Assessment of a Novel Delivery System for Microbial Inoculants and the Novel Microbe Mitsuaria Spp

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Assessment of a novel delivery system for microbial inoculants and the novel microbe Mitsuaria spp. H24L5A

THESIS

Presented in Partial Fulfillment of the Requirements for the Degree Master of Science in the Graduate School of The Ohio State University

Donald Patriq Bruce Gillis

Graduate Program in Plant Pathology

The Ohio State University

2016

Master's Examination Committee:

Dr. Christopher G. Taylor, Advisor

Dr. Joshua Blakeslee

Dr. Michelle Jones

Copyrighted by

Donald Patriq Bruce Gillis

2016

Abstract

The demand for alternatives to chemical based products has increased along with the popularity of natural products. Microbial based products including biopesticides and biofertilizers are being used for the promotion of plant growth and control of pests.

Delivery of these products has improved in recent years; many formulations and delivery methods have been examined and tested to determine the optimal conditions for growth and delivery of microbial products. In this study, a quality control assessment was carried out on a novel fermentation system created by an Ohio based company. This product utilizes actively growing bacterial strains to directly inoculate seeds or soil with beneficial microbes. The microbes used in this system are Pseudomonas brassicacearum strains. Additionally, field and greenhouse studies were conducted that examined the efficacy of microbes in this novel fermentation system as well as a novel microbe isolated from Ohio soils, Mitsuaria spp. H24L5A compared to industry standards and other know beneficial microbes. Small increases were seen in bacterial numbers during increasing days of storage while detection of inoculants was possible early after initial inoculation of the system. Mitsuaria spp. H24L5A showed a small increase in stand and stand and yield

ii on corn and soybean plots when used as a seed treatment. A trend of small increases in plant growth was also noted with soil inoculation of the novel microbe. This data indicates that there is potential for the novel fermentation system to be used to increase bacterial biomass soon after introduction of the target microbe for future delivery as a seed or soil treatment. The plant growth promoting activity of Mitsuaria spp. H24L5A is also suggested by the increases seen in both field and greenhouse experiments.

iii

Dedication

To my ever supportive family:

Mom and dad, I thank you for your endless support over the years since I realize my passion for science. David and Maya, thank you for your patience; even when you were

ready for me to come home you always supported me from 600 miles away. And to my

two angels in heaven, Eva and Elmer, this is for you.

Acknowledgments

I would like to thank:

My advisory committee members Dr. Christopher Taylor, Dr. Joshua Blakeslee and Dr. Michelle Jones. Your support over the last year has made this moment in time possible.

All members of the McSpadden Gardener and Taylor labs. All of you have been my family away from home and an amazing support system both in and out of the lab. I would not have made it through the program without friends like you.

The Department of Plant Pathology and everyone in Selby and Kottman; thank you for letting me be me and accepting me and allowing me to be a part of your family.

My best friends: Ashley, Loren, Vashti, Kandyce, Adrienne, Sue, Martavius,

Bianca, Corey, Fred, Brooke, Taylor, Terrance and Samantha. You all have been my main support system these last few years and I thank God that I have you all in my corner. You all definitely kept me grounded and focused on the end goal and I thank you.

My line brothers for being supportive and patient with the distance as I pursued my passion.

Finally, my family, for their support and understanding during this time

Vita

2009...... B.S. Biology, Morehouse College

2013 to present ...... Graduate Student, Department of Plant

Pathology, The Ohio State University

Fields of Study

Major Field: Plant Pathology

Table of Contents

Abstract ...... ii

Dedication ...... iv

Acknowledgements ...... v

Vita ...... vi

Table of Contents ...... vii

List of Tables ...... ix

List of Figures ...... xi

Chapter 1. Introduction ...... 1

Chapter 2: Formulation, stability and purity of a bacterial inoculant in a novel delivery sytem ...... 34

Abstract ...... 34

Introduction ...... 36

Materials and Methods ...... 40

Results ...... 45

vii

Discussion ...... 49

Chapter 3: Assessment of Mitsuaria spp. H24L5A plant growth promotion, pathogen

suppression activity and mode of action ...... 74

Abstract ...... 74

Introduction ...... 76

Materials and Methods ...... 80

Results ...... 89

Discussion ...... 92

List of References ...... 123

Appendix: Bioinformatic analysis of Mitsuaria spp. H24L5A for select biocontrol

enzymes...... 137

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List of Tables

Table 1.1. List of commercially available microbial based products...... 32

Table 1.1 Continued. List of commercially available microbial based products ...... 33

Table 3.1. List of treatments used in field assays on corn and soybean seeds and greenhouse assays on ...... 106

Table 3.2. Average stand and yield across 10 counties for corn and 6 counties for soybean

...... 107

Table 3.3. Average stand and yield per treatment for soybeans across six counties in Ohio

...... 108

Table 3.4. Stand and yield data from a soybean field site in Mercer County, OH (Site

Code: C1). No significant differences were seen across treatments ...... 109

Table 3.5. Stand and yield data from a soybean field site in Clark County, OH (Site Code:

C2). No significant differences were seen across treatments ...... 110

Table 3.6. Stand and yield data from soybean field site in Henry County, OH (Site code:

N1). No significant differences were seen across treatments ...... 111

Table 3.7. Stand and yield data from soybean field site in Erie County, OH (Site code:

N2). No significant differences were seen across treatments ...... 112

Table 3.8. Stand and yield data from soybean field site in Preble County, OH (Site code:

S1). No significant differences were seen across treatments ...... 113

Table 3.9. Stand and yield data from soybean field site in Clinton County, OH (Site code:

S2). No significant differences were seen across treatments ...... 114

Table 3.10. Summary of disease suppression assays from Summer 2015 greenhouse trials

...... 115

List of Figures

Figure 2.1. Bioreactord developed by 3Bar Biologics Inc. Caps contain solid soybean

matrix with target microbe(s)...... 59

Figure 2.2. Bacterial counts on a seed matrix in 1/10 TSB after 1, 7, 21, 90 and 180 days of cap storage ...... 60

Figure 2.3. Bacterial counts on a seed matrix in 1/10 TSB+Rif50 after 1, 7, 21, 90 and 180

days of cap storage ...... 61

Figure 2.4. Bacterial counts in an actively growing bioreactor system in 1/10 TSB after 4,

14, 42, and 78 days of storage and 24 hours of incubation ...... 62

Figure 2.5. Bacterial counts in an actively growing bioreactor system in 1/10 TSB+Rif50

after 4, 14, 42, and 78 days of storage and 24 hours of incubation ...... 63

Figure 2.6. Bacterial counts in an actively growing bioreactor system in 1/10 TSB after

4, 14, 42, and 78 days of storage and 7 days of incubation ...... 64

Figure 2.7. Bacterial counts in an actively growing bioreactor system in 1/10 TSB+Rif50

after 4, 14, 42, and 78 days of storage and 7 days of incubation ...... 65

Figure 2.8. Amplification of phlD by polymerase chain reaction (PCR) for 1 day, 7 days

and 21 days post cap inoculation with target microbes in 1/10 TSB on a soybean matrix.

Lanes marked with 1 contained samples inoculated with Pseudomonas brassicacearum

strain Wood1R, lanes with 3 contained samples inoculated with P. brassicacearum strain

Wood3R and lanes marked with 0 contained samples inoculated with sterile water. Lanes with (+) were positive controls with Pseudomonas brassicacearum strain Wood3R.

Lanes with (-) were negative controls with sterile water. Products were separated on a

1.5% agarose gel and visualized with ethidium bromide staining ...... 66

Figure 2.9. Amplification of phlD by polymerase chain reaction (PCR) for 90 days and

180 days post cap inoculation with target microbes in 1/10 TSB on a soybean matrix.

Lanes marked with 1 contained samples inoculated with Pseudomonas brassicacearum

strain Wood1R, lanes with 3 contained samples inoculated with P. brassicacearum strain

Wood3R and lanes marked with 0 contained samples inoculated with sterile water.

Products were separated on a 1.5% agarose gel and visualized with ethidium bromide

staining ...... 67

Figure 2.10. Amplification of phlD by polymerase chain reaction (PCR) for 1 day, 7 days

and 21 days post cap inoculation with target microbes in 1/10 TSB amended with

Rifampicin on a soybean matrix. Lanes marked with 1 contained samples inoculated with

Pseudomonas brassicacearum strain Wood1R, lanes with 3 contained samples inoculated

with P. brassicacearum strain Wood3R and lanes marked with 0 contained samples

inoculated with sterile water. Lanes with (+) were positive controls with Pseudomonas

brassicacearum strain Wood3R. Lanes with (-) were negative controls with sterile water.

xii

Products were separated on a 1.5% agarose gel and visualized with ethidium bromide

staining...... 68

Figure 2.11. Amplification of phlD by polymerase chain reaction (PCR) for 90 days and

180 days post cap inoculation with target microbes in 1/10 TSB amended with

Rifampicin on a soybean matrix. Lanes marked with 1 contained samples inoculated with

Pseudomonas brassicacearum strain Wood1R, lanes with 3 contained samples inoculated

with P. brassicacearum strain Wood3R and lanes marked with 0 contained samples

inoculated with sterile water. Products were separated on a 1.5% agarose gel and

visualized with ethidium bromide staining ...... 69

Figure 2.12. Amplification of phlD by polymerase chain reaction (PCR) for 4 days and

14 days post cap inoculation with target microbes in 1/10 TSB in actively growing bioreactors. Numbers in parentheses are days after activation of bioreactors. Lanes marked with 1 contained samples inoculated with Pseudomonas brassicacearum strain

Wood1R, lanes with 3 contained samples inoculated with P. brassicacearum strain

Wood3R and lanes marked with 0 contained samples inoculated with sterile water. Lanes with (+) were positive controls with Pseudomonas brassicacearum strain Wood3R.

Lanes with (-) were negative controls with sterile water. Products were separated on a

1.5% agarose gel and visualized with ethidium bromide staining...... 70

Figure 2.13. Amplification of phlD by polymerase chain reaction (PCR) for 14 days and

42 days post cap inoculation with target microbes in 1/10 TSB in actively growing

bioreactors. Numbers in parentheses are days after activation of bioreactors. Lanes

marked with 1 contained samples inoculated with Pseudomonas brassicacearum strain

Wood1R, lanes with 3 contained samples inoculated with P. brassicacearum strain

xiii

Wood3R and lanes marked with 0 contained samples inoculated with sterile water. Lanes with (+) were positive controls with Pseudomonas brassicacearum strain Wood3R.

Lanes with (-) were negative controls with sterile water. Products were separated on a

1.5% agarose gel and visualized with ethidium bromide staining...... 71

Figure 2.14. Amplification of phlD by polymerase chain reaction (PCR) for 4 days and

14 days post cap inoculation with target microbes in 1/10 TSB amended with Rifampicin in actively growing bioreactors. Numbers in parentheses are days after activation of bioreactors. Lanes marked with 1 contained samples inoculated with Pseudomonas brassicacearum strain Wood1R, lanes with 3 contained samples inoculated with P. brassicacearum strain Wood3R and lanes marked with 0 contained samples inoculated with sterile water. Lanes with (+) were positive controls with Pseudomonas brassicacearum strain Wood3R. Lanes with (-) were negative controls with sterile water.

Products were separated on a 1.5% agarose gel and visualized with ethidium bromide staining...... 72

Figure 2.15. Amplification of phlD by polymerase chain reaction (PCR) for 14 days and

42 days post cap inoculation with target microbes in 1/10 TSB amended with Rifampicin in actively growing bioreactors. Numbers in parentheses are days after activation of bioreactors. Lanes marked with 1 contained samples inoculated with Pseudomonas brassicacearum strain Wood1R, lanes with 3 contained samples inoculated with P. brassicacearum strain Wood3R and lanes marked with 0 contained samples inoculated with sterile water. Lanes with (+) were positive controls with Pseudomonas brassicacearum strain Wood3R. Lanes with (-) were negative controls with sterile water.

xiv

Products were separated on a 1.5% agarose gel and visualized with ethidium bromide staining...... 73

Figure 3.1. Map of Ohio with corn and soybean sites used in study. Sites marked in red are corn and sites marked in black are soybean ...... 117

Figure 3.2. Growth index of tomatoes from greenhouse bioassays. Treatments that share a letter are not significantly different (P-value >0.05) ...... 118

Figure 3.3. Dry shoot weight of tomatoes from greenhouse bioassays. Treatments that share a letter are not significantly different (P-value >0.05) ...... 119

Figure 3.4. Dry root weight of tomatoes from greenhouse bioassays. Treatments that share a letter are not significantly different (P-value >0.05) ...... 120

Figure 3.5 Chitin amended media with clearing halos surrounding Bacillus cereus strain 63B7 colonies. Presence of halos means positive for chitinase production...... 121

Figure 3.6. Chitosan amended media with clearance zones by Bacillus cereus strain 63B7. Presence of clearance means strain is positive for chitosanase production ...... 120

Figure A.1. Alignment of amino acid sequences of chitosanase genes for Serratia marcescens* (977773457), Bacillus cereus* (28883525), Paenibacillus spp. 1794*

(399936398), Mitsuaria chitosanitabida* (8131580), Mitsuaria spp. 67* (57471770),

Flavobacterium spp. 2* (67866611), Mitsuaria spp. 141* (327082573),

Sphingobacterium spp. 62* (57471768), Janthinobacterium agaricidamnosum*

(571466520), Streptomyces coelicolor (21219207), Mitsuaria spp. H24L5A (Mitsuaria), and Streptomyces spp. N174 (ICHKA and ICHKB) (1633271 and 1633272). Those with

xv an * have known enzyme activity. Alignment was made using MUSCLE program

(http://www.ebi.ac.uk/Tools/msa/muscle/) ...... 137

Figure A.2. Alignment of amino acid sequences of chitinase genes for Serratia marcescens* (92647632), Bacillus thuringensis* (922897298), Streptomyces coelicolor*

(21224292), Streptomyces halstedii* (134026356), Stenotrophomonas maltophilia*

(2429326), Mitsuaria spp. H24L5A (Mitsuaria), Serratia marcescens* (635010865),

Paenibacillus chitinolyticus* (754868291), and Bacillus cereus* (45827175). Those with an * have known enzyme activity. Alignment was made using MUSCLE program

(http://www.ebi.ac.uk/Tools/msa/muscle/) ...... 141

Figure A.3. Alignment of amino acid sequences of tannase precursor genes for

Xanthomonas campestris pv. campestris ATCC 33913 (21113223), Acetobacter pomorum (685627598), Mitsuaria spp. H24L5A (Mitsuaria), Pseudomonas stutzeri

ATCC 17588-LMG11199 (338801025), Pseudomonas stutzeri DSM 4166 (327480286),

Burkholderia caribensis MBA4 (944369702), Burkholderia caenocepacia H111

(590121330), Klebsielle pneumoniae subsp. Pneumoniae 1158 (743574068), Pantoea spp. A5-DWVM4 (544019939), Bacillus thermotolerans (805309945), and Variovorax spp. WDC1 (983055850. Alignment was made using MUSCLE program

(http://www.ebi.ac.uk/Tools/msa/muscle/) ...... 144

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CHAPTER 1

Introduction

Importance of agriculture

There is a growing demand for food production not only by the U.S., but globally.

The United States Department of Agriculture’s Economic Research Service (USDA ERS) reported that the world population is projected to grow from 6.3 billion to 9.3 billion by

2050, a 47% population increase. Tilman et al. (2002) predicted that “By 2050, the global population is projected to be 50% larger than at present and global grain demand is projected to double”. The majority of this population growth is expected in sub-Saharan

Africa (USDA, 2014). Global per capita income is also expected to increase, with a resulting shift in diets worldwide to processed foods and food rich in refined sugars and animal protein, thus putting further demand on food crop production (USDA, 2014).

There are a number of factors that will affect our ability to produce the necessary food to support the predicted rise in population. Large scale changes in land use, changes in environmental climate, reduction in soil fertility, erosion of soils, conversion of arable land for use in producing biofuels or non-agricultural uses, and crop losses due to plant pathogens and insects are just some of the factors that will affect our ability to meet the growing demand for food production. On top of these factors, developing methods for more sustainable farming practices that reduce the negative impacts of agriculture on the environment and on the health of the human population makes the growing production challenges even more daunting. Though the scope of the problems 1

facing modern agriculture is enormous, this chapter will examine biological-based factors that affect production in four of Ohio’s major crops, namely corn, soybean, tomato and wheat. This chapter will review important diseases affecting these major crops and the potential of novel biologically-based products that may augment current production systems to enhance disease resistance, improve plant growth and increase yield.

Biological-based factors that contribute to decreases in agricultural production systems

Biological-based factors that affect crop production systems in Ohio can be grouped into seven major groups; insects, nematodes, fungi, oomycetes, phytoplasma, bacteria and viruses. Historically the study of insects (also known as Entomology) has been separated from the study of the other six groups (loosely grouped together in the field of Plant Pathology). Although insects are important factors in crop production systems and numerous insects and related arthropods are used as biocontrol agents, for the purpose of this review we will focus on those biological factors (both disease and beneficial) that fall normally in the area of Plant Pathology.

Plant pathogens are responsible for billions of dollars of losses across various crops worldwide. It was reported in 1994 that North America had an estimated loss of

$7.1 billion due to plant diseases from 1988 to 1990 (Oerke et al., 1999). The losses in potential production (actual production plus estimated losses) were 9.7% across all crop systems in North America. Losses were even higher in other regions of the globe (Oerke et al., 1999). Plant diseases continue to cause significant losses in all crops grown.

Currently, a combination of approaches including biological control (Keel et al., 1992;

Nejad and Johnson, 2000), cultural practices (Howard, 2009), chemical control (Anke,

1994), and host-disease resistance (Demirbas et al., 2001) can assist in decreasing the

incidence of disease.

Plant diseases often manifest themselves in the form of disease symptoms. There

are a wide range of symptoms associated with plant diseases that includes

underdeveloped plant tissue such as stunting or malformed leaves, overdevelopment of

tissue such as galls on roots or stems, tissue death seen in necrotic lesions, and alteration

of a plant’s normal appearance such as mosaic patterns on leaves (Riley et al., 2002).

Ultimately, these changes in plant growth reduce yield and result in economic losses to

the grower. There are many factors that contribute to disease development. These factors

include temperature, humidity or moisture, inoculum levels, virulence of the pathogen,

host genetics and cultural practices. For example, Aspergillus flavus prefers hot, dry

conditions for infection of maize and other related plants (Amaike and Keller, 2011).

Sclerotinia sclerotiorum, the causal agent of white mold, has been shown to have

increased symptom development when incubated at lower temperatures (10°C - 25°C)

and high relative humidity (Weiss et al., 1980). Disease incidence was also increased in field plots with increased irrigation (Weiss et al., 1980). These are just a few of the factors that can affect disease development that can ultimately lead to crop loss.

Important pathogens on Ohio crops

There are numerous pathogens that attack corn, soybean, tomato and wheat. It is difficult to narrow down management to just one pest as there is rarely only one stressor contributing to plant health decline. Furthermore, many pathogens can have multiple hosts whose methods of control can vary from crop to crop. However, there are several

important diseases of some of the biggest crops grown in Ohio in which proper

management can impact plant growth and health and increase yield.

Corn (also maize; Zea mays), a crop that is grown in large quantities and easily stored for long term use, is widely grown throughout the U.S. and has a number of uses including animal feed, human consumption, biofuel production and industrial product production. In 2015, 3.5 million acres of corn were planted with a reported yield of 153 bushels per acre (USDA, 2016). Ohio is ranked seventh in corn production in the United

States with 760,000 acres harvested in 2014 in Northwest Ohio alone (USDA, 2015).

However, corn production is impacted by several important diseases in Ohio and across the U.S. In 2012 in the 12 most northern corn producing states (of which Ohio is included), Aspergillus (Aspergillus flavus) and Fusarium (Fusarium verticillioides) ear rot caused 99.9 and 89.9 million bushels of lost corn, respectively (Wise, 2014). Both pathogens cause infection by way of their mycelia from germinated conidia (Oren et al.,

2003; Amaike and Keller, 2011). Airborne fungal conidia infect the silks of maize plants and move to the kernels where rot symptoms develop (Oren et al., 2003; Amaike and

Keller, 2011). These pathogens and their subsequent disease affect grain quality and crop marketability as well as livestock health due to mycotoxins produced by the disease agent

(Woloshuck and Wise, 2011). Other important diseases of corn include Pythium damping off (Pythium ultimum), corn smut (Ustilago maydis), Fusarium stalk rot (Fusarium verticillicoides), grey leaf spot (Cercospora zeae-maydis), and Northern corn leaf blight

(Exoserhilum tercicum), each having an impact in reducing yield (Wise, 2014).

Management of diseases such as these are important in ensuring the health of the

harvested crop, as it can proliferate and lead to significant crop losses if not managed

properly.

In 2015, over 4 million acres of soybean (Glycine max) were planted in Ohio

(USDA, 2016). Soybeans are susceptible to a number of foliar, root, and stem diseases.

Some of the most economically important diseases that affect soybean plants are soybean

cyst nematode (SCN; Heterodera glycines) and Phytophthora root and stem rot

(Phytophthora sojae). In 2006 in the United States, SCN was responsible for the loss of

3368 thousand metric tons of soybean while Phytophthora root and stem rot was

responsible for the loss of 1464 thousand metric tons (Wrather et al., 2010). The life

cycle of SCN begins as a freshly hatched infective second-stage juvenile (J2) that locates

and enters a soybean root. Once in the root the juvenile nematode will travel

intracellularly to the vasculature (Niblack, 2005). The juvenile will then form a feeding

site called a syncytium. This feeding site will be maintained as long as the nematode is

present in the roots (Niblack, 2005). Eventually, the nematode will molt to become a

male and leave the root to find a mate, or a female that will continue to swell until they

burst from the root. The females will lay 400 to 600 eggs that are kept within the female

body. Upon death the female’s body (or cyst) will melanize allowing the cyst to protect

the unhatched eggs for years as they remain in the soil (Niblack, 2005). Large

populations of SCN in the field will lead to stunting of plants in the field, chlorosis of the

canopy, and poorly developed root systems (Niblack, 2005).

Phytophthora sojae, an oomycete, grows primarily as aseptate hyphae. It

normally produces sporangia, zoospores and chlamydospores which all contribute to its

reproduction (Tyler, 2007). The sporangia can germinate directly to form hyphae or they

can produce zoospores that will encyst on the root surface, germinate, and then penetrate

plant cells to cause infection. P. sojae infection often causes damping-off of seedlings as

well as root and stem rot symptoms in mature, established plants (Tyler, 2007). The

pathogen can overwinter in the soil as chlamydospores or oospores during unfavorable

conditions and cause later infections when conditions are favorable (Tyler, 2007).

Tomatoes (Solanum lycopersicum) are also susceptible to a large number of

pathogens. In 2014, 8400 acres of tomatoes were planted for fresh market sales and

processing (USDA, 2015). Ohio is one of the largest producers of tomatoes in the U.S.

and managing diseases on this crop is important for maintaining regular tomato

production. Bacterial spot and speck caused by Xanthomonas campestris pv. vesicatoria

and Pseudomonas syringae pv. tomato respectively, are two widespread diseases in many

growing operations. These bacterial pathogens can cause crop problems, especially on

fruits, if left unchecked. Oftentimes the pathogens can be found together, but are known

to occur separately (Delahut and Stevenson, 2004). In warm or cool, moist conditions,

localized epidemics can occur for either pathogen (Miller, 1996). While similar at first,

the symptoms of each disease can be used to differentiate between the pathogens.

Bacterial spot lesions will be small and have a water-soaked appearance (Miller, 1996).

Lesion centers can also become an irregular brown with scabby surface and be accompanied by a white halo (Miller, 1996). Bacterial speck will appear on fruits as black, sunken lesions; however, these lesion types will not be seen on mature fruit for either disease (Miller, 1996). Both pathogens can be seed borne or overwinter on infected

plant debris (Delahut and Stevenson, 2004). Both pathogens will enter through the

stomata or other wounds that will provide an entry point for the bacteria (Delahut and

Stevenson, 2004). Spread of both diseases occurs via splash dispersal (Delahut and

Stevenson, 2004). Disease symptoms on tomato fruits can make them unfit for market, thus decreasing sales. Bacterial spot infection can cause decreases in fruit weight of up to

50% and speck infection can cause yield loss in the field of up to 75% during early stages of growth (Shenge et al., 2010). Monitoring the environmental conditions, including moisture level, is necessary when managing the development and spread of these diseases.

There are a number of diseases that can attack and devastate a wheat (Triticum spp.) crop, many of which will infect at different stages of the plant’s development. One of the most important diseases of wheat is Fusarium head blight (FHB) or scab caused by the fungal pathogen, Fusarium graminearum. The pathogen overwinters on infected plant debris and produce asexual spores or macroconidia that will be dispersed onto plants via wind or splash (Schmalle and Bergstrom, 2003). The macroconidia then germinate and infect wheat heads (Schmalle and Bergstrom, 2003). Infection can also occur by way of the sexual stage of the fungus, Giberrella zeae, which produces ascospores that can also infect wheat heads (Schmalle III and Bergstrom, 2003). Infected wheat heads will exhibit bleaching symptoms shortly after flowering and if conditions are favorable, pink colored spores may appear (Schmalle III and Bergstrom, 2003). Production of mycotoxins is also associated with this fungal infection of wheat which can also lead to crop losses due to its deleterious effects upon ingestion (Diamond et al., 2013). Between 1998 and 2000, the central U.S. suffered a loss of almost $2.7 billion due to FHB infcection (Diamond et al.,

2013).

Disease management can be one of the most important aspects in a crop

production system to ensure future success for the grower. If not managed properly, disease causing organisms can become widespread and ultimately lead to substantial economic losses for the growers. In 2012, across 22 states and parts of Canada, a 10.9% loss of corn was seen due to a combination of diseases that included root rots, seedling

blights, leaf and aboveground diseases, stalk rots, ear rots, and mycotoxin contamination,

for a total of 1.3 billion bushels (Wise, 2014). Soybean growers can have a yield loss of

up to 50% if SCN is not managed properly and a loss of up to 11% can be observed

across Ohio during a wet growing season as a result of Phytophthora sojae infection

(Dorrance and Mills, 2009). Different management strategies must be adopted for

growers to be able to combat multiple disease causal agents. Plant pathogens may have

numerous survival strategies, live on alternative hosts or persist in a wide array of

environments. Knowing how different management strategies work and those that work

best in conjunction with each other can assist in ensuring healthy growth and

development of the crop. For effective disease control, oftentimes a multi-pronged

control strategy must be adopted.

Agricultural practices for disease management

Thurston stated that understanding traditional practices for disease management is

important for plant pathologists to be effective at addressing the world food issue (1990).

Traditional or primitive management practices have been used for years by many

cultures. It has been theorized that since the beginning of crop production 10,000 years

ago, management practices have been used to ensure growing success (Thurston, 1990).

Many of these practices, according to Thurston, included; altering crop architecture,

adjusting crop density, changing time of planting, rotating different crops in succession,

and tillage practices (1990).

Many of the traditional practices mentioned by Thurston have evolved and are

still used today. Cultural practices have continued with the aim to produce healthy plants

rather than only controlling the pathogen (Howard, 2009). Cultural practices such as tillage, crop rotation, rouging and others are often used together to manage disease levels.

These practices offer the grower the opportunity to change the environment or alter the plant and even the pathogen to achieve disease control (Howard, 2009). Tillage and crop

rotation play a role in disease management in growing operations. Peters et al. (2003)

found that crop rotation and minimal tillage can suppress fungal disease on potato. It was

even noted that disease-suppressive effects as a result of tillage and rotation could be

transferred from the field to the greenhouse (Peters et al., 2003).

A more conventional means of disease management utilizes a chemical based

approach. One of the earliest examples of chemical control of disease is the Bordeaux

mixture, first discovered in 1885 (De Waard et al., 1993). It marked a large advancement

in chemical disease control as a first generation fungicide (De Waard et al., 1993). Many

products have been produced over the years as a means to better manage a variety of

diseases. Strobilurins are antifungal compounds that have been adopted due to their high

antagonistic activity to fungal pathogens as well as their low toxicity to mammals (Anke,

1994). Some chemistries have seen the development of resistance by pathogens such as

the wheat pathogen, Mycosphaerella graminicola, and its resistance to strobilurin

fungicides (Mikaberidze et al., 2014). There have also been reports of non-target effects

9 of chemical management strategies. In a study by Munoz-Leoz et al. (2013), application of a fungicide, herbicide, and insecticide caused decreases in microbial density in the soil.

This could potentially affect beneficial microbes present in the soil, which are explored later in this chapter. Other means of chemical control exist to manage bacterial, fungal and nematode infections with varying chemistries and modes of action.

Genetic resistance is another management strategy that has been adopted to decrease a plants susceptibility to disease. Resistance is a plant’s ability to fight off infection from a pathogen which can be shown in a number of ways including the hypersensitive response (HR). This results in localized cell death around the area of infection to halt disease development (Staskawicz et al., 1995). Research by Flor (1954), who assisted in characterizing HR, served as the basis for cloning genes that confer resistance in plants to pathogens. HR and other reactions that lead to necrosis of plant tissue are thought to lead to other plant responses to pathogen attack (Staskawicz et al.,

1995). Pathogen attacks not only cause an HR response, but depending on the pathogen’s method of infection, can lead to induced resistance in plants, such as systemic acquired resistance (SAR) and induced systemic resistance (ISR) (Ryals, 1996; Vallad and

Goodman, 2004). By understanding how genes for resistance function, we can use this information to develop more resistant varieties that exhibit these activities in response to pathogen attacks (Louws et al., 2001). While host resistance has proven useful in managing plant diseases, some pathogens are capable of overcoming that resistance and still causing disease. Some pathogens, at the cost of fitness, can become virulent on a host

(Lannou, 2012). Pathogens can mutate and adapt to host resistance over time at the cost

of fitness aspects such as spore production to cause disease on hosts with resistance genes

(Lannou, 2012; Montarry et al., 2010).

While the previously described management strategies are used worldwide, there are significant concerns about the over reliance on single methods for disease control, impacts on the environment and health, and the long-term effectiveness of the method.

There is a large growing demand for the development of alternative strategies that are long lasting, benign to the environment, and provide alternatives to chemical control of plant diseases. The Microbial Bioproducts Scale-up and Applications (MBSA) team at

The Ohio State University and other researchers worldwide have now turned their focus toward the development and testing of biological-based pesticides, stimulants, and fertilizers, also referred to as biopesticides, biostimulants and biofertilizers.

A large variety of microbial-based products are commercially available for pathogen protection as well as plant growth promotion (Table 1.1). For example, a number of bacterial species have been shown to have antagonistic or biopesticide activity towards fungal pathogens (Huang et al., 2012; Chen et al., 2013; Sivasakthi et al., 2014).

Strains of Azospirillum spp., Bacillus spp., and Pseudomonas spp. are now being used as active ingredients in a number of commercially sold products. Bioproducts labeled as biofertilizers promote the conversion of normally non-usable forms of nutrients into a form usable by the plant (Vessey, 2003). For example, Activate™ 2004 (Natural

Resources Group, Inc., Woodlake, CA) contains various Bacillus spp. as active ingredients that promote plant growth by colonizing the root zone and increasing soil biodiversity. These microbes may secrete compounds that stimulate host processes or allow for easier nutrient uptake by host plants. Biostimulants are bioproducts that

promote the emergence and growth of plants through production of specific secondary

compounds that interact and promote plant growth and development. One example of a

biostimulant is BioGenesis III™ Seed Treatment (Tainio Technology and Technique,

Inc., Cheney, WA) which contains a mixture of Azosprillum, Azotobacter, Bacillus,

Pseudomonas, Micrococcus, and Streptomyces species. When applied to plants or seeds, the mix of bacteria is reportedly designed to colonize the rhizosphere and help young plants become established.

It is unlikely that bioproducts by themselves will solve our growing demand for food production. Modern agriculture will likely have to rely on a multi-pronged approach to address the many factors that affect food production today. For example,

Integrated Pest Management (IPM) greatly assists in disease management as it serves as a multi-step approach to control plant pathogens. The Environmental Protection Agency

(EPA) defines IPM as an approach that is environmentally sensible and combines information on the pests as well as current control methods to manage damages due to pests (EPA, 2014). There are important steps to consider when developing an IPM strategy that will be useful in managing disease. Proper diagnosis of disease is the first step in developing an integrated management strategy followed by understanding both the pest and host life cycles, monitoring for disease, evaluating action thresholds, and implementing an appropriate strategy to manage the target pest (Ehi-Eromosele et al.,

2013; Wolf and Verreet, 2002). IPM combines the beneficial activity of some of the control strategies described above (i.e. chemical application, host resistance, bioproducts, crop rotation, tillage) and creates a multi-pronged approach capable of addressing a variety of plant health issues that can affect overall crop production.

Microbes as beneficial inoculants for plant health and growth

Multiple types of organisms have been identified, characterized and

commercialized for use in crop production systems. The most heavily characterized

organisms are those that were easily culturable, easy to manipulate and readily

fermentable. To date, the most widely used types of organisms are those from the

bacterial and fungal kingdoms. Much research has been described and reviewed about

the role of specific fungi in the promotion of plant growth and plant health. Mycorrhizal

fungi (Glomus intraradices, G. mosseae, G. aggregatum, G. etunicatum; Datnoff et al.,

1995; Barea and Azcon-Aguilar, 1982; Habte et al., 1999; Mendoza and Borie, 1998),

yeast (Cryptococcus spp.; Schisler et al., 2002) and nematode trapping fungi

(Artrhobotrys oligospora; Mostafanezhad et al., 2014) have been identified, characterized

and commercialized for use as biofertilizers and biopesticides. However, given the

research focus of this thesis is around the testing and development of bacterial-based bioproducts we will not discuss fungal-derived bioproducts further.

Plants create an ideal environment for bacterial communities to develop due to their ability to concentrate moisture and nutrients from surrounding soils, generate energy rich compounds from photosynthates, and provide unique habitats where bacteria can persist and colonize (Beattie, 2007). The rhizosphere is defined as the portion of soil that directly surrounds the roots and is influenced by the compounds and proteins roots secrete (Podile and Kishore, 2007). The rhizosphere fosters the largest and most diverse communities of bacteria known. Characterization of bacteria that reside in the rhizosphere has identified many bacteria that exhibit beneficial properties to the plant

(Beneduzi et al., 2012). These bacteria can decrease the incidence of disease as biological control agents by directly antagonizing the pathogens, outcompeting other microorganisms for nutrients, activating plant defenses, or converting non-usable forms of nutrients to forms readily used by the plant (Beneduzi et al., 2012). Other rhizospheric bacteria are known to exhibit properties that promote plant growth and development.

These microbes, referred to as plant growth promoting rhizobacteria or PGPR, can provide benefits to plants in different ways. Weller (1988) stated that PGPR are thought to promote plant growth when they colonize the roots to occupy niches that pathogenic organisms may reside, induce host defenses or through direct suppression of the pathogenic organisms by producing antagonistic compounds. Kim et al. (2011) provided a multifactorial basis for plant health promotion by bacteria that are found associated with plants. Kim reported that there are more than two dozen genera that have been found to exhibit biocontrol and/or plant growth promoting activity (Kim et al., 2011).

Phytohormone production and catabolism, production of volatiles and water soluble small molecules have all been presented as modes of action for plant growth promoting bacteria (Kim et al., 2011). Exploration of the rhizosphere to identify new strains of microbes with properties that enhance crop production can aid in our ability to meet the predicted demand for sustainable food production.

Products that utilize beneficial microorganisms can be divided into three major categories: biofertilizers, biostimulants and biopesticides. Microorganisms that act as biofertilizers promote plant growth by increasing the availability of nutrients in the soil

(Vessey, 2003). These biological fertilizers are defined as living organisms when applied to seeds, roots or other plant surfaces, colonizes that environment and increase the

nutrient supply to the plant (Vessey, 2003). Beneficial bacteria that act as biofertilizers

can act through nitrogen fixation, changing root and shoot morphology and/or enhancing

other beneficial pathways that are inherent in the plant (Vessey, 2003). For example,

nitrogen in the soil is transformed by bacteria into forms that are utilizable by plants

(Ahemad and Kibret, 2014). They can be legume-associated bacteria (Bradyrhizobium

spp.) that form nitrogen fixing nodules on plant roots or free-living bacteria that are able

to increase nutrient solubilzation in the soil for plant hosts to utilize (Azotobacter spp.,

Bacillus spp.) (Ahemad and Kibret, 2014). Increases in root and shoot biomass were

reported by Bashan and Dubrovsky (1995) when plants were inoculated with

Azospirillum spp. a genus of bacteria known for colonizing the rhizosphere of non-

leguminous crops that fix nitrogen from the atmosphere. Sometimes biofertilizers are

added in conjunction with other organisms. One study found that plant biomass

increased by up to 45% when bacterial isolates of Azospirillum brasilense and Bacillus

polymyxa were inoculated in conjunction with an arbusuclar mycorrhizal fungus (Ratti et

al., 2000).

Microbial based products can also function as biostimulants. Biostimulants are

defined by the European biostimulants industry council as “containing substances and/or microorganisms whose function when applied stimulates natural processes to enhance/benefit nutrient uptake, nutrient efficiency, abiotic stress tolerance, and crop quality” (Brown and Saa, 2015). Many microbes found in association with plants may have multiple modes of action. Antoun et al. (1998) isolated 266 bacterial strains from the soil that produced a wide spectrum of compounds with plant-associated activities.

The bacteria produced a variety of compounds including auxin (indole-3-acetic acid;

IAA), a plant hormone for regulating growth (Zhao, 2010), organic acids that promote phosphorous solubilization (Mardad et al., 2013) and siderophores, which allow bacteria to scavenge iron from their environment and make it available to plants (Rungin et al.,

2012). These findings point to the potential of these microbes to be beneficial for plants.

While both biofertilizers and biostimulants are involved in increased nutrient uptake to host plants, biostimulants activate the host plant’s natural processes to enhance nutrient acquisition as well as increase tolerance to external plant stressors rather than directly producing the nutrients themselves. Biostimulants can also be derived from a variety of biological and inorganic substances such as microbial fermentation products, protein hydrolysate, composts, and industrial waste products (Brown and Saa, 2015).

Not only can microbes be used for promotion of plant growth, many are also useful in suppressing plant pathogens through various antagonistic mechanisms; these beneficial bacteria are often referred to as microbial biopesticides. The EPA defines biopesticides as “pesticides derived from natural materials such as animals, plants, or bacteria” (EPA, 2015). Many PGPR have been characterized for their ability to be antagonistic toward the growth of plant pathogens. Numerous strains from the Bacillus,

Burkholderia, Pseudomonas and Streptomyces genera have been isolated from the rhizosphere and studied under greenhouse and field conditions for their ability to control important pathogens of grains and fruit. Bacillus cereus strain UW85, was shown to decrease damping-off disease of alfalafa seedlings caused by Phytophthora meagasperma f. spp. medicaginis (Handelsman, 1990). Other Bacillus species have been shown to produce antifungal compounds that inhibit the growth and development of fungal and oomycete pathogens, useful traits which could contribute to their usefulness as a

biopesticide-based PGPR (Handelsman, 1990). Even the use of PGPRs to control post-

harvest diseases has been noted. Mari et al. (1996) examined Bacillus pumilus strain

3PPE and Bacillus amyloliquefaciens strain 2TOE for their effectiveness in reducing gray mold on pear fruit and saw a decrease in disease incidence with these microbe treatments.

One example of a genus that is often associated with biopesticide activity,

Pseudomonas, is abundant in soils and an excellent colonizer of the rhizosphere (Aly,

2009). Pseudomonas spp. have also been found to be beneficial in promoting plant

growth and decreasing pathogen pressures in the soil. Kloepper et al. (1988) reported that

some Pseudomonas strains increased yield, controlled soil-borne pathogens, promote emergence and even the activity of other PGPR. Certain strains of Pseudomonas have

been correlated with playing a role in suppressive soils (Weller et al., 2002). Suppressive

soils have generally been defined as the ability of soils to suppress the growth of

soilborne pathogens (Weller et al., 2002). The Pseudomonas spp. in these suppressive

soils lead to reduction in a variety of plant diseases including: Fusarium wilt, potato scab

decline, apple replant disease and take all decline (Weller et al., 2002). P. fluorescens has

also been found to reduce galls on chilli (Capsicum annum) roots caused by root-knot

nematodes by colonizing the rhizosphere and forming a protective layer around the roots

(Thiyagarajan and Kuppusamy, 2014).

Pseudomonades have a variety of mechanisms by which they can be antagonistic toward plant pathogens. These antagonistic activities include production of antibiotics, proteins, and release of materials that lead to a decrease in disease (Aly, 2009).

Antimicrobial compound such as 2, 4-diacetylpholorglucinol (2,4-DAPG), phenazines, and pyrrolnitrin (PRN) are produced by several different species of Pseudomonas such as

P. fluorescens or P. putida (Aly, 2009). These compounds have been found to reduce

bacterial and fungal diseases (Keel et al., 1992; Cartwright et al., 1995). Other bacterial

isolates that contain these compounds have also been found to be associated with

decreased pathogen incidence. Burkholderia cenocepacia 869T2, a pyrrolnitrin and

pyrroloquinone producer, has been associated with decreased Fusarium wilt on banana as

well as increased plant growth in the same system (Ho et al., 2015). Additional studies

have also found that Pseudomonas fluorescens mutants with increased 2, 4-DAPG

production have increased inhibitory effects on bacterial wilt of tomato (Zhou et al.,

2014).

Members of the Streptomyces genus have also been reported to reduce the

incidence of disease. Xiao et al. (2002) reported several antibiotic-producing

Streptomyces spp. that reduced root-rot symptoms caused by Phytophthora medicaginis and P. sojae on alfalfa and soybean. Of the 53 Streptomyces isolates that were tested,

66% of them resulted in a significant reduction in symptoms caused by P. medicaginis and 74% saw a reduction in symptoms caused by P. sojae. Six isolates were also tested for plant growth promoting activity and five of the six showed a positive effect on seedling growth (Xiao, 2002).

Although pseudomonades make up a large number of PGPR that have been studied for their plant growth promotion activity and subsequent commercialization

(Mavrodi et al., 2012; Xue et al., 2009), other rhizopheric microbes have been isolated that have potential for utilization as a PGPR based product. One such genus, Mitsuaria,

has not been studied in depth for its plant growth promoting capabilities. Little is known

about its level of activity and effectiveness, mode of action, or the required delivery

18 mechanism. A study by Benitez and McSpadden Gardener (2009) showed the potential for Mitsuaria spp. as a PGPR used for promotion of plant health and growth. In both tomatoes and soybeans, lesion severity caused by fungal and oomycete pathogens,

Rhizoctonia solani and Pythium aphanidermatum respectively, was reduced significantly when treated with Mitsuaria isolate H24L5A (Benitez and McSpadden Gardener, 2009).

It was also found that the isolates used exhibited chitinolytic activity in vitro (Benitez and

McSpadden Gardener, 2009). Other studies have also reported the presence of chitosanase genes and subsequent degradation of chitosan by isolates of Mitsuaria (Peng et al., 2013). More research is currently being done to fully elucidate the beneficial activity and modes of action of Mitsuaria and many other microbes within the rhizosphere.

Commercialization of beneficial microbes

Microbial-based products are slowly becoming an alternative to conventional agricultural practices for disease management. Conventional agriculture is often dependent on chemical inputs to ensure crop production; however, harmful aspects of these chemicals (i.e. toxicity to non-target organisms, residual chemicals in the food, environmental pollution, and ground water contamination) are a driving factor for the development of alternative methods (Mark et al., 2006). Researchers at The Ohio State

University reported sales of bioproducts are now over $500 million annually (Boehm et al., 2015). The continued growth of bioproducts in the last decade has demonstrated a growing demand for chemical alternatives. This demand for alternatives to conventional control methods has led to the development of a large variety of commercially available

microbial-based products (Table 1.1). While not an exhaustive list, many microbial-based

products are being used to supplement conventional disease control measures.

Many PGPR are now being utilized in commercial products as biopesticides

(Table 1.1). Due to the nature of the plant growth promoting and pathogen suppressing

activity, PGPR have been developed for commercially available inoculants.

Bradyrhizobium japonicum and Streptomyces lydicus WYEC 108 are two PGPRs that are

currently being utilized as commercial biological fungicides. Being sold as Vault

(BASF, Ludwigshafen, Germany) and Actinovate (Valent Biosciences Corp.,

Libertyville, IL) respectively, both PGPRs as the active ingredients in the products, have been shown to increase plant growth. B. japonicum sold as Vault was shown to increase nodule weight, plant biomass, and nitrogen fixation on soybeans (Atieno et al., 2012).

Other Bradyrhizobium japonicum containing products have been shown to increase plant biomass, nodulation and overall nitrogen fixation when combined with Bacillus subtilis

(Thuita et al., 2012). S. lydicus sold as Actinovate was shown to increase marketable yield on watermelon when in combination with a green manure (Himmelstein et al.,

2014). A decrease in Fusarium wilt symptoms of up to 7% was seen with treatment of

Actinovate (Himmelstein et al., 2014). Serenade® (Bayer Crop Sciences, Research

Park Triangle, NC), a formulation of Bacillus subtilis QST-713, has been shown to decrease incidence of clubroot on canola caused by Plasmodiophora brassicae (Lahlali et al., 2013). A reduction in root hair infection of 94% and 96% was observed upon treatment with Serenade® at seven and 14 days after seeding respectively (Lahlali et al.,

2013). A decrease in pathogen presence on the roots in those same treatments was also seen by PCR (Lahlali et al., 2013). Bioplin™ (Kan Biosys, Maharashtra, India) and

Phosfert™ (Kan Biosys, Maharashtra, India) which utilize Azotobacter spp. and

Azotobacter spp. mixed with Bacillus polymyxa respectively, have both been associated

with plant growth promoting activity. An increase in seedling germination in dormant

Rosa damascene Mill seeds (Kazaz et al., 2013). A small, non-significant increase in seed

germination was seen at with Bioplin™ treatment (compared to the control at 66.7%) at

68% germination (Kazaz et al., 2010). A larger but still non-significant increase in seed

germination was seen with seeds treated with Phosfert™ (compared to the same control

at 66.7%) at 84% germination (Kazaz et al, 2010). Blight Ban A506, a formulation of

Pseudomonas fluorescens A506, has also been associated with beneficial activity. A 73%

decrease in blossom blight on ‘Johnathan’ apple trees infected with fire blight (Erwinia

amylovora) was seen upon treatment with Blight Ban A506 (Jurgens and Babadoost,

2013). Many more beneficial bacteria are currently being used to promote plant growth

and decrease disease for a variety of crops.

Formulations for beneficial microbes

Biological products are prepared in a variety of ways. Formulating PGPR for use as inoculants is crucial in ensuring their survival and success in promoting plant growth and health. Research is still being conducted on microbes with potential beneficial activity that may one day be used as a commercial product (Beneduzi et al., 2012;

Dimkic et al., 2013; Correa et al., 2014; Compant et al., 2013).

To be able to utilize PGPR as inoculants, a number of factors must be considered

when formulating the new product. Schisler (2004) defined formulations as, “…a product

composed of biomass of a biological control agent and ingredients to improve the

survival and effectiveness of the product”. The formulation of microbials is necessary for

the potency of biological inoculants. How the organism is being maintained and delivered

ultimately determines the efficacy that will be seen. Protecting the bacterial cells and

allowing microbial populations to multiply contributes greatly to the success of the

formulated project.

PGPRs have been prepared in a variety of ways for agricultural systems. Wettable

powders, fluid suspensions and alginate formulations are all used for delivery of

microbes to plants. Microbial suspensions can be mixed with water and kaolin clay,

dried, and resuspended for application to plants as a wettable powder (Connick et al.,

1990). Using saturated bacterial cultures, suspensions are prepared by diluting to the

desired concentration then applying to the crop. Alginate, a naturally occurring

polysaccharide, has been used in formulations for slow release of bacteria to assist with

plant growth and health (Bashan, 1986). Beads made with sodium alginate and skim milk

can increase bacterial populations of Azospirillum brasilense and Pseudomonas spp.

strain 84313 (Bashan, 1986). Slow release of beneficial bacteria concomitantly with seed

germination can directly contribute to protection and health of seedlings in the soil.

Alginate beads were able to act as carriers for the microbes. Carriers like alginate beads play a large role in the overall effectiveness of microbial inoculants.

Carriers and the resultant formulations of PGPR assist in allowing those microbes

to survive and reproduce and ultimately impart their benefits. This affects the

performance, shelf life, and safety of the product (Fravel, 2005). Not only is the

formulation important, the delivery of the PGPR in its new formulation is also important

for its overall effectiveness. Delivery options, such as a fluid suspensions or wettable

22 powders, are also important to consider when developing PGPR for products in agricultural systems (Xue et al., 2009). There are limitations to many of the products that are currently used. A large number of currently used formulations deliver microbes in an arrested state as part of a dried powder or a liquid that must be refrigerated (Boyetchko,

1999). These limitations may affect how early the product will become active and decrease the overall effectiveness of the PGPR used in the formulation. It is necessary to determine how these factors will affect the specific microbe and how it will behave in the pathosystem and cropping system the microbial will be added to.

Opportunities to develop new formulations and microbial inoculants

As previously mentioned, research continues on discovering new microbes with beneficial activity that can be utilized in a product. One such beneficial microbe that is being studied is Mitsuaria spp. H24L5A. This microbe, introduced previously, was first isolated from Ohio soils were a disease suppressive phenomenon was observed (Benitez and McSpadden Gardener, 2009). While the beneficial activity has been somewhat characterized, currently there are no studies on how this novel microbe can be delivered to different cropping systems. A novel delivery system developed by 3Bar Biologics, Inc.

(Columbus, OH) utilizes concepts from currently used formulations to fully examine the activity of Mitsuaria. This delivery system utilizes a solid matrix, which the microbes are adhered to via a liquid inoculation. The solid matrix is housed in a sterile plastic cap that is mounted onto a bottle of liquid media. Upon activation, the solid matrix with inoculated bacteria is dropped in the media and allowed to incubate for a predetermined time. This technology allows for the fast growth of bacteria that can then be used as a soil

23 drench or seed treatment. The delivery system uses actively growing microbes, that when inoculated into cropping systems, will begin working upon their arrival. Knowing how microbial inoculants will behave in this novel delivery system is important for future development of formulations that can readily be used by growers.

The overall objective of this study is to determine the stability of a microbial inoculant in the 3Bar delivery system and the subsequent efficacy of the system. Chapter

1 provided a brief introduction to the importance of developing sustainable means for crop growing systems. Chapter 2 will address the novel delivery system developed by

3Bar Biologics, Inc. using pseudomonades as the model organism. The formulation, purity and stability of microbes in the system will be assessed, thus providing information on shelf life and longevity. Chapter 3 will examine the efficacy of Mitsuaria spp.

H24L5A in greenhouse and field settings as well as begin to address the potential mode of action of Mitsuaria spp. H24L5A using the 3Bar Biologics, Inc. delivery technology.

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CHAPTER 2

Formulation, stability and purity of a bacterial inoculant in a novel delivery system

ABSTRACT

Plant growth-promoting rhizobacteria (PGPR) can be delivered to agricultural

systems in a variety of ways. They can be applied as soil drenches, foliar sprays or seed

treatments. Before large-scale application, the development of a stable and effective

method for production and delivery is necessary. A large variety of microbial

formulations exist utilizing large-scale systems that create favorable conditions for

microbial growth. To ensure the success of microbial products, quality assurance

assessments are routinely conducted to examine the purity and overall integrity of the

product. We initiated a project working with 3 Bar Biologics, Inc. (an Ohio State

University startup company) that has developed a novel delivery system for production

and delivery of microbial inoculants. A series of quality control experiments using 3

Bar’s novel delivery system for microbial inoculants were carried out to determine the

effectiveness of the system for producing and delivering putative PGPRs. Two PGPRs,

Pseudomonas brassicacearum strains Wood1R and Wood3R, were evaluated for their

ability to persist and grow in 3 Bar Biologics’ delivery system. Serial dilutions and

polymerase chain reaction (PCR) were used to quantify and confirm the presence and

amounts of inoculated Pseudomonas brassicacearum strains at varying times of product storage. Serial dilutions were carried out in the presence and absence of rifampicin since

34 these strains were previously reported to be rifampicin resistant. An increase in bacterial cell numbers was seen for early time points with or without antibiotic addition. Detection of inoculated pseudomonades was observed at early time points (days) but were not observed at later time points (weeks). Observations from these experiments suggest that this novel delivery system may be useful in producing PGPRs such as pseudomonades but long-term storage could be problematic.

INTRODUCTION

How microbial-based products are prepared and formulated can affect their

overall efficacy. Jones and Burges (1998) define formulations as aids used to preserve,

deliver and increase the activity of an organism for a desired use. Plant growth-

promoting rhizobacteria, or PGPRs, are often produced using specific formulations that

favor the growth of a desired bacterium. Conditions for optimal PGPR growth must be

realized to ensure that maximal amount of viable material is available for delivery. The

life stage, site of action and target crop must be considered when developing an optimal

bacterial formulation for use in crop production systems. Many formulated microbial products don’t meet all of the desired requirements needed to ensure delivery of quality product for agronomic use (Jones and Burges, 1998). Meeting these requirements, discussed later in this chapter, will help ensure that growers and other end users of microbial formulations will get the desired benefits when applied in an appropriate manner.

There are many factors that must be considered to ensure that microbial

inoculants will be active and stable upon delivery. These include the choice of microbes that are able to persist and flourish in their target environment, the use of appropriate nutrients and growth media, the proper environment to grow the inoculum and proper

storage conditions to maintain efficacy (Jones and Burges, 1998). Some microbial

inoculants are better suited for growth than others due to their growth and survival

36 strategies. Members of the Bacillus genus are able to persist in a resistant spore stage

that is inherently more stable than an active living stage, and therefore are more readily

utilized in formulated products compared to microbes that do not have these stable forms

(Schisler et al., 2004). Many PGPRs do not exhibit these survival type stages and thus

require the development of suitable formulations that optimize survival and activity of the

PGPR prior to delivery.

How formulated PGPRs are maintained and delivered determines will determine

their potency and effectiveness in agricultural systems. Baker and Henis (1998) defined

two necessary requirements for formulations of commercially viable microbials. First, the

formulation must preserve the microbe and second, formulated cells must maintain their

viability or have a shelf life of at least a year. This combination is desired for

formulations to maintain efficacy (Baker and Henis, 1998). Other desirable aspects of a

successful formulation include: large microbial populations, inexpensive materials used

for preserving and enhancing the longevity of the product while in storage, and a fluid/substrate suitability that is compatible with the delivery system that is used by the farmer to apply the bioproduct to their crops (Baker and Henis, 1998). Bacteria that are used in formulated products are usually mass-produced using various fermentation systems (Boyetchko et al., 1999). Biomass produced by liquid fermentation can be amended with other materials to lead to solid, liquid, slurry, powder or granular products

(Boyetchko et al., 1999). An important aspect to the development of a successful formulation is the carrier used. Jones and Burges (1998) state that a suitable carrier allows for maximal survival of the microbe during storage, successful application of the microbe to the target environment, and protects the microbe after its application.

37 Several commercially available PGPRs are currently produced and sold: Bacillus subtilis (Cohn) Y1336 and Streptomyces lydicus (Actinovate AG) (Valent Biosciences

Corp., Libertyville, IL) are sold as a wettable powder while Pseudomonas fluorescens

(Migula) and Bradyrhizobium japonicum (Vault) (BASF, Ludwigshafen, Germany) are sold in a fluid suspension (Xue et al., 2009). Wettable powders are dried products that may include kaolin clay as a carrier in conjunction with the target microbe (Connick et al., 1990). Fluid suspensions, such as Vault, normally come as a mixture of the microbe with a liquid medium that delivers the organism in a stable manner. In these fluid suspensions, alginates, a naturally occurring polysaccharide, are often added to encapsulate PGPRs for delivery to crops in a slow release fashion to benefit plant growth

(Bashan et al., 1986; DeLucca et al., 1990).

Each type of formulation is crafted to assist in increasing microbial activity upon delivery. However, many formulations are limited in their capacity to both activate

PGPRs beneficial mechanisms and provide a stable environment for microbes to persist through delivery (Lumsden et al., 1995). Boyetchko (1999) indicated that there are many tradeoffs between delivering dormant microbes and those microbes that are metabolically active. Dormant microbes contribute to increased shelf life, but there is often a lag between delivery and when they actually confer benefits to the plant (Boyetchko, 1999).

Microbes that are metabolically active upon delivery to the plant system can deliver their benefits quickly; however, these formulations are less tolerant to environmental changes and have shorter shelf lives (Boyetchko, 1999).

This study focuses on the development of a novel formulation and delivery system for microbial inoculants. The bioreactor (Fig. 2.1) developed by 3Bar Biologics,

38 Inc. (Columbus, OH), combines both a semi-dormant microbial stock with the ability to create a metabolically active stage of the product. In this system, a solid soybean-based matrix is inoculated with the target microbe(s). After the microbes have been added to the solid matrix, a set quantity of matrix is placed in a sterile plastic cap and sealed according to company standards. Each cap is then added to a large plastic bottle containing mineral water and the bioreactor is stored. Activation of this system is achieved by pushing the button on the top of the cap which dispenses the contents of matrix and microbe into the mineral water. This system creates a liquid culture of microbes that once grown, can be applied by growers. This novel system is easy for farmers to store and use. In this study, we focused on examining the potential shelf life of the product both before and after activation. In our studies we evaluated two previously characterized PGPRs (Mavrodi et al., 2012), namely Pseudomonas brassicacearum strains Wood1R and Wood3R, for their stability in the bioreactor. Stability of the inoculum on the solid matrix was measured at various time points as well as the stability of the activated product. Purity of the product was tested using PCR-based analyses to confirm inoculum identity using primers specific for the phlD gene involved in 2,4- diacetylphloroglucinol (2, 4-DAPG) biosynthesis from both the solid matrix and the final activated product. In this study, we observed no significant increases or decreases in the number of culturable bacteria on the matrix or in the actively growing product. Detection of pseudomonades inoculated into this novel delivery system was seen only during the early time points examined. Long term storage and testing revealed the presence of an autoclave resistant microbe that eventually overwhelmed the bioreactor system.

39 MATERIALS AND METHODS

Bacterial inoculants and seeds

Soybean seeds (Glycine max) were provided by 3Bar Biologics, Inc. (Columbus,

OH). Preparation of seeds for the bioreactor system was also done by 3Bar Biologics,

Inc. (Columbus, OH) by grinding soybean seeds then passing them through a number two sieve. Seed matrix particles of one to two millimeters in size were autoclaved (121oC for

45 minutes) and 6 grams of soybean matrix was added to a sterile cap. Pseudomonas brassicacearum strains, Wood1R and Wood3R, were kindly provided by Dr. Brian

McSpadden Gardener (OSU, Wooster, OH; Mavrodi et al., 2012). Bioreactor caps that contained Wood1R and Wood3R were prepared by 3Bar Biologics, Inc. by adding 1 mL of overnight bacterial culture (109 cells/mL) grown in 1/10 strength tryptic soybean broth

(TSB; Sigma Aldrich Co., St. Louis, CO) to 6 grams of the soybean matrix and mixed.

Sterile water was used as a negative control (NC) in the system.

Glycerol stock preparation

Nutrient agar plates, 1/10 strength tryptic soy agar (TSA; Sigma Aldrich Co., St.

Louis, CO), were used for growth of bacterial cultures. Bacteria were streaked onto 1/10 strength TSA and incubated for 48 hours at room temperature. Liquid cultures for glycerol stocks were prepared using a nutrient medium, 1/10 strength tryptic soy broth

(TSB). One hundred mL of 1/10 strength TSB was autoclaved in 250 mL flasks and cooled to room temperature. A separate flask was prepared for each bacterial strain tested. A single colony from bacterial culture plates (described above) was added to flasks of 1/10 strength TSB and then incubated at 28°C and shaken at 200 RPM for 24

40 hours. A 35% glycerol solution was prepared by adding 70 mL of 99% glycerol to 200

mL of sterile, distilled water. After liquid culture incubation, 600 µL of 35% glycerol was added to a sterile, 2 mL microcentrifuge tube. Six hundred µL of the bacterial liquid culture was then added to each tube. Glycerol stocks were stored in -80° C freezers until needed.

Generation of inoculum for bioreactor caps

Inoculum for bioreactor caps was prepared by 3Bar Biologics, Inc. Bacterial strains mentioned above were grown in nutrient media for 24 hours until saturation (109 cells/mL). Bacterial cultures were then diluted with sterile distilled water to 106 cells/mL

and inoculated onto the soybean matrix by adding 1 mL of diluted bacterial culture to 6

grams of sterile soybean seed matrix. Caps were sealed according to 3Bar Biologics, Inc.

standards and labeled by microbe added.

Viability of bacterial inoculum on soybean matrix

Mock bioreactors were made using three 500 mL plastic bottles. Three hundred

mL of sterile, distilled water was placed into each bottle; one replicate of each treatment

was done. Caps labeled with each treatment, W1 (Wood1R), W3 (Wood3R) and NC

(negative control – water inoculated only) were placed on filled bottles. 96-well culture

plates were prepared for serial dilutions by adding 200 µL of 1/10 strength TSB in each

well or 200 µL of 1/10 strength TSB amended with rifampicin (Sigma Aldrich Co., St.

Louis, CO) dissolved in 100% methanol at a concentration of 50 µg/mL (1/10

TSB+Rif50); 0.5 grams of rifampicin was dissolved in 10 mL of methanol. Bioreactors

41 were activated and then shaken for 30 seconds. Aliquots of 80 µL were removed from

each bottle and placed into the first well on a culture plate. A 3.5 fold serial dilution was

done for each sample by removing 80 µL from one well and moving to the adjacent well,

mixing the contents (pipetting up/down five times to mix and then discarding of the used

tip after each mixing step). The process was repeated serially until dilutions had reached

the end of each row (dilution ratios achieved were (bacteria solution : water solution in

µL) 1:3.5, 1:7, 1:43, 1:150, 1:525, 1:1.8x103, 1:6.43x103, 1:2.3x104, 1:7.9x104, 1:2.8x105,

1:9.7x105, 1:3.4x106 for dilutions in columns 1 through 12 respectively). Microtiter culture plates were incubated in the dark for 72 hours at room temperature, approximately

24° C. Following incubation, plates were examined using a spectrophotometer (ELx800 microplate spectrophotometer, Bio-Tek Instruments, Inc., Winooski, VT) to determine

the terminal dilution. Terminal dilutions that were positive for growth (optical density

measured at 595 nm ≥ 0.055) (McSpadden Gardener et al., 2000) were used to calculate

the amount of bacteria present. Calculations were done using the following formula:

Colony Forming Units (CFU) = 300 x 3.5n+1, where 300 is the volume of the bacterial

stock, 3.5 is the dilution factor [final volume (280 µL) / aliquot volume (80 µL)], n is the

terminal dilution and 1 is added to account for skips or empty wells that occur before the

terminal dilution (McSpadden Gardener et al., 2000). This process was repeated for each

of the five time points: one day, seven days, 21 days, 90 days and 180 days after

bioreactor cap inoculation. The amount of bacterial growth was examined using serial

dilutions that were incubated for 3 days then assayed spectrophotometrically. Terminal

dilutions were used to calculate the amount of bacteria present as previously described.

42 Plates were sealed and stored at -80° C until needed for use in PCR assays described

below.

Viability of bacterial inoculum in liquid after activation

Three bioreactors (Fig. 2.1) were prepared using 4 L (1 gallon) sized plastic

bottles. 1.5 L of non-sterilized mineral water was placed into each bottle. Caps where

labeled with each treatment, Wood 1R (W1), Wood3R (W3) and untreated water NC

(negative control) and placed on filled bottles. Serial dilutions and cell counts were

carried out as previously described. After activation, samples from the liquid were

collected after 24 hours and then again seven days after activation of the bioreactor. This

process was repeated for four additional time points during storage; 4, 14, 42, and 78

days after the bioreactor cap inoculation. For each storage time point, serial dilutions

were done after one and seven days of incubation after bioreactor activation. One and

seven day time points were used to determine length of viability of an activated

bioreactor. The amount of bacterial growth was determined using serial dilutions as

previously described and terminal dilutions were used to calculate the amount of bacteria

present. Plates were sealed and stored at -80° C for use in PCR assays described below.

PCR-based detection of phlD gene

Serial dilution plates previously described were used for the following PCR assays. For all time points, plates were removed from -80° C freezer prior to running polymerase chain reactions (PCR). Each 96-well plate containing terminal dilutions was

placed in a heated oven (55° C) with mechanical convection for 15 minutes until thawed.

43 Once thawed, samples were returned to the -80° C freezer for 5 minutes until frozen.

Freeze-thaw process was repeated a total of 3 times to release DNA from each sample and was then used as a template. The freeze thaw process was also done on 2 μL centrifuge tubes with Wood3R resuspended in water to use as a positive control; sterile water was used as a negative control.

PCR reactions were carried out using the following mixture per reaction: 12.7 μL of sterile ddH2O, 5 μL of 5X Green GoTaq® Flexi Buffer (Promega, Madison, WI), 1.8

μL of 25mM MgCl2, 2.5 μL of dNTP’s (Promega, Madison, WI), 0.25 μL of the forward

primer B2BF (ACC CAC CGC AGC ATC GTT TAT GAG C), 0.25 μL of the reverse

primer BPR4 (CCG CCG GTA TGG AAG ATG AAA AAG TC), 0.33 μL of GoTaq®

Flexi DNA Polymerase, 0.04 μL of RNase ONE™ Ribonuclease (Promega, Madison,

WI) and 2.5 μL of the DNA template from the extraction process for a total of 25 μL.

The phlD PCR program was added to the C1000 TouchTM Thermocycler (Bio-

Rad Laboratories, Inc.). The program steps were: Step 1: 95.0° C for 3 min, Step 2: 94.0°

C for 1 min, Step 3: 60.0° C for 1 min, Step 4: 72.0° C for 1 min, Step 5: GO TO Step 2,

34 times, Step 6: 72.0° C for 5 min and Step 7: 10.0° C Infinite hold. For visualization of the reactions, a 1.5% agarose gel was prepared using 7.5 g of agarose and 500 mL of

0.5X Tris/Borate/EDTA (TBE) buffer.

From each PCR reaction 4 μL was added to the agarose gel and on both ends 2 μL of 1kb DNA ladder (0.1 μg/ μL) (Promega, Madison, WI) was added. The gel ran for 30 minutes at 60 V then two hours at 140 V. The gel was stained using ethidium bromide

(EtBr) for 20 minutes and destained using deionized water for 20 minutes. The gel was

44 visualized using the Kodak Gel Imaging System (Eastman Kodak Company, Rochester,

NY) to confirm the presence of a 629 bp product representing the phlD gene.

RESULTS

Viability of bacterial inoculum on soybean matrix

In our initial set of experiments, we wanted to determine whether our

Pseudomonas strains were able to persist on the soybean matrix used in 3 Bar Biologic’s

bioreactor. To simulate normal operating procedures for the bioreactor, all samples were

activated prior to sampling the liquid so as to limit any bacterial growth while in the

bioreactor solution. Dilutions in 1/10 TSB media showed am increasing trend in the

number of culturable cell over time (Fig. 2.2) for all samples tested. It should be noted

that only one sample was collected for each time point for each treatment, thus no

statistical analyses were possible. All observations described should be treated as trends

rather than statistically significant observable findings.

After one day of storage, we observed an increase in CFU for both Pseudomonas

treated samples (W1 and W3) compared to the non-treated control (NC). We observed minimal differences between the non-treated control as compared to the Pseudomonas

treated samples at seven and 21 days of storage. Interestingly, when compared to initial

measurements at one day of cap storage, samples stored at 90 and 180 days showed

increased numbers of culturable cells (Fig. 2.2). After one day of cap storage on the

matrix, Wood3R produced more culturable cells per mL as compared to Wood1R and the

control (Fig. 2.2). However at later time points of storage Wood3R did not exceed the

number of culturable cells as compared to the other two treatments.

45 Repeating the dilutions in 1/10 TSB+Rif50 media allowed us to select only those

microbes that are rifampicin resistant (the Pseudomonas strains used in this study were

rifampicin resistant). Similar to that observed in the 1 day of storage we observed an

increase in rifampicin resistant bacteria in the Wood3R treatment as compared to the

control and Wood1R treated caps (Figure 2.3). At the later storage time points, all

treatments produced the same number of culturable bacteria as that of the non-treated

control. Only the 90 day treatment resulted in an increase in rifampicin resistant bacteria,

but that was observed for all treatments. Data shown in Figures 2.2 and 2.3 reflects the

only biological replicate of the experiment that was completed. No statistical analysis

was done with this data due to limited sample size.

Viability of bacterial inoculum in liquid

This set of experiments examines whether the Pseudomonas strains were able to be recovered after storage on the soybean matrix used in 3 Bar Biologic’s bioreactor system. Bioreactor solutions were diluted in 1/10 TSB media 24 hours and 7 days after activation of the bioreactor using inoculated soybean stored in caps for 4, 14, 42 and 78 days after inoculation. Regardless of the days in storage, at 24 hours after initiating each of the units we observed a large number of culturable cells. The number of culturable cells ranged from 9.7x106 to 6.2x1010 CFUs per mL of bioreactor solution (Figure 2.4).

However when we examined culturable rifampicin CFUs we found that the number of

cells dropped several orders of magnitude for most of the treatments (Figure 2.5). As

expected we did see a large number of rifampicin culturable cells for the Wood3R

treatment. However the Wood1R treatment failed to produce measurable numbers of

46 rifampicin resistant CFUs as compared to the non-treated control (NC). Interestingly, we

did see a large portion of cells that were rifampicin resistant in the 78 day-stored treatments, though these only represented a fraction of the total culturable cells observed in the 78 day-stored treatment in the non-rifampicin treated dilution series. Data shown in Figures 2.4 and 2.5 reflects the only biological replicate of the experiment that was completed. No statistical analysis was done with this data due to limited sample size.

A similar pattern was shown for cell counts after seven days of incubation at

increasing days of cap storage. In 1/10 TSB media alone we saw large numbers of

culturable cells (Figure 2.6). CFU per treatment ranged from 3.4x106 to 7.6x1011. As

expected, we saw in 1/10 TSB media amended with rifampicin a large number of

rifampicin resistant culturable cells for Wood1R (4.1x108 CFU) and Wood3R

(7.7x107CFU) (Figure 2.7). The number of rifampicin resistant CFUs in samples stored

for 14 and 42 days decreased during longer periods of storage. Similar to the 24 hour

incubation results, however, 78 day-stored samples showed high levels of rifampicin resistant colonies in all treatments examined. Data shown in Figures 2.6 and 2.7 reflects the only biological replicate of the experiment that was completed. No statistical analysis was done with this data due to limited sample size.

PCR-based detection of phlD in stored and fermented samples

In these experiments we tested for the presence of the phlD gene as a marker for

the presence of Wood1R and Wood3R bacteria in our bioreactor. As positive controls,

both Pseudomonas brassicacearum strains, Wood1R and Wood3R, were positive via the

PCR assay for the presence of the phlD gene. We examined the initial time points for

47 storing Pseudomonas treated soybean samples in the caps to determine if we could detect

the presence of the bacteria. Using the initial dilution, we examined each of the stored

samples (1, 17, 21, 90 and 180 days) using the two media types, 1/10 TSB and 1/10

TSB+Rif50. For non-selective samples using the 1/10 TSB only, the presence of phlD

was only detected in the wells containing Wood3R, however, it was only detectable at 1

day and 7 days (Fig. 2.8, and Fig.2.9) after storage. For all other time points using the

1/10 TSB media only, no detection of the phlD gene was observed. Using the selective

media, 1/10 TSB plus rifampicin, we observed the presence of the phlD gene only in wells containing Wood3R stored for 1 and 7 days only (Fig. 2.10 and Fig. 2.11). The presence of phlD in Wood1R treated samples was weakly detected after 1 day of cap storage but failed to be detected in all other stored samples. Samples stored longer than seven days failed to produce a phlD gene signal for all treatments tested (Fig. 2.8-11).

We also examined each treatment for the presence of the phlD gene on the matrix and after activating the bioreactor. This allowed for the analysis of the potential recovery of the Pseudomonas strains once they have been introduced and allowed to grow within the bioreactor. For our negative controls we observed only two false positives (14 day stored caps grown for seven days and serial diluted with 1/10TSB with or without rifampicin). In bioreactors initiated with caps stored for four days we observed the presence of the phlD gene at one and seven days of incubation for Wood3R treated samples regardless of the absence or presence of rifampicin in the serially diluted plates

(Fig. 2.12–15). Wood3R treated samples stored for 14 days also produced a phlD positive band but only in samples that were serial diluted in 1/10 TSB amended with rifampicin (either sample grown for either 1 or 7 days in the biorector). Samples stored

48 for 42 days failed to produce a phlD positive signal regardless of the time in the biorector

with or without the addition of rifampicin in the serial dilutions.

The phlD gene was successfully amplified from caps stored for four days in

Wood1R treated samples (Fig. 2.12–15). The phlD gene for Wood1R from caps stored

for four days was detected in samples grown for seven days in the bioreactor and serial

diluted with 1/10 TSB without rifampicin and in samples grown for one and seven days

in the bioreactor and serially diluted with 1/10 TSB with rifampicin. The only other phlD

amplified for Wood1R treated samples was observed for caps stored at 14 days, grown in

the bioreactor for seven days and serially diluted in 1/10TSB amended with rifampicin.

All other time points and conditions failed to produce a positive phlD signal for Wood1R.

DISCUSSION

We evaluated the use of a novel delivery system developed by 3Bar Biologics for use in propagating PGPRs. We evaluated the system for the production of two different

Pseudomonas brassicacearum strains, Wood1R and Wood3R. A soybean matrix was inoculated with freshly grown bacterial culture and added to specially designed caps that can be sterilized and hermetically sealed. Graham-Weiss et al. (1987) conducted a similar study using vermiculite as a matrix for bacterial inoculation; they found that after a week of incubation on the matrix, bacterial numbers increased 100,000 fold. This study included several bacterial strains that included Pseudomonas spp., and findings were consistent for all strains tested (Graham-Weiss et al., 1987). Inoculated caps were stored for varying times (days) and then used. Prior to extended incubation, samples of the bioreactor solution were examined for culturable bacteria. The quantity of living

49 culturable bacteria was determined through serial dilutions on microtiter plates containing

1/10 strength TSB media. The number of CFUs was determined for each bacteria tested

across different storage times. As part of this research we wanted to determine if PGPRs

like Pseudomonas can survive for extended periods of time on the soybean matrix.

Previous studies that examined the longevity of microbial inoculants on a matrix found

that many factors play a role in microbe survival (Graham-Weiss et al., 1987; Roughley

et al., 1967; Strijdom and van Rensburg, 1981). Temperature of storage, pH, carrier type,

sterilization techniques and moisture content all affect the overall survival and

subsequent growth of microbe-based products (Graham-weiss et al., 1987; Roughley et al., 1967; Strijdom and van Rensburg, 1981).

Serial dilution counts revealed that over time, there were no changes in culturable bacterial cells on the matrix. However, when we used rifampicin in our serial dilutions to only allow those bacteria that are rifampicin resistant to grow, we saw a large decrease in the number of culturable bacteria. The Pseudomonas strains we used in this study were rifampicin resistant and should have been the only rifampicin resistant strain in the bioreactor if wholly sterile material was used. Our data suggests that a bacterial contaminant(s) was present in the bioreactor system prior to inoculation.

Since most of the culturable bacteria (as determined by growth in the serial dilution plates on 1/10 TSB) was not rifampicin resistant, we suspect that the contaminant(s) was present either in the soybean matrix or in the mineral water used to start the assay. Preliminary evidence suggests that the contaminant was possibly an endophyte of the soybean seed used in this study. Spreading of the seed on 1/10 TSB agar plates showed potential bacterial contamination by the presence of distinct colonies

50 (data not shown). Though the soybean seed was autoclaved, we are not certain whether the contaminant(s) was sufficiently destroyed by 3 Bar Biologics’ autoclaving process or whether a contaminant(s) was introduced to the soybean matrix during the preparation of a fully charged cap.

Within the system, our lack of consistent detection of inoculated bacterial strains suggests a more dominant microbe may be present within the system. The presence of phlD was only confirmed at earlier time points which suggests that the population of inoculated Pseudomonas spp. declined on the matrix and/or in the actively growing medium. Molina et al. (2000) reported that Pseudomonas putida KT2440 inoculated into soil were no longer detectable 50 days after inoculation. Bacterial numbers decreased by four orders of magnitude (<102 CFU g-1 of soil), however, recovery was possible up to

200 days from the start of the experiment with selective enrichment (Molina et al., 2000).

It is possible that in our samples the bacterial populations dropped below a detectable limit and therefore could not be identified using the described PCR conditions.

Inoculated bacteria may also simply not be culturable due to their lack of activity.

A “viable but not culturable” (VBNC) state of bacteria has been studied that addresses potential difficulties with culturing bacteria (Mascher et al., 2000; Oliver, 2004). Certain abiotic stress conditions such as high salt concentrations, limited oxygen and a reduced redox potential (Mascher et al., 2000), can lead to this bacterial phenomenon. Cells in this state demonstrate decreased metabolic activity for extended periods of time. It has been reported that Pseudomonas fluorescens can maintain this state for up to a year in soil

(Oliver, 2000). Bacteria inoculated onto our matrix and subsequently activated using the novel delivery system may be undergoing a variety of abiotic stresses that were not

51 initially considered, which in turn can potentially lead to this VBNC state. Means of

“resuscitation” of bacteria such as changing temperature have been studied to increase

recovery of bacteria by others (Oliver, 2000) but due to material constraints we were not

able to test this possibility.

With the lack of detection of our target microbe in the system, it is possible the

numbers seen are from a different Pseudomonas species or a different genus of bacteria

entirely. Having a soybean seed-based matrix, many seed endophytes are present, including Bacillus and Paenebacillus (Senthilkumar et al., 2009). Certain species of

Bacillus are known to produce spores that allow them to persist in soil and other environments (Setlow, 2005). These spores are resistant to a number of sterilization techniques including heating and radiation, and this can lead to increased populations of non-target bacteria over time in a system if spore germination occurs (Setlow, 2005).

Small increases in bacterial counts over time as well as a lack of detection of our target microbe supports the idea the counts recorded may be due to populations of latent bacteria coming from the matrix.

Analysis of the serial dilutions in 1/10 TSB amended with rifampicin suggests that longevity of the strains is somewhat limited. Experiments in which stored caps were examined for the presence of rifampicin-culturable bacteria illustrates that rifampin- resistant bacteria are present and make up a portion of the culturable bacteria for up to two weeks of storage. As confirmation that these strains are pseudomonades we used

PCR to confirm that the culturable bacteria in our test contained the phlD gene, which is found in many Pseudomonas strains, including the two strains tested in this study. The presence of the phlD gene was confirmed in treatments that were stored for up to and

52 including 14 days. Beyond 14 days we did not observe any culturable bacteria that were

phlD positive.

Interestingly, our tests suggest that when the matrix (inoculated or control) is

stored for a long period of time, the level of culturable bacteria that grow once the

bioreactor system is activated exceeds that of the shorter time periods. This may be due

to changes in the soybean matrix that facilitate the growth of the contaminating bacteria

during incubation. With our seed-based carrier, low numbers of bacteria observed in the

treatments that were stored for shorter periods of time could be due to lack of

consideration of other factors. Only autoclaving was used for sterilization of the matrix.

Effects of various sterilization processes including autoclaving have been shown to have

effects on protein and amino acid content in cowpea, pea, and kidney bean for instance

(Khattab et al., 2009; Khattab et al., 2009). Changes in the matrix may affect the ability

of microbes to properly colonize and develop robust populations. Previous research

reports the effects that moisture content, pH and temperature can have on bacterial

growth either by altering the enzymatic activity, water potential within cells, or energy

transduction (Stark and Firestone, 1995; Russell et al., 1979; Ahring et al., 2000). Going

forward, these factors also need to be addressed for our novel system to achieve higher

numbers of culturable bacteria.

This work represents preliminary studies for the quality control of microbial inoculant systems. We focused solely on the purity and stability of our target inoculum within this novel system and did not consider other factors. Going forward, effects of pH, temperature, matrix or carrier type, salinity and oxygen availability need to be considered to better understand how the product can be optimally stored. As each of these factors has

53 been shown in previous research to affect bacterial populations (Graham-Weiss et al.,

1987; Roughley et al., 1967; Strijdom and van Rensburg, 1981), consideration of each as it pertains to our novel system can potentially increase the viability of our target microbes. In our studies, sample sizes for our counts were also smaller than desired as these were preliminary studies for quality control and as such were limited by amount of supplies provided by the company. In future experiments, increasing the number of bioreactors for each treatment and performing multiple (>3) technical replicates in our dilution plates will increase our confidence in the analysis of this delivery system.

When considering dilution counts, a more selective nutrient medium could also be considered. King’s B medium (KB), a medium that is typically used for isolation of

Pseudomonas spp., especially fluorescent pseudomonades (Johnsen and Nielsen, 1999), would allow for more selective activity in our dilution counts. KB medium would also be used as a nutrient base amended with rifampicin in future experiments to increase selective activity of the medium even further. It is possible for some bacterial strains to proliferate over time at lower concentrations of rifampicin; some Pseudomonas and

Bacillus spp. have developed mutations to become resistant to rifampicin at lower concentrations (Ingham and Furneaux, 2000; Kubo et al., 2012). As many pseudomonades are rifampicin resistant, rifampicin coupled with King’s B medium would increase the ability of working with a bacterial population that is primarily

Pseudomonas spp.

PCR-based assays using proper controls and adequate replication will need to be conducted to have a more complete quality control and quality assurance assessment of the system. In our study we used Wood3R, a Pseudomonas brassicacearum strain that

54 has shown to be positive for our gene of interest as our positive control. In future experiments, other known root colonizers that have this gene can be used to further confirm target gene presence in our samples. Multiple PCR assays also need to be done with the increased sample size from the terminal dilutions mentioned above. Similar to the increased sample size for bacterial enumeration experiments, increasing the number of bioreactors for each treatment to three and performing more technical replicates in our dilution plates will increase our sample size from two which will allow for more samples in our PCR assays; additional biological replicates will allow for increased replicates of

PCR assays to determine the presence of our target gene. In our preliminary study, the focus was on bacterial counts and subsequent identification of pseudomonades in the system using specific primers. Future investigations need to include full sequencing of samples from the matrix and the actively growing liquid culture to determine the presence of all bacteria. Quantitative PCR (qPCR) amplifying the 16S sequence, coupled with species-specific genes also needs to be conducted to determine if our inoculated microbe versus another bacterial genus is dominant; this will not only give an answer as to the amount of the target PGPRs that can be produced using this system but also identify any potential seed endophytes or other microbes that can potentially contaminate this novel delivery system. Knowing what other bacteria are present other than the inoculant will inform decisions for sterilization, carrier or matrix type, and isolation or recovery techniques when doing quality control experiment.

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11. Jones, K.A. and Burges, H.D. 1998. Technology of formulation and application, in: Burges, H.D., Formulation of microbial biopesticides: Beneficial microorganisms, nematodes and seed treatments. Kluwer Academic Publishers, Dordrecht, The Netherlands. 7-30. 12. Khattab, R.Y., Arntfield, S.D., Nyachoti, C.M. 2009. Nutritional quality of legume sees as affected by some physical treatments, Part 1: Protein quality evaluation. LMT – Food Science and Technology. 42, 1107-1112 13. Khattab, R.Y., Arntfield, S.D. 2009. Nutritional quality of legume sees as affected by some physical treatments 2. Antinutritional factors. LMT – Food Science Technology. 42, 1113-1118. 14. Kubo, Y., Inaoka, T., Hachiya, T., Miyake, M., Hase, S., Nakagawa, R., Hasegawa, H., Funane, K., Sakakibara, Y., Kimura, K. 2013. Journal of Bioscience and Bioengineering. 115(6), 654-673. 15. Lumsden, R. D., Lewis, J. A., Fravel, D. R. 1995. Formulation and delivery of biocontrol agents for use against soilborne plant pathogens, in: Hall, F. R. and Barry, J. W. Biorational pest control agents: Formulations and delivery. American Chemical Society, Washington, DC. 166-182. 16. Mascher, F., Hase, C., Moenne-Loccoz, Y., Defago, G. 2000. The viable-but-not- culturable state induced by abiotic stress in the biocontrol agent Pseudomonas fluorescens CHA0 does not promote strain persistence in soil. Applied and Environmental Microbiology. 66(4), 1662-1667. 17. McSpadden Gardener, B. B., Mavrodi, D. V., Thomashow, L. S., Weller, D. M. 2000. A rapid polymerase chain reaction-based assay characterizing rhizosphere populations of 2,4-diacetylphloroglucinol-producing bacteria. Phytopathology. 91, 44-54. 18. Molina, L., Ramos, C., Duque, E., Ronchel, M.C., Garcia, J.M., Wyke, L., Ramos, J.L. 2000. Survival of Pseudomonas putida KT2440 in soil and in the rhizosphere of plants under greenhouse and environmental conditions. Soil Biology and Biochemistry. 32(3), 315-321. 19. Oliver, J.D. 2005. The viable but not culturable state of bacteria. The Journal of Microbiology. 43, 93-100. 20. Roughley, R.J. and Vincent, J.M. 1967. Growth and survival of Rhizobium spp. in peat culture. J. Appl. Bact. 30(2), 362-376. 21. Russell, J.B., Sharp, W.M., Baldwin, R.L. 1979. The effect of pH on maximum bacterial growth rate and its possible role as a determinant of bacterial competition in the rumen. Journal of Animal Science. 48(2), 251-255. 22. Schisler, D.A., Slininger, P.J., Behle, R.W., Jackson, M.A. 2004. Formulation of Bacillus spp. for biological control of plant diseases. Phytopathology. 94, 1267- 1271. 23. Setlow, P. 2006. Spores of Bacillus subtilis: their resistance to and killing by radiation, heat and chemicals. Journal of Applied Microbiology. 101, 614-525. 24. Senthilkumar, M., Swarnalakshimi, K., Govindasamy, V., Lee, Y.K., Annapurna, K. 2009. Biocontrol potential of soybean bacterial endophytes against charcoal rot fungus, Rhizoctonia bataticola. Curr. Microbiol. 58, 288-293. 25. Stark, J.M. and Firestone, M.K. 1995. Mechanisms for soil moisture effects on

57 activity of nitrifying bacteria. Applied and Environmental Microbiology. 61(1), 218-221. 26. Strijdom, B.W. and van Rensburg, H.J. 1981. Effect of steam sterilization and gamma radiation of peat on quality of Rhizobium inoculants. Applied and Environmental Microbiology. 41(6), 1344-1347. 27. Xue, Q., Chen, Y., Li, S., Chen, L., Ding, G., Guo, D., Guo, J. 2009. Evaluation of the strains of Acinetobacter and Enterobacter as potential biocontrol agents against Ralstonia wilt of tomato. Biological Control. 48, 252-258

Fig. 2.1. Bioreactor developed by 3Bar Biologics Inc. Caps contain solid soybean matrix with target microbe(s).

59 12 Day s of Cap Storage 10 1 L

m 7

/ 21 B

S 90 T 8 180 n i

s l l e c 6 d e r u t l u

c 4

f o

g o L 2

0 Days of Cap Storage 1 7 21 90 180 1 7 21 90 180 1 7 21 90 180 Treatment NC Wood 1 Wood 3

Figure 2.2. Bacterial counts on a soybean seed matrix in 1/10 TSB after 1, 7, 21, 90 and 180 days of cap storage.

12 Day s of Cap Storage L 10

m 1 /

f 7 i

R 21

+ 90 B 8 S 180 T

n i

s l l

e 6 c

d e r u t

l 4 u c

f o

o 2 L

0 Days of Cap Storage 1 7 21 90 180 1 7 21 90 180 1 7 21 90 180 Treatment NC Wood 1 Wood 3

Figure 2.3. Bacterial counts on a soybean seed matrix in 1/10 TSB+Rif50 after 1, 7, 21, 90 and 180 days of cap storage.

12 Day s of Cap Storage 4

L 10 14 m

/ 42 B

S 78 T 8 n i

s l l e c 6 d e r u t l u

c 4

f o

g o L 2

0 Days of Cap Storage 4 14 42 78 4 14 42 78 4 14 42 78 Treatment NC Wood 1 Wood 3

Figure 2.4. Bacterial counts in an actively growing bioreactor system in 1/10 TSB after 4, 14, 42, and 78 days of storage and 24 hours of incubation.

12 Day s of Cap Storage L

m 10 4 / f

i 14

R 42 + 78 B 8 S T

n i

s l l

e 6 c

d e r u t

l 4 u c

f o

o 2 L

0 Days of Cap Storage 4 14 42 78 4 14 42 78 4 14 42 78 Treatment NC Wood 1 Wood 3

Figure 2.5. Bacterial counts in an actively growing bioreactor system in 1/10 TSB+Rif50 after 4, 14, 42, and 78 days of storage and 24 hours of incubation.

12 Day s of Cap Storage L 4 m

/ 10 14 f i

R 42

+ 78 B S

T 8

n i

s l l e

c 6

d e r u t l

u 4 c

f o

o 2 L

0 Days of Cap Storage 4 14 42 78 4 14 42 78 4 14 42 78 Treatment NC Wood 1 Wood 3

Figure 2.6. Bacterial counts in an actively growing bioreactor system in 1/10 TSB after 4, 14, 42, and 78 days of storage and 7 days of incubation.

12 Day s of Cap Storage L 4 m 10

/ 14 f i

R 42

+ 78 B

S 8 T

n i

s l l

e 6 c

d e r u t l 4 u c

f o

o 2 L

0 Days of Cap Storage 4 14 42 78 4 14 42 78 4 14 42 78 Treatment NC Wood 1 Wood 3

Figure 2.7. Bacterial counts in an actively growing bioreactor system in 1/10 TSB+Rif50 after 4, 14, 42, and 78 days of storage and 7 days of incubation.

Fig. 2.8. Amplification of phlD by polymerase chain reaction (PCR) for 1 day, 7 days and 21 days post cap inoculation with target microbes in 1/10 TSB on a soybean matrix. Lanes marked with 1 contained samples inoculated with Pseudomonas brassicacearum strain Wood1R, lanes with 3 contained samples inoculated with P. brassicacearum strain Wood3R and lanes marked with 0 contained samples inoculated with sterile water. Lanes with (+) were positive controls with Pseudomonas brassicacearum strain Wood3R. Lanes with (-) were negative controls with sterile water. Products were separated on a 1.5% agarose gel and visualized with ethidium bromide staining.

Fig. 2.9. Amplification of phlD by polymerase chain reaction (PCR) for 90 days and 180 days post cap inoculation with target microbes in 1/10 TSB on a soybean matrix. Lanes marked with 1 contained samples inoculated with Pseudomonas brassicacearum strain Wood1R, lanes with 3 contained samples inoculated with P. brassicacearum strain Wood3R and lanes marked with 0 contained samples inoculated with sterile water. Products were separated on a 1.5% agarose gel and visualized with ethidium bromide staining.

Fig. 2.10. Amplification of phlD by polymerase chain reaction (PCR) for 1 day, 7 days and 21 days post cap inoculation with target microbes in 1/10 TSB amended with Rifampicin on a soybean matrix. Lanes marked with 1 contained samples inoculated with Pseudomonas brassicacearum strain Wood1R, lanes with 3 contained samples inoculated with P. brassicacearum strain Wood3R and lanes marked with 0 contained samples inoculated with sterile water. Lanes with (+) were positive controls with Pseudomonas brassicacearum strain Wood3R. Lanes with (-) were negative controls with sterile water. Products were separated on a 1.5% agarose gel and visualized with ethidium bromide staining.

Fig. 2.11. Amplification of phlD by polymerase chain reaction (PCR) for 90 days and 180 days post cap inoculation with target microbes in 1/10 TSB amended with Rifampicin on a soybean matrix. Lanes marked with 1 contained samples inoculated with Pseudomonas brassicacearum strain Wood1R, lanes with 3 contained samples inoculated with P. brassicacearum strain Wood3R and lanes marked with 0 contained samples inoculated with sterile water. Products were separated on a 1.5% agarose gel and visualized with ethidium bromide staining.

Fig. 2.12. Amplification of phlD by polymerase chain reaction (PCR) for 4 days and 14 days post cap inoculation with target microbes in 1/10 TSB in actively growing bioreactors. Numbers in parentheses are days after activation of bioreactors. Lanes marked with 1 contained samples inoculated with Pseudomonas brassicacearum strain Wood1R, lanes with 3 contained samples inoculated with P. brassicacearum strain Wood3R and lanes marked with 0 contained samples inoculated with sterile water. Lanes with (+) were positive controls with Pseudomonas brassicacearum strain Wood3R. Lanes with (-) were negative controls with sterile water. Products were separated on a 1.5% agarose gel and visualized with ethidium bromide staining.

Fig. 2.13. Amplification of phlD by polymerase chain reaction (PCR) for 14 days and 42 days post cap inoculation with target microbes in 1/10 TSB in actively growing bioreactors. Numbers in parentheses are days after activation of bioreactors. Lanes marked with 1 contained samples inoculated with Pseudomonas brassicacearum strain Wood1R, lanes with 3 contained samples inoculated with P. brassicacearum strain Wood3R and lanes marked with 0 contained samples inoculated with sterile water. Lanes with (+) were positive controls with Pseudomonas brassicacearum strain Wood3R. Lanes with (-) were negative controls with sterile water. Products were separated on a 1.5% agarose gel and visualized with ethidium bromide staining.

Fig. 2.14. Amplification of phlD by polymerase chain reaction (PCR) for 4 days and 14 days post cap inoculation with target microbes in 1/10 TSB amended with Rifampicin in actively growing bioreactors. Numbers in parentheses are days after activation of bioreactors. Lanes marked with 1 contained samples inoculated with Pseudomonas brassicacearum strain Wood1R, lanes with 3 contained samples inoculated with P. brassicacearum strain Wood3R and lanes marked with 0 contained samples inoculated with sterile water. Lanes with (+) were positive controls with Pseudomonas brassicacearum strain Wood3R. Lanes with (-) were negative controls with sterile water. Products were separated on a 1.5% agarose gel and visualized with ethidium bromide staining.

Fig. 2.15. Amplification of phlD by polymerase chain reaction (PCR) for 14 days and 42 days post cap inoculation with target microbes in 1/10 TSB amended with Rifampicin in actively growing bioreactors. Numbers in parentheses are days after activation of bioreactors. Lanes marked with 1 contained samples inoculated with Pseudomonas brassicacearum strain Wood1R, lanes with 3 contained samples inoculated with P. brassicacearum strain Wood3R and lanes marked with 0 contained samples inoculated with sterile water. Lanes with (+) were positive controls with Pseudomonas brassicacearum strain Wood3R. Lanes with (-) were negative controls with sterile water. Products were separated on a 1.5% agarose gel and visualized with ethidium bromide staining.

73 CHAPTER 3

Assessment of Mitsuaria spp. H24L5A plant growth promotion, pathogen suppression activity and mode of action

ABSTRACT

Numerous root-associated bacteria have been characterized and developed as inoculants to improve plant growth and disease resistance. Such inoculants have been applied to crops in a variety of ways including seed treatments, sprays, and soil drenches.

A novel bacterium, Mitsuaria spp. strain H24L5A, isolated from the rhizosphere of mixed-species hay, has previously been shown to exhibit direct pathogen suppression activity in vitro and in planta. More recently, plant growth promotion and disease suppression was reported on tomato and wheat when Mitsuaria spp. H24L5A was applied as a soil drench. We hypothesized that increases in plant growth would also be seen under greenhouse and field conditions. Greenhouse and field experiments were conducted to examine the effects of Mitsuaria spp. H24L5A on tomato, corn and soybean. Mitsuaria spp. H24L5A’s potential to produce enzymes linked to biocontrol activity was also examined. From field and greenhouse experiments, yield, stand and plant growth index data were collected. In greenhouse applications, no significant increases in improved plant growth were observed. Similar to greenhouse experiments, no significant increases in stand or yield were seen with seeds treated with Mitsuaria spp.

H24L5A when planted under field conditions. Overall, no significant improvements in plant growth and health were observed using this particular strain of Mitsuaria. Analysis

74 of enzyme activity linked to putative biocontrol activity (chitinase, chitosanase or tannase) for this strain failed to produce expected enzymatic activity. Future work will involve further investigation of other Mitsuaria isolates identified from the previously described study to determine if they have useful properties for use in plant growth and disease protection.

INTRODUCTION

Soil inhabiting microbes are thought to be the most diverse and abundant

microorganisms in the world (Fierer and Jackson, 2006). Billions of bacteria

representing thousands of different species can be found in a single gram of soil (Torsvik

and Ovreas, 2002). These bacteria exist in a myriad of complex niches found in the

heterogeneous makeup of the soil and contribute to the health and function of soil. Some

soil microbes have evolved the ability to interact with plants. These interactions can lead

to changes in plant growth and development as well as alter the health status of the plant.

Of those microbes present in the soil, those associated with plant roots may be the most

important in influencing activity in the plant and have the biggest impact on agronomic

production (Marschner, 2001). These influences can be either beneficial or detrimental to

plant health and development and how these influences are manifested are dictated by

genomic (host and bacteria) and environmental factors. While harmful effects on plant

growth are important to address, identifying ways of utilizing and promoting the

beneficial activity of some of these root-associated microbes could be important for improving crop production systems.

Many living organisms, bacteria in particular, are used by growers to suppress plant pest. These organisms are referred to as biological control, biocontrol agents or biopesticides (Baker and Dunn, 1990). Numerous examples of bacterial-based biocontrol agents have been described including those found in the Pseudomonas (Dey et al., 2004;

Keel and Defago, 1995), Bacillus (Kloepper et al., 2004; Asaka and Shoda, 1996) and

76 Streptomyces genera (El-Abyad et al., 1993; Yuan and Crawford, 1995). Many studies investigated the beneficial activity of these soil microbes and assessed their ability to reduce pathogen severity on a variety of crops under field and greenhouse conditions

(Larkin and Fravel, 1998; Siddiqui and Shaukat, 2003; Mao et al., 1997). The observed biocontrol activity exhibited by these useful organisms can be direct or indirect. Some microbes produce secondary metabolites that directly attack the plant pathogen in the surrounding environment (Raaijimakers et al., 2002). Molecules including HCN and 2,4-

Diacetylphloroglucinol (2,4-DAPG) can directly inhibit biological functions in competing organisms. HCN blocks the cytochrome oxidase pathway which interrupts cellular respiration and leads to cellular death (McSpadden Gardener and Pal, 2006). The mechanism for 2,4-DAPG activity is not well understood, but both it and HCN have both been associated with microbes that exhibit pathogen suppressive activity (Lanteigne et al., 2012; Voisard et al., 1989). Examples of indirect biocontrol activity can be through the stimulation of plant defenses such as activation of induced systemic acquired resistance (Kloepper et al., 2004) or through the competition of limited resources where the biocontrol agents outcompete the pathogens for essential nutrients (Lugtenberg and

Kamilova, 2009). Elicitation of host resistance may occur by inoculation with beneficial microbes as a result of compounds they produce. Some Bacillus strains produce compounds that are often associated with induced systemic resistance (ISR) such as peroxidases and salicylic acid. For competition, many non-pathogenic microbes associated with plants quickly colonize the rhizosphere and thus deplete available nutrients for their pathogenic competitors (McSpadden Gardener and Pal, 2006).

77 Bacterial inoculants are not solely used for disease control. Many soil microbes have been characterized for their ability to promote plant growth. These plant growth promoting rhizobacteria (PGPR) are often sold as biostimulants or biofertilizers. Similar to biocontrol agents, the activity of these types of plant growth promoting bacteria can be direct or indirect. For example, Rhizobium and Bradyrhizobium spp. fix nitrogen in nodules on leguminous plants where it is then shared with the host plant resulting in improved growth while simultaneously receiving nutrients from its host (Lugtenberg and

Kamilova, 2009). Other microbes produce auxin, a growth hormone that directly alters plant growth and development through promotion of cell division and increased root formation (Tsavkelova et al., 2006). Indirect effects of PGPRs on plants could be through the modification of soil microenvironments that assist plants in tolerating abiotic stress conditions. For example, some Bacillus spp. have been shown to produce organic acids such as gluconic, citric and fumaric acid, that increase the solubility of phosphorous in conditions where phosphorous is limited (Pindi et al., 2014).

Microbial bioproducts are often tested under field and greenhouse conditions to determine the degree of disease control or growth benefits a specific microbe may offer

(Fravel, 2005). Consistency in activity from the greenhouse to the field is an important factor when considering utilizing a microbe for use on plants. Often times, screening for beneficial microbes arises when a specific disease control or growth benefit phenomenon is observed under a specific set of environmental conditions or settings (greenhouse vs. field). One such study was conducted by Benitez and McSpadden Gardener (2009) where a difference in disease pressure in an Ohio field was observed. Using molecular tools to identify target microbes with biocontrol or plant growth-promoting activity, a

78 root-associated bacterium from the genus Mitsuaria was identified as being correlated with disease suppressive activity (Benitez and McSpadden Gardener, 2009). The

Mitsuaria genus of bacteria was initially characterized by Amakata et al. (2005) where screening soils in Matsue City, Japan for chitosanase producing bacteria, the researchers identified 30 bacterial isolates that produced a zone of clearance on chitosan amended media. One chitosan-utilizing isolate, now identified as Mitsuaria chitosanitabida strain

3001T belonged to a new group of uncharacterized betaproteobacteria (Amakata et al.,

2005).

Ohio isolates of the newly discovered genus, Mitsuaria, have been shown to have disease suppressive and plant growth promotion activity (Benitez and McSpadden

Gardener, 2009; Cepeda, 2012). In vitro tests revealed that Mitsuaria spp. H24L5A had pathogen suppression activity (Benitez and McSpadden Gardener, 2009) and subsequent greenhouse testing began investigating pathogen suppression and plant growth promotion in planta. In this study, our objectives were to develop bioassays in both field and greenhouse settings to further examine if Mitsuaria spp. H24L5A exhibited any plant growth promoting and/or plant protective qualities. Using previously generated genome sequences for this strain we examined the genome for the presence of genes encoding biocontrol related enzymes and conducted test to confirm whether these biocontrol enzymes exhibited any activity in vitro. Mitsuaria spp. H24L5A was tested as a seed treatment in the field on corn and soybeans and as a soil amendment on tomatoes in the greenhouse. Data obtained from our studies observed no plant growth promoting effects for this strain under greenhouse and field conditions. Furthermore, production of

79 chitinase, chitosanase and tannase appeared to be limiting suggesting that this strain of

Mitsuaria may have limited use under conditions tested.

MATERIALS AND METHODS

Seeds, inoculants and pathogens

Corn seeds (Zea mays, hybrid SC11AQ03) were obtained from Seed Consultants,

Inc. (Washington Court House, OH). Tomato seeds (Solanum lycopersicum ‘Oregon

Spring’) were obtained from Johnny’s Select Seeds (Winslow, ME). Soybean seeds

(Glycine max, Asgrow variety AG3231), were treated, planted and managed by Dr. Laura

Lindsey lab according to protocols described below (Columbus, OH). Pseudomonas

syringae pv. tomato and Xanthomonas campestris, the causal agents of bacterial speck

and bacterial spot respectively were provided by the Dr. Brian McSpadden Gardener lab

(Wooster, OH). Inoculants tested are described in Table 3.1.

Microbial inoculant preparation

Glycerol stocks of Mitsuaria spp. strain H24L5A were maintained in 35% sterile

glycerol stored at -80°C. Fresh cultures were prepared from the frozen stock on 1/10

strength tryptic soy agar (TSA)plates and incubated for 48 hours at room temperature. A

single colony was added to a 250 mL flask containing fresh 1/10 strength tryptic soy

broth (TSB) then incubated at 28°C and shaken at 200 RPM for 24 hours. Cell density

was determined using a hemocytometer. Cell cultures were diluted to106 cells/mL were

done using with sterile distilled. Diluted cultures were used in both field and greenhouse

experiments. Cultures of Mitsuaria spp. strain H24L5A were also prepared in a novel

delivery system otherwise known as a bioreactor for greenhouse experiments (3Bar

80 Biologics, Inc., Columbus, OH). The bioreactor was activated according to labeled

instructions and incubated for 48 hours at room temperature. Cultures of Pseudomonas

spp. strain Wood1R and strain Wood3R (Bio – YIELD) were prepared in separate

bioreactors (3Bar Biologics, Inc., Columbus, OH). Bioreactors were activated according

to labeled instructions and incubated for 48 hours at room temperature. Actinovate AG

(Valent Biosciences Corp., Libertyville, IL), a commercial fungicide containing

Streptomyces lydicus, was dissolved in sterile, distilled water at a rate of 37 mg per liter.

TM Germination (Best Environmental Technologies, Edmonton, AB, Canada), a

commercially sold product for increased seed germination and plant establishment was

applied at 4 ounces per 100 lbs. of seed respectively. Mineral water was applied as a

negative control (NC) to account for bioreactors containing mineral water.

For bacterial pathogen preparation, cultures of Pseudomonas syringae pv. tomato

and Xanthomonas campestris were maintained in 35% sterile glycerol stored at -80°C.

Fresh cultures were prepared from the frozen stock on 1/10 strength TSA plates and

incubated for 48 hours at room temperature. A single colony was added to a 250 mL flask

containing fresh 1/10 strength TSB then incubated at 28°C and shaken at 200 RPM for 24

hours; separate flasks were prepared for each pathogen. Cell density was determined

using a hemocytometer. Cell cultures were diluted to a concentration of 106 cells/mL

using sterile distilled water. Diluted cultures were used only for greenhouse experiments.

Testing of biocontrol agents under field conditions.

A field experiment was performed on treated corn and soybean seeds during

Summer 2014. The following treatments were tested in the field: Bio – YIELD

81 (Pseudomonas brassicacearum strain Wood3R, 3 Bar Biologics Inc., Columbus, OH),

Mitsuaria spp. H24L5A, commercial product TM Germination (Best Environmental

Technologies, Australia), TM Germination in combination with Bio – YIELD and P. brassicacearum strain Wood1R, and two experimental Pseudomonas species (P. chloraphis strain 48B8 and P. rhodesiae strain 88A6; Taylor laboratory, unpublished data). Other treatments included a water treated control (NC) and an untreated control

(UC). See Table 3.1 for all treatments tested in the field.

Field bioassays for corn and soybean consisted of eight seed coat treatments and two negative controls. For corn, a randomized complete block design with four replicates of each treatment per site were planted; field plots were planted in four 30” rows in a 25- foot long plot. For soybean, a randomized complete block design was also used with four replicates of each treatment per site; field plots were planted with 15” rows in a 28-foot by 5-foot plot. Field experiments were conducted in Clark, Crawford, Darke, Fayette,

Liking, Mahoning, Van Wert, Wood, Wayne and Wyandot counties for corn and Clark,

Clinton, Erie, Henry, Mercer and Preble counties for soybean. Two hundred grams of corn and soybean seed were treated at a time in plastic bags. Eight ounces of each treatment was applied per 100 pounds of seed (or approximately one mL of treatment for each 200 grams of sample). Treatments were added to sterile, pre-calibrated sprayers set to release 0.5 mL per treatment. For each 200 gram bag of seed, the bag was first flattened to avoid seed stacking inside the bag, and then sprayed once to deliver 0.5 mL to one side of the seeds. Seeds were then flattened down to ensure that treatment was on the surface of the seed, then the bag was flipped and this process was repeated. After treatments were applied to both sides, seeds were shaken for one minute to ensure

82 complete coverage of each seed. Seeds were placed into seed packages and stored at

10°C for no more than 48 hours prior to planting. A non-treated set of 200 grams of seed

was generated as described treated with sterile water only. Corn seeds were treated in the

Dr. Brian McSpadden Gardener’s laboratory while soybean seeds were treated in Dr.

Laura Lindsey’s laboratory.

The number of seeds that germinated and emerged from the soil (stand) and the

amount of seed produced at the end of the season (yield) was collected by Rich Minyo for

corn and Dr. Laura Lindsey laboratory members for soybean. Raw data from soybean

fields was obtained from Dr. Laura Lindsey lab and analyzed. Raw data from corn

experiments were not made available.

Testing of biocontrol agents under greenhouse conditions

Greenhouse experiments were performed on tomatoes. Tomato seeds (Solanum

lycopersicum ‘Oregon Spring’) were sown into seedling trays with mixed-blend compost

(Snyder Farm, OARDC). When young tomato seedlings developed their second trifoliate

leaf, they were transplanted to four-inch pots filled with the same growing medium. A slow release fertilizer, Osmocote® (Yoder’s Produce LTD, Fredericksburg, OH) was incorporated into mixed-blend compost with 5 mL of fertilizer added to each pot. Five experimental replicates were carried out with six plants for each of our seven treatments

(n=42) in a complete randomized-block design. All experiments were carried out under greenhouse conditions with temperatures ranging from 70-80° F daily. Pots were

watered with 60 mL of tempered water daily to decrease the amount of leaching of water

and treatments from the growth medium. Each experiment was repeated five times.

83 Experiments included in this study were done during the summer of 2015; other

biological replicates (data not shown) were conducted in the summer and fall of 2014.

For the tomato biocontrol assays, treatments included Actinovate® AG (Valent

Biosciences Corp., Libertyville, IL) as an industry standard, Mitsuaria spp. H24L5A in a

novel delivery system (3Bar Biologics bioreactor), Mitsuaria spp. H24L5A grown under

normal laboratory culture conditions (described above), two Pseudomonas

brassicacearum strains, Wood1R and Wood3R as positive controls, a bioreactor liquid

media control (NC) and an untreated control. Treatments were applied as a soil drench of

50 mL (for concentrations see Table 3.1) to tomato plants at the second trifoliate stage.

On the day of treatment, data to calculate the growth index (GI) of each plant was also

collected; width across entire plant (W1), width across the largest leaf (W2) and height

(H) all in cm. GI was calculated using the following equation: (((W1 + W2/2)/2) + H/2).

GI data was collected weekly for up to two weeks after inoculation. When tomatoes developed five to six trifoliate leaves, a mixture of P. syringae pv. tomato (bacterial speck) and X. campestris (bacterial spot) was applied to each plant at a concentration of

106 cells/mL. Plants were sprayed with pathogen mixture until runoff which delivered

approximately 30 mL to each plant. Plants were covered with plastic bags for 36 hours.

After incubating, bags were removed and leaves were monitored for disease development

of bacterial spot and speck (presence of chlorotic haloes and necrotic lesions). Disease

severity was recorded using the following rating 0 to 4 rating scale: 0 = 0% of leaf

surface showing symptoms, 1 = 1-25% of leaf surface showing symptoms, 2 = 26-50% of

leaf surface showing symptoms, 3 = 51-75% of leaf surface showing symptoms and 4 =

76-100% of leaf surface showing symptoms 7 days after pathogen inoculation. At the

84 conclusion of the experiment, biomass data was collected from shoots and roots. Fresh

weight of roots and shoots was collected and plant tissue was then placed in a drying

oven for three days at 55°C then dry weight was collected.

Bacterial strains for enzyme assays

Bacillus cereus strains, 63B7, 79A1 and 54D7 and Escherichia coli strain DH5α

was provided by Dr. Christopher Taylor’s laboratory (Wooster, OH). Pseudomonas spp.

strain Wood3R and Mitsuaria spp. H24L5A were obtained from Dr. McSpadden

Gardener laboratory (Wooster, OH).

Preparation of bacterial cultures for enzyme testing.

One hundred mL of TSB was autoclaved in 250 mL flasks and cooled to room

temperature; a separate flask was prepared for each bacterial strain. A single colony from

bacterial culture plates was added to flasks of nutrient media and then incubated at 28°C

and shaken at 200 RPM for 24 hours. These cultures were used for enzyme assay inoculations.

Preparation of chitin substrate

Chitin (Sigma Aldrich Co., St. Louis, CO) preparation was adapted from Kokalis-

Burelle et al. (2002). Chitin substrate was prepared by suspending 30 grams of chitin in

300 mL of concentrated hydrochloric acid (HCl) in a large, glass beaker. The suspension

was mixed four times during a 30-minute time period. After mixing, the substrate was

allowed to settle for 30 minutes before adding four liters of distilled water and then it was

85 stirred. The mixture sat overnight and chitin was allowed to settle. After 24 hours, water

was poured off, more water was added and then mixed with the chitin and allowed to

settle again. This process was repeated until the pH was above 2. After the desired pH

was reached, the remaining liquid was removed and the mixture was stirred. Ten mL was

removed from the mixture and dried to determine the percentage of chitin per milliliter.

The mixture was adjusted to 1% chitin. Two hundred mL of the dissolved chitin was

mixed with 300 mL of 0.1M phosphate buffer and added to a blender to homogenize the

mixture. Two g of TSB and 15 g of agar was added to the chitin and buffer mixture and

pH was adjusted to 6.5 using 1M KOH before autoclaving the mixture. The media was

cooled then 25 mL was poured into sterile 100 mm x 15 mm petri plates. Plates were

divided into 3 quadrants: positive controls (three B. cereus strains with one strain per

plate), negative control (E. coli), and the test strain, Mitsuaria spp. H24L5A with three replicates of each plate. Five microliters from bacterial cultures were streaked in the respective quadrants. Plates were incubated for seven days at room temperature and later examined for the presence of clear halos surrounding bacterial colonies, which is positive for chitinase production.

Preparation of chitosan substrate

Chitosan was purchased from Sigma Aldrich (St. Louis, CO). Colloidal chitosan

preparation was adapted from Choi et al. (2004). Chitosan substrate was prepared by suspending 10 grams of chitosan in 400 mL of sterile, distilled water in a two liter

Erlenmeyer flask. While the mixture was stirred, 90 mL of 1M acetic acid was added.

After dissolving, the mixture was brought to a final volume of 1 L using sterile, distilled

86 water. Chitosan agar media was prepared using DF minimal salts media adapted from

Penrose et al. (2003). DF salts minimal media was prepared in the following way:

solution (1) 10 mg H3BO3, 11.19 mg MnSO4 • H2O, 124.6 mg ZnSo4 • 7H2O, 78.22 mg

CuSO4 • 5H2O, 10.0 mg MoO3 dissolved in 100 mL sterile, distilled water and stored at

4° C; solution (2) 100.0 mg FeSO4 • 7H2O dissolved in 10 mL sterile, distilled water and

stored at 4° C; solution (3) 4.0 g KH2PO4, 6.0 g Na2HPO4, 0.2 g MgSO4 • 7H2O, 2.0 g

glucose was added to 0.1 mL of solution (1) and 0.1 mL of solution (2) then brought to

volume with one liter of sterile, distilled water. The pH was adjusted to above 5.0 using

1M KOH before autoclaving. Chitosan was added to mixture along with 15 g of agar and

then it was autoclaved for 20 minutes to avoid creating a precipitate. Media was cooled,

and then 25 mL was poured into sterile 100 mm x 15 mm petri plates. Plates were divided

into 3 quadrants for positive controls (three B. cereus strains with one strain per plate),

negative control (Pseudomonas spp.), and the test strain, Mitsuaria spp. H24L5A with

three replicates of each plate. Five microliters from bacterial cultures were streaked in the

respective quadrants. Plates were incubated for seven days and then examined for zones

of clearance surrounding bacterial colonies, which is positive for chitosanase production.

Preparation of tannic acid substrate

Tannic acid was purchased from MP Biomedicals, LLC (Solon, OH) by Dr. Sally

Miller lab (Wooster, OH). Tannic acid preparation was adapted from Jana et al. (2012).

Tannic acid media was prepared as follows: 4.0 g tannic acid, 3.0 g NH4Cl, 0.5 g

K2HPO4, 0.5 g MgSO4, 0.1 g glucose and 15 g of agar. The pH of the media was adjusted

to 5.0 using 1M KOH and then it was autoclaved. Media was cooled then 25 mL was

87 poured into sterile 100 mm x 15 mm petri plates. Plates were divided into 3 quadrants for

positive controls (three B. cereus strains with one strain per plate), negative control (E.

coli), and the test strain, Mitsuaria spp. H24L5A with three replicates for each plate. Five

microliters from bacterial cultures were streaked in the respective quadrants. Plates were

incubated for seven days then examined for the presence of clear halos surrounding

bacterial colonies, which is positive for tannase production.

Bioinformatic analysis of Mitsuaria spp. H24L5A for select biocontrol enzymes

The draft genome sequence for Mitsuaria spp. H24L5A (Rong et al., 2012) was examined for the presence of genes encoding chitosanase, chitinase and tannase enzymes.

References genes used for mining were: a chitosanase from a previous characterized

Mitsuaria strain (3001) (Amakata et al., 2005); a chitinase gene from a previously characterized Bacillus cereus strain (28-9) (Huang et al., 2005); and a tannase gene from

a previously characterized Pseudomonas stutzeri strain (DSM1466) (Yu et al., 2011).

Using the TBLASTN, protein sequences for each of the reference genes were blasted

against the Mitsuaria spp. H24L5A draft genome sequence and the NCBI database to

identify putative biocontrol proteins. The FASTA files for each strain examined were

then placed into MUSCLE (Multiple Sequence Comparison by Log-Expectation), a

multiple sequence alignment program that would “best match” the sequences and provide

us with a gene alignment (see Appendix; protein alignments kindly generated by Rebecca

Kimmelfield).

Statistical analysis

88 Analysis of variance (ANOVA) were run using MINITAB (ver. 16.1.1)

(Minitab, Inc., State College, PA) using a general linear model and pairwise comparisons were made using Tukey’s Comparison Test for all greenhouse assays and soybean field assays.

RESULTS

Bioassay under field conditions

We wanted to test whether Mitsuaria spp. strain H24L5A exhibited any improvement in stand or yield enhancement under field conditions. Treatments where tested in ten different counties in Ohio for corn and six different counties in Ohio for soybean (Fig. 3.1). Averaging data from Mitsuaria spp. H24L5A treated seeds and untreated controls, no differences were for soybean and corn (Table 3.2). Treated seed experiments in the field showed no significant differences in stand or yield across treatments. Raw data for corn experiments were not made available. Stand and yield data for soybean was made available. The average stand and yield was determined for each treatment across all six counties. No significant differences in stand or yield across treatments were observed in our soybean experiments. There were also no significant differences across treatments when all sites were compared (Fig. 3.3).

For the six soybean sites, no significant differences were seen across treatments

(Table 3.4-3.9). For seeds treated with Mitsuaria spp. H245A, the lowest stand count

(1315625.5 plants/acre) was seen at the Clinton County site (Table 3.9) with the highest stand count (140625.0 plants/acre) seen at the Mercer County site (Table 3.4). For treated soybean seeds, in 83% of sites examined, non-significant increases in stand counts

(plants/acre) were seen in Mercer County (Table 3.4), Clark County (Table 3.5), Henry

89 County (Table 3.6), Erie County (Table 3.7) and Preble County (Table 3.8). The high

value for stand count for Mitsuaria spp. H24L5A treated seeds, while not significant, was

higher than the untreated control in Mercer County, OH (Table 3.4). However, this

pattern was reversed in the low end of the range of stand count for Mitsuaria spp.

H24L5A treated seeds compared to the untreated control in Clinton County, OH) (Table

3.9). Mitsuaria spp. H24L5A treated seeds in field sites in Preble and Clark County

yielded the highest stand counts across all treatments at those sites (139733.8 and

136562.5 plants/acre, respectively; Table 3.8 and 3.5, respectively). However, these

average stand counts were not significant among the treatments tested.

The highest value for yield of Mitsuaria spp. H24L5A treated seeds, while not

significant, was higher compared to the untreated control at the Preble County, OH site

(Table 3.9). However, at the lowest yielding site (Mercer County, OH) yield for the

Mitsuaria spp. H24L5A treatment was lower (albeit not significantly) than both treated and untreated controls (Table 3.4). Looking across all soybean treatments, 67% of the sites had small, yet non-significant increases in yield (Henry County (Table 3.6), Erie

County (table 3.7), Preble County (Table 3.8) and Clinton County (Table 3.8)).

Bioassay under greenhouse conditions

Tomatoes treated with Mitsuaria spp. H24L5A in the greenhouse were not significantly different from other treatments when growth index (Fig. 3.2), dry shoot weight (Fig. 3.3) and dry root weight (Fig. 3.4) were examined. Experiments were repeated multiple times (n=5) and no significance was seen for any experiments. Data presented is from the last experiment conducted during Summer 2015 and follows the

90 same pattern as previous experiments. When compared to the untreated control, values for both Mitsuaria spp. H24L5A treatments (MC and MIC), were similar and not significantly different.

For pathogen suppression experiments using Pseudomonas syringae pv. tomato and Xanthomonas campestris, no disease was observed on any plants including the untreated controls. Ratings were not conducted due to no observable symptoms of disease on any plants in the experiment (Table 3.10).

Enzyme activity assays

For enzyme activity assays, no definitive conclusions could be made based on results. When examining plates for clearing halos, none were detected on media plates made using methods described above for Mitsuaria spp. H24L5A (Table 3.11). For described methods, all three Bacillus cereus strains which served as positive controls

(54D7, 63B7 and 79A1), showed clearing halos on both chitin and chitosan amended media in only one experiment (Table 3.11) (Fig. 3.5-3.6); only strain 63B7 is shown but all strains tested were similar in clearance observed. Bacterial growth was not observed on tannic acid amended media for any strains used in this experiment. Enzyme activity of

Mitsuaria spp. H24L5A was not confirmed for the three enzymes tested. Data presented in Table 3.11 represents results from one independent run of the experiment; experiment was repeated multiple times using various media recipes amended from those described above.

DISCUSSION

In this study we examined the effect of a novel microbe on plant growth promotion in different plants and under different crop systems. Mitsuaria spp. H24L5A was originally isolated from a field with natural disease suppression, thus our studies focused on fully elucidating its plant-growth promotion and disease suppression activity.

Stand and yield data from field trials suggests a non-significant positive effect on plant growth with the inoculation of Mitsuaria spp. H24L5A on seeds. A non-significant increase was seen in both growth measurements on corn (Table 3.3) and soybeans

(Tables 3.4-3.9) when compared to the untreated control. This pattern of non-significant increase was not seen in greenhouse experiment using Mitsuaria spp. H24L5A as a soil drench. Previously described growth measurements from the greenhouse showed that, when compared with the untreated control, no positive effect was seen. In five repeats of the greenhouse experiment, data was similar to what was reported in this study (Fig. 3.2-

3.4); the data presented is from the final repeat of the experiment. Rakholiya and Jadeja

(2010) conducted a similar seed treatment experiment on groundnut using two select biocontrol agents to look at disease management. It was found that there was an increase in pod yield when the biocontrol agents were used as a seed treatment on groundnut

(Rakholiya and Jadeja, 2010). The biocontrol agents used were Trichoderma harzianum and Pseudomonas fluorescens, two genera that have been noted in other studies to have positive effects on plant growth (Kleifeld and Chet, 1992; Mavrodi et al., 2012). Other studies have also examined colonization of biocontrol agents to correlate presence of the microbe and the effect seen on growth (Suslow and Schroth, 1982). It was found that

92 many of the microbes that had a positive effect on growth in both field and greenhouse settings were detectable in the soil after 10, 25, 35 and 56 days (Suslow and Schroth,

1982). This suggests that there is a relationship between numbers of inoculated bacteria present in the field and the amount of increase seen in plant growth experiments. While increases were non-significant, Weller (1988) mentioned that if an increase is seen in

70% to 80% of field sites inoculated with a beneficial microbe, there is a positive effect as a result of its addition, similar to what was seen with our field data.

Previous studies have examined soil drenches using bacteria to examine plant growth promotion and found positive effects. Small increases were seen in fruit yield in greenhouse settings when soil was inoculated with a number of bacterial species that included Pseudomonas spp. (Gravel et al., 2007). Small increases were seen in fruit yield compared to the control with tomatoes grown in two plant growth media, rockwool and an organic medium that included peat, pine, sawdust and compost (Gravel et al., 2007).

The lack of differences across our treatments may have arisen for a number of reasons. Our target microbe may not have been able to properly colonize the rhizosphere of our plants. Many competing microbes may have been present in our field soil and greenhouse growth medium; thus decreasing the effect Mitsuaria may have had on plant growth and disease suppression. There is a chance that Mitsuaria spp. H24L5A was not the dominant microbe present and thus a large effect may not be seen (Kloepper and

Beauchamp, 1992). Motility has also been shown to be important for root colonization of bacteria (Weert et al., 2002). Studies using Pseudomonas fluorescens showed motility and chemotaxis towards roots was necessary for root colonization. Mutants that lacked flagella-driven chemotaxis were not be able to properly colonize tomato roots (Weert et

93 al., 2002). It is possible that flagella present on our novel microbe are not able to allow proper motility through the soil to colonize plant roots. No known studies have been done to examine the motility of Mitsuaria spp. H24L5A through the soil. Future studies that look at chemotaxis towards roots could further the knowledge on how to obtain the maximum benefit in terms of plant colonization potential. The number of times plants were treated with Mitsuaria spp. H245A may also affect the outcome of the experiment.

Treatments were applied only once to the soil when transplants occurred. Future experiments that not only consider the concentration of bacteria delivered to the system but also the number of times they are applied needs to be examined to further determine if there are any positive benefits of adding this microbe to plant systems.

The lack of disease symptoms (Table 3.10) may have occurred due to improper incubation conditions. Epiphytic pathogens like P. syringae pv. tomato and X. campestris, are capable of maintaining higher populations in higher humidity for specified amounts of time (O’Brien and Lindow, 1988). It is possible under our greenhouse conditions, the ideal humidity was not reached and thus bacterial populations may not have been large enough to effectively infect plant leaves. New incubation methods may also need to be adopted to assist in the successful infection of tomato leaves. A method used by the Dr. Sally Miller lab (Wooster, OH), consists of bagging tomato plants for 24 hours to stimulate stomatal opening, apply pathogens and bag again for another 24 hours has been suggested as a way to get successful infection. Future experiments will consider not only incubation conditions but also how incubation is done to achieve successful bacterial infections. For the five replicates of our greenhouse bioassays, disease symptoms were never observed (Table 3.10).

94 We also examined the potential mode of action of Mitsuaria spp. H24L5A as a biocontrol agent and plant growth promoter by testing for chitinase, chitosanase and tannase activity. Previous research has shown that other Mitsuaria isolates contain chitosanase genes (Park et al., 2005; Rong et al., 2011) that may make it useful as a biocontrol agent. Chitosanase was chosen as a potentially secreted enzyme by our isolate. Benitez and McSpadden Gardener (2009) noted that Mitsuaria spp. H24L5A was positive for chitinolytic activity using chitin amended media and genes for this enzyme were also found to be present (Rong et al., 2011). As both chitosan and chitin are important enzymes to consider for biological activity, enzyme activity assays were performed for both to further confirm production and activity. Tannase often plays a role in food and beverage production, but some studies have found that bacteria that produce tannase or enzymes that degrade related compounds such as gallic acid may be important for establishing itself in various environments (Muller et al., 2007). Muller at al. (2007) found that an isolate of Mitsuaria was able to degrade tannic acid and polyphenols to survive in an aquatic environment where they may occupy a niche where potentially pathogenic organisms could exist.

For enzyme activity assays, production of chitinase, chitosanase and tannase could not be confirmed. While Bacillus cereus has been shown to be positive for production of chitinase, chitosanase and tannase (Chang et al., 2002; Gao et al., 2008;

Mondal et al., 2001), clearing halos were only seen in the first independent run of these experiments. Subsequent independent runs used differing media recipes adapted from

Kokalis-Burelle et al. (2002), Choi et al. (2004) and Jana et al. (2012) for chitinase, chitosanase and tannase failed to produce enzyme activity, respectively. As mentioned

95 above, positive controls for enzyme production only showed clearing halos in the first

independent run using the previously described media recipes. Five independent runs

were done using these recipes. A media recipe using only chitin, chitosan or tannic acid

substrate concentrations described in this study were used amended with a nutrient agar

(TSB) to test for positive bacterial growth as well as enzyme production (data not

shown). Three independent runs of this media recipe with three replicates of each

bacterial type for each substrate was examined for clearing halos, clearance was not observed for these media recipes for any bacterial strains other than Mitsuaria spp.

H24L5A on chitin amended media; positive controls did not show clearing. Tannic acid amended media showed no bacterial growth for any strains tested. A third media recipe using the previously described substrates as a nitrogen source and glucose as a carbon source was also tested to examine enzyme production. Three independent runs with three replicates for each strain tested was examined for clearance; similar to TSB amended media, Mitsuaria spp. H24L5A showed no halos on chitin amended media with glucose, but positive controls did show clearing halos. For tannic acid assays, five concentrations of tannic acid were also tested (4 mg/mL, 3 mg/ mL, 2 mg/mL, 1 mg/mL and 0.5 mg/mL). No bacterial strains (control or Mitsuaria) were able to grow on any

concentrations of tannic acid (data not shown).

Chitosan is a deacetylated derivative of chitin (Allan and Hadwiger, 1979) that is

present in cell walls of some fungi. While our strain did not demonstrate chitosanase activity under the described conditions, positive chitosanase activity has previously been reported for this strain (Park et al., 1999; Peng et al., 2013). It is possible that chitosanase activity of our microbe was not observed due to differences in environmental conditions

96 including, buffers, pH and temperature. Previous studies have shown chitinase enzyme to

be temperature sensitive with optimal chitosanase activity observed at 20° C (Fenton and

Eveleigh, 1981). Warmer than usual conditions occur often in Selby Hall and thus

temperatures can exceed 30oC (all test are done on the benchtop). Other possibilities include, experimental error, improper growth conditions, differences in gene or promoter sequence that alter or produce a non-functional enzyme or prevent or alter when the gene encoding the chitosanase is expressed.

We further examined why our Mitsuaria isolate was not positive for enzyme activity by aligning genes present in our isolate’s genome with those of other Mitsuaria isolates and microbes known to have these genes. To do this, we took the RAST annotation of our isolate, Mitsuaria spp. H24L5A, and focused on the genes associated with our target enzymes. We then searched the NCBI database for microbes that had been shown to have activity for our target enzymes in literature. If those isolates did not have genome data available we used a related species from the NCBI database that had our desired gene. The FASTA files for each strain examined were then placed into MUSCLE

(Multiple Sequence Comparison by Log-Expectation), a multiple sequence alignment program that would “best match” the sequences and provide us with a gene alignment

(Refer to Appendix).

Our isolate (Mitsuaria spp. H24L5A), when compared to two known Mitsuaria isolates that were positive for chitosanase production (Mitsuaria spp. 141, Peng et al.,

2013; Matsuebacter chitosanitabidus 3001, Park et al., 1999), showed differences in amino acid sequences for the chitosanase enzyme (Appendix: Fig. A.1). Those differences in amino acid sequences could give insight as to why our isolate was not

97 consistently positive for chitosanase activity. Other enzymes have been reported that

share sequence similarity, but are sufficiently different can lead to inactivity or altered

substrate specificity for that enzyme (Todd et al., 2002). It is possible that our isolate,

where it differs from previously characterized genes that code for the same enzyme, lead

to its inactivity, alteration in substrate specificity or the need for specific growth

conditions for activity to be observed.

Chitinase activity for our Mitsuaria isolate was briefly examined in one

published experiment (Benitez and McSpadden Gardener, 2009). However, in our

studies we failed to confirm the presence of chitinase activity. It is possible that chitinase

activity was not seen due to improper environmental conditions. Temperature, pH and

other conditions need to be further examined to fully elucidate conditions for enzyme

activity from our strain. Similar to our chitosanase gene, we compared the chitinase gene

from our Mitsuaria strain with genes from other bacteria known to produce an active chitinase enzyme. Other Mitsuaria strains have not been characterized for chitinase

activity, so other biological control organisms positive for activity were used in this

analysis (Appendix: Fig. A.2). Bacillus cereus 28-9 has been examined for chitinase

production as well as its potential for use as a biological control agent (Huang et al.,

2005). While not in the same genus, comparing our isolate to a known producer of a

biocontrol relevant enzyme provides information as to its lack of activity. Similar to our

chitosanase alignments, there are many differences between our protein sequence for

chitinase and those of know producers like Bacillus cereus 28-9 and others which may

once again point to the reason for the lack of activity under our experimental conditions

(Appendix: Fig. A.2).

98 Utilization of tannic acid by Mitsuaria spp. isolates has also been reported

(Muller et al., 2007). However, in our assays we were not able to get bacterial growth of

Mitsuaria spp. H24L5A or controls. It is possible that the concentrations of tannic acid used were toxic to our strain. Chung et al. (1993) showed inhibition of bacterial growth using tannic acid as well as gallic acid, ellagic acid and propyl gallate. Similar to chitinase and chitosanase activity, it is also possible that the media recipes that were followed were not conducive for growth of our microbe.

While production of tannase has not been confirmed in our isolate, some strains of

Mitsuaria have been shown to degrade and utilize tannic acid related compounds as a carbon source to survive in specific environments (Muller et al., 2007). Some microbes may even produce tannases to overcome tannin production in plants, which normally inhibits microbial growth (Bhat et al., 1998). Being able to overcome the inhibitory effects of natural tannins would allow microbes to establish themselves in plant environments and those with potential biological control activity can occupy a niche that microbial pathogens who lack tannase activity cannot. We compared a gene from our

Mitsuaria strain for a tannase precursor to other microbes with related genes similar to what was done with chitosanase and chitinase. Our gene was compared to those from genera that have similar tannase annotated genes in their genome (Pan et al., 2014; Yu et al., 2011). Similar to what was seen with chitinase and chitosanase, differences in amino acid sequences for a tannase precursor from our Mitsuaria spp. strain (H24L5A) compared to other published gene sequences were observed (Appendix A.3). While only a precursor, there have been Mitsuaria isolates (Matsuebacter FB25, Muller et al., 2007) that were able to utilize tannic acid related compounds which may point to production of

99 tannase or related enzymes. The differences that were observed between tannase

precursor genes for our isolate and other microbes may suggest that the enzymatic

properties of our enzyme may have limited activity against the tannic acids used in our

study and is thus was not conducive to our isolate’s growth.

Further studies utilizing other media mixtures and growth conditions need to be

examined to obtain maximum bacterial growth and enzyme activity. This will allow us to

fully elucidate the role these enzymes potentially play in Mitsuaria spp. H24L5A

beneficial activity. These enzyme assays were a preliminary study on the mode of action

of Mitsuaria spp. H24L5A. Confirming the production of these enzymes and others that

are present in the genome could lead to later utilization of the microbe in a variety of

settings. Studies have been done on increasing the secretion of chitosanase from a strain

of Mitsuaria (Yun et al., 2006), which can potentially be repeated, with our strain.

Increasing secretion of target enzymes from our target microbe would allow better

utilization of the microbe as a biocontrol agent. Chitin and chitosan are components of

fungal cell walls, and being able to increase the production of an enzyme that breaks

these polymers down would allow for a decrease in the presence of pathogenic fungi.

With tannic acid being toxic to some bacteria (Chung et al., 1993), having a microbe that

can degrade this may allow other beneficial microbes present in the soil to proliferate,

allowing them to impart their benefit as well.

Biobased products are becoming more popular as demands for alternatives to convention management strategies are made. It is important to continue research to test the efficacy of potential biological control agents as future alternatives to some conventional chemistries. In this study we examined a novel microbe’s potential as a

100 biological control agent in both field and greenhouse settings. We also examined the potential mode of action that may contribute to the small, non-significant affects that were seen in this study. Further studies will aim to uncover under what conditions our isolate is able to produce biocontrol related enzymes that may lead to beneficial activity that has been suggested by previous experiments as well as data from this study.

101

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Table 3.1. List of treatments used in field assays on corn and soybean seeds and greenhouse assays on tomatoes.

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Table 3.2. Average stand and yield across 10 counties for corn and 6 counties for soybean.

107 Table 3.3. Average stand and yield per treatment for soybeans across six counties in Ohio