agriculturally beneficial endophytic bacteria of wild plants

Agriculturally beneficial endophytic bacteria of

wild plants

By

Imran Afzal

Department of Biotechnology

Faculty of Biological Sciences

Quaid-i-Azam University

Islamabad

2017

Agriculturally beneficial endophytic bacteria of

wild plants

A thesis submitted in the partial fulfillment of requirements for the degree of

Doctor of Philosophy

In

Plant Biotechnology

By

Imran Afzal

Department of Biotechnology

Faculty of Biological Sciences

Quaid-i-Azam University

Islamabad

2017

DEDICATED TO MY LOVING

PARENTS, Wife and kids

For their support &

prayers

Contents

Acknowledgement i

Index of Figures iii

Index of Tables v

List of Abbreviations vi

Summary vii

Chapter 1 Introduction and Literature Review 1-27

1.1 Introduction 1

1.2 Types of endophytic bacteria 3

1.3 Colonization of plants by endophytic bacteria 4

1.3.1 Rhizosphere colonization by the endophytic bacteria 4

1.3.2 Root colonization by the endophytic bacteria 5

1.3.3 Systemic colonization of aerial plant tissues by the endophytic

bacteria 7

1.4 Diversity of endophytic bacteria 7

1.4.1 Factors affecting endophytic bacterial diversity of a plant 7

1.4.2 Methods for studying endophytic diversity bacteria 9

1.4.3 Endophytic bacteria diversity of different Plants 12

1.5 Mechanisms of Host Plant growth promotion 12

1.5.1 Nutrient acquisition 16

1.5.1.1 Nitrogen availability 16

1.5.1.2 Phosphorus availability 17

1.5.1.3 Iron availability 17

1.5.2 Phytohormone production and modulation 18

1.5.2.1 Moderating plant Indole Acetic Acid levels 18

1.5.2.2 Control of ethylene levels 20

1.5.2.3 Production of Plant Cytokinins and Gibberellins 20

1.5.3 Indirect growth promotion by suppression of phytopathogens 21

1.6 Bacterial genes expressed in the endosphere 23

1.7 Host specificity of growth promoting endophytic bacteria 24

Aims and Objectives 27

Chapter 2 Selective isolation and characterization of agriculturally

beneficial endophytic bacteria from Wild Hemp using Canola 28-62

Abstract 28

2.1 Introduction 29

2.2 Materials and Methods 30

2.2.1 Collection of plant samples 30

2.2.2 Isolation of Endophytic Bacteria 31

2.2.3 Enumeration of endophytic bacteria 32

2.2.4 Selection and storage of pure strains 32

2.2.5 Bacterial preservation in glycerol stock 32

2.2.6 In-vivo plant growth promotion assay 32

2.2.6.1 Seed collection 33

2.2.6.2 Canola gnotobiotic root elongation assay 33

2.2.7 Confirmation of endophytic growth 33

2.2.8 Salt stress tolerance 34

2.2.9 In-vitro plant growth promotion assays 34

2.2.9.1 Indole acetic acid production 34

2.2.9.2 Phosphate solubilization 35

2.2.9.3 Siderophore production 36

2.2.10 Plant cell-wall degrading enzymes 36

2.2.10.1 Cellulase activity 36

2.2.10.2 Pectinase activity 37

2.2.11 Fungal cell-wall degrading enzymes 37

2.2.11.1 Protease activity 37

2.2.11.2 Chitinase activity 38

2.2.12 Antifungal Activity 38

2.2.13 Molecular identification of endophytic bacterial 38

2.2.13.1 Bacterial genomic DNA extraction 39

2.2.13.2 PCR amplification of 16S rRNA gene 39

2.2.13.3 Confirmation of PCR product using Agarose Gel electrophoresis 39

2.2.13.4 PCR product purification 40

2.2.13.5 16S rRNA gene sequencing 40

2.2.13.6 16S rRNA gene sequences analysis 41

2.2.14 Phylogenetic analysis of endophytic bacteria 41

2.3 Results 41

2.3.1 Isolation of endophytic bacteria 41

2.3.2 Identification of endophytic bacteria 42

2.3.3 Phylogenetic Analysis 45


2.3.5 Nutrient availability 48

2.3.6 Fungal cell-wall degrading enzyme 50

2.3.7 Antifungal Assay 52

2.3.8 Production of IAA 52


2.3.9.1 Canola gnotobiotic root elongation 54

2.3.9.2 Confirmation of endophytic presence 55

2.3.9.3 Canola gnotobiotic root elongation under salt stress 58

2.3.10 Growth under salt stress 58

2.4 Discussion 59

Chapter 3 Plant growth-promoting potential of endophytic bacteria

isolated from roots of wild Dodonaea viscosa L. 63-86

Abstract 63

3.1 Introduction 64


3.2.1 Collection of plant samples 65


3.2.3 Enumeration of endophytic bacteria 66

3.2.4 Selection and maintenance of pure strains 66

3.2.5 Bacterial preservation in glycerol stock 66


3.2.6.1 Seed Collection 67

3.2.6.2 Gnotobiotic Canola root elongation assay 67

3.2.7 In-vitro plant growth promotion assays 68

3.2.7.1 Indole acetic acid production 68

3.2.7.2 Phosphate solubilization 68

3.2.7.3 Siderophore production 68


3.2.8.1 Cellulase activity 69

3.2.8.2 Pectinase activity 69

3.2.9 Fungal cell-wall degrading enzymes 70

3.2.9.1 Protease activity 70

3.2.9.2 Chitinase activity 70

3.2.10 Antagonistic activities against pathogenic fungi 70

3.2.11 Molecular identification of endophytic bacterial 71

3.2.11.1 Bacterial genomic DNA extraction 71

3.2.11.2 PCR amplification of 16S rRNA gene 71

3.2.11.3 PCR product purification 72

3.2.11.4 16S rRNA gene sequencing and analysis 72

3.2.11.5 Phylogenetic analysis of endophytic bacteria 72

3.3 Results 73


3.3.2 Identification of endophytic bacteria 73

3.3.3 Phylogenetic Analysis 76

3.3.4 Production of IAA 77

3.3.5 Nutrient availability 77

3.3.6 Production of plant cell-wall degrading enzymes 79

3.3.7 Production of Fungal cell-wall targeting enzyme 80

3.3.8 Antifungal Assay 81

3.3.9 Canola gnotobiotic root elongation assay 82

3.4 Discussion 84

Chapter 4 Comparative in-planta transcriptome profiling of selected

Burkholderia phytofirmans PsJN genes using qPCR 87-110

Abstract 87

4.1 Introduction 88


4.2.1 Performance of experimental work 89

4.2.2 Propagation of Bacteria 89

4.2.3 Plant bacterization using Vacuum Infiltration 90

4.2.4 Bacterial estimates in the inoculated plants 90

4.2.5 Bacterial Recovery for RNA extraction 91

4.2.6 RNA extraction from bacterial pellets 92

4.2.7 cDNA synthesis from extracted RNA 94

4.2.8 qPCR Primer designing 94

4.2.9 Standard PCR for cDNA analysis 95

4.2.10 qPCR for in planta differential gene expression 96

4.3 Results 97

4.3.1 Bacterial estimates in the inoculated plants 97

4.3.2 RNA extraction from bacterial pellets 99

4.3.3 Standard PCR for cDNA analysis 101

4.3.4 qPCR for in-planta differential gene expression 102

4.4 Discussion 105

Conclusions 111

References 113

Appendix A 140

Appendix B 149

Publications 162

i

Acknowledgements

All the praises for the almighty ALLAH the most omnipotent, the most merciful, who

bestowed us with the ability and potential to seek knowledge of his creatures, and his Prophet

Muhammad (S.A.W.W), who is forever a source of guidance and knowledge for humanity

as a whole. I also pay my gratitude to the Almighty for enabling me to complete this research

work within due course of time.

The successful completion of this journey is due to the combined efforts of many people.

PhD is a long and complicated journey. During this journey, I was helped by many and I

would like to show my gratitude to all of them. This work could not have been finished

without their help.

Primarily, I am extremely grateful to my supervisor, Dr. Zabta Khan Shinwari, Professor,

Department of Biotechnology, Biological Sciences, Quaid-i-Azam University, Islamabad, for

his dynamic and valuable supervision. It is his confidence, imbibing attitude, splendid

discussions and endless endeavors through which I have gained significant experience.

Without his much needed support that he extended every step of the way, this endeavor

would never have been possible. I will remain deeply indebted to him for the rest of my life.

My special thanks are due to, Dr. Muhammad Naeem, Chairman Department of

Biotechnology, Quaid-i-Azam University, Islamabad, and Dr. Bilal Haider Abbasi,

Associate professor, Department of Biotechnology, Quaid-i-Azam University, Islamabad, for

their valuable guidance throughout my PhD period.

I must acknowledge my debt to Prof. Steven E. Lindow, Department of Plant and Microbial

Biology, University of California, Berkeley, USA, for providing me an opportunity to carry

out a part of my research project at his facility. His constructive comments, guidance and

great co-operation played a fundamental role in carrying out this epic work. This project was

supported by Higher Education Commission of Pakistan (HEC), and I acknowledge this

institution for providing me Indigenous and Overseas IRSIP Scholarship for my research in

Pakistan and USA.

I am also thankful to my colleagues and my lab fellows, especially Irum Iqrar, Khansa Jamil

and Nadia Batool, for helping me during my difficult times. I must mention my dear friend,

ii

Sohail Irshad, for encouraging and helping me in every step of the way, and enabling me to

achieve the nearly impossible.

Lastly, this work would never have been possible without the support of my parents and my

wife, who never gave up in believing in me, and empowering me during my difficult times.

Imran Afzal

iii

List of Figures

Figure 1.1 Plant root section showing three types of endophytic bacteria 3

Figure 1.2

Mechanisms used by endophytic bacteria for plant colonization and

growth promotion (Pink, establishment in host; blue, plant growth

promotion; black, rhizosphere competence and attachment). Processes

labeled with star are experimentally (mostly mutational) verified while

others are suspected, inferred from literature or genome comparisons.

22

Figure 2.1 Standard curve of Indole Acetic Acid 35

Figure 2.2 Plate showing growth of isolated endophytic bacteria 42

Figure 2.3

Agarose gel electrophoresis of PCR amplified 16S rRNA gene of

bacterial isolates. First lane, 1 kb DNA ladder; second lane, negative

control; third lane, positive control; lanes 1, 2, 3, 4, 5, 6, 7 and 8 PCR

amplified DNA of ~1465bp size.

43

Figure 2.4 Electropherogram of 16S rRNA gene from bacterial isolate MOSEL-

w2. 43

Figure 2.5 Percentage of endophytic bacterial genera obtained from C. sativa using

direct isolation method 44

Figure 2.6 Percentage of endophytic bacterial genera obtained from C. sativa using

selective isolation 44

Figure 2.7

Phylogenetic tree of endophytic bacteria from C. sativa (direct and

selective isolation) constructed with 16S rRNA gene sequences using

the Neighbour-Joining method. Branch points show bootstrap

percentages (500 replicates). Bar 0.02 indicates changes per nucleotide

position. Cluster enclosed in red box contains isolates significantly

promoting canola growth.

47

Figure 2.8 Pectinase (left) and Cellulase (right) activity of four bacterial isolates on

Pectin and Cellulose (CMC) containing medium. 48

Figure 2.9

Cellulase (blue bars) and Pectinase (orange bars) assay of endophytic

bacteria isolated from C. sativa using direct isolation. Values of zones

of hydrolysis produced by bacteria have been organized into three

categories based on the size: 3, large (>1.0 cm); 2, medium (0.5-1 cm);

1, small (<0.5 cm).

49

Figure 2.10

Cellulase (blue bars) and pectinase (orange bars) assay of endophytic

bacteria isolated from C. sativa using selective isolation. Values of

zones of hydrolysis produced by bacteria have been organized into three

categories: 3, large (>1.0 cm); 2, medium (0.5-1 cm); 1, small (<0.5

cm).

49

Figure 2.11 Mineral phosphate solubilization activities of four bacterial isolates on

insoluble mineral phosphate containing medium. 50

Figure 2.12

Mineral phosphate solubilization activity of bacteria isolated from C.

sativa using direct isolation. Values of zones of hydrolysis produced by

bacteria have been organized into three categories: 3, large (>1.0 cm); 2,

medium (0.5-1 cm); 1, small (<0.5 cm).

50

Figure 2.13

Mineral phosphate solubilization activity of bacteria isolated from C.

sativa using selective isolation. Values of zones of hydrolysis produced

by bacteria have been organized into three categories: 3, large (>1.0

cm); 2, medium (0.5-1 cm); 1, small (<0.5 cm).

51

Figure 2.14 Protease activity of bacteria isolated from C. sativa using selective

isolation. Values of zones of hydrolysis produced by bacteria have been 51

iv

organized into three categories: 3, large (>1.0 cm); 2, medium (0.5-1

cm); 1, small (<0.5 cm).

Figure 2.15 Dual culture antifungal assay of five selected endophytic bacteria

against Aspergillus niger (left) and Fusarium oxysporum (right) 52

Figure 2.16

IAA production by bacteria isolated from C. sativa using direct isolation

(Blue bars, without tryptophan; Orange bars, with tryptophan). Values

represent mean of three replicates.

55

Figure 2.17

IAA production by bacteria isolated from C. sativa using selective

isolation (Blue bars, without tryptophan; Orange bars, with tryptophan).

Values represent mean of three replicates.

56

Figure 2.18 Root elongation of canola by three selected growth promoting bacteria

under gnotobiotic conditions. Scale indicates values in centimeters. 56

Figure 2.19

Canola gnotobiotic root elongation assay of endophytic bacteria isolated

from C. sativa roots using direct isolation. Each bar represents mean

root length (± SE, n=12) of five day old plantlets treated with sterile

0.03M MgSO4 (Control) or bacterial suspension in 0.03M MgSO4

(0.1±0.02 OD at 600nm). Green bars represent isolates significantly

increasing root length and red bars significantly decreasing root length

compared to control (Least significant difference, p ≤ 0.05).

57

Figure 2.20


from C. sativa rhizosphere by selective isolation using canola. Each bar

represents mean root length (± SE, n=12) of five day old plantlets

treated with sterile 0.03M MgSO4 (Control) or bacterial suspension in

0.03M MgSO4 (0.1 ± 0.02 OD at 600nm). Green bars represent isolates

significantly increasing root length compared to control (Least

significant difference, p ≤ 0.05).

57

Figure 2.21

Root elongation of canola by three selected growth promoting bacteria

under gnotobiotic condition and 125mM NaCl stress. Scale indicates

values in centimeters.

58

Figure 2.22

Canola gnotobiotic root elongation assay of three growth promoting

bacteria in the presence of 125mM NaCl stress. Each bar represents

mean root length (± SE, n=12) of five day old plantlets treated with

sterile 0.03M MgSO4 (Control) or bacterial suspension in 0.03M

MgSO4 (0.1 ± 0.02 OD at 600nm). Green bars belong to isolates

significantly increasing root length under stress compared to control

(Least significant difference, p ≤ 0.05).

59

Figure 3.1 Percentage of endophytic bacterial genera isolated from D. viscosa 74

Figure 3.2

Phylogenetic tree of endophytic bacteria isolated from Dodonaea

viscosa roots constructed with 16S rRNA gene sequences using the

Neighbour-Joining method. Branch points show bootstrap percentages

(500 replicates). Bar 0.02 indicates changes per nucleotide position.

Clusters enclosed in red boxes contain isolates significantly promoting

canola growth.

76

Figure 3.3

IAA production by bacteria isolated from Dodonaea viscosa roots (Blue

bars, without tryptophan; Orange bars, with tryptophan). Values

represent mean of three replicates.

77

Figure 3.4 Tri-calcium phosphate medium plate showing phosphate solubilization

activity of Streptomyces caeruleatus MOSEL-RD17 78

Figure 3.5 Siderophore production by Bacillus cereus MOSEL-RD27 on the test

media. 78

v

Figure 3.6

Cellulase (blue bars) and Pectinase (orange bars) assay of endophytic

bacteria isolated from Dodonaea viscosa roots. Values of zones of

hydrolysis produced by bacteria have been organized into three

categories based on the size: 3, large (>2 cm); 2, medium (1-2 cm); 1,

small (<1 cm).

80

Figure 3.7

Skimmed milk containing media showing Protease activity (left) and

Colloidal chitin media showing Chitinase activity (right) by Bacillus

subtilis MOSEL-RD28

82

Figure 3.8

Anti-Aspergillus niger (left) and Anti-Fusarium oxysporum (right)

activity of selected endophytic bacteria isolated from Dodonaea viscosa

roots.

82

Figure 3.9


from Dodonaea viscosa roots. Each bar represents mean root length (±

SE, n=12) of five day old plantlets treated with sterile 0.03M MgSO4

(Control) or bacterial suspension in 0.03M MgSO4 (0.1±0.02 OD at 600

nm). Green bars represent isolates significantly increasing root length

and red bar significantly decreasing root length compared to control

(Least significant difference, p ≤ 0.05).

83

Figure 4.1

Bacterial counts in leaf tissue at four different day (0, 2, 4, 6) after

inoculation with three different dose of bacterial suspension (104 cfu/ml,

blue; 106 cfu/ml, red; 108 cfu/ml, green), using vacuum infiltration

method.

98

Figure 4.2

Bacterial counts in leaf tissue at four different days (0, 2, 4, 6) after

inoculation with 109 cfu/ml bacterial suspension, using vacuum

infiltration method.

99

Figure 4.3

Bioanalyzer results for in-planta bacterial RNA samples. The peaks for

16S and 23S rRNA are indicated along with a virtual gel of the run

sample.

100

Figure 4.4 Bioanalyzer results for M9 bacterial RNA samples. The peaks for 16S

and 23S rRNA are indicated along with a virtual gel of the run sample. 100

Figure 4.5

Agarose gel electrophoresis of three PCR amplified strain PsJN genes

from in-planta (P1, P2, P3) and M9 (M1, M2, M3) samples using the

first strand cDNA as template. The respective RT controls (PC and

MC), non-bacterized plant sample (C), and 100 bp ladder (L) are also

shown.

101

Figure 4.6

In-planta gene expression profile of 15 Burkholderia phyrofirmans PsJN

genes versus M9 cultured bacteria using Relative Quantification qPCR

(Green bars, upregulated genes; Red bars, downregulated genes; Gray

bars, no change).

104

Figure 4.7 Dissociation curve analysis for ACCD gene (Bphyt_5397) for both M9

and in-planta samples indicating a single product type. 105

vi

List of Tables

Table 1.1 Some common endophytic bacterial genera isolated from agronomic

plants reported in literature 13

Table 1.2 Diversity of endophytic bacterial isolated from some wild plants. 14

Table 1.3 Selected bacterial genes involved in endosphere colonization, host

interaction and promotion of plant growth 25

Table 2.1 Number of bacterial isolates recovered from two isolation procedures

along with average cell counts recovered on three growth media. 42

Table 2.2

Identification of endophytic bacteria resulting from selective isolation

method based on the partial 16S rRNA gene sequence. GenBank match

similarity was ≥99% for all isolates while their Eztaxon match similarity

and GenBank accession is given below.

45

Table 2.3

Identification of endophytic bacteria resulting from direct isolation

method based on the partial 16S rRNA gene sequence. GenBank match

similarity was ≥99% for all isolates while their Eztaxon match similarity

and GenBank accession is given below.

46

Table 2.4

Protease production (PRO), Chitinase production (CHI), Siderophore

production (SID), Anti Aspergillus niger (AN), and anti Fusarium

oxysporum (FO) activities of endophytic bacteria isolated from C. sativa

using direct isolation.

53

Table 2.5

Protease production (PRO), Chitinase production (CHI), Siderophore

production (SID), Anti-Aspergillus niger (AN), and anti-Fusarium

oxysporum (FO) activities of endophytic bacteria isolated from C. sativa

using selective isolation.

54

Table 3.1 Number of bacterial isolates recovered from Dodonaea viscosa roots

along with average cell counts recovered on three growth media. 73

Table 3.2

Identification of endophytic bacteria isolated from Dodonaea viscosa

roots. GenBank match similarity was ≥99% for all isolates while their

Eztaxon match similarity and GenBank accession is given below.

75

Table 3.3 Phosphate solubilization and Siderophore production activity of

endophytic bacteria isolated from Dodonaea viscosa roots. 79

Table 3.4

Protease production (PRO), Chitinase production (CHI), Anti-

Aspergillus niger (AN), and Anti-Fusarium oxysporum (FO) activities of

endophytic bacteria isolated from Dodonaea viscosa roots.

81

Table 4.1

Selected (15) strain PsJN genes used for expression analysis, their

function, and their qPCR primer sequences, and expected product size

are given. Two bacterial housekeeping genes used as endogenous control

and bacterial detection in in-planta samples are also provided.

95

vii

List of Abbreviations

(A)RISA (Automated) Ribosomal intergenic spacer analysis

°C Degree celcius

µg/ml Microgram per milliliter

µl Microlitre

ACC 1-aminocyclopropane-1-carboxylate

AN Aspergillus niger

ANOVA Analysis of variance

ARDRA Amplified rDNA Restriction Analysis

BLAST Basic Local Alignment Search Tool

bp Base pair

C2H4 Ethylene

CAS Chrome Azurol S

CEL Cellulase activity

cfu/gfw Colony forming units per gram fresh weight

CHI Chitinase activity

cm Centimeter

CMC Carboxymethyl cellulose

Ct Threshold cycle

DGGE Denaturing Gradient Gel Electrophoresis

DNA Deoxyribonucleic acid

EDTA Ethylenediaminetetraacetic acid

ET Ethylene

F Forward primer

Fe3 Ferric

FISH Fluorescence in situ hybridization

FO Fusarium oxysporum

gfp Green fluorescent protein

gusA beta-glucuronidase gene

h Hours

HDTMA Hexadecyltrimetyl ammonium bromide

IAA Indole acetic acid

ISR Induced systemic resistance

IVET In-vivo expression technology

JA Jasmonic acid

kb kilobase

L Litre

log Logarithm

LPS Lipo-polysaccharides

LSD Least Significant Difference

M Molar

MEGA5 Molecular evolutionary genetics analysis 5

MgSO4 Magnesium sulphate

ml Milliliter

mM Millimolar

MOSEL Molecular systematics and applied ethnobotany laboratory

N2 Nitrogen

viii

NA Nutrient agar

NaCl Sodium chloride

NaOCl Sodium hypochlorite

NARC National Agricultural Research Centre

NCBI National Center for Biotechnology Information Search database

ng Nanogram

nm Nanometer

O2 Oxygen

OD Optical density

PCR Polymerase chain reaction

PDA Potato dextrose agar

PEC Pectinase activity

PGP Plant growth promoting

PGPB Plant growth promoting bacteria

PGPR Plant growth promoting rhizobacteria

pH Potential of hydrogen

PHO Phosphate solubilization

PIPES Piperazine-1,4-bis (2- ethanesulfonic acid)

PRO Protease activity

psi Pascal per square inch

qPCR Quantitative Polymerase chain reaction

QS Quorum sensing

R Reverse primer

rDNA Ribosomal Deoxyribonucleic acid

RIN RNA Integrity Number

RNA Ribonucleic acid

RNA-seq Ribonucleic acid sequencing

ROS Reactive oxygen species

rpm Revolutions per minute

RQ Relative quantification

rRNA Ribosomal ribonucleic acid

S Svedberg

s Seconds

SA Salicylic acid

SE Standard error

TAE Tris acetate EDTA (Ethylenediaminetetraacetic acid)

TGGE Temperature Gradient Gel Electrophoresis

Tm Melting temperature

T-RFLP Terminal Restriction Fragment Length Polymorphism

Tris Tris (hydroxymethyl) aminomethane

TSA Tryptic Soya agar

TSB Tryptic soya broth

V/cm Volts per centimeter

VNC Viable but nonculturable

w/v Weight / Volume

ix

Summary

Endophytic bacteria colonize internal plant tissues and can improve plant growth under

normal and stressed conditions. Most past work has focused on the endophytic bacteria of

agronomic plants. Wild perennial plants remain little investigated for their endophytic

diversity. Unlike crop plants, wild plants are constantly challenged by adverse environmental

conditions. Choosing the right endophytic partner can abet wild plants to survive better under

adversity. Since endophytic bacteria can have broad host range, identifying agriculturally

beneficial endophytic bacteria of wild plants can have great agricultural significance.

Therefore, the present work focused on the isolation and characterization of plant beneficial

endophytic bacteria from wild perennial plants to assess their growth promoting potential on

Canola (Brassica napus). Moreover, in-planta gene expression profiling of a model

endophytic bacterium was also undertaken to identify the bacterial traits important during

endophytic growth.

Endophytic bacteria were isolated from two wild perennial plants, Cannabis sativa L. and

Dodonaea viscosa L. For C. sativa, two different approaches were used to isolates endophytic

bacteria. The first approach involved direct isolation from C. sativa roots while the second

novel approach utilized canola plants to selectively isolate endophytes from C. sativa

rhizosphere. Selective method isolated 18 distinct bacteria while direct method isolated 16

bacteria. The bacteria were identified using 16S rRNA gene sequence. The selective method

yielded 13 unique bacterial genera while the direct method isolated 11 genera. Overall, the

most abundant genera were Acinetobacter, Chryseobacterium, Enterobacter,

Microbacterium, Nocardioides, Paenibacillus Pseudomonas, Stenotrophomonas. Moreover,

six (33.3%) isolates from selective method significantly promoted canola root growth under

gnotobiotic conditions, as compared to two (12.5%) isolates from direct method. The bacteria

that significantly promoted canola growth were found to be phylogenetically related.

Furthermore, C. sativa roots contained 8×107 cfu/gfw bacterial cells.

From the second wild plant used for isolating endophytic bacteria, D. viscosa , the bacteria

were isolated from roots of the healthy plants, which contained 1×107 cfu/gfw bacterial cells.

Bacterial identification based on 16S rRNA gene sequence revealed 11 distinct bacterial

genera, where Bacillus, Xanthomonas and Streptomyces were the most predominant. Many

isolates (67%) significantly promoted canola root growth; Bacillus, Pseudomonas and

Xanthomonas were prominent genera in this regard. These bacteria were also found to be

x

phylogenetically related, strengthening the argument that plant growth promoting ability of

the endophytic bacteria is evolutionary conserved.

Many traits required for plant growth promotion and colonization were detected in the

endophytic isolates from C. sativa and D. viscosa. Most of the bacteria produced plant cell-

wall degrading enzymes (cellulase and pectinase) needed for systemic plant colonization.

Moreover, all isolates produced phytohormone IAA, where majority of the growth promoting

isolates produced IAA in the range 2-10 µg/ml. The isolates also possessed phosphate

solubilization and siderophore production. Moreover, seven isolates of C. sativa and D.

viscosa inhibited the growth of two phytopathogenic fungi Aspergillus niger and Fusarium

oxysporum. Most pronounced antifungal activity was observed for the genera Bacillus,

Paenibacillus, Pseudomonas and Streptomyces. All the fungal antagonists produced fungal

cell-wall targeting enzymes, chitinase and protease.

Burkholderia phytofirmans PsJN is a model endophytic bacterium that can promote growth of

a variety of non-host plants. Expression of 15 selected strain PsJN genes was analyzed and

compared between bacterial growth in-planta and growth on M9 minimal media. For this,

strain PsJN was vacuum infiltrated into tomato plants, and inoculum dose was first optimized

for maximum bacterial extraction from leaf tissues. Out of four inoculum doses tested, the

dose 109 cfu/ml yielded the highest cells counts (108 cfu/gfw on second day) and was used to

inoculate plants for gene expression study. Compared to M9 grown bacteria, total bacterial

RNA extracted from in-planta bacteria was lower in quantity and quality, but RNA was

analyzable using qPCR. Bacterial gene expression was analyzed and compared between in-

planta and M9 bacteria using relative quantification qPCR. Eight genes were upregulated

during in-planta growth: Cellulase and Pectinase (plant colonization), IAA degradation and

ACC deaminase (plant growth promotion), β-xylosidase and β-galactosidase (sugar

metabolism), peroxidase (oxidative stress reduction) and one quorum sensing gene (cell-cell

communication); three genes were downregulated: IAA synthesis (phytohormone), flagella

(movement), and second quorum sensing gene. Expression of Pili (cell attachment),

aerobactin (siderophore), hemagglutinin and Type III secretion system gene (virulence) was

similar between the two growth conditions. Gene expression study revealed that the

bacterium was active in the tomato leaves and expressed traits that are compatible with plant

growth promotion and invasion. The present work concludes that wild perennial plants harbor

unique and agriculturally beneficial endophytic bacteria with multiple plant growth

promoting traits that are expressed during endophytic growth.

Chapter 1

Introduction and Literature Review

Chapter 1 Introduction & Literature Review

Agriculturally beneficial endophytic bacteria of wild plants 1

1.1 Introduction

Plants can develop associations with members of their ecosystem to thrive in their natural

environments. Microorganisms are one of the most important organisms that can develop

beneficial associations with plants (Santoyo et al., 2016). Such plant-beneficial bacteria are a

class of bacteria that provide numerous benefits to their host plants, helping them in

tolerating various biotic and abiotic stresses that can challenge their growth (Miliute et al.,

2015). These bacteria can live both externally or internally in their host plant. Bacteria that

live outside their host plants are either epiphytic, those living on the plant leaf surfaces, or

rhizospheric, those inhabiting plant roots within the soil (Compant et al., 2010). While the

bacteria that live and thrive inside the host plant are called endophytic bacteria (Hardoim et

al., 2008). All these classes of bacteria share numerous characteristics essential for host plant

growth promotion (Compant et al., 2010).

Endophytic bacteria are considered a subclass of rhizospheric bacteria, commonly called as

plant growth promoting rhizobacteria (PGPR). These are in fact a specialized group of

rhizobacteria that have acquired the ability to invade their plant host (Reinhold-Hurek and

Hurek, 2011). They share all the important traits consistent with the host plant growth

promotion found in rhizobacteria. In fact, the beneficial effects provided by endophytic

bacteria to host plants are usually greater than those provided by many rhizospheric bacteria.

However, these effects may exacerbate when the plants are challenged by stress conditions

(Chanway et al., 2000; Hardoim et al., 2008).

In 1926, endophytic growth was described as a particular stage of bacterial growth, where

bacteria infect and develop a close mutualistic relation with plants (Perotti, 1926). Thus,

endophytic bacteria are now described as the bacteria that are isolated from surface sterilized

plant tissues and do not cause any noticeably harm to their host plants (Santoyo et al., 2016).

These bacteria can exists within the plant host, including aboveground and underground plant

parts and even seeds, thereby positively affecting plant development (Chebotar et al., 2015).

The bacteria use the plant endosphere as a unique protective ecological niche that provides a

safe and consistent environment unperturbed by fluctuating environmental conditions

affective rhizospheric and epiphytic bacteria (Senthilkumar et al., 2011). Moreover, most



endophytic bacteria have a biphasic life cycle that alternates between plants and the soil

environment.

Nearly 300,000 plant species that exist on the earth are thought to be a host to one or more

endophytes (Ryan et al., 2008). Theses endophytes can be both fungi and bacteria (Singh et

al., 2011; Reinhold-Hurek and Hurek, 2011). The endophytic bacteria can not only promote

growth of the host plant, but also help the host in tolerating stress conditions, and produce

allelopathic effects against other competing plant species (Rosenblueth and Martínez-

Romero, 2006; Mei and Flinn, 2010; Cipollini et al., 2012). Thus, they enable their host to

have better survival against biotic and abiotic challenges and competition by other plants.

Endophytic bacteria have been isolated and characterized from diverse type of plant hosts.

These include agronomic crops, prairie plants, plants growing in extreme environments, and

wild and perennial plants (Zinniel et al., 2002; Nair and Padmavathy, 2014; Yuan et al.,

2014). Endophytic bacteria have been isolated from different plant parts that are above and

below ground (Senthilkumar et al., 2011). The parts include roots, stems, leaves, seeds,

fruits, tubers, ovules and nodules, where roots have the greatest numbers of bacterial

endophytes as compared to above ground tissues (Rosenblueth and Martínez-Romero, 2006).

Numerous reports exist regarding useful endophytic bacteria in plant growth promotion of

plants like wheat, rice, canola, potato, tomato, and many more (Sturz and Nowak, 2000; Mei

and Flinn, 2010). Most of these studies involve the possible growth promotion potential of

the endophytes isolated from the same plants. However other studies have reported the

growth promotion effect of endophytic bacteria on non-host plants (Sessitsch et al., 2005).

There have been contrasting reports about the host specificity of endophytes. Some

researchers have indicated that the endophytes are only able to promote plant growth in plants

that are very closely related to their natural host (Long et al., 2008). On the other hand, there

have been reports regarding the growth promotion due to endophytes among diverse hosts

(Ma et al., 2011; Sessitsch et al., 2005). Nevertheless, broad host range of endophytes makes

a power tool in agriculture biotechnology. Therefore, endophytes have a great potential to be

used as biofertilizers and biopesticides and in developing a sustainable, safe and effective

agriculture system.



1.2 Types of endophytic bacteria

Hardoim et al. (2008) have categorized the endophytic bacteria based on their endophytic

lifestyle and ability to invade plant hosts. Based on their life strategies, endophytic bacteria

are categorized as ‘obligate endophytes’ or ‘facultative endophytes’ (Figure 1.1). The

obligate endophytes strictly depend on plant host for growth and survival and are transmitted

to a new host plant either vertically or by means of a vector. Facultative endophytes only live

a stage of their life cycle in their host plants and they can also survive in other habitats.

Facultative endophytes are further characterized into three types: competent, opportunistic

and passenger endophytes. Competent endophytes are the bacteria that can effectively

colonize the plant tissues, have the ability to manipulate host physiology, and are favored by

the plant host, leading to a positive plant-microbe association (Hardoim et al., 2012).

Opportunistic endophytes are the bacteria that only occasionally enter the plant host to get

more nutrients, increased protection from predators, and to escape competition (Reinhold-

Hurek and Hurek, 1998). The passenger endophytes are the bacteria that enter plant by

accident and lack features that allow systematic colonization of plant host (Hardoim et al,

2008).

Soil bacteria can become

endophytic by: (1) accidently

entering the host via wounds and

are retained in the root zone

(passenger endophytes, red cells);

(2) active invasion of host to get

benefit from the host where they are

mostly retained in root tissues,

(opportunistic endophytes, blue

cells); (3) using specialized

mechanism to invade host roots,

systematically infect the above-

ground parts of the host, develop a

positive association, and adapt to

the internal environment of the host

plant (competent endophytes,

yellow cells).

Figure 1.1 Plant root section showing three types of endophytic bacteria (Hardoim et al., 2008)



1.3 Colonization of plants by the endophytic bacteria

Endophytic bacteria can be considered a subset of the rhizospheric bacteria (Misko and

Germida, 2002; Marquez-Santacruz et al., 2010). However, compared to rhizobacteria,

endophytic growth has an added advantage over rhizospheric growth. Living within plant

tissues allows endophytic bacteria to be in close contact with the plant host to readily exert a

direct beneficial effect in return for consistent supply of nutrients. In fact, endophytic bacteria

represent a class of specialized rhizobacteria that have acquired the ability to invade plant

roots after establishing a rhizospheric population (Compant et al., 2005).

Endophytic colonization of host by the bacteria is determined by a battery of different

bacterial traits. These traits are collectively referred to as colonization traits and regulate the

entire process of plant colonization. The colonization process involves complex

communication between the two partners. The process usually starts from the roots, and

requires recognition specific compounds in the root exudates by the endophytic bacteria (De

Weert et al., 2002; Rosenblueth and Martínez-Romero, 2006). Plants produce these root

exudates to interact with beneficial bacteria for their own ecological advantage (Compant et

al., 2005a). Moreover, it has been observed that endophytic bacteria colonize plant interior in

a sequence of events similar to rhizosphere colonization by the rhizobacteria (Hallman et al.,

1997). However, endophytic colonization involves a suite of environmental and genetic

factors that allow a bacterium to enter plant endophere (Compant et al., 2010). Although,

endophytic bacteria usually enter the plants through the root zone, the aerial parts of the

plants, including stems, leaves, flowers and cotyledons, may also be used (Zinniel et al.,

2002). Once inside the roots, endophytic bacteria can now systemically infect the adjacent

plant tissues.

1.3.1 Rhizosphere colonization by the endophytic bacteria

The rhizosphere colonization is a highly competitive task for endophytic bacteria to occupy

spaces and get nutrients (Raaijmakers et al., 2002). Only those bacteria, either beneficial or

pathogenic, that can competitively colonize plant rhizosphere will thrive in this environment

and have an effect on plant growth and development (Haas and Keel, 2003). Bacterial traits



like motility and polysaccharide production are important in the colonization of plant

rhizosphere by Alcaligenes faecalis and Azospirillum brasilense (Santoyo et al., 2016)

Bacterial rhizosphere population can range between 107-109 cfu per gram of rhizosphere soil

(Benizri et al., 2001); rhizoplane population ranges from 105 to 107 colony forming units per

gram fresh weight (Benizri et al., 2001; Bais et al., 2006). Bacterial detection systems based

on gfp/gusA labelled strains, immunomarkers, and fluorescence in situ hybridization (FISH)

have revealed that bacterial cells first colonize the rhizosphere after they have been

inoculated into the soil (Gamalero et al., 2003). The bacterial cells then attach to the root

surfaces forming a string of cells (Hansen et al., 1997). The bacteria can then colonize the

entire root surface and some rhizodermal cells, leading to establishment of microcolonies or

biofilms by the bacrteria (Benizri et al., 2001). Rhizoplane colonization has been investigated

in both plants growing in-vitro and plants growing in natural soil (Compant et al., 2010).

To confer beneficial effects on host plant, the bacteria have to competently colonize the plant

rhizosphere and rhizoplane (Compant et al., 2005b). They also have to compete with other

rhizospheric members while colonizing the host plant (Whipps, 2001). Moreover, the bacteria

do not colonize the host plant root system in a uniform manner. For example, Gamalero et al.

(2004) reported that while colonizing tomato plants, distribution and density of Pseudomonas

fluorescens strain A6RI varied according to the root zone. This non-uniform colonization of

plant root by the bacteria is a result of different factors controlling the process of root

colonization. These factors include root exudation patterns, bacterial attachment and motility,

bacterial quorum sensing, bacterial growth rate, and minimizing competition by producing

antagonistic substances and acquiring nutrients efficiently (Compant et al., 2010). Moreover,

to be successful, the bacteria need to metabolically adapt to the range of nutrients available in

the plant roots exudates. This was demonstrated by Matilla et al. (2007) in the gene

expression analysis Pseudomonas putida KT2440 competently colonizing corn rhizosphere,

where bacterial genes involved in metabolism and oxidative stress were upregulated.

1.3.2 Root colonization by the endophytic bacteria

After establishing themselves in the rhizoshere and rhizoplane, bacterial endophytes are

known to make their way inside the plant root and colonize themselves with subpopulations

ranging from 105-107 cfu/gfw (Hallmann, 2001). This involves bacterial adhesion to cell



surface structures, which is mediated by polysaccharides, pili and bacterial adhesins (Hori

and Matsumoto, 2010). Once on the root surface, the bacteria might reach the root entry sites,

like lateral root emergence and wounds, using type IV pili mediated twitching motility.

Importance of this feature was demonstrated in diazotrophic endophyte Azoarcus sp. BH72

colonizing rice roots, where mutant defective in pilus retraction showed decreased root

surface colonization compared to the wild-type bacteria (Böhm et al. 2007). Nevertheless,

every endophytic bacterium has its own distinct colonization pattern and colonization site

preferences (Zachow et al. 2010). Once these bacteria have established themselves on the

roots surfaces, they start to penetrate into the root interior using specialized mechanism.

The process of penetration into the host can be passive or active. Passive penetration can

occur at cracks present at root emergence areas, root tips, or those created by deleterious

organisms (Hardoim et al., 2008). Active penetration by competent endophytic bacteria is

achieved by means of dedicated machinery of attachment and proliferation. This involves

presence of lipopolysaccharides, flagella, pili, twitching motility, and quorum sensing which

can affect endophytic colonization and bacterial movement inside the host plants (Duijff et

al., 1997; Dörr et al., 1998; Böhm et al., 2007; Suarez-Moreno et al., 2010). In addition, the

secretion of cell-wall degrading enzymes, mainly pectinases and cellulases are known to be

involved in bacterial penetration and spreading within the plant (Compant et al., 2005a).

Although not experimentally proven, it has been proposed that endophytic bacteria produce

low levels of cell-wall degrading, as compared to phytopathogens that produce deleteriously

high levels of these enzymes, and can thus avoid triggering plant defense system (Elbeltagy

et al. 2000). Furthermore, another way by which endophytic bacteria avoid being detected as

a pathogen by the plant is maintaining low cell densities (2-6 log cfu/gfw) as compared to

pathogenic bacteria (7-10 log cfu/gfw) (Zinniel et al., 2002). Hence, the endophytic presence

of bacteria is determined by chance factors and bacterial genetic determinants that enable

bacterial-plant crosstalk leading to active endophytic colonization process (Hardoim et al.,

2008). The plant host also plays a critical role in selecting an endophytic partner where

secretion of specific root exudates and a selective plant defense response are considered

important factors in selection of specific endophytes (Rosenblueth and Martínez-Romero,

2006).



1.3.3 Systemic colonization of aerial plant tissues by the endophytic bacteria

After entry into the roots, the endophytic bacteria can spread systemically to colonize above

ground tissue. They can establish stems and leaves population densities between 103-104

cfu/gfw under natural conditions (Compant et al, 2010). It is not clear whether bacterial

colonization of higher plant tissues confer similar beneficial effects on plant host as those

seen with root colonization. Nevertheless, only few bacteria can colonize aerial vegetative

parts of their host plants due to the physiological requirements needed to occupy these plant

niches (Hallmann, 2001). Thus, the bacteria that migrate to the above ground plant tissue are

well adapted to this particular endophytic niche. Bacterial movement inside plants is

supported by bacterial flagella and plant transpiration stream (James et al., 2002; Compant et

al., 2005a). Migration along intercellular spaces requires the secretion of cell-wall degrading

enzymes like cellulases and pectinases (Compant et al., 2010). However, movement through

xylem element occurs through perforated plates that allow movement of bacteria through

large pores without requiring cell-wall degrading enzymes (Bartz, 2005). The final sink for

these specialized endophytic bacteria is leaf tissue. Endophytic bacterial mostly colonize the

leaf tissues from plant roots, but just like phytopathogenic bacteria, endophytic bacteria can

gain entry into the leaves from the phyllosphere via leaf stomata (Senthilkumar et al., 2011).

1.4 Diversity of endophytic bacteria

Bacterial endophytes have been found in every plant species that has been studied. Thus, an

endophyte-free plant is a rare exception in the natural environment (Partida-Martínez and

Heil, 2011). In fact, a plant without the associated beneficial bacteria would be less fit to deal

with phytopathogens and more susceptible to the stress conditions (Timmusk et al., 2011).

The type of endophytic diversity present in a plant can depend on several factors which are

discussed below.

1.4.1 Factors affecting endophytic bacterial diversity of a plant

Apart from bacterial competence to colonize plants as endophytes, the host plant and

environmental factors can strongly influence the endophytic diversity of a particular plant.



Host plant age, genotype, geographical location, and even the tissue being analyzed can

determine the types of endophytic bacteria it harbors (Hallmann and Berg, 2006). Moreover,

host plant growth stages can also determine the endophytic diversity of a plant, where plant

stages enriched in nutrient availability tend to have increased bacterial diversity (Shi et al.,

2014). Not only that, the climatic conditions can also influence the endophytic colonizers of a

plant species. Penuelas et al. (2012) observed that changes in climate significantly altered the

abundance and composition of endophytic bacteria within the leaf tissues.

Another important factor affecting the observable endophytic diversity of a plant is the

method used to study these bacteria. The spectrum of bacteria recovered from a plant can

depend on the nature, concentration and even length of treatment time for a sterilizing agent

used to recover bacteria (Hallmann and Berg, 2006, Hallman et al., 2006).

The type of endophytic community of a plant is strongly influenced by nature of the plant

host species (Ding and Melcher, 2016). Different plant species growing in the same soil can

have distinctly different endophytic diversity. Germida et al. (1998) reported that canola and

wheat plants grown in the same field had very different spectrum of bacterial species as

endophytes. This observation was supported by Ding et al. (2013) who identified the host

species being the most important determinant in selecting its endophytic community,

followed by sampling dates and sampling locations. In fact, different cultivars of a plant

species grown in the same soil can also differ in their endophytic diversity, as reported by

Granér et al. (2003) for four different cultivars of Brassica napus having different endophytic

bacterial inhabitants. Thus the host plant species strongly governs the type of endophytic

bacteria colonizing it.

More interestingly, the type of soil used to grow a plant can also determine its endophytic

community. Thus, the same plant cultivar growing in different agricultural soils can have

very different endophytic bacteria. This was observed by Song et al. (1999) who reported

significantly different endophytic bacterial diversity for peanut cultivar grown in different

fields. Moreover, Rashid et al. (2012) isolated different types of endophytic bacteria by

growing one cultivar of tomato in 15 different agricultural soils. Collectively, these findings

indicate that occurrence of different endophytes is due to the diverse nature of soil samples.

The difference in endophytic community can also result by the preference imposed by the

plant host in response to soil and stress conditions. Siciliano et al. (2001) reported that plants,

while growing in the petroleum hydrocarbon contaminated soil, recruited those endophytic



bacteria which had the necessary contaminant-degrading genes. Moreover, the genes

encoding for nitro-aromatic compound degradation were more prevalent in endophytic strains

selected by the plants than within rhizospheric or soil microbial communities. Similarly,

Granér et al. (2003) reported that wilt resistant cultivar of oilseed rape contained a higher

proportion of endophytic bacteria antagonistic to the wilt causing Verticillium longisporum

than the susceptible cultivar. Presence of phytopathogens in plants has been considered an

important factor in the restructuring of endophytic bacterial communities. This was noticed

by Bogas et al. (2015) for their work on the restructured endophytic communities of

asymptomatic and symptomatic Paullinia cupana plants challenged by Colletotrichum spp.

Hence, the selection of endophytic bacterial communities is a dynamic process that is tightly

controlled by host plant (Berg and Hallmann, 2006; Trivedi et al., 2010).

1.4.2 Methods for studying endophytic diversity bacteria

Endophytic bacterial communities are conventionally studied using culturing based methods

(Ding et al., 2013). However, to investigate the endophytic bacterial communities using these

methods, the bacteria must be cultivable under laboratory conditions. Cultivation procedure

relies on the isolation of endophytic bacteria from plant tissue. The isolation procedure

should be sensitive enough to recover most of the cultivable endophytic bacteria, but should

be strong enough to eliminate epiphytes and other contaminating bacteria from the plant

tissues being processed. Commonly, isolation protocol requires surface sterilization of plant

tissues followed by their maceration, serial dilution and plating on the bacterial growth

medium (Barac et al., 2004). Sterilizing agents like sodium hypochlorite, ethanol and

hydrogen peroxide are commonly used to achieve the surface sterilization, and usually these

chemicals are used in a series to improve the effectiveness of the sterilization procedure

(Schulz et al., 1993; Romero et al., 2001; Lodewyckx et al., 2002). The sterilized tissue is

washed with sterile distilled water several times to remove the residual chemicals. The

sterilization is confirmed by plating small amount of distilled water from the last wash on the

culture media, where absence of bacteria confirms the effectiveness of sterilization

procedure. Moreover, surface sterilization producing high numbers of endophytic bacterial

growth on agar media indicates minimum damage to the endophytic population by the

sterilization procedure (Eevers et al., 2015). This is desired as any damage to the endophytic

community by the sterilizing agent can comprise the authenticity of a bacterial diversity

analysis. These cultivable bacteria are then identified using morphological, physiological,



biochemical and molecular approaches, where molecular approaches being the most accurate

of all (Ma et al., 2016). A number of molecular markers have been identified that permit the

identification of specific microbial taxa and their phylogenetic classification. Among these

molecular markers, 16S rRNA is most commonly employed to identify bacteria and

determine their phylogenetic relatedness (Srinivasan et al., 2015).

Total populations estimates of endophytic bacteria in plants may vary. These estimates can

depend on the type of growth media used for isolation, growth conditions of the host plant,

and method used to sterilize plant tissue (Romero et al., 2001; Lodewyckx et al., 2002;

Hallmann et al, 2006; Eevers et al., 2015). For example, a successful surface sterilization can

result in the penetration of these sterilizing chemicals in to the interior tissues, sometimes

killing the endophytic colonizers and compromising the correct bacterial estimates

(Lodewyckx et al., 2002; Hallmann et al., 2006). Similarly, selection of growth medium also

affects the numbers and diversity of endophytes that can be isolated from a specific plant

tissue, as no medium can meet the nutritional and growth requirements of all the bacteria

(Reiter et al., 2002; Eevers et al., 2015). Growth media are not always the reason for the

inability to culture bacteria as some bacteria can enter viable but nonculturable (VNC) state

and are unable to divide (Sessitsch et al., 2002). Moreover, even when endophytic bacteria

have been successfully isolated, maintaining them on growth media can sometimes prove to

be difficult (Trivedi et al., 2011; Eevers et al., 2015). Nevertheless, it is recommended that

endophytic bacteria are isolated using more than one type of growth media, and

supplementing these media with plant extracts can increase the overall diversity of bacteria

isolates (Hallmann et al., 2006; Eevers et al., 2015). However, cultivation-dependent methods

can strongly underestimate the number of bacteria present in plant tissues (Bogas et al.,

2015), as cultivable bacteria usually represents only 0.001% to 1% of the actual endophyte

counts (Torsvik and Øvreås, 2002; Alain and Querellou, 2009). Thus, the culture-based

methods have been surpassed by culture-independent methods, which tend to be less biased

in analyzing the true endophytic diversity.

Culture-independent methods to study endophytic diversity mostly rely on the total bacterial

genomic DNA extraction from plant tissues. The plant tissue is first processed to remove the

surface bacteria. This is usually achieved using aseptic peeling technique to remove the

surface layers, or by vigorously shaking the plant tissues with acid-washed glass beads in

saline solutions to dislodge the surface bacteria, followed by washes with sterile distilled

water. The processed plants tissues are then homogenized to extract the bacteria genomic



DNA (Sessitsch et al., 2002). The genomic DNA can then be analyzed using a range of

molecular fingerprinting techniques. Mostly commonly, the genomic DNA is used to amplify

a marker gene, usually the 16S rRNA gene, to analyze the bacterial diversity (Garbeva et al.,

2001). The variety of amplified gene fragments, representing the entire endophytic

population of a plant, are then analyzed using community DNA fingerprinting techniques like

Amplified rDNA Restriction Analysis (ARDRA), Denaturing Gradient Gel Electrophoresis

(DGGE), Temperature Gradient Gel Electrophoresis (TGGE), and Terminal Restriction

Fragment Length Polymorphism (T-RFLP) (Hallmann et al., 2006; Ma et al., 2016).

Alternatively, the highly variable region between 16S and 23S rDNA can be analyzed using

(Automated) Ribosomal Intergenic Spacer Analysis (ARISA) for the community

fingerprinting (Saito et al., 2007). However, to be detected by these fingerprinting techniques,

an endophytic population must represent about 1% of the total community (Smalla 2004).

Moreover, chances of detecting novel bacteria using these methods are low, as databases of

fingerprinting methods are largely incomplete (Ding et al., 2013).

The DNA fingerprinting techniques have largely been superseded by more advance

molecular techniques like metagenomics to study the microbial diversity. Metagenomics

involves DNA extraction from the entire bacterial population for analysis of its gene content

using next generation sequencing (Allan, 2014). The sequencing could be done for the entire

DNA, which is then assembled and annotated, or it could be done for one particular gene or

phylogenetic marker, like 16S rRNA. Thus, the metagenomics approaches allow full depth of

endophytic diversity analysis in comparison to traditional fingerprinting. Using

metagenomics approach, Sessitsch et al. (2012) uncovered the hidden community of rice

endorhizosphere, and deciphered many traits shared by the endophytic inhabitants that might

be crucial in their endophytic competence and success of the endophytes. However, the

DNA-based community analysis cannot selectively analyze the viable or metabolically active

bacterial cells. For this, RNA-based approaches are utilized, which can specifically determine

the metabolically active population, as the amount of RNA can be correlated to the growth

activity of the endophytic bacteria. Sharma et al. (2004) compared the rhizosphere bacterial

communities of three related legume plants and observed that metabolic profiles of the three

bacterial communities were more dissimilar (45-50% similarity) as compared to DNA-based

profiling (70-90% similarity). Similarly, comparative mRNA-based and DNA-based analyses

of root-associated communities in rice plants revealed that only a fraction of nitrogen fixing

bacteria actively performed the activity (Knauth et al., 2005; Diallo et al., 2008).



Endophytic bacterial populations can also be studied directly in their natural settings.

Techniques like fluorescence in situ hybridization (FISH) have allowed studying the

endophytic bacteria in the natural habitat (Piccolo et al., 2010). Moreover, by combing FISH

with other DNA fingerprinting techniques, the dominant population of the endophytic

community of a plant can also be identified (Sun et al., 2008). Such a polyphasic approach

that combines different methods is indeed recommended when analyzing endophytic bacterial

communities. In fact, combinatorial approaches, combining both culture-dependent and

culture-independent methods, can increase the likelihood of completely analyzing the

structure and function of endophytic bacterial community of a plant (Sessitsch et al., 2004;

Hallmann et al., 2006).

1.4.3 Endophytic bacteria diversity of different Plants

Endophytic bacterial diversity has been reported for a number of plant species. In general,

Proteobacteria is the most predominant phylum frequently isolated from plants, including the

classes α-, β-, and γ-proteobacteria, where γ-proteobacteria is the most diverse and dominant.

(Miliute et al., 2015; Santoyo et al., 2016). Members of the Actinobacteria, Bacteroidetes,

and Firmicutes are also among the classes most commonly found as endophytes (Reinhold-

Hurek and Hurek, 2011). Other classes such as Acidobacteria, Planctomycetes and

Verrucomicrobia are less commonly found as endophytes (Santoyo et al., 2016). However,

predominance of these phyla can vary with the type of host plant species (Bodenhausen et al.,

2013; Ding and Melcher, 2016). Among the most commonly isolated bacterial genera are

Bacillus, Burkholderia, Microbacterium, Micrococcus, Pantoea, Pseudomonas and

Stenotrophomonas, where Bacillus and Pseudomonas are the predominant genera (Hallmann

et al., 2006; Chaturvedi et al., 2016). A list of endophytic bacteria isolated from some

agronomic crop plants and some wild plants is provided in Table 1.1 and 1.2.

1.5 Mechanisms of Host Plant growth promotion

Endophytic bacteria have been shown to impart several beneficial effects on their plant host

directly or indirectly. They can benefit plants directly by assisting plants in getting nutrients,

and improve plant growth by modulating growth related hormones, which can help plants

grow better under normal and stressed conditions (Ma et al., 2016). Indirectly, endophytic

bacteria improve plant growth by discouraging phytopathogens using mechanisms like



antibiotic and lytic enzyme production, nutrient unavailability for the pathogens, and priming

plant defense mechanisms and thereby protecting the plants from future attacks by pathogens

(Miliute et al., 2015). These beneficial processes are discussed below.

Table 1.1 Some common Endophytic bacterial genera isolated from agronomic plants reported in

literature (Hallmann et al., 2006; Rosenblueth and Martínez-Romero, 2006; Miliute et al., 2015)

Plant Endophytic bacteria genera

Alfalfa Bacillus, Erwinia, Microbacterium, Pseudomonas, Salmonella

Banana Azospirillum, Burkholderia, Citrobacter, Herbaspirillum, Klebsiella

Black pepper

Arthrobacter, Bacillus, Curtobacterium, Micrococcus, Pseudomonas, Serratia

Canola Acidovorax, Agrobacterium, Aureobacterium, Bacillus, Chryseobacterium,

Cytophaga, Flavobacterium, Micrococcus, Pseudomonas, Rathayibacter,

Carrot Agrobacterium, Bacillus, Klebsiella, Pseudomonas, Rhizobium, Salmonella,

Staphylococcus

Clover Agrobacterium, Bacillus, Methylobacterium, Pseudomonas, Rhizobium

Cotton

Bacillus, Burkholderia, Clavibacter, Erwinia, Phyllobacterium, Pseudomonas

Cucumber

Agrobacterium, Bacillus, Burkholderia, Chryseobacterium, Clavibacter,

Curtobacterium, Enterobacter, Micrococcus, Paenibacillus, Phyllobacterium,

Pseudomonas, Serratia, Stenotrophomonas

Grapevine Comamonas, Enterobacter, Klebsiella, MoraxellaPantoea, Pseudomonas,

Rahnella, Rhodococcus, Staphylococcus, Xanthomonas

Maize

Achromobacter, Agrobacterium, Arthrobacter, Bacillus, Burkholderia,

Corynebacterium, Curtobacterium, Enterobacter, Erwinia, Herbaspirillum,

MicrobacteriumMicrococcus, Paenibacillus, Phyllobacterium, Pseudomonas,

Rhizobium, Serratia

Pineapple Azospirillum, Burkholderia

Potato

Acidovorax, Acinetobacter, Actinomyces, Agrobacterium, Alcaligenes,

Arthrobacter, Bacillus, Capnocytophaga, Chryseobacterium, Comamonas,

Corynebacterium, Curtobacterium, Enterobacter, Erwinia, Klebsiella,

Leuconostoc, Methylobacterium, Micrococcus, Paenibacillus, Pantoea,

Pseudomonas, Psychrobacter, Serratia, Shewanella, Sphinogomonas,

Stenotrophomonas, Streptomyces, Vibrio, Xanthomonas

Radish Proteobacteria, Salmonella

Red clover

Acidovorax, Agrobacterium, Arthobacter, Bacillus, Bordetella, Cellulomonas,

Comamonas, Curtobacterium, Escherichia, Klebsiella,

Methylobacterium, Micrococcus, Pantoea, Pasteurella, Phyllobacterium,

Pseudomonas, Psychrobacter, Rhizobium, Serratia, Sphingomonas, Variovorax,

Xanthomonas

Rice (wild and

cultivated)

Agrobacterium, Azoarcus, Azorhizobium, Azospirillum, Bacillus,

Bradyrhizobium, Burkholderia, Chromobacterium, Enterobacter,

Herbaspirillum, Ideonella, Klebsiella, Micrococcus, Pantoea, Pseudomonas,

Rhizobium, Serratia, Stenotrophomonas

Soybean Erwinia, Agrobacterium, Pseudomonas, Klebsiella, Enterobacter, Pantoea,

Bacillus

Sugar cane Acetobacter, Gluconacetobacter, Herbaspirillum, Klebsiella

Tomato Brevibacillus, Escherichia, Pseudomonas, Salmonella

Wheat Bacillus, Burkholderia, Flavobacterium, Klebsiella, Microbispora, Micrococcus,

Micromonospora, Mycobacterium, Nacardiodes, Rathayibacter, Streptomyces



Table 1.2 Diversity of endophytic bacterial isolated from some wild plants.

Plant Location Endophytic bacteria Reference

Alnus firma Mine tailing Bacillus sp. Shin et al., 2012

Alyssum

bertolonii Serpentine outcrop

Arthrobater

Bacillus

Curtobacterium

Leifsonia

Microbacterium

Paenibacillus

Pseudomonas

Staphylococcus

Barzanti et al., 2007

Calystegia soldanella Sand dunes

Acinetobacter

Arthrobacter

Chryseobacterium

Curtobacterium

Enterobacter

Microbacterium

Pantoea

Pedobacter

Pseudomonas

Stenotrophomonas

Park et al., 2005

Commelina

communis Mine wasteland

Arthrobacter

Arthrobacter

Bacillus

Bacillus pumilus

Herbaspirillum

Microbacterium

Sphingomonas

Sun et al., 2010

Cressa cretica,

Salicornia brachiate,

Suadea nudiflora,

Sphaeranthus indicus

Coastlines

Acinetobacter

Arthrobacter

Bacillus

Kocuria

Oceanobacillus

Paenibacillus

Pseudomononas

Virgibacilus

Arora et al., 2014

Elsholtzia

Splendens Mine wasteland

Acinetobacter calcoaceticus

Acinetobacter junii

Bacillus

Bacillus firmus

Bacillus megaterium

Burkholderia

Exiguobacterium aurantiacum

Micrococcus luteus

Moraxella

Paracoccus

Serratia marcescens

Sun et al., 2010

Elymus mollis Sand dunes

Acinetobacter

Arthrobacter

Chryseobacterium

Enterobacter

Exiguobacterium

Flavobacterium

Klebsiella

Pedobacter

Pseudomonas

Stenotrophomonas

Park et al., 2005



Table 1.2 continued


Halimione portulacoides

Salt marsh

Altererythrobacter

Hoeflea

Labrenzia

Marinilactibacillus

Microbacterium

Salinicola

Vibrio

Fidalgo et al., 2016

Mammillaria fraileana

(cactus) Wild rocky habitat

Azotobacter vinelandii

Bacillus megaterium

Enterobacter sakazakii

Pseudomonas putida

Lopez et al., 2011

Miscanthus sinensis Mine wasteland Pseudomonas koreensis Babu et al., 2015

Noccaea caerulescens Metal contaminated

site

Agreia

Arthrobater

Bacillus

Kocuria

Microbacterium

Sthenotrophomonas

Variovorax

Visioli et al., 2014

Pachycereus pringlei

(cardon cactus) Volcanic areas

Acinetobacter

Bacillus

Citrobacter

Klebsiella

Paenibacillus

Pseudomonas

Staphylococcus

Puente et al., 2009a

Pinus contorta (Lodgepole pine)

Sub-boreal Pine

Spruce

Bacillus

Brevibacillus

Brevundimonas

Cellulomonas

Kocuria

Paenibacillus

Pseudomonas

Bal et al., 2012

Pinus sylvestris Mine wasteland Bacillus thuringiensis Babu et al., 2013

Polygonum pubescens Heavy metal

contaminated soil Rahnella sp. JN6 He et al., 2013

Prosopis strombulifera Saline environment

Achromobacter xylosoxidans

Bacillus licheniformis

Bacillus pumilus

Bacillus subtilis

Brevibacterium halotolerans

Lysinibacillus fusiformis

Pseudomonas putida

Sgroy et al., 2009

Salix caprea Heavy metal

contaminated soil

Bacillus

Frigoribacterium

Frondihabitans

Kocuria

Leifsonia

Massilia

Methylobacterium

Microbacterium

Ochrobactrum

Pedobacter

Plantibacter

Rhodococcus

Sphingomonas

Spirosoma

Subtercola

Kuffner et al., 2010



Table 1.2 continued


Sedum alfredii Hance Mining area

Burkholderia

Sphingomonas

Variovorax

Zhang et al., 2013

Thuja plicata (Red cedar)

Sub-boreal Pine

Spruce

Arthrobacter

Bacillus

Paenibacillus

Pseudomonas

Streptoverticillium

Bal et al., 2012

Wild Prairie Plants Prairie

Cellulomonas

Clavibacter

Curtobacterium

Microbacterium

Zinniel et al., 2002

1.5.1 Nutrient acquisition

Soils usually lack a sufficient quantity of one or more of the nutrient compounds necessary

for plant growth. The endophytic bacteria can help their host plants is by getting increased

amounts of the limiting plants nutrients, which include nitrogen, iron, and phosphorus (Glick,

2012). These mechanisms are discussed below and also summarized in Figure 1.2.

1.5.1.1 Nitrogen availability

Endophytic bacteria can increase the Nitrogen availability for their host plants. These bacteria

can supply fixed atmospheric nitrogen to their host plants by expressing nitrogenase activity

(Montañez et al., 2012). Nitrogenase is a highly conserved protein and all N2 fixing bacteria

have this enzyme, with ample evidence suggesting lateral gene transfer (Ivleva et al., 2016).

Nitrogen fixing bacteria like Azoarcus sp. BH72, Azospirillum brasilense, Burkholderia spp.,

Gluconacetobacter diazotrophicus, and Herbaspirillum seropedicae have been reported to

increase the host plant biomass by N2 fixation under controlled conditions (Bhattacharjee et

al. 2008). Associative nitrogen-fixing endophytes perform better than rhizosphere

microorganisms in enabling plants to thrive in nitrogen limited soil environments and

promote plant health and growth (Hurek and Reinhold-Hurek, 2003). Gupta et al. (2013)

reported that endophytic nitrogen-fixing bacteria may also enhance the rate of nitrogen

fixation and accumulation in plants residing in nitrogen limited soils. Endophytic bacteria are

not as efficient as root nodule associated Rhizobium in Nitrogen-fixation ability. However,

endophytic strains of Gluconacetobacter diazotrophicus perform exceptionally well in this

ability. Strains of Gluconacetobacter diazotrophicus have been identified living in symbiosis

with sugarcane and pine plants (Dong et al., 1994; Carrell and Frank, 2014). Similarly,



Nitrogen-fixing endophyte Paenibacillus strain P22 has been found in poplar tree, which was

shown to contribute to the total nitrogen pool of the host plant (Scherling et al., 2009).

1.5.1.2 Phosphorus availability

Phosphorous is another major micronutrients crucial for enzymatic reactions responsible for

many plant physiological processes (Ahemad, 2015). Although present in ample quantities,

most of the soil phosphorus is insoluble, and therefore cannot support the plant growth due to

its unavailability. Moreover, almost 75% of phosphorus applied as fertilizer forms complexes

with soil and becomes unavailable for plants (Ezawa et al., 2002). Endophytic bacteria can

increase the availability of phosphorus for plants by solubilizing precipitated phosphates,

using mechanisms like acidification, chelation, ion exchange and production of organic acid

(Nautiyal et al., 2000). They can also increase phosphorus availability in the soil by secreting

acid phosphatase that can mineralize organic phosphorus (van der Hiejden et al., 2008).

Moreover, endophytic bacteria can prevent phosphate adsorption and fixation under

phosphate-limiting conditions by assimilating solubilized phosphorus (Khan and Joergensen,

2009). Thus, these bacteria can act as a sink to provide phosphorus to the plants when they

need it. Phosphate solubilization feature is commonly found in endophytic bacteria. For

instance, around 59-100% of endophytic populations from cactus, strawberry, sunflower,

soybean and other legumes were mineral phosphates solubilizers (Kuklinsky-Sobral et al.

2004; Forchetti et al. 2007; Dias et al. 2009; Palaniappan et al. 2010; Puente et al. 2009a).

Puente et al. (2009b) examined the role of phosphate solubilizing endophytic bacteria by

growing bacteria-free cacti on mineral phosphate supplemented with either endophytes or

nutrients, and compared them with plants grown under sterile conditions. The inoculated

plants grew well without nutrient addition, and their growth was comparable to fertilized

plants, whereas the bacteria-free cacti failed to grow. This indicated that endophytic bacteria

provided the developing plantlets with limiting nutrient.

1.5.1.3 Iron availability

Iron is important element of life required by most organisms. Iron is part of many iron-

containing proteins controlling important physiological processes like transpiration and

respiration (Ma et al., 2016). Iron usually occurs in the insoluble ferric (Fe3) that is

unavailable to most plants, which includes carbonates, hydroxides, oxides and phosphates of



iron. Endophytic bacteria produce iron chelating agents called siderophores that can bind

insoluble ferric ions, and plants can acquire iron from these bound siderophores via root

based chelate degradation or ligand exchange (Rajkumar et al., 2009; Ma et al., 2016). Hence,

bacterial siderophores play a major role in providing iron to plants under iron limitation (Ma

et al., 2011). Marques et al. (2010) demonstrated that siderophore production by plant

beneficial bacteria strongly correlated with maize plant growth traits including shoot and root

biomass. Furthermore, Radzki et al. (2013) recently demonstrated that bacterial siderophores

efficiently provided iron to tomato plants during growth in hydroponic culture. Iron

acquisition is not the only benefit provided to the plants by siderophore producing bacteria.

Endophytic bacteria can also discourage the growth of phytopathogens by siderophore

production, possibly by iron depletion (Ahmad et al., 2008). In fact, Calvente et al. (2001)

demonstrated that the bacterial siderophore containing spent media inhibited the growth of

phytopathogenic molds, and antifungal activity was correlated to siderophore concentration.

1.5.2 Phytohormone production and modulation

Endophytic bacteria can enhance nutrients accumulation and metabolism of host plants by

producing growth regulating phytohormones. Recent studies examining the possible role of

plant hormones released by endophytic bacteria have shown that the endophytic colonization

caused enhanced plant nutrient uptake and biomass (Gravel et al., 2007; Shi et al., 2009;

Phetcharat and Duangpaeng, 2012). In general, there are five types of plant hormones,

namely abscisic acid, cytokinins, ethylene, gibberellins and indole-3-acetic acid (IAA), where

IAA and ethylene are the most important homones in plant-bacterial interactions.

1.5.2.1 Moderating plant Indole Acetic Acid levels

IAA is a major plant auxin that is involved in numerous plant physiological processes. These

processes include cell-cell signaling, regulation of plant development, and induction of plant

defense system (Navarro et al., 2006; Gravel et al., 2007; Spaepen et al., 2007). IAA can also

initiate lateral and adventitious root formation, mediates responses to stimuli, affects

photosynthesis and biosynthesis of metabolites, and mediate resistance to stress conditions

(Glick, 2012). Further, IAA can even control synthesis of other plant hormones like ethylene

(Woodward and Bartel, 2005).



Modulating plant IAA pools is an important trait by which endophytic bacteria can enhance

plant growth. IAA production by the endophytic bacteria can result in improved plant root

biomass and surface area, and increased production of lateral roots in host plants (Kuklinsky-

Sobral et al., 2004; Tsavkelova et al., 2007; Taghavi et al. 2009; Dias et al., 2009).

Tsavkelova et al. (2007) reported that endophytic bacteria that were isolated from terrestrial

orchids produced IAA. They noticed that the culture supernatant of the bacteria stimulated

root formation of kidney beans by significantly increasing root length and the number of

developing roots, indicating possible role of bacterial IAA in the development plant root

system. A more direct evidence of the role of bacterial IAA in plant beneficial effects came

from Patten and Glick (2002), who showed that Pseudomonas putida GR12-2 defective in

IAA synthesis was unable to increase plant root growth and lateral root formation.

While lower amounts of IAA production by bacteria can enhance plant root growth, higher

quantities can cause stunting of root growth (Malik and Sindhu, 2011). In a continuation

work to Patten and Glick (2002) to study the effects of IAA levels on plant growth,

Pseudomonas putida GR12-2 mutant, that was modified to overproduce IAA, produced much

shorter roots in mung bean compared to uninoculated control plants. This is not surprising as

high IAA production is known to be the characteristic of plant pathogens (Rashid et al.,

2012), and can cause increased production of ethylene, which is a plant stress hormone

(Woodward and Bartel, 2005).

IAA production is not the only way by which endophytic bacteria can improve host plant

growth. Indeed, the reverse activity, degradation of IAA, can also play a significant role in

enhancing plant growth. This was demonstrated by Leveau and Lindow (2005) for the plant

growth prompting and IAA degrading Pseudomonas putida Strain 1290, which completely

abolished the inhibitory effects of exogenous IAA on the elongation of radish roots. The

bacteria also produced IAA in the presence of tryptophan, which is a precursor of IAA.

However, it was shown that IAA production by Pseudomonas putida Strain 1290 did not

have the similar deleterious effects on radish roots as did the high IAA-producing strains.

Thus, the authors suggested that this dual status, the ability to both produce and destroy IAA,

enables this bacteria to finely control IAA levels to produce a net positive effect on host

plant. Similarly, Zúñiga et al. (2013) showed that mutant Burkholderia phytofirmans PsJN,

which was defective in IAA mineralization, was unable to alleviate the inhibitory effects of

exogenous IAA in the roots of Arabidopsis thaliana compared to wild type strain.

Nevertheless, Bacterial IAA production is considered a very important trait in selecting plant



beneficial bacteria. Moreover, plant IAA levels can also determine whether bacterial IAA

stimulates or suppresses plant growth, where bacterial IAA production benefiting those plants

with low levels of endogenous IAA (Glick, 2012).

1.5.2.2 Control of ethylene levels

Ethylene is an important plant hormone that controls the plant response to abiotic and biotic

stresses. It can control different developmental and physiological processes like root

initiation, leaf senescence, root nodulation, abscission, cell elongation, fruit ripening and

auxin transport (Sun et al., 2006). Biotic and abiotic stress results in an increased ethylene

production in plants that leads to inhibition of root elongation, development of lateral roots

and formation of root hair. Endophytic bacteria produce an enzyme called 1-

aminocyclopropane-1-carboxylate (ACC) deaminase that can hydrolyze ACC, which is a

precursor of plant hormone ethylene. ACC degrading bacteria can bind to plant roots and

cleave the exuded ACC into a-ketobutyrate and ammonia to use it as a nitrogen source (Sun

et al., 2009). Thus, hydrolysis of ACC can alleviate plant stress, thereby improving plant

growth under stress conditions (Santoyo et al. 2016). A number of plant growth promoting

endophytic bacteria have been reported to have ACC deaminase activity (Zhang et al., 2011;

Nikolic et al., 2011; Rashid et al., 2012). In fact, ability of these bacteria to benefit plant

growth can be related to ACC deaminase production. This was demonstrated by Sun et al.

(2009) who mutated the ACC deaminase gene of the canola growth promoting Burkholderia

phytofirmans PsJN and observed that the mutant was no longer able to promote canola root

growth. However, introduction of the wild-type ACC deaminase gene restored the growth

promoting ability of mutant Burkholderia phytofirmans PsJN, indicating the crucial role this

enzyme plays in growth promotion of host plants.

1.5.2.3 Production of Plant Cytokinins and Gibberellins

Several studies have shown that many plant beneficial endohytic bacteria can produce

cytokinins gibberellins. Cohen et al. (2009) revealed the effects of Azospirillum lipoferum in

maize plants treated with inhibitor of Gibberellins synthesis and subjected to drought stress or

well watered. The gibberellin produced by the endophytic bacterium was important in plant

stress alleviation. Similarly, Bhore et al. (2010) identified cytokinin-like compounds in the

broth-extracts of two endophytic bacteria, isolated from Gynura procumbens, using cucumber



cotyledon greening bioassay. The two bacteria were identified as Psuedomonas resinovorans

and Paenibacillus polymaxa. More work is needed to elucidate the role of bacterial

gibberellins and cytokinins in improving plant growth.

1.5.2.4 Indirect growth promotion by suppression of phytopathogens

Endophytic bacteria enhance the host plant growth indirectly by discouraging the growth of

phytopathogens and plant pests. They can produce substances that reduce phytopathogen

caused diseases like antibiotics, toxins, siderophores, hydrolytic enzymes and antimicrobial

volatile organic compounds (Sheoran et al., 2015). Both bacterial and fungal pathogens can

be targeted by endophytic bacteria (Lodewyckx et al. 2002). Bacteria belonging to

Actinobacteria, Bacillus, Enterobacteor, Paenibacillus, Pseudomonas and Serratia are the

most commonly reported genera for their antimicrobial activity against phytopathogens

(Lodewyckx et al. 2002; Aktuganov et al., 2008; Liu et al., 2010). Endophytic bacteria have

been demonstrated to successfully suppress fungal disease in plants like black pepper, potato

and wheat (Coombs et al. 2004; Sessitsch et al. 2004; Aravind et al. 2009). These

antimicrobial activities against fungi can be result from production of fungal cell-wall

targeting enzymes chitinase, proteases and glucanases (Zarei et al., 2011; Zhang et al., 2012).

Antimicrobial activity against bacterial pathogens has been reported for Bacillus subtilis

BSn5 that targeted plant pathogen Erwinia carotovora subsp. carotovora. However, the exact

mechanism of action against the pathogen is not known (Dong et al., 2001; Deng et al.,

2011). Moreover, an endophytic bacteria Pantoea vagans C9-1 has been commercialized as a

bacterial biocontrol agent for fire blight (Smits et al., 2011). Activity against nematodes was

reported by Aravind et al., 2010 for suppression of phytopathogenic burrowing nematode

(Radopholus similis Thorne) by endophytic bacteria Bacillus megaterium BP 17 and

Curtobacterium luteum TC 10. Endophytic bacteria active against plant pest have also been

demonstrated, where genetically modified endophytic Pseudomonas fluorescens expressing

Bacillus thuringiensis toxin and Serratia marcescens chitinase effectively targeted Eldana

saccharina (Sugarcane Borer) larvae (Downing et al., 2000).

Plant beneficial bacteria can use a mechanism called induced systemic resistance (ISR) to

protect their host plants from phytopathogens. ISR induced by endophytic bacteria can

protect host against various different fungal, bacterial and viral pathogens (Alvin et al.,

2014). The ISR primes plant defense mechanisms, thereby protecting unexposed plant parts



against future pathogenic attacks against microbes and herbivorous insects. Endophytic

bacteria can initiate ISR using salicylic acid (SA), or jasmonic acid (JA) and ethylene (ET)

mediated type pathways, which are usually a network of interconnected signaling pathways

involved in ISR induction (Pieterse et al., 2012). Endophytic bacteria of genus Bacillus,

Pseudomonas and Serratia have been shown to protect plant hosts using defense priming by

ISR (Kloepper and Ryu, 2006; Pieterse et al., 2014). The bacteria must also be able to

overcome these host defense responses in order to colonize the host plant (Ma et al., 2016).

Figure 1.2 Mechanisms used by endophytic bacteria for plant colonization and growth promotion

(Pink, establishment in host; blue, plant growth promotion; black, rhizosphere competence and

attachment). Processes labeled with star are experimentally (mostly mutational) verified while others

are suspected, inferred from literature or genome comparisons. (Reinhold-Hurek and Hurek, 2011)



ISR may involve both the SA and JA/ET pathways. Niu et al. (2011) showed that Bacillus

cereus AR156 triggered both the SA and JA/ET signaling pathways in Arabidopsis to induce

ISR, which led to an additive effect of plant protection. Similarly, Conn et al. (2008)

indicated that A. thaliana plants inoculated with endophytic Actinobacteria showed

upregulation of both defense pathways, thereby protecting against subsequent infection by

phytopathogenic bacteria Erwinia carotovora and fungus Fusarium oxysporum. However, the

primed defense pathways differed for the two pathogen types. The resistance to Erwinia

carotovora was by JA/ET pathway, while resistance towards Fusarium oxysporum was by

SA pathway. Thus, the same bacteria were able to prime two different pathways to confer

resistance to different pathogen (Conn et al., 2008).

1.6 Bacterial genes expressed in the endophere

Endophytic bacteria colonize the plant endosphere and confer growth benefits to their host by

using a wide variety of traits. Some of these traits have been confirmed using techniques like

gene deletion / disruption and complementation (Sun et al., 2009; Zúñiga et al., 2013), real-

time PCR (Yousaf et al., 2011; Zhao et al., 2016), in-vivo expression technology (IVET)

(Rediers et al., 2003), gusA fusion reporter system (Roncato-Maccari et al., 2003), gene

overexpression (Fan et al., 2013), gene introduction (Cho et al., 2007), and RNA-seq based

whole transcriptome profiling (Sheibani-Tezerji et al., 2015).

Most of these studies have been done on Burkholderia phytofirmans strain PsJN, a model

endophytic bacterium, with the ability to competently colonize (both rhizosphere and

endosphere) and promote growth of a variety of different plant hosts, including Arabidopsis

thaliana, grape, maize, potato, switch-grass, tomato, and wheat (Sessitsch et al., 2005;

Sheibani-Tezerji et al., 2015). Moreover, strain PsJN can also increase tolerance of host

plants to abiotic stress such as chilling and drought (Barka et al., 2006; Naveed et al., 2014),

and biotic stress like inhibiting growth of fungal phytopathogens (Sharma and Nowak, 1998;

Barka et al., 2002). Strain PsJN have been shown to require IAA degradation, ACC

deaminase, and quorum sensing to colonize host plants and produce beneficial effects (Sun et

al., 2009; Zúñiga et al., 2013). Moreover, in-planta gene expression profiling revealed that,



during its growth inside host plants, the bacterium expresses a number of different traits

related cellular homeostasis, cell redox homeostasis, energy production, general metabolism

(amino acids, lipids, nucleotides, sugars), and transcription regulation (Sheibani-Tezerji et al.,

2015). The same study revealed that bacterium expresses enzyme related to oxidative stress

when host plants are challenged with drought stress. Another study on strain PsJN indicated

that bacterium expresses traits involving iron uptake and storage (Zhao et al., 2016).

Nevertheless, more work is needed to elucidate the importance of different genes required by

strain PsJN for its endophytic success. Other bacteria have also been studied for their

endophytic gene expression and lifestyle, which have been summarized in Table 1.3.

1.7 Host specificity of growth promoting endophytic bacteria

The plant growth promoting ability of endophytic bacteria can be influenced by the genotype

of plant host. Long et al. (2008) noticed that plant growth promoting bacteria of Solanum

nigrum that were highly host specific, where these bacteria were unable to produce growth

enhancement in Nicotiana attenuate, a non-host plant. Similarly, Kim et al. (2012) reported

that growth promotion of switch grass by Burkholderia phytofirmans PsJN is plant genotype

dependent. However, many endophytic bacteria can have a broad host range, as has been

demonstrated in the case of Burkholderia phytofirmans PsJN, isolated from onion roots

(Pillay and Nowak, 1997), which can promote growth of Arabidopsis thaliana, grape, maize,

potato, switch-grass, tomato, and wheat (Sessitsch et al., 2005; Sheibani-Tezerji et al., 2015).

Bacterial genotype can also strongly influence the growth promoting effects of bacterial

endophytes on host plants. This was demonstrated by Trognitz et al. (2008), where different

strains of Burkholderia phytofirmans differed markedly in their growth promoting abilities of

same potato cultivar. Similarly, Dong et al. (2003) reported that four strains of endophytic

Salmonella enterica colonize alfalfa roots and hypocotyl differently. Hence, plant

colonization and growth promotion by the endophytic bacteria appears to be an active process

that is controlled by the genetic factors of both partners.



Table 1.3 Selected bacterial genes involved in endosphere colonization, host interaction and

promotion of plant growth.

Gene Function Technique Bacteria Reference

acds

(ACC deaminase) Stress reduction

Gene deletion,

complementation

; gene disruption

Burkholderia

phytofirmans

PsJN

Sun et al., 2009;

Zúñiga et al.,

2013

iacC IAA degradation Gene disruption

Burkholderia

phytofirmans

PsJN

Zúñiga et al.,

2013

N-acyl-

homoserine

lactone synthase

Quorum Sensing Gene disruption

Burkholderia

phytofirmans

PsJN

Zúñiga et al.,

2013

nifH

(nitrogenase) Nitrogen fixation

Pnif: :gusA fusion

reporter system;

RT-PCR

Herbaspirillum

seropedicae;

Bradyrhizobium,

Pelomonas,

Bacillus sp.,

Cyanobacteria

Roncato-Maccari

et al., 2003;

Terakado-

Tonooka et al.,

2008

eglA; eglS

(endoglucanse)

Systemic

colonization

Transposon

mutagenesis; gene

disruption by

homologous

recombination

Azoarcus sp.

strain BH72;

Bacillus

amyloliquefaciens

Reinhold-Hurek

et al., 2006; Fan

et al., 2016

Pectinase Systemic

colonization

Gene

overexpression Bacillus Fan et al., 2013

alkB

(alkane

monooxygenase)

Diesel

degradation Real-time PCR

Pseudomonas sp.,

Rhodococcus sp.

Andria et al.,

2009

carAB

Pathogen cell-cell

signaling

disruption

Gene disruption,

complementation

Pseudomonas sp.

strain G

Newman et al.,

2008

aiiA

(N-acyl-

homoserine

lactonase)

Pathogen quorum

sensing disruption

Gene introduction

by electroporation

Burkholderia sp.

KJ006 Cho et al., 2007

Multiple genes

Stress response,

chemotaxis,

metabolism, and

global

regulation

dapB-Based In

Vivo Expression

Technology

System

Pseudomonas

stutzeri A15

Rediers et al.,

2003

CYP153 genes

(alkane

degradation)

Petroleum

hydrocarbon

defradation

Real-time PCR

Enterobacter

ludwigii;

Pseudomonas

sp. strain ITRI53,

Pantoea sp. strain

BTRH7

Yousaf et al.,

2011; Afzal at al.,

2011

pilT

(type IV pili)

Endophytic

colonization by

Twitching

Motility

Deletion mutation Azoarcus sp.

Strain BH72 Böhm et al., 2007

O-antigenic

side chain Attachment

Spontaneous

phage-mediated

mutant

Pseudomonas

fiuorescens

strain WCS417r

Duijff et al., 1997



Table 1.3 continued

Gene Function Technique Bacteria Reference

Multiple genes

Transcription

regulation,

general

metabolism

(sugars, amino

acids,

lipids, and

nucleotides),

energy

production,

cellular

homeostasis, cell

redox

homeostasis, ECF

group IV sigma

factors

In-planta RNA-

seq based

transcriptome

profile

Burkholderia

phytofirmans

PsJN

Sheibani-Tezerji

et al., 2015

Ferritin Iron storage Real-time PCR

Burkholderia

phytofirmans

PsJN

Zhao et al., 2016

TonB-dependent

siderophore

receptor

Siderophore

mediated iron

uptake

Real-time PCR

Burkholderia

phytofirmans

PsJN

Zhao et al., 2016

L-ornithine5-

monooxygenase

Siderophore

synthesis Real-time PCR

Burkholderia

phytofirmans

PsJN

Zhao et al., 2016

There are numerous reports of non-host plant growth promotion by endophytic bacteria. Ma

et al. (2011) isolated Nickel resistant Pseudomonas sp. A3R3 from Nickel accumulating

Alyssum serpyllifolium. The bacteria promoted the growth of the host plant and the non-host

Brassica juncea under metal stress. Similarly, Sun et al. (2015) showed that Copper-resistant

Burkholderia sp. GL12 and Bacillus megaterium JL35 could significantly promote growth of

host Elsholtzia splendens and a non-host Brassica napus grown in heavy metal-contaminated

soils. Thomas and Upreti (2014) demonstrated that endophytic bacterial isolated from crops

plants that could inhibit Ralstonia solanacearum (wilt pathogen) also mitigated the disease

effects of Ralstonia solanacearum on a non-host tomato plant. Moreover, endophytic bacteria

isolated from different agricultural soils using tomato plants were able to promote canola

growth under gnotobiotic conditions (Rashid et al., 2012). Collectively, these finding suggest

that endophytic bacteria can have broad host range in terms of their plant growth promoting

potential, a feature that could be exploited in agriculture sector.



Aims and Objectives

The rationale of the proposed study is that wild plants that grow under challenging conditions

and exhibit unique survival abilities may harbor interesting endophytic bacteria. Those

exceptional survival capabilities of the plants may be due to their endophytic bacterial

inhabitants. As endophytic bacteria are known to have a broad host range, the unique survival

abilities they impart to their host may not be species specific. Hence the potential to isolate

useful agricultural beneficial endophytic bacteria from wild plants is immense, since this area

remains largely neglected. Furthermore, a comparison between the successful and

unsuccessful colonizers of a new host plant may reveal the bacterial traits needed to promote

growth of a wide variety of non-host plants. The expected outcome of the proposed research

work will be unearthing of new agriculturally beneficial bacteria as bio-inoculants for crop

plant, and an improved understanding of bacterial traits important for general plant beneficial

effects. The specific objectives are as follows.

1. To isolate and identify endophytic bacteria from wild perennial plants.

2. Investigate the in-vivo growth promotion potential of isolated bacteria on a crop plant.

3. Explore the bacterial mechanisms of plant invasion and growth promotion using in-vitro

assays (plant colonization, phytohormone production, and nutrient availability).

4. Investigate the biocontrol potential of bacterial isolates against phytopathogenic fungi.

5. Undertake in-planta gene expression profiling of a growth promoting endophytic bacteria

to identify genes of endophytic colonization and growth promotion.

Chapter 2

Selective isolation and characterization of agriculturally

beneficial endophytic bacteria from Wild Hemp using

Canola

Chapter 2


Selective isolation and characterization of agriculturally beneficial endophytic bacteria

from Wild Hemp using Canola

Abstract

Endophytic bacteria can function as biofertilizers and biopesticdes to improve

plant growth thereby decreasing the use of dangerous chemical fertilizers and

pesticides. Wild perennial plants remain a neglected niche to isolate plant beneficial

endophytic bacteria for commercial application to crops. Present study isolated

endophytic bacteria from wild Cannabis sativa L. (hemp) using two different methods

to examine their ability to promote Canola growth. The first method involved

isolation of endophytic bacteria directly from the roots; while, the second novel

approach involved selective isolation of endophytic bacteria from C. sativa

rhizosphere using a second host plant, Canola. Selective isolation yielded six bacteria

that significantly promoted canola root growth while direct isolation produced only

two such bacteria. Most noticeable isolates with multiple plant benefical traits were

Pantoea vagans MOSEL-t13, Pseudomonas geniculata MOSEL-tnc1, and Serratia

marcescens MOSEL-w2. These bacteria endured NaCl stress upto 7% and benefited

canola growth under NaCl stress. Most of the isolated bacteria possed plant beneficial

traits like IAA production, mineral phosphate solubilization, and siderophore

production to improve iron uptake. Most isolates also produced cellulase and

pectinase that allow bacteria to target plant cell-wall and systemically colonize plants.

Some isolates also antogonized the growth of two plant fungal pathogens in dual

culture assay, and produced chitinase and protease, indicating their usefulness as

biocontrol agents. Paenibacillus sp. MOSEL-w13 was most prominent bacteria in

antifungal activity. These results conclude that wild perennial plants harbor distinct

plant benefical endophytic bacteria and demonstrates the usefulness of newly

proposed selectively isolation for the improved isolation of these bacteria.

Chapter 2


2.1 Introduction

Endophytic bacteria are a group of plant associated bacteria known to improve growth

of their plant host. The bacteria achieve this by producing plant hormones, increasing nutrient

availability and mitigating biotic and abiotic stress (Glick, 2012). Unlike rhizobacteria, the

well-known bacteria establishing symbiotic relationships with many plants, endophytes thrive

within the internal tissues of plants and use specialized mechanisms to enter the host

(Compant et al., 2010). Primarily, they enter the host from the rhizosphere soil surrounding

the roots (Conn and Franco, 2004). This entry is also regulated by the plant host itself (Dong

et al., 2003). As a result, plants are known to harbor specific microflora as their mutualistic

symbionts. On the other hand, endophytic bacteria can have multiple hosts, being either host

specific or general endophytes (Hardoim et al., 2008).

Most of the work on endophytic bacteria has been focused on agricultural crops.

However, a large number of plants still remain unstudied for their endophytic diversity,

particularly the wild and perennial plants. Wild and perennial plants provide an interesting

niche to screen for the potential plant growth promoting bacteria. Unlike crop plants, wild

plants are constantly challenged by harsh and adverse conditions, including water and

nutrient scarcity, extreme weather and attacks by pests and pathogens. They ensure their

vitality using a range of mechanisms. This includes choosing the right endophytic partners

that help them withstand such difficulties (Rout et al., 2013). Therefore, identifying

potentially useful endophytic bacteria of wild plants, that can also improve growth of crop

plants, can be extremely beneficial for the agricultural sector.

Wild hemp (Cannabis sativa L.) is a good candidate for the evaluation of useful

endophytic bacteria. It is a common herbaceous plant in many parts of the world, known for

its medicinal use as well as a source of recreational drug. In Pakistan, it is a native plant that

grows wildly and perennially in most areas of Pakistan, occurring more abundantly in

northern Punjab (Ashraf et al., 2012). Although some work has been done on endophytic

bacteria of wild plants including C. sativa (Hung et al., 2007; Kusari et al., 2014; Zinniel et

al., 2002), there are only limited studies where these bacteria were tested for their usefulness

on commercial crops (Ma et al., 2011; Zhang et al., 2011).

Researchers have used different properties of bacteria to select plant growth

promoting bacteria. The most widely used method is to select bacteria with ACC deaminase,

Chapter 2


an enzyme that breaks down the precursor of plant stress hormone thereby improving plant

growth (Sun et al., 2009). Using this approach, endophytic bacteria have been isolated, both

from wild plants and agricultural soils, promoting growth of a non-host canola plant (Rashid

et al., 2012; Zhang et al., 2011). However, the growth promoting ability of ACC deaminase

producing bacteria can be limited to the original host (Long et al., 2008). Moreover, some

non-ACC deaminase bacteria can also enhance plant growth similar to ACC deaminase

bacteria (Ma et al., 2011; Sheng et al., 2008).

Aims and objectives

The aim of present study was to isolate and characterize useful endophytic bacteria

from C. sativa with ability to promote canola growth. In addition to direct isolation from

surface sterilized host tissues (Beneduzi et al., 2013), endophytic bacteria were also

selectively isolated using a new approach. The isolated bacteria were tested for different traits

consistent with the plant growth promotion. Some growth promoting bacteria were also tested

for their ability to reduce the inhibitory effects of salt stress on plant growth.

2.2 Materials and Methods

The study presented was carried out in the Molecular Systematics and Applied Ethnobotany

Laboratory (MOSEL), Department of Biotechnology, Quaid-i-Azam University, Islamabad.

The experiments performed included isolation and identification of endophytic bacteria from

Cannabis sativa, and their characterization on the basis of various in-vivo and in-vitro plant

growth promotion and biocontrol assays. Detailed methods are as under and recipes are

provided in Appendix A.

2.2.1 Collection of plant samples

Wild Cannabis sativa L. was collected from three sites located within the campus area

of Quaid-i-Azam University, Islamabad. The samples were immediately brought to

laboratory and processed for isolation of endophytic bacteria.

Chapter 2


2.2.2 Isolation of Endophytic Bacteria

Culturable bacteria were isolated from the healthy Cannabis sativa plants growing in the

wild. Two different approaches were used for the isolation. The first approach was direct

isolation of endophytic bacteria from roots of C. sativa using a modified approach of Rashid

et al. (2012). The roots were washed using tap water and then chopped into 2-3 cm lengths.

The cuttings were surface sterilized by washing with 70% ethanol (2 minutes) followed by a

wash with commercial bleach (5 minutes), and then washed 10 times with sterile distilled

water. Water from the last wash was plated on Tryptic Soy agar (TSA) to ensure no epiphytes

were selected. About 5-6 cuttings were macerated in 5 ml of sterile 0.03 M MgSO4 using an

autoclaved mortar and pestle, and kept in a laminar flow cabinet for 30 minutes at room

temperature. The macerate (100 µl) was serially diluted up to 10-3 using 900 µl of diluent

(0.03 M MgSO4) in each dilution tube, and 100 µl of each dilution was spread plated on half

strength Tryptic Soya agar (TSA) and Nutrient agar (NA), and on R2A agar medium. The

inoculated media were incubated for 3-5 days at 30°C. Dilutions were plated in replicates on

each growth medium.

The second approach was novel and involved selective isolation of endophytic bacteria from

rhizosphere of C. sativa using canola. About 1% rhizosphere soil was added to 50 ml half

strength tryptic soy broth (TSB). The inoculated broth was incubated at 30°C for 48 hours

with 150 rpm orbital shaking. About 1 ml of the resulting mixed culture was added to fresh

50 ml half strength TSB with 5% rhizospheric soil extracts and incubated under conditions

indicated earlier. The resulting mixed culture was washed twice with 0.03 M MgSO4 and

adjusted to an absorbance of 0.2 at 600 nm. Agricultural soil was autoclaved twice for one

hour at 120°C and 15 psi and added to plastic pots. The resulting soil was also plated on TSA

to ensure it contained no indigenous microbes. Canola seeds were surface sterilized and sown

in the autoclaved soil. The soil was then thoroughly drenched with bacterial culture

suspension prepared earlier. The pots were placed on a lab bench top and plants emerging

from the seeds were grown for 4 weeks to give them ample time to take up endophytic

bacteria from the enriched rhizobacterial pool. The plants were then uprooted, washed

thoroughly with tap water, reduced to 2-3 cm cuttings, and endophytic bacteria were isolated

as described earlier.

Chapter 2


2.2.3 Enumeration of endophytic bacteria

After 3-5 days incubation, several morphologically different colonies appeared on all the

above three types of media (TSA, R2A agar and NA). All the incubated plates were carefully

observed and the numbers of colonies were counted for each media plate, and finally bacteria

were enumerated as colony forming units per gram fresh weight (cfu/gfw) using the

following formula.

Plate

count

X

10 X Dilution

Factor X 50 ÷

Weight

of

roots

= cfu /

gfw

30-300

colonies

Cells in

1 ml of

dilution

Cells in

macerate

serially

diluted

Cells in

total

macerate

Grams

Cells

per

gram

root

tissue

2.2.4 Selection and storage of pure strains

Morphologically distinct bacterial colonies were selected from the isolation procedure on the

basis of color, shape, texture, size and gram reaction, The pure bacteria were maintained on

half strength TSA slants at 4°C.

2.2.5 Bacterial preservation in glycerol stock

Glycerol stocks are important for long-term storage of bacterial strains. Tryptic Soya broth

(TSB) medium was prepared and autoclaved for 20 minutes at 121°C. A pure bacterial

culture was inoculated into the broth using a wireloop, and the culture was incubated

overnight at 30°C. Next day, 700 µl of the overnight culture was mixed with 300 µl of 50%

glycerol solution (50% glycerol in 50% distilled water) in a cryovile. The prepared bacterial

glycerol stocks (15% glycerol) were immediately stored at -80°C.

2.2.6 In-vivo plant growth promotion assay

Bacterial isolates were examined for their ability to promote canola plants using gnotobiotic

roots elongation assay.

Chapter 2


2.2.6.1 Seed collection

Canola seeds were collected from National Agricultural Research Centre (NARC),

Islamabad.

2.2.6.2 Canola gnotobiotic root elongation assay

Canola seeds were surface sterilized by washing with 70% ethanol for 1 min and 20%

commercial bleach (1% NaOCl) for 10 min. Residual chemicals were removed by washing

10 times with sterile distilled water. Bacteria were grown in half strength TSB for 48 hours,

cells were harvested by centrifugation at 5000 rpm at 4°C and washed twice with 0.03 M

MgSO4 and resuspended to an absorbance of about 0.1±0.02 at 600 nm. The suspension was

used to treat the surface sterilized seeds for 1 hour at room temperature. The treated seeds

were placed in tubes containing 0.5% water agar (1 seed per tube and 18 tubes per treatment).

Surface sterilized seeds, treated with sterile 0.03 M MgSO4 were used as a negative control.

The tubes were placed at 25°C and 60% relative humidity in a plant growth chamber with 12

h light / dark cycles. The root lengths of plants were measured on day 5. The roots lengths of

top 12 plantlets (showing highest root length) per treatment were considered for further

analysis. Treated plant root lengths were compared to control plants by means of one way

ANOVA (p value ≤ 0.05) and Least Significant Difference (LSD) (pairwise comparison) at p

value = 0.05 using Statistix 8.1 software.

For testing growth promotion of canola by selected bacteria under salt stress, water agar was

supplemented with 25 mM NaCl in the gnotobiotic assay.

2.2.7 Confirmation of endophytic growth

Selected plant growth promoting bacteria were tested for their endophytic presence. Surface

sterilized seeds were treated with test bacteria as described before. The seeds were grown in

flasks containing Murashige and Skoog Basal Salt (Sigma-Aldrich M5524) medium

supplemented with 3% sucrose and 0.8% agar. Flasks were placed at 25°C and 60% relative

humidity in a plant growth chamber with 12 h light / dark cycles. Plantlets were harvested

after 2 weeks and surface sterilized by washing with 70% ethanol (30 seconds) and 1%

Chapter 2


commercial bleach (2 min) followed by 10 washes with sterile distilled water. To confirm the

sterilization process, water from the last wash was plated on TSA medium. The surface

sterilized plant (root and stem) were macerated and plated on TSA medium to confirm

presence of test bacteria.

2.2.8 Salt stress tolerance

Selected plant growth promoting bacteria were tested for their ability to tolerate different salt

concentration. For this, bacteria were grown in TSB in the presence of 0%, 1%, 2%, 3%, 5%,

7% and 10% NaCl concentration for 24 h at 30°C. Bacterial growth was measured by taking

absorbance at 600 nm using uninoculated broth as blank.

2.2.9 In-vitro plant growth promotion assays

The isolated endophytic bacteria were analyzed for different traits consistent with plant

growth promotion, plant colonization and biocontrol of phytopathogens. The details are as

under.

2.2.9.1 Indole acetic acid production

Calorimetric estimation method (modified) was used to evaluate the indole acetic acid (IAA)

production by endophytic bacteria proposed by Gordon and Weber (1951). For this, bacteria

were used for inoculating into 5 ml of TSB with and without tryptophan (200 μg/ml).

Incubation was done at 30˚C for 24 hours. After incubation, cultures were centrifuged for 10

minutes at 10,000 rpm and supernatants were shifted to new tubes. For estimating the amount

of IAA produced by the bacteria, one part of supernatant was mixed with 2 parts of

Salkowski reagent. For control (blank), uninoculated broth was used in place of supernatant.

The resulting mixture was left for incubation at room temperature for 25 minutes. Strains

capable of producing indole acetic acid developed pink color that was analyzed at 535 nm

using a spectrophotometer (UV3000 spectrophotometer), where the control reaction was used

as spectrophotometer blank. Amount of IAA produced by individual strains was evaluated

using a standard curve of IAA as described below. Experiment was performed in duplicate

and values were averaged.

Chapter 2


2.2.9.1.1 Standard curve of IAA

IAA stock solution (5 µg/ml) was prepared by dissolving IAA (0.001 grams) in

2% ethanol solution (200 ml). The stock was twofold serially diluted up to 0.313 µg/ml by

mixing 1 part sample with 1 part diluent. Then, one part of each dilution was mixed with 2

parts of Salkowsky reagent. The mixtures were incubated at room temperature for 25

minutes. The resulting reaction was analyzed at 535 nm using a spectrophotometer (Gordon

and Weber, 1951). The process was performed in duplicate. IAA concentrations and their

corresponding absorbance (average of two replicates) were plotted in a graph using Microsoft

Excel program (Figure 2.1).

Figure 2.1 Standard curve of Indole Acetic Acid

Finally, the concentration of IAA produced by individual strains was calculated using the

following formula generated using a standard curve.

IAA produced (µg/ml) = (Sample Absorbance + 0.004) ÷ (0.0369)

2.2.9.2 Phosphate solubilization

The tri-calcium phosphate containing minimal medium was used to qualitatively

measure of bacterial phosphate solubilization (Kuklinsky-Sobral et al., 2004). The bacteria

y = 0.0369x - 0.004R² = 0.9992

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

0 1 2 3 4 5 6

Ab

sorb

ance

(5

35

nm

)

IAA concetration (µg/ml)

Chapter 2


capable of solubilizing mineral phosphate can produce a clear zone around them on the milky

white media. An overnight bacterial culture was spot inoculated on the test media. The

inoculated media was incubated for 2-3 days at 30˚C. Zone of clearing around the colonies

was used to identify phosphate solubilizing bacteria. Zones of clearing (cm) produced by

bacteria were converted into three categories (large, >1.0 cm; medium 0.5-1 cm; small, <0.5

cm) for plotting them in graph.

2.2.9.3 Siderophore production

Ability of the bacteria to produce siderophore was determined qualitatively using a modified

approach of Pérez-Miranda et al. (2007) based on chrome-Azurol S (CAS) based agar

medium (Schwyn and Neilands, 1987). The CAS medium (1L) prepared by mixing Chrome

Azurol S (CAS) 60.5 mg, 72.9 mg, Piperazine-1,4-bis (2- ethanesulfonic acid) (PIPES) 30.24

g, and 1 mM FeCl3·6H2O in 10 mM HCl 10 mL. Agarose (0.9%, w/v) was used as gelling

agent. Siderophores detection was achieved after 10 ml overlays of this medium were applied

over TSA media (supplemented with 50 µg/ml of 8-Hydroxyquinoline) plates with overnight

grown bacteria. After 15 minutes, a change in color in the overlaid medium confirmed

siderophore producer by microorganisms, where blue to purple indicated catechol type

siderophores, and blue to orange indicated hydroxamate type siderophores. All these

experiments were performed in triplicate.

2.2.10 Plant cell-wall degrading enzymes

Isolated bacteria were examined for the ability to produce plant cell-wall targeting Cellulase

and Pectinase using qualitative assays.

2.2.10.1 Cellulase activity

In order to determine the Cellulase activity of the selected bacterial strains, all the strains

were processed in triplicates. Cellulase activity of the bacterial strains was analyzed by

Hendricks et al. (1995) method. For this, cellulose-Congo red agar was prepared and

autoclaved at 121ºC for 20 minutes. After autoclaving the media was cooled and poured into

plates. The isolates were inoculated on the media plates and incubated at 30ºC for 3-5 days.

After incubation, Cellulase activity was confirmed by identifying zone of clearing around the

Chapter 2


bacteria. The test was performed in triplicate. Zones of hydrolysis (cm) produced by bacteria

were converted into three categories (large, >1.0 cm; medium 0.5-1 cm; small, <0.5 cm) for

plotting them in graph.

2.2.10.2 Pectinase activity

Pectin containing minimal media was used to identify pectinase producing bacteria (Hankin

et al., 1971). Overnight grown bacteria were inoculated on the media plates and incubated at

30ºC for 3-5 days. The zones of hydrolysis of pectin around bacterial colonies were

visualized by flooding culture plates with iodine solution (Ouattara et al., 2008). The

experiment was performed in triplicate. Zones of hydrolysis (cm) produced by bacteria were

converted into three categories (large, >1.0 cm; medium 0.5-1 cm; small, <0.5 cm) for


2.2.11 Fungal cell-wall degrading enzymes

Isolated bacteria were examined for the ability to produce fungal cell-wall targeting Protease

and Chitinase using qualitative assays.

2.2.11.1 Protease activity

The protease activity of selected bacterial strains was determined using skim milk agar

medium of Bibi et al. (2012). For this, full strength medium TSA was prepared first. Then, in

another flask 2% (w/v) of skimmed milk was dissolved in distilled water equal in volume to

that of TSA. Both preparations were autoclaved at 121ºC for 20 minutes. After autoclaving,

TSA and skimmed milk preparations were mixed together to produce half strength TSA

containing 1% skimmed milk. The media was poured in to sterile petri plates. The test

bacteria were spot inoculated on the media. Cultures were then placed in an incubator at 30ºC

for 2 days. Protease activity was confirmed by the appearance of zones of clearing around the

colonies. Test was performed in triplicate. Zones of hydrolysis (cm) produced by bacteria

were converted into three categories (large, >1.0 cm; medium 0.5-1 cm; small, <0.5 cm) for


Chapter 2


2.2.11.2 Chitinase activity

Chitinase activity was tested by using chitinase screening media containing chitin (Bibi et al.,

2012). Chitinase media was prepared by adding 0.6% w/v colloidal chitin to half strength

TSA. Colloidal chitin was prepared by adding 2 grams of crab chitin in 100 ml of

Hydrochloric acid and left for 24 hours at 4ºC in a refrigerated orbital shaker incubator at 150

rpm. After incubation, about 2 liter of sterile distilled water was added to the mixture and left

overnight at 4ºC. Supernatant was then removed carefully and the remaining solution

containing the precipitates was filtered followed by washing of precipitates thoroughly with

sterile distilled water to neutralize the pH of resulting colloids. The colloidal chitin prepared

was used for media preparation. The media was autoclaved and poured in sterilized petri

plates. Bacteria were inoculated on media plates and incubated for 5 days at 30º C. Chitinase

production was detected by the appearance of clear zones around the bacteria. The tests were

performed in triplicate. Zones of hydrolysis (cm) produced by bacteria were converted into

three categories (large, >1.0 cm; medium 0.5-1 cm; small, <0.5 cm) for plotting them in

graph.

2.2.12 Antifungal Activity

To test the antifungal potential of the bacteria, Fusarium oxysporum (accession no: 1114) and

Aspergillus niger (accession no: 1109) were obtained from the Fungal Culture Bank,

University of the Punjab, Lahore. Dual culture method was used for this purpose by

inoculating bacteria on the sides and the test fungi in the center of agar medium containing

1:1 ratio of potato dextrose agar (PDA) and TSA (Kumar et al., 2012). Culture plates were

incubated at 30°C for 5-7 days and bacterial colonies antagonizing fungal growth were

identified by presence of zone of inhibition at the point of interaction. The test was performed

in triplicate.

2.2.13 Molecular identification of endophytic bacterial

Bacterial isolates were identified based on their 16S rRNA gene sequence. For this, the test

bacteria were propagated on TSA by incubating at 30°C for 24 hours. The bacteria were then

processed for genomic DNA extraction, followed by PCR amplification of 16S rRNA gene,

Chapter 2


purification of the PCR product, sequencing of the PCR product, and analyses of resulting

sequences for identification of bacteria.

2.2.13.1 Bacterial genomic DNA extraction

Purified bacterial colonies were processed for genomic DNA isolation. Each colony was

carefully transferred to a PCR tube with the help of sterilized loop and 100 μl of lysis buffer

was added to each tube and the contents were thoroughly mixed. Lysis buffer (2 ml) was

prepared by mixing 1.75 ml nuclease free water, 200 μl 10% Triton X-100, 40 μl 1M Tris

HCl (pH 8.0) and 8 μL 0.5 M of EDTA (pH 8.0). For each reaction/cell lysis we used 100 μl

of this buffer. PCR tubes containing the mixture were heated at 95°C for 10 minutes in

thermocycler followed by centrifugation at 14000 rpm for 10 minutes to pellet the cell debris.

The supernatant containing genomic DNA was collected and stored at -20°C for further

processing.

2.2.13.2 PCR amplification of 16S rRNA gene

Supernatant (containing genomic DNA) collected from above procedure was used as a

bacterial template for PCR reaction. Bacterial 16S rRNA gene was amplified using the

universal primers 27F (5'-AGAGTTTGATCCTGGCTCAG-3') and 1492R (5'-

GGTTACCTTGTTACGACTT-3'), as proposed by Weisburg et al. (1991). PCR reaction

mixture (50 µL) was prepared containing 0.3 µM of forward and reverse primers, about 4 µL

template DNA and 1×GoTaq® Green Master Mix (Promega, USA) in PCR grade water. PCR

amplification was performed with initial denaturation at 94°C for 5 minutes, followed by 30

cycles of denaturation (94°C for 30s), annealing (55°C for 30s) and extension (72°C for 1

minute) with a final extension at 72°C for 10 min.

2.2.13.3 Confirmation of PCR product using Agarose Gel electrophoresis

The resulting PCR product (approximately 1500 bp) was visualized on 1% agarose gel

containing ethidium bromide and compared to a 1 kb ladder (ThermoFisher Scientific, USA)

for size confirmation. For this, about 1 g agarose (Fisher Scientific, USA) was dissolved in

1×TAE buffer and heated in microwave oven for mixing. The gel was cooled down and then

Chapter 2


50 μl of 10 mg/ml ethidium bromide (ThermoFisher Scientific, USA) was added and mixed,

and the gel was casted in the electrophoresis tray with the fitted comb. After casting, the tray

containing gel was shifted to electrophoresis chamber containing the 1×TAE buffer. The gel

was completely submerged in the tank buffer. About 3 μl of amplified DNA samples were

mixed with 1 μl 6× loading dye (ThermoFisher Scientific, USA) and loading into the wells of

the gel. The first well was loaded with a 1 kb ladder (ThermoFisher Scientific, USA) to verify

correct size amplicons. The power supply was connected and the electrophoresis was

performed at a constant voltage of 5 V/cm for 40 minutes. The DNA bands were analyzed

using Gel Doc System (Dolphin-Doc Plus, Wealtec Bioscience).

2.2.13.4 PCR product purification

PCR products were purified using PureLink PCR Purification Kit (Invitrogen, USA)

according to provided instructions. For this, Binding Buffer B2 containing isopropanol (4

parts) was mixed with PCR product (1 part). The contents were transferred to Spin Column in

a collection tube. The tubes were centrifuged 10,000×g for 1 minute at room temperature.

The resulting flow through was discarded. Then, about 650 μL of Wash Buffer with ethanol

was added to the column containing the bound amplified DNA. The tube was again

centrifuged 10,000×g for 1 minute and the flow through was discarded. The tubes were then

centrifuged at maximum speed at room temperature for 2-3 minutes to remove any residual

Wash Buffer to the column. The columns were then shifted to Elution Tube. Then, about 50

μL of Elution Buffer was added to the columns, which were then incubated at room

temperature for 1 minute. The tubes were centrifuged at maximum speed to elute the PCR

amplified DNA. The purified DNA was confirmed by agarose gel electrophoresis as

described above and stored at -20°C for further processing.

2.2.13.5 16S rRNA gene sequencing

For sequencing of 16S rRNA gene, the purified PCR products of amplified 16S rRNA gene

were sent to Macrogen, Inc. (South Korea).

Chapter 2


2.2.13.6 16S rRNA gene sequences analysis

The sequences were analyzed for their quality using BioEdit v7.0.5 program and trimmed.

The trimmed sequences were used to identify bacteria using Basic Local Alignment Search

Tool (BLAST) search tool against the GenBank database available at the National Center for

Biotechnology Information Search database (NCBI; https://www.ncbi.nlm.nih.gov/) website.

The bacteria were identified based on their maximum score and percentage similarity (≥99%)

with other GenBank bacterial accession. For determining bacterial similarity with type

strains, Eztaxon server version 2.1 was used (http://www.ezbiocloud.net/; Kim et al., 2012b).

The sequences of the identified bacteria were deposited at GenBank.

2.2.14 Phylogenetic analysis of endophytic bacteria

The evolutionary linkages among the isolates were assessed through phylogenetic analysis.

For this, multiple alignments were first performed for the 16S rRNA gene sequences of the

isolates using ClustalXv2.1. The aligned sequences were then constructed into a phylogenetic

tree based on Neighbor-Joining method (Bootstrap using 500 replicates) using MEGA5

software.

2.3 Results

The present investigation was carried out for the isolation, screening and characterization of

endophytic bacterial strains from Cannabis sativa. The bacteria were isolated using two

different approaches, and were identified and analyzed for different traits consistent with

plant growth promotion, plant invasion and biocontrol of phytopathogenic fungi. The details

of the results are as follows:

2.3.1 Isolation of endophytic bacteria

After enumeration of isolated bacteria, a total of 34 bacterial colonies were selected on the

basis of colony size, morphology, color, shape and growth pattern (Figure 2.2). Out of 34

morphologically distinct bacteria isolated from C. sativa, sixteen were directly isolated from

the surface sterilized roots, and eighteen were selectively isolated from the enriched

rhizosphere bacteria using canola plants. From both the sources, highest cell counts were on

Chapter 2


R2A agar (Direct isolation, 8×107 cfu/gfw; Selective isolation, 6 × 104 cfu/gfw) followed by

TSA (Direct, 3×106 cfu/gfw; Selective, 4.9×104 cfu/gfw) and NA (Direct, 1×106 cfu/gfw;

Selective, 8×103 cfu/gfw). Moreover, bacteria cells recovered were more in case of direct

isolation compared to selective isolation (Table 2.1). Morphologically similar bacteria

isolated from the two sources were considered among the isolates from C. sativa roots. These

selected colonies were further purified by repeated sub culturing.

Figure 2.2 Plate showing growth of isolated endophytic bacteria

Table 2.1 Number of bacterial isolates recovered from two isolation procedures along with average

cell counts recovered on three growth media.

Source Direct Isolation Selective isolation

Total bacteria isolates 16 18

TSA 3×106 cfu/gfw 4.9×104 cfu/gfw

R2A 8×107 cfu/gfw 6×104 cfu/gfw

NA 1×106 cfu/gfw 8×103 cfu/gfw

2.3.2 Identification of endophytic bacteria

Bacteria were identified based on their 16S rRNA gene sequence. For this, genomic DNA

was extracted from overnight grown bacteria and was used as a template in the PCR reaction.

PCR amplification of the 16S rRNA gene of isolates, using 27F and 1492R universal primers,

Chapter 2


yielded a product close to 1500 bp (Figure 2.3). PCR amplicons were sequenced

commercially and sequence quality was analyzed using BioEdit program. The sequencing

electropherogram revealed that all sequences were clean and of good quality (Figure 2.4).

The resulting partial sequences were used to identify the endophytic isolates using GenBank

and Eztaxon databases.

Figure 2.3 Agarose gel electrophoresis of PCR amplified 16S rRNA gene of bacterial isolates. First

lane, 1 kb DNA ladder; second lane, negative control; third lane, positive control; lanes 1, 2, 3, 4, 5, 6,

7 and 8 PCR amplified DNA of ~1465bp size.

Figure 2.4 Electropherogram of 16S rRNA gene from bacterial isolate MOSEL-w2.

Results from GenBank and Eztaxon analysis revealed that a diversity of bacterial genera were

isolated from the two isolation methods, where the most prominent genera were

Chapter 2


Acinetobacter, Chryseobacterium, Enterobacter, Microbacterium, Nocardioides,

Paenibacillus Pseudomonas, Stenotrophomonas. The direct method isolated 13 unique

bacterial genera while selective method isolated 11 genera (Figure 2.5 and 2.6).

Figure 2.5 Percentage of endophytic bacterial genera obtained from C. sativa using direct isolation

method

Figure 2.6 Percentage of endophytic bacterial genera obtained from C. sativa using selective isolation

Most of the isolates shared more than 99% homology to the closest type strain based on the analysis

of EzTaxon server. However, four isolates (MOSEL-w4, MOSEL-p22, MOSEL-w2.5 and MOSEL-

r15) shared about 98% similarity, while MOSEL-w13 and MOSEL-n5 shared about 97% similarity to

the closest type strain. Further, all isolates shared 99-100% similarity to a GenBank submission,

analyzed using BLAST program. The 16S rRNA gene sequences of identified endophytic bacteria

have been deposited at GenBank database, where each submission has been given a unique accession

number (Table 2.2 and 2.3).

0

5

10

15

20

25P

erce

nta

ge

0

5

10

15

20

Per

cen

tage

Chapter 2


Table 2.2 Identification of endophytic bacteria resulting from selective isolation method based on the

partial 16S rRNA gene sequence. GenBank match similarity was ≥99% for all isolates while their


Strain

(MOSEL) GenBank closest match

EzTaxon closest match

(type strain)

Similarity

(%)

Genbank

accession

w4 Chryseobacterium sp. YU-SS-

B-43

Chryseobacterium

indologenes LMG 8337 98.57 KF307668

p22 Bacterium 1A5 Chryseobacterium tructae

1084-08 98.49 KF307670

w15 Curtobacterium sp. EP_L_2 Curtobacterium

flaccumfaciens LMG 3645 100 KF307671

p6 Enterobacter hormaechei

strain SR3

Enterobacter cancerogenus

LMG 2693 99.62 KF307674

w7 Enterobacter cloacae strain

RM20

Enterobacter cloacae subsp.

dissolvens LMG 2683 99.81 KF307675

w12 Exiguobacterium acetylicum

strain ZYJ-7

Exiguobacterium indicum

HHS31 99.62 KF307677

w2.16 Microbacterium sp. ZL2 Microbacterium

ginsengiterrae DCY37 99.14 KF307678

w2.5 Microbacterium sp. Am3 Microbacterium natoriense

TNJL143-2 98.86 KF307679

w2.1 Microbacterium sp. THG S3-

10

Microbacterium

phyllosphaerae DSM 13468 99.52 KF307680

w13 Paenibacillus sp. 512(2014) Paenibacillus hunanensis

FeL05 97 KF307683

w1 Paenibacillus sp. BL14 Paenibacillus tundrae A10b 99.14 KF307684

w6 Pantoea anthophila strain L8-

457

Pantoea anthophila LMG

2558 99.52 KF307685

w16 Paracoccus marcusii strain

BF13-3

Paracoccus marcusii DSM

11574 99.62 KF307687

tnc1 Pseudomonas geniculata strain

R6-798

Pseudomonas geniculata

ATCC 19374 99.71 KF307689

tnc2 Pseudomonas sp. DT1 Pseudomonas koreensis Ps

9-14 99.9 KF307691

p18 Pseudomonas plecoglossicida

S20411

Pseudomonas

plecoglossicida FPC951 100 KF307693

w2 Serratia marcescens strain

MUGA199

Serratia marcescens subsp.

sakuensis KRED 99.9 KF307696

tnc3 Stenotrophomonas rhizophila

strain HR89

Stenotrophomonas

rhizophila e-p10 99.62 KF307697

2.3.3 Phylogenetic Analysis

Evolutionary relatedness of the endophytic bacterial isolates was determined based on

their 16S rRNA gene sequences. For this, sequences were first aligned with ClustalX v2.1

and a phylogenetic tree was constructed using Mega5 software. The results revealed that all

bacteria significantly promoting canola root growth (MOSEL-t13, MOSEL-t15, MOSEL-p6,

Chapter 2


MOSEL-tnc1, MOSEL-tnc2, MOSEL-tnc3, MOSEL-w2, MOSEL-w7) clustered together

(100% Bootstrap value). The isolates belonged to genera Enterobacter, Pantoea,

Pseudomonas, Serratia, and Stenotrophomonas (Figure 2.7). Since all the members included

in a single cluster are phylogenetically related, the present result indicates that the ability to

promote plant growth is evolutionarily conserved in the endophytic bacteria.

Table 2.3 Identification of endophytic bacteria resulting from direct isolation method based on the

partial 16S rRNA gene sequence. GenBank match similarity was ≥99% for all isolates while their


Strain ID

(MOSEL) GenBank closest match EzTaxon closest match

Similarity

(%)

Genbank

accession

r2 Acinetobacter sp. SZ-1 Acinetobacter gyllenbergii

1271 99.44 KF307663

n6 Acinetobacter sp. R4-413 Acinetobacter

nosocomialis LMG 10619 99.62 KF307664

t7 Acinetobacter gyllenbergii

A207

Acinetobacter parvus DSM

16617 99 KF307665

r8 Acinetobacter oleivorans

strain Z-A18

Acinetobacter pittii LMG

1035 99.33 KF307666

r4 Bacillus anthracis strain UM-

5

Bacillus anthracis ATCC

14578 100 KF307667

n5 Chryseobacterium

kwangjuense strain KJ1R5

Chryseobacterium

vrystaatense LMG 22846 97.28 KF307669

t15 Bacterium OX_LEAF4 Enterobacter asburiae

JCM 6051 99.43 KF307672

r7 Enterococcus casseliflavus

strain ALK061

Enterococcus casseliflavus

CECT969 99.52 KF307676

r13 Nocardioides albus Nocardioides albus KCTC

9186 99.52 KF307681

r15 Bacterium 405 Nocardioides kongjuensis

A2-4 98.67 KF307682

t13 Pantoea agglomerans strain

PGHL1

Pantoea vagans LMG

24199 99.81 KF307686

n9 Planomicrobium chinense

strain L10-2

Planomicrobium chinense

DX3-12 99.71 KF307688

t14 Pseudomonas putida strain

CSM10

Pseudomonas taiwanensis

BCRC 17751 99.78 KF307694

n12 Agrobacterium tumefaciens

strain R6-409

Rhizobium radiobacter

ATCC 19358 99.43 KF307695

n11 Streptomyces werraensis

strain 1165

Streptomyces eurocidicus

NRRL B-1676 99.52 KF307698

r5 Xanthomonas arboricolapv.

pruni strain BCRC80481

Xanthomonas gardneri

ATCC 19865 100 KF307699

Chapter 2


Figure 2.7 Phylogenetic tree of endophytic bacteria from C. sativa (direct and selective isolation)

constructed with 16S rRNA gene sequences using the Neighbour-Joining method. Branch points show

bootstrap percentages (500 replicates). Bar 0.02 indicates changes per nucleotide position. Cluster

enclosed in red box contains isolates significantly promoting canola growth.


The isolates were examined for Cellulase and Pectinase production using qualitative tests

(Figure 2.8). All bacteria isolated from canola plants possessed Cellulase activity, and with

the exception of MOSEL-tnc3, all isolates also showed a positive pectinase activity. Most

isolates (88%) from C. sativa roots were also Cellulase positive, with the exception of

Chapter 2


MOSEL-t7 and MOSEL-r7. While, only nine isolates (56%) were found to possess Pectinase

activity (Figure 2.9 and 2.10).

Figure 2.8 Pectinase (left) and Cellulase (right) activity of four bacterial isolates on Pectin and

Cellulose (CMC) containing medium.

Overall, some isolates showed a more pronounced Cellulase (MOSEL-w4, MOSEL-w12,

MOSEL-w13, MOSEL-tnc1, MOSEL-tnc3 and MOSEL-n5) and pectinase (MOSEL-w12,

MOSEL-w2.5, MOSEL-w13, MOSEL-w1, MOSEL-r13 and MOSEL-n11) activity than

others based on the size of zone of hydrolysis produced on respective media. Moreover, most

of the isolates possessed similar levels of Cellulase and Pectinase activity. Isolates with

pronounced activity were more abundant in the bacteria isolated from canola. Finally,

MOSEL-t7 and MOSEL-r7, isolated from the C. sativa roots, were the only two isolates

lacking both Cellulase and Pectinase activities.

2.3.5 Nutrient availability

Bacterial isolates were assessed for their ability to facilitate phosphorus and iron availability

for plant host. In the qualitative assay of phosphate solubilization (Figure 2.11), eight isolates

(44%) from canola solubilized tri-calcium phosphate. Such isolates were more abundant

(56%) in bacteria isolated from roots of C. sativa, and displayed more noticeable activity

apparent from larger halos formed around their colony. Overall, MOSEL-p6, MOSEL-t13

and MOSEL-t15 possessed the highest mineral phosphate solubilization ability (Figure 2.12

and 2.13). Moreover, thirteen isolates (72%) from canola produced siderophore, apparent

from the change in color of overlaid medium from blue to purple or orange by the bacteria

after incubation, while only nine isolates (56%) from C. sativa roots were siderophore

producers (Table 2.4 and 2.5).

Chapter 2


Figure 2.9 Cellulase (blue bars) and Pectinase (orange bars) assay of endophytic bacteria isolated

from C. sativa using direct isolation. Values of zones of hydrolysis produced by bacteria have been

organized into three categories based on the size: 3, large (>1.0 cm); 2, medium (0.5-1 cm); 1, small

(<0.5 cm).


from C. sativa using selective isolation. Values of zones of hydrolysis produced by bacteria have been

organized into three categories: 3, large (>1.0 cm); 2, medium (0.5-1 cm); 1, small (<0.5 cm).

2

1 1

2

3

1

2

1 1

2

1 1

2

11

2 2

1

3

1 1

3

2

3

2

1 1 1

3

2 2

1

3

1 1 1

3

2

1

2

3

2 2

1 1 1

3

2

3

2

3 3

1 1 1 1

2

1

Chapter 2


Figure 2.11 Mineral phosphate solubilization activities of four bacterial isolates on insoluble mineral

phosphate containing medium.

Figure 2.12 Mineral phosphate solubilization activity of bacteria isolated from C. sativa using direct

isolation. Values of zones of hydrolysis produced by bacteria have been organized into three

categories: 3, large (>1.0 cm); 2, medium (0.5-1 cm); 1, small (<0.5 cm).

2.3.6 Fungal cell-wall degrading enzyme

The bacterial isolates were tested for their Chitinase and Protease production ability using

qualitative tests. Three isolates from canola (16%) showed positive chitinase activity

(MOSEL-w2, MOSEL-13, and MOSEL-tnc3), forming clear halos around them on chitin

containing medium, while only MOSEL-r4 from C. sativa root showed positive activity. In

2 2 2

1

3

1

3

2

1 1

Chapter 2


protease activity analysis, ten isolates (55%) from canola and seven (43%) from C. sativa root

were able to hydrolyze milk casein to produce zone of clearing on the test medium (Figure

2.14). Overall, four isolates, MOSEL-w2, MOSEL-w13, MOSEL-tnc3 and MOSEL-r4,

possessed both chitinase and protease activity (Table 2.4 and 2.5).

Figure 2.13 Mineral phosphate solubilization activity of bacteria isolated from C. sativa using

selective isolation. Values of zones of hydrolysis produced by bacteria have been organized into three

categories: 3, large (>1.0 cm); 2, medium (0.5-1 cm); 1, small (<0.5 cm).

Figure 2.14 Protease activity of bacteria isolated from C. sativa using selective isolation. Values of

zones of hydrolysis produced by bacteria have been organized into three categories: 3, large (>1.0

cm); 2, medium (0.5-1 cm); 1, small (<0.5 cm).

3

1 1 1 1

2

1

2

Chapter 2


2.3.7 Antifungal Assay

Antifungal activity of the bacterial isolates against phytopathogenic fungi was examined

using dual culture assay (Figure 2.15). Four isolates from selective isolation (MOSEL-w2,

MOSEL-w7, MOSEL-w13 and MOSEL-tnc3) were effective against both A. niger and F.

oxysporum, while MOSEL-tnc2 was effective against A. niger only. Among the isolates from

C. sativa roots, MOSEL-r4, MOSEL-t14 and MOSEL-r5 were effective against both the test

fungi, whereas MOSEL-t13 and MOSEL-t15 were effective against F. oxysporum and A.

niger, respectively. Overall, MOSEL-w13 possessed the most prominent antifungal activity

against the two test fungi (Table 2.4 and 2.5).

Figure 2.15 Dual culture antifungal assay of five selected endophytic bacteria against

Aspergillus niger (left) and Fusarium oxysporum (right)

2.3.8 Production of IAA

All isolates were able to produce IAA like molecule. The amount of IAA produced ranged

from 0.2-5.1 µg/ml in the absence of tryptophan, the precursor of IAA. MOSEL-r8 (5.1

µg/ml) produced the highest amount of IAA among all the isolates followed by MOSEL-w16

(3.9 µg/ml) and MOSEL-w2 (3.02 µg/ml). Ability of the isolates to produce IAA was

increased by 1.5 to 4 fold in the presence of tryptophan (200 µg/ml). After supplementation

with tryptophan, maximum IAA production was observed for MOSEL-n2 (13.2 µg/ml)

followed by MOSEL-r8 (10 µg/ml) and MOSEL-t13 (7.7 µg/ml) (Figure 2.16 and 2.17).

Chapter 2


Table 2.4 Protease production (PRO), Chitinase production (CHI), Siderophore production (SID),

Anti-Aspergillus niger (AN), and anti Fusarium oxysporum (FO) activities of endophytic bacteria

isolated from C. sativa using direct isolation.

Isolate PRO CHI SID AN FO

Acinetobacter gyllenbergii MOSEL-r2 + - - - -

Acinetobacter nosocomialis MOSEL-n6 - - + - -

Acinetobacter parvus MOSEL-t7 - - - - -

Acinetobacter pittii MOSEL-r8 - - - - -

Bacillus anthracis MOSEL-r4 +++ + + + +

Chryseobacterium sp. MOSEL-n5 ++ - + - -

Enterobacter asburiae MOSEL-t15 - - - + -

Enterococcus casseliflavus MOSEL-r7 + - - - -

Nocardioides albus MOSEL-r13 ++ - + - -

Nocardioides kongjuensis MOSEL-r15 - - + - -

Pantoea vagans MOSEL-t13 - - + - +

Planomicrobium chinense MOSEL-n9 - - - - -

Pseudomonas taiwanensis MOSEL-t14 + - + + +

Rhizobium radiobacter MOSEL-n12 - - - - -

Streptomyces eurocidicus MOSEL-n11 - - + - -

Xanthomonas gardneri MOSEL-r5 + - + + +

(+), activity present; (-), activity absent; (+), smaller halos around colonies (<0.5 cm); (++), medium

halos around colonies (0.5-1 cm); (+++), large halos around colonies (>1.0 cm).


Bacterial isolates were examined for their ability to promote the growth of canola plants

using gnotobiotic roots elongation assay in water agar. Selected growth promoting bacteria

were also analyzed for growth promotion of salt stressed canola plants using the same assay.

Chapter 2


Table 2.5 Protease production (PRO), Chitinase production (CHI), Siderophore production (SID),

Anti-Aspergillus niger (AN), and anti Fusarium oxysporum (FO) activities of endophytic bacteria

isolated from C. sativa using selective isolation.

Isolate PRO CHI SID AN FO

Chryseobacterium sp. MOSEL- w4 ++ - + - -

Chryseobacterium sp. MOSEL-p22 ++ - - - -

Curtobacterium flaccumfaciens MOSEL-w15 + - + - -

Enterobacter cancerogenus MOSEL-p6 - - - - -

Enterobacter cloacae MOSEL-w7 - - - + +

Exiguobacterium indicum MOSEL-w12 ++ - + - -

Microbacterium ginsengiterrae MOSEL-w2.16 - - - - -

Microbacterium sp. MOSEL-w2.5 ++ - + - -

Microbacterium phyllosphaerae MOSEL-w2.1 - - - - -

Paenibacillus sp. MOSEL-w13 +++ ++ + + +

Paenibacillus tundrae MOSEL-w1 - - + - -

Pantoea anthophila MOSEL-w6 - - + + -

Paracoccus marcusii MOSEL-w16 - - + - -

Pseudomonas geniculata MOSEL-tnc1 ++ - + - -

Pseudomonas koreensis MOSEL-tnc2 + - + + -

Pseudomonas plecoglossicida MOSEL-p18 - - + - -

Serratia marcescens MOSEL-w2 ++ +++ + + +

Stenotrophomonas rhizophila MOSEL-tnc3 ++ + + + +

(+), activity present; (-), activity absent; (+), smaller halos around colonies (<0.5 cm); (++), medium

halos around colonies (0.5-1 cm); (+++), large halos around colonies (>1.0 cm).

2.3.9.1 Canola gnotobiotic root elongation

Ability of the isolates to confer growth benefit on canola was assessed using gnotobiotic

assay in water agar and roots were measured after 5 days (Figure 2.18). The bacteria isolated

from two approaches performed differently in the assay. Isolates from canola were much

Chapter 2


better in the growth promoting ability, where six isolates significantly enhanced root lengths

of the test plant (Least significant difference; p ≤ 0.05). However, the performance of the six

isolates did not differ significantly from each other. On an average, MOSEL-w7 (29.2%

increase), MOSEL-tnc1 (31.41%) and MOSEL-w2 (32.15%) produced longer root lengths

than MOSEL-p6 (17.39%), MOSEL-tnc2 (19.6%) and MOSEL tnc3 (16.28%). On the other

hand, only two isolates from C. sativa roots significantly enhanced root length of test plant,

where MOSEL-t13 (38.63%) performed better than MOSEL-t15 (16.97%). However, their

performance also did not vary significantly compared to each other, or compared to the six

isolates from canola (Figure 2.19 and 2.20).

Figure 2.16 IAA production by bacteria isolated from C. sativa using direct isolation (Blue bars,

without tryptophan; Orange bars, with tryptophan). Values represent mean of three replicates.

2.3.9.2 Confirmation of endophytic presence

The eight growth promoting bacteria were analyzed to confirm their endophytic presence in

bacterized canola plants grown in plant culturing media. All eight bacteria were recovered

from the surface sterilized canola plants inoculated with these bacteria, indicating their

endophytic presence. The endophytic bacterial counts were between 103-104 cfu/gfw of plant.

0

2

4

6

8

10

12

14

16

IAA

pro

du

ced

(µ

g/m

l)

Chapter 2


Figure 2.17 IAA production by bacteria isolated from C. sativa using selective isolation (Blue bars,

without tryptophan; Orange bars, with tryptophan). Values represent mean of three replicates.

Figure 2.18 Root elongation of canola by three selected growth promoting bacteria under gnotobiotic

conditions. Scale indicates values in centimeters.

0

1

2

3

4

5

6

7

8

IAA

pro

du

ced

(µ

g/m

l)

Chapter 2


Fig. 2.19 Canola gnotobiotic root elongation assay of endophytic bacteria isolated from C. sativa

roots using direct isolation. Each bar represents mean root length (±SE, n=12) of five day old plantlets

treated with sterile 0.03 M MgSO4 (Control) or bacterial suspension in 0.03 M MgSO4 (0.1±0.02 OD

at 600 nm). Green bars represent isolates significantly increasing root length and red bars significantly

decreasing root length compared to control (Least significant difference, p ≤ 0.05).

Fig. 2.20 Canola gnotobiotic root elongation assay of endophytic bacteria isolated from C. sativa

rhizosphere by selective isolation using canola. Each bar represents mean root length (±SE, n=12) of

five day old plantlets treated with sterile 0.03 M MgSO4 (Control) or bacterial suspension in 0.03 M

MgSO4 (0.1±0.02 OD at 600 nm). Green bars represent isolates significantly increasing root length

compared to control (Least significant difference, p ≤ 0.05).

5

6

7

8

9

10

11

12

13

14

Root

len

gth

(cm

)

5

6

7

8

9

10

11

12

13

Root

Len

gth

(cm

)

Chapter 2


2.3.9.3 Canola gnotobiotic root elongation under salt stress

Three prominent plant growth promoting bacteria, MOSEL-tnc1, MOSEL-w2 and MOSEL-

t13 were also tested for their ability to ameliorate the inhibitory effects NaCl on canola

(Figure 2.21). Under 125 mM NaCl stress, plants showed stunted growth compared to non-

stressed plants, and under stress condition, plants treated with MOSEL-t13 and MOSEL-tnc1

produced significantly longer roots then non-bacterized plants(LSD; p ≤ 0.05). MOSEL-w2

treated plants also produced longer roots then control plants although the difference was

insignificant. Overall, bacterized plants showed better growth compared to non-bacterized

plants (Figure 2.22).

Figure 2.21 Root elongation of canola by three selected growth promoting bacteria under gnotobiotic

condition and 125 mM NaCl stress. Scale indicates values in centimeters.

2.3.10 Growth under salt stress

The three bacteria tested for salt tolerance were able to grow under most salt concentrations

tested. MOSEL-w2 (Turbidity 0.265±0.01) appeared to be most salt tolerant at 7% NaCl

followed by MOSEL-t13 (0.185±0.01) and MOSEL-tnc1 (0.08±0.01). At 10% salt

concentration, only MOSEL-w2 (0.05±0.01) showed measurable but little growth.

Chapter 2


Figure 2.22 Canola gnotobiotic root elongation assay of three growth promoting bacteria in the

presence of 125 mM NaCl stress. Each bar represents mean root length (±SE, n=12) of five day old

plantlets treated with sterile 0.03M MgSO4 (Control) or bacterial suspension in 0.03 M MgSO4

(0.1±0.02 OD at 600 nm). Green bars belong to isolates significantly increasing root length under

stress compared to control (Least significant difference, p ≤ 0.05).

2.4 Discussion

In the present study, endophytic bacteria were isolated from Cannabis sativa and investigated

for their potential as bio-inoculants for canola, a commercial crop. Selective isolation

procedure yielded six bacteria that significantly promoted the root growth of test plant under

gnotobiotic conditions, as compared to two isolates from direct isolation. The bacteria were

also recovered from the surface sterilized bacterized canola plants confirming their

endophytic presence (Rashid et al., 2012). Although statistically insignificant, remaining

isolates from selective isolation also performed better in promoting canola growth as

compared to isolates from direct isolation. The difference in performance could be due to the

host plant type. Long et al. (2008) noticed this for plant growth promoting bacteria of

Solanum nigrum that were unable to produce growth enhancement in Nicotiana attenuate, a

non-host plant. Plant genotype can also influence the ability of bacteria to promote plant

growth. This was reported by Kim et al. (2012a) in their work on growth promotion of switch

grass cultivars by Bukholderia phytofirmans PsJN. Hence, selecting endophytic bacteria

using canola produced more isolates that positively affected the growth of the same host

3

4

5

6

7

8

9

Root

len

gth

(cm

)

Chapter 2


plant. On the other hand, endophytic bacteria selected by C. sativa performed less efficiently

when tested on canola, an unrelated plant host.

The bacteria isolated from C. sativa roots represented endophytes selected by that plant from

the rhizosphere bacterial pool. These bacteria were found to be different from the isolates

selected by canola from the same pool. Hence, C. sativa and canola can take up their

respective endophytic bacteria differently. Germida et al. (1998) reported similar observation

for their work on canola and wheat plants grown in the same field. Nevertheless, the enriched

rhizospheric community of C. sativa did yield a unique set of microbes when selected using

canola plant. Most of these bacteria were not found to be part of the endophytic community

of canola reported by earlier researchers (Germida et al., 1998; Granér et al., 2003; Misko

and Germida, 2002; Siciliano and Germida, 1999). Further, Kusari et al. (2014) recently

reported their work on the endophytic bacteria of C. sativa sampled from Bedrocan BV,

Netherlands. They recovered only two bacterial genera with Bacillus being more predominant

than Mycobacterium. The isolates obtained from C. sativa roots in the present study appear to

be different from these findings, and more bacterial genera were recorded. Collectively, these

observations support the idea that endophytic community of a plant is defined by the nature

of its surrounding soil (McInroy and Kloepper, 1995; Rashid et al., 2012).

In the present work, most of the isolated bacteria produced Cellulase and Pectinase. This is

not surprising, since plant cell-wall degrading enzymes are known to play an important role

in the invasion and systematic dissemination of endophytic bacteria in the host tissues

(Reinhold-Hurek et al., 2006; Reinhold-Hurek and Hurek, 2011). Endophytic bacteria can

also make plant nutrients like phosphorus and iron more accessible for their hosts (Young et

al., 2013). A number of bacteria also solubilized inorganic phosphate, and the activity was

more pronounced in Acinetobacter, Enterobacter, Pantoea, Pseudomonas and Serratia.

These genera are frequently reported for their ability to solubilize phosphate (Sharma et al.,

2013).

All isolates were found to produce IAA like molecule albeit a moderate to low level. While

high IAA production is known to be a characteristic of plant pathogens and can cause

stunting of root growth (Malik and Sindhu, 2011; Kunkel and Chen, 2006), lower amounts

can increase plant growth (Marques et al., 2010). In the present study, many isolates did

promote root length in the inoculated plants compared to non-bacterized plants while only

few adversely affected root growth. Interestingly, two highest IAA producing bacteria,

Chapter 2


Agrobacterium tumefaciens MOSEL-n12 and Acinetobacter pittii MOSEL-r8, produced

comparably lesser root lengths in canola than the bacteria that improved host root growth

significantly. In fact, bacteria producing IAA in the range of 4-8 µg/ml produced a more

enhanced root growth of the host plant. Long et al. (2008) also reported similar effects by

growth promoting bacteria on Solanum nigrum. Hence, plant growth promoting ability of

bacteria appears to be dependent on the amount of IAA produced by them, where lower

amounts tend to favor plant growth.

Endophytic bacteria can also benefit their host plant by discouraging the growth of

phytopathogens. They can accomplish this by using strategies like limiting nutrient

availability and colonization sites, by producing antagonistic substances, and by forming

biofilms (Compant et al., 2010). In the present work, dual culture assay identified useful

endophytic bacteria that retarded the growth of two phytopathogenic fungi, Aspergillus niger

and Fusarium oxysporum. Interestingly, all chitinase producing bacteria were antagonistic

towards the two test fungi, and most of them also produced protease. The antifungal ability of

bacteria can be due to their Chitinolytic and Proteolytic activity (Kim and Chung, 2004).

Among the antifungal bacteria, Paenibacillus sp.MOSEL-w13 exhibited the most prominent

antifungal activity against the two fungi. The isolate was also positive for various enzyme

activities tested. Paenibacillus are well known for their antifungal potential (Aktuganov et

al., 2008; Beatty and Jensen, 2002). However, the antifungal potential of P. hunanensis, the

bacteria most similar to MOSEL-w13, has not been reported before. Other interesting

antifungal isolates were Enterobacter cloacae MOSEL-w7, Enterobacter asburiae MOSEL-

t15, Pantoea vagans MOSEL-t13, Pseudomonas koreensis MOSEL-tnc2, Serratia

marcescens MOSEL-w2 and Stenotrophomonas rhizophila MOSEL-tnc3, and they also

significantly promoted root growth of canola.

A good number of isolates including most antifungal bacteria also produced siderophores.

Siderophore producing bacteria can discourage the growth of competing organisms by

limiting iron availability in the environment (Marques et al., 2010). Bacterial siderophore

production can also benefit plant host by improving its iron acquisition (Masalha et al.,

2000).

Most interesting plant growth promoting isolates were identified as Pseudomonas geniculata

MOSEL-tnc1, S. marcescens MOSEL-w2 and P. vagans MOSEL-t13. P. geniculata has been

reported as endophytic bacteria in switch grass and rice although it was not shown to be plant

Chapter 2


growth promoting (Nhu and Diep, 2014; Xia et al., 2013). The isolate was able to tolerate up

to 7% NaCl stress and also promoted growth of canola under salt stress. Interestingly, S.

marcescens MOSEL-w2 was the only isolate that showed activity in all the assays. The

isolate was able to produce plant and fungal cell-wall degrading enzymes, produced IAA and

siderophore, solubilized inorganic phosphate, retarded growth of phytopathogenic fungi, and

promoted canola growth under normal and stressed condition. It is a well-known plant

associated bacteria that was found to be endophytic and growth promoting in rice

(Gyaneshwar et al., 2000), and conferred cold tolerance in wheat (Selvakumar et al., 2007).

In the present study, the highest root elongation under normal and stressed conditions was

recorded for Pantoea vagans MOSEL-t13. The isolate also produced the highest IAA (7.7

µg/ml) among all the growth promoting bacteria and antagonized growth of F. oxysporum. A

strain of P. vagans has been commercialized as a bacterial biocontrol agent for fire blight

(Smits et al., 2011). As previously demonstrated, all three isolates belonging to Enterobacter

significantly promoted plant growth in the present study (Ahemad and Khan, 2010; Saleh and

Glick, 2001; Jha et al., 2012). As all the isolates that significantly promoted canola growth

were also phylogenetically related, the present study revealed that the ability to promote plant

growth is evolutionarily conserved in the studied endophytic bacteria.

Chapter 3

Plant growth promoting potential of endophytic bacteria

isolated from roots of wild Dodonaea viscosa L.

Chapter 3


Plant growth promoting potential of endophytic bacteria isolated from roots of wild

Dodonaea viscosa L.

Abstract

Wild perennial shrub Dodonaea viscosa can tolerate harsh environmental conditions and is a

good candidate for isolating useful endophytic bacteria. The present work was aimed to

isolate endophytic bacteria from roots of Dodonaea viscosa and to determine their ability to

promote canola growth. Isolates were identified on the basis of 16S rRNA gene and screened

for various traits consistent with plant growth promotion. Out of 15 isolates, the 10 bacteria

that significantly promoted canola root growth in gnotobitic assay belonged to Agrococcus,

Bacillus, Microbacterium, Pseudomonas, Streptomyces and Xanthomonas, while others

positively affected canola root growth, albeit insignificantly. All isolates produced IAA, an

important plant hormone, where some produced quantities higher than others; the ability

improved in the presence of tryptophan. The isolates also produced plant cell-wall targeting

cellulase and pectinase, needed to systemically colonize host. Most isolates could improve

plant nutrient availability by solubilizing mineral phosphate and producing siderophores,

which are also important in biocontrol of plant pathogens. Members of Bacillus,

Pseudomonas and Streptomyces inhibited two pathogenic fungi in dual-culture assay, and

many isolates also produced fungal cell-wall targeting chitinase and protease. These results

confirm Dodonaea viscosa endophytic bacteria as PGPBs. Furhter investigation is needed to

establish their potential as bio-inoculants for crops and to identify molecular mechanisms of

plant growth promotion.

Chapter 3


3.1. Introduction

Modern agricultural practices are heavily dependent on the use of chemical pesticides and

fertilizers to improve crop yield for meeting the demands of increasing human population.

This overuse can lead to various problems that include environmental contamination

affecting human health, disturbance of natural nutrient cycling, and damage to natural

microbial communities that support crop health (Enebak et al., 1998). This has lead to an

increased interest in ecofriendly organic farming practices that pose no threat the

environment (Esitken et al., 2005). In this regard, the use of bacteria as fertilizers and

pesticides has become an interesting method to improve crop productivity.

Endophytic bacteria are a good choice as bio-inoculants, as they develop a much closer

association with their host to impart growth benefits as compared to rhizospheric bacteria

(Compant et al., 2010). These plant beneficial endophytic bacteria inhabit the internal plant

tissues without cauing any harm to the host plant and can benefit their host in various ways

(Reiter and Sessitsch, 2006). They can safely be used as fertilizers or pesticides, without

exerting any ecological damage and environment hazard (Pavlov et al., 2011). They improve

plant growth by producing plant hormones, by increasing nutrient avalaiblility for plants, by

alleviating plant stress, and by inhibit plant pests and pathogens (Ahemed and Khan, 2011).

Many species of Alcaligenes, Arthrobacter, Azospirillum, Azotobacter, Bacillus,

Burkholderia, Enterobacter, Klebsiella, Pseudomonas, and Serratia have been reported as

plant beneficial endophytic bacteria (Ji et al., 2014). Thus, endophytic bacteria isolated from

untapped wild sources having plant beneficial traits may serve as bio-inoculants for the

commercial crops (Jasim et al., 2014).

Aims and objectives

In the present work, Dodonaea viscosa L. (Sanatha) was used as a host plant to isolate

endophytic bacteria. This woody and evergreen perennial wild plant remains unstudied for

the bacteria it harbours. D. viscosa is a native Australian plant, but is widely distributed

throughout the tropics and used for its medicinal effects (Rajamanickam et al., 2010).

Therefore, the present study isolated endophytic bacteria from wild D. visocosa to evaluate

Chapter 3


their beneficial traits, including effects on Canola growth. The bacteria were also tested for

their antifungal ability against phytopathogenic fungi.


The study presented was carried out in the Molecular Systematics and Applied Ethnobotany

Laboratory (MOSEL), Department of Biotechnology, Quaid-i-Azam University, Islamabad.

The experiments performed included the isolation and identification of endophytic bacteria

from Dodonaea viscosa, and their characterization on the basis of various in-vivo and in-vitro

plant growth promotion and biocontrol assays. Detailed methods are as under and recipes are

provided in Appendix A.

3.2.1 Collection of plant samples

Wild Dodonaea viscosa L. was collected from three sites located within the campus area of

Quaid-i-Azam University, Islamabad. The samples were immediately brought to laboratory

and processed for isolation of endophytic bacteria.


Culturable bacteria were isolated from the roots of D. viscosa using a modified approach of

Rashid et al. (2012). The roots were washed with tap water to remove adering soil and

reduced to 2-3 cm cuttings and mixed together. The cuttings were then surface sterilized by

washing with 70% ethanol (2 minutes) followed by a wash with commercial bleach (5

minutes), and then washed 5 times with sterile distilled water. Water from the last wash was

plated on Tryptic Soy agar (TSA) to ensure no epiphytes were selected. About 5-6 cuttings

were macerated in 5 ml of sterile 0.03 M MgSO4 using an autoclaved mortar and pestle, and

kept in a laminar flow cabinet for 30 minutes at room temperature. The macerate (100 µl)

was serially diluted up to 10-3 using 900 µl of diluent (0.03 M MgSO4) in each dilution tube,

and 100 µl of each dilution was spread plated on half strength Tryptic Soya agar (TSA) and

Nutrient agar (NA), and on R2A agar medium. The inoculated media were incubated for 3-5

days at 30°C. Dilutions were plated in replicates on each growth medium.

Chapter 3


3.2.3 Enumeration of endophytic bacteria

After 3-5 days incubation, several morphologically different colonies appeared on all the

above three types of media (TSA, R2A agar and NA). All the incubated plates were carefully

observed and the numbers of colonies were counted for each media plate, and finally bacteria

were enumerated as colony forming units per gram fresh weight (cfu/gfw) using the

following formula.

Plate

count

X

10 X Dilution

Factor X 50 ÷

Weight

of

roots

= cfu /

gfw

30-300

colonies

Cells in

1 ml of

dilution

Cells in

macerate

serially

diluted

Cells in

total

macerate

Grams

Cells

per

gram

root

tissue

3.2.4 Selection and maintenance of pure strains

Morphologically distinct bacterial colonies were selected from the isolation procedure on the

basis of color, shape, texture, size and gram reaction, The pure bacteria were maintained on

half strength TSA slants at 4°C.

3.2.5 Bacterial preservation in glycerol stock

Glycerol stocks are important for long-term storage of bacterial strains. Tryptic Soya broth

(TSB) medium was prepared and autoclaved for 20 minutes at 121°C. A pure bacterial

culture was inoculated into the broth using a wireloop, and the culture was incubated

overnight at 30°C. Next day, 700 µl of the overnight culture was mixed with 300 µl of 50%

Chapter 3


glycerol solution (50% glycerol in 50% distilled water) in a cryovile. The prepared bacterial

glycerol stocks (15% glycerol) were immediately stored at -80ºC.


Bacterial isolates were examined for their ability to promote canola plants using gnotobiotic

roots elongation assay on filter paper.

3.2.6.1 Seed Collection

Canola seeds were collected from National Agricultural Research Centre (NARC),

Islamabad.

3.2.6.2 Gnotobiotic Canola root elongation assay

Modified method of Penrose and Glick (2003) was used to determine the ability of

endophytic bacteria to enhance canola root elongation. Canola seeds were surface sterilized

by washing with 70% ethanol for 1 min and 20% commercial bleach (1% NaOCl) for 10 min.

Residual chemicals were removed by washing 10 times with sterile distilled water. Bacteria

were grown in half strength TSB for 48 hours, cells were harvested by centrifugation at 5000

rpm at 4°C and washed twice with 0.03 M MgSO4 and resuspended to an absorbance of about

0.1±0.02 at 600 nm. The suspension was used to treat the surface sterilized seeds for 1 hour at

room temperature. The bacterized seeds were then dried on sterile filter paper in petri plates

for 15 minutes. Then, the treated seeds were transferred to sterile petri plates containing filter

paper flooded with 5 ml sterile distilled water. Each treatment contained 18 seeds arranged in

6 plates (3 seeds per plate). Surface sterilized seeds treated with sterile 0.03 M MgSO4 were

used as a control. The prepared plates were incubated at 25°C and 60% relative humidity in a

plant growth chamber with 12 h light/dark cycles. Root emerging from the plantlets were

measured on day 5. The roots lengths of top 12 plantlets (showing highest root length) per

treatment were considered for further analysis. Treated plant root lengths were compared to

control plants by means of one way ANOVA and Least Significant Difference (LSD)

(pairwise comparison) at p value ≤0.05 using Statistix v8.1 software.

Chapter 3


3.2.7 In-vitro plant growth promotion assays

The isolated endophytic bacteria were analyzed for different traits consistent with plant

growth promotion, plant colonization and biocontrol of phytopathogens. The details are as

under.

3.2.7.1 Indole acetic acid production

IAA production by the bacterial endophytes was estimated using the modified method of

Gordon and Weber (1951), as described in Section 2.2.9.1. Briefly, bacteria were grown in

TSB at 30˚C for 24 hours in the presence and absence of tryptophan (200 μg/ml). The cells

were harvested by centrifugation at 10,000 rpm for 10 minutes. The supernatant (1 part) was

mixed with Salkowski reagent (2 parts), mixture was incubated at room temperature for 25

minutes, and the reaction was analyzed at 535 nm. Amount of IAA produced by individual

strains was evaluated using the formula generated through the standard curve of IAA (Section

2.2.9.1.1). Experiment was performed in duplicate and values were averaged.

IAA produced (µg/ml) = (Sample Absorbance + 0.004) ÷ (0.0369)

3.2.7.2 Phosphate solubilization

The tri-calcium phosphate containing minimal medium was used to qualitatively measure of

bacterial phosphate solubilization (Kuklinsky-Sobral et al., 2004). The media was prepared

and sterilized by autoclaving. An overnight bacterial culture was spot inoculated on the

prepared media. The inoculated media was incubated for 2-3 days at 30°C. Bacteria

producing zone of clearing around the colony were taken as positive for the phosphate

solubilization activity. The experiment was performed in triplicate.

3.2.7.3 Siderophore production

Siderophore production by the isolates was tested using the CAS agar medium prepared

following a modified method of Schwyn and Neilands (1958) as described by Alexander and

Chapter 3


Zuberer (1991). The media contents were prepared in four separate parts (Fe-CAS indicator

solution, 1; buffer solution, 2; nutrient solution, 3; casamino acid solution, 4). To prepare the

final media, sterile nutrient solution (cooled to 50°C) was mixed with sterile buffer solution

along with 30 ml filter-sterilized casamino acids solution, and indicator solution was added to

this mix with gentle stirring to mix the contents without forming bubbles. The media was

poured in the sterile plates and allowed to solidify. Overnight bacteria cultures were spot

inoculated on the prepared media and incubated at 30ºC for 48-72 hours. Production of a

yellow to orange halo around the bacterial colony confirmed siderophore production. The

experiment was performed in triplicates.


Isolated bacteria were examined for the ability to produce plant cell-wall targeting Cellulase

and Pectinase using qualitative assays.

3.2.8.1 Cellulase activity

Cellulose-congo red agar was used to analyze the cellulase production by the isolates as

described in Section 2.2.10.1 (Hendricks et al., 1995). Briefly, bacterial were spot inoculated

on the media and incubated for 3-5 days at 30ºC. Following incubation, the clearing zones

around colonies indicated Cellulase production. The test was performed in triplicate. Zones of

hydrolysis (cm) produced by bacteria were converted into three categories (large, >2.0 cm;

medium 1-2 cm; small, <1 cm) for plotting them in graph.

3.2.8.2 Pectinase activity

Pectin containing minimal media was used to identify Pectinase producing bacteria (Hankin

et al., 1971). Overnight grown bacteria were inoculated on the media and incubated at 30ºC

for 3-5 days. The zones of hydrolysis of pectin around bacterial colonies were visualized by

flooding culture plates with iodine solution (Ouattara et al., 2008). The experiment was

performed in triplicate. Zones of hydrolysis (cm) produced by bacteria were converted into

three categories (large, >2.0 cm; medium 1-2 cm; small, <1 cm) for plotting them in graph.

Chapter 3


3.2.9 Fungal cell-wall degrading enzymes

Isolated bacteria were examined for the ability to produce fungal cell-wall targeting Protease

and Chitinase using qualitative assays.

3.2.9.1 Protease activity

The protease activity of selected bacterial strains was determined using skim milk agar

medium (Bibi et al., 2012) as described in section 2.2.11.1. Briefly, media was prepared by

mixing TSA with 1% skimmed milk. Overnight grown bacterial cultures were spot inoculated

on the prepared media and incubator at 30ºC for 2 days. Protease activity was confirmed by

the appearance of zones of clearing around the colonies. Test was performed in triplicate.

Zones of hydrolysis (cm) produced by the bacteria were converted into three categories

(large, >2.0 cm; medium 1-2 cm; small, <1 cm).

3.2.9.2 Chitinase activity

Chitinase activity was tested by using chitinase screening media containing chitin (Bibi et al.,

2012). Chitinase media was prepared by adding 0.6% w/v colloidal chitin to half strength

TSA as described in section 2.2.11.2. Bacteria were spot inoculated on media and incubated

at 30º C for 5 days. Appearance of clear zones around the bacteria indicated Chitinolytic

activity and the bacteria were noted as positive for the activity. The tests were performed in

triplicate.

3.2.10 Antagonistic activities against pathogenic fungi

Antifungal potential of the isolated bacteria was determined against Aspergillus niger and

Fusarium oxysporum using Dual culture method as described previously in section 2.2.12.

Test bacteria were inoculated on the sides and the fungi were inoculated in the center of agar

medium containing 1:1 ratio of potato dextrose agar (PDA) and TSA (Kumar et al., 2012).

Culture plates were incubated at 30°C for 5-7 days and bacterial colonies antagonizing fungal

Chapter 3


growth were identified by presence of zone of inhibition at the point of interaction. The test

was performed in triplicate.

3.2.11 Molecular identification of endophytic bacterial

Bacterial isolates were identified based on their 16S rRNA gene sequence. For this, the test

bacteria were propagated on TSA by incubating at 30°C for 24 hours. The bacteria were then

processed for genomic DNA extraction, followed by PCR amplification of 16S rRNA gene,

purification of the PCR product, sequencing of the PCR product, and analyses of resulting

sequences for identification of bacteria.

3.2.11.1 Bacterial genomic DNA extraction

Purified bacterial colonies were processed for genomic DNA isolation as described in

previously in section 2.2.13.1. Briefly, each colony was carefully transferred to a PCR tube

containing 100 μl of lysis buffer. The tubes containing the mixture were heated at 95°C for

10 minutes in thermocycler followed by centrifugation at 14000 rpm for 10 minutes to pellet

the cell debris. The supernatant containing genomic DNA was collected and stored at -20°C

for further processing.

3.2.11.2 PCR amplification of 16S rRNA gene

Supernatant (containing genomic DNA) collected from above procedure was used as a

bacterial template for PCR reaction as described in section 2.2.13.2. Bacterial 16S rRNA

gene was amplified using the universal primers 27F and 1492R. PCR reaction mixture (50

µL) was prepared containing forward and reverse primers, template DNA, and PCR Master

Mix in PCR grade water. PCR amplification was performed with initial denaturation at 94°C

for 5 minutes, followed by 30 cycles of denaturation (94°C for 30s), annealing (55°C for 30s)

and extension (72°C for 1 minute) with a final extension at 72°C for 10 min. The resulting

PCR product (approximately 1500 bp) was visualized on 1% agarose gel containing ethidium

bromide and compared to a 1 kb ladder for size confirmation, as described in section 2.2.13.3.

Chapter 3


3.2.11.3 PCR product purification

PCR products were purified using PureLink PCR Purification Kit (Invitrogen, USA)

according to provided instructions, as described in section 2.2.13.4. The purified DNA was

confirmed by agarose gel electrophoresis as described in section 2.2.13.3 and stored at -20°C

for further processing.

3.2.11.4 16S rRNA gene sequencing and analysis

For sequencing of 16S rRNA gene, the purified PCR products of amplified 16S rRNA gene

were sent to Macrogen, Inc. (South Korea). The sequences were analyzed for their quality

using BioEdit v7.0.5 program and trimmed. The trimmed sequences were used to identify

bacteria using Basic Local Alignment Search Tool (BLAST) search tool against the GenBank

database available at the National Center for Biotechnology Information Search database

(NCBI; https://www.ncbi.nlm.nih.gov/) website. The bacteria were identified based on their

maximum score and percentage similarity (≥99%) with other GenBank bacterial accession.

For determining bacterial similarity with type strains, Eztaxon server version 2.1 was used

(http://www.ezbiocloud.net/; Kim et al., 2012b). The sequences of the identified bacteria

were deposited at GenBank.

3.2.11.5 Phylogenetic analysis of endophytic bacteria

The evolutionary linkages among the isolates were assessed through phylogenetic analysis.

For this, multiple alignments were first performed for the 16S rRNA gene sequences of the

isolates using ClustalXv2.1. The aligned sequences were then constructed into a phylogenetic

tree based on Neighbor-Joining method (Bootstrap using 500 replicates) using MEGA5

software.

Chapter 3


3.3 Results

The present work was carried out for the isolation, screening and characterization of

endophytic bacteria from Dodonaea viscosa. The bacteria were isolated from roots, and were

identified and then analyzed for different traits consistent with plant growth promotion, plant

invasion and biocontrol of phytopathogenic fungi. The details of the results are as follows:


After enumeration of isolated bacteria, a total of 15 distinct bacteria were selected on the

basis of colony size, morphology, shape, and color and growth pattern. Highest cell counts

were on R2A agar (1×107 cfu/gfw) followed by TSA (8.5×106 cfu/gfw) and NA (5×106

cfu/gfw) (Table 3.1). These selected colonies were further purified by repeated sub culturing.

Table 3.1 Number of bacterial isolates recovered from Dodonaea viscosa roots along with average

cell counts recovered on three growth media.

Source Direct Isolation

Total bacteria isolates 15

TSA 8.5×106 cfu/gfw

R2A 1×107 cfu/gfw

NA 5×106 cfu/gfw

3.3.2 Identification of endophytic bacteria

Bacteria were identified based on their 16S rRNA gene sequence. For this, genomic DNA

extracted from the overnight grown bacteria was used as a template for PCR reaction. PCR

amplification of the 16S rRNA gene of the isolates yielded a product close to 1500 bp. PCR

amplicons were sequenced commercially and sequence quality was analyzed using BioEdit

program. The sequencing electropherogram revealed that all sequences were clean and of

good quality. The resulting partial sequences were used to identify the endophytic isolates

using GenBank and Eztaxon databases.

Chapter 3


Results from GenBank and Eztaxon analysis revealed that a diversity of bacterial genera were

isolated from Dodonaea viscosa roots. The identified bacteria belonged to 10 distinct genera

namely Agrococcus, Bacillus, Brevundimonas, Inquilinus, Microbacterium, Pseudomonas,

Rhizobium, Streptomyces, Stenotrophomonas, and Xanthomonas, (Figure 3.1). Bacillus was

the major genus representing 26% of all the isolated strains. Xanthomonas and Streptomyces

represent 13% each, while rest of the genera represented 7% of the total isolates.

Figure.3.1 Percentage of endophytic bacterial genera isolated from D. viscosa

Most of the isolates shared more than 99-100% homology to the closest type strain based on

the analysis of EzTaxon server. However, three isolates (MOSEL-RD3, MOSEL-RD25 and

MOSEL-RD40) shared less than 99% similarity to their respective type strains, while

MOSEL-RD14 was least similar (98.48%) to the closest type strain among all the tested

isolates. Furthermore, all isolates shared 99-100% similarity to a GenBank submission,

analyzed using BLAST program. The 16S rRNA gene sequences of identified endophytic

bacteria have been deposited at GenBank database, where each submission has been given a

unique accession number (Table 3.2)

0

5

10

15

20

25

30

Per

cen

tag

e

Chapter 3


Table 3.2 Identification of endophytic bacteria isolated from Dodonaea viscosa roots. GenBank

match similarity was ≥99% for all isolates while their Eztaxon match similarity and GenBank

accession is given below.

Strain

(MOSEL) GenBank closest match

EzTaxon closest match

(type strain)

Similarity

(%)

Genbank

accession

RD1 Inquilinus limosus Inquilinus limosus AU476

99.71 KJ591012

RD2 Xanthomonas sp. Xanthomonas sacchari LMG

471 99.60 KJ591013

RD3 Streptomyces sp. Streptomyces alboniger

NBRC 12738 98.90 KJ591014

RD7 Bacillus idriensis Bacillus idriensis SMC

4352-2 99.30 KJ591015

RD9 Xanthomonas translucens Xanthomonas translucens

DSM 18974 99.80 KJ591016

RD12 Rhizobium huautlense Rhizobium huautlense S02 100.00 KJ591017

RD14 Microbacterium sp

Microbacterium

trichothecenolyticum IFO

15077

98.48 KJ591018

RD17 Streptomyces caeruleatus Streptomyces caeruleatus

GIMN4 99.90 KJ591019

RD19 Bacillus simplex Bacillus simplex NBRC

15720 100.00 KJ591020

RD23 Pseudomonas putida Pseudomonas taiwanensis

BCRC 17751 99.90 KJ591021

RD25 Brevundimonas sp.

Brevundimonas

subvibrioides ATCC 15264

98.90 KJ591022

RD27 Bacillus cereus Bacillus cereus ATCC 14579 100.00 KJ591023

RD28 Bacillus subtilis Bacillus subtilis NCIB 3610

99.90 KJ591024

RD36 Pseudomonas geniculata Pseudomonas geniculate

ATCC 19374 100.00 KJ591025

RD40 Agrococcus terreus Agrococcus terreus DNG5 98.60 KJ591026

Chapter 3


3.3.3 Phylogenetic Analysis

Evolutionary relatedness of the endophytic bacterial isolates was determined based on

their 16S rRNA gene sequences. For this, sequences were first aligned with ClustalX v2.1

and a phylogenetic tree was constructed using Mega5 software. The results revealed that all

bacteria significantly promoting canola root growth (MOSEL-RD2, MOSEL-RD3, MOSEL-

RD7, MOSEL-RD9, MOSEL-RD14, MOSEL-RD17, MOSEL-RD19, MOSEL-RD23,

MOSEL-RD27, MOSEL-RD28, MOSEL-RD36, and MOSEL-RD40) clustered together in to

two separate clades (100% Bootstrap value). The isolates belonged to genera Agrococcus,

Bacillus, Microbacterium, Pseudomonas, Streptomyces, and Xanthomonas (Figure 3.2). Since

all the members included in a single cluster are phylogenetically related, the present result

indicates that the ability to promote plant growth is evolutionary conserved in the endophytic

bacteria.

Figure 3.2 Phylogenetic tree of endophytic bacteria isolated from Dodonaea viscosa roots constructed

with 16S rRNA gene sequences using the Neighbour-Joining method. Branch points show bootstrap

percentages (500 replicates). Bar 0.02 indicates changes per nucleotide position. Clusters enclosed in

red boxes contain isolates significantly promoting canola growth.

Chapter 3


3.3.4 Production of IAA

All the isolates produced IAA and the ability imporved in the presence of tryptophan (Figure

3.3). IAA concentrations in the medium after 2 days ranged from 0.88-23.7 µg/ml with

tryptophan and from 0.36-9.02 µg/ml without tryptophan. Isolates in order Pseudomonas

taiwanensis (23.7 µg/ml), Agrococcus terreus (15.34 µg/ml), Pseudomonas geniculate (15.32

µg/ml), Bacillus cereus (10.8 µg/ml), Bacillus idriensis (10.12 µg/ml) and Bacillus subtilis

(8.5 µg/ml) were the highest IAA producing strains.

Figure 3.3 IAA production by bacteria isolated from Dodonaea viscosa roots (Blue bars, without

tryptophan; Orange bars, with tryptophan). Values represent mean of three replicates.

3.3.5 Nutrient availability

Bacterial isolates were assessed for their ability to facilitate phosphorus and iron availability

for plant host. Among the 15 isolates, some 12 isolates (80%) were phosphate solubilizer as

confirmed by clear zones around their colonies (Figure 3.4). These phosphate solubilizers

0

5

10

15

20

25

IAA

pro

du

ced

(µ

g/m

l)

Chapter 3


belonged to the genera Bacillus, Brevundimonas, Inquilinus, Pseudomonas, Rhizobium,

Streptomyces, and Xanthomonas (Table 3.3). Furthermore, all isolates belonging to Bacillus

and Streptomyces were mineral phosphate solubilizers.

Figure 3.4 Tri-calcium phosphate medium plate showing phosphate solubilization activity of

Streptomyces caeruleatus MOSEL-RD17

Furthermore, about 60% isolates produced Siderophores indicated by the appearance of

orange halos around the bacterial colony on a blue media (Figure 3.5). Most prominent

Siderophore producing bacteria belonged to genera Bacillus and Streptomyces while others

belonged to Agrococcus, Microbacterium, and Pseudomonas (Table 3.3).

Figure.3.5 Siderophore production by Bacillus cereus MOSEL-RD27 on the test media.

Chapter 3


Table 3.3 Phosphate solubilization and Siderophore production activity of endophytic bacteria

isolated from Dodonaea viscosa roots.

Isolate P solubilization Siderophore

Agrococcus terreus MOSEL-RD40 - +

Bacillus cereus MOSEL-RD27 + +

Bacillus idriensis MOSEL-RD7 + +

Bacillus simplex MOSEL-RD19 + -

Bacillus subtilis MOSEL-RD28 + +

Brevundimonas subvibrioides MOSEL-RD25 - -

Inquilinus limosus MOSEL-RD1 + -

Microbacterium trichothecenolyticum MOSEL-RD14 - +

Pseudomonas geniculata MOSEL-RD36 + +

Pseudomonas taiwanensis MOSEL-RD23 + +

Rhizobium huautlense MOSEL-RD12 + -

Streptomyces alboniger MOSEL-RD3 + +

Streptomyces caeruleatus MOSEL-RD17 + +

Xanthomonas sacchari MOSEL-RD2 + -

Xanthomonas translucens MOSEL-RD9 + -

(+), activity present; (-), activity absent.

3.3.6 Production of plant cell-wall degrading enzymes

The isoaltes were tested for their ability to produce plant cell-wall degrading enzymes

Cellulase and Pectinase. All strains showed strong Pectinase activity indicated by large zone

of hydrolysis on pectin containing media. Moreover, all isolates produced zones of hydrolysis

larger than 1 cm while 54% produced zones larger than 2 cm. The isolates with highest

activites belonged to the genera Bacillus, Microbacterium, Streptomyces, Xanthomonas

(Figure 3.6). Furthermore, all the isolates also displayed Cellulase activity indicated by zone

of hydrolysis produced on Cellulose (CMC) containing media. Most of the isolates (67%)

Chapter 3


produced zones larger than 1 cm while 26% produced zones larger than 2 cm for the

Cellulase activity. The isolates producing highest zone sizes belonged to the genera Bacillus,

Microbacterium and Streptomyces. Finally, all isolates displaying strong Cellulase activity

were also prominent in their Pectinase activity (Figure 3.6).


from Dodonaea viscosa roots. Values of zones of hydrolysis produced by bacteria have been

organized into three categories based on the size: 3, large (>2 cm); 2, medium (1-2 cm); 1, small (<1

cm).

3.3.7 Production of Fungal cell-wall targeting enzyme

The bacterial isolates were tested for their Protease and Chitinase production ability using

qualitative tests (Figure 3.7). With the exception of Bacillus simplex MOSEL-RD19 and

Rhizobium huautlense MOSEL-RD12, all the isolates displayed protease activity. Moreover,

about 74% of the isolates produced zones larger than 1 cm while 34% produced zones larger

than 2 cm when tested for Protease activity. Xanthomonas was the prominent genera for

Protease activity followed by Agrococcus, Bacillus and Microbacterium. In case of Chitinase

1

3

2 2

3

1 1

3

2 2 2

3

1

2

1

2

3 3

2

3

2 2

3

2 2 2

3 3 3 3

Chapter 3


activity, only 40% of the isolates were positive for the activity. These isolates belonged to

genera Bacillus Microbacterium, Pseudomonas and Streptomyces. Finally, all Chitinase

positive bacteria were also positive for Protease activity (Table 3.4)

Table 3.4 Protease production (PRO), Chitinase production (CHI), Anti-Aspergillus niger (AN), and

Anti-Fusarium oxysporum (FO) activities of endophytic bacteria isolated from Dodonaea viscosa

roots.

Isolate PRO CHI AN FO

Agrococcus terreus MOSEL-RD40 +++ - - -

Bacillus cereus MOSEL-RD27 ++ + + +

Bacillus idriensis MOSEL-RD7 ++ + + +

Bacillus simplex MOSEL-RD19 - - - -

Bacillus subtilis MOSEL-RD28 +++ + + +

Brevundimonas subvibrioides MOSEL-RD25 ++ - - -

Inquilinus limosus MOSEL-RD1 + - - -

Microbacterium trichothecenolyticum MOSEL-RD14 +++ - - -

Pseudomonas geniculata MOSEL-RD36 ++ + + +

Pseudomonas taiwanensis MOSEL-RD23 ++ + + +

Rhizobium huautlense MOSEL-RD12 - - - -

Streptomyces alboniger MOSEL-RD3 + + + +

Streptomyces caeruleatus MOSEL-RD17 ++ + + +

Xanthomonas sacchari MOSEL-RD2 +++ - - -

Xanthomonas translucens MOSEL-RD9 +++ - - -

(+), activity present; (-), activity absent; (+), smaller halos around colonies (<1 cm); (++), medium

halos around colonies (1-2 cm); (+++), large halos around colonies (>2 cm)

3.3.8 Antifungal Assay

Antifungal activity of the bacterial isolates against phytopathogenic fungi was examined

using dual culture assay (Figure 3.8). All the isolates were screened for antifungal activity

against Fusarium oxysporum and Aspergillus niger. About 47% of the isolates inhibited the

Chapter 3


growth of the two phytopathogenic fungi. Bacillus and Streptomyces were the most

prominent genera in this activity followed by Pseudomonas. Interestingly, all active isolates

inhibited the growth of both the test fungi. Moreover, all the active isolates also displayed

Chitinase activity indicating strong correlation between these activities (Table 3.4).

Figure 3.7 Skimmed milk containing media showing Protease activity (left) and Colloidal chitin

media showing Chitinase activity (right) by Bacillus subtilis MOSEL-RD28

Figure 3.8 Anti-Aspergillus niger (left) and Anti-Fusarium oxysporum (right) activity of selected

endophytic bacteria isolated from Dodonaea viscosa roots.

3.3.9 Canola gnotobiotic root elongation assay

Canola root elongation assay was performed under controlled condition. Canola seeds were

inoculated and grown in petri plates on filter paper for five days. After five days root length

of emerging platelets was measured and results were compared with uninoculated control

Chapter 3


platelets. Results revealed that 67% of the isolates significantly promoted canola root growth

(LSD; p ≤ 0.05) (Figure 3.9). Compared to the root lengths of non-bacterized control

(9.5±0.33), highest root elongation was done by B. subtilis MOSEL-RD28 (11.92±0.29),

followed by B. idriensis MOSEL-RD7 (11.82±0.34), X. sacchari MOSEL-RD2 (11.52±0.47),

B. cereus MOSEL-RD27 (11.16±0.40), X. translucens MOSEL-RD9 (11.06±0.43), P.

taiwanensis MOSEL-RD23 (10.96±0.28), P. geniculata MOSEL-RD36 (10.76±0.23), S.

alboniger MOSEL-RD3 (10.58±0.30), M. trichothecenolyticum MOSEL-RD14 (10.54±0.43)

and A. terreus MOSEL-RD40 (10.5±0.24).

Figure 3.9 Canola gnotobiotic root elongation assay of endophytic bacteria isolated from Dodonaea

viscosa roots. Each bar represents mean root length (±SE, n=12) of five day old plantlets treated with

sterile 0.03 M MgSO4 (Control) or bacterial suspension in 0.03 M MgSO4 (0.1±0.02 OD at 600 nm).

Green bars represent isolates significantly increasing root length and red bar significantly decreasing

root length compared to control (Least significant difference, p ≤ 0.05).

5

6

7

8

9

10

11

12

13

Ro

ot

len

gth

(cm

)

Chapter 3


Most prominent genera for canola plant growth promotion were Bacillus, Pseudomonas and

Xanthomonas. Present study is the first report of Bacillus idriensis (MOSEL-RD7) as

endophytic growth promoting bacteria and possessed many plant beneficial traits.

Furthermore, most of the bacteria promoting canola root growth produced IAA in the range

of 2-10 µg/ml (Figure 3.3).

3.4 Discussion

In the present work, endophytic bacteria of Dodonaea viscosa roots were investigated

for their potential as bio-inoculants for canola, a commercial crop. A total of 15 endophytic

bacteria were isolated and were screened for different activities important for plant growth

promotion, plant invasion and biocontrol of phytopathogenic fungi. The endophytic bacterial

isolates possessed many plant growth promoting (PGP) traits including phosphare

solubilization, IAA production, and siderophore production. Bacillus was the predominant

bacterial genera this was also reported by Kim et al. (2011). Bacillus has also been reported

as an endophyte in Tomato, Polygonum cuspidatum and Aquilaria spp. (Figueiredo et al.,

2009; Krishnan et al., 2012; Feng et al., 2013). Futhermore, Bacillus and Pseudomonas have

been frequetly reported to endophytically colonize the plant roots and benefit their host

(Kumar et al., 2011). Similarly, Microbacterium genera isolated here as an endophyte was

also reported by Rashid et al. (2012) as a tomato endophyte. These findings are further

supported by the work of Kim et al. (2012c), as they isolated Actinobacteria (endophytic

Microbacterium) from herbaceous plants.

Plant cell-wall targeting Cellulases and Pectinases are important for the systemic plant

colonization and plant beneficial endophytic bacteria are known to produce these hydrolytic

enzymes (Verma et al., 2001). All the endophytic strains in the present work produced

Cellulase and Pectinase. Cellulases and pectinases are found to be important in root

colonization of microbes within host plant tissue for a deeper interaction (Reinhold-Hurek

and Hurek, 2011) and to protect plant host (Quadt-Hallmann and Kleopper, 1996). This trait

is more important for the establishment of these strains on a wide variety of plant hosts.

All the isolates produced IAA in lowers amounts and production increase 2-3 folds in the

presence of tryptophan. Few isolates Agrococcus terreus, Bacillus cereus, Bacillus idriensis,

Bacillus subtilis, Pseudomonas geniculate, and Pseudomonas taiwanensis showed higher

Chapter 3


IAA production than other bacteria. Bacteria producing IAA in the range of 2-10 µg/ml were

mostly plant growth promoting. IAA producing bacteria are known to enhance root length

(Patten and Glick, 2002).

Most of the phosphate solubilizing isolates belonged to the genera Bacillus, Brevundimonas,

Inquilinus, Pseudomonas, Rhizobium, Streptomyces, and Xanthomonas. Bacillus,

Enterobacter, Pseudomonas and Serratia have been repored for their mineral phosphate

solubilizing potential to benefit plant growth (Frey-Klett et al., 2005; Hameeda et al., 2008).

Improved phosphorous nutrition can indeed influence overall plant health by improving root

development (Jones and Darrah, 1994). Bacteria belonging to the genera Bacillus,

Pseudomonas, Microbacterium and Streptomyces also produced siderophore. Numerous

reports have indentified Bacillus, Enterobacter, Pseudomonas and Streptomyces as

siderophore producers (Tian et al., 2009; Khamna et al., 2009). Siderophore production by by

the endophytic bacteria can improve plant growth and health by imcreasing iron availability

for the host plant and depleting iron for the pathogens to limit their growth Pieterse et al.,

2001; Glick, 2003).

Some endophytic isolates also produced fungal cell wall trgeting Chitinases and Proteases

The bacteria can be employ these enxymes to control plant fungal diseases. Bacterial strains

belonging to genera Bacillus, Pseudomonas and Streptomyces showed chitinase activity.

These strains also showed antifungal activity against Fusarium oxysporum and Aspergillus

niger. Azotobacter sp., Pseudomonas sp. and Bacillus sp. are reported for antifungal activity

(Ahmad et al., 2008). Degradation of fungal cell wall by Chitinases is reported by Gupta et al.

(2006). Kim and Chung (2004) reported that Proteases and Chitinases are involved in

inhibiting plant fungal pathogen to function as biological control agents. Infact,

Agrobacterium, Azotobacter, Bacillus, Enterobacter, Erwinia, Serratia, Streptomyces and the

fluorescent Pseudomonas strains can function capable as biocontrol agents (Narula et al.,

2009). Plant beneficial bacteria can also act as biocontrol agents by producing hydrogen

cyanide besides producing fungal cell-wall targeting enzymes (Hayat et al., 2010). Bacillus

subtilis and Bacilli cereus are the usual candidates for use as biocontrol agents (Nagórska et

al., 2007).

Chapter 3


All the endophytic bacteria isolated in this study showed at least one positive activity of plant

growth promotion. Roots were elongated by all isolates except Inquilinus limosus and

Rhizobium huautlense which showed negative effects i.e. root length value lower than the

negative. Canola root elongation assay results showed that Xanthomonas sacchari, Bacillus

idriensis, Xanthomonas translucens, Bacillus cereus and Bacillus subtilis significantly

promoted Canola root length as compared to negative control. Bacillus sp. and Pseudomonas

sp. have been stated to promote plant growth in grape wine, tomato, maize, rice and sugar

beet through various mechanisms (Chauhan et al., 2013). Patel et al. (2012) studied that

Pseudomonas were efficient in enhancing host plant roots. Improved root and shoot

development by Bacillus was reported by Vivas et al. (2003). More interestingly, all the

isolates reported here that significantly promoted canola growth are phylogenetically related,

indicating the ability to promote plant growth is evolutionary conserved.

The plant growth promotion can be strongly attributed to the ability of the bacteria to produce

IAA. Indeed phytohormone IAA can influence plant root growth and development and

thereby improves nutrient uptake from soil (Khalid et al., 2004). However, among all PGP

traits of the isolates, IAA production was the most predominant PGP traits, indicating its

importance for the endophytic growth. IAA can increase root size and surface area which can

lead to increased nutrient uptake by the plants (Li et al., 2008).

To conclude, endophytic bacteria reported here possess numerous traits consistent with PGP.

These bacteria can be exploited for beneficial effects on canola and other commercially

important crop plants. However, to fully harness their plant growth promoting and biocontrol

potential, further investigation is warranted.

Chapter 4

Comparative in-planta transcriptome profiling of selected

Burkholderia phytofirmans PsJN genes using qPCR

Chapter 4


Comparative in-planta transcriptome profiling of selected Burkholderia phytofirmans

PsJN genes using qPCR

Abstract

Burkholderia phytofirmans PsJN is a well-known endophytic bacterium that can promote

growth of a variety of host plants. Only few studies have been done to decipher the

endophytic success of this bacterium. Present investigation is a comparative study to identify

selective expression of 15 bacterial genes during in-planta growth using relative

quantification qPCR. Strain PsJN was vacuum infiltrated into tomato plants and inoculum

dose was optimized for maximum bacterial extraction from leaf tissues. Analysis revealed

that bacteria were actively growing inside the leaf tissues. Since out of four inoculum doses

tested, the dose 109 cfu/ml produced the highest cells counts (108 cfu/gfw) on second day,

this dose was used to inoculate plants for gene expression study. The bacteria were also

grown on M9 minimal media for comparative analysis. Compared to M9 grown bacteria,

total bacterial RNA extracted from in-planta bacteria was lower in quantity and quality, but

RNA was analyzable using qPCR. Using rpoD as an endogenous control for qPCR, the gene

expression was compared between in-planta and M9 bacteria. Eight genes (Cellulase,

Pectinase, IAA degradation, ACC deaminase, β-xylosidase, β-galactosidase, Peroxidase and

one quorum sensing gene) were upregulated in in-planta bacteria, while three genes (IAA

synthesis, Flagella, and second quorum sensing gene) were downregulated. Expression of

Pili, Aerobactin, Hemagglutinin and Type 3 secretion system gene was similar between the

two growth conditions. Present investigation concludes that the bacteria are active in leaf

tissues and confirms expression of bacterial traits compatible with plant growth promotion

and invasion. The present comparative transcriptome profiling of strain PsJN will likely

better elucidate host-bacterial relationship and thus explicate endophytic role of B.

phytofirmans.

Chapter 4


4.1 Introduction

Burkholderia phytofirmans PsJN is a well-known plant growth promoting endophytic

bacteria isolated from onion roots (Pillay and Nowak, 1997). The endophyte can form

beneficial association with a variety of plant hosts, including Arabidopsis thaliana, canola,

grape, maize, potato, switch-grass, tomato and wheat (Sessitsch et al., 2005; Sun et al., 2009;

Sheibani-Tezerji et al., 2015), and can establish endophytic and rhizospheric population in

high numbers (Compant et al., 2008). Many of its plant growth promoting traits have been

identified. These include regulating the plant growth related hormones, ethylene, auxin, and

cytokinins; enhancing plant resistance to plant pathogens; and improving plant adaptation to

environmental stresses like drought, cold, heat and salinity (Sessitsch et al., 2005; Kim et al.,

2012; Theocharis et al., 2012). Moreover, Strain PsJN can successfully establish endophytic

population by their ability to produce plant cell-wall degrading enzymes, cellulase and

pectinase (Compant et al., 2005a). Therefore, Strain PsJN serves to be a model endophytic

bacterium for identifying genes important in the endophytic success of bacteria.

Many plant beneficial endophytic bacteria have been studied to identify genes important in

developing an association and promote of plant growth. The genes identified include those

required for interaction with plant metabolism (Hardoim et al., 2008), production of

metabolites targeting plant pathogens (Mendes et al., 2007), detoxification of contaminants

(Yousaf et al., 2011), bacterial motility and attachment to host cells (Reinhold-Hurek and

Hurek, 2011), bacterial quorum sensing (Zúñiga et al., 2013), production of plant cell-wall

targeting enzymes (Reinhold-Hurek et al., 2006), regulation of plant hormones (Sun et al.,

2009; Zúñiga et al., 2013), environment sensing, and mitigation of oxidative stress (Sheibani-

Tezerji et al., 2015). These studies have made use of mutational approaches (Sun et al.,

2009), RNAseq transcriptome profiling (Sheibani-Tezerji et al., 2015), Relative

Quantification PCR (qPCR) (Zhao et al., 2016), and promoter capturing techniques like in-

vivo expression technology (IVET) and recombinase-based in-vivo expression technology

(RIVET) (Rediers et al., 2003; Ryan et al., 2008).

Although many traits revealing the lifestyle of endophytic bacteria have been identified, little

is known about bacterial physiology, response, and adaptation processes in-planta.

Investigation done by Sheibani-Tezerji et al. (2015) on the transcriptome of Strain PsJN

could not identify many genes deemed crucial for the endophytic colonization and growth

promotion of host plant. Since, Strain PsJN establishes in-planta population in low number,

Chapter 4


getting sufficient quantities of high quality bacterial transcripts can be extremely challenging

(Compant et al., 2005a; Kim et al., 2012; Su et al., 2016). Therefore, a comparative

transcriptome profiling of strain PsJN can reveal a much better picture of bacterial traits

required for a successful host-bacterial relationship, that has not been reported earlier

(Sheibani-Tezerji et al., 2015).

Aims and objectives

Aim of the present work was to study the in-planta expression of 15 Burkholderia

phytofirmans PsJN genes important for plant growth promotion, plant invasion and

association. For this, expression of the genes was compared with the bacteria grown on M9

minimal media to identify the genes selectively expressed during in-planta bacterial growth.

The comparative transcriptome profiling of strain PsJN will likely better elucidate host-

bacterial relationship and thus explicate endophytic role of the bacterium.


4.2.1 Performance of experimental work

The experiments were performed in the Department of Plant and Microbial Biology,

University of California Berkeley, California, USA. All materials required for the

experimentation were provided by the department. The details of methods are as under and

recipes are provided in the Appendix A.

4.2.2 Propagation of Bacteria

Burkholderia phytofirmans strain PsJN was grown overnight in Kings B broth at 30°C

(Sessitsch et al., 2005). The cells were harvested through centrifugation at 5000 rpm for 10

min and suspended in 10 mM potassium phosphate and the suspension was used to inoculate

tomato plants. Four different cell densities (104, 106, 108, and 109 cfu/ml) were prepared for

inoculating the test plants.

Chapter 4


4.2.3 Plant bacterization using Vacuum Infiltration

To ensure that maximum bacteria are introduced in to the plants to attain high cell densities,

Vacuum Infiltration technique was employed (Yu et al., 2013). For this, tomato plants were

grown for four weeks under greenhouse conditions using a standard potting mix. Plants were

then brought to the lab for inoculation with strain PsJN. About 1.5 L of bacterial suspension

was prepared to completely submerge plants during the inoculation process. The pots were

first covered with paper towels to prevent soil from contaminating the suspension during the

process and to prevent suspension from flooding the pot soil. The filtration assembly was

setup in a fume hood by connecting the vacuum chamber to the intermediate cooling flask

connected to a vacuum pump through flexible pipes. The cooling flask was placed in a bucket

containing dry ice to improve the suction process. The container filled with 1.5 L of bacteria

suspension was placed in the vacuum chamber and the tomato plants were inverted and

submerged, ensuring that only the plant part is dipped in the suspension. The vacuum pump

was switched on for about 3 minutes to allow leaf stomata to open and suck up the inoculum.

After bubbling, the pump was switched off and the vacuum was kept for about 2 minutes to

stabilize the suspension. Then, the vacuum was gradually released by removing the pipe

connected to the vacuum chamber, thus preventing the inoculum to escape from the opened

leaf stomata. The inoculated plants were dried at room temperature by placing them on lab

bench top for 1 hour. The bacterized plants were placed in green house to allow bacterial-

plant interactions to develop. Non-bacterized control plants were also placed in the green

house.

4.2.4 Bacterial estimates in the inoculated plants

To determine the ideal inoculation dose for obtaining high cell number from leaf tissues, the

tomato plants were inoculated with four different doses of bacterial suspension (104, 106, 108,

and 109 cfu/ml). In order to determine the abundance of bacteria post inoculation, three

leaves from bacterized plants were collected at day 0, 2, 4 and 6. The leaves were washed

with tap water, weighed and surface sterilized by dipping in a solution of 15% Hydrogen

Peroxide for 3 minutes. The residual chemical was removed by washing the sterilized leaves

(5 times) with sterile distilled water. To confirm the surface sterilization, small volume of

water from the last wash was plated on Kings B agar and incubating overnight at 30°C.

Sterilized leaves were macerated using mortar and pestle in 5 ml of 10 mM potassium

phosphate and 100 µl of macerate was serially diluted using the same buffer (900 µl diluent

Chapter 4


in each tube). The dilutions were plated (100 µl) on Kings B Agar, incubated overnight at

30°C, and then bacteria were enumerated for tested dose and day of analysis using the

equation shown below.

Plate count

X

10 X Dilution

Factor X 50 ÷

Weight of

leaves = cfu / gfw

(30-300

colonies)

(cells in

dilution

tube)

Serial

Dilution

plated

(total cells

in

macerate)

grams

Cells per

gram leaf

tissue

The bacterial counts were converted to log values and plotted on graph using Microsoft Excel

program.

4.2.5 Bacterial Recovery for RNA extraction

Bacteria were recovered on day two post inoculation (plants inoculated with 109 cfu/ml

bacteria) using a modified approach of Yu et al. (2013) and four plants were processed at a

given time. To ensure protection of bacteria RNA during recovery process, RNA protective

solution was used to collect bacteria cells from bacterized leaves. A total of 30-50 leaves

were collected and submerged immediately in 1 L of ice cold Phenol-Ethanol Stop solution

(RNA protective solution), which is an acidic phenol RNA-stabilizing solution that protects

cellular RNA from degradation by RNases.

The leaves were evenly chopped into 0.5 cm squares while submerged in the ice cold

protective solution, and the plant mixture was sonicated for 10 min to dislodge the bacterial

cells from internal leaf tissue. The mixture was initially filtered through Whatman No. 1 filter

using a vacuum filtration flask to remove plant material, with repeated filter changes for a

better flow rate. The filtrate was centrifuged at 10,000 rpm for 10 min, and the pellet was

suspended in residual supernatant. To remove smaller plant matter, the resulting suspension

was filtered through a 5-μm filter, by repeatedly changing the filter for a better flow. The

bacterial cells were harvested from the final filtrate by centrifugation at 10,000 rpm for 10

min, and the pellets were stored at -80°C. The cells collected from four plants on a single day

served as a biological replicate, and three biological replicates were thus produced. Non-

bacterized control plants were processed following the same recovery process.

Chapter 4


For a comparative study, strain PsJN was also propagated on a minimal media. For this, the

bacteria were grown overnight on M9 minimal agar at 30°C. Growth was removed with a flat

spatula and immediately transferred to 5 ml of ice cold RNA-Stop solution. The mixture was

vortexed for 30 seconds to evenly dissolve the cells in the protective solution. The mixture

was then centrifuged at 10,000 rpm for 5 minutes at -20°C, and the resulting pellets were

stored at -80°C.

4.2.6 RNA extraction from bacterial pellets

For RNA extraction, frozen cell pellets were thawed by keeping on ice for 5-10 minutes, and

three biological replicates were mixed two make one sample. Total RNA extraction from

these cells was performed using the TRIzol-RNeasy hybrid RNA extraction protocol. The

bacterial pellets were resuspended in 1 ml of TRIzol reagent (Invitrogen, USA) and were

transferred to 2 ml sterile screw-cap microcentrifuge tube. Cells were homogenized by

vigorous pipetting and vortex for 30 seconds their disruption. The homogenate was incubated

for 5 minutes at room temperature. About 200 µl of Chloroform was added to the

homogenate; mixture was shaken vigorously by hand for 15 seconds, and incubated at room

temperature for 2-3 minutes. The mixture was centrifuged for 15 minutes at 12,000 rpm at

4°C, resulting in three distinct phases; a botton red colored phenol-chloroform phase, a

middle white interphase, and a top colorless aqueous phase containing the bacterial RNA.

Using a micropipette, the top aqueous phase was carefully removed and transferred to a fresh

tube. An equal volume of pure RNA-free Ethanol was slowly added to the sample.

The mixture obtained through Trizol method was processed further using the RNeasy Mini

Kit (Qiagen, Germany) following the standard protocol. About 700 µl of the sample was

loaded into an RNeasy column seated in a collection tube and spun for 30 seconds at 10,000

rpm and the flow-through was discarded. About 350 μl buffer RW1 was added to the column

and spun for 30 seconds at 10,000 rpm and the flow-through was discarded. To eliminate the

contaminating genomic DNA, the column was then treat with RNase-free DNase I (Qiagen,

Germany) by adding 80 μl of prepared enzyme solution (10 μl DNase I stock solution in 70

μl Buffer RDD) right on the column membrane. The treated column was kept at room

temperature for 15 minutes. About 350 μl Buffer RW1 was added to the column and column

was centrifuge for 30 seconds at 10,000 rpm and flow-through was discarded. The column

was then shifted to a new collection tube. About 500 μl of RPE buffer (containing ethanol)

was loaded on the column, and the column was spun for 30 seconds at 10,000 rpm. The flow-

Chapter 4


through Discard. The column was again treated with 500 μl of RPE buffer and now spun for

2 minutes at 10,000 rpm. To elute the purified RNA, the column was shifted to a new

microfuge tube (1.5 μl) and 50 μl of RNase-free water was directly added on to the RNeasy

silica-gel membrane. The tube was closed gently, and centrifuged for 1 min at 10,000 rpm.

The elution contain the purified bacterial RNA and was immediately stored at -80°C.

Integrity of the purified RNA samples was determined using an Agilent 2100 Bioanalyzer by

submitting the samples to qb3 facility (University of California, Berkeley), and the results

were provided to the lab. Quantity and purify of the extracted RNA was estimated using the

Nanodrop 1000 (Thermo Scientific, USA). Non-bacterized control plant pellets were

processed in the same manner.

The parameters to determine the quality and quantity of RNA from Nanodrop analysis are as

below:

Parameter Description Expected Result Quantity of RNA Measured in ng/µl Higher are better

Quality of RNA

260/280

ratio

Ratio of absorbance at 260 nm

and 280 nm. Measures purity

of Nucleic acids

~2.0 indicates pure RNA;

lower value indicates

DNA/protein contamination

~1.8 for Pure DNA; lower

value indicates DNA/protein

contamination

260/230

ratio

Ratio of absorbance at 260 nm

and 230 nm. A secondary

measure of nucleic acid purity

2.0-2.2; lower value indicates

presence of contaminants

The parameters to determine the integrity of purified RNA from Bioanalyzer analysis are as

below:

Parameter Description Expected Result

RNA Integrity Number (RIN)

Measures integrity of RNA;

measured from 1 to 10;

1 highly degraded RNA,

10 fully intact RNA

Higher are better; ideal value

is 10

23S / 16S ratio

Secondary measure for RNA

integrity; intact bacterial RNA

sample should have a ratio of

approximately 2:1 for 23S and

16S rRNA, respectively.

Higher are better; ideal value

is 2.0

Chapter 4


4.2.7 cDNA synthesis from extracted RNA

First strand of cDNA was generated from extracted RNA using SuperScript II (Invitrogen

Life Technologies, U.S.A.) and random hexamers as primers. First, RNA-primer mixture was

prepared by adding 2 μl RNA sample to 1 μl 10 mM dNTP mix, around 2 μl random

hexamers (50 ng/μl) and 5 μl of RNase-free water to make a total volume of 10 μl. The RNA-

primer mixture was incubated at 65°C for 5 minutes, and was then placed on ice for 1 minute.

In a separate tube, a 2X reaction mix was prepared containing 10X RT buffer (2 μl), 25 mM

MgCl2 (4 μl), 0.1 M DTT (2 μl) and RNaseOUT (1 μl). The prepared 2X reaction mix (9 μl)

was added to RNA/primer mixture, the contents were mixed gently, and collected by brief

centrifugation using a short spin. The resulting mix was kept at room temperature for 2

minutes. About 1 μl of SuperScript II was added to the prepared mix. For a control reaction,

the same procedure was followed, but 1 μl RNases-free water was added instead of

SuperScript II. The final mix was kept at room temperature for 10 minutes and then incubated

at 42°C for 50 minutes using a thermocycler. The synthesis reaction was terminated by

keeping the mix at 70°C for 15 minutes. The mix containing the first strand cDNA was kept

on ice for some time and was then collected by a brief short spin. To degrade the RNA, the

mix was treated with 1 μl of RNase H and incubated for 20 minutes at 37°C. The synthesized

first strand cDNA was stored at -20°C. Non-bacterized control plant RNA was processed in

the same manner.

4.2.8 qPCR Primer designing

Fifteen genes (and two housekeeping genes for used for gene expression normalization and

bacterial RNA confirmation) of strain PsJN studied for in-planta gene expression (Table 4.1)

were selected for their involvement in plant growth promotion, plant invasion and infection.

Primers for the genes were designed, specifically for qPCR SYBR Green Fluorescent

Chemistries, using the Primer Blast (Primer3 software) provided at www.ncbi.nlm.nih.gov.

Strain PsJN genome sequences were accessed through GenBank database. For convenience,

the graphical view of the genome sequence was used to easily locate the target genes and

Primer Blast the gene region. The parameters for designing the primers were followed as

described by Thornton and Basu (2011). The length of the primers was kept between 18-24

bp. Melting temperatures (Tm) were kept between the optimal Tm of 63–64°C. The primer

pairs were designed to generate 80 and 200 bp of product. For a stable primer-template

Chapter 4


duplex, GC clamps 1 to 2 were chosen for the primer selection. The rest of the parameters

were left at default values.

Table 4.1 Selected (15) strain PsJN genes used for expression analysis, their function, and their qPCR

primer sequences, and expected product size are given. Two bacterial housekeeping genes used as

endogenous control and bacterial detection in the in-planta samples are also provided.

Sr. # Gene Function Primers Product

(bp)

1. Bphyt_0126 Quorum Sensing

(luxI) F - AGTTCCAGCCCGAAACGTCG

R - GTCGGGCATGTCCCTGTTCC 120

2. Bphyt_0280 Siderophore

(Aerobactin) F - CGGCATTTCACCTTCGCTGC

R - GGCCGGGTTGAAGATGGAGG 98

3. Bphyt_0418 Hemagglutinin F - CGCCGACGACACGAATTTCC

R - GCGGCGACCTCGACAATACG 192

4. Bphyt_2078 Peroxidase F - CCAAAGGTGCCGACGAAACG

R - GCGAGCTGATCGGGATTTTCC 148

5. Bphyt_2156 IAA degradation

(iacC) F - GCTCGAGAACACCACCGACC

R - TCGACGATTTCGGGCACCAG 174

6. Bphyt_3289 Pili

(type IV pilin protein) F - CGACCCGAATGGACTCGACG

R - GTTGGCGGTGGCTGAAAACG 95

7. Bphyt_3832 Flagella

(fliC) F - ATGTCGGCAGCGAAGATCGG

R - TGGCCGTGTTGTTCTGGTCC 178

8. Bphyt_4275 Quorum Sensing

(luxI) F - ATCTGGTCGGCGAACGTCAC

R - AAACCGGCGGTGAGGAACAG 85

9. Bphyt_4858 Pectinase

(Endopolygalacturonase) F - GTCCGTTGAGCACCGAGGTC

R - GCGCCAACGGCAATCTGTTC 132

10. Bphyt_5212 Type 3 Secretion System F - CCGGGTCGATGCGTTTTGC

R - TGTAATGGCGCCGACAATGG 191

11. Bphyt_5397 ACC Deaminase F - ACCGGGTCGGCAACATTCAG

R - AGCCAGCCGGAATCGCATAC 153

12. Bphyt_5838 Cellulase

(Endoglucanase) F - TTACACGCAGTTGGGCGAGG

R - TTGAAGCCTTGCGGTCCAGG 105

13. Bphyt_5888 β-galactosidase F - GCGGCACGTCCCTGAAACC

R - CGACGGCGACATGCAAACC 110

14. Bphyt_6420 IAA Synthesis F - AGCGGATTTCGGATCGCTCG

R - AGCGTGTCCAACTGGCCTTG 161

15. Bphyt_6562 β-xylosidase F - GCTGGTGCTGTGTCCATTGC

R - GCGCCGATCCCATCGAAGAAG 127

- Bphyt_6584 rpoD

(qPCR control) F - CCCTCGCCGCTGAAGAAGAC

R - AGGCAGTCGCTCGTGAGTTG 160

- Bphyt_0737 dnaK

(bacterial detection) F - CGTTCCTGGGCGGTGAAGAC

R - TGCTGGCTCGACGACAGTTC 160

4.2.9 Standard PCR for cDNA analysis

Standard PCR was performed on the first strand cDNA samples to confirm presence of

bacterial cDNA generated from total RNA and to ensure effective elimination of bacterial

genomic DNA during DNase treatment. PCR was performed for three bacterial genes, ACC

Chapter 4


Deaminase (Bphyt_5397), rpoD (Bphyt_6584), and dnaK (Bphyt_0737). For this, PCR

master mix (Invitrogen Superscript II Kit, USA) was prepared by mixing 5 μl of 10X PCR

buffer, 3 μl of 25 mM MgCl2, 1 μl of 10 mM dNTP mix, 1 μl each of 1 μM forward and

reverse primer (separate reaction for each gene), 1 μl of 1:10 dilution of first strand cDNA,

and 0.4 μl of Taq DNA polymerase (Invitrogen, USA). The final volume of the mix was

adjusted to 50 μl using RNase-free water. For the control reaction, 1 μl of the RT control

(prepared in section 4.3.7) was used instead of first strand cDNA and primers for all three

genes were added to same reaction tube. PCR amplification was performed with initial

denaturation at 94°C for 2 minutes, followed by 30 cycles of denaturation (94°C for 15s),

annealing (55°C for 30s) and extension (68°C for 1 minute) with a final extension at 72°C for

10 min. the amplified samples were stored at 4°C before analysis.

The resulting PCR product (approximately 150-160 bp) was visualized on 1% agarose gel

containing ethidium bromide and compared to a 1 kb ladder (ThermoFisher Scientific, USA)

for size confirmation. For this, about 1g agarose (Fisher Scientific, USA) was dissolved in 1×

TAE buffer and heated in microwave oven for mixing. The gel was cooled down and then 50

μl of 10 mg/ml ethidium bromide (ThermoFisher Scientific, USA) was added and mixed, and

the gel casted in the electrophoresis tray with the fitted comb. After casting, the tray

containing gel was shifted to electrophoresis chamber containing the 1× TAE buffer. The gel

was completely submerged in the tank buffer. About 5 μl of amplified DNA samples were

mixed with 1 μl 6x loading dye (ThermoFisher Scientific, USA) and loading into the wells of

the gel. The first well was loaded with a 100 bp ladder (ThermoFisher Scientific, USA) to

verify correct size amplicons. The power supply was connected and the electrophoresis was

performed at a constant voltage of 5 V/cm for 40 minutes. The DNA bands were analyzed

using Gel Doc System (Biorad, USA).

To verify the cDNA as bacterial, PCR for all three bacterial genes (single reaction tube) was

performed using the cDNA samples synthesized from non-bacterized control plants with

primers for all three genes. Absence of DNA bands was taken as confirmation that cDNA

from bacterized plants was of bacterial origin.

4.2.10 qPCR for in planta differential gene expression

To analyze the differential expression of genes for bacteria grown in planta, relative

quantification qPCR was performed for the selected bacterial genes (Table 4.1). For a

Chapter 4


comparative analysis, cDNA prepared from the in-planta grown bacterial cells was used as a

test sample, while cDNA prepared from M9 cultured bacteria was used as a calibrator

sample. The rpoD was used as an endogenous control (internal control) to normalize the gene

expression between the test and calibrator samples (Savli et al., 2003; Wang et al., 2016).

SYBR® 2X Green PCR Master Mix (Applied Biosystems, USA) was used as qPCR master

mix and Applied Biosystems 7300 Real-Time PCR System (USA) was used to study relative

quantification of genes. A 25 μl qPCR reaction was prepared for each sample replicate by

mixing 12.5 μl of master mix, 1 μl 1:10 dilution of first strand cDNA strand (template), 1 μl

of 300 nM forward and reverse primers, and 10 μl of PCR grade water. Three replicates for

each gene were used. A profile for relative quantification qPCR was set on the Sequence

Detection Software v1.3 of AB7300 qPCR system with rpoD set as internal control. The

thermocycling conditions were set as follows: 2 minutes at 50°C, 10 min at 95°C, followed

by 45 cycles at 95°C for 15 s and 60°C for 1 min.

The completed qPCR run was analyzed using the Relative Quantification plugin provided

with the software. The software was operated according to the directions provided in the

software manual. Genes up and down regulated were identified using the graphical view of

the analyzed results. The results were exported into a Microsoft Excel Spreadsheet.

The amplified products obtained by qPCR amplification were analyzed using Dissociation

Curve Analysis to confirm a single product type. For this, a dissociation curve profile was set

on the qPCR software with a single cycle of 95°C for 15 minutes, 60°C for 30 minutes and

again 95°C for 15 minutes. The results were exported into a Microsoft Excel Spreadsheet.

4.3 Results

4.3.1 Bacterial estimates in the inoculated plants

The plants inoculated with four bacterial doses (104, 106, 108, and 109 cfu/ml) were tested on

day 0, 2, 4 and 6 to check the abundance of bacteria in leaf tissue (Figure 4.1 and 4.2). This

also allowed identifying best inoculation dose for maximal bacterial recovery for RNA

extraction.

Among the three doses initially tested (104, 106 and 108 cfu/ml), the maximum bacteria were

recovered from the highest of 108 cfu/ml dose on day 6 (5.59±0.15 log cfu/gfw). However,

Chapter 4


recovery was not much different from day 2 and 4 (5.29±0.1 and 5.24±0.17 log cfu/gfw).

Dose 106 cfu/ml exhibited second highest abundance of bacteria with highest counts on day 6

(4.49±0.22 log cfu/gfw). The counts increased from day of inoculation (log cfu/gfw: Day 0,

3.39±0.06; Day 2, 3.83±0.15; Day 4, 4.34±0.14), indicating that bacterial population is

growing inside leaf issue. Dose 104 cfu/ml yielded least count among the bacterial doses

tested, with highest counts observed on day 6 (2.99±0.43 log cfu/gfw) that increased from the

day of inoculation (log cfu/gfw: Day 0, 2.32±0.06 log cfu/gfw; Day 2, 2.81±0.13; Day 4,

2.6±0.17). It was evident from these results that bacterial population was growing slowly in

the leaf tissue before reaching the highest achievable cell density of around 4.68x105 cfu/gfw

the tissue. Likely, any further increase in cell density would require treatment with a more

concentrated inoculum dose.

Figure 4.1 Bacterial counts in leaf tissue at four different day (0, 2, 4, 6) after inoculation with three

different dose of bacterial suspension (104 cfu/ml, blue; 106 cfu/ml, red; 108 cfu/ml, green), using

vacuum infiltration method.

On treatment with 109 cfu/ml bacterial suspension, the maximum bacterial counts post

inoculation were observed on day 2 (8.26±0.1 log cfu/gfw) which declined from day of

inoculation (Day 0, 7.8±0.19 log cfu/gfw). The counts continued to decline thereafter, with

the lowest counts observed for day 6 (log cfu/gfw: Day 6, 7.62±0.26, Day 4, 7.76±0.13).

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As the aim of the present study was to isolate maximum bacterial biomass that survives for

some time in-planta to allow plant specific bacterial gene expression to occur, the bacterial

cells from day 2 were collected for further process after inoculating the plants with 109 cfu/ml

bacterial suspension.

Figure 4.2 Bacterial counts in leaf tissue at four different days (0, 2, 4, 6) after inoculation with 109

cfu/ml bacterial suspension, using vacuum infiltration method.

4.3.2 RNA extraction from bacterial pellets

Bacterial pellets were recovered from a total of 12 bacterized plants and four plants were

processed at a given time (one biological replicate). The three combined biological replicates

were processed using TRIzol-RNeasy hybrid RNA extraction protocol, for both in-planta and

M9 grown bacteria, and analyzed for RNA quantity and quality.

Nanodrop analysis revealed that in-planta RNA sample contained about 14 ng/µl of total

RNA and the quality ratio for RNA purity were 2.16 (260/280) and 1.90 (260/230). The RNA

samples from M9 grown bacteria contained much higher RNA yield (101.2 ng/ul), and the

RNA purity was also much better (260/280 ratio, 2.16; 260/230 ratio, 2.41).

Bioanalyzer analysis examining the RNA integrity revealed that in-planta RNA sample

suffered moderate degradation during processing, as revealed by poor 16S rRNA and 23S

rRNA peaks and low RIN value (6.3) and 23s/16s ratio (1.1) (Figure 4.3). Nevertheless,

distinct bacterial 16S and 23S rRNA peaks were observed, indicating presence of bacterial

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RNA in the in-planta samples. Moreover, the contaminating plant RNA was also suspected to

be present, thereby compromising the overall results for bacterial RNA quality of the in-

planta sample. On the other hand, M9 bacterial RNA sample showed much better results and

clear and distinct peaks for the two bacterial RNA types were visible (Figure 4.4). The RIN

value (9.9) and the 23S/16S ratio (1.5) were also very high for the M9 sample, indicating a

high quality sample.

Figure 4.3 Bioanalyzer results for in-planta bacterial RNA samples. The peaks for 16S and 23S rRNA

are indicated along with a virtual gel of the run sample.

Figure 4.4 Bioanalyzer results for M9 bacterial RNA samples. The peaks for 16S and 23S rRNA are

indicated along with a virtual gel of the run sample.

Chapter 4


4.3.3 Standard PCR for cDNA analysis

A standard PCR was run for three strain PsJN genes (ACC Deaminase, dnaK, rpoD) using

the first strand cDNA generated from bacterial RNA. The amplicons were analyzed using

agarose gel electrophoresis.

All tested genes were detected in both in-planta and M9 samples. The ACC deaminase gene

gave a faint band in both the samples, verified by the correct size amplicon band (Lane P1,

M1; 153 bp) visualized on the gel. The gene dnaK produced bands of variable intensity, with

a much thicker band in M9 sample (Lane P2, M2; 160 bp). This indicated that the expression

of this gene is not consistent between the two types of samples. The third gene, rpoD (Lane

P3, M3; 160 bp), produced intense bands in both the samples, indicating that gene has a high

expression independent of growth conditions. Both samples showed fairly consistent

expression of the rpoD.

L 100 bp Ladder M1 ACC Deaminase (Bphyt_5397)

P1 ACC Deaminase (Bphyt_5397) M2 dnaK (Bphyt_0737)

P2 dnaK (Bphyt_0737) M3 rpoD (Bphyt_6584)

P3 rpoD (Bphyt_6584) MC M9 RT control

PC In-plata RT control C Non-Bacterized plant

Figure 4.5 Agarose gel electrophoresis of three PCR amplified strain PsJN genes from in-planta (P1,

P2, P3) and M9 (M1, M2, M3) samples using the first strand cDNA as template. The respective RT

controls (PC and MC), non-bacterized plant sample (C), and 100 bp ladder (L) are also shown.

100 bp

200 bp

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The lane PC and MC loaded with control reactions (amplified using RT-PCR control of in-

planta and M9 samples) showed no amplicon bands. This confirmed that the amplicons

generated for the three tested genes originated from bacterial RNA and not the contaminating

bacterial genomic DNA. Finally, Lane C was loaded with reaction performed with cDNA

samples of non-bacterized control plant. Again, no DNA band was detected in this last lane,

verifying that amplicons generated for the three test genes from bacterized plants cDNA

samples were in fact of bacterial origin and not from contaminating plant RNA (Figure 4.5).

4.3.4 qPCR for in-planta differential gene expression

Relative quantification qPCR was performed to explore the differential expression of 15

genes important for plant growth promotion and association. For this, expression of these

genes was compared between bacteria grown in-planta to the bacteria grown on M9 minimal

media using rpoD gene (Bphyt_6584) as an endogenous control (Figure 4.6). All amplicons

were tested by dissociation curve analysis to verify a single product type for both in-planta

and M9 samples.

Two plant growth hormone modulating genes studied presently showed increased expression

during in-planta bacterial growth. The gene involved in IAA degradation (Bphyt_2156) was

upregulated by 5.23 fold, had an average Ct value of 38.79 for in-planta grown bacteria and

31.34 for M9 grown bacteria, and a single product was detected with dissociation curve

analysis for both sample types (85.2°C). While ACC deaminase gene (Bphyt_5397),

targeting plant stress hormone ethylene, was slightly upregulated 1.93 fold during in-planta

growth. The average Ct values for this gene were 36.93 (in-planta) and 28.942 (M9) with a

single product type (87.2°C) detected by dissociation curve (Figure 7).

Three plant cell-wall targeting enzymes were also increasingly expressed in bacteria growing

in-planta. Cellulase gene (Bphyt_5838) was upregulated by 6.33 fold in the in-planta bacteria

with average Ct values of 33.09 (in-planta) and 25.86 (M9). The gene amplicons contained a

single product (87.0°C) identified through dissociation curve analysis. Compared to

Cellulase, Pectinase (Bphyt_4858) was upregulated to a higher level with 19.92 fold

increased expression in bacteria growing in-planta. The average Ct values for this gene were

39.45 (in-planta) and 34.551 (M9) with a single detected product (85.9°C). The third enzyme,

β-xylosidase (Bphyt_6562), was also highly upregulated in the in-planta bacteria with 14.05

Chapter 4


fold increased expression compared to M9 bacteria. Average Ct values for this gene were

34.54 (in-planta) and 28.57 (M9) with a single product (85.2°C).

Sugar metabolism gene β-galactosidase (Bphyt_5888) was also upregulated during in-planta

growth of the bacteria. The expression of the gene increased by 9.26 fold during in-planta

bacterial growth with average Ct of 36.67(in-planta) and 29.99 (M9) and a single product was

verified (84.2°C).

Expression of two Quorum Sensing genes was different for the two bacterial growth

environments. One LuxI gene (Bphyt_0126) was upregulated during in-planta bacterial

growth by 5.02 fold. The Ct values for the gene were 39.25 (in-planta) and 31.79 (M9)

indicating overall low copy number of the transcripts. Again, a single amplicons was

confirmed by dissociation curve analysis (85.9°C). In contrast, the second LuxI gene

(Bphyt_4275) was downregulated by 0.43 fold during in-planta bacteria growth, with average

Ct values of 34.91 (in-planta) and 23.91 (M9). The gene product was verified by detecting a

single product (82.2°C).

Among the other genes downregulated was the gene for IAA synthesis. The Indole

Acetamide Hydrolase (Bphyt_6420) was downregulated 0.08 fold during in-planta bacterial

growth compared to M9 bacterial growth. This result is consistent with the finding that

expression of IAA degrading enzyme (Bphyt_2156) was upregulated during in-planta

bacterial growth, indicating that bacteria decrease the IAA concentration while growing in-

planta. The average Ct value for the gene were 41.34 (in-planta) and 28.97 (M9) with a single

product detected by dissociation curve (82.4°C). Similarly, the expression of flagellar protein

gene was also decreased during in-planta growth. The gene was downregulated by 0.131 fold

during in-planta growth with the average Ct values of 33.50 (in-planta) and 20.79 (M9) and a

single amplicon (87.1°C).

Interestingly, genes consistent with bacterial pathogenicity were also expressed more by the

host beneficial bacteria during in-planta growth. Among the three genes studied, Peroxidase

gene (Bphyt_2078) showed considerably high expression compared to the other two genes,

with 5.90 fold upregulation during in-planta bacterial growth. The average Ct values for the

gene were 32.62 (in-planta) and 25.28 (M9) with a single amplicon confirmed by dissociation

curve (85.4°C). The other two genes also showed an overall upregulation during in-planta

bacterial growth, but the expression was not much higher compared to M9 grown bacteria,

indicated by the overlapping RQ error range of the in-planta and M9 samples. Among these

Chapter 4


two genes, a Type III secretion system gene (Bphyt_5212) was upregulated by 2.92 fold

during in-planta growth, with average Ct values of 40.70 (in-planta) and 34.45 (M9) and a

single gene product (88.6°C). The other gene, Hemagglutinin (Bphyt_0418), was only

slightly upregulated by 2.02 fold during in-planta growth with an average Ct values of 37.28

(in-plant) and 27.85 (M9) for the single product detected (88.2°C).

Figure 4.6 In-planta gene expression profile of 15 Burkholderia phyrofirmans PsJN genes versus M9

cultured bacteria using Relative Quantification qPCR (Green bars, upregulated genes; Red bars,

downregulated genes; Gray bars, no change).

Lastly, gene expression of two traits remained unchanged for the two bacterial growth

conditions studied. The Siderophore gene (Bphyt_0280) showed no change in the gene

expression with an average Ct values of 37.89 (in-planta) and 28.58 (M9) and displayed a

single product (81.2°C). The second gene, Pili (Bphyt_3289) which is important in bacterial

attachment to substratum and surfaces, was in fact slightly downregulated in-planta, but the

overall expression of the gene was similar to bacteria growing on M9 media. The expression

of the gene was 0.957 fold less in-planta with average Ct values of 37.51 (in-planta) and

28.65 (M9). However, by taking the RQ error range in to account for the two sample types,

the expression of the gene appeared to be very similar for in-planta and M9 bacteria. Again, a

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single product was confirmed by dissociation curve for ACC deaminase gene (86.1°C)

(Figure 4.7).

Figure 4.7 Dissociation curve analysis for ACCD gene (Bphyt_5397) for both M9 and in-planta

samples indicating a single product type.

4.4 Discussion

Present work was conducted to study the gene expression of 15 bacterial genes important for

plant growth promotion and association in the plant growth promoting Burkholderia

phytofirmans PsJN. For this, expression of these genes was compared between Strain PsJN

grown inside tomato plants to the bacterium grown on M9 minimal media using Relative

Quantification qPCR. Results indicated that the bacterium actively grows inside leaf tissues.

More importantly, during the in-planta growth, the bacterium expresses traits compatible with

plant growth promotion and invasion. The present comparative transcriptome profiling of

strain PsJN will likely better elucidate host-bacterial relationship and thus explicate

endophytic role of the bacterium.

Previously only few studies have reported strain PsJN gene expression in-planta. In the first

study, the research group did an RNAseq based transcriptome analysis for the bacterium

infecting potato plants with and without drought stress (Sheibani-Tezerji et al., 2015). While

the second study reported the in-planta expression of selected Strain PsJN genes involved in

iron transport and sequestration in Arabidopsis thaliana (Zhao et al., 2016). Although, in both

Chapter 4


studies similar procedure was used for RNA and cDNA preparations, different shoot samples

were employed for bacterial RNA extraction. Both studies proposed similar findings

suggesting increased expression of iron acquisition and transport genes.

Presently, at start of this work, two important factors needed to be addressed that limited the

scope of the study in getting quality bacterial transcripts for any gene expression study. One

such factor was getting enough bacterial cells from plant tissue for mRNA extraction. Unlike

pathogenic bacteria, plant growth promoting bacteria are known to establish low cell numbers

in host tissue (Yu et al, 2013; Compant et al., 2010). Here, Strain PsJN was observed to

maintain a modest cell density (5.59±0.15 log cfu/gfw) in the tomato leaf tissue. Similar

counts have been reported for the bacterium endophytically colonizing switchgrass,

Arabidopsis thaliana and grapevine leaf tissues (Compant et al., 2005a; Kim et al., 2012; Su

et al., 2016). Endophytic bacterial population depends on many factors, including the type,

tissue and age of the plant host (Costa et al., 2012; Hardoim et al. 2015). Nevertheless, to get

high cell counts for maximum bacterial RNA extraction, plants were treated with a much

higher dose of 109 cfu/ml. Appreciable total bacterial RNA quantities were recovered using

this dose (14 ng/µl). The other two studies on Strain PsJN in-planta gene expression did not

report on the bacterial RNA quantities obtained from their extraction methods.

The other limiting factor for the present study was getting high quality bacterial RNA. Due to

poor half-life of bacterial RNA, rapidity of extraction and lysis of bacterial cells is very

important (Mangan et al., 1997; Jahn et al., 2008). Moreover, getting sufficient quantities of

high quality RNA also depends on plant inoculation and sampling methods (Kałużna et al.,

2016). The methods employed in the present work for bacterial inoculation, recovery and

total RNA extraction produced in-planta bacterial RNA of modest quality (RIN 6.3), while

high quality RNA was recovered from M9 grown bacterial (RIN 9.9). This difference in RNA

quality recovered from in-planta and M9 samples could be explained by the fact that bacterial

RNA extraction is affected by the type of bacteria species, plant material and the environment

from where bacteria have been isolated (Nolan et al., 2006). Nevertheless, RIN values higher

than 5 are considered sufficient for routine gene expression studies (Fleige and Pfaffl 2006;

Jeffries et al. 2014). The in-planta grown bacterial RNA obtained in the present study was in

fact analyzable for gene expression study conducted here.

In the present study, bacterial genes for plant cell-wall degrading enzymes were upregulated

during in-planta growth. Moreover their expression was highest compared to other genes

Chapter 4


analyzed in the study. This indicates the importance of these genes for the bacterium for

effective colonization of tomato plants. The present finding also supports the work of

Compant et al. (2005a) on colonization of grapevine by Strain PsJN, who proposed the

possible role of cell-wall degrading Cellulase and Pectinase of Strain PsJN in systematically

colonization of the host. Importance of these enzymes in endophytic colonization was also

indicated in Bacillus strains in two separate studies, one involving overexpression of

Pectinase gene and the other involving deletion mutation of Cellulase gene (Fan et al., 2013;

Fan et al., 2016). Interestingly, Sheibani-Tezerji et al. (2015) did not find the transcripts of

these cell-wall targeting enzymes. Nevertheless, these enzymes are of prime importance in

the endophytic growth of a bacterium, and the present work confirms their expression during

endophytic growth Strain PsJN.

The bacterium also expressed enzymes for sugar metabolism during in-planta growth. β-

galactosidase and β-xylosidase were both significantly upregulated during in-planta growth,

indicating that the bacteria is metabolically active in the plant host. Enzymes like β-

xylosidase can convert hemicellulose into easily metabolizable sugars (Fouts et al., 2008;

Shao et al., 2011). Bacteria, both beneficial and pathogenic, can use these enzymes

synergistically with other plant cell-wall targeting enzymes to get carbon for their growth

(Mitter et al., 2013). In the present study, β-xylosidase was among the highly upregulated

genes, and expression was comparably similar to that of Cellulase and Pectinase genes.

Therefore, it may be assumed that strain PsJN expresses these enzymes for getting nutrients

during endophytic growth besides using them to systematically colonize the host. Sheibani-

Tezerji et al. (2015) also proposed the expression of sugar metabolism genes in strain PsJN

proposing that bacteria was metabolizing plant sugars to thrive inside plant host.

Endophytic bacteria can also improve plant growth by modulating the levels of plant-growth

related hormones. Of these, Indole Acetic Acid (IAA) can regulate several plant development

related processes by controlling both plant growth promotion and inhibition, including leaf

development and morphogenesis (Wang et al., 2005; Glick, 2012). Endophytic bacteria can

finely control the levels of IAA pool inside plant host by either degrading or producing these

hormones, thereby imparting growth effects on host plant (Leveau and Lindow, 2005). In the

present study, gene for IAA degradation was upregulated and one of the genes involved in

IAA synthesis was downregulated during in-planta bacterial growth. This indicates that the

bacterium probably responds to increased levels of IAA in plant host by degrading the

hormone, further supporting the previous explanation. Indeed, this finding also supports the

Chapter 4


work of Zúñiga et al. (2013), who identified the importance of IAA degradation by Strain

PsJN to improve Arabidopsis thaliana growth. They noticed that iacC mutant Strain PsJN

(detective in IAA degradation) was unable to confer growth promoting effects on their plant

host that wild type Strain PsJN produced. In contrast to present work, Sheibani-Tezerji et al.

(2015) detected the transcripts for IAA synthesis genes and not the iacC transcript in their in-

planta Strain PsJN transcriptome. Nevertheless, further work is needed to precisely identify

the interplay of these gene functions during in-planta growth of beneficial bacterial.

The other tested gene involved in modulating plant hormone, was ACC deaminase. This

enzyme can target the precursor of plant hormone ethylene, which is expressed by plants

during stress and causes growth inhibition. Moreover, ethylene signaling is also involved in

the development of plant leaf from juvenile to adult phase (Schaller, 2012). Expression of the

enzyme by growth promoting endophytic bacteria can alleviate the inhibitory effect of

ethylene by reducing the levels of this hormone in plant tissues (Glick, 2012). Here, the gene

of ACC deaminase was only slightly upregulated during in-planta growth of Strain PsJN. Sun

et al. (2009) showed that ACC deaminase deletion mutant of Strain PsJN had impaired canola

growth promoting activity compared to wild type bacterium. However, Sheibani-Tezerji et al.

(2015) did not identify ACC deaminase transcripts in the in-planta grown PsJN

transcriptome. Therefore, the present work identifies for the first time the expression of ACC

deaminase gene by strain PsJN selectively during in-planta growth.

Bacterial attachment and motility are known to play a role in rhizosphere, rhizoplane and

endophytic competence of endophytic bacteria (Compant et al., 2010). In the present work,

one of the flagellar genes tested was downregulated in the in-planta bacteria, while gene of

Pili showed no change in expression between the two growth environments studied. Lack of

flagella might also improve the endophytic colonization by decreasing host defense response,

as studied for Salmonella infecting Medicago (Iniguez et al., 2005). Therefore, the exact role

of flagella mediated endophytic competence is still not known (Reinhold-Hurek and Hurek,

2011). However, the in-planta bacteria studied here did produce flagella, indicated by higher

transcript copy of the gene (Ct value 33.50), suggesting that the bacterial movement in the

plant endosphere. Besides, active movement might be more important for the bacteria in the

growth media, as bacteria flagellar gene expression was higher in M9 media. Sheibani-

Tezerji et al. (2015) proposed that active bacterial movement in plants is less important once

bacterial population has established itself. Further investigation might reveal a better picture

about the involvement of these traits in bacterial endosphere competence.

Chapter 4


Bacterial quorum sensing (QS) is an important trait required for maintaining bacterial cell

population. A regulatory mechanism, QS is used by bacteria to regulate gene expression in a

cell density-dependent manner (Mitter et al., 2013). This mechanism can regulate various

functions required for establishing pathogenic or symbiotic relationships (Loh et al., 2002).

Two QS systems exist in strain PsJN, where the one has been implicated in the growth

promoting ability of the bacterium: Zúñiga et al. (2013) showed that stain PsJN defective in

one of the N-acyl homoserine lactone gene (Bphyt_0126), was inefficient in colonizing and

establishing a beneficial interaction with Arabidopsis thaliana. Their findings are supported

by the present study, where this gene was in fact upregulated during in-planta bacterial

growth. On the other hand, the second QS N-acyl homoserine lactone gene tested was slightly

downregulated in the in-planta bacteria. Zúñiga et al. (2013) noted that second quorum

system was not required by Strain PsJN for host colonization and growth promotion.

Furthermore, QS has been indicated to require bacterial cell densities greater then 107cfu/ml

(Deep et al., 2011). While endophytic bacteria are known to establish root endophytic

population between 105-107 cfu/gfw, strain PsJN is reported to maintain root endophytic

population between 104-107cfu/gfw in different host plants (Pillay and Nowak, 1997;

Compant et al., 2005a; Kim et al., 2012). In the present study, however, strain PsJN cell

densities were close to 108 cfu/gfw on the day of extraction (Day 2 post inoculation) because

a high inoculum dose (109 cfu/ml) was used to infiltrate host plant. Interestingly, strain PsJN

cell densities reported by Zúñiga et al. (2013) inside Arabidopsis thaliana roots were

unusually very high (108 cfu/mg fresh weight) for an endophytic bacterium, as much lower

bacterial counts (104 cfu/gfw) were latter reported by Su et al. (2015) for strain PsJN

endophytically colonizing Arabidopsis thaliana roots. Nevertheless, we can conclude from

this discussion that strain PsJN requires only one of the QS systems to competitively colonize

host plant to initiate beneficial interaction, and that this system can probably operate with cell

densities lower than 107 cfu/gfw.

Three bacterial pathogenesis genes were also investigated in the present study. Out of these,

only Peroxidase gene was significantly upregulated in the in-planta bacteria, indicating that

the bacteria were challenged inside host plant by oxidative stress. Endophytic bacteria can

often elicit an oxidative burst like defense response in their host plants (Mitter et al., 2013).

Strain PsJN has also been shown to induce host defense response in grapevines during

endophytic growth (Compant et al., 2005a). This induction can be linked to the fact that

endophytic bacteria produce cell-wall degrading enzymes to systematically colonize host, a

Chapter 4


characteristic also shared by plant pathogenic bacteria (Buonaurio, 2008). The other two

pathogenicity genes, Hemagglutinin gene and one Type III secretion system gene, despite

showing a slight increase, were not significantly upregulated in in-planta bacteria. Thus, these

functions are less important for endophytic competence of bacteria. Sheibani-Tezerji et al.

(2015) also did not observe the transcripts of these functions in Strain PsJN infecting potato

plants.

Conclusions

Conclusions


Conclusions

Wild perennial plants represent a rich source to isolate new and interesting bacteria with

biotechnological potential.

Wild Cannabis sativa and Dodonaea viscosa harbor many endophytic bacteria with

multiple plant growth promoting traits, which are also agriculturally beneficial.

Selective isolation method proposed in the present study can improve the isolation of

potential plant growth promoting endophytic bacteria.

The endophytic bacteria of C. sativa and D. viscosa can enhance the growth of non-host

canola plants.

The growth promoting endophytic bacteria isolated from C. sativa and D. viscosa are

phylogenetically related, indicating that this ability is evolutionary conserved.

IAA production is an important bacterial trait for plant growth promotion. The bacteria

that produce IAA in the range 2-10 µg/ml can generally have plant growth promoting

effects on canola plants. The plant growth promoting Burkholderia phytofirmans PsJN

expresses gene of IAA production very modestly during in-planta growth. Collectively,

this indicates that endophytic bacteria that produce lower amounts of IAA tend to be plant

growth promoting.

Endophytic bacteria isolated from C. sativa and D. viscosa also possesses the ability to

inhibit the growth of phytopathogenic fungi. The bacteria also produce fungal cell-wall

degrading enzymes and siderophore, which may play a role in inhibiting the fungal

growth.

Most of the endophytic bacteria produce plant cell-wall degrading enzymes needed for

plant colonization. The endophytic strain PsJN also expresses this trait during in-planta

growth.

Endophytic bacteria isolated from C. sativa and D. viscosa also possess the ability to

solubilize inorganic phosphate, thereby increasing phosphorus availability for the plants.

The most interesting isolates from C. sativa were Pantoea vagans MOSEL-t13,

Pseudomonas geniculata MOSEL-tnc1, Serratia marcescens MOSEL-w2, Enterobacter

asburiae MOSEL-t15, Pseudomonas koreensis MOSEL-tnc2, Stenotrophomonas

rhizophila MOSEL-tnc3, and Enterobacter cloacae MOSEL-w7. These bacteria had

multiple plant growth promoting traits, could promote canola growth under normal and

salt-stress conditions, and could inhibit the growth of phytopathogenic fungi.

Conclusions


Paenibacillus sp. MOSEL-w13 also deserves especial consideration, as the strain strongly

inhibited fungal growth, and showed only 97% similarity to the type strain, indicating that

the bacterium may be novel.

The most interesting isolates from D. viscosa were Bacillus subtilis MOSEL-RD28,

Bacillus idriensis MOSEL-RD7, Bacillus cereus MOSEL-RD27, Pseudomonas

geniculata MOSEL-RD36, and Streptomyces alboniger MOSEL-RD3. These bacteria had

multiple plant growth promoting traits, could promote canola growth, and could inhibit

the growth of phytopathogenic fungi.

Getting high quality and quantity bacterial RNA to study in-planta bacterial gene

expression is extremely challenging. The procedure followed in the present study allows

the extraction of RNA from in-planta grown bacteria that is analyzable through qPCR.

Thus, the procedure can be used to study the gene expression of endophytic bacteria that

are growing inside host plant.

The present gene expression study confirms for the first time that bacteria express ACC

deaminase while growing inside plants. By producing this enzyme, the plant beneficial

bacteria are known to modulate growth of their host plants.

Gene expression study concluded that the Burkholderia phytofirmans PsJN was active in

tomato leaves and expressed traits that are compatible with plant growth promotion and

invasion.

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Appendix A

Appendix A


Appendix A

Table A1: 0.03 M MgSO4

Ingredients Quantity (g/L)

MgSO4.7H2O 7.39

Contents dissolved in distilled water.

Autoclave was done by heating at 121°C and 15 psi pressure for 20 minutes.

Table A2: Tryptic Soya Agar


Tryptone Soya Agar (Oxoid CM0129) 30

Content dissolved in distilled water.

Autoclaving was done by heating at 121°C and 15 psi pressure for 20 minutes.

For half strength media, 15 g was dissolved in 1 liter distilled water.

Table A3: Tryptic Soya Broth


Tryptone Soya Broth (Oxoid CM0131) 40




Table A4: Nutrient agar (Half strength)


Nutrient Agar (Oxoid CM0003) 14



Table A5: R2A Agar


R2A Agar (Oxoid CM0906) 18.1



Appendix A


Table A6: 70% Ethanol

Ingredients Quantity (ml)

Ethanol (Scharlau ET00052500) 700

Distilled water 300

Table A7: 50% glycerol solution


R2A Agar (Scharlau GL00261000) 500

Distilled water 500


Table A8: 20% Bleach solution


Clorox® regular 200

Distilled water 800

Table A9: 0.5% Water agar


Agar technical (Oxoid LP0013) 5



Table A10: 0.5% Water agar with 25 mM NaCl



NaCl 1.46



Table A11: Murashige and Skoog Basal Salt medium


MS basal salts (Sigma-Aldrich M5524) 4.3

Sucrose 30




Appendix A


Table A12: Tryptic Soya Broth with Tryptophan (200 µg/ml)



Tryptophan (Scharlau TR04000025) 0.2




Table A13: Indole Acetic Acid Stock

Ingredients Quantity

IAA (Sigma-Aldrich I2886) 0.005 grams

Ethanol 20 ml

Distilled Water As needed to make 1000 ml total volume

Table A14: Salkowski Reagent

Solution A: 0.5 M FeCl3


FeCl3.6H2O 135.15

Distilled Water added to make 1 L total volume

Solution B: 35 % HClO4


HClO4 650

Distilled water 350

Reagent


Solution A 20

Solution B 980

Table A15: Tri-calcium phosphate minimal medium (Kuklinsky-Sobral et al., 2004)


Glucose 10

NH4Cl 5

NaCl 1

MgSO4.7H2O 1

Ca3(HPO4)2 0.8

Agar 15


pH was adjusted to 7.2


Appendix A


Table A16: Chrome-Azurol S (CAS) Agar (Pérez-Miranda et al., 2007)

Solution A

Ingredients Quantity (g/ 990 ml)

Chrome Azurol S (CAS) 0.060

Hexadecyltrimetyl ammonium bromide

(HDTMA)

0.073

Piperazine-1,4-bis (2- ethanesulfonic acid)

(PIPES)

30.24

Agarose 9


Solution B

Ingredients Quantity (10 ml)

FeCl3.6H2O 0.002 grams

HCl 0.008 ml

H2O Up to 10 ml

Final Media

Solution A 10 ml

Solution B 990 ml



Table A17: Cellulose Congo Red Agar (Hendricks et al., 1995)


K2HPO4 0.5

MgSO4 0.25

CMC (Sigma-Aldrich 419273) 1.88

Congo Red 0.20

Gelatin 2.0

Tap water 100 ml

Agar 15




Table A18: Pectin Minimal Agar (Hankin et al., 1971)


(NH4)2SO4 1

Na2HPO4 6

KH2PO4 3

Polygalacturonic acid (Pectin) 5

Agar 15

Contents were dissolved in distilled water.



Appendix A


Table A19: Pectin Minimal Agar (Hankin et al., 1971)


Iodine 3

Potassium Iodide 15

Contents were dissolved in distilled water to a final volume of 1 L.

Table A20: Skimmed Milk Agar (Bibi et al., 2012)

Solution A

Ingredients Quantity (g)

2X Tryptone Soya Broth (Oxoid CM0131) 80

Contents dissolved in 500 ml distilled water.



Solution B


Skimmed milk 40 grams



Full Media

Solution A 500 ml

Solution B 500 ml

The two solutions were mixed after autoclaving prior to pouring in petri plates

Table A21: Colloidal Chitin Agar (Bibi et al., 2012)



Colloidal Chitin 6

Agar 15




Table A22: Dual Culture Antifungal Agar (Bibi et al., 2012)


Tryptone Soya Agar (Oxoid CM0129) 15

Potato Dextrose Agar (Oxoid CM0139) 19.5



Appendix A


Table A23: Chrome-Azurol S (CAS) Agar (Alexander and Zuberer, 1991).

Solution 1 (Fe-CAS indicator solution)

Ingredients Quantity

Solution B (Table A16) 10 ml

CAS dye solution (0.06 g dye in 50 ml H2O) 50 ml

HDTMA solution (0.073 g in 40 ml H2O) 40 ml

The Solution B was fist mixed with CAS dye solution.

The resulting solution was slowly added to HDTMA solution with constant mixing.


Solution was cooled to 50°C.

Solution 2 (Buffer solution)


PIPES 30.24 g

KH2PO4 0.3

NaCI 0.5

NH4Cl 1.0

Agar 15

Contents were dissolved in 750 ml distilled water.

pH was adjusted to 6.8 using 50% KOH.

Final volume was adjusted to 800 ml using distilled water.



Solution 3 (Nutrient solution)


Glucose 2

Mannitol 2

MgSO4.7H2O 0.473

CaCl2 0.011

MnSO4.H2O 0.00117

H3BO3 0.0014

CuSO4.5H2O 0.00004

ZnSO4.7H2O 0.0012

Na2MoO4.2H2O 0.001




Solution 4 (Casamino acid solution)


Casamino acid 3

Contents dissolved in distilled water to a final volume of 30 ml.

Solution was filter sterilized.

CAS Media

Solution 1 100 ml

Solution 2 800 ml

Solution 3 70 ml

Solution 4 30 ml

Solution 2,3 and 4 were mixed first and the solution 1 was slowly added to the mix.

Appendix A


Table A24: M9 Minimal Agar

Solution A (20% Glucose)


Glucose 200


Solution was filter sterilized.

Solution B (1 M CaCl2)


CaCl2 110.98

Contents were dissolved in distilled water.


Solution C (1 M MgSO4)


MgSO4 120.36



Solution D (5× M9 Salts)


M9 Salts (Sigma-Aldrich M6030) 56.4



Solution E (Water Agar)


Agar 15

Content dissolved in distilled water to a final volume of 780 ml.


M9 Media

Solution A 20 ml

Solution B 200 ml

Solution C 0.1 ml

Solution D 2 ml

Solution E 780 ml

Table A25: Kings Broth B


Peptone 20

K2HPO4 1.5

MgSO4.7H2O 1.5


pH was adjusted to 7.2.


Appendix A


Table A26: Kings Agar B


Peptone 20

K2HPO4 1.5

MgSO4.7H2O 1.5

Agar 15


pH was adjusted to 7.2.


Table A27: 10 mM potassium phosphate

Kits Quantity (g/L)

KH2PO4 1.36

Content was dissolved in distilled water.

Table A28: Cell Lysis Buffer

Solution A (1 M Tris)


Tris (hydroxymethyl) aminomethane Base 121.4

Content was dissolved in distilled water.

pH was adjusted to 8.0 using HCL (concentrated)

Solution B (0.5 M EDTA)


Ethylenediaminetetraacetic acid (EDTA) 186.1

Content were dissolved in distilled water with constant mixing and maintaining pH at 8.0

pH was maintained at 8.0 by gradually adding NaOH (pellets)

Solution C (10% Triton X)


Triton X 100 ml

Distilled H2O 900 ml

Lysis Solution (1 L)

Solution A 20 ml

Solution B 4 ml

Solution C 100 ml

Distilled H2O 876 ml

Table A29: TAE buffer (50×)


Tris (hydroxymethyl) aminomethane Base 242 g

Glacial acetic acid 57.1 ml

0.5 M EDTA (Solution B, Table A28) 100 ml

Contents dissolved in distilled water to a final volume of 1 L.

1×TAE was prepared by mixing 20 ml of 50× in 980 ml of distilled water.

Appendix A


Table A30: 1% Agarose

Kits Quantity (g/L)

Agarose 10

Content was dissolved in 1×TAE (Table A29)

Table A31: Phenol-Ethanol Stop Solution

Kits Quantity (ml)

Water-Saturated Phenol (Invitrogen

AM9710)

5

Ethanol 95

Distilled Water 900

Table A32: Commercial Kits and Reagents

Ingredients Make

GoTaq® Green Master Mix Promega, USA (M7122)

GeneRuler 1 kb DNA Ladder ThermoFisher Scientific, USA (SM0311)

Ethidium Bromide Solution (10 mg/mL) ThermoFisher Scientific, USA (17898)

DNA Gel Loading Dye (6X) ThermoFisher Scientific, USA (R0611)

PureLink® PCR Purification Kit Invitrogen, USA (K310001)

TRIzol® Reagent Invitrogen, USA (15596026)

RNeasy Mini Kit Qiagen, Germany (74104)

RNase-free DNase I Qiagen, Germany (79254)

SuperScript First-Strand Synthesis System Invitrogen, USA (11904-018)

GeneRuler 100 bp Plus DNA Ladder ThermoFisher Scientific, USA (SM0321)

SYBR® Green PCR Master Mix Applied Biosystems, USA (4309155)

Table A33: Software and Services

Tools Link

BioEdit v7.0.5 http://www.mbio.ncsu.edu/BioEdit/bioedit.html

BLAST https://blast.ncbi.nlm.nih.gov/Blast.cgi

Eztaxon http://www.ezbiocloud.net/

ClustalXv2.1 http://www.clustal.org/clustal2/

MEGA5 http://www.megasoftware.net/

Statistix 8.1 http://statistix.software.informer.com/8.1/

Macrogen, Inc. http://www.macrogen.com/

qb3 facility http://qb3.berkeley.edu/

Sequence Detection Software v1.3 Applied Biosystems, USA

Appendix B

Appendix B


Table B1: IAA dilutions with their respective absorbance values.

Dilution IAA concentration

(μg/ml)

Absorbance (535 nm)

Replicate 1 Replicate 2 Average

1 0.313 0.007 0.009 0.008

2 0.625 0.016 0.022 0.019

3 1.25 0.039 0.040 0.040

4 2.5 0.092 0.090 0.091

5 5.00 0.178 0.181 0.180

Table B2: Cellulase (CEL), Pectinase (PEC), Phosphate solubilization (PHO), Protease

(PRO), Chitinase (CHI), and Indole Acetic Acid (IAA, without tryptophan; IAA-T, with

tryptophan) activities of endophytic bacteria isolated from Cannabis sativa (Direct method).

Values represent average of three replicates.

Isolate CEL

(cm)

PEC

(cm)

PHO

(cm)

PRO

(cm)

CHI

(cm)

IAA

(µg/ml)

IAA-T

(µg/ml)

Acinetobacter gyllenbergii MOSEL-r2 0.8 - 0.6 0.3 - 4.56 7.2

Acinetobacter nosocomialis MOSEL-n6 0.4 0.4 0.8 - - 2.54 4.02

Acinetobacter parvus MOSEL-t7 - - - - - 2.02 3.14

Acinetobacter pittii MOSEL-r8 0.4 - 0.8 - - 5.14 10.68

Bacillus anthracis MOSEL-r4 1.0 0.8 0.5 2.1 0.4 1.68 3.04

Chryseobacterium sp. MOSEL-n5 1.3 0.9 - 0.4 - 2.12 3.26

Enterobacter asburiae MOSEL-t15 0.4 0.3 2 - - 1.94 4.28

Enterococcus casseliflavus MOSEL-r7 - - 0.4 0.4 - 1.84 4

Nocardioides albus MOSEL-r13 0.6 1.2 - 0.7 - 1.34 4.56

Nocardioides kongjuensis MOSEL-r15 0.4 0.4 - - - 0.24 1

Pantoea vagans MOSEL-t13 0.3 - 1.1 - - 2.92 7.7

Planomicrobium chinense MOSEL-n9 0.8 - - - - 0.92 3.52

Pseudomonas taiwanensis MOSEL-t14 0.4 0.3 0.7 0.4 - 3.64 4.82

Rhizobium radiobacter MOSEL-n12 0.4 - 0.4 - - 3.8 13.34

Streptomyces eurocidicus MOSEL-n11 0.8 1.5 0.4 - - 0.98 1.8

Xanthomonas gardneri MOSEL-r5 0.4 0.9 - 0.4 - 1.4 5.1

Appendix B




tryptophan) activities of endophytic bacteria isolated from Cannabis sativa (Selective

method). Values represent average of three replicates.

Isolate CEL

(cm)

PEC

(cm)

PHO

(cm)

PRO

(cm)

CHI

(cm)

IAA

(µg/ml)

IAA-T

(µg/ml)

Chryseobacterium sp. MOSEL- w4 2.2 0.9 - 0.8 - 0.51 1.29

Chryseobacterium sp. MOSEL-p22 0.9 0.6 - 0.8 - 0.4 1.4

Curtobacterium flaccumfaciens MOSEL-w15 0.4 0.4 - 0.4 - 1.8 5.1

Enterobacter cancerogenus MOSEL-p6 0.4 0.4 1.1 - - 2.92 6.94

Enterobacter cloacae MOSEL-w7 0.4 0.3 0.4 - - 2.38 4.56

Exiguobacterium indicum MOSEL-w12 1.9 1.8 0.3 1 - 2.22 4

Microbacterium ginsengiterrae MOSEL-w2.16 0.8 0.8 - - - 0.62 2.69

Microbacterium sp. MOSEL-w2.5 1 1.5 - 0.7 - 0.13 1.6

Microbacterium phyllosphaerae MOSEL-w2.1 0.4 0.9 - - - 0.15 1.48

Paenibacillus sp. MOSEL-w13 1.9 2 0.4 1.8 0.9 0.2 0.82

Paenibacillus tundrae MOSEL-w1 0.3 1.8 - - - 1.4 3.01

Pantoea anthophila MOSEL-w6 0.3 0.3 0.3 - - 1.6 3.5

Paracoccus marcusii MOSEL-w16 0.4 0.4 - - - 3.9 5.36

Pseudomonas geniculata MOSEL-tnc1 1.5 0.4 - 0.8 - 1.2 5.42

Pseudomonas koreensis MOSEL-tnc2 0.8 0.4 0.7 0.4 - 1.78 6.5

Pseudomonas plecoglossicida MOSEL-p18 0.4 0.7 0.4 - - 1.84 2.92

Serratia marcescens MOSEL-w2 0.9 0.4 0.8 0.7 1.1 3.02 5.64

Stenotrophomonas rhizophila MOSEL-tnc3 1.7 - - 0.8 0.4 1.92 4.02

Appendix B




tryptophan) activities of endophytic bacteria isolated from Dodonaea viscosa roots. Values

represent average of three replicates.

Isolate CEL

(cm)

PEC

(cm)

PHO

(cm)

PRO

(cm)

CHI

(cm)

IAA

(µg/ml)

IAA-T

(µg/ml)

Inquilinus limosus MOSEL-RD1 0.8 1.3 0.5 0.7 - 0.44 1.28

Xanthomonas sacchari MOSEL-RD2 1.5 1.9 0.6 2.0 - 1.38 4.06

Streptomyces alboniger MOSEL-RD3 2.1 1.7 0.4 0.6 0.5 1.06 3.26

Bacillus idriensis MOSEL-RD7 1.7 1.7 0.7 1.8 0.4 2.46 10.12

Xanthomonas translucens MOSEL-RD9 0.6 1.6 0.8 2.1 - 0.84 2.54

Rhizobium huautlense MOSEL-RD12 1.3 1.2 0.5 - - 0.36 0.88

Microbacterium trichothecenolyticum MOSEL-

RD14 2.3 1.8 - 2.1 - 1.24 7.1

Streptomyces caeruleatus MOSEL-RD17 0.8 1.8 0.5 1.7 0.6 0.8 2.86

Bacillus simplex MOSEL-RD19 1.5 1.2 0.6 - - 1.18 2.32

Pseudomonas taiwanensis MOSEL-RD23 1.8 1.2 0.7 1.5 0.5 9.02 23.7

Brevundimonas subvibrioides MOSEL-RD25 0.5 1.1 - 1.4 - 0.9 3.44

Bacillus cereus MOSEL-RD27 2.1 1.7 0.7 1.5 0.6 5.32 10.8

Bacillus subtilis MOSEL-RD28 2.3 1.5 0.9 2.2 0.4 2.26 8.5

Pseudomonas geniculata MOSEL-RD36 1.7 1.4 0.5 1.2 0.5 3.72 15.32

Agrococcus terreus MOSEL-RD40 0.9 1.2 - 2.2 - 2.54 15.34

Appendix B


Table B5: Canola gnotobiotic root elongation assay of endophytic bacteria isolated from

Cannabis sativa (Direct method). Values represent mean of 12 replicates along with the

respective standard error values. LSD based pairwise comparison (p ≤ 0.05) of means

analyzed using one way ANOVA is also shown, where means having the same letter are not

statistically different from each other.

Isolate Mean Root

length (cm)

Standard

Error (cm)

Statistical

comparison

Acinetobacter gyllenbergii MOSEL-r2 9.48 0.48 BC

Acinetobacter nosocomialis MOSEL-n6 10.08 0.57 BC

Acinetobacter parvus MOSEL-t7 9.70 0.47 BC

Acinetobacter pittii MOSEL-r8 9.13 0.26 CD

Bacillus anthracis MOSEL-r4 10.38 0.41 BC

Chryseobacterium sp. MOSEL-n5 9.50 0.50 BC

Enterobacter asburiae MOSEL-t15 10.88 0.64 B

Enterococcus casseliflavus MOSEL-r7 9.93 0.41 BC

Nocardioides albus MOSEL-r13 10.07 0.53 BC

Nocardioides kongjuensis MOSEL-r15 9.42 0.61 CD

Pantoea vagans MOSEL-t13 12.88 0.54 A

Planomicrobium chinense MOSEL-n9 8.01 0.31 DE

Pseudomonas taiwanensis MOSEL-t14 9.97 0.29 BC

Rhizobium radiobacter MOSEL-n12 9.57 0.36 BC

Streptomyces eurocidicus MOSEL-n11 7.01 0.5 E

Xanthomonas gardneri MOSEL-r5 10.07 0.71 BC

Control 9.23 0.38 CD

Appendix B


Table B6: One-way ANOVA test report generated by Statistix v8.1 done for the comparison

of root lengths of canola plants treated with endophytic bacteria (gnotobiotic root elongation

assay) isolated from Cannabis sativa (Direct method). LSD All-Pairwise comparisons test of

means is also shown.

One-Way ANOVA

Source DF SS MS F P V001 16 140.983 8.81145 5.72 0.0000

Error 85 130.935 1.54041

Total 101 271.918

Grand Mean 9.7892 CV 12.68

Chi-Sq DF P Bartlett's Test of Equal Variances 11.7 16 0.7653

Cochran's Q 0.1170

Largest Var / Smallest Var 7.4578

Component of variance for between groups 1.21184

Effective cell size 12

V001 Mean V001 Mean control 9.233 r4 10.383

n11 7.017 r5 10.067

n12 9.617 r7 10.267

n5 9.500 r8 9.133

n6 10.083 t13 12.883

n9 8.017 t14 9.967

r13 10.067 t15 10.883

r15 9.417 t7 10.000

r2 9.883

Observations per Mean 12

Standard Error of a Mean 0.5067

Std Error (Diff of 2 Means) 0.7166

LSD All-Pairwise Comparisons Test of V002 by V001

(Comparison shown in table B5)

Alpha 0.05 Standard Error for Comparison 0.7166

Critical T Value 1.988 Critical Value for Comparison 1.4247

There are 5 groups (A, B, etc.) in which the means are not significantly different from one another.

Appendix B



Cannabis sativa (Selective method). Values represent mean of 12 replicates along with the




Isolate Mean Root

length (cm)

Standard

Error (cm)

Statistical

comparison

Chryseobacterium sp. MOSEL- w4 9.38 0.32 CDEF

Chryseobacterium sp. MOSEL-p22 8.95 0.52 EF

Curtobacterium flaccumfaciens MOSEL-

w15 10.03 0.46 CDEF

Enterobacter cancerogenus MOSEL-p6 10.62 0.59 ABCD

Enterobacter cloacae MOSEL-w7 11.67 0.50 AB

Exiguobacterium indicum MOSEL-w12 9.38 0.50 CDEF

Microbacterium ginsengiterrae MOSEL-

w2.16 10.30 0.67 BCDE

Microbacterium sp. MOSEL-w2.5 9.32 0.38 CDEF

Microbacterium phyllosphaerae MOSEL-

w2.1 9.47 0.41 DEF

Paenibacillus sp. MOSEL-w13 8.62 0.65 F

Paenibacillus tundrae MOSEL-w1 8.67 0.46 F

Pantoea anthophila MOSEL-w6 10.20 0.38 CDE

Paracoccus marcusii MOSEL-w16 10.35 0.56 BCDE

Pseudomonas geniculata MOSEL-tnc1 11.87 0.38 A

Pseudomonas koreensis MOSEL-tnc2 10.80 0.58 ABC

Pseudomonas plecoglossicida MOSEL-p18 9.87 0.73 CDEF

Serratia marcescens MOSEL-w2 11.93 0.64 A

Stenotrophomonas rhizophila MOSEL-tnc3 10.55 0.50 ABCD

Control 9.03 0.43 EF

Appendix B


Table B8: One-way ANOVA test report generated by Statistix v8.1 done for the comparison

of root lengths of canola plants treated with endophytic bacteria (gnotobiotic root elongation

assay) isolated from Cannabis sativa (Selective method). LSD All-Pairwise comparisons test

of means is also shown.

One-Way ANOVA


Error 95 154.493 1.62625

Total 113 267.184



Cochran's Q 0.1043




V001 Mean V001 Mean control 9.033 w15 10.033

p18 9.867 w16 10.350

p22 8.950 w2 11.933

p6 10.617 w2.1 9.317

tnc1 11.867 w2.16 10.300

tnc2 10.800 w2.5 9.467

tnc3 10.550 w4 9.383

w1 8.667 w6 10.200

w12 9.383 w7 11.667

w13 8.617









Appendix B



Dodonaea viscosa roots. Values represent mean of 12 replicates along with the respective

standard error values. LSD based pairwise comparison (p ≤ 0.05) of means analyzed using

one way ANOVA is also shown, where means having the same letter are not statistically

different from each other.

Isolate Mean Root

length (cm)

Standard

Error (cm)

Statistical

comparison

Inquilinus limosus MOSEL-RD1 8.1 0.250998 H

Xanthomonas sacchari MOSEL-RD2 11.52 0.467333 ABC

Streptomyces alboniger MOSEL-RD3 10.58 0.295635 CDE

Bacillus idriensis MOSEL-RD7 11.82 0.342637 AB

Xanthomonas translucens MOSEL-RD9 11.06 0.427317 ABCDE

Rhizobium huautlense MOSEL-RD12 8.56 0.208806 GH

Microbacterium trichothecenolyticum

MOSEL-RD14 10.54 0.430813 DE

Streptomyces caeruleatus MOSEL-RD17 10.26 0.428486 DEF

Bacillus simplex MOSEL-RD19 10.42 0.274591 DEF

Pseudomonas taiwanensis MOSEL-RD23 10.96 0.276767 BCDE

Brevundimonas subvibrioides MOSEL-RD25 10.14 0.374967 EF

Bacillus cereus MOSEL-RD27 11.16 0.398246 ABCD

Bacillus subtilis MOSEL-RD28 11.92 0.287054 A

Pseudomonas geniculata MOSEL-RD36 10.76 0.233666 CDE

Agrococcus terreus MOSEL-RD40 10.5 0.240832 DE

Control 9.5 0.330151 FG

Appendix B


Table B10: One-way ANOVA test report generated by Statistix v8.1 done for the

comparison of root lengths of canola plants treated with endophytic bacteria (gnotobiotic root

elongation assay) isolated from Dodonaea viscosa roots. LSD All-Pairwise comparisons test

of means is also shown.

One-Way ANOVA


Error 64 36.736 0.57400

Total 79 119.488



Cochran's Q 0.1189




V001 Mean V001 Mean control 9.500 rd25 10.140

rd1 8.100 rd27 11.160

rd12 8.560 rd28 11.920

rd14 10.540 rd3 10.580

rd17 10.260 rd36 10.760

rd19 10.420 rd40 10.500

rd2 11.520 rd7 11.820

rd23 10.960 rd9 11.060









Appendix B


Table B11: Canola gnotobiotic root elongation assay of three plant growth promoting

bacteria under 125 mM NaCl stress. Values represent mean of 12 replicates along with the




Isolate Mean Root

length (cm)

Standard

Error (cm)

Statistical

comparison

Pseudomonas geniculata MOSEL-tnc1 7.1 0.48 A

Serratia marcescens MOSEL-w2 6.78 0.48 AB

Pantoea vagans MOSEL-t13 7.4 0.46 A

Control 5.58 0.56 B

Appendix B


Table B12: One-way ANOVA test report generated by Statistix v8.1 done for the

comparison of root lengths of canola plants treated with three endophytic bacteria

(gnotobiotic root elongation assay) under 125 mM NaCl stress. LSD All-Pairwise

comparisons test of means is also shown.

One-Way ANOVA


Error 16 19.7760 1.23600

Total 19 29.3255



Cochran's Q 0.3169




V001 Mean control 5.5800

t13 7.4000

tnc1 7.1000

w2 6.7800








There are 2 groups (A and B) in which the means are not significantly different from one another.

Appendix B


Table B13: Bacterial cell counts observed in the leaves of tomato plants inoculated with four

Burkholderia phytofirmans PsJN inoculum doses measured at different days post inoculation.

The values are in log colony forming units per gram fresh weight (log cfu/gfw), and average

counts along with standard error are also shown.

Dose 104 cfu/ml

Day Replicate

Average Standard

Error 1 2 3 4 5

0 2.20 2.43 2.24 2.17 2.47 2.32 0.06

2 2.75 2.66 3.11 2.45 3.10 2.81 0.13

4 3.09 2.89 2.24 2.49 2.30 2.60 0.17

6 1.73 3.19 3.48 3.55 3.02 2.99 0.43

Dose 106 cfu/ml

Day Replicate

Average Standard

Error 1 2 3 4 5

0 3.15 3.39 3.41 3.48 3.51 3.39 0.06

2 3.87 3.75 3.87 3.80 3.86 3.83 0.04

4 4.09 4.07 4.63 3.93 4.68 4.34 0.14

6 4.60 4.60 5.01 5.03 4.12 4.49 0.22

Dose 108 cfu/ml

Day Replicate

Average Standard

Error 1 2 3 4 5

0 4.78 4.93 4.43 4.75 4.66 4.71 0.08

2 4.94 5.29 5.41 5.54 5.28 5.29 0.1

4 4.61 5.16 5.59 5.34 5.51 5.24 0.17

6 5.03 5.69 5.88 5.78 5.58 5.59 0.15

Dose 109 cfu/ml

Day Replicate

Average Standard

Error 1 2 3 4 5

0 8.49 8.07 8.35 7.99 8.4 8.26 0.10

2 8.34 7.72 7.83 7.94 7.18 7.80 0.19

4 8.09 7.67 7.82 7.92 7.31 7.76 0.13

6 7.81 7.05 8.16 6.97 8.13 7.62 0.26

Appendix B


Table B14: Relative quantification qPCR analysis data of 15 Burkholderia phytofirmans

PsJN genes used for in-planta gene expression study along with the exogenous control gene

(rpoD).

Gene Sample Ct

SE

Avg

Ct

Avg

dCt

dCt

SE ddCt RQ

RQ

min

RQ

max

Log

RQ

Log

RQR DC

ACCD

Bphyt_5397

In-planta 0.17 36.93 2.06 0.21 -0.95 1.93 1.21 3.08 0.29 0.20 87.2

M9 0.04 28.94 3.01 0.06 0.00 1.00 0.90 1.12 0.00 0.05 87.2

IAA

degradation

Bphyt_2156

In-planta 0.21 38.79 2.69 0.29 -2.39 5.23 2.78 9.84 0.71 0.27 85.2

M9 0.09 31.34 5.08 0.10 0.00 1.00 0.83 1.21 0.00 0.08 85.2

LuxI 1

Bphyt_0126

In-planta 0.07 39.25 4.51 0.12 -2.33 5.02 3.47 7.27 0.70 0.16 85.9

M9 0.13 31.79 6.84 0.13 0.00 1.00 0.78 1.28 0.00 0.10 85.9

LuxI 2

Bphyt_4275

In-planta 0.07 34.91 0.17 0.13 1.22 0.43 0.29 0.63 -0.37 0.16 82.2

M9 0.07 23.91 -1.05 0.08 0.00 1.00 0.86 1.16 0.00 0.06 82.2

Cellulase

Bphyt_5838

In-planta 0.21 33.10 -1.66 0.33 -2.66 6.33 3.37 11.86 0.80 0.27 87

M9 0.14 25.86 1.01 0.21 0.00 1.00 0.63 1.58 0.00 0.16 87

Pectinase

Bphyt_4858

In-planta 0.02 39.45 5.34 0.21 -4.32 19.92 12.42 31.94 1.30 0.20 85.9

M9 0.23 34.55 9.66 0.24 0.00 1.00 0.63 1.58 0.00 0.16 85.9

B-xylosidase

Bphyt_6562

In-planta 0.43 34.54 -0.19 0.44 -3.81 14.05 5.33 37.01 1.15 0.42 85.2

M9 0.05 28.57 3.62 0.05 0.00 1.00 0.90 1.11 0.00 0.05 85.2

Pili

Bphyt_3289

In-planta 0.47 37.51 1.90 0.51 0.06 0.96 0.36 2.55 -0.20 0.43 86.1

M9 0.05 28.65 1.83 0.05 0.00 1.00 0.91 1.10 0.00 0.04 86.1

Flagella

Bphyt_3832

In-planta 0.07 33.50 -1.23 0.13 2.93 0.13 0.10 0.17 -0.88 0.12 87.1

M9 0.12 20.79 -4.16 0.13 0.00 1.00 0.78 1.28 0.00 0.11 87.1

Indole

Acetamide

Hydrolase

Bphyt_6420

In-planta 0.34 41.34 5.72 0.39 3.57 0.08 0.04 0.20 -1.08 0.37 82.4

M9 0.09 28.97 2.15 0.09 0.00 1.00 0.84 1.19 0.00 0.07 82.4

Aerobactin

Bphyt_0280

In-planta 0.11 37.89 2.77 0.23 -0.05 1.03 0.62 1.73 0.01 0.22 81.2

M9 0.01 28.58 2.82 0.02 0.00 1.00 0.95 1.05 0.00 0.02 81.2

Peroxidase

Bphyt_2078

In-planta 0.34 32.62 -2.14 0.42 -2.56 5.90 2.64 13.19 0.77 0.35 85.4

M9 0.07 25.28 0.42 0.17 0.00 1.00 0.72 1.39 0.00 0.06 85.4

β-galactosidase

Bphyt_5888

In-planta 0.26 36.67 1.92 0.36 -3.21 9.26 4.61 18.61 0.97 0.30 84.2

M9 0.02 29.99 5.13 0.16 0.00 1.00 0.74 1.35 0.00 0.13 84.2

Hemagglutinin

Bphyt_0418

In-planta 0.28 37.28 0.29 0.28 -1.02 2.02 0.87 4.71 0.30 0.37 88.2

M9 0.01 27.85 1.31 0.06 0.00 1.00 0.90 1.11 0.00 0.05 88.2

T3SS

Bphyt_5212

In-planta 0.19 40.70 6.98 0.26 -1.55 2.92 1.36 6.26 0.47 0.33 88.6

M9 0.26 34.45 8.53 0.27 0.00 1.00 0.59 1.69 0.00 0.23 88.6

rpoD

Bphyt_6584

In-planta 0.07 33.86 - - - - - - - - 88.5

M9 0.04 26.09 - - - - - - - - 88.5

Ct SE, Ct standard error; AvgCt, average Ct; Avg dCt , average ∆Ct; dCt SE, ∆Ct standard error; ddCt, ∆∆Ct;

RQ, relative quantification; RQ min, relative quantification minimum; RQ max, relative quantification

maximum; LogRQ, log relative quantification; LogRQR, Log relative quantification range; DC, dissociation

curve.

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