Waheed Akram Institute of Agricultural Sciences

STUDIES ON EFFICACY AND MECHANISMS OF BACILLUS STRAINS TO INDUCE SYSTEMIC RESISTANCE IN TOMATO AGAINST FUSARIUM WILT

A thesis submitted to the University of the Punjab in partial fulfillment of the requirement for the degree of doctor of philosophy in Agricultural Sciences

WAHEED AKRAM

INSTITUTE OF AGRICULTURAL SCIENCES UNIVERSITY OF THE PUNJAB LAHORE

STUDIES ON EFFICACY AND MECHANISMS OF BACILLUS STRAINS TO INDUCE SYSTEMIC RESISTANCE IN TOMATO AGAINST FUSARIUM WILT

A thesis submitted to the University of the Punjab in partial fulfillment of the requirement for the degree of doctor of philosophy in Agricultural Sciences

Waheed Akram

Supervisor

Dr. Tehmina Anjum Assistant Professor

Co-supervisor Dr. Basharat Ali Assistant Professor

INSTITUTE OF AGRICULTURAL SCIENCES UNIVERSITY OF THE PUNJAB LAHORE

CERTIFICATE This is to certify that the research entitled “Studies on efficacy and mechanisms of Bacillus strains to induce systematic resistance in tomato against fusarium wilt” described in this thesis by Mr. Waheed Akram, is an original work of the author and has been carried out under my direct supervision. I have personally gone through all the data, results, materials reported in the dissertation and certify their correctness and authenticity. I further certify that the material included in this thesis has not been used in part or full in a dissertation already submitted or in the process of submission in partial or complete fulfillment of the award of any other degree from any institution. I also certify that the thesis has been prepared under my supervision according to the prescribed format and I endorse its evaluation for the award of Ph.D. degree through the official procedures of the University of the Punjab, Lahore.

Supervisor

Dr. Tehmina Anjum Assistant Professor

Dr. Basharat Ali Assistant Professor

Date: ______

DECLARATION CERTIFICATE

This thesis which is being submitted for the degree of Ph.D. in the University of the Punjab does not contain any material which has been submitted for the award of Ph.D. Degree in any University and, to the best of my knowledge and belief, neither does this thesis contain any material published or written previously by another person, except when due reference is made to the source in the text of the thesis.

(Waheed Akram) Ph.D. Scholar

DEDICATED TO MY BELOVED PARENTS AND

TEACHERS

iii

ACKNOWLEDGMENTS

All praises and gratitude is to the splendor of Almighty ALLAH, the Beneficent and the Merciful, Whose blessings facilitated me to fulfill this research work. I pay all compliments to the Holy Prophet Muhammad (Sallal laho Alahe Wa’alhe Wasallam), the wisdom and gateway of the comprehension. First of all we are very thankful to Higher Education Commission of Pakistan for providing financial support to perform this whole research work and financial aid to researcher and supervisor. I express my cordial gratitude to my supervisors Dr. Tehmina Anjum, Assistant Professor, Institute of Agricultural Sciences, University of the Punjab, Lahore and Dr. Basharat Ali, Assistant Professor, Department of Microbiology and Molecular Genetics, University of the Punjab, Lahore for their enthusiastic concern, precious implications, regular encouragement and kind attitude during the course of this research venture. For numerous supportive suggestions during research studies, I am grateful to Dr. M. Saleem Haider, Professor and Director, Institute of Agricultural Sciences, University of the Punjab, Lahore. I may never forget support of Dr. Ahmad Ali Shahid, Associate Professor, CEMB, university of the Punjab, during my studies. Heartfelt thanks are also being extended to Dr. Amir Ali, Associate Professor, Department of Botany, University of Sargodha, Sargodha for his support from beginning of my studies and his valuable guidance in the molecular and statistical analysis. I feel enormous gratification to state my earnest admiration and gratefulness to Malik Muhammad Zaheer, Resident Officer-II, University of the Punjab, Lahore for his kind guidance, help and support during these studies. I am also grateful to my friends especially Aqeel Ahmad, my colleagues and all staff members of IAGS for their assistance and good desires throughout my research work. Sincere thanks are also for Syed Ehsan Haider Zaidi for helping in formatting this dissertation. Last but not the least, I am proud of my family members for their ethical and pecuniary support and encouraging manner to attain my goal and they extended their hands of sincerity towards me to accomplish higher targets of life.

(Waheed Akram)

Summary

Plant diseases are the most common reason for reduction in agricultural crop yield. Tomato (Lycopersicon esculentum Mill.) is among the most prevalent vegetables cultivated throughout the world. Lifecycle of this crop is threatened by an inclusive array of fungal, bacterial and viral pathogens. Fusarium wilt disease of tomato is economically important due to yield and quality loss of the crop. Fungicides are the only option that farmers use against this pathogen. These fungicides are hazardous for our environment and human health as these toxify food commodities and ground water reserves. Moreover, they can never be the best option to manage the disease due to their extensive toxicity and minuscule degradability. These facts engender the need of development of some alternate measure for controlling the pathogen.

Induced resistance is the potential alternate means of controlling fungal pathogens of plants. In last decade, tomato plant has become a successful model plant to investigate the induction of defense pathways after exposure to biotic and abiotic elicitors which act as a trigger of these mechanisms of resistance. Understanding these mechanisms in order to improve crop protection is a main goal for Plant Pathology. Present study was aimed on screening different native Bacillus strains to induce systemic resistance in tomato plants against fusarim wilt along with elucidation of immune responses attributable to the defense systems of plant and to search bacterial determinant/s which actually trigger systemic resistance inside the plant body.

 First, ten isolated strains of Fusarium oxysporum f.sp. lycopersici. (Fol) were tested for their virulence against 23 varieties of tomato. After interacting Fol strains and tomato varieties in all possible combinations, most virulent Fol strain ‘Fol7’ and three tomato varieties with varying susceptibility viz: Fine Star (72%), Rio Grande (49%) and Red Power (24%) were selected for further experimentations.  Different native non-pathogenic rhizospheric Bacillus strains were procured from two different bacterial conservatories of University of the Punjab Lahore,

Pakistan. All Bacillus strains were screened to manage fusarium wilt of tomato under split root system. Two strains viz: B. fortis IAGS162 and B. subtilis IAGS174 provided most significant protection against fusarium wilt. These strains reduced >70% disease severity in comparison to the pathogen control. In this experiment, all Bacillus strains were again interacted with tomato plants in split root experiment and changes were denoted in quantities of different defense related biochemicals like total phenolics and some enzymes involved in phenylpropenoid pathway in time course manner. B. fortis IAGS162 and B. subtilis IAGS174 provided highest significant up-regulations in these biochemicals as compared to control plants.  In next experiment, study was undertaken in an effort to elaborate understandings about “how a beneficial bacterium and plant host crosstalk with one another in the presence of a pathogen”. For that purpose, molecular, histological and biochemical mechanisms were elucidated. Both these strains induced tomato plants for higher expression levels of PR-genes, extensive localization of lignin, phenolics and peroxidases in stem and root tissues. GC/MS analysis of total metabolites showed extensive re-modulation of primary and secondary metabolism in tomato plants under influence of these bacterial strains. Most of the up-regulated biochemicals were belonging to pathways like primary metabolism, TCA cycle, phenylpropenoid pathway and signaling pathways. Taken all these together eventually led to protection in tomato plants against fusarium wilt along with growth promotion.  Two best performing Bacillus strains were further evaluated in field studies in the form of talc based formulations. Formulation containing both Bacillus strain viz: B. fortis IAGS162 and B. subtilis IAGS174 showed maximum protection against fusarium wilt disease along with increase in growth and yield. This treatment reduced disease index up to 58% respectively on average basis in all the three tomato varieties across both seasons.  To conclude this work, studies were undertaken to search out determinant/s of induced systemic resistance from these best performing bacterial strains. Initially, it was observed that ISR determinant/s were extracellular metabolites in nature secreted in media from both bacterial strains. Further experimentations clued out that two aromatic compounds viz: Benzene acetic

acid and Phthalic acid methyl ester as ISR determinants from B. fortis IAGS162 and B. subtilis IAGS174 respectively.  To assess the significance of the results obtained during various experiments data was subjected to a number of statistical analyses. These analyses include analysis of variance (ANOVA) and Duncan’s Multiple Range Test (DMRT).

In conclusion, B. fortis IAGS162 and B. subtilis IAGS174 are able to mitigate fusarium wilt disease of tomato by activation of defence responses in the rhizosphere, in which phthalic acid methyl ester and benzeneacetic acid plays a major role as an elicitor for stimulation of the immune response. These results reinforce the biotechnological potential of B. fortis IAGS162 and B. subtilis IAGS174 as inducers of systemic resistance.

vii

Contents:

Page Certificate i Declaration certificate ii Dedications iii Acknowledgments iv Summary v Table of contents viii List of figures xi List of tables xiii Abbreviations xiv

1. Introduction

1.1. Introduction 1 1.2. Susceptibility of tomato to different pathogens 2 1.3. Fusarium wilt of tomato 3 1.3.1. Control of fusarium wilt of tomato 5

1.4. Induced systemic resistance (ISR) 6 1.4.1. Historical background of ISR 7 1.4.2. Mechanism of ISR 8 1.4.3. Use of bacterial microbes as elicitors of ISR 11 1.4.4. Bacterial determinants of ISR 15

1.5. Plant growth promotion by ISR capable bacteria 17 1.6. Concluding remarks and outlook 20 1.6.1. Gaps about knowledge of native bacterial strains 20 1.6.2. Applied aspects of beneficial bacterial strains 20

1.7. Aims and objectives 21

2. Material and methods

2.1..Selection of most virulent pathogen isolate and susceptible tomato varieties against fusarium wilt 22 2.1.1. Screening of tomato varieties against fusarium wilt 22 2.1.2. Genetic fingerprinting of Fol isolates by ISSR markers 25

2.2..Screening of Bacillus strains capable of inducing resistance in tomato against fusarium wilt under split root system 26 2.2.1..Potential of Bacillus strains to manage fusarium wilt under split root system 26 2.2.2. Analysis of changes in defense related biochemicals in tomato plants under influence of Bacillus strains 29 2.2.3. Isozyme analysis of Peroxidase and Polyphenoloxidase 32

2.3..Elucidation of molecular, histological and biochemical basis of ISR mediated by Bacillus strains against fusarium wilt of tomato 33

viii

2.3.1..Elucidation of molecular basis of resistance induced by selected Bacillus strains against fusarium wilt 34 2.3.2. Elucidation of histological and histochemical basis of resistance induced by selected Bacillus strains against fusarium wilt 37 2.3.3..Elucidation of biochemical basis of resistance induced by selected Bacillus strains against fusarium wilt 38

2.4..Evaluation of best performing Bacillus strains for their plant growth promoting efficacy 40 2.4.1. Potential of selected Bacillus strains to promote growth of tomato plant under greenhouse conditions 40 2.4.2..Effect of selected Bacillus strains on total chlorophyll, carotenoids and total soluble sugar contents of tomato plants 41 2.4.3. Characterization of selected Bacillus strains for production of plant growth promoting substances 41

2.5..Development of bacterial formulation and field evaluations of best performing Bacillus strains 43 2.5.1..Selection of carrier material for development of bacterial formulation 44 2.5.2..Efficacy of bacterial formulation to manage fusarium wilt under field conditions 44 2.5.3. Efficacy of bacterial formulation to promote growth and yield of tomato under field conditions 45

2.6. Screening of ISR determinants from selected Bacillus strains 46 2.6.1..Preliminary screening of potential ISR determinants from selected Bacillus strains 46 2.6.2. Isolation of ISR determinants from cell free culture filtrates of selected Bacillus strains 47 2.6.3. Identification of ISR determinant/s by GC/MS analysis 48 2.6.4. ISR bioassays with pure compounds 49

3. Results

3.1. Selection of most virulent pathogen isolate and susceptible tomato varieties against fusarium wilt 52 3.1.1. Screening of tomato varieties against fusarium wilt 52 3.1.2. Genetic fingerprinting of Fol isolates by ISSR markers 53

3.2..Screening of Bacillus strains capable of inducing resistance in tomato against fusarium wilt under split root system 60 3.2.1. Potential of Bacillus strains to manage fusarium wilt under split root system 60 3.2.2. Analysis of changes in defense related biochemicals in tomato plants under influence of Bacillus strains 64 3.2.3. Isozyme analysis of Peroxidase and Polyphenoloxidase 77

3.3. Elucidation of molecular, histological and biochemical basis of ISR mediated by Bacillus strains against fusarium wilt of tomato 81 3.3.1. Elucidation of molecular basis of resistance induced by selected

Bacillus strains against fusarium wilt 81 3.3.2. Elucidation of histological and histochemical basis of resistance induced by selected Bacillus strains against fusarium wilt 85 3.3.3..Elucidation of biochemical basis of resistance induced by selected Bacillus strains against fusarium wilt 88 88

3.4. Evaluation of best performing Bacillus strains for their plant growth promoting efficacy 99 3.4.1. Potential of selected Bacillus strains to promote growth of tomato plants under greenhouse conditions 99 3.4.2...Effect of selected Bacillus strains on total chlorophyll, carotenoids and total soluble sugar contents of tomato plants 100 3.4.3. Characterization of selected Bacillus strains for production of plant growth promoting substances 100

3.5. Development of bacterial formulation and field evaluations of best performing Bacillus strains 105 3.5.1..Selection of carrier material for development of bacterial formulation 105 3.5.2..Efficacy of bacterial formulation to manage fusarium wilt under field conditions 105 3.5.3. Efficacy of bacterial formulation to promote growth and yield of tomato under field conditions 106

3.6. Screening of ISR determinants from selected Bacillus strains 117 3.6.1..Preliminary screening of potential ISR determinants from selected Bacillus strains 117 3.6.2. Isolation of ISR determinants from cell free culture filtrates of selected Bacillus strains 117 3.6.3. Identification of ISR determinant/s by GC/MS analysis 122 3.6.4. ISR bioassays with pure compounds 122

4. Discussion

4.1. Discussion 126 4.2. Conclusion and future prospects 139

References 140 Appendix 1 171 Appendix 2 178 Appendix 3 181 Publications 183

List of Figures

Title Page Fig. 1.1: Symptoms of fusarium wilt of tomato. 5

Fig. 1.2: Signal transduction pathway of ISR and SAR. 11 Fig. 1.3: Schematic illustration of important mechanisms known for plant growth promotion by plant growth promoting bacterial microbes. 19 Fig. 2.1: Split root design used to screen Bacillus strains against fusarium wilt disease. 27 Fig. 2.2: Different steps involved in chemical extraction of ISR determinants from Bacillus strains. 52 Fig. 2.3: Experimental setup of screening of different treatments of CFCF Bacillus strains for presence of ISR determinant/s. 51 Fig. 3.1: Isolation and identification of Fusarium oxysporum f.sp. lycopersici (Fol). 54 Fig. 3.2: Susceptibility level of different tomato cultivars against all Fol isolates as governed by mean disease index. 56 Fig. 3.3:.Pathogenicity level of different Fol isolates against all tomato varieties. 57 Fig. 3.4: Cluster analysis showing grouping of different tomato varieties based on disease index. 58

Fig. 3.5: DNA finger printing of Fol isolates by ISSR markers. 59 Fig. 3.6: Effect of Bacillus strains on development of fusarium wilt on plants of three tomato varieties under split root system 63 Fig. 3.7: Changes in defense related biochemicals in tomato plants of variety ‘Fine Star’ under influence of Bacillus strains at different time intervals. 71 Fig. 3.8: Changes in defense related biochemicals in tomato plants of variety ‘Rio Grande’ under influence of Bacillus strains at different time intervals. 72 Fig. 3.9: Changes in defense related biochemicals in tomato plants of variety ‘Red Power’ under influence of Bacillus strains at different time intervals. 73 Fig. 3.10: Native-PAGE analysis showing isoform pattern of peroxidases in plants of three different tomato varieties treated with selected Bacillus strains. 79 Fig. 3.11: Native-PAGE analysis showing isoform pattern of polyphenol oxidases in plants of three different tomato varieties treated with selected Bacillus strains. 80 Fig. 3.12: Quantification of amplified product by GelAnalyzer Software. 83 Fig. 3.13: Influence of Bacillus strains on expression of defense related genes in tomato plants. 84 Fig. 3.14: Influence of Bacillus strains on histology and cytochemistry of stem of tomato plants. 86 Fig. 3.15: Influence of Bacillus strains on histology and cytochemistry of root of tomato plants. 87

Fig. 3.16: GCMS chromatograms showing changes in total metabolites of 90

tomato plants under influence of Bacillus strains. Fig. 3.17: GC/MS chromatogram showing change in metabolite contents of tomato plants under influence of B. subtilis IAGS174. 91 Fig. 3.18: Heat map showing changes in metabolites contents of tomato plants under influence of B. fortis IAGS162. 92 Fig. 3.19: Heat map showing changes in metabolites contents of tomato plants under influence of B. subtilis IAGS174. 93 Fig. 3.20: Effect of B. fortis IAGS162 on primary metabolism of tomato plants. 96 Fig. 3.21: Effect of B. subtilis IAGS174 on primary metabolism of tomato plants. 97 Fig. 3.22: Characterization of Bacillus strains for production of plant growth related substances. 101 Fig. 3.23: Effect of Bacillus strains on growth of tomato plants of variety ‘Fine Star’. 102 Fig. 3.24: Effect of Bacillus strains on total chlorophyll, indole acetic acid and total soluble sugar contents of tomato plants. 104

Fig. 3.25: Viability of bacterial propagules in different carrier materials. 108 Fig. 3.26: Different stages of field experiment for management of fusarium wilt of tomato under influence of Bacillus strains. 109 Fig. 3.27: Field efficacy of Bacillus strains for management of fusarium wilt of tomato of variety ‘Fine Star’ during the year 2011. 110 Fig. 3.28: Field efficacy of Bacillus strains for management of fusarium wilt of tomato of variety ‘Fine Star’ during the year 2012. 111 Fig. 3.29: Effects of bacterial strains on fruit set and yield of tomato plants under field conditions. 116 Fig. 3.30: Preliminary screening of ISR determinants from selected Bacillus strains 119 Fig. 3.31: Flow sheet of whole process involved in searching ISR determinant/s from B. fortis IAGS162. 120 Fig. 3.32: GC/MS Chromatogram of ISR active sub-fraction of cell free culture filtrates of B. fortis IAGS162. 121 Fig. 3.33: Flow sheet of whole process involved in searching ISR determinant/s from B. subtilis IAGS174. 123 Fig. 3.34: GC/MS Chromatogram of ISR active sub-fraction of cell free culture filtrates of B. subtilis IAGS174. 124 Fig. 3.35: Influence of root treatment of pure biochemicals present in ISR active sub-fraction on the disease development on tomato plants after inoculation with fusarium wilt pathogen. 125

xii

List of Tables

Title Page

Table 1.1: Tomato production in Pakistan. 4 Table 1.2: Bacterial determinants of induced systemic resistance for different plant species. 17 Table 2.1: Temperature conditions for PCR reaction carried out for Fol identification. 23 Table 2.2: Scoring of wilt symptoms in tomato. 24 Table 2.3: Details of native Bacillus strains used in this study. 27 Table 2.4: Details of treatments for split root experiment. 29 Table 2.5: Temperature conditions of PCR cycles for amplification of single stranded cDNA. 36 Table 2.6: List of defense gene primers for RT-PCR analysis. 36 Table 2.7: Description of treatments for field experiments. 45 Table 3.1: Details of ISSR Primers used for genetic fingerprinting of Fol isolates. 53 Table 3.2: Susceptibility of tomato varieties against selected Fol isolates. 55 Table 3.3: Potential of Bacillus strains to control fusarium wilt in tomato plants of three different varieties under split root experiment. 62 Table 3.4: Changes in defense related biochemicals in tomato plants of variety ‘Fine Star’ under influence of Bacillus strains. 74 Table 3.5: Changes in defense related biochemicals in tomato plants of variety ‘Rio Grande’ under influence of Bacillus strains. 75 Table 3.6: Changes in defense related biochemicals in tomato plants of variety ‘Red Power’ under influence of Bacillus strains. 76 Table 3.7: Functional category distribution among differentially expressed metabolites of tomato under influence of Bacillus strains. 98 Table 3.8: Characterization of Bacillus strains for production of IAA, siderophores and phosphorus solubilization. 103 Table 3.9: Effect of Bacillus strains on growth parameters of three tomato varieties. 103 Table 3.10: Potential of bacterial formulation to manage fusarium wilt under field conditions in the year 2011. 113 Table 3.11: Potential of bacterial formulation to manage fusarium wilt under field conditions in the year 2012. 113 Table 3.12: Effect of bacterial formulation on growth and yield of tomato plants under field conditions in the year 2011. 114 Table 3.13: Effect of bacterial formulation on growth and yield of tomato plants under field conditions in the year 2012. 115 Table 3.14: Preliminary screening of ISR determinants from selected Bacillus strains. 118

xiii

List of Abbreviations

CFU Colony forming unit % Percentage rpm Revolutions per minute pH Hydrogen ion concentration °C Degree centigrade DI Disease index PAGE Polyacrylamide gel electrophoresis MSTFA N-methyl-N-(trimethylsilyl) trifluoroacetamide MOX Methoxyamination DNA Deoxyribo nucleic acid RNA Ribo nuclei acid PCR Polymerase chain reaction RT Reverse transcrptase cDNA Complementary deoxyribo nucleic acid FAA Formalin: Acetic acid: Alcohol; 1:1:1 gL-1 Gram per liter mM Millimolar mg Milligram µL Microliter mL Milliliter L mL-1 Micro liter per milliliter µg mL-1 Micro gram per milliliter µm Micrometer cm Centimeter mm Millimeter OD Optical density ng Nanogram w/v Weight per volume dNTP Dinitrotriphosphate pmol Picomoles bp Base pairs APS Ammonium per sulfate TEMED N, N, N’, N’- Tetramethyl-ethylenediamine MS Mass Spectrum ≤ Less than and equal to ANOVA Analysis of variance LSD Least significant difference DMRT Duncan’s Multiple Range Test PCA Principle Component Analysis ISR Induced systemic resistance × 푔 Multiple of gravity NIST The National Institute of Standards and Technology

xiv

Chapter : 1

INTRODUCTION

Chapter: 1 Introduction

1.1:.Introduction

Vegetables constitute an important component of cropping system because of increasing pressure on food. Short maturity period of vegetables makes them fit for most farming systems in the whole world. In addition, higher yield potential and nutritional values further ads in their importance. These provide human beings with proteins, minerals and vitamins. Pakistan is an agriculture based country. It is now recognized as exporter of agriculture and horticulture produce in the whole world. Nearly 35 kinds of vegetables are grown in different farming systems of Pakistan. Pakistan is capable of year round production of different kinds of vegetables because of varied agro-climatic conditions, which prevails in different provinces of the country. In Pakistan, all provinces are capable of producing vegetables but Punjab and Sindh are important in this regard. These two have suitable climate, good infrastructure along with expertise. Skill full farmers make it possible to produce good quality of vegetable crops. About 588 thousand hectare area comes under production of vegetables in Pakistan as calculated in past ten years (Table 1.1) (GoP, 2006; 2008; 2012). The total export market of fruits and vegetables was 120 billion dollars in 2012. Punjab province contributes nearly 60% in export of vegetable and fruits every year (GoP, 2012).

Tomato (Lycopersicon esculentum Mill) is an important and widely grown crop in both tropical and subtropical regions. This crop is native to tropical America. It is believed that tomato was first domesticated in Mexico and a variant of wild tomato was being cultivated in 700AD. Cultivation of tomato has increased dramatically in mid- nineteenth century because of its capability to survive in varied climatic conditions. Tomato fruit is rich in vitamins, minerals and other organic substances. This fruit is used in fresh and numerous processed forms. Tomato has become one of the top selling vegetables round the world. Its cultivation is increasing in the world because of horticulture industry that has solely focused on production of tomato among vegetable crops. China is the world’s leader in tomato production. Tomato crop occupies more than 4.6 million hectares through the world with annual production of 128 million tons (Tahir et al., 2012). Tomato is an important rabi crop of Pakistan and is cultivated on over 54.23 thousand hectares in Pakistan (GoP, 2008; 2012). In Pakistan, average yield of tomato is

Chapter: 1 Introduction

9.6 tons per hectare (GoP, 2008; 2012) that is extremely low because of several pathological constraints. Today, many varieties of tomatoes are being cultivated in the whole world. Huge quantity of tomato is processed and preserved in several forms. Tomato paste is the most widely processed form of tomato that is used to make several products as sauces, juice and soups (FAO, 2000). Such type of versatility coupled with increasing demand of tomato fresh fruit, has made tomato as one of the major crops of the present century. 1.2: Susceptibility of tomato to different pathogens Various pests and diseases attack tomato and cause great economic losses. Injury of tomato at any growth stage can cause huge losses in final yield. Some pests of tomato remain resent during all growth stages of tomato and effect plant severely. Under field conditions, many fungal pathogens attack tomato plant and cause losses ranging from mild damages to plant death. In Pakistan, tomato is also attacked by variety of pathogens under field conditions, among which fungal diseases are most dominant (Taskeen-un- Nisa et al., 2011). Fungal wilts and rots are found in the whole world (Sokhi and Sohi, 1974). These diseases are also most prevalent in Pakistan, found commonly in areas with moderate temperature. The principal fungal diseases of tomato all over the world includes alternaria leaf spots and rots caused by Alternaria solani Sorauer and A. tenuis Nees, phytophthora rot caused by Phytophthora infestans (Mont.) de Bary, Phytophthora nicotianae Breda de Haan var. parasitica, anthracnose ripe caused by Colletotrichum phomoides (Sacc.) Chaster, phoma rot by Phoma destructiva Plowr and fusarium wilt caused by Fusarium oxysporum (Sacc.) Snyder and Hansen (Jones et al., 2014).

Fusarium wilt of tomato is caused by Fusarium oxysporum f.sp. lycopersici. That is considered as one of the most economically important and widespread diseases of the cultivated tomato (Solanum lycopersicum L.) under field conditions. Yield losses are recorded between 10-50% by that fungus both in greenhouse and field grown tomato (Larkin and Fravel, 1998; Borrero et al., 2004). This disease is also prevalent in Pakistan causing severe losses and has got status of a major disease of tomato in Pakistan (Tahir et al., 2012).

Chapter: 1 Introduction

1.3: Fusarium wilt of tomato

Fusarium wilt is most common vascular wilt of several plant species. This is highly disparaging disease, capable of causing severe damages in economically important plants. Both cultivated and wild types of plant species are prone to this disease (Wilhelm, 1981; Subbarao et al., 1997).

On the whole, species of three fungal genera i.e. fusarium, ophiosotma and verticilium are reported for vascular wilt diseases (Agrios, 2005). Fusarium spp. contains several features that make them one of the most devastating phytopathogen. These are true plant pathogens that rely completely on host plant but can also thrive outside the host. This obligate pathogen get engaged in many sophisticated activities of plants and redirect their nutrients flow leading to growth retardation or even death (Jackson and Taylor, 1996). Fusarium spp. produce infection structures that penetrate the vascular system of plant and remain in xylem causing browning of vessels. This pathogen can penetrate other tissues of host also. These have broad host range and can infect more than 700 plant species. Propagules of Fusarium spp. can remain viable in soil for several years. Fusarium oxysporum can produce three types of asexual spores as macroconidia, microconidia and chlamydospores (Nelson et al., 1983). Morphological classification of F. oxysporum is largely based on shape and size of macroconodia, structure features of microconidia and formation and position of chlamydospores (Beckman, 1987). Fusarium reproduces asexually by both micro and macroconidia. Sexual state of this fungus has never been observed (Booth, 1971).

Life cycle of F. oxysporum starts with a saprophytic phase. This fungus survives in soil in the form of chlymadospores (Beckman and Roberts, 1995). These remain dormant in decayed plant parts and start germinating in response to root exudates of plants (Stover, 1962; Beckman and Roberts, 1995). This fungus then penetrates plant and grows in vascular system and in parenchyma cells of the plant. Here it produces large number of spores. Process of disease development by F. oxysporum is very complex. Wilt diseases are caused by a combination of processes. First of all fungal mycelia accumulates inside xylem vessels and produce certain types of toxic materials (Beckman, 1987).

Chapter: 1 Introduction

529.6

476.8

561.9

536.2

502.3

468.1

426.2

412.8

306.3

294.1

268.6

(x000Tons)

Production

Total

52.3

50.0

53.4

53.1

47.1

46.2

41.4

39.0

31.0

29.4

27.9

Area

(x000Hec)

57.8

52.9

35.1

213.8

179.2

226.7

212.3

216.2

193.6

181.6

155.6

(x000Tons)

Production

Baluchistan

5.5

5.0

3.8

18.4

18.7

19.0

20.6

17.0

15.4

14.4

12.5

Area

(x000Hec)

113.2

119.3

161.8

162.0

160.8

161.6

146.9

157.5

148.3

146.2

140.0

(x000Tons)

Production

KPK

12.6

13.1

16.5

16.1

15.8

15.1

14.6

14.1

13.6

Area

(x000Hec)

)

2012

91.8

60.5

48.3

34.0

35.7

35.0

32.8 32.9

114.8

100.4

100.9

(x000Tons)

Production

GoP

(

Sindh Sindh

2012

8.7

9.4

6.1

6.2

6.1

5.8

6.1

14.6

12.2

12.3

10.9

Area

(x000Hec)

Pakistan

87.8

77.9

72.5

70.1

64.8

64.6

63.7

64.0

65.2

62.2 60.8

roduction in Pakistan. roduction

(x000Tons)

Production

statistics

Punjab

6.7

6.0

5.6

5.5

5.3

5.1

5.2

4.8

4.5

4.4 Area

Tomato p Tomato

(x000Hec)

Tomato production Pakistan. in Tomato

Agriculture

Year

2010

2009

2008

2007

2006

2005

2004

2003

2002

2001

2000

Source Table 1.1: 1.1: Table

Table 1.1.

Chapter: 1 Introduction

Symptoms of wilt appear because of severe water deficiency as a result of vessel occlusions. Wilting symptoms are variable also depending on plant species. These include wilting, chlorosis, necrosis and abscissions. Under severe conditions plant die, whereas under mild conditions plant growth is reduced (MacHardy and Beckman, 1981). Vascular browning is most prominent symptom of vascular wilt disease (Fig. 1.1B) (MacHardy and Beckman, 1981).

A B

Fig. 1.1: Symptoms of fusarium wilt of tomato. A= Aerial parts showing wilt symptoms. B= Vascular browning in fusarium wilt infected plants.

1.3.1: Control of fusarium wilt of tomato

Control of soil borne diseases has always been a challenge in conventional agriculture systems. Chemical fungicides such as benomyl, thiram, thiabendazole and carbendazim, and soil fumigators have been used to control fusarium wilt of tomato (Akram and Anjum, 2011). However, toxicity and accumulation of these chemical fungicides in the environment have become a serious environmental issue (Takken and Rep, 2010). These fungicides may adversely affect the rhizosphere microflora, with their inadvertent consequences for crop health.

Additionally, the effectiveness of these chemical fungicides is also vulnerable to the appearance of insensitive pathogen strains (Marchetti et al., 2000). Inconsistency and relatively lower effectiveness of many fungicides against soil borne pathogens under field conditions has been repeatedly reported (Marchetti et al., 2000; Takken and Rep, 2010). In recent years, efforts have been concentrated on the biological control of plant diseases including soil borne diseases like fusarium wilt of

Chapter: 1 Introduction tomato. Recently induced resistance has been identified as an effective biological control tool against fusarium wilt (Ramamoorthy et al., 2002; Srivastava et al., 2010).

1.4: Induced systemic resistance (ISR)

Induced resistance (IR) is a state of increased defensive capacity elicited by specific environmental stimuli (van Loon et al., 1998). Induced resistance (IR) enables plants to combat against a wide range of pathogens. This defense system reacts against external attack with some physiological, biochemical and histological changes that lead to initiation of immunity system of plants. Scientists have recognized two main types of IRs: Systemic acquired resistance (SAR) and Induced systemic resistance (ISR). These two can be differentiated on nature of elicitor and governing pathways (Fig. 1.2). Systemic acquired resistance occurs when a plant is exposed to virulent or avirulent pathogenic microbes or with some chemicals such as salicylic acid (Stitcher et al., 1997). Induced systemic resistance is a physiological state of enhanced defensive capacity elicited by specific environmental stimuli, whereby the plant’s innate defenses are potentiated against subsequent biotic challenges (Devendra et al., 2007).

Induced systemic resistance is effective against a wide range of pathogens. ISR differs from SAR in that microbes inducing ISR does not cause any visible symptoms in plants (van Loon et al., 1998). Mostly reported ISR phenomenon involved free living rhizobacterial strains. Certain endophytic bacteria have also been reported to induce ISR activity (Compant et al., 2005). Previously, it was stated that in contrast to SAR, ISR does not involves the elicitation of pathogenesis related (PR) proteins and accumulation of salicylic acid and relies on jasmonic acid or ethylene pathways (Maurhofer et al., 1994; Pieterse et al.,1998). These findings were based on limited number of ISR studies. Currently, ISR examples are more related to production of salicylic acid and siderophores by microbes and enhanced production of PR proteins in plants (Odjakova and Hadjiivanova, 2001; Yan et al., 2008).

Some endophytic microbes can protect their host from pest and pathogens either directly by process of antagonism or by competing for space or nutrition, or in an indirect way by inducing systemic resistance in plants against invading pathogen (Bakker et al., 1991; Hofte et al., 1997; Cordier, 1998; Devendra et al., 2007; Berg,

Chapter: 1 Introduction

2009). Concept of ISR was recognized nearly 100 years ago. Since then, it is being studied for its effectiveness to protect plants from fungi, bacteria and viral pathogens. In the past decade, discovery of biocontrol agents and knowledge regarding plant defense mechanism have led to grasp the fact that plant resistance to diseases is the best prospect for management of plant diseases. Transcription of defense related genes can be stimulated by external signals. Plants can defend themselves from pathogens by verity of mechanisms that can be either constituted or inducible (Franceschi et al., 1998; 2000). Inducible resistance mechanism is broad spectrum in nature. This can be induced by bio-agents or by the use of chemical agents (Elliston et al., 1977). Bio-agents like non-pathogenic microbes can induce resistance in different plant species against a wide array of diseases. These include diseases caused by fungi (Howell and Stipanovic, 1979) bacteria (Park and Kloepper, 2000) and viruses (Maurhofer et al., 1994). Chemicals used for IR may be of synthetic in nature or some macromolecules derived either from microorganisms or from host plants (Dixon et al., 1995). Varieties of synthetic chemicals have been used by researchers to enhance resistance levels in plants. These includes benzothiadiazole (Lawton et al., 1996), 2,6- dichloroisonicotinic acid (Uknes et al., 1992) and salicylic acid (Lawton et al., 1995).

1.4.1: Historical background of ISR

ISR was first studied by Ray (1901) and Beauvene (1901). They were working on gray mold caused by Botrytis cinerea (De Bary) Whetzel. Previously in 1899, Beauvene found that virulence of a strain of Botrytis cinerea can be altered by giving hot or cold shock. He discovered that resistance can be induced in Begonia under influence of strain of pathogen whose virulence was altered by hot or cold shocks. There are many ways of challenging the plants with the inoculum of bio-agent being used for induction of systemic resistance. Soil inoculation, root priming, foliar spray and injection methods have been used by various authors in their experiments of ISR. Ross (1961) carried out first investigation under lab conditions to induce systemic resistance in single leaf of tobacco with tobacco mosaic virus. He observed reduction in disease severity in rest of the leaves on the plants. Next work related to IR was carried out on tobacco under field conditions when suspension of spores of Peronospora tabacina D.B. Adam, was injected in stem of tobacco plants to control blue mold of tobacco caused by same virus (Cohen and Kuc, 1981). Scientists from different parts of the world have carried out their studies on various types of plants to

Chapter: 1 Introduction investigate phenomenon of ISR (Hunt and Ryals 1996; Schneider et al., 1997). Rhizospheric bacteria were initially applied to improve growth of the plants but later used as biocontrol agents for suppression of plant diseases (Dunleavy, 1955; Broadbent et al., 1971, Schippers et al., 1987). First biocontrol product was introduced by Gustafsons Inc. (Plano, Texas) in which biocontrol agent used was Bacillus subtilus (Ehrenberg) Cohn (Broadbent et al., 1971). Wide range of chemical compounds such as oligosachrides (Yoshikawa et al., 1993), glycoproteins and peptides (Benhamous, 1992) and salicylic acid (Yalpani, 1991) has been used to demonstrate their effects for induction of systemic resistance in different plants. For the first time a chemical agent arachidonic acid was used in 1984 by Bloch et al., for induction of phenolic compounds in tomato plants.

1.4.2: Mechanisms of ISR

Plant pathogenic agents as fungi and bacteria make the host plants to initiate defense response to restrict growth and invasion of pathogen. But this defense response is very slow and weak enough to prevent a pathogen colonization inside a host plant (Thordal-Christensen, 2003). These resistance reactions can be triggered before pathogen attack to restrict pathogen colonization up to certain cells or penetrating site (Kuc, 1982). If infection ceases along with restriction of pathogen damage, this phenomenon is called Induced Systemic Resistance (ISR). Induced systemic resistance triggers a wide range of resistance phenomenon elicited by nonpathogenic organisms (van Loon and Glick, 2004). This induced resistance generally is systemic, because it protects not only infection focus but also other parts of the plant (Ross, 1961). These distant sites are protected because of accumulation of salicylic acid, pathogen related gene expressions and stimulation of other defense related mechanisms (Durrant and Dong, 2004). Some microbes like non-pathogenic bacteria and fungi induce systemic resistance in plants by stimulating production of pathogenesis related proteins. This mechanism closely resembles with systemic resistance induced by pathogenic fungi (Lambais and Mehdy, 1995; Cordier et al., 1998). Fungi are seemed to activate defense response by producing auxins or auxin precursors. Auxin regulated ISR pathway may be responsible for ISR in plants (Madi and Katan, 1998). In case of chemicals agents for induction of resistance in plants, salicylic acid has been used by various researchers. It is believed that salicylic is

Chapter: 1 Introduction involved in signaling transduction pathway that leads to formation of defense related proteins (Metraux, 2001; Shah, 2003; Vimal and Suriachandraselvan, 2009).

The way in which bacteria induce systemic resistance is phenotypically similar to systemic acquired resistance SAR and is not always associated with salicylic acid production (Pieterse et al., 1996). Jasmonate and ethylene are involved in bacterial mediated ISR (van Loon et al., 1998). Transduction of both ISR and SAR are dependent on NPR1 regulatory proteins (Pieterse et al., 1998). van Wees et al. (1999) proved that ISR in arabidopsis was associated with up-regulation of jasmonate pathway. In another study Shoresh et al. (2005) showed that ethylene signaling pathway was associated with ISR in cucumber under influence of Trichoderma asperellum (Samuels) Lieckf & Nirenberg Ahn et al. (2007) also showed that in arabidopsis plants, ISR was dependent on NPR1, ethylene and jasmonic acid pathway. Zhang et al. (2002) found that ISR in test plants was associated with increased amount of salicylic acid. Plants that were treated with Bacillus pumilus Scot, provided higher quantities of salicylic acid as compared to control plants. In another study, De Meyer et al. (1999) proved that ISR in tobacco plants was associated with accumulation of salicylic acid.

In most cases where bacteria are used to induce systemic resistance in plants increased resistance to diseases is usually associated with defense related biochemicals such as phenolics, peroxidase (PO), phenylalanine ammonia lyase (PAL), phytoalexins, polyphenol oxidase (PO), and/or chalcone synthase in cells (van peer and Schippers, 1992; Ramamoorthy et al., 2002; Chen et al., 2000; Ownley et al., 2003), accumulation of pathogenesis related (PR) proteins as PR-1, PR-2, chitinases, and some peroxidases (Maurhofer et al., 1994; Mpiga et al., 1997; Viswanathan and Samiyappan, 1999; Park and Kloepper, 2000; Ramamoorthy et al, 2002; Jeun et al., 2004). In a study carried out by Benhamou et al. (1998) accumulation of phenolic compounds was detected in cell walls and intercellular spaces of berries treated with ISR capable bacterial strains. In another study carried out by Audenaert et al. (2002), tomato plants were treated with Pseudomonas aeruginosa (Schroter) Migula to induce systemic resistance against botrytis blight. They observed increased activity of total phenolics and other plant defense related biochemicals upon treatment with P. aeruginosa. It was observed in a study that ISR triggered by Bacillus mycoides was associated with increased production of some

Chapter: 1 Introduction phenylpropanoids like peroxidase (Bargabus et al., 2002). In a similar study, Pathak et al. (2004) described ISR potential of a Pseudomonas strain in rice against sheath blight diseases. They observed significant increase in total phenolics and other Phenylpropenoids like PO, PPO and PAL in bacterial treated plants.

Role of pathogenesis related proteins have been controversial in ISR process. Genes encoding PR proteins are not always expressed in ISR (van Loon et al., 1998) while in case of bacterial inducers, PR proteins have been found to accumulate inside plant body during ISR (Maurhofer et al., 1994; Park and Kloepper, 2000). Ward et al. (1991) discovered that by use of synthetic chemicals for activation of system resistance in plants, same set of PR genes activates in plants as in case of bioagents like bacteria and fungi. Pieterse et al. (1996) proved that ISR in arabidopsis was independent of PR gene expression under influence of a bacterial inducer while Zdor and Anderson (1992) found an association of PR proteins with ISR. When bean plants were inoculated with a bacterial inducer for induction of systemic resistance against Botrytis cinerea, significant up-regulation in levels of certain PR proteins were recorded. In the same way, Maurhofer et al. (1994) reported accumulation of PR proteins in tobacco plants when these were inoculated with Pseudomonas fluorescens (Flugge) Migula for induction of systemic resistance. They also proved that the bacterial strains unable to induce systemic resistance did not showed accumulation of PR proteins. Similarly, Nandakumar et al. (2001) reported up-regulation of PR proteins like PAL, chitinase and β1, 3-glucanase in rice under influence of some rhizobacterial strains. In a recent study Khan et al. (2012) reported up-regulation of PR protein genes in tomato inoculated with Paenibacillus lentimorbus Ash to induce systemic resistance against alternaria leaf spot disease.

On the other hand, Hoffland et al. (1995 and 1996) reported that ISR process in arabidopsis was not associated with accumulation of PR proteins. They inoculated arabidopsis plants with P. fluorescens to induce resistance against F. oxysporum f. sp. raphani. They observed no significant changes in levels of PR proteins. In the same way, van Wees et al. (1997) confirmed no accumulation of PR proteins in arabidopsis plants when inoculated with some bacterial strains to induce systemic resistance.

Chapter: 1 Introduction

Fig. 1.2: Signal transduction pathway of ISR and SAR. Adapted from (Vallad and Goodman (2004). Systemic acquired resistance, induced by the exposure of root or foliar tissues to abiotic or biotic elicitors, is dependent of the phytohormone salicylate (salicylic acid), and associated with the accumulation of pathogenesis-related (PR) proteins. Induced systemic resistance, induced by the exposure of roots to specific strains of plant growth-promoting rhizobacteria, is dependent of the phytohormones ethylene and jasmonate (jasmonic acid), independent of salicylate, and is not associated with the accumulation of PR proteins.

1.4.3: Use of Bacterial microbes as elicitors of ISR

To check the efficacy of bacterial bioagents for induction of ISR in plants, scientists carried our various experimentations in lab, green house and field conditions. In a study, Pseudomonas flourescens and Serratia marcescens Bizio were used as seed dressing to protect plants from Cucumber Mosaic Virus (CMV) (Raupach et al., 1996). Significant reduction in disease severity was observed in plants inoculated with these bacterial inducers. In the same way, Murphy and coworkers (2003) carried out experiments to manage tomato mottle virus (TMV) by using PGPR strains belonging to Bacillus and Pseudomonas genera. They used bacterial strains as seed dressings under field conditions. Plants receiving bacterial agents showed more than 50% reduction in disease severity. Furthermore, plants receiving bacterial inducers showed enhanced defense related biochemicals.

Chapter: 1 Introduction

Some bacterial inducers have also been identified as ISR elicitors to control various diseases under field trials. Zehnder et al. (2001) used seed bacteriziation technique under field conditions to induce systemic resistance against cucumber mosaic virus (CMV). Plants receiving bacterial inducers showed 63% reduction in disease severity as compared to un-treated control plants. In the same way, Raupach and Kloepper (2000) observed that use of several bacterial inducers instead of single provide improved control of angular leaf spots and anthracnose of cucumber under field conditions. They provided bacterial formulation containing a combination of bacterial inducers to field grown cucumber plants. These plants were left for subsequent attack of leaf spot and anthracnose pathogens. They observed significant reduction in disease severities for both diseases.

In another field study, Bacillus pumilis Scot was used to control cucurbit wilt disease of cucumber caused by Erwinia tracheiphila (Smith) Bergry (Zehnder et al., 2001). Bacteria were applied as seed treatment. Both treated and non-treated plants were transferred in the fields. In two years test, disease was significantly reduced in treated plants.

A strain of Bacillus viz: B. mycoides, significantly reduced cercospora leaf spot disease of sugar beet under field conditions (Bargabus et al., 2002). This strain provided up to 91% reduction in disease as compared to untreated control. The level of disease reduction provided by B. mycoides was comparable with fungicide triphenyltin hydroxide which is commonly used to control cercospora leaf spot disease.

In a research work, Jetiyanon and Kloepper (2002) used mixture of Bacillus strains for elicitation of ISR under field conditions. It was observed that Bacillus strains used in mixture protected against disease in a more consistent way than did a single strain. In two seasons experiments, mixture of Bacillus amyloliquefaciens Priest and B. subtilis (Ehrenburg) Cohn provided remarkable protection against all diseases under observations viz: CMV of cucumber, southern blight of tomato and anthracnose of pepper. Two bacterial strains P. putida Trevisan and B. subtilis were incorporated in soilless media against late blight disease caused by Phytophthora infestans (Yan et al., 2002). Plants receiving bacterial inducers showed significant reduction in disease along with enhanced production of defense related biochemicals.

Chapter: 1 Introduction

Bacillus subtilis formulated in chitosan induced systemic resistance in CMV under greenhouse conditions (Murphy et al., 2003). Cucumber plants were treated with this bacterial formulation and were subsequently challenged with pathogen. This bacterial treatment provided significant protection against disease severity by showing more than 50% reduction in disease severity. In-vitro study was carried out by Sharma et al. (2003) using a strain of pseudomonas against pre and post emergence damping off caused by Pythium aphanidermatum (Edson) Fitzipand and Phytophthora nicotianae Breda de Haan, in tomato and chilli. This single strain impaired significant reduction in disease severity caused by both pathogens in chilly plants. Disease reduction was compare able in case of both pathogens. In another study, Bacillus cereus Frankland and Frankland caused significant reduction in early blight of tomato when inoculated onto tomato seeds (Silva et al., 2004). Up to 60% reduction in disease severity was noted under field conditions.

Li et al. (2008) carried out a study to manage bacterial wilt of tomato by using Bacillus subtilis, as control agent. Tomato plants primed with this bacterial strain provided more than 70% reduction in disease incidence as compared to pathogen control plants. This strain also elicited tomato plants for higher production of different defense related biochemicals. Time course studies showed higher levels of H2O2 and different defense related enzymes in tomato plants receiving B. subtilis.

In 2006, a study was carried out by Harish et al. They used a mixture of bacterial strains belonging to Bacillus and Pseudomonas genera to manage banana bunchy top virus. Bio-formulation of these bacterial microbes was applied in rhizosphere of banana plants. Researchers observed more than 80% reduction in disease severity under greenhouse and 52% reduction in disease under field conditions (Harish et al., 2006).

A greenhouse study was carried out by Anitha and Rabeeth (2010) to manage fusarium wilt of tomato. They used Streptomyces griseus Waksman and Henrici, as a bio-control agent. When tomato plants were treated with bacterial strain in the form of root-dipping, a significant decrease of 63% was observed in fusarium wilt disease severity. In the same year, Sankari et al. (2010) used Pseudomonas flouresence to manage root knot nematodes Meloidogyne incognita Frankland and Frankland. Soil application of this bacterial strain provided significant protection levels against root

Chapter: 1 Introduction knot nematodes. Highest accumulation of chitinase was observed in host plant cells that restricted penetration of nematode in root tissues.

In another study, non-pathogenic pseudomonas strains were used to protect grapevine against Botrytis (Bas et al., 2010). Grapevine seedlings were primed with two pseudomonas strains viz: P. fluorescens and P. aeruginosa followed by pathogen challenge. Bacterial treated plants showed up to 50% reduction in disease. This disease reduction was associated with enhanced defense related compounds in plants which were induced by bacterial strains (Bas et al., 2010). In the same year, a study was carried out by Fu et al. (2010). They used Bacillus subtilis to control banana leaf spot disease caused by a complex of fungal pathogens. They carried out both greenhouse and field studies. Bacterial strain was provided in soil in both studies. Results showed 72% reduction in disease index in greenhouse studies. In the same way up to 48% reduction in disease index was recorded under field studies in consecutive experiments.

In a study carried out by Jung et al. (2011), soybean plants were treated with Pseudomonas aureofaciens Kluyver to induce resistance against Rhizoctonia solani G J Kuhn. Pseudomonas aureofaciens significantly suppressed damping-off symptoms caused by Rhizocotonia solani JG Kuhn. In 2012, Khan et al. used Paenibacillus lentimorbus (Dutky) Pettersson to control early blight disease in tomato. In this greenhouse study, foliar application of bacterial strain was provided to tomato plants which significantly suppressed disease parameters under observation. Furthermore, plants receiving bacterial inducers provided higher expression levels of defense related genes which was attributed in terms of induced systemic resistance.

Kurabachew and Wydra (2013) carried out a study to induce systemic resistance in tomato plants against bacterial wilt disease. They treated tomato plants with different bacterial inducers belonging to Bacillus and Pseudomonas genera in split root trial. Among different strains, B. cereus and P. putida Trevisna performed best and showed up to 48% reduction in bacterial wilt incidence.

In a recent research work carried out by Mei et al. (2014), a bacterial strain Paenibacillus polymyxa (Prazmoviski) Ahn was shown to induce systemic resistance in tomato plants against fusarium wilt disease. In greenhouse experiment, tomato plants were inoculated with P. polymyxa and challenged with fusarium wilt pathogen.

Chapter: 1 Introduction

This bacterial strain suppressed disease incidence up to 60% and showed significant increases in activities of different defense related biochemicals inside tomato plants. In another research work carried out by Sang et al. (2014), two bacterial strains Pseudomonas azotoformans L Izuka and Komagata and Paenibacillus elgii successfully induced systemic resistance in cucumber against leaf spot disease caused by Colletotrichum orbiculare Berk & Mont. Arx. Both of these strains were provided in the form of root treatment. These strains elicited ISR in cucumber plants and significantly reduced disease incidence in cucumber plants. As a result of root priming, production of different defense related proteins was significantly up- regulated in cucumber plants.

1.4.4: Bacterial determinants of ISR

Microbial communities are present in huge numbers on the root surface of plants because plant exudates provide them with foods (Lynch and Whipps, 1991). Many bacterial strains can directly antagonize plant pathogens (Bakker et al.,1991; Wei et al., 1996). If we want to prove phenomenon of ISR by any microbe, it would remain separated from pathogen to prevent direct antagonism with pathogen. During interaction of microbial inducer and host plant, microbe would produce one or more elicitors of ISR. These elicitors must then be perceived by receptors present on plant surface.

Several biochemicals in bacteria are responsible for elicitation of defense response in plants (Table 1.2). In elicitation of systemic resistance in carnation plants against fsuarium, lipopolysachrides of Pseudomonas flourescens were found to be most effective in triggering pant defense responses (van Peer and Schippers, 1992). This indicates the role of lipopolysachrides of bacterial strain as determinants of ISR in plants. Same biochemicals have also found effective for induction of systemic resistance in radish (Leeman et al., 1995). In the same way, cell wall extracts of P. flourescens or purified lipopolysaccharides have been reported equally effective for ISR in reddish. Bacterial mutants for lipopolysaccharide production were unable to elicit ISR. These results prove the role of bacterial lipopolysaccharides determines the ISR. Plants can perceive lipopolysaccharides by both roots and aerial parts.

These bacterial lipopolysaccharides also aid in growth and survival of bacterial organisms inside plants by aiding in several mechanisms (Newman et al.,

Chapter: 1 Introduction

1995). These mechanisms include colonization, acting barrier to plant defense mechanisms and by modifying certain biochemical pathways of host plant (Newman et al., 1995). Siderophores also act as determinant of ISR produced by certain bacterial strains. These are produced inside bacterial cells under low iron conditions. Purified siderophores of P. fluorescence induced systemic resistance in radish plants at the same level as lipopolysaccharides did (Leeman, 1996).

Certain bacterial strains are capable of production of salicylic acid (SA) as an extra siderophores (Meyer et al., 1992; Visca et al., 1993). Pseudomonas fluresences induced systemic resistance in tobacco that was because of production of SA by that bacterial strain (Maurhofer et al., 1998). In the same way, P. aeruginosa that was unable to produce SA, failed to induce ISR in bean and tobacco plants (De Meyer and Hofte, 1997). But when strain of same bacterial species were applied that were capable of SA production, resistance was induced effectively in plants. Studies also demonstrate that ISR in plants is triggered only by SA produced by bacterial strains which leads to the activation of SA dependent-SAR pathway. Bacterial strains unable to produce SA can only trigger SA-independent SAR pathway (Pieterse et al., 1996 and 1998; Press et al., 1997).

It has also been shown that some plants have sensitive perception system for bacterial proteins “Flagellins” (Felix and Boller, 2003). In a recent research work, a flagellinin protein receptor of arabidopsis worked as a kinase receptor having similarity with plant pathogen resistance related genes (Gomez-Gomez and Boller, 2002). These results indicate that bacterial flagella can elicit plant defense response (Leeman et al., 1995; van Wees et al., 1997). Recently it is discovered that N-Acyl homoserine lactones are also involved in ISR mediated by bacteria which stimulate chalcone synthase in plants (Mathesius et al., 2003). Volatile organic compounds may play a significant role in enhanced protection in plants against diseases (Ping and Boland, 2004; Ryu et al., 2004). This was confirmed by studying ISR mediated by volatile compounds secreted by Bacillus subtilis and B. amyloquefaciens (Ryan et al., 2001).

Chapter: 1 Introduction

Table 1.2: Bacterial determinants of induced systemic resistance for different plant species.

Bacteria Plant specie Determinants References

Bacillus cereus C1L Corn Dimethyl Disulfide Huang et al., 2012 Pseudomonas putida WCS 358 Arabidopsis LPS, Siderophore, Meziane et al., Flagella 2005 Bacillus sp. BS107 Tobacco 2-Aminobenzoic acid Yang et al., 2011 Pseudomonas putida BTP1 Bean N-alkylated Ongena et al., 2005 Benzylamine B. amyloliquefaciens IN937a Arabidopsis 2,3-butanediol Ryu et al., 2004 B. subtillis GB03 Arabidopsis 2,3-butanediol Ryu et al., 2004 P. fluorescens GRP3 Rice Siderophore Pathak et al., 2004 P. fluorescens WCS 374 Arabidopsis LPS Weller et al., 2004 P. fluorescens CHA0 Arabidopsis 2,4 DAPG Iavicoli et al., 2003 Rhizobium etli G12 Potato LPS Reitz et al., 2002 P. aeruginosa 7 NSK2 Bean SA De Meyer et al., 1997 P. fluorescens Q2-87 Arabidopsis 2,4 DAPG P. fluorescens WCS 417 Arabidopsis LPS van Wees et al., 1999 S. marcescens 90-166 Tobacco Fe-regulated Press et al., 1997 compounds

1.5: Plant growth promotion by ISR capable bacteria

A single bacterial strain can harbor multiple beneficial effects for plants. In parallel to disease suppression, plant growth promotion is also observed under influence of bacterial inducers. Bacterial microbes can stimulate plant growth by improving plant nutrition status. Possible mechanisms behind plant growth promotion are by production of plant hormones, increasing host anabolism, controlling plant hormones level and by making certain nutrients available to plants (Mehboob et al., 2008). Figure 1.3 illustrates possible mechanism behind growth promotion by plant growth promoting bacteria.

Some bacterial strains have been previously reported to promote growth of different plants along with protection against different diseases by inducing systemic resistance. Nandakumar et al. (2001) used a formulation consisting of different

Chapter: 1 Introduction bacterial strains for management of sheath blight disease of rice. Along with reduction in disease severity, significant increases were observed in different plant growth related parameters. They also observed more than 23% increase in yield of rice plants under influence of bacterial formulation. This plant growth promoting effect was attributed to different endogenous properties of bacterial strains like phosphorus solubilization and indole acetic acid production.

In 2004, Madhaiyan et al. used different bacterial strains belonging to Methylobacterium genera for growth promotion and induction of resistance in rice plants against sheath blight disease. Inoculation of bacterial strains significantly increased germination rate and seedling vigor or rice plants. The average yield increased up to 24% in rice plants receiving bacterial treatment. In the same ways, same bacterial strains significantly reduced sheath blight incidence in rice plants. Rice plants receiving bacterial strains also showed increased activities of different defense related biochemicals.

Latha et al. (2009) reported increase in growth parameters in tomato plants under influence of some plant growth promoting bacterial strains along with protection against alternaria leaf spot disease. They used different bacterial strains mainly belonging to Bacillus and Pseudomonas genera and observed significant increases in fruit yield in tomato plants that were under influence of bacterial strains. In same type of study, P. fluorescens was shown to promote growth of chilli plants along with induction of systemic resistance against damping-off disease (Muthukumar et al., 2010).

Akila et al. (2011) carried out a study to manage fungal wilt of banana. They observed plant growth promoting abilities of some bacterial strains along with disease protection. Two bacterial strains viz: Bacillus subtilis and Pseudomonas fluorescens significantly increased different growth parameters of banana plants like plant height, stem girth and leaf area. These two bacterial strains also provided significant protection levels against fungal wilt disease under greenhouse experiment. Same types of findings were got in field trials.

A research was carried out by Senthilraja et al. (2013) to elucidate beneficial effects of some rhizospheric bacterial strains on groundnut plants. They treated groundnut plants with bacterial strains and subsequently challenged plants with collar

Chapter: 1 Introduction rot pathogen. Two bacterial strains viz: Pseudomonas fluorescens and Beauveria bassiana (Bals-Criv) Vuill significantly increased germination rate, shoot length, root length and total biomass of groundnut plants. In the same way, these two strains significantly suppressed collar rot disease incidence. In another research work Kurabachew and Wydra (2013) used different bacterial strains for management of bacterial wilt of tomato. These strains were also characterized for plant growth promoting properties. Tomato plants co-cultivated with Serratia marcescens Bizio, Bacillus cereus Frankland and Frankland and Pseudomonas putida Trevisan provided increased total biomass. Furthermore, these bacterial strains were got positive in IAA production and phosphate solubilization.

Fig. 1.3: Schematic illustration of important mechanisms known for plant growth promotion by plant growth promoting bacterial microbes. (Adopted from Ahemad and Kibret, 2014). Different mechanisms can be broadly studied under biofertilization, biocontrol of plant pathogens, N2 fixation, siderophore production and phosphorus solubilization.

Chapter: 1 Introduction

1.6:.Concluding remarks and outlook

1.6.1: Gaps about knowledge of native bacterial strains

As described in this section, by understanding useful aspects of bacterial endophytes, strategies can be design to improve growth and health of plant community. These microbes become very useful when plants are needed to be developed under biotic or abiotic stressful conditions. Hence this beneficial association of plants with these microbes can be seen as highly valuable way of sustainable agriculture. However there is a need to screen native bacterial strains for their ability to improve plants. At the same time, the complexity of interaction between a plant and microbial endophyte is poorly understood. It should be further investigated to get real glimpse of this beneficial relationship.

Moreover, it also appears that available knowledge of bacterial inducers of world community has strong overlaps with our native bacterial strains. Sufficient progress have not been made in past in describing community structure and usefulness of our own bacterial endophytes. In the same way, there is dearth of studies that precisely elucidate the mechanism of interaction between a specific bacterial strain and host plant under a specific type of stress.

1.6.2: Applied aspects of beneficial bacterial strains

It becomes clear from previously described material that plant protection provided by induction of systemic resistance is an effective and simple approach of disease management. This approach also reduces use of harmful agrochemicals. There are several limitations including the stability, duration of induced systemic resistance, efficacy of such formulations under commercial conditions and their stability under field conditions. In spite of these limitations, advances in understandings about the phenomena of ISR proves great potential of its use in near future.

Chapter: 1 Introduction

1.7:.Aims and objectives

The main objective of this study was to search native Bacillus strain having potential to induce systemic resistance in plants against fusarium wilt of tomato and to elucidate mechanism behind ISR. These objectives were achieved by following steps:  Screening of virulent strains of Fusarium oxysporum f.sp. lycopersici and tomato varieties with varying susceptibility against Fol.  Screening of native Bacillus strains for induction of systemic resistance in tomato against Fol.  Testing field efficacy of best performing bacterial strains.  Checking efficacy of best performing bacterial strains for tomato growth potentials.  Elucidation of biochemical, histological and molecular mechanism behind ISR phenomenon.  Searching potential ISR determinants from best performing bacteria.

Chapter: 2

& METHODS

MATERIAL

Chapter: 2 Material & Methods

2.1:.Selection of most virulent pathogen isolate and susceptible tomato varieties against fusarium wilt

This experiment was performed for selection of most virulent Fusarium oxysporum f.sp. lycopersici (Fol) strain and tomato varieties with different susceptibility levels against fusarium wilt disease. Fol strains were isolated from fields and identified with both morphological and molecular techniques. Germplasm of tomato was screened for their susceptibility against these different Fol strains and selection was made for further research work. 2.1.1:.Screening of tomato varieties against fusarium wilt

2.1.1.1: Pathogen isolation

Strains of F. oxysporum f.sp. lycopersici (Fol) were isolated from infected tomato plants. For isolation purpose root samples of ten naturally infected wilted plants showing vascular browning (Fig. 3.1 A) were collected from the Vegetable Research Farm, University of the Punjab and from tomato field form District Kasur of Punjab Province, Pakistan in the March and April months of the year 2011. Infected roots were surface sterilized in 1% sodium hypochloride solution followed by washing in sterilized distilled water. These infected roots were excised into small pieces, plated on PCNB Dextrose Agar media (Appendix 1) and incubated at 35oC until small colonies appeared. Fungal colonies were purified by successive transformation on Potato Dextrose Agar (PDA) (Appendix 1). Purified fungi were identified according to their morphological and microscopical characters viz; colony color, conidial shape and size etc. as described in fusarium identification key prepared by Jens et al. (1991) (Fig. 3.1 C and D). This identification was re-confirmed by using specie specific primer in PCR reaction as described in section 2.1.3. These Fol strains were preserved on PDA media in glass culture tubes at 4oC.

2.1.1.2: Molecular identification of Fol.

Identification of Fol isolates was further confirmed by molecular techniques. For this purpose Fusarium oxysporum specific primers were used. For fungal mass

Chapter: 2 Material & Methods cultivation, 2% Malt Extract broth media was made and inoculated with fungi for each strain separately. After two weeks of incubation at 35oC, fungal mats were taken and dried at 50oC overnight in hot air oven. Next day, fungal DNA was extracted by using Enzynimics DNA extraction kit (Korea) according to provided methodology. DNA quality was checked on 1% Agarose gel. PCR was carried with Fol specific primers i.e. FOF1 5P-ACATACCACTTGTTGCCTCG-3P and FOR1 5P- CGCCAATCAATTTGAGGAACG-3P (Edel et al., 1995). Amplifications were carried out in 20 µL reaction mixture (Appendix 2). Temperature conditions for PCR reaction are provided in Table 2.1.

Microfuge vials were placed on a PCR thermal cycler (PLT-06, MEERAD Pakistan). After PCR procedure, samples were stored at 4oC. PCR products were envisioned on 1% agarose gel. Presence of single band at approximately 700 bp confirmed identification of isolated fungi as Fusarium oxysporum (Fig 3.1 E).

Table 2.1: Temperature conditions for PCR reaction carried out for Fol identification.

Step Temperature (oC) Duration No of Cycles Initial denaturation 95 4 min 1 Denaturation 95 1 min Annealing 50 40 sec Elongation ]36 72 1.5 min

Final extension 72 15 min 1 Hold 4 60 min 1

Chapter: 2 Material & Methods

2.1.1.3: Preparation of pathogen inoculum

Fusarium oxysporum f.sp. lycopersici (Fol) strains were inoculated on PDA media (Appendix 1) in Petri-plates separately. After one week of incubation at 35oC, spore suspensions were prepared for each Fol strain in distilled sterilized water. Suspensions were sieved by muslin cloth and concentration was adjusted with the help of haemocytometer for each strain at 3000 spores/mL.

2.1.1.4: Greenhouse experiment

A greenhouse experiment was performed to screen tomato varieties against fusarium wilt disease. For that experiment twenty three tomato varieties were used (Table 3.2). Seeds of these tomato varieties were procured from Federal Seed Certification and Registration (FSC & RD) Pakistan. Ten isolates of Fol viz (Fol1 to Fol10) were used for screening purposes. Seedlings of all varieties were grown on sterilized peat moss in plastic pots under controlled conditions. Plastic pots of four inch diameter were purchased. These were filled with 0.5 Kg sterilized sandy loamy soil. Each pot was provided with 50 mL of Fol inoculum. Initially three seeds were sown in each pot that was thinned to one healthy seedling upon emergence and left for incubation. Each combination contained five replicate pots.

2.1.1.5: Scoring of wilting and disease index

Three plants aere randomly selected from each treatment. Scoring of wilting was performed by criteria developed by Epp (1987) (Table 2.2).

Table 2.2: Scoring of wilt symptoms in tomato. Score Wilting condition 0 No wilt symptoms 1 Less than 25% plant parts turned yellowish 2 Yellowing and browning covered less than 50% of plant 3 Whole plant turned brown and died

Chapter: 2 Material & Methods

Following equation was used to calculate disease index (DI):

DI = [(Σni × si)/(N × S)] × 100

Here, ni: number of tomato plants with wilt symptoms, si: value of the score of symptoms, N: total number of tested tomato plants, and S: the highest value of score of symptoms (Cachinero et al., 2002).

Overall responses of the tested tomato varieties against fusarium wilt was established using the following criteria: if the value of DI is equal to 0%; immune; if 1- 20%; resistant, if 21-40%; moderately susceptible, if 41-70%; susceptible, if 71- 100%; and very susceptible (dan-Sudarsono et al., 2004).

2.1.2: Genetic fingerprinting of Fol isolates by ISSR markers

Genomic DNA from fungi was extracted by using Enzynomics DNA extraction kit (Korea) according to the provided methodology. Sequences of ISSR primers used in this study are described in Table 3.1. For PCR amplifications, 2X nTaq PCR reaction mixture was used provided by Enzynomics® Korea. Amplifications were performed in a 25 µL reaction volume. PCR reaction was performed in a 96-well Asco PCR. Temperature conditions used in PCR reaction are described in Table 2.1 with an exception of annealing temperature that was kept 45-52oC. PCR product was electrophoresed on 1.5% agarose gel in TAE buffer at 100V. Bands were visualized on gel and scored as present (1) or absent (0). Dendrogram was constructed by using Single Linkage Euclidean Distance method with the help of MYSTAT® program.

Chapter: 2 Material & Methods

2.2:.Screening of Bacillus strains capable of inducing resistance in tomato against fusarium wilt under split root system

This experiment was performed to screen our native Bacillus strains for their ability to induce systemic resistance, irrespective of the antagonism ability of these strains against Fol. Native rhizospheric Bacillus strains were obtained from bacterial conservatories of two institutes of University of the Punjab, Lahore, Pakistan. To prove effectiveness of our hypothesis, three tomato varieties were used with varying susceptibility against fusarium wilt. On the basis of split root experiment, most efficient strain was selected. In ISR process, split root layout is used to avoid antagonism between pathogen and inducer. These studies were also extended to the elucidation of biochemical basis of induced systemic resistance in a separate experiment. 2.2.1:.Potential of Bacillus strains to manage fusarium wilt under split root system

2.2.1.1: Selection of biological material

Split root design was used to check ability of microbial strains to specifically induce systemic resistance. Lay out of split root system is described in figure 2.1. Three susceptible tomato verities viz; ‘Fine Star’, ‘Rio Grande’ and ‘Red Power’ with varying susceptibility against fusarium wilt and most virulent Fol strain i.e. (Fol 7) was used in this experiment. These were selected based on the results of previous experimentations.

Native non-pathogenic rhizospheric Bacillus strains were procured from Bacterial Conservatory of Institute of Agriculture Sciences, University of the Punjab Lahore and Bacterial Conservatory of Institute of Microbiology and Molecular Genetics, University of the Punjab Lahore. All the strains were maintained on Luria Broth agar (LB) media in culture tubes at 4oC for further experimentation. Details of these bacterial strains used in this study are provided in Table 2.3.

Chapter: 2 Material & Methods

Table 2.3: Details of native Bacillus strains used in this study.

No Bacterial specie Strain NCBI Accession no 1 B. fortis IAGS324 KM99038 2 B. fortis IAGS223 KM99040 3 B. fortis IAGS162 KM99037 4 B. thuringiensis IAGS199 KM99039 5 B. thuringiensis IAGS002 KM99041 6 B. subtilis MCR7 JF894160 7 B. subtilis IAGS170 KM99036 8 B. subtilis IAGS174 KM99035 9 B. subtilis FBL10 KM99034 10 B. megaterium ZMR3 JF894163 11 B. megaterium ZMR4 JF894164 12 B. megaterium ZMR6 JF894165 13 B. megaterium MCR8 JF894161 14 B. megaterium OSR3 JF894162

Fig. 2.1: Split root design used to screen Bacillus strains against fusarium wilt disease.

Chapter: 2 Material & Methods

2.2.1.2: Development of tomato seedlings Tomato seedlings were raised in sterilized sandy loam in 14 inch diameter plastic pots under greenhouse conditions. These pots were provided with water whenever needed. After three weeks of emergence, these seedlings were subjected to further experimentations.

2.2.1.3: Preparation of fungal inoculum

Pertriplates containing Potato dextrose agar (PDA) media were prepared. Fusarium oxysporum strain ‘Fol 7’ was inoculated onto these plates and kept for incubation at 35oC for one week. After one week of incubation, spores were harvested in distilled sterilized water. Concentration of spore suspension was adjusted to 3000 spores/mL with the help of haemocytometer. This spore suspension was kept at 4oC for further use.

2.2.1.4: Preparation of bacterial inoculum

LB broth media was prepared in conical flasks and inoculated with bacterial strains separately. These flasks were incubated for 24 hours at 35oC. Media containing bacterial growth was centrifuged at 4000rpm for 15 minutes and pellet was resuspended in sterile distilled water. Concentration of inoculum was adjusted to 107-8 cfu/mL by taking OD of 0.8 at 600nm (Park et al., 2013). This inoculum was used for further experimentation.

2.2.1.5: Split root experiments Split root experiment was performed to screen bacterial strains capable of inducing systemic resistance. Layout of split root design is shown in figure 2.1. Details of treatments are provided in Table 2.4. Previously prepared inoculum of Bacillus inducers and fusarium wilt pathogen were provided in allotted pots at rate of 50 mL each. Pots were kept in green house for incubation. Each treatment was replicated thrice and each replicate included fifteen plants. These pots were provided with distilled sterilized water whenever needed.

Chapter: 2 Material & Methods

2.2.1.6: Harvest

Harvest was taken after thirty days of inoculation. Disease index was calculated by using same formulae as described in section 2.1.1.5. Biocontrol effect was sorted out according to the formula provided by Li et al. (2008).

Biocontrol effect (%) = (Disease index of pathogen control- diseased index of bacterial control) x100 Disease index of pathogen control

Table 2.4: Details of treatments for split root experiment.

Treatment Inducer side Responder side T1 B. fortis IAGS 324 Fol7 T2 B. fortis IAGS 223 Fol7 T3 B. fortis IAGS 162 Fol7 T4 B. thuringiensis IAGS 199 Fol7 T5 B. thuringiensis IAGS 002 Fol7 T6 B. subtillis MCR7 Fol7 T7 B. subtillis IAGS 170 Fol7 T8 B. subtillis IAGS174 Fol7 T9 B. subtillis FBL10 Fol7 T10 B. megaterium ZMR-4 Fol7 T11 B. megaterium ZMR-6 Fol7 T12 B. megaterium ZMR-3 Fol7 T13 B. megaterium MCR-8 Fol7 T14 B. megaterium OSR-3 Fol7 Pathogen control Dist. Sterilized water Fol7 Dist. Sterilized Non-treated Control Dist. Sterilized water water

2.2.2:.Analysis of changes in defense related biochemicals in tomato plants under influence of Bacillus strains

Another independent split root experiment was performed as described in section 2.2.1.5. Here also pathogen inoculum was provided in responder side of roots. Inducer side received 50 mL of respected bacterial inoculum was provided as described in section 2.2.1.5. Biochemical basis of resistance were elucidated by quantification of total phenolics and enzymes involved in ‘Phenylpropanoid’ pathway viz: Peroxidase (PO),

Chapter: 2 Material & Methods

Poly phenoloxidase (PPO) and Phenylalanine ammonia-lyase (PAL). Assays were performed in a time course manner. Three plants were randomly selected. Sampling was done during morning hours. Roots samples of responder sides were taken for assays. Roots were excised into small pieces and then placed into labeled polythene bags separately after drying in between two layers of blotting paper and carried to the laboratory.

2.2.2.1: Quantification of total phenolics

Phenolic compounds provide front line of defense against plant pathogens. Quantification of total phenolic compounds was performed by using method of Zieslin and Ben–Zaken (1993). For that purpose, one gram root samples were homogenized in water: methanol (20:80) solution and agitated for 15 min at 70oC. This solution was passed through filter paper and collected in a new flask. Five mL of distilled water was taken in a clean test tube. Further 1 mL of methanolic extract and 250 µL of 50% Folin Ciocaltueau reagent was added inside this tube and kept for incubation in dark for half an hour. After half an hour, 1 mL of 50% solution of sodium carbonate was added and incubated for further 10 minutes inside dark. After incubation, absorbance was measured using spectrophotometer at 725nm. Standard curve was drawn using Catechol. Quantity of total phenolics was given as ‘µg catechol mg-1’ by comparing with standard curve.

2.2.2.2:.Quantification of enzymes involved in phenylpropenoid pathway

Phenylpropenoid pathway is responsible for production of numerous defense related biochemicals inside plant body. Different enzymes involved in phenylpropenoid pathway including Peroxidase (PO), Polyphenoloxidase (PPO) and Phenylalanine ammonia lyase (PAL) are considered as biomarkers to observe induction of systemic resistance.

To quantify these enzymes, 1 g of washed root sample was taken and crushed in pre-chilled mortar containing five mL of ice cold 100 mM phosphate buffer (pH 7.0) (Appendix 1). After crushing, whole material was transferred inside falcon tube and

Chapter: 2 Material & Methods centrifuged at 5000 rpm for 15 min at 4oC. Upper clear supernatant was collected inside new tube and used for enzyme quantifications.

2.2.2.3: Quantification of Peroxidases

Peroxidase (PO) is very important enzyme of plant defense system, having major role in lignin, suberin and phytoalexin synthesis. Peroxidase activity was measured by using method of Fu and Huang (2001). Guaiacol was used as substrate. For that purpose, 10 mL of 10 mM sodium phosphate buffer (Appendix 1) (pH 6.0) was taken in clean glass tube. In this tube, 250 µL of guaiacol and 100 µL of hydrogen peroxide were mixed. At the end, 3 mL of enzyme mixture was added and kept for five minutes at room temperature for incubation. After incubation, absorbance was taken at 470 nm. Peroxidase activity was expressed as ∆470nm/g fresh wt/minute.

2.2.2.4: Quantification of Polyphenoloxidases

Polyphenoloxidase (PPO) enzymes play role in formation of quinones, which are plant defense related biochemicals. Polyphenoloxidase activity was measured by using method of Mayer et al. (1965). In this method, catechol is used as substrate to measure enzyme activity. To make reaction mixture, 1.5 mL of 10 mM sodium phosphate buffer (pH 6.0) (Appendix 1) was poured in a clean glass tube. To this solution 150 µL of 0.1M catechol solution was added and mixed. At the end, 200 µL of enzyme mixture was added and kept for incubation at room temperature for one hour. After one hour, absorbance was taken at 495 nm. PPO activity was denoted as ∆495 nm min-1mg-1 protein.

2.2.2.5: Quantification of Phenylalanine ammonia lyase

Phenylalanine ammonia lyase (PAL) enzyme plays its role in converting L- phenylalanine to trans-cinnamic acid. Burrell and Rees (1974) method was used to measure PAL activity in the presence of L-phenylalanine as substrate. For that purpose, 2.5 mL of sodium borate buffer (pH 8.8) (Appendix 1) was taken in a clean glass tube. Inside this, 250 µL of 0.3 M solution of L-phenylalanine solution was added. To initiate reaction, 200 µL of reaction mixture was added and kept at incubation for one hour at room temperature. After one hour, 0.5 mL of 1.0 M trichloro acetic acid solution was

Chapter: 2 Material & Methods added. Absorbance was noted at 290 nm and enzyme activity was expressed as µg of trans-cinnamic acid h-1mg-1 protein.

2.2.3:.Isozyme analysis of Peroxidase and Polyphenoloxidase

To observe qualitative changes in defense system induced inside plant body, isozyme analysis of PO and PPO was performed by Native PAGE analysis. Enzymes were extracted by crushing one gram of plant root sample in 4 mL of 100 mM sodium phosphate buffer (Appendix 1) (pH7.2). Material was centrifuged at 15000rpm for 15min at 4oC and supernatant was collected in sterilized tube.

Electrophoresis was performed in 7.5% Native Polyacrylamide resolving gel (Appendix 3). Forty microliters of supernatant was loaded mixed with 1x Native PAGE loading buffer (Appendix 3). Gel was run at 150 volts for one hour in tris glycene native PAGE buffer (Appendix 3) (Goldenberg, 1989).

Peroxidase isozymes were seen by placing gel in 10 mM sodium phosphate buffer (pH 6.0) (Appendix 1) containing 0.25% guaiacol reagent few drops of of hydrogen peroxide until bands were observed. Polyphenol oxidase isozymes were visualized by incubating gels in 100mM acetate buffer (pH 6.0) (Appendix 1) containing 0.03 M catechol for one hour.

2.2.4: Data analysis

The statistical analysis was performed by One-way ANOVA (P = 0.05) using computer aided software “DSASTAT” (Onofri Italy). Subsequently Duncan’s new multiple range tests was applied to the data set to test the significance of difference between the treatments (P < 0.05).

Chapter: 2 Material & Methods

2.3:.Elucidation of molecular, histological and biochemical basis of ISR mediated by Bacillus strains against fusarium wilt of tomato

Experiments were designed to dissect molecular, histological and biochemical basis of resistance in tomato induced by our best strains viz: B. fortis IAGS162, and B. subtilis IAGS174 following pathogen challenge. In these experiments a susceptible tomato variety ‘Fine Star’ was used as representative variety. Tomato plants were provided with selected Bacillus strains and fungal wilt pathogen. To elucidate molecular basis of resistance, time course gene expression analysis was performed by RT-PCR analysis and comparisons were made among control and bacterial treated plants. Histological studies were performed by observing physical defense barriers under microscope after bacterial and pathogen inoculation. For biochemical basis of resistance, GC/MS analysis of whole metablome of both bacterial treated and control tomato plants was carried out and changes were interpret in the form of heat maps and metabolic pathways.

Seedlings of tomato variety ‘Fine Star’ were developed in sterilized sandy loam soil media. Plastic pots of 6 inch diameter were filled with sterilized sandy loam soil as growth media. Tomato seedlings were transplanted in these pots after three weeks of emergence at the rate of one seedling per pot. Inoculum of both bacterial strains B. fortis IAGS162, and B. subtilis IAGS174 was prepared separately as described in section (2.2.1.4) and was provided in a quantity of 50 mL each. Control treatments got 50mL of distilled sterilized water. After two days, each pot received 50 mL pathogen inoculum in the form of conidial suspension prepared as described in section (2.2.1.3). Plants were kept in green house for incubation. Experiment was performed in triplicates and each replicate was consisted of fifteen plants.

Chapter: 2 Material & Methods

2.3.1:.Elucidation of molecular basis of resistance induced by selected Bacillus strains against fusarium wilt

Pathogenesis related (PR) proteins play crucial role in inducible defense system of plants. Expression of PR protein genes is considered as molecular marker for observation of ISR phenomenon. RT-PCR is a widely used technique to assess changes in expression levels of different genes. Changes in expression of different pathogenesis related genes including PR1, PR2, PR3, PR5 and PR7 were analyzed by using this technique. For that purpose, root samples of both treated and control tomato plants were taken at 0, 1, 2 and 4 days after pathogen inoculation and subjected to RT-PCR analysis.

2.3.1.1: RNA extraction

RNA extraction was performed by using Triazole reagent. One hundred mg plant root material was crushed in liquid nitrogen. This material was transferred into sterilized 1.5 mL centrifuge tubes and 1 mL Triazole reagent was added in it. Tubes were vortexed to ensure mixing of material and incubated for 5 minutes at room temperature. After incubation, centrifugation was performed at 12000 rpm for 15 minutes at 4oC. Resulting supernatant was poured in a new sterilized tube. Chloroform (0.2 mL) was added to the supernatant and incubated for two minutes at room temperature. Afterwards, sample was centrifuged at 12000 rpm for 15 minutes at 4oC. Upper aqueous phase was transferred to a new tube. Equal amount of isopropyl alcohol was then added in this tube for RNA precipitation. Again incubation was performed at room temperature for ten minutes. Samples were centrifuged at 12000 rpm for 10 minutes at 4oC to settle down RNA. RNA pallet was washed with diluted ethanol. Sample was centrifuged at 7,500 rpm for 5 minutes and supernatant was discarded carefully. RNA pallet was air dried for 5 minutes and re-dissolved in Diethylpyrocarbonate (DEPC) treated water for further use.

2.3.1.2: RNA quantity and quality estimation

The concentration of RNA was assessed spectrophotometrically by taking absorbance at 260nm. To test the quality of RNA samples were mixed with RNA loading dye (Appendix 2) and electrophoresed on 0.8 per cent agarose gel in 1x TAE (Appendix

Chapter: 2 Material & Methods

2) amended with 1 mL of 37% formaldehyde and 3 µL of 0.1% ethidium bromide solution (Appendix 2).

2.3.1.3: RT-PCR analysis

RT-PCR analysis was performed to analyze changes in expression of pathogenesis related (PR) gene in the presence of a house keeping gene. Samples were firstly calibrated to final concentration of 100 ng/µL of RNA. Sequences of primers are provided in table 2.6.

M-MLV cDNA synthesis kit provided by Enzynimics Korea was used according to the provided instructions. Single stranded cDNA was prepared by using random hexamer primers. Reaction mixture recipe is provided in (Appendix 2). Reaction was performed at 37°C for two hours. Process was stopped by increasing temperature at 70oC for few minutes.

In next step, double stranded DNA was synthesized by using single strand of cDNA as a template in the presence of gene specific primers. Composition of reaction mixture is provided in (Appendix 2). PCR cycles temperature conditions are provided in table 2.5.

2.3.1.4:.Quantification of amplified products

Quantification of amplified genes was performed by adopting methodology of Wang et al. (2006). For that purpose, the resultant products were electrophoresed on 1% agarose gel in 1X TAE buffer (Appendix 2) and stained with ethedium bromide. Ten microliters from each tube was mixed with 2x of RNA loading dye (Appendix 2) and loaded onto agarose gel. Electrophoresis was performed at 100 volts using 1 x TAE buffer (pH 8.0) (Appendix 2). Photographed of gels were taken by gel documentation system of Daihon, Korea. Quantifications of PCR products were estimated using the Gel Analyzer1-D analysis software (Fig. 3.12). Fold change in defense related genes expression was calculated with following equation devised by Schnable Lab, Iowa State University USA.

QTarget ∆Q (Target)(Control−Treated) Fold change in expression = QRef ∆Q Ref (Control−Treated)

Chapter: 2 Material & Methods

Here Q represents quantity of amplified products as provided by ‘Gel Analyzer’ software. Target= defense related gene under observation, Ref= “Acting” gene that was used as internal amplification control.

Table 2.5: Temperature conditions of PCR cycles for amplification of single stranded cDNA.

Step Temperature (oC) Duration No of Cycles Initial denaturation 95 4 min 1 Denaturation 95 1 min Annealing 40-55 60 sec 36 Elongation 72 1.5 min ]

Final extension 72 15 min 1 Hold 4 60 min 1

Table 2.6: List of defense gene primers for RT-PCR analysis.

Chapter: 2 Material & Methods

2.3.2:.Elucidation of histological and histochemical basis of resistance induced by selected Bacillus strains against

fusarium wilt

Different selective staining techniques have been established to study change in histology and histochemistry of plants under influence of any stimulus. Tomato plants were selected randomly from both treated and control plants after one week of pathogen challenge, to carry out histological and histochemical observations. Both root and shoot sections were stained. For roots, soil was washed from roots and central root was selected for these analyses.

2.3.2.1: Sample preparation

Fine sections of central root were prepared by sharp razor blade from both treated and control tomato plants. These sections were fixed in FAA (Formaldehyde, Glacial Acetic Acid and Ethyl Alcohol (1:1:18) for 24 hours and then stored in ethanol 50% as described by Kraus and Arduin (1997). Sections were clarified by dipping in 50% sodium hypochlorite solution followed by washing with distilled water to remove the excess reagent. These sections were placed in 1% acetic acid solution to neutralize the hypochlorite effects and were washed once more, concluding the process.

2.3.2.2: Histological analysis

Microscopic observations were performed on free hand sections according to the method of Mouzeyar et al. (1993). Lignin deposition was studied by phloroglucinol HCl method. Peroxidase was stained by dipping sections in 0.1% guaicol reagent in the presence of H2O2.

2.3.2.3: Staining of lignin components

Lignin staining was performed according to the method of (Nakano and Meshitsuka, 1992). Previously prepared sections of fresh samples were dipped in a few drops of 1% phloroglucinol solution in 95% ethanol on a glass slide. Afterwards these

Chapter: 2 Material & Methods sections were treated with 1 drop of 35% HCl. With this process, lignin containing coniferyl aldehyde structures achieves a purple-red color and guaiacyl lignin a dark- brown color.

2.3.2.4: Staining of phenolic compounds

Phenolics were stained by using FeCl3 as described. For that purpose, sections were immersed in 10% FeCl3 solution followed by washing with distilled sterilized water. These sections then were observed under microscope.

2.3.2.5: Staining of peroxidase

Peroxidase contents were stained by using guaicol reagent. Plant sections were placed in 1% solution of guaicol reagent in 100mM sodium phosphate buffer (pH 7) containing a few drops of hydrogen peroxide. After one hour of incubation, sections were observed under microscope for development of brown coloration.

2.3.3: Elucidation of biochemical basis of resistance induced by

selected Bacillus strains against fusarium wilt

GC/MS is widely used technique that can provide us a detailed image of metabolites in any living system. Like previous experiment, control and treated tomato plants were selected randomly after one week of pathogen challenge to elucidate metabolomics basis of resistance.

2.3.3.1: Extraction of metabolites

Metabolite extraction was performed by using youngest leaves. One gram leaf sample was taken from bacterial treated and control plants individually. Leaf samples were grinded in liquid nitrogen. This powdered material extracted by using 10 mL of extraction solvent consisting on methanol, chloroform and water mixed in a ratio of 80:10:10 respectively. This material was left overnight for extraction at room temperature. Next day this material was filtered by using micro filters.

Chapter: 2 Material & Methods

2.3.3.2: Derivatization

This technique is used to transform a chemical compound into products similar to its chemical structure. Derivatization of previously extracted plant metabolites was performed by using MOX and MSTFA reagents as described by Warth et al, (2014). Initially 300 µL of previously extracted metabolite sample was taken in glass bottle and aqueous solution of ribitol was mixed in it at known concentration to act as internal standard. This solution was dried with nitrogen gas. After complete drying of liquids, 25 µL of MOX reagent was poured in glass bottle and vortexed briefly. This solution was left overnight at room temperature. Next day, 80 µL of MSTFA was added in this solution and incubated for two hours at room temperature.

2.3.3.3: GCMS analysis

GC/MS analysis was performed in Agilent apparatus containing capillary column (0.25 ID × 30 m × 0.25 μm film thickness). Electron ionization (EI) was used as ion source. Helium was provided as carrier gas with flow rate of 1.0 mL/min. The column temperature was set at 30oC for 3 min then raised at 50oC/min to 180oC and by 40oC/min to 200oC. One µL sample was injected in GC/MS machine.

Chapter: 2 Material & Methods

2.4: Evaluation of best performing Bacillus strains for their plant growth promoting efficacy

An independent pot experiment was performed to analyze growth promoting potential of best performing Bacillus strains in previous experiment viz: B. fortis IAGS 162 and B. fortis IAGS174, under greenhouse conditions. Firstly, these strains were screened for production growth promoting substances. Pot media was provided with bacterial inoculum and tomato seeds were sown. After six weeks of incubation, growth parameters were analyzed.

2.4.1:.Potential of selected Bacillus strains to promote growth of tomato plants under greenhouse conditions

Plastic pots of 10 inch diameter were used in this experiment. Sandy loam was used as potting media. For this purpose, pot media was sterilized by moist heat method. Bacterial inoculum was prepared as described in section (2.2.1.4). Sterilized media (1.5 kg) was filled in each pot. Afterwards, 100 mL of bacterial inoculum was provided in respected pots. Tomato seeds of three varieties viz: Fine Star, Rio Grande and Red Power were surface sterilized with 1% solution of Sodium hypochlorite. Ten seeds were sown in each pot and upon emergence, thinning was performed by leaving four uniformly looking seedlings per pot. Untreated control was only provided with 100 mL of distilled sterilized water. Pots were kept under greenhouse conditions for incubation. These were provided with distilled sterilized water when ever needed. Experiment was performed in triplicates. There were five pots in each replicate.

2.4.1.1: Harvest

Harvest was taken after 45 days. For this purpose, five plants were randomly uprooted from each treatment and growth parameters like, shoot and root length, fresh and dry biomass were analyzed.

Chapter: 2 Material & Methods

2.4.2:.Effect of selected Bacillus strains on total chlorophyll, carotenoids and total soluble sugar contents of tomato plants

2.4.2.1:.Estimation of total chlorophyll content

One gram leaf samples from young shoots were taken from greenhouse grown plants at final harvest. These leaf samples were extracted with methanol. Whole material was filtered and collected in a new tube. For total chlorophyll estimations, absorbance was taken at 645 and 663 nm and values placed in following formula (Arnon, 1949).

2.4.2.2:.Estimation of carotenoid content

For carotenoid quantification, methanol extraction method was used. Carotenoid quantification was performed by using equation (Lichtenthaler and Wellburn 1983).

2.4.2.3:.Estimation of total soluble sugar content

Total sugars were estimated by the phenol sulphuric method (Dubois et al., 1956). Firstly plant material was extracted with 80% methanol. One mL of extracted material was taken in clean glass tube and mixed with 1 mL of phenol water solution at ratio of

(5:95). Further, 5 mL of concentrated H2SO4 was mixed and vortexed. These tunes were incubated for 30 minutes at room temperature and absorption was taken at 490nm. 2.4.3:.Characterization of selected Bacillus strains for production of plant growth promoting substances

2.4.3.1: Siderophore detection This assay was performed by using methodology of (Perez-Miranda et al., 2007) with some modifications. Bacteria were grown in LB broth media overnight. Next day

Chapter: 2 Material & Methods clear supernatant was collected by centrifugation. Agar media plates were prepared by adding 10% O-CAS dye. Wells were made in the petriplates with cork borer. One hundred microliters of supernatant of each bacterial strain was poured inside wells separately. Development of orange color around wells was taken as positive result. For quantitative analysis, OD of this clear supernatant was observed at 630. Bisucaberin standard curve was used to quantify siderophore production.

2.4.3.2: Phosphate solubilization Selected Bacillus strains were checked for their phosphate solubilization ability by growing them on plates containing Pikovskaya’s agar medium (Appendix 1) (Pikovskaya, 1948; Fischer et al., 2007). Bacteria were inoculated onto plates and incubated for a week at 28-30 oC. Production of clear zones was seen around bacterial colonies for positive results. Quantitative phosphate solubilization efficiency of isolated strains was determined on NBRIP medium (Nautiyal, 1999). The inoculum was prepared by preculturing the bacteria in NBRIP medium at 30°C in a temperature controlled incubator shaker at 100 rpm for one week. Samples (5.0 ml) from each flask were withdrawn aseptically. Phosphate solubilization rate (increase in soluble phosphorus concentration/h) was measured after diluting the samples with 1.0 mol/l HCl (1:1) to dissolve the left over Ca3(PO4)2 (Pérez et al., 2007).

2.4.3.3: Auxin production

Auxins are phytohormones accelerating plant growth by different physiological mechanisms. To asses auxin production, bacterial strains were grown in LB broth media supplemented with 0.1% tryptophan or not for 24 hours. Supernatant was obtained by centrifugation of growth media at 4000 rpm for 15 minutes. One mL of supernatant was mixed with 2 mL of Salkowski reagent (Appendix 1) (Benizri et al., 1998). This solution was kept 30 minutes at room conditions. Development of a pink colour confirmed IAA production. For quantitative analysis, the OD of resultant solution was checked at 530 nm. Standard curve was made by dissolving pure IAA in LB broteh at concentrations viz: 0, 5, 10, 20, 50, and 100 µg/ml (ppm).

Chapter: 2 Material & Methods

2.5:.Development of bacterial formulation and field evaluations of best performing Bacillus strains

This experiment was performed to select carrier material providing maximum shelf life to bacterial cells and to test efficacy of selected bacterial strains viz: B. fortis IAGS162 and B. subtilis IAGS174 under field conditions. Initially, four carrier materials were checked for their suitability to be used in inoculum development. Best performing material was then selected to prepare inoculum of selected two strains for field trials. Disease index and growth parameters were evaluated to make final assessments. 2.5.1: Selection of carrier material for development of bacterial formulation

2.5.1.1: Bacterial strain and inoculum preparation

Bacterial strains viz: B. fortis IAGS162, and B. subtilis IAGS174 were grown in LB broth media (Appendix 1) over night at 35oC. Bacterial cells were collected by centrifugation at 4000 rpm for 15 min. Pallet was washed twice with 1 mL of 0.01 M phosphate buffer saline (PBS) (Appendix 1), pH 7.0. These bacterial cells were resuspended in sterile distilled water and their concentration was adjusted at 107-8 cfu/mL by taking OD of 0.8 at 600nm (Park et al., 2013) before the addition of carrier material.

2.5.1.2: Sterilization and inoculation of carrier materials

Four carrier materials viz: talc, bentonite, soil and saw dust were used in this study. One hundred grams of each carrier material was taken. These carriers were sterilized by autoclaving at 121oC for 30 minutes. One hundred mL of bacterial suspension was mixed in 100 grams of carrier material inside opaque polythene bag and sealed.

2.5.1.2: Bacterial enumeration

Viability of bacterial strain in the inoculant carrier materials was assessed at regular intervals of 15 days up to 60 days by using dilution plate method. For that purpose, one gram material was taken from each carrier material. This material was

Chapter: 2 Material & Methods transferred inside sterilized falcon tube and 10 mL distilled sterilized water was added. Tubes were vortexed for proper mixing. Resulting material was further serially diluted in distilled sterilized water. One hundred microliters of this sample was poured on LB agar media plates (Appendix 1). After 24 hours incubation at 35oC, colonies were counted to assess viability of bacterial strains inside carrier material. 2.5.2:.Efficacy of bacterial formulation to manage fusarium wilt under field conditions

This experiment was performed twice in Experimental station of Institute of Agriculture sciences, University of the Punjab, Lahore, during the tomato growing season (February-June 2011 and 2012). Two best performing strains in split root experiment viz: B. fortis IAGS162 and B. subtilis IAGS174 were selected for field evaluations. Their inoculum were prepared using carrier selected previously. Pathogen inoculum was prepared on sweet sorghum grains. Single row plot design was used for this experiment. Tomato seedlings were developed in sterilized media in plastic pots. Experiment was performed under both axenic and non-sterilized soil conditions. Soil was sterilized with methylene bromide to ensure axenic conditions and left for five days to eliminate residual effects of methylene bromide. Fusarium sick plots were made by providing inoculum one week before seedlings transplantation to ensure establishment of pathogen. Roots of seedlings were primed with bacterial inoculum. Description of treatments is provided in Table 2.7. Three replicates were made for each treatment. Disease index and control effects were evaluated after 60 days of transplantation as described in sections 2.2.6.

2.5.3:.Efficacy of bacterial formulation to promote growth and yield of tomato plants under field conditions

In this field experiment, potential of bacterial formulation to promote growth and yield of tomato plants was also assed. For that purpose, parameters related to growth promotion viz: shoot length, total fresh and dry biomass and total number of fruits were determined at final harvest.

Chapter: 2 Material & Methods

2.5.4: Data analysis The statistical analysis was performed by One-way ANOVA (P = 0.05) using computer aided software “DSASTAT”. Subsequently Duncan’s new multiple range test was applied to the data set to test the significance of difference between the treatments (P < 0.05).

Table 2.7: Description of treatments for field experiments.

Treatments Description

1 B. fortis IAGS162 + Fol 7 2 B. subtillis IAGS174 + Fol 7 3 B. fortis IAGS162 + B. subtillis IAGS174 +Fol 7 4 B. subtillis IAGS174 5 B. fortis IAGS162 + B. subtillis IAGS174 6 Pathogen control 7 Untreated control

Chapter: 2 Material & Methods

2.6:.Screening of ISR determinants from selected

Bacillus strains

This experiment was performed to check the potential of culture filtrates of best performing strains viz: B. fortis IAGS162 and B. subtilis IAGS174 to act as elicitors of induce systemic resistance. Bacterial strains were raised in liquid broth and obtained cell free culture filtrate (CFCF). These CFCFs were then provided to susceptible tomato variety ‘Fine Star’ with different combinations. 2.6.1:.Preliminary screening of potential ISR determinants from selected Bacillus strains

2.6.1.1:.Preparation of bacterial cell suspension, intracellular components and cell free culture filtrates

Preliminary tests were conducted to determine if the ISR determinants are bacterial cell components or extra-cellular metabolites. For that purpose, our best performing bacterial strains viz: B. fortis IAGS162, and B. subtilis IAGS174 were inoculated in 100 mL LB broth media (Appendix 1) separately. These flasks were incubated at 35oC overnight. On next day, culture mixture was poured in 50 mL falcon tubes and centrifuged at 4000 rpm for 15 minutes. Supernatant was collected in new sterilized falcon tubes and used for ISR assay. Bacterial cell pallet was washed and resuspended in distilled sterilized water. To determine if the ISR determinants are from bacterial cell components, bacterial cells were heat killed by autoclaving, re-suspended in distilled sterilized water. Cell breakdown was performed by sonicating six times at resonance amplitude for 15 seconds at 4oC to release all types of cell components in solution. Concentration of bacterial inoculum was kept at 108 cfu/mL by taking 107-8 cfu/mL by taking OD of 0.8 at 600nm (Park et al., 2013) for both alive and heat killed bacterial cells.

Chapter: 2 Material & Methods

2.6.1.2: Plant growth and inoculation

Seedlings of susceptible tomato variety ‘Fine Star’ were developed in sterilized media. Plastic pots of 6 inch diameter were filled with sterilized sandy loam soil as growth media. Tomato seedlings were transplanted in these pots after three weeks of emergence at the rate of one seedling per pot. Four treatments were made for each bacterial strain viz: alive cell suspension, dead cells, intra-cellular metabolites and extracellular metabolites. Fifty mL of each treatment were provided in respected pot according to the experimental design. Pathogen was provided as 50 mL of conidial suspension that was prepared as described in section (2.2.1.3). One treatment served as pathogen control which got only pathogen inoculum, whereas untreated control got distilled sterilized water only.

2.6.1.3: Harvest

After fifteen days of incubation, data regarding disease index was calculated as described in section (2.1.1.5). 2.6.2:.Isolation of ISR determinants from cell free culture filtrates of selected Bacillus strains

2.6.2.1: Solvent extraction of bacterial metabolites

Both bacterial strains were cultivated on LB broth media on a rotary shaker at 30oC for 48 hours. Cells were separated from growth media by centrifugation at 8000 g for ten minutes. Clear supernatant was then subjected to heat treatment by autoclaving. This supernatant was extracted twice with double volumes of different organic solvents like ethyl acetate, chloroform, n-hexane and n-butanol (Fig. 2.2 A). Left over aqueous phase and rest of the extracts were evaporated in rotary evaporators until dryness. These extracts were then dissolved in 10% dimethylsulfoxide (DMSO) and subjected to ISR experimentation (Fig. 2.2 B).

Chapter: 2 Material & Methods

2.6.2.2:.Initial screening of bacterial metabolites extracted with different solvents for ISR activity

Tomato seeds of susceptible variety ‘Fine Star’ were sown onto MS media inside culture tubes (Fig. 2.3). These tubes were kept in growth chamber at 25oC for development of seedlings. After five days of seedling emergence, these seedlings were provided with pathogen inoculum and bacterial metabolites extracted with different solvents at concentration of 1.0% w/v for each solvent system independently. Seedlings were left for incubation on same conditions and observations were made after one week of incubation regarding disease development. Treatment showing minimum disease development was subjected to further screening for ISR determinant/s.

2.6.2.3:.Fractionation of best performing metabolites by column chromatography and selection of most ISR active fraction

Metabolites which performed best were further subjected to Silica gel column chromatography. For that purpose, open type column was packed with silica gel and washed with two bed volumes of ethyl acetate and methanol (Fig. 2.2 C). The extracts were poured in column and fractioned with ethyl acetate and methanol in stepwise elution process with increased concentration of methanol in ethyl acetate. These fractions were dried and dissolved in 10% dimethylsulfoxide (DMSO) and subjected again to ISR experimentation as described in upper section (Fig. 2.2 D).

2.6.3: Identification of ISR determinant by GC/MS analysis

GC/MS analysis was performed to identify putative ISR determinants produced by our bacterial strains. GC/MS analysis was performed in Agilent apparatus containing capillary column (0.25 ID × 30 m × 0.25 μm film thickness). Electron ionization (EI) was used as ion source. Helium was provided as carrier gas with flow rate of 1.0 mL/min. The column temperature was set at 30oC for 3 min then raised at 50oC/min to 180oC and by 40oC/min to 200oC.

Chapter: 2 Material & Methods

2.6.4: ISR bioassays with pure compounds

Biochemicals present in ISR active sub-fraction were purchased from Sigma Aldrich. Another culture tubes bioassay was performed to screen exact ISR determinate/s by adopting same methodology as described in section (2.2). Three different concentrations viz: 0.01, 0.1, 1.0 mM of each pure biochemical were provided to MS media inside culture tubes. Observations were made after one week of incubation. Five replications of each treatment were used. Here again data were taken regarding disease index.

2.6.5: Data analysis

Statistical analysis was performed by One-way ANOVA (P = 0.05) using computer aided software “DASTAT”. Subsequently Duncan’s new multiple range tests was applied to the data set to test the significance of difference between the treatments (P < 0.05).

Chapter: 2 Material & Methods

Fig. 2.2: Different steps involved in chemical extraction of ISR determinants from Bacillus strains. A= Solvent extraction of CFCF. B= Recovery of CFCF extracted by different organic solvents. C= Column chromatography of ISR active phase of CFCF. D= Collection of different fractions fractionated by column chromatography.

Chapter: 2 Material & Methods

Fig. 2.3: Experimental setup of screening of different treatments of CFCF Bacillus strains for presence of ISR determinant/s.

Chapter: 3

RESULTS

Chapter: 3 Results

3.1:.Selection of most virulent pathogen isolate and succeptible tomato varieties against fusarium wilt

3.1.1: Screening of tomato varieties against fusarium wilt This experiment was performed to select most virulent isolate of Fusarium oxysporum f.sp. lycopersici (Fol) and to analyze selected tomato varieties for their susceptibility levels against fusarium wilt. Fol isolates were isolated from roots of infected tomato plants and identified by both morphological and molecular methods (Fig. 3.1). Statistical analysis demonstrated significant interaction between Fol isolates and tomato varieties (Table 3.2). One Fol isolate was unable to cause uniform level of disease in all tomato varieties. Similarly one tomato variety showed different disease indexes with different Fol isolates. ‘Red Cloud’ and ‘Cosmos 101’ showed less susceptibility towards Fol 2 but more against Fol 3 as represented by disease index values (Table 3.2). ‘Red Stone’ was having disease index of 84.6% against Fol 3 but against Fol 6, disease index remained only 22.5%. When ‘Early Boy’ was checked against selected Fol isolates, higher disease indexes were recorded representing that this variety is prone to most of the tested Fol isolates (Table 3.2). Similarly, most striking differences were observed among different Fol isolates for their disease incidences. Isolate Fol 2 and Fol 10 resulted in lowest disease index on ‘Sun Grape’ but highest when checked on ‘Early Boy’ (Table 3.2).

After categorization of varieties based on mean of disease index (MDI), none of the variety was found immune or resistant against Fol infection (Fig. 3.2). Three varieties viz: ‘Pride Burn’, ‘Red Power’ and ‘Sun Grape’ were found moderately susceptible against tested pathogen. Seventeen varieties were found susceptible against tested pathogen with mean disease index ranging between 40-70%. Varieties i.e. ‘Early Boy’ and ‘Fine Star’ were found highly susceptible as they showed mean disease index more than 70% (Fig. 3.2). On the other hand when mean disease index was taken for single Fol isolate against all tomato varieties, Fol 7 was found most virulent strain with 73.87% MDI followed by Fol 3 with 69.42% MDI (Fig. 3.3).

Chapter: 3 Results

A polar dendrogram was constructed based on susceptibility levels of tomato varieties against tested Fol isolates by Single Linkage Euclidean Method. Point of maximum dissimilarity divided all tomato varieties into three groups (Fig. 3.3). Moderately susceptible varieties like ‘Red Power’, ‘Pine Red’, ‘Sun Grape’ and ‘Pride Burn’ shared group 1 while group 2 and 3 contained susceptible and highly susceptible varieties all together (Fig. 3.4).

As a result of this experiment, most virulent strain i.e. Fol 7 and three tomato varieties viz: ‘Red Power’, ‘Rio Grande’ and ‘Fine Star’ with varying disease susceptibility levels were selected for further experimentation (Table: 3.2).

3.1.2: Genetic fingerprinting of Fol isolates by ISSR markers

A total of fifteen ISSR primers were evaluated for their ability to reveal genetic dissimilarity among tested Fol isolates. Seven ISSR primers were able to reveal polymorphism among Fol isolates (Table 3.1). These primers amplified both monomorphic and polymorphic bands. A total of 110 loci were amplified out of which 82 were polymorphic. Primer ‘841’ amplified maximum polymorphic alleles (Table 3.1). All the ten Fol isolates were separated in to two main groups (Fig. 3.5). Isolates Fol1, Fol 2, Fol 3, Fol 4, Fol 6, Fol 8 were in one group and rest of the isolates were in second group (Fig. 3.5). This variability in the genetic material provides basis of difference in virulence of different Fol isolates.

Table 3.1: Details of ISSR primers used for genetic finger printing of Fol isolates.

Annealing Total no Polymorphic %age of Primer Sequence (5’-3’) Temperature of bands bands polymorphism (oC) 810 GAGAGAGAGAGAGAGAT 50 17 11 64.70 823 TCTCTCTCTCTCTCTCC 50 23 14 60.86 826 ACACACACACACACACC 51 15 09 60.00 841 GAGAGAGAGAGAGAGAYC 52 16 14 87.50 845 CTCTCTCTCTCTCTCTAGG 52 11 07 63.63 855 ACACACACACACACACYT 50 18 13 72.22 856 ACACACACACACACACCTA 52 10 04 60.00 Total 110 82 74.54

Chapter: 3 Results

A B

C D

Fig. 3.1: Isolation and identification of Fusarium oxysporum f.sp. lycopersici (Fol). A= Tomato stem section showing vascular browning. B= Different strains of F. oxysporum recovered from infected samples. C= Macroconidia of F. oxysporum. D=Microconidia produced on conidiophore of F. oxysporum. E= Molecular identification of F. oxysporum by using specie specific primers.

Chapter: 3 Results Small . ) 05 . Ig He Hc Hc Ab Eef EFf HIe Dee EFe EFd DEf 10 FGe DEc DEe ABc DEd ABd CDd GHe 0 EFcd BCab ABcd > 09.0 P 20.3 22.9 22.8 67.9 Fol 41.5 38.2 18.2 43.5 37.0 39.1 46.4 31.9 46.8 43.9 63.7 43.1 63.2 51.3 26.4 38.2 ( 55.9 62.0 . ) at 05 . 0 d - Fc Eb > Fbc Ebc Cab Cbc - Eab Dab Gde - Ic Id Eb - Aa Hc - - - - Ide - - - Hab FGc ABb GHb D EFbc C EFbc ABab GHde D C C E A A B P C ( DNMRT Fol 9 Fol 24.4 29.2 84.8 54.4 30.9 at 54.1 62.8 81.7 56.0 69.5 66.2 71.8 66.1 83.6 57.5 67.5 72.8 70.3 64.1 79.1 78.2 75.9 72.4 and Fe Fd Ed - - - Cf Gf Ae He He Cd Ae Hg EFf EFf Ccd FGe FGc FGg ABc BCd BCd BCd D D C BCde CDcd DNMRT Fol 8 Fol 37.3 17.8 53.2 00.0 00.0 37.4 52.6 00.0 26.2 26.4 ANOVA 37.9 24.9 19.8 23.6 46.7 42.1 39.3 38.4 28.6 28.1 33.3 41.9 and 35.4 by Jc Fa Ca Ea Ca Ea Da Gb Ld Fab - Kd Eab ------7 - La - Lb Aa Aa Aa - IJc - HIc FGa ABa J I H GHb HIbc D C C A A B E D C ANOVA Fol 45.6 49.1 93.5 94.8 93.4 59.3 63.5 72.8 governed 91.1 53.0 56.1 60.8 68.1 by 63.8 77.0 81.6 81.7 88.6 87.1 84.7 74.5 77.9 81.2 as

Ic Jd Ib Fb Eb Db - Fbc Ke Ka - Kd Cbc Gcd - - Dbc Hbc - Lde - 6 Kde Ld ------Mg - - Aab - F KLc KLd I I G I H C B B J ABab ABab I C E A B D governed varieties Fol 34.8 22.5 as 86.5 59.9 41.5 41.6 48.6 51.8 56.3 49.9 53.6 67.0 71.0 75.7 43.4 82.9 78.9 49.8 68.1 63.1 76.0 74.2 64.2 tomato Ec Eb Eb Eab Eab Eab isolates Dbc - - - 5 Fc Fc Hf Hf Aa Aa Gc Hc Aa - - - Hd - Ebc EFc Aab BCa DEb C C C ABab C B B B all Fol Fol 56.2 54.8 31.1 35.6 89.1 89.5 45.6 26.1 91.7 26.9 68.9 58.6 87.0 79.7 69.0 74.1 72.4 73.3 83.1 73.8 75.8 74.8 78.3 all isolates. against Fb Eb Eb Gc Fol Cab Ecd Dab Dab - Gde Gbc - - - 4 He Aa Aa - - Hb - - - - Hef Aab Gcd Hcd FGc FGb FGb DEb ABb B B D E C E E A against A A isolate Fol 44.6 86.6 88.2 34.2 39.4 84.2 51.4 37.9 59.7 58.5 59.3 70.6 82.7 73.5 72.6 69.6 62.7 71.0 65.4 65.0 81.6 79.3 79.1 Fol variety Ia Id Ca Ca Ca Eb Cb Da Da Db Icd Icd - - Hbc Gab Gab ------Jc - - - 3 Lc Le - Aa Kd Ibc - - - F E ABa ABa C A A A F B A A B D single C C C tomato Fol of 45.3 21.6 23.6 92.9 33.3 62.1 63.7 66.4 88.8 89.6 76.7 85.7 85.0 84.6 63.4 79.8 81.4 81.3 78.5 71.6 73.2 74.1 74.2 single Je of Da Gc Icd Db Gc Gb - Fbc Fbc Cab Dab - Hbc - - - - - 2 Le Kf - - Aa Nd - IJb - Lef - JKd IJcd ABa H E E E B B G MNef LMde D D F B A interaction Fol 28.7 43.8 in 94.5 08.2 53.2 27.9 48.5 53.8 87.3 57.2 67.3 68.1 69.2 80.3 77.9 61.0 18.6 25.3 72.0 70.7 65.0 79.1 86.7

of tomato varieties against selected Fol isolates. against selected varieties of tomato interaction in Id Fc Ide Gc Hd Fde - Ecd - Jf Je - Jd - - 1 - Ba Ba Aa Cb - Jfg Ide Ibc Hic Bab Cab CDc ABa G D E E G ABab D C significance Fol 19.5 19.7 13.6 81.5 83.5 91.5 71.3 15.9 47.1 48.7 53.2 83.5 71.6 71.8 84.2 55.8 63.2 61.9 61.3 55.7 85.4 63.5 66.4 of significance level of

Susceptibility Susceptibility show Susceptibility Susceptibility tomato of varieties against selected level Sahil Nova Rando Slumac letters Pot King Pot Fine Star Fine Red Pine Red TaraRed Tin Time Tin Varieties Varieties show Early Early Boy Red Stone Red Roma 505Roma Rio Grand Rio Sun Grape Sun Red Cloud Red Pride BurnPride Red Power Red Terminator Cosmos 101Cosmos Lemon Hunt Lemon Wall Ground Wall Ever Green IF California California Sun

Table. 3.2: Table 3.2: Table Capital letters

Chapter: 3 Results

Mean Mean

70%]. 70%]. (HS)= Highly Susceptible [

40%]. 40%]. (S)= Susceptible [Mean disease index = 41

Susceptibility Susceptibility level of different tomato cultivars against all selected Fol isolates as governed by mean disease index. (MS)

Fig. 3.2: Moderately Susceptible [Mean disease index = 21 <70%]. index disease

Chapter: 3 Results

10 Mean Disease Severity Index (%) Index Severity Disease Mean 0 Fol1 Fol2 Fol3 Fol4 Fol5 Fol6 Fol7 Fol8 Fol9 Fol10

Fig. 3.3: Pathogenicity level of different Fol isolates against all tomato varieties.

Chapter: 3 Results

Group 1

Group 2

Group 3 1=3

Fig. 3.4: Cluster analysis showing grouping of different tomato varieties based on disease index. Dendrogram was constructed by using Single Linkage Euclidean Distance method with MYSTAT software.

Chapter: 3 Results

A B

Fig. 3.5: DNA finger printing of Fol isolates by ISSR markers. A & B = ISSR marker profiles of Fol isolates generated by ISSR primers. C= Dendrogram showing relationships between Fol isolates using ISSR data made by using Single Linkage Euclidean Distance method with MYSTAT software.

Chapter: 3 Results

3.2:.Screening of Bacillus strains capable of inducing resistance in tomato against fusarium wilt under split root system

3.2.1:.Potential of Bacillus strains to manage fusarium wilt under split root system

Treatment of tomato roots with selected Bacillus strains significantly (P< 0.05) reduced fusarium wilt disease in split root experiment in all the three selected tomato varieties viz: ‘Red Power’, ‘Rio Grande’ and ‘Fine Star’ (Fig. 3.6). This demonstrated an effective resistance response in treated plants in interaction to the bacterial strains (Fig. 3.6). Out of the fourteen tested Bacillus strains, most significant (P< 0.05) reduction in disease index was caused by B. fortis IAGS162, and B. subtilis IAGS174 (Table 3.3). Both of these strains reduced disease index up to 68 and 73% respectively as compared to the pathogen control and provided biocontrol effect of 57.70 and 63.10% respectively on average basis for all the three selected tomato varieties (Table 3.3).

Consistent with these observations, B. subtilis IAGS174 showed highest reduction in disease index ranging between 69.34 to 87.61% as compared to the pathogen control in all the three tomato varieties. This strain provided biocontrol effect of 66.29, 72.93 and 68.08% in ‘Fine Star’, ‘Rio Grande’ and ‘Red Power’ respectively (Table 3.3). Bacillus fortis IAGS162 closely followed this as it caused a reduction in disease index ranging between 52.35 to 83.44% across all the three tomato varieties. This strain provided biocontrol effect ranging from 52.37 to 63.98% in these tomato varieties (Table 3.3).

These results were followed by B. thuringiensis IAGS199 that resulted in a reduction of disease index ranging between 56.62 to 66.66% and B. thuringiensis IAGS002 with 41.03 to 57.13% decrease in disease index in three selected tomato varieties. Biocontrol effect caused by the above two strains was 43.02 and 31.12% respectively on average basis (Table 3.3).

Chapter: 3 Results

Bacillus megaterium ZMR6 reduced disease index up to 56.15, 45.78 and 33.61% with a biocontrol effect of 44.53, 35.15 and 23.92% in ‘Fine Star’ ‘Rio Grande’ and ‘Red Power’ respectively. Biocontrol effect caused by B. subtilis IAGS170 ranged between 33.37 to 40.75% in selected three tomato varieties. This strain reduced disease index between 48.36 to 61.44% across all these varieties (Table 3.3). Bacillus thuringiensis IAGS002 reduced disease index up to 38.91% that was significantly equal to that recorded in ‘Rio Grande’ plants treated with different as in case of B. subtilis IAGS170 (39.81%) in tomato variety ‘Rio Grande’ (Table 3.3). In ‘Red Power’, reduction in disease index was 59.64, 53.62 and 43.39% for B. megaterium ZMR6, B. thuringiensis IAGS002 and B. subtilis IAGS170 respectively as compared to the pathogen and these strains provided biocontrol effect of 33.37, 32.42 and 30.15% respectively. Both B. megaterium ZMR3 and B. megaterium MCR8 reduced disease index more than 37% across all the three tomato verities (Table 3.3).

On the contrary, application of B. fortis IAGS223 could not suppress fusarium wilt of tomato. In this case disease index was comparable with pathogen control even after treatment with this strain (Table 3.3). For this strain, disease index was recorded 86.23 and 78.19%, in varieties ‘Fine Star’ and ‘Rio Grande’ respectively (Table 3.3). These values were not significantly different with pathogen control with disease index of 89.6% and 83.05% for both varieties respectively (Table 3.3). Based on these results, two best performing strains viz: B. fortis IAGS162 and B. subtilis IAGS174 were selected for further experimentations.

Chapter: 3 Results

F F F E A H FG DE BC DE BC CD CD GH

14.53 14.53 13.32 14.23 26.73 26.73 52.37 52.37 03.68 11.46 11.46 30.21 30.21 48.14 30.15 36.51 32.42 32.42 33.37 06.84 Effect (%) Effect Bio Control Bio

F F E D D

- - - - - F B B G A EF EF EF Red Power Power Red BC BC D D C B B

Disease 16.82 16.82 26.30 26.30 26.34 14.83 14.83 57.31 18.00 18.00 18.16 17.41 23.34 23.34 24.17 Index (%) Index 19.16 19.34 20.01 20.01 23.67 23.67 23.41

F E B C C C G G D A G DE DE BC

three different varieties under split under different varieties three

21.64 21.64 32.18 32.18 63.98 63.98 49.73 49.73 46.73 44.87 07.56 07.56 11.98 39.81 72.97 08.39 38.91 38.91 35.15 49.70 Effect (%) Effect Bio Control Bio

I J B B C H D H H A Rio Grande Grande Rio EF EF DE AB GH

tomato plants of tomato Disease 24.16 24.16 15.83 15.83 73.33 73.33 76.67 65.52 65.52 32.55 32.55 53.51 33.50 35.05 83.02 42.50 42.50 45.00 48.10 48.10 78.31 78.31 36.67 36.67 Index (%) Index

F E E C C C C C G D A D FG AB

0.05) as governed by ANOVA and and by ANOVA governed DNMRT. as 0.05)

> -

P 05.97 05.97 15.61 15.61 22.66 45.02 45.02 40.75 44.53 41.35 44.30 03.12 03.12 31.51 66.20 36.36

11.19 11.19 59.76 59.76 Effect (%) Effect Bio Control Bio

Fine Fine Star

F F F F E B C G G D A F E D AB

significantly (

- 31.3 31.3 43.3 43.3 57.5 57.5 Disease 35.02 35.02 31.67 31.76 28.34 86.6 86.6 41.16 80.20 80.20 70.55 70.55 15.83 15.83 11.00 60.13 89.39 Index (%) Index

IAGS IAGS 199 IAGS 002

ZMR6 ZMR4 ZMR3 MCR8 OSR3

Potential of Bacillus strains to control fusarium wilt in to fusarium strains control Potential Bacillus of

MCR7 IAGS 170 IAGS174 FBL10

IAGS IAGS 324 IAGS 223 IAGS 162 Treatment

Table. 3.3: root experiment. non differ letter with same Values B. fortis B. fortis B. fortis B. theruingenesis B.theruingenesis B. subtilis B. subtilis B. subtilis B. subtilis B. megaterium B. megaterium B. megaterium B. megaterium B. megaterium Pathogenic Control

Chapter: 3 Results

Fig. 3.6: Effect of Bacillus strains on development of fusarium wilt on plants of three different tomato varieties under split root system. A=Fine Star, B= Rio Grande, C= Red Power. PC= Pathogen Control. UC= Untreated Control. T1= B. subtilis IAGS174+ Fol. T2= B. fortis IAGS162 + Fol. Fol= F. oxysporum f.sp. lycopersici Fol7.

Chapter: 3 Results

3.2.2: Analysis of changes in defense related biochemicals of tomato plants under influence of Bacillus strains

To support the hypothesis of ISR, tomato plants treated with different bacterial inducers were assayed for induction of defense related biochemicals. For this purpose, total phenolics, Peroxidase (PO), Polyphenol oxidase (PPO) and Phenylalanine ammonia lyse (PAL) were quantified calorimetrically. Plants inoculated with selected bacterial inducers accumulated much larger quantities of these defense related biochemicals. Results were represented in time course manner to denote overall trends behind induction of systemic resistance and average values were used to make statistical comparisons among different treatments.

3.2.2.1: Quantification of total phenolics

Tested Bacillus species induced all the three selected tomato varieties for over production of phenolic compounds with some variations. Bacillus fortis IAGS162 and B. subtilis IAGS174 inoculated plants of all the three varieties showed highly significant (P>0.05)increase in phenolics production ranging between 54 to 86% over control. This was followed by B. megaterium ZMR4 that resulted in an increment of 72.20% in ‘Fine Star’ and 48.80 and 41.66% more phenolic were recorded in tomato plants of varieties ‘Red Power’ and ‘Rio Grande’ (Table 3.4; 3.5 and 3.6). Bacillus magaterium MCR8 highly significantly (P>0.05) induced the plants of ‘Fine Star’ and ‘Red Power’ as these varieties showed an upsurge of total phenolics (Table 3.4 and 3.5). However, tomato variety “Rio Grande” showed only 29.16% increase in phenolic production over control when grown under the influence of B. megaterium MCR8 (Table 3.5).

In ‘Fine Star’ next most efficient strains were B. thuringiensis IAGS002, B. megaterium ZMR3, B. thuringiensis IAGS199, B. megaterium MCR6 and B. subtilis FBL10 that triggered the plants to increase the production of phenolics ranging between 38 to 48% (Table 3.4). These were followed by B. fortis IAG324 and B. subtilis MCR7 that resulted in an increase of 35.76 and 33.57% in their treated plants. Least significant

Chapter: 3 Results increment in plants of ‘Fine star’ was recorded when they were treated with B. subtilis IAGS170, B. megaterium OSR3 and B. fortis IAGS223 (Table 3.4).

In ‘Rio Grande’ B. thuringiensis IAGS199, B. fortis IAGS223 induced plants as efficiently as B. megaterium ZMR4 for phenolics production (Table 3.5). This was followed by B. megaterium OSR3 and B. megaterium ZMR6 that triggered the plants for 34.74 and 33.33% more phenolics production. Other tested Bacillus species failed to produce significant results (Table 3.5).

In case of “Red Power” most significant treatment after B. megaterium MCR8 was B. megaterium ZMR3 (43.02%) and B. thuringiensis IAGS002 (45.83%). Bacillus fortis IAGS324, B. thuringiensis IAGS199, B. megaterium ZMR6 and B. megaterium OSR3 closely followed these results (Table 3.6). Rest of the Bacillus strains failed to induce tomato variety “Red Power” for production of phenolics in higher quantity in comparison to the plants only treated with the pathogen (Table 3.6).

Time course analysis revealed that quantities of total phenolics increased rapidly after inoculation till 2nd day. It was highest at 4th day post inoculation (dpi). Later on at 8 dpi, a decreasing trend was observed in quantities of total phenolics (Fig. 3.7). In case of B. subtilis IAGS174, total phenolics content got increased up to 1.3 to 1.9 folds at 0.5 and 1 dpi as compared to 0 dpi. Maximum increase was observed at 2 and 4 dpi, with an increase of 2.1 and 3.4 fold as compared to 0 dpi on average basis in all the three tomato varieties. At 8 dpi, a decreasing trend was recorded in all the three tomato varieties. Whereas, B. fortis IAGS162 induced tomato plants for 1.3 and 2.2 folds increase in total phenolics content at 0.5 and 1.0 dpi as compared to 0 day interval on average basis in all the three tomato varieties. Total phenolics content were at peak at 4 dpi with an increase of 3.6 folds as compared to 0 day interval on average basis in all the three tomato varieties. Untreated control plants maintained a consistent lower level of total phenolics at all times intervals (Fig. 3.7, 3.8 and 3.9).

Chapter: 3 Results

3.2.2.2: Quantification of Peroxidases

In ‘Fine Star’ maximum increase of 56.70% in PO activity was recorded in plants treated with B. subtilis IAGS174 (Table 3.4). This was followed by the plants grown under the influence of B. fortis IAGS162 that showed an increment of 49.48% in this variety. Bacillus megaterium OSR3 and B. thuringiensis IAGS002 followed these results with an increment ranging between 41 to 42%. Plants treated with B.fortis 1AGS324 showed an increase of 37.11% in peroxidase activity (Table 3.4). Bacillus subtilis MCR7 and B. thuringiensis 1AGS199 resulted in an increase of 32.98% in PO activity of this variety which was 23.72% less than that caused by B. subtilis IAGS174 in this variety. B. megaterium ZMR3 and B. megaterium ZMR6 caused even less significant increase in PO activity when compared with the control (Table 3.4). Following this, plants grown in combination with B. fortis IAGS223 showed 20.61% increase in PO activity over control. All other Bacillus strains failed to produce any significant difference in PO activity of their treated plants in comparison to the plants only exposed to the pathogens (Table 3.4).

Similar to ‘Fine Star’, tomato variety ‘Rio Grande’ also showed maximum increase in PO activity when treated with B. fortis IAGS182 (52.51%) and B. subtilis IAGS774 (45.60%) (Table 3.5). However, in contrast to ‘Fine Star’ this variety under the influence of B. megaterium ZMR4 showed equally significant (P>0.05) increase in PO activity as recorded in plants treated with B. subtilis IAGS174 (Table 3.5). Following this, B. subtilis FBL10, B. fortis IAGS324, B. thuringiensis IAGS002, B. megaterium MCR8 and B. megaterium ZMR6 treated plants showed statistically equally significant increments in level of PO activity. All the other Bacillus species did not produce any significant increase in their PO activity when compared to that of plants only treated with the pathogen (Table 3.5).

Tomato variety ‘Red Power ‘also showed significant (P>0.05) increase in PO activity when grown in presence of B. subtilis IAGS174. However, this increase was 7.54% less than that was recorded in ‘Fine Star’. B. megaterium ZMR4 also showed equally significant results (Table 3.6). This was followed by B. megaterium ZMR6 that supported increase in PO activity in plants by 38.32%. Bacilllus subtilis MCR7, B. fortis

Chapter: 3 Results

IAGS324, B. subtilis IAGS170 and B. megaterium ZMR3 showed statistically equal significant results and the plants grown with these bacteria showed an increase of 31.84 to 32.40% in PO activity (Table 3.6). Bacillus thuringiensis IAGS199 showed an increase of 35.75% in PO activity in this variety (Table 3.6). Bacillus subtilis IAGS223 followed these results and the plants grown under its influence showed an increment of 27.37% in PO activity when compared to the control (Table 3.6). Bacillus fortis IAGS162 and B. megaterium MCR8 also significantly induced “Red Power” plants for over-production of PO. Other tested Bacilli could not produce significant results when compared to the pathogenic control (Table 3.6).

Time course studies also confirmed increase in PO activity in all the three tomato varieties when grown in combination with selected Bacillus strains. Bacillus fortis IAGS162 and B. subtilis IAGS174 showed maximum increase in PO activity with an increment of 2.1to 2.7 and 1.9 to 2.3 folds at 1 and 2 dpi in comparison to 0 day (Fig. 3.6, 3.7 and 3.8).

3.2.2.3: Quantification of Polyphenoloxidases

Selected Bacillus strains induced tomato plants for significantly higher (P>0.05) production of PPO in all the three tomato varieties. Likewise total phenolics and peroxidase activity, plants receiving B. fortis IAGS162 and B. subtilis IAGS174 showed most significant increase in production of PPO. In variety ‘Fine Star’ these strains increased 71.59 and 57.98% PPO activity respectively as compared to the non-treated control plants (Table 3.4). In this variety next most efficient strains were B. megaterium ZMR3 and B. megaterium ZMR4, which induced tomato plants for 41.56 and 46.49% increase in PPO activity respectively as compared to the non-treated control plants (Table 3.4). Plants receiving B. fortis IAGS324, B. thuringienesis IAGS002 and B. subtilis IAGS170 resulted in an increase in PPO activity ranging between 41.56 to 44.83% as compared to the non-treated control plants. Following this, plants grown in combination of B. subtilis MCR7 and B. fortis IAGS223 showed 37.55 and 27.67% increased PPO activity as compared to the non-treated control plants. Least significant increment in

Chapter: 3 Results

PPO production was recorded when plants were grown under influence of B. megaterium MCR8 and B. subtilis FBL10 (Table 3.4).

In the same way, in variety ‘Rio Grande’ plants co-cultivated with B. fortis IAGS162 and B. subtilis IAGS174 resulted in maximum significant (P>0.05) increase in PPO activity (Table 3.5). These strains provided 57.93 and 73.55% increase in PPO activity as compared to the non-treated control plants. This increase was followed by B. thuringiensis IAGS002 (44.83%) and B. subtilis MCR7 (33.50%) (Table 3.5). Here strains B. megaterium ZMR4, B. thuringienesis IAGS199 showed statistically equal results with an increase of 30% in PPO activity as compared to the non-treated control plants. Least significant difference in PPO activity was observed in plants treated with B. fortis IAGS223 (12.34%) and B. megaterium OSR3 (10.63%) (Table 3.5).

A slightly varying trend was observed in case of tomato variety ‘Red Power’. Here plants grown in presence of B. subtilis IAGS174 and B. megaterium ZMR3 showed maximum significant (P>0.05) increment in PPO quantities (Table 3.6). These two strains induced the plants to increase PPO activity 48.12 and 51.34% as compared to the non-treated control plants. This trend was followed by B. fortis IAGS162 (41.05%) and B. megaterium OSR3 (37.30%) (Table 3.6). Bacillus megaterium ZMR6 and B. subtilis MCR8 induced tomato plants of this variety for 26.17 and 24.06% increased PPO activity as compared to the non-treated control plants. Strains B. subtilis FBL10 and B. megaterium MCR8 were unable to provide significant increase in PPO activity as compared to the pathogen control plants of this variety (Table 3.6).

Time course analysis revealed that in case of B. fortis IAGS162, PO activity increased rapidly and maintained higher inducible levels at 2 and 4 dpi where it was 2.4 and 2.7 fold high as compared to 0 day interval on average basis in all the three tomato varieties (Fig. 3.7, 3.8 and 3.9). In case of B. subtilis IAGS174 treated plants, PO activity increased up to 2.1 and 2.5 fold at 2 and 4 dpi intervals as compared to 0 dpi interval on average basis in all the three tomato varieties (Fig. 3.7, 3.8 and 3.9). Non-treated control plants maintained consistent lower levels at all time points (Fig. 3.7, 3.8 and 3.9).

Chapter: 3 Results

3.2.2.4: Quantification of Phenylalanine ammonia lyase

Selected Bacillus strains induced plants of all the three tomato varieties for increased PAL activity as compared to the non-treated control plants. In tomato variety ‘Fine Star’ plants co-cultivated with B. fortis IAGS162 and B. subtilis IAGS174 provided highly significant (P>0.05) increase in PAL activity (Table 3.4). These strains showed 65.15 and 57.51% increase in PAL activity respectively as compared to the non-treated control plants. In this variety, next most efficient strains were B. megaterium ZMR6 and B. megaterium ZMR4 (Table 3.4). These performed on statistically equally significant level and induced tomato plants for 50% increase in PAL activity as compared to the non-treated control plants. Plants cultivated under influence of B. thuringienesis IAGS199 (12.62%) and B. fortis IAGS324 (16.16%) followed this trend. Bacillus fortis IAGS223, B. subtilis MCR7 and B. megaterium MCR8 were unable to provide significant increase in PAL activity as compared to the pathogen control plants (Table 3.4).

In the same way, in tomato variety ‘Rio Grande’ B. fortis IAGS162 and B. subtilis IAGS174 triggered plants for maximum significant (P>0.05) increase in PAL activity. Both of these strains performed on same statistically significant level (Table 3.5). Next most efficient strains were B. thuringiensis IAGS002 (45.16%), B.megaterium ZMR4 (41.13%) and B. subtilis IAGS170 (44.70%) (Table 3.5). These were followed by B. megaterium ZMR6, B. fortis IAGS324 and B. thuringiensis IAGS002. These strains induced the plants to increase the PAL production ranging between 36.24 to 41.13% as compared to the non-treated control plants. Rests of the strains were unable to provide significant increase in PAL activity as compared to the pathogen control plants (Table 3.5).

Tomato variety ‘Red Power’ also showed significant (P>0.05) increases in PAL activity under influence of selected bacterial strains (Table 3.6). Plants of this variety grown in the presence of B. fortis IAGS162 and B. subtilis IAGS174 showed more than 75% increase in PAL activity as compared to the non-treated control plants (Table 3.6). In this variety next efficient strains were B. megaterium ZMR6 (66.91%), B. megaterium

Chapter: 3 Results

ZMR4 (63.90%) and B. subtilis MCR7 (61.65%). Plants grown in the presence of B. fortis IAGS324 and B. thuringiensis IAGS002 closely followed this trend. Rest of the strains showed least significant effect (Table 3.6).

Time course analysis also supported increase in polyphenol oxidase activity in all the three tomato varieties when co-cultivated with bacterial strains. Polyphenol oxidase activity got increased consistently up to 2 dpi intervals and maintained higher levels at 2, 4 dpi intervals but showed a decreasing trend at later on time intervals. B. fortis IAGS increased PPO activity up to 2.1, 2.7 and 2.4 folds at 1, 2 and 4 dpi intervals as compared to 0 day interval on average basis in all the three varieties. While in case of B. subtilis IAGS174, same type of increases were 1.9, 2.3 and 2.8 fold as compared to 0 dpi interval respectively. Non-treated control plants maintained consistently lower levels of PPO activity during whole time points (Fig. 3.7, 3.8 and 3.9).

Chapter: 3 Results

0DPI 0.5DPI 1DPI 2DPI 4DPI 8DPI 4 3.5 3

2.5

)

1 -

g 2

1.5 Total Phenolics Total 1

(catechol equivalents released equivalents (catechol 0.5 0 8

)

g 1

- 4 min

PPO Activity PPO 2 (changes in absorbancein (changes 0 3 2.5

)

g 1

- 1.5 min

PO Activity PO 1

(changes in absorbancein (changes 0.5 0

2.5

)

g 1 1 - 2 1.5 1

0.5 PAL Activity PAL

0 (nmol of transcinnamic acid min acid oftranscinnamic (nmol

Fig. 3.7: Changes in defense related biochemicals in tomato plants of variety ‘Fine Star’ under influence of Bacillus strains at different time intervals. Vertical bars represent standard error between different replicates of same treatment. DPI = Days post inoculation.

Chapter: 3 Results

4 0DPI 0.5DPI 1DPI 2DPI 4DPI 8DPI

) 3

1 -

released g released Total PhenolicsTotal

(catechol equivalents equivalents (catechol 1

0 4

)

g 1

- 2

min PO Activity PO

1 (changes in absorbancein (changes

0 8

)

g 1

- 4

min PPO Activity PPO

2 (changes in absorbancein (changes

)

g 1 1 - 2.5 2 1.5 1

PAL Activity PAL 0.5

0 (nmol of transcinnamic acid min acid oftranscinnamic (nmol

Fig. 3.8: Changes in defense related biochemicals in tomato plants of variety ‘Red Power’ under influence of Bacillus strains at different time intervals. Vertical bars represent standard error between different replicates of same treatment. DPI = Days post inoculation.

Chapter: 3 Results

4 0DPI 0.5DPI 1DPI 2DPI 4DPI 8DPI

) 3

1 -

released g released Total PhenolicsTotal

(catechol equivalents equivalents (catechol 1

0 4

)

g 1

- 2

min PO Activity PO

1 (changes in absorbancein (changes

0 8

)

g 1

- 4

min PPO Activity PPO

2 (changes in absorbance in (changes

3.5

)

g 1 1 - 3 2.5 2 1.5

1 PAL Activity PAL 0.5

0 (nmol of transcinnamic acid min acid oftranscinnamic (nmol

Fig. 3.9: Changes in defense related biochemicals in tomato plants of variety ‘Rio Grande’ under influence of Bacillus strains at different time interval. Vertical bars represent standard error between different replicates of same treatment. DPI = Days post inoculation.

Chapter: 3 Results - F F F E E E B C C A D G D FG FG Small . ) 07.57 07.05 06.31 16.16 12.62 14.14 57.57 50.42 50.20 65.15 43.93 01.51 45.42 05 04.54 04.75 . 0 % I OI C % > P ( . ) at B B A A A . BC BC BC BC BC BC BC 05 AB AB AB CD .

0 ) 1 - g > 1 02.33 02.26 03.27 03.12 03.01 - P 02.23 02.07 02.13 02.01 02.12 02.10 02.06 02.85 02.98 02.88 01.98 ( PAL PAL (nmol (nmol of min DNMRT Activity at transcinnamic transcinnamic acid and - F F F F E E C B C A A G G - DE CD C DNMRT 27.67 25.13 30.16 29.34 37.55 46.94 57.98 47.88 71.59 68.56 19.01 18.54 40.16 44.83 ANOVA 42.48 and % I OI C %

‘Fine Star’ under influence of by

I I I J F E - - A G G G G ------HI F BC BC AB CD G D F C E E ANOVA D 5.23 4.26 governed by 7.31 5.26

variety 5.69 6.07 6.73 7.29 6.62 5.51 6.17 5.99 6.30 5.89 5.86 6.10

as /gram PPO (change (change in Activity absorbance /min absorbance /min governed - F F E E B C C A D G H varieties GH GH GH GH as

plants of 26.80 26.80 32.98 32.98 49.48 41.23 42.26 56.70 37.11 20.61 15.46

19.98 17.52 19.58 16.49 tomato isolates % I OI C % all Fol F F B A G D D G G G H - - all - - - FG FG BC CD CD D D E E E against

0.05) as governed by ANOVA and and by ANOVA governed DNMRT. as 0.05) 1.45 1.52 1.29 1.29 1.12 0.97 1.14 1.13 1.38 1.33 1.34 1.23 1.23 1.17 1.16 1.16

> /gram) against

P (change (change in isolate absorbance /min absorbance /min PO Activity PO Fol I J - variety E E B C A H K EF EF FG DE CD GH single 17.51 24.08 40.14 40.82 67.15 55.26 72.47 29.19 12.40 37.95 38.68 35.76 48.17 tomato 51.87 33.57 of % I OI C %

significantly ( single

- F F F E E E B C A H G G H ------of - - - CD CD GH D F D D C C C E E ) 1 - interaction 2.29 2.13 2.36 1.37 in 2.03 2.08 1.54 1.86 1.61 1.83 1.89 1.92 1.90 1.92 1.77 1.70 catechol Total ( equivalents equivalents released released g Phenolics interaction in significance of significance level

of IAGS IAGS 199 IAGS 002 show ZMR ZMR 6 ZMR 4 ZMR 3 MCR 8 OSR 3 level

Changes Changes in defense related biochemicals in tomato Elucidation Elucidation of biochemical of resistance basis under influence in tomato variety of bacterial ‘Fine Star’ strains

Treatments MCR7 IAGS 170 IAGS174 FBL10 IAGS IAGS 324 IAGS 223 IAGS 162 letters show fortis fortis fortis theruingenesis theruingenesis Capital letters

Values with same letter differ non differ letter with same Values B. B. B. B. B. subtilis B. subtilis B. subtilis B. subtilis B. megateriumB. megateriumB. megateriumB. megateriumB. megateriumB. Pathogenic Control Untreated Control Table 3.4: Table

Table 3.4: strains. Bacillus

Chapter: 3 Results Small . ) DE BC A J B J B A J CD BC GH FG I EF - 05 . 0 % I OI C % > 36.24 26.47 51.52 09.27 45.16 12.50 44.70 51.88 14.59 38.06 41.13 28.40 31.65 23.09 32.86 P ( . .

influence influence of ) at 05 . 0 ) 1 C C C C D D E D ------g > A A A E AB DE AB A A A B A A C A E 1 - P ( PAL PAL (nmol (nmol of min DNMRT

Activity at transcinnamic transcinnamic acid 02.40 02.22 02.67 01.82 02.56 01.98 02.55 02.67 02.43 02.43 02.49 02.64 02.31 02.10 02.33 01.76 and DNMRT EF HI B E C D G A F G E G D I I - ANOVA and % I OI C % by 29.47 12.34 57.93 33.24 44.83 33.50 16.62 73.55 26.19 18.13 31.73 17.30 38.88 10.63 08.33 ANOVA governed by F F E - - - under influence under influence of bacterial strains CD FG A C B BC EF A C D C D BC FG FG G

variety variety ‘Rio Grande’ under as /gram PPO (change (change in Activity absorbance /min absorbance /min 5.14 4.46 6.72 5.29 5.78 5.30 4.63 6.89 5.01 4.69 5.23 4.66 5.47 4.35 4.29 3.97 governed varieties as

plants of C E A D C D D B C C B D C D D Rio Grande’ Rio Grande’ ‘ tomato isolates % I OI C % all 32.03 09.70 52.51 23.30 30.97 25.24 23.30 45.60 34.95 29.12 41.74 22.33 31.06 25.24 23.30 - Fol all against CD A DE CD DE E A BC CD B E CD DE E F CD /gram) against

0.05) as governed by ANOVA and and by ANOVA governed DNMRT. as 0.05) (change (change in isolate

> absorbance /min absorbance /min PO Activity PO 1.36 1.33 1.54 1.25 1.34 1.28 1.27 1.51 1.39 1.31 1.46 1.26 1.35 1.28 1.27 1.03

P Fol variety single F D A D G H C B FG E D H F E GH - tomato of % I OI C % 29.16 38.54 86.52 42.72 25.00 20.83 48.95 68.75 26.04 33.33 41.66 20.83 29.16 34.75 23.95 single

significantly ( of

- ) 1 - interaction I I H H - in - - - F DE A D G I C B F EF D I F EF HI J catechol Total ( equivalents equivalents released released g Phenolics interaction 1.24 1.33 1.79 1.37 1.20 1.16 1.43 1.62 1.21 1.28 1.36 1.16 1.24 1.29 1.19 0.96 in significance of significance level

. of IAGS IAGS 199 IAGS 002 ZMR ZMR 6 ZMR 4 ZMR 3 MCR 8 OSR 3

Changes Changes in defense related biochemicals in tomato show

level Elucidation Elucidation of biochemical of resistance basis in tomato variety MCR7 IAGS 170 IAGS174 FBL10 Treatments IAGS IAGS 324 IAGS 223 IAGS 162 letters show Capital letters B. fortis B. fortis B. fortis B. theruingenesisB. theruingenesisB. subtilis B. subtilis B. subtilis B. subtilis B. megateriumB. megateriumB. megateriumB. megateriumB. megateriumB. Pathogenic Control Untreated Control

Values with same letter differ non differ letter with same Values Table 3.4: Table

Table 3.5: strains Bacillus

Chapter: 3 Results

Small

)

14.28

34.58

34.46

43.98

46.61

76.31

66.91

28.94

21.99

81.95

21.42

59.02

30.45

61.65

63.90

% I OI C %

(

)

02.66 02.66

04.84 04.84

(

PAL PAL

03.04 03.04

03.90 03.90

04.30 04.30

04.36 04.36

04.44 04.44

04.69 04.69

04.32 04.32

03.51 03.51

03.63 03.63

(nmol (nmol of

03.47 03.47

03.38 03.38

03.43 03.43

03.41 03.41

03.32 03.32

min DNMRT

Activity

transcinnamic transcinnamic acid

and

DNMRT

12.58 12.58

22.51 22.51

41.05 41.05

37.30 37.30

35.32 35.32

51.43 51.43

07.28 07.28

48.12 48.12

50.77 50.77

26.71 26.71

ANOVA

11.92 11.92

12.58 12.58

11.03 11.03

08.61 08.61

and

24.06 24.06

% I OI C % by

‘Red Power’ under influence of

ANOVA

governed

4.53 4.53

6.22 6.22

6.13 6.13

6.39 6.39

5.51 5.51

5.62 5.62

5.55 5.55

6.86 6.86

6.71 6.71

6.83 6.83

5.07 5.07

5.10 5.10

5.03 5.03 5.10 5.10

variety

4.86 4.86

4.90 4.90

under influence under influence bacterial of strains

as /gram

PPO

(change (change in

Activity

absorbance /min absorbance /min

governed

varieties

E E

plants of

Red Power’ Red Power’

38.32 38.32

21.78 21.78

50.70 50.70

49.16 49.16 ‘

22.90 22.90

24.58 24.58

22.34 22.34

35.75 35.75

tomato

32.40 32.40

27.37 27.37

31.84 31.84

25.13 25.13

26.81 26.81

isolates

% I OI C %

all

Fol

all

against

1.79 1.79

2.18 2.18

2.19 2.19

2.67 2.67

2.24 2.24

2.20 2.20

2.24 2.24

2.23 2.23

2.43 2.43

2.28 2.28

2.50 2.50

2.36 2.36

2.31 2.31

2.36 2.36

2.37 2.37

/gram) against

0.05) as governed by ANOVA and and by ANOVA governed DNMRT. as 0.05)

(change (change in isolate

absorbance /min absorbance /min PO Activity PO

Fol

variety

single

32.73 32.73

41.66 41.66

42.25 42.25

41.07 41.07

42.85 42.85

45.83 45.83

54.16 54.16

48.80 48.80

57.73 57.73

35.11 35.11

36.30 36.30

tomato

34.52 34.52

49.40 49.40

38.09 38.09

47.02 47.02

% I OI C %

single

G G

significantly (

D of

)

interaction

1.68 1.68

2.32 2.32

2.38 2.38

2.39 2.39

2.37 2.37

2.40 2.40

2.59 2.59

2.51 2.51

2.50 2.50

2.23 2.23

2.26 2.26

2.65 2.65

2.27 2.27

2.29 2.29

2.45 2.45

2.47 2.47

catechol

Total

(

equivalents equivalents

released released g

Phenolics

interaction

significance

significance level

IAGS IAGS 002 IAGS IAGS 199

Changes Changes in defense related biochemicals in tomato

OSR OSR 3

MCR MCR 8

ZMR ZMR 3

ZMR ZMR 4

ZMR ZMR 6 show

level

Elucidation Elucidation of biochemical resistance of basis tomato in variety

FBL10

IAGS174

IAGS IAGS 170

MCR7

Treatments

IAGS IAGS 162

IAGS IAGS 223

IAGS IAGS 324

letters

show

letters

Capital

Untreated Control

Pathogenic Pathogenic Control

B. megateriumB.

B. subtilis B.

B. theruingenesisB.

B. fortis B.

B. fortis B. B. fortis B.

Values with same letter differ non differ letter with same Values Table 3.4: Table

Table 3.6: strains. Bacillus

Chapter: 3 Results

3.2.3:.Isozyme analysis of Peroxidases and Polyphenoloxidases

Peroxidase isozyme analysis was performed by Native PAGE analysis to investigate qualitative changes in peroxidase isozymes in plants exposed to selected bacteria. For that purpose, plants of all three tomato varieties were co-cultivated with selected bacterial strains and at final harvest, proteins were extracted from roots of responder portions. These proteins were electrophorised under native conditions and stained for peroxidase isozymes. Native PAGE analysis confirmed that selected bacterial strains induced tomato plants for over production of some peroxidase isozymes and production of some extra isozymes in all the three tomato varieties but with varying trends (Fig. 3.10).

A total of four isozymes (PO1, PO2, PO3 and PO4) were stained in bacterial treated and control plants of tomato varieties. Here PO1, PO2, PO3 were found in all the three varities (Fig. 3.10). Analysis revealed similar isoform expression in bacterial treated and control plants but differing in staining intensities. In plants of variety ‘Fine Star’ Peroxidase isozyme PO1 showed higher staining intensity in samples extracted from plants grown under the influence of B. fortis IAGS162, B. subtilis IAGS174 and B. megaterium ZMR3. Whereas, isozyme PO2 showed no difference in staining intensities of samples taken from control and treated plants (Fig. 3.10 A). For PO3 and PO4 isozymes, intense staining was recorded in samples from plants exposed to B. fortis IAGS162, B. subtilis IAGS174 and B. subtilis FBL10. Samples from plants only treated with selected pathogen showed intense staining of only single isozyme PO1 (Fig. 3.10 B). Similarly in case of tomato plants of ‘Rio Grande’ variety, a total of four isozymes were observed. In this variety, strains viz: B. fortis IAGS162, B. subtilis IAGS174 and B. megaterium ZMR4 provided intense staining for PO isozymes as compared to rest of the bacterial strains, pathogen control and untreated control.

Tomato varieties ‘Red Power’ revealed different pattern of isozymes in comparison to ‘Fine Star’ and ‘Rio Grande’. Here differences were not only observed in band intensities but also among number of total isozymes as revealed after staining for PO isozymes. This variety provided a total of five isozymes PO1, PO2, PO3, PO4 and

Chapter: 3 Results

PO5, but with varying trend of presence and intensities (Fig. 3.10 B). Bacterial strains B. fortis IAGS162, B. subtilis IAGS174 and B. megaterium ZMR4 provided intense staining for PO iozymes in this variety as compared to rest of the bacterial strains, pathogen control and untreated control (Fig. 3.10 B). One extra isozyme PO3 was expressed in tomato plants that got inoculum of B. fortis IAGS162 and B. subtilis IAGS174 on inducer side of roots in this variety. Pathogen alone was unable to provide drastic differences in isozyme pattern as compared to the untreated control (Fig. 3.10 B).

Polyphenol oxidase (PPO) isozymes were also studied by Native PAGE analysis. Gels were stained to visualize PPO isozymes. Observations were made to assess the ability of our selected bacterial strains for induction of changes in PPO isozymes pattern in treated plants. Change in staining intensity and number of isozymes were observed (Fig. 3.11). Some bacterial strains viz; B. fortis IAGS162, B. subtilis IAGS174, B. megaterium ZMR3 and B. megaterium ZMR4 were able to effectively alter PPO isozyme profile as compared to untreated control plants. All the three tomato varieties behaved in nearly similar way. In varieties, ‘Fine Star’ and ‘Rio Grande’ a total of three PPO isozymes PPO1, PPO2 and PPO3 were observed (Fig. 3.11). In tomato variety ‘Fine Star’ two PPO isozymes PPO1 and PPO3 were commonly found in all treatments with different intensities. Bacterial strains B. fortis IAGS162, B. subtilis IAGS174 and B. megaterium ZMR3 provided intense staining for both isozymes. Strain B. subtilis IAGS174 induced tomato plants for production of one extra isozyme PPO2 (Fig. 3.11 A).

Tomato variety ‘Rio Grande’ provided three PPO isozymes. Differences were seen in isozyme intensities and number as in “Fine Star’ variety. Plants treated with bacterial strains B. fortis IAGS162, B. subtilis IAGS174, B. megaterium ZMR3 and B. megaterium ZMR4 showed intense staining of PPO isozymes (Fig. 3.11B). Here one extra isozyme PPO2 was produced by ‘Rio Grande’ variety. Upon pathogen inoculation, this variety was unable to show any drastic variation in isozyme pattern in comparison with untreated control (Fig. 3.11B).

Tomato variety ‘Red Power’ behaved in different way. It showed a total of four PPO isozymes i.e. PPO1, PPO2, PPO3 and PPO4 (Fig. 3.11C). Two isozymes PPO2 and

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PPO3 provided nearly same staining intensities in all treatments. However, differences were observed in staining intensities for isozymes PPO1 and PPO4. Some bacterial strains like B. fortis IAGS162, B. subtilis IAGS174, and B. megaterium OSR3 provided intense staining for these two isozymes (Fig. 3.11C). Here pathogen also provided difference in isozyme profile as compared to untreated control. PPO4 was intensely stained in pathogen control in comparison to the untreated control.

PO1 PO2 PO3

PO4

PO1 PO2

PO3 PO4

PO1 PO2 PO3 PO4 PO5

Fig. 3.10: Native-PAGE analysis showing isoform pattern of peroxidases in plants of three different tomato varieties treated with selected Bacillus strains. A= Fine Star. B= Rio Grand. C= Red Power. T1=B. fortis IAGS324. T2=B. fortis IAGS223. T3=B. fortis IAGS162. T4=B. thuringiensis IAGS199. T5= B. thuringiensis IAGS002. T6=B. subtilis MCR7. T7=B. subtilis IAGS170, T8=B. subtilis IAGS174. T9=B. subtilis T10=B. subtilis FBL10. T11=B. megaterium ZMR6. T11=B. megaterium ZMR4. T12=B. megaterium ZMR3. T13=B. megaterium MCR8. T14=B. megaterium OSR3. PC= Pathogen control. UC= Untreated Control.

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PPO1 PPO2 PPO3

PPO1 PPO2 PPO3 PPO4 PPO5

Fig. 3.11: Native-PAGE analysis showing isoform pattern of polyphenol oxidases in plants of three different tomato varieties treated with selected Bacillus strains. A= Fine Star. B= Rio Grand. C= Red Power. T1=B. fortis IAGS324. T2=B. fortis IAGS223. T3=B. fortis IAGS162. T4=B. thuringiensis IAGS199. T5= B. thuringiensis IAGS002. T6=B. subtilis MCR7. T7=B. subtilis IAGS170, T8=B. subtilis IAGS174. T9=B. subtilis T10=B. subtilis FBL10. T11=B. megaterium ZMR6. T11=B. megaterium ZMR4. T12=B. megaterium ZMR3. T13=B. megaterium MCR8. T14=B. megaterium OSR3. PC= Pathogen control. UC= Untreated Control.

Chapter: 3 Results

3.3:.Elucidation of molecular, histological and biochemical basis of ISR mediated by Bacillus

strains against fusarium wilt of tomato

3.3.1:.Elucidation of molecular basis of resistance induced by

selected Bacillus strains against fusarium wilt

To investigate molecular basis of ISR provided by selected bacterial strains, another independent experiment was performed. Tomato seedlings of susceptible variety (Fine Star) were raised and transplanted in pots containing fusarium infested soil. In this experiment three treatments were made. In treatment one and two, plants got inoculum of B. fortis IAGS162 and B. subtilis IAGS174 respectively followed by pathogen challenge. Third treatment got only pathogen and served as control. Relative transcript levels of defense related mRNAs were analyzed by RT-PCR technique at different intervals. Transcript profile of selected defense related genes of each tomato variety under influence of bacterial inducers and pathogen is provided in figure 3.13.

Firstly, expression levels of each pathogenesis related protein (PR) genes which are also called defense related genes were normalized to constitutively expressed actin gene. Then it was observed that expression levels of PR genes in tomato plants provided with bacterial strains increased significantly as compared to water control after pathogen challenge. These results strongly indicate that expression of these defense related genes was up-regulated under the influence of these bacterial strains.

There were significant differences in induced expression levels of PR1 under influence of both bacterial strains as compared to the control at different time intervals. It was observed that expression of PR1 at 1day post inoculation (dpi), increased up to 1.92 and 2.37 folds under influence of B. fortis IAGS162 and B. subtilis IAGS174 respectively as compared to the control (Fig. 3.13).

Chapter: 3 Results

At 2dpi, B. fortis IAGS162 treated tomato plants showed 2.03 fold increase in PR1, while B. subtilis IAGS174 treated plants showed 2.28 fold increase in expression of PR1 gene as compared to non-treated control. After 4 days of inoculation, PR1 expression level reduced to nearly pre-challenge (0 dpi) expression level in all the three tomato varieties (Fig. 3.13).

For all the defense related genes that were analyzed, more pronounced and rapidly induced expression levels were observed for PR2 gene with pathogen challenge and bacterial inducers. Results indicated that expression of PR2 gene following pathogen challenge got increased up to 1.36, 2.08 and 2.92 folds at 0.5, 1 and 2 dpi under influence of B. subtilis IAGS174 as compared to water control. In the same way, when compared to control, maximum significant increase of 2.78 folds was provided by B. subtilis IAGS174 at 1 dpi. Here in B. fortis IAGS162 treated plants provided 0.83, 1.79 and 2.43 folds increase in expression levels of PR2 at 0.5, 1 and 2 dpi as compared to the non-treated control (Fig. 3.13).

Like PR1 and PR2 expression level of PR3 genes also significantly up regulated in tomato plants following pathogen challenge under influence of bacterial inducers. It was observed that expression of PR3 got increased up to 1.32, 1.97 and 1.12, 2.31 folds at 1 and 2 dpi as compared to 0 dpi under influence of B. fortis IAGS162 and B. subtilis IAGS174 respectively (Fig. 3.13).

Similarly, PR7 and CAT genes were also up regulated under influence of selected bacterial inducers in tomato plants following pathogen challenge. Transcript levels of PR7 got increased up to 0.87 and 1.62 folds under influence of B. fortis IAGS162 and 1.13 and 1.93 folds in plants treated with B. subtilis IAGS174 at intervals of 0.5 and 1 dpi respectively as compared to the non-treated control. Control plants provided differences of 0.63, 0.92 and 1.66 at 0.5, 1 and 2 dpi in expression of PR7 gene after inoculation of pathogen alone (Fig. 3.13).

Transcript levels of CAT gene increased significantly during time course analysis likewise rest of the PR genes. Here also plants represented pronounced effects as compared to the control. Here at initial time intervals of 0.5 and 1dpi, expression of CAT

Chapter: 3 Results gene was nearly same in bacterial treated plants in comparison to control plants exposed only to the pathogen (Fig. 3.13). Expression levels of CAT gene increased significantly 1.67 folds in tomato plants when treated with B. subtilis IAGS174 at 2 dpi interval as compared to 0 hour interval. Similarly an increase of 1.83 folds was recorded when tomato plants were treated with B. fortis IAGS162 (Fig. 3.13).

Fig. 3.12: Quantification of amplified product by GelAnalyzer Software.

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Fig. 3.13: Influence of Bacillus strains on expression of defense related genes in tomato plants. (*) represents treatments with statistically significant difference as compared to control as governed by ANOVA at P=0.05.

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3.3.2:.Elucidation of histological and histochemical basis of resistance induced by selected Bacillus strains against

fusarium wilt

This experiment was performed to elucidate histological basis of resistance in tomato plants as a result of induced systemic resistance. Here also single tomato variety ‘Fine Star’ was used as representative variety. Tomato plants were co-cultivated with bacterial resistance inducers followed by pathogen challenge. After one week of challenge, plants were investigated for histological and histochemical changes induced by bacterial microbes in the presence of pathogen. For that purpose, fine root and shoot sections were made. Central root was selected for root sectioning. Shoot sections were taken 10-15cm above ground level. Stained sections were observed under Nikon compound microscope and photographs were captured with Sony Cybershot 5.0 Megapixle camera fitted on eyepiece of microscope.

To observe deposition of lignin, phloroglucinol HCl staining was used. This stain gives red color to guaicyl lignin and pink to syringil lignin. Heavy lignin deposition was seen in plants receiving both inducers and pathogen in both root and shoot sections (Fig. 3.14 and 3.15). In root and shoot sections, cell walls were highly esterified with lignin compound. This esterification was more evident in vascular area (Fig. 3.14 and 3.15). Both strains provided esterification of lignin in vascular area but B. subtilis IAGS174 provided more intense lignification in root sample as compared to B. fortis IAGS162 which provided intense staining in case of root (Fig. 3.14 and 3.15). To observe histochemical changes, different specific stains were used capable of staining different defense related biochemicals. Ferric chloride was used to stain phenolics in plant sections. It gives black color to different phenolic acids. Likewise lignin, cell walls and cell lumens were highly esterified with phenolic compounds in root sections of plants receiving both inducer and pathogen (Fig. 3.14 and 3.15). This esterification was less evident in shoot tissues as compared to root sections. Pathogen alone was also capable of inducing phenolic compounds in root sections but with low

Chapter: 3 Results intensity (Fig. 3.14 and 3.15). Here both strains provided intense localization of phenolic compounds. Guaicol and hydrogen peroxide were used to observe localization of peroxidases. Both root and shoot sections were used for observations. These chemicals impaired brown color to peroxidases. Lumen of epidermal cells were highly esterified with peroxidases in plants receiving bacterial inducers in both root and shoot sections (Fig. 3.14 and 3.15). Here B. subtilis IAGS174 behaved in different way and provided more intense esterification of peroxidases (Fig. 3.14 and 3.15). In root section of plants treated with pathogen alone, esterification of peroxidase was negligible (Fig. 3.14 and 3.15).

Fig. 3.14: Influence of Bacillus strains on histology and cytochemistry of stem of tomato plants.

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Fig. 3.15: Influence of Bacillus strains on histology and cytochemistry of roots of tomato plants.

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3.3.3:.Elucidation of biochemical basis of resistance induced by

selected Bacillus strains against fusarium wilt

Metabolic changes in tomato plants were analyzed under influence of two different resistance inducers viz: B. fortis IAGS162 and B. subtilis IAGS174. Extensive metabolic profiling was carried out regarding primary and secondary metabolism of tomato plants by using an established gas chromatography–mass spectrometry GC/MS analysis (Fig. 3.16 and 3.17). For that purpose, a susceptible tomato variety was exposed to selected bacterial inducers individually. After one week of treatment, total metabolites were extracted and subjected to GCMS analysis after derivitization. Metabolites were quantified accurately by using dose response curve. More than 100 metabolites were identified including sugars, aminoacids, alcohols, organic acids, flavonoids, alkaloids, hormones and vitamins (Fig. 3.17, 3.18 and 3.19). Metabolite data sets were profiled in the form of heat map for control and treated plants (Fig. 3.18 and 3.19). These maps represent increase or decrease in metabolites in treated tomato plants relative to control by using false color scale. Tomato plants treated with these two bacterial strains viz: B. fortis IAGS162 and B. subtilis IAGS174 showed considerable overlap in quantities of different metabolites.

In case of plants grown under influence of B. fortis IAGS162, quantitative differences in different metabolites ranged between 0.073 and 5.978 times compared to metabolic quantities of control tomato plants. In total 109 metabolites belonging to different chemical groups were putatively identified by using three different MS libraries. These metabolites were assigned chemical formulae based on ionization patterns. Figure 3.18 represents quantitative changes induced by B. fortis IAGS162 in different metabolites expressed in the form of heat map. Among 103 different sugars observed, 83 were up-regulated in comparison to the control as represented in heat map (Fig. 3.18). Whereas, in case of plants treated with B. fortis IAGS174, quantitative differences in different metabolites ranged between 0.19 and 6.083 times compared to metabolic quantities of control tomato plants. In total 113 metabolites belonging to different chemical groups identified and were named by comparing with MS libraries. Figure 3.20

Chapter: 3 Results represents quantitative changes induced by B. subtilis IAGS174 in different metabolite expressed in the form of heat map. Among 113 metabolites observed, 83 were up- regulated in comparison with control and represented in heat map (Fig. 3.19).

3.3.3.1:.Change in organic acid contents

For purpose of metabolite analysis, different organic acids were quantified and comparisons were made among control and treated tomato plants. Considerably higher levels of different organic acids were observed in treated tomato plants. Aminobutyric acid, carboxylic acid, hydroxypropanoic acid, ribonic acid, Salicyclic acid and Succinic acid were among some organic acids that commonly increased in case of both bacterial strains (Fig. 3.18 and 3.19). In case of B. fortis IAGS162 treated plants, prominent increase was seen in levels of some organic acids like acetic acid, hexonic acid, malic acid and quinic acid. For some acids like hexonic acid, nanoic acid and uric acid, same level was observed in control and treated ones (Fig. 3.18). In plants exposed to B. subtilis IAGS174, higher quantities were denoted for acids like altronic acid, carboxilic acid, indole-3-acetic acid and sulfanilic acid as compared to the control (Fig. 3.19).

3.3.3.2:.Change in sugar and sugar alcohol contents

Some major sugars and sugar alcohols identified were fructose, glucose, glactose, mannose and Inositol. Contents of some sugars were much higher in tomato plants like sucrose, glucose and glactopyranose. Significantly higher amounts were observed in levels of galactopyranose, glucose and mannose, in plants treated with bacterial strain B. fortis IAGS162. In the same way, significant decrease was observed in quantities of some sugars like arabinopyranose and hexapyranose in plants grown under influence of B. fortis IAGS162 with respect to the level determined in control plants (Fig. 3.18). In plants treated with B. subtilis IAGS174, a major increase was recorded in levels of altropyranose, lyxose and ribose with respect to the control. Decrease in quantities was observed in levels of hexopyranose and D-glactosamine as compared to the control. The levels of sugars like arabinose remained same among control and treated ones (Fig. 3.19).

Chapter: 3 Results

under influence of influence under

plants

total metabolites of tomato metabolites total

IAGS162

B. fortis

showing changes in showing changes

IAGS174 IAGS174

subtilis

GCMS chromatograms GCMS chromatograms

Fig. 3.16: strains. Bacillus

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under influence of influence under

plants

GC/MS chromatogram showing change of tomato contents GC/MS in metabolite chromatogram

IAGS174.

Fig. 3.17 subtilis

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Fig. 3.18: Heat map showing changes in metabolites contents of tomato plants under influence of B. fortis IAGS162.

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Fig. 3.19: Heat map showing changes in metabolites contents of tomato plants under influence of B. subtilis IAGS174.

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3.3.3.3:.Change in amino acid contents Bacterial treated tomato plants were analyzed quantitatively for different amino acids. Major amino acids identified were alanine, cystine, glutamine, lysine and glutaminic acid, in tested tomato samples (Fig. 3.18 and 3.19).

Significantly higher amino acid contents were found in treated tomato plants as compared to the control ones. The differences observed in treated plants with respect to bacterial strains were variable. For example amino acids like alanine, cystine and phenylalanine were higher in tomato plants grown under influence of B. fortis IAGS162 as compared to the control plants (Fig. 3.18). In the same way, amino acids like cystine, lysine, phenylalanine and glutamic acid, increased in plants treated with B. subtilis IAGS174 as compared to the control (Fig. 3.19).

3.3.3.4: Other metabolites including alkaloids and flavonoids

In addition to metabolite groups described above, further metabolites were quantified that included alkaloids, flavonoids and some intermediates of metabolic cycles. Some alkaloids and flavonoids were marginally higher in bacterial treated plants but with varying extant. Some metabolites viz: amino chlorocoumarin, dihydroxy acetone, glycerone were found in higher quantities commonly for B. fortis IAGS162 and B. subtilis IAGS174 treated plants as compared to the treated one (Fig. 3.18 and 3.19).

In the same way, level of some metabolic cycle intermediates like castanospermine, cyclic AMP, D-glucoside, gibberlin, glutathione, phenolic phosphate and xanthine were observed in different quantities in control and treated tomato plants. The levels of metabolites like chlorocoumarine, cyclic AMP, D-ribulose-5-phosphate, dihydroxy acetone, glycerone and methyl quercetine, were higher in B. fortis IAGS162 treated plants in comparison to the control (Fig. 3.18). On the other hand B. subtilis IAGS174 supported the production of metabolites including chlorocoumarine, cyclic AMP, dihydroxy acetone, glycerone, phenolic phosphate, and thymidine monophosphate, in higher concentrations when compared to the control plants (Fig. 3.19).

Chapter: 3 Results

Some metabolites were found in higher quantities in control plants as compared to the treated tomato plants. These metabolites belonged to different groups. Some down regulated metabolites common in plants treated with both strains individually, were D- glucoside, 1-methyl-4-phenylpyridinium , as compared to the treated ones. On individual basis, down regulated metabolites in B. fortis IAGS162 treated plants included columbamine, D-dlucoside, and MPP+ (Fig. 3.18). In the same way in B. subtilis IAGS174 treated plants up-regulated metabolites were castanospermine, columbamine, pyrollidone and xanthine (Fig. 3.19).

3.3.3.5:.Impact of bacterial inducers on regulatory and metabolic pathways of tomato

Metabolites were annotated and grouped into respective biological processes and categories (Table 3.7). Some metabolites were grouped into unknown categories. In this experiment, when Bacillus treated plants were challenged with fusarium wilt pathogen, metabolites belonging to different categories were up-regulated compared to pathogen control plants. Moreover, metabolites were assigned into functional categories like signal transduction, response to stresses, nucleic acid metabolism, Pentose pathway, phenylpropenid pathway etc. Metabolites belonging to these biological functions were over presented under bacterial stimulus compared to the control plants (Table 3.7).

Metabolites in bacterial treated plants with significant changes over control were highlighted manually in photosynthesis-primary metabolism adopted from literature for both bacterial strains (Fig. 3.20 and 3.21). Visualization of metabolites affected by bacterial strains in tomato plants revealed global positive up-regulation of primary metabolic pathways and secondary metabolism like phenylpropenoid biosynthesis. Responses of metabolic processes in tomato under influence of bacterial inducers were attenuated further. For that purpose, a primary metabolic pathway was developed according to previously published literature, for both bacterial strains independently showing increase or decrease in quantity of metabolites related to different biological pathways (Table 3.7). In particular, metabolites involved in glycolysis, pentose pathway, signal transduction, phenylpropenoid and photosynthesis were up regulated under influence of both Bacillus strain as compared to the control (Table 3.7).

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Fig. 3.20: Effect of B. fortis IAGS162 on primary metabolism of tomato plants. Red color represents significantly up-regulated metabolites. Green color blocks represent significantly down-regulated metabolites.

Chapter: 3 Results

Fig. 3.21: Effect of B. subtilis IAGS174 on primary metabolism of tomato plants. Red color represents significantly up-regulated metabolites. Green color blocks represent significantly down-regulated metabolites.

Chapter: 3 Results

Table 3.7: Functional category distribution among differentially expressed metabolites of tomato plants under influence of Bacillus strains.

B. fortis IAGS162 B. subtilis IAGS174 Functional category Up Down Up Down regulated regulated regulated regulated Amino acid Metabolism 27 09 19 11 Carbohydrate Metabolism 15 06 27 13 Fatty acid Metabolism 31 17 39 24 Glycolysis 08 03 07 05 Pentose Pathway 09 04 07 03 Phenylpropenoids 06 - 07 02 Photosynthesis 11 02 15 04 Signal Transduction 14 03 12 07 Stress response 12 07 17 08 TCA cycle 05 04 06 02 Transport Activity 03 06 09 05 Unknown 13 07 22 14

Chapter: 3 Results

3.4:.Evaluation of best performing Bacillus strains for

their plant growth promoting efficacy

3.4.1:.Potential of selected Bacillus strains to promote growth of tomato plants under greenhouse conditions

Bacterial strains under investigation significantly improved growth aspects of tomato plants (Fig. 3.23, Table 3.8). A significant increase was recorded in shoot lengths of all the three tomato varieties under influence of both bacterial inducers. B. subtilis IAGS174 provided 43.87 to 56.44% increase in shoot length of tomato plants across all the three tomato varieties as compared to the non-treated control plants (Table 3.8). In the same way, B. fortis IAGS162 increased shoot length ranging between 34.61 to 48.82% across all the three varieties (Table 3.8).

Root length was also significantly increased under influence of both bacterial inducers. A significant increase of 37.9, 42.3 and 37.6% in root length was recorded in ‘Fine Star’, ‘Rio Grande’ and ‘Red Power’ respectively under influence of B. subtilis IAGS174. Whereas the second strain (B. fortis IAGS162) provided 23.2 to 46.8% increase in root length across all the three varieties as compared to the untreated control (Table 3.8).

Selected bacterial strains also significantly increased biomass of tested tomato varieties (Table 3.8). B. subtilis IAGS174 provided 47.3 to 69.5% increase in fresh biomass across all the three varieties as compared to the untreated controls. B. fortis IAGS162 increased fresh biomass ranging between 37.6 to 59.1% in all the three tomato varieties (Table 3.8). B. fortis IAGS162 provided 31.7 to 56.6% increase in dry biomass across all the three tomato varieties (Table 3.8). In case of B. subtilis IAGS174, increase in dry biomass ranged between 21.2 to 39.6% across all the tomato varieties (Table 3.8).

Chapter: 3 Results

3.4.2:.Effect of selected Bacillus strains on total chlorophyll, carotenoids and total soluble sugar contents of tomato plants

Some biochemicals like total chlorophyll content, carotenoids and total soluble sugars are considered as biomarkers of plant growth. Selected Bacillus strains significantly (P< 0.05) up regulated synthesis and production of these biochemicals in all the three tomato varieties as compared to the untreated control plants (Fig. 3.24). Bacillus subtilis IAGS174 and B. fortis IAGS162 increased production of total chlorophyll contents up to 1.87 and 1.57 folds in all the three tomato varieties on average basis as compared to the untreated plants (Fig. 3.24). Carotenoids content of tomato plants also increased up to 1.67 and 2.06 folds on average basis for all three varieties when treated with B. fortis IAGS162 and B. subtilis IAGS174 respectively (Fig. 3.24).

In the same way, significant increases were observed for total soluble sugar contents. These got nearly doubled in bacterial treated plants as compared to untreated control. Like total chlorophyll and carotenoid contents, B. subtilis IAGS174 provided more pronounced increment in total soluble sugars in all the three tomato varieties (Fig. 3.24). Tomato plants co-cultivated with this strain showed 2.23 fold higher total sugar contents on average basis as compared to the untreated control, whereas B. fortis IAGS162 caused 1.72 folds increase in sugar level on average basis in all the three tomato varieties as compared to the non-treated control plants (Fig. 3.24). 3.4.3:.Characterization of selected Bacillus strains for production of plant growth promoting substances

Selected Bacillus strains were screened for production of different plant growth promoting substances. To observe auxin synthesis, bacterial strains were grown on LB agar media provided with tryptophan. After incubation, supernatant of bacterial growth media was reacted with Salkowski reagent. Pink color developed provided evidence for production of auxins. Both bacterial strains were found positive for auxin production (Fig. 3.22C, Table 3.9). Quantitative assay proved that bacterial strain B. subtilis

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IAGS174 was able to produced 29.5 and 35.6% higher quantities of IAA in the presence and absence of L-tryptophan respectively (Fig. 3.22C; Table 3.9).

Siderophores production was assessed by allowing bacteria to grow in the presence of an iron salt. Here production of orange hallo around bacterial colony was taken as positive result for production of siderophores by selected Bacillus strains. Only Bacillus subtilis IAGS 174 showed evidence for siderophores production (Fig. 3.22B; Table 3.9).

Phosphate solubilization ability of selected Bacillus strains was estimated by growing them on Pikovskaya’s medium and production of clear zone denoted positive results. Both Bacillus strains provided positive response in this evaluation (Fig. 3.22A, Table 3.9). Like IAA production, B. subtilis IAGS174 provided 44.8% more phosphate solubilization activity as compared to B. fortis IAGS162 (Fig. 3.22A; Table 3.9).

Fig. 3.22: Characterization of Bacillus strains for production of plant growth related substances. A= Phosphate solubilization. B= Siderophores production. C= IAA production.

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Fig. 3.23: Effect of Bacillus strains on growth of tomato plants of variety ‘Fine Star’.

102

Chapter: 3 Results B C A . B (01.71) (01.92) (01.07) = 9.96 9.96 7.26 7.26 5.60 2 Dry subtilis T . . ) B 1 – B C A . = 162 B A 2 T 08.35) 14.38) (05.25) (07.64) (02.81) + + . 182 329 ( ( 73.68 IAGS 62.42 38.61 Fresh (μg mL (μg Total Biomass (g) Biomass Total 162 Phosphorus solubilization treatment B C A fortis . IAGS . Red Power Power Red (03.56) (04.22) (02.51) same B (cm) 32.81 32.81 20.11 = 26.20 26.20 Root Root of 1 Length . fortis T . . ) B B C A treatment = 05 . 1 ) (05.92) (02.54) (03.82) 0 1 T replicates – > (cm) 43.88 43.88 31.05 31.05 22.55 same . Shoot P ) Length ( 0.08) of ND + 05 2.23 solubilization ( . at B C 0 A (μg mL (μg > different P ( (01.48) (00.81) (00.92) Dry 07.49 07.49 05.36 05.36 04.07 at replicates DNMRT Siderophores production Siderophores phosphorus B C A between and . and (05.76) (03.24) (03.51) DNMRT different error 49.74 49.74 43.28 43.28 23.55 Fresh Total Biomass (g) Biomass Total and B A ANOVA varieties B C A Tryptophan 0.83) 1.32) - between + + by standard ( ( (03.53) (02.86) (01.17) 09.79 ) 15.07 Rio Grande Grande Rio siderophores 22.75 (cm) 26.12 26.12 15.73 15.73 Root Root ANOVA tomato Length mL error / With L With by IAA, μg B C A represent three governed of (02.57) (04.60) (02.62) of as standard (cm) 37.33 37.33 23.18 23.18 20.04 Shoot signs Length governed + as C A AB production with represent (01.82) (00.94) (00.81) parameters Tryptophan B A for - Dry 06.92 06.92 IAA Production ( Production IAA 04.15 significantly 05.89 05.89 0.02) 0.07) + + ( ( 0.83 1.39 signs Values . + B A A growth strains differ significantly on (06.51) (04.67) (02.57) Without L Without with not 51.47 51.47 56.57 31.17 31.17 Fresh Control (g) biomass Total differ do Bacillus strains B C A not of Values . Fine Star Fine do (04.43) (03.21) (02.86) letters 18.17 Untreated (cm) 29.10 29.10 23.55 23.55 Root Root Length Bacillus IAGS174 Control IAGS 162 IAGS same of letters UC= B C A . the (03.44) (06.87) (02.19) 174 same Effect subtilis Characterization (cm) 32.44 32.44 26.51 26.51 17.57

. Shoot B. fortis B. Length :

: Untreated B. B. the

9 15 . 14 IAGS . sharing 3 Bacterial Bacterial species 3 :

UC= Treatments . T1 T2 UC sharing Table Values subtilis Table

Table 3.8: Table 3. 174 Values IAGS

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B. fortis IAGS162 B. subtilis IAGS174 Control

(mg/g FW)

Total contents chlorophyll

(µg/g FW)

Carotenoids contents

(%)

Total contents sugar

Fine Star Rio Grande Red Power

Fig. 3.24: Effect of Bacillus strains on total chlorophyll, indole acetic acid and total soluble sugars of tomato plants. Values with same letter differ non-significantly (P>0.05) as governed by ANOVA and DNMRT. Vertical bars represent standard error between different replicates of same treatment.

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3.5:.Development of bacterial formulation and field evaluations of best performing Bacillus strains

3.5.1: Selection of carrier material for development of bacterial formulation

This experiment was performed to select carrier material for inoculum development of best performing Bacillus strains. Four carrier materials were screened in this regard. These formulations were stored under room temperature for maximum of three months. Among all three carrier materials, talc performed best as provided significantly highest numbers of viable bacterial count. On average basis, viability of bacterial propagules was more than 80% at the end of three month storage period for all three bacterial formulations in talc based formulation viz: (B. fortis IAGS162), (B. subtilis IAGS174) and (B. fortis IAGS162 + B. subtilis IAGS174) (Fig. 3.25). Bentonite performed second best in this regard and viability remained 71.3, 66.5 and 69.1% in case of (B. fortis IAGS162), (B. subtilis IAGS174) and (B. fortis IAGS162 + B. subtilis IAGS174) at the end of storage period (Fig. 3.25). In soil and saw dust, viability of bacterial propagules reduced more than 50% for all types of bacterial formulations (Fig. 3.25).

3.5.2:.Efficacy of bacterial formulation to manage fusarium wilt under field conditions

Bacterial strains that performed best under greenhouse conditions were further evaluated for their efficacy under field conditions. Talc based formulations of B. fortis IAGS162 and B. subtilis IAGS174 strains were used individually and in combination (B. fortis IAGS162 + B. subtilis IAGS174) to test their efficacy against fusarium wilt in the fields (Fig. 3.27 and 3.28). These treatments significantly reduced disease as compared to untreated plants but with varying effectiveness. As evident from the data, bio control effect was maximum under treatment T3 in which both bacterial strains were applied in combination (B. fortis IAGS162 + B. subtilis IAGS174) (Table 3.10 and 3.11). This

105

Chapter: 3 Results treatment reduced disease index up to 63.9 and 52.9% and provided bio control effect of 61.6 and 57.9% on average basis in all the three tomato varieties when checked in 2011 and 2012 respectively (Table 3.9 and 3.10). Bacillus subtilis IAGS174 (T2) induced bio control effect of 52.6 and 45.6% by reducing disease index up to 47.9 and 41.2% during 2011 and 2012 respectively (Table 3.10 and 3.11). Plants receiving treatment T1 i.e. B. fortis IAGS162 showed least biocontrol effect. On average they showed 41.3 and 34.1% biocontrol effect over untreated plants in experiments performed during 2011 and 2012 respectively (Table 3.10 and 3.11).

3.5.3:.Efficacy of bacterial formulation to promote growth and yield of tomato plants under field conditions

Effect of these bacterial treatments on growth of tomato plants under field conditions was also explored. Data presented in Table 3.12 and 3.13 demonstrates responses of selected tomato varieties regarding growth parameters as effected by selected Bacillus strains either alone or in combinations after one month of transplantation in fields.

Highest significant (P< 0.05) increase of 51.2 and 43.7 % in plant height was measured on average basis for all the three tomato varieties for the years 2011 and 2012 respectively when inoculum of combined inducers was provided (T3) (Table 3.12 and 3.13). Whereas, B. subtilis IAGS174 (T2) performed next to T3. This strain promoted shoot length of tomato plants up to 39.3 and 33.1% on average basis in all the three varieties as compared to the untreated control during the years 2011 and 2012 respectively (Table 3.12 and 3.13).

Bacterial inducers also provided significant (P< 0.05) increase in total fresh and dry biomass of tomato plants. Treatment T3 (B. fortis IAGS162 + B. subtilis IAGS174) increased fresh biomass of shoots up to 63 and 54% in the years 2011 and 2012 respectively on average basis of all the three tomato varieties as compared to the non- treated control plants (Table 3.12 and 3.13). Here T2 (B. subtilis IAGS174) performed as second significant treatment and increased fresh biomass up to 42.6 and 36.9% on

106

Chapter: 3 Results average basis across all the three varieties as compared to the non-treated control plants in the years 2011 and 2012 respectively (Table 3.12 and 3.13). Whereas, T1 (B. fortisIAGS162) increased shoot fresh biomass up to 31 and 29% on same basis in the years 2011 and 2012 respectively. Similar effect was recorded on dry biomass. T3 (B. fortis IAGS162 + B. subtilis IAGS174) induced tomato plants for maximum dry biomass production. Dry biomass increased up to 41.4 and 33.7% on average basis in all the three tomato varieties in the years 2011 and 2012 under influence of T3 as compared to the non-treated tomato plants (Table 3.12 and 3.13). Little variation was recorded among varieties. On individual basis, dry biomass increased up to 47.1, 39.5 and 41.3% in tomato varieties ‘Red Power’, ‘Rio Grande’ and ‘Fine Star’ respectively under influence of T3 in the year 2011 (Table 3.12). Whereas T2 (B. subtilis IAGS174) elevated dry biomass up to 36.2, 29.8, and 38.4% in tomato varieties ‘Red Power’, ‘Rio Grande’ and ‘Fine Star’ respectively in the year 2011 (Table 3.13).

Along with protection from disease, these selected bacterial strains promoted plants for increased fruit set and yield. At final harvest, tomato plants were analyzed for fruit number and yield. Significant increases were recorded in total number of fruits and yield in tomato plants which received bacterial inducers either alone or in combination (Fig. 3.29). Like disease control and vegetative growth, maximum significant number of fruits per plant was observed where both strains were provided in combination (T3) (Table 3.12 and 3.13). In (T3) fruit set was increased up to 43.8 and 39.5% on average basis for all the three tomato varieties as compared to untreated control for the years 2011 and 2012 respectively (Fig. 3.29). Bacillus subtilis IAGS174 (T2) followed this and provided an increase of 32.7 and 26.4 % when plants were challenged with this bacterial strain in the year 2011 and 2012 respectively (Fig. 3.29). On individual basis, T3 promoted 47.2, 32.8 and 35.4% more fruit set in tomato variety ‘Red Power’ ’Rio Grande’ and ‘Fine Star’ respectively in the year 2011 (Fig. 3.29). Whereas in the year 2012, an increase of 39.6, 28.5 and 31.2% in fruit number was recorded when compared to the untreated control (Fig. 3.29).

To denote increase in yield, five plants were randomly selected from plot of each treatment at final harvest and total weight of fruits was determined. Treatment in which

107

Chapter: 3 Results tomato plants were co-cultivated with both bacterial strains (T3), increased yield up to 47.8 and 41.7% on average basis for all the three tomato varieties in the years 2011 and 2012 respectively as compared to the untreated control (Table 12 and 13). Whereas T2 (B. subtilis IAGS174) provided increase in yield up to 38.1 and 33.9% on average basis in the years 2011 and 2012 respectively in comparison to the untreated control (Fig. 3.29).

Fig. 3.25: Viability of bacterial propagules in different carrier materials. A= B. fortis IAGS162. B=B. subtilis IAGS174. C=B. fortis IAGS162+ B. subtilis IAGS174.

108

Chapter: 3 Results

Fig. 3.26: Different stages of field experiment for management of fusarium wilt of tomato under influence of Bacillus strains.

109

Chapter: 3 Results

A B

C D

Fig. 3.27: Field efficacy of Bacillus strains for management of fusarium wilt of tomato of variety ‘Fine Star’ during the year 2011. A= B. fortis IAGS162 + B. subtilis IAGS174 + Fol. B = B. subtilis IAGS174 + Fol. C= B. fortis IAGS162 + Fol7. D= Pathogen control. E= Untreated control.

110

Chapter: 3 Results

A B

C D

Fig. 3.28: Field efficacy of Bacillus strains for management of fusarium wilt of tomato of variety ‘Fine Star’ during the year 2012. A= B. fortis IAGS162 + B. subtilis IAGS174 + Fol. B = B. subtilis IAGS174 + Fol. C= B. fortis IAGS162 + Fol7. D= Pathogen control. E= Untreated control.

111

Chapter: 3 Results

+ B C A -

ented ND ND 07.38) 03.81) 09.52) ed ed here. + + + ( ( ( 68.15 68.15 58.07 58.07 47.29 ent

year 2011. year

Effect (%) Effect Bio Control Control Bio

the

B A D BC ND 05.68) 03.16) 05.78) 07.56) Red Power Power Red + + + + ( ( ( ( 83.67 83.67 46.29 46.29 23.87 23.87

PC= PathogenPC= control. UC= 37.86 37.86

(%) Disease index Disease Values same with letter non differ Values

IAGS174. C B A

ND ND 07.57) 04.83) (08.34) + + ( ( 71.52 71.52 42.53 42.53 54.51 IAGS174. Effect (%) Effect

B. subtilis Bio Control Control Bio

subtilis B. B. signs represent represent signs standard error between replicates different of B A D BC + ND

0.05) as governed by ANOVA and DNMRT. Values with 11.32) 06.95) 07.26) 03.57) Rio Grande Grande Rio +

> + + +

IAGS162 + ( ( ( (

P 79.39 79.39 22.11 22.11 33.53 33.53 28.16 28.16 (%) IAGS162 + IAGS162

B. fortis Disease index Disease fortis C B A

significantly ( B. B.

- ND ND 08.84) 06.43) 09.15) + + + ( ( ( 64.58 64.58 53.33 53.33 57.28 management management under field conditions the in year 2011. Effect (%) Effect

IAGS174. T3=

Bio Control Control Bio IAGS174. T3= T3= IAGS174. fusarium B C A CD ND Fine StarFine

B. subtilis 03.60) 05.29) 02.90) 07.88) + + + + ( ( ( ( 61.09 61.09 29.30 29.30 22.67 subtilis 19.42 19.42 (%) B. B. Disease index Disease

IAGS162.T2=

Values with same letter differ non

0.05) as governed by ANOVA and DNMRT. Values with Values and DNMRT. ANOVA 0.05) as governed by >

Potential of bacterial formulation to manage fusarium wilt under field conditions in fusarium field wilt under to manage formulation Potential bacterial of

P IAGS162. T2= T2= IAGS162. Effect Bacillus of Effect on strains

B. fortis B. T1 T2 T3 PC UC fortis Treatments B. B. Disease parameters parameters Disease were taken after one monthtransplantation of the in fields and mean values three of replicates are repres T1= significantly ( treatment. same

Table 3.10:

Disease parameters were taken after one month of transplantation in the fields and mean values of three replicates are repres here. T1= Untreated control. signs represent standardbetween error different replicates of same treatment. Table 3.16: 3.16: Table

112

Chapter: 3 Results

ented

10.62)

06.46)

05.82)

ed ed here.

(

76.87 76.87

64.08 64.08

62.34 62.34 ent

year 2012. year

Effect (%) Effect Bio Control Control Bio

the B

PC= Pathogen control.

A D

08.61)

02.66)

04.50)

05.28)

Red Power Power Red

(

75.93

31.11 31.11

19.57 19.57

28.81 28.81 (%)

IAGS174.

Disease index Disease

Values same with letter non differ Values

2012.

09.62)

04.46)

06.53)

+ +

B. subtilis

(

( (

62.36 62.36

57.66 57.66

51.08 51.08

IAGS174.

Effect (%) Effect Bio Control Control Bio

0.05) as governed by ANOVA and DNMRT. Values

> subtilis

IAGS162 +

B. B.

signs represent represent signs standard error between replicates different of

A D

09.50)

02.86)

04.55)

03.87)

Rio Grande Grande Rio

(

71.30 71.30

29.39 29.39

19.07 19.07 24.68 24.68

B. fortis

(%) IAGS162 + IAGS162

significantly (

Disease index Disease

fortis

B. B.

11.57)

13.70)

07.93)

(

73.60 73.60

62.76 62.76 46.60 46.60

IAGS174. T3= management management under field conditions the in year

Effect (%) Effect

Bio Control Control Bio

IAGS174. T3= T3= IAGS174.

fusarium

A D

B. subtilis

Fine StarFine

14.68)

04.71)

03.95)

06.53)

(

73.57 73.57

28.11 28.11

35.21 35.21

18.96 18.96

subtilis

(%) B. B.

Values with same letter differ non Disease index Disease

AGS162. T2=

0.05) as governed by ANOVA and DNMRT. Values with Values and DNMRT. ANOVA 0.05) as governed by

P IAGS162. T2= T2= IAGS162.

Potential of bacterial formulation to manage fusarium wilt under in conditions to manage field formulation bacterial of Potential

B. fortis

Effect Bacillus of Effect on strains

PC UC

signs represent standard error betweendifferent replicates of same treatment. fortis

Treatments

3.17: 3.17: B. B.

Disease Disease parameters were taken after one month of transplantation in the fields and mean values of three replicates are repres here. T1= UC= Untreated control. with

same treatment. treatment. same

significantly significantly (

T1= T1=

Disease parameters parameters Disease were taken after one monthtransplantation of the in fields and mean values three of replicates are repres Table Table

Table 3.11:

113

Chapter: 3 Results

nted

year 2011. year

A ed ed here.

the

03.48)

06.39)

02.26)

04.80)

Dry

(01.05)

(

22.32

28.26

19.66

35.53

33.48

ent

2012.

DE BC

0.05). Values with Total Biomass (g) Biomass Total

17.53)

14.82)

15.83) 16.96)

(13.58)

(

Fresh Fresh

153.26

123.81

166.52

103.96

149.06 Red Power Red

PC= PC= Pathogen control. UC=

03.59)

02.82)

03.19)

03.58)

(cm) (cm)

(04.28)

Plant Plant

(

32.22

47.52

44.26

29.17

52.33

Height Values same with letter non differ Values

IAGS174.

01.81)

03.95)

03.07)

02.59)

IAGS174.

Dry

(01.47)

(

( (

B. subtilis

06.43

11.68

22.40

16.52 20.26

subtilis

B. B.

signs represent represent signs standard error between replicates different of

Total Biomass (g) Biomass Total

12.51)

19.62)

08.86)

09.55)

+ (08.36)

IAGS162 +

(

Fresh Fresh 56.08

117.52

76.31

126.80

103.53

Rio Grande Rio

A AB

B. fortis

IAGS162 + IAGS162

04.64)

05.58)

05.48)

07.82)

(cm) (cm)

(03.17)

Plant Plant

(

22.86

13.98

37.82

Height

33.12

30.52

fortis

B. B.

03.73)

05.16)

03.51) 02.99)

IAGS174. T3=

Dry

+ +

(02.03)

(

11.64

16.68

22.42

30.92

27.82

IAGS174. T3= T3= IAGS174.

C D

B. subtilis

Total Biomass (g) Biomass Total

10.48)

17.23)

12.05)

16.23)

(12.58)

(

Fresh Fresh

98.63

74.08

131.82

141.07

136.62

subtilis

Fine Star Fine

B. B.

05.11)

06.73)

03.88)

04.52)

(cm) (cm) (01.17)

IAGS162. T2=

Plant Plant

(

( (

Capital letters represents levels of significance as governed by ANOVA and DNMRT at (

21.14

37.23 44.90

Height

32.52

28.63

0.05) as governed by ANOVA and DNMRT. Values with Values and DNMRT. ANOVA 0.05) as governed by

P IAGS162. T2= T2= IAGS162.

Effect of bacterial formulation on growth and yield of tomato plants under field conditions field under plants of bacterial tomato in on growth yield of formulation and Effect

B. fortis Effect Bacillus of Effect on plant strains parameters growth tomato of plants under field during conditions the year

Treatment

fortis

3.19: 3.19: B. B.

ntreated control.

Growth parameters were taken after one month of transplantation in the here. T1= fields and mean values of three replicates are represe U signs represent standardbetween error different replicates of same treatment.

same treatment. treatment. same

significantly significantly (

T1= T1=

Disease parameters parameters Disease were taken after one monthtransplantation of the in fields and mean values three of replicates are repres Table Table

Table 3.12:

114

Chapter: 3 Results

year 2012. year E B A D

BC - 06.56) 09.34) 07.27) 02.67) (01.88)

the + + + + ( ( ( ( ed ed here.

11.58 31.69 37.52 18.89 Dry 29.54 ent

nted here. T1= 2011. E

ntreated control. A D BC AB 12.15) 21.58) 05.96) 09.27) (09.51) + + + + Total Biomass (g) Biomass Total year year ( ( ( ( 72.36 172.80 138.26 Fresh Fresh

signs represent standard 163.26 168.52

Red Power Red

+ E C A D AB 11.26) 05.35) 08.26) 04.02) (01.84) + + + + ( ( ( ( 26.58 48.58 69.42 37.35 (cm) (cm) 61.82 Plant Plant Height Height Values same with letter non differ Values B A D - DE BC B 02.90) 05.82) 05.32) 02.74) (09.62)

0.05). Values with + + + + ( ( ( (

PC= PathogenPC= control. UC= U

> 21.52 23.81

IAGS174. Dry 08.36 18.52

P 14.96 E C A D subtilis AB 13.28) 17.24) 18.15) 06.31)

IAGS174. (08.73) B. B.

signs represent represent signs standard error between replicates different of + + + + Total Biomass (g) Biomass Total ( ( ( ( 76.98 94.26 + 111.28 139.96 Fresh Fresh 126.85

ield of tomato plants under field conditions field under plants tomato in ield of Rio Grande Rio B A

B. subtilis DE BC CD IAGS162 + IAGS162 07.11) 07.51) 05.23) 01.51) (01.91) + + + + ( ( ( ( 36.86 41.05 (cm) (cm) 21.72 31.51 27.64 Plant Plant Height Height fortis B. B. E C B A

IAGS162 +

on growth y and 05.11) 07.11) 06.27) 02.92) (02.77) + + + + ( ( ( ( 10.43 20.42 25.08 33.05 Dry 18.19

B. fortis E C A D IAGS174. T3= T3= IAGS174. AB 16.06) 26.32) 19.95) 15.56) (11.58) + + + + Total Biomass (g) Biomass Total ( ( ( ( 89.43 113.26 126.04 146.72 Fresh Fresh 131.56 subtilis Fine Star Fine

rial formulation formulation rial B. B.

IAGS174. T3= B E

A BC CD 06.13) 07.26) 04.28) 02.77) + (04.35) + + + ( ( ( ( 43.45 28.37 48.02 (cm) (cm) 39.21 32.93 Plant Plant Height Height

B. subtilis 0.05) as governed by ANOVA and DNMRT. Values with Values and DNMRT. ANOVA 0.05) as governed by > P IAGS162. T2= T2= IAGS162.

Effect of bacte Effect

Effect Bacillus of Effect on plant strains parameters growth tomato of plants under field during conditions the Treatment fortis T1 T2 T3 PC UC 3.18: 3.18: B. B.

IAGS162. T2=

Disease parameters parameters Disease were taken after one monthtransplantation of the in fields and mean values three of replicates are repres T1= significantly ( treatment. same Table Table

Table 3.13:

Growth parameters were taken after one month of transplantation in the fields and mean values of three replicates are represe B. fortis Capital letters represents levels of significance as governed by ANOVA and DNMRT at ( errorbetween different replicates of same treatment.

115

Chapter: 3 Results

Fig. 3.29: Effect of bacterial strains on fruit set and yield of tomato plants under field conditions. Values represented are mean of three replicates. Data was taken three months after transplantation in fields. Small letters represents level of significance as governed by ANOVA and DNMRT at (P>0.05). T1=B. fortis IAGS162. T2=B. subtilis IAGS174. T3= B. fortis IAGS162 + B. subtilis IAGS174. PC= Pathogen control. UC= Untreated control.

116

Chapter: 3 Results

3.6:.Screening of ISR determinants from selected Bacillus strains

3.6.1:.Preliminary screening of potential ISR determinants from selected Bacillus strains

In this experiment efforts were made to screen out determinates of ISR from B. fortis IAGS162 and B. subtilis IAGS174. For that purpose fusarium wilt susceptible tomato variety ‘Fine Star’ was used. Initially both intra and cell free culture filtrates (CFCF) were checked for their abilities to suppress fusarium wilt under greenhouse conditions. Here alive cells of both strains were used as positive control. After fifteen days of incubation, disease index and bio control effects were analyzed (Table 3.14 and Fig. 3.30).

During initial screening of ISR determinant/s, extracellular metabolites, also termed as cell free culture filtrate (CFCF) of both bacterial strains suppressed fusarium wilt effectively as compared to intracellular metabolites. These CFCF were effective in reducing disease severity more than 60% as compared to the pathogen control for both bacterial strains. Cell free culture filtrates were found as effective as parent strains (Table 3.14; Fig. 3.30).

Intracellular metabolites of both bacterial strains provided minimum disease control as compared to the rest of the treatments viz: alive cell suspensions and intracellular metabolites. These reduced disease index up to 07.91 and 11.38% as compared to the pathogen control plants in case of B. fortis IAGS162 and B. subtilis IAGS174 respectively (Table 3.14; Fig. 3.30). 3.6.2:.Isolation of ISR determinants from cell free culture filtrates of selected Bacillus strains

In second phase of ISR determinants, extracellular metabolites were fractionated with different organic solvents (Fig. 3.31) and extracted organic and rest of the aqueous phases were added in MS plant growth medium for ISR assay. Tomato plant and

117

Chapter: 3 Results pathogen were co-cultivated in this MS medium. ISR active fractions were screened based on disease severity on visual basis. It was evident from results that ethyl acetate fraction from B. subtilis IAGS174 and n-butyl acetate phases of B. fortis IAGS162 provided maximum protection to tomato plants as compared to the rest of the phases (Fig. 3.22).

Table 3.14: Preliminary screening of ISR determinants from selected Bacillus strains. B. fortis IAGS162 B. subtilis IAGS174 Treatments Disease Bio Control Disease Bio Control Index (%) Effect (%) Index (%) Effect (%) 22.18 D 69.33 AB 33.55 D 51.23 AB Live cells (+03.82) (+04.29) (+02.82) (+02.09) 81.06 AB 14.03 EF 79.21 C 12.34 CD Heat killed cells (+11.26) (+00.92) (+09.13) (+01.57) Intra-cellular 78.92 B 19.51 E 58.18 B 39.67 E components (+06.91) (+01.68) (+02.66) (+02.28) Extracellular 34.38 C 57.41 CD 29.08 AB 64.52 EF metabolites (+02.08) (+06.26) (+01.97) (+04.21) 86.53 A 81.38 A Pathogen control - - (+11.47) (+05.42)

Capital letters represents levels of significance as governed by ANOVA and DNMRT at (P>0.05). Values with + signs represent standard error between different replicates of same treatment.

118

Chapter: 3 Results

B. B.

B. fortis

cellular cellular components of

IAGS174. IAGS174. T4= CFCF of

Bacillus strains. T1= Alive cells of

subtilis

selected

IAGS174. IAGS174. T6= Intra

treated control.

B. subtilis

IAGS162. IAGS162. CFCF of

B. fortis

cellular components of

C= Pathogen control. UC= Un control. Pathogen C=

Preliminary screening of ISR determinants from

IAGS174. IAGS174. Alive cells of

IAGS162. P IAGS162.

` Fig. 3.30 subtilis IAGS162. T5= Intra fortis

119

Chapter: 3 Results

Fig. 3.31: Flow sheet of whole process involved in searching ISR determinant/s from B. fortis IAGS162.

120

Chapter: 3 Results

Fig. 3.32: GC/MS Chromatogram of ISR active sub-fraction of cell free culture filtrates of B. fortis IAGS162. A= GC/MS chromatogram. B= Ionization pattern of ISR determinant from B. fortis IAGS162.

121

Chapter: 3 Results

3.6.3:.Identification of ISR determinant by GC/MS analysis

ISR active phases were subjected to column chromatography by stepwise elution and resulting fractions were again tested for ISR in MS medium as in previous experiment. Fractions providing maximum protection against disease were subjected to GCMS analysis for elucidation of biochemicals present in these fractions. Bacillus fortis IAGS162 provided five biochemicals viz: tyrosine, thymol, acetic acid methyl ester, methoxy butanol, palmitic acid (Fig. 3.32). Whereas, B. subtilis IAGS174 provided four biochemicals in ISR active fraction viz: eugenol acetate; thymol, 3-methoxy butyl acetate and phthalic acid methyl ester (Fig. 3.32).

3.6.4:.ISR bioassays with pure compounds

This experiment was performed to screen pure ISR determinant. Pure bio chemicals were added in MS medium at final concentrations of 0.01, 0.1 and 1.0 mM and ISR assay was performed again by co-cultivating tomato and pathogen in MS media. Fig. 3.31 and 3.33 represents detailed flow sheet process of identification of potential ISR determinant/s from both bacterial strains. From disease index it was evident that biochemicals providing maximum reduction in disease index were benzene acetic acid (also known as phenyl acetic acid) from B. fortis IAGS162 (Fig. 3.31 and 3.35A) and dimethyl phthalate from B. subtilis IAGS174 (Fig. 3.33 and 3.35B). Benzene acetic acid provided 23.15, 34.47 and 67.85% reduction in disease index at concentrations of 0.01, 0.1 and 1.0mM respectively as compared to control (Fig. 3.35A). In the same way, dimethyl phthalate provided 58.4 and 76.7% reduction in disease index at concentrations of 0.01 and 1.0mM as compared to the control while higher concentration of it was found lethal to plants (Fig. 3.35B).

122

Chapter: 3 Results

Fig. 3.33: Flow sheet of whole process involved in searching ISR determinant/s from B. subtilis IAGS174.

123

Chapter: 3 Results

Fig. 3.34: GC/MS Chromatogram of ISR active sub-fraction of cell free culture filtrates of B. subtilis IAGS174. A= GC/MS chromatogram. B= Ionization pattern of ISR determinant from B. subtilis IAGS174.

124

Chapter: 3 Results

0.01mM 0.1mM 1.0mM

A 100 90 80 70 60 50 40 * 30

Disease (%)Disease Index 20 ** 10 0 Control Eugenol Thymol 3-Methoxy Phthalic Acid Butylacetate Methyl Ester

0.01mM 0.1mM 1.0mM B 90 80 70 60 50 * 40 30

20 ** Disease (%)Disease Index 10 0 Control Tyrosine Propanol Palmitic acid Phenylacetic Acetic acid acid Methyl Ester

Fig. 3.35: Influence of root treatment of pure biochemicals present in ISR active sub-fraction on the disease development on tomato plants after inoculation with fusarium wilt pathogen. A= B. fortis IAGS162. B= B. subtilis IAGS174. Vertical bar represents standard errors. Asterisks indicate statistically significant reduction in disease index as compared to pathogen control as governed by ANOVA at (P<0.05).

125

Chapter: 4

DISCUSSION

Chapter: 4 Discussion

4.1:.Discussion

Tomato (Solanum lycopersicon Mill.) is an economically important vegetable crop belonging to the family solanaceae. Tomato is cultivated in both open fields and under green houses. In Pakistan, area under tomato cultivation is increasing rapidly both in reclaimed lands and greenhouses (Tahir et al., 2012). This crop provides high profit to farmers and a lot of employment opportunities to rural persons (Mari et al., 2007). In Pakistan, growth rate recorded for tomato is 8% that is highest from other tomato producing countries like China, Sri Lanka and India (Tahir et al., 2012).

Pathogenic microbes are major threat to food production. These also negatively effects crop rotation and hinder in breeding for resistance against diseases (Joshi and Gardener, 2006). Application of pesticides is not enough to combat root borne diseases in plants (Johri et al., 2003). Biological control has gained wide acceptance in recent years as a result of agriculture trends towards greater sustainability and public concern about the use of hazardous chemicals. Chemical fungicides have been extensively used for a long time as common strategy for control of fungal diseases and subsequently to achieve high yield (Keinath, 1998; Jahn et al., 2002). With the passage of time, fungicides resistant races of different pathogens have been evolved (Brent and Hollomon, 1998; McDonald and Linde, 2002).

Fusarium wilt, caused by Fusarium oxysporum f. sp. Lycopersici (Fol), is one of the major fungal diseases of tomato (Browers and Locke, 2000). Tomato plants attacked with Fol show symptoms of root and stem rotting. Severely infected plants wilt at the time of fruit bearing and die. Generally, fusarium wilt, root, and stem rot diseases of vegetable crops are managed by development of resistant varieties and avoidance of primary inoculum. Breeding for resistance is a difficult task because of genes conferring resistance has not been fully identified that provide protection against fusarium wilt disease in different vegetable crops (Fravel et al., 2003; Ozbay and Newman, 2004). Elimination of primary inoculum is considered an effective approach by using chemical fungicides, heat treatment, pathogen free seeds and fumigation. Several studies have demonstrated use of biological agents like bacteria and fungi to manage plant diseases caused by Fusarium oxysporum (Fravel et al., 2003).

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Diverse inhabitants of aerobic endospore forming bacteria like Bacillus, are found in agricultural ﬁelds and subsidize to crop production by both direct and indirect ways (Priest, 1993; Grayston et al., 1998; Sturz et al., 2000; Gutierrez-Manero et al., 2001). Some physiological traits which make Bacillus a suitable biocontrol agent are presence of stress resistant endospore, thick cell wall, production of peptide antibiotics, signal molecules, and extracellular enzymes (Podile and Dube, 1988; Liu and Sinclair, 1992; Podile et al., 1995; Gardener, 2004; Joshi and Gardener, 2006; Idris et al., 2007). All these characters aid in survival of Bacillus under hostile environment for long durations. Bacillus species can manage plant diseases by inducing systemic resistance and can express antagonistic activities by suppressing plant pathogens (Chen et al., 2009; Arrebola et al., 2010).

Findings of present study are consistent to the hypothesis that some native Bacillus strains can provide protection against fusarium wilt disease of tomato along with growth promotion. In first phase of study, most virulent isolate of F. oxysporum f.sp. lycopersici and three varieties of tomato with varying susceptibility against fusarium wilt were screened, which were used for further experimentations. In second phase of study, different native non-pathogenic, rhizospheric Bacillus strains were screened for their ability to induce systemic resistance in tomato against fusarium wilt. The study confirmed the effectiveness of indigenous Bacillus strains in controlling fusarium wilt in tomato among which the top two strains were B. fortis strain IAGS162 and B. subtilis strain IAGS174. Selected strains provided promising protection against fusarium wilt both under split root system in greenhouse and field conditions. The decrease in fusarium wilt disease achieved by these two strains demonstrates that these strains are capable of interaction with plant immune system and involved in elicitation of different plant defense responses. In order to provide better disease suppression, two best performing strains wereapplied together in field experiments that provided even better disease control. Use of biological inducers in mixture have displayed increased defense related biochemicals in plant body (Raupach and Kloepper, 2000; Jetiyanon and Kloepper, 2002). Similarly El-Sheikh et al. (2002) found that combined inoculation of tested bacterial strains were more effective than single bacterial strain applied to control Phytophthora infestans on potato. In another research carried out by Raupach and

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Kloepper (2000), mixture of bacterial strains provided better protection against cucumber leaf spot disease.

Various strains of Bacillus like B. pumilus, B. amyloliquefaciens Priest, B. subtilis, B. cereus, B. mycoides and B. sphaericus are reported producers of potential elicitors of ISR that have shown signiﬁcant reductions either in incidence or severity of various diseases on diverse plant hosts (Kloepper et al., 2004; Choudhary and Johri, 2008). Many researchers have reported efficacy of Bacillus strains in controlling wide spectrum of fungal plant pathogens like Sclerotium rolfsii Sacc (Bhatia et al., 2005), Pythium aphanidermatum (Edson) Fitzp (Ramesh and Korikanthimath, 2010), Rhizoctonia solani Kuhn (Nandakumar et al., 2001) and Colletotrichum gleosporiodes Penz and Sacc (Vivekananthan et al., 2004a). Similarly, in current study, two Bacillus strains viz: B. fortis strain IAGS162 and B. subtilis strain IAGS174 provided more than 70% reduction in fusarium wilt disease under both greenhouse and field conditions.

Both of these strains have several valuable traits which can make them fit for potential biopesticides. These strains are well-studied and non-pathogenic (Harwood and Wipat, 1996). Both of these can produce resistant spores and therefore can withstand high temperature and lack of food and water (Piggot and Hilbert, 2004). This spore forming capability can be exploited in industrial processes and spore formation can be induced (Monteiro et al., 2005). Because of this property, these Bacillus strains can be easily converted to powdered formulations without impressive mortality as can be seen in non- spore forming bacteria (Lolloo et al., 2010). Similar observations were recorded in current investigation when viability of bacterial strains was observed on different powdered formulations. This sporulating property enhances shelf life of microbial based biopesticides and requires less storage precautions (Losick and Kolter, 2008; Rosas- Garcia, 2009). Beside spore forming property, best performing Bacillus strains in current research work possess several characteristics which can enhance their survival in rhizosphere and make them suitable for a biopesticide (Nakano and Hulett, 1997). Most Bacillus species are aerobic. Some Bacillus strains including B. fortis and B. subtilis can live as facultative anaerobe that is advantageous in rhizospheric survival. B. subtilis is motile bacterium that can move towards root surface thus facilitates colonization of new ecological niches (Joshi and Gardener, 2006).

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Previous studies have focused primarily on the degree of disease reduction using Bacillus microbes in biological control. Keeping in view, a need for deeper understanding of mechanism behind disease suppression current study was designed to analyze ISR phenomenon at biochemical, histological, and molecular levels. Bacteria and their secreted metabolites exhibited ISR activity against fungal wilt disease of tomato. Their involvement in elicitation of plant defense responses is fascinating properties that were explored in more details. In second phase of study, an independent experiment was performed to explore ISR capabilities of selected Bacillus strains. For that purpose, changes in production of different defense related biochemicals including total phenolics, peroxidases, polyphenoloxidases and phenylamonialyase were observed (Gardener and Driks, 2004). These biochemicals are also considered as biomarkers of ISR phenomenon.

Treatment of tomato plants with Bacillus strains resulted in systemic elevation of all these biochemical markers of ISR but with varying trends. These results are in line with previous investigators regarding ISR phenomenon in tomato and several other plants. Plant samples analyzed in this study were collected at different time intervals. Maximum increase in defense related compounds were provided by two strains viz: B. fortis IAGS162 and B. subtilis IAGS174. Increase in levels of these biochemicals in plants grown under influence of above microbial strains represents a phenomenon of cross-talk between plants and microbes (Anfoka and Buchenauer, 1997; Kunkel and Brooks, 2002; Silva et al., 2004; Thaler et al., 2004). These rapid changes in quantities of defense related biochemicals after inoculation with Bacillus strains, represents elicitation of ISR provided by these Bacillus strains (Thaler et al., 2004). Earlier literature also provides evidences that bacterial microbes can accumulate some plant defense related enzymes (PO, PPO and PAL), pathogenicity-related proteins, phytoalexins, lignin and phenolic compounds (Hammerschmidt et al., 1982; Zdor and Anderson, 1992; Hammerschmidt and Kuc 1995; Alvarez et al., 1998; Yedidia et al., 1999; Chen et al., 2000; Prathuangwong and Buensanteai, 2007; Buensanteai et al., 2008).

In plants, phenolic compounds have abundant tasks like defence form herbivory and carry toxicity against several bacterial and fungal pathogens (Heldt, 1997). Resistance in plants against pathogens is supplemented by increased activities of phenolic compounds and some other phytoalexins synthesized by phenylpropenoid pathway. Up-

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Chapter: 4 Discussion regulation of phytoalexins and enzymes involved in phenylpropenoid pathway viz peroxidases, polyphenol oxidases, phenylalanine ammonia lyases, are directly or indirectly related to ISR phenomenon under any chemical or biological inducer (Trotel- Aziz et al., 2008; Radjacommare et al., 2010; Akram and Anjum, 2011). Above mentioned enzymes play crucial role in formation of phytoalexins inside plant body which hinder pathogen invasion and reproduction by different ways (Jourdan et al., 2009). Some phytoalexins such as quinones destroy pectolytic enzymes machinery of pathogens (Li and Stiffens, 2002; Kavino et al., 2008). Enzymes like peroxidases are involved in production of certain defense barriers such as lignin and reactive oxygen species (ROS) which restrict pathogen growth (van Loon, 1999).

These findings are in agreement with several previous studies. Recently Senthilraja et al. (2013) observed significant increase in total phenolics and enzymes involved in phenylpropenoid pathways in groundnut plants under influence of some rhizospheric bacterial strains. In the same way, in a study carried out by Aziz (2007), a rapid increase in phytoalexins was recorded in grapevine plants when inoculated with bacterial inducers. Vivekananthan et al. (2004b) specifically observed up-regulations in defense related enzymatic machinery induced by Pseudomonas fluorescens in mango against anthracnose pathogen.

Single PGP strain can harbor more than one plant beneficial properties. From ecological basis, it has also been proved that PGP bacteria form coherent beneficial associations with plants by many biotic and abiotic factors which in term can modulate plants for increased growth and systemic resistance against diseases. Along with disease reduction, plant growth enhancement can also be seen induced by bacterial inducers (Gupta et al., 2000; Adhikari et al., 2001; Nihorimbere et al., 2010). This advantageous influence of Bacillus strains on growth of plants is because of some diverse mechanism (Bacon and Hinton, 2002; Ping and Boland, 2004; Berg, 2009). As was observed in current investigation, growth was significantly increased in bacterial treated plants both under greenhouse studies and field conditions. Since these strains were capable of triggering ISR in previous experiment, it was anticipated that these strains can also promote growth of tomato. To prove this hypothesis another independent experiment was performed. In this experiment, initially production of plant growth related traits of these

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Chapter: 4 Discussion bacterial strains like IAA production, siderophores production and phosphate solubilization were evaluated. Bacillus subtilis IAGS174 was found superior in observed traits as compared to B. fotris IAGS162. To make observations concerning the effect of bacterial strains on growth promotion greenhouse studies were performed. In greenhouse experiment root inoculation of tested bacterial strains significantly promoted growth attributes of tomato plants of all the three tomato varieties. Greenhouse studies were further supported by field evaluations. These strains provided significant increase in shoot length and yield of tomato plants. Strain B. subtilis IAGS174 was proved as the most efficient strain in promoting these traits.

Many plants have been shown to perform better in the presence of bacteria capable of releasing phytohormones, siderophores and phosphorus solubilization (Garcia- de-Salamone et al., 2001; Egamberdiyeva, 2005). Phytohormones accelerate plant growth by modulating plant growth and developmental processes. Exogenous IAA produced by bacteria controls array of processes of plant growth and development. Indole acetic acid (IAA) stimulates primary and lateral root growth and increase root hair formation (Dobbelaere et al., 1999; Patten and Glick, 1996; Remans et al., 2008). Growth promotion of tomato plants can be concomitant with more than one plant growth promoting traits of bacteria like siderophores production, hydrogen cyanide production (HCN), AAC (1-aminocyclopropane-1-carboxylic acid) deaminase activity and phosphorus solubilization ability (Sundra et al., 2002). Results indicated that B. subtilis IAGS174 provided statistically higher growth promotion as compared to B. fortis IAGS162. This can be attributed for enhanced phosphate solubilization, IAA production and siderophores production ability of B. subtilis IAGS174 in comparison to B. fortis IAGS162.

In current study, it was observed that plants inoculated with selected Bacillus strains showed increased chlorophyll, carotenoid and sugar contents. These findings provided additional evidence supporting the finding of previous studies. These biochemicals are considered as markers of plant growth. Application of PGP microbes induces plants for higher production of these biochemicals in plants. These plant mediated mechanisms are proposed by researchers as driving force behind plant growth promotion by PGP bacterial strains (Silva et al., 2003). A research was carried out by

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Karakurt et al. (2011) to evaluate plant growth promotion abilities of some bacterial strains. They attributed enhanced growth of cherry plant towards increased production of these plant growth related biochemicals under influence of PGP bacterial strains. In another research, increase in plant growth related parameters including chlorophyll content, due to bacterial inoculation in crop plants, under cold on highland areas of Turkey, has also been reported (Elkoca et al., 2008).

Previous studies also describe beneficial effects of these bacterial microbes for management of plant diseases but there is dearth of studies dealing mechanism underlying induced resistance or disease protection provided by these bacterial strains. For that reason, an independent experiment was performed, in which molecular, histological and biochemical studies were carried out to dissect mechanism underlying disease protection by these bacterial strains. In this experiment, plants were provided with selected bacterial strains followed by pathogen challenge. Control plants were only provided with pathogen. After incubation, plants were observed for molecular, histological and biochemical changes induced by bacterial strains in presence of the pathogen. To explore molecular mechanism, RT-PCR assay was performed and changes in expression levels of different pathogenesis related (PR) genes were observed in a time course manner.

PR proteins are induced after pathogen infection (van Loon, 1985; Linthorst, 1991; van Loon, 1997, 1999, 2001). Functions of some PR proteins have been clearly identified. A major function of PR proteins is their antifungal effect inside plant body (van Loon, 2001). PR-2 and PR-3 proteins hydrolyze fungal cell walls (Berg, 2009). Some PR proteins help in stimulation of lignin synthesis (Berg, 2009). PR-5 proteins are shown to restrict hyphal growth or spore germination of various fungi (Nasser et al., 1990; Shewry and Lucas, 1997). Most of the PR proteins act as direct antimicrobial agents. Some of them work indirectly by catalysing cross-linking of macro molecules in the cell wall (Niki et al., 1998; Waniska et al., 2001; Gozzo, 2003).

PR proteins have been shown to elevate during ISR process (Ward et al., 1991). Different bacterial inducers have been shown to strongly induce transcription of the pathogenesis-related proteins (Tjamos et al., 2005; Wang et al., 2006; Cartieaux et al.,

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2008). Same was observed in present studies. At initial time interval, low expression profiles were observed for nearly all PR protein genes under observations while on later intervals; significant up-regulations were seen in expression levels of these PR genes. Major increase was seen at 2 and 4 dpi whereas on later intervals expression levels started decreasing. The fact that these Bacillus strains can induce higher transcription levels of PR genes is related to their role in different defense mechanisms against pathogens. These findings are in agreement with a recent study performed by Srivastava et al. (2012). They performed detailed molecular analysis of Arabidopsis thaliana co- cultivated with Pseudomonas putida. This strain up-regulated numerous genes of Arabidopsis plant related to growth, signaling, stress response and ISR. In another study, Yi et al. (2013) found that inoculation of Bacillus pumilus significantly up-regulated defense related genes of pepper against bacterial spot disease. As conclusion, RT-PCR assay during this study demonstrated that these bacterial inducers were able to differentially induce expression levels of PR protein genes with respect to control plants that only received pathogen.

In plant-microbe interactions, deposition of lignin has been suggested as defense responses of plants against pathogen attack (Moura et al., 2010). The synthesis of some physical barriers like lignin rich materials or callose around vascular areas is a phenomenon that can be related induced resistance against pathogens in plants (Hahn et al., 1989; Kosack and Jones, 1996). In the same way, phenolic deposition provides toxic environment to penetrating pathogens inside plant body. It is possible that inhibition of proliferation of F. oxysporum in tomato roots is due to the deposition of lignin and phenolic compounds. In different studies, researchers have observed deposition of lignin, phenolics, callose and suberins in resistance interactions between plants and pathogens. In the same way in current studies, plants receiving bacterial inducers showed intense localization of lignin, phenolics and peroxidase contents. At some places, whole lumens of cells were esterified with phenolic compounds in both root and shoot sections in bacterial treated plants.

In conclusion to these histological and histochemical observations, the inductions of plant histological defense responses reflect initiation of certain resistance mechanisms

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Chapter: 4 Discussion induced by tested bacterial strains. These modifications are reminiscent of plant defense responses to pathogens as can be observed in incompatible interactions between a pathogen and resistant plant variety (Kosack and Jones, 1996; Collinge et al., 1997).

Under influence of pathogen and biotic or abiotic inducers, change in plant metabolism is another expected activity. Bacterial inducers can act on host biochemical cycles by different ways like interfering with host metabolites, transporters and by redirecting nutrients. Upregulation of several metabolic pathways like amino acids biosynthesis, pentose pathway, signaling transduction, TCA cycle has been found in different plants under influence of biological inducers (Verhagen et al., 2004; Shoresh and Harman, 2008; Damodaran et al., 2010; Brotman et al., 2012). Same was observed in this study. GC/MS analysis of metabolites extracted from both bacterial treated and control plants were carried out. Differences in quantities of different metabolites were expressed in the form of heat map and annotated in physiological pathways. Up- regulation in levels of different metabolites belonging to different important physiological processes was observed in case of plants treated with both bacterial strains. These changes were seen in pathways belonging to plant growth, photosynthesis, signaling processes and defense pathways like phenylpropenoid pathway. Increase in resistance against fusarium wilt pathogen in bacterial treated tomato plants can be attributed to up regulation of this phenylpropenoid pathway. In the same way, increase in growth in bacterial treated tomato plants can be linked with increase with some primary metabolic pathways like Pentose pathway, TCA and aminoacid biosynthesis. A same type of study was carried out by Bortman et al. (2012) to observe changes induced by Tricoderma in Arabisopsis. Researchers observed massive re-modulations in metabelomics of Arabisopsis. Different metabolites showed significant quantitative changes that were annotated to different pathways like glycolysis, pentose pathways, signaling network and defense system etc.

In GC/MS analysis significant increase in quantities of some carbohydrates like fructose, glucose, mannose etc was recorded. Increase in quantities of carbohydrates is considered as a signal that induces expression of certain defense related mechanisms and photosynthetic processes (Ehness et al., 1997; Sinha et al., 2002; Roitsch et al., 2003; Berger et al., 2007; Kocal et al., 2008). Polyamines are biochemicals involved in

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Chapter: 4 Discussion numerous physiological processes (Tonon et al., 2004). Levels of some polyamines were significantly increased in bacterial treated plants in this study. Sarjala et al. (2010) have represented data indicating co-relation between growth increase and ployamines quantities in pine seedlings under influence of a biological inducer. A similar co-relation can be documented here as growth promotion in tomato plants under influence of Bacillus strains. A clear increase in amino acids level was measured in Bacillus treated plants. Some amino acids are important precursors of plant defense biochemicals as cyanogenetic glycosides, and glucosinolates (Coruzzi and Last, 2000). In the same way, some aromatic acids were up-regulated in Bacillus treated tomato plants followed by pathogen challenge. These aromatic acids play an important role in shikimate pathway. This pathway is responsible for synthesis of aromatic compounds required for different functions as UV protection, electron transport, signalling, communication, plant defence, structural components and the wound response (Tzin and Galili, 2010). Quantitative modulations in metabolites involved in defense responses of tomato against fusarium wilt confirmed elicitation of ISR provided by these two particular Bacillus strains. Moreover, it is remarkable that root colonization by beneficial bacteria ameliorated general physiological pathways of tomato plants showing massive re-distribution of energy towards growth promotion and defense responses.

Taken together these molecular, histological and biochemical results suggest that plant disease protection is proportional to the amount of enhanced enzyme activity, pathogenicity-related proteins, phenolic compounds and tomato metabolomic profiles. The higher levels of all molecular, biochemical and histological markers elicited by the B. fortis IAGS162 and B. subtilis IAGS174 in the present study might have played an important role in protecting tomato plants against fusarium wilt disease. In non- bacterized, pathogen control plants, PR gene expression levels increased at slower rate and similar findings were seen in histological and metabolic analysis.

In last phase of studies, efforts were made to screen potential elicitors of ISR from both bacterial strains. In first step, different treatments containing live cells, cell free culture filtrates and intra-cellular metabolites of both bacterial strains were tested for ISR activity in order to determine nature of potential ISR determinant. Results showed that tomato plants treated with CFCF of B. subtilis and B. fortis provided maximum

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Chapter: 4 Discussion protection against disease in contrast to intracellular metabolites, which were unable to provide any significant protection against the pathogen.

Different biochemicals from bacteria have been shown to elicit systemic resistance in plants against different pathogens (Choudhary and Johri, 2008). These biochemicals can be of either extra-cellular or intra-cellular in nature. Several studies show that biochemical eliciting systemic resistance retain in cultural filtrates of that bacterial strain (van Peer and Schippers, 1992; Leeman et al., 1996; Gomez and Boller, 2002). In this research work, when initially CFCF were provided in the growth media of tomato, the disease incidence lowered as compared to the untreated control. This proved that active ISR determinants were retained in CFCF of tested bacterial strains. These culture filtrates were partitioned using different organic and aqueous fractions.

ISR bioassay performed by using these fractions showed that compounds in the ethyl acetate fraction have ISR eliciting capability while rest of the fractions were lacking ISR activity in case of B. subtilis IAGS174 while for B. fortis IAGS162, chloroform retained ISR active biochemicals. These ISR active fractions were further partitioned into ten sub-fractions through silica gel column chromatography under step wise elution system. These ten sub-fractions were again subjected to ISR bioassay. GC/MS analysis revealed that compounds present in ISR active sub-fraction were eugenol, 3-methoxy butylacetate; pentachloroanilin and pthalic acid dimethyl ester in B. subtilis IAGS174. Whereas in case of ISR active fraction of B. fortis IAGS162, biochemicals identified were acetic acid methyl ester, benzene acetic acid, palmitic acid, propanol and tyrosine. In another ISR bioassay using these pure chemicals showed that, benzene acetic acid, also known as phenylacetic acid from B. fortis IAGS162 and phthalic acid dimethyl ester from B. subtilis IAGS174 effectively elicited systemic resistance in tomato plants against fusarium wilt. Growth of pathogen was evident in all test tubes receiving both of these organic acids at all concentrations. This represents that these compounds were lacking antifungal activity but effectively induced ISR.

Benzene acetic acid also known as phenylacetic acid, is an organic chemical containing a phenyl and carboxylic acid functional group while phthalic acid (dicarboxalic acid), is diacid form of aromatic carboxylic acid. Different carboxylic acids

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Chapter: 4 Discussion are active allelochemicals, capable of changing plant growth and physiology (Ignacimuthu 1997; Piccolo et al., 2003). Both of these organic acids viz: benzene acetic and pthalic acid are produced by both plants and bacteria (Wightman and Lighty, 1982; Sarwar and Franckenberger et al.,1995; Ignacimuthu, 1997; Piccolo et al., 2003; Hao and Wang, 2004; El-Mehalawy et al., 2008; Sani and Pateh, 2009; Sumayo et al., 2013).

Benzeneacetic acid is naturally occurring auxin produced by plant species (Abe et al., 1974; Schneider and Wightman 1986). In this study benzeneacetic acid also effectively elicited ISR in tomato plants when applied at 0.1 and 1.0 mM concentrations. Recently, a study was carried out by Sumayo et al. (2013) to search potential ISR determinants from a bacterial strain Ochrobactrum lupine KUDC1013. They also reported benzeneacetic acid as ISR determinant of this bacterium along with 1- hexadecene and Linolic acid.

In an investigation, exposure of apple plants to a carboxalic acid (phthalic acid) elicited production of anti-oxidant enzymes and reactive oxygen species (ROS) (Bai et al., 2009). Reactive oxygen species (ROS) are major component of the signal transduction cascade involved in plant adaptation to the changing environment (Mehdy,

1994; Neill et al., 2002). Among ROS, H2O2 takes part in plant defense related mechanisms, like reinforcement of plant cell wall and phytoalexin production (Dempsey and Klessig, 1995). In plant-microbe interactions, H2O2 production in plants can kill the pathogen directly or induces defense genes to limit infection by the microbe. These ROS can be used asa marker in plants for analysis of the occurrence of plant basal defense reactions (Bozso et al., 2005). In current investigation it can be attributed that both of these carboxalic acid viz: phthalic acid and benzeneacetic acid, elicited production of ROS which then triggered an array of defense responses inside plant body. Some monoacid forms of carboxylic acids are precursors of salicyclic acid formation which is an important signaling biochemical of plant defense related systems.

Some biologically active metabolites play a role as elicitors of ISR at low concentration but show antimicrobial activity at higher concentration (Tosi and Zazzerini, 2000; Rohilla et al., 2002). In this study, treatment of tomato plants with 1.0 mM phthalic acid dimethyl ester caused death of plants but in lower concentration of 0.1mM of it

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Chapter: 4 Discussion significantly decreased fusarium wilt incidence. This suggests that this chemical at higher concentration is toxic to plants but is more effective in eliciting ISR at lower concentrations. In the same way, the ISR active metabolite 4-aminocarbonyl phenylacetate from Pseudomonas chlororaphis (Guignard and Sauvageau) Bergey applied at 68.0 mM elicited ISR activity against wildfire pathogen at a level similar to 1.0 mM salicylic acid (Park et al., 2008). The ISR effect of butyl 2-pyrrolidone-5- carboxylate (BPC) from Klebsiella oxytoca (Flugge) Latrup was observed at 12 mM (Park et al., 2009).

Recent progress in understanding plant immunity is a driving force in crop protection in fields. With the discovery of new microbial associated microbial patterns (MAMPs), produced by beneficial ISR inducing microbes can help in development of formulation capable of eliciting ISR in plants in conventional agriculture system. ISR is a long lasting phenomenon and effective against broad range of diseases and not conducive for development of pathogen resistance. Discovery of new MAMPs can provide efficient structural patterns for boosting plant immunity against diseases. These MAMPs should be produced biotechnologically for commercialization. Knowledge of these MAMPs can provide basis for development of new structural derivate with higher activity and shelf life. Based on these findings, it is obvious that colonization of B. subtilis IAGS174 with plants roots can promote plant defense system against pathogens and phthalic acid dimethyl ester is ISR determinant produced by this bacterial strain in the rhizosphere.

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4.2: Conclusion and future prospects:

The potential of some bacterial strains as resistance inducer in plants drove researcher’s attention for screening of some native non-plant pathogenic Bacillus strains to manage fusarium wilt of tomato. Significant effective control of fusarium wilt of tomato under split root system confirmed potential of two strains viz: B. fortis IAGS162 and B. subtilis IAGS 174 capable to elicit ISR in tomato. Same type of significant suppressions in disease control by these two bacterial strains was also seen in field conditions along with growth and yield promotion capabilities. Higher induced levels of defense related biochemicals in tomato plants under influence of bacterial strain also supported hypothesis of ISR phenomenon.

 Regarding future research work, improvements should be made in application technologies of these ISR capable microbes that would likely produce the greatest gains in disease control.  There is a need to elucidate mechanism of ISR by using other plant species and against other pathogens.  Detailed studies at molecular and metabolic level would be very useful to dissect signaling pathways triggered by biotic inducers involved in ISR phenomenon.  Besides a lot of studies performed to search elicitors of ISR in plants, only a small number of these have appeared in real world scenario. There is a need to discover much more elicitors having strong capability to appear in daily agriculture system.

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170

APPENDIXES

Appendix

Appendix 1

Luria-Bertani agar S. No COMPONENTS g/L 1 Tryptone 10.0 2 NaCl 5.0 3 Yeast extract 5.0 4 Agar 15.0 pH adjusted at 7.0 Luria-Bertani broth S. No COMPONENTS g/L 1 Tryptone 10.0 2 NaCl 5.0 3 Yeast extract 5.0 pH adjusted at 7.0 Potato Dextrose Agar S. No COMPONENTS g/L 1 Potatoes (sliced washed unpeeled) 200 2 Dextrose 20 3 Agar powder 20 4 Distilled water 1000

PCNB Dextrose Agar S. No COMPONENTS g/L 1 PCNB 1.0 2 Dextrose 20 3 Agar powder 20 4 Distilled water 1000

171

Appendix

1.0% Sodium hypochlorite S. No COMPONENTS mL/mL 1 Sodium hypochlorite 1.0 2 Distilled water 100

Quantification of Phenolics Methanol 80% S. No COMPONENTS mL/10mL

1 Methanol 8 2 Distilled water 2 10 mL of methanol was used. FolinCiocaltueau reagent 50%

S. No COMPONENTS mL 1 Folinciocaltueau reagent 2.50 2 Distilled water 2.50

Quantifications of enzymes involved in Phenylpropenoid pathway

Sodium Phosphate buffer S. No COMPONENTS mL 1 DiSodiumPhosphate 510

Na2HPO4.H2O

2 Sodiumbiphosphate NaH2PO4 490 pH was adjusted to 6.8-7 500 mL of Sodium Phosphate buffer was used. 10 mM Reaction mixture for the activity of PO S. No COMPONENTS mL 1 0.25 % Guaiacol 0.25

2 0.1 M H2O2 3.4 3 Sodium Phosphate Buffer 96.35 pH adjusted at 6.0 10 mL of reaction mixture was used.

172

Appendix

Activity of PPO 0.01 M catechol

S. No COMPONENTS mL 1 1 0.01 M Catechol 0.001 . 2 Distilled water 10

Activity of PAL

0.03 M L-phenylalanine

S. No COMPONENTS g/10 mL 1 0.03 M L-phenylalanine 0.052 2 Distilled water 10 4.95 mL of catechol was used. 1M TCA (Trichloro acetic acid) S. No COMPONENTS g/10 mL 1 1 M TCA (trichloro acetic acid) 1.63 2 Distilled water 10 0.5 mL of TCA was used

Sodium Borate Buffer S. No COMPONENTS mL 1 Boric acid 0.06 2 NaCl 0.04 3 Sodium Tetra Borate 0.09 4 Distilled water 8.1 pH adjusted to 8.8 2.5 mL of Sodium Borate Buffer was used.

173

Appendix

Histological studies

72% (v/v) H2SO4

S. No COMPONENTS mL

1 H2SO4 72

2 Distilled water 28

1 mL of H2SO4 was used.

Staining of lignin 2% (w/v) Phloroglucinol solution S. No COMPONENTS g/mL 1 Phloroglucinol solution 2 2 Distilled water 98 1 mL of Phloroglucinol solution was used.

95%Ethanol S. No COMPONENTS mL 2 Ethanol/water (95/5 v/v) 9.5 3 Distilled water 0.5 1 mL of HCl was used.

2.17 50% (v/v) HCl S. No COMPONENTS mL 1 50% (v/v) HCl 5 2 Distilled water 5 1 mL of HCl was used.

174

Appendix

1% ABTS solution S. No COMPONENTS mL 1 ABTS solution 0.1 2 Distilled water 10

Sodium Citrate Buffer S. No COMPONENTS g/L 1 Citric acid 21

2 Sodium citrate 9.4 3 Distilled water 1 pH 6.0 500 mL of buffer was used.

Salkowski’s reagent Solution I 0.05m Ferric chloride solution

S. No COMPONENTS 10 mL-1 (w/v)

1 FeCl3 0.08125

Solution II Perchloric acid

S. No Components 10 mL-1 (v/v)

1 HClO4 50

One ml of 0.05M FeCl3 was mixed in 50 ml of 35% perchloric acid to prepare Salkowski reagent.

175

Appendix

Chrome azurol S (CAS) solution a)- 1mM FeCl3.6H2O

S. No Components g 100mL-1

1 FeCl3.6H2O 0.027

1 mM FeCl3.5H2O was prepared in 10 mM HCL b)- Aqeous solution of CAS

S. No Components mg 50mL-1 1 CAS 60.50

c)- Hexadecyl-trimethylammonium bromide (HDTMA)

S. No Components mg 40mL-1 1 HDTMA 72.80 Fe-CAS indicator solution was prepared by mixing “solution a” with 50 mL of “solution b”. The resulting dark purple mixture was added slowly with constant stirring to 40 of HDTMA (solution c). This will yield a dark blue solution which was autoclaved, then cooled to 50oC.

176

Appendix

Medium for Phosphate Solubilization assay (Pikovskaya agar medium)

S. No Components g L-1

1 Glucose 10

2 Ca3(PO4)2 5

3 (NH4)2SO4 0.5 4 NaCl 0.2

5 MgSO4.7H2O 0.1 6 KCl 0.2 7 Yeast extract 0.5

8 MnSO4 Trace

9 FeSO4.7H2O Trace 10 Agar 15 pH adjusted to 7 to 7.2

177

Appendix

Appendix 2

TAE Buffer 50X Chemical Concentration Mass/ Volume for 500 mL buffer

Tris 2M 242 g EDTA 0.5M 37.2 g Glacial Acetic 5.71% 57.1 mL Acid Total Volume 1000 mL

20 mL of 50X Tank buffer was diluted to 1000 mL with distilled water.

Agarose Gel Composition Tray 1X TAE 1% 1.5% Buffer Agarose Agarose

7×10cm 50 mL 0.5g 0.75g 10×10cm 75 mL 0.75g 11.25g 15×10cm 100 mL 1g 1.5g

DNA Loading Buffer Chemical Concentration Mass/ Volume

Glycerol 50% 5 mL 200 µL of 50X CTAB Buffer 1X Stock Bromophenol Blue 1% 0.1 g Xylene Cyanol 1% 0.1%

Ethidium Bromide Solution Chemical Mass/ Volume

Ethidium bromide 0.01g Glycerol 1 mL

3 µL of Ethidium bromide solution was added in an agarose gel of 50mL.

178

Appendix

Amplification PCR Reaction Mixture

Mass/ Chemicals Concentration Volume

Taq Buffer 1X 1.25 µL

MgCl2 2 mM 0.5 µL dNTPs 0.12 mM 0.3 µL Primer-forward 0.2 µM 0.25 µL Primer-reverse 0.2 µM 0.25 µL BSA 8 µg/mL 0.1 µL

dd H2O 7.55 µL

Total 12.5 µL

RT-PCR Reaction Mixture

First strand cDNA synthesis

Mass/ Chemical Concentration Volume

Reverse transcriptase buffer 10X 05 µL MMLV- Reverse transcriptase 5 units/ µL 1 µL dNTP mixture 2mM 05 µL RNA 500ng/ µL 2.5 µL Random hexamers primer 5pmol/ µL 2.5 µL

dd H2O 34 µL Total 50 µL

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Second strand Reaction mixture

Mass/ Chemicals Concentration Volume

Taq Buffer 10X 1.25 µL

MgCl2 2 mM 0.5 µL dNTPs 0.12 mM 0.3 µL Primer-forward 0.2 µM 0.25 µL Primer-reverse 0.2 µM 0.25 µL BSA 8 µg/mL 0.1 µL cDNA 500ng/µL 2.5 µL

dd H2O 7.55 µL

Total 12.5 µL

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Appendix 3

Isozyme enzyme extraction 0.01M Phosphate Buffer S. No COMPONENTS mL 1 Di Sodium Phosphate 5.1

Na2HPO4.H2O

2 Sodium biphosphate NaH2PO4 4.9 pH adjusted to 7. 4 mL of Phosphate Buffer was used. Solution for Tris/Glycine -Polyacrylamide Gel Electrophoresis S. No COMPONENTS 15 mL

1 H2O 5.9 2 30% Acrylamide mix 5 3 Tris (pH=8.8) 3.8 4 10% APS 0.15 5 TEMED 0.006 30% Acrylamide mix S. No COMPONENTS mL 1 Acrylamide 29 2 Bisacrylamide 1 Distilled water 100 For 15 mL reaction mixture 5mL of 30% Acrylamide mix was used.

10% APS S. No COMPONENTS mL 1 10% APS 10 2 Distilled water 90 For 15 mL reaction mixture 0.15 mL of 10% APS was used.

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Stacking Gel S. No COMPONENTS 5 mL 1 H2O 3.4 2 30% Acrylamide mix 0.83 3 Tris base (pH=8.8) 0.63 4 10% APS 0.05 5 TEMED 0.005 5 mL of stacking gel was used. Lammeli Sample Buffer S. No COMPONENTS g/1000 mL 1 Glycine 14.4 2 Tris 3 3 Distilled water 1000 500 mL of Lammeli sample buffer was used. 0.25 % Guaiacol S. No COMPONENTS mL 1 0.25 % Guaiacol 0.5 2 Distilled water 200 200 mL of 0.3 % Hydrogen Peroxide was used. 0.3 % Hydrogen Peroxide S. No COMPONENTS mL 1 H2O2 0.6 2 Distilled water 200

0.03 M catechol S. No COMPONENTS g/L 1 Catechol 0.03 2 Distilled water 1000

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0.05% L-Phenylenediamine S. No COMPONENTS mL 1 0.5% APS 0.5 2 Distilled water 99.5

Acetate Buffer S. No COMPONENTS g/mL 1 Ammonium acetate 100 2 Distilled water 300 3 Glacial acetic acid 4.1 Adjust the pH 6.0 pH (2.2.3) if necessary using ammonia or acetic acid and dilute to 500.0 mL with water.

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PUBLICATIONS

Searching ISR determinant/s from Bacillus subtilis IAGS174 against Fusarium wilt of tomato

Waheed Akram, Tehmina Anjum & Basharat Ali

BioControl Journal of the International Organization for Biological Control

ISSN 1386-6141

BioControl DOI 10.1007/s10526-014-9636-1

1 23 Your article is protected by copyright and all rights are held exclusively by International Organization for Biological Control (IOBC). This e-offprint is for personal use only and shall not be self-archived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at link.springer.com”.

1 23 Author's personal copy

BioControl DOI 10.1007/s10526-014-9636-1

Searching ISR determinant/s from Bacillus subtilis IAGS174 against Fusarium wilt of tomato

Waheed Akram • Tehmina Anjum • Basharat Ali

Received: 4 March 2014 / Accepted: 12 November 2014 Ó International Organization for Biological Control (IOBC) 2014

Abstract Bacillus subtilis IAGS174 has been pre- polyphenol oxidase, and peroxidase. Our research viously shown to induce systemic resistance in tomato indicates that B. subtilis IAGS174 has great potential plants against Fusarium wilt disease. In the present for use as a biological control agent, and PAME is the investigation, the resistance-inducing determinant was ISR determinant secreted by this bacterium into the isolated from cell-free culture filtrates (CFCF) of this rhizosphere. This determinant can effectively trigger bacterium. For this purpose, CFCF was extracted by a defense responses in tomato plants. series of organic solvents, and the fraction that showed induced systemic resistance (ISR) activity was further Keywords Induced systemic resistance (ISR) partitioned into sub-fractions by column chromatog- B. subtilis IAGS174 Tomato Fusarium wilt disease raphy by using a stepwise elution method. Gas Phthalic acid methyl ester Phenylalanine ammonia- chromatography/mass spectrometry analysis identi- lyase Polyphenol oxidase Peroxidase fied four compounds in the ISR-active sub-fraction viz. eugenol, 3-methoxy butyl acetate, pentachloroaniline and phthalic acid methyl ester (PAME). Subsequent bioassays proved that PAME is the Introduction potential ISR determinant that significantly ameliorated Fusarium wilt disease of tomato at concentra- Plants have evolved a great variety of active and tions of 0.01 and 0.1 mM. Furthermore, compared to passive defense systems against pathogenic infections the respective controls, tomato plants treated with (Somssica and Hahlbrock 1998; van Loon and van PAME showed increased activities of defense-related Strien 1999; Garcia-Brugger et al. 2006). Since they enzymes such as phenylalanine ammonia-lyase, lack mobile defense systems and adaptive immunity, plants rely solely on innate immunity, which is based on signals originating from the infection sites (Dangl Handling Editor: Monica Hofte and Jones 2001; Ausubel 2005; Jones and Dangl 2006). Specific defense signals, originating from a W. Akram (&) T. Anjum Institute of Agricultural Sciences, University of the localized microbial infection site, can trigger defense Punjab, Lahore, Pakistan systems at both infected and healthy parts of the plant e-mail: [email protected] (Montensano et al. 2003; Boller and Felix 2009; Nicaise et al. 2009;Shah2009). These defense signals B. Ali Department of Microbiology and Molecular Genetics, can also be artificially provided to plants for rapid University of the Punjab, Lahore, Pakistan activation of a plethora of biochemical and physical 123 Author's personal copy

W. Akram et al. defense responses (Conrath et al. 2006; Schreiber and Bacillus subtilis IAGS174 is a plant growth- Desveaux 2008; Conrath 2009, 2011; Jourdan et al. promoting bacterium capable of suppressing soil- 2009; Katagiri and Tsuda 2010). borne Fusarium wilt disease of tomato by inducing Plants respond to infectious agents by recognizing systemic resistance (Akram et al. 2013). In the current an array of microbial signals (Go´mez-Va´squez et al. study, tomato was again used as model system to 2004; Garcia-Brugger et al. 2006; Conrath 2011). identify bacterial determinant/s involved in the pro- These microbial signals are termed as elicitors and they cess of ISR in tomato against Fusarium wilt. initiate defense responses (Montensano et al. 2003; Ryan and Pearce 2003;Go´mez-Va´squez et al. 2004). Scientists have categorized these elicitors into two Materials and methods major types, general and specific (Montensano et al. 2003). General plant defense elicitors are also termed Preliminary screening of ISR determinants from B. as pathogen-associated molecular patterns (PAMP) subtilis IAGS174 (Felix and Boller 2003; Ron and Avni 2004). Some elicitors, which are associated with non-pathogenic The experiment was performed to screen the intra- endophytic microbes, are termed as microbe-associ- cellular metabolites and cell-free culture filtrates ated molecular patterns (MAMPs) (Boller and Felix (CFCF) of B. subtilis IAGS174 for their ability to 2009; Mishra et al. 2009). Upon recognition, these induce ISR in tomato plants against Fusarium wilt elicitors trigger plants to activate basal resistance disease. Two-week-old seedlings of tomato, grown in responses throughout the plant body (Zipfel et al. 2004, sterilized river silt, were used for the experiment. B. 2006; Mishra et al. 2009). These defense barriers are subtilis IAGS174 was inoculated in 100 ml Luria– effective enough to stop infection before pathogen Bertani (LB) broth and incubated overnight at 35 °C. establishment (Katagiri and Tsuda 2010). Hence, The culture was pelleted by centrifugation at 4,0009g elicitor-induced basal immunity is considered as a for 15 min, and the supernatant was collected in fresh, key component in the plant disease management sterilized falcon tubes and used for ISR assay. For program (Nurnberger et al. 2004; Park et al. 2008). extraction of intracellular metabolites, the bacterial Plant growth-promoting bacteria can trigger induced cell pellet was washed and resuspended in sterile resistance in plants by their specific MAMPs, which are distilled water. Cell lysis was performed by sonicating also termed as induced systemic resistance (ISR) the cell suspension six times at resonance amplitude determinants (Bakker et al. 2003; Persello-Cartieaux for 15 s at 4 °C to release all the cell components into et al. 2003; van loon et al. 1998; Lugtenberg and the solution. In total, 50 ml of both formulations were Kamilova 2009). In contrast to PAMPs, very little provided in 500 g of sterilized potting media placed information is available about the ISR determinants of inside sterilized plastic pots. The positive control growth-promoting microbes. Recognition of MAMPs treatment received 50 ml of a water formulation of B. produced by these bacteria would provide better under- subtilis IAGS174 at a concentration of 104 cfu ml-1, standing about the molecular crosstalk between bacteria while the untreated control received 50 ml of sterile and the host plant. Some known ISR determinants distilled water. The pathogen was provided by include flagellin produced by Pseudomonas putida adding 50 ml of the conidial suspension prepared strain WCS358 (Meziane et al. 2005), lipopolysaccha- in distilled sterilized water at a concentration of rides produced by Pseudomonas fluorescens (Duijff 105 conidia ml-1. The pots were incubated in a et al. 1997), P. putida (Meziane et al. 2005), Burk- greenhouse for two weeks, and the disease index holderia cepacia (Reitz et al. 2002), and Rhizobium etli (DI) was noted. Ten replicates of each treatment were strain G12 (Reitz et al. 2002), pyoverdine produced by used. To determine the DI, wilting was scored based P. fluorescens (Budzikiewicz, 2004), salicylic acid on the criteria developed by (Epp 1987)(0= no wilt produced by Pseudomonas aeruginosa (De Meyer and symptoms; 1 = less than 25 % of the plant turned Hofte 1997;DeMeyerandHofte1999), N-alkylated yellow; 2 = yellowing and browning covered nearly benzylamine derivate produced by P. putida (Ongena 50 % of plant; 3 = whole plant turned brown and et al. 2005), and N-acyl-L-homoserine lactone produced died). The equation described by Cachinero et al. by a rhizobacterium (Schuhegger et al. 2006). (2002) was used to calculate the DI. 123 Author's personal copy

Searching ISR determinant/s from B. subtilis IAGS174

DI ¼ RðÞni si =ðÞN S 100 and Skoog (MS) medium-containing culture tubes, which were kept in a growth chamber at 25 °C for the where, ni is the number of tomato plants with wilt development of seedlings. Five days after emergence, symptoms i, si is the value of the symptom score, N is the seedlings were provided with different prepara- the total number of tested plants, and S is the highest tions that were tested for ISR activity. The pathogen value of the symptom score. inoculum was prepared as described before. After 48 h of treatment application, 10 ll of the pathogen Isolation of ISR determinants from CFCF of B. inoculum was administered in the form of an subtilis IAGS174 aqueous spore suspension at a concentration of 105 conidia ml-1. The methodology proposed by Sumayo et al. (2013)was Seedlings were incubated under identical condi- adopted to identify ISR determinants from the CFCF of tions, and disease development and DI were recorded B. subtilis IAGS174. Bacterial cells were cultivated in after one week of incubation, as described earlier. Ten LB broth on a rotary shaker at 30 °C for 48 h, separated replicates of each treatment were carried out, and each from the growth medium by centrifugation at experiment was repeated thrice. 8,0009g for 10 min and the resultant CFCF was extracted twice with double volumes of ethyl acetate, chloroform, n-hexane, and n-butanol. The residual Estimation of the levels of defense-related aqueous phase and the remaining extracts were thor- enzymes oughly dried in rotary evaporators. These extracts were then dissolved in 10 % dimethylsufoxide, added to a Tomato seedlings were grown as described previ- plant growth medium to obtain a final concentration of ously. Five days after the seedlings emerged, the 0.1 %, and subjected to ISR bioassay, as described following treatments were provided: (1) untreated below. The extract with the highest ISR activity was plants, (2) plants treated with 0.1 mM phthalic acid further subjected to silica gel column chromatography. methyl ester (PAME), (3) plants treated with After equilibrating the column with two bed volumes of 0.1 mM PAME and inoculated with the pathogen ethyl acetate andmethanol, theextracts were loaded onto after 48 h, and (4) plants inoculated with the the column and fractioned by a stepwise elution process pathogen alone. Tomato leaves were harvested at with increasing concentration of methanol in ethyl different time points. Leaf samples were immedi- acetate. These fractions were dried and dissolved in ately frozen in liquid nitrogen and processed for 10 % dimethylsufoxide, and 10 ll of each fraction was extraction. Ten replicates of each treatment were again subjected to ISR bioassay, as described below. performed, and each experiment was repeated The sub-fraction with the highest ISR activity was twice. subjected to GC/MS analysis, performed using an For extraction of enzymes, leaf samples (0.4 g Agilent apparatus, containing a capillary column fresh weight) were ground in liquid nitrogen and (0.25 ID 9 30 m 9 0.25 lm film thickness). Electron homogenized with 3 ml of 100 mM ice-cold boric ionization (EI) was used as an ion source. Helium was -1 acid buffer (pH 8.8) for extracting phenylalanine provided as a carrier gas at a flow rate of 1 ml min . ammonia-lyase (PAL) and with 50 mM sodium Column temperature was set at 30 °C for 3 min and then phosphate buffer (pH 7.8) for extracting polyphenol raised to 180 °C at a rate of 50 °Cmin-1 and to 200 °C -1 oxidase (PPO) and peroxidase (POD). The homog- at a rate of 40 °Cmin . The compounds present in the enates were centrifuged at 4,0009g for 15 min, and ISR-active sub-fraction were purchased from Sigma- the resultant crude supernatant was used as the Aldrich and subjected to ISR bioassay at final concen- source of enzymes. All steps were carried out at trations of 0.01, 0.1, and 1.0 in a plant growth medium. 4 °C. The changes in POD, PPO, and PAL activities were determined by colorimetric assays that have Plant material and ISR bioassays been described earlier (Hammerschmidt et al. 1982; Mayer et al. 1965; Dickerson et al. 1984). Enzyme Wilt-susceptible tomato seeds were surface-sterilized activities were expressed in terms of change in with 1 % sodium hypochlorite and sown in Murashige absorbance min-1 g-1 fresh weight. 123 Author's personal copy

W. Akram et al.

Statistical analysis against Fusarium wilt disease (Fig. 1). Thus, these results were strongly indicative of the fact that CFCF The results were statistically evaluated by performing from B. subtilis IAGS174 carried the potential ISR analysis of variance (ANOVA) with the statistical determinants. software ‘DSAASTAT’. Treatment means were separated by Duncan’s new multiple range test at Isolation of ISR determinants from CFCF of B. P \ 0.05. subtilis IAGS174

For further screening of ISR determinants, CFCF was Results extracted by a series of organic solvents. ISR bioassay was performed by using organic extracts and the Preliminary screening of ISR determinants from B. residual aqueous phase. The ISR-active component, subtilis IAGS174 which was retained in the ethyl acetate fraction (Fig. 2), was further sub-fractionated by silica gel The goal of the current study was to screen for ISR chromatography to separate metabolites, and the sub- determinants from B. subtilis IAGS174 that induce fractions were subjected to ISR bioassays. The most protection against Fusarium wilt disease. For this marked reduction in Fusarium wilt disease was purpose, intracellular metabolites and CFCF were observed when the plants were treated with sub- screened for the presence of potential ISR determi- fraction 3 (Fig. 2). GC/MS analysis revealed that this nants. Both CFCF and live cells of B. subtilis ISR-active sub-fraction contained four compounds, IAGS174, which were used as a positive control, eugenol, 3-methoxy butyl acetate, pentachloroaniline provided promising signiﬁcant protection against and PAME (Fig. 3). Fusarium wilt disease of tomato (F = 366.8; df = 3, When the ISR bioassays were repeated using the 16; P \ 0.01) (Fig. 1). Indeed, CFCF was as effective pure biochemicals, only PAME was found to induce as the bacterial culture and reduced DI up to 73 % as systemic resistance in tomato against Fusarium wilt compared to that in plants that had been treated with disease (Figs. 2, 4). Treatments with 0.01 and 0.1 mM the pathogen alone. In contrast, intracellular metabo- PAME signiﬁcantly reduced DI up to 58.4 and 76.7 %, lites were unable to provide considerable protection respectively, as compared to that in the pathogen control (F = 73.6; df = 10, 44; P \ 0.01) (Fig. 4). A lower DI reduction was obtained by rest of the biochemicals with values not above the 23 % reduction in DI as compared to pathogen control (Figs. 2, 4).

Estimation of the levels of defense-related enzymes

The activities of different enzymes involved in the phenylpropanoid pathway i.e., PAL, POD, and PPO, were measured at specific time points. The results show that application of PAME increased the activity levels of these enzymes (Fig. 5), while the non- inoculated control plants consistently maintained low levels of activity of these enzymes (Fig. 5). Fig. 1 Potential of intra-cellular metabolites and cell free PAL activity was lower in plants inoculated with culture filtrates (CFCF) of B. subtilis IAGS174 to induce pathogen alone as compared to that in plants treated with systemic resistance in tomato against Fusarium wilt. Data are PAME at all the time points investigated. In tomato means of three independent experiments. Vertical bars represent plants receiving PAME in combination with the path- SE. Mean values followed by a different lower case letter are significantly different at P \ 0.05, according to Duncan’s new ogen, PAL activity increased and persisted at higher multiple range test levels at two and four days post-inoculation (DPI). 123 Author's personal copy

Searching ISR determinant/s from B. subtilis IAGS174

Fig. 2 Extraction procedure and ISR activity of crude and puriﬁed metabolites from cell free culture ﬁltrates (CFCF) of B. subtilis IAGS174

However, the activity declined at later time points. The In PAME treated tomato plants, POD activity PAL activity was maximum at 2 DPI, where it was 2.2 started increasing from the ﬁrst day after treatment and times higher than that in the untreated control plants peaked at 2 DPI (Fig. 5b). In plants co-inoculated with (Fig. 5a). In plants receiving the pathogen alone, PAL PAME and pathogen, the POD activity increased 2.8 activity increased at the initial time points of 1 and 2 and 1.7-fold at 2 and 4 DPI as compared to untreated DPI, but subsequently decreased (Fig. 5a). control (Fig. 5b). Plants inoculated with pathogen

123 Author's personal copy

W. Akram et al.

Fig. 3 Elucidation of biochemicals presents in ISR active sub-fraction in cell free culture ﬁltrates of B. subtilis IAGS174. a Chromatogram of gas chromatography and mass spectrometry analysis (GC/ MS) for identiﬁcation of the ISR determinant/s of B. subtilis IAGS174 present in the ISR-active sub-fraction. b The mass spectrum analysis obtained by electrospray ionization of phthalic acid methyl ester (PAME)

Fig. 4 Influence of root treatment with chemicals present in chemically treated plants mean that this concentration was lethal ISR active sub-fraction on the disease development on tomato to plant and plants died after treatment. Data are means of three plants after inoculation with Fusarium wilt pathogen. Sterile independent experiments. Vertical bars represent SE. Mean distilled water was used as positive control. ISR eliciting sub- values followed by a different lower case letter are significantly fraction was subjected to GC/MS analysis and chemicals present different at P \ 0.05, according to Duncan’s new multiple range were purchased and subjected to ISR bioassay. Absent bars in test alone showed a maximum POD activity that was 1.4 alone was also able to induce higher activity levels of times higher than that in the control at 2 DPI (Fig. 5b). PPO in tomato plants at the initial time points of 1–4 Similar to that observed with PAL and POD DPI, as compared to that observed at day 0 (Fig. 5c). activities, PAME induced higher PPO activity in tomato plants (Fig. 5c). PPO activity levels increased from 1 to 4 DPI and declined at later time points in Discussion plants that received PAME before being subsequently challenged with the pathogen (Fig. 5c). PPO activity Previous studies have shown that B. subtilis IAGS174 increased 1.7 and 2.4-fold at 2 and 4 DPI under the can induce systemic resistance in tomato plants influence of this treatment. Nearly the same trend was against Fusarium wilt disease (Akram et al. 2013). noted in plants receiving PAME alone. The pathogen The present study was carried out to screen the ISR 123 Author's personal copy

Searching ISR determinant/s from B. subtilis IAGS174

some studies, it has been shown that biochemicals eliciting systemic resistance were retained in culture filtrates of the bacterial strain (Gomez-Gomez and Boller 2002; Leeman et al. 1996; van Peer and Schippers 1992). The ethyl acetate fraction of the CFCF from B. subtilis IAGS174 culture, which was shown by initial experiments to have ISR-eliciting ability, was then partitioned into sub-fractions and subjected to GC/MS analysis. This resulted in the identification of PAME, along with four other compounds in the active sub-fraction. Subsequent ISR bioassay by using these pure compounds showed that among them, only PAME elicited systemic resistance in tomato plants against Fusarium wilt disease (Fig. 4). Phthalic acid (dicarboxalic acid) is a diacid form of aromatic carboxylic acids. Different carboxylic acids including phthalic acids are active allelochemicals, capable of changing plant growth and physiology (Ignacimuthu 1997; Piccolo et al. 2003). Phthalic acid is produced by both plants (Ignacimuthu 1997; Piccolo et al. 2003; Sani and Pateh 2009) and bacteria (Hao et al. 2004; El-Mehalawy et al. 2008). In an investigation, exposure of apple plants to phthalic acid elicited production of anti-oxidant enzymes and reactive oxygen species (ROS) (Bai et al. 2009). ROS are the major components of the signal transduction cascade involved in plant defense related mechanisms, like reinforcement of plant cell wall and phytoalexin production (Dempsey and Klessig 1995; Neill et al. 2002). These ROS can be used as a marker for the analysis of occurrence of plant basal defense reactions (Bozso´ et al. 2005). In current investigation it can be attributed that PAME elicited production of ROS, which then triggered an array of defense Fig. 5 Changes in defense related enzymes activity in tomato responses inside plant body. plants under influence of phthalic acid methyl ester (PAME) and Some biologically active metabolites play a role as F. oxysporum f. sp. lycopersici (Fol) inoculation. a Phenylala- nine ammonia-lyase (PAL) activity, b peroxidase (POD) ISR elicitors at low concentration but show antibiotic activity and c polyphenol oxidase (PPO). Vertical bars represent activity at higher concentration (Rohilla et al. 2002; SE Tosi and Zazzerini, 2000). In our study, treatment of tomato plants with 1.0 mM PAME caused death of determinants from this strain by using tomato as a plants but, in lower concentration of 0.1 mM, it model plant and Fusarium oxysporum subsp. lycoper- significantly decreased Fusarium wilt incidence. This sici as the challenging pathogen. In the initial phase, suggests that this chemical at higher concentration is significant reduction of disease symptoms was toxic to plants but is more effective in eliciting ISR at observed by treating with CFCF and alive B. subtilis lower concentrations. In another study, an ISR-active IAGS174 cells. This was in contrast to the effect of biochemical, 4-aminocarbonyl phenylacetate, pro- intracellular metabolites that were unable to provide duced by P. chlororaphis O6, when applied at a any significant protection against pathogen (Fig. 1). In concentration of 68 mM, elicited ISR activity against 123 Author's personal copy

W. Akram et al. the wildfire pathogen at a level similar to that elicited Acknowledgments We are thankful to Forman’s Christian by 1 mM salicylic acid (Park et al. 2008). Similarly, College, Lahore, Pakistan for providing us assistance to perform GCMS analysis. We are also thankful to First Fungal Culture the ISR effect of butyl 2-pyrrolidone-5-carboxylate Bank of Pakistan for providing microbial strains. produced by K. oxytoca C1036 was observed when applied exogenously to tobacco plants at a concentra- References tion of 12 mM (Park et al. 2009). Generally, plants have evolved a large variety of Akram W, Anjum T, Ali B, Ahmad A (2013) Screening of defense responses against pathogenic infection, which native bacillus strains to induce systemic resistance in include the synthesis of pathogenesis-related (PR) tomato plants against Fusarium wilt in split root system proteins and phytoalexins, the enforcement of cell wall and its field applications. Int J Agric Biol 15:1289–1294 polymers with deposition of lignin, and enhanced Anterola AM, Lewis NG (2002) Trends in lignin modification: a comprehensive analysis of the effects of genetic manipu- activity of various defense-related enzymes (Anterola lations/mutations on lignification and vascular integrity. et al. 2002; Busam et al. 1997; Conrath et al. 2001). In Phytochemistry 61:221–294 this study, we subsequently studied the influence of Ausubel FM (2005) Are innate immune signaling pathways in PAME on the activities of some defense-related plants and animals conserved? Nat Immunol 6:973–979 Bai R, Ma F, Liang D, Zhao X (2009) Phthalic acid induces enzymes in tomato seedlings. Calorimetric enzyme oxidative stress and alters the activity of some antioxidant analysis indicated that the ISR against the Fusarium enzymes in roots of Malus prunifolia. J Chem Ecol wilt disease pathogen induced by PAME application 35:488–494 appears to be associated with increased activities of Bakker P, Ran LX, Pieterse CMJ, van Loon LC (2003) Under- standing the involvement of rhizobacteria-mediated defense-related enzymes such as PAL, PPO, and POD induction of systemic resistance in biocontrol of plant (Li and Steffens 2002; Baysal et al. 2003; Trotel-Aziz diseases. Can J Plant Pathol 25:5–9 et al. 2006; Pina and Errea 2008). Baysal O, Soylu EM, Soylu S (2003) Induction of defence- Moreover, the time points at which the levels of related enzymes and resistance by the plant activator acibenzolar-S-methyl in tomato seedlings against bacterial these defense-related enzymes increased (1, 2, and 4 canker caused by Clavibacter michiganensis ssp. michi- DPI) coincided with the early infection events of the ganensis. Plant Pathol 52:747–753 pathogen, thereby implicating an effective role in Boller T, Felix G (2009) A renaissance of elicitors: perception of PAME-mediated resistance against the Fusarium wilt microbe-associated molecular patterns and danger-signals by pattern recognition receptors. Annu Rev Plant Biol disease pathogen in tomato. Tomato plants treated 60:379–406 with PAME in combination with the pathogen chal- Bozso´ Z, Ott PG, Szama´ri A´ , Zelleng A´ C, Varga G, Besenyei E, lenge provided the maximum increase in the levels of Sardi E, Banyei E, Klement Z (2005) Early detection of defense-related enzymes (Fig. 5), suggesting a posi- bacterium-induced basal resistance in tobacco leaves with diaminobenzidine and dichlorofluorescein diacetate. tive synergistic effect of PAME and pathogen. This J Phytopathol 153:596–607 observation was similar to that noted in a previous Budzikiewicz H (2004) Bacterial catecholate siderophores. study (Song et al. 2011) where application of exog- Mini-Rev Org Chem 1:163–168 enous abscisic acid on tomato plants induced ISR Busam G, Kassemeyer HH, Matern U (1997) Differential expression of chitinases in Vitis vinifera L. responding to against F. oxysporum. systemic acquired resistance activators or fungal challenge. Recent progress in understanding plant immunity is a Plant Physiol 115:1029–1038 driving force for crop protection in fields. The discovery Cachinero JM, Hervas A, Jimenez-Diaz RM, Tena M (2002) of MAMPs, produced by beneficial microbes, can help Plant defence reactions against Fusarium wilt in chickpea induced by incompatible race 0 of Fusarium oxysporum f. in the development of new formulations capable of sp. ciceris and non-host isolates of F. oxysporum. Plant eliciting ISR in plants in the conventional agricultural Pathol 51:765–776 system. In conclusion, current investigations imply that Conrath U (2009) Priming of induced plant defence responses. PAME is an ISR determinant of B. subtilis IAGS174. Its In: van Loon LC (ed) Plant innate immunity. Elsevier, Burlington, USA, pp 361–395 application can effectively activate ISR against Fusar- Conrath U (2011) Molecular aspects of defence priming. Trends ium wilt disease in tomato plants. In our attempts to Plant Sci 16:524–531 elucidate the mechanism underlying ISR induced by Conrath U, Thulke O, Katz V, Schwindling S, Kohler A (2001) PAME, we showed that its application seemed to Priming as a mechanism in induced systemic resistance of plants. Eur J Plant Pathol 107:113–119 activate defense-related enzymes like PAL, PPO, and Conrath U, Beckers GJM, Flors V, Garcia-Agustin P, Jakab G, PODintomatoplants. Mauch F, Newman MA, Pieterse CMJ, Poinssot B, Pozo- 123 Author's personal copy

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INTERNATIONAL JOURNAL OF AGRICULTURE & BIOLOGY ISSN Print: 1560–8530; ISSN Online: 1814–9596 13S–005/2013/15–6–1289–1294 http://www.fspublishers.org

Full Length Article

Screening of Native Bacillus Strains to Induce Systemic Resistance in Tomato Plants against Fusarium Wilt in Split Root System and its Field Applications

Waheed Akram1*, Tehmina Anjum1, Basharat Ali2 and Aqeel Ahmad1 1Institute of Agriculture Sciences, University of the Punjab, Lahore, Pakistan 2Department of Microbiology and Molecular Genetics, University of the Punjab Lahore, Pakistan *For correspondence: [email protected]

Abstract

A study was carried out to screen some bacillus strains for their ability to induce systemic resistance against fusarium wilt of tomato under both split root system and field conditions. Fourteen bacillus strains were used for initial screening of resistance induction under split root design in green house evaluations. Increase in quantities of defense related biochemicals as total phenolics, PO, PPO and PAL enzymes were examined to document induced systemic resistance (ISR) phenomenon in tomato plants under influence of these bacterial inducers. Two Bacillus strains viz., B. fortis IAGS162 and B. subtilis IAGS174 provided maximum control over fusarium wilt under split root system. Calorimetric assays proved highly significant for defense related biochemicals in tomato plants under the influence of these two bacterial strains. Talc based formulations of these two strains were prepaired to check their efficacy under field conditions. These not only provided protection against fusarium wilt, but also markedly enhanced growth and fruit yield of plants under field conditions. Our study clearly indicated the importance of these microbial organisms for suppression of Fusarium wilt and growth promotion in our agriculture system. © 2013 Friends Science Publishers

Keywords: Bacillus strains; Fusarium wilt; Induced systemic resistance; Disease index; Control effects; Growth promotion

Introduction inside plant body (Cachinero et al., 2002; Shoresh et al., 2010). All these events confer resistance against penetrating Like all living organisms, plants must face infections and pathogen and make plant safe from subsequent pathogen diseases following the attacks of a mass of plant pathogens attack. and pests from animal, microbial or viral origin. Plant Biocontrol of soil borne diseases is considered as diseases are responsible for the loss of at least 10% of global effective disease management strategy (Wenhua and food production, representing a threat to food security Hetong, 1997; Thakore, 2006; Kavino et al., 2007). (Strange and Scott, 2005). Fusarium is common in both Significant reduction in disease and increase in growth of tropical and subtropical environments and some of its crop plants in response to inoculation with certain bacterial members are most destructive pathogens of several plant strains have been repeatedly reported (Asghar et al., 2002; species (Nelson et al., 1983; Zhang et al., 1996; Bokshi et Vessey, 2003; Gray and Smith, 2005; Silva et al., 2006; al., 2003). Fusarium wilt of tomato is a serious problem in Figueiredo et al., 2008; EPA, 2011). Bacteria in the genera all tomato growing areas of the world. Bacillus, Streptomyces, Pseudomonas, Burkholderia, and Defense mechanisms of plant can be activated by Agrobacterium are the biological control agents external stimuli before infection of a pathogen (Pieterse and predominantly studied (Bashan, 1998; Lucy et al., 2004). Van Loon, 1999; Stadnik, 2000). This phenomenon is called These bacterial strains can either produce antibiotics or Induced systemic resistance (ISR). Both biotic and abiotic siderophores that leads to induction of systemic resistance agents have been successfully used in ISR in plants against (Tenuta, 2003). According to Hallman et al, (1997), pathogens (Akram and Anjum, 2011). ISR has been endophytic bacteria involved in biological control show successfully used for plant protection under both green advantages of having the same ecological niche of the house and field conditions for longer times. Inducible pathogen and could be protected from diverse abiotic systemic resistance responses include cell wall influences. strengthening by deposition of lignin and callose, In the current investigation, we tested our production of antimicrobial compounds like phytoanticipins hypothesis that our native bacillus strains can induce and overexpression of pathogenesis related PR proteins systemic resistance in tomato against Fusarium wilt disease.

To cite this paper: Akram, W., T. Anjum, B. Ali and A. Ahmad, 2013. Screening of native bacillus strains to induce systemic resistance in tomato plants against fusarium wilt in split root system and its field applications. Int. J. Agric. Biol., 15: 1289‒1294

Akram et al. / Int. J. Agric. Biol., Vol. 15, No. 6, 2013

So the present study was aimed on screening different native Table 1: Potential of Bacillus strains to control Fusarium bacillus strains for their ability to indue resistance in tomato wilt in three different varieties of tomato under split root against fusarium wilt disease and elucidation of mechanism experiment behind induced resistance. This was the first study carried out by using our native Bacillus strains under both split root Treatments Disease Control system and field conditions to induce resistance against Inducer Side Responder Index (%) Effect (%) Side Fusarium wilt of tomato. B. fortis IAGS 324 Fol 20.01±2.31c-e 26.73±3.83e Materials and Methods B. fortis IAGS 223 Fol 23.34±1.58bc 14.53±1.53f B. fortis IAGS 162 Fol 14.83±3.05g 52.37±4.64a Efficacy of Bacillus Strains against Fusarium Wilt under B. thuringiensisIAGS 199 Fol 19.16±2.86d-f 30.21±2.10de B. thuringiensisIAGS 002 Fol 18.00±2.60ef 32.42±2.91cd Split Root System B. subtilis MCR7 Fol 24.17±3.46bc 11.46±2.93fg B. subtilis IAGS 170 Fol 18.16±0.96ef 33.37±2.73cd Fourteen Bacillus strains belonging to four species were B. subtilis IAGS174 Fol 16.82±2.26f 48.14±3.37bc obtained from bacterial conservatories of Institute of B. subtilis FBL10 Fol 26.30±3.43b 03.68±0.57h B. megaterium ZMR-4 Fol 23.67±1.75b-d 13.32±1.53f Agricultural Sciences and Department of Microbiology and B. megaterium ZMR-6 Fol 19.34±3.67d-f 30.15±2.44de Molecular Genetics, University of the Punjab, Lahore, B. megaterium ZMR-3 Fol 23.41±2.26b-d 14.23±2.72f Pakistan. These strains were mostly rhizospheric in nature B. megaterium MCR-8 Fol 17.41±3.92ef 36.51±3.62bc whise, details are provided in Table 1. Bacterial inoculum B. megaterium OSR-3 Fol 26.34±1.08b 06.84±1.05gh Water Fol 57.31±4.23a - was prepared by growing in Luria Broth (LB) medium. water water - - Media containing bacterial growth was centrifuged and Mean ± standard deviation. Values with same letter differ non-significantly pellet was resuspended in sterile distilled water to obtain the (P>0.05) as governed by ANOVA and DNMRT. UC=Untreated Control. final bacterial concentration of 104 cfu/mL by taking OD of PC=Pathogen Control. Fol=F. oxysporum f. sp. Lycopersici 0.1 at 600nm. Virulent strain of F. oxysporum f.sp. lycopersici (Fol) was obtained from Fungal Biotechnology Lab at the University of the Punjab, Pakistan. Pathogen inoculum was prepared by harvesting both micro- and macro-conidia from seven days old cultures grown on sterile PDA media at concentration of 1 x 103 conidia/mL, by haemocytometer. Tomato seedlings of vaerity „Rio Grand‟ were raised in sterilized sandy loamy soil. Green house evaluations were carried under split root design. For that purpose, roots of 30 days old tomato seedlings were splited into two halves and single seedling was tranfered in two combined pots (Fig. 1). In each treatment, inducer side was provided with 50 mL of bacterial inoculum and responder side got 50 mL of pathogen inoculum. For pathogen control, inducer side got distilled sterelized water and responder side got pathogen inoculum. Untreated control got distilled sterilized water on both sides. Pots were kept in green house for incubation. Disease index and control effects were analyzed after 30 days of inoculation. To sort out disease index, first severity of wilt was determined using a rating scale of 0~4 on the basis of root discoloration or leaf yellowing: 0: no root Fig. 1: Split Root Design discoloration or leaf yellowing; 1: 1~25% root discoloration or one leaf yellowed; 2: 26~50% root discoloration or more Elucidation of Biochemicals Basis of ISR than one leaf yellowed; 3: 51~75% root discoloration plus one leaf wilted; 4: up to 76% root discoloration or Quantifications of defense related biochemicals were completely dead plants (Epp. 1987). Disease index and performed at regular intervals of five days from the day of biocontrol effect were calculated according to the method of inoculation to final harvest and their mean values were used Li et al. (2008). for comparison. For that purpose, root samples were taken

∑(Grade of disease severity±diseased plants of this grade) from responde sides of the tomato plants for each treatment Disease index (%) = X100 Total plants assed X Highest grade of disease severity and total phenolics, peroxidase (PO), polyphenoloxidase

Biocontrol effect (%) = (Disease index of pathogen control- diseased index of bacterial control) X 100 (PPO) and phenyl ammonia lyase (PAL) were quantified by Disease index of pathogen control following methods.

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Quantifications of total phenolics: One gram plant the Punjab, Lahore Pakistan. Randomized split plot design material was extracted with 10 mL of 80% methanol at was used for field experiments with three replicates per 70oC for 15 min. Reaction mixture was containing 1 mL of treatment. Main plots were further divided into subplots of methanolic extracts and 5 mL of distilled sterilized water 2×3 m2. Tomato seedlings were raised in sterilized potting 250 μL of Folin-Ciocalteau reagent (1 N). This solution was media as described in previous section. Fol inoculum was kept at 25oC. The absorbance of the developed blue color developed on sweet sorghum grains and applied in allotted was measured using a spectrophotometer at 725 nm. Gallic subplots at rate of 100 g/plot and left for two weeks for acid was used as standard. The amount of total phenolics establishment of pathogen. Tomat oseedlings were primed was expressed on gallic acid equivalent basis (Zieslin and with talc based bacterial formulations and transferred in Ben-Zaken, 1993). field. Details of treatments are provided in Table 4. Data Quantifications of PO, PPO and PAL activity: One gram regarding disease index, and control effect was noted after of plant material was homogenized with 2 mL of 0.1 M 60 days of transplantations as described prevously. Plant sodium phosphate buffer (pH 7.0) in ice bath for enzyme height and fruit yield was also noted at final harvest to assays. The homogenates were then centrifuged at 10,000 g observe grown promoting capabilitis of our selected strains. for 10 min. Supernatants were used to analyze the PO, PPO and PAL activities. Statistical Analysis Method of Fu and Huang (2001) was used to estimate the PO activity. For this purpose 50 µL of enzyme extract All the results were analyzed by performing ANOVA and was added to 2.85 mL of 0.1 M phosphate buffer (pH 7.0) DNMRT (Steel and Torrie 1980) with the help of computer and mixed with 0.05 mL of 20 mM guaiacol reagent. The aided program “DSASTAT”. reaction was started by the addition of 0.02 mL of 40 mM hydrogen peroxide to the mixture. Rate of increase in Results absorbance at 470 nm was measured over 1 min. PPO activity was determined according to method proposed by Efficacy of Bacillus Strains against Fusarium Wilt under Mayer et al. (1965). The reaction mixture was containing Split Root System 200 μL enzyme extract and 1.5 mL of 0.01 M catechol. Activity was expressed as changes in absorbance at 495 nm. The purpose of this experiment was to screen bacterial strain PAL activity was determined according to method of capable of inducing systemic resistance in tomato plants Burrell and Rees (1974). The reaction mixture contained against fusarium wilt using split root experiment, which 0.03 M L-phenylalanine and 0.2 mL enzyme extract in a tried to avoid direct antagonism between pathogen and total 2.5 mL of sodium borate buffer (pH 8.8). This reaction bacterial strains. During incubation period in greenhouse, mixture was kept in a water bath at 37oC for 1 h and 0.5 mL symptoms first appeared as mild temporary wilting then of 1 M trichloroacetic acid was added. The amount of trans- effecting whole plant. In case of bacterial treated plants cinnamic acid formed from L-phenylalanine was measured along with pathogen, delay in symptoms appearance was spectrophotometerically at 290 nm. observed as compared to pathogen control plants. Some of our bacterial strains significantly controlled fusarium wilt Development of Talc Based Inoculum disease as compared to pathogen control. Conspicuously, disease severity and control effect index (Table 1) Two best performing strains were selected for field represented that B. fortis IAGS162 (T3) and B. subtilis evaluations. Their inoculum was prepared on sterilized Talc IAGS174 (T8) performed batter in this regard with for application under field conditions. Three types talc minimum disease index of (Fig. 2). These two strains formulations were prepaired viz. Both bacterial strains were provided maximum protection against fusarium wilt and grown in LB broth media separately. After overnight growth were used for field evaluations. o at 35 C, bacterial cells were collected by centrifugation at 4000 rpm for 15 min. Bacterial cell pellets were Elucidation of Biochemical Basis of Defense Induction resuspended in sterilized distilled water at concentrations of 104 cfu/mL. Fifty mL of this bacterial inoculum was Presence of bacillus strains induced tomato plants for mixed in 100 gram of sterilized talc. Formulation in which significantly (P>0.05) higher production levels of phenolics, both bacterial strains were added, 25 mL inoculum of each PO, PPO and PAL as compared to pathogen alone and strain was taken and mixed with 100 gram of sterilized talc. untreated controls (Table 2). B. fortis IAGS162 (T3) and B. subtilis IAGS174 (T8) increased phenolics quantities up to Field Experiment 67.15 and 55.47% as compared to untreated control (Table 2). In the same way, an increase of 56.70, 41.56 and 57.57% Field experiment was performed twice in years of 2011 and was recorder in PO, PPO and PAL activities under influence 2012 in tomato growing season in Agriculture Research of B. subtilis IAGS174 (T8) compared to untreated control. Station of Institute of Agricultural Sciences, University of Such differences (P>0.05) in quantities of total phenolics,

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Table 2: Effect of bacterial inducers on elicitation of defense related biochemicals in tomato plants under split root system

Treatments Phenolics % IOUC PO Activity % I OUC PPO Activity % I OUC PAL Activity % I OUC Inducer Side Responder side (µg/h/gfw) ( µg/h/gfw) ( µg/h/gfw) ( µg/h/gfw) B. fortis IAGS 324 Fol 1.86±0.07d-f 35.76±4.25fg 1.33±0.08cd 37.11±2.53d 6.07±0.59bc 42.48±3.07c-e 2.23±0.64bc 16.16±2.46e B. fortis IAGS 223 Fol 1.61±0.06f-h 17.51±2.67j 1.17±0.15e-g 20.61±1.19g 5.89±0.61e-g 27.67±1.52f 2.07±0.39bc 04.54±0.82fg B. fortis IAGS 162 Fol 2.29±0.09b 67.15±4.28b 1.45±0.09b 49.48±3.82b 7.31±0.88a 71.59±9.21a 3.27±0.51a 65.15±7.39a B. thuringiensisIAGS 199 Fol 1.92±0.10c-e 40.14±3.92e 1.29±0.13d 32.98±2.51e 5.69±0.37f-i 25.13±3.43f 2.33±0.08b 12.62±2.03e B. thuringiensisIAGS 002 Fol 2.03±0.08cd 48.17±2.36ef 1.34±0.67cd 41.23±2.43c 6.17±0.70d-f 44.83±2.30cd 2.85±0.13ab 43.93±6.53d B. subtilis MCR7 Fol 1.83±0.09d-f 33.57±3.91gh 1.29±0.18d 32.98±2.18e 5.86(±0.62e-g 37.55±4.48e 2.13±0.42bc 07.57±1.04f B. subtilis IAGS 170 Fol 1.77±0.11e-g 29.19±2.42h 1.16±0.07e-g 19.98±1.08gh 5.99±0.82fg 40.16±5.69de 2.01±0.71bc 01.51±0.13g B. subtilis IAGS174 Fol 2.13±0.09c 55.47±4.52c 1.52±0.12a 56.70±3.44a 7.29±0.72ab 41.56±3.55c-e 3.12±0.36a 57.57±4.63b B. subtilis FBL10 Fol 1.89±0.08d-f 37.95±2.63ef 1.12±0.19g 15.46±1.47h 5.26±0.61hi 19.01±2.27g 2.26±0.41b 14.14±2.21e B. megaterium ZMR-4 Fol 1.90±0.12c-e 38.68±3.82ef 1.23±0.07d-f 26.80±1.92f 6.10±0.32d-g 30.16±3.27f 2.98±0.76ab 50.42±3.58c B. megaterium ZMR-6 Fol 2.36±0.09b 72.26±6.53a 1.14±0.13fg 17.52±1.50gh 6.62±0.53cd 46.94±2.82c 3.01±0.11a 50.20±2.68c B. megaterium ZMR-3 Fol 1.93±0.08c-e 40.87±2.24e 1.23±0.06d-f 26.80±2.83f 6.73±0.72bc 57.98±4.67b 2.88±0.28a 45.42±3.05d B. megaterium MCR-8 Fol 2.08±0.15cd 51.82±3.50cd 1.16±0.08e-g 19.58±3.49gh 5.23±0.60i 18.54±2.07g 2.12±0.94bc 07.05±1.14f B. megaterium OSR-3 Fol 1.70±1.05e-g 24.08±1.05i 1.38±1.05bc 42.26±1.05c 6.30±0.95c-e 47.88±5.36c 2.10±0.26bc 06.31±1.26f Water Fol 1.54±1.05gh 12.40±1.05k 1.13±1.05fg 16.49±1.05gh 5.51±0.24g-i 29.34±2.75f 2.06±0.17bc 04.75±0.85fg water water 1.37±1.05h - 0.97±0.08h - 4.26±0.34j - 1.98±0.06cd - Mean ± standard deviation. Values with same letter differ non-significantly (P>0.05) as governed by ANOVA and DNMRT. UC=Untreated Control. PC=Pathogen Control. IOUC=Increase over untreated control

Table 3: Potential of selected bacillus strains on fusarium Discussion wilt management under field conditions This study showed that our native bacillus strains have Treatments Experiment 1 Experiment 2 Disease index Control effect Disease index Control effect potential benefits in practical agriculture. Numerous reports (%) (%) (%) (%) show that beneficial microbes can protect plants against a BS 37.86±4.23c 58.07±5.42b 28.81±7.43bc 62.34±5.80b wide range of disease (Raaijmakers et al., 1995; Latha et al., BF 46.29±5.77b 47.29±4.63c 31.11±3.29b 64.08±7.43b 2009). Bacterial inducers remain restricted up to root system BS±BF 23.87±3.92d 68.15±8.61a 19.57±2.41d 76.87±11.81a PC 83.67±8.61a ND 75.93±09.51a ND of the plant. But the phenomenon of ISR is because of UC ND ND ND ND lipopeptides of the surfactin and fengyci, that play the role Mean ± standard deviation. Values with same letter differ non-significantly of elicitor for activation of pant defense system (Ongena et (P>0.05) as governed by ANOVA and DNMRT. BS=B. subtilis IAGS174. al., 2007; Jourdan et al., 2009). Bacterial inducers BF=B. fortis IAGS 162. UC=Untreated Control. PC=Pathogen Control comprised variable degree of disease controlling phenomenon in our current investigation. This can be PO, PPO and PAL were observed for B. fortis IAGS162 attributed the differences that might result from the different (T3) when comparisons were made between control origins of each isolate (Raaijmakers et al., 1995; Mercado- treatments (Table 2). Blanco and Bakker, 2007). In our split root investigations, B. fortis IAGS162 and B. subtilis IAGS174 showed better Field Experiment suppression of disease as compared to other bacilli strains.

Like split root experiment, our bacterial inducers provided Efficacy of bacillus genera to control other plant diseases promising protection against fusarium wilt under field has also been documented against several other plant conditions. Treatments in which we used combination of diseases. B. subtilis proved effective to control B. cinerea on strains provided excellent protection against fusarium wilt. grapes (Magnin-Robert et al., 2007; Trotel-Aziz et al., This treatment provided biocontrol effect of more than 60% 2008). in both field experiments (Table 3). Under field conditions, combination of these two Along with protection agiainst Fusarium wilt, our microbes provided better level of protection against bacterial inducers also promoted growth and yield of fusarium wilt disease. Some researchers showed that tomato plants under field conditions (Table 4). Tomato combination of bacterial strains provided better protection seedlings that were primed with bacterial inducers, against diseases. In a research, mixture of bacterial inducers provided significantly (P>0.05) higher plant height and provided ISR against a cucumber leaf spot disease (Raupach biomasses as compared to untreated control plots. and Kloepper, 2000). It is suggested that use of bacterial Treatments in which both straisn were applied, promoted inducers in combination display increased defense related height of plant upto 37 and 28% in experiment I and II, biochemicals inside plant body (Raupach and Kloepper, respectively. Samely, yield of tomato plants was positively 2000; Jetiyanon and Kloepper, 2002). It is also proposed influenced by bacterial inducers at significant levels (Table that use of combination of bacterial inducers can provide 4). These data provide strong evidence in favor of our protection against a wide range of pathogens to plants. bacterial inducers under field conditions. Considering the spatial separation of applied bacteria at the root level, the disease protection by bacteria results

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Table 4: Effect of bacillus strains on plant growth parameters under field conditions

Treatment Experiment 1 Experiment 2 Plant Height Total Biomass (g) Number of Plant Height Total Biomass (g) Number of (cm) Fresh Dry Fruits (cm) Fresh Dry Fruits BS 33.27±2.16b 113.29±16.73bc 13.90±04.13ab 15.18±3.96bc 38.07±5.14b 127.29±15.50b 21.38±4.71b 14.11±3.17c BF 30.38±4.29bc 102.55±11.25c-e 10.74±02.82b-d 17.73±2.72b 35.36±4.18bc 112.55±19.72c 16.97±2.98c 11.53±2.25cd BS±BF 38.92±5.14a 123.94±13.52ab 15.03±02.36a 23.43±4.80a 41.26±3.26ab 159.49±17.53a 26.72±5.31a 21.37±4.30a PC 18.27±3.36e 51.29±08.61g 06.75±01.17de 07.06±1.18d 21.07±3.52e 66.92±07.58d 09.73±3.76e 04.42±1.06e UC 27.64±3.04cd 94.26±07.43ef 08.96±02.25cd 16.65±3.95b 32.93±5.24cd 123.26±22.48b 14.19±1.58cd 17.61±2.16bc Mean ± standard deviation. Values with same letter differ non-significantly (P>0.05) as governed by ANOVA and DNMRT. BS=B. subtilis IAGS174. BF=B. fortis IAGS 162. UC=Untreated Control. PC=Pathogen Control from an ISR in plants (Magnin-Robert et al., 2007). Bacillus solubilization of phosphorus, iron and other strains can induce resistance against a number of diseases in oligoelements (Ryu et al., 2003). Seemingly increasing field crops (Akram and Anjum, 2011). Previously, mostly fruit was observed set when experiment was performed researchers have performed ISR experiments in single pot under field conditions. system but we applied split root system in our initial In conclusion this work illustrates the effectiveness of screening that confirms ISR phenomenon and negated bacillus strains to induce systemic resistance and growth chances of direct antagonism. Bacterial organisms have the promotion in tomato plants under both greenhouse and field potential to elicit ISR in plants. This activated defense conditions. 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Full Length Article

Basal Susceptibility of Tomato Varieties against Different Isolates of Fusarium oxysporum f. sp. lycopersici

Waheed Akram*, Tehmina Anjum and Aqeel Ahmad Institute of Agricultural Sciences, University of the Punjab, Pakistan *For correspondence: [email protected]

Abstract

Basal susceptibility of tomato varieties was studied against Fusarium wilt by using ten different isolates of Fusarium oxysporum f. sp. lycopersici (Fol). These isolates were collected from infected tomato plants from different tomato fields. A total of 230 combinations of Fol isolates and tomato varieties were evaluated and disease index was calculated. Mean disease index against all Fol isolates was used to govern susceptibility of single tomato variety against Fusarium wilt disease. Based on this mean disease index, varieties were classified into five groups viz., immune, resistant, moderately resistant, susceptible and very susceptible. None of the variety was completely resistant or immune against Fol. Three varieties viz., Pride Burn, Red Power, Sun Grape were moderately resistant. All other varieties were either susceptible or very susceptible against Fol infection. Varying levels of susceptibility of tomato varieties was observed against different isolates of Fol. Clusters analysis based on disease index values placed all tomato varieties in three different groups. Genetic finger printing of all Fol isolates was performed by using ISSR markers. Dendrogram based on the ISSR analysis divided all Fol isolates in two major groups. This is first study carried out in Pakistan by using multiple strains of Fol to declare basal susceptibility of tomato germplasm against Fusarium wilt. © 2014 Friends Science Publishers

Keywords: Fusarium oxysporum f. sp. Lycopersici; Tomato; Mean disease index; ISSR markers

Introduction responsible for important crop losses in the tomato fields (Benhamou et al., 1998). Tomato (Lycopersicon esculentum Miller) is the second Control of F. oxysporum infection in the field is major vegetable product of Pakistan (Mirza, 2007). Tomato difficult because the pathogen can survive for a long period farming covered 63 thousand hectares during 2009-2010, of time in the form of mycelium in infected plant debris or with an average yield of 10522 kg/ha (Anonymous, 2011). in the form of chlamydospores in soil (Haware et al., 1996; This yield is very low as compared to that of the developed Agrios, 1997). Chemical control of wilt has not been countries, where it can reach up to an average of 1562 effective because pathogen is both soil and seed-borne. kg/hectare (Sajjad et al., 2011). Several fungal, bacterial and Some other control strategies against Fusarium wilt include some viral diseases of tomato contribute in severe yield loss employing antagonistic microbes and applying botanical of tomato under field conditions. pesticides (Di Pietro et al., 2003; Djatnika and Hermanto, Fusarium wilt disease has ever been the most 2003). Some studies have indicated the ability of destructive plant diseases in history (Halila and Strange, antagonistic microbes to control Fol, but their effectiveness 1996). All members of F. oxysporum are successful in the field has not yet been proven (Bastasa and Baliad, saprophytes and capable to survive for long periods of time 2005). Genetic resistance in tomato germplasm against this under most of the edaphic conditions. Some isolates induce disease is considered as efficient mean of controlling this root-rot and vascular diseases on specific hosts (Olivain et disease (Medina-Filho and Tanksley, 1983). This approach al., 1981; Olivain and Alabouvette, 1997; 1999; Olivain et is also considered as an ecofriendly control measure. The al., 2003) and are classified into approx. 120 formae ideal strategy for managing Fusarium wilt disease is by speciales and races, based on the plant species and cultivars cultivating resistant germplasm. they infect (Armstrong and Armstrong, 1981; Tello and Sexual mode of reproduction in pathogen provides Lacasa, 1988; Gordon and Okamoto, 1992; Alabouvette et them new genetic recombination and thus evolving new al., 2001). Pathogenic isolates of F. oxysporum often pathogenic populations (Pushpavathi et al., 2006). For display a high degree of host speciﬁcity (Sakai, 1998). development of resistant plant germplasm against diseases, Infection occurs when the pathogen penetrates in roots of there is need of complete knowledge of variability in the plant. Fusarium oxysporum f. sp. lycopersici (Fol) is virulence and genetic makeup of different strains of a single

To cite this paper: Akram, W., T. Anjum and A. Ahmad, 2014. Basal susceptibility of tomato varieties against different isolates of F. oxysporum f. sp. Lycopersici. Int. J. Agric. Biol., 16: 171–176

Akram et al. / Int. J. Agric. Biol., Vol. 16, No. 1, 2014 pathogen. In past, scientists have mostly screened tomato sterilized water at concentration of 2000 spores/mL with germplasm against fusarium wilt of tomato by using a single the help of haemocytometer. Fifty mL of this spore pathogen strain of Fol. The objectives of this investigation suspension was used for pathogen inoculum. Plastic pots (4 were to determine pathogenicity extent and genetic inch diameter) each containing 0.5 Kg sterilized sandy polymorphism among different isolates of Fol isolated from loamy soil was used for pathogenicity test. Each pot was different tomato growing areas of Punjab for identification planted with three surface sterilized seeds. Upon emergence of resistant tomato variety and most virulent strain of Fol of seedlings, pot was thinned to one healthy seedling. Pots that could be helpful in breeding or Fol management were watered to field capacity and left for incubation in programs. green house. Each variety was subjected to all ten Fol isolates separately, leaving behind 230 host pathogen Materials and Methods combinations. Three replicates were mad for each treatment.

Fol Isolation and Identification Scoring of Wilting and Disease Intensities

Response of tomato germplasm against Fusarium wilt was F. oxysporum f. sp. lycopersici (Fol) isolates were isolated determined by first scoring of wilting symptoms and then by from roots of infected tomato plants collected from tomato determining disease index based on this scoring. Scoring of fields of Punjab province, Pakistan. Infected plants roots wilting symptoms in tested tomato entries due to Fol were surface sterilized (5% sodium hypochlorite solution) infection (score 0-3) was conducted by using following for 2 min, re-washed several time in sterilized distilled criteria developed by Epp (1987) and is provided in Table 1. water, dried between sterilized filter papers. Small portions Disease Index (DI) was calculated using the following of infected tissues were cut, and plated onto fusarium o equation: specific media “PCNB Agar” and incubated at 25 C for 3-5 days. The resultant fungus was isolated and purified using DI = [(ni x si)/(N x S)] x 100% the hyphal tip and/or the single spore methods (Hawker, Where, ni: number of tomato plants with wilt 1950). Ten Fol isolates were initially identified according to symptoms, si: value of the score of symptoms, N: total their morphological and microscopic characters as described number of tested tomato plants, and S: the highest value of by Jens et al. (1991) Barnett and Hunter (2003) and Leslie score of symptoms (Cachinero et al., 2002). et al. (2006). Fig. 1 represents different steps of pathogen Overall responses of the tested tomato varieties against isolation and identification. Fusarium wilt was established using the following criteria: if Fol isolates identification was further confirmed by the value of DI is equal to 0%; immune – if 1-20%; molecular methods by using Fol strain FCBP119 as resistant, if 21-40%; moderately susceptible, if 41-70%; reference. Fungal Genomic DNA was extracted from susceptible, if 71- 100%; and very susceptible (dan mycelium by using methodology as proposed by Lodhi et Sudarsono, 2004). Cluster analysis of tomato varieties was al. (1994). 2x nTaq PCR reaction mixture provided by performed by considering disease index values against all Enzynomics® Korea was used to carry out PCR reaction. Fol strains by using Single Linkage Euclidean Distance PCR was carried out by Fol specie specific primers method with the help of MYSTAT® program. (EF15´ATGGGTAAGGA(A/G)GACAAGAC-3´) and EF2 5´GGA(G/A)GTACCAGT (G/C)ATCATGTT -3´(Edel et Genetic Fingerprinting of Fol Isolates by ISSR Markers al., 2000). Amplifications were performed in a 25 µL reaction volume. PCR reaction was performed in a 96-well Fungal Genomic DNA was extracted from mycelium by Asco PCR System under the Following cycle program: using methodology as described by Lodhi et al. (1994). initial denaturation step for 4 min at 94oC, denaturation at Quantification of isolated DNA was performed by 94oC for 30s x36, annealing at 60oC for 45s and extension at measuring OD at 260 nm (Sambrook et al., 1989). Ten 72oC for 120 s, Followed by a final extension step at 72oC ISSR primers were used in this study. Here also 2X nTaq for 7 min. Amplified product at ~700bp were visualized on PCR reaction mixture provided by Enzynomics® Korea was 1% agarose gel (Fig. 1e). used. Amplifications were performed in a 25 uL reaction volume. PCR reaction was performed in a 96-well Asco Screening of Tomato Varieties against Fusarium Wilt PCR System equipped with a Hot Bonnet under the Following cycle program: initial denaturation step for 4 This research was carried out under green house of Institute min at 94oC, denaturation at 94oC for 30s x36, annealing of Agricultural Sciences, University of the Punjab Lahore. at 45- 52oC for 45s, and extension at 72oC for 120s, Twenty three tomato varieties, obtained from market and followed by a final extension step at 72oC for 7 min. „Federal Seed Certification and Registration (FSC and RD) Amplified bands from each primer were scored as Pakistan‟ were used in this experiment. For inoculum present (1) or absent (0). Here also dendrogram was preparation, Fol isolates were grown on MEA broth media. constructed by using Single Linkage Euclidean Distance Spore suspensions of these isolates were prepared in dist. method with the help of MYSTAT® program.

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Statistical Analysis of Data

All the data were statistically analyzed by performing Analysis of variance (ANOVA) and DNMRT by „DSSTAT‟ software (Steel et al., 1997).

Results

Screening of Tomato Varieties against Fusarium Wilt

After categorization of varieties based on mean of disease index (MDI), none of the variety was immune or resistant against Fol infection. Three varieties viz: „Pride Burn‟, „Red Power‟ and „Sun Grape‟ were moderately resistant against fusarium wilt disease. Seventeen varieties were susceptible against fusarium wilt with mean disease index of 40-70%. Varieties as „Early Boy‟ and „Fine Star‟ were very susceptible by showing mean disease index <70%. Analysis of Variance demonstrated significant interaction between Fol isolates and tomato varieties. Same Fol isolate was unable to cause uniform level of disease for all tomato varieties. Because a same tomato variety represented different disease index with different Fol isolates. „Red Cloud‟ and „Cosmos 101‟ were having less susceptibility for Fol 2 but more for Fol 3 as represented by disease index values (Table 2). „Red Stone‟ was having disease index level of 84.6 for Fol 3 but for Fol 6, disease index level was 22.5. When „Early Boy‟ was checked Fig. 1: Isolation and identification of Fol isolates. (a) against all Fol isolates, higher disease index values were Infected tomato stem showing vascular browning. (b) observed representing that this entry was prone to mostly Culture purification of Fol isolates. (c) Macrocondia of Fol. Fol isolates. Similarly, most striking differences were (d) Microconidia production by Fol. (e) molecular observed among different Fol isolates for their disease identification of Fol by specie specific primer incidence. Isolate Fol 2, Fol 10 exhibited lowest disease index for „Sun Grape‟ but highest when infecting „Early Boy‟ (Table 2). On the other hand when mean of disease index was taken for single Fol isolates against all tomato varieties, Fol 7 was most virulent strain with 73.87% MDI Followed by Fol 3 with 69.42% MDI (Table 2). We constructed polar dendrogram based on susceptibility level of tomato entries against all Fol isolates by Single Linkage Euclidean Method. Point of maximum dissimilarity divided all tomato varieties into three groups (Fig. 2).

Genetic Fingerprinting of Fol Isolates by ISSR Markers

Seven ISSR primers were able to revel polymorphism among Fol isolates (Table 3). A total of 110 loci were amplified out of which 82 were polymorphic. Primer „841‟ amplified maximum polymorphic alleles (Table 2). All ten Fol isolates were separated in two main groups (Fig. 3). Isolates Fol1, Fol 2, Fol 3, Fol 6, Fol 4, Fol 8 were in one group and rest of the isolates were in second group (Fig. 3). Fig. 2: Dendrogram showing grouping of different tomato varieties based on disease index data Discussion Statistical analysis illustrated a significant interaction Pathogenicity test of the different isolates for the isolated between tomato cultivars and Fusarium isolates. Same Fol fungus was carried out under green-house conditions. isolate was unable to infect all tomato varieties uniformly.

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Table 1: Scoring of wilt symptoms

Wilt score Symptoms 0 No wilt symptom 1 Less than 25% plant parts turned yellow 2 Yellowing and browning covered less than 50% plant parts 3 Infected plant parts turned brown and died, hence covered more than 50% plant parts

Table 2: Susceptibility of tomato varieties against different Fol isolates

Varieties Fol 1 Fol 2 Fol 3 Fol 4 Fol 5 Fol 6 Fol 7 Fol 8 Fol 9 Fol 10 MDI Response California Sun 63.5D-Fde 57.2H-Je 71.6D-Icd 65.4E-Gde 78.3B-Dbc 86.5Aab 91.1ABa 37.3Cf 64.1E-Gde 46.4DEf 66.14** S Cosmos 101 55.7G-Ide 43.8Kf 73.2C-Hbc 79.3A-Dab 89.1Aa 64.2D-Gcd 84.7B-Da 53.2Ae 57.5GHde 38.2EFf 63.89** S Early Boy 71.3Cb 94.5Aa 88.8ABa 70.6DEb 56.2Fc 67.0C-Fb 88.6A-Ca 46.7ABc 84.8Aa 67.9Ab 73.64** VS Ever Green IF 85.4ABab 67.3E-Gc 92.9Aa 44.6He 31.1Hf 49.8I-Kde 53.0J-Ld 26.2EFf 81.7ABb 43.5Dee 57.55** S Fine Star 71.8CDc 72.0D-Fbc 85.7A-Ca 81.6A-Cab 89.5Aa 74.2B-Dbc 81.2C-Eab 42.1BCd 72.8C-Ebc 51.3CDd 72.22** VS Lemon Hunt 91.5Aa 70.7D-Fbc 63.4F-Icd 73.5B-Eb 72.4C-Eb 68.1C-Fbc 56.1I-Kd 00.0He 66.2EFbc 62.0ABcd 62.39** S Nova 84.2ABa 79.1B-Dab 74.1C-Gab 72.6B-Eb 69.0DEb 71.0B-Eb 77.9D-Fab 28.1D-Fd 79.1A-Cab 46.8DEc 68.19** S Pine Red 19.7Je 25.3LMde 33.3Kd 58.5FGb 45.6Gc 59.9F-Ib 72.8FGa 35.4CDcd 56.0GHb 20.3He 42.68** S Pot King 61.3E-Hd 86.7A-Cab 89.6ABa 71.0C-Ecd 74.1C-Ec 48.6I-Ke 93.5Aa 26.4EFf 78.2A-Cbc 63.2ABd 69.26** S Pride Burn 13.6Jd 08.2Nd 21.6Lc 34.2Hb 26.1Hc 51.8I-Ka 45.6La 00.0He 24.4Ic 22.9Hc 24.84** MS Rando 55.8G-Id 61.0G-Icd 85.0A-Ca 65.0E-Gbc 68.9Ebc 53.6H-Jd 74.5E-Gb 17.8Gf 67.5D-Fbc 31.9FGe 58.10** S Red Cloud 63.2D-Fc 48.5JKd 76.7C-Eb 86.6Aa 73.3C-Eb 75.7B-Db 60.8H-Jc 39.3BCd 62.8FGc 26.4GHe 61.33** S Red Power 19.5Jf 27.9Lef 45.3Jc 59.3FGb 79.7BCa 41.5KLc 81.6C-Ea 00.0Hg 30.9Ide 38.2EFcd 39.42** MS Red Stone 47.1Ide 53.8IJcd 84.6A-Ca 39.4Hef 35.6Hf 22.5Mg 59.3IJc 23.6FGg 71.8C-Eb 41.5Eef 47.92** S Red Tara 83.5Bab 77.9B-Db 81.4A-Cb 82.7ABb 87.0Aab 56.3G-Ic 94.8Aa 37.4Cd 83.6ABab 63.7ABc 74.83** S Rio Grand 53.2Hic 28.7Le 81.3A-Da 59.7FGc 73.8C-Eab 41.6KLd 63.8HIbc 24.9FGe 54.4Hc 18.2HIe 49.96** S Roma 505 61.9E-Gc 68.1E-Gc 78.5B-Db 84.2Aab 91.7Aa 82.9ABab 87.1A-Ca 38.4BCd 69.5D-Fc 39.1EFd 70.14** S Sahil 66.4C-Ecd 87.3ABa 63.7F-Id 88.2Aa 83.1ABab 76.0A-Cbc 93.4Aa 52.6Ae 72.4C-Eb-d 43.9DEe 72.75** VS Slumac 81.5Ba 69.2E-Gb 74.2C-Gab 79.1A-Dab 75.8B-Eab 78.9ABab 81.7C-Ea 19.8FGc 75.9B-Dab 22.8Hc 65.89** S Sun Grape 15.9Jfg 18.6MNef 23.6Le 69.6D-Fb 58.6EFc 63.1E-Hbc 77.0D-Fa 33.3C-Ed 29.2Id 09.0Ig 39.79** MS Terminator 71.6Cab 80.3B-Da 62.1Ibc 51.4Gcd 54.8Fc 43.4J-Lde 68.1GHb 41.9BCde 70.3C-Eab 37.0EFe 58.09** S Tin Time 83.5Ba 65.0F-Hbc 79.8B-Da 62.7E-Gc 74.8B-Eab 49.9I-Kd 63.5HIc 28.6D-Fe 66.1EFbc 43.1DEd 61.70** S Wall Ground 48.7Ibc 53.2IJb 66.4E-Ia 37.9Hcd 26.9Hd 34.8Ld 49.1Lb 37.9Ccd 54.1Hab 55.9BCab 46.49** S MDI 59.55** 58.44** 69.42** 65.96** 65.88** 59.18** 73.87** 30.03** 64.05** 40.57** Capital letters shows level of significance in interaction of single Fol isolate against all tomato varieties as governed by DNMRT at p=0.05. Small letters shows level of significance in interaction of single tomato variety against all Fol isolates as governed by DNMRT at p=0.05. MDI= Mean Disease Index. (**)= significant difference among values at p=0.01 as governed by ANOVA. (MS)= Moderately Susceptible. (S)= Susceptible. (VS)= Very Susceptible

Table 3: Details of ISSR Primers used for genetic fingerprinting of Fol isolates

Primer Sequence (5‟-3‟) Ann. Tepm. Total no of bands Polymorphic bands %age polymorphism 810 GAGAGAGAGAGAGAGAT 50 17 11 64.70 823 TCTCTCTCTCTCTCTCC 50 23 14 60.86 826 ACACACACACACACACC 51 15 09 60.00 841 GAGAGAGAGAGAGAGAYC 52 16 14 87.50 845 CTCTCTCTCTCTCTCTAGG 52 11 07 63.63 855 ACACACACACACACACYT 50 18 13 72.22 856 ACACACACACACACACCTA 52 10 04 60.00 Total 110 82 74.54

Similarly same tomato variety displayed different levels of millet varieties. In another investigation, Casela and Ferreira susceptibility against different isolates. This suggests that (1995) observed different virulence levels of Colletotrichum presence of multi–allelic or multi–genic responses towards graminicola against sorghum. resistance mechanisms of tomato varieties against Fusarium Variable patterns of disease causing ability of Fol wilt disease (Saxena and Cramer, 2009). Tomato varieties isolates of different tomato varieties cannot be easily and Fol isolates interaction could produce different levels understood by analyzing the mean values of disease index, and patterns of defense related biochemical compounds because of the nature of interactions between tomato which eventually may cause variation in disease severity germplasm and Fol. isolates. A complete understanding (Özer et al., 2003). of this variable disease patterns between different Pattern of disease occurrence of different isolates of a tomato germplasm is necessary for extracting useful pathogen for different varieties of a same crop is highly information regarding resistance mechanisms. The most variable phenomenon (Sivaramakrishnan et al., 2003). striking difference in resistance mechanism was observed Thakur and Rao (1997) found variation in virulence among between „Cosmos 101‟ „Rando‟ and „Red Stone‟ (Table 1). different isolates of Sclerospora graminicola against pearl These were resistant to one isolate of Fol but susceptible to

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Puccinia striiformis because of polymorphism in their genetic material. However, difference in virulence of Fol isolates along with differences in their genetic makeup provides bases for future studies. In conclusion, the use of single pathogen isolate for screening of resistant source against a plant disease is not sufficient. Pathogen virulence analysis based on disease development using different varieties of host is more useful as compared to molecular analysis alone. Screening of different tomato varieties by multiple isolates of pathogen will provide useful information for development of resistance source by breeding program. A combination of current approach along with molecular investigations is needed to describe tomato and Fol relation dynamics.

References

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176 International Research Journal of Agricultural Science and Soil Science (ISSN: 2251-0044) Vol. 1(8) pp. 286-292, October 2011 Available online http://www.interesjournals.org/IRJAS Copyright ©2011 International Research Journals

Review

Use of bioagents and synthetic chemicals for induction of systemic resistance in tomato against diseases

Waheed Akram * and Tehmina Anjum

Institute of Agriculture Sciences, University of the Punjab, Pakistan

Accepted 05 October, 2011

Plants and pathogens have developed an intricate relationship based on mutual information. Pathogens develop various strategies to attack successfully plants and in return, plants develop strategies to protect themselves from pathogens. Over the last two decades, a number of approaches have been applied by pathologists to enhance disease resistance in plants. Among these, induction of systemic resistance as an integrated control strategy offers exciting opportunities. Induced resistance (IR) could be developed by two main mechanisms: Systemic acquired resistance (SAR) and induced systemic resistance (ISR). Systemic acquired resistance (SAR) is a phenomenon by which a plant activates its own defense under the influence of a bio-agent or a chemical. This resistance develops with changes in the biochemistry and physiology of the cell that is further accompanied by structural modifications in the plants that act as physical barriers to restrict pathogen penetration. It is effective under field conditions and is a natural mechanism for bio-control of plant diseases. Scientists have used several agents to induce systemic resistance in tomato including bacteria, fungi and chemicals. Major areas discussed in this paper are historical background, mechanism of IR and its induction in tomato by various bio-agents and chemicals.

Keywords: Induced systemic resistance ISR, systemic acquired resistance SAR, bacteria, fungi, tomato.

INTRODUCTION

Concept of induced resistance (IR) was recognized under the influence of a bio-agent, physical injury or a nearly 100 years ago by researchers and since then, it chemical. This resistance develops with changes in has been studied for its effectiveness to protect plants biochemistry and the physiology of cell that is further from fungi, bacterial and viral pathogens. In the past accompanied by structural modifications in the plants that decade, discovery of biocontrol agents and knowledge act as physical barriers to restrict pathogen penetration. regarding plant defense mechanism led to the ISR is known to have originated from colonization of roots understanding of the fact that inducing resistance in plant by certain non-pathogenic bacteria. SAR can be induced against diseases is the best prospect for management of by bio-agent such as challenging plant with a weak strain plant diseases. Transcription of defense related genes of a specific pathogen or by using a chemical agent can be stimulated by external signals. Plants can defend (Eliston et al., 1977). Bio-agents can induce resistance themselves from pathogens by variety of mechanism that against diseases caused by fungi (Howell and Stipanovic, can be either constituted or inducible (Franceschi et al., 1979), bacteria (Park and Kloepper, 2000) and viruses 1998: 2000). Inducible resistance can be developed by (Maurhofer et al., 1994). Chemicals used for ISR may be two mechanisms such as systemic acquired resistance synthetically or naturally produced either by (SAR) and induced systemic resistance (ISR); both have microorganisms or host plants (Dixon et al., 1995). broad spectrum of action on pathogen. SAR is a Tomato is an economically important crop cultivated in phenomenon by which a plant activates its own defense all parts of the world. This is used as a fruit, a vegetable and in medicinal industry. In the fields, tomatoes are vulnerable to numerous diseases caused by fungi, bacteria and viruses, leading to dramatic losses in the *Corresponding Author. E-mail: [email protected]. production. Farmers tend to use huge amounts of che- Akram and Anjum 287

micals to get rid of plants diseases. Tolerances to cause the host plants to initiate defense response to pesticides increase the use of several hazardous restrict growth and invasion of pathogen. But this agrochemicals that can destroy both human and animal response is very slow and weak enough to prevent this life. Therefore, great efforts to develop new effective and pathogen colonization inside the host plant (Thordal- environmentally safe approaches for management of Christene 2003). These resistance reactions can be plant diseases are needed. The objectives of this review triggered before pathogens’ attack to restrict their are to discus ISR history, its general mechanisms and the colonization of certain cells or by blocking their involvement of bio-agents and chemicals for the induction penetrating site (Kuc, 1982). If infection ceases along of systemic resistance in tomato. with the restriction of pathogen damage, this phenomenon is called induced systemic resistance ISR. ISR initiates a wide range of resistance phenomenon Historical background elicited by nonpathogenic organisms (Van Loon, 2000). This induced resistance is generally systemic, as it ISR was first studied by Ray (1901) and Beauvene protects not only infection focus but also other parts of (1901). They worked on gray mold caused by Botrytis the plant (Ross, 1961). These distant sites are protected cinerea . At that time Beauvene (1899) had already because of the pathogen related gene expressions and discovered that ISR could be induced in Begonia sp. stimulation of other defense related mechanisms (Durrant which was under the influence of pathogen B. cinerea . and Dong, 2004). Non-pathogenic fungi induce systemic The virulence was altered by cold shock. There are many resistance in plants by stimulating production of ways of challenging the plants with the inoculum of bio- pathogenesis related proteins. This mechanism closely agent being used to induce systemic resistance. Soil resembles systemic resistance induced by pathogenic inoculation, root priming, foliar spray and injection fungi (Lambais and Mehdy, 1995; Cordier et al., 1998). methods have been used by various authors in their Fungi seem to activate defense response by producing experiments of ISR. In 1961, Ross carried out the first auxins or auxins precursors. Auxin regulated IR pathway investigation under laboratory conditions on the induced may be responsible for ISR in plants (Madi and Katan systemic resistance in a single leaf of tobacco with 1998). tobacco mosaic virus. He observed a reduction in the In case of chemicals agents, salicylic acid has been disease severity in the rest of the plant leaves. After that, used by several researchers to induce systemic another experiment on ISR was carried out on tobacco resistance. It is believed that salicylic acid is involved in under field conditions, where a suspension of signaling transduction pathway that leads to the Peronospora tabacina spores was injected in the stem of production of defense related proteins (Vimal et al., 2009; tobacco plants to control mold caused by the same virus Shah, 2003; Metraux, 2001). (Cohen and Kuc, 1981). Since then, Scientists from The way in which bacteria induce systemic resistance different parts of the world have also carried out their is not associated with salicylic acid production (Pieterse studies on various types of plants to investigate et al., 1991). Jasmonate and ethylene are involved in phenomenon of ISR (Hunt and Ryals, 1996; Schneider et bacterial mediated ISR (Van Loon et al., 1998). Both ISR al., 1997). Rhizospheric bacteria were initially applied to and SAR transductions are dependent on regulatory improve growth of the plants but later they were used as proteins NPR1 (Pieterse et al., 1996). Pathogen related bio-control agents for suppression of plant diseases genes are not expressed in ISR (Van Loon et al., 1998). (Dunleavy, 1955; Broadbent et al., 1971; Schippers et al., Increase of resistance to diseases in plants is usually 1987; Kloepper, 1993). First, bio-control product was associated with phenylpropanoid and oxylipin pathway. introduced by Gustafsons Inc. (Plano, Texas); bio-control Volatile organic compounds may play a significant role in agent used was Bacillus subtilus A-10 (Broadbent et al., enhancing protection in plants against diseases (Ping 1977). and Boland, 2004; Ryu et al., 2004). This was confirmed A wide range of chemical compounds such as by studying ISR mediated by volatile compounds oligosaccharides (Yokoshiwa et al., 1993), glycoprotein secreted by B. subtilis GBO3 and B. amyloquefaciens and peptides (Benhamou, 1992) and salicyclic acid IN937a (Ryan et al., 2001). (Yalpani et al., 1991) has been used to demonstrate their ISR protects plants from pathogens by inducing cell effects for induction of systemic resistance in different wall thickening and other changes in host physiology, plants. The first chemical agent used to induce the such as enhancing the production of defense related production of phenolics compounds in tomato plants was compounds like phenolics and proteins (Nowak and arachidonic acid (Bloch et al., 1984). Shulaev. 2003; Ramamoorthy et al., 2001; Duijff et al., 1997). In most cases, where bacteria are used to induce Mechanisms systemic resistance in plants, there will be cell wall thickening due to the deposition of callos and increase in Plant pathogenic agents, such as fungi and bacteria total phenolics contents at the site where pathogen 288 Int. Res. J. Agric. Sci. Soil Sci.

attacks (Benhamous et al., 1996; Benhamous et al.,1998; significant reduction in early blight of tomato when it was MPiga et al., 1997). It can also be due to accumulation of inoculated onto tomato seeds (Silva et al., 2004); a pathogenesis related (PR) proteins such as PR-1 and reduction of up to 18% was observed. Different bacterial PR-2, chitinases, some peroxidases (Jenu et al., 2004; agents used for induction of systemic resistance in Maurhofer et al., 1994; MPiga et al., 1997; Park et al., tomato are summarized in Table 1. 2000; Ramamoorthy et al., 20001; Viswanathan et al., 1999), increase in the quantities of peroxidase, phenylalanine ammonia lyase, phytoalexins, polyphenol Fungi oxidase, and/or chalcone synthase in plant cells (Chen et al., 2004; Ownley et al., 2003; Ramamoorthy et al., 2001; Numerous fungi have also been checked for their efficacy Van Peer et al., 1991) and the productions of antibiotics in induction of systemic resistance in tomato. A research like phID (Austin and Noel, 2003; Bangera and work was carried by Saksirirat et al. (2005) to investigate Thomashow, 1999).Recently, it is discovered that N-Acyl effects of species of Trichoderma in induction of systemic homoserine lactones are also involved in ISR mediated resistance in tomato against Fusarium wilt disease. A by bacteria which stimulate chalcone synthase in plants significant reduction in symptoms was observed under (Mathesi et al., 2003). field conditions. In another study, Penicillium oxalicum was used to suppress fungal wilting diseases in tomato under greenhouse conditions (Larena et al. (2003). Use of bio-agents for the induction of systemic Increase in pathogen related proteins was observed in resistance treated plants as compared to untreated control. Fungal agents used for induction of systemic resistance in Bacteria tomato are summarized in Table 2.

To check the efficacy of bacterial bioagents for induction of ISR in tomato, scientists had already carried out Use of synthetic chemicals to induce systemic various experiments in laboratory, green houses and resistance under field conditions. For example, they have carried out an experiment on tomato caused by Meloidogyne Synthetic chemicals have also been used as elicitors of incognita. The highest accumulation of chitinase was ISR in tomato plants. Benhamos et al. (1998) carried out observed in tomato cells which reduced nematode an experiment to investigate the potential of chitosan in penetration in root tissues. Sharam et al., (2003) carried induction of systemic resistance in tomato plants. Plants out an in vitro study using Pseudomonas sp. strain GRP3 were treated with chitosan as foliar spray or root coating. against pre and post emergence damping off caused by Growth of Fusarium sp. was restricted to epidermis and Pythium aphanidermatum and Phytophthora nicotianae in outermost cortical cell layer; fungal hyphae were unable tomato and chilli. In other studies, it was also stated that to penetrate the inner most cortical layer. This localized tomato mottle virus was a limiting factor in tomato colonization was associated with the induction of defense production areas in Florida since 1990s Kring et al., barriers in host plants when treated with chitosan. This 1991; McGovern et al., 1995; Simone et al., 1990). In was due to deposition of the callose that enhanced the order to manage mottle virus, Murphy and coworkers level of phenolic compounds when under the influence of (2000) used two strains of PGPR (SE34 and IN937) as chitosan treatment. In addition, salicylic acid (SA) seed dressings under field conditions. A significant represents an interesting new opportunity in controlling reduction in the disease severity and incidence was fungal and bacterial diseases of tomato plants. Salicylic recorded. Another study was done by Sankari et al. acid has been studied by various authors (Table 3) to (2010), who used Pseudomonas flourescens strain Pf induce defense in tomato plants. Table 3 shows different 128 to control root knot nematodes. P. flourescens strain synthetic chemicals used for induction of systemic 89B-27 and S. marcescens strain 90-166 were used as resistance in tomato. seed dressing to protect tomato plants from Cucumber mosaic virus (CMV) (Raupach et al., 1996). Bacillus subtilus strain GB03 induced systemic resistance in CMV CONCLUSION under greenhouse conditions (Murphy et al., 2003). Zehnder et al. (2000) used seed dressing technique to Plant protection provided by induction of systemic induce systemic resistance in tomato plants against CMV resistance is an effective and simple approach of disease under field conditions. management. This approach also reduces the use of Two bacterial strains P. putida 89B-61 and B. subtilis harmful agrochemicals. Nevertheless, this type of GB03 were incorporated in soilless media against late treatment has several limitations including stability, blight of tomato caused by Phytophthora infestans (Yan duration of induced systemic resistance, efficacy of such et al., 2002). In another study, Bacillus cereus caused formulations under commercial conditions and their sta- Akram and Anjum 289

Table 1. Different bacterial strain used for induction of systemic resistance in tomato

Bacterial strain Disease Reference Bacillus cereus B 101 R Early blight Silva et al. (2004) B. cereu B 212 K B. subtilis GB03 CMV Murphy et al. (2003) B. pumilus strains SE34 B. amyloliquefaciens IN937a B. subtilis IN937b B. subtilis GB03 Late blight Yan et al. (2002) B. cereus Foliar diseases Silva et al. (2004) B. pumilus SE34 Bacterial wilt Enebak and Carey (2000) Pseudomonas aeruginosa 7NSK2 Grey mold Audenaert et al. (2002) P. fluorescens 89B-27 CMV Raupach et al. (1996) P. fluorescens 89B61 Bacterial wilt Ryu et al. (2004) P.putida WCS358 Grey mold Meziane et al. (2005) P. aeruginosa 7NSK2 Grey mold Audenaert et al. (2002) P. fluorescens 63-28 Fusarium wilt MPiga et al. (1997) P. fluorescens Pf1 Fungal and bacterial wilt Ramamoorthy et al. (2002) P. fluorescens WCS417r Fusarium wilt Duijff et al. (1998) P. putida BTP1 Grey mold Mariutto et al. (2011) PGPR Cucumber mosaic virus Murphy et al. (2003) Zehnder et al. (2000) PGPR Late blight Yan et al. (2002) PGPR strain SE34 Tomato mottle virus Murphy et al. (2000) PGPR strain IN937 Pseudomonas sp. GRP3 Pre and post emergence damping off Sharma et al. (2003) Serratia marcescens 90-166 CMV Raupach et al. (1996) S. marcescens 90-166 Bacterial wilt Ryu et al. (2004)

Table 2. Different fungal strain used for induction of systemic resistance in tomato

Fungus Disease Reference Actinomycete A 068 R Early blight Silva et al. (2004) Bacterial spots Fusarium oxysporum f.sp. Fungal and bacterial wilts Ramamoorthy et al. (2002) lycopersici Penicillium oxalicum Fungal Wilt diseases Larena et al. (2003) Phytophthora cryptogea Fusarium wilt Attitalla et al. (2001) T. harzianum Verticilium wilt Khiareddine et al. (2009) T.viride T.virens T. asperellum Fusarium wilt Cotxarrera et al. (2002) T. harizanum T39 Grey mold De Meyer et al. (1998) T.harzianum Fusarium wilt Amel et al. (2010) Trichoderma spp. Fusarium wilt Hibar et al. (2007)

bility under field conditions. In spite of these limitations, and development is restricted by structural and the advance in knowledge of the ISR phenomenon biochemical barriers in plant tissues under the influence proves the great potential of its use in the near future. of systemic resistance inducers. This approach can play Actually, experiments have proven that pathogen growth a key role in the management of large number of plant 290 Int. Res. J. Agric. Sci. Soil Sci.

Table 3. Different synthetic chemicals used for the induction of a systemic resistance in tomato.

Chemical Disease Reference Acibenzolar-S-methyl Bacterial wilt Anith et al. (2004) Benzothiadiazole Fusarium wilt Benhamous and B´elanger (1998) Chitosan Crown and root rot Benhamous (1992) Chitosan Fusarium wilt Benhamous et al. (1998) Harpin, Phosphorus acid Late blight Necip et al. (2003) Phosphate Late blight F¨orster et al. (1998) Validamycin Fusarium wilt Teraoka et al. (2005) Validoxylamine Fusarium wilt Teraoka et al. (2005)

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