio,

MA, USA), and chromosomal DNA template from each enrichment time point. Thermocycler conditions were set for an initial denaturation at 94˚C for 2 min, followed by 35 cycles of denaturation at 94˚C for 5 min, annealing at 50˚C for 1 min, and elongation at 68˚C for 1.5 min, with a final extension cycle at 68˚C for 10 min before holding at 4˚C. A negative control PCR for each primer set was performed without template. The triplicate samples were combined, visualized on a 1% agarose gel, and purified using the PCR Purification Kit (Qiagen). The concentration of each sample was measured using Qubit at the Virginia Tech Biocomplexity

Institute (VTBI), and samples pooled for 250 nt paired-end read Illumina MiSeq (VTBI)

(Caporaso et al., 2012).

MiSeq data analysis

The Illumina sequencing data generated for the forward sequences was 15,377,857 total sequences, with 4,455,215 of those reads unassigned to a specific sample due to insufficient barcode sequence quality. Sequencing data was provided demultiplexed into the 15 original samples (five time points, three replicate digestors each) and analyzed with the program

Quantitative Insights Into Microbial Ecology (QIIME, v. 1.9.1). Individual samples ranged between 317,933- 816,771 sequences. Each sample was quality filtered to remove sequences shorter than 200 nucleotides, sequences with a phred score less than 20, and those with more

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than six ambiguous bases. After quality filtering, the new sequence range was 286,912 - 714,010, so all samples were rarefied to 286,900 reads. These were then clustered via UCLUST into operational taxonomic units (OTUs) with a threshold of 97% similarity (Caporaso et al., 2010).

An OTU threshold minimum set at 0.001% of the total sequences was implemented, resulting in the total sequence count for the OTU table to be 8,658,900 reads. OTU tables were generated based on these rarefied values and exported into a spreadsheet. A Shannon index was calculated to give the alpha diversity across all three replicate reactor samples for each time point, and the estimated number of families (ENF) was also calculated (Table 4.1) (Jost, 2006).

Pure culture strain isolation from enrichment cultures

At the end of an eight-day enrichment experiment, the solid materials from one anaerobic reactor were used to obtain 10 pure isolated colonies for follow-up monoculture studies. The anaerobic reactors were not run to achieve a steady state; instead, the short time frame of the enrichment was designed to select for the fastest growing organisms. In addition, sampling throughout the enrichment process by intention was not kept strictly anaerobic to select for facultative organisms. Fast growing, facultative organisms were preferable for possible downstream commercial applications. Therefore, subsequent organism isolation was performed in parallel using both anaerobic and aerobic conditions in batch culture in an attempt to obtain a diversity of organisms in pure culture. Part of the sample was transferred to a Coy anaerobic chamber (Coy Laboratory Products, MI, USA), where it was T-streaked onto TSA and grown anaerobically for 48 hr at 37˚C. Colonies of various morphologies were then purified into separate stocks for further use and designated UAN (Unknown Anaerobe; Table 4.2). This

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isolation process was repeated aerobically, and purified stocks were designated UAE (Unknown

Aerobe; Table 4.2).

One additional monoculture, M11, was isolated aerobically from a contaminated batch of syrup received from FHR that was not used as a growth substrate. The source of this contaminant is unknown.

Monoculture and binary-combination growth assays of microbial strains

Strains of interest were grown overnight at 37ᵒC with shaking at 250 rpm in trypticase- soy broth (TSB; Table 4.2) and subcultured into fresh medium to a 1:100 dilution, followed by growth for four hr. These actively growing cultures were then each diluted in phosphate buffered saline (PBS; 137 mM NaCl, 2.7 mM KCl, 10 mM Na2HPO4 and 2 mM KH2PO4, pH 7.4) to an

OD600 of 0.1. After dilution, 1.4 mL of the suspended cells were pelleted via centrifugation

(Eppendorf 5424R centrifuge with FA-45-24-11 rotor, Germany) for 5 min at 5,000 rpm, washed with 0.5 mL PBS, and recentrifuged. The pellet was resuspended in 1.4 mL PBS then diluted

1:10 with PBS to a final OD600 of 0.01.

Each of the three processed syrups (batches 1-3) from the three corn ethanol production facilities was separately diluted 1:4 (volume/volume) with milliQ dH2O, and 100 µL added to wells in the Nunclon Delta Surface 96-well plate (Thermo Scientific, MA, USA). No pH adjustment was made to the growth medium. For the monoculture growth assays, 100 µL culture in PBS (OD600 of 0.01) was added to the three syrups (final processed syrup dilution of 1:8; final

OD600 at 0.005) in triplicate. Triplicate wells of each syrup with 100 µL PBS were used as

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negative controls to ensure that there was no microbial contamination from the syrup, and cultures with 100 µL TSB were used as positive viability controls. Microtiter plates were incubated at 37ᵒC in standing conditions for four days. Absorbance readings (600 nm) were taken using the SpectraMax M5 spectrophotometer (Molecular Devices, CA, USA) each day, including an initial reading. For the binary culture assays, cultures were grown and washed separately, then 50 µL of each were added to the appropriate well (Table S4.2). Binary culture assays only used syrup 2.

Strain identification

Unknown isolates (Table 4.2) were grown overnight at 37ᵒC in TSB. Microscopy and a

Gram stain were performed on each of the unknown monocultures. DNA from Gram-positive bacterial monocultures was extracted using the DNeasy Blood and Tissue Kit (Qiagen) per the manufacturer’s recommended protocol. For the M11 yeast strain, cells grown overnight at 37ᵒC on TSA were added via toothpick to 300 µL of NTES (0.5 M NaCl, 0.2 Tris HCl, pH 7.5, 0.01 M

Na3 EDTA, 1% SDS). Glass beads (300-650 µL; G-8772, acid-washed, Sigma-Aldrich, MO,

USA) and 300 µL 1:1 phenol:chloroform were added and vortexed for 7 min at 4˚C. After centrifugation at 12,000 rpm (Eppendorf 5417R centrifuge with F45-30-11 rotor) for 10 min at

4˚C, the aqueous phase was transferred to 800 µL cold ethanol and stored at -20˚C overnight.

Then, samples were centrifuged for 10 min at 4˚C, washed with 70% ethanol, recentrifuged, then dried and dissolved in 30 µL dH2O (Elder, Loh, & Davis, 1983). PCR was performed using 0.2

µM of universal primers, 515F and 806R, designed for the 16S rRNA gene for strain identification, or the internal transcribed spacer (ITS2) region for the yeast identification (Table

S4.1), as well as 1X OneTaq Quick-Load Master Mix, and chromosomal DNA template of each

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unknown microbe species. Thermocycler conditions were per enzyme protocol (New England

Biolabs, MA, USA). Initial denaturation was at 94˚C for 30 sec, followed by 30 cycles of denaturation at 94˚C for 30 sec, annealing at 45˚C for 1 min, and extension at 68˚C for 1.5 min.

Final extension was at 68˚C for 5 min. More specific identification for select bacterial samples was performed using primers for housekeeping genes gyrB, pyrE, and rpoB (Liu et al., 2013).

PCR was performed as above with each appropriate primer (Table S4.1), and thermocycler conditions were identical except for a shortened extension time at 68˚C for 45 sec with 30 cycles.

Products of all reactions were visualized on a 1% agarose gel. These were extracted via a Gel

Extraction Kit (Qiagen) and sequenced (VTBI). The Basic Local Alignment Sequencing Tool

(BLAST; NCBI) was used to determine the sequence identities via a nucleotide Megablast search within the nucleotide collection (nt/nr) and 16S rRNA sequences databases. Those with the highest Max Score (highest query and identity percentages, and E-value closest to 0.0) were used as the identity of the unknown organisms (Table 4.2).

Accession numbers

Paired-end sequencing reads from the 15 samples of enriched bacterial communities (i.e. five time points with combined triplicate samples from three separate reactors) with syrup were deposited into the NCBI Sequence Read Archive (SRA) with accession number SRP144322.

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Results

Community profiling illustrates succession of enriched bacterial families

Anaerobic digestor reactors were used to enrich for soil bacteria capable of using syrup produced as a byproduct of corn ethanol production for their sole growth substrate with the goal of obtaining pure cultures of facultative organisms from the reactors. Temporal sampling for three separate reactors was performed to obtain five samples across an eight-day digestion enrichment to determine the bacterial community composition via 16S rRNA gene sequencing so that this profile could later be compared to the list of organisms isolated in culture. This also provided insights into the different families of organisms capable of using the syrup as a growth medium. For each of the three reactors utilized, solid materials from the bottom of the reactor were processed to purify DNA and then PCR was performed in triplicate. The PCR products were combined to produce the five temporal samples per reactor (i.e. 15 samples in total). At each time point the data from samples for the three reactors was averaged for determining the percent of dominant families present across all of the reactors (Figure 4.1). Additionally, the data was also used for the calculation of the alpha diversity and ENF. Both of these calculations showed an overall decrease in diversity as time progressed, with a slight increase toward the end of the enrichment period examined (Table 4.1). The system was intentionally not run to a steady state as the most rapidly growing organisms were desirable for downstream applications. The dominant families fluctuated over the eight-day enrichment, beginning with a very large increase in the Pseudomonadaceae family on the first day of enrichment (Figure 4.1). Subsequently, by the fourth day, organisms belonging to the Clostridiaceae family dominated the reactors at an 117

average level of 35%, with Enterobacteriaceae, Bacillaceae and Burkholderiaceae following at

25%, 17%, and 15% respectively. After the removal of the liquid top layer and addition of fresh syrup, Clostridiaceae became even more dominant with 61% of reads belonging to that family on day five. On the final eighth day, 93.7% of the organisms present in the community belonged to the Clostridiaceae (28.0%), Alicyclobacillaceae (15.4%), Ruminococcaceae (14.0%),

Burkholderiaceae (12.7%), Bacillaceae (11.3%), Veillonellaceae (6.7%), and

Enterobacteriaceae (5.7%) families, and were more evenly present. The total number of families found across all three reactors ranged from an initial 66-81 on day zero to only 19-24 after eight days.

Monoculture growth revealed differences in growth yield between strains

Solid material from the final day of bioreactor enrichment (day eight) was plated onto

TSA under both aerobic and anaerobic conditions. A total of 10 pure-culture isolates were randomly selected from these agar plates to test for growth yield with the syrup as the sole nutrient source. An additional eight known stock cultures (designated M for pure monoculture), seven of which were lab stocks and the last obtained from a commercial yogurt product were also utilized (Table 4.2). Another organism, M11, was separately isolated from a contaminated batch of syrup unusable as a growth substrate. All newly isolated enrichment strains were identified via microscopy and a Gram stain as Gram-positive bacteria except M11, which was putatively identified as a yeast strain from the cell size and morphology. The aerobic (UAE) and anaerobic (UAN) isolates obtained from the reactors that maintained viability under facultative growth conditions, desired for future work, were monitored for their growth yield.

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Monoculture assays were performed on three lots of syrup from different production facilities to examine the robustness of growth across similar, but not identical growth substrates.

Growth occurred on all three syrups, but was not equivalent across the different syrups or the different organisms (Table 4.3 and Figure S4.1). The most rapid phase of growth was between day 0 and day 1, with the majority of strains achieving their maximum yield by day 1 (S4.1

Figure). For the monocultures examined, the day 1 growth levels were highest, on average, for pure culture isolates M1-3 and M11 and enrichment culture isolates UAE2, UAE4, UAE5 and

UAN4 across the three syrups (Table 4.3, gray highlights). Thus these strains exhibited the desire characteristics of rapid growth and robustness across a variety of similar substrates.

Binary culture combinations showed no synergism

To explore whether two monocultures together would result in an increased maximum growth yield, binary combination growth assays were performed using select monoculture strains with syrup 2 as the medium, since it was also the substrate used in the bioreactors (Table S4.2).

Growth patterns in the binary assays showed a predominant number of combinations (30 out of

34) to have very similar growth trends with at least one of the original monoculture growth patterns, suggesting no synergistic effects between those organisms (S4.2 Figure). Two combinations, M2 with M6 and M2 with M7, resulted in a yield that was intermediate between the two monoculture growth patterns, as each organism alone had a very different yield (S4.2

Figure). M11 with UAE2 and M11 with UAE5 did show slight increases in combined yield, but these were not considered to be important differences (S4.2 Figure). These results suggest that for the culture combinations examined, neither organism present generated a product(s) that noticeably aided in the growth of the other organism.

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Pure-culture isolates from reactors were Bacillus species

Industrial application of cultured biomass for animal consumption requires knowledge of the exact composition and growth capabilities of the organisms present to ensure safety. To determine the identification of the UAE and UAN enrichment isolates used in the microtiter growth assays, and to correlate this information to the community profiles found in the bioreactors, the 16S rRNA gene from each enrichment monoculture isolate was subject to sequencing. Sequencing results revealed that all of them belonged to the Bacillus genus (Table

4.2). The conserved nature of the 16S rRNA gene within the Bacillus genus hindered identification of each isolate at the species level. Because the biomass was proposed to be used for animal consumption followed by human consumption, any sequencing result that suggested an organism might be a potential pathogen, such as Bacillus anthracis or Bacillus cereus, led to the organism being removed from further consideration. Therefore, additional characterization at the species level was performed on UAE2, UAE4, and UAE5 using genes gyrB, pyrE, and rpoB for a more specific species determination. UAE2 and UAE5 were both found to be either

Bacillus pumilus or Bacillus safensis, while UAE4 was found to be either Bacillus amyloliquefaciens, Bacillus subtilis or Bacillus velezensis (Table 4.2). Thus, the UAE2, UAE4 and UAE5 isolates are considered to be candidates for future work to develop them into safe direct fed protein supplements for aquaculture feed, in addition to the pure culture isolates M1,

M2 and M3.

Discussion

The purpose of this study was to identify pure culture isolates obtained from laboratory stocks and a soil enrichment community that could grow using a byproduct of ethanol 120

fermentation production as their sole nutrient source. At the final time point (day eight) of the anaerobic digestion with the syrup and soil (Figure 4.1), there were seven dominant organism families that were enriched including the Bacillaceae family that proved to be the group of organisms of greatest interest. The other six families enriched in the bioreactor were

Clostridiaceae, Alicyclobacillaceae, Ruminococcaceae, Burkholderiaceae, Veillonellaceae, and

Enterobacteriaceae. However, of those enriched, only four, the Bacillaceae, Burkholderiaceae,

Alicyclobacillaceae, and Enterobacteriaceae families, have members that are facultative anaerobes. Our procedures were designed to select against organisms that were obligate aerobes or anaerobes. Facultative growth is an ideal trait that enables handling of organisms under aerobic conditions, while allowing fermentation in large-scale industrial vats.

The monoculture assays revealed Bacillus species as the organisms capable of the highest levels of growth with the syrup substrate. While the most productive monocultures exclusively belonged to the Bacillaceae family, the enrichment study revealed a more diverse community of seven dominant families capable of growth on the syrup. In fact the Bacillaceae family represented just 11.3% of the total community. Antagonism and/or competition were probable contributing factors within the reactors limiting the growth of the Bacillaceae. However, the

Bacillaceae were the most successful group of organisms at adapting to the different selections we applied with regard to oxygen availability (i.e. anaerobic and aerobic growth) and medium choice (TSA and syrup). Since variability in syrup composition and nutritional content is known

(Belyea et al., 1998), a highly desirable trait is the capacity for robust growth across different batches. The Bacillaceae examined appear to have this desired characteristic.

Interestingly, numerous studies have shown Bacillus sp. to be able to utilize multiple carbon sources, and they are capable of catabolite repression when grown in the presence of 121

more than one source (Singh et al., 2008; Yoshida et al., 2001). More recently, interest in

Bacillus sp. metabolism has increased regarding carbon sources that are industrially relevant, including the anhydrosugar levoglucosan from burning biomass or hemicellulose from plant residues (Iwazaki et al., 2018; Lian et al., 2016; Saha, 2003). Since the process used by the FHR production facilities does not entail very high temperatures, with all steps occurring at less than

87.8ᵒC (190ᵒF) it would be unlikely that anhydrosugars would be formed. Instead, glycerol, dextrin (DP4), and maltose (DP2) were the most abundant carbohydrates in the solid fraction of the FHR syrups.

Thirty-four binary combinations of the microbes were grown on the syrup to see if the initial syrup substrate might be interconverted into metabolites better supporting growth of the mixed community. The binary growth assays revealed no apparent synergistic growth effects, as none of the combinations tested grew any better than did just one of the individual organisms (S4.2

Figure). This indicates that there are no beneficial metabolites produced for the paired organisms to use. Despite this, synergism could be possible between the top Bacillus species isolates and other organisms that were present in the initial bioreactor community.

The discovery that Bacillus species utilize the syrup as their sole nutrient source has the potential for future applications. For example, bacteria in the Bacillus genus have been used as a supplement with aquaculture feed in industrial practices, specifically for probiotic benefit, stimulating fish immune system, and even improving water quality (Balcázar et al., 2006). In addition, their ability to form highly stable dormant spores makes long-term transport and storage possible (Schisler et al., 2004; Setlow, 1995). By dry weight, Bacillus cells are roughly

50% protein, thus they could be used as a supplement instead of expensive fishmeal in the feed

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of aquaculture-grown animals. This study identified some promising Bacillus isolates that would be considered safe for animal consumption as a substitute for fishmeal.

In 2016, about 20 million tons of global fish production went toward fishmeal or fish oil use, almost 12% of total fish production worldwide (FAO, 2018). A rise in demand due to increased aquaculture practices combined with the irregular supply of fishmeal due to overfished marine environments has resulted in a heightened cost of fishmeal (FAO, 2018; Index Mundi, n.d.).

These trends suggest a need for additional and alternative nutritional material for a permanent aquaculture feed supplement. Therefore, the use of the syrup substrate as a means to cultivate microbes, such as Bacillus species, would provide enhanced economic and sustainability benefits not only to the process of ethanol production, but also to commercial aquaculture.

Acknowledgements

We thank Brian Badgley, Silke Hauf, Christopher Lawrence and Stephen Melville at Virginia

Tech for sharing procedures and equipment and Jason Bootsma for serving as our liaison with

Flint Hills Resources.

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Additional Information and Declarations

Data Availability

Paired-end sequencing reads from the 15 samples of enriched bacterial communities with syrup were deposited into the NCBI Sequence Read Archive (SRA) with accession number

SRP144322. All other relevant data is within the paper and its Supporting Information files.

Funding

Flint Hills Resources (DDK, RSS and AMS) and Virginia Tech's Open Access Subvention Fund supported the publication of this work. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests

Flint Hills Resources was the commercial funder for this study. This does not alter our adherence to PLOS ONE policies on sharing data and materials

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Table 4.1. Estimated Number of Families and alpha diversity of the soil enrichment community. Sample Time Point a Estimated Number of Familiesb Alpha Diversity b Day 0 22 3.1 Day 1 12 2.5 Day 4 5.2 1.7 Day 5 3.7 1.3 Day 8 8.0 2.1 a Calculations made using data from three pooled PCR technical replicates from each of the three replicate reactors. b Shannon index used for alpha diversity calculations and ENF calculation.

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Table 4.2. Microbes used in this study.a Strain Strain Identity Source Sequenced Gene Code Target M1 Bacillus subtilis ATCC 23857 Known – not sequenced M2 Bacillus licheniformis ATCC 9945A Known – not sequenced M3 Bacillus subtilis ATCC 6051 Known – not sequenced M5 Enterococcus faecium ATCC 19434 Known – not sequenced M6 Enterococcus lactis ATCC 11454 Known – not sequenced M7 Saccharomyces cerevisiae Virginia Tech Known – not Teaching Labs sequenced M8 Bifidobacterium lactis Commercial Known – not yogurt isolate sequenced M9 Pantoea stewartii subsp. stewartii Coplin et al., Known – not DC283 1986 sequenced M11 Pichia kudriavzevii Syrup ITS2 region contaminant UAE1 Bacillus cereus, Bacillus mycoides, Soil enrichment 16S rRNA gene Bacillus subtilis, Bacillus thuringiensis, isolate Bacillus weihenstephanensis UAE2 Bacillus pumilus, Bacillus safensis Soil enrichment 16S rRNA gene, isolate gyrB, rpoB, pyrE UAE3 Bacillus cereus, Bacillus mycoides, Soil enrichment 16S rRNA gene Bacillus thuringiensis, Bacillus isolate toyonensis, Bacillus weihenstephanensis UAE4 Bacillus amyloliquefaciens, Bacillus Soil enrichment 16S rRNA gene, subtilis, Bacillus velezensis isolate gyrB, rpoB, pyrE

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UAE5 Bacillus pumilus, Bacillus safensis Soil enrichment 16S rRNA gene, isolate gyrB, rpoB, pyrE UAE6 Bacillus anthracis, Bacillus cereus, Soil enrichment 16S rRNA gene Bacillus subtilis, Bacillus thuringiensis isolate UAE7 Bacillus anthracis, Bacillus cereus, Soil enrichment 16S rRNA gene Bacillus toyonensis, Bacillus isolate thuringiensis UAE8 Bacillus anthracis, Bacillus cereus, Soil enrichment 16S rRNA gene Bacillus toyonensis, Bacillus isolate thuringiensis UAE10 Bacillus cereus, Bacillus mycoides, Soil enrichment 16S rRNA gene Bacillus pseudomycoides isolate UAN4 Bacillus anthracis, Bacillus cereus, Soil enrichment 16S rRNA gene Bacillus thuringiensis isolate aMultiple species listed for organisms with 100% sequencing identity using the listed gene(s) as sequencing targets.

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Table 4.3. Growth yields of monocultures on syrup from three production facilities.a

Monoculture Syrup 1 Syrup 2 Syrup 3 Syrup Average M1 0.28 ± 0.12 0.41 ± 0.23 0.58 ± 0.01 0.43 ± 0.12 M2 0.09 ± 0.10 0.41 ± 0.07 0.47 ± 0.04 0.32 ± 0.17 M3 0.40 ± 0.21 0.47 ± 0.27 0.57 ± 0.02 0.48 ± 0.07 M5 0.04 ± 0.01 0.15 ± 0.01 0.18 ± 0.03 0.13 ± 0.06 M6 0.10 ± 0.01 0.26 ± 0.01 0.20 ± 0.02 0.19 ± 0.07 M7 0.08 ± 0.01 0.11 ± 0.01 0.20 ± 0.04 0.13 ± 0.05 M8 0.15 ± 0.00 0.28 ± 0.01 0.26 ± 0.04 0.23 ± 0.06 M9 0.02 ± 0.01 0.06 ± 0.02 0.05 ± 0.01 0.04 ± 0.02 M11 0.56 ± 0.02 0.75 ± 0.07 0.56 ± 0.05 0.62 ± 0.09 UAE1 0.02 ± 0.01 0.38 ± 0.24 0.18 ± 0.18 0.20 ± 0.15 UAE2 0.10 ± 0.06 0.29 ± 0.02 0.52 ± 0.06 0.30 ± 0.17 UAE3 0.03 ± 0.02 0.61 ± 0.18 0.12 ± 0.04 0.26 ± 0.25 UAE4 0.35 ± 0.02 0.68 ± 0.05 0.53 ± 0.02 0.52 ± 0.13 UAE5 0.11 ± 0.06 0.49 ± 0.08 0.53 ± 0.10 0.38 ± 0.19 UAE6 0.03 ± 0.02 0.35 ± 0.03 0.23 ± 0.03 0.20 ± 0.13 UAE7 0.01 ± 0.01 0.29 ± 0.08 0.24 ± 0.09 0.18 ± 0.13 UAE8 0.02 ± 0.00 0.26 ± 0.07 0.16 ± 0.04 0.15 ± 0.10 UAE10 0.01 ± 0.01 0.35 ± 0.01 0.07 ± 0.06 0.14 ± 0.15 UAN4 0.01 ± 0.01 0.76 ± 0.05 0.13 ± 0.03 0.30 ± 0.33 aM = monoculture from laboratory isolates. UAE = unknown aerobically plated environmental isolate. UAN = unknown anaerobically plated environmental isolate. Optical density data

(OD600) readings from day 1 of growth averaged from three replicate growth assay plates, with data from each plate an average of three replicate wells. Background correction performed by subtracting averages of syrup with PBS wells from each plate. Standard deviations calculated for

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each individual syrup experiment across the independent replicate plates, and across the independent syrup experiments. Gray boxes denote the organisms with the highest average growth across all syrups.

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Figure 4.1. Bacterial community profile across anaerobic syrup enrichment cycles. Reads were averaged from the PCR pools for each of the three replicate reactors across five time points over the eight-day enrichment. Dominant families listed throughout the enrichment are indicated with the following labels: A = Alicyclobacillaceae, Ba = Bacillaceae, Bu = Burkholderiaceae, C

= Clostridiaceae, E = Enterobacteriaceae, P = Pseudomonadaceae, R = Ruminococcaceae, and

V = Veillonellaceae.

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CHAPTER FIVE Concluding Remarks

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Corn is the number one agricultural crop in the United States (U.S.), contributing to human and animal food sources as well as to biofuel production. Since corn is such an important economic commodity, research in many different areas is attempting to improve yield and quality of the corn crop. One major focal point is the study of pathogens of corn, including the work described here for Pantoea stewartii subsp. stewartii.

P. stewartii is the causal agent of Stewart’s wilt disease in sweet corn, popcorn and susceptible field corn plant varieties (Roper, 2011). It is endemic to the U.S. and the corn flea beetle vector that harbors the bacterium is also endemic in the same region (Pataky, 2004).

However, in addition to yield losses, the disease also impacts U.S. export practices, as it is important to quarantine this pathogen to the area it is currently prevalent. Initial symptoms occur for Stewart’s wilt when the beetle transfers bacteria into the leaf of the plant during feeding. The bacteria cause a water-soaking symptom when inside the apoplast before moving to the xylem.

Once there, they can proliferate and create a biofilm that disrupts host water transport. In seedlings the disease is most severe, causing stunted growth, wilting, necrosis of host cells, and eventual death of the plant.

In comparison to most other bacterial phytopathogens, P. stewartii has a limited number of virulence factors that it employs to cause disease symptoms. Therefore, teasing apart the nuanced interaction of the bacteria with the host plant may provide insight as a model for more complex plant pathogen interactions. The work described in Chapters 2 and 3 of this dissertation aims to fill in the gaps of knowledge in this system. In Chapter 2, the focus was to identify what genes were differentially expressed in the bacteria from an in planta-derived community compared to in vitro grown cells. This work was one of the first transcriptome-based approaches from an in planta derived bacterial culture published. In addition to providing information about 135

the P. stewartii in planta lifestyle, this study was also important for development of a methods pipeline in the lab that has been used since for bacterial in planta retrieval, RNA extraction, and subsequent transcriptome experiments and analysis.

Already, insights from the RNA-Seq data have been leveraged to interpret related findings about the P. stewartii lifestyle from the scientific community. It was noted in a recent study that the corn plants are sequestering their nutrients to prevent P. stewartii from accessing them during pathogen attack (Doblas-Ibáñez et al., 2019). This may be why it was found in the transcriptome that the bacterial transporters are so highly upregulated when the bacterium is in the xylem. The nutritional need would be heightened for the bacteria within the host, and the ability to import these metabolites would be crucial to their survival. However, to investigate this further, reverse genetics approaches are needed to determine if nutrient transporters are important for in planta survival and perhaps even virulence. Since some transporters would perhaps be expected to have redundant functions, multiple gene deletions may be required to determine how specific nutrients are utilized. Confirmation of nutrients available within the xylem during infection would also be critical to understanding this interaction.

Chapter 3 aimed to delve further into the transcriptome network utilized in planta by applying a specific targeted approach, via reverse genetics of select transcription factor genes, to assign physiological roles to genes in planta. In conjunction with the findings from Chapter 2, genes were chosen for further study from a Tn-Seq study (Duong, Jensen, & Stevens, 2018).

Analysis of corresponding gene deletion and complementation strains through in planta and in vitro assays revealed IscR impacts colonization of P. stewartii in planta, both NsrR and IscR serve as transcriptional regulators of other genes, and Lrp impacts virulence, perhaps through involvement with capsule synthesis and motility. Although there is clear evidence that NsrR and 136

IscR regulate other genes during in planta growth of the bacterium, to ascertain the entire regulatory network and the potential cross-talk between different regulons including definitive connections with other known P. stewartii pathways, full RNA-Seq studies of the NsrR and IscR regulons are warranted. Not only could this reveal novel regulon targets for each transcription factor, but the regulated genes could then be tested for direct binding via electrophoretic mobility shift assays (EMSA) and DNase I protection assays (footprinting) to understand the downstream regulatory cascade necessary for survival of P. stewartii in planta.

One confounding problem when studying gene expression of bacteria growing in the xylem is precisely measuring their rate of growth. It would be interesting from a temporal perspective to see exactly when these transcription factors or their downstream regulons are expressed, whether just in the xylem or earlier during infection. This may be accomplished by sampling at an earlier infection timepoint for transcriptome analysis (i.e., RNA-Seq for bacteria in the apoplast), or completing a temporal study using transcriptional fusions that may also show plant tissue localization in conjunction with the expression in real time. For the transcription factors that did not show a phenotype for the in planta assays, it is possible these are more critical at a time point that was not accurately assayed during the studies described here.

A very intriguing finding was the reduced ability for the lrp mutant to cause disease, and the subsequent observed reduction in the strain’s capsule and motility phenotypes. However, it was also seen that the complementation strain was unable to restore wild-type phenotypic levels in these qualitative assays. Therefore, before investing more effort to establish the role of lrp further within P. stewartii, it would be critical to first genotype the lrp mutant. This could be accomplished through PCR to screen known unstable areas within the chromosome (Duong &

Stevens, 2017), or through whole genome sequencing to look for secondary mutation sites. In 137

the event no additional chromosomal modifications can be found in the deletion or complementation strain, it is possible a reconstruction of the complementation strain should be performed to increase promoter size or using an alternative approach. Perhaps complementation back into the native site would be appropriate to ensure proper regulation of the gene.

Surprisingly, many of the results for the genes tested from Chapter 3 were not consistent with the findings from the previously published Tn-Seq paper (Duong, Jensen, & Stevens, 2018).

For future studies, an additional approach may be warranted that uses a comparative genomics analysis. By doing this with other bacterial plant pathogens, especially those capable of causing wilt disease, and phylogenetically more closely related Pantoea species that are unable to cause disease in plants, additional gene targets for future work could be elucidated. Combining this approach with the Tn-Seq and RNA-Seq data available would strengthen the gene selection choices for understanding the roles of additional genes in the P. stewartii genome towards in planta growth.

Chapter 4 was focused on a growing area of research contributing toward biofuel sustainability. These findings demonstrated the ability of bacteria to grow on the syrup substrate, with the goal of using that biomass as a fishmeal supplement. However, application studies would need to confirm that these strains would be suitable for this use. First, cultivation of this biomass on an industrial scale may reveal changes in yield and growth rate of the bacterial culture. Implementing the bacteria as a feed supplement would also require trials with the fish, including their willingness to consume the modified feed, the potential impact these species could have on the native microbiome, and ultimately the impact on fish physiology, health, and resulting palatability. Finally, although the combinations tested in the study were not confirmed to have improved synergistic effects, to ensure a robust system it would be a potential benefit to 138

test additional strains in conjunction with the Bacillus species chosen to find an advantageous combination.

The analyses described in this dissertation were performed with the motivation to improve upon the fundamental knowledgebase for scientists working within plant and microbial systems. By determining the mechanism by which P. stewartii colonizes and causes disease in the plant host, these findings could be expanded to other host-pathogen systems and could reveal intervention targets for disease mitigation. For the study of the ethanol production byproduct, repurposing resources for improving sustainability is a worthy endeavor that could benefit a broad range of industrial and agricultural practices to the benefit of society.

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References Doblas-Ibáñez, P, Deng, K, Vasquez, MF, Giese, L, Cobine, PA, Kolkman, JM, King, H, Jamann, TM, Balint-Kurti, P, De La Fuente, L, Nelson, RJ, Mackaey, D, & Smith LG. 2019. Dominant, heritable resistance to Stewart’s wilt in maize is associated with an enhanced vascular defense response to infection with Pantoea stewartii. Molecular Plant-Microbe Interactions 32(12): 1581-1597. https://doi.org/10.1094/MPMI-05-19- 0129-R Duong DA, Stevens AM. 2017. Integrated downstream regulation by the quorum-sensing controlled transcription factors LrhA and RcsA impacts phenotypic outputs associated with virulence in the phytopathogen Pantoea stewartii subsp. stewartii. PeerJ. 5:e4145. doi:10.7717/peerj.4145 Duong, DA, Jensen, RV, & Stevens, AM. 2018. Discovery of Pantoea stewartii ssp. stewartii genes important for survival in corn xylem through a Tn-Seq analysis. Molecular Plant Pathology 19(8):1929–1941. https://doi.org/10.1111/mpp.12669 Pataky, JK. 2004. Stewart's wilt of corn. The Plant Health Instructor. DOI:10.1094/PHI-I-2004- 0113-01 Roper, MC. 2011. Pantoea stewartii subsp. stewartii: lessons learned from a xylem-dwelling pathogen of sweet corn. Molecular Plant Pathology 12(7):628-637.

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APPENDIX A Chapter 2 Supplementary Information

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Table S2.1. Strains and plasmids used in this study Strain/ Plasmid Descriptiona E. coli Top10 Competent strain P. stewartii DC283 Wild-type strain, Nalr p-GEM-T Cloning vector, Ampr p-GEM-T+ CKS_3263 CKS_3263 coding region for cloning inserted into p-GEM-T vector p-GEM-T+ CKS_3793 CKS_3793 coding region for cloning inserted into p-GEM-T vector (Kernell Burke et al., 2015) p-GEM-T+ rmf rmf coding region for cloning inserted into p-GEM-T vector p-GEM-T+ bfr bfr coding region for cloning inserted into p-GEM-T vector p-GEM-T+ CKS_3570 CKS_3570 coding region for cloning inserted into p-GEM-T vector p-GEM-T+ aceB aceB coding region for cloning inserted into p-GEM-T vector p-GEM-T+ yeaG yeaG coding region for cloning inserted into p-GEM-T vector p-GEM-T+ CKS_2505 CKS_2505 coding region for cloning inserted into p-GEM-T vector p-GEM-T+ hupA hupA coding region for cloning inserted into p-GEM-T vector p-GEM-T+ CKS_4537 CKS_4537 coding region for cloning inserted into p-GEM-T vector p-GEM-T+ recF recF coding region for cloning inserted into p-GEM-T vector p-GEM-T+ atpD atpD coding region for cloning inserted into p-GEM-T vector p-GEM-T+ gyrB gyrB coding region for cloning inserted into p-GEM-T vector aNalr = nalidixic acid resistance, Ampr = ampicillin resistance

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Table S2.2. RNA-Seq data of differentially expressed genes between the in planta culture and the pre- inoculum in vitro liquid culturea

DESeq Locus RPM Fold Fold DESeq Tag Annotation Regulation Regulation padj CKS_4725 hypothetical protein A 65.18 32.69 3.68E-21 CKS_3692 hypothetical protein A 56.09 30.15 6.34E-24 CKS_3263 HrpA family pilus protein A 52.64 34.17 1.09E-85 CKS_5750 acid shock protein A 49.49 10.42 2.36E-04 CKS_2320 putative alkanal monooxygenase A 38.39 22.22 4.30E-24 CKS_3793 cytochrome d ubiquinol oxidase subunit I A 36.48 23.81 2.78E-59 CKS_3039 hypothetical protein A 35.53 22.76 4.44E-39 periplasmic-binding component of an ABC CKS_3355 superfamily ribose transporter A 33.06 20.26 1.17E-26 CKS_2883 predicted dethiobiotin synthetase A 31.33 19.41 8.43E-28 CKS_3407 phosphoenolpyruvate synthase A 30.76 19.58 2.67E-36 CKS_2379 nudix hydrolase A 30.68 18.88 4.68E-27 periplasmic-binding component of an ABC CKS_3537 superfamily L-arabinose transporter A 29.41 19.22 2.16E-56 CKS_4032 ribosome modulation factor A 28.23 17.29 3.37E-21 CKS_3794 cytochrome d terminal oxidase subunit II A 28.18 18.52 9.78E-51 ATP-binding component of an ABC CKS_1610 superfamily taurine transporter A 27.50 12.87 2.66E-08 bacterioferritin iron storage and detoxification CKS_1591 protein A 27.19 17.89 1.27E-50 CKS_2202 hypothetical protein A 27.12 16.70 5.90E-24 fasciclin-like repeat-containing CKS_2922 secreted/surface protein A 26.37 17.22 4.33E-40 CKS_3795 membrane-bound protein A 25.59 16.89 1.32E-45 CKS_3356 hypothetical protein A 24.51 14.80 4.89E-18 CKS_2442 aldehyde dehydrogenase B A 23.70 15.58 2.52E-37 CKS_4281 hypothetical protein A 23.51 13.17 9.43E-13 CKS_0668 predicted quinol oxidase subunit A 22.60 13.69 8.70E-19 CKS_2380 hypothetical protein A 22.17 13.82 4.61E-22 CKS_3948 predicted inner membrane protein A 21.90 14.35 1.16E-33 ATP-binding component of an ABC CKS_0801 superfamily predicted amino-acid transporter A 21.75 14.24 2.44E-30 CKS_0368 L-lactate dehydrogenase FMN-linked A 21.46 11.94 1.52E-10 CKS_0515 predicted dioxygenase A 20.57 12.70 1.38E-21 membrane component of an ABC superfamily CKS_1609 taurine transporter A 20.25 10.23 9.28E-08 143

CKS_2375 hypothetical protein A 20.00 11.57 3.76E-12 CKS_3270 HrpF family protein A 19.63 13.29 1.80E-62 CKS_3570 AraC family transcriptional regulator A 19.33 12.66 2.19E-33 CKS_3281 HopAM1-1 family type III effector A 19.28 12.43 9.41E-29 CKS_3513 oxidoreductase domain protein A 18.47 12.03 4.38E-32 CKS_2985 hypothetical protein A 18.01 10.46 2.81E-11 CKS_3320 GGDEF domain protein A 17.30 11.00 1.08E-16 CKS_1103 stress-induced protein A 16.70 10.85 4.87E-20 CKS_4575 secretion system chaperone A 16.57 10.59 5.67E-24 CKS_3796 YbgE family protein A 15.82 10.59 8.32E-34 permease component of an ABC superfamily CKS_4955 transporter A 15.79 9.96 1.37E-17 CKS_4830 Amidohydrolase A 15.67 10.21 8.43E-28 CKS_1508 hypothetical protein A 15.52 10.12 1.41E-22 CKS_2384 hypothetical protein A 15.52 9.17 6.35E-10 CKS_3767 hypothetical protein A 15.27 9.96 8.32E-23 CKS_4657 malate synthase A A 15.20 9.76 2.40E-20 CKS_3265 HrpB family protein A 14.99 9.94 3.73E-28 membrane component of an ABC superfamily CKS_2186 methyl-galactoside transporter A 14.99 10.08 1.48E-36 CKS_0687 predicted pirin-related protein A 14.88 9.14 1.07E-13 CKS_3512 oxidoreductase domain protein A 14.69 9.79 2.18E-27 CKS_3503 methyl-accepting chemotaxis protein A 14.60 9.70 1.03E-23 CKS_4279 hypothetical protein A 14.60 9.19 3.75E-15 CKS_2376 hypothetical protein A 14.52 9.23 6.34E-15 CKS_3267 type III secretion system lipoprotein A 14.32 9.45 1.90E-26 CKS_0560 hypothetical protein A 14.07 9.65 3.62E-55 CKS_3851 8-amino-7-oxononanoate synthase A 13.99 9.32 2.23E-28 CKS_5439 hypothetical protein A 13.72 8.61 1.52E-15 CKS_3275 HrpN family hypersensitivity reaction elicitor A 13.62 9.05 3.83E-24 CKS_4573 hypothetical protein A 13.54 8.90 7.83E-25 CKS_2772 anthranilate phosphoribosyltransferase A 13.32 8.72 3.88E-24 ATP-binding component of an ABC CKS_2488 superfamily sugar transporter A 13.29 8.95 1.28E-30 putative MFS superfamily benzoate CKS_3579 transporter A 13.24 8.98 1.27E-37 periplasmic-binding component of an ABC CKS_1611 superfamily taurine transporter A 13.12 4.67 1.79E-02 putative type III secretion system effector CKS_4574 protein A 12.95 8.59 1.42E-27 CKS_0908 Pirin A 12.78 8.25 3.58E-18

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conserved inner membrane protein involved in CKS_4719 acetate transport A 12.70 7.88 7.29E-11 CKS_2366 hypothetical protein A 12.63 7.83 6.07E-10 CKS_2378 hypothetical protein A 12.38 8.05 3.25E-16 CKS_0370 hypothetical protein A 12.16 8.22 3.08E-32 CKS_0371 hypothetical protein A 12.05 8.24 1.14E-41 CKS_3850 biotin synthase A 11.91 7.96 9.41E-29 CKS_2371 hypothetical protein A 11.84 7.61 6.83E-14 CKS_3319 predicted inner membrane protein A 11.65 7.58 8.54E-13 CKS_2373 hypothetical protein A 11.65 7.53 2.41E-13 CKS_2372 putative transcriptional regulator A 11.54 7.42 7.14E-13 CKS_4954 Aryldialkylphosphatase A 11.52 7.64 7.24E-20 CKS_0204 ammonium transporter A 11.47 4.16 3.00E-02 gamma-aminobutyrate:alpha-ketoglutarate CKS_2504 aminotransferase A 11.42 7.63 1.32E-19 CKS_3539 L-arabinose transport system permease protein A 11.35 7.45 1.33E-16 CKS_0380 hypothetical protein A 11.33 6.65 7.39E-07 CKS_2984 hypothetical protein A 11.32 7.17 2.23E-12 CKS_4282 hypothetical protein A 11.32 7.35 1.61E-15 CKS_4280 hypothetical protein A 11.29 7.67 8.75E-34 CKS_3715 hypothetical protein A 11.24 7.31 5.57E-12 putative type III secretion system apparatus CKS_4585 protein A 11.21 7.66 2.11E-40 ATP-binding component of an ABC CKS_3538 superfamily L-arabinose transporter A 11.16 7.55 8.94E-27 CKS_1361 PLP-binding diaminopimelate decarboxylase A 11.05 7.23 1.52E-13 CKS_1282 sulfate adenylyltransferase subunit 1 A 11.03 6.86 8.16E-11 CKS_4249 putative membrane protein A 10.97 6.97 3.08E-12 CKS_0390 hypothetical protein A 10.95 7.25 9.20E-16 CKS_2383 hypothetical protein A 10.95 6.75 6.83E-09 3-isopropylmalate isomerase subunit CKS_5150 dehydratase component A 10.85 7.27 6.58E-21 CKS_0948 mannonate hydrolase A 10.84 7.12 3.80E-15 membrane component of an ABC superfamily CKS_0963 D-ala-D-ala transporter A 10.71 7.16 1.15E-23 CKS_4658 isocitrate lyase A 10.56 6.78 1.11E-11 pyridine nucleotide transhydrogenase beta CKS_2855 subunit A 10.52 6.81 6.90E-11 pyridine nucleotide transhydrogenase alpha CKS_2854 subunit A 10.46 6.81 4.87E-12 CKS_4572 hypothetical protein A 10.45 6.69 1.37E-11 CKS_2773 component I of anthranilate synthase A 10.21 6.76 1.15E-19

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putative type III secretion system effector CKS_4576 protein A 10.12 6.89 2.44E-32 CKS_1281 adenosine 5'-phosphosulfate kinase A 10.10 6.42 6.74E-11 CKS_4283 hypothetical protein A 10.09 6.63 1.61E-13 CKS_2381 hypothetical protein A 10.07 6.74 1.19E-19 mannose-specific enzyme IID component of CKS_2679 PTS A 9.99 6.67 1.64E-15 CKS_4634 mutator family transposase A 9.90 6.43 8.37E-13 CKS_3535 L-arabinose isomerase A 9.86 6.53 5.70E-17 CKS_4586 secretion system apparatus protein A 9.82 6.73 2.84E-41 CKS_4953 hypothetical protein A 9.78 6.45 2.05E-15 alkanesulfonate monooxygenase FMNH(2)- CKS_4019 dependent A 9.66 5.89 3.45E-07 CKS_0367 DNA-binding transcriptional repressor A 9.58 5.65 4.71E-05 mannose-specific enzyme IIC component of CKS_2680 PTS A 9.47 6.26 1.01E-12 CKS_3254 HrpO family protein A 9.41 6.04 5.24E-10 drug/metabolite transporter (DMT) CKS_1762 superfamily permease A 9.37 6.12 1.67E-13 CKS_3623 hypothetical protein A 9.35 6.38 5.97E-29 CKS_4829 integral membrane protein A 9.31 5.85 3.52E-09 CKS_2321 putative cytoplasmic protein A 9.30 5.45 1.95E-05 CKS_5511 hypothetical protein A 9.29 5.42 9.29E-06 CKS_1541 IMP dehydrogenase A 9.27 6.30 3.56E-25 periplasmic-binding component of an ABC CKS_0962 superfamily D-ala-D-a la transporter A 9.26 6.34 1.61E-31 CKS_3354 short-chain dehydrogenase/reductase A 9.22 6.13 2.40E-13 CKS_3597 Catalase A 9.20 5.96 6.37E-13 type III secretion system inner membrane CKS_4597 protein A 9.20 5.93 1.12E-10 CKS_3619 hypothetical protein A 9.17 6.21 1.21E-18 CKS_2495 FAD dependent oxidoreductase A 9.13 5.89 3.29E-10 CKS_4596 hypothetical protein A 9.09 6.10 4.87E-20 permease component of an ABC superfamily CKS_2489 ribose/xylose/arabinose/galactoside transporter A 9.08 6.14 3.49E-18 CKS_1283 sulfate adenylyltransferase subunit 2 A 9.08 5.60 1.54E-06 CKS_5454 putative cell wall-associated hydrolase A 9.07 6.16 3.11E-19 CKS_3982 predicted transporter A 9.06 6.02 2.82E-19 CKS_4701 hypothetical protein A 9.04 5.90 4.93E-12 CKS_2765 hypothetical protein A 8.99 6.06 5.43E-20 CKS_3268 HrpD family protein A 8.97 5.93 2.69E-13 CKS_4331 PTS system cellobiose-specific IIB component A 8.90 5.75 5.40E-09

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enoyl-CoA hydratase/3-hydroxyacyl-CoA CKS_2016 dehydrogenase A 8.89 5.97 2.11E-13 putative formate dehydrogenase CKS_2806 oxidoreductase protein A 8.84 5.29 2.87E-05 CKS_4653 periplasmic binding protein A 8.83 5.88 2.77E-19 anaerobic ribonucleoside-triphosphate CKS_4923 reductase A 8.78 5.97 1.16E-29 CKS_4463 sn-glycerol-3-phosphate transporter A 8.76 5.77 6.04E-10 CKS_4583 secretion system apparatus protein A 8.69 5.91 4.88E-28 CKS_0940 myo-inositol 2-dehydrogenase A 8.68 5.73 3.28E-12 CKS_4009 uncharacterized DUF882 family protein A 8.65 5.94 5.86E-27 CKS_2222 predicted peptidase A 8.62 5.31 2.29E-07 CKS_2800 L-ribulose-5-phosphate 4-epimerase A 8.51 5.74 1.58E-16 CKS_2792 aconitate hydratase 1 A 8.45 5.73 1.16E-22 CKS_4024 dihydro-orotate oxidase FMN-linked A 8.43 5.64 4.20E-15 CKS_2150 hypothetical protein A 8.42 5.63 1.85E-17 membrane component of an ABC superfamily CKS_3201 polar amino acid transporter A 8.37 5.60 2.31E-12 CKS_2368 gp55 family protein A 8.35 5.53 5.56E-11 CKS_0451 hypothetical protein A 8.27 5.36 2.79E-10 CKS_2385 hypothetical protein A 8.27 5.48 2.65E-11 CKS_4509 hypothetical protein A 8.25 5.54 3.66E-12 CKS_2714 serine-protein kinase A 8.22 5.66 1.38E-29 HrcJ family type III secretion system CKS_3258 component protein A 8.21 5.60 5.17E-23 CKS_0452 putative peptidase A 8.19 5.57 1.41E-21 CKS_2972 hypothetical protein A 8.19 5.44 2.51E-12 23-diketo-L-gulonate dehydrogenase NADH- CKS_4763 dependent A 8.17 5.29 2.45E-10 CKS_3703 L-fucose operon activator A 8.13 4.99 3.78E-05 CKS_4588 type III secretion system apparatus protein A 8.13 5.48 5.17E-16 CKS_3984 pyruvate formate-lyase A 8.11 5.53 1.15E-18 CKS_2370 Heptosyltransferase A 8.09 5.25 1.25E-08 CKS_4579 hypothetical protein A 8.08 5.40 7.10E-16 CKS_4767 3-keto-L-gulonate 6-phosphate decarboxylase A 8.02 5.05 8.75E-07 medium-long-chain fatty acyl-CoA CKS_0306 dehydrogenase A 8.01 5.39 9.63E-13 CKS_3858 molybdopterin biosynthesis protein A A 8.01 5.48 3.82E-23 CKS_2367 Chitinase A 8.00 5.41 7.63E-15 CKS_0961 D-ala-D-ala dipeptidase Zn-dependent A 7.99 5.44 3.81E-17 CKS_4272 putative DNA modification methylase A 7.97 5.38 6.19E-16

147

ATP-binding component of an ABC superfamily galactose/methyl galactoside CKS_2185 transporter A 7.93 5.36 2.98E-12 CKS_0468 hypothetical protein A 7.91 5.35 2.78E-15 CKS_5152 2-isopropylmalate synthase A 7.89 5.43 1.25E-28 CKS_3446 superoxide dismutase Cu Zn A 7.84 5.37 9.71E-18 cytosine/purine/uracil/thiamine/allantoin CKS_0266 permease family protein A 7.83 4.16 4.59E-03 CKS_5467 OspG family protein A 7.80 5.10 9.66E-09 membrane component of an ABC superfamily CKS_0964 D-ala-D-ala transporter A 7.76 5.13 7.66E-13 CKS_2106 hypothetical protein A 7.75 4.92 1.85E-05 methyl-accepting chemotaxis sensory CKS_3278 transducer A 7.67 5.21 1.82E-19 CKS_3038 iron-uptake factor A 7.66 5.17 1.31E-12 CKS_3837 galactose-1-epimerase (mutarotase) A 7.65 5.20 2.68E-18 membrane component of an ABC superfamily CKS_3739 glutamate and aspartate transporter A 7.62 5.21 2.63E-16 CKS_2472 hypothetical protein A 7.62 5.23 1.85E-17 RND multidrug efflux membrane fusion CKS_3569 protein A 7.61 5.03 8.62E-11 putative type III secretion system apparatus CKS_4584 protein A 7.59 5.19 5.90E-24 CKS_1750 N-acetylmuramoyl-L-alanine amidase A 7.58 5.00 1.02E-08 CKS_3852 malonyl-CoA methyltransferase A 7.57 5.03 4.35E-11 putative mannosyl-3-phosphoglycerate CKS_2563 phosphatase A 7.53 5.07 1.42E-13 DNA-binding transcriptional dual regulator of CKS_2490 nitrogen assimilation A 7.52 4.36 9.02E-04 CKS_4021 NAD(P)H-dependent FMN reductase A 7.50 4.29 1.22E-03 putative permease component of an ABC CKS_0288 superfamily amino acid transporter A 7.50 4.31 9.38E-04 CKS_1697 divalent cation transport protein A 7.49 5.15 1.09E-25 CKS_5453 hypothetical protein A 7.48 5.00 2.57E-09 CKS_0429 hypothetical protein A 7.47 5.07 3.28E-18 CKS_4333 beta-glucosidase A 7.43 5.01 6.13E-14 CKS_2635 hypothetical protein A 7.37 4.59 9.39E-06 CKS_2586 putative adenine methylase A 7.35 4.25 4.83E-04 GAF domain/GGDEF domain/EAL domain CKS_3094 protein A 7.34 4.65 5.52E-07 CKS_3527 stress-induced protein A 7.31 4.94 1.05E-16 periplasmic substrate-binding component of an CKS_4761 ABC superfamily ribose transporter A 7.30 4.96 6.63E-21

148

permease component of an ABC superfamily CKS_3738 glutamate/aspartate transporter A 7.29 4.96 9.17E-20 CKS_3534 membrane-fusion protein A 7.27 4.55 5.69E-06 CKS_3859 molybdopterin biosynthesis protein B A 7.26 4.92 3.78E-14 putative ATP-binding component of an ABC CKS_0290 superfamily amino acid transporter A 7.26 4.30 3.38E-04 CKS_4952 acetylornithine deacetylase A 7.23 4.80 4.37E-11 CKS_4273 hypothetical protein A 7.21 4.77 4.08E-10 CKS_2803 hypothetical protein A 7.20 4.91 2.24E-15 CKS_4654 hypothetical protein A 7.19 4.84 2.37E-17 CKS_3146 dihydrodipicolinate synthase A 7.18 4.71 3.98E-08 CKS_1233 protein disaggregation chaperone A 7.17 4.57 5.59E-07 CKS_1882 hypothetical protein A 7.16 4.85 1.33E-15 CKS_2441 Methyltransferase A 7.15 4.59 3.46E-07 CKS_2493 aldehyde dehydrogenase A 7.14 4.61 3.24E-07 CKS_3607 tail fiber assembly protein A 7.03 4.72 1.13E-10 CKS_2924 metal-activated pyridoxal enzyme A 7.02 4.72 2.70E-11 CKS_2808 hypothetical protein A 6.97 4.68 6.71E-13 CKS_2377 hypothetical protein A 6.96 4.74 3.08E-13 CKS_1834 glycerol dehydrogenase A 6.95 4.77 1.01E-19 CKS_2713 uncharacterized DUF444 family protein A 6.93 4.78 1.33E-20 succinate-semialdehyde dehydrogenase I CKS_2492 NADP-dependent A 6.92 4.67 1.02E-11 indole-3-glycerol-phosphate synthase/anthranilate CKS_2771 phosphoribosyltransferase A 6.91 4.69 1.51E-18 CKS_3460 hypothetical protein A 6.90 4.60 1.05E-07 CKS_2301 gamma-Glu-putrescine synthase A 6.90 4.74 9.14E-16 CKS_2205 DEAD/DEAH box helicase domain protein A 6.84 4.26 7.01E-05 CKS_2364 hypothetical protein A 6.81 4.66 1.32E-12 CKS_2487 putative periplasmic binding protein A 6.80 4.57 5.74E-09 CKS_4915 putative collagenase-like peptidase A 6.78 4.57 7.98E-14 permease component of an ABC superfamily CKS_2525 ribose transporter A 6.77 4.43 2.29E-07 CKS_4056 WrbA family flavoprotein A 6.71 4.63 2.85E-21 CKS_0338 glycerol dehydrogenase NAD A 6.66 4.51 8.57E-10 CKS_0912 hypothetical protein A 6.60 4.44 1.13E-10 CKS_5151 3-isopropylmalate dehydrogenase A 6.59 4.54 1.81E-19 CKS_2642 hypothetical protein A 6.57 4.40 3.60E-10 CKS_3276 putative avirulence protein A 6.56 4.50 3.73E-19 aspartate carbamoyltransferase catalytic CKS_4940 subunit A 6.52 4.48 3.07E-24

149

CKS_2983 phytochelatin synthase A 6.41 4.37 1.86E-16 permease component of an ABC superfamily CKS_2062 spermidine/putrescine transporter A 6.36 4.32 1.49E-14 periplasmic-binding component of an ABC CKS_4020 superfamily alkanesulfonate transporter A 6.35 3.86 8.08E-04 putative binding periplasmic protein of ABC CKS_4958 transporter A 6.34 4.34 1.67E-12 CKS_2386 hypothetical protein A 6.34 4.26 1.15E-08 CKS_3621 aldo-keto reductase A 6.32 4.26 7.76E-10 CKS_0379 hypothetical protein A 6.30 4.18 4.91E-07 putative formate dehydrogenase CKS_3519 oxidoreductase protein A 6.27 4.28 1.42E-15 CKS_2413 uncharacterized DUF883 family protein A 6.22 4.08 5.38E-06 CKS_0657 altronate hydrolase A 6.21 4.23 7.13E-13 CKS_4593 hypothetical protein A 6.20 4.24 3.24E-16 CKS_1037 predicted transporter A 6.19 4.27 4.13E-15 CKS_1859 hypothetical protein A 6.18 4.20 3.42E-11 CKS_4960 hypothetical protein A 6.17 4.25 2.30E-18 CKS_3620 hypothetical protein A 6.17 4.18 5.42E-10 long-chain fatty acid outer membrane CKS_2012 transporter A 6.16 4.24 1.03E-15 CKS_4762 Gluconolactonase A 6.13 4.21 3.42E-18 periplasmic substrate binding component of an CKS_3702 ABC superfamily sugar transporter A 6.12 3.93 5.66E-05 CKS_1706 phosphoribosylaminoimidazole synthetase A 6.12 4.22 1.56E-14 inner membrane iron-sulfur protein in SoxR- CKS_3489 reducing complex A 6.12 4.21 2.64E-20 CKS_4340 heat shock chaperone A 6.04 3.82 9.88E-05 serine--pyruvate aminotransferase / L- CKS_0291 alanine:glyoxylate aminotransferase A 6.03 3.78 1.31E-04 CKS_5149 3-isopropylmalate isomerase subunit A 6.02 4.12 2.87E-12 type III secretion system outermembrane pore CKS_3271 forming protein A 5.99 4.09 3.58E-14 CKS_3206 putative amidohydrolase A 5.97 3.54 3.74E-03 CKS_4275 hypothetical protein A 5.96 3.87 1.32E-05 CKS_3622 pyruvate/alpha-keto-acid decarboxylase A 5.95 4.09 1.21E-19 CKS_1696 magnesium transporter A 5.91 4.07 9.07E-15 CKS_4764 hypothetical protein A 5.90 3.89 1.01E-06 permease component of an ABC superfamily CKS_4760 ribose transporter A 5.89 4.04 1.99E-13 CKS_5026 hypothetical protein A 5.89 3.48 3.32E-03 CKS_2921 putative RNA polymerase sigma factor A 5.88 4.04 1.12E-12 CKS_3540 DNA-binding transcriptional dual regulator A 5.88 4.00 1.51E-08 150

CKS_4914 predicted protease A 5.87 4.04 3.01E-16 CKS_3983 pyruvate formate lyase activating enzyme 1 A 5.86 4.03 2.13E-12 CKS_1698 hypothetical protein A 5.86 4.04 5.43E-14 CKS_4484 3-ketoacyl-CoA thiolase (thiolase I) A 5.85 4.03 5.09E-19 CKS_3202 ABC superfamily transporter A 5.84 3.98 1.49E-10 CKS_3860 molybdopterin biosynthesis protein C A 5.84 3.99 3.84E-13 CKS_0941 inosose dehydratase A 5.83 3.93 2.14E-08 CKS_4376 putative transcriptional regulator A 5.81 3.95 6.14E-08 CKS_3516 oligogalacturonide transporter A 5.79 3.94 5.00E-10 CKS_4718 acetate permease A 5.78 3.89 2.23E-08 ATP-binding component of an ABC CKS_0965 superfamily D-ala-D-ala transporter A 5.78 3.97 6.69E-15 CKS_2401 hypothetical protein A 5.77 3.85 1.10E-06 periplasmic-binding component of an ABC CKS_0922 superfamily leucine transporter A 5.76 3.95 1.85E-13 ATP-binding component of an ABC CKS_4759 superfamily ribose transporter A 5.76 3.96 9.04E-14 CKS_4571 virulence protein A 5.73 3.94 5.87E-15 CKS_2641 phage baseplate assembly protein V A 5.67 3.82 4.58E-10 CKS_3471 malto-oligosyltrehalose trehalohydrolase A 5.64 3.87 6.02E-11 putative formate dehydrogenase CKS_3520 oxidoreductase protein A 5.64 3.89 1.61E-15 putative type III secretion system effector CKS_4577 protein A 5.63 3.86 6.00E-17 CKS_3241 amidinotransferase family protein A 5.60 3.74 8.90E-09 CKS_2588 hypothetical protein A 5.59 3.27 7.97E-03 CKS_2640 hypothetical protein A 5.58 3.77 8.40E-11 CKS_3150 predicted mannonate dehydrogenase A 5.57 3.77 6.32E-11 CKS_3853 dethiobiotin synthetase A 5.56 3.78 4.02E-09 CKS_5373 mobilization protein A 5.55 3.83 7.52E-14 CKS_0791 predicted reductase A 5.54 3.73 1.49E-07 CKS_0403 hypothetical protein A 5.50 3.59 4.26E-06 CKS_4569 secreted effector protein A 5.49 3.79 8.20E-16 CKS_0376 putative phage transposase A 5.45 3.74 9.64E-13 CKS_4010 predicted metal-binding enzyme A 5.43 3.72 3.18E-16 CKS_2496 extracellular solute-binding protein family 5 A 5.39 3.63 4.24E-08 CKS_2880 predicted transporter A 5.36 3.67 2.88E-09 CKS_2398 hypothetical protein A 5.35 3.46 4.35E-04 CKS_3219 cellulose synthase (UDP-forming) A 5.34 3.60 2.44E-07 CKS_3441 putative TetR family transcriptional regulator A 5.33 3.69 2.69E-15 CKS_4144 hypothetical protein A 5.32 3.66 1.26E-09

151

anaerobic ribonucleotide reductase activating CKS_4922 protein A 5.31 3.66 2.90E-15 CKS_4247 putative alpha/beta hydrolase A 5.30 3.63 5.46E-08 CKS_2299 DNA-binding transcriptional repressor A 5.29 3.61 1.24E-09 CKS_2389 hypothetical protein A 5.28 3.63 9.02E-13 CKS_2587 hypothetical protein A 5.28 3.20 3.94E-03 CKS_3955 hypothetical protein A 5.27 3.55 2.22E-07 membrane component of an ABC superfamily CKS_4389 dipeptide transporter A 5.25 3.53 5.49E-07 inner membrane subunit of SoxR-reducing CKS_3490 complex A 5.24 3.62 5.40E-13 CKS_2387 hypothetical protein A 5.24 3.47 1.05E-05 CKS_5000 hypothetical protein A 5.23 3.53 9.25E-08 CKS_5834 hypothetical protein A 5.22 3.28 1.25E-03 CKS_0375 putative DNA-binding protein A 5.21 3.47 2.19E-05 nitric oxide dioxygenase/dihydropteridine CKS_1509 reductase 2 A 5.21 3.54 4.60E-08 CKS_3442 uncharacterized DUF1289 family protein A 5.18 3.53 5.29E-07 CKS_4594 hypothetical protein A 5.17 3.51 4.46E-10 CKS_4485 fatty acid oxidation complex subunit alpha A 5.17 3.57 2.63E-11 CKS_5438 hypothetical protein A 5.17 3.41 2.75E-06 CKS_1045 acetolactate synthase large subunit A 5.14 3.55 1.25E-12 glycine decarboxylase PLP-dependent subunit CKS_1384 (protein P) of glycine cleavage complex A 5.14 3.53 5.02E-18 periplasmic-binding component of an ABC CKS_2526 superfamily ribose transporter A 5.08 3.42 1.25E-05 ATP-binding component of an ABC CKS_0054 superfamily sulfate/thiosulfate transporter A 5.08 3.31 1.36E-04 CKS_3401 hypothetical protein A 5.07 3.51 4.26E-11 CKS_3242 nikkomycin biosynthesis domain protein A 5.07 3.46 1.23E-10 adenosylmethionine-8-amino-7-oxononanoate CKS_3849 aminotransferase A 5.05 3.47 2.29E-13 type III secretion system cytoplasmic ATP CKS_3255 synthase A 5.03 3.45 1.31E-11 putative permease component of an ABC CKS_0289 superfamily amino acid transporter A 5.03 3.04 1.09E-02 CKS_3536 L-ribulokinase A 5.02 3.38 8.23E-06 CKS_2308 hydroxypyruvate isomerase A 5.01 3.40 9.12E-07 CKS_2399 phage tail-like protein A 5.00 3.41 2.19E-08 CKS_4288 uncharacterized DUF1040 family protein A 5.00 3.42 8.18E-09 type III secretion system peptide export CKS_4523 protein A 4.98 3.43 4.98E-16

152

putative hybrid two-component system CKS_2523 regulatory protein A 4.98 3.39 9.48E-08 CKS_2540 IS66 family transposase A 4.97 3.38 2.26E-08 CKS_1538 hypothetical protein A 4.97 3.42 9.91E-09 CKS_2369 hypothetical protein A 4.96 3.30 1.81E-04 CKS_1867 putative ABC-type transport protein A 4.96 3.16 2.09E-03 DNA-binding transcriptional dual regulator CKS_1857 with FlhC A 4.96 3.39 2.34E-10 CKS_0881 uncharacterized DUF1471 family protein A 4.95 3.37 3.06E-05 CKS_5446 hypothetical protein A 4.94 3.41 4.60E-12 CKS_4800 predicted dehydrogenase A 4.94 3.33 2.70E-06 CKS_3243 hypothetical protein A 4.94 3.37 9.25E-11 CKS_4162 hypothetical protein A 4.93 3.19 1.13E-03 CKS_3021 putative NADH:flavin oxidoreductase A 4.92 3.36 1.57E-13 CKS_4712 hypothetical protein A 4.92 3.39 3.85E-12 CKS_2550 DgsA-binding anti-repressor A 4.91 3.34 1.69E-06 CKS_2920 hypothetical protein A 4.90 3.38 8.33E-10 CKS_4956 ABC transporter A 4.89 3.24 5.83E-04 CKS_2350 hypothetical protein A 4.85 3.26 2.72E-06 CKS_2804 putative carbon starvation protein A A 4.84 3.27 4.25E-05 CKS_3144 hypothetical protein A 4.83 3.25 4.53E-06 CKS_3826 PhoH family ATPase A 4.83 3.23 2.75E-06 CKS_0943 5-deoxy-glucuronate isomerase A 4.80 3.32 2.61E-10 CKS_2494 type II haloacid dehalogenase A 4.80 3.15 9.16E-04 membrane component of an ABC superfamily CKS_0921 leucine/isoleucine/valine transporter A 4.79 3.29 6.57E-09 CKS_4332 PTS system cellobiose-specific IIC component A 4.78 3.27 9.32E-09 CKS_0377 phage transposase A 4.76 3.17 1.09E-04 type III secretion system inner membrane CKS_3257 channel protein A 4.76 3.27 9.03E-11 ATP-binding component of an ABC CKS_4016 superfamily alkanesulfonate transporter A 4.76 3.10 6.53E-04 zinc-containing alcohol CKS_0640 dehydrogenase/quinone oxidoreductase A 4.76 3.29 7.87E-13 phosphoribosylglycinamide formyltransferase CKS_1811 2 A 4.76 3.29 6.96E-12 CKS_2361 DNA adenine methylase A 4.74 3.22 2.74E-07 CKS_4591 secretion system apparatus protein A 4.73 3.26 1.83E-15 CKS_2363 phage antitermination protein Q A 4.70 3.20 3.69E-06 CKS_1546 hypothetical protein A 4.68 3.22 1.45E-06 CKS_5025 phage-related protein A 4.68 2.82 1.62E-02 regulator of penicillin binding proteins and CKS_0221 beta lactamase transcription (morphogene) A 4.68 3.22 2.13E-10 153

CKS_5455 putative exported protein A 4.68 3.14 4.48E-04 CKS_3205 predicted monooxygenase A 4.64 2.87 1.15E-02 CKS_3273 HrpT family protein A 4.64 3.16 2.03E-07 putative type III secretion system ATP CKS_4592 synthase A 4.60 3.19 7.52E-14 CKS_2015 acetyl-CoA acetyltransferase A 4.59 3.16 2.12E-06 CKS_1835 hypothetical protein A 4.58 3.14 1.04E-11 CKS_5052 YaiA family protein A 4.57 3.12 2.42E-05 CKS_2644 hypothetical protein A 4.57 3.06 1.22E-05 CKS_1436 putative transposase A 4.57 3.12 1.11E-06 CKS_3386 hypothetical protein A 4.55 3.13 3.04E-07 CKS_3701 ABC superfamily transporter A 4.55 3.08 5.20E-05 ATP-binding component of an ABC CKS_2524 superfamily ribose transporter A 4.55 3.09 1.85E-06 CKS_4055 putative cytoplasmic protein A 4.54 3.11 5.07E-06 CKS_1044 acetolactate synthase small subunit A 4.54 3.10 3.78E-10 CKS_5349 putative exported protein A 4.53 3.05 3.21E-04 CKS_0960 putative RpiR family transcriptional regulator A 4.52 3.10 7.58E-06 CKS_5754 hypothetical protein A 4.51 2.75 1.62E-02 CKS_5332 hypothetical protein A 4.51 3.03 7.86E-06 CKS_2589 phage-related protein A 4.50 2.73 1.91E-02 CKS_2306 uncharacterized DUF1537 family protein A 4.50 3.05 1.91E-04 CKS_1516 inositol monophosphatase A 4.50 3.03 7.45E-08 CKS_4567 secretion system regulatory protein A 4.50 3.08 6.49E-09 CKS_1463 NrdI family ribonucleotide reduction protein A 4.49 3.00 1.18E-03 CKS_0658 altronate oxidoreductase NAD-dependent A 4.49 3.10 2.21E-08 CKS_3968 cold shock protein A 4.48 3.05 2.64E-04 CKS_5389 putative exported protein A 4.47 3.01 6.53E-04 CKS_3939 putative transport system permease protein A 4.46 3.10 3.81E-11 CKS_1713 hypothetical protein A 4.46 3.02 2.53E-06 34-dihydroxy-2-butanone-4-phosphate CKS_0516 synthase A 4.46 3.06 8.45E-13 CKS_5413 hypothetical protein A 4.45 3.07 3.69E-08 CKS_1289 endoribonuclease L-PSP A 4.45 3.08 2.65E-13 CKS_3552 mannose-6-phosphate isomerase A 4.44 3.03 1.37E-06 CKS_4462 HD superfamily hydrolase A 4.42 3.02 4.41E-06 CKS_5393 putative exported protein A 4.42 2.97 1.25E-03 CKS_3315 Acyltransferase A 4.42 3.06 2.00E-12 membrane component of an ABC superfamily CKS_3844 molybdate transporter A 4.42 3.05 1.22E-12 CKS_3145 Na+/solute symporter A 4.41 3.02 6.31E-07 CKS_2307 predicted class II aldolase A 4.38 2.97 1.19E-05 154

CKS_2905 putative sugar transporter A 4.38 3.02 1.78E-07 CKS_4941 hypothetical protein A 4.36 3.01 4.89E-09 predicted universal stress (ethanol tolerance) CKS_0970 protein B A 4.35 2.98 7.34E-10 CKS_0773 uncharacterized DUF1471 family protein A 4.35 2.75 7.69E-03 CKS_3470 malto-oligosyltrehalose synthase A 4.34 2.99 2.20E-07 CKS_2947 maltose regulon periplasmic protein A 4.33 2.98 1.52E-06 CKS_2637 hypothetical protein A 4.33 2.96 4.31E-09 CKS_0887 maltodextrin phosphorylase A 4.33 3.00 4.44E-08 CKS_3252 type III secretion system protein A 4.33 2.99 5.82E-09 methyl-accepting chemotaxis sensory CKS_0598 transducer A 4.32 2.95 1.25E-07 CKS_5199 LysR family transcriptional regulator A 4.32 3.00 1.25E-14 CKS_3147 alcohol dehydrogenase A 4.30 2.91 3.78E-05 CKS_4192 dihydro-orotase A 4.27 2.97 3.60E-10 CKS_3143 hypothetical protein A 4.26 2.85 1.66E-04 CKS_3462 predicted FAD-binding phosphodiesterase A 4.26 2.96 1.27E-13 CKS_4768 predicted L-xylulose 5-phosphate 3-epimerase A 4.24 2.80 2.18E-04 CKS_2392 hypothetical protein A 4.23 2.92 3.94E-08 CKS_5356 putative outer membrane adhesion protein A 4.23 2.93 2.21E-13 membrane component of an ABC superfamily CKS_2050 histidine/lysine/arginine/ornithine transporter A 4.23 2.92 2.51E-08 CKS_2505 AsnC family transcriptional regulator A 4.20 2.89 1.45E-09 CKS_2017 phosphohistidine phosphatase A 4.19 2.91 2.52E-14 predicted oxidoreductase flavin:NADH CKS_3210 component A 4.18 2.64 1.51E-02 CKS_2105 large repetitive protein A 4.18 2.87 1.76E-05 branched chain amino acid transporter (LIV- CKS_5039 II) A 4.18 2.88 3.41E-12 CKS_5330 putative outer membrane adhesion protein A 4.18 2.87 1.21E-07 CKS_2590 hypothetical protein A 4.17 2.52 4.03E-02 binding-protein-dependent transport systems CKS_2498 inner membrane component A 4.17 2.71 5.60E-03 CKS_0285 gamma-glutamyltranspeptidase A 4.17 2.63 2.33E-02 CKS_1444 GroES family alcohol dehydrogenase A 4.16 2.89 1.90E-08 CKS_1664 anti-sigma factor A 4.15 2.86 7.41E-10 CKS_3277 putative avirulence protein A 4.14 2.86 1.11E-07 CKS_1861 trehalose-6-phosphate phosphatase A 4.14 2.88 4.40E-13 CKS_2228 multidrug efflux system subunit A A 4.12 2.83 8.24E-10 CKS_1517 tRNA:Cm32/Um32 methyltransferase A 4.12 2.82 2.97E-08 CKS_1464 glutaredoxin-like protein A 4.12 2.77 2.56E-03 CKS_4630 Cellulose A 4.09 2.79 3.83E-08

155

CKS_2706 PLP-binding alanine racemase 2 A 4.08 2.83 2.91E-07 CKS_4828 L-arabinolactonase A 4.08 2.76 1.92E-05 CKS_2629 phage tail sheath protein FI A 4.08 2.75 3.16E-06 thiamine pyrophosphate protein TPP binding CKS_2506 domain protein A 4.07 2.83 3.85E-09 CKS_3594 hypothetical protein A 4.06 2.80 5.78E-05 CKS_0600 hypothetical protein A 4.06 2.55 1.95E-02 CKS_4298 glutamine synthetase A 4.05 2.80 1.61E-09 CKS_1870 hydroxyacylglutathione hydrolase A 4.05 2.80 2.37E-06 CKS_3854 putative amino acid transporter A 4.04 2.63 5.31E-03 CKS_2899 salicylate hydroxylase A 4.04 2.59 1.14E-02 CKS_4580 hypothetical protein A 4.03 2.78 1.14E-09 CKS_0272 phytanoyl-CoA dioxygenase family protein A 4.01 2.68 1.11E-03 CKS_4983 GGDEF domain-containing protein A 4.00 2.78 1.09E-08 CKS_0016 50S ribosomal subunit protein L7/L12 R 4.02 5.63 1.24E-33 CKS_4368 superoxide dismutase Mn R 4.05 5.50 2.36E-19 peptidyl-prolyl cis-trans isomerase B CKS_0117 (rotamase B) R 4.08 5.65 2.64E-30 CKS_4123 putative bacteriophage protein R 4.09 5.66 8.22E-23 chorismate mutase I/cyclohexadienyl CKS_1240 dehydrogenase R 4.16 5.72 1.59E-17 CKS_4772 aerobactin siderophore receptor R 4.25 5.51 5.25E-11 CKS_0364 LysR family transcriptional regulator R 4.34 5.96 2.87E-26 CKS_4239 PTS system glucose-specific IICB component R 4.35 5.94 1.68E-25 CKS_4125 putative bacteriophage protein R 4.42 6.15 1.05E-26 CKS_4121 putative bacteriophage protein R 4.51 6.25 5.40E-26 HU DNA-binding transcriptional regulator CKS_0004 alpha subunit R 4.58 6.30 2.94E-30 CKS_3013 L-24-diaminobutyrate decarboxylase R 4.59 6.26 1.14E-14 CKS_4122 hypothetical protein R 4.69 6.39 3.07E-19 CKS_0095 hypothetical protein R 4.72 6.09 1.20E-08 CKS_4134 putative bacteriophage protein R 4.76 6.59 1.52E-25 CKS_0017 50S ribosomal subunit protein L10 R 4.80 6.68 1.54E-32 CKS_5198 dihydrolipoamide dehydrogenase R 4.82 6.71 1.23E-30 CKS_0744 30S ribosomal subunit protein S6 R 4.84 6.71 1.34E-25 CKS_4717 putative exported protein R 4.87 6.75 3.04E-28 CKS_5580 phage lysozyme R 4.89 5.12 2.09E-03 CKS_5259 protein chain elongation factor EF-Ts R 4.97 6.84 7.21E-21 CKS_4536 type III secretion system effector protein R 4.99 6.86 3.72E-30 CKS_4535 type III secretion system regulatory protein R 5.36 7.22 5.63E-19 CKS_0742 30S ribosomal subunit protein S18 R 5.52 7.61 3.50E-27 CKS_5601 hypothetical protein R 5.55 6.00 2.05E-04 156

CKS_4124 hypothetical protein R 5.71 7.77 5.69E-23 CKS_1527 nucleoside diphosphate kinase R 5.76 7.90 6.96E-32 CKS_4120 putative bacteriophage protein R 5.78 8.02 3.40E-41 CKS_4099 putative phage primase R 5.88 7.78 1.78E-13 CKS_4115 putative bacteriophage protein R 6.00 8.32 2.15E-40 CKS_4116 putative bacteriophage protein R 6.00 8.20 3.71E-27 CKS_5565 antiterminator Q R 6.06 5.68 2.13E-03 CKS_5581 hypothetical protein R 6.07 6.22 3.73E-04 CKS_0743 primosomal replication protein N R 6.09 8.40 4.73E-30 CKS_4117 putative bacteriophage protein R 6.11 8.39 1.49E-34 CKS_4137 hypothetical protein R 6.20 8.34 4.09E-19 CKS_4135 putative bacteriophage protein R 6.25 8.45 9.85E-21 CKS_4109 putative bacteriophage protein R 6.28 8.66 1.24E-34 CKS_0741 50S ribosomal subunit protein L9 R 6.33 8.73 1.54E-32 CKS_0094 hypothetical protein R 6.37 8.16 6.37E-12 CKS_5585 hypothetical protein R 6.56 6.92 8.70E-05 ADP-heptose--lipooligosaccharide CKS_1116 heptosyltransferase II R 6.57 9.01 3.81E-46 CKS_4113 hypothetical protein R 6.72 9.24 3.55E-34 CKS_5130 putative outer membrane protein R 6.83 8.87 1.16E-13 CKS_5588 hypothetical protein R 7.25 4.86 1.75E-02 CKS_4114 putative bacteriophage protein R 7.32 10.06 1.57E-44 CKS_0132 hypothetical protein R 7.44 9.91 9.62E-25 CKS_4119 putative bacteriophage protein R 7.55 10.37 7.44E-42 CKS_4531 type III secretion system apparatus protein R 7.65 10.55 3.77E-55 CKS_4091 hypothetical protein R 7.82 10.47 3.37E-23 CKS_4118 putative bacteriophage protein R 7.99 10.75 2.87E-31 CKS_4092 hypothetical protein R 8.20 11.12 8.61E-31 CKS_4136 putative bacteriophage tail protein R 8.32 11.27 6.23E-31 3-deoxy-D-arabino-heptulosonate-7-phosphate CKS_1241 synthase tyrosine-repressible R 8.70 10.58 8.06E-12 CKS_4538 type III secretion system apparatus protein R 8.80 11.97 2.47E-53 CKS_1225 hypothetical protein R 8.91 12.00 2.40E-39 CKS_4095 hypothetical protein R 9.89 13.00 1.33E-24 CKS_5564 Cro repressor R 10.16 6.62 2.75E-03 CKS_5584 membrane glycoprotein R 11.66 5.97 7.91E-03 CKS_4089 hypothetical protein R 13.42 17.32 1.10E-28 CKS_4090 hypothetical protein R 13.63 17.96 6.46E-36 CKS_5586 hypothetical protein R 14.19 11.73 3.52E-06 CKS_4088 hypothetical protein R 16.02 20.13 1.25E-28 CKS_4082 hypothetical protein R 16.02 19.51 1.72E-22 CKS_4093 CP4-57 family phage integrase R 16.35 20.69 9.41E-29 157

CKS_4081 hypothetical protein R 16.79 20.73 1.75E-25 CKS_4084 phage lysozyme R 17.69 21.56 2.40E-24 CKS_4537 type III secretion system effector protein R 18.27 23.86 8.75E-59 CKS_4085 hypothetical protein R 18.62 22.54 3.47E-24 CKS_5587 hypothetical protein R 21.31 10.26 1.96E-04 CKS_4083 hypothetical protein R 22.82 28.20 3.45E-33 CKS_4087 hypothetical protein R 25.57 31.54 3.41E-36 aA = activated in the in planta culture compared to the pre-inoculum liquid culture (lower in liquid culture), R = repressed in the in planta culture compared to the pre-inoculum liquid culture (higher in liquid culture)

158

Table S2.3. RNA-Seq data of differentially expressed genes between the in planta culture and the in vitro plate culture a Locus RPM Fold DESeq Fold DESeq Tag Annotation Regulation Regulation padj CKS_3692 hypothetical protein A 73.74 45.35 2.03E-34 periplasmic-binding component of an ABC CKS_3355 superfamily ribose transporter A 69.73 45.91 3.79E-45 CKS_4725 hypothetical protein A 65.98 38.91 3.97E-27 CKS_3263 HrpA family pilus protein A 58.52 41.81 3.36E-90 CKS_2320 putative alkanal monooxygenase A 52.46 34.16 8.32E-36 CKS_0368 L-lactate dehydrogenase FMN-linked A 48.38 29.49 2.46E-21 periplasmic-binding component of an ABC CKS_3537 superfamily L-arabinose transporter A 46.70 33.82 1.08E-82 CKS_3570 AraC family transcriptional regulator A 45.70 32.15 2.94E-52 medium-long-chain fatty acyl-CoA CKS_0306 dehydrogenase A 42.17 30.62 4.68E-89 CKS_5750 acid shock protein A 40.09 10.72 3.29E-04 CKS_4485 fatty acid oxidation complex subunit alpha A 37.14 27.45 1.63E-105 CKS_2015 acetyl-CoA acetyltransferase A 35.62 25.32 5.44E-41 CKS_2379 nudix hydrolase A 33.59 23.10 4.93E-33 periplasmic-binding component of an ABC CKS_2184 superfamily methyl-galactoside transporter A 33.27 24.34 1.08E-69 CKS_0367 DNA-binding transcriptional repressor A 33.05 13.32 8.25E-06 ATP-binding component of an ABC CKS_1610 superfamily taurine transporter A 32.62 10.90 1.40E-04 CKS_3319 predicted inner membrane protein A 31.76 23.54 2.79E-82 CKS_3793 cytochrome d ubiquinol oxidase subunit I A 31.45 11.51 7.77E-05 CKS_2380 hypothetical protein A 30.37 21.03 1.87E-30 CKS_5511 hypothetical protein A 29.97 18.60 5.55E-18 CKS_3621 aldo-keto reductase A 29.63 21.18 1.64E-38 ATP-binding component of an ABC superfamily galactose/methyl galactoside CKS_2185 transporter A 28.73 20.86 2.60E-54 CKS_3320 GGDEF domain protein A 28.09 20.92 1.14E-75 putative formate dehydrogenase CKS_2806 oxidoreductase protein A 27.14 10.41 1.42E-04 CKS_3354 short-chain dehydrogenase/reductase A 26.87 19.19 4.03E-36 membrane component of an ABC CKS_1609 superfamily taurine transporter A 26.81 10.15 1.33E-04 CKS_0948 mannonate hydrolase A 26.64 18.93 8.50E-32 CKS_0338 glycerol dehydrogenase NAD A 25.84 18.09 7.39E-25 CKS_3039 hypothetical protein A 25.68 18.73 1.64E-41

159

PTS system cellobiose-specific IIB CKS_0373 component A 25.25 17.55 8.23E-24 CKS_3794 cytochrome d terminal oxidase subunit II A 24.97 16.45 2.29E-15 CKS_0379 hypothetical protein A 24.08 16.13 6.57E-21 CKS_3795 membrane-bound protein A 23.60 15.97 2.84E-17 CKS_2014 3-ketoacyl-CoA thiolase A 23.54 17.04 2.03E-34 CKS_0375 putative DNA-binding protein A 23.08 15.35 2.53E-18 IIA and HPr components of fructose-specific CKS_2163 PTS enzyme A 23.05 16.32 6.50E-26 CKS_2442 aldehyde dehydrogenase B A 22.99 16.75 2.90E-44 CKS_3356 hypothetical protein A 22.66 15.67 1.50E-22 CKS_3275 HrpN family hypersensitivity reaction elicitor A 21.21 15.36 5.62E-33 periplasmic-binding component of an ABC CKS_1611 superfamily taurine transporter A 21.18 7.82 1.27E-03 CKS_3270 HrpF family protein A 20.78 15.48 1.21E-60 CKS_0515 predicted dioxygenase A 19.90 13.94 1.48E-27 CKS_5455 putative exported protein A 18.99 13.41 2.61E-21 CKS_2164 fructose-1-phosphate kinase A 18.24 13.25 1.57E-33 CKS_5349 putative exported protein A 17.83 12.65 2.79E-22 CKS_5393 putative exported protein A 17.45 12.35 4.29E-20 CKS_0380 hypothetical protein A 17.17 11.01 1.05E-10 CKS_0366 L-lactate permease A 16.85 11.16 2.03E-11 ATP-binding component of an ABC CKS_0801 superfamily predicted amino-acid transporter A 16.83 12.04 1.23E-31 CKS_5389 putative exported protein A 16.57 11.79 5.24E-21 CKS_3968 cold shock protein A 16.43 11.99 1.34E-32 CKS_0376 putative phage transposase A 16.09 11.84 4.39E-35 24-dienoyl-CoA reductase NADH and FMN- CKS_0649 linked A 15.71 11.75 2.08E-56 CKS_4657 malate synthase A A 15.65 11.35 1.23E-26 CKS_3021 putative NADH:flavin oxidoreductase A 15.50 11.47 1.32E-30 CKS_0570 thymidine phosphorylase A 15.40 11.43 8.99E-35 CKS_4830 amidohydrolase A 15.14 11.06 2.80E-33 bacterioferritin iron storage and CKS_1591 detoxification protein A 14.97 10.99 1.79E-24 CKS_4767 3-keto-L-gulonate 6-phosphate decarboxylase A 14.79 9.95 1.39E-12 CKS_4956 ABC transporter A 14.79 10.72 1.78E-31 CKS_4575 secretion system chaperone A 14.78 10.67 1.38E-29 CKS_4463 sn-glycerol-3-phosphate transporter A 14.69 10.66 1.53E-22 CKS_5579 lysis protein S A 14.59 9.37 6.02E-10 CKS_3407 phosphoenolpyruvate synthase A 14.54 10.61 1.67E-24 CKS_0960 putative RpiR family transcriptional regulator A 14.48 10.78 2.88E-37

160

CKS_0687 predicted pirin-related protein A 14.37 9.96 6.48E-17 CKS_2804 putative carbon starvation protein A A 14.30 10.32 1.37E-21 enoyl-CoA hydratase/3-hydroxyacyl-CoA CKS_2016 dehydrogenase A 14.07 10.54 2.75E-44 ATP-binding component of an ABC CKS_2488 superfamily sugar transporter A 13.75 10.25 3.98E-41 permease component of an ABC superfamily CKS_4955 transporter A 13.66 9.71 2.11E-20 CKS_3540 DNA-binding transcriptional dual regulator A 13.66 10.10 4.78E-32 CKS_4279 hypothetical protein A 13.27 9.47 3.08E-18 CKS_0668 predicted quinol oxidase subunit A 13.06 9.01 2.40E-15 CKS_5753 hypothetical protein A 13.03 9.80 9.61E-49 CKS_4281 hypothetical protein A 12.99 9.05 3.47E-14 alkanesulfonate monooxygenase FMNH(2)- CKS_4019 dependent A 12.90 8.74 4.06E-12 membrane component of an ABC CKS_2186 superfamily methyl-galactoside transporter A 12.73 9.37 7.14E-30 gamma-aminobutyrate:alpha-ketoglutarate CKS_2504 aminotransferase A 12.38 9.16 9.59E-27 CKS_4653 periplasmic binding protein A 12.34 9.30 2.74E-45 ATP-binding component of an ABC CKS_4759 superfamily ribose transporter A 12.00 8.88 5.25E-30 CKS_4658 isocitrate lyase A 11.88 8.53 7.22E-16 mannose-specific enzyme IIC component of CKS_2680 PTS A 11.86 8.65 4.28E-19 CKS_2375 hypothetical protein A 11.85 8.29 4.81E-11 CKS_2765 hypothetical protein A 11.83 8.78 1.46E-22 putative type III secretion system effector CKS_4576 protein A 11.82 8.83 1.19E-38 CKS_2372 putative transcriptional regulator A 11.80 8.39 1.24E-15 CKS_0377 phage transposase A 11.68 8.26 7.13E-13 CKS_2383 hypothetical protein A 11.68 8.21 1.64E-12 PTS system cellobiose-specific IIB CKS_4331 component A 11.55 8.31 2.84E-15 CKS_3796 YbgE family protein A 11.51 8.43 6.66E-16 conserved inner membrane protein involved CKS_4719 in acetate transport A 11.47 8.04 1.97E-12 CKS_4953 hypothetical protein A 11.42 8.30 3.49E-22 CKS_4579 hypothetical protein A 11.19 8.13 1.90E-22 CKS_3715 hypothetical protein A 11.14 8.35 3.60E-36 CKS_3265 HrpB family protein A 11.13 8.23 1.45E-24 CKS_0940 myo-inositol 2-dehydrogenase A 11.09 8.10 6.26E-16 CKS_2366 hypothetical protein A 11.00 7.94 4.82E-16

161

CKS_1750 N-acetylmuramoyl-L-alanine amidase A 10.94 7.95 1.83E-15 3-isopropylmalate isomerase subunit CKS_5150 dehydratase component A 10.93 8.12 1.21E-23 CKS_2985 hypothetical protein A 10.92 7.65 2.31E-11 RND multidrug efflux membrane fusion CKS_3569 protein A 10.87 7.88 9.80E-19 L-arabinose transport system permease CKS_3539 protein A 10.82 7.93 2.05E-20 CKS_4282 hypothetical protein A 10.81 7.83 3.98E-19 CKS_2384 hypothetical protein A 10.62 7.52 3.22E-11 membrane component of an ABC CKS_3201 superfamily polar amino acid transporter A 10.61 7.79 2.49E-20 CKS_2487 putative periplasmic binding protein A 10.60 7.77 2.14E-26 periplasmic-binding component of an ABC CKS_0962 superfamily D-ala-D-a la transporter A 10.58 7.96 1.18E-34 CKS_0390 hypothetical protein A 10.51 7.61 5.83E-12 CKS_3767 hypothetical protein A 10.45 7.66 4.96E-20 CKS_3267 type III secretion system lipoprotein A 10.36 7.68 2.34E-23 CKS_1289 endoribonuclease L-PSP A 9.98 7.47 2.31E-33 CKS_5413 hypothetical protein A 9.95 7.43 4.60E-20 CKS_3512 oxidoreductase domain protein A 9.87 7.33 1.84E-25 CKS_2586 putative adenine methylase A 9.87 6.60 2.75E-07 aerobic FAD/NAD(P)-binding sn-glycerol-3- CKS_0891 phosphate dehydrogenase A 9.84 7.44 6.94E-42 CKS_3022 anion transporter A 9.81 7.24 5.71E-15 CKS_1749 hypothetical protein A 9.78 7.26 9.65E-18 CKS_5454 putative cell wall-associated hydrolase A 9.73 7.30 5.25E-26 CKS_1089 glycerol facilitator A 9.60 7.18 3.98E-29 putative type III secretion system effector CKS_4574 protein A 9.57 7.04 7.08E-24 CKS_1044 acetolactate synthase small subunit A 9.52 7.11 4.13E-23 putative MFS superfamily benzoate CKS_3579 transporter A 9.44 7.09 9.11E-30 membrane component of an ABC CKS_0964 superfamily D-ala-D-ala transporter A 9.44 7.01 2.89E-23 CKS_4954 aryldialkylphosphatase A 9.41 6.97 5.42E-23 CKS_0560 hypothetical protein A 9.35 7.08 7.33E-36 pyridine nucleotide transhydrogenase beta CKS_2855 subunit A 9.35 6.84 9.54E-13 CKS_3254 HrpO family protein A 9.32 6.71 8.43E-13 CKS_2381 hypothetical protein A 9.28 6.92 2.24E-19 CKS_2373 hypothetical protein A 9.27 6.68 6.90E-14 CKS_1233 protein disaggregation chaperone A 9.25 6.54 1.60E-11 162

CKS_4654 hypothetical protein A 9.24 6.96 4.88E-33 CKS_4586 secretion system apparatus protein A 9.23 6.97 2.28E-30 CKS_3513 oxidoreductase domain protein A 9.22 6.91 3.47E-26 CKS_4829 integral membrane protein A 9.19 6.51 4.31E-12 CKS_1037 predicted transporter A 9.17 6.92 2.16E-26 CKS_4792 Maltoporin A 9.09 6.80 1.19E-24 CKS_0961 D-ala-D-ala dipeptidase Zn-dependent A 9.07 6.82 5.29E-27 putative type III secretion system apparatus CKS_4585 protein A 9.04 6.80 2.83E-22 CKS_2370 heptosyltransferase A 8.94 6.44 3.97E-12 CKS_4247 putative alpha/beta hydrolase A 8.92 6.62 1.16E-13 CKS_4588 type III secretion system apparatus protein A 8.87 6.60 2.10E-18 CKS_4333 beta-glucosidase A 8.87 6.61 8.21E-19 CKS_2182 DNA-binding transcriptional repressor A 8.82 6.62 1.00E-26 CKS_4320 Epimerase A 8.79 6.39 3.37E-14 CKS_3281 HopAM1-1 family type III effector A 8.75 6.45 1.79E-19 PTS system cellobiose-specific IIC CKS_0374 component A 8.74 6.50 2.38E-19 CKS_3948 predicted inner membrane protein A 8.73 6.53 2.38E-25 CKS_2791 hypothetical protein A 8.70 6.55 2.31E-33 CKS_4573 hypothetical protein A 8.67 6.40 1.30E-20 periplasmic substrate-binding component of CKS_4761 an ABC superfamily ribose transporter A 8.66 6.50 4.52E-29 putative type III secretion system effector CKS_4577 protein A 8.66 6.52 1.60E-26 HrcJ family type III secretion system CKS_3258 component protein A 8.65 6.42 8.16E-23 CKS_2495 FAD dependent oxidoreductase A 8.64 6.24 2.43E-13 CKS_1361 PLP-binding diaminopimelate decarboxylase A 8.58 6.38 2.53E-24 CKS_4720 acetyl-CoA synthetase A 8.57 6.40 6.14E-21 CKS_3038 iron-uptake factor A 8.57 6.39 1.37E-15 CKS_2371 hypothetical protein A 8.47 6.23 1.03E-13 CKS_4249 putative membrane protein A 8.46 6.08 5.04E-12 DNA-binding transcriptional dual regulator CKS_2490 of nitrogen assimilation A 8.41 5.53 1.13E-05 PTS system sucrose-specific IIBC CKS_4791 components A 8.37 6.30 4.11E-22 CKS_3860 molybdopterin biosynthesis protein C A 8.33 6.26 6.60E-20 putative permease component of an ABC CKS_0288 superfamily amino acid transporter A 8.29 5.44 1.69E-05 methylmalonate-semialdehyde CKS_0944 dehydrogenase A 8.26 6.19 1.84E-22 CKS_3619 hypothetical protein A 8.23 6.19 3.19E-20 163

membrane component of an ABC CKS_3844 superfamily molybdate transporter A 8.21 6.19 5.71E-26 CKS_3206 putative amidohydrolase A 8.15 5.40 2.16E-05 CKS_2376 hypothetical protein A 8.13 5.95 4.92E-14 PTS system mannitol-specific EIIABC CKS_4373 component A 8.13 6.03 9.32E-16 CKS_2623 hypothetical protein A 8.11 6.10 5.32E-23 23-diketo-L-gulonate dehydrogenase NADH- CKS_4763 dependent A 8.09 5.91 1.05E-14 CKS_4283 hypothetical protein A 8.08 5.94 1.09E-16 fasciclin-like repeat-containing CKS_2922 secreted/surface protein A 8.08 6.05 1.51E-22 membrane component of an ABC CKS_0963 superfamily D-ala-D-ala transporter A 7.91 5.95 1.54E-19 ATP-binding component of an ABC CKS_1227 superfamily ribose transporter A 7.82 5.89 2.26E-27 ATP-binding component of an ABC CKS_3538 superfamily L-arabinose transporter A 7.80 5.85 2.28E-24 CKS_3623 hypothetical protein A 7.74 5.78 3.95E-14 CKS_4800 predicted dehydrogenase A 7.68 5.69 1.18E-12 holliday junction resolvase/crossover junction CKS_2609 endodeoxyribonuclease A 7.63 5.55 5.05E-12 pyridine nucleotide transhydrogenase alpha CKS_2854 subunit A 7.61 5.61 8.60E-10 CKS_5452 N-acetylmuramoyl-L-alanine amidase A 7.61 5.63 3.75E-15 permease component of an ABC superfamily ribose/xylose/arabinose/galactoside CKS_2489 transporter A 7.54 5.69 1.35E-22 CKS_5877 mobilization protein A 7.52 5.54 7.73E-16 CKS_3826 PhoH family ATPase A 7.51 5.50 6.13E-13 CKS_2493 aldehyde dehydrogenase A 7.50 5.42 1.58E-09 anaerobic ribonucleoside-triphosphate CKS_4923 reductase A 7.42 5.46 5.53E-09 CKS_3440 N-ethylmaleimide reductase FMN-linked A 7.39 5.60 2.50E-23 CKS_2984 hypothetical protein A 7.38 5.39 7.62E-12 CKS_2625 hypothetical protein A 7.38 5.44 1.80E-17 CKS_4952 acetylornithine deacetylase A 7.31 5.38 3.37E-14 CKS_2306 uncharacterized DUF1537 family protein A 7.26 5.34 3.04E-13 CKS_3838 Galactokinase A 7.23 5.39 3.55E-17 CKS_4596 hypothetical protein A 7.22 5.39 6.71E-16 CKS_0908 Pirin A 7.18 5.19 7.62E-12 CKS_0771 NAD(P)-binding malate dehydrogenase A 7.18 5.41 2.00E-14 CKS_2803 hypothetical protein A 7.16 5.34 6.70E-17

164

serine--pyruvate aminotransferase / L- CKS_0291 alanine:glyoxylate aminotransferase A 7.16 4.98 3.45E-07 CKS_2641 phage baseplate assembly protein V A 7.15 5.32 9.23E-14 CKS_1042 dihydroxyacid dehydratase A 7.13 5.41 1.02E-22 type III secretion system inner membrane CKS_4597 protein A 7.11 5.16 1.36E-08 CKS_3837 galactose-1-epimerase (mutarotase) A 7.05 5.31 2.00E-13 CKS_3549 Oxidoreductase A 7.03 5.17 8.52E-12 PTS system fructose-specific IIB'BC CKS_2165 component A 7.02 5.31 6.15E-23 CKS_3622 pyruvate/alpha-keto-acid decarboxylase A 6.99 5.28 9.03E-21 permease component of an ABC superfamily CKS_4760 ribose transporter A 6.99 5.25 1.86E-19 CKS_1045 acetolactate synthase large subunit A 6.98 5.28 1.08E-20 CKS_2792 aconitate hydratase 1 A 6.92 5.23 2.69E-20 CKS_0370 hypothetical protein A 6.90 5.22 3.64E-19 permease component of an ABC superfamily CKS_2525 ribose transporter A 6.88 5.05 7.32E-10 CKS_0371 hypothetical protein A 6.81 5.17 7.03E-23 CKS_0657 altronate hydrolase A 6.80 5.09 4.82E-16 CKS_5309 DNA polymerase V subunit D A 6.79 4.95 5.25E-08 succinate-semialdehyde dehydrogenase I CKS_2492 NADP-dependent A 6.77 4.92 3.75E-11 CKS_2222 predicted peptidase A 6.75 5.05 4.84E-10 ATP-binding component of an ABC CKS_0965 superfamily D-ala-D-ala transporter A 6.75 5.09 2.36E-18 membrane component of an ABC superfamily glutamate and aspartate CKS_3739 transporter A 6.69 5.07 1.30E-20 periplasmic-binding component of an ABC CKS_0922 superfamily leucine transporter A 6.69 5.05 6.10E-15 CKS_3984 pyruvate formate-lyase A 6.68 4.83 9.76E-06 CKS_3859 molybdopterin biosynthesis protein B A 6.65 5.00 9.19E-15 CKS_2626 hypothetical protein A 6.64 5.01 4.90E-19 CKS_2530 putative response regulator protein A 6.61 4.91 4.64E-17 CKS_2629 phage tail sheath protein FI A 6.56 4.92 1.29E-14 CKS_4762 gluconolactonase A 6.54 4.94 9.74E-21 CKS_2642 hypothetical protein A 6.54 4.83 2.27E-13 CKS_5411 Endonuclease A 6.50 4.87 7.16E-17 putative type III secretion system apparatus CKS_4584 protein A 6.50 4.91 6.17E-21 CKS_0939 epi-inositol hydrolase A 6.47 4.86 1.51E-13 CKS_3703 L-fucose operon activator A 6.46 4.61 1.93E-06 165

CKS_2425 Transketolase A 6.46 4.72 6.34E-08 CKS_0658 altronate oxidoreductase NAD-dependent A 6.43 4.83 1.50E-16 CKS_0204 ammonium transporter A 6.42 3.10 1.02E-01 PTS system mannose-specific IIAB CKS_2681 component A 6.41 4.79 1.91E-11 CKS_2378 hypothetical protein A 6.37 4.73 2.58E-12 PTS system cellobiose-specific IIC CKS_4332 component A 6.35 4.77 1.77E-14 CKS_4046 DNA-binding protein hemimethylated A 6.34 4.53 4.04E-07 CKS_2744 alcohol/acetaldehyde-CoA dehydrogenase A 6.34 4.76 1.14E-09 CKS_4280 hypothetical protein A 6.32 4.78 1.03E-20 CKS_2622 hypothetical protein A 6.31 4.76 1.60E-16 periplasmic-binding component of an ABC CKS_4020 superfamily alkanesulfonate transporter A 6.26 4.31 4.88E-05 CKS_5453 hypothetical protein A 6.25 4.61 1.04E-10 CKS_0592 hypothetical protein A 6.24 4.71 9.97E-18 CKS_2587 hypothetical protein A 6.21 4.32 3.61E-05 drug/metabolite transporter (DMT) CKS_1762 superfamily permease A 6.19 4.60 8.99E-12 membrane component of an ABC CKS_4390 superfamily dipeptide transporter A 6.18 4.62 2.09E-10 CKS_2386 hypothetical protein A 6.16 4.59 1.05E-10 membrane component of an ABC CKS_4389 superfamily dipeptide transporter A 6.16 4.60 3.98E-10 CKS_5394 putative inner membrane protein A 6.13 4.61 3.03E-13 CKS_3243 hypothetical protein A 6.13 4.64 4.51E-16 CKS_4593 hypothetical protein A 6.07 4.55 3.43E-17 CKS_5456 putative inner membrane protein A 6.04 4.55 6.40E-13 CKS_1836 copper homeostasis protein A 6.03 4.49 3.90E-15 CKS_5350 putative inner membrane protein A 6.02 4.54 4.47E-13 CKS_0468 hypothetical protein A 5.98 4.48 1.78E-09 CKS_0452 putative peptidase A 5.95 4.51 3.56E-15 CKS_0791 predicted reductase A 5.95 4.41 3.77E-11 mannose-specific enzyme IID component of CKS_2679 PTS A 5.94 4.47 1.77E-11 CKS_4594 hypothetical protein A 5.93 4.47 1.00E-14 CKS_3146 dihydrodipicolinate synthase A 5.93 4.38 1.39E-08 CKS_4754 outer membrane glucose/carbohydrate porin A 5.92 4.50 8.72E-23 CKS_2590 hypothetical protein A 5.92 4.07 1.66E-04 CKS_5026 hypothetical protein A 5.91 4.09 1.11E-04 CKS_3535 L-arabinose isomerase A 5.89 4.37 1.06E-12 CKS_4583 secretion system apparatus protein A 5.88 4.45 2.71E-16

166

CKS_2921 putative RNA polymerase sigma factor A 5.87 4.43 5.39E-20 membrane component of an ABC superfamily leucine/isoleucine/valine CKS_0920 transporter A 5.86 4.41 4.10E-13 CKS_5412 putative DSBA oxidoreductase A 5.86 4.44 3.17E-12 CKS_2588 hypothetical protein A 5.85 4.01 3.03E-04 CKS_2920 hypothetical protein A 5.85 4.44 1.99E-16 CKS_5152 2-isopropylmalate synthase A 5.83 4.43 3.41E-21 CKS_2628 hypothetical protein A 5.83 4.35 1.57E-13 putative ATP-binding component of an ABC CKS_0290 superfamily amino acid transporter A 5.83 4.01 1.52E-04 CKS_2800 L-ribulose-5-phosphate 4-epimerase A 5.80 4.37 3.67E-16 CKS_3982 predicted transporter A 5.77 4.37 3.84E-21 CKS_4764 hypothetical protein A 5.77 4.26 1.78E-08 CKS_2924 metal-activated pyridoxal enzyme A 5.75 4.32 7.89E-13 CKS_1226 predicted cytoplasmic sugar-binding protein A 5.71 4.26 1.62E-14 CKS_0551 carbonic anhydrase A 5.70 4.10 6.47E-08 CKS_2635 hypothetical protein A 5.69 4.00 1.25E-05 CKS_2305 NAD-binding dehydrogenase A 5.67 4.25 2.38E-13 CKS_4578 secretion system effector protein A 5.67 4.27 2.79E-16 CKS_4272 putative DNA modification methylase A 5.65 4.25 5.36E-14 CKS_2387 hypothetical protein A 5.64 4.20 4.58E-08 CKS_2496 extracellular solute-binding protein family 5 A 5.57 4.13 1.30E-10 CKS_2705 D-amino acid dehydrogenase small subunit A 5.56 4.23 1.69E-17 putative type III secretion system ATP CKS_4592 synthase A 5.53 4.21 1.47E-15 CKS_2883 predicted dethiobiotin synthetase A 5.53 3.25 5.97E-02 ATP-binding component of an ABC CKS_4391 superfamily dipeptide transporter A 5.53 4.17 9.56E-10 permease component of an ABC superfamily CKS_3738 glutamate/aspartate transporter A 5.51 4.16 1.43E-15 CKS_2550 DgsA-binding anti-repressor A 5.49 4.07 4.51E-09 anaerobic ribonucleotide reductase activating CKS_4922 protein A 5.48 4.10 3.27E-07 CKS_0340 dihydroxyacetone kinase subunit A 5.47 4.10 4.17E-09 permease component of an ABC superfamily CKS_2062 spermidine/putrescine transporter A 5.47 4.13 1.24E-12 CKS_0429 hypothetical protein A 5.47 4.15 6.31E-14 CKS_3209 predicted oxidoreductase A 5.46 3.95 8.57E-06 CKS_5620 partitioning protein SpyA A 5.46 3.99 2.96E-07 CKS_2202 hypothetical protein A 5.45 3.92 5.09E-04 CKS_3534 membrane-fusion protein A 5.42 3.90 5.28E-06

167

periplasmic substrate-binding component of CKS_3843 an ABC superfamily molybdate transporter A 5.41 4.09 1.70E-17 CKS_2637 hypothetical protein A 5.41 4.07 3.38E-15 CKS_3137 hypothetical protein A 5.38 3.99 1.37E-08 long-chain fatty acid outer membrane CKS_2012 transporter A 5.36 4.02 5.71E-13 membrane component of an ABC superfamily leucine/isoleucine/valine CKS_0921 transporter A 5.36 4.05 3.28E-12 DNA-binding transcriptional dual regulator CKS_4703 Fe-S center for redox-sensing A 5.34 3.95 4.24E-09 CKS_3147 alcohol dehydrogenase A 5.33 3.96 2.16E-08 CKS_2640 hypothetical protein A 5.32 3.99 3.74E-12 CKS_5481 mobilization protein A 5.32 3.97 3.65E-11 CKS_3861 molybdopterin synthase small subunit A 5.32 4.02 2.30E-12 CKS_4766 L-xylulose kinase A 5.30 3.93 7.58E-10 type III secretion system outermembrane pore CKS_3271 forming protein A 5.29 4.02 1.81E-13 membrane-bound lytic murein CKS_2423 transglycosylase E A 5.29 4.00 2.73E-16 CKS_5477 mobilization protein A 5.28 3.94 1.07E-10 CKS_4591 secretion system apparatus protein A 5.26 4.00 4.67E-17 CKS_5064 hexuronate transporter A 5.25 3.90 1.50E-09 CKS_1090 glycerol kinase A 5.23 3.90 1.05E-11 CKS_3552 mannose-6-phosphate isomerase A 5.22 3.94 2.38E-09 CKS_3503 methyl-accepting chemotaxis protein A 5.21 3.97 5.82E-14 CKS_2644 hypothetical protein A 5.21 3.85 4.58E-08 type III secretion system cytoplasmic ATP CKS_3255 synthase A 5.20 3.95 1.24E-12 CKS_4340 heat shock chaperone A 5.17 3.65 5.95E-05 CKS_0659 uronate isomerase A 5.15 3.89 1.03E-15 ATP-binding component of an ABC CKS_2753 superfamily oligopeptide transporter A 5.13 3.88 5.47E-09 cytosine/purine/uracil/thiamine/allantoin CKS_0266 permease family protein A 5.12 2.61 1.82E-01 CKS_2368 gp55 family protein A 5.10 3.79 1.37E-08 CKS_0874 phosphoenolpyruvate carboxykinase A 5.07 3.85 2.35E-17 CKS_5356 putative outer membrane adhesion protein A 5.06 3.86 2.49E-17 CKS_5151 3-isopropylmalate dehydrogenase A 5.06 3.85 1.36E-14 CKS_5834 hypothetical protein A 5.03 3.58 1.36E-04 CKS_4718 acetate permease A 5.03 3.79 2.04E-08 putative mannosyl-3-phosphoglycerate CKS_2563 phosphatase A 5.03 3.78 3.04E-09 168

CKS_5404 putative outer membrane adhesion protein A 5.03 3.83 2.35E-13 CKS_2592 hypothetical protein A 4.99 3.51 6.12E-04 CKS_3268 HrpD family protein A 4.97 3.71 6.23E-09 CKS_5754 hypothetical protein A 4.96 3.50 2.24E-04 CKS_3620 hypothetical protein A 4.95 3.72 6.02E-10 CKS_1696 magnesium transporter A 4.93 3.75 1.44E-09 CKS_3858 molybdopterin biosynthesis protein A A 4.92 3.75 7.23E-12 CKS_0571 Phosphopentomutase A 4.92 3.76 8.75E-16 CKS_4484 3-ketoacyl-CoA thiolase (thiolase I) A 4.91 3.69 5.80E-15 CKS_2880 predicted transporter A 4.91 3.72 4.10E-13 CKS_2624 hypothetical protein A 4.86 3.68 1.99E-13 CKS_3983 pyruvate formate lyase activating enzyme 1 A 4.85 3.65 9.35E-06 CKS_4056 WrbA family flavoprotein A 4.85 3.67 9.41E-08 CKS_5446 hypothetical protein A 4.85 3.65 3.04E-14 GAF domain/GGDEF domain/EAL domain CKS_3094 protein A 4.84 3.55 9.00E-06 CKS_4794 beta-D-galactosidase A 4.83 3.68 1.91E-12 CKS_4942 ornithine carbamoyltransferase 1 A 4.83 3.67 3.11E-17 CKS_2589 phage-related protein A 4.82 3.39 8.85E-04 CKS_4712 hypothetical protein A 4.82 3.63 2.78E-14 gluconate transporter high-affinity GNT I CKS_3714 system A 4.81 3.63 4.35E-08 CKS_2494 type II haloacid dehalogenase A 4.81 3.56 1.51E-06 CKS_5310 DNA polymerase V subunit C A 4.79 3.61 5.84E-10 CKS_1538 hypothetical protein A 4.78 3.64 1.65E-09 CKS_2385 hypothetical protein A 4.77 3.52 6.93E-07 methyl-accepting chemotaxis sensory CKS_3278 transducer A 4.77 3.59 1.43E-11 CKS_5439 hypothetical protein A 4.76 3.51 1.83E-07 CKS_0191 L36 family ribosomal protein A 4.76 3.51 4.85E-08 CKS_3385 predicted phosphotransferase/kinase A 4.75 3.62 1.42E-12 CKS_5025 phage-related protein A 4.74 3.34 8.63E-04 CKS_4021 NAD(P)H-dependent FMN reductase A 4.73 3.20 4.53E-03 CKS_0561 methyl-accepting chemotaxis protein A 4.73 3.53 3.26E-10 CKS_4590 secretion system apparatus protein A 4.73 3.57 2.84E-12 CKS_4571 virulence protein A 4.72 3.58 5.52E-14 CKS_2947 maltose regulon periplasmic protein A 4.71 3.54 4.05E-09 CKS_0943 5-deoxy-glucuronate isomerase A 4.71 3.59 1.12E-12 CKS_4742 ferrous iron uptake protein A 4.70 3.57 1.68E-07 acyl-CoA synthetase long-chain-fatty-acid-- CKS_2693 CoA ligase A 4.70 3.56 4.26E-16 CKS_0912 hypothetical protein A 4.69 3.49 1.94E-09 169

zinc-containing alcohol CKS_0640 dehydrogenase/quinone oxidoreductase A 4.68 3.56 1.96E-10 CKS_1810 uncharacterized DUF533 family protein A 4.67 3.48 9.72E-08 CKS_4162 hypothetical protein A 4.64 3.32 3.31E-04 CKS_3536 L-ribulokinase A 4.63 3.47 1.96E-08 CKS_1698 hypothetical protein A 4.62 3.53 2.19E-10 CKS_2594 hypothetical protein A 4.60 3.24 1.55E-03 CKS_4512 putative inner membrane protein A 4.59 3.51 4.28E-12 CKS_1697 divalent cation transport protein A 4.57 3.49 3.94E-11 CKS_0941 inosose dehydratase A 4.56 3.40 2.89E-07 CKS_5024 hypothetical protein A 4.55 3.20 1.54E-03 2-deoxyribose-5-phosphate aldolase NAD(P)- CKS_0569 linked A 4.54 3.46 1.26E-12 CKS_0292 N-carbamoyl-L-amino acid hydrolase A 4.54 3.35 5.50E-06 CKS_4462 HD superfamily hydrolase A 4.53 3.43 3.83E-07 CKS_5352 outer membrane adhesion/aggregation protein A 4.51 3.44 4.11E-14 CKS_0412 hypothetical protein A 4.51 3.34 5.94E-07 CKS_2983 phytochelatin synthase A 4.51 3.40 2.70E-11 membrane component of an ABC CKS_1228 superfamily D-ribose transporter A 4.50 3.42 4.71E-11 CKS_3273 HrpT family protein A 4.48 3.39 1.28E-08 CKS_2377 hypothetical protein A 4.46 3.36 3.44E-10 CKS_2593 single-stranded DNA-binding protein A 4.45 3.16 1.59E-03 CKS_5480 MbeA family protein A 4.45 3.38 1.02E-13 CKS_0476 3-oxoadipate CoA-transferase subunit B A 4.45 3.26 6.93E-05 putative periplasmic substrate-binding component of an ABC superfamily amino CKS_0287 acid transporter A 4.45 3.07 3.43E-03 CKS_2706 PLP-binding alanine racemase 2 A 4.43 3.37 5.22E-10 CKS_3409 predicted inner membrane protein A 4.41 3.37 5.62E-10 CKS_3241 amidinotransferase family protein A 4.40 3.30 2.28E-09 ATP-binding component of an ABC CKS_2524 superfamily ribose transporter A 4.40 3.31 6.78E-08 CKS_3276 putative avirulence protein A 4.39 3.31 2.66E-10 CKS_3825 uncharacterized UPF0054 family protein A 4.38 3.28 3.95E-09 CKS_2627 hypothetical protein A 4.34 3.27 1.30E-10 CKS_3256 type III secretion system protein A 4.33 3.29 1.70E-09 periplasmic substrate binding component of CKS_3702 an ABC superfamily sugar transporter A 4.33 3.19 9.16E-05 membrane component of an ABC CKS_2752 superfamily oligopeptide transporter A 4.33 3.27 1.78E-06 CKS_3150 predicted mannonate dehydrogenase A 4.32 3.28 2.11E-05 CKS_3127 hypothetical protein A 4.32 3.28 2.27E-07 170

serine endoprotease (protease Do) membrane- CKS_5250 associated A 4.30 3.26 6.31E-09 CKS_4572 hypothetical protein A 4.29 3.20 5.44E-07 site-specific recombinase phage integrase CKS_0540 family A 4.29 3.19 3.41E-05 CKS_4208 FlgF family flagellar basal-body rod protein A 4.28 3.15 2.10E-04 putative binding periplasmic protein of ABC CKS_4958 transporter A 4.28 3.26 4.96E-11 CKS_2106 hypothetical protein A 4.27 3.23 8.26E-07 CKS_5716 hypothetical protein A 4.27 2.99 3.27E-03 CKS_1191 D-xylose isomerase A 4.26 3.21 2.18E-09 type III secretion system inner membrane CKS_3257 channel protein A 4.25 3.23 2.76E-10 CKS_2307 predicted class II aldolase A 4.22 3.19 8.40E-07 CKS_2441 methyltransferase A 4.22 3.11 2.77E-05 CKS_3596 putative acetyltransferase A 4.22 3.15 1.55E-07 CKS_3202 ABC superfamily transporter A 4.21 3.19 4.31E-08 CKS_5183 GMP reductase A 4.21 3.22 5.36E-09 CKS_0469 4-hydroxybenzoate transporter A 4.20 3.15 4.15E-08 CKS_4273 hypothetical protein A 4.20 3.16 1.71E-07 CKS_3862 molybdopterin synthase large subunit A 4.20 3.19 2.88E-09 CKS_5017 hypothetical protein A 4.19 2.35 2.30E-01 CKS_4163 hypothetical protein A 4.15 3.12 1.19E-07 CKS_5419 hypothetical protein A 4.15 3.12 4.91E-09 CKS_2361 DNA adenine methylase A 4.14 3.13 1.99E-07 type III secretion system peptide export CKS_4523 protein A 4.14 3.15 5.80E-13 CKS_2639 hypothetical protein A 4.13 3.11 8.86E-09 CKS_3593 hypothetical protein A 4.13 3.14 2.33E-08 CKS_1043 branched-chain amino-acid aminotransferase A 4.12 3.15 7.35E-09 CKS_0328 transcriptional activator-regulatory protein A 4.12 3.15 8.99E-12 CKS_1541 IMP dehydrogenase A 4.12 3.14 1.04E-09 CKS_3024 fumarase A A 4.10 3.14 2.18E-09 CKS_3839 galactose-1-phosphate uridylyltransferase A 4.09 3.11 4.80E-09 CKS_0440 hypothetical protein A 4.09 3.09 4.16E-11 CKS_0312 hypothetical protein A 4.09 3.10 1.06E-09 CKS_0477 3-oxoadipate CoA-transferase subunit A A 4.07 2.99 1.30E-04 CKS_1444 GroES family alcohol dehydrogenase A 4.07 3.11 7.16E-08 ATP-binding component of an ABC CKS_3845 superfamily molybdate transporter A 4.07 3.11 1.47E-08 CKS_5149 3-isopropylmalate isomerase subunit A 4.07 3.11 4.82E-07 CKS_4801 putative polygalacturonase protein A 4.05 3.07 4.12E-07

171

CKS_1988 phage-related protein A 4.05 3.03 4.14E-05 CKS_3469 glycogen debranching enzyme A 4.04 3.07 1.38E-06 CKS_3872 UDP-galactose-lipid carrier transferase A 4.03 3.07 1.62E-09 CKS_3627 GCN5 family N-acetyltransferase A 4.03 3.08 1.98E-08 predicted oxidoreductase flavin:NADH CKS_3210 component A 4.03 2.90 2.99E-03 CKS_2603 hypothetical protein A 4.02 2.98 2.55E-04 CKS_2369 hypothetical protein A 4.02 2.95 1.75E-04 ATP-binding subunit of oligopeptide ABC CKS_2754 transporter A 4.02 3.07 9.85E-07 CKS_3143 hypothetical protein A 4.01 3.03 1.50E-05 CKS_0272 phytanoyl-CoA dioxygenase family protein A 4.01 2.99 3.85E-04 CKS_2591 hypothetical protein A 4.01 2.84 6.09E-03 CKS_4095 hypothetical protein R 4.03 5.08 2.08E-15 CKS_1527 nucleoside diphosphate kinase R 4.06 5.10 1.83E-14 CKS_4091 hypothetical protein R 4.06 5.09 2.85E-17 CKS_4133 putative bacteriophage protein R 4.06 5.08 2.65E-18 CKS_4368 superoxide dismutase Mn R 4.10 5.21 2.20E-18 CKS_4082 hypothetical protein R 4.10 5.02 4.62E-09 CKS_5095 Trp operon repressor R 4.16 5.28 5.53E-27 CKS_5071 uncharacterized DUF1328 family protein R 4.31 5.44 3.22E-28 CKS_4088 hypothetical protein R 4.33 5.31 8.01E-11 IucA family aerobactin siderophore CKS_4776 biosynthesis protein R 4.36 5.53 2.65E-17 CKS_5576 hypothetical protein R 4.48 5.60 6.54E-13 CKS_0178 adenylate kinase R 4.51 5.66 4.67E-17 peptidyl-prolyl cis-trans isomerase B CKS_0117 (rotamase B) R 4.56 5.75 6.60E-20 CKS_0744 30S ribosomal subunit protein S6 R 4.60 5.83 3.93E-19 CKS_4081 hypothetical protein R 4.61 5.69 8.96E-12 HU DNA-binding transcriptional regulator CKS_0004 alpha subunit R 4.71 5.93 7.63E-19 CKS_3122 DNA-binding protein H-NS R 4.75 6.01 1.33E-19 FKBP-type peptidyl-prolyl cis-trans CKS_0733 isomerase (rotamase) R 4.83 6.13 6.64E-25 CKS_4137 hypothetical protein R 4.87 6.13 2.87E-20 ADP-heptose--lipooligosaccharide CKS_1116 heptosyltransferase II R 4.88 6.16 4.11E-20 CKS_0742 30S ribosomal subunit protein S18 R 4.91 6.20 5.73E-19 CKS_4089 hypothetical protein R 4.95 6.18 6.42E-17 thiamin (pyrimidine moiety) biosynthesis CKS_0010 protein R 4.96 6.21 2.96E-27 CKS_4127 putative bacteriophage protein R 4.99 6.28 4.66E-25 172

CKS_4084 phage lysozyme R 5.00 6.10 1.66E-12 CKS_5198 dihydrolipoamide dehydrogenase R 5.03 6.39 3.80E-34 type III secretion system cytoplasmic ATP CKS_4530 synthase R 5.03 6.26 4.39E-26 CKS_4132 phage-related protein R 5.12 6.47 4.94E-31 diaminobutyrate-pyruvate transaminase/L-24- CKS_0644 diaminobutyrate decarboxylase R 5.23 6.52 4.64E-17 CKS_4085 hypothetical protein R 5.25 6.44 7.57E-15 CKS_4125 putative bacteriophage protein R 5.26 6.64 2.65E-35 CKS_4123 putative bacteriophage protein R 5.31 6.65 4.80E-29 CKS_0741 50S ribosomal subunit protein L9 R 5.37 6.77 1.59E-20 CKS_5070 periplasmic protein R 5.41 6.86 1.04E-36 CKS_4093 CP4-57 family phage integrase R 5.42 6.79 8.33E-21 CKS_0743 primosomal replication protein N R 5.48 6.87 4.09E-18 CKS_4126 putative bacteriophage protein R 5.56 7.00 4.37E-31 CKS_4109 putative bacteriophage protein R 5.60 7.00 8.76E-30 CKS_4092 hypothetical protein R 5.84 7.37 8.32E-36 CKS_1031 malate:quinone oxidoreductase R 5.95 7.20 1.24E-13 CKS_3057 ThiS family thiamine biosynthesis protein R 6.04 7.48 2.71E-26 CKS_4122 hypothetical protein R 6.27 7.78 1.05E-28 putative alpha/beta superfamily CKS_5211 hydrolase/acyltransferase R 6.28 7.92 5.87E-31 CKS_4090 hypothetical protein R 6.30 7.91 1.55E-28 CKS_4083 hypothetical protein R 6.36 7.83 7.74E-20 CKS_5188 quinolinate phosphoribosyltransferase R 6.38 7.98 2.21E-36 3-deoxy-D-arabino-heptulosonate-7- CKS_1241 phosphate synthase tyrosine-repressible R 6.41 7.62 4.90E-11 CKS_4136 putative bacteriophage tail protein R 6.45 8.14 8.79E-38 CKS_4717 putative exported protein R 6.62 8.31 3.46E-25 CKS_4115 putative bacteriophage protein R 6.74 8.42 3.22E-38 short chain dehydrogenase,putative CKS_2902 oxidoreductase R 6.88 8.55 9.89E-35 CKS_4134 putative bacteriophage protein R 6.95 8.74 2.69E-44 CKS_4087 hypothetical protein R 6.99 8.62 8.50E-21 CKS_3613 quinolinate phosphoribosyltransferase R 7.07 8.84 5.44E-41 thiamin phosphate synthase (thiamin CKS_0011 phosphate pyrophosphorylase) R 7.10 8.91 4.23E-40 CKS_4121 putative bacteriophage protein R 7.29 9.14 6.91E-43 putative binding-protein-dependent transport CKS_2885 system component R 7.31 9.14 1.35E-41 CKS_4117 putative bacteriophage protein R 7.45 9.15 1.12E-31 CKS_4114 putative bacteriophage protein R 7.69 9.59 5.69E-41

173

CKS_4116 putative bacteriophage protein R 7.72 9.62 1.96E-39 CKS_4135 putative bacteriophage protein R 7.93 9.91 9.12E-35 component of the MscS mechanosensitive CKS_1399 channel R 8.06 10.13 1.01E-54 CKS_4124 hypothetical protein R 8.12 10.11 1.49E-35 CKS_4535 type III secretion system regulatory protein R 8.39 10.35 3.11E-25 CKS_4721 glutamate/aspartate:proton symporter R 8.48 10.56 1.73E-29 CKS_4120 putative bacteriophage protein R 8.63 10.85 1.14E-50 CKS_0950 hypothetical protein R 8.64 10.82 2.13E-41 CKS_4113 hypothetical protein R 8.85 11.12 1.12E-46 CKS_3058 glycine oxidase R 9.22 11.55 1.49E-46 putative membrane component of an ABC CKS_2887 superfamily transporter R 9.33 11.50 2.15E-34 CKS_4118 putative bacteriophage protein R 10.71 13.17 9.23E-44 CKS_4119 putative bacteriophage protein R 10.89 13.60 2.68E-58 periplasmic substrate-binding component of an ABC superfamily glycine/betaine CKS_2886 transporter R 10.96 13.74 9.75E-61 CKS_4536 type III secretion system effector protein R 11.16 13.91 3.06E-45 CKS_4531 type III secretion system apparatus protein R 14.13 17.42 1.55E-68 CKS_4538 type III secretion system apparatus protein R 15.91 19.65 1.17E-59 CKS_1225 hypothetical protein R 23.57 28.75 5.57E-63 CKS_4537 type III secretion system effector protein R 36.62 44.52 1.97E-89 aA = activated in the in planta culture compared to in vitro plate culture (lower in plate culture), R = repressed in the in planta culture compared to in vitro plate culture (higher in plate culture)

174

Table S2.4. Primers designed for the genes of interest selected for cloning and qRT-PCRa Function (Annealing Temperature Gene 5’-3’ Primer Sequence °C) CKS_3263 F: CAGAACTGAATGGCTTTTGC Cloning CDS R: GGACTTGGTGGTCCACT CKS_3263 coding region CKS_3263 F: TATGACCGGAGTTGATTTCTTTGG qRT-PCR RT R: TGCCCAGGCAGCTAAAATGA (60°C) CKS_3793 F: ATGCTAGATATCGTCGAACTGTC Cloning CDS R: TCTGTTCATGGTGATAGCGC CKS_3793 coding region (Kernell Burke et al., 2015) CKS_3793 F: CCTTTGTGGGCCTGTTCTTTTT qRT-PCR RT R: ACCGCCAGATGCTGCACTT (64°C) (Kernell Burke et al., 2015) rmf CDS F: ATGAAGAGACAGAAACGAGACC Cloning rmf R: TCCCAACCAGTGAGACTTAGC coding region rmf RT F: CAGAAACGAGACCGCCTTGA qRT-PCR R: GCGTCCTGTAATGCCAGCTT (64°C) bfr CDS F: ATGAAGGGCGATGCGAAAATCATAAG Cloning bfr R: TTACTCTTCTTTGATTTGCGCCTG coding region bfr RT F: TGATTACGTAAGCCGCGATATG qRT-PCR R: CAGTCGATATGATGCTCCTCATCTT (60°C) CKS_3570 F: TTTATTCACGATCTGATTAACTGGATTGAC Cloning CDS R: AACACCATACTGACGCTTGAAGC CKS_3570 coding region CKS_3570 F: CTCGATCTCGATACGGTTTCTGA qRT-PCR RT R: ATCCGTTGCAGGTGCCATT (64°C) aceB CDS F: ATGACAGACTCAGTTATTACCCACGAATTACAC Cloning aceB R: TTACGTGCGCTGTCTTTACTTGG coding region aceB RT F: TGGCTGGCACATTGTCTCATA qRT-PCR R: GGATCGGCGCGAAGCT (60°C) yeaG CDS F: TACCTTGGCACCATTATGTCG Cloning yeaG R: ATCGTCGTGTTTCTTCTGCTCATCC coding region yeaG RT F: ACCGACCCGAAAGCGAAAT qRT-PCR R: CGTCCACGCCCGCATA (64°C) CKS_2505 F: CTACTGGCTTCCGTATTCCATCG Cloning CDS R: ATGAACGGCTTAATGAAACTCGATCG CKS_2505 coding region 175

CKS_2505 F: TTTGGGCATCGAGCATCTTC qRT-PCR RT R: CGCTTTATCACCCGCAGTATTG (64°C) hupA CDS F: AAAGCTGACCTGTCTAAAACCCAG Cloning hupA R: ACGGCGTCTTTCAGAGCTTTACC coding region hupA RT F: GCTGAGCGTACCGGTCGTAA qRT-PCR R: TGCCGCAGCGATTTTGAT (64°C) CKS_4537 F: CGGAAGTTCTGAATAATGGCTGCG Cloning CDS R: CTGATACAAACCCAAGCCCCACG CKS_4537 coding region CKS_4537 F: CAAGAGCCTTTTGGGCATCCT qRT-PCR RT R: CTCGGTCGCATTCGAAACC (60°C) recF CDS F: TTAATCTTTAGGTTGAACCGCTATTTTACCCTG Cloning recF R: GCTTTAACCCGCCTGCTAATAAAAGATTTTCG coding region recF RT F: AGAGGCAAAGTCATCAATGAGGTAAA qRT-PCR R: GGGCGAGTTCCTGACTAACCA (60°C) atpD CDS F: TTAAGAATGGTGATGCTCGTCTGG Cloning atpD R: CTTCTTCGATGGCACCAACC coding region atpD RT F: GGTGCGGGTGTGGGTAAAA qRT-PCR R: GCTCAGCCGCAATGTTACG (64°C) gyrB CDS F: TTAGATATCGATGTTAGCGGCTTTCAGC Cloning gyrB R: coding region ATGTCGAATTCTTATGACTCTTCAAGTATCAAAGTTCTG gyrB RT F: GACGTGACCACGCTCAATAATTTC qRT-PCR R: CGGCTCGCACATTCGTACA (60°C) aPrimers listed as coding DNA sequence (CDS) were for the cloning of each gene into pGEM-T, and RT was for the qRT-PCR protocol.

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Table S2.5. RNA-Seq data of differentially expressed genes found in the in planta culture compared to both the pre-inoculum in vitro liquid culture and the in vitro plate culturea In planta In planta RPM Fold RPM Fold Regulation Regulation Locus Tag Annotation vs. Liquid vs. Plate CKS_4725 hypothetical protein A 65.18 65.98 CKS_3692 hypothetical protein A 56.09 73.74 CKS_3263 HrpA family pilus protein A 52.64 58.52 CKS_5750 acid shock protein A 49.49 40.09 CKS_2320 putative alkanal monooxygenase A 38.39 52.46 CKS_3793 cytochrome d ubiquinol oxidase subunit I A 36.48 31.45 CKS_3039 hypothetical protein A 35.53 25.68 periplasmic-binding component of an ABC CKS_3355 superfamily ribose transporter A 33.06 69.73 CKS_2883 predicted dethiobiotin synthetase A 31.33 5.53 CKS_3407 phosphoenolpyruvate synthase A 30.76 14.54 CKS_2379 nudix hydrolase A 30.68 33.59 periplasmic-binding component of an ABC CKS_3537 superfamily L-arabinose transporter A 29.41 46.70 CKS_3794 cytochrome d terminal oxidase subunit II A 28.18 24.97 ATP-binding component of an ABC CKS_1610 superfamily taurine transporter A 27.50 32.62 bacterioferritin iron storage and detoxification CKS_1591 protein A 27.19 14.97 CKS_2202 hypothetical protein A 27.12 5.45 fasciclin-like repeat-containing CKS_2922 secreted/surface protein A 26.37 8.08 CKS_3795 membrane-bound protein A 25.59 23.60 CKS_3356 hypothetical protein A 24.51 22.66 CKS_2442 aldehyde dehydrogenase B A 23.70 22.99 CKS_4281 hypothetical protein A 23.51 12.99 CKS_0668 predicted quinol oxidase subunit A 22.60 13.06 CKS_2380 hypothetical protein A 22.17 30.37 CKS_3948 predicted inner membrane protein A 21.90 8.73 ATP-binding component of an ABC CKS_0801 superfamily predicted amino-acid transporter A 21.75 16.83 CKS_0368 L-lactate dehydrogenase FMN-linked A 21.46 48.38 CKS_0515 predicted dioxygenase A 20.57 19.90 membrane component of an ABC superfamily CKS_1609 taurine transporter A 20.25 26.81 CKS_2375 hypothetical protein A 20.00 11.85 CKS_3270 HrpF family protein A 19.63 20.78 177

CKS_3570 AraC family transcriptional regulator A 19.33 45.70 CKS_3281 HopAM1-1 family type III effector A 19.28 8.75 CKS_3513 oxidoreductase domain protein A 18.47 9.22 CKS_2985 hypothetical protein A 18.01 10.92 CKS_3320 GGDEF domain protein A 17.30 28.09 CKS_4575 secretion system chaperone A 16.57 14.78 CKS_3796 YbgE family protein A 15.82 11.51 permease component of an ABC superfamily CKS_4955 transporter A 15.79 13.66 CKS_4830 amidohydrolase A 15.67 15.14 CKS_2384 hypothetical protein A 15.52 10.62 CKS_3767 hypothetical protein A 15.27 10.45 CKS_4657 malate synthase A A 15.20 15.65 CKS_3265 HrpB family protein A 14.99 11.13 membrane component of an ABC superfamily CKS_2186 methyl-galactoside transporter A 14.99 12.73 CKS_0687 predicted pirin-related protein A 14.88 14.37 CKS_3512 oxidoreductase domain protein A 14.69 9.87 CKS_3503 methyl-accepting chemotaxis protein A 14.60 5.21 CKS_4279 hypothetical protein A 14.60 13.27 CKS_2376 hypothetical protein A 14.52 8.13 CKS_3267 type III secretion system lipoprotein A 14.32 10.36 CKS_0560 hypothetical protein A 14.07 9.35 CKS_5439 hypothetical protein A 13.72 4.76 CKS_3275 HrpN family hypersensitivity reaction elicitor A 13.62 21.21 CKS_4573 hypothetical protein A 13.54 8.67 ATP-binding component of an ABC CKS_2488 superfamily sugar transporter A 13.29 13.75 CKS_3579 putative MFS superfamily benzoate transporter A 13.24 9.44 periplasmic-binding component of an ABC CKS_1611 superfamily taurine transporter A 13.12 21.18 putative type III secretion system effector CKS_4574 protein A 12.95 9.57 CKS_0908 pirin A 12.78 7.18 conserved inner membrane protein involved in CKS_4719 acetate transport A 12.70 11.47 CKS_2366 hypothetical protein A 12.63 11.00 CKS_2378 hypothetical protein A 12.38 6.37 CKS_0370 hypothetical protein A 12.16 6.90 CKS_0371 hypothetical protein A 12.05 6.81 CKS_2371 hypothetical protein A 11.84 8.47 CKS_3319 predicted inner membrane protein A 11.65 31.76 CKS_2373 hypothetical protein A 11.65 9.27 178

CKS_2372 putative transcriptional regulator A 11.54 11.80 CKS_4954 aryldialkylphosphatase A 11.52 9.41 CKS_0204 ammonium transporter A 11.47 6.42 gamma-aminobutyrate:alpha-ketoglutarate CKS_2504 aminotransferase A 11.42 12.38 CKS_3539 L-arabinose transport system permease protein A 11.35 10.82 CKS_0380 hypothetical protein A 11.33 17.17 CKS_2984 hypothetical protein A 11.32 7.38 CKS_4282 hypothetical protein A 11.32 10.81 CKS_4280 hypothetical protein A 11.29 6.32 CKS_3715 hypothetical protein A 11.24 11.14 putative type III secretion system apparatus CKS_4585 protein A 11.21 9.04 ATP-binding component of an ABC CKS_3538 superfamily L-arabinose transporter A 11.16 7.80 CKS_1361 PLP-binding diaminopimelate decarboxylase A 11.05 8.58 CKS_4249 putative membrane protein A 10.97 8.46 CKS_0390 hypothetical protein A 10.95 10.51 CKS_2383 hypothetical protein A 10.95 11.68 3-isopropylmalate isomerase subunit CKS_5150 dehydratase component A 10.85 10.93 CKS_0948 mannonate hydrolase A 10.84 26.64 membrane component of an ABC superfamily CKS_0963 D-ala-D-ala transporter A 10.71 7.91 CKS_4658 isocitrate lyase A 10.56 11.88 pyridine nucleotide transhydrogenase beta CKS_2855 subunit A 10.52 9.35 pyridine nucleotide transhydrogenase alpha CKS_2854 subunit A 10.46 7.61 CKS_4572 hypothetical protein A 10.45 4.29 putative type III secretion system effector CKS_4576 protein A 10.12 11.82 CKS_4283 hypothetical protein A 10.09 8.08 CKS_2381 hypothetical protein A 10.07 9.28 mannose-specific enzyme IID component of CKS_2679 PTS A 9.99 5.94 CKS_3535 L-arabinose isomerase A 9.86 5.89 CKS_4586 secretion system apparatus protein A 9.82 9.23 CKS_4953 hypothetical protein A 9.78 11.42 alkanesulfonate monooxygenase FMNH(2)- CKS_4019 dependent A 9.66 12.90 CKS_0367 DNA-binding transcriptional repressor A 9.58 33.05 mannose-specific enzyme IIC component of CKS_2680 PTS A 9.47 11.86 179

CKS_3254 HrpO family protein A 9.41 9.32 drug/metabolite transporter (DMT) CKS_1762 superfamily permease A 9.37 6.19 CKS_3623 hypothetical protein A 9.35 7.74 CKS_4829 integral membrane protein A 9.31 9.19 CKS_5511 hypothetical protein A 9.29 29.97 CKS_1541 IMP dehydrogenase A 9.27 4.12 periplasmic-binding component of an ABC CKS_0962 superfamily D-ala-D-a la transporter A 9.26 10.58 CKS_3354 short-chain dehydrogenase/reductase A 9.22 26.87 type III secretion system inner membrane CKS_4597 protein A 9.20 7.11 CKS_3619 hypothetical protein A 9.17 8.23 CKS_2495 FAD dependent oxidoreductase A 9.13 8.64 CKS_4596 hypothetical protein A 9.09 7.22 permease component of an ABC superfamily CKS_2489 ribose/xylose/arabinose/galactoside transporter A 9.08 7.54 CKS_5454 putative cell wall-associated hydrolase A 9.07 9.73 CKS_3982 predicted transporter A 9.06 5.77 CKS_2765 hypothetical protein A 8.99 11.83 CKS_3268 HrpD family protein A 8.97 4.97 CKS_4331 PTS system cellobiose-specific IIB component A 8.90 11.55 enoyl-CoA hydratase/3-hydroxyacyl-CoA CKS_2016 dehydrogenase A 8.89 14.07 putative formate dehydrogenase CKS_2806 oxidoreductase protein A 8.84 27.14 CKS_4653 periplasmic binding protein A 8.83 12.34 anaerobic ribonucleoside-triphosphate CKS_4923 reductase A 8.78 7.42 CKS_4463 sn-glycerol-3-phosphate transporter A 8.76 14.69 CKS_4583 secretion system apparatus protein A 8.69 5.88 CKS_0940 myo-inositol 2-dehydrogenase A 8.68 11.09 CKS_2222 predicted peptidase A 8.62 6.75 CKS_2800 L-ribulose-5-phosphate 4-epimerase A 8.51 5.80 CKS_2792 aconitate hydratase 1 A 8.45 6.92 membrane component of an ABC superfamily CKS_3201 polar amino acid transporter A 8.37 10.61 CKS_2368 gp55 family protein A 8.35 5.10 CKS_2385 hypothetical protein A 8.27 4.77 HrcJ family type III secretion system CKS_3258 component protein A 8.21 8.65 CKS_0452 putative peptidase A 8.19 5.95

180

23-diketo-L-gulonate dehydrogenase NADH- CKS_4763 dependent A 8.17 8.09 CKS_3703 L-fucose operon activator A 8.13 6.46 CKS_4588 type III secretion system apparatus protein A 8.13 8.87 CKS_3984 pyruvate formate-lyase A 8.11 6.68 CKS_2370 heptosyltransferase A 8.09 8.94 CKS_4579 hypothetical protein A 8.08 11.19 CKS_4767 3-keto-L-gulonate 6-phosphate decarboxylase A 8.02 14.79 medium-long-chain fatty acyl-CoA CKS_0306 dehydrogenase A 8.01 42.17 CKS_3858 molybdopterin biosynthesis protein A A 8.01 4.92 CKS_0961 D-ala-D-ala dipeptidase Zn-dependent A 7.99 9.07 CKS_4272 putative DNA modification methylase A 7.97 5.65 ATP-binding component of an ABC superfamily galactose/methyl galactoside CKS_2185 transporter A 7.93 28.73 CKS_0468 hypothetical protein A 7.91 5.98 CKS_5152 2-isopropylmalate synthase A 7.89 5.83 cytosine/purine/uracil/thiamine/allantoin CKS_0266 permease family protein A 7.83 5.12 membrane component of an ABC superfamily CKS_0964 D-ala-D-ala transporter A 7.76 9.44 CKS_2106 hypothetical protein A 7.75 4.27 methyl-accepting chemotaxis sensory CKS_3278 transducer A 7.67 4.77 CKS_3038 iron-uptake factor A 7.66 8.57 CKS_3837 galactose-1-epimerase (mutarotase) A 7.65 7.05 membrane component of an ABC superfamily CKS_3739 glutamate and aspartate transporter A 7.62 6.69 RND multidrug efflux membrane fusion CKS_3569 protein A 7.61 10.87 putative type III secretion system apparatus CKS_4584 protein A 7.59 6.50 CKS_1750 N-acetylmuramoyl-L-alanine amidase A 7.58 10.94 putative mannosyl-3-phosphoglycerate CKS_2563 phosphatase A 7.53 5.03 DNA-binding transcriptional dual regulator of CKS_2490 nitrogen assimilation A 7.52 8.41 CKS_4021 NAD(P)H-dependent FMN reductase A 7.50 4.73 putative permease component of an ABC CKS_0288 superfamily amino acid transporter A 7.50 8.29 CKS_1697 divalent cation transport protein A 7.49 4.57 CKS_5453 hypothetical protein A 7.48 6.25 CKS_0429 hypothetical protein A 7.47 5.47 181

CKS_4333 beta-glucosidase A 7.43 8.87 CKS_2635 hypothetical protein A 7.37 5.69 CKS_2586 putative adenine methylase A 7.35 9.87 GAF domain/GGDEF domain/EAL domain CKS_3094 protein A 7.34 4.84 periplasmic substrate-binding component of an CKS_4761 ABC superfamily ribose transporter A 7.30 8.66 permease component of an ABC superfamily CKS_3738 glutamate/aspartate transporter A 7.29 5.51 CKS_3534 membrane-fusion protein A 7.27 5.42 CKS_3859 molybdopterin biosynthesis protein B A 7.26 6.65 putative ATP-binding component of an ABC CKS_0290 superfamily amino acid transporter A 7.26 5.83 CKS_4952 acetylornithine deacetylase A 7.23 7.31 CKS_4273 hypothetical protein A 7.21 4.20 CKS_2803 hypothetical protein A 7.20 7.16 CKS_4654 hypothetical protein A 7.19 9.24 CKS_3146 dihydrodipicolinate synthase A 7.18 5.93 CKS_1233 protein disaggregation chaperone A 7.17 9.25 CKS_2441 methyltransferase A 7.15 4.22 CKS_2493 aldehyde dehydrogenase A 7.14 7.50 CKS_2924 metal-activated pyridoxal enzyme A 7.02 5.75 CKS_2377 hypothetical protein A 6.96 4.46 succinate-semialdehyde dehydrogenase I CKS_2492 NADP-dependent A 6.92 6.77 CKS_2487 putative periplasmic binding protein A 6.80 10.60 permease component of an ABC superfamily CKS_2525 ribose transporter A 6.77 6.88 CKS_4056 WrbA family flavoprotein A 6.71 4.85 CKS_0338 glycerol dehydrogenase NAD A 6.66 25.84 CKS_0912 hypothetical protein A 6.60 4.69 CKS_5151 3-isopropylmalate dehydrogenase A 6.59 5.06 CKS_2642 hypothetical protein A 6.57 6.54 CKS_3276 putative avirulence protein A 6.56 4.39 CKS_2983 phytochelatin synthase A 6.41 4.51 permease component of an ABC superfamily CKS_2062 spermidine/putrescine transporter A 6.36 5.47 periplasmic-binding component of an ABC CKS_4020 superfamily alkanesulfonate transporter A 6.35 6.26 putative binding periplasmic protein of ABC CKS_4958 transporter A 6.34 4.28 CKS_2386 hypothetical protein A 6.34 6.16 CKS_3621 aldo-keto reductase A 6.32 29.63

182

CKS_0379 hypothetical protein A 6.30 24.08 CKS_0657 altronate hydrolase A 6.21 6.80 CKS_4593 hypothetical protein A 6.20 6.07 CKS_1037 predicted transporter A 6.19 9.17 CKS_3620 hypothetical protein A 6.17 4.95 long-chain fatty acid outer membrane CKS_2012 transporter A 6.16 5.36 CKS_4762 gluconolactonase A 6.13 6.54 periplasmic substrate binding component of an CKS_3702 ABC superfamily sugar transporter A 6.12 4.33 CKS_4340 heat shock chaperone A 6.04 5.17 serine--pyruvate aminotransferase / L- CKS_0291 alanine:glyoxylate aminotransferase A 6.03 7.16 CKS_5149 3-isopropylmalate isomerase subunit A 6.02 4.07 type III secretion system outermembrane pore CKS_3271 forming protein A 5.99 5.29 CKS_3206 putative amidohydrolase A 5.97 8.15 CKS_3622 pyruvate/alpha-keto-acid decarboxylase A 5.95 6.99 CKS_1696 magnesium transporter A 5.91 4.93 CKS_4764 hypothetical protein A 5.90 5.77 permease component of an ABC superfamily CKS_4760 ribose transporter A 5.89 6.99 CKS_5026 hypothetical protein A 5.89 5.91 CKS_2921 putative RNA polymerase sigma factor A 5.88 5.87 CKS_3540 DNA-binding transcriptional dual regulator A 5.88 13.66 CKS_3983 pyruvate formate lyase activating enzyme 1 A 5.86 4.85 CKS_1698 hypothetical protein A 5.86 4.62 CKS_4484 3-ketoacyl-CoA thiolase (thiolase I) A 5.85 4.91 CKS_3202 ABC superfamily transporter A 5.84 4.21 CKS_3860 molybdopterin biosynthesis protein C A 5.84 8.33 CKS_0941 inosose dehydratase A 5.83 4.56 CKS_4718 acetate permease A 5.78 5.03 ATP-binding component of an ABC CKS_0965 superfamily D-ala-D-ala transporter A 5.78 6.75 periplasmic-binding component of an ABC CKS_0922 superfamily leucine transporter A 5.76 6.69 ATP-binding component of an ABC CKS_4759 superfamily ribose transporter A 5.76 12.00 CKS_4571 virulence protein A 5.73 4.72 CKS_2641 phage baseplate assembly protein V A 5.67 7.15 putative type III secretion system effector CKS_4577 protein A 5.63 8.66 CKS_3241 amidinotransferase family protein A 5.60 4.40

183

CKS_2588 hypothetical protein A 5.59 5.85 CKS_2640 hypothetical protein A 5.58 5.32 CKS_3150 predicted mannonate dehydrogenase A 5.57 4.32 CKS_0791 predicted reductase A 5.54 5.95 CKS_0376 putative phage transposase A 5.45 16.09 CKS_2496 extracellular solute-binding protein family 5 A 5.39 5.57 CKS_2880 predicted transporter A 5.36 4.91 anaerobic ribonucleotide reductase activating CKS_4922 protein A 5.31 5.48 CKS_4247 putative alpha/beta hydrolase A 5.30 8.92 CKS_2587 hypothetical protein A 5.28 6.21 membrane component of an ABC superfamily CKS_4389 dipeptide transporter A 5.25 6.16 CKS_2387 hypothetical protein A 5.24 5.64 CKS_5834 hypothetical protein A 5.22 5.03 CKS_0375 putative DNA-binding protein A 5.21 23.08 CKS_4594 hypothetical protein A 5.17 5.93 CKS_4485 fatty acid oxidation complex subunit alpha A 5.17 37.14 CKS_1045 acetolactate synthase large subunit A 5.14 6.98 type III secretion system cytoplasmic ATP CKS_3255 synthase A 5.03 5.20 CKS_3536 L-ribulokinase A 5.02 4.63 CKS_4523 type III secretion system peptide export protein A 4.98 4.14 CKS_1538 hypothetical protein A 4.97 4.78 CKS_2369 hypothetical protein A 4.96 4.02 CKS_5446 hypothetical protein A 4.94 4.85 CKS_4800 predicted dehydrogenase A 4.94 7.68 CKS_3243 hypothetical protein A 4.94 6.13 CKS_4162 hypothetical protein A 4.93 4.64 CKS_3021 putative NADH:flavin oxidoreductase A 4.92 15.50 CKS_4712 hypothetical protein A 4.92 4.82 CKS_2550 DgsA-binding anti-repressor A 4.91 5.49 CKS_2920 hypothetical protein A 4.90 5.85 CKS_4956 ABC transporter A 4.89 14.79 CKS_2804 putative carbon starvation protein A A 4.84 14.30 CKS_3826 PhoH family ATPase A 4.83 7.51 CKS_0943 5-deoxy-glucuronate isomerase A 4.80 4.71 CKS_2494 type II haloacid dehalogenase A 4.80 4.81 membrane component of an ABC superfamily CKS_0921 leucine/isoleucine/valine transporter A 4.79 5.36 CKS_4332 PTS system cellobiose-specific IIC component A 4.78 6.35 CKS_0377 phage transposase A 4.76 11.68

184

type III secretion system inner membrane CKS_3257 channel protein A 4.76 4.25 zinc-containing alcohol CKS_0640 dehydrogenase/quinone oxidoreductase A 4.76 4.68 CKS_2361 DNA adenine methylase A 4.74 4.14 CKS_4591 secretion system apparatus protein A 4.73 5.26 CKS_5025 phage-related protein A 4.68 4.74 CKS_5455 putative exported protein A 4.68 18.99 CKS_3273 HrpT family protein A 4.64 4.48 putative type III secretion system ATP CKS_4592 synthase A 4.60 5.53 CKS_2015 acetyl-CoA acetyltransferase A 4.59 35.62 CKS_2644 hypothetical protein A 4.57 5.21 ATP-binding component of an ABC CKS_2524 superfamily ribose transporter A 4.55 4.40 CKS_1044 acetolactate synthase small subunit A 4.54 9.52 CKS_5349 putative exported protein A 4.53 17.83 CKS_0960 putative RpiR family transcriptional regulator A 4.52 14.48 CKS_5754 hypothetical protein A 4.51 4.96 CKS_2589 phage-related protein A 4.50 4.82 CKS_2306 uncharacterized DUF1537 family protein A 4.50 7.26 CKS_0658 altronate oxidoreductase NAD-dependent A 4.49 6.43 CKS_3968 cold shock protein A 4.48 16.43 CKS_5389 putative exported protein A 4.47 16.57 CKS_5413 hypothetical protein A 4.45 9.95 CKS_1289 endoribonuclease L-PSP A 4.45 9.98 CKS_3552 mannose-6-phosphate isomerase A 4.44 5.22 CKS_4462 HD superfamily hydrolase A 4.42 4.53 CKS_5393 putative exported protein A 4.42 17.45 membrane component of an ABC superfamily CKS_3844 molybdate transporter A 4.42 8.21 CKS_2307 predicted class II aldolase A 4.38 4.22 CKS_2947 maltose regulon periplasmic protein A 4.33 4.71 CKS_2637 hypothetical protein A 4.33 5.41 CKS_3147 alcohol dehydrogenase A 4.30 5.33 CKS_3143 hypothetical protein A 4.26 4.01 CKS_5356 putative outer membrane adhesion protein A 4.23 5.06 predicted oxidoreductase flavin:NADH CKS_3210 component A 4.18 4.03 CKS_2590 hypothetical protein A 4.17 5.92 CKS_1444 GroES family alcohol dehydrogenase A 4.16 4.07 CKS_2706 PLP-binding alanine racemase 2 A 4.08 4.43 CKS_2629 phage tail sheath protein FI A 4.08 6.56 185

CKS_0272 phytanoyl-CoA dioxygenase family protein A 4.01 4.01 CKS_4368 superoxide dismutase Mn R 4.05 4.10 peptidyl-prolyl cis-trans isomerase B (rotamase CKS_0117 B) R 4.08 4.56 CKS_4123 putative bacteriophage protein R 4.09 5.31 CKS_4125 putative bacteriophage protein R 4.42 5.26 CKS_4121 putative bacteriophage protein R 4.51 7.29 HU DNA-binding transcriptional regulator CKS_0004 alpha subunit R 4.58 4.71 CKS_4122 hypothetical protein R 4.69 6.27 CKS_4134 putative bacteriophage protein R 4.76 6.95 CKS_5198 dihydrolipoamide dehydrogenase R 4.82 5.03 CKS_0744 30S ribosomal subunit protein S6 R 4.84 4.60 CKS_4717 putative exported protein R 4.87 6.62 CKS_4536 type III secretion system effector protein R 4.99 11.16 CKS_4535 type III secretion system regulatory protein R 5.36 8.39 CKS_0742 30S ribosomal subunit protein S18 R 5.52 4.91 CKS_4124 hypothetical protein R 5.71 8.12 CKS_1527 nucleoside diphosphate kinase R 5.76 4.06 CKS_4120 putative bacteriophage protein R 5.78 8.63 CKS_4115 putative bacteriophage protein R 6.00 6.74 CKS_4116 putative bacteriophage protein R 6.00 7.72 CKS_0743 primosomal replication protein N R 6.09 5.48 CKS_4117 putative bacteriophage protein R 6.11 7.45 CKS_4137 hypothetical protein R 6.20 4.87 CKS_4135 putative bacteriophage protein R 6.25 7.93 CKS_4109 putative bacteriophage protein R 6.28 5.60 CKS_0741 50S ribosomal subunit protein L9 R 6.33 5.37 ADP-heptose--lipooligosaccharide CKS_1116 heptosyltransferase II R 6.57 4.88 CKS_4113 hypothetical protein R 6.72 8.85 CKS_4114 putative bacteriophage protein R 7.32 7.69 CKS_4119 putative bacteriophage protein R 7.55 10.89 CKS_4531 type III secretion system apparatus protein R 7.65 14.13 CKS_4091 hypothetical protein R 7.82 4.06 CKS_4118 putative bacteriophage protein R 7.99 10.71 CKS_4092 hypothetical protein R 8.20 5.84 CKS_4136 putative bacteriophage tail protein R 8.32 6.45 3-deoxy-D-arabino-heptulosonate-7-phosphate CKS_1241 synthase tyrosine-repressible R 8.70 6.41 CKS_4538 type III secretion system apparatus protein R 8.80 15.91 CKS_1225 hypothetical protein R 8.91 23.57 CKS_4095 hypothetical protein R 9.89 4.03 186

CKS_4089 hypothetical protein R 13.42 4.95 CKS_4090 hypothetical protein R 13.63 6.30 CKS_4088 hypothetical protein R 16.02 4.33 CKS_4082 hypothetical protein R 16.02 4.10 CKS_4093 CP4-57 family phage integrase R 16.35 5.42 CKS_4081 hypothetical protein R 16.79 4.61 CKS_4084 phage lysozyme R 17.69 5.00 CKS_4537 type III secretion system effector protein R 18.27 36.62 CKS_4085 hypothetical protein R 18.62 5.25 CKS_4083 hypothetical protein R 22.82 6.36 CKS_4087 hypothetical protein R 25.57 6.99 aA = activated in the in planta culture compared to both the pre-inoculum in vitro liquid culture and the in vitro plate culture (lower in the liquid and plate cultures), R = repressed in the in planta culture compared to both the pre-inoculum in vitro liquid culture and the in vitro plate culture (higher in the liquid and plate cultures)

187

Table S2.6. Additional genes with greater than four-fold regulation as calculated through the DESeq analysisa Locus RPM Fold DESeq Fold DESeq Tag Annotation Regulation Regulation padj In planta vs. Pre-inoculum in vitro Liquid Culture predicted DNA-binding CKS_1022 transcriptional regulator R 3.91 5.44 5.70E-31 component of the MscS CKS_1399 mechanosensitive channel R 3.92 5.43 4.16E-30 CKS_1838 predicted metal-binding enzyme R 3.83 5.35 3.30E-28 gluconate-6-phosphate CKS_2276 dehydrogenase decarboxylating R 3.83 5.33 3.76E-28 CKS_0841 hypothetical protein R 3.80 5.31 3.09E-28 CKS_5399 hypothetical protein R 3.75 5.24 1.09E-26 CKS_1952 hypothetical protein R 3.63 5.08 1.56E-26 CKS_4126 putative bacteriophage protein R 3.64 5.06 1.32E-17 diaminobutyrate-pyruvate transaminase/L-24- CKS_0644 diaminobutyrate decarboxylase R 3.85 5.04 2.46E-09 50S ribosomal subunit protein CKS_1580 L29 R 3.62 5.04 6.05E-16 CKS_3122 DNA-binding protein H-NS R 3.59 5.01 2.73E-22 CKS_4472 uridine phosphorylase R 3.53 4.92 4.60E-30 IucB family aerobactin CKS_4775 siderophore biosynthesis protein R 3.66 4.89 6.42E-12 CKS_0018 50S ribosomal subunit protein L1 R 3.52 4.89 1.02E-15 CKS_1166 hypothetical protein R 3.48 4.84 1.32E-23 CKS_2826 lipid hydroperoxide peroxidase R 3.46 4.82 2.28E-29 CKS_0093 hypothetical protein R 3.62 4.79 8.12E-07 DNA-binding transcriptional CKS_4927 repressor R 3.41 4.78 2.93E-28 CKS_5361 hypothetical protein R 3.42 4.74 9.07E-15 50S ribosomal subunit protein CKS_1145 L33 R 3.39 4.73 3.45E-19 CKS_5267 outer membrane protein R 3.39 4.72 1.43E-26 LysR family transcriptional CKS_4782 regulator R 3.33 4.65 9.41E-29 CKS_4076 hypothetical protein R 3.53 4.58 1.54E-05 CKS_5596 putative phage portal protein R 3.75 4.58 5.40E-04 putative phage terminase large CKS_5594 subunit R 3.87 4.58 1.18E-03 peptidoglycan-associated outer CKS_3802 membrane lipoprotein R 3.28 4.55 1.10E-19

188

50S ribosomal subunit protein CKS_3391 L20 R 3.22 4.52 3.89E-28 membrane-bound lytic murein CKS_1267 transglycosylase B R 3.20 4.50 6.73E-26 type III secretion system CKS_4530 cytoplasmic ATP synthase R 3.18 4.46 4.68E-28 putative LysR-type CKS_4835 transcriptional regulator R 3.18 4.45 1.07E-20 CKS_0022 translation elongation factor Tu R 3.21 4.44 3.32E-11 50S ribosomal subunit protein CKS_1581 L16 R 3.18 4.43 2.06E-13 CKS_4127 putative bacteriophage protein R 3.20 4.43 6.73E-12 CKS_1087 putative cytoplasmic protein R 3.13 4.38 6.76E-29 CKS_5600 putative phage capsid protein R 3.60 4.35 1.09E-03 CKS_0852 predicted transporter R 3.09 4.32 9.17E-26 CKS_5582 hypothetical protein R 3.74 4.31 2.85E-03 CKS_4862 30S ribosomal subunit protein S9 R 3.02 4.24 3.67E-21 CKS_0181 DNA-binding protein R 3.02 4.23 2.30E-18 CKS_5792 predicted transcriptional regulator R 3.02 4.22 7.48E-19 peptidyl-prolyl cis/trans CKS_0220 isomerase (trigger factor) R 3.03 4.22 1.41E-12 predicted metallodependent CKS_4238 hydrolase R 3.00 4.21 1.08E-22 NADP-specific isocitrate CKS_4269 dehydrogenase R 3.00 4.18 5.60E-15 CKS_5589 hypothetical protein R 3.63 4.18 4.66E-03 CKS_4108 hypothetical protein R 3.05 4.17 1.60E-07 CKS_1582 30S ribosomal subunit protein S3 R 3.00 4.17 4.45E-11 CKS_0936 DcrB family protein R 2.98 4.17 7.15E-17 50S ribosomal subunit protein CKS_4226 L32 R 2.96 4.17 4.75E-27 CKS_1096 hypothetical protein R 3.00 4.16 3.34E-18 CKS_4132 phage-related protein R 2.98 4.16 8.55E-16 30S ribosomal subunit protein CKS_1579 S17 R 2.96 4.14 5.24E-13 CKS_0625 hypothetical protein R 2.95 4.09 4.00E-10 IucC family aerobactin CKS_4774 siderophore biosynthesis protein R 3.11 4.09 1.23E-07 cytidine/deoxycytidine CKS_2189 deaminase R 2.96 4.08 2.05E-15 O-antigen lipopolysaccharide CKS_2277 chain length regulator R 2.91 4.07 5.09E-19 CKS_5258 30S ribosomal subunit protein S2 R 2.90 4.07 1.83E-20 CKS_3134 hypothetical protein R 2.90 4.07 1.13E-16 189

CKS_1453 alcohol dehydrogenase R 2.96 4.06 2.92E-08 glutamate/aspartate:proton CKS_4721 symporter R 2.89 4.04 2.40E-19 enoyl-[acyl-carrier-protein] CKS_2811 reductase NADH-dependent R 2.87 4.03 2.58E-22 CKS_3164 hypothetical protein R 2.89 4.02 8.07E-18 FKBP-type peptidyl-prolyl cis- CKS_0733 trans isomerase (rotamase) R 2.86 4.02 2.03E-22 50S ribosomal subunit protein CKS_3390 L35 R 2.86 4.02 6.40E-22 putative DNA damage-inducible CKS_4139 protein R 3.00 4.02 1.10E-05 In planta vs. In vitro Plate Culture CKS_5267 outer membrane protein R 3.88 4.95 8.37E-19 CKS_0667 inner membrane protein R 3.84 4.86 9.03E-21 enoyl-[acyl-carrier-protein] CKS_2811 reductase NADH-dependent R 3.78 4.80 8.65E-20 ThiG family thiazole biosynthesis CKS_3056 protein R 3.78 4.76 4.02E-22 uncharacterized DUF615 family CKS_0714 protein R 3.73 4.75 3.24E-18 CKS_3134 hypothetical protein R 3.74 4.75 2.59E-16 CKS_2419 hypothetical protein R 3.73 4.74 5.20E-19 CKS_4984 hypothetical protein R 3.73 4.73 2.50E-14 CKS_2158 putative membrane protein R 3.74 4.73 7.99E-12 putative ATP/GTP-binding component of an ABC CKS_2884 superfamily transporter R 3.87 4.73 1.34E-12 gluconate-6-phosphate CKS_2276 dehydrogenase decarboxylating R 3.74 4.72 3.14E-14 50S ribosomal subunit protein CKS_0017 L10 R 3.63 4.61 2.21E-13 CKS_2217 hydoxyethylthiazole kinase R 3.61 4.59 1.18E-15 23S rRNA pseudouridine CKS_3089 synthase R 3.61 4.58 1.49E-13 CKS_1838 predicted metal-binding enzyme R 3.58 4.56 2.16E-22 protein chain elongation factor CKS_5259 EF-Ts R 3.59 4.56 2.47E-15 CKS_5399 hypothetical protein R 3.58 4.54 2.99E-13 CKS_0841 hypothetical protein R 3.57 4.53 3.04E-13 CKS_0132 hypothetical protein R 3.63 4.52 1.05E-10 uncharacterized DUF2002 family CKS_1466 protein R 3.66 4.50 6.80E-10 CKS_4138 hypothetical protein R 3.51 4.45 2.21E-14 190

CKS_2428 hypothetical protein R 3.53 4.43 2.84E-18 global DNA-binding CKS_0800 transcriptional dual regulator R 3.45 4.39 8.76E-12 CKS_2826 lipid hydroperoxide peroxidase R 3.46 4.38 1.27E-21 NADP-specific isocitrate CKS_4269 dehydrogenase R 3.44 4.37 6.48E-15 CKS_1087 putative cytoplasmic protein R 3.43 4.36 8.99E-14 CKS_0740 hypothetical protein R 3.44 4.31 1.10E-09 membrane-bound lytic murein CKS_1267 transglycosylase B R 3.37 4.30 7.90E-21 50S ribosomal subunit protein CKS_1145 L33 R 3.34 4.23 1.32E-09 peptidyl-prolyl cis/trans CKS_0220 isomerase (trigger factor) R 3.33 4.23 2.47E-15 CKS_0181 DNA-binding protein R 3.31 4.22 1.04E-18 CKS_2726 predicted oxidoreductase R 3.29 4.19 6.27E-16 CKS_1952 hypothetical protein R 3.29 4.19 1.35E-15 CKS_1096 hypothetical protein R 3.29 4.16 2.24E-13 2345-tetrahydropyridine-2- carboxylate N- CKS_5255 succinyltransferase R 3.25 4.15 5.55E-18 CKS_4099 putative phage primase R 3.28 4.14 4.66E-12 CKS_1904 hypothetical protein R 3.36 4.10 1.88E-05 uncharacterized DUF218 family CKS_2187 protein R 3.20 4.09 2.85E-18 DNA-binding transcriptional dual CKS_5195 regulator R 3.18 4.06 2.36E-16 conserved inner membrane CKS_0666 protein R 3.15 4.01 9.59E-17 acetyl-CoA carboxylase CKS_5274 carboxytransferase alpha subunit R 3.13 4.00 8.79E-14 aR = repressed in the in planta culture compared to either the pre-inoculum in vitro liquid culture or the in vitro plate culture (higher in the liquid or plate cultures)

191

Table S2.7. Results for qRT-PCR validation for the in planta culture and the pre-inoculum in vitro liquid culture comparisona. Fold Fold Fold Regulation Regulation Regulation RNA-Seq (recF (atpD (gyrB RPM Fold Locus Tag Gene reference) reference) reference) Regulation CKS_3263 139.65 38.51 244.12 52.64 CKS_3793 15.47 4.27 27.04 36.48 CKS_4032 rmf 34.02 9.38 59.47 28.23 CKS_1591 bfr 31.85 8.78 55.68 27.19 CKS_3570 39.12 10.79 68.39 19.33 CKS_4657 aceB 45.69 12.60 79.88 15.20 CKS_2714 yeaG 44.55 12.28 77.88 8.22 CKS_2505 7.92 2.18 13.85 4.20 CKS_0004* hupA 2.22 8.33 1.27 4.58 CKS_4537* 3.70 14.29 2.13 18.27 aGenes upregulated (activated) in planta, with the exception of those designated * which were downregulated (repressed) in planta.

192

Table S2.8. Results for qRT-PCR validation for the in planta culture and the in vitro plate culture comparisona. Fold Fold Fold Regulation Regulation Regulation RNA-Seq (recF (atpD (gyrB RPM Fold Locus Tag Gene reference) reference) reference) Regulation CKS_3263 188.99 159.30 200.06 58.52 CKS_3793 47.56 40.09 50.34 31.45 CKS_4032 rmf 4.38 3.69 4.63 3.70 CKS_1591 bfr 26.75 22.54 28.31 14.97 CKS_3570 24.22 20.42 25.64 45.70 CKS_4657 aceB 35.46 29.89 37.54 15.65 CKS_2714 yeaG 6.97 5.88 7.38 3.16 CKS_2505 5.46 4.60 5.78 2.13 CKS_0004* hupA 3.85 4.55 3.57 4.71 CKS_4537* 3.45 4.17 3.33 36.62 aGenes upregulated (activated) in planta, with the exception of those designated * which were downregulated (repressed) in planta.

193

Table S2.9. GO gene groups from four-fold regulated genes in the in planta culture compared to the pre-inoculum in vitro liquid culture.

GO.ID Term Annotated Significant Expected weight01Fisher Upregulated in planta oxidation- reduction GO:0055114 process 164 31 12.6 1.10E-06 biotin biosynthetic GO:0009102 process 7 6 0.54 1.30E-06 leucine biosynthetic GO:0009098 process 4 4 0.31 3.40E-05 GO:0006810 transport 510 61 39.2 0.00035 GO:0009405 pathogenesis 17 5 1.31 0.0073 GO:0009306 protein secretion 41 8 3.15 0.011 Downregulated in planta GO:0006323 DNA packaging 8 2 0.09 0.0030 GO:0006412 translation 108 6 1.17 0.0037 tyrosine biosynthetic GO:0006571 process 1 1 0.01 0.011 UTP biosynthetic GO:0006228 process 1 1 0.01 0.011 CTP biosynthetic GO:0006241 process 1 1 0.01 0.011 GO:0015758 glucose transport 1 1 0.01 0.011 GTP biosynthetic GO:0006183 process 1 1 0.01 0.011 GO:0009405 pathogenesis 17 2 0.18 0.014

194

Table S2.10. GO gene groups from four-fold regulated genes in the in planta culture compared to the in vitro plate culture.

GO.ID Term Annotated Significant Expected weight01Fisher Upregulated in planta phosphoenolpyruvate- dependent sugar phosphotransferase GO:0009401 system 34 12 3.45 6.50E-05 oxidation-reduction GO:0055114 process 164 33 16.62 9.00E-05 leucine biosynthetic GO:0009098 process 4 4 0.41 0.00010 GO:0006810 Transport 510 88 51.7 0.00021 GO:0009405 Pathogenesis 17 7 1.72 0.00081 Mo-molybdopterin cofactor biosynthetic GO:0006777 process 9 5 0.91 0.00092 galactose metabolic GO:0006012 process 4 3 0.41 0.0038 GO:0015689 molybdate ion transport 4 3 0.41 0.0038 glucuronate catabolic GO:0006064 process 2 2 0.2 0.010 Downregulated in planta NAD biosynthetic GO:0009435 process 6 2 0.09 0.0031 GO:0006323 DNA packaging 8 2 0.12 0.0058 thiamine biosynthetic GO:0009228 process 8 2 0.12 0.0058

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REFERENCES Kernell Burke A, Duong DA, Jensen RV, Stevens AM. 2015. Analyzing the transcriptomes of two quorum-sensing controlled transcription factors, RcsA and LrhA, important for Pantoea stewartii virulence. PLoS ONE 10:e0145358.

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APPENDIX B Chapter 3 Supplementary Information

197

0.1

0.01 Relative Competition Index Competition Relative

0.001 ompC DSJ_00125 DSJ_03645 DSJ_18135 DSJ_21690

Figure S3.1. Competition assay for P. stewartii mutant strains lacking select unannotated genes. Deletion (NalR) and complementation (NalR/CmR) strain sets of DSJ_00125, DSJ_03645,

DSJ_18135, and DSJ_21690 mutants, and the ompC positive control, were co-inoculated into the corn seedlings at a 1:1 ratio. The relative competition index (RCI) for each set was calculated as the ratio of deletion to complementation strains extracted five days post-inoculation over the ratio of deletion to complementation strains in the inoculum. N ≥ 5 per inoculum.

198

5 4.5 4 3.5 3 2.5 2

Disease Disease Score 1.5 * 1 0.5 * 0

Figure S3.2. Virulence of P. stewartii DSJ_00125, DSJ_03645, DSJ_18135, and DSJ_21690 mutant and complementation strains. Average disease score for the following P. stewartii strains: wild type (WT; white), ∆rcsA as a positive control (gray), ∆00125, ∆00125/00125+

(orange), ∆03645, ∆03645/03645+ (blue), ∆18135, ∆18135/18135+ (green), ∆21690, and

+ ∆21690/21690 (yellow). PBS was used as a negative control. Scores were collected ten days post-inoculation from a minimum of 15 plants. An asterisk (*) represents a significant difference from the wild-type strain (p ≤ 0.01) using the Student’s T-Test. Error bars were calculated using the standard error for each set.

199

A B 4 4 3 3 2 2 1 1 0 0

-1 -1 Relative Expression Relative Relative Expression Relative -2 -2 cydA hmp lysP

Figure S3.3. qRT-PCR expression of select genes in the WT strain compared to transcription factor deletion strains. Transcripts using qRT-PCR from in planta grown WT P. stewartii (blue) are shown with in planta grown A) ∆iscR and B) ∆nsrR and strain transcripts

(orange). Ct values are averaged from three experimental samples per strain analyzed in triplicate and were normalized using the Ct values of the reference gene atpD. Error bars are represented as estimates of the sample standard error across the three biological replicates.

200

Figure S3.4. Capsule production phenotype of DSJ_00125, DSJ_03645, DSJ_18135, and

DSJ_21690 mutant and complementation strains with controls. All photographs were taken at the same magnification after a 48 hr incubation in 30°C on CPG agar.

201

Figure S3.5. Surface motility phenotype of DSJ_00125, DSJ_03645, DSJ_18135, and

DSJ_21690 strains with controls. All photographs were taken at the same magnification after a

48 hr incubation in 30°C on LB medium (0.4% agar, 0.4% glucose).

202

APPENDIX C Chapter 4 Supplementary Information

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Table S4.1. Primers used in this studya,b Amplification Target and Sequence Source Purpose 16S rRNA gene coding F: AGA GTT TGA TCM TGG CTC AG Weisburg et sequence (27F-1492R) R: ACC TTG TTA CGA CTT al., 1991 ITS2 region F: AGGAGAAGTCGTAACAAGGT White et al., R: TCCTCCGCTTATTGATATGC 1990 gyrB partial coding sequence F: TAC ATC GGA TCA ACT AAC AGC This study R: CGT ATC AGT GAT CGT TCT CG pyrE partial coding sequence F: TTT ACG CCC GAA TGA GCC This study R: TTG ACT CGG GAT TCT GTT TCC rpoB partial coding sequence F: GTT GGC TTC ATG ACT TGG GA Liu et al., R: ACG TTC CAT ACC TAA ACT TTG 2013 Illumina MiSeq sequencing F: TAT GGT ATT TGT GTG YCA GCM GCC EMP GCG GTA A R: AGT CAG CCA GCC GGA CTA CNV GGG TWT CTA AT Index: ATT GAT ACG GCG ACC ACC GAG ATC TAC ACG CT 16S rRNA gene V4 region CAA GCA GAA GAC GGC ATA CGA GAT EMP reverse primer (with adapter, AGT CAG CCA GCC GGA CTA CNV GGG primer pad, linker) TWT CTA AT 16S rRNA gene V4 region AATGATACGGCGACCACCGAGATCTACA EMP forward primer: R1D0 CGCTAAGTCACACACATATGGTAATTGT GTGYCAGCMGCCGCGGTAA 16S rRNA gene V4 region AATGATACGGCGACCACCGAGATCTACA EMP forward primer: R1D1 CGCTTTACTTATCCGATATGGTAATTGTG TGYCAGCMGCCGCGGTAA 16S rRNA gene V4 region AATGATACGGCGACCACCGAGATCTACA EMP forward primer: R1D4 CGCTGTGTCGAGGGCATATGGTAATTGT GTGYCAGCMGCCGCGGTAA 16S rRNA gene V4 region AATGATACGGCGACCACCGAGATCTACA EMP forward primer: R1D5 CGCTACGGCGTTATGTTATGGTAATTGT GTGYCAGCMGCCGCGGTAA 16S rRNA gene V4 region AATGATACGGCGACCACCGAGATCTACA EMP forward primer: R1D8 CGCTAGTTGTAGTCCGTATGGTAATTGT GTGYCAGCMGCCGCGGTAA 16S rRNA gene V4 region AATGATACGGCGACCACCGAGATCTACA EMP forward primer: R2D0 CGCTGAAGTAGCGAGCTATGGTAATTGT GTGYCAGCMGCCGCGGTAA 16S rRNA gene V4 region AATGATACGGCGACCACCGAGATCTACA EMP forward primer: R2D1 CGCTATGGGACCTTCATATGGTAATTGT GTGYCAGCMGCCGCGGTAA

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16S rRNA gene V4 region AATGATACGGCGACCACCGAGATCTACA EMP forward primer: R2D4 CGCTTTCCACACGTGGTATGGTAATTGT GTGYCAGCMGCCGCGGTAA 16S rRNA gene V4 region AATGATACGGCGACCACCGAGATCTACA EMP forward primer: R2D5 CGCTGAACCGTGCAGGTATGGTAATTGT GTGYCAGCMGCCGCGGTAA 16S rRNA gene V4 region AATGATACGGCGACCACCGAGATCTACA EMP forward primer: R2D8 CGCTAGGGACTTCAATTATGGTAATTGT GTGYCAGCMGCCGCGGTAA 16S rRNA gene V4 region AATGATACGGCGACCACCGAGATCTACA EMP forward primer: R3D0 CGCTTGGCAGCGAGCCTATGGTAATTGT GTGYCAGCMGCCGCGGTAA 16S rRNA gene V4 region AATGATACGGCGACCACCGAGATCTACA EMP forward primer: R3D1 CGCTGTGAATGTTCGATATGGTAATTGT GTGYCAGCMGCCGCGGTAA 16S rRNA gene V4 region AATGATACGGCGACCACCGAGATCTACA EMP forward primer: R3D4 CGCTTATGTTGACGGCTATGGTAATTGT GTGYCAGCMGCCGCGGTAA 16S rRNA gene V4 region AATGATACGGCGACCACCGAGATCTACA EMP forward primer: R3D5 CGCTAGTGTTTCGGACTATGGTAATTGT GTGYCAGCMGCCGCGGTAA 16S rRNA gene V4 region AATGATACGGCGACCACCGAGATCTACA EMP forward primer: R3D8 CGCTATTTCCGCTAATTATGGTAATTGTG TGYCAGCMGCCGCGGTAA aBarcodes for the 16S rRNA gene V4 region forward primers are indicated by the underlined sequences. Remaining sequence includes adapter, primer pad, linker, and actual primer sequence, which are all identical for the barcoded primers. Reactor samples are designated by replicate (R) and day of enrichment (D). An example is R1D4, a sample from the first reactor replicate, taken on the fourth day of enrichment. bEMP = Earth Microbiome Project (Gilbert, Jansson, & Knight, 2014), ITS2 = internal transcribed spacer region 2

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Table S4.2. Binary growth combinations performed with laboratory strains and environmental isolatesa M1 M2 M3 M11 UAE2 UAE4 M2 X M3 X X M5 X X X M6 X X X M7 X X X M11 X X X UAE2 X X X X UAE4 X X X X X UAE5 X X X X X X UAE10 X X X X aCombinations performed are designated with “X”

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S4.1 Figure. Growth rates and yields of laboratory strains and enrichment isolates grown in monoculture on syrup from three production facilities. M = monoculture from laboratory isolates. UAE = unknown aerobically plated environmental isolate. UAN = unknown anaerobically plated environmental isolate. Data averaged from three replicate growth assay plates, with data from each plate an average of three replicate wells across four days. Error bars were estimated using the sample standard error of the log absorbance across three independent replicate plates.

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S4.2 Figure. Growth of binary combinations of laboratory strains and environmental isolates. Graphs depicting example trends for intermediate combination growth (A), combination growth aligning with monoculture growth (B), or slight increase in combination growth compared to monocultures (C). Syrup 2 was used for all experiments. Data averaged from three replicate plates, with data from each plate an average of three replicate wells. Error bars were estimated with the sample standard error of the log absorbance across three independent replicate plates.

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REFERENCES Gilbert JA, Jansson JK, Knight R. 2014. The Earth Microbiome project: successes and aspirations. BMC Biol 12(1). doi:10.1186/s12915-014-0069-1 Liu Y, Lai Q, Dong C, Sun F, Wang L, Li G, Shao Z. 2013. Phylogenetic diversity of the Bacillus pumilus group and the marine ecotype revealed by multilocus sequence analysis. PLoS ONE 8(11):e80097. doi: 10.1371/journal.pone.0080097 Weisburg WG, Barns SM, Pelletier DA, Lane DJ. 1991. 16S ribosomal DNA amplification for phylogenetic study. J Bacteriol 173(2):697-703. White TJ, Bruns T, Lee S, Taylor J. 1990. Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. In: Innis MA, Gelfand DH, Sninsky JJ, and White TJ (ed.). PCR Protocols: A Guide to Methods and Applications. San Diego, CA: Academic Press, 315-22.

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