Characterization and Management of Ralstonia Solanacearum Populations in South Asia

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Characterization and Management of Ralstonia solanacearum Populations in South Asia

DISSERTATION

Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University

Nagendra Subedi

Graduate Program in Plant Pathology

The Ohio State University

2015

Dissertation Committee:

Sally A. Miller, Advisor

Christopher G. Taylor

Pierce A. Paul

Anne E. Dorrance

Copyrighted by

Nagendra Subedi

2015

Abstract

Bacterial wilt caused by Ralstonia solanacearum (Smith) Yabuuchi is a major problem for tomato, eggplant and pepper production in South Asia. This disease is difficult to manage due to viability, adaptability, and diversity of the pathogen. To develop information regarding local pathogen population structure to inform disease management strategies, we characterized a collection of 100 R. solanacearum strains from South Asia using classical and recent molecular tools. All of the strains in this collection were race 1, phylotype I, and biovar III or IV. Based on phylogenetic analysis of endoglucanase gene sequences, we identified three sequevars (14, 47, and 48), and two putatively new sequevars among the South Asian strains. Cluster analysis of genomic fingerprinting profiles created by Rep-PCR divided strains into eight groups. Strains were not grouped based on geographic origin, host or biovar in either analysis. To identify resistant tomato, eggplant and pepper genotypes that can potentially be used in South

Asia to manage this disease, we screened a worldwide collection of 37 tomato, eggplant, and pepper accessions against six selected South Asian R. solanacearum strains. Six tomato, nine eggplant, and three pepper accessions were highly resistant (≤10% wilt), and three tomato, two eggplant and one of the pepper accessions were moderately resistant

(≤30% wilt).

Biological control is a potentially economically feasible and environmentally safe and sustainable disease management practice. In this study we investigated 54 previously characterized bacterial biocontrol agents for their activity against diverse R. solanacearum strains from South Asia and evaluated the value of integration of these biocontrol agents with partial host resistance of tomato in management of bacterial wilt.

Based on in vitro antagonism against 15 selected South Asian R. solanacearum strains, six biocontrol agents were selected to evaluate their biocontrol efficacy in a susceptible

(L390) and a partially resistant (IRAT L3) tomato accessions. Biocontrol agents were almost four times more effective in suppressing bacterial wilt in IRAT L3 than in L390.

Pseudomonas brassicacearum strains 93D8 and Wood 1R, and P. protegens strain Clinto

1 were the most effective strains with biocontrol efficacy of 67, 50 and 58% respectively, in IRAT L3. Bacterial wilt incidence was suppressed in all four experiments by Pseudomonas brassicacearum strain 93D8, and in three out of four experiments by P. vranovensis strain 15D11, P. protegens strain Clinto 1, and P. brassicacearum strain

Wood 1R, in IRAT L3. However, in L390, the disease incidence was suppressed in only one experiment by P. protegens strains 15G2 and Clinto 1, and a mixture of all biocontrol agents. These results highlight the value of integration of biocontrol agents with host resistance in management of bacterial wilt.

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Dedication

Dedicated to My Family

Acknowledgments

I wish to express my sincere thanks to my supervisor Professor Sally A Miller for her support and guidance throughout my research.

I would like to thank the members of my student advisory committee, Dr.

Christopher G Taylor, Dr. Pierce A. Paul and Dr. Anne E. Dorrance for their helpful comments and support. I am thankful to Dr. Brian McSpadden Gardener for helping me design and execute biocontrol experiments.

My special thanks to Dr. Fulya Baysal Gurel, Dr. Melanie L. Ivey, Jony Mera,

Bob James, Mafruha Afroz (Limi), Anna Testan, Claudio Vrisman, Nitika Khatri, Mynul

Islam, Ferdous Elahi (Jabin), Xing Ma, Nick Rehm, Hugo Pantigoso and Angela Nanes for helping me carryout my experiments.

I would like to thank Dr. Jaw-Fen Wang, AVRDC, Taiwan, Dr. Marie Christine

Daunay, INRA, France, and Dr. Yousouf Mian, BARI, Bangladesh, for providing seeds for this research; and Bangladesh Agricultural Research Institute (BARI) and Nepal

Agricultural Research Council (NARC) for providing laboratory facilities in Bangladesh and Nepal, respectively. I would like to acknowledge Integrated Pest Management

Innovation Lab (IPM IL) and U.S. Agency for International Development (USAID) for financial support.

Vita

2001...... M. Sc. Botany, Tribhuvan University

2009...... M. S. Plant Pathology, The Ohio State University

2011 to present ...... Graduate Research Associate, Department of Plant

Pathology, The Ohio State University

Publications

Miller, S. A., Mera, J. R., Pantigoso, H. A., Vrisman, C. M., and Subedi, N. 2015.

Evaluation of fungicides for the control of foliar and fruit diseases of processing tomatoes, 2014. PDMR 9:V062. The American Phytopathological Society, St. Paul,

MN.

Subedi, N., Testen, A. L., Baysal-Gurel, F. and Miller, S. A.. 2014. First Report of Black

Leaf Mold of Tomato Caused by Pseudocercospora fuligena in Ohio. Plant Disease

99:285.

Subedi, N., Gilbertson, R. L., Osei, M. K., Cornelius, E. and Miller, S. A. 2014. First

Report of Bacterial Wilt Caused by Ralstonia solanacearum in Ghana, West Africa.

Plant Disease 98:840.

Subedi, N., and Miller, S. A. 2014 Resistance of a worldwide collection of resistant tomato, eggplant and pepper lines to South Asian strains of Ralstonia solanacearum

Phytopathology 104:S3.

Baysal-Gurel, F., Subedi, N., Mamiro, D. and Miller, S. A. 2014. First Report of

Anthracnose of Onion Caused by Colletotrichum coccodes in Ohio. Plant Disease

98:1271.

Testen, A. L., Mamiro, D. P., Meulia, T., Subedi, N., Islam, M., Baysal-Gurel, F. and

Miller, S. A. 2014. First Report of Leek yellow stripe virus in Garlic in Ohio. Plant

Disease 98:574.

Subedi, N., Baysal-Gurel, F., Hoitink, H., Ivey, M. and Miller, S. A. 2010. Regulation of genes involved in the interaction of tomato, Trichoderma hamatum 382 and Xanthomonas euvesicatoria. Phytopathology 100:S124

Miller S. A., Mera, J. R., Baysal-Gurel, F., and Subedi. N. 2009. Evaluation of fungicides to control Sclerotinia drop in Lettuce, 2008. PDMR 3:V010. The American

Phytopathological Society, St. Paul, MN.

Subedi, N. 2009. Use of biorational products for the control of diseases in high tunnel tomatoes and induction of certain defense genes in tomato by Trichoderma hamatum 382. MS Dissertation, The Ohio State University, Document no. osu1250602215.

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Fields of Study

Major Field: Plant Pathology

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Table of Contents

Abstract ...... ii

Dedication...... iv

Acknowledgments ...... v

Vita ...... vi

List of Tables...... xi

List of Figures ...... xiii

Chapter 1: Introduction ...... 1

Chapter 2: Characterization of Ralstonia solanacearum populations and screening host resistance to manage bacterial wilt in South Asia ...... 27

Introduction ...... 28

Materials and Method ...... 31

Results ...... 34

Discussion ...... 38

References...... 45

Chapter 3: Combining partial host resistance with bacterial biocontrol strains improves outcomes for tomatoes infected with Ralstonia solanacearum ...... 71 ix

Introduction...... 72

Materials and Methods...... 75

Results...... 79

Discussion...... 82

References...... 88

Bibliography...... 111

List of Tables

Table 2.1 Tomato, eggplant and pepper accessions screened for bacterial wilt resistance against six selected South Asian strains of Ralstonia solanacearum representing different phylogenetic groups...... 50

Table 2.2 Geographical origin, host and physiological and genetic characteristics of

Ralstonia solanacearum strains...... 52

Table 2.3 Distribution of biovar in different locations...... 58

Table 2.4 Interactions between 37 tomato, pepper and eggplant accessions and six South

Asian Ralstonia solanacearum strains expressed as percentage wilt...... 59

Table 2.5 Diversity and aggressiveness of Ralstonia solanacearum strains selected to screen host resistance of tomato, eggplant and pepper accessions...... 61

Table 3.1 Antagonism of bacterial biocontrol strains in an in vitro inhibition assay against

Ralstonia solanacearum strain NCSU...... 94

Table 3.2 Geographical origin, original host, and biovar of Ralstonia solanacearum strains ...... 97

Table 3.3 Bacterial wilt incidence in tomato lines IRAT L3 and L390, 29 days after inoculation with a mixture of three South Asian Ralstonia solanacearum strains. Plants were treated twice, immediately after seeding, and 3 weeks after seeding, i.e. 1 week prior to pathogen inoculation, with one of the six biocontrol agents (P. vranovensis strain

15D11, P. protegens strains 15G2 and Clinto 1, E. ludwigii strain 31D2, and P. brassicacearum strains Wood 1R and 98D3), and a mixture of all six strains, following root injury in the first two experiments and without root injury in the remaining experiments...... 98

Table 3.4Impact of root wounding on bacterial wilt incidence in tomato lines IRAT L3 and L390 inoculated with a mixture of three South Asian Ralstonia solanacearum strains, in the presence or absence of biocontrol agents ...... 99

Table 3.5 Bacterial wilt incidence expressed as percentage wilt and AUDPC in tomato lines IRAT L3 and L390 in A, the first two experiments, in which Ralstonia solanacearum was inoculated following root wounding, and B, the last two experiments in which the pathogen was inoculated without root wounding...... 100

Table 3.6 Biocontrol efficacy expressed as percentage reduction in wilt due to application of biocontrol agents to suppress bacterial wilt incidence in tomato lines L390 and IRAT

L3 and its correlation with in vitro inhibition of Ralstonia solanacearum...... 103

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List of Figures

Figure 2.1 Map of A, Bangladesh and B, Nepal showing origin of Ralstonia solanacearum strains characterized in this study...... 63

Figure 2.2 Phylogenetic tree created by Neighbor-joining algorithm where evolutionary distances were computed using Jukes and Cantor method with 1,000 bootstrap resampling. Empty and filled circles represents Ralstonia solanacearum strains from

Nepal and India, respectively. Other strains with SM numbers are from Bangladesh. All other strains are reference strains...... 65

Figure 2.3 Composite dendrogram created by combining genomic fingerprinting profiles obtained from BOX- and REP-PCR. Cluster analysis was performed with UPGMA algorithm to similarity matrix generated by Pearson's correlation coefficient from whole pattern of each fingerprinting profile. Groups were determined based on the minimum similarity (*) among ten lanes of 1Kb-plus ladder run separately in five different gels along with Ralstonia solanacearum strains. Strains GMI1000, K60, WW386 and

WW443 were used as reference strains for phylotpye I, II, III and IV respectively...... 66

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Figure 2.4 Mean bacterial wilt incidence by six Ralstonia solanacearum strains, selected based on geographical origin, host, biovar, and endoglucanase and Rep-PCR groups, in each of A, tomato, B, eggplant and C, pepper accessions, five weeks after inoculation.

Four-week-old seedlings were inoculated with 5 ml of R. solanacearum suspension (108

CFU/ml) following root injury. Bars with different letters are significantly different according to Fisher's LSD test

(P≤0.05)...... 68

Figure 3.1Mean zones of inhibition produced by 13 biocontrol agents (P. protegens strains 15G2 and Clinto 1, S. plymuthica strain 15H10, E. ludwigii strain31D2, P. frederiksbergensis strain 36C8, P. chlororaphis strain 48B8, P. fluorescens strains 48D1 and 48D5, P. vranovensis strain 15D11, and P. brassicacearum strains 38D4, 93D8,

93G8 and Wood 1R) against 15 South Asian Ralstonia solanacearum strains. A, Mean zone of inhibition produced by each biocontrol agent across all R. solanacearum strains.

B, Mean zone of inhibition produced against each R. solanacearum strain by all biocontrol agents. A suspension of 100 µl of R. solanacearum (108 CFU/ml) was spread onto PF medium. After the plates were dried in a laminar flow hood, 2.5 µL aliquots of biocontrol agents (109 CFU/ml) were dropped onto the plates and incubated for 48 h at

28oC, when zones of inhibition were measured. Bars with different letters are significantly different according to Fisher's LSD test...... 105

Figure 3.2 Incidence of bacterial wilt caused by R. solanacearum over time, in A, partially resistant tomato line IRAT L3 and, B, susceptible tomato line L390 treated with

xiv biocontrol agents P. protegens strains 15G2 and Clinto 1, E. ludwigii strain 31D2, P. vranovensis strain 15D11, or P. brassicacearum strains 93D8 and Wood 1R, immediately after seeding, and 3 weeks after seeding, i.e. 1 week prior to pathogen inoculation. Plants were maintained under greenhouse conditions and wilt progression was recorded 7 days after pathogen inoculation and every other day therafter, until the wilt progression stablized. This figure was created from data generated in experiment 3, including ‘Mixed’ treatment, a mixture of all six biocontrol agents. Data generated in the three other experiments were statiscally similar...... 107

Fig 3.3 Impact of biocontrol agents (BCAs) on bacterial wilt incidence in patially resistant (IRAT L3) and susceptible (L390) tomato accessions. Biocontrol agents werer applied immediately after seeding, and 3 weeks after seeding, i.e. 1 week prior to pathogen inoculation. The figure was created by combining data from all four experiments...... 109

Figure 3.4 Populations of Ralstonia solanacearum in root plugs (potting mix plus roots) treated with biocontrol agents P. protegens strains 15G2 and Clinto 1, E. ludwigii strain

31D2, P. vranovensis strain 15D11, or P. brassicacearum strains 93D8 and Wood 1R at different time intervals. biocontrol agents were applied 0 and 3 weeks after seeding. R. solanacearum was inoculated 4 weeks after seeding. Plugs treated only with R. solanacearum were used as a control. Populations of R. solanacearum were determined

0, 1, 2 and 3 weeks after inoculation with the pathogen by dilution plating on modified

SMSA medium...... 110

Chapter 1: Introduction

Ralstonia solanacearum (Smith) Yabuuchi is a β-proteobacterium in the

Burkholderia group. It was initially named Bacillus solanacearum, followed by

Pseudomonas solanacearum (Yabuuchi et al. 1992, 1995). It is an aerobic, rod shaped, non-spore forming, non-capsulate, gram-negative bacterium that accumulates poly-B- hydroxybutyrate intracellularly. This bacterium is oxidase positive and arginine dihydrolase negative (Kelman 1981, Denny 2007, Kelman 1981).

Most strains grow optimally at 30-32°C; they do not multiply at 4 or 40oC and growth is highly inhibited in 2% NaCl. They produce fluidal, irregularly round, white colonies with pink centers on 2,3,5-triphenyltetrazolium chloride-amended (TZC) medium (Kelman 1954). Avirulent mutants that can develop in culture are non-fluidal, uniformly round, butyrous, and deep red in color. Such mutants are highly motile with the help of a polar flagellum (Kelman and Hruschka 1973, Husain and Kelman 1958).

Conversion of a virulent wild type to avirulent mutant is a part of the survival strategy of this microorganism. Some factors such as susceptible host can revert the avirulent mutant to the virulent wild type (Denny et al. 1994, Poussier et al. 2005).

It is one of the most important soil borne plant pathogenic bacteria globally. It causes devastating wilt on over 450 plant species belonging to 54 families, covering both monocots and dicots (Wicker et al. 2007, Hayward 1991). The disease can be found in all tropical, subtropical and warm temperate regions of the world (Hayward 2005).

Wide host range and broad geographical distribution have made R. solanacearum an economically significant pathogen. Potato, tomato, tobacco, eggplant, banana, groundnut, and ginger are some of the economically important hosts. Bacterial wilt of potato has been estimated to cause annual losses of more than $950 million globally

(Walker and Collin 1998). Up to 100% loss of potato has been reported in certain parts of Nepal (Gurung and Vaidya 1997) with approximately 14% annual losses reported in

Bangladesh (Elphinstone 2005). This disease has been reported to cause up to 5% crop loss in South Carolina, USA, 70% in Australia and 91% in India. In addition to affecting potatoes, this is also a serious threat for banana and plantain production in Central and

South America, groundnut production in Vietnam and China, and ginger production in certain parts of India (reviewed in Elphinstone 2005).

After observing the geographical distribution and host range of R. solanacearum,

Buddenhagen, in 1986, mentioned that “there are many bacterial wilts and there are many

Pseudomonas solanacearums” (reviewed in Denny 2007). All R. solanacearum, along with R. syzgii, the causal agent of Sumatra disease of clove trees, and Blood Disease

Bacterium (BDB), the causal agent of blood disease of banana and a few other members of Musaceae in Indonesia, forms a complex called the Ralstonia solanacearum species

2 complex (RSSC) (Gillings and Fahy, 1994). Phenotypic, DNA-DNA hybridization and partial 16s rDNA sequence data of R. syzgii and BDB have shown them to be closely related to R. solanacearum (Roberts et al. 1990, Seal et al. 1993).

Ralstonia solanacearum strains were initially characterized based on their host range and biochemical properties. Buddenhagen et al (1962) identified three races on the basis of host range. Currently RSSC is divided into five races. Race 1 has very wide host range, whereas race 2 includes strains from banana and other Musa species. Race 3 includes the strains from potato, some other solanaceous crops, geranium and a few other species. Similarly, race 4 and 5 includes pathogens from ginger and mulberry, respectively (Daughtery 2003). Races in RSSC, however, do not resemble the races in other bacterial pathosystems, in which races are determined by differential reactions with different cultivars of a single host species (Alvarez 2005). RSSC is classified into five biovars based on the utilization and oxidation pattern of a set of carbohydrates and alcohols (Hayward 1964, French el al. 1995). Biovar 2 strains isolated from potato are further characterized as biovar 2-T (adapted in tropical habitat) and 2-A (adapted in

Andean habitat) using an extended panel of carbohydrates and aggressiveness of strains on potato at 25oC (French et al. 1993, Hayward 1994).

Cook et al. (1989) first used a molecular approach to characterize R. solanacearum. They used Restriction Fragment Length Polymorphism (RFLP) analysis on 62 isolates of R. solanacearum from Asia, Oceania and the Americas. A similar study was carried out again with more isolates (Cook and Sequeira 1994). Both studies

3 identified two major divisions and various subdivisions. Division I contained strains from

Asia and Oceania and division II included American strains. Strains from biovar 3, 4 and

5 were in division I, whereas division II encompassed biovars 1 and 2. The above finding was further consolidated by a phylogenetic analysis based on 16s rRNA gene sequences that identified two major phylogenetic groups among RSSC. Division I included Asian strains and division II was further divided into three sub-divisions: IIa, containing

American strains, IIb containing R. syzygii and BDB, and IIc containing African strains

(Taghavi et al. 1996, Poussier et al. 2000).

A relatively recent and widely accepted system of classification, called the

'phylotyping scheme’, has been proposed by Fegan and Prior (2005). They divided RSSC in four monophyletic groups called phylotypes based on analysis of internal transcribed spacer (ITS) region, and hrp B and endoglucanase (egl) gene nucleotide sequences.

Phylotype can easily be determined in the laboratory using multiplex PCR primers targeting the ITS region. Phylotype I and II include Asian and American strains, respectively. Similarly, Phylotype III includes African strains and Phylotype IV includes strains from Indonesia, Australia, Japan, and BDB and R. syzygii. Each phylotype is further divided into several ‘sequevars’ or sequence variants, based on analysis of partial endoglucanase gene sequences. Each sequevar is further composed of several clonal populations, determined by DNA fingerprinting techniques such as rep-PCR, amplified fragment length polymorphism (AFLP) or pulsed-field gel electrophoresis (PFGE). The phylotyping scheme has recently been employed by a large number of researchers to characterize RSSC populations from different parts of the world (Ivey et al. 2007, Xue et 4 al. 2012, Hong et al. 2012, Ramsubhag et al. 2012, Ramesh et al. 2014, Fonseca et al.

2014, Lin et al. 2014).

Sequence analysis of five housekeeping genes from the chromosome and three virulence-related genes from the megaplasmid further confirmed the presence of four clear phylogenetic groups (phylotypes). This study also revealed the presence of two sub- clusters (IIa and IIb) within phylotype II (Castillo and Greenberg 2007). With the help of multilocus sequence analysis (MLSA) Wicker et al (2011) identified eight groups of strains (clades) with distinct evolutionary patterns within already established phylotypes.

Based on recombination analysis they hypothesized that the pathogen evolved in or around Indonesia as phylotype IV. Migration of phylotype IV from Indonesia to other parts of the world followed by adaptation to different environments and hosts resulted in the evolution of other phylotypes (Wicker et al. 2011).

Availability of whole genome sequences has increased the understanding of phylogeny of the RSSC. After analyzing average nucleotide identity (ANI) of six genomes from RSSC, including all phylotypes but R. syzygii and BDB, Remenant et al.

(2010) recognized three distinct taxonomic groups, each with less than 70% DNA homology. They proposed to divide four phylotypes into three species; phylotypes II and

IV making two distinct species and phylotypes I and III combined to make the third.

Later, a study that included the whole genome sequences of R. syzygii and BDB along with other R. solanacearum strains concluded R. syzygii, BDB and phylotype IV strains make one genomic species (Ramenant et al. 2011). Based on this evidence, strains from

RSSC have been proposed to classify into three species. Strains from phylotype I and III have been proposed as Ralstonia sequeirae. Similarly, strains from phylotype IV including R. syzygii and BDB would be renamed as R. haywardii, and the phylotype II strains have been left as R. solanacearum. Based on phenotype and life cycle, R. haywardii has further been proposed to divide into three subspecies, namely R. haywardii subspecies solanacearum, R. haywardii subspecies celebensis and R. haywardii subspecies syzygii (Remenant et al. 2011, Genin and Denny, 2012).

Ralstonia solanacearum survives in soil saprophytically. After sensing root exudates, it moves toward roots with the help of flagella. Pili and lipopolysaccharides help it to attach to root surfaces and colonize zones of root elongation, the site for later root emergence. It enters plant roots either through mechanical wounds or through natural wounds formed at root axils during lateral root emergence (Alvarez et al. 2010, Vasse et al. 1995). Once inside the plant roots, R. solanacearum moves towards the vascular region with the help of exopolysaccharides

(EPS) and pectinolytic and cellulolytic enzymes (Gonzalez and Allen 2003, Liu et al.,

2005).

Exopolysaccharides (EPS), type III secretion system (T3SS), type IV secretion system (T4SS), type VI secretion system (T6SS), exogenous lytic enzymes, membrane- bound and cytosolic chemoreceptors, and mobility proteins have been reported to be involved in virulence of R. solanacearum (Meng 2013, Genin and Denny 2012, Schell

2000, Zhang et al. 2014). Global transcriptional factor PhcA, whose activity is controlled

6 by a quorum-sensing mechanism, controls a network of several transcriptional factors involved in regulation of these virulence factors. When density of R. solanacearum is low before it penetrates plant roots, PhcA is suppressed, which induces expression of motility factors, endopolygalacturonase, siderophores and T3SS. After entering plant roots, bacteria multiply rapidly resulting in activation of PhcA. Activated of PhcA induces EPS,

β-1,4 endoglucanase, pectin methyl-ester, and cellulase formation; and represses motility factors, endopolygalacturonase, siderophores and T3SS (Bhatt 2004, Brown and Allen

2004, Tans-Kersten et al. 1998, Tans-Kersten et al. 2004).

This model, however, is controversial as recent studies (Jacobes et al. 2012, Meng

2013, Monteiro et al. 2012) reported the presence of T3SS related products such as hrp B and other effectors at high concentration even at the later stage of colonization when bacterial density was still high.

Ralstonia solanacearum has the ability to colonize even highly resistant genotypes. Grimault et al. (1994) observed that tomato cultivars with 100% survival rate were colonized by R. solanacearum. However, the colonization was limited to lower parts of stems in these cultivars. Nakaho et al. (2004) reported that the pathogen was limited to the protoxylem, and was not able to spread to primary and other xylem tissue, in resistant cultivars. Therefore, as suggested by Lebeau et al. (2011), host resistance to bacterial wilt is an ability to adopt latent infection or an ability to contain pathogens in the lower parts of the stem.

Host resistance to bacterial wilt is quantitative, polygenic, strain/phylotype- specific, and greatly influenced by temperature, soil moisture and pH (Acosta 1978,

Hanson et al. 1996, Scott et al. 2005, Wang et al. 2013). Bacterial wilt resistant quantitative trait loci (Bwr QTL) have been found in chromosomes 2, 3, 4, 5, 6, 8, 11 and

12 in tomato accession Hawaii 7996 (Thoquet et al. 1996a, b; Wang et al. 2000, 2013;

Carmeille et al. 2006). Among them, the QTL in chromosome 12 (Bwr-12), reported as phylotype I-specific, has the largest effect controlling 17.9 to 56% of total resistance, followed by QTL in chromosome 6 (Bwr-6), contributing 11.5 to 22.2% of the total resistance (Wang et al. 2013). However, successful incorporation of these resistant genes in cultivars with desired agronomic traits has been very rare due to linkage between host resistance and small fruit size (Scott et al. 2004).

The most effective and practical approach to managing bacterial wilt is by using resistant cultivars (Lopez and Elena 2005, Liao 2005). A bacterial wilt resistant peanut cultivar was successfully screened in early 1900s in Indonesia. Currently, more than 170 bacterial wilt- resistant peanut genotypes have been identified worldwide. ‘Schwarz 21’, a resistant peanut genotype developed about 85 years ago, is still resistant to all the strains of R. solanacearum under diverse environmental conditions (Mehan and Liao

1997, Liao 2005). However, the story with other economically important crops is completely different. Screening for bacterial wilt resistance in other crops poses two major problems. Firstly, the resistance does not last for long. Secondly, the genotype screened under one environmental condition to a strain of the pathogen, may not work in other environmental conditions, to other pathogen strains (Serraf et al. 1991, Mendoza 8

1994, Fock et al. 2005). This demands a continuous screening for resistance in different environmental conditions with various strains of the pathogen.

In an evaluation of 35 tomato lines in 11 locations of 10 countries, a tomato line,

‘Hawaii 7996,’ expressed the highest level of resistance to bacterial wilt in most of the locations. Other lines showing high levels of resistance were BF-Okitsu 101, Hawaii

7997, Hawaii 7998, CRA 66, Tml 114-48-5-N-spreading, Tml 46-N-12-N-early N.T., R-

3034-3-10-N-UG, and F7-80-465-10-pink (Wang et al. 1998a). In another study, a set of

344 eggplant accessions, most of them from Indonesia, Malaysia, Thailand and India, were screened for R. solanacearum strains. Seventeen of them, including EG 219, EG

203, EG 192, TS 69, TS 3, TS 47A, TS 56B, TS 7, and EG 190 expressed higher level of resistance (Wang et al. 1998b).

Recently, Lebeau et al. (2011) collected a set of 30 tomato, eggplant and pepper varieties from different parts of the world, that are currently being used as sources of resistance to bacterial wilt. The collection, which they termed ‘Core-TEP’, was screened against 12 diverse strains of R. solanacearum. Different members of Core-TEP expressed different levels of resistance to different strains of R. solanacearum. A few strains of R. solanacearum overcame resistance of all hosts tested. Based on virulence of Core-Rs2 on

Core-TEP, they identified six groups, which were termed "pathoprofiles". Similarly, from the interactions of Core-Rs2 with individual plant species, i.e. tomato, eggplant and pepper; five, six and three groups, respectively, were identified and called "pathotypes".

Grafting scions with high agronomic value onto resistant rootstocks is a common practice to manage bacterial wilt. Grafting not only protects plants from bacterial wilt but also increases yield by extending growing season, and increasing tolerance to abiotic stresses such as soil moisture and salinity (Miller et al. 2005, Rivard and Louws 2011).

Grafting commercial eggplant varieties on Solanum sisymbriifolium (sticky nightshade), a bacterial wilt and root knot nematode (RKN) resistant rootstock, have been reported to increase net income of farmers by 2.4 to 8 times in Bangladesh (Miller et al. 2005).

Inherent resistance within rootstocks, induced host resistance due to movement of nucleic acids and proteins from rootstocks to scions, shift of rhizosphere microbial populations, and improved nutrient uptake have been considered as possible mechanism of protection and yield increase in grafted plants (Guan and Zhao 2012, Haroldsen et al. 2012).

Bacterial wilt is one of the most important diseases of tomato, eggplant and pepper in South Asia. The disease is difficult to manage due to variability, adaptability and diversity of the pathogen. Host resistance is one of the best options available to tackle this disease. However, the strain/phylotype specificity of host resistance limits relevance of this approach. Only pathogen-targeted management approaches, that require prior knowledge of local pathogen populations, can provide satisfactory and sustainable control of this disease. Therefore, the first objective of this research was to characterize populations of R. solanacearum strains collected from South Asia using the classical as well as recent molecular techniques, and the second objective was to screen a worldwide collection of resistant tomato, pepper and eggplant accessions against representative

South Asian strains, to identify suitable hosts that can potentially be utilized to manage bacterial wilt in South Asia.

Predicting potential damage bacterial wilt would cause, the European and

Mediterranean Plant Protection Organization (EPPO) has listed R. solanacearum as an

A2 quarantine pest (Lee et al. 2012). Similarly, the Agricultural Bioterrorism Protection

Act 2002 has designated race 3 biovar 2 of R. solanacearum as a select agent in the

United States. Bacterial wilt can be prevented in disease-free areas by adopting strict quarantine regulations, however, no single management practice gives satisfactory result in locations where the disease is endemic (Saddler 2005, Lopez and Biosca 2005).

Integration of different management practices such as using disease-free planting materials, selecting less susceptible crop varieties, rotating with non-host crops and amending soil with biological or non-biological agents is very promising (Akiew and

Trevorrow 1994, Saddler 2005).

Crop rotations reduce the pathogen population in soil. Efficacy of crop rotation depends on duration and crop type used. Rice, maize, wheat, lupine, garlic, sweet potato, sugarcane, finger millet, sorghum, carrot, onion, pea, cabbage, fescue, French marigold, fescue, okra, cowpea and beans were successfully used as rotation crops, singly or in different combinations (Vinh et al. 2005, El-Ghafar 1998, Verma and Shekhawat 1991,

Melton and Powell 1991, Terblanche and Villiers 1998, Adhikari and Basnyat 1998,

Katafiire et al. 2005). One season rotation with corn, okra, cowpea, or a partially resistant tomato delayed the onset of tomato wilt by 1-3 weeks and reduced the severity by 20-

26% in central Nepal (Adhikari and Basnyat 1998). Weeding is an important component 11 of crop rotation for bacterial wilt management. Several weeds have been reported to harbor R. solanacearum in and around the cropping fields (Pradhanang and Elphinstone

1996, Hayward 1991, Tusiime et al. 1998). Poor or non-host crops can be used as rotation crops. Non-host crops capable of releasing compounds toxic to R. solanacearum into the soil make ideal rotation crops. In absence of suitable rotation crop, leaving fields fallow also reduces wilt incidence. However, leaving the fields unused and planting crops with low economic or agronomic value are not always in the best interest of farmers

(Lopez and Elena, 2005). Further, the wide range of weed host limits the impact of crop rotation (Hayward 1991).

Soil borne diseases can also be addressed by directly treating soil against pathogens. This approach has been tested for bacterial wilt management with mixed results. Soil amendment with stable bleaching power and a mixture of urea and lime has reduced the potato wilt incidence in Nepal (Dhital et al. 1997), India (Kishore et al. 1996) and Bangladesh (personal communication with Dr. Rahman, Bangladesh Agricultural

Research Institute, BARI). Five out of six plant essential oils investigated have shown in vitro activities against R. solanacearum (Lee et al. 2012), when used as soil amendment agents. Thymol or palmarosa oil provided complete protection from tomato wilt by reducing the pathogen population to an undetectable level under greenhouse conditions

(Ji et al. 2005). The disease was suppressed about 45-60% under field conditions (Ji et al.

2005). In another study, thymol, when applied singly, failed to provide any protection against tomato wilt under field conditions (Hong et al. 2011). Soil amendment with organic and chemical fertilizers (NPK), acidified nutrients and S-H mixture (agricultural 12 and industrial wastes) has provided various levels of protection against bacterial wilt

(Roy et al. 1999, Yi and Sul 1998, Yao et al. 1994). Soil solarization, generally used in combination with other soil amendment/ fumigation agents does not have a consistent impact on bacterial wilt. Solarization, when combined with biological control agent(s)

(Anith et al. 2000, Kumar and Sood, 2001) or a fumigant Dazomet (Yamada et al. 1997) reduced the incidence of tomato wilt. But when combined with other chemical fumigants such as metham sodium, 1,3-dicholropropane, chloropicrin, methyl bromide, pebulate or a biological fumigant, cabbage residue, no protection was afforded (Chellemi et al.

1997). The effect of soil amendments on R. solanacearum populations is related to soil type (Michel and Mew 2008), which may be a reason for inconsistent performance.

A relatively new technique called biological soil disinfection (BSD) has reduced the population of R. solanacearum by more than 90% in soil. This technique creates an anaerobic environment in the soil covered by airtight plastic through anaerobic decomposition of fresh organic amendments (Messiha et al. 2007b, Blok et al. 2000).

Solarization and microwave treatment has also been tested successfully to disinfect the seed rhizomes of ginger from R. solanacearum (Kumar et al. 2005).

Transgenic tobacco lines expressing the wheat TaPIMP1 gene, a transcription factor, have shown increased resistance to bacterial wilt (Liu et al 2011). However, lack of acceptance of a transgenic food crop can be a potential restriction of this approach.

Chemical bactericides such as copper compounds and antibiotics have limited impact

(Hartman and Elphinstone 1994). Besides, overuse increases the risk of resistance development in R. solanacearum (Lopez and Elena, 2005).

Biocontrol is considered a potentially economically feasible and environmentally safe and sustainable disease management practice. Biological control agents (BCAs) or chemicals that mimic BCAs are intensively investigated for bacterial wilt management.

Avirulent hrp mutants of R. solanacearum (Frey et al. 1994) and R. solanacearum infected with lytic bacteriophages (Akiko et al. 2011, Addy et al. 2012) have provided some protection from bacterial wilt. In the latter case, phage-infected R. solanacearum stimulated the expression of pathogenesis-related (PR) proteins in the host plants (Addy et al. 2012). Hence the protection might be through enhanced plant resistance.

Acibenzolar-S-Methyl (ASM) is a synthetic chemical compound that induces systemic acquired resistance (SAR) in plants. ASM reduced bacterial wilt when combined with a moderately resistant cultivar (Pradhanang et al. 2005), thymol (Hong et al. 2011), or plant growth promoting rhizobacteria (PGPR) (Anith and Momol 2004, Albo-Elyousr et al. 2012). However, the outcome was mixed when applied singly.

Besides protecting plants by antagonism, competition and induction of host resistance, BCAs also enhance plant vigor by stimulating nutrient uptake (Pal and

McSpadden Gardener 2006, McSpadden Gardener 2004). Several species of

Pseudomonas, Burkholderia, Bacillus, Streptomyces, Actinomycetes, Acinetobacter,

Enterobacter, Escherichia, Erwinia, Stenotrophomonas, Serratia, phlD+ rhizobacteria and ectomycorrhizal fungi have been studied for their biocontrol activity against bacterial

14 wilt (Saddler 2005, Messiha et al. 2007a, Xue et al. 2009, Wei et al. 2011, Ramesh and

Phadke 2012, Ramadasappa et al. 2012).

Though the majority of biocontrol agents tested provide satisfactory results under controlled environments, their performance is not consistent under field conditions. This situation can be improved either by exploring new biocontrol agents against bacterial wilt or by integrating biocontrol agents with other disease management practices. Hence, the third objective of this research was to investigate a collection of previously characterized bacterial biocontrol agents, with several traits desired in a biocontrol agent, for their antagonistic activities against R. solanacearum and to test the value of integration of selected antagonistic bacteria with partial host resistance in management of bacterial wilt.

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Chapter 2: Characterization of Ralstonia solanacearum populations and screening

for host resistance to manage bacterial wilt in South Asia

ABSTRACT

Bacterial wilt caused by Ralstonia solanacearum (Smith) Yabuuchi is a major problem for tomato, eggplant and pepper production in South Asia. The disease is difficult to manage due to viability, adaptability and diversity of R. solanacearum. A collection of 100 R. solanacearum strains from South Asia collected in Bangladesh,

Nepal and India were characterized using classical as well as molecular tools. All strains in our collection were race 1, phylotype I, and biovar III (60%) or IV (40%). Based on phylogenetic analysis of endoglucanase gene sequence, three predetermined sequevars

(14, 47, and 48), and two putatively new sequevars were identified among the South

Asian strains. Cluster analysis of genomic fingerprinting profiles created by Rep-PCR divided strains into eight groups. Strains were not grouped based on geographic origin, host or biovar in either analysis. To identify resistant tomato, eggplant and pepper genotypes that can potentially be used in South Asia to manage this disease, we screened a worldwide collection of 37 Solaneaceous hosts of tomato, eggplant and pepper accessions against six selected South Asian R. solanacearum strains representing the

27 diversity. Six tomato, nine eggplant, and three pepper accessions were highly resistant

(≤10% wilt), and three tomato, two eggplant and one of the pepper accessions were moderately resistant (≤30% wilt). The outcomes of this study will support farmers and plant breeders in South Asia to manage bacterial wilt by identifying the lines most resistant to local R. solanacearum populations. Resistant lines can also be considered for use as rootstocks in grafting programs.

INTRODUCTION

Ralstonia solanacearum (Smith) Yabuuchi is a β-proteobacterium of the

Burkholderia group that causes vascular wilt in over 450 plant species belonging to 54 families (Hayward 1991, Wicker et al. 2007). The disease is distributed in all warm and humid tropical and sub-tropical regions. However, several strains of R. solanacearum, causing potato brown rot, are also found in cool temperate regions (Hayward 2005).

R. solanacearum is an economically significant pathogen of tomato, potato, tobacco, eggplant, banana, groundnut, ginger and several other agronomically important crops. The pathogen has been traditionally divided into five races, based on host range

(Buddenhagen et al. 1996, Daughtery 2003), and five biovars, based on their biochemical properties. Biovar 2 strains isolated from potato are further characterized as biovar 2-T, adapted in tropical habitats, and 2-A, adapted in Andean habitats (French et al. 1995,

Hayward 1994). The race and biovar system of classification does not reflect aggressiveness or geographic origin of pathogen populations.

Classifications based on molecular data have provided better insight on geographical distribution/origin of R. solanacearum populations. Phylogenetic analyses of restriction fragment length polymorphisms (RFLP) (Cook et al. 1989, Cook and

Sequeira 1994) and 16s rRNA gene sequences (Poussier et al. 2000, Taghavi et al. 1996) have identified two major divisions and various subdivisions based on geographic origin.

In a more recent study, R. solanacearum strains were clustered into four monophyletic groups called phylotypes based on phylogenetic analysis of internal transcribed spacer

(ITS) region, hypersensitive response and pathogenicity B (hrpB) and endoglucanase

(egl) gene sequences (Fegan and Prior 2005). Phylotypes I, II and III contain strains from

Asia, America and Africa, respectively, whereas phylotype IV includes strains from

Indonesia, Australia, Japan, the blood disease bacterium (BDB) and R. syzygii, two close relatives of R. solanacearum. Each phylotype is divided into several ‘sequevars’ or sequence variants, based on analysis of partial endoglucanase gene sequences (Fegan and

Prior 2005). Each sequevar is further divided into several clonal populations, determined by DNA fingerprinting techniques such as rep-PCR, AFLP or pulsed-field gel electrophorosis (PFGE). The phylotyping scheme has recently been employed by a large number of researchers to characterize R. solanacearum species complex populations from different parts of the world (Albuquerque et al. 2014, Fonseca et al. 2014, Lin et al. 2014,

Ramsubhag et al. 2012, N'Guessan et al. 2012, Sagar et al. 2014, Xue et al. 2012).

Bacterial wilt is a major constraint for production of eggplant, tomato and pepper in South Asia. Host resistance is the most practical and sustainable approach to manage this disease (Liao 2005, Lopez and Elena 2005), however very few bacterial wilt

29 resistance hosts are available. In the Check List of Commercial Varieties of Vegetables published by the Government of India, eight tomato, three eggplant, and no pepper varieties were listed as resistant to bacterial wilt (Singh 2012). Tomato lines Arka ananya, Arka abhijit, Arka abha, CLN2020C, All Rounder, Swarakhsha, Rakshak,

Trishul, and, and eggplant lines Kata Begun, Marich Begun, Pusa purple cluster, JC-2,

Pant samrat, Arka anand and Uttar are major bacterial wilt resistant cultivars used in

South Asia (Dutta and Rahman 2012, Rahman et al. 2011, Sing 2012, Timila and Joshi

2007).

Grafting desired commercial varieties onto resistant rootstocks is another approach to combat bacterial wilt (Rivard et al. 2012). Bacterial wilt resistant Solanum sisymbriifolium, also known as Sticky nightshade, Fire-and-ice plant, Litchi tomato, etc., is a popular root stock in South Asia that is also resistant to species of Meloidogyne causing root knot. Plants grafted onto S. sisymbriifolium not only reduce the incidence of bacterial wilt but also increase marketable yield, even in the absence of disease pressure

(Miller et al. 2005). However, recent failures of S. sisymbriifolium at several locations in

Bangladesh and Nepal are of a major concern for researchers and growers in this region.

Host resistance to bacterial wilt is strain specific (Danesh and Young, 1994, Wang et al.

1998). Therefore, the objectives of this study were to characterize R. solanacearum strains from South Asia using classical as well as molecular techniques, and to screen a worldwide collection of tomato, eggplant and pepper genotypes for resistance to representative South Asian strains of R. solanacearum.

MATERIALS AND METHODS

Bacterial strains. A survey was conducted during 2012 to collect R. solanacearum strains in major vegetable growing regions of Bangladesh and Nepal (Fig. 1). Bacterial strains were isolated from symptomatic eggplant, tomato, pepper and Solanum sisymbriifolium (used as root stock of tomato and pepper scions) on tetrazolium chloride

(TZC) medium (Kelman 1954). Identity of bacteria was confirmed based on colony morphology on TZC medium, R. solanacearum-specific ImmunoStrips (Agdia Inc.,

Elkhart, IN), and a polymerase chain reaction (PCR) assay using R. solanacearum species complex-specific primers 759/760 (Opina et al. 1997) as described previously

(Ivey et al. 2007). Six strains from India were also included in the study.

Biovar determination. The biovar designation of each strain was determined based on the ability to utilize and oxidize a panel of disaccharides and hexose alcohols as described by French et al. (1995) with slight modifications. One hundred fifty microliters of basal medium containing 1% cellobiose, lactose, maltose, dulcitol, mannitol or sorbitol were dispensed into 96-well plates. A droplet (7 µl) of 48-h-old culture suspension (~109

CFU/ml) was inoculated into each well and incubated for two weeks at 28°C before observation. Basal medium without a sugar/alcohol amendment was used as negative control.

Phylotype determination. Phylotype-specific multiplex PCR (Pmx-PCR) was performed using five phylotype-specific (Fegan and Prior 2005) and two species complex-specific

(Opina et al. 1997) primers. Reaction mixture preparation, amplification and gel electrophorosis were performed as described previously (Ivey et al. 2007). Genomic

DNA of strains GMI 1000, K60, WW386 and WW443 (kindly provided by Dr. Caitlyn

Allen, University of Wisconsin, Madison), were used as positive control for phylotypes I,

II, III and IV respectively.

Endoglucanase (egl) gene sequence analysis. Partial endoglucanase gene fragments were amplified by PCR using primers EndoF and EndoR (Fegan et al. 1998). Each 25 µL reaction mixture contained 50 ng of template DNA, 0.6 µM of each primer and 12.5 µl of

2X GoTaq Green Master Mix (Promega Corporation, Madison, WI). PCR was performed as: one cycle of denaturation at 96°C for 9 min, followed by 30 cycles of 95°C for 1 min,

70°C for 1 min, 72°C for 2 min; and a final extension at 72°C for 10 min. Presence of amplicons was confirmed by gel electrophoresis. Amplicons were purified using Wizard

SV Gel and PCR Clean-Up System (Promega Corporation, Madison, WI) and sequenced at the Plant-Microbe Genomics Facility, The Ohio State University, Columbus.

Sequences were manually edited using Chromas LITE 2.1.1 (Technelysium Pty Ltd.,

Australia), and aligned, trimmed and analyzed with e MEGA 5.2 (Tamura et al. 2011).

Phylogenetic analyses were performed using a neighbor-joining (NJ) algorithm in which evolutionary distances were computed using the Jukes and Cantor method (Juke and

Cantor 1969).

Genomic fingerprinting with rep-PCR. DNA fingerprinting profiles were created using

BOX-PCR with BOX A1R primer (Versalovic et al. 1994) and ERIC-PCR with

ERIC1R/ERIC2 primers (de Bruijin, 1992) as described earlier (Louws et al. 1994), with slight modifications. For both PCR assays, reaction mixtures contained 50 ng of template

DNA, 6 µm of each primer and 12.5 µl of 2X GoTaq Green Master Mix (Promega

Corporation, Madison, WI). Final volume was adjusted to 25 µl with nuclease-free water.

PCR amplifications were carried out using the following programs: 7 min at 95°C, 30 cycles of 1 min at 94°C, 1 min at 53°C for BOX-PCR and 52°C for ERIC-PCR, 8 min at

65°C, and a 16 min final extension at 65°C. Gel electrophoresis was carried out with 10 µl of PCR product with 2% (wt/vol) agarose gel in 1× Tris-borate EDTA (TEB) buffer at 50

V for 7.5 h. Gels were stained in ethidium bromide solution (2 µg/ml) and photographed under UV light. Fingerprinting patterns were analyzed with GelCompar II (version 5.0) software (Applied Maths, Belgium). Cluster analysis was performed with UPGMA algorithm to similarity matrix generated by Pearson's correlation coefficient from whole pattern of each fingerprinting profile.

Host resistance screening. Seeds of 37 accessions of tomato, eggplant and pepper

(TEP), including Core-TEP, a worldwide collection of 30 tomato, eggplant and pepper accessions assembled by Lebeau et al. (2011), were obtained from AVRDC (The World

Vegetable Center, Taiwan), INRA (Institut National de la Recherche Agronomique,

France), BARI (Bangladesh Agricultural Research Institute, Bangladesh), and Makerere

University, Uganda (Table 1). Seeds were sown in plastic trays with 2.5 x 2.5 cm2 cells containing planting medium (Sungro Horticulture, Agawam, MA). Four-week-old seedlings were inoculated with a 5 ml suspension (1×107 CFU/ml) of each of six R. solanacearum strains (SM 701, SM 716, SM 732, SM 738, SM 743 and MB 1) selected based on host, origin, biovar and genetic diversity, determined as described above.

Inoculum was prepared in sterile distilled water from 48 h old cultures growing on casamino acid, peptone, glucose (CPG) medium at 28°C. Seedlings were inoculated

33 following root wounding with sterile scalpel blade. Plants were monitored for wilt symptoms daily and wilt incidence was recorded twice weekly for 5 weeks after inoculation. The experiment was conducted twice as a randomized complete block design with three replications (blocked by time) of 15 plants per replication, with a split-plot arrangement. Ralstonia solanacearum strains were applied as the main plot effect and

TEP seedling were arranged in sub-plots. The experiment was conducted in a Biosecurity

Level 2 laboratory and greenhouse, all experimental plants were destroyed by autoclaving and all surfaces in contact with experimental treatments were disinfected at the end of the experiment.

RESULTS

Bacterial strains, biovars and phylotypes. A total of 100 strains of R. solanacearum were characterized in this study, 94 of which were collected from 12 major solanaceous vegetable growing regions of Bangladesh and Nepal; six were obtained from four states in India (Table 2). Based on host (eggplant, tomato, pepper and S. sisymbriifolium), all strains were classified as race 1. Biochemical tests differentiated all the strains into two biovars. Sixty percent of the strains were biovar III, which utilized carbon from all six sources, and the remaining 40% were biovar IV, which utilized carbon from dulcitol, mannitol and sorbitol. Except for Norsindhi and Comilla in Bangladesh, biovar III was predominant in all locations where three or more isolates were obtained (Table 3).

Phylotype-specific multiplex PCR of all 100 strains tested resulted in R. solanacearum species complex-specific (280 bp) and phylotype I specific (150 bp) amplicons,

34 indicating that all the strains tested were members of the R. solanacearum species complex originated in Asia.

Endoglucanase gene sequence analysis. Phylogenetic analysis of partial (671 bp) endoglucanase gene sequences of 40 selected strains was performed along with 24 reference strains representing four phylotypes, including all known sequevars of phylotype I, and three recently described unknown or new phylotype I strains from India

(Ramesh et al. 2014, Hong et al. 2012, Xue et al. 2011). Among the 671 bp sequence of the South Asian strains (n = 40), 648 bp were conserved and 23 were variable, of which

13 were phylogenetically informative.

Phylogenetic analysis of endoglucanase gene sequences divided strains from four different phylotypes into four distinct clades, all strains from this study fall within phylotype I clade (Fig. 2). Phylotype I strains were separated with shorter branch lengths compared to strains from other phylotypes, indicating smaller genetic diversity within this group. South Asian strains were divided into four groups (bootstrap value ≥ 70%).

Group 1 was the largest group containing 17 strains, 15 from Bangladesh and two from

Nepal, along with reference strain GMI8214 (sequevar 47). Group 2 was the second largest group with 8 strains, seven from Bangladesh and one from Nepal. This group does not contain any reference strains, making it genetically distinct from all R. solanacearum strains described so far. Group 3 contains four strains, three from Bangladesh and one from Nepal, along with reference strain M2 (sequevar 48). Group 4 contains three South

Asian strains, all from Bangladesh, along with reference strains MAD17 (sequevar 46),

P16 (sequevar 18), GMI1000 (sequevar 12 or 18) and CFBP2968 (sequevar 13 to 18).

Strain SM 743, isolated from tomato grafted on S. sisymbriifolium in Nepal, aligned with reference strain PSS81 (sequevar 14) but not with any other South Asian strains.

Similarly, strain MB1 from India aligned with a reference strain Rs 10-282 (unknown sequevar) from India. The remaining seven strains were singletons.

Phylogenetic analysis of partial endoglucanase gene identified three predetermined sequevars: 14, 47 and 48 among South Asian strains. Strains in group 2, and strain SM 651, that aligned with an Indian reference strain, may be new sequevars.

Group 4 includes strains from multiple sequevars and strains with multiple sequevar assignment. The phylogenetic status of strains in group 4 and the remaining seven strains that did not align with other strains is ambiguous. Among four S. sisymbriifolium strains used in this analysis, three from Bangladesh aligned with reference sequevar 47 in group

1, and one, isolated from Nepal aligned with reference sequevar 14 but not with other

South Asian strains.

Genomic fingerprinting with rep-PCR. A composite dendrogram, created by combining fingerprinting profiles obtained from BOX and REP-PCR, identified eight groups (Fig. 3). Strains SM 677 and SM 704 did not cluster with other strains. Strains were clustered in groups with 70% similarity, the minimum similarity among 10 lanes of

1Kb-plus ladder run separately in five different gels along with South Asian strains.

Reference strains representing phylotypes II, III, and IV were separated from South Asian strains at the 25% similarity level. Strains collected from South Asia did not cluster based on geographic origin, host, biovar or endoglucanase group (identified based on endoglucanase gene sequence analysis), however, four out of eight groups, had a majority

(at least 50%) of strains from one location. Group 5 was the largest cluster, containing 52 strains including phylotype I reference strain GMI1000. This group contained strains from all locations, hosts, and biovars. One strain from Nepal was placed in group 4, while the remaining 13 strains clustered in group 5. Similarly, among the six strains collected in

India, four clustered in group 3, one in group 4, and one in group 5. Strains from

Bangladesh were present in all eight groups. Strains isolated from S. sisymbriifolium were in groups 2, 4, 5, and 6.

Host resistance screening. Incidence of bacterial wilt among the 37 accessions by each of the six selected South Asian R. solanacearum strains is presented in Table 4. Mean wilt incidence in the susceptible tomato (L390), eggplant (MM136) and pepper (Yolo

Wonder) controls was 85.5, 83.6 and 50%, respectively. Mean wilt incidence in all tomato, eggplant and pepper accessions was 25.2, 20.4 and 21.1% respectively (Table 5).

Aggressiveness of R. solanacearum strains varied with host species, and among accessions within a species. Strain SM 738, originally isolated from eggplant, was the most aggressive across all three host species. Strain SM 732, isolated from S. sisymbriifolium in Bangladesh, was highly aggressive on tomato (36% wilt) but was the least aggressive on pepper (2.5% wilt). Strain SM 743, isolated from S. sisymbriifolium in

Nepal, was the most aggressive on pepper (38.2% wilt) and less aggressive on tomato and eggplant (11.7 and 18% wilt, respectively). All strains, except SM 651 and SM 732, caused bacterial wilt in all three susceptible controls. These two strains did not cause disease in Yolo Wonder, a susceptible pepper variety; however, they caused 38.8 and

25.1% wilt respectively, in pepper accession PM702.

Mean wilt incidence in each accession across all six R. solanacearum strains is presented in Figure 4. Six tomato (TML46, R3034, CLN1463, Hawaii 7996, Mt 56, and

L285) (Fig. 4A), nine eggplant (EG 219, MM 152, BARI 8, MM 648, EG 203, MM853,

S56B, EG 190 and S. sisymbriifolium) (Fig. 4B) and three pepper (0209-4, PBC 66 and

PBC 361A) (Fig. 4C) accessions were highly resistant to bacterial wilt, with less than

10% disease incidence. Three tomato (BF Okitsu, CAR 66 and NC 72 TR 4-4), two eggplant (MM 960 and MM 195) and one pepper (PM 1022) accession were moderately resistant with less than 30% wilt. Wilt incidence in tomato accessions TML46, R3034,

CLN1463 and Hawaii 7996 were less than 1%. Solanum sisymbriifolium was resistant to four strains including SM 732, isolated from eggplant grafted on S. sisymbriifolium in

Bangladesh. However two other strains, SM 716 and SM 743 caused wilt in this accession. Strain SM 716, isolated from pepper, was more aggressive on S. sisymbriifolium than SM 743, isolated from this species in Nepal.

DISCUSSION

Bacterial wilt is one of the most important diseases of tomato, eggplant and pepper in South Asia. The disease is difficult to manage due to viability, adaptability and diversity of the pathogen. Host resistance is one of the best options available to manage this disease. However, the strain specificity of host resistance limits relevance of this approach. Only pathogen-targeted management approaches, that require prior knowledge of local pathogen populations, can provide satisfactory and sustainable control of this disease. Therefore, we characterized populations of R. solanacearum strains collected

38 from South Asia using the phylotyping scheme proposed by Fegan and Prior (2005), and then screened a worldwide collection of tomato, pepper and eggplant accessions against representative South Asian strains, to identify suitable hosts that can potentially be utilized to manage bacterial wilt in South Asia.

All strains, except for six reference strains obtained from India, characterized in this study were collected in 2012. Therefore, this study represents fairly recent population structures and diversity of R. solanacearum strains at these locations. Phylotype-specific multiplex PCR identified all strains as phylotype I. This finding is in congruence with a recent study on a large collection of R. solanacearum strains isolated from different parts of India (Ramesh et al. 2014). Unlike other parts of the world, such as China (Xu et al.

2009, Xue et al. 2011), Japan (Suga et al. 2013), Taiwan (Lin et al. 2014), Korea

(Yeonhwa and Kang 2007), West Indies (Ramsubhag et al. 2012), Ghana (Subedi et al.

2014), and the United States (Hong et al. 2012, Ji et al. 2007), South Asia appears to lack phylotype diversity. As bacterial wilt resistant quantitative trait loci (QTL) have been reported to be phylotype specific (Carmeille et al. 2006a), this information is of great significance to identify and employ pathogen targeted management tactics. The largest effect QTL (Bwr-12) present in tomato accession Hawaii 7996 has been reported to be phylotype I specific (Wang et al. 2013).

Sixty percent of strains in this study were identified as biovar III and the remaining 40% as biovar IV. One of the six Indian strains in this study was biovar IV.

Ramesh et al. (2014) reported all 232 strains isolated from India as biovar III. This indicates the presence of a very small proportion of biovar IV strains in India compared

39 to other parts of South Asia. Such an uneven distribution of biovars in geographically close locations is unexplained. This also suggests limited movement of R. solanacearum strains to India from her neighbors. Biovar III strains isolated from ginger were more aggressive than biovar IV strains (Kumar et al. 2014, Lum 1973). Lin et al. (1999) reported that all latently infected weed hosts in Taiwan were colonized by biovar III strains. Lin et al (2014) suggested that biovar III strains are genetically more diverse and better colonizers of weed hosts than biovar IV strains. Therefore, in locations such as

South Asia with dominant biovar III populations, management of bacterial wilt by cultural practices such as crop rotation may be less effective than expected due to continuous supply of pathogens from weed hosts.

Analysis of partial endoglucanase gene sequences and DNA fingerprinting profiles generated with Rep (BOX and REP) PCR, as suggested by Fegan and Prior

(2005) and followed by many others (Fonseca et al. 2014, Ivey et al. 2007, Ramsubhag et al. 2012, Norman et al. 2009, Xue et al. 2011, Zulperi et al. 2014) were used to characterize strains in this study. Combining fingerprinting patterns produced by different rep-PCR provides higher resolution than by individual fingerprinting patterns (Norman et al. 2009), for this reason, a composite dendrogram created from BOX- and REP-PCR is presented for discussion. As reported in the majority of the studies on R. solanacearum diversity (Jeong et al. 2007, Ramesh et al. 2014, Ramsubhag et al. 2012), most of strains in this study did not cluster based on host, origin or biovar in endoglucanase sequence and genomic fingerprinting profile analyses. Ralstonia solanacearum strains use different virulence genes to attack different hosts (Lin et al. 2008). The inability of these

40 techniques to distinguish strains based on host suggests that the techniques used to classify R. solanacearum strains did not capture the underlying genetics of host preference. Similarly, distribution of strains from one location into different clusters might be due to regular gene flow among strains located at different locations, as suggested by Ramsubag et al. (2012). This result however, contradicts with finding of

Xue et al. (2011), where majority of Chinese strains were grouped in BOX clusters based on host, origin and biovar. Ivey et al. (2007), in a study of R. solanacearum populations from Philippines, observed a correlation between ERIC clusters and locations of origin but not between ERIC clusters and biovars.

Genomic fingerprinting profiles generated by techniques such as Rep-PCR are widely used to study populations of R. solanacearum due to its ability to discrete polymorphisms at the sub-species level. These techniques are relatively cheaper, and easier to perform, especially in developing countries that lack sequencing facilities (Ivey et al. 2007). However, lack of inter-laboratory portability of fingerprinting profiles limits utility of this approach to compare R. solanacearum populations with published data.

Sequence analysis, especially the endoglucanase gene sequence in the case of R. solanacearum, is used to determine sequavar and to compare populations with published data. Due to lack of consensus in assigning sequevars, several putative new sequevars already published and available in the public domain do not have sequevar assignments

(Ramesh et al. 2014). Hong et al. (2012) highlighted impacts of algorithms and number of strains used in phylogenetic analysis of endoglucanase sequences. Phylogenetic trees generated from the Neighbor-joining (NJ) algorithm, the most commonly used algorithm

41 to study R. solanacearum populations, were different from the trees generated by

Maximum parsimony (MP), Maximum likelihood (ML) and Bayesian algorithms.

Similarly, an analysis of 186 strains grouped phylotype IV strains within phylotype I strains. However, analysis of 121 strains with the same algorithm separated phylotype I strains from phylotype IV strains. Therefore, they suggested multiple sequevar assignments for single strains in the published literature might be due to inconsistencies in analysis. The presence of different sequevar strains, including GMI100 and

CFBP2968, which are assigned multiple sequevar numbers, in a group (group 4) in this study might be due to above mentioned inconsistencies in phylogenetic analysis of endoglucanase gene sequences. This emphasizes the need for a standard protocol and consensus in phylogenetic analysis of endoglucanase gene sequences and sequevar assignment to strains to make phylogenetic analysis of R. solanacearum more organized and uniform.

Host resistance to bacterial wilt is quantitative, polygenic, strain-specific, and greatly influenced by temperature, soil moisture and pH (Acosta 1978, Hanson et al.

1996, Scott et al. 2005, Wang et al. 2013). The main sources of bacterial wilt resistance in tomato are its wild relatives such as Solanum pimpinellifolium, S. hirsutum and S. peruvianum (Carmeille et al. 2006b). Of the 37 accessions used in this study, the pedigrees of 30 are described by Lebeau et al. (2011). BARI 2 and BARI 8 are resistant tomato and eggplant lines developed by Bangladesh Agricultural Research Institutes

(BARI). Tomato MT56 was received from Uganda but its pedigree is uncertain.

Eggplant EG190, EG219 and tomato BF Okitsu were developed by AVRDC. Solanum

42 sisymbriifolium is a common weed in South Asia used as rootstock to manage bacterial wilt and root knot nematode in tomato and eggplants.

An objective of AVRDC research on bacterial wilt resistance was to develop resistant lines with more than 90% survival rate (Hanson and Wang 1996). Therefore,

TEP accessions with less than 10% wilt incidence in this study are considered highly resistant. Based on this parameter, 18 TEP accessions were identified as highly resistant.

However, among these 18 TEP accessions, nine accessions, including one tomato (L285), five eggplant (EG190, EG203, EG219, S56B and S. sisymbriifolium) and two pepper

(PBC631A and PBC66), exhibited more than 10% wilt incidence with at least one R. solanacearum strain (Table 4). This accession-strain interaction must be kept in mind before employing these accessions in South Asia. Such variation in host resistance with

R. solanacearum strains is very common. Tomato accession Hawaii 7966 was more resistant (0% wilt) to race 1 strains but was less resistant (52% wilt) to race 3 strains of R. solanacearum (Carmeille et al. 2006). In an interaction between 30 TEP accessions and

12 genetically diverse R. solanacearum strains, Lebeau et al. (2011) found a higher level of bacterial wilt resistance in pepper and eggplant than in tomato accessions. Similar results were observed in this study with 25.2, 20.4 and 21.1% wilt in tomato, eggplant and pepper accessions, respectively. However, the four most resistant accessions with less than one percent wilt incidence were all tomato accessions. This shows large variations in resistance among tomato accessions to South Asian strains of R. solanacearum.

Here we characterized populations of R. solanacearum strains from South Asia and identified the most resistant tomato, eggplant and pepper accessions that can potentially be used to manage bacterial wilt in South Asia. As resistance of these tomato, eggplant and pepper accessions were evaluated under greenhouse conditions, they must be assessed in field conditions of South Asia before employing them at large scale. To our knowledge this is the first study on the population structure of R. solanacearum strains from Bangladesh and Nepal using molecular tools.

ACKNOWLEDGEMENTS

I would like to thank Dr. Jaw-Fen Wang, AVRDC, Taiwan, Dr. Marie Christine Daunay,

INRA, France, and Dr. Yousouf Mian, BARI, Bangladesh, for providing seeds for this study; and BARI and Nepal Agricultural Research Council (NARC) for providing laboratory facilities in Bangladesh and Nepal, respectively. This work was supported by the Agriculture Office within the Bureau for Economic Growth, Agriculture, and Trade

(EGAT) of the U.S. Agency for International Development, under the terms of the IPM-

CRSP (Award EPP-A-00-04-00016-00).

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TABLES

Table 2.1. Tomato, eggplant and pepper accessions screened for bacterial wilt resistance to six selected South Asian strains of Ralstonia solanacearum representing different phylogenetic groups.

Accession Species Seed sourcea Tomato CRA66 Solanum lycopersicum var. cerasiforme INRA Okitsu Sozai no. 1 S. lycopersicum INRA NC 72 TR 4-4 S. lycopersicum INRA IRAT L3 S. lycopersicum INRA Hawaii 7996 S. lycopersicum INRA TML46 S. lycopersicum AVRDC CLN1463 S. lycopersicum AVRDC R3034 S. lycopersicum AVRDC L285 S. lycopersicum var. cerasiforme AVRDC Mt 56 S. lycopersicum Makerere Univ. BARI 2 S. lycopersicum BARI BF Okitsu S. lycopersicum AVRDC L390 S. lycopersicum var. cerasiforme AVRDC Eggplant MM853 S. melongena INRA MM643 S. melongena INRA MM152 S. melongena INRA EG203 S. melongena AVRDC MM931 S. melongena INRA MM960 S. melongena INRA MM195 S. melongena INRA MM738 S. melongena INRA S56B S. melongena AVRDC Eg 190 S. melongena AVRDC Eg 203 S. melongena AVRDC S. sysimbriifolium S. sysimbriifolium BARI BARI 8 S. melongena BARI MM136 S. melongena INRA Pepper PM1443 Capsicum annuum INRA Table 2.1 Continued 50

Table 2.1 Continued PM687 C. annuum INRA PM1022 C. baccatum INRA PM702 C. annuum INRA 0209-4 C. annuum × C. chinense AVRDC PBC631A C. annuum AVRDC PBC66 C. annuum AVRDC PM659 C. annuum INRA PBC384 C. annuum AVRDC Yolo Wonder C. annuum INRA

aAVRDC: The World Vegetable Center, Taiwan; BARI: Bangladesh Agricultural

Research Institute; INRA: Institute National de la Recherche Agronomique, France;

Makerere University, Kampala, Uganda

Table 2.2. Geographical origin, host and physiological and genetic characteristics of

Ralstonia solanacearum strains

Rep- Strain IDa Location, Countryb Hostc Biovard Egl groupe groupf

SM 737 Bogra, BD Eggplant III 2

SM 738 Bogra, BD Eggplant III 1 8

SM 739 Bogra, BD Eggplant III 5

SM 740 Bogra, BD Eggplant III 3

SM 741 Bogra, BD Eggplant IV 3

SM 742 Bogra, BD Eggplant III 1 3

SM 717 Braminbaria, BD Eggplant IV 5

SM 718 Braminbaria, BD Eggplant IV 1 3

SM 746 Chitwan, NP Eggplant III 5

SM 747 Chitwan, NP Eggplant III 5

SM 748 Chitwan, NP Eggplant III 1 5

SM 749 Chitwan, NP Eggplant III 1 5

SM 750 Chitwan, NP Eggplant III 5

SM 751 Chitwan, NP Eggplant III 3 5

SM 705 Comilla, BD Eggplant IV 3

SM 706 Comilla, BD Eggplant IV 3

SM 707 Comilla, BD Eggplant IV 3

Table 2.2 Continued

SM 708 Comilla, BD Eggplant IV 3

SM 709 Comilla, BD Eggplant IV Singleton 3

SM 710 Comilla, BD Eggplant IV 5

SM 711 Comilla, BD Eggplant IV 3

SM 712 Comilla, BD Eggplant IV 2

SM 713 Comilla, BD Eggplant IV 2 5

SM 714 Comilla, BD Pepper IV Singleton 5

SM 715 Comilla, BD Pepper IV 5

SM 716 Comilla, BD Pepper IV 4 5

SM 649 Goa, IND Eggplant IV Singleton 3

SM 650 Goa, IND Eggplant III 3

SM 719 Hathazaria, BD Eggplant III 5

SM 720 Hathazaria, BD Eggplant III 4 5

SM 721 Hathazaria, BD Eggplant IV 1 5

SM 722 Hathazaria, BD Eggplant IV 5

SM 723 Hathazaria, BD Eggplant III 1 5

SM 724 Hathazaria, BD Eggplant III 5

SM 725 Hathazaria, BD Eggplant III 1 5

SM 726 Hathazaria, BD Eggplant III 4 8

NA Jamalpur, BD Eggplant IV 7

Table 2.2 Continued

SM 666 Jamalpur, BD Eggplant III 1 5

SM 667 Jamalpur, BD Eggplant III 5

SM 668 Jamalpur, BD Eggplant III 1 5

SM 669 Jamalpur, BD Eggplant III 5

SM 670 Jamalpur, BD Eggplant III 5

SM 671 Jamalpur, BD Eggplant III 5

SM 672 Jamalpur, BD Eggplant III 5

SM 673 Jamalpur, BD Eggplant III 5

SM 674 Jamalpur, BD Eggplant III 1 5

NA Jamalpur, BD Pepper IV 7

SM 648 Jessor, BD Eggplant III 4

SM 691 Jessor, BD Eggplant III 5

SM 692 Jessor, BD Eggplant III 5

SM 693 Jessor, BD Eggplant III 5

SM 694 Jessor, BD Eggplant III 5

SM 695 Jessor, BD Eggplant III 3 5

SM 696 Jessor, BD Eggplant III 5

SM 697 Jessor, BD Eggplant III 3 5

SM 698 Jessor, BD Eggplant III 5

SM 699 Jessor, BD Eggplant III Singleton 5

Table 2.2 Continued

SM 700 Jessor, BD Eggplant III 5

SM 701 Jessor, BD Eggplant III 3 1

SM 702 Jessor, BD Eggplant III 1

SM 703 Jessor, BD Eggplant III 1

SM 704 Jessor, BD Eggplant III Singleton Singleton

SM 735 Joydebpur, BD Eggplant IV 2 3

SM 736 Joydebpur, BD Eggplant IV 1 2

SM 653 Karnataka, IND Tomato III 4

SM 645 Kathmandu, NP Eggplant III 5

SM 643 Kathmandu, NP Tomato III 4

SM 644 Kathmandu, NP Tomato IV 2 5

SM 646 Kathmandu, NP Tomato IV 5

SM 647 Kathmandu, NP Tomato III 5

SM 652 Kerala, IND Tomato III Singleton 3

SM 651 Maharastra, IND Eggplant III Singleton 3

SM 654 Maharastra, IND PEPPER III Singleton 5

SM 675 Norsindhi, BD Eggplant IV 3

SM 676 Norsindhi, BD Eggplant III 5

SM 677 Norsindhi, BD Eggplant IV Singleton

SM 678 Norsindhi, BD Eggplant IV 2

Table 2.2 Continued

SM 679 Norsindhi, BD Eggplant IV 2

SM 680 Norsindhi, BD Eggplant IV 2 3

SM 681 Norsindhi, BD Eggplant IV 2 4

SM 682 Norsindhi, BD Eggplant IV 2 3

SM 683 Norsindhi, BD Eggplant IV 2 3

SM 684 Norsindhi, BD Eggplant IV 3

SM 685 Norsindhi, BD Eggplant IV 3

SM 686 Norsindhi, BD Eggplant IV 5

SM 687 Norsindhi, BD Eggplant IV 3

SM 688 Norsindhi, BD Eggplant III 5

SM 689 Norsindhi, BD Eggplant III 1 5

SM 690 Norsindhi, BD Eggplant IV 1

SM 743 Synjga, NEP Sst III Singleton 5

SM 744 Synjga, NEP Sst III 5

SM 745 Synjga, NEP Sst III 5

SM 734 Tangail, BD Eggplant III 5

SM 727 Tangail, BD Sse IV 1 2

SM 728 Tangail, BD Sse III 6

SM 729 Tangail, BD Sse III 1 5

SM 730 Tangail, BD Sse III 5

Table 2.2 Continued

SM 731 Tangail, BD Sse III 1 5

SM 732 Tangail, BD Sse IV 6

SM 733 Tangail, BD Sse IV 6

aNA= Strain identification not available for these strains. bCountry: BD = Bangladesh, IND = India, NP = Nepal. cSst = tomato grafted on Solanum sisymbriifolium, Sse = eggplant grafted on S. sisymbriifolium dBiovar identified based on ability of strains to utilize cellobiose, lactose, maltose, dulcitol, mannitol and sorbitol. eDetermined based on phylogenetic analysis of partial endoglucanase gene sequence.

Singleton = did not group with other South Asian strains. fIdentified based on cluster analysis of composite dendrogram created by combining genomic fingerprinting profile obtained from BOX- and REP-PCR. Singleton = did not group with other South Asian strains.

Table 2.3. Distribution of biovar in different locations

Biovarb Location, Countrya Total III IV

Bogra, BD 5 1 6

Braminbaria, BD 0 2 2

Chitwan, NP 6 0 6

Comilla, BD 0 12 12

Hathazaria, BD 6 2 8

Jamalpur, BD 9 2 11

Jessor, BD 15 0 15

Joydebpur, BD 0 2 2

Kathmandu, NP 3 2 5

Norsindhi, BD 3 13 16

Syangja, NP 3 0 3

Tangaile, BD 5 3 8

Various locations, IND 5 1 6

Total 60 40 100

aCountry: BD = Bangladesh, NP = Nepal, IND = India. b Biovar identified based on ability of strains to utilize carbon from cellobiose, lactose, maltose, dulcitol, mannitol and sorbitol. Biovar III strains utilize carbon from all sources; biovar IV strains utilize carbon from dulcitol, mannitol and sorbitol only.

Table 2.4. Interactions between 37 tomato, pepper and eggplant accessions and six South Asian

Ralstonia solanacearum strains expressed as percentage wilt

Hosta Accession SM 738 MB 1 SM 716 SM 743 SM 701 SM 732 Meanb Tomato CRA66 48.9 51.1 5.6 2.2 6.7 51.2 27.6 Tomato Okitsu Sozai no 1 92.2 88.9 65.6 42.3 45.6 93.4 71.3 Tomato NC 72 TR 4-4 53.3 53.4 3.4 4.5 1.1 60.3 29.3 Tomato IRAT L3 47.5 71.8 10.4 11.1 8.9 62.2 35.3 Tomato Hawaii 7996 3.3 0.0 0.0 0.0 1.1 1.1 0.9 Tomato TML46 0.0 2.2 0.0 0.0 0.0 0 0.4

59 Tomato CLN1463 2.2 1.1 0.0 0.0 0.0 0 0.6 Tomato R3034 1.1 0.0 0.0 0.0 0.0 1.1 0.4 Tomato L285 4.5 22.2 3.4 0.0 0.0 6.7 6.1 Tomato Bari 2 62.2 67.8 31.3 16.7 14.6 64.4 42.8 Tomato BF Okitsu 33.4 41.1 12.2 5.6 12.2 33.3 23.0 Tomato Mt 56 4.5 11.1 5.6 6.7 0.0 1.1 4.8 Tomato L390 92.3 96.9 88.9 63.7 77.8 93.4 85.5 Eggplant MM853 12.2 12.2 5.6 0.0 0.0 3.3 5.5 Eggplant MM643 13.4 14.4 1.1 1.1 0.0 0.0 5.0 Eggplant MM152 13.0 7.8 1.1 2.2 0.0 4.8 4.8 Eggplant EG203 13.4 7.8 4.4 2.2 0.0 2.2 5.0 Eggplant MM931 62.3 52.0 20.6 14.5 21.1 23.3 32.3 Eggplant MM960 62.8 2.2 0.0 4.6 16.9 4.5 15.2 Eggplant MM195 51.6 31.9 20.5 13.4 6.7 24.5 24.7 Table 2.4 Continued

Table 2.4 Continued Eggplant MM738 94.5 81.1 85.6 83.4 63.4 70.0 79.6 Eggplant S56B 15.6 7.8 1.1 1.1 2.2 7.2 5.8 Eggplant Eg 190 7.8 11.1 4.4 7.8 2.2 3.3 6.1 Eggplant Eg 219 8.9 10.0 0.0 1.1 0.0 3.3 3.9 Eggplant Bari 8 6.7 14.4 4.5 1.1 0.0 3.4 5.0 Eggplant MM136 93.2 91.4 96.4 95.6 50.0 75.2 83.6 Pepper PM1443 63.4 0.0 36.4 58.9 23.3 0.0 30.3 Pepper PM687 60.0 1.1 58.8 55.2 25.6 0.0 33.4 Pepper PM1022 43.9 0.0 24.0 64.6 16.1 0.0 24.8 Pepper PM702 37.9 38.8 41.9 35.4 21.5 25.1 33.4

Pepper 0209-4 5.7 0.0 2.2 7.8 0.0 0.0 2.6 Pepper PBC631A 14.6 0.0 7.8 15.6 9.2 0.0 7.9 Pepper PBC66 11.3 0.0 5.6 18.9 0.0 0.0 5.9 Pepper PM659 28.5 0.0 13.4 20.0 7.8 0.0 11.6 Pepper PBC384 21.2 0.0 7.8 23.4 11.1 0.0 10.6 Pepper Yolo Wonder 94.8 0.0 73.9 82.6 49.0 0.0 50.0 S. sysimbriifolium S. sysimbriifolium 0.0 0.0 33.2 19.5 0.0 0.0 8.8 aFour-week-old seedlings were inoculated with 5 ml of R. solanacearum suspension (108

CFU/ml) following root injury. Mean final percentage wilt of two experiments recorded five

weeks after inoculation is presented in the table.

bMean percentage wilt in each TEP accessions across all six R. solanacearum strains.

Table 2.5. Diversity and aggressiveness of Ralstonia solanacearum strains selected to screen

host resistance of tomato, eggplant and pepper accessions

a b egl Rep- Wilt incidence Strain ID Origin Host Biovar c d group group Tomato Eggplant Pepper Mean SM 738 Bangladesh Eggplant III 1 8 34.3 a 32.5 a 38.1 a 35.0 SM 716 Bangladesh Pepper IV 4 5 17.4 b 19.6 c 27.2 ab 21.4 SM 701 Bangladesh Eggplant III 3 5 13.0 b 11.6 d 16.3 b 13.6 SM 651 India Eggplant III Singleton 3 39.0 a 24.6 b 4.0 c 22.5

61 SM 743 Nepal Sst III Singleton 5 11.7 b 18.0 c 38.2 a 22.6

SM 732 Bangladesh Sse IV ND 6 36.0 a 16.1d 2.5 c 18.2

Mean 25.2 20.4 21.1 22.2

aSst = tomato grafted on Solanum sisymbriifolium, Sse = eggplant grafted on S. sisymbriifolium

bBiovar identified based on ability of strains to utilize cellobiose, lactose, maltose, dulcitol,

mannitol and sorbitol.

cDetermined based on phylogenetic analysis of partial endoglucanase gene sequence. Singleton =

did not group with other South Asian strains.

Table 2.5 Continued 61

Table 2.5 Continued dIdentified based on cluster analysis of composite dendrogram created by combining genomic fingerprinting profile obtained from BOX- and REP-PCR.

eMean wilt incidence by each strain in all three host species.

FIGURES

Fig. 2.1

Fig 2.1. Map of A, Bangladesh and B, Nepal showing origin of Ralstonia solanacearum strains characterized in this study. 63

Fig. 2.2. Phylogenetic tree created by Neighbor-joining algorithm where evolutionary distances were computed using Jukes and Cantor method with 1,000 bootstrap resampling. Empty and filled circles represents Ralstonia solanacearum strains from

Nepal and India, respectively. Other strains with SM numbers are from Bangladesh. All other strains are reference strains.

Fig 2.2

Fig. 2.3. Composite dendrogram created by combining genomic fingerprinting profiles obtained from BOX- and REP-PCR. Cluster analysis was performed with UPGMA algorithm to similarity matrix generated by Pearson's correlation coefficient from whole pattern of each fingerprinting profile. Groups were determined based on the minimum similarity (*) among ten lanes of 1Kb- plus ladder run separately in five different gels along with Ralstonia solanacearum strains.

Strains GMI1000, K60, WW386 and WW443 were used as reference strains for phylotpye I, II,

III and IV respectively.

Fig 2.3

Fig. 2.4. Mean bacterial wilt incidence by six Ralstonia solanacearum strains, selected based on origin, host, biovar, and endoglucanase and Rep-PCR groups, in each of A, tomato, B, eggplant and C, pepper accessions, five weeks after inoculation. Four-week- old seedlings were inoculated with 5 ml of R. solanacearum suspension (108 CFU/ml) following root injury. Bars with different letters are significantly different according to

Fisher's LSD test (P≤0.05).

Fig. 2.4

90 a A 80 b 70 60 50 c 40 c e e 30 e 20 Percentage wilted Percentage f f 10 f f f f 0

Tomato genotype

90.0 a a 80.0 B

70.0 60.0 50.0 40.0 b 30.0 c

Percentage wilt Percentage 20.0 d de 10.0 e e e e e e e e 0.0

Eggplant genotypes

Fig. 2.4 Continued

90 80 C 70 60 a 50 40 b b b 30 b

Percentage wilt Percentage 20 c c c 10 c c 0

Pepper genotypes

Chapter 3: Combining Partial Host Resistance with Bacterial Biocontrol Agents

Improves Outcomes for Tomatoes Infected with Ralstonia solanacearum

ABSTRACT

Biological control is a potentially economically feasible and environmentally safe and sustainable disease management practice. In this study we investigated 54 previously characterized Pseudomonas and other bacterial biocontrol strains for their activity against diverse Ralstonia solanacearum strains from South Asia and evaluated the value of integration of these biocontrol agents with partial host resistance of tomato in management of bacterial wilt. Based on in vitro antagonism against 15 selected South

Asian R. solanacearum strains, six biocontrol agents were selected to evaluate their biocontrol efficacy in a susceptible (L390) and a partially resistant (IRAT L3) tomato accessions. Biocontrol agents were almost four times more effective in suppressing bacterial wilt in IRAT L3 than in L390. Pseudomonas brassicacearum strain 93D8 and

P. fluorescens strain Clinto 1 were the most effective strains with biocontrol efficacy of

67, 50 and 58% respectively, in IRAT L3. Bacterial wilt incidence was suppressed in all four experiments by P. brassicacearum strain 93D8, and in three out of four experiments by P. vranovensis strain 15D11, P. protegens strain Clinto 1, and P. brassicacearum strain Wood 1R, in IRAT L3. However, in L390, the disease incidence was suppressed in only one experiment by P. protegens 71 strains 15G2 and Clinto 1, and a mixture of all biocontrol agents. These results highlight the value of integration of biocontrol agents with host resistance in management of bacterial wilt.

INTRODUCTION

Bacterial wilt, caused by Ralstonia solanacearum (Smith) Yabuuchi, is one of the most important soil-borne plant diseases of the tropics and sub-tropics, as well as certain warm temperate regions of the world (Hayward 2005). The pathogen can infect over 250 plant species belonging to 54 families, including both monocots and dicots

(Hayward1991, Wicker et al 2007). Bacterial wilt is difficult to manage due to the genetic diversity and aggressiveness of the pathogen, its ability to survive in varied and adverse environmental conditions, its modes of dissemination, and the large number of weed hosts (Ramesh and Phadke 2012, Saddler 2005). Crop loss due to bacterial wilt has been estimated to be more than $950 million globally in the potato industry alone (Walker and

Collin 1998). Bacterial wilt has been a severe problem in South Asia. Wilt incidence across all commercially grown tomato cultivars was reported to range from 9 to 39% in

Karnataka state of India (Vanitha et al. 2009). Crop loss in some parts of India and Nepal reached up to 91 and 100%, respectively, and about 14% on average in Bangladesh

(Elphinstone 2005, Gurung and Vaidya 1997).

Different practices have been employed to manage bacterial wilt. Chemical bactericides such as copper compounds and antibiotics have limited impact (Hartman and

Elphinstone 1994). The risk of developing resistance in R. solanacearum to these

72 bactericides is high (Lopez and Elena 2005). Transgenic tobacco lines expressing the wheat TaPIMP1 gene, a transcription factor, have shown increased resistance to bacterial wilt (Liu et al. 2011). However, the lack of acceptance of a transgenic food crops currently restricts this approach. Crop rotation (Adhikari and Basnyat 1998), soil amendment with various antimicrobial compounds (Dhital et al. 1997, Hong et al. 2011,

Lee et al. 2012), biological soil disinfection (Bloke et al. 2000, Messiha et al. 2007b), soil solarization (Anith et al. 2000, Chellemi et al. 1997), soil fumigation (Chellemi et al.

1997), host resistance inducers (Anith and Momol 2004, Pradhanang et al. 2005), flooding (Michel et al. 1996) and microwave disinfection of seeding materials (Kumar et al 2005) provide variable degrees of protection from bacterial wilt.

The use of resistant cultivars is one of the most effective and practical means of bacterial wilt management (Rivard et al. 2012, Lopez and Elena 2005,). Tomato lines

CLN2020C, CLN2026D, All Rounder, Swarakhsha, Rakshak, Trishul, and Arka Alok, and eggplant lines Kata Begun, Marich Begun and Uttar are a few of the bacterial wilt resistant cultivars used in South Asia (Dutta and Rahman 2012, Rahman et al. 2011,

Timila and Joshi 2007). However, full deployment of this approach may be hampered by partial resistance, a lack of desired horticultural traits in resistant lines (Walter 1967,

Wang et al 1998), and instability, and location and strain specificity of resistance (Rivard et al. 2012, Lebau et al. 2011, Lin et al. 2008, Wang et al. 2013). Grafting desirable varieties of solanaceous fruiting vegetables onto R. solanacearum-resistant rootstocks, including wild Solanum species, has been shown to reduce wilt incidence and increase yields (Rivard et al. 2012). Despite the additional cost of producing grafted seedlings,

73 adoption of this tactic in certain production systems such as high tunnels is increasing

(Miller et al. 2005).

Biological control of plant diseases has yet to be widely adopted in solanaceous fruiting vegetables, despite its desirability as a potentially sustainable disease management practice. Biological control agents (BCAs) employ several mechanisms such as antagonism, competition and induction of host resistance to suppress plant diseases (McSpadden Gardener 2004, Pal and McSpadden Gardener 2006, Pieterse and

Wees 2015). Some BCAs are also known to degrade signals that activate pathogens

(Molina et al. 2003). Strains of Pseudomonas, Burkholderia, Bacillus, Streptomyces,

Actinomyces, Acinetobacter, Enterobacter, Escherichia, Erwinia, Stenotrophomonas,

Serratia, Ralstonia, several phlD+ rhizobacteria, and ectomycorrhizal fungi have been studied for their efficacy against bacterial wilt (Ramadasappa et al. 2012, Ramesh and

Phadke 2012, Messiha et al. 2007a, Saddler 2005, Wei et al. 2013, Xue et al. 2009).

Performance of these biocontrol agents depends highly on biotic and abiotic factors such as environmental conditions, soil type, soil microbiota, and disease pressure (Gerbore et al. 2014)

Bacterial wilt can be prevented in disease-free areas by adopting strict exclusion practices, however no single management practice provides satisfactory results where the disease is endemic (Lopez and Biosca 2005, Saddler 2005). The majority of hosts highly resistant to bacterial wilt lack desired agronomic traits, and the performance of biological control agents is often poor when disease pressure is high. Therefore, the first objective of this study was to investigate a collection of previously characterized bacterial

74 biocontrol agents (Aly 2009, Mavrodi et al. 2012, McSpadden Garderer et al. 2005,

Raudales et al. 2009) for their antagonistic activities against R. solanacearum. The second objective was to test the value of integration of selected antagonistic bacteria with partial host resistance in management of this disease.

MATERIALS AND METHODS

Bacterial strains. A total of 54 previously characterized Pseudomonas and other bacterial biocontrol strains (Aly 2009, Mavrodi et al. 2012, McSpadden Garderer et al.

2005, Raudales et al. 2009) (Table 3.1) were tested as potential biocontrol agents against

R. solanacearum strain NCSU 68 (biovar I, phylotype II) isolated in North Carolina from tobacco, and 15 South Asian R. solanacearum strains differing in biovar (French et al.

1995), host and geographic origin (Table 3.2).

In vitro antagonistic assay. Cultures of R. solanacearum grown for 48 h on casamino acid peptone glucose (CPG) medium (French et al. 1995) at 28ºC were suspended in sterile distilled water and adjusted to a final concentration of 108 CFU/ml with sterilized water. The concentration of the bacterial suspension was adjusted to an optical density

(OD) of 0.1 to 0.2 at 600 nm and confirmed by dilution planting. Suspensions of candidate antagonistic bacteria were prepared from 48-h cultures growing on

Pseudomonas Agar F (PF) medium (BD, New Jersey) at 28ºC and adjusted to a final concentration of 109 CFU/ml with sterilized water. Lawns of R. solanacearum were prepared by spreading 100 µl aliquots onto PF medium using sterile glass beads. After the cultures were dried in a laminar flow hood for 5 min, three 2.5 µl aliquots of each of

75 three antagonistic bacterial strains were dropped onto each culture. Each assay was replicated three times and the experiment was repeated once. The zone of inhibition around each antagonistic bacterial strain was measured 2 days after incubation at 28ºC.

Biocontrol of bacterial wilt in tomato seedlings. Seeds of the bacterial wilt susceptible tomato line L390 and partially resistant tomato line IRAT L3 were obtained from

AVRDC (The World Vegetable Center, Taiwan) and INRA (Institut National de la

Recherche Agronomique, France), respectively. Seeds were sown in plastic trays with 2.5 x 2.5 cm2 cells containing planting medium (Fafard super-fine germinating mix, Sungro

Horticulture, Agawam, MA). Each cell was drenched immediately after seeding with 10 ml of a suspension, prepared in sterilized distilled water from 48-h-old colonies growing on PF medium at 28ºC, of an antagonistic bacterial strain containing 109 CFU/ml. Each strain was applied again 3 weeks after seeding. Four-week-old plants were drench- inoculated with a 5 ml suspension of 108 CFU R. solanacearum/ml prepared as described above. Inoculum was prepared by mixing three South Asian strains of R. solanacearum

(SM651-12, SM734-12 and SM743-12) highly aggressive to a collection of 37 tomato, eggplant and pepper lines (unpublished). Five days after pathogen inoculation, seedlings were transplanted into 400 ml styrofoam cups containing field soil steam sterilized at

250oC for 12 h under 30 lb psi and placed in plastic trays. Plants were maintained in a

Biosecurity Level 2 greenhouse at 21ºC-32ºC under a 16-h day and 8-h night cycle. Plants were irrigated directly in trays as needed and fertilized every other week with Jack's

Classic All Purpose 20-20-20 (JR Peters Inc., Allentown, PA), with the exception of the third experiment in which plants were fertilized every week. The experiment was

76 conducted four times and plants were arranged in a randomized, complete block design with five replications of eight plants per replication. In the first two experiments, R. solanacearum suspensions were applied after wounding roots with sterile scalpel blades, and in the final two experiments, the pathogen was applied without root wounding. An additional treatment, “Mixed”, a mixture of all six biocontrol agents, was included in the third and the fourth experiments. All experimental plants were destroyed by autoclaving and all surfaces in contact with experimental treatments were disinfected at the end of the experiment. Plants were monitored every day and disease incidence was assessed 7 days after inoculation with R. solanacearum and every other day thereafter by counting the plants exhibiting wilt symptoms. Disease incidence was recorded until disease progression stabilized. Area under the disease progress curves (AUDPC) were calculated from percentage wilt data according to Madden et al. (2007). Biocontrol efficacy was calculated as described by Lemessa and Zeller (2007) as:

Biocontrol efficacy = [(percent wilted in control - percent wilted in treated plants)/percent wilted in control] *100%

Effect of antagonistic bacteria on tomato plant growth. Tomato lines L390 and IRAT

L3 were raised in a greenhouse and treated with antagonistic bacteria as described above and fertilized weekly. Height and fresh and dry biomass of each plant were measured at the end of the experiment, 60 days after sowing. For dry biomass, plants were dried at

60ºC for 7 days. The experiment was conducted twice in a randomized, complete block design with five replications with one plant per replication.

Population dynamics of R. solanacearum in plants treated with biocontrol agents.

Partially resistant tomato line IRAT L390 inoculated with R. solanacearum only or with both R. solanacearum and antagonistic bacteria, and non-treated, non-inoculated plants were maintained in plastic trays. Immediately after inoculation and weekly thereafter for three weeks, each plant was removed from the tray, excised at the soil line and the entire plug (roots plus planting medium) was added to a 532 ml whirl pack sample bag (Nasco,

Fort Atkinson, WI) containing 90 ml sterilized 0.1 M potassium phosphate buffer (pH

7.4). Ten-fold serial dilutions were plated on modified SMSA medium (French et al.

1995) and incubated for 3 days at 28ºC. The identity of colonies grown on the medium was confirmed by Ralstonia species complex-specific PCR (Opina et al. 1997). The experiment was performed as a randomized complete block design with three replications, blocked in time.

Statistical analysis Analysis of variance (ANOVA) was performed to determine the impact of antagonistic bacteria using GLIMMIX procedure. Means were separated using

Fisher's least significant difference (LSD) test with SAS software (SAS Institute, Inc.,

Cary, NC). Effect of root wounding on wilt incidence, and correlation between zone of inhibition and biocontrol efficacy of biocontrol agents were examined using two-sample t-test and Pearson Correlation, respectively, with Minitab statistical software version 16

(Minitab Inc., State College, PA).

RESULTS

In vitro assay for antagonistic Pseudomonas spp. Forty-two of 54 putative biocontrol strains tested produced zones of inhibition of R. solanacearum NCSU68 ranging from 1-

11 mm (Table 3.1). Thirteen biocontrol agents, including seven highly inhibitory

(inhibition zones of 6-11 mm: P. vranovensis strain 15D11, P. fluorescens strain 48D1,

Serratia plymuthica strain 15H10, Enterobacter ludiwigii strain 31D2, P. poae strain

36C8, and P. brassicacearum strains 48D5 and 93D8); five moderately inhibitory

(inhibition zones of 3-5 mm: P. brassicacearum strains 93G8 and Wood 1R, P. protegens strains Clinto 1 and 15G2, and P. chlororaphis strain 48B8), and one non-inhibitory (P. brassicacearum strain 38D4) were selected for further in vitro antagonism assays against

15 South Asian strains of R. solanacearum (Table 3.2). Pseudomonas vranovensis strain

15D11 produced the largest and P. brassicacearum strain 38D4 the smallest zone of inhibition (mean of 7.8 and 0.3 mm respectively, across 15 South Asian strains of R. solanacearum) (Figure 3.1A). R. solanacearum strain SM646-12 was inhibited the most and strain SM737-12 the least (mean zones of inhibition of 5.7 and 2.4 mm respectively, across 13 biocontrol agents) (Figure 3.1B).

Biocontrol of bacterial wilt in tomato seedlings. Wilt symptoms first appeared 5 to 7 days after R. solanacearum inoculation in non- treated control seedlings (Fig. 3.2).

Disease progression was slower in IRAT L3 than in L390. Incidence of bacterial wilt across all biocontrol agents treated and the non-treated control was significantly higher

29 days after pathogen inoculation in susceptible line L390 than partially resistant line

IRAT L3, in all experiments (Table 3.3). Root wounding did not increase wilt incidence

79 in plants that were not treated with biocontrol agents (non-treated control) in either tomato line. However, root wounding increased wilt incidence in L390 plants treated with biocontrol agents (Table 3.4).

In the first experiment bacterial wilt, measured by both final percentage of wilted plants and AUDPC, in the partially resistant tomato line IRAT L3 was significantly reduced by P. vranovensis strain 15D11, P. brassicacearum strains 93D8 and Wood 1R, and P. protegens strain 15G2 compared to the non-treated control (Table 3.5A). In the susceptible tomato line L390, none of the biocontrol agents reduced the final wilt percentage, although the AUDPC was significantly reduced by P. brassicacearum strain

93D8, indicating slower progression of the disease. In the second experiment, all biocontrol agents significantly reduced final bacterial wilt incidence, and all except P. protegens strain 15G2 reduced the AUDPC in IRAT L3. No treatment inhibited bacterial wilt in the susceptible tomato line. In the third experiment (roots not wounded),

Pseudomonas vranovensis strain 15D11, P. brassicacearum strains 93D8 and Wood 1R,

P. protegens strain Clinto 1, and ‘Mixed’, significantly reduced the disease in IRAT L3, while none of the strains suppressed bacterial wilt in L390 (Table 3.5B). In the fourth experiment, P. protegens strain Clinto 1 significantly suppressed the disease in both tomato lines. Pseudomonas brasicacearum strain 93D8 provided complete protection

(0% wilt) to IRAT L3. Pseudomonas protegens strain 15G2, E. ludwigii strain 31D2

(AUDPC only), P. brassicacearum strain Wood 1R, and the 'Mixed' treatment (AUDPC only) were also effective in reducing bacterial wilt in L390.

Pseudomonas brassicacearum strain 93D8 significantly reduced bacterial wilt incidence in IRAT L3 in all experiments, with both wounded and non-wounded plant roots, while P. protegens strain Clinto 1 and P. brassicacearum strain Wood 1R suppressed the disease in three of four experiments. Pseudomonas. vranovensis strain

15D11 reduced final disease incidence in IRAT L3 in three of four experiments, but

AUDPC was reduced in only two of four experiments. Pseudomonas protegens strains

15G2 and Clinto 1, and P. brassicacearum strain Wood 1R significantly reduced final wilt incidence and AUDPC in the susceptible line L390 in one experiment, but slowed disease progress in this line in two of four experiments. Enterobacter ludwigii strain

31D2 and P. brassicacearum strain 93D8 reduced the AUDPC in L390 in one and two experiments, respectively.

Biocontrol agents were more effective when combined with the partially resistant line IRAT L3 than with the susceptible line L390 (Fig 3.3). The mean biocontrol efficacy of biocontrol agents in the partially resistant line IRAT L3 was 42%, almost four times higher than in susceptible tomato line L390 (11%) (Table 3.6). Three highly effective biocontrol agents, P. brassicacearum strains 93D8 and Wood 1R, and P. protegens strain

Clinto 1 demonstrated biocontrol efficacies of 67%, 50%, and 58% on IRAT L3 and 8%,

16%, and 13% on L390, respectively. Except for P. vranovensis strain 15D11 on L390, on average all biocontrol agents demonstrated positive biocontrol efficacy on the both hosts. There was no significant (P< 0.05) correlation between zones of inhibition produced by biocontrol strains and biocontrol efficacy of these strains in either tomato line (Table 3.6).

Application of biocontrol agents, singly or in combination, did not affect plant height, fresh weight or dry weight in either tomato line.

Population dynamics of R. solanacearum in biocontrol agent-treated plants. R. solanacearum was consistently isolated from inoculated root plugs (potting mix plus roots) but not from non-inoculated control root plugs. Immediately after inoculation with

5x108 CFU R. solanacearum, population densities of ~106 CFU/g dry weight root plugs were recovered from all biocontrol agent-treated plants and the non-treated control

(Figure 3.4). Populations declined in all treatments and the non-inoculated control 1 week after inoculation. Two weeks after inoculation, R. solanacearum populations increased in

E. ludwigii strain 31D2 -treated plugs, and were significantly higher than in P. protegens strain Clinto 1 and P. brassicacearum strain 98D3 -treated plugs. There was no large change in pathogen populations in other plugs. In the third week, populations of R. solanacearum decreased in E. ludwigii strain 31D2 and P. brassicacearum strain Wood

1R -treated plugs and increased in other plugs including the control. However, pathogen populations were not significantly different among treatments.

DISCUSSION

Bacterial wilt, caused by R. solanacearum, is one of the most difficult soilborne diseases to manage in tomato. The disease is particularly important in Solanceous crops in tropical climates where high temperatures and abundant rainfall during the growing season promote disease development and dissemination. Temperature and soil moisture range from 28-36°C and 50-100% respectively, in the majority of tomato growing areas

82 in South Asia (Ramadasappa et al. 2012). Tactics applied individually are generally ineffective, or in the case of resistant varieties, likely to fail over time. Therefore, integration of disease management strategies is highly recommended. Combining biocontrol agents and disease resistant hosts offers a potentially sustainable approach to improved management of this disease. We investigated a collection of bacterial biocontrol agents for their antagonistic activity against R. solanacearum. To examine the possible outcomes of integration of these antagonistic bacteria with host resistance, we further tested the efficacy of these biocontrol agents in partially resistant and highly susceptible tomato lines.

All 54 antagonistic bacteria used in this study possess several characteristics desirable in a biocontrol agent, and have inhibited several plant pathogens in previous studies (Aly 2009, Mavrodi et al. 2012, McSpadden Garderer et al. 2005, Raudales et al.

2009). There was no correlation between in vitro inhibition of Ralstonia strains as measured by zones of inhibition and biocontrol efficiency in tomato plants challenged with R. solanacearum. Pseudomonas vranovensis strain 15D11 was the most antagonistic towards R. solanacerum strains in vitro, but was moderately effective in reducing bacterial wilt when used to treat tomato plants later challenged with the pathogen.

Pseudomonas brassicacearum strains 93D8 and Wood 1R , and P. protegens strain

Clinto 1 , which were less inhibitory than P. vranovensis strain 15D11 in in vitro antagonism assays, were significantly more effective than this strain in vivo. Such inconsistency between the results of in vitro assays and bioassays have been observed in other studies (Lemessa and Zeller 2007, Rajkumar et al 2005, Ran et al 2005). An in vitro

83 inhibition assay is a quick, easy and inexpensive method of screening antagonistic organisms, however results depend highly on availability of nutrients in the medium required for antagonistic bacteria to produce inhibitory substances (Chen et al. 2003,

McSpadden Gardener et al. 2005). As plate-based methods account for growth inhibition due to production of these substances, mostly antibiotics, the methods are of limited use to screen organisms that can provide biocontrol by inducing host resistance or degrading signals that activate pathogens (Molina et al. 2003). Therefore, the other biocontrol agents that were not used in the bioassay portion of this study cannot be considered non- effective against bacterial wilt unless verified with further experiments.

Bioassays conducted under field conditions tend to be more accurate in determining biocontrol efficacy of antagonistic organisms (Serfling et al. 2007). As tomato bacterial wilt is not present in Ohio, we used field soil to conduct bioassays under greenhouse conditions. The pathogen enters plant roots via wounds, which can be mechanically induced or naturally formed during lateral root emergence (Vasse et al.

1995). Root wounding did not increase wilt incidence in this study when plants were not protected with biocontrol agents suggesting that the natural root cracks provided suffiecient entry points for R. solanacearum. Therefore, additional root wounding may not be necessary in greenhouse studies meant to simulate the field environment.

Applying different biocontrol agents as a mixture can enhance biocontrol efficacy by employing different disease control mechanisms. Several studies have shown such synergistic effect of biocontrol agents against various plant pathogens (de Boer et al.

2003, Jetiyanon and Kloepper 2002, Raupach and Kloepper 1998, Seenivasan et al. 2012,

Stockwell et al. 2011). However, the mixture of biocontrol agents used in this study was moderately effective. As the biocontrol efficacy is population dependent (Raaijmakers and Weller, 1998), absence of synergystic effects in the mixture might be due to insufficient populations of each biocontrol agent or lack of variation in disease control mechanisms among the biocontrol agents.

Mean wilt incidence in non-treated susceptible tomato line L390 was 96%, compared to 62% in partially resistance line IRAT L3. According to a classification of host resistance to bacterial wilt by Lebeau et al. (2011), based on wilt incidence in this study, lines L390 and IRAT L3 are considered highly susceptible and susceptible hosts, respectively. When these lines were treated with antagonistic bacteria, final wilt incidence was reduced by 42% in the susceptible host and 11% in the highly susceptible host compared to untreated controls. Vanitha et al. (2009) tested efficacy of P. fluorescens as a seed treatment against bacterial wilt in 20 different tomato cultivars.

Though wilt incidence was significantly reduced in all cultivars, the level of protection provided by P. fluorescens was higher for cultivars in which wilt incidence was lower in the non-treated controls. Their finding is in agreement with the results of this experiment, in which a higher degree of biocontrol was achieved with increased host resistance. In a different pathosystem, Phytophthora dieback of rhododendron was suppressed by

Trichoderma hamatum 382 in susceptible cv. 'Roseum Elegans', however, the disease was not suppressed by T. hamatum 382 in highly susceptible cvs. 'Aglo' and 'PJM Elite'.

The authors suggest the differences in efficacy of T. hamatum 382 might be due to the level of host resistance (Hoitink et al 2006). We hypothesize that the higher degree of

85 protection observed in relatively resistant hosts might be due to: (i) the pathogen population that makes contact with the host after overcoming barriers created by biocontrol agents might be enough to cause disease in susceptible hosts, but not in more resistant hosts; or (ii) the combination of host resistance and induced resistance (by biocontrol agents) might be sufficient to reduce pathogen attack compared to induced resistance alone. Biocontrol agents utilize several mechanisms such as competition, antibiosis, destruction of pathogen signals and virulence factors, and induction of host resistance (Compant et al. 2005, Molina et al. 2003, Pal and McSpadden Gardener 2006).

Most of the biocontrol agents used in this study tested positive for hydrogen cynide

(HCN), siderophore, and 2,4-Diacetylphloroglucinol (DAPG) production, and have shown exoprotease activity (Aly 2009, Mavrodi et al, 2012). As several mechanisms are employed by biocontrol agents, the exact mechanisms of bacterial wilt suppression in this study are not known.

In addition to suppressing plant diseases, biocontrol agents are known to promote plant growth via several mechanisms, including production of phytohormones and other secondary metabolites, changing host physiology (Kim et al. 2011), reducing stress and providing biofertilizers (Lugtenberg and Kamilova 2009). However, we were unable to detect biocontrol agent-induced plant growth promotion in this study. In a separate study

P. vranovensis strain 15D11, P. protegens strain 15G2, and P. brassicacearum strain

Wood 1R increased plant biomass and leaf length of wheat by suppressing the root pathogens Pythium ultimum and Rhizoctonia solani (Mavrodi et al 2012). In another study, P. brassicacearum strain Wood 1R increased yield and biomass of soybean but not

86 of corn (McSpadden Gardener et al. 2005). Test plants in this study were fertilized regularly and were not inoculated with pathogens. Hence the failure of biocontrol agents to enhance plant growth in this study might be due to lack of disease pressure, host preference by biocontrol agents and presence of sufficient nutrients for plant growth.

Pseudomonas brassicacearum strains 93D8 and Wood 1R, P. protegens strain

Clinto 1 , and P. vranovensis strain 15D11 have shown potential to suppress bacterial wilt of tomatoes under greenhouse conditions. The effects of these bacteria under field conditions should be tested before considering them effective biocontrol agents. These strains were more consistent and effective in the partially resistant line IRAT L3 than in susceptible line L390, which suggests that the host resistance, even of small magnitude, highly enhances biocontrol efficacy of antagonistic bacteria against bacterial wilt.

ACKNOWLEDGEMENTS

I would like to thank Dr. Christophor G. Taylor and Dr. Brian McSpadden

Gardener for providing antagonistic bacterial strains; and Dr. Jaw-Fen Wang, AVRDC,

Taiwan and Dr. Marie Christine Daunay, INRA, France, for providing seeds for this study. This work was supported by the Agriculture Office within the Bureau for

Economic Growth, Agriculture, and Trade (EGAT) of the U.S. Agency for International

Development, under the terms of the IPM-CRSP (Award EPP-A-00-04-00016-00).

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TABLES

Table 3.1: Antagonism of bacterial biocontrol agents in an in vitro inhibition assay against Ralstonia solanacearum strain NCSU 68

Zone ofc Bacteriala SN Source Nameb inhibition strains (mm) 1 1 B1 Mississippi River Pseudomonas protegens 5.3 2 1 C5 Mississippi River Pseudomonas protegens 5.3 3 1 F2 Mississippi River Pseudomonas protegens 5.3 4 12 H11 Missouri River Pseudomonas protegens 3.0 5 14 B11 Missouri River Pseudomonas chlororaphis 6.7 6 14 B2 Missouri River Pseudomonas protegens 2.7 7 14 D6 Mississippi River Pseudomonas chlororaphis 7.3 8 15 D11e Mississippi River Pseudomonas vranovensis 11.0 9 15 G2e Missouri River Pseudomonas protegens 3.3 10 15 G6 Missouri River Pseudomonas protegens 3.3 11 15 H10f Missouri River Serratia plymuthica 8.3 12 15 H3 Missouri River Pseudomonas protegens 2.3 13 2 F9 Missouri River Pseudomonas fluorescens 5.3 14 24 D3 Herbarium Pseudomonas fluorescens 3.3 15 28 B5 Herbarium Pseudomonas fluorescens 5.3 16 29 G9 Herbariumd Pseudomonas poae 6.3 17 3 D6 Missouri River Serratia plymuthica 2.7 18 31 D2e Herbarium Enterobacter ludwigii 7.7 19 36 B3 Wyoming soil Pseudomonas fluorescens 0.0 20 36 B7 Wyoming soil Pseudomonas brassicacearum 0.0 21 36 C6 Wyoming soil Pseudomonas frederiksbergensis 0.7 22 36 C8f Wyoming soil Pseudomonas poae 6.0 23 36 D4 Wyoming soil Pseudomonas brassicacearum 0.0 24 36 F3 Wyoming soil Pseudomonas fluorescens 0.0 25 36 G2 Wyoming soil Pseudomonas fluorescens 4.3 26 37 A10 Wyoming soil Pseudomonas frederiksbergensis 0.0 27 37 A11 Wyoming soil Pseudomonas frederiksbergensis 1.7 28 37 D10 Wyoming soil Pseudomonas brassicacearum 0.0 29 37 F8 Wyoming soil Pseudomonas fluorescens 3.0 30 38 D4f Wyoming soil Pseudomonas brassicacearum 0.0 31 38 D7 Wyoming soil Pseudomonas brassicacearum 0.0 Table 3.1 Continued

Table 3.1 Continued 32 38 E5 Wyoming soil Pseudomonas borealis 0.0 33 38 F7 Wyoming soil Pseudomonas frederiksbergensis 1.3 34 38 G2 Wyoming soil Pseudomonas protegens 3.0 35 39 A2 Wyoming soil Pseudomonas frederiksbergensis 2.0 36 48 B8f Wisconsin soil Pseudomonas chlororaphis 3.3 37 48 C10 Wisconsin soil Pseudomonas lini 1.7 38 48 D1f Wisconsin soil Pseudomonas fluorescens 9.3 39 48 D5f Wisconsin soil Pseudomonas fluorescens 6.3 40 48 G9 Wisconsin soil Pseudomonas chlororaphis 5.0 41 48 H11 Wisconsin soil Pseudomonas brassicacearum 0.0 42 528C10 Missouri River Bacillus sp. 0.0 43 88 A6 Missouri soils Pseudomonas rhodesiae 1.7 44 89 F1 Missouri soils Pseudomonas fluorescens 0.0 45 90 D7A Missouri soils Pseudomonas fluorescens 3.3 46 90 F12-1 Missouri soils Pseudomonas rhodesiae 4.3 47 93 D8e Missouri soils Pseudomonas brassicacearum 6.0 48 93 F8 Missouri soils Pseudomonas brassicacearum 4.7 49 93 G8f Missouri soils Pseudomonas brassicacearum 4.7 50 94 A2 Missouri soils Serratia plymuthica 5.0 51 94 G2 Missouri soils Pseudomonas frederiksbergensis 4.0 52 Clinto 1e Ohio soil Pseudomonas protegens 4.0 53 Wayne 1R Ohio soil Pseudomonas protegens 0.0 54 Wood 1Re Ohio soil Pseudomonas brassicacearum 3.3

aAll strains except Pseudomonas protegens strains Clinto 1 and Wayne 1R, and P. brassicacearum strain Wood 1R (McSpadden Gardener et al 2005) were first described by Aly (2009). b Identity of bacterial strains based on seven housekeeping genes (acs A, aro E, pps A, pyr C, rec A, rpo B, and mut L. cMean zone of inhibition (mm) of three replicates of R. solanacearum strain NCSU 68 2 days after inoculation with biocontrol strains. dHerbarium specimens of Missouri Botanical Garden, St. Louis, MO.

Table 3.1 Continued

Table 3.1 Continued ebiocontrol strains selected for greenhouse bioassay experiments based on their performanance against South Asian strains of R. solanacearum. f Biocontrol strains selected for in vitro inhibition assay against selected South Asian strains of R. solanacearum.

Table 3.2. Geographical origin, original host, and biovar of Ralstonia solanacearum

strains

SN Strain ID Origina Host Biovarb

1 SM673-12 Jamalpur, Bangladesh Chili pepper III 2 SM680-12 Norsindhi, Bangladesh Eggplant IV 3 SM681-12 Norsindhi, Bangladesh Eggplant IV 4 SM682-12 Norsindhi, Bangladesh Eggplant IV 5 SM683-12 Norsindhi, Bangladesh Eggplant IV 6 SM699-12 Jessor, Bangladesh Eggplant III 7 SM743-12 Syangja, Nepal Grafted tomatoc III 8 SM709-12 Comilla, Bangladesh Eggplant IV 9 SM714-12 Comilla, Bangladesh Chili pepper IV 10 SM718-12 Braminbaria, Bangladesh Eggplant IV 11 SM729-12 Tangile, Bangladesh Grafted eggplantc III 12 SM737-12 Bogra, Bangladesh Eggplant III 13 SM738-12 Bogra, Bangladesh Eggplant III 14 SM646-12 Kathmandu, Nepal Tomato IV 15 SM651-12 Maharastra, India Eggplant III 16 NCSU 68 North Carolina, USA Tobacco I

aLocations from which the strains were isolated. NCSU 68 kindly provided by Dr. AL

Mila, North Carolina State University.

bBiovar determined based on utilization of cellobiose, lactose, maltose, dulcitol,

mannitol, and sorbitol (Smith et al. 1995).

cSolanum sisymbriifolium, a wild eggplant, was used as rootstock.

Tomato line Percentage wilted/dead plantsa Roots wounded Roots not wounded Expt I Expt II Meanb Expt III Expt IV Meanc IRAT L3 47 a 32 a 40 a 39 a 37 a 38 a L390 90 b 92 b 91 b 93 b 74 b 84 b

aData from all biocontrol treatments and the non-treated control were combined for each tomato line. Values in the same column followed by different letters are significantly different according to the Fisher's LSD test (P≤0.05). bMean wilt incidence in IRAT L3 and L390 when pathogen was inoculated following root injury. cMean wilt incidence in IRAT L3 and L390 when pathogen was inoculated without root injury.

Table 3.4. Impact of root wounding on bacterial wilt incidence in tomato lines IRAT L3 and L390 inoculated with a mixture of three South Asian Ralstonia solanacearum strains, in the presence or absence of biocontrol agents.

Percentage of wilted plantsa Non-treated control Biocontrol agent- treated IRAT L3 L390 IRAT L3 L390 Wounded 66 a 93 a 40 a 91 a Not wounded 58 a 99 a 38 a 84 b

a Percentage of tomato lines IRAT L3 and L390 wilted 29 days after inoculation with R. solanacearum. Inoculum was applied after root wounding in the first two experiments and without root wounding in the remaining two experiments. Data for experiments I and

II (roots wounded) and III and IV (roots not wounded) were pooled. Means in each column followed by same letter are not significantly different (t-test, P≤0.05).

Table 3.5. Bacterial wilt incidence expressed as percentage wilt and AUDPC in tomato lines IRAT L3 and L390 in A,

the first two experiments, in which Ralstonia solanacearum was inoculated following root wounding, and B, the last

two experiments in which the pathogen was inoculated without root wounding

A. Biocontrol agenta Wilt incidence (%) AUDPCb (BCA) IRAT L3 L390 IRAT L3 L390

Expt I Expt II Expt I Expt II Expt I Expt II Expt I Expt II

P. vranovensis 15D11 35 bc 33 b 90 ab 100 a 500 cd 520 bc 1350 abc 1820 ab

100 P. protegens 15G2 35 c 33 b 88 ab 93 a 455 d 595 ab 1358 abc 1513 ab

E. ludwigii 31D2 67 a 33 b 100 a 88 a 1003 ab 500 bc 1720 a 1415 a

P. brassicacearum 93D8 28 c 28 b 75 abc 98 a 397 d 428 bc 1175 bcd 1675 ab

P. protegens Clinto-1 50 ab 18 b 95 ab 95 a 780 abc 278 c 1623 ab 1685 ab

P. brassicacearum Wood 1R 40 bc 28 b 88 ab 83 a 615 bcd 383 bc 1373 abc 1295 a

Control 75 a 58 a 98 a 88 a 1160 a 995 a 1858 a 1515 a

BCA × Host (P-value) 0.026 0.862 0.026 0.862 0.119 0.059 0.119 0.059

Table 3.5 Continued

100

Table 3.5 Continued

B. Biocontrol agenta Wilt incidence (%)b AUDPCc (BCA) IRATL3 L390 IRATL3 L390

Expt III Expt IV Expt III Expt IV Expt III Expt IV Expt III Expt IV

P. vranovensis 15D11 40 bc 63 abcde 100 a 98 a 775 abc 1163 a 2121 ab 1944 ab

P. protegens 15G2 48 abc 40 ef 100 a 50 e 775 bc 880 abc 2199 a 794 f

E. ludwigii 31D2 55 ab 48 cde 95 a 75 abc 1015 ab 941 ab 1758 abcd 1465 bc

P. brassicacearum 93D8 30 c 0 g 93 a 85 ab 594 c 0 e 2064 abc 1405 bcd

101 P. protegens Clinto-1 28 c 15 f 90 ab 53 e 498 c 266 d 1475 cdef 906 cdef

P. brassicacearum Wood 1R 15 c 38 de 88 ab 63 bcde 233 d 814 ab 1341 def 1096 cdef Mixed 33 c 43 cde 83 ab 73 abcd 578 c 891 a 1562 bcde 1294 bcde

Control 65 a 50 bcde 100 a 98 a 1191 a 1039 a 2152 ab 2344 a

BCA × Host (P-value) 0.0016 <0.0001 0.0016 <0.0001 0.015 <0.0001 0.015 <0.0001 Table 3.5 Continued

101

Table 3.5 Continued aBiocontrol agents were applied twice, immediately after seeding and a week prior to

Ralstonia solanacearum inoculation. A mixture of three South Asian strains of R. solanacearum was inoculated 4 weeks after seeding. In the third and the fourth experiments an additional treatment, Mixed, a mixture of all six biocontrol agents, was applied. bFinal wilt incidence was recoreded 4 weeks after pathogen inoculation. Values presented are means of five replications, each with eight plants. Values in the same column followed by different letters are significantly different (P<0.05) by Fisher's LSD test. c Area Under the Disease Progress Curve (AUDPC) values were calculated as: ∑([(xi+xi-

1)/2](t1-ti-1)) where xi is the rating at each evaluation time and (t1-ti-1) is the number of days between evaluations. Values in the same column followed by different letters are significantly different (P<0.05) by Fisher's LSD test.

102

Table 3.6. Biocontrol efficacy expressed as percentage reduction in wilt due to application of biocontrol agents to suppress

bacterial wilt incidence in tomato lines L390 and IRAT L3, and its correlation with in vitro inhibition of

Ralstonia solanacearum

a b Biocontrol agentsc Roots wounded Roots not wounded d Exp I Exp II Exp III Exp IV Mean (BCAs) L390 IRAT L3 L390 IRAT L3 L390 IRAT L3 L390 IRAT L3 L390 IRAT L3 P. vranovensis 15D11 7.7 a 53.3 ab -14.3 a 52.2 a 0.0 b 38.5 bcd 0.0 c -25.0 c -1.6 29.7

P. protegens 15G2 10.3 a 53.3 ab -5.7 a 43.5 a 0.0 b 26.9 cde 48.7 a 20.0 b 13.3 35.9

E. ludwigii 31D2 -2.6 b 10.0 cd 0.0 a 43.5 a 5.0 b 15.4 de 23.1 bc 5.0 b 6.4 18.5

103 P. brassicacearum 93D8 23.1 a 63.3 a -11.4 a 52.2 a 7.5 ab 53.8 ab 12.8 bc 100.0 a 8.0 67.3

P. protegens Clinto 1 2.6 a 33.3 bc -8.6 a 69.6 a 10.0 ab 57.7 ab 46.2 ab 70.0 a 12.5 57.6 10.3 a 46.7 ab 5.7 a 52.2 a 12.5 ab 76.9 a 35.9 abc 25.0 b 16.1 50.2 P. brassicacearum Wood 1R ND ND ND ND 17.5 a 50.0 abc 25.6 bc 15.0 b 21.6 32.5 Mixed

Control 0.0 ab 0.0 cd 0.0 a 0.0 b 0.0 b 0.0 e 0.0 c 0.0 bc 0.0 0.0

Mean 10.9 41.7

BCAs × host (P-value) 0.2937 0.0542 0.0916 0.0036 Pearson's rf 0.08 0.39 -0.54 0.14 -0.39 0.10 -0.67 -0.50 -0.71 -0.18 (P-value) (0.87) (0.44) (0.27) (0.79) (0.44) (0.85) (0.15) (0.30) (0.11) (0.73)

Table 3.6 Continued

103

Table 3.6 Continued aPathogen was drench-inoculated onto each plant followed by root wounding in experiments

I and II bPathogen was drench-inoculated onto each plant without root wounding in experiments III and IV cBiocontrol agents were applied twice, 0 and 3 weeks after seeding. In the third and the fourth experiments an additional treatment, ‘Mixed’, a mixture of all six biocontrol agents, was also used. dMean biocontrol efficacy of biocontrol agents in tomato lines L390 and IRAT L3 in four experiments. eDifference of biocontrol efficacy of biocontrol agents in tomato lines L390 and IRAT L3. fCoefficient of correlation between zones of inhibition produced by biocontrol agents and

their biocontrol efficiencies.

104

FIGURES

Fig. 3.1. Mean zones of inhibition produced by 13 biocontrol agents (P. protegens strains 15G2 and Clinto 1, S. plymuthica strain 15H10, E. ludwigii strain31D2, P. frederiksbergensis strain 36C8, P. chlororaphis strain 48B8, P. fluorescens strains

48D1 and 48D5, P. vranovensis strain 15D11, and P. brassicacearum strains 38D4,

93D8, 93G8 and Wood 1R) against 15 South Asian Ralstonia solanacearum strains. A,

Mean zone of inhibition produced by each biocontrol agent across all R. solanacearum strains. B, Mean zone of inhibition produced against each R. solanacearum strain by all biocontrol agents. A suspension of 100 µl of R. solanacearum (108 CFU/ml) was spread onto PF medium. After the plates were dried in a laminar flow hood, 2.5 µL aliquots of biocontrol agents (109 CFU/ml) were dropped onto the plates and incubated for 48 h at 28oC, when zones of inhibition were measured. Bars with different letters are significantly different according to Fisher's LSD test.

105

Fig. 3.1

a A

6 b bc c cd de de e 4 f g

Zone of inhibition (mm) inhibitionof Zone h h i 0

Biocontrol agents

8 B

6 a b c cd cd de 4 de de ef efg fg fg gh hi i

2 Zone of inhibition (mm) inhibitionof Zone 0

Ralstonia solanacearum strains

106

Figure 3.2 Incidence of bacterial wilt caused by R. solanacearum over time, in A, partially resistant tomato line IRAT L3 and, B, susceptible tomato line L390 treated with biocontrol agents P. protegens strains 15G2 and Clinto 1, E. ludwigii strain 31D2,

P. vranovensis strain 15D11, or P. brassicacearum strains 93D8 and Wood 1R, immediately after seeding, and 3 weeks after seeding, i.e. 1 week prior to pathogen inoculation. Plants were maintained under greenhouse conditions and wilt progression was recorded 7 days after pathogen inoculation and every other day therafter, until the wilt progression stablized. This figure was created from data generated in experiment 3, including ‘Mixed’ treatment, a mixture of all six biocontrol agents. Data generated in the three other experiments were statiscally similar.

107

Fig. 3.2

P. vranovensis 15D11 P. protegens 15G2 A E. ludwigii 31D2 P. brassicacearum 98D3 P. protegens Clinto 1 Control Mixed P. brassicacearum Wood1R 100 90 80

60 50

40 Percent wilt Percent 30 20 10 0 7 9 11 13 15 17 19 21 23 25 27 29 Days post inoculation

100 90 B 80

70 60 50 40

Percent wilt Percent 30 20 10 0 7 9 11 13 15 17 19 21 23 25 27 29 Days post inoculation

108

Fig. 3.3

100

40 With BCAs Without BCAs Percentage wilt Percentage 20

0 L390 IRAT L3 Tomato accessions

Fig 3.3. Impact of biocontrol agents (BCAs) on bacterial wilt incidence in patially resistant (IRAT L3) and susceptible (L390) tomato lines. Biocontrol agents were applied immediately after seeding, and 3 weeks after seeding, i.e. 1 week prior to pathogen inoculation. The figure was created by combining data from all four experiments.

109

Fig. 3.4

P. vranovensis 15D11 P. protegens 15G2 E. ludwigii 31D2 P. brassicacearum 98D3 P. protegens Clinto 1 P. brassicacearum Wood 1R Control

6.5 * 6

5.5

4.5 Log CFU/g dry wt. of root plugroot of wt.dry CFU/g Log 0 1 2 3 Weeks post inoculation

Fig. 3.4. Populations of Ralstonia solanacearum in root plugs (potting mix plus roots) treated with biocontrol agents P. protegens strains 15G2 and Clinto 1, E. ludwigii strain

31D2, P. vranovensis strain 15D11, or P. brassicacearum strains 93D8 and Wood 1R at different time intervals. biocontrol agents were applied 0 and 3 weeks after seeding.

R. solanacearum was inoculated 4 weeks after seeding. Plugs treated only with R. solanacearum were used as a control. Populations of R. solanacearum were determined

0, 1, 2 and 3 weeks after inoculation with the pathogen by dilution plating on modified

SMSA medium.

*Populations of R. solanacearum in root plugs treated with E. ludwigii strain 31D2 were significantly higher than in root plugs treated with P. protegens strain Clinto 1 and

P. brassicacearum strain 98D3 2 weeks after R. solanacearum inoculation.

110

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