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GENETIC EXPRESSION AND BIOINFORMATICS OF PQQ

DEPENDENT GLUCOSE DEHYDROGENASE (GDH) AND

PROBING ITS ROLE IN PLANTS

By

MUHAMMAD NAVEED

Department of Plant Sciences,

Faculty of Biological Sciences,

Quaid-i-Azam University,

Islamabad

2015

GENETIC EXPRESSION AND BIOINFORMATICS OF PQQ

DEPENDENT GLUCOSE DEHYDROGENASE (GDH) AND

PROBING ITS ROLE IN PLANTS

A thesis submitted in partial fulfillment of the requirements for the

degree of

Doctor of Philosophy

In

Genetics and Genomics

By

MUHAMMAD NAVEED

Department of Plant Sciences,

Faculty of Biological Sciences,

Quaid-i-Azam University,

Islamabad

2015

DECLARATION

I hereby declare that this thesis is my own work and effort

and that it has not been submitted anywhere for any

award. Where other source of information has been used,

they have been acknowledged.

MUHAMMAD NAVEED

Dedicated to

My Beloved Country “Pakistan” and my Research field

Special Thanks

I am immensely thankful to Prof. Dr. Monica Hofte (Lab of phytopathology and

Molecular Biotechnology, Department of Crop protection, Ghent University,

Belgium) for his guidance, help and his valuable assistance during my visiting

session at Ghent University, Belgium.

I pay my special thanks to Higher Education Commission, Pakistan that provides

me financial support throughout my research with Indigenous Fellowship as well as

awarding me PhD sandwich scholarship for Ghent University, Belgium under

International support Initiative Programme (IRSIP).

Certificate This is to certify that this thesis entitled as “Genetic Expression and Bioinformatics of PQQ Dependent Glucose Dehydrogenase (GDH) and Probing its Role in Plants” submitted by Muhammad Naveed is accepted in its present form and satisfying the thesis requirement for the degree of Doctor of Philosophy (Ph.D) in the subject of “Genetics and Genomics” by Department of Plant Sciences, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad Supervisor:

__________________ Dr. Abdul Samad Mumtaz

Assistant Professor Department of Plant Sciences

Quaid-i-Azam University Islamabad

External Examiner:

_____________________ Prof. Dr. Muhammad Gulfraz

Chairman, Department of Biochemistry

PMAS Arid Agriculture University Rawalpindi

External Examiner:

_____________________ Prof. Dr. Hamid Rasheed

Department of Bioinformatics Mohammad Ali Jinnah University

Islamabad

Chairman:

_____________________ Dr. Tariq Mehmood

Department of Plant Sciences Quaid-i-Azam University

Islamabad

Dated: _____________________

Plagiarism Certificate It is certified that Muhammad Naveed S/O Muhammad Hanif registration number 03041013004 has completed his Ph.D thesis on 31st March, 2014. The title of his thesis is “Genetic Expression and Bioinformatics of PQQ Dependent Glucose

Dehydrogenase (GDH) and Probing its Role in Plants”. His thesis has been checked on Turnitin for similarity index and found 9% (Paper ID: 411167882) that lies in the limit provided by HEC (19%) while the chapter wise similarity index is given below. Introduction 14% (Paper ID: 411170430) Materials and Methods 10% (Paper ID: 411170835) Results 8% (Paper ID: 411172563) Discussion 11% (Paper ID: 411171332)

Supervisor: __________________

Dr. Abdul Samad Mumtaz Assistant Professor

Department of Plant Sciences Quaid-i-Azam University

Islamabad

In charge Department: _____________________

Dr. Triq Mahmood Department of Plant Sciences

Quaid-i-Azam University Islamabad.

i

List of Contents

Chapter

No.

Content

No. Title

Page

No.

List of Tables vii

List of Figures viii

Glossary of Terms and Abbreviations xiv

List of Publications xvii

Acknowledgment xviii

Abstract xx

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INTRODUCTION

1

Part A: PQQ dependent Glucose Dehydrogenase (GDH) 3

1.1 Glucose Dehydrogenase (GDH) 3

1.2 PyrroloQuinoline Quinine (PQQ) 4

1.2.1 Present status and significance of PQQ 6

1.2.2 Biosynthesis and genetics of PQQ 6

Part B: The Bioinformatics 10

1.3 Structural characterization of PQQ dependent GDH 10

1.3.1 The chemistry of PQQ operon 12

Part C: PQQ Potentials / Applications 16

1.4 PQQ as Plant Growth Promoter 16

1.5 PQQ as an antioxidant 18

Part D: Mutagenesis 19

1.6 Transposons mutagenesis 19

Part E: Induced Systemic Resistance (ISR) 21

1.7 Gene expression and Induced Systemic Resistance (ISR) 21

1.8 Aims and Objectives 24

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MATERIALS AND METHODS

25

2.1 Collection of samples 25

2.1.1 Bacterial isolation from field 25

2.2 Screening and characterization of phosphate solubilizing

bacteria

27

2.2.1 Change in medium pH by phosphate solubilizing bacteria 27

2.2.2 Biochemical and physiological characterization of phosphate

solubilizing bacteria

27

2.2.2.1 N-acyl homoserine lactone (AHL) test 28

2.2.2.2 Nitrogenase activity 28

2.2.2.3 Indole production and Catalase test 28

2.3 Molecular characterization of phosphate solubilizing bacteria 29

2.3.1 Genomic DNA isolation 29

2.3.2 Molecular identification by 16S rRNA and Multilocus

Sequence Analysis (MLSA)

29

2.3.3 16S rRNA and MLSA gene sequencing and analysis 30

2.4 Identification of gdh and pqq genes by PCR amplification 31

2.4.1 Amplification of gdh gene 31

2.4.2 Amplification of pqq operon (pqqABCDEF) 32

2.5 Bioinformatics based structural characterization of GDH

protein

33

2.5.1 Sequence identity and physico-chemical properties of GDH 33

2.5.2 Structural Analysis of GDH Protein 34

2.5.2.1 Prediction of secondary structure 34

2.5.2.2 Three-dimensional (3D) modeling 34

2.5.2.3 Homology Modeling based on 3D structure 34

2.5.2.4 Ligand binding prediction 34

2.5.3 Functional Analysis of GDH Protein 35

iii

2.5.3.1 Annotations of Functional residues 35

2.5.3.2 Functional Prediction through I-TASSER server 35

2.5.3.3 Structural based function annotations 35

2.5.3.4 Functional domains prediction 36

2.5.3.5 Gene Ontology (GO) 36

2.6 The gdh mutagenesis (Tn5) and its implications 36

2.6.1 Conjugation 36

2.6.1.1 Tn5 Mutant characterization 37

2.6.2 Knock out site directed PCR based deletion mutation 38

2.6.2.1 Designing of primers 38

2.6.2.2 PCR amplification for mutation 38

2.6.2.3 Restriction digestion of Plasmid pMQ30 39

2.6.2.4 In vivo cloning and transformation 39

2.6.2.5 Plasmid extraction 41

2.6.2.6 Electroporation 41

2.6.2.7 Conjugation or biparental mating (1st cross over 41

2.6.2.8 Selection and Merodiploid 41

2.6.2.9 Mutants selection (2nd cross over) 42

2.6.2.10 Mutant confirmation 42

2.6.3 Characterization of pqqC mutants 42

2.6.3.1 Screening of pqqC mutants for phosphate solubilization 42

2.6.3.2 Effects on acidification of medium 43

2.6.3.3 The pqqC mutant characterization by API-20E kit 43

2.6.3.4 Carbon source utilization test 43

2.6.3.5 Antioxidant activity 43

2.6.3.5.1 DPPH radical scavenging activity 43

2.6.3.5.2 Reducing power 44

iv

2.7 PQQ’s role in plant growth promotion 44

2.7.1 Lettuce (Lactuca sativa) 44

2.7.2 Bean 45

2.7.2.1 Data analysis 45

2.8 Tagging of bacterial strains by Tn7-gfp mutation 46

2.8.1 Conjugation 46

2.8.2 Pseudomonads in root colonization of Lettuce 47

2.9 Role of PQQ in plant disease control 47

2.9.1 In vitro antagonistic activity against phytopathogenic fungi 47

2.9.1.2 Data analysis 48

2.9.2 In vivo antagonistic activity of pqq mutants against

Rhizoctonia solani

48

2.9.2.1 Bacterial inoculum 48

2.9.2.2 Fungal inoculum and Experimental set-up 48

2.9.3 Disease rating of Pseudomonas strains and its pqqC mutants

by root colonization

48

2.10 PQQ and Induced systemic resistance (ISR) in rice 49

2.10.1 The qPCR analysis of cell cultures treated with Pseudomonas

supernatant

49

2.10.2 Induced resistance bio-assays 50

2.10.2.2 Pathogen Inoculation 50

2.10.2.3 Sample collections 50

2.10.2.4 RNA extraction from Rice 51

2.10.2.4(a) Homogenization 51

2.10.2.4(b) Phase Separation 51

2.10.2.4(c) RNA Precipitation 51

2.10.2.4(d) RNA Wash 52

2.10.2.4(e) Redissolving the RNA 52

v

2.10.2.5 DNase treatment and cDNA synthesis 52

2.10.2.6 Real time quantitative PCR (RT-PCR) analysis 52

2.10.2.7 Gene expression analysis 53 C

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RESULTS 55

3.1 Screening of bacteria for phosphate solubilization 55

3.2 Biochemical and physiological characterization of phosphate

solubilizing bacteria

57

3.3 Molecular characterization 57

3.3.1 Identification of isolates by 16S rRNA gene 57

3.3.2 Multilocus sequence analysis (MLSA) 61

3.3.2.1 The rpoB gene 61

3.3.2.2 The rpoD gene 63

3.3.2.3 The recA gene 64

3.4 Identification of gdh and pqq genes 66

3.4.1 PCR amplification of quinoproteins glucose dehydrogenase

(gdh) gene

66

3.4.2 Amplification of ‘pqq’ genes (pqqABCDEF) 67

3.5 Bioinformatics analysis 70

3.5.1 Physico-chemical properties of GDH 70

3.5.2 Structural analysis of GDH Protein 70

3.5.2.1 Homology modeling based on 3D structures 71

3.5.3 Prediction of Ligand and active sites of GDH models 74

3.5.4 Functional Analysis of GDH Protein 76

3.5.4.1 Annotations of functional residues 76

3.5.4.2 Functional insights based on 3D models 78

3.5.4.3 Functional domain prediction of GDH protein 78

3.5.4.4 Gene Ontology (GO) 80

3.6 Mutagenesis 82

3.6.1 The gdh mutagenesis and its implications 82

3.6.1.1 gdh mutant characterization 82

3.6.1.2 Comparative effect of gdh and gdh mutant on plant growth 82

vi

promotion

3.6.2 Knock out gene expression analysis of pqq 84

3.6.2.1 PCR based mutant identification 84

3.6.2.2 Mutants confirmation: phosphate solubilization and change in

pH

84

3.6.2.3 Biochemical characterization of pqqC mutants (qualitative) 87

3.6.2.4 Carbon source utilization 90

3.6.2.5 Antioxidant activity of PQQ 91

3.6.2.5.1 DPPH scavenging activity 91

3.6.2.5.2 Reducing power 91

3.7 Role of PQQ in plants growth promotion 93

3.7.1 In vitro effect of pqqC mutation on lettuce root length 93

3.7.2 Effects of pqqC mutation: the in vivo demonstration 94

3.7.2.1 Bean 94

3.8 Tagging of bacterial strains by Tn7-gfp mutation 97

3.9 Role of PQQ in plant disease control 99

3.9.1 In vitro antagonistic activity of bacterial strains against

phytopathogenic fungi

99

3.9.2 In vivo antagonistic activity of PQQ against Rhizoctonia root

rot

100

3.10 PQQ and Induced systemic resistance (ISR) in rice 102

3.10.1 Pseudomonas CMR12a and QAU92 trigger JA/ET signaling

pathways

102

3.10.2 Induced Resistance against Cochliobolus miyabeanus in Rice 104

3.10.2.1 EBP89 susceptible gene expression analysis 104

3.10.2.2 PR1a (pathogenesis-related protein 1a gene) expression

analysis

105

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DISCUSSION 110

4.1 Biochemical and Physiological characterization and

phenotypic diversity

110

4.2 Molecular identification and genetic diversity 112

4.3 New insight for Plant microbe association 113

4.4 Bioinformatics reveals structure characterization of PQQ

dependent GDH

114

vii

List of Tables

Table

No. Title

Page

No.

1.1 The percentage similarities between pqqBCDE genes of different bacteria

(Felder et al., 2000)

9

2.1 The primer sequences used for 16S rRNA and housekeeping loci of bacterial

isolates

30

2.2 PCR profile for housekeeping gene (MLSA) and antibiotics 30

2.3 primer list for pqq and gdh amplification 32

2.4 The gdh gene amplification profile 32

2.5 pqq genes amplification profile 33

2.6 The primers used for PCR based deletion mutation 38

2.7 Gene-specific primers used for quantitative real-time qPCR 54

3.1 Phosphate solubilization of bacterial isolates 56

3.2 Molecular identification of bacterial isolate by 16S rRNA and sequences

submission to NCBI Genbank

59

3.3 The physico-chemical characterization of GDH proteins 72

4.5 Mutagenesis revealed complementary role of PQQ and GDH 115

4.5.1 Role of GDH in plant growth promotion 115

4.5.2 Multiple roles of PQQ in Plants 116

4.6 The antagonistic role of PQQ 118

4.6.1 PQQ’s role in disease control 118

4.6.2 PQQ role in Induced systemic resistance (ISR) 119

Conclusions 121

Future Recommendation 123

REFERENCES 124

Appendix 148

viii

3.4 Functional characterization of GDH by Gene ontology (I-TASSER) 81

3.5 The effect of wild type and pqqC mutant strains on pH 86

3.6 Biochemical characterization of wild type and pqqC mutant strains by API

20E system (qualitative data)

89

3.7 Statistical analysis of wild type and pqqC mutant strains in plant growth

promotion

96

3.8 The growth inhibition (%age) of phytophathogens by antagonistic

Pseudomonas strains

99

3.9 Root colonization data for non-washed bacteria of Pseudomonas CMR12a

and QAU92 and mutants CMR12a-3 and QAU92-2 in the absence of

Rhizoctonia solani or after inoculation with R. solani anastomosis group

(AG) 2-2

102

List of Figures

Figure

No. Title

Page

No.

1.1 The anticipated pathway for catabolism of glucose in Pseudomonas is

conversion of molecules and transport using enzymes/proteins encoded by

genes. The pathways are specified for each step: gcd, glucose

dehydrogenase; gntP, gluconate permease; oprB, glucose/carbohydrate outer

membrane porin; gad, gluconate dehydrogenase; glk, glucokinase; gnuk,

gluconokinase; kguT, putative 2-ketogluconate transporter; zwf, glucose 6-

P-dehydrogenase; kguK, 2-ketogluconate kinase; edd, phosphogluconate

dehydratase; OM, outer membrane; kguD, ketogluconate 6-P-reductase; eda,

keto-deoxy-phosphogluconate aldolase. IM, inner membrane and PS,

periplasmic space (Miller et al., 2010).

4

1.2 The Chemical structure of PQQ 5

1.3 Comparison of the pqq gene clusters of P. fluorescens B16, Acinetobacter

calcoaceticus, P. fluorescens pf01, Klebsiella pneumonia,

Methylobacterium extorquens AM1 and Gluconobacter oxydans

ATCC9937. Locations and alignments of the pqq genes are designated by

colored arrows. The identical colors represent homologous encoded proteins

(Choi et al., 2008)

7

1.4 Purposed scheme for bioinformatics work of PQQ (Shen et al., 2012) 12

1.5 The role of quinoprotein glucose dehydrogenases (GDH) in extra

cytoplasmic glucose metabolism. The D-Glucose is oxidized to D-glucono-

1, 5-lactone by the action of GdhS in the periplasm, a process require

pyrroloquinoline quinone (PQQ) and hydrolyzed to D-gluconic acid (Fender

17

ix

et al., 2012)

2.1 Map showing parts of Pakistan where collections were made highlighted as

red stars as described below: (1) Rawalpindi, (2) Islamabad, (3) Multan, (4)

Jacobabad and (5) Gujrat & Gujranwala (overlapping so appeared bold).

26

2.2 mTn5gfp–pgusA contains a promoterless gfp gene and a constitutively

expressed gusA gene. The remaining mini-Tn5 elements carry a

promoterless gusA gene and a constitutively expressed gfp gene. The 5 end

of the DNA sequence of the promoterless gfp and gusA cassettes is shown

above the mTn5gfp–pgusA and mTn5gusA–pgfp elements. Translational

stops in the three reading frames are indicated by asterisks (*). The

ribosome-binding site is underlined and the KpnI site is italicized; letters

below the DNA sequence represent the amino-terminal amino-acids of GFP

and GusA (Chuanwu et al.1999).

37

2.3 Yeast-based allelic exchange vector maps used for pqqC mutation are

shown the oriT, origin of conjugal transfer; sacB, Bacillus subtilis

levansucrase gene for counter selection; T1T2, E. coli rrnB transcriptional

terminators; ColE1, high-copy-number variants of the narrow-host-range

ColE1 origin of replication; URA3, orotidine-5-phosphate decarboxylase

gene from S. cerevisiae; lacZα, lacZα with multi cloning site driven by the

lactose promoter; aacC1, gentamicin resistance determinant from Tn1696;

p15a, narrow-host-range, low-copy origin of replication and CEN/ARSH,

low-copy yeast replication and segregation machinery

40

2.4 Map of Tn7 element of delivery plasmids which can be used for gfp-tagging

of strains (A) pBK-miniTn7-gfp2, pUC19-based delivery plasmid for

miniTn7-gfp2. GmR, CmR, ApR, mob., Tn7L and Tn7R, the 166-bp left

and 199-bp right ends of Tn7 (Koch et al., 2001) and (B) the helper plasmid

(pUX-BF13), pUX-BFI3 was constructed by moving the 9.0-kb EcoRI

fragment of pCW4 (McKown et al., 1987) into the EcoRI site of pGP704 (J.

Mekalanos, personal communication), an R6K-repIicon-based plasmid

lacking the pir gene and with an RP4-derived mob site, MCS, multiple

cloning site

46

3.1 Phosphate solubilization activity of QAU90 and QAU92 isolates on

Pikovskaya’s agar medium incubated at 280C for 4 days (solubility index

(SI) measured in mm)

56

3.2 16S rRNA amplification of all bacterial strains; where (L: 1kb Ladder; Lane

1: QAU51; Lane 2: QAU53; Lane 3: QAU54; Lane 4: QAU56; Lane 5:

QAU60; Lane 6: QAU62; Lane 7: QAU63; Lane 8: QAU64; Lane 9:

QAU66; Lane 10: QAU67; Lane 11: QAU68; Lane 12: QAU90 and Lane

13: QAU92)

57

3.3 Neighbor-joining phylogenetic tree showing the inter-relationship of all

strains with the closely related validly published type species inferred from

sequences of 16S rRNA gene. Pseudomonas oryzihabitans LMG 7040 was

used as an out group. Bootstrap values are expressed as a percentage of

1000 replications, are given at the branching point

59

3.4 The rpoB (MLSA) gene amplification (508bp) of bacterial strains; where (L:

1kb Ladder; Lane 1: CMR12a; Lane 2: QAU67; Lane 3: QAU90; Lane 4:

QAU92).

61

3.5 Neighbor-joining phylogenetic tree showing the inter-relationship of strain

QAU67, QAU90 and QAU92 with the closely related validly published

species inferred from sequences of rpoB gene. Pseudomonas aeruginosa

62

x

was used as an out group. Bootstrap values are expressed as a percentage of


3.6 Housekeeping (MLSA) gene amplification of all bacterial strains; where (L:

1kb Ladder; Lane1-4: gyrB (CMR12a, QAU67, QAU90 and QAU92) Line

5-8: rpoD (CMR12a, QAU67, QAU90 and QAU92) and line 9-12: recA

(CMR12a, QAU67, QAU90 and QAU92)

63



species inferred from sequences of rpoD gene. The strain QAU92 was

behaved an out group. Bootstrap values are expressed as a percentage of


64



species inferred from sequences of recA gene. Pseudomonas protegens-Pf-5

was used as an out group. Bootstrap values are expressed as a percentage of


65

3.9 gdh gene amplification of all bacterial strains; of partial sequence (A)

Enterobacter strains (QAU64 & QAU66) and full length sequence of (B)

Pseudomonas strains where (L: 1kb Ladder; Lane 1: CMR12a; Lane 2:

QAU90; Lane 3: QAU92; Lane 4: QAU67).

66


CMR12a, QAU67 and QAU90 with the closely related validly published

species inferred from sequences of gcd genes. The strain QAU92 was

behaved an out group. Bootstrap values are expressed as a percentage of


67

3.11 The pqqBCD genes amplification (2.1 kb) of all bacterial strains; where (L:

1kb Ladder; Lane 1: CMR12a; Lane 2: QAU67; Lane 3: QAU90; Lane 4:

QAU92).

68



species inferred from sequences of pqqBCD genes. The strain P. fluorescens

strain B16 was used as out group. Bootstrap values are expressed as a

percentage of 1000 replications, are given at the branching point

69

3.13 Comparison of the PQQ gene clusters of P. fluorescens CMR12a, P.

fluorescens QAU67, P. putida QAU90 and Pseudomonas sp. QAU92 with

reference strains of Gluconobacter oxydans ATCC9937 and P. fluorescens

B16. Positions and orientations of the pqq genes are indicated by colored

arrows. The same colors represent homologous encoded proteins. The

organization and size of the genes are depicted based on nucleotide

sequence data from GenBank

70

3.14 Predicted 3D model from I-TASSER and visualized on Jmol (A-D). Protein

function annotations based on the sequence-to-structure-to-function

paradigm for GDH. The right panel is the function similarity identified by

global and local matches of I-TASSER models showing binding sites of

PQQ cofactor and similarity with template with TM-score (TM score is a

measure of global structural similarity between query and template protein)

74

3.15 Glucose dehydrogenase (GDH) models comprised of ligand binding (PQQ

and Ca2+), active site, residue binding sites and functional domain which

were predicted by INTERPROSCAN and COFACTOR respectively, and

then illustrated in DOG 2.0 (illustrator of protein domain structures); (A)

76

xi

Functional domains of QAU66, (B) P. fluorescens CMR12a, (C) P. putida

QAU90 and (D) Pseudomonas sp. QAU92.

3.16 Schematic diagram of the MEMSAT3 and MEMSAT-SVM predictions for

the query sequence of glucose dehydrogenases of P. fluorescens CMR12a,

P. putida QAU90 and Pseudomonas sp. QAU92. Traces indicate the RAW

outputs for the prediction SVMs. Dashed lines indicate the prediction

threshold and H-P : Helix prediction, PL: Pore lining residue, SP: Signal

peptide residue and RE: Re-entrant helix residue

77

3.17 The structure based functional domain prediction of glucose dehydrogenase

(GDH) by Interproscan tool: (A) Leclercia sp. QAU66 (B) P. fluorescens

CMR12a (C) P. putida QAU90 (D) Pseudomonas sp. QAU92

80

3.18 Phosphate solubilization index (SI) of (A) Pseudomonas putida QAU90

(wild type) and (B) Tn5 based insertional GDH mutant Pseudomonas putida

QAU90-23

82

3.19 The comparative performance of Pseudomonas putida QAU90 (wild type)

and Tn5-induced gdh mutant (QAU90-23) on bean plant growth. 83

3.20 Growth promotion activities of bean (Phaseolus vulgaris) by Pseudomonas

putida QAU90 (wild type) and Tn5 based insertional GDH mutant

Pseudomonas putida QAU90-23 inoculated plant with water treated control

plants. Plant parameters are plant height, root length, fresh weight (shoot ×

root) and leaf area (length × width) with average of 10 plants from three

replicate

83

3.21 PCR based identification of pqqC mutants of bacterial strains; (A) P.

fluorescens CMR12a, (B) P. fluorescens QAU67, (C) P. putida QAU90 and

(D) Pseudomonas sp. QAU92. The E. coli strain with the plasmid was used

as a positive control and wild type strain used as a negative control

85

3.22 Phosphate solubilization capability of wild and pqqC mutant strains on

pikovskaya medium (A) P. fluorescens CMR12a with its pqqC mutant P.

fluorescens CMR12a-3, (B) P. putida QAU90 with its pqqC mutant P.

putida QAU90-2 and (C) Pseudomonas sp. QAU92 with its pqqC mutant

Pseudomonas sp. QAU92-4

86

3.23(A) Biochemical characterization of wild type and their pqqC mutant strains by

API 20E kit. The impact of mutation is obvious when comparing wild type

P. fluorescens CMR12a and its pqqC mutant strain along with negative

control and scores in Table 3.6.

87

3.23(B) Biochemical characterization of wild type and their pqqC mutant strains by

API 20E kit. The impact of mutation is obvious when comparing wild type

P. fluorescens QAU67, (C) P. putida QAU90 and (D) Pseudomonas sp.

QAU92 and their pqqC mutant strains along with negative control and

scores in Table 3.6.

88

3.24 Comparison of carbon source utilization by wild strains (P. fluorescens

CMR12a, P. fluorescens QAU67, P. putida QAU90 and Pseudomonas sp.

QAU92) and their pqqC mutant (P. fluorescens CMR12a-3, P. fluorescens

QAU67-14, P. putida QAU90-4 and Pseudomonas sp. QAU92-2) strains

with standard deviation of two replicates

90

3.25 DPPH radical showed a concentration (20, 40 and 80 ug/ml) dependent

percent scavenging antioxidant activity of pqq extract from wild type (P.

fluorescens CMR12a, P. fluorescens QAU67, P. putida QAU90 and

Pseudomonas sp. QAU92) strains and their pqqC mutants (P. fluorescens

CMR12a-3, P. fluorescens QAU67-14, P. putida QAU90-4 and

92

xii

Pseudomonas sp. QAU92-2) at absorbance of 517 nm. Legends showed

concentrations

3.26 Antioxidant activities of the wild type (P. fluorescens CMR12a, P.

fluorescens QAU67, P. putida QAU90 and Pseudomonas sp. QAU92)

strains and their PQQ mutants (P. fluorescens CMR12a-3, P. fluorescens

QAU67-14, P. putida QAU90-4 and Pseudomonas sp. QAU92-2) with

different concentrations (0, 10, 20, 40 and 80 ug/ml) were measured by the

reducing power method. Each absorbance value represented the average of

triplicates of different samples analyzed. Increase in the absorbance at 700

nm indicates the reducing power

93

3.27 The comparison in performance of wild type (P. fluorescens CMR12a, P.

putida QAU90 and Pseudomonas sp. QAU92), their derived pqqC mutants

(P. fluorescens CMR12a-3, P. putida QAU90-4 and Pseudomonas sp.

QAU92-2) and control treatments as assessed in lettuce root length

94

3.28 The comparison in performance of wild type, their derived pqqC mutant

strains and control treatments as assessed in bean growth improvement in

box-plot analysis. The growth parameters PH (plant height), RL (root

length), fresh weight S×R (shoot × root) and leaf area L×W (length × width)

were assessed by inoculated above mention three wild strains with their

pqqC mutants. . (CMR12; P. fluorescens CMR12a, CMRMUTAN; P.

fluorescens CMR12a-3, QAU90; P. putida QAU90, QAU90MUT; P. putida

QAU90-4, QAU92; Pseudomonas sp. QAU92 and QAU92MUT;

Pseudomonas sp. QAU92-2)

95

3.29 Plant growth promotion activities of wild type and mutant strains in lettuce

(in vitro) and Bean (in vivo) (A) P. fluorescens QAU67 and its pqqC mutant

(P. fluorescens QAU67-14) with control treated Lettuce plants. (B) The P.

fluorescens CMR12a and its pqqC mutant (P. fluorescens CMR12a-3) with

control treated bean plants, here only showed one bacterial treatment for

each plant

96

3.30 The detection of Tn7-gfp-tagged wild type (P. fluorescens CMR12a and

Pseudomonas sp. QAU92) and two pqqC mutant (P. fluorescens CMR12a-3

and Pseudomonas sp. QAU92-2) strains colonizing the root surface of the 7-

day-old lettuce on MS medium. All images were taken from the root and

Pseudomonas cells appeared in greenish color. (A) Control root inoculated

with water under normal light without gfp, (B) Control root inoculated with

water under fluorescent light without gfp, (C) mini Tn7-gfp2-tagged P.

fluorescens CMR12a (wild type strain) inoculated root, (D) mini Tn7-gfp2-

tagged P. fluorescens CMR12a-3 (pqqC mutant strain) inoculated root, (E)

mini Tn7-gfp2-tagged Pseudomonas sp. QAU92 (wild type strain)

inoculated root, (F) mini Tn7-gfp2-tagged Pseudomonas sp. QAU92-2

(pqqC mutant strain) inoculated root

98

3.31 In vivo antagonistic activity of pseudomonad and their pqqC mutant strains

against R. solani AG2-2. (A) P. fluorescens CMR12a and its pqqC mutant

P. fluorescens CMR12a-3 with disease control plant , (B) P. putida QAU90

and its pqqC mutant P. putida QAU90-4 with disease control plant and (C)

Pseudomonas sp. QAU92 and its pqqC mutant Pseudomonas sp. QAU92-2

with disease control plant

101

3.32 Expression of hormone marker genes in rice cell cultures treated with

supernatant of P. fluorescens CMR12a, Pseudomonas sp. QAU92 and

their pqqC mutant (P. fluorescens CMR12a-3, Pseudomonas sp.

103

xiii

QAU92-2). Supernatant of Pseudomonas bacteria grown in LB broth

was applied to 5-days-old rice cell suspension cultures. Control

samples were treated with LB only. At different time points after

inoculation (1, 3 and 6 hours), cell cultures were harvested and

subjected to quantitative RT-PCR analysis for the following

transcripts: (A) JiOsPR10, (B) JAMYB and (C) EBP89. Actin

(Os03g071810) was used as an internal reference to normalize the

gene expression levels and calculated relative to the expression in

mock-treated control cells at 1, 3 and 6 hour. Data presented are

means and standard error of two replicates from a representative

experiment

3.33 Role of PQQ in induced systemic resistance of rice against C. miyabeanus

by genetic expression of EBP89 gene with reference to actin in P.

fluorescens CMR12a, Pseudomonas sp. QAU92 and their pqqC mutants P.

fluorescens CMR12a-3 and Pseudomonas sp. QAU92-2 in 1st biological

repeat. (12a, 92W; wild type strains, 12a-3M, 92-2M; pqqC mutant strains,

1st (12); time point after 12 hpi, 2nd (24); time point after 24 hpi, 3rd (36);

time point after 36 hpi and 4th (48); time point after 48 hpi, m; mock

treatment and I; infected treatment).

106

3.34 Role of PQQ in induced systemic resistance of rice against C.

miyabeanus by genetic expression of EBP89 gene with reference to

actin in P. fluorescens CMR12a, Pseudomonas sp. QAU92 and their

pqqC mutants P. fluorescens CMR12a-3 and Pseudomonas sp.

QAU92-2 in 2nd biological repeat. (12a, 92W; wild type strains, 12a-

3M, 92-2M; pqqC mutant strains, 1st (12); time point after 12 hpi,

2nd (24); time point after 24 hpi, 3rd (36); time point after 36 hpi and

4th (48); time point after 48 hpi, m; mock treatment and I; infected

treatment).

107


miyabeanus by genetic expression of PR1a gene with reference to



QAU92-2 in 1st biological repeat. (12a, 92W; wild type strains, 12a-




treatment).

108


miyabeanus by genetic expression of PR1a gene with reference to



QAU92-2 in 1st biological repeat. (12a, 92W; wild type strains, 12a-




treatment).

109

xiv

List of Abbreviations

PQQ Pyrroloquinoline quinone

GDH Glucose dehydrogenase

ADH Alcohol dehydrogenase

rpoB RNA polymerase bet-subunit encoding gene

rpoD major sigma factor

recA homologous recombination-encoding gene

I-TASSER iterative threading assembly refinement server

Pfam Protein families

PCR polymerase chain reaction

AG Antagonistic

MLSA Multilocus sequence analysis

ISR induced systemic resistance

DAPG diacetylphloroglucinol

PSB Phosphate-solubilizing bacteria

qRT-PCR Quantitative Real time PCR

GFP Green fluorescent protein

3D 3-dimensional model

LOMETS locally installed meta-threading server

BLAST Basic Local Alignment Search Tool

ROS reactive oxygen species

SA salicylic acid

PRs pathogenesis related

PGPR Plant growth promoting rhizobacteria

ET ethylene

JA jasmonic acid

VOCs Volatile organic compound

xv

Milli-Q Millipore 'ultrapure' water

KB King B

LB Luria Broth

TY Tryptone Yeast Extract

YEM Yeast extract mannitol

NFb nitrogen-free semisolid malate Media

PLT pyoluteorin

NCBI National Centre of Biotechnology Information

MEGA Molecular Evolutionary Genetics Analysis

HF High fidelity

NJ neighbor joining

MP maximum parsimony

MLH maximum likelihood

PDB protein database

YPD yeast pepton dextrose

DPPH 2,2-Diphenyl-1-Picrylhydrazyl

DAP L-a,b-Diaminopropionic acid

Gm Gentamycin

TRI Trizol

DEPC Diethylpyrocarbonate

eEF1a eukaryotic translation elongation factor 1A

EBP89 Ethylene-responsive TF 89

TLC thin layer chromatography

PCA phenazine-1-carboxylate

xvi

AHL acyl-homoserine lactone

HTH helix-turn-helix

IAA indole acetic acid

IPTG isopropyl b-D-1-thiogalactopyranoside

Km kanamycin

mRNA messenger ribonucleic acid

nod nodulation

OD optical density

ONPG 2-nitrophenyl-b-D-galactopyranoside

ORF open reading frame

rRNA ribosomal ribonucleic acid

SAM S-adenosyl methionine

SDS sodium dodecyl sulphate

TBE tris/borate/EDTA

TEMED N,N,N',N'-tetramethylethylenediamine

UV ultraviolet µl Microlitre

CTAB Cetyltrimethyl ammonium bromide

DNTPs Deoxynucleotide Triphosphates

EDTA Ethylene diamine tetra acetate

mM milli Molar

rpm Revolution per minute

SDS Sodium Dodecyl Sulphate

T.E Tris borate

Taq Thermus aquaticus

xvii

List of Publications

1. M. Naveed, Y. Sohail, N. Khalid, I. Ahmed, A. S. Mumtaz, M. Hofte. 2014.

Evaluation of Glucose Dehydrogenase and Pyrroloquinoline Quinine Mutagenesis

that Renders Functional Inadequacies in Host Plants. Journal of Microbiology and

Biotechnology. (Accepted; Manuscript ID: 150105)

2. Muhammad Naveed, Nam Phuong Kieu, Abdul Samad Mumtaz and Monica

Hofte. Role of pseudomonas pyrroloquinoline quinone (pqq) in phosphate

solubilization and plants growth promotion. Journal of Applied Microbiology.

(Under Review; Manuscript ID: 1418114).

3. Muhammad Naveed, Samavia Mubeen, SamiUllah Khan, Iftikhar Ahmed,

Nauman Khalid, Hafiz Ansar Rasul Suleria, Asghari Bano, Abdul Samad

Mumtaz. Identification and Characterization of Rhizospheric Microbial Diversity

by 16S rRNA Gene Sequencing. Brazilian Journal of Microbiology; 45(3):985-

993.

4. Muhammad Naveed, Iftikhar Ahmed, Nauman Khalid, Abdul Samad Mumtaz.

Bioinformatics based structural characterization of glucose dehydrogenase (gdh)

gene and growth promoting activity of Leclercia sp. QAU-66. Brazilian Journal of

Microbiology; 45(2):603-611.

5. Samiullah Khan, Abdul Samad Mumtaz, Ghulam Mustafa, M. Naveed, Zabta

Khan Shinwari, Allan Downie. The LC-MS/MS profiling of AHLS produced in

Sinorhizobium meliloti nodulating Alysicarpus bupleurifolius. Pakistan Journal of

Botany; 45(6):2037– 2041.

6. Sadia Latif, Samiullah Khan, Muhammad Naveed, Ghulam Mustafa, Tasmia

Bashir, Abdul Samad Mumtaz. 2013. The diversity of Rhizobia, Sinorhizobia and

novel non-Rhizobial Paenibacillus nodulating wild herbaceous legumes. Archives

of Microbiology, 195:647–653.

xviii

Acknowledgements

All the praises, thanks and acknowledgements are for the Creator Allah Almighty, the most

beneficent, the most merciful, who gave me strength and enabled me to undertake and execute this

research task. Countless salutations upon the Holy Prophet Hazrat Muhammad (S.A.W), source of

knowledge for enlightening with the essence of faith in Allah and guiding the mankind, the true path

of life. In obeyance of Almighty Allah’s order his creature must also be acknowledged.

I would like to express my gratitude to all those who gave me the possibility to complete this

thesis and to do the necessary research work. I am obliged to Prof. Dr. Waseem ahmed Dean, Faculty

of Biological Sciences, and Dr. Tariq mahmood In charge, Department of Plant Sciences, Quaid-i-

Azam University, Islamabad, for providing the technical support and research facilities, I have needed

to produce and complete my thesis.

First and foremost I offer my sincerest gratitude to my supervisor, Dr. Abdul Samad

Mumtaz, Assistant Professor, Department of Plant Sciences, Faculty of Biological Sciences, Quaid-i-

Azam University, Islamabad, who has supported me throughout my thesis with his patience and

knowledge whilst allowing me to work in my own way. I attribute the level of my Doctor of

Philosphy (PhD) degree to his encouragement and effort and without him this thesis, too, would not

have been completed or written. One simply could not wish for a better or friendlier supervisor.

I am very thankful to Higher education commission (HEC), Pakistan for awarding me two

scholarships during my PhD. First full funded PhD indigenous scholarship and second a sandwich

PhD scholarship for University of Ghent, Belgium. I am also thankful to Prof. Dr. Monica Hofte, my

promoter in university of Ghent, who has supported me throughout my research work in Lab of

phytopathology and molecular Biotechnology, university of Ghent, Belgium. I also praised the help of

my co-supervisors Dr. Kieu Phuong Nam (In-charge microbial group) and Dr. David (Group leader

Gene expression group) in Molecular Biotechnology Lab, university of Ghent, Belgium.

I am most grateful to say thanks to my seniors Lab fellow Dr. Sami Ullah Khan Kahloon for

their enjoyable company, care and concern, persistent support and encouragement in my research and to

Dr. Ghulam Mustaf Bajwa for his timely help and sharing problem during my research work. I want to

acknowledge the company of my colleague and friend Younas Sohail during my PhD and say thanks to

my senior Dr. Rizwana khanum.

I would like to acknowledge my old lab fellows Tasmia Awan, Samavia Mubeen, Sadia Latif, Huma

Raja, Iftikhar ahmed sarki, M.Maqsood Alam, Sana Awan, Shumaila Bano, Lala Basir, Nabila

Sarwar, Qaisar khan, Haris, Amjad ur Rehman, Usman khatik, Fakhira, Anmol Fatima and Qura tul

ain. Heartiest thanks to all my newly enrolled lab fellows especially PhD champs Hussain Badsha,

Syed Afzal shah and M.Phil fellows Kinza Ghazal, Mariah shabir, Bazgha,Farzana, Zeshan khan,

Farzana Kausar, Taimoor Alizai, Amna Javeed, Rimsha Gondal, khansa kayani, Zainab, Mushtaq,

Barkat, Baddar and Pakeeza.

xix

I would like to acknowledge all the clerical staff Mr. Izhar, Mr. Shakeeb, chacha Afzal and Mr. Amir

of Department of Plant Sciences, and other administrative staff always provided me technical

guidance along with required resources and our Laboratory assistant Yasir Mehmood Rumli whose

presence somehow perpetually refreshed, helpful, and memorable. I also enjoying teaching time during

practical class of Genetics and learn and teach M.Sc students (2010-2014) batches which are good

experience and pay effect on my future assignments.

Everlasting and heartfelt thanks to my dearest and time-tested friends and department fellows Abdul

Aziz Napir (Roomate) Asim shehzad, Nadeem Badshah, Awais Rasheed, Jabir Hussain, Motasim

Billah, Tamoor, Sheikh Nadeem, Abdul shakoor, Imran khan, Muhammad Ibrahim, Nazman, Jawad,

Iqtidar Ali, Zia ul slam, Sheikh Zain, Abbad, Aamir Qaisrani, Kaleem Iqbal (Late) and Mujeeb kakar

for their emotional backing, encouragement, concerns, love and care. The good time spent with them

can never be erased from my memories.

No acknowledgement could ever adequately express my feelings to my affectionate and adorable family

without whom I feel myself incomplete. I have no words to express my gratitude for my family

especially my Ammi (Razia Hanif) and Abbu (Haji Muhammad Hanif), without their love, care,

encouragement and support I would not be able to achieve any goal in my life. The concern and

encouragement of my humble, supportive sisters Aliya Muqadas, Asma Hanif, Kianat Hanif and

chooti Maham who are always there for me to help to pray for my success to show me right and wrong.

Thanks to my adorable, humble, and charming brothers Wasim Hanif, Touqir Asad and Ali Raza for

their prayers, sincere support and love.

In the end I want to present my unbending thanks to all those hands who prayed for my betterment

and serenity.

Muhammad Naveed

xx

Abstract

The study focused at understanding the role of pyrroloquinoline quinone (PQQ)

dependent glucose dehydrogenase (GDH) in plant growth promotion. For this purpose,

rhizosphere of crops plants and root nodules associated with cultivated and non-

cultivated legumes were screened for bacteria. Ninety two individual bacterial isolates

were recorded, which were studied biochemically for phosphate solubilizing capacity.

Among these, the fifteen top phosphate solubilizing isolates were screened for loci

responsible for production of PQQ and Glucose dehydrogenase (GDH) and twelve were

found positive. The isolates were further identified based on the 16S rRNA data as:

Ensifer, Bacillus, Pseudomonas, Enterobacter and Rhizobium. Some of the most

promising phosphate solubilizer isolates were further subjected to the multilocus

sequence analysis (MLSA) using rpoB, rpoD and recA genes for species identification

(P. fluorescens QAU67, P. putida QAU90 and Pseudomonas sp. QAU92).

The physiological and biochemical characterization of Pseudomonads and

Enterobacter (QAU66, QAU67, QAU90 and QAU92) in the collection revealed their

multi potential nature e.g. the biocontrol capacity in addition to phosphate solubilization

and plant growth promotion, for which purpose the P. fluorescens CMR12a (from Ghent)

was used as a reference strain. The Pseudomonads QAU90 and QAU92 were efficient

biocontrol strains producing antibiotics, cyclic lipopeptides (CLPs) and the antagonistic

activity. These root-colonizing Pseudomonads promoted plant growth by increasing

phosphate solubilization with secretion of gluconic acid which requires the PQQ

dependent glucose dehydrogenase (GDH).

A detailed structural characterization of the GDH protein was carried out using

bioinformatics tools; Pfam, PSIpred, InterProScan, I-TASSER and COFACTOR

predicting the functional homology of PQQ domains in GDH and identified functional

protein residues. The role of PQQ and GDH was investigated using: Tn5 random

mutation in QAU90 obtaining the gdh mutant (QAU90-23) and site directed knock out

pqqC gene mutation obtaining four mutants (CMR12a-3, QAU67-14, QAU90-4 and

QAU92-2). The role of pqq was further investigated using plant models; lettuce (Lactuca

sativa), rice cv. C-039 (Oryza sativa), bean (Phaseolus vulgaris) and tomato (Solanum

xxi

lycopersicum) plants. The results showed significant differences (p≤0.05) in plant height,

leaf number, fresh weight and dry weight etc., deciphering a clear role of PQQ in plant

growth promotion. Furthermore PQQ’s role in disease control was tested against

Rhizoctonia solani (AG2-2) causing root rot in bean. The wild-type strains reduced

disease severity caused by R. solani AG2-2 but the pqqC deficient mutant of CMR12a

unable to suppress disease while the QAU90-4 mutant still protected bean plants, albeit to

a lesser extent compared with the wild type. The pBKminiTn7-gfp2 mutation system was

used to tag the wild type and pqqC mutant strains in root colonization experiment to

confirm their presence and role in disease control. The role of PQQ in induced systemic

resistance (ISR) in rice against C. miyabeanus was checked by gene expression analysis

using qRT-PCR and recorded enhanced expression against infection of C. miyabeanus in

wild type strains as compared the pqqC mutants, this has been elucidated here for the first

time.

In summary, the 16S rRNA and housekeeping genes (MLSA) revealed species

level identification and diversity among studied isolates. The bioinformatics based

structural characterization revealed insights for the probable mechanism of phosphate

solubilization by PQQ dependent glucose dehydrogenase (GDH). The plant based

experimental data revealed a complementary role of PQQ and GDH, as mutating either of

these loci has resulted in loss of GDH function. The PQQ promotes the plant growth and

plays a role in disease (and biological) control as revealed in Pseudomonas strains

elucidated for the first time through expression analysis.

CHAPTER 1

Introduction and review of literature

Microbial diversity plays a vital role in maintaining the ecosystem and its functioning

such as to support life on earth. There are over 1.7 million strains registered and stored in World

Data Centre for Microorganisms. Microbial interaction with plants through cell signaling is

known as plant microbial interaction (Hooper and Gordon, 2001). This interaction results in

revealing important information and application in the field of biofertilizer, biofilming,

bioinoculant and bioprocessing, phosphate solubilization, nitrogen fixation, plant growth

improvement and induced systematic resistance (Rodriguez et al., 2004; Choi et al., 2008; Berg,

2009; Hayat et al., 2010).

Furthermore, the plant health is also affected by chemical fertilizers. However,

considering the hazards associated with the use of chemical fertilizers, these ought to be

substituted by environment friendly alternatives emerging through biotechnology (Dobbelaere et

al., 2003). As a consequence these will limit the use of chemicals in agriculture. The plant

growth promoting rhizobacteria (PGPR) can be used as an alternative or in supplemental manner

(Postma, et al., 2003; Welbaum, 2004; Gerhardson, 2002). Several crops have been supplied

with PGPR to promote growth, emergence of seed, disease control some of them have gained

commercial importance and crop yield (Kloepper, 1992; Dey et al., 2004). Certain PGPR strains

result in induced systemic resistance (ISR) in plants and markedly improve the plant’s defense

mechanisms, thus counteracting the infection caused by pathogen (Van Loon, 1998). A range of

antibiotics such as phenazines, hydrogen cyanide, viscosinamide, 4-diacetylphloroglucinol

(DAPG), tensin, and pyrrolnitrin formed through pseudomonads (Bloemberg and Lugtenberg

2001; Nielsen et al., 2000; Haas and Defago 2005). This achieves the crop improvement by re-

precipitation and transformation of insoluble phosphates into soluble form. This by evidence is

accomplished by Phosphate-solubilizing bacteria (PSB) (Viverk and Singh, 2001; Sudhakara et

al., 2002; Peix et al., 2001 ab).

The Gram negative bacteria present in soil secret gluconic acid by the enzymatic reaction

of glucose dehydrogenase (GDH). GDH functions to dissolve the mineral phosphate multiplexes

and fulfills the deficiency of phosphate (Goldstein, 2003) in soil. GDH belongs to the quino-

Chapter 1 Introduction and Review of Literature

“Genetic Expression and Bioinformatics of PQQ dependent glucose dehydrogenase (GDH) and Probing its Role in Plants” 2

protein family (Anthony, 1996) and offers carbon to perform important bioenergetics and govern

the bacterial intracellular metabolism. GDH uses PQQ along with some metal ions such as Ca2+

(or Mg2+ in vitro), for its proper functioning (Duine et al., 1979). Quinoprotein glucose

dehydrogenase (PQQGDH) by direct oxidation converts glucose and other aldose sugars into

corresponding acids. These acids cause the periplasmic space to develop acidic and hence in this

manner phosphate solubilization is attained (Duine 1991). In preponderance of bacterial species;

A. calcoaceticus (Hauge, 1966), P. aeruginosa (Midgley and Dawes, 1973), G. suboxydans

(Ameyama et al., 1981), and Kl. aerogenes (Neijssel et al., 1983) the activity of GDH relies on

PQQ and these strains produce PQQ themselves despite the fact that for GDH activity in E. coli

(Hommes et al., 1984) and A. lwoffi (van Schie et al., 1987) they entail the exogenous supply of

PQQ.

Pyrroloquinoline Quinone (PQQ) is water soluble, heat stable, aromatic, tricyclic ortho-

quinone that acts as cofactor for several bacterial dehydrogenases like ethanol and glucose

dehydrogenases (Duine and Jongejan, 1989). PQQ has been considered as the third category of

coenzymes after flavins and pyridine, in the biological oxido-reduction (Duine, 1991; Klinman &

Mu, 1994). The PQQ dependent GDH catalyzes direct oxidation of glucose into gluconic acid,

which in turn solubilizes the insoluble phosphate by Pseudomonas spp. in soil (De Werra et al.,

2009). The acid moiety produced by oxidation of glucose indicates the action of PQQ dependent

periplasmic membrane-bound glucose dehydrogenase (GDH).

The cofactor PQQ has multiple beneficial effects and so far reported in Acinetobacter

calcoaceticus, K. pneumoniae, M. extorquens AM1 Pseudomonas fluorescens CHA0 and

Methylobacterium organophilum DSM 760 (Morris et al., 1994). PQQ has recently been

reported as plant and bacteria growth promotion factor largely due to its antioxidant properties.

The PQQ synthesized from P. fluorescens B16 has been reported as growth promoter in tomato,

cucumber, Arabidopsis and hot pepper (Choi et al., 2008). It also induces systemic resistance in

plants (Han et al., 2008) and is directly related to the production of antimicrobial substances

(Guo et al., 2009).



Part A: PQQ dependent Glucose Dehydrogenase (GDH)

1.1 Glucose Dehydrogenase (GDH)

Glucose dehydrogenase (GDH) belongs to quinoprotein group which uses Pyrroloquinoline

Quinine (PQQ) as a redox cofactor (Duine et al., 1989) with specific binding sites of Ca2+ (in

vivo), Mg2+ (in vitro), ubiquinone and glucose as a substrate. Moreover, on the basis of their

localization within the cell, two kinds: GDH-A and GDH-B have been identified. GDH-A is

generally reported from Acinetobacter calcoaceticus, Klebsiella aerogenes, Pseudomonas

aeruginosa, Acinetobacter lwoffi, Gluconobacter suboxydans and Escherichia coli. It is a

membrane bound enzyme (m-GDH) of 88 kDa monomeric protein, present in various bacteria

with similar primary structure but different in substrate specificities. The m-GDH has a

hydrophobic n-terminal with five transmembrane segments. These anchor the protein in

membrane, whereas the c-terminal domain has a large conserved PQQ-binding site with catalytic

functions (Yamada et al., 1993). On the other hand GDH-B is a soluble enzyme (s-GDH) and

reported only in A. calcoaceticus (Cleton-Jansen et al., 1988).

GDH plays an important role in phosphate solubilization by acidification in the periplasmic

space of bacteria through direct oxidation of glucose into gluconic acid and then to 2-

ketogluconic acid (Duine et al., 1979; Anthony and Ghosh, 1997). The membrane bound

gluconic acid dehydrogenases (GADHs), involved in oxidation of gluconic acid to 2-

ketogluconic acid (Figure 1.1) which was characterized and purified from and P. aeruginosa

(Matsushita et al., 1980), K. Pneumoniae, Pseudomonas fluorescens, Serratia marcescens

(Matsushita et al., 1997) and G. dioxyacetonicus (Shinagawa et al., 1984). This pathway is

important for the endurance of enteric bacteria in aquatic, aerobic and low-phosphate

environments (Fliege et al., 1992).

The production of acids as a result of direct oxidation pathway occurs at the cell surface

because the GDH enzyme is bound to the inner membrane but its catalytic activity is towards

external surface of the cytoplasmic membrane and the periplasmic spaces provide the substrate

oxidation site (Midgley and Dawes 1973). Therefore these products which are the resultant of the

process of oxidation cause the medium to acidify by their direct release into extracellular space.

Furthermore, GDH plays an important regulatory and bioenergetics character in these bacteria in

which carbon is provided for intracellular metabolism (Sashidhar and Podile, 2009).



Figure 1.1: The anticipated pathway for catabolism of glucose in Pseudomonas is conversion of

molecules and transport using enzymes/proteins encoded by genes. The pathways are specified

for each step: gcd, glucose dehydrogenase; gntP, gluconate permease; oprB,

glucose/carbohydrate outer membrane porin; gad, gluconate dehydrogenase; glk, glucokinase;

gnuk, gluconokinase; kguT, putative 2-ketogluconate transporter; zwf, glucose 6-P-

dehydrogenase; kguK, 2-ketogluconate kinase; edd, phosphogluconate dehydratase; OM, outer

membrane; kguD, ketogluconate 6-P-reductase; eda, keto-deoxy-phosphogluconate aldolase. IM,

inner membrane and PS, periplasmic space (Miller et al., 2010).

1.2 PyrroloQuinoline Quinine (PQQ)

Pyrroloquinoline quinone (4, 5-dihydro-4, 5-dioxo-1H-pyrrolo- [2, 3- ] quinoline-2, 7, 9-

tricarboxylic acid) is a tricyclic ortho-quinone (Figure 1.2) that acts as redox cofactor for

numerous bacterial dehydrogenases like: glucose, ethanol and methanol dehydrogenases. PQQ

was originally reported as a coenzyme in methylotrophic bacteria (Westerling et al., 1979) for

methanol dehydrogenase in 1979 and was termed as methoxatin. PQQ is well renowned as the

third redox cofactors succeeding flavin dependent cofactors and pyridine nucleotide and

associates the oxidation of various diverse compounds to respiratory chain (Klinman, 1996).



The PQQ cofactor has been described in oxygenases, dehydrogenases, hydratases,

decarboxylases and oxidases. PQQ functions as prosthetic group of bacterial dehydrogenases

such as for methanol dehydrogenase (MDH) in gram negative methylotrophs, quinate

dehydrogenase, alcohol dehydrogenase and some glucose dehydrogenases (Duine and Jongejan

1989). PQQ structure suggests that PQQ has been derived from glutamic acid and tyrosine

(Houck, 1988) however the pathway for the biosynthesis of PQQ is still unidentified.

Figure 1.2: The Chemical structure of PQQ.

(Source: http://www.chris-anthony.co.uk/reseach%20pics/pqq)

Although PQQ was reported in many foods (Kumazava et al., 1995; Mitchell et al., 1999)

but microbes are major source of PQQ. The amounts of PQQ excreted by different

microorganisms differ from 1tg to 1mg/ml and are influenced by the growth medium

composition (Urakami et al., 1992). Escherichia coli lack PQQ synthase and therefore has been

used to clone PQQ synthase gene (pqqC) from Pseudomonas cepasia (Babu-Khan et al., 1995),

E. intermedium (Kim et al., 2003), Ervinia harbicola (Liu et al., 1993), Rahnella aquatilis (Kim

et al., 1998), and D. radiodurans (Khairnar et al., 2003). Meanwhile the cloning of PQQ

synthase gene from different bacteria is carried out in E.coli using the functional alternative for

mineral phosphate solubilization activity (MPS) and the synthesis of PQQ has been corroborated

by expressing the PQQ synthesis operon from G. oxidans in E. coli (Yang et al., 2010).



1.2.1 Present status and significance of PQQ

PQQ has also considered as a candidate vitamin; however its fate is yet to be determined.

Previously, Dr. U. Suzuki documented thirteen (13) substances as vitamins in 1910. His list

included vitamin B1, one of the earliest described vitamins and also the latest described vitamin:

vitamin B12, found in 1948. It was after 55 years that PQQ has been considered as a new vitamin

(Kashara and kato 2003). Since the occurrence of PQQ as bacterial enzymes its occurrence in

higher organisms is being sought. So far it has been reported in the tissues of citrus fruits,

mammalian milk and certain body fluids (Paz, 1988).

1.2.2 Biosynthesis and genetics of PQQ

The genetics involved in the biosynthesis of PQQ has been studied in A. calcoaceticus

(Goosen et al., 1989), Kl. pneumoniae (Meulenberg et al., 1992), P. fluorescens CHA0 (Schnider

et al., 1995), M. extorquens AM1 (Toyama et al., 1997), E. intermedium 60-2G (Kim et al.,

2003), G. oxydans (Hölscher and Görisch 2006) and P. fluorescens B16 (Choi et al., 2008). In A.

calcoaceticus four genes are associated with the biosynthesis of PQQ whereas in case of

methylotrophs and G. oxidans, 6-7 genes are linked with the production of PQQ. Majority of the

PQQ synthesizing bacteria have operon containing 6-7 genes i.e. (pqqABCDEF/G). Five pqq

genes were recognized and sequenced in A. calcoaceticus, labelled as IV, V, I, II and III

(Schnider, 1995). In corresponding to K. pneumoniae genes, which were recognized as

pqqABCDE immediately a sixth gene designated as pqqF was found downstream of pqqE

(Kumazawa, 1995). A five gene constellation (labeled pqqDGCBA) was recognized by

complementation analysis in Methylobacterium strain ((Abdel-Monem et al., 2001) and the

sequence data from M. extorquens AM1 demonstrated analogy between the pqqDGC and

pqqABC of K. pneumoniae (Stites et al., 2000). The genes analog of pqqFAB of K. pneumoniae

in P. fluorescens have also been sequenced (Ahmed and Shahab, 2010). The PQQ operon in P.

fluorescens B16 is comprised of 11 genes (Figure 1.3) designated as: pqq-A, -B, -C, -D, -E, -F, -

H, -I, -J, -K, and -M (Choi et al., 2008), among these pqqFHIJK are not fully characterized.



Figure 1.3: Comparison of the pqq gene clusters of P. fluorescens B16, Acinetobacter

calcoaceticus, P. fluorescens pf01, klebsiella pneumonia, Methylobacterium extorquens AM1

and Gluconobacter oxydans ATCC9937. Locations and alignments of the pqq genes are

designated by colored arrows. The identical colors represent homologous encoded proteins (choi

et al., 2008).

The PQQ operon of G. oxydans ATCC 9937 was cloned and sequenced in 2000 and it

contained pqqABCDE (Felder et al., 2000). The sequencing of the entire genome of G. oxydans

621H in 2005 exhibited that the pqqABCDE operon showed maximum resemblance (Table 1.1)

with that of pqqABCDE operon from G. oxydans ATCC 9937 (Prust et al., 2005). Holscher and

Gorisch (2006) further described that a G. oxydans 621H gene displaying maximum similarity

with E. coli tldD gene is mandatory to the pqqABCDE cluster. The gene, tldD, from G. oxydans

621H might be comparable in function to the pqqF genes in other PQQ synthesizing bacteria.

The PQQ biosynthetic pathway has not yet been clearly enlightened but glutamate and

tyrosine have been recommended as precursors for PQQ synthesis (Van Kleef & Duine, 1988).

In all studies, a small gene (pqqA) in the pqq operon, that encodes a minor peptide of 23-29

amino acids with conserved glutamate and tyrosine residues was thought to be a PQQ precursor

(Goosen et al., 1992), as also demonstrated later (Velterop, 1995). Since the E. coli protease III



(or pitrilysin) and insulinase showed affinity with K. pneumoniae pqqF gene product and it was

proposed that the PqqA precursor cleavage was carried out by PqqF enzyme (Meulenberg et al.,

1992).

All other quinone cofactors such as; tryptophan tryptophylquinone (TTQ), cysteine

tryptophylquinone (CTQ), topaquinone (TPQ) and lysyl tyrosylquinone (LTQ) (Pearson et al.,

2004; DuBois et al., 2005) are allied to amino acid backbone through covalent bond. However

the PQQ detaches itself from apoenzyme freely, hence its biogenesis is autonomous of its

catalytic function. It has been suggested that a small peptide acts as a substrate to synthesize a

free form of PQQ, while others are derived from the amino acid residue(s) on the peptide

backbone of premature proteins through post-translational modifications; LTQ from tyrosine and

a lysyl residue, TTQ from two tryptophan residues and TPQ from tyrosine (McIntire 1991).

Only apo-GCD can be synthesized by means of firmly associated to E. coli and S.

typhimurium but PQQ is not synthesized by them (Hommes et al., 1984, 1986). However, active

holo-GCD can be acquired from apo-GCD via adding PQQ extra-cellular (Van Schie et al.,

1987). It has been determined that the genes responsible for synthesis of PQQ are lacking in S.

typhimurium and E. coli and the role of such apo-GCD remains unclear. It has been

recommended that organisms which are incompetent to synthesize PQQ can scavenge it from

other sources and elicit their apo-quinoproteins (Matsushita et al., 1997).

Six PQQ genes from K. pneumoniae when articulated in E.coli resulted in the formation

of PQQ and an active GCD. Probably the synthesis of PQQ occurs in cytoplasm and then

released into medium and periplasm faced by the PQQ binding site of GCD (Yamada et al.,

1993). The growth revisions of E. coli ptsHI mutants accompanied with plasmids deficient one

of the six PQQ genes or with a complete K. pneumoniae PQQ gene-set determined the

measurement of PQQ biosynthesis in the growth medium and verified the biosynthesis of PQQ

each with six genes (Velterop et al., 1995).

The genes for the biosynthesis of PQQ may be described in two groups as: pqqAB (C/D)

E and pqqFG in Methylobacterium extorquens AM1 (Toyama et al., 1997). The description of

these genes standardized the taxonomy of K. pneumonia. These genes were previously described

as pqqDGCBA and pqqEF (Morris et al., 1994) in Methylobacterium strains. The pqqC and



pqqD are merged in a solitary gene called pqqCD in M. extorquens AM1. The pqqA was

investigated at transcriptional level in M. extorquens AM1 (Ramamoorthi & Mary, 1995) and act

as a precursor for PQQ.

Table 1.1: The percentage similarities between pqqBCDE genes of different bacteria

(Felder et al., 2000)

In conclusion the PQQ biosynthesis pathway is comprised of six most conserved PQQ

genes (pqqABCDEF) in most of the bacterial strains. For biosynthesis, the small peptide (23 to

29 amino acids) with conserved glutamate and tyrosine residue, provide the backbone for PQQ

biosynthesis (Van Kleef et al., 1988). The pqqE (belong radical Sadenosylmethionine (SAM)

enzymes family) catalyzes a radical driven C-C bond needed to connect the glutamate and

tyrosine moieties at positions C9 and C9a of PQQ (Puehringer et al., 2008). The processing of

the peptide precursor of PQQ (glutamate and tyrosine) was carried out through pqqF and pqqG

(Meulenberg et al., 1992). The PQQ biosynthesis is performed by pqqC (cofactor-less PQQ

synthase) because it catalyzes the final step in PQQ biosynthesis pathway (Magnusson et al.,

2004). The pqqD then plays a part in releasing PQQ from pqqC and binding of pqqB to pqqC

(Puehringer et al., 2008). As a last step, the pqqB protein transfers the PQQ into periplasm

(Velterop et al., 1995).



Part B: The Bioinformatics

1.3 Structural characterization of PQQ dependent GDH

Protein structure prediction involves generating 3-dimensional models (3D) from amino

acid sequences by computer algorithms. However, it is actually the combination of human expert

information with biochemical knowledge (catalytic residues, mutagenesis and function etc.) to

build a structural assembly and also model selection (Ginalski et al., 2003). The iterative

threading assembly refinement server (I-TASSER) is an assimilated platform used for the

prediction of computerized protein structure and functional prediction, created on a sequence-to-

structure-to-function paradigm. I-TASSER first makes 3D structure starting with an amino acid

sequence of the predicted protein by structural assembly simulations and multiple threading

alignments. Then prediction on function of the protein was obtained from structural correspond

to the 3D models with available proteins structures in protein databases. I-TASSER provides

full-length secondary and tertiary structure of predicted protein query, Enzyme Commission

numbers, functional annotations based on ligand binding sites and the Gene Ontology as output.

The estimation of precision in predictions was reflected by confidence score of the modeling

(Roy et al., 2010).

To predict protein structure analysis by I-TASSER and COFACTOR servers of Zhong

Lab, the query sequence is matched by position-specific iterated BLAST against non-redundant

sequences (Altschul et al., 1997), to identify evolutionary relatives. On the base of multiple

alignments of the sequence homologs, a sequence profile is created which is then used for

secondary structure prediction using PSIPRED (Jones, 1999). Supported by the predicted protein

secondary structure and sequence profile, the query sequence then threaded over the

representative PDB structure library LOMETS (locally installed meta-threading server) (Wu et al

2007). In threading programs, the templates are graded by a variety of structure-based and

sequence-based scores then the top template hits selected was selected for more consideration.

The value of the template alignments is judged on the base of statistical significance i.e., the Z-

score, which is the energy score in standard deviation units comparative to the statistical average

of all alignments.



The biological function of a protein is predicted by its 3D shape, largely depicts how

protein interrelates with ligands and other protein molecules (Lopez et al., 2011), In a latest

advancement of I-TASSER (Roy et al., 2012), the method was extended for interpreting the

biological function by predicted protein structures which was based on the local and global

structural resemblances with proteins of well-known functions. This method was used for the

biological functions and identification based on similarities to non-homologous proteins, which

otherwise could not have been predicted from profile-based searches and sequence (Altschul et

al., 1997).

For prokaryotic organisms, the increasing number of genomic sequences when

investigated through bioinformatics reflected orphan pathways with anonymous products of

possible therapeutic application (McClerren et al., 2006). Indeed, for recognizing such pathways,

gene products from the PQQ operon were previously being used as guides (Haft, 2011). To

recognize the sequence motifs and structural characters that differentiate each biosynthetic

protein from functionally deviating homologues, structural phylogenomic analyses were applied

(Sjolander, 2010). For envisaging putative part designed for open reading frames within the PQQ

operon and investigating the involvement of conserved amino acid side chains in the gene

products with verified function, these studies aid as a guide (Shen et al., 2012).

Bioinformatics analysis has been useful in characterization and identification of

homologues and corresponding PFAM domains respectively (Bateman et al., 2004). The analysis

further revealed comparative similarities and functions. Homologue identification, multiple

sequence alignment, construction and analysis of phylogenetic tree, prediction of protein

structure and identification of functional site were performed by Shen et al., (2012) for every

single gene in the PQQ operon for five bacterial species (Figure 1.4). UniProt protein database

(released in 2010-11) was used to retrieve homologues by applying the FlowerPower

phylogenomic software to choose proteins sharing the same domain design (Krishnamurthy et

al., 2007). For the construction of Multiple sequence alignments (MSAs), MAFFT was used

(Katoh et al., 2002), followed by masking for the removal of columns with >70% gap characters.

Using RAxML trees with maximum likelihood were projected from the masked MSAs

(Stamatakis, 2006). Through an amalgamation of evolutionary preservation and structural



information, residues that seemed to be functionally important were recognized using INTREPID

and Discern algorithms (Sankararaman et al., 2008; 2010).

Figure 1.4: Purposed scheme for bioinformatics work of PQQ (Shen et al., 2012).

1.3.1 The chemistry of PQQ operon

The pqqA gene encodes 23 to 29 amino acids. It is relatively conserved in bacterial

species, encoding 23 amino acids in K. pneumoniae (Morris et al., 1994), 24 or 39 amino acids in

P. fluorescens (Schnider et al., 1995), 24 amino acids in M. flagellatum and 29 amino acids in

M. extorquens (Schwarzenbacher et al., 2004). Glutamate and tyrosine, the conserved residues

are positioned in the glu-X-X-X-tyr which is in the center of pqqA peptide. The expression of

PqqA is 20 folds greater than the PqqC or PqqE at protein level (Morris et al., 1994).

The molecular mass of pqqB protein is about 33 kDa with 300 residues and a theoretical

pI around 5.7. The main function of pqqB protein is to transfer PQQ into periplasm in its

biosynthesis pathway. A formerly unlabeled unique cysteine-rich sequence is present at the N-

terminus of pqqB. When pqqB was knocked out only minor amount of PQQ got synthesized in

the cytosol (Velterop et al., 1995) and no PQQ was secreted in the periplasm. The quantity of

PQQ in the cytosol was in the equimolar association to pqqC which highlighted only an indirect



requirement of pqqB for the biosynthesis of PQQ and involved in the transportation of PQQ into

cytoplasm where the bacterial dehydrogenases reside. The release of PQQ from pqqC may

require as PQQ-acceptor. Puehringer et al. (2008) scrutinized the sequence of pqqB and

characterized it to be a member of the metallo-β-lactamase superfamily. PhnP is shown to be

closest to the functionally distinct homologue of pqqB and it is a phosphodiesterase with 26%

sequence similarity with pqqB (Podzelinska et al., 2009).

The molecular mass of pqqC protein is about 29 kDa with 250 residues and a theoretical

pI of 6.9. The main function of pqqC is to produce cofactor-less PQQ synthase that catalyzes the

final step in PQQ biosynthesis pathway (Magnusson et al., 2004). The crystal structure of PqqC

from Kl. pneumonia (Meulenberg et al., 1992) showed that the enzyme is a 58kDa homodimer,

where each monomer is folded into a compressed helix bundle, among which the six helices are

circularly line up, while the seventh a hydrophobic helix. The reaction catalyzed by pqqC has

been documented and PqqC came out to be an oxidase and its uniqueness is characterized via

absence of redox-metal or other cofactor. The reaction of PQQ with oxygen produced free

radicals (Aizenman et al., 1992) which have toxic effects on cell, now the question how PQQ

discharges from pqqC.

It is probable that an additional member of the pathway acts as a carrier that uses PQQ as

a cofactor and prompts the discharge of PQQ. Similarly in vitro, if there is no other enzyme then

pqqC reaction is under the product inhibition control and only computable at single turnover

circumstances. The pqqC is the most important in the pathway and the final steps i.e oxidation

and cyclization of the transitional 3a-(2-amino-2-carboxy-ethyl)-4, 5-dioxo-4, 5, 6, 7, 8, 9-

hexahydroquinoline-7, 9-dicarboxylic acid to PQQ in the biosynthesis of PQQ, are carried out by

it and is encoded by nucleotide sequence of pqqC gene (Magnusson et al., 2004).

The final step of PQQ biosynthesis is the oxidation of 3a-(2- amino-2-carboxyethyl)-4,

5-dioxo-4, 5, 6, 7, 8, 9- hexahydroquinoline- 7, 9-dicarboxylic acid (AHQQ), in which eight

protons and electron are donated to molecular oxygen in order to make hydrogen peroxide/water.

This step is catalyzed by pqqC. TenA is the intimate functionally discrete homologue of PqqC

recognized in the phylogenetic tree. TenA has its place to thiaminase II class of enzymes and it

hydrolyses 4-amino-5-aminomethyl-2-methylpyrimidine as portion of a pathway for retrieving



base-degraded thiamin (Toms et al., 2005). The pqqC and TenA are similar in structure when

they are compared but PqqC has distinct active site from that of TenA.

The pqqD is a small protein with 90 residues. Its function can only be speculated and it

should catalyze one of the so far un-assigned but necessary transformations. Three probable

functions have been supposed for pqqD: First, it can play a part in the release of PQQ from

PqqC; second: it can be responsible for binding of pqqB to pqqC; third: its deoxygenase role in

the pathway. The Robetta server (Chivian et al., 2003) based de novo modeling illustrated that

the protein entails 4 helices and 3 β-strands that produced a β-sheet. The preserved residues were

chiefly constrained to an exposed, unstructured domain of pqqD suggesting that significant

restructuring of pqqD may be facilitated by interaction of pqqD protein with PqqE (Wecksler et

al., 2009).

The molecular mass of pqqE protein is about 43 kDA with 380 residues. The sequences

of pqqE suggest that it has SAM domain with iron-sulfur cluster, based on this it is determined

that pqqE belonged to the radical Sadenosylmethionine (SAM) enzyme family. The pqqE

catalyses a radical driven C-C bond construction needed to bind glutamate and tyrosine moieties

at position C9 and C9a of PQQ. The active site harbored by the cavity with iron-sulfur-cluster

and the linked to SAM. Since we know that β-strand is formed by PqqA, there is a channel to the

active site, hypothesized that it is pqqA moves to the iron-sulfur group through this via Tyrosine

and glutamate side chains. The residues are highly conserved and are likely to be entangled in

the identification and alignment of substrate (Puehringer et al., 2008). The NirJ is closest

functional homologue of pqqE as it shares 26% of sequence similarity (by NirJ from Sulfurovum

sp., UniProt entry A6X6Z2) and catalyzes the biosynthesis of heme d1 (Brindley et al., 2010).

The pqqF is a long protein with 760 residues with molecular weight of 84 kD and the

biggest in the pathway. It shares a sequence similarity of 17% with pqqF and human insulin-

degrading enzyme (IDE) (a metalloendopeptidase). Therefore, pqqF is most probably a

metalloendopeptidase which plays its role in dealing with the tyrosine and glutamate of pqqA at

R1–R3 with a Zinc core in its active site. It has sequence similarity of 15–20% with insulin-

degrading enzymes and protease III of Bacteria. Perhaps pqqF follow similar mechanism to that

of insulin degrading enzyme where charge dispersal and size of the cavity are used by the

enzyme to capture polypeptides selectively that are structurally diverse (Shen et al., 2006).



Sequence similarity is shown by pqqF and pqqG with a family of divalent cation-comprising

endo-peptidases that chop small peptides (Meulenberg et al., 1992).



Part C: PQQ Potentials / Applications

1.4 PQQ as Plant Growth Promoter

The cofactor PQQ has several beneficial effects. The presence of PQQ in food depicts its

possible role as a growth-promoting factor (He et al., 2003; Steinberg et al., 2003). PQQ has

recently been reported as plant and bacterial growth promotion factor on the basis of its

antioxidant properties. The PQQ produced by P. fluorescens B16 has been reported as growth

promoter in tomato, cucumber, Arabidopsis and hot pepper (Choi et al., 2008). It also induces

systemic resistance in plants (Han et al., 2008) and is directly related to the production of

antimicrobial substances (Guo et al., 2009). Gluconic acid produced by the isolates of a non-

fluorescent Pseudomonas is deemed important for biological control against diseases (Kaur et

al., 2006).

There are only few studies available on the functional role of PQQ in plants. Some of the

recent studies have highlighted PQQs role in, in vitro pollen germination in Camellia, Tulipa and

Lillium (Xiong et al., 1988; 1990), yet with an unknown mechanism. In the assays considering

redox cycling potentials, PQQ has been reported 100 times more proficient as compared to iso-

flavonoids, ascorbic acid and polyphenolic compounds (Stites et al., 2000). PQQ could also be

responsible for scavenging toxic free radicals besides scavenging superoxide, a property quite

comparable to the flavonoids, vitamin C, b-carotene and carotenoids, vitamin B, phenolic

compounds and conjugated linoleic acid (McIntire, 1998). PQQ was also found in traces in plant

and animal tissues, though these systems do not produce PQQ themselves (Kumazawa et al.,

1992). Considerably enhanced total fruit weight, fruit number, flower number and height is

displayed by plants that are cultured in hydroponic culture systems using rhizobacterium while

these features are not identified in rhizobacteria that are genetically modified and incompetent to

synthesize PQQ (Choi et al., 2008).

To some extent, the role of PQQ is connected with the uptake of phosphate via plants, as

a cofactor for rhizobacteria dehydrogenases. PQQ aids in making the soil and the surrounding

environment more acidic (Rodriguez et al., 2000) consequently more phosphate is available to

plants (Figure 1.5). Furthermore, through viral protection, antioxidant defense, activation of cell

signaling and independent role has been recommended for PQQ associated to growth of plants



(Pierpoint, 1990). It is probable to recognize new factors in plant microbe interaction by the use

of molecular techniques (Berg, 2009). For instance, a genomic library of PQQ biosynthetic genes

of P. fluorescens B16, was recognized as being accountable for plant growth promotion besides

it antioxidant properties (Choi et al., 2008).

Recently it was reported that mutation in PQQ synthesis genes, it lost the plant growth

promoting activity (Ahmed and Shahab, 2010). Until now the useful effects of PQQ were suitably

explained on the basis of its capacity to produce organic acids. Substantial increase in fresh

weight of cucumber has been noticed when synthetic PQQ was supplemented as a nutrient this

confirmed PQQ as a plant growth promoting factor yet with unknown mechanism. The role of

PQQ in productivity of crops is in addition to its role in solubilization of insoluble phosphates

(Choi et al., 2008).

Figure 1.5: The role of quinoprotein glucose dehydrogenases (GDH) in extra cytoplasmic

glucose metabolism. The D-Glucose is oxidized to D-glucono- 1, 5-lactone by the action of

GdhS in the periplasm, a process require pyrroloquinoline quinone (PQQ) and hydrolyzed to D-

gluconic acid (Fender et al., 2012).



1.5 PQQ as an antioxidant

PQQ is also recognized as an antioxidant and its role in scavenging reactive oxygen

species (ROS) has been described in E. coli (Misra et al., 2004). Furthermore the enhanced

formation of Reactive Oxygen Species results in oxidative stress in cell. Reactive

oxygen/nitrogen species are produced under normal processes of energy metabolism. Though,

when the cells are exposed to abiotic stresses like dehydration salinity, radiation, high

temperature etc., the levels of such species increase several folds (Halliwel and Gutteridge,

1999).

When the PQQ structure was investigated for its antioxidant traits, it revealed high

electron density in its heterocyclic backbone which confers good neutralization of ROS. The

PQQ synthase gene taken from D. radiodurans was engineered for expression in a bacterium E.

coli which is sensitive to both γ –radiation and oxidative stress. The E. coli cells with the PQQ

synthase gene were examined for UV resistance and oxidative stress tolerance (Schaefer et al.,

2000). Almost, four fold higher protections of proteins from damage induced by γ radiation was

shown by E. coli cells producing high levels of PQQ as compared to control cells that were not

producing PQQ. These results point to the PQQ functions to protect the cells in oxidative stress

(Khairnar et al., 2003).

PQQ revealed affinity with hydroxyl, superoxide and oxygen free radicals produced via

pulse radiolysis. The rate of reaction of this compound was slightly less as paralleled to trolox

and ascorbic acid, with hydroxyl radical. The rate of reaction of PQQ with superoxide radical is

faster in contrast to trolox and ascorbic acid. Around six fold protection of double stranded DNA

and 2.5 fold protection of purified protein from damage brought by γ radiation were exposed

through PQQ at 10 μM concentrations (Misra et al., 2004). This suggest that PQQ function in

vitro efficiently as an antioxidant and is involved in the protection of biomolecules from

hazardous effects of radiations. The ability of PQQ as an antioxidant was extremely appreciated

for the reason that majority of antioxidants and radioprotectors illustrate anticipated activity in

vitro and not in vivo. In advanced investigation, the phosphate-solubilizing bacteria extracted

from soils lacking in phosphate were studied for tolerance to oxidative stress. Greater tolerance

was shown to hydrogen peroxide and the effect of γ radiation by PQQ producing bacteria

(Shrivastava et al., 2010).



Part D: Mutagenesis

1.6 Transposons mutagenesis

Transposons are extensively implemented tools for arbitrary mutagenesis in vitro and in

vivo in diverse group of organisms extending from gram-negative E. coli to eukaryotes and for

introgression of useful traits, engineered transposons have been developed (Bordi et al., 2008;

Petzke and Luzhetsky, 2009). The causal agents of numerous deletion, insertion, inversion and

chromosomal fusion mutations are transposons. Once transposons are introduced in the suitable

position of the genome, they introduce mutation which made the critical genes silent or activated

(Chandler and Mahillon 2002; Reznikoff 2003). Though, various transposon transport systems

have been established for gram negative bacteria, these introgress selectable markers are not

advantageous in gram-positive bacteria (Bordi et al., 2008). ‘Replicative transposition’ and ‘Cut

and paste’ are the two mechanisms involved in the movement of transposons (Hayes, 2003).

The transposons are preferred as genetic tools, as those incorporate arbitrary random

mutations. The first so used Tn3 was Tn3-like transposon in B. subtilis for the introduction of a

promoterless lacZ. The advantages of using ‘Tn’ system are their insertional capability at

numerous positions in a chromosome. Example of such a system is the Tn917 used for

introducing insertions in B. subtilis chromosome (Youngman et al., 1985). Similarly a

transposon based Tn5 derivative was reported to study a constitutively expressed reporter gene

(gusA) (Ausubel et al., 1989).

The bacterial transposon Tn7 inserts on the chromosome in a number of Gram-negative

bacteria at a great frequency into a definite intergenic site at Tn7 (Craig, 1989). The Tn7

transposon is a useful tool for the insertion of cloned DNA delivery system due to its precise

insertion. The accurate recognition of the tagged bacteria in normal environments is the possible

uses of Tn7-based systems and stable insertion of marker genes (Berg et al., 1999) along with

gene expression studies insertion of transcriptional fusions in a single copy on the chromosome.

On the other hand the random insertion of Tn5-based vectors into chromosome cause positional

effects expression of inserted genes and insertional inactivation of host genes (Sousa et al., 1997)

The single-copy DNA insertion into the chromosome is vulnerable by the limited number

of unique cloning sites in current Tn7-based vector system (Bao et al., 1991; Barry, 1988).



Besides, only few Tn7-based vectors are available for specific gfp tagging. Therefore, Gram-

negative bacteria employ the lux genes encoding bacterial luciferase as marker and the lacZ gene

encoding β-galactosidase (Shen et al., 1992). The green fluorescent protein (GFP) encoding gene

from jellyfish (Aquorea victoria) possessed several advantages over β-galactosidase markers. For

instance, it can be identified in cells in situ, and proper folding of the protein depends on oxygen

and GFP responsible for fluorescence not the substrates used (Heim et al., 1994). Therefore, the

gfp gene is considered the finest tool for in situ studies of cell localizations in complex system

using flow cytometry or fluorescence microscopy (Normander et al., 1999). The mini-Tn7-gfp

tagged clearly indicated expression gene in the barley rhizosphere and should be useful for

upcoming environmental studies addressing gene expression and population dynamics (Koch et

al., 2001).



Part E: Induced Systemic Resistance (ISR)

1.7 Gene expression and Induced Systemic Resistance (ISR)

The term ‘acquired physiological immunity’ was suggested by Chester (1933), on the

basis of induced defense in plants against many pathogens. Later quite a few terms such as;

systemic acquired resistance (Ross, 1961), translocated resistance and plant immunization

(Tuzun and Kuc, 1991) have been used to define the process of induced resistance. Induced

resistance was described as development of the plant's defensive ability against all kind of

pathogens and pests. Hammerschmidt and Kuc (1982) identified a subsequent by higher

resistance caused by pathogen infection and referred to as induced systemic resistance (ISR).

Various methods are available for inducing systemic resistance in plants, such as those involving

chemical inducers that are applied exogenously (Edreva, 2004; Ahn, 2005; Saikia et al., 2006).

An alternative to these methods is the systemic resistance stimulated by rhizobacteria usually

called induced systemic resistance (ISR). The activity of pathogenic microorganism can be

reduced not only through microbial antagonism, but can also be employed for the induction of

systemic resistance in plants. Such a method offers protection to various phytopathogenic

organisms including bacteria, fungi and viruses. It is considered as improved defensive ability

termed as induced systemic resistance (ISR) (Van loon, 2006).

ISR is controlled by diverse signaling pathways that regulate systemic acquired resistance

(SAR). The ISR pathway is encouraged when plant is confronted with non-pathogenic organism

producing siderophores, N-acyl-homoserine lactones, O-antigen of lipopolysaccharide and

salicylic acid that activate ISRs. The expression of genes related to defense is triggered by some

PGPR while other illustrations seem to work entirely by priming of efficient mechanisms of

resistance (Conrath et al., 2002; Berg 2009). Van Peer et al., (1991) for the first time

demonstrated the evidence of ISR in carnation that was protected systemically against Fusarium

oxysporum f.sp. dianthi after treatment with P. fluorescens WCS417. Similarly Wei et al., (1996)

reported ISR in cucumber (Cucumis sativus) with decreased vulnerability to foliar disease

instigated through C. orbiculare.

SAR is activated by a confined contagion with a necrotizing pathogen and is marked by

the systemic increases in salicylic acid (SA) with the accumulation of pathogenesis related (PRs)



proteins (Grant and Lamb, 2006). When PGPR colonized the roots of selected host plants, it led

to Induced Systemic Resistance (ISR) (Van Loon et al., 1998). Several studies are available on

rhizobacteria-mediated ISR functions independently of SA but require components of the

ethylene (ET) and jasmonic acid (JA) response pathways in Arabidopsis and rice (Pieterse et al.,

1998; Verhagen et al., 2004; De Vleesschauwer et al., 2008; De Vleesschauwer and Höfte,

2009).

Signal transduction pathways of provoked plants when investigated, proposed that some

of the alike pathways are triggered by Bacillus sp. as those activated via Pseudomonas spp. The

Pseudomonad PGPR that induces ISR is independent to SA whereas on ethylene, JA, and Npr1,

a regulatory gene that bring the nucleotide sequence for salicylate dehydrogenase, is dependent.

The result is analogous to several Bacillus sp. strains but other cases exhibited that Bacillus sp.

elicited ISR is autonomous of jasmonic acid and NPR1 while dependent on SA. Signal

transduction pathways liberated of JA, SA and Npr1 were involved in the ISR triggered through

VOCs of Bacillus amyloliquefaciens IN937a and Bacillus subtilis GB03. Furthermore, in some

cases, a defense gene PRI accumulates in plants using ISR induced by Bacillus sp. (Kumar et al.,

2012; Ryu et al., 2004).

The 5-week-old rice CO39 seedlings were sprayed and then inoculated with the virulent

strain Cm988. The previous reports treatment 0.1 mM JA (Ahn et al., 2005) produced no

significant defense against C. miyabeanus; however this concentration is quite enough to induce

JA-responsive JIOsPR10 transcription (Jwa et al., 2001). JA higher concentrations also failed to

activate induced resistance, signifying that JA might not be a major signal for the initiation of

defenses against C. miyabeanus. Interestingly, pretreatment with an ET-releasing plant growth

regulator (0.5 mM ethephon), rendered plants more susceptible to brown spot disease as

compared with non-induced controls (De Vleesschauwer et al., 2010)

A phosphate-solubilizing bacterium, E. intermedium 60-2G, has the capability of

inducing systemic resistance in plants in contrast to Erwinia carotovora which is soft rot

pathogen and the biocontrol ability of the mutants is disappeared when they carry mutations in

pqqA and pqqB genes. Interestingly, for Magnaporthe grisea KI-409, a rice pathogen, both

pqqA and pqqB mutants of E. intermedium vanished their bio-control capability as well as their

capacity to upsurge the systemic resistance to the infection instigated by fungal pathogens



suggest contribution of PQQ in MPS, antifungal activity and in elaboration of induced systemic

resistance of E. intermedium (Han et al., 2008). There are not too many studies are reported for

expressional analysis of PQQ in plants, so the present study is aim to investigate the expressional

analysis of PQQ against plant diseases.



1.8. Aims and objectives of the study

The overall aim is to study the role of PQQ dependent glucose dehydrogenase in plant growth

promotion.

The specific aims of this study are:-

A. To characterize the phenotypic diversity of bacterial isolates.

B. The molecular identification of strains using 16S rRNA and multilocus sequence analysis

(MLSA) genes.

C. The structural characterization of PQQ dependent Glucose dehydrogenase (GDH)

through Bioinformatics tools.

D. To study the roles of PQQ and GDH in phosphate solubilization and plant growth

promotion through mutagenesis.

E. To characterize the PQQ role in disease control and induced systemic resistance.

CHAPTER 2

Materials and Methods

The screening and characterization of bacterial isolates was carried out in Plant Genetics

and Genomics laboratory at Quaid-I-Azam University Islamabad, Pakistan, while the mutational

analysis, the phytopathology and molecular work was carried out in the Phytopathology

Laboratory at Ghent University, Belgium. The work mainly focused at Pyrroloquinoline

quinolone (PQQ) dependent glucose dehydrogenase (GDH) by characterization the phosphate

solubilizing bacteria (PSB), their identification, molecular characterization, mutagenesis, their

role in plant growth promotion, disease control, induced systemic resistance and bioinformatics

based structural analysis.

2.1 Collection of samples

The rhizosphere and the root nodules samples were collected from different field grown

crops, wild leguminous and non-leguminous plants from different regions of Pakistan (Figure 1),

mainly to explore the bacterial potential for phosphate solubilization. The rhizospheric soil

samples were collected from various sites (Appendix A). The soil particles adhering to the roots

were washed carefully by shaking the roots for 5 min in Milli-Q water followed by isolation.

2.1.1 Bacterial isolation and preservation

Rhizospheric root samples associated with several crops (Appendix A) were taken from

three replicate plots (three samples in total, one sample consisting of the roots of 10 plants taken

from each plot). The passport information on the samples has been provided in Appendix B.

After washing, roots were briefly dried on paper. Each root sample was placed in a 100 ml

Erlenmeyer flask partly filled with 50 ml sterile 0.9% NaCl solution and stored overnight at 4°C.

The root suspensions were then shaken for 30 min at 350 rpm. Subsequently, root suspensions

were inoculated in 1:9 ratio in the King’ B (King et al., 1954) broth medium (Appendix D) for

Pseudomonads and Luria-Bertini (LB) medium (Appendix C) (Sambrook and Russell, 2001)

grown overnight with slight agitation at 28°C for other bacterial isolates. Serial dilutions were

Chapter 2 Materials and Methods


prepared and plated onto KB/LB agar plates from KB/LB broth cultures. After incubation for 48

h, 40 to 50 colonies were selected per root sample.

Leguminous plant root nodules were used to isolate nodulating strains using a method

describe in Vincent (1970). The nodule extracts were streaked on yeast extract mannitol (YEM)

agar (Beck et al., 1993) medium with following recipe mentioned in Appendix G. The pH of the

medium was maintained at 6.8-7.0 and samples were allowed to grow at 28°C. Single rhizobial

colonies, appeared on YEM agar plates in 48 to 72 hours of incubation, were picked and sub-

cultured repeatedly on fresh YEM medium to obtained purified culture.

Figure 2.1: Map showing parts of Pakistan where collections were made highlighted as red stars

as described below: (1) Rawalpindi, (2) Islamabad, (3) Multan, (4) Jacobabad and (5) Gujrat &

Gujranwala (overlapping so appeared bold).



Bacterial cultures were preserved in glycerol at -80˚C for further experimentation. For

culture preservation 1 ml of sterilized glycerol (40%) was mixed with 1 ml of LB broth culture

of each isolates in an eppendorf tube and cultures free of contamination were preserved at -80˚C.

2.2 Screening and characterization of phosphate solubilizing bacteria

Phosphate solubilization activity of bacterial isolates were determined on Pikovskaya

(Pikovskaya, 1948) medium (Appendix F) at a pH 7. The medium was prepared and autoclaved

at 121 ̊C for 20 minutes. After autoclaving, the medium was allowed to cool and poured into

sterilized petri plates. As the media solidified, each isolate was pin pointed in center of plates

which were then incubated at 28 ̊C for 4-7 days. The halo zone formation around the bacterial

colony was considered as an indicator of phosphate solubilization. Strains were pin pointed on

Pikovskaya medium for three consecutive times to (re)confirm the phosphate solubilization

activity. The solubilization efficiency was determined by measuring the halo diameter (HD) and

the colony diameter (CD). The following formula was used to determine ‘solubilization index’:

Colony diameter + Halo diameter

Solubilization Index = ____________________________

Colony diameter

2.2.1 Change in medium pH by phosphate solubilizing bacteria

The experiment was carried out in a 250 ml Erlenmeyer flask and 100 ml of Pikovskaya

broth medium was poured into each flask. Before inoculation, the initial pH of the medium was

determined. Each bacterial isolate was inoculated in sterilized Pikovskaya broth medium and

incubated at 28 ̊C on a shaker with continuous agitation for 5 days. The pH of the broth was

immediately measured after sampling using electric cathode. The change in pH was determined

by subtracting the final value from the initial value.

2.2.2 Biochemical and physiological characterization of phosphate solubilizing bacteria

The bacteria that showed positive activity for phosphate solubilization were further

characterized for their morphological, biochemical, physiological and molecular traits and

assessed for their potential role in plant disease control and growth promotion. The colony



morphology and studied character states are given in (Appendix J). The process of Gram’s

staining (Appendix H) was performed as described by Gephardt et al., (1981).

2.2.2.1 N-acyl homoserine lactone (AHL) test

The indicator strain Chromobacterium violaceum was inoculated on LB broth media and

was allowed to grow at 36±1 ̊C for 24 hours with continuous shaking. The test organisms

(strains) were streaked on tryptone yeast extract (TY) medium (Beringer, 1974) and incubated at

37 ̊C for 24 hours (Appendix E). The Soft LB (0.6% agar) was melted and allowed to cool at

45 ̊C. The strains after overnight growth was overlaid with 5 ml of soft LB in a test tube which

contained the indicator strain and plasmid (pRL1J) used as positive strain (Danino et al., 2003).

The plates were incubated at 37 ̊C for 2 days after overlay. Purple color inhibition zone around

the bacterial colony indicated positive results.

2.2.2.2 Nitrogenase activity

For nitrogenase activity, the prepared media contained Malic acid 0.5 g/l, K2HPO4 0.5

g/l, KOH 4 g/l, FeSO4.7H2O 0.5 g/l, MgSO4. 7H2O 0.2 g/l, NaCl 0.1 g/l, CaCl2 0.02 g/l,

Na2MoO4.2H2O 0.002 g/l, alcoholic bromothymole blue 2 ml and pH set at 7-7.2 before adding

Agar 2%. A single pure bacterial culture was streaked on nitrogen-free semisolid malate (NFb)

medium (Döbereiner et al., 1976) containing Bromothymole as a pH indicator and incubated at

30 ± 2 °C for 24 hours. A clear blue zone indicated the presence of nitrogenase activity.

2.2.2.3 Indole production and Catalase test

Indole production was checked using peptone water (Appendix O) and Kovac’s reagent

(Eaton et al., 2005). This test determines the ability of micro-organisms to degrade the amino

acid tryptophan and convert it into indole pyruvic acid and ammonia. For indole production

autoclaved peptone water was inoculated with isolate and incubated at 28 ̊C after 24 hours of

growth. The presence of indole was detected by adding 2-3 drops of Kovac’s reagent. Production

of pink to cherry red layer indicated the presence of Indole. A drop of H2O2 was poured on to a

sterilized glass slide. Single colony of each bacterial isolate was taken by a sterilized wooden

applicator and put on to the H2O2 drop. Immediate production of bubbles indicated the catalase

activity. The presence of bio-surfactants (lipopeptides) and siderophores production were tested



by the drop collapse technique as described by Jain et al. (1991) and Loper and Buyer (1991)

respectively.

2.3 Molecular characterization of phosphate solubilizing bacteria

2.3.1 Genomic DNA isolation

Genomic DNA of isolates was extracted by the CTAB method (Ausubel et al., 2002).

The pure strain cultures (1.5 ml each) with sufficient growth were harvested through

centrifugation at 13000 rpm for 5 min and the pellet was isolated. The pellet was suspended in

576μl 1X TE buffer (Appendix I) and vortexes to dissolve. A volume of 30 μl SDS (10%) and 3

µl proteinase-K was added and mixed thoroughly and incubated at 37 ̊C for 60 min. After

incubation added 80 µl CTAB and 100 µl 5M NaCl and mixed thoroughly and again incubated at

67 ̊C for 30 mins. The Chloroform: Isoamyl-alcohol (24:1) were added and centrifuged at 13000

rpm for 5 min. Aqueous layer was taken in a new tube. An equal volume of Phenol: Chloroform:

Isoamylalcohol (25:24:1) was added, centrifuged at 13000 rpm for 5 min again. Aqueous layer

was taken, added 1 ml of pure ethanol and stored at -80 ̊C for 30 min and centrifuged at 13000

rpm for 10 min. The supernatant was discarded, the pellet was air dried and re-suspended in 20

μl 1X TE buffer. A 2 μl RNase (10 mg ml-1) was added and the tubes were incubated at 37 ̊C in

water bath for 30 min. After incubation 30 µl 1X TE and 150 µl chilled ethanol were added and

mixed gently by inverting the tube several times. Centrifuged at 13000 rpm for 10 min and the

supernatant were discarded and the pellet was air-dried completely before dissolving in 50 µl of

TE buffer.

2.3.2 Molecular identification by 16S rRNA and Multilocus Sequence Analysis (MLSA)

The strains were identified using 16S rRNA and the housekeeping genes (rpoB, rpoD and

recA). Universal primers P1 (forward primer) and P6 (reverse primer) were used for 16S RNA

gene amplification (Tan et al., 1997). The forward primer corresponded to E. coli positions 8-37

and 1479-1506 for reverse primer to amplify 1500 bp fragment. The primers sequences are listed

in Table 2.1. The Taq DNA polymerase and Q-solution were purchased from Qiagen (Venlo,

The Netherlands) and polymerase chain reaction was carried out with an initial denaturation at

94 oC for 2 min, followed by 30 cycles of denaturation at 94 oC for 1 min, annealing at 54 oC for

1 min and extension at 72 oC for 1 min for 16S rRNA gene amplification.



Colony PCR was carried out for MLSA genes (Perneel et al., 2007) as mentioned in

Table 2.2. The 16S rRNA and MLSA amplified PCR products were resolved on 2% agarose gel

in 1X TBE (Tris-borate-EDTA) buffer containing ethidium bromide (20 ug/ml). A 1 kb DNA

ladder (Fermentas) was used as a size marker. The gel was visualized under UV light and

photographed using gel documentation system (BioRad).

Table 2.1: The primer sequences used for 16S rRNA and housekeeping loci of bacterial

isolates

Primer Name Sequences (5′→3′) Anneal

ing

(Temp)

Expected

Product References

16S rRNA P1-F AGAGTTTGATCCTGGTCAGAACGAACGCT 550C 1500bp Tan et al.,

1997 16S rRNA P6-R TACGGCTACCTTGTTACGACTTCACCCC

recA-F TGGCTGCGGCCCTGGGTCAGATC 580C 540bp Frapolli et

al., 2007 recA-R ACCAGGCAGTTGGCGTTCTTGAT

rpoB-F CAGTTCATGGACCAGAACAACCCGCT 540C 508bp Frapolli et

al., 2007 rpoB-R CCCATCAACGCACGGTTGGCGTC

rpoD-F ACTTCCCTGGCACGGTTGACCA 580C 695bp Frapolli et

al., 2007 rpoD-R TCGACATGCGACGGTTGATGTC

Table 2.2: PCR profile for housekeeping gene (MLSA)

STEPS

TEMPERATURE ºC

TIME

Initial denaturation 94.0 10 minutes

Denaturation 94.0 30 sec

Annealing 54.0 for rpoB, 58.0 for rpoD

and RecA 30 sec

Extension 72.0 30 sec

Go to step 2; 30 cycles

Final extension 72.0 10 minutes

Incubation 4.0 10 minutes

2.3.3 16S rRNA and MLSA gene sequencing and analysis

Amplified PCR products (with double primers and without cloning) of the selected

strains were sequenced by Sanger dideoxy-sequencing using commercial service of

MACROGEN (http://dna.macrogen.com/eng/ Seoul, Korea) and LGC genomics GmbH (England)

branch (http://www.lgcgroup.com/our-science/genomics-solutions/dna-sequencing/sanger/

Germany). The strains were identified using the sequence of 16S rRNA gene on Ez-Taxon

http://dna.macrogen.com/eng/

http://www.lgcgroup.com/our-science/genomics-solutions/dna-sequencing/sanger/



Server (http://eztaxon-e.ezbiocloud.net) and BLAST search on NCBI servers

(http://www.ncbi.nlm.nih.gov/blast/Blast.cgi). The sequences alignment and editing was

performed using CLUSTAL X (version 1.8msw) (Sturz et al., 1997) and the BioEdit (Hall 1999)

software package. The phylogenetic analyses were performed as described previously (Roohi et

al., 2012) using neighbor joining (NJ) algorithms by MEGA version 5.10 program (Tamura et

al., 2011). The reliability of clustering was assessed by bootstrap analysis (Felsenstein, 2005)

using 1000 iterations and the tree topology was obtained using neighbor-joining method.

The best characterized and reliably identified strains by 16S rRNA gene and a subset of

the MLSA genes were then assigned to their respective hosts to assess their natural association.

The 16S rRNA identified strains sequences were submitted to Genbank of National Centre of

Biotechnology Information (NCBI). The CMR12a strain was previously characterized as P.

fluorescens (Perneel et al., 2007) provided by the Laboratory of Phytopathology, Ghent, Belgium

and was used as reference strain in initial screening and candidate strain for rest of pqq and gdh

analysis along other Pseudomonas strains.

2.4 Identification of gdh and pqq genes by PCR amplification

2.4.1 Amplification of gdh gene

Three set of primers were used to amplify the gdh gene encoding the glucose

dehydrogenase. The first primer set (gcd Fp-Rp-Entero) was designed based on the sequence

information of Enterobacter cloacae (Accession: NC_014121.1) gdh gene. The second pair of

oligonucleotides (PorinB-F & gdh-R- PF) were designed from genome sequences of

Pseudomonas protegens CHA0 (Accession: CP003190.1) for Pseudomonas strain CMR12a,

QAU67 and the third pair (gdh-F & gdh-R- PP) from P. putida KT2440 (Accession:

AE015451.1) for the strains QAU90 and QAU92. The primer sequences are listed in Table 2.3.

Polymerase chain reaction was carried out in a total volume of 50 μl using Phusion high-fidelity

DNA polymerase (Thermo-scientific, USA). The PCR mixture consisted of: H2O: 33.5 μl; 5X

Phusion HF Buffer: 10μl; 10 mM dNTP mix: 1μl; P1: 2.5μl; P2:2.5μl; Phusion HF polymerase

0.5μl. The PCR conditions have been described in Table 2.4.



Table 2.3: primer list for pqq and gdh amplification

Primer Name Sequences (5′→3′) Anne

aling

Product

size

References

PqqAB-F TGTGGACCAAACCTGCATACACTG 550C 924bp This study

PqqAB-R GATGCTCATGCCATCGAA

pqqBCD-F TTCAAGATGCTCAGCCACTG 540C 2000bp This study

pqqBCD-R CGATCTTGTCGATGTTGTGC

PqqE-F GATCGTCCTCGCCTGAGTT 580C 1000kb This study

PqqE-R GATGACACGGGAGTTTCGAT

PqqF-F CCAACTTACCCTCGCCAAT 600C 2033bp This study

PqqF-R CAGCGTTGGCCAAACATAG

gdh-Fp (Entero) CCCGAATTCGGCGTGATCCGTGGTT 540C 1400bp This study

gdh-Rp (Entero) ATGCGTCGACTAGTCGCCCATCTT

PorinB-F (PF) AACCTGCAGTACATCCGCCA 550C 2000bp This study

gdh-R (PF) ACGTACTGCTTGCCGTCCTT

gdh-F (PP) AAGGCCACCGACGTCTATAA 550C 2033bp This study

gdh-R (PP) GATGACGCTTCCTTGGTGT

Table 2.4: The gdh gene amplification profile

STEPS

TEMPERATURE ºC

TIME

Initial denaturation 98.0 30 sec


Annealing 54.0 (Enterobacter) &

55.0 (Pseudomonas) 30 sec





2.4.2 Amplification of pqq operon (pqqABCDEF)

The PCR amplification of pqq genes were carried out with newly designed

oligonucleotides (Table 2.4) using sequence information of Pseudomonas protegens CHA0

(Accession: CP003190.1). Polymerase chain reaction was carried out in a total volume of 50μl

using Go®Taq DNA polymerase (Promega, USA). The PCR mixture consisted of following

components: 33μl H2O; 10μl Master Amp GoTaq® 5X PCR Buffer; 1μl dNTP mix; P1: 10pm;

P2: 10pm; 0.25μl GoTaq® polymerase and then colony PCR was carried out (Table 2.5). The

gdh and pqq genes amplified PCR products were resolved on 2% agarose gel in 1X TBE



(Trisborate-EDTA) buffer (Appendix I) containing ethidium bromide (20 ug/ml). A 1 kb DNA

ladder (Fermentas) was used as a size marker. The gel was visualized under UV and

photographed using gel documentation system (BioRad).

Table 2.5: pqq genes amplification profile

STEPS

TEMPERATURE ºC

TIME

Initial denaturation 95.0 5 minutes


Annealing pqqAB at 55°C

pqqBCD at 54°C

pqqE at 58°C

pqqF1 at 60°C

30 sec





Amplified PCR products of pqq and gdh genes without cloning (double primers) were

sequenced by Sanger dideoxy- sequencing using commercial service of MACROGEN

(http://dna.macrogen.com/eng/ Seoul, Korea) and LGC Genomics (Germany). The cluster analysis

was performed as previously described in section 2.3.3.

2.5 Bioinformatics based structural characterization of GDH protein

2.5.1 Sequence identity and physico-chemical properties of GDH

ExPASy translated program (http://web.expasy.org/translate/) and ORF (Open Reading

Frame) finder tool of NCBI were used to translate the nucleotide sequences into respective

amino acid according to the standard genetic code. Then protein Blast (BlastP) was used to find

the sequences identity with previously reported sequences in NCBI databases and ClustalW2 tool

for multiple sequence alignment (MSA) of protein sequences.

The physico-chemical properties of GDH were calculated using the bioinformatics tools:

Emboss Pepstats (Harrison, 2000) was used to calculate the average residue weight, molecular

weight, isoelectric point and charge. ProtParam (Gasteiger et al., 2005) was used to compute

amino acid composition, molecular weight, atomic composition estimated half-life and instability

index. Whereas, Pepwindow (Kyte and Doolittle, 1982) was used to draw a hydropathy plot

http://dna.macrogen.com/eng/

http://web.expasy.org/translate/



which is valuable in determining the distribution of polar and apolar residues of GDH protein

sequence.

2.5.2 Structural Analysis of GDH Protein

2.5.2.1 Prediction of secondary structure

PSIPRED v3.3 and CSSFP (Buchan et al., 2013) are the online accessible server based

tools (http://bioinf.cs.ucl.ac.uk/psipred/) used to predict the secondary structure of GDH protein.

These tools were also used to predict and assess the percentage composition of α-helix, β-strands

and coils of GDH proteins.

2.5.2.2 Three-dimensional (3D) modeling

The protein 3D structure (PDB file) and ligand binding sites were predicted using

COACH, a meta-server (http://zhanglab.ccmb.med.umich.edu/COACH/). The output files were

then viewed on ‘Jmol’ an open source Java viewer with features for biomolecules, chemicals

materials and 3D crystals structure.

2.5.2.3 Homology Modeling based on 3D structure

The iterative threading assembly refinement (I-TASSER) server was used to generate

high quality three-dimensional (3D) models for GDH (Zhang 2008) based on multiple-threading

alignments and the structural assembly simulations of amino acid sequences. The GDH model

was compared with an already available homology model in the protein database for ligand

binding, active site and function residue binding sites. All predictions of homology modeling

depend on the confidence score (C-score) with PDB protein ID. For instance, the C-score is the

confidence score for the predicted binding site in the model and it value ranges between 0 and 1,

where a higher score indicates a more reliable prediction and TM-score is the structural

alignment between the query structure and known structures in the PDB library and predicts the

ranking of proteins.

2.5.2.4 Ligand binding prediction

COACH server was also used to generate the complementary ligand binding site

predictions using two comparative methods, S-SITE and TM-SITE, which identify the ligand-

http://zhanglab.ccmb.med.umich.edu/COACH/



binding templates from protein function database (BioLiP) using sequence profile comparisons

and binding-specific substructure. These predictions of the GDH protein and the mutual results

from methods like: FINDSITE, COFACTOR and ConCavity were compared to illustrate the

final PQQ ligand binding site predictions.

2.5.3 Functional Analysis of GDH Protein

2.5.3.1 Annotations of Functional residues

The FFPRED tool of PSIPRED server (http://bioinf.cs.ucl.ac.uk/psipred/) was used for

schematic presentation of secondary structure of Glucose dehydrogenase (GDH) of strains and

position dependent features of phosphorylation. The line height of the Phosphorylation features

reflects the confidence of the residue prediction. MEMSAT3 and MEMSAT-SVM tools of

PSIPRED were used for helix prediction, Pore lining residue, Signal peptide residue and Re-

entrant helix residue. MEMPACK cartoons predicted the interaction of transmembrane helix or

helices of GDH protein and helix was oriented to maximize number of residues with predicted

interactions.

2.5.3.2 Functional Prediction through I-TASSER server

The I-TASSER server (http://zhanglab.ccmb.med.umich.edu/I-TASSER/) was used for

function prediction of GDH which generates information on the sequence-to-structure-to-

function paradigm. The function prediction of the GDH protein was based on the local and

global structural resemblance of the 3D models of known protein structures of protein database

(PDB). An estimate of accuracy of the prediction is provided as the confidence score of the

modeling (Roy et al., 2010). This method was used for the biological functions including

Enzyme Commission (EC) numbers, Gene Ontology (GO) terms and ligand-binding sites of

protein targets.

2.5.3.3 Structural based function annotations

It is a structure based method for the prediction of biological function of the GDH protein

molecules. COFACTOR threads the 3D structure through three inclusive function libraries using

local and global structure matches to predict the homologies and functional sites of GDH. The

biological and functional insights of predicted model were done by matching with protein

http://bioinf.cs.ucl.ac.uk/psipred/

http://zhanglab.ccmb.med.umich.edu/I-TASSER/



function database. The structure based functions like gene ontology terms, ligand binding sites

and enzyme classification of GDH proteins were determined by COFACTOR program (Roy et

al. 2012).

2.5.3.4 Functional domain prediction

Functional sites or domains of GDH protein, occurrence in the sequence, domain length

and family of GDH proteins were determined with the help of InterProScan tool (Quevillon et

al. 2005) and Pfam domain tool (http://pfam.xfam.org/). These tools provided the alignments and

hidden Markov models for protein domains. Further, GPS 2.1 DOG programme (Ren et al. 2009)

was used for the construction of GDH protein domains, functional peptides, active site and the

PQQ ligand binding sites of GDH protein.

2.5.3.5 Gene Ontology (GO)

The GO tool (http://geneontology.org/) was used to develop the structurally controlled

vocabularies (ontologies) of gene products in relation to their cellular components, biological

processes and molecular functions in a species-independent way. The exact vocabularies are

structured that allows annotators to allocate properties to gene products at different ranks

depending upon the depth of knowledge.

2.6. The gdh mutagenesis (Tn5) and its implicaions

The E. coli WM3064 vector with Pfaj-1518 plasmid (Figure 2.2) was cultured in 5 ml LB

broth with 10 ppm DAP (10ul/ml) and kanamycin (50ppm). The wild strains (CMR12a, QAU67,

QAU90 and QAU92) were cultured in LB and incubated at 28 0C overnight for conjugation.

2.6.1 Conjugation

1 ml sample from the overnight culture of E. coli WM3064 (+Pfaj-1518) was centrifuged

at 14000 rpm for 5 minutes, the supernatant was discarded, and a 500 ul overnight culture of

wild strain was added. The conjugated culture of two strains was mixed by pipetting and poured

onto LB+DAP agar plate, when culture got dried, it was incubated overnight at 280C. The

overnight culture was collected from plates by loop and placed into the 1 ml LB (broth). After

mixing the culture, a dilution (100-10-7) of this conjugated culture was made in LB or saline

http://pfam.xfam.org/

http://geneontology.org/



solution. 100 ul of each conjugated culture was plated on to LB+Km (50 ppm) and incubated at

280C. The growth of colonies was checked after incubation corresponding to the dilution factor

(QAU90 grew well at 10-1) and replica plating was done.

2.6.1.1 Tn5 Mutant characterization

All colonies were checked for their ability to solubilize the inorganic phosphate on

Pikoviskay medium and QAU90 strain with its mutant was further checked for their role in plant

growth promotion using bean plants as host. Plant parameters assessed were: plant height, root

length, fresh weight (shoot × root) and leaf area (length × width) with observations made on an

average of 10 plants from three replicate experiments.

Figure 2.2: mTn5gfp–pgusA contains a promoterless gfp gene and a constitutively expressed

gusA gene. The remaining mini-Tn5 elements carry a promoterless gusA gene and a

constitutively expressed gfp gene. The 5`end of the DNA sequence of the promoterless gfp and

gusA cassettes is shown above the mTn5gfp–pgusA and mTn5gusA–pgfp elements.

Translational stops in the three reading frames are indicated by asterisks (*). The ribosome-

binding site is underlined and the KpnI site is italicized; letters written beneath the DNA

sequence represent the amino-terminal amino-acids of GFP and GusA (Chuanwu et al., 1999).



2.6.2 Knock out site directed PCR based deletion mutation

2.6.2.1 Designing of primers

To make PQQ deletion mutants, specific primers were designed specific to pqqC locus

from already available genome sequences of Pseudomonas protegens CHA0 (Accession:

CP003190.1) on NCBI Genbank. Within the PQQ operon, pqqC locus was selected and mutated

because it is reported as conserved and a pivotal gene in PQQ biosynthesis. The sequences of

primers named as: pqqC-UP-F/R (upstream sequence of pqqC) and pqqC-DOWN-F/R

(downstream sequences of pqqC) (with recombination sites for the plasmid) for pqq gene shown

in Table 2.6.

Table 2.6: The primers used for PCR based deletion mutation

Primer

Name

Sequences (5′→3′) Product

size

Reference

pqqC-Up-F GGAATTGTGAGCGGATAACAATTTCACACAG

GAAACAGCTGTTCAAGATGCTCAGCCACTG

1000bp This study

pqqC-Up-R CAGTTCATAGGCCATGCTCAATGGGGATGTT

CACCTGGTA

pqqC-

Down-F

TACCAGGTGAACATCCCCATTGAGCATGGCC

TATGAACTG

1000bp This study

pqqC-

Down-R

CCAGGCAAATTCTGTTTTATCAGACCGCTTCT

GCGTTCTGATCGATCTTGTCGATGTTGTGC

pqqC-F TTCAAGATGCTCAGCCACTG 2200bp This study

pqqC-R CGATCTTGTCGATGTTGTGC

2.6.2.2 PCR amplification for mutation

Knock out mutation dependent on the amplification of desired deleted region of PQQ

operon (pqqC). Polymerase chain reaction was carried out in total volume of 50 μl in 1.5 ml

microfuge tubes by using Go®Taq DNA polymerase (Promega, USA). The PCR mixture

consisted of following components H2O: 33.75 μl; Master Amp GoTaq® 5X PCR Buffer: 10μl;

dNTP mix: 1μl; P1: 2.5μl; P2:2.5μl; GoTaq® polymerase 0.25μl. The colony PCR was carried

out as mentioned in Table 2.5. The concentrations of the two PCR-products (UP and DOWN)

were determined by spectrophotometry (Multiskan EX, Thermo Labsystems).



2.6.2.3 Restriction digestion of Plasmid pMQ30

The plasmid pMQ30 (Figure 2.3) was purified by miniprep kit (Promega) and digested

with EcoRI and BamHI restriction enzymes as following in 20 µl reaction, 5 µl plasmid pMQ30

(purified with miniprep), 4 µl buffer Tango Yellow (2x), 0.5 µl EcoRI, 1 µl BamHI (2-fold

excess), 9.5 µl milliQ. The reaction mixture incubated for 2 h at 37°C for complete digestion,

checked 5 µl on agarose gel (without heat inactivation) and then determined the concentration of

digests (150ng/µl).

2.6.2.4 In vivo cloning and transformation

The yeast Saccharomyces cerevisiae InvSc was cultured overnight in yeast peptone

dextrose (YPD) medium (Appendix P-I) at 30°C and 0.5 ml of this culture was centrifuged at

14000 rpm for 1 min, the supernatant was discarded and cells were washed with 0.5 ml sterile

TE buffer at 14000 rpm for 1 min. The pellet was dissolved in 0.5 ml Lazy Bones Solution. The

20 µl carrier DNA (2 mg/ml – single stranded) boiled for 10 min in boiling water and

immediately placed on ice, was mixed with 5 µl digested plasmid pMQ30, and 45 µl PCR

product each of UP and DOWN primers. The mixture was gently agitated for 1 minute and

incubated at room temperature overnight.

After overnight incubation, the mixture was warmed at 42°C for 12 minutes and then

centrifuged at 3000rpm for 1 minute. The supernatant was discarded and the cells were washed

with 0.6 ml TE-buffer (PEG inhibits growth). The pellet was re-suspended in 0.6 ml TE. Plate

everything on SD-uracil- selective medium (2 x 50 µl, 2 x 100 µl and 2 x 150 µl) and incubated

at 30°C, for 3 to 4 days. S. cerevisiae InvSc can only grow on this medium when it contains

plasmid pMQ30. Once the yeast colonies were obtained, these were picked over on new plate

SD-URA, and grown in 6 ml liquid SD-URA. 2 ml of this culture was used for the preservation

purpose in 40% glycerol at -80°C.



Figure 2.3: Yeast-based allelic exchange vector maps used for pqqC mutation are shown the

oriT, origin of conjugal transfer; sacB, Bacillus subtilis levansucrase gene for counter selection;

T1T2, E. coli rrnB transcriptional terminators; ColE1, high-copy-number variants of the narrow-

host-range ColE1 origin of replication; URA3, orotidine-5-phosphate decarboxylase gene from

S. cerevisiae; lacZα, lacZα with multi cloning site driven by the lactose promoter; aacC1,

gentamicin resistance determinant from Tn1696; p15a, narrow-host-range, low-copy origin of

replication and CEN/ARSH, low-copy yeast replication and segregation machinery.



2.6.2.5 Plasmid extraction

Plasmid (pMQ30) was extracted by Lars Dietrich Protocol for miniprep (Fermentas) and

4 ml of SD-URA culture was used for this purpose. During the extraction, vortex step was

crucial, therefore done manually (for 5 minutes) and a homogenizer machine may also be used.

The extracted plasmid was eluted with 25 µl milliQ and rechecked on agrose gel.

2.6.2.6 Electroporation

Electroporation was performed using MicroPulser ™ (Bio-Rad) by transferring the 8 µl

plasmid in E. coli WM3064 competent cells, mixed with dropper on ice and placed in the

electroporator. After electroporation, one ml LB (broth) was incubated at 37°C while on shaker

for 2 h. These were then spread gently on LB + DAP + Gm20 and incubated at 37°C for 2 days

and further assessed through colony PCR.

2.6.2.7 Conjugation or biparental mating (1st cross over)

E. coli WM3064 containing pMQ30 deletion construct was cultured in LB (DAP + Gm-

20) along with wild type strain (CMR12a, QAU67, QAU90 and QAU92) in LB broth at 28°C

overnight. It was then centrifuged 1 ml of pMQ30 deletion construct overnight culture,

supernatant was discarded and 250 ml of wild type strain culture was added and mixed by

pipetting and then spot on LB+DAP plate. The pMQ30 deletion constructs culture also preserved

in 40% glycerol and checked by colony PCR.

2.6.2.8 Selection and Merodiploid

All colonies from the overnight LB (DAP + Gm-20) cultures were collected using a loop

into 1 ml LB (broth) and used for making serial dilutions (10-1 to 10-5). Take 100 ul from each

dilution and spread on LB (+ Gm25-100) along with 100 ul on LB (broth) as control and E. coli

WM3064 did not grow without DAP. Colonies growing on gentamycin (Gm) were called

merodiploids because they contained complete plasmid in their genome after 1st cross over. This

was confirmed with F+R primer by colony PCR and picked a good colony and streak it out on

LB + Gm, to get single colonies.



2.6.2.9 Mutants selection (2nd cross over)

The merodiploids colony (one colony from the plate) was grown overnight in LB without

antibiotics, 1 out of 1000 cells loosed the plasmid by the second cross-over, that gave the

deletion mutant. A dilution series of the overnight LB culture was made and as a control plated

100 µl of dilutions 10-3 until 10-7 on LB. For second-crossovers plated 100 µl of dilutions 10-1

until 10-5 on LB + 10% sucrose without NaCl. The Colonies that were grow on sucrose, lost the

plasmid (and so sacB and the GmR-gene). SacB causes polymerization of sucrose inside the

cells, causing a lot of water to come inside the cell making the cell collapse. That’s why no NaCl

may be inside the medium, because then there could be an osmotic equilibrium between cells and

the medium.

2.6.2.10 Mutant confirmation

The colony PCR was carried out on 10 µl of suspension in a total volume of 30 µl PCR.

E. coli strain with the plasmid was used as positive control and a wild type colony as a negative

control. Replica test was carried with the colonies growing on sucrose and streaked onto LB +

Gm (25-100 ppm) along with LB and the lack of growth on LB + Gm medium was taken as an

indication of mutation. Such Gm-sensitive colonies were then purified.

2.6.3 Characterization of pqqC mutants

The pqq mutants were confirmed by phosphate solubilization test, acid production test

and characterized by API 20E (BioMerieux) kit, utilization of carbon, nitrogen sources,

antioxidant activity, effect on plant growth promotion and plant disease control.

2.6.3.1 Screening of pqqC mutants for phosphate solubilization

Phosphate solubilization activity of wild type (P. fluorescens CMR12a, P. fluorescens

QAU67, P. putida QAU90 and Pseudomonas sp. QAU92) and pqqC mutant (P. fluorescens

CMR12a-3, P. fluorescens QAU67-14, P. putida QAU90-4 and Pseudomonas sp. QAU92-2)

strains were determined on Pikovskaya (1948) medium culture plates as described in section 2.2.



2.6.3.2 Effects on acidification of medium

The experiment was carried out into 250ml Erlenmeyer flask and 100ml of Pikovskaya’s

broth medium as described in section 2.2.2 for wild type (P. fluorescens CMR12a, P. fluorescens

QAU67, P. putida QAU90 and Pseudomonas sp. QAU92) and pqqC mutant (P. fluorescens

CMR12a-3, P. fluorescens QAU67-14, P. putida QAU90-4 and Pseudomonas sp. QAU92-2).

2.6.3.3 The pqqC mutant characterization by API-20E kit

The PQQ mutants were characterized by API-20E kit (Bio Merieux, USA) for utilization

of carbon and nitrogen source and role in regulation of enzymatic activity involved in oxidation-

reduction and fermentation process. This kit embedded with 20 biochemical tests to evaluate the

difference between wild type and mutant strains.

2.6.3.4 Carbon source utilization test

The carbon source utilization test was designed to identify the enzyme that PQQ served

as cofactor by the wild type and mutant strains. For this purpose, 1% of each eight carbon source

(Glucose, Acetate, Na-citrate, Na-succinate, manitol, glycerol, ethanol and methanol) was used

with the M-9 nutritional media (Appendix P-II) for an overnight growth of all strains with a

concentration of 106 colony forming unit (CFU). After 24 hours of growth the M9 media were

sampled for the observation of OD at 620nm. The mixtures were processed in 96 well plates in

12 replicate for OD. The difference in utilization of carbon source by wild and mutant strains

was recorded.

2.6.3.5 Antioxidant activity

2.6.3.5.1 DPPH radical scavenging activity

The DPPH assay was carried out as described in Gyamfi et al. (1999) with some

modifications and PQQGDH enzyme was extracted as describe by Geiger and Gorisch (1987).

The stock solution was prepared by dissolving 24 mg DPPH with 100 ml methanol and working

solution was obtained by diluting DPPH with methanol to obtain an absorbance of about 0.980

(± 0.02) at 517 nm using the spectrophotometer. A 3 ml aliquot of this solution was mixed with

100 µl of the samples at varying concentrations (25-250 µg/ml). The solution in the test tubes



were shaken well and incubated in the dark for 15 min at room temperature. Then the absorbance

was taken at 517 nm. The scavenging activity was estimated based on the percentage of DPPH

radical scavenged as the following equation:

Scavenging effect (%) = [(control absorbance-sample absorbance) / (control absorbance)] ×100.

EC50 value was taken as the effective concentration to scavenge 50% of the DPPH radicals.

Ascorbic acid and rutin standard were used as positive references. Each fraction was assayed in

triplicate.

2.6.3.5.2 Reducing power

The reducing power of the extracts was determined according to the method described by

Chung et al. (2005). The 0.1 ml of each extract, ascorbic acid, rutin or gallic acid (0.05–250

mg/ml) were mixed with an equal volume of 0.2 M phosphate buffer (pH 6.6) and 1% potassium

ferricyanide then incubated at 50°C for 20 min. The 0.25 ml of 1% trichloroacetic acid was

added to the mixture to stop the reaction and the mixture was centrifuged at 2790g for 10 min.

The supernatant (0.25 ml) was mixed with 0.25 ml distilled water and 0.1% FeCl3 (0.5 ml) and

the absorbance was measured at 700 nm.

2.7 PQQ’s role in plant growth promotion

Four plants i-e lettuce (Lactuca sativa), tomato (Solanum lycopersicum), rice (Oryza

sativa) C-039 and bean (Phaseolus vulgaris) ‘Prelude’ (Het Vlaams Zaadhuis, Waarschoot,

Belgium) were used to check the role of PQQ in plant growth promotion.

2.7.1 Lettuce

Lettuce seeds were pre-germinated in Murashige and Skoog (MS) medium (Appendix N)

for three days at 220C before bacterial inoculation. After taking OD620 of overnight LB culture

of all strains in three replicates (106 CFU) in saline solution and dipped pre-germinated 10 seeds

in each strain culture for 10 minutes. Then seeds was placed in MS agar plates in three replicates

for each strain with control and incubated in growth chamber for one week. The data of root

length of all plants was recorded after one week.



2.7.2 Bean

In vivo plant experiments were carried out using seeds of Phaseolus vulgaris ‘Prelude’

(Het Vlaams Zaadhuis, Waarschoot, Belgium). To reduce the variability in emergence, seeds

were pregerminated before sowing. Seeds were surface sterilized in 1% sodium hypochlorite

solution for 5 minutes, rinsed thrice in sterile distilled water and after air drying, 25 seeds were

sown into each petri dish having soaked filter papers for germination at 28oC.

Bacterial strains were grown on KB plates for 48 h at 28oC. Bacterial suspensions were

collected from plates after adding sterile saline solution. OD of these bacterial suspensions was

determined at 620 nm. The suspensions were diluted using saline solution to 2800 g x 106 CFU

per 200 ml. These dilutions served as bacterial inoculum for the plant experiment. After 3 days,

germinated seed were sown in four perforated plastic trays (22 by 15 by 6 cm) filled with 700 g

of a soil mixture composed of 50% sand and 50% non-sterile potting soil (wt/wt) (Structural;

Snebbout, Kaprijke, Belgium). 200 ml diluted bacterial suspension were mixed thoroughly with

2.8 kg of soil for 2 min to get a final concentration of 106 CFU kg-1 soil. Thus there were four

replicates for each treatment.

Soil mixed with 200 ml saline solution served as positive controls. Ten pre-germinated

bean seeds were sown in each box and all plants were incubated in a growth chamber (28oC,

relative humidity of 70%, 16 h photoperiod). The plants were irrigated daily to maintain soil

moisture. A completely randomized design was employed with four replications per treatment.

Data was recorded on growth parameters (viz. plant root, shoot length and weight, leaf area

index and total number of leaves) on five plants which were randomly uprooted from each plot

after 15 days of growth.

2.7.2.1 Data analysis

The data were recorded on growth parameters (viz. plant root, shoot length and weight,

leave area index, dry weight and total number of leafs) on 10 plants from 3 replicates and

analysed with software package SPSS 15.0 for Windows (SPSS Inc., Chicago). The

nonparametric data were analysed using Kruskal-Wallis and Mann-Whitney comparisons (α =

0.05). The data are presented as box plots.



2.8 Tagging of bacterial strains by Tn7-gfp mutation

The E. coli WM3064 vector with gfp labeling plasmid (Figure 2.4) was cultured in 5 ml

LB broth with 10 ppm DAP (10ul/ml) + gentamycin (25 ppm). The wild strains (CMR12a and

QAU92) were cultured in LB and incubated at 280C overnight for conjugation.

Figure 2.4: Map of Tn7 element of delivery plasmids which can be used for gfp-tagging of

strains (A) pBK-miniTn7-gfp2, pUC19-based delivery plasmid for miniTn7-gfp2. GmR, CmR,

ApR, mob., Tn7L and Tn7R, the 166-bp left and 199-bp right ends of Tn7 (Koch et al., 2001) and

(B) the helper plasmid (pUX-BF13), pUX-BFI3 was constructed by moving the 9.0-kb EcoRI

fragment of pCW4 (McKown et al., 1987) into the EcoRI site of pGP704 (Mekalanos, personal

communication), an R6K-repIicon-based plasmid lacking the pir gene and with an RP4-derived

mob site, MCS, multiple cloning site.

2.8.1 Conjugation

The 1 ml overnight culture of E. coli WM3064 (gfp plasmid) was centrifuged at 14000

rpm for 5 minutes, discard the supernatant, add 500 ul overnight culture of wild strain. The

conjugated culture of both strains was mixed by pipetting and poured onto LB+ DAP agar plate,

when culture got dried it was incubated overnight at 280C. The overnight culture was collected

from plates by loop and put onto 1 ml LB (broth). After mixing the culture, serial dilutions (100-

10-7) were made in saline solution. 100 ul of each conjugated culture was plated on LB+Gm (25

ppm) and incubated at 280C. The growth of colonies was checked corresponding to dilution

factor and QAU92 grew well at 10-2.

Tn7R

Tn7L

PstI

GmR

T0

CmR

SacII

Kpn

NotI

ApaI

Ml

MluI

AflII A

pBK-miniTn7-gfp2



2.8.2 Pseudomonads in root colonization of Lettuce

When the Tn7-gfp mutation was done, the mutant colonies were confirmed through

fluorescent microscopy. The wild type (P. fluorescens CMR12a and Pseudomonas sp. QAU92)

and two pqqC mutant (P. fluorescens CMR12a-3 and Pseudomonas sp. QAU92-2) strains were

used for Tn7-gfp tagging with roots of lettuce.

Lettuce seeds were pre-germinated in MS medium for three days at 220C before bacterial

inoculation and then take OD at 620nm of all strains in saline solution for 106 CFU. Then ten

seeds were soaked in each strain culture for 10 minutes and grown on MS agar plates in three

replicates and incubated in growth chamber for one week. The data on root length of all plants

were taken after one week. The gfp Tn7 insertion labeling mutants were used for root

colonization. Bacterial colonies showing the fluorescent characteristics of Pseudomonas under

fluorescent microscope were counted after an incubation period of 36-48 h at 280C.

2.9 Role of PQQ in plant disease control

2.9.1 In vitro antagonistic activity against phytopathogenic fungi

The P. fluorescens CMR12a, P. putida QAU90 and Pseudomonas sp. QAU92 were

tested for in vitro antagonism against three fungal pathogens (Rhizoctonia solani, Fusarium

solani and Pythium sp.) using standard co-inoculation technique on potato dextrose agar (PDA)

medium (Appendix P-III) (Sakthivel and Gnanamanickain, 1987). All bacterial isolates were

streaked at two sides of petri plate with PDA medium and seven day old 9 mm mycelial discs

from PDA culture of all fungi were placed in middle of petri dishes following incubation at

28±2ºC for 7 days in three replicates. Single and dual inoculated cultures of the fungus were set

as controls. The mycelial growth of all test pathogens and width of inhibition zone were recorded

using the formula proposed by Vincent (1927) as follows:

Percent inhibition (I) = C-T/C ×100

Here, C- mycelia growth of pathogen in control and T- mycelia growth of pathogen in dual plate



2.9.1.2 Data analysis

The antagonist data were assessed using the analysis of variance (ANOVA) according to

Steel and Torrie (1980). Computer program software SAS was used for data analysis. Least

significant difference (LSD≤0.05) was used to evaluate the response of each strain against fungi.

2.9.2 In vivo antagonistic activity of pqq mutants against Rhizoctonia solani

The bio-control P. fluorescens CMR12a, P. putida QAU90 and Pseudomonas sp. QAU92

strains and their pqqC mutants were studied in vivo on bean plants to assess their antagonistic

impact on Rhizoctonia solani. The Phaseolus vulgaris ‘Prelude’ (Het Vlaams Zaadhuis) was

used to check the efficiency of pqq mutant Pseudomonas against rhizoctonia root rot. The bean

seeds were surface sterilized using 1% sodium hypochlorite solution for 5 min, rinsed thrice in

sterile distilled water and about 25 seeds were placed on wet filter paper in petri dishes. The

seeds were incubated at 28oC for 3 days before setting up the experiment. Bacteria strains were

grown on KB agar plates for 48 h at 28ºC and bacterial inoculum used as described in section

2.7.2.

2.9.2.2 Fungal inoculum and experimental set-up

Inoculum of R. solani AG 2-2 was produced on water-soaked wheat kernels, which were

autoclaved twice on two consecutive days, as described in Scholten et al. (2001). The plastic

trays containing bean seedlings were inoculated 3 days after sowing by placing a row of 40

infected wheat kernels in the middle of the tray at a depth of approximately 2cm and a distance

of 3cm from the bean seedlings. Seven days after inoculation, disease symptoms were evaluated

according to Nerey et al. (2010). All experiments were carried out in a growth chamber (250C,

16 h photoperiod). Each experiment consisted of four replications per treatment with 10 bean

plants per replication and each time healthy and infected control treatments were included. The

observations on disease severity were made after six days inoculation of R. solani using disease

classes or scores as described by Keijer et al. (1997).

2.9.3 Disease rating of Pseudomonas strains and its pqqC mutants by root colonization

At the time of disease rating, miniTn7-gfp labeled wild type (P. fluorescens CMR12a,

Pseudomonas sp. QAU92) and pqqC mutant strains (P. fluorescens CMR12a-3, Pseudomonas



sp. QAU92-2) were used for the root colonization in bean plants. Roots of five plants were

excised and rinsed under tap water to remove the soil. After weighing, roots were macerated in

sterile saline using a mortar and pestle and serial dilutions were plated on KB agar. Bacterial

colonies showing the fluorescent characteristics of Pseudomonas CMR12a and QAU92 were

counted after an incubation period of 36 to 48 h at 280C. The statistical analysis of disease

control data was performed using the software package SPSS 15.0 for Windows (SPSS Inc.,

Chicago). Neither the ordinal data of the disease severity nor the data of the root colonization

experiments met the conditions of normality and homogeneity of variances, therefore,

nonparametric Kruskal-Wallis and Mann-Whitney comparisons (α = 0.05) were performed.

2.10 PQQ and Induced systemic resistance (ISR) in rice

Induced systemic resistance (ISR) is a well-studied phenomenon by which plants exhibit

increased levels of resistance to a broad spectrum of pathogens in response to root colonization

by plant growth-promoting rhizobacteria. So two experiments i.e. with rice plants and with rice

cell suspension cultures were performed to assessed the role of wild and pqqC mutant strains in

suppressing the rice brown spot disease.

2.10.1 The qPCR analysis of cell cultures treated with Pseudomonas supernatant

The wild type P. fluorescens CMR12a, Pseudomonas sp. QAU92 strain and their pqqC

mutants P. fluorescens CMR12a-3 and Pseudomonas sp. QAU92-2 strains were cultured for 24h

at 28°C on LB plates. Bacteria cultured on solid LB medium were scraped off the plates and

suspended in 10 ml of sterile demineralized water. Then bacterial suspensions were vortexed and

centrifuged for 10 min at 10,000 x g. The supernatant was passed through a 0.22 μm filter and

added to 5-day-old rice cell suspension cultures (1 ml supernatant per 3 ml of cells). Cells were

harvested at 1, 3 and 6 hours post treatment and subjected to RNA extraction analysis as

described in section 2.10.2.4. According to the bacteria growth conditions, either LB broth or

sterile demineralized water was used as control. Following treatment with wild type

Pseudomonas and pqqC mutant strains supernatant, expression of JA marker genes JAMYB and

JiOsPR10 were checked along with the ET-related gene EBP89 and Actin (Os03g071810) used

as an internal reference to normalize the gene expression levels.



2.10.2 Induced resistance bio-assays

Induced resistance bio-assays were performed essentially as described by De

Vleesschauwer et al. (2006). Briefly, plants were grown under growth chamber conditions

(28°C, relative humidity: 60%, 12/12 light regimen) in commercial potting soil (Structural;

Snebbout) on alternate days for 21 min. Rice seeds were surface sterilized with 1% sodium

hypochlorite for 2 min, rinsed thrice with sterile, demineralized water and incubated on wet

sterile filter paper for 5 days in the dark at 28°C to germinate. The bacteria (P. fluorescens

CMR12a, Pseudomonas sp. QAU92 and their pqqC mutants P. fluorescens CMR12a-3 and

Pseudomonas sp. QAU92-2 ) inoculum were thoroughly mixed with the potting soil to a final

density of 5 × 107 cfu g-1, 12 days later, applied a second time as a soil drench. In control

treatment, soil and rice plants were treated with equal volumes of sterilized saline.

2.10.2.2 Pathogen Inoculation

The C. miyabeanus strains Cm988 (brown spot) used for infection trials were grown for

sporulation on potato dextrose agar at 28 oC. Seven-days-old mycelia were spread onto the

medium and exposed to blue light (combination of Philips TLD 18W/08 and Philips TLD

18W/33) for 3 days to induce sporulation. Upon sporulation, conidia were harvested and re-

suspended in 0.5% gelatin (type B from bovine skin; Sigma-Aldrich G-6650) to a final density of

1×104 conidia mL-1. For inoculation, 5-week-old seedlings (6.5-leaf stage) were misted with

conidial suspension (1mL per plant) using an artist airbrush powered by an air compressor.

Immediately after inoculation, plants were moved to a dew chamber (30 oC, with a relative

humidity 92% or more) to facilitate fungal penetration and 18 hrs later transferred to greenhouse

conditions (280C ± 40C, 16-h-light/8-h-dark regime) for disease development.

2.10.2.3 Sample collections

After fungal inoculation, leaf samples of infected, mock and control rice plants were

collected at four time points (i.e.12h, 24h, 36h and 48h after inoculation) in two biological

repeats. For two bacterial inocula P. fluorescens CMR12a, Pseudomonas sp. QAU92 and their

pqqC mutants; P. fluorescens CMR12a-3 and Pseudomonas sp. QAU92-2, a total of 40 samples

for one biological repeat and for four time points were collected, so 80 samples were collected

for two biological repeats for RNA extraction and further RT-PCR expression analyses.



2.10.2.4 RNA extraction from Rice

2.10.2.4 (a) Homogenization

After harvesting, rice leaf tissues were submerged in liquid nitrogen quickly to avoid

possible RNA degradation. The tissues were ground to a fine powder using a mortar and pestle.

RNA yield often depends upon grinding. For best practice, pre-chilled mortars treated with liquid

nitrogen were used and the plant material was kept under frozen conditions throughout. Then 1

ml of TRI reagent was added under the fume hood in a 100 mg of tissue powder and vortex

instantly and vigorously for at least 60 seconds.

2.10.2.4 (b) Phase Separation

The homogenized samples were incubated at room temperature for 5 minutes to permit

complete dissociation of nucleoprotein complexes. Then 0.2 ml of chloroform was added for

each 1 ml of TRI reagent used (in fume hood) and capped securely. Samples were shaken

vigorously for 15 seconds and incubated at room temperature for 2 to 3 minutes, followed by

centrifugation at 12000 x g for 15 minutes at 4 °C. The mixtures were then separated as: a lower

red, phenol-chloroform phase, an interphase and a colorless upper aqueous phase. The RNA

remains exclusively in the aqueous phase. The volume of the aqueous phase was about 60% of

the volume of TRI reagent used for homogenization.

2.10.2.4 (c) RNA Precipitation

The aqueous phase was transferred to a fresh tube, the organic phase here may be used

for isolation of DNA or protein is desired, and mixed with isopropanol to precipitate RNA. A

0.25 ml of isopropanol and 0.25 ml of RNA precipitation solution (1.2 M NaCl, 0.8M disodium

citrate) per 1 ml of TRI reagent were used for the initial homogenization. Samples were

incubated at room temperature for 10 minutes and centrifuged at 12000 x g for 10 minutes at

4°C. The RNA precipitate, often remains invisible before centrifugation, settles as a gel-like

pellet at the bottom.



2.10.2.4 (d) RNA Wash

The supernatant was removed by inverting the tubes. The RNA pellet was washed once

with 75% ethanol, adding 1 ml of 75% ethanol per 1 ml of TRI reagent used for the initial

homogenization. The samples were mixed by vortexing for 10 seconds only and centrifuged at

7000 rpm for 5 minutes at 4 °C. Following centrifugation, pour away the supernatant, the

samples were short spinned and the residual supernatant was removed using a pipette.

2.10.2.4 (e) Redissolving the RNA

Briefly air-dry the RNA pellet (for 10 minutes). It is important not to let the RNA pellet

dry completely as this will greatly decrease its solubility. Partially dissolved RNA samples were

quantified at A260/280 ratio (values should be < 1.6), and resuspended in 40 µl of DEPC-treated

RNase-free Milli Q and incubated for 10 minutes at 65 °C. The fresh RNA samples must be kept

on ice for immediate use or at -70 °C for long-term storage.

2.10.2.5 DNase treatment and cDNA synthesis

The extracted RNA treated with DNase (Turbo DNase, Ambion/Applied Biosystems).

RNA concentrations were measured before and after Turbo DNase digestion with a Nanodrop

ND-1000 Spectrophotometer. First-strand cDNA was synthesized from 1 μg of total RNA using

GoScript Reverse Transcription System (Promega) according to the manufacturer’s instructions.

2.10.2.6 Real time quantitative PCR (RT-PCR) analysis

Quantitative PCR (qPCR) amplifications were conducted in optical 96-well plates with

the Mx3005P real-time PCR detection system (Stratagene), using Sybr Green Master Mix

(Stratagene/Bio-Connect) to monitor double-stranded DNA synthesis. The expression of each

gene was assayed in duplex in a total volume of 25 μl including a passive reference dye (ROX)

according to the manufacturer’s instructions (Stratagene). The thermal profile used consisted of

an initial denaturation step at 95°C for 10 min, followed by 40 cycles of 95°C for 30 s, 60°C for

60 s and 72°C for 60 s. Fluorescence data were collected during the annealing stage of

amplification. To verify amplification of a specific target cDNA, the melting-curve analysis was

included according to the thermal profile as suggested by the manufacturer.



2.10.2.7 Gene expression analysis

The amount of plant RNA in each sample was normalized using actin (Os03g0718100) or

eukaryotic translation elongation factor 1A (eEF1a - Os03g0178000) as an internal control, and

samples collected from control cell cultures were selected as a calibrator, pathogenesis-related

(PR) class 1 (PR1a) and Ethylene-responsive TF 89 susceptible gene (EBP89) were used for

pqq gene expression analysis. For all amplification plots, the optimal baseline range and

threshold cycle values were calculated using the Mx3005P algorithm (Stratagene). Gene

expression in control, mock control and bacteria-treated samples expressed relative to the

calibrator and as a ratio to actin or eukaryotic translation elongation factor 1A (eEF1a)

expression using the measured efficiency for each gene. Primer sequences used for this analysis

are listed in Table 2.7.



Table 2.7: Gene-specific primers used for quantitative real-time PCR (qPCR)

Pathway Gene Annotation Locus number Forward (5’-3’) Reverse (3’-5’)

Housekeeping

gene Actin

Rice actin 1 Os03g0718100 GCGTGGACAAAGTTTTCAACCG TCTGGTACCCTCATCAGGCATC

eEF1a Eukaryotic

elongation

factor 1A

Os03g0178000 GGCTGTTGGCGTCATCAAGA CCGTGCACAAAACTACCATT

Ethylene (ET) EBP89 Ethylene

responsive TF

89

Os03g0182800

TGACGATCTTGCTGAACTGAA

CAATCCCACAAACTTTACACA

Jasmonic acid

(JA)

JAMYB JA-inducible

Myb TF

Os11g0684000

TGGCGAAACGATGGAGATGG

CCTCGCCGTGATCAGAGATG

JiOsPR10 JA-inducible

PR10 protein

Os03g0300400

CGGACGCTTACAACTAAATCG AAACAAAACCATTCTCCGACAG

OsPR1a pathogenesis-

related protein

(PR) class 1

Os07g03710 GTCGGAGAAGCAGTGGTACG GGCGAGTAGTTGCAGGTGAT



Chapter 3 Results

“Genetic Expression and Bioinformatics of PQQ dependent glucose dehydrogenase (GDH) and Probing its Role in Plants”

`CHAPTER 3

Results

3.1 Screening of bacteria for phosphate solubilization

Sixty bacterial isolates from the associated rhizosphere of different plant species

(Appendix A) and thirty two isolates from nodules of nine leguminous species, coded as

QAU01 to QAU92 (Appendix B) were screened for phosphate solubilizing ability.

Among rhizospheric isolates, ten (16%) showed halo zone formation and thus phosphate

solubilizing ability (Figure 3.1), however these revealed variable capacities, as described

in Table 3.1.

Among top solubilizers were: QAU90 with maximum solubilization index (SI) of

3.9mm followed by QAU92 (SI=3.7mm) (Figure 3.1). Other isolates which showed

considerable solubilizing capacity were: QAU66 (3.3mm) and QAU67 (3.2mm). Among

isolates from root nodules, five (16%) showed phosphate solubilization and halo-zone

formation. The best phosphate solubilizers were: QAU53 (SI= 4.73mm) and QAU54

(SI=4.82mm). A change in pH was observed for each of these isolates. The maximum

drop in pH was observed for QAU92 (from 7.0 to 4.11) followed by QAU90 (to 4.14)

and QAU66 (to 4.40). Among nodule isolates QAU60 (SI=4.94) showed the highest drop

in pH. The solubility index and change in pH by all isolates have been summarized in

Table 3.1.

Chapter 3 Results


Figure 3.1: Phosphate solubilization activity of QAU90 and QAU92 isolates on

Pikovskaya’s agar medium incubated at 280C for 5 days (solubility index (SI) measured

in mm).

Table 3.1: Phosphate solubilization of bacterial isolates

aTri calcium phosphate (Ca3(PO4)2 solubilization efficiency calculated according to Edi-Premoto et al.

(1996) method on Pikovskaya medium plat with S.D of 3 replicates; bChange in pH calculated by

subtracting final value from initial value and cGDH (Glucose dehydrogenase) encoding gene gdh presence

tested by PCR and 12/15 found positive for gdh gene.

Isolates ID Phosphate solubilizationa (mm) pH changeb GDHc

QAU51 2.6±0.035 6.7 +

QAU53 3.8±0.030 6.1 +

QAU54 3.8±0.04 6.2 –

QAU56 3.2±0.02 6.5 +

QAU60 2.6±0.058 4.9 –

QAU62 3.5±0.057 5.8 –

QAU63 2.7±0.063 5.0 +

QAU64 3.0±0.073 4.4 +

QAU65 3.3±0.02 4.5 +

QAU66 3.3±0.051 4.4 +

QAU67 2.9±0.046 4.6 +

QAU68 3.3±0.055 5.3 +

QAU69 3.3±0.052 4.6 +

QAU90 3.9±0.035 4.14 +

QAU92 3.7±0.07 4.11 +

Chapter 3 Results


3.2 Biochemical and physiological characterization of phosphate solubilizing

bacteria

All phosphate solubilizers were catalase producing, except QAU62, while all

were negative for IAA production, except QAU67, QAU90 and QAU92 (Appendix Q),

and all were negative for the nitrogenase activity. However, the isolates QAU67 and

QAU90 were recorded as N-acyl homoserine lactone (AHL) producing. Among

nodulating isolates, QAU53 and QAU54 were positive for catalase activity, however

unlike rhizospheric isolates, the nodulating isolates were found positive for the

nitrogenase activity (Appendix Q). Similarly, only QAU51 showed positive results for

AHL production. Their colony morphology and gram’s staining attributes have been

summarized in Appendix K. The antifungal (qualitative data) and lipopeptides production

recorded in QAU90 and QAU92 and siderophores production in QAU67 (Appendix M).

3.3 Molecular characterization

3.3.1 Identification of isolates by 16S rRNA gene

Ten rhizobacterial isolates (QAU62, QAU63 QAU64, QAU65, QAU66, QAU67,

QAU68, QAU69, QAU90 and QAU92) and five nodulating isolates (QAU51, QAU53,

QAU54, QAU56 and QAU60), with phosphate solubilizing capacity, were identified

using 16S rRNA gene sequence. A product of 1.5kb for each of the isolates was amplified

and sequenced. The isolates were identified by comparing the 16S rRNA gene sequences

on Ez-Taxon Server (Figure 3.2).

Figure 3.2: 16S rRNA gene amplification of all bacterial strains; where (L: 1kb Ladder;

Lane 1: QAU51; Lane 2: QAU53; Lane 3: QAU54; Lane 4: QAU56; Lane 5: QAU60;

Lane 6: QAU62; Lane 7: QAU63; Lane 8: QAU64; Lane 9: QAU66; Lane 10: QAU67;

Lane 11: QAU68; Lane 12: QAU90 and Lane 13: QAU92).

Chapter 3 Results


On the basis of full length 16S rRNA sequence, the rhizospheric strain QAU62

and QAU68 showed 99% and 95% identity respectively with Bacillus anthracis (var.

cereus) ATCC 14578T and QAU63 showed 97% identity with Bacillus subtilis subsp.

spizizenii NRRL B-23049T while QAU64 and QAU66 showed 99% identity with

Leclercia adecarboxylata GTC 1267T. The isolates QAU65 and QAU67 showed

maximum identity 99% with Pseudomonas moorei RW10 T and QAU69 showed 99%

affinity with Pseudomonas vancouverensis ATCC 700688T, while QAU92 showed

(89%) identity with Pseudomonas putida ATCC 12633 and QAU90 showed (99%)

identity with Pseudomonas mosselli CIP 105259T. Among nodulating isolates, QAU56

showed (99%) identity with Ensifer kostiensis LMG 19227T, and QAU53 showed (98%)

to Ensifer arboris LMG 14919T, while QAU54 showed (99%) with Bacillus drentensis

LMG 21831T on the basis of full length 16S rRNA sequences (Table 3.2). The isolates

QAU51 and QAU60 did not show any identity due to insufficient sequence data on 16S

rRNA gene.

The full length 16S rRNA gene sequences, aligned and compared with the type

strain, revealed that QAU53 has close neighboring with Ensifer arboris LMG 14919T

and QAU54 clustered with Bacillus drentensis LMG 21831T and clustered with Ensifer

kostiensis LMG 19227T (Figure 3.3). The rhizospheric strain QAU62 and QAU68

clustered together with Bacillus cereus ATCC 14578T, while the QAU63 clustered with

Bacillus subtilis subsp. spizizenii NRRL B-23049T. The strain QAU64 and QAU66

clustered together with Leclercia adecarboxylata GTC 1267T. Similarly, QAU65,

QAU67 and QAU69 clustered together with Pseudomonas moorei RW10 T while

QAU90 clustered with Pseudomonas mosselli CIP 105259T and QAU92 with

Pseudomonas putida ATCC yet with low bootstrap value (70%) and depicted as a

possible novel strain. The 16S rRNA identified strains were then submitted to the

National Centre of Biotechnology Information (NCBI) Genbank database and assigned

the accession numbers (Table 3.2) with taxonomic reliability

http://www.ncbi.nlm.nih.gov/nuccore/KC679991 and strains conformation from EzTaxon

Server (http://eztaxon-e.ezbiocloud.net) database.

http://www.ncbi.nlm.nih.gov/nuccore/KC679991

http://eztaxon-e.ezbiocloud.net/

Chapter 3 Results

“Genetic Expression and Bioinformatics of PQQ dependent glucose dehydrogenase (GDH) and Probing its Role in Plants”59

Table 3.2: Molecular identification of bacterial isolate by 16S rRNA and submission to NCBI Genbank

Strain ID Strain Name /

Genus

Source of isolation Location of

isolation

Number of

nucleotides of

16S rRNA gene

Genbank

Accession

numbers

Closely related taxa identified by using the

EzTaxa on Server Database

(http://eztaxon-e.ezbiocloud.net)

Sequence identity (%) of 16S

rRNA gene with closely

related taxa

Sequence

query

coverage

(%)

QAU53 Ensifer sp. Nodules of Melilotus indicus

Islamabad 1383 KC679988 Ensifer arboris LMG 14919T (AM181744) 98.76 99.6

QAU54 Bacillus sp. Nodules of

Indigofera linifolia

Islamabad 1543 KC679987 Bacillus drentensis LMG 21831T (AJ542506) 99.22 100

QAU56 Ensifer sp. Nodules of

Crotalaria

medicaginea

Islamabad 1398 KC679989 Ensifer kostiensis LMG 19227T (AM181748) 99.64 100

QAU62 Bacillus sp. Rhizosphere of

Gossypium hirsutum

Jacobabad 1077 KC679986 Bacillus anthracis ATCC 14578T

(AB190217)

99.71 73.5

QAU63 Bacillus sp. Rhizosphere of Lycopersicon

esculentum

Jacobabad 1483 KC679985 Bacillus subtilis subsp. spizizenii NRRL B-23049T (CP002905)

97.01 100

QAU64 Leclercia sp. Rhizosphere of Vigna mungo

Islamabad 1501 KC886280 Leclercia adecarboxylata GTC 1267 T (AB273740)

99.46 100

QAU65 Pseudomonas sp. Rhizosphere of

Pisum sativum

Islamabad 1431 KC679990 Pseudomonas moorei RW10 T (AM293566) 99.79 98.7

QAU66 Leclercia sp. Rhizosphere of

Vigna mungo

Islamabad 1500 KC679993 Leclercia adecarboxylata GTC 1267 T

(AB273740)

99.39 100


Gossypium hirsutum

Multan 1431 KC679991 Pseudomonas moorei RW10 T (AM293566) 99.93 98.0

QAU68 Bacillus sp. Rhizosphere of Zea mays

Multan 1470 KC679984 Bacillus anthracis ATCC 14578T (AB190217) 95.75 100

QAU69 Pseudomonas sp. Rhizosphere of Zea

mays

Multan 1492 KC679992 Pseudomonas vancouverensis ATCC 700688T

(AJ011507)

99.52 100


Triticum aestivum

Gujranwala 1374 KM251449 Pseudomonas mosselii CIP 105259T 100% 100%

QAU92 Pseudomonas sp. Rhizosphere of Triticum aestivum

Gujrat 1384 KM251450 Flavimonas oryzihabitans IAM 1568T 99.49% 94.7%

http://eztaxon-e.ezbiocloud.net/

http://eztaxon-e.ezbiocloud.net/ezt_hierarchy?m=nomen_view&nid=Ensifer+kostiensis

http://bccm.belspo.be/db/lmg_strain_details.php?NUM=19227

http://bccm.belspo.be/db/lmg_strain_details.php?NUM=19227

http://eztaxon-e.ezbiocloud.net/ezt_hierarchy?m=browse&k=AB190217&d=2

Chapter 3 Results


Figure 3.3: Neighbor-joining phylogenetic tree showing the inter-relationship of strains

with the validly published type species inferred from sequences of 16S rRNA gene.

Pseudomonas oryzihabitans LMG 7040 was used as an out group. Bootstrap values are

expressed as a percentage of 1000 replications, are given at the branching point.

3.3.2 Multilocus sequence analysis (MLSA)

The Pseudomonas strains: QAU67, QAU90 and QAU92 were further

characterized using rpoB, rpoD and recA gene analysis. These analyses helped in

identification of isolates at specific level. Since the CMR12a strain was previously

Chapter 3 Results


characterized as P. fluorescens (Perneel et al., 2007) was used as a reference for this

analysis.

3.3.2.1 The rpoB gene

The rpoB gene amplified 508bp for bacterial strains (Figure 3.4) and the sequence

analyses revealed that the strain QAU90 belongs to Pseudomonas putida group, based on

sequence identity (96%) of rpoB locus with Pseudomonas putida (Acc. no. CP005976.1)

similarly, the isolate QAU92 showed identity (95%) with Pseudomonas sp. R-26428

(Acc. no. AM944726.1). The cluster analysis (Figure 3.5) based on neighbor joining

method of the rpoB gene sequence showed QAU92 in proximity with P. putida however,

with poor (30%) bootstrap support and a possible novel nature (however, this requires

further confirmation, and is beyond the scope of this study). The strain QAU67 showed

98% identity with Pseudomonas mandelii strain McBRA2 (JQ317869.1) and neighboring

with P. mohni, suggesting its affinity with the P. fluorescens group.

Figure 3.4: The rpoB (MLSA) gene amplification (508bp) of bacterial strains; where (L:

1kb Ladder; Lane 1: CMR12a; Lane 2: QAU67; Lane 3: QAU90; Lane 4: QAU92).

Chapter 3 Results


Figure 3.5: Neighbor-joining phylogenetic tree showing the inter-relationship of strain

QAU67, QAU90 and QAU92 with the validly published species inferred from sequences

of rpoB gene. Pseudomonas aeruginosa was used as an out group. Bootstrap values are

expressed as a percentage of 1000 replications and given at the branching point.

Chapter 3 Results


3.3.2.2 The rpoD gene

The rpoD gene amplified 690bp and sequence analysis depicted a complete

(100%) identification of isolate QAU90 with that of Pseudomonas putida KT2440

(AE015451.1). Further the phylogenetic analysis revealed the QAU90 clustering with the

strain P. monteilii ATCC 14164T well supported with the bootstrap value (89%).

Similarly, the strain QAU92 showed 85% identity with Pseudomonas putida W619

(CP000949.1) however, it did not cluster with any of the known/submitted strains and

behaved as an outlier (Figure 3.7). The isolate QAU67 showed 96% identity with

Pseudomonas reinekei DSM 18361 (FN678362.1) and appeared in close neighboring

with P. mohni. The latter belonged to the P. fluorescens group.

Figure 3.6: Housekeeping (MLSA) genes amplification of bacterial strains; where (L:

1kb Ladder; Lane1-4: gyrB (CMR12a, QAU67, QAU90 and QAU92) Line 5-8: rpoD

(CMR12a, QAU67, QAU90 and QAU92) and line 9-12: recA (CMR12a, QAU67,

QAU90 and QAU92).

Chapter 3 Results




of rpoD gene. The strain QAU92 was behaved an out group. Bootstrap values are

expressed as a percentage of 1000 replications, are given at the branching point.

3.3.2.3 The recA gene

The recA locus amplification (Figure 3.6) and subsequent sequence analysis for

the isolate QAU90 showed its 96% sequence identity with recombinase A (recA) gene of

Pseudomonas putida KT2440 (AE015451.1) The phylogenetic analysis further showed

its close neighboring (93%) with Pseudomonas putida KT2440. The isolate QAU92

showed 89% identity with Pseudomonas putida W619 (CP000949.1), however, the

phylogenetic analysis (Figure 3.8) showed its clustering with the type strains of P.

aeruginosa ICMP 8847T not well supported (22%) in the bootstrap analysis. Hence, the

position of QAU92 remains unclear. The isolate QAU67 showed 96% identity with

Pseudomonas fluorescens strain SF4c (JQ036170.1) and further showed 82% clustering

with Pseudomonas fluorescens Pf0-1.

Chapter 3 Results


Collating data of 16S rRNA and multilocus sequence analysis of rpoB, rpoD and

recA loci, it is concluded that QAU90 is Pseudomonas putida and closely related to the

P. putida strain KT2440, Similarly the isolate QAU67 has been identified as

Pseudomonas fluorescens Pf0-1 strain. The strain QAU92 showed identity with

Pseudomonas putida group however, the phylogenetic analysis did not achieve the

statistical support in bootstrap analysis in any of the marker locus utilized and hence

depicted its most probable novel status. In all analyses, CMR12a has been revealed as P.

fluorescens as already reported in Perneel et al (2007). It is pertinent to mention that

another locus known as gyrB (Figure 3.6) was also probed however it could not reveal the

sequencing results. The sequences generated for all genes/loci have been submitted to

NCBI Genbank database (Appendix L).



of recA gene. Pseudomonas protegens-Pf-5 was used as an out group. Bootstrap values

with 1000 replications, are expressed as percentages and are given at the branch points.

Chapter 3 Results


3.4 Identification of gdh and pqq genes

3.4.1 PCR amplification of quinoproteins glucose dehydrogenase (gdh) gene

The gdh primers for glucose dehydrogenase designed on the Enterobacter

background amplified a partial amplicon of 1400bp (KF156751) for the isolate QAU66

identified as Leclercia adecarboxylata. The nucleotide BLAST search (Blastn) results

showed that gdh gene of QAU66 was closely related to Enterobacter cloacae

(CP003678.1) with 95% sequence identity. The gdh primers designed on the base of

Pseudomonas genus, amplified a full length 2400bp product in CMR12a, QAU67,

QAU90 and QAU92 (Figure 3.9). BLASTN result showed that gdh gene of Pseudomonas

fluorescens CMR12a and P. fluorescens QAU67 were most closely related to the

quinoprotein glucose dehydrogenase gene of P. fluorescens CHA0 (CP003190) and

Pseudomonas fluorescens A506 (CP003041.1) with sequence identity of 92% each. The

Pseudomonas putida QAU90 and Pseudomonas sp. QAU92 showed sequence identity of

89% and 88% with PQQ dependent glucose dehydrogenase of P. entomophila

(CT573326.1) and P. putida W619 (CP000949) respectively.

Figure 3.9: gdh gene amplification of all bacterial strains; of partial sequence (A)

Enterobacter strains (QAU64 & QAU66) and full length sequence of (B) Pseudomonas

strains where (L: 1kb Ladder; Lane 1: CMR12a; Lane 2: QAU90; Lane 3: QAU92; Lane

4: QAU67).

Further analysis showed that QAU66 gdh sequence information matched with the

gdh of Enterobacter cloacae; that of QAU67 showed close neighboring with P.

fluorescens strain A506; that of CMR12a showed close neighboring with P. protegens pf-

5 (CP000076.1) and CHAO (FI143714.1) and that of QAU90 matched with P. putida

Chapter 3 Results


group. However, the sequence data of QAU92 showed only poor match with P. putida

and largely appeared distinct (Figure 3.10).


CMR12a, QAU66, QAU67 and QAU90 with the closely related validly published species

inferred from sequences of gdh genes. The strain QAU92 was behaved an out group.

Bootstrap values are expressed as a percentage of 1000 replications, are given at the

branching point.

3.4.2 Amplification of ‘pqq’ genes (pqqABCDEF)

PCR amplification of pqq genes were obtained Pseudomonas CMR12a, QAU67,

QAU90 and QAU92 with some annealing variation (as described in materials and

methods section) while the amplifications have been shown as gel pictures in appendix R

and pqqBCD in figure 3.11. The blastn results showed that pqqBCD of Pseudomonas

fluorescens CMR12a and P. fluorescens QAU67 were most closely related to the

Chapter 3 Results


pqqBCD cluster of P. fluorescens CHA0 and Pseudomonas fluorescens Pf0-1 with

identity of 89% and 88% respectively. The P. putida QAU90 and Pseudomonas sp.

QAU92 showed sequence identity of PQQ dependent glucose dehydrogenase 90% and

86% with P. entomophila and P. putida GB-1 respectively. The pqq operon was

annotated (as pqqA, B, C, D, E, F) and gdh gene sequences were submitted to NCBI

Genbank database http://www.ncbi.nlm.nih.gov/nuccore/KM251417 (Appendix L).

The cluster analysis (Figure 3.12) based on the sequence data of pqqBCD genes of

P. putida QAU90 matched with P. putida W619 with a bootstrap value of 61%. The

strain QAU92 again did not show enough match with any other strain. The strain QAU67

showed close neighboring (88%) with Pseudomonas sp. UW4 and CMR12a showed good

neighboring (74%) with P. fluorescens CHA0. Since the rest of pqq genes did not show

variability with any of the pqq locus, these were not considered in cluster analysis.

Subsequently, the sequences obtained for each isolate were characterized for the position,

direction and orientation (Figure 3.13) with reference to those of Gluconobacter oxydans

ATCC9937 (Hölscher and Görisch 2006) and Pseudomonas fluorescens B16 strains

(Choi et al., 2008).

Figure 3.11: The pqqBCD genes amplification (2.1 kb) of all bacterial strains; where (L:

1kb Ladder; Lane 1: CMR12a; Lane 2: QAU67; Lane 3: QAU90; Lane 4: QAU92).

http://www.ncbi.nlm.nih.gov/nuccore/KM251417

Chapter 3 Results



QAU67, QAU90 and QAU92 with the closely related validly published species inferred

from sequences of pqqBCD genes. The strain P. fluorescens strain B16 was used as out

group. Bootstrap values are expressed as a percentage of 1000 replications, are given at

the branching point.

Chapter 3 Results


Figure 3.13: Comparison of the pqq gene clusters of P. fluorescens CMR12a, P.

fluorescens QAU67, P. putida QAU90 and Pseudomonas sp. QAU92 with reference

strains of Gluconobacter oxydans ATCC9937 and P. fluorescens B16. Positions and

orientations of the pqq genes are indicated by colored arrows. The same colors represent

homologous encoded proteins. The organization and size of the genes are depicted based

on nucleotide sequence data from GenBank.

3.5 Bioinformatics analysis

3.5.1 Physico-chemical properties of GDH

The identified open reading frame (ORF) information for ‘gdh’ was used in silico

to obtain corresponding GDH protein for: Leclercia sp. QAU66 (with 377 amino acids),

P. fluorescens CMR12a (with 679 amino acids), P. putida QAU90 (with 556 amino

acids), Pseudomonas sp. QAU92 (with 700 amino acids) and QAU67 showed same

structural features as CMR12a, so not consider for structural analysis. The bioinformatics

based translational sequence of GDH analysis revealed Physico-chemical properties of all

Pseudomonas strain which have been listed in Table 3.3.

3.5.2 Structural analysis of GDH Protein

Analysis on the secondary structure of GDH further revealed the presence of β-

strands (37%) in Leclercia sp. QAU66, (64.8%) in P. fluorescens CMR12a, (52.3%) in P.

Chapter 3 Results


putida QAU90 and (70.7%) in Pseudomonas sp. QAU92 corresponds to their β propeller

nature which is the structural property of GDH protein (Appendix S).

3.5.2.1 Homology modeling based on 3D structures

The predicted GDH structure of Leclercia sp. QAU66 showed identity with the

quinohemoprotein alcohol dehydrogenase (1yiqA1) template with TM-score of 0.800 (an

algorithm to calculate the structural alignment between query structure and known

structure in pdb library). The P. fluorescens CMR12a was found identical to the

quinohemoprotein alcohol dehydrogenase reported in C. testosteroni (1kb0A) template

with TM-score of 0.67; P. putida QAU90 showed identity to the quinoprotein ethanol

dehydrogenase from P. aeruginosa (1flgA) template with TM-score of 0.74 and

Pseudomonas sp. QAU92 showed identity to the Apo-dipeptidyl peptidase IV/CD26

(1tk3A) template with TM-score of 0.36. The low value identity depiction for QAU92

depicts significant variation compared to the known proteins (with the TM score range 0-

1) (Figure 3.14).

Chapter 3 Results


Table 3.3: The physico-chemical characterization of GDH proteins

Strains Protein

residue

(Amino

acid)

Molecular

Formula

Molecula

r weight

(gram)

Net

charge

(coulomb

)

Isoelectric

point

GRAVY Instability

index

Estimated half-

life

(Escherichia

coli, in vivo)

Transme

mbrane

α-Helix

Leclercia sp.

QAU66

377 C1840H2829N483O526S19 40741.6 4.0

8.5

-0.209 38.24 >10 hours 0

P.fluorescens

CMR12a

579 C3288H5165N907O947S26 73387.2 13.5 8.9633 -0.197 36.50

>10 hours 5

P.putida QAU90 556 C2696H4279N843O764S17 61270.8 38.5

11.1155 -0.587 49.46

>10 hours 5

Pseudomonas

sp. QAU92

700 C3388H5292N940O986S28 75866.6 8.5

7.9662 -0.170 37.64

>10 hours 5

Chapter 3 Results


Chapter 3 Results


Figure 3.14: Predicted 3D model from I-TASSER and visualized on Jmol (A-D). Protein

function annotations based on the sequence-to-structure-to-function paradigm for GDH. The

right panel is the function identity which was identified by global and local matches of I-

TASSER models showing binding sites of PQQ cofactor and identity with template with TM-

score (TM score is a measure of global structural identity between query and template protein).

3.5.3 Prediction of ligand and active sites of GDH models

The binding sites of GDH protein having PQQ and Ca+2 ligands revealed C-scores for

Leclercia sp. QAU66 (0.12), P. fluorescens CMR12a (0.46), P. putida QAU90 (0.22) and

Pseudomonas sp. QAU92 (0.01). The PQQ and the calcium ion binding sites were predicted in

all of the GDH models which elaborated the GDH model generated (Figure 3.15). The residues

at active sites of GDH were predicted as: in Leclercia sp. QAU66 (from 240 to 350 amino acids),

P. fluorescens CMR12a (165-597 amino acids), P. putida QAU90 (126-202 amino acids) and in

Pseudomonas sp. QAU92 (1- 433 amino acids).

Chapter 3 Results


A

B

C

Chapter 3 Results


Figure 3.15: Glucose dehydrogenase (GDH) models comprised of ligand binding (PQQ and

Ca2+), active site, residue binding sites and functional domain which were predicted by

INTERPROSCAN and COFACTOR respectively, and then illustrated in DOG 2.0 (illustrator of

protein domain structures); (A) Functional domains of QAU66, (B) P. fluorescens CMR12a, (C)

P. putida QAU90 and (D) Pseudomonas sp. QAU92.

3.5.4 Functional Analysis of GDH Protein

3.5.4.1 Annotations of functional residues

The PSIPRED tools predictied the five transmembare helicles in P. fluorescens CMR12a,

P. putida QAU90 and Pseudomonas sp. QAU92. On the contrary, no transmembrane helixes

were found in Leclercia sp. QAU66 GDH protein. The residues involved in signal peptide

present at the N-terminus in majority of de novo synthesized proteins are destined towards the

secretory pathway and predicted in P. fluorescens CMR12a, P. putida QAU90 but no signal

peptide was found in Pseudomonas sp. QAU92 and Leclercia sp. QAU66 GDH protein. The

analysis further predicted residues (amino acids) involved in extracellular, cytoplasmic,

transmembrane and re-entrant helix residues in P. fluorescens CMR12a, P. putida QAU90 and

Pseudomonas sp. QAU92 (Figure 3.16).

All five transmembrane helices of P. fluorescens CMR12a, P. putida QAU90 and

Pseudomonas sp. QAU92 GDH proteins showed better interaction with amino acid residues

involved in helix formation shown as (pink and purple) circular nodes and Interactions between

residues are indicated on edges. Helices are oriented to maximize the number of residues with

predicted interactions (Appendix T).

D

Chapter 3 Results


Signal peptides Cytoplasmic Extracellular

Re-entrant Helix Transmemberane Helix

Figure 3.16: Schematic diagram of the MEMSAT3 and MEMSAT-SVM predictions for the

query sequence of glucose dehydrogenases of P. fluorescens CMR12a, P. putida QAU90 and

Pseudomonas sp. QAU92. Traces indicate the RAW outputs for the prediction SVMs. Dashed

lines indicate the prediction threshold and H-P : Helix prediction, PL: Pore lining residue, SP:

Signal peptide residue and RE: Re-entrant helix residue.

Chapter 3 Results


3.5.4.2 Functional insights based on 3D models

The functional classification done through COFACTOR tool depicted top five enzyme

homologs of Leclercia sp. QAU66 GDH protein with a C-score of 0.398 and revealed a close

structural identity with quinohemoprotein alcohol dehydrogenase (1yiqA1). The C-score obtained

for P. fluorescens CMR12a GDH protein was 0.49 and identity with quinohemoprotein alcohol

dehydrogenase known in C. testosteroni (1kb0A), P. putida QAU90 revealed a C-score 0.36 and

identity with quinoprotein ethanol dehydrogenase reported in P. aeruginosa (1flgA) and finally,

the Pseudomonas sp. QAU92 showed a low C-score of 0.15 and identity with Apo-dipeptidyl

peptidase IV/CD26 (1tk3A).

The amino acid involved in phosphorylation with secondary structure of Glucose

dehydrogenases (GDH) of all strains and position dependent features of Phosphorylation features

reflected the confidence of the residue prediction. The maximum residues involved in

phosphorylation were predicted in GDH structure of Pseudomonas sp. QAU92 (Appendix U).

3.5.4.3 Functional domain prediction of GDH protein

The functional domains of GDH protein determined by InterProScan showed that

Leclercia sp. QAU66 has three PQQ repetitive domain sites (in between 18-50, 243-277 and

303-340 residues) and revealed good functional identity with quinoprotein alcohol

dehydrogenase (148-375 residues) without any signal peptide. Variation in depiction was also

noted. For instance in P. fluorescens CMR12a two PQQ repetitive domains sites (between 242-

270, and 461-490 residues) were depicted, however its functional identity remained with

quinoprotein alcohol dehydrogenase (174-295 and 424-677 residues) with a signal peptide (1-45

residues). Similarly, P. putida QAU90 has only one PQQ domain site (between 228-252

residues) and functional identity with quinoprotein alcohol dehydrogenase (162-285 and 406-454

residues) with a signal peptide (1-32 residues) at the start of GDH protein while Pseudomonas

sp. QAU92 has three PQQ repetitive domain sites (between 92-121, 309-344 and 652-680

residues) and revealed good functional identity with two quinoprotein alcohol dehydrogenase

like domains (219-296 and 586-697 residues) without signal peptide. The PQQ domains were

further confirmed with Pfam program (Punta et al., 2012) which showed the presence of PQQ

repeats in GDH protein (Figure 3.17).

Chapter 3 Results


Chapter 3 Results


Figure 3.17: The structure based functional domain prediction of glucose dehydrogenase (GDH)

by Interproscan tool: (A) Leclercia sp. QAU66 (B) P. fluorescens CMR12a (C) P. putida

QAU90 (D) Pseudomonas sp. QAU92.

3.5.4.4 Gene Ontology (GO)

Gene ontology predicted the biological, molecular and cellular functions of GDH protein

showing its oxidation-reduction processes, oxidoreductase activity (acting on CH-OH group of

donors), presence in the outer membrane-bound periplasmic space and quinone binding thus

depicting functional identity and features of glucose dehydrogenase (Table 3.4). Based on the

functions, the overall functional models were generated (Figure 3.15).

Chapter 3 Results


Table 3.4: Functional characterization of GDH by Gene ontology (I-TASSER)

Strains/ GDH

protein

Molecular Function Biological Process Cellular Location

GO term Function GO term Function GO term Function

Leclercia sp.

QAU66

GO:0055114 oxidoreductase

activity

GO:0055114

oxidation-

reduction

process

GO:0016020 membrane

GO:0005509 calcium ion

binding

GO:0034308 primary

alcohol

metabolism

GO:0030288 presence in outer

membrane

bounded

periplasmic space

GO:0048038 quinone

binding

P. fluorescens

CMR12a

GO:0016491

oxidoreductase

activity

GO:0055114

oxidation-

reduction

process

GO:0005886 cytoplasmic

membrane

GO:0005509

calcium ion

binding

GO:0015945 methanol

metabolism


membrane

Bounded

periplasmic space

GO:0005215

transporter

activity

GO:0006811

ion transport

P. putida

QAU90

GO:0009055 electron carrier

activity

GO:0055114

oxidation-

reduction

process

GO:0016020 membrane

GO:0055114 oxidoreductase

activity

GO:0034308 primary

alcohol

metabolism


membrane

Bounded

periplasmic space

GO:0005509 calcium ion

binding

Pseudomonas

sp. QAU92

GO:0005198

structural

molecule

activity

GO:0006486

protein

glycosylation

GO:0016020 membrane

GO:0048038 quinone

binding

GO:0055114

oxidation-

reduction

process

GO:0004872

receptor

activity

GO:0007165

signal

transduction

Chapter 3 Results


3.6: Mutagenesis

3.6.1 The gdh mutagenesis and its implications

Among the Pseudomonas strains, the gdh locus mutations (using Tn5 insertion mutation

with E. coli WM3064 and pfaj1815 plasmid) were successfully obtained for the isolate QAU90

and therefore it was further used for mutant characterization, as described below:

3.6.1.1 gdh mutant characterization

A total of 340 colonies were screened for insertion mutation considering their ability to

solubilize inorganic phosphate on Pikoviskya medium. The QAU90-23 was found to solubilize

only 0.67 mm phosphate as compared to wild type (3.90 mm), which indicated the effective role

of gdh locus (Figure 3.18).

Figure 3.18: Phosphate solubilization index (SI) of (A) Pseudomonas putida QAU90 (wild type)

and (B) Tn5 based insertional gdh mutant Pseudomonas putida QAU90-23.

3.6.1.2 Comparative effect of gdh and gdh-mutant on plant growth promotion

The P. putida QAU90, known to carry gdh locus was test inoculated on bean plants that

demonstrated an improved height of 70.4 cm as compared to the control (51cm). The Tn5-

induced gdh mutant (QAU90-23) did not perform any better to that of the control obtaining an

average height of 47cm keeping all variable same (Figure 3.20). Furthermore, the wild type

Chapter 3 Results


inoculated plants showed a clear difference in leaf area (74.8 cm2) as compared to the control

(55.4 cm2) and the gdh mutant inoculated plants (51.6 cm2). These results, showed a clear

difference between wild type and gdh mutant performance both in case of phosphate

solubilization and subsequently the plant growth promotion (Figure 3.19).

Figure 3.19: The comparative performance of Pseudomonas putida QAU90 (wild type) and

Tn5-induced gdh mutant (QAU90-23) on bean plant growth.

Figure 3.20: Growth promotion activities of bean (Phaseolus vulgaris) by Pseudomonas putida

QAU90 (wild type) and Tn5 based insertional gdh mutant Pseudomonas putida QAU90-23

inoculated plant with water treated control plants. Plant parameters are plant height, root length,

fresh weight (shoot × root) in gram and leaf area (length × width) with average of 10 plants from

three replicate.

0

10

20

30

40

50

60

70

80

90

Plant height Root length Fresh weight (S*R) Leaf area (L*W)

Gro

wth

pro

mo

tio

n (

cm)

Plant growth parameters

Control QAU90 QAU90-23

Chapter 3 Results


3.6.2 Knock out gene expression analysis of pqq

Subsequent to the characterization of gdh gene, the complementary role of its cofactor

pqq was probed. Thus a knockout mutation was carried out to understand the mechanism of

action for pqq. The impact of mutation at pqqC, following a site directed mutation of pqqC

locus, was tested in plant growth promotion, utilization of enzymes and amino acid, carbon and

nitrogen source utilization, in vivo antagonistic and disease control activities, as described below:

3.6.2.1 PCR based mutant detection

Mutants were detected on the basis of deletion of 1 kb segment that appeared on the gel

as a smaller product size (Figure 3.21). Thus, the isolates: CMR12a, QAU67, QAU90 and

QAU92 subjected to knockout mutation produced as many as 15, 14, 12 and 9 mutants

respectively. These mutants were further studied as follows:

3.6.2.2 Mutants characterization: phosphate solubilization and change in pH

Assessment of phosphate solubilization revealed that all pqqC mutants irrespective of

their type showed no halo zone formation on pikoviskya medium (Figure 3.22), except for P.

fluorescens QAU67. Similarly, maximum difference in pH was observed between the wild type

P. putida QAU90 (4.11) and Pseudomonas sp. QAU92 (4.14) and their pqqC mutants: QAU90-4

(5.86) and QAU92-2 (5.92). The acidophilic nature showed by wild type strains as compared to

pqqC mutant strains depicted that the pqq dependent glucose dehydrogenase (GDH) works well

in wild type strains compared to their mutants (Table 3.5).

Chapter 3 Results


Figure 3.21: PCR based identification of pqqC mutants of bacterial strains; (A) P. fluorescens

CMR12a, (B) P. fluorescens QAU67, (C) P. putida QAU90 and (D) Pseudomonas sp. QAU92.

The E. coli strain with the plasmid was used as a positive control (1 kb) and wild type strain

(2,1kb) used as a negative control.

Chapter 3 Results


Figure 3.22: Phosphate solubilization capability of wild and pqqC mutant strains on pikovskaya

medium (A) P. fluorescens CMR12a with its pqqC mutant P. fluorescens CMR12a-3, (B) P.

putida QAU90 with its pqqC mutant P. putida QAU90-2 and (C) Pseudomonas sp. QAU92 with

its pqqC mutant Pseudomonas sp. QAU92-4.

Table 3.5: The effect of wild type and pqqC mutant strains on pH

Wild type strains pH pqqC Mutants pH

CMR12a 4.24 CMR12a-3 5.73

QAU67 4.92 QAU67-14 5.38

QAU90 4.11 QAU90-4 5.86

QAU92 4.14 QAU92-2 5.92

Chapter 3 Results


3.6.2.3 Biochemical characterization of pqqC mutants (qualitative)

The Pseudomonas derived pqqC mutants were biochemically characterized by API 20E

kit embedded with twenty tests (as described in the Materials and Methods chapter). The mutants

CMR12a-3, QAU90-4 and QAU92-2 showed significant differences between the wild type and

control reactions (Table 3.6). The CMR12a strain utilized the L-omithin, glucose, sorbitol, L-

rhamnose, D-melibiose, amygdaline and L-arabinose but its mutant (CMR12a-3) could not

demonstrate their utilization (Figure 3.23). Furthermore, QAU90 and QAU92 additionally

utilized 2-nitrophenyl-BD-galactopyranosie, urea and sucrose, pointing to the possible role of

PQQ’s in processes like fermentation and oxidation-reduction as well as the enzymatic and

amino acid catabolism reactions. Intriguingly, QAU67 behaved odd, this is because its mutant

QAU67-14 up-regulated the expression in a number of tests embedded in the kit (Figure 3.23b)

compared to other strains.

Figure 3.23 (A): Biochemical characterization of wild type and their pqqC mutant strains by

API 20E kit. The impact of mutation is obvious when comparing wild type P. fluorescens

CMR12a and its pqqC mutant strain along with negative control and scores in Table 3.6.

Chapter 3 Results


Figure 3.23 (B): Biochemical characterization of wild type and their pqqC mutant strains by

API 20E kit. The impact of mutation is obvious when comparing wild type P. fluorescens

QAU67, (C) P. putida QAU90 and (D) Pseudomonas sp. QAU92 and their pqqC mutant strains

along with negative control and scores in Table 3.6.

Chapter 3 Results


Table 3.6: Biochemical characterization of wild type and pqqC mutant strains by API 20E

system (qualitative data)

Tests CMR12a

CMR12a-3

QAU67

QAU67-14

QAU90

QAU90-4

QAU92

QAU92-2

OPNG − − − + + − + −

ADH + + + + + + + +

LDC − − − + + − − −

ODC + − − − + + + −

CIT + + + + + + + +

H2S − − − − − − − −

URE − − − − − + − −

TDA − − + − − − − −

IND − − − − − − − −

VP − − − − − − − −

GEL + + − − + + − −

GLU + − − + + − + −

MAN + − − + + − + −

INO − − − − − − − −

SOR + − − + + − + −

RHA + − − + + − + −

SAC − − − + + − + −

MEL + − − + + − + −

AMY + − − + + − + −

ARY + − − + + − + −

OPNG (Ortho Nitrophenyl-βD-glactopyranoside), ADH (Arginine Dihydrolase), LDC (Lysine

Decarboxylase), ODC (Omithin Decarboxylase), CIT (Citrate utilization), H2S (H2S production),

URE (Urease), TDA (Tryptophane Desaminase), IND (Indole production), VP (Acetoin

production), GEL (Gelatinase), GLU (Glucose), MAN (Manitol), INO (Inositol), SOR (Sorbitol),

RHA (Rhamnose), SAC (Sacharose), MEL (D-melibiose), AMY (Amygdaline) and ARY

(Arabinose).

Chapter 3 Results


3.6.2.4 Carbon source utilization

The wild type and pqqC mutants were utilized to identify enzymes for which PQQ serves

as cofactor in the bacterial system based on the carbon source utilization assay. For this purpose,

eight different carbon sources (Glucose, Acetate, Na-citrate, Na-succinate, manitol, glycerol,

ethanol and methanol) were screened. Differences in utilization of ethanol and methanol were

recorded for CMR12a and its derived mutant (CMR12a-3), suggesting this to belong to the

alcohol dehydrogenase family. The strain QAU67 and QAU90 efficiently utilized glucose as

carbon source as compared to their pqqC mutants, suggesting their glucose dehydrogenase

nature. However, unlike these, the QAU92 isolate was found to have utilized glycerol and

ethanol as carbon source. Hence, this strain belongs to the alcohol dehydrogenase family.

However intriguingly it was also capable of utilizing glycerol which warrants further analysis

(Figure 3.24).

Figure 3.24: Comparison of carbon source utilization by wild strains (P. fluorescens CMR12a,

P. fluorescens QAU67, P. putida QAU90 and Pseudomonas sp. QAU92) and their pqqC mutant

(P. fluorescens CMR12a-3, P. fluorescens QAU67-14, P. putida QAU90-4 and Pseudomonas sp.

QAU92-2) strains with standard deviation of two replicates. The X-axis represent %age

utilization of carbon source and arrow showed the less carbon source utilization by mutants.

Chapter 3 Results


3.6.2.5 Antioxidant activity of PQQ

3.6.2.5.1 DPPH scavenging activity

The a-diphenyl-b-picrylhydrazyl (DPPH) antioxidant activity of the PQQ was estimated

through the absorbance of the free radicals. At a concentration 80 ug/ml, the highest DPPH-

scavenging activity among the pqq extracts was produced by Pseudomonas sp. QAU92 (97.5%)

followed by P. putida QAU90 (95.43%), P. fluorescens QAU67 (94.8%), P. fluorescens

CMR12a (90.45%) while at the same concentration, the scavenging effects of pqq deficient

mutants Pseudomonas sp. QAU92-2 and P. putida QAU90-4, P. fluorescens CMR12a-3, P.

fluorescens QAU67-14 were only 67.84%, 70.95%, 72.51% and 80.8% respectively (Figure

3.25). The pattern was also higher at other concentrations as compared to the pqqC mutant

strains and showed a clear difference in the scavenging capacity. It was evidently suggested that

the pqq extracts had proton-donating ability and served as free radical inhibitors or scavengers.

The results showed a concentration (20, 40 and 80 ug/ml) dependent percent scavenging

antioxidant activity of pqq from wild type (P. fluorescens CMR12a, P. fluorescens QAU67, P.

putida QAU90 and Pseudomonas sp. QAU92) and their pqqC mutants (P. fluorescens CMR12a-

3, P. fluorescens QAU67-14, P. putida QAU90-4 and Pseudomonas sp. QAU92-2) strains at an

absorbance of 517 nm.

3.6.2.5.2 Reducing power

The reducing capacity of pqq was investigated by transition of Fe3+/ferricyanide complex

to Fe2+. At a concentration of 80ug/ml, the Pseudomonas sp. QAU92 showed highest reducing

power of 1.10 while at same dosage pqqC mutant of P. fluorescens QAU67-14 exhibited a low

reducing power value of 0.54 (Figure 3.26). These results revealed that the pqq was electron

donor and also could react with the free radicals, converting them to more stable products and

terminating the radical chain reaction. At an absorbance of 700 nm, the reducing power of all

wild type strains was generally found significantly pronounced than those of the pqqC mutant

strains. Furthermore, the pqq extracts of Pseudomonas sp. QAU92 showed the highest reducing

power, followed by the P. putida QAU90, P. fluorescens CMR12a, P. fluorescens QAU67, P.

putida QAU90-4 (pqqC mutant) P. fluorescens CMR12a-3 (pqqC mutants), Pseudomonas sp.

QAU92-2 (pqqC mutant) and P. fluorescens QAU67-14 (pqqC mutant) in a decreasing order.

Chapter 3 Results


The presence of pqq (when acted as antioxidant) in the samples has resulted in the reduction of

the Fe3+/ferricyanide complex to its ferrous form. It is significant to mention that the pqq and the

derived mutants exhibited a dose dependent reducing power activity within the applied

concentrations (0, 10, 20, 40 and 80 ug/ml). The reducing capacity of a PQQ may serve as a

significant indicator for its potential antioxidant activity which further improved the plant growth

and disease control.

Figure 3.25: DPPH radical showed a concentration (20, 40 and 80 ug/ml) dependent percent

scavenging antioxidant activity of pqq extract from wild type (P. fluorescens CMR12a, P.

fluorescens QAU67, P. putida QAU90 and Pseudomonas sp. QAU92) strains and their pqqC

mutants (P. fluorescens CMR12a-3, P. fluorescens QAU67-14, P. putida QAU90-4 and

Pseudomonas sp. QAU92-2) at absorbance of 517 nm. Legends showed concentrations.

Chapter 3 Results


Figure 3.26: Antioxidant activities of the wild type (P. fluorescens CMR12a, P. fluorescens

QAU67, P. putida QAU90 and Pseudomonas sp. QAU92) strains and their PQQ mutants (P.

fluorescens CMR12a-3, P. fluorescens QAU67-14, P. putida QAU90-4 and Pseudomonas sp.

QAU92-2) with different concentrations (0, 10, 20, 40 and 80 ug/ml) were measured by the

reducing power method. Each absorbance value represented the average of triplicates of different

samples analyzed. Increase in the absorbance at 700 nm indicates the reducing power.

3.7 Role of PQQ in plant growth promotion

Pseudomonas strains and their knockout pqqC mutants were tested for plant growth

promotion in vitro using lettuce plant model and in vivo using bean, tomato and rice model as

described below:

3.7.1 In vitro effect of pqqC mutation on lettuce root length

All mutated strains (P. fluorescens CMR12a-3, P. fluorescens QAU67-14, P. putida

QAU90-4 and Pseudomonas sp. QAU92-2) for pqqC locus showed a marked effect on root

length of lettuce assessed in vitro compared to the wild type (P. fluorescens CMR12a, P.

fluorescens QAU67, P. putida QAU90 and Pseudomonas sp. QAU92) (Figure 3.29a).The

CMR12a showed prominent effect (10.53 cm) in root elongating as compared to its pqqC mutant

(CMR12a-3) which is about 7.82 cm. In fact, the effect of mutated strains was comparable to that

0

0.2

0.4

0.6

0.8

1

1.2

0 10 20 40 80

Ab

sorb

ance

at

70

0 n

m

Concentration ug/ml

Role of PQQ in reducing power activity

CMR12a

CMR12a-3

QAU67

QAU67-14

QAU90

QAU90-4

QAU92

QAU92-2

Chapter 3 Results


of the control (no treatment). Hence a mutation in pqqC motif has resulted in a functional

deficiency of the otherwise growth promotion by the pqq domain (Figure 3.27).

Figure 3.27: The comparison in performance of wild type (P. fluorescens CMR12a, P. putida

QAU90 and Pseudomonas sp. QAU92), their derived pqqC mutants (P. fluorescens CMR12a-3,

P. putida QAU90-4 and Pseudomonas sp. QAU92-2) and control treatments as assessed in

lettuce root length.

3.7.2 Effects of pqqC mutation: the in vivo demonstration

3.7.2.1 Bean

A comparison was made between the wild type (P. fluorescens CMR12a, P. putida

QAU90 and Pseudomonas sp. QAU92) and pqqC mutant (P. fluorescens CMR12a-3, P. putida

QAU90-4 and Pseudomonas sp. QAU92-2) but the control data is missing in this case. The data

analysis was carried out to assess the wild and mutant strains. The analysis suggested clear

difference in performance of before and after pqqC mutagenesis as may be visualized using box

plot (Figure 3.28).

The data analysed for eight different parameters using the Kruskal-Wallis statistics

revealed p value = 0.00 < 0.05=α therefore on the basis of scores, the null hypothesis (that there

was no significant difference between the treatments) is rejected (Table 3.7). Hence there exists

enough evidence to conclude that there is difference between wild and mutated strains treatments

(Figure 3.29b). The situation/ significance level did not change even upon considering their

medians. The statistical analyses thus clearly demonstrated the role of pqq in plant growth

7.15

7.65

8.15

8.65

9.15

9.65

10.15

10.65

11.15

11.65

12.15

Ro

ot

len

gth

(cm

)

Strains, Mutants and Control

Chapter 3 Results


promotions. Furthermore, same growth promotion activities of PQQ were recorded with rice and

tomato plants (data not presented).

Figure 3.28: The comparison in performance of wild type, their derived pqqC mutant strains and

control treatments as assessed in bean growth improvement in box-plot analysis. The growth

parameters PH (plant height), RL (root length), fresh weight S×R (shoot × root) and leaf area

L×W (length × width) were assessed by inoculated above mention three wild strains with their

pqqC mutants. . (CMR12; P. fluorescens CMR12a, CMRMUTAN; P. fluorescens CMR12a-3,

QAU90; P. putida QAU90, QAU90MUT; P. putida QAU90-4, QAU92; Pseudomonas sp.

QAU92 and QAU92MUT; Pseudomonas sp. QAU92-2)

Chapter 3 Results


Figure 3.29: Plant growth promotion activities of wild type and mutant strains in lettuce (in

vitro) and Bean (in vivo) (A) P. fluorescens QAU67 and its pqqC mutant (P. fluorescens

QAU67-14) with control treated Lettuce plants. (B) The P. fluorescens CMR12a and its pqqC

mutant (P. fluorescens CMR12a-3) with control treated bean plants, here only showed one

bacterial treatment for each plant.

Table 3.7: Statistical analysis of wild type and pqqC mutant strains in plant growth

promotion

Wild and

pqqC

mutated

Strains

Statistical

parametersa,b

Inoculation with Bean plants

Plant

Height Root length

Fresh weight

(S×R)

Leaf area

(L×W)

CMR12 and

CMR12a-3

Chi-Square 14.307 10.630 14.296 14.286

Df 1 1 1 1

Asymp. Sig. 0.000 0.001 0.000 0.000

QAU90 and

QAU90-4

Chi-Square 14.286 14.318 14.318 14.286

Df 1 1 1 1

Asymp. Sig. 0.000 0.000 0.000 0.000

QAU92 and

QAU92-2

Chi-Square 14.296 14.296 14.318 14.296

Df 1 1 1 1

Asymp. Sig. 0.000 0.000 0.000 0.000

Asymp. Sig (Asymptotic significance) = P-value, Df (Degree of freedom), a. Kruskal Wallis

Test, b. Grouping Variable: CLASSES, L (Length), W (Width), S (Shoot), R (Root) and *

control treatment along with wild and mutant strains.

Chapter 3 Results


3.8 Tagging of bacterial strains by Tn7-gfp mutation

The wild type (P. fluorescens CMR12a and Pseudomonas sp. QAU92) and two pqqC

mutants (P. fluorescens CMR12a-3 and Pseudomonas sp. QAU92-2) were tagged by Tn7-gfp

mutation. All four strains tagged with gfp were then confirmed by fluorescent microscopy and

further used for the root colonization of lettuce plant. At the time of disease rating, bacterial

colonization of the lettuce roots showed the presence of bacteria in rhizosphere, which confirmed

that inoculated bacterial strains have effect on plants not the environmental factors. The

Pseudomonas cells were found in great numbers colonizing the root hair zones of plants, cells

appeared as single units along the root surface and extruding the root hairs, while the distal root

parts were found poorly colonized. These observations indicated expression of tagged genes in

the lettuce roots (Figure 3.30).

Chapter 3 Results


Figure 3.30: The detection of Tn7-gfp-tagged wild type (P. fluorescens CMR12a and

Pseudomonas sp. QAU92) and two pqqC mutant (P. fluorescens CMR12a-3 and Pseudomonas

sp. QAU92-2) strains colonizing the root surface of the 7-day-old lettuce on MS medium. All

images were taken from the root and Pseudomonas cells appeared in greenish color. (A) Control

root inoculated with water under normal light without gfp, (B) Control root inoculated with

water under fluorescent light without gfp, (C) mini Tn7-gfp2-tagged P. fluorescens CMR12a

(wild type strain) inoculated root, (D) mini Tn7-gfp2-tagged P. fluorescens CMR12a-3 (pqqC

mutant strain) inoculated root, (E) mini Tn7-gfp2-tagged Pseudomonas sp. QAU92 (wild type

strain) inoculated root, (F) mini Tn7-gfp2-tagged Pseudomonas sp. QAU92-2 (pqqC mutant

strain) inoculated root.

Chapter 3 Results


3.9 Role of PQQ in plant disease control

3.9.1 In vitro antagonistic activity of bacterial strains against phytopathogenic fungi

The P. fluorescens CMR12a, P. putida QAU90 and Pseudomonas sp. QAU92 showed

significant in vitro antagonism activity against the three fungal pathogens (Rhizoctonia solani,

Fusarium solani and Pythium sp.). The P. fluorescens CMR12a and P. putida QAU90 strains

inhibited the growth of Rhizoctonia solani and Fusarium solani significantly as compared to

Pseudomonas sp. QAU92 which through inhibited the growth of these fungi but to a lesser extent

(Appendix V) and P. fluorescens QAU67 did not show antagonistic activity against any of the

fungi.

In quantitative terms, the P. putida QAU90 strain dominantly inhibited the growth of

Fusarium solani (62.5d) as compared to other strains. On the other hand, Pseudomonas sp.

QAU92 strain significantly inhibited the growth of Rhizoctonia solani (59.3f) followed by P.

fluorescens CMR12a inhibited (55g) with (0.864) least significant difference (LSD≤0.05). But

all of the strains showed almost equal inhibition capability against Pythium sp. with (0.867) least

significant difference (LSD≤0.05). The statistical analysis further confirmed that the P.

fluorescens CMR12a, P. putida QAU90 and Pseudomonas sp. QAU92 strains have good

biocontrol potential and therefore are potential candidates for plants disease control experiments

(Table 3.8).

Table 3.8: The growth inhibition (%age) of phytophathogens by antagonistic Pseudomonas

strains

Strains Rhizoctonia solani Fusarium Solani Pythium sp.

Mycelium

growth(mm) Growth

inhibition

(%)

Mycelium

growth(mm) Growth

inhibition

(%)

Mycelium

growth(mm)

Growth

inhibition

(%)

CMR12a 40b 55g 37d 55f 39c 55.6f

QAU90 45a 43.7L 30g 62.5d 35e 56.2f

QAU92 32.5g 59.3f 40c 50i 37d 53.7g

L.S.D 0.5% 0.876 0.864 0.867 0.865 0.842 0.867

Least significant difference (LSD≤0.05) was used separately to evaluate the response of each

character. Different letters indicate statistically significant differences between growth

inhibitions of fungi.

Chapter 3 Results


3.9.2 In vivo antagonistic activity of PQQ against Rhizoctonia root rot

Biocontrol of Rhizoctonia root rot of bean by Pseudomonas fluorescens CMR12a, P.

putida QAU90, Pseudomonas sp. QAU92 and their pqqC mutants P. fluorescens CMR12a-3, P.

putida QAU90-4 and Pseudomonas sp. QAU92-2 were investigated in vivo against Rhizoctonia

root rot of bean. A significant reduction in disease severity (DS) caused by R. solani on bean

plants was observed for the wild-type strains Pseudomonas CMR12a, QAU90, QAU92 but the

pqqC mutants showed only a reduced potential of the disease control (Figure 3.31).

The P. fluorescens CMR12a inoculated to a moderately aggressive isolate of R. solani

AG 2-2 caused a reduction in disease severity (DS) from ≈4.2 ± 1.2 to 0.9 ± 0.9. P. putida

QAU90 caused a comparable reduction in DS from ≈3.7 ± 0.7 to 1.1 ± 1.0; while Pseudomonas

sp. QAU92 reduced DS from ≈4.0 ± 0.9 to 1.4 ± 1.2 (P = 0.000). Treatments with the mutant

strains performed significantly worse. The CMR12a-3 and QAU90-4 mutants, deficient in PQQ

production, demonstrated a complete loss in bio-control capacity and the DS for these strains

very near to that of the control but the mutant QAU92-2 still possessed a little biocontrol activity

but not as shown by the wild type strain. This numerical data described here are valid for 1st trial

of bacterial count in root colonization (Table 3.9) and 2nd trial also yielded similar results.

The miniTn7-gfp labeled wild type (P. fluorescens CMR12a and Pseudomonas sp.

QAU92) and pqqC mutant strains (P. fluorescens CMR12a-3 and Pseudomonas sp. QAU92-2)

count revealed differences in bacterial populations on the roots (Table 3.9). Bacterial

concentrations observed for the parental strain and the mutants were variable among treatments

and repetitions in time. However, the concentration factor did not influence the disease-

suppressive capacity, suggesting that root colonization was sufficiently high for optimal

biological control. The two mutants P. fluorescens CMR12a-3a and P. putida QAU92-2, lacking

pqq, predominantly had the lowest bacterial root concentration and subsequent root colonization.

Chapter 3 Results


Figure 3.31: In vivo antagonistic activity of pseudomonad and their pqqC mutant strains against

R. solani AG2-2. (A) P. fluorescens CMR12a and its pqqC mutant P. fluorescens CMR12a-3

with disease control plant , (B) P. putida QAU90 and its pqqC mutant P. putida QAU90-4 with

disease control plant and (C) Pseudomonas sp. QAU92 and its pqqC mutant Pseudomonas sp.

QAU92-2 with disease control plant.

Chapter 3 Results


Table 3.9: Root colonization data for non-washed bacteria of Pseudomonas CMR12a and

QAU92 and mutants CMR12a-3 and QAU92-2 in the absence of Rhizoctonia solani or after

inoculation with R. solani anastomosis group (AG) 2-2

Strain names 1st trial 2nd trial

1 CMR12a 6.81± 0.39a 6.31± 0.47b

2 CMR12a-3 5.38± 0.31c 5.53± 0.37c

3 QAU92 6.41± 0.42b 6.89± 0.24a

4 QAU92-2 5.21± 0.35c 5.61± 0.35c

The root colonization data represented as averages ± standard deviations of two replicates per

treatment. Different letters indicate statistically significant difference between treatments by

Kruskal-Wallis and Mann-Whitney nonparametric tests (α = 0.05).

3.10 PQQ and Induced systemic resistance (ISR) in rice

3.10.1 Pseudomonas CMR12a and QAU92 trigger JA/ET signaling pathways

The hormone signaling pathways following the treatment with Pseudomonas CMR12a

and CMR12a-3 mutant supernatant, expression of JA marker genes JiOsPR10 and JAMYB was

recorded as 3 and 7-fold by infected control plants, 3 and 10-fold by pqqC mutant (P. fluorescens

CMR12a-3) inoculated plants as compared to wild type (P. fluorescens CMR12a) which has

higher expression about 8 and 36-fold at 6 hpi, respectively (Figure 3.32 A, B). Under similar

conditions, the ET-related gene EBP89 showed an 6-fold expression by infected control plants,

10-fold expression by pqqC mutant (P. fluorescens CMR12a-3) inoculated plants and up-

regulation of wild type (P. fluorescens CMR12a) which expressed about 24-fold at 6 hpi (Figure

3.32 C). Together these results suggested that pqq genes of CMR12a have resulted in activation

of JA and ET pathways while pqq deletion mutant (CMR12a-3) was unable to activate the

hormone up to the level of wild type P. fluorescens strain CMR12a.

Similarly, the quantitative reverse transcription analysis revealed an accumulation of JA

transcripts upon treatment with Pseudomonas sp. QAU92 supernatant (Figure 3.32 A and B) not

as much as with pqqC mutant Pseudomonas sp. QAU92-2 supernatant. The application of

QAU92 supernatant entailed a fast and strong accumulation of JiOsPR10, with mRNA levels

peaking at 1 hpi as 3 fold found in mock-inoculated controls, 7-fold in pqqC mutant (QAU92-2)

and 15-fold upregulated with wild type (QAU92).

The use of QAU92 supernatant also induced a strong (11-fold) up-regulation of EBP89

(Figure 3.32C) gene expression than control and pqqC mutant strain, while much weaker

Chapter 3 Results


changes were observed in response to EBP89 at 1 and 3 hpi than mock control. These changes

indicate that PQQ produced in the LB broth-culture by the strain QAU92 triggered the JA/ET

signaling pathways.

Figure 3.32: Expression of hormone marker genes in rice cell cultures treated with supernatant

of P. fluorescens CMR12a, Pseudomonas sp. QAU92 and their pqqC mutant (P. fluorescens

CMR12a-3, Pseudomonas sp. QAU92-2). Supernatant of Pseudomonas bacteria grown in LB

broth was applied to 5-days-old rice cell suspension cultures. Control samples were treated with

LB only. At different time points after inoculation (1, 3 and 6 hours), cell cultures were

harvested and subjected to quantitative RT-PCR analysis for the following transcripts: (A)

JiOsPR10, (B) JAMYB and (C) EBP89. Actin (Os03g071810) was used as an internal reference

to normalize the gene expression levels and calculated relative to the expression in mock-treated

control cells at 1, 3 and 6 hour. Data presented are means and standard error of two replicates

from a representative experiment.

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Chapter 3 Results


3.10.2 Induced Resistance against Cochliobolus miyabeanus in Rice

The PQQ based induced resistance in rice (Oryza sativa indica cv CO39) was assessed

against C. miyabeanus strain Cm988 using wild type (P. fluorescens CMR12a, Pseudomonas sp.

QAU92) and their pqqC mutants (P. fluorescens CMR12a-3 and Pseudomonas sp. QAU92-2).

The analysis showed clear differences in resistance against C. miyabeanus disease induced by

wild type strains as compared to the pqqC mutants. Gene expression in control, mock control and

bacteria-treated samples was articulated as a ratio to actin or eukaryotic translation elongation

factor 1A (eEF1a) expression using the measured efficiency for each gene by RT-PCR. Based on

the expression of reference genes (actin and eEF1a), the ct value of Eef1a fluctuated more than

the actin gene, therefore actin was chosen as reference gene.

3.10.2.1 EBP89 susceptible gene expression analysis

Ethylene-responsive TF 89 (EBP89), a susceptible gene used as a reference, was up

regulated in infected control plants than in mock treatment, suggesting the infection prone nature

of plants. It was further observed that the EBP89 manifested a 21 and 18 fold higher expressions

in infected control plants than in mock control plants after 36 and 48 hours post inoculation

(hpi), respectively (Figure 3.34). For both the wild type strains and pqq mutant strains, it showed

less susceptibility to pathogen than the control plants, depicting resistance to the pathogen. All

mutants showed susceptibility to pathogen than wild type strains. The results of disease

susceptibility in two biological repeats were same but the expression was much higher in the 2nd

biological repeat (Figure 3.33 & 3.34).

The EBP89 expression responded strongly to pathogen infection in infected control

plants and pqqC mutants than both wild-types, resulting in the expression of approximately 21-

fold by infected control plants, 17-fold by pqqC mutant (P. fluorescens CMR12a-3) plants as

compared to wild type (P. fluorescens CMR12a) which respond only 5 fold at 36 hpi and 19-fold

induction by infected control plants, 17-fold induction by pqqC mutant (P. fluorescens CMR12a-

3) as compared to the wild type (P. fluorescens CMR12a) which induced only 4-fold at 48 hpi in

2nd biological repeat (Figure 3.34). However, suppression of Cm988-induced EBP89 expression

resulting from wild-type (Pseudomonas sp. QAU92) plants was higher than pqqC mutant

(Pseudomonas sp. QAU92-2) in two biological repeats. In the light of these results, it is

Chapter 3 Results


interpreted that pqq induced resistance against C. miyabeanus in wild type inoculated plants was

higher than pqq deleted mutant plants.

3.10.2.2 PR1a (pathogenesis-related protein 1a gene) expression analysis

The PR1a is a dephosphorylation mediated pathogenesis-related protein 1a (PR1a).

Expression of PR proteins is generally pathogen and host specific. The expression of PR1a gene

was much higher in infected control and pqqC mutant plant than in wild type inoculated plants,

resulting in an approximately 47-fold induction by infected control plants, 41-fold induction by

pqqC mutant (P. fluorescens CMR12a-3) inoculated plants as compared to wild type (P.

fluorescens CMR12a) which induced 8-fold at 36 hpi in 2nd biological repeat (Figure 3.36). In 1st

biological repeat similar results were revealed for CMR-12a (Figure 3.35).

However, suppression of Cm988-induced PR1a expression resulting from wild-type

(Pseudomonas sp. QAU92) plants was higher than pqqC mutant (Pseudomonas sp. QAU92-2) in

two biological repeats at all observation points (12h, 24h, 36h and 48h hpi). An approximately

47-fold induction by infected control plants, 39-fold induction by pqqC mutant (Pseudomonas

sp. QAU92-2) inoculated plants as the wild type (Pseudomonas sp. QAU92) induced about 15-

fold at 36 hpi and 46-fold induction by infected control plants, 37-fold induction by pqqC mutant

(Pseudomonas sp. QAU92-2) and wild type (Pseudomonas sp. QAU92) showed 17-fold

induction at 48 hpi in the 2nd biological repeat (Figure 3.36). Hence the PQQ induced resistance

against C. miyabeanus in wild type inoculated plants was recorded higher as compared to pqq

deleted mutant plants. The OsPR1a gene selected here clearly up-regulated in a compatible C.

miyabeanus fungus interaction, indicating that the pqq gene has effect in suppressing the disease.

Chapter 3 Results


Figure 3.33: Role of PQQ in induced systemic resistance of rice against C. miyabeanus by genetic expression of EBP89 gene with

reference to actin in P. fluorescens CMR12a, Pseudomonas sp. QAU92 and their pqqC mutants P. fluorescens CMR12a-3 and

Pseudomonas sp. QAU92-2 in 1st biological repeat. (12a, 92W; wild type strains, 12a-3M, 92-2M; pqqC mutant strains, 1st (12); time

point after 12 hpi, 2nd (24); time point after 24 hpi, 3rd (36); time point after 36 hpi and 4th (48); time point after 48 hpi, m; mock


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PQQ gene expression by EBP89 gene (1st biological repeat)EBP89 gene expression

Chapter 3 Results


Figure 3.34: Role of PQQ in induced systemic resistance of rice against C. miyabeanus by genetic expression of EBP89 gene with


Pseudomonas sp. QAU92-2 in 2nd biological repeat. (12a, 92W; wild type strains, 12a-3M, 92-2M; pqqC mutant strains, 1st (12); time



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Chapter 3 Results


Figure 3.35: Role of PQQ in induced systemic resistance of rice against C. miyabeanus by genetic expression of PR1a gene with





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Chapter 3 Results


Figure 3.36: Role of PQQ in induced systemic resistance of rice against C. miyabeanus by genetic expression of PR1a gene with





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Chapter 3 Results


CHAPTER 4

Discussion

Microbial diversity plays a vital role in maintaining ecosystem especially the

physiological functioning and in sustaining the producers. Therefore, recent research in the areas

of plant-microbe interaction (Hooper and Gordon, 2001) reveals a tangible role of microbes and

its application in the fields of biofertilizer, biofilming, bioinoculant & bioprocessing, phosphate

solubilization, nitrogen fixation, induced systematic resistance and plant growth promotion

(Hayat et al., 2010; Berg, 2009; Choi et al., 2008; Rodriguez et al., 2004; Bloemberg and

Lugtenberg, 2001). The biologically controlled systems for example the plant growth promotion

has a far better impact on plant health and is environmentally safe as opposed to the application

of chemical fertilizer for the same purpose (Gerhardson, 2002, Postma, et al., 2003; Welbaum,

2004). However, it requires not only an optimized system, but also a better understanding of the

underlying genetics that reserves the control of such natural systems.

Therefore, the focus of present study was to explore the role of Pyrroloquinoline quinone

(PQQ) dependent glucose dehydrogenase (GDH) in phosphate solubilization, antioxidant

activity, plant growth promotion, plant disease control and induced systemic resistance (ISR).

This was achieved by inducing mutagenesis of gdh genes caused by Tn5 transposon insertion as

well as the knock out site directed mutagenesis of pqqC to study the exact mechanism involved

in plant growth promotion. Furthermore, the first detailed structural characterization of GDH was

carried out using bioinformatics tools enabling prediction of the PQQ dependent GDH

mechanism for the said activities.

4.1 Biochemical and Physiological characterization and phenotypic diversity

The studied isolates belong to three major families of bacteria which perform multiple

functions such as a role in plant growth promotion, gauged through their phosphate solubilizing

efficiency and presence of pqq and gdh loci (Gyaneshwar et al., 1998). Such capability has also

been reported in Pseudomonas aeruginosa (Midgley and Dawes, 1973) and Enterobacter

asturiae (Tripura et al., 2007).

Chapter 4 Discussion

“Genetic Expression and Bioinformatics of PQQ dependent glucose dehydrogenase (GDH) and Probing its Role in Plants”. 111

It was previously reported that bacterial strains showing catalase activity must be highly

resistant to environmental, mechanical and chemical stresses; enhance the growth, seed

emergence, crop yield and contributes to the protection of plants against pathogens and pests

(Dey et al., 2004; Herman et al., 2008; Kloepper et al., 2004; Minorsky, 2008; Kokalis-Burelle

et al., 2006). In the present study all isolates (rhizobacteria and root nodulating) tested for

catalase production showed positive results (Appendix Q). Therefore these isolates would

potentially be highly capable of the above mention traits. Later analysis proved this to be true for

the Pseudomonas stains studied in detail. Furthermore, two of the Pseudomonas strains QAU67

and QAU90 produced acyl homoserine lactone (AHL) and depicted their possible role in plant

growth promotion and disease control. Diggle et al. (2007) stated that sensing the “signal

molecule” or AHL produced by bacteria in tomato rhizosphere, increased the salicylic acid

production in leaves, and enhanced the systemic resistance of Serratia liquefaciens MG1

inoculated tomato plants against the fungal leaf pathogen Alternaria alternata (Schuhegger et al.,

2006).

Some of the isolates also revealed other unique characteristics for instance the production of

siderophore (data not shown here) which is an iron chelating molecule and plays an important

role in supply of iron to the cell ultimately affecting the plant growth promotion. One of the

isolates P. fluorescens QAU67 has shown this potential. The siderophores production in plants

and plant-associated microorganisms was originally reported by Loper and Buyer (1991), who

described its role in plant-microbe interactions and plant-pathogen interactions and hence was

consider as a major factor in the biological control (Leong, 1989). The role of siderophore in

plant growth promotion has been reported in P. aeruginosa (Höfte et al., 1991) and in P.

fluorescens (Sokol, 1992). The production of siderophores one of isolates in the present study

indicated its possible potential in plant growth promotion.

Similarly, the P. putida QAU90 and Pseudomonas sp. QAU92 produced bio-surfactants

(lipopeptides). This indicated the possible role of these strains in the biological control of R.

solani root rot. Previously Perneel et al. (2007) reported that P. fluorescens CMR12a produced

phenazines and biosurfactants which were the key factors in the biological control of cocoyam

root rot. The subsequent analysis endorsed the biological control of P. putida QAU90 and



Pseudomonas sp. QAU92 towards R. solani. This study therefore, provides evidence of diverse

morphological, physiological and biochemical behavior in the isolated strains.

4.2 Molecular identification and genetic diversity

The identification of microbes under study remains a fundamental yet tricky task and

usually done through amplifying conserved loci. The molecular phylogeny thus constructed

extends our knowledge regarding organismic relationship and provides the foundation for

accurate identification (Singh et al., 2007). One of the most widely used locus has been the 16S

rRNA gene sequences (Woese and Fox, 1977). For the present study, amplification of 16S rRNA

revealed diverse pool of isolates (as anticipated since taken from different sites). The analysis

revealed representatives of Bacillus, Pseudomonas, Rhizobium, Enterobacter etc. much the same

as previously reported (Whitelaw, 2000).

The 16S rRNA gene sequences as assessed for sequence homology with those available

at NCBI. A rationale used is that the bacterial strains with similarity less than 97% can be

declared as novel after complete taxonomic characterization (Lim et al., 2006). In the present

study, the 16S rRNA sequence homology for some strains was found low as compared to the

already submitted sequences at NCBI. For instance, 97% homology of QAU63 with Bacillus sp.

represented a border line case considering the above rationale while the homology score for

QAU68 was only 95% with Bacillus, and suggested its novel nature. However, later analyses

with other loci evidently disproved this notion. Hence the identification and phylogeny

construction should be done cautiously. Furthermore, one of the isolates QAU92 showed 89%

homology with Pseudomonas putida, a level much lower than the threshold thus pointing to its

possible novel status.

Employing alternative analysis to 16S rRNA often provides complementary information

necessary for reliable assignment of isolated strains to their taxonomic groups. Although, the

identification based on 16S rRNA gene sequences is considered as the gold standard for

estimating phylogenetic diversity in microbial populations (Lane et al., 1985; Ward et al., 1990

and Hugenholtz et al., 1998) yet it also revealed lack of variability and remained limited in

identification of closely related species (or subspecies). In the present study, the strain QAU67

showed maximum similarity (99%) with Pseudomonas moorei RW10 T as revealed in the



phylogenetic analysis based on 16S rRNA gene sequences and was deemed related to the P.

jessenii subgroup. The housekeeping gene/MLSA analysis revealed QAU67 as closely related to

P. mohni, based on the rpoB which is the subgroup of P. fluorescens. The rpoD based analysis

revealed 95% neighboring with P. mohni and recA analysis showed 96% neighboring with

Pseudomonas fluorescens strain SF4c. From these results it is clear that the strain QAU67

belonged to P. mohni rather than P. moorei. Therefore considering the consensus among

housekeeping gene analysis, facilitated the species identifications especially the closely related

species or subspecies. It has been previously deliberated that careful use of housekeeping gene

sequence analysis may surpass the accuracy of DNA–DNA hybridization for quantification of

genome relatedness and novel species identification (Zeigler, 2003). The strain QAU92 that

showed 89% homology in the earlier analysis and also revealed low level homology and a poor

bootstrap value with loci used in MLSA, thus endorsing its novel nature. However, it is

important to mention that its novel status requires complete taxonomic characterization (Lim et

al., 2006), which is in progress.

4.3 New insight for Plant-microbe association

The plant microbe interaction is a developing area of research, therefore reporting novel

strains and novel association is a common place. Recently, Sphingobacterium pakistanensis sp.

nov., has been reported as a novel species (Ahmed et al., 2014). Similarly some examples of

novel plant microbe associations are: Bacillus with Gossypium hirsutum (Saharan and Nehra,

2011); Ensifer sp. with other plants (Degefu et al., 2012) and Penibaccilus sp. with Trifolium

pretense (Latif et al., 2013). One such example from the present study is the novel association

found for Leclercia sp. QAU66 with Vigna mungo, which is reported here for the first time under

subtropical conditions (Naveed et al., 2014). It is also intriguing to note that this species was

previously known as a human pathogen (Brenner et al., 1986). Furthermore, the QAU53 and

QAU56 (both identified as Ensifer arboris) have been found associated with Melilotus indicus

and Crotalaria medicaginea respectively. Therefore the present and previous all such studies

remain useful for understanding the plant microbe-interaction better than ever before and also in

planning future studies meant to harness the potentials of these diverse natural resources.



4.4 Bioinformatics reveals structure characterization of PQQ dependent GDH

Bioinformatics has a lead role in structure based functional determination, gene

expression, ligands binding sites and phylogenetic analysis of proteins (Shen et al., 2012). In this

study, various bioinformatics tools have been used to characterize the glucose dehydrogenase of

Leclercia sp. QAU66, P. fluorescens CMR12a, P. putida QAU90 and pseudomonas sp. QAU92

for physic-chemical properties, structure based functional predictions, ligand binding and active

site predictions, homology modeling and functional domains prediction. Hydropathicity grand

average score (GRAVY) showed negative value for all strains indicating that all GDH proteins

have more hydrophilic residues and exposed to the surface of the protein and hence potentially

antigenic (Kyte and Doolittle, 1982) which depicts its catalytic activity

The glucose dehydrogenase putative proteins have c-terminal PQQ domain and n-

terminal domain having a transmembrane α-helix with β−strands which anchor the protein in cell

membrane. A similar concept was earlier described by Yamada et al. (1993) that GDHs

anchorage in membrane was due to five transmembrane segments n-terminal hydrophobic

domain whereas the catalytic activity was because of conserved pyrroloquinoline quinone (PQQ)

on c-terminal. The secondary structure of GDH proteins of P. fluorescens CMR12a, P. putida

QAU90 and Pseudomonas sp. QAU92 also possessed five transmembrane helices and PQQ on c-

terminal (Figure 3.16). Chen et al., (2002) determined the conserved nature of PQQ domain in

alcohol dehydrogenase (ADH) protein of Pseudomonas putida HK5 and has catalytic activity for

the production of gluconic acid. Leclercia sp. QAU66, P. fluorescens CMR12a, P. putida

QAU90 and Pseudomonas sp. QAU92 GDH have similar conserved PQQ repetitive domains

suggesting its activity in conversion of glucose into gluconic acid.

The overall structure and position of GDH protein domains revealed the presence of

excessive β-strands in secondary structure, maximum in P. putida QAU90 (70.7%) which

depicted its resemblance with 8 propeller β-strand like structure described for alcohol

dehydrogenase (ADH) (Chen et al., 2002). Pfam, a comprehensive collection of protein domains

and families (Bateman et al., 2004), was used to differentiate homologues sharing of GDH

domain with same function from those that have divergent function in different Pfam families.



In Leclercia sp. QAU66 the GDH protein showed structural homology with

Quinohemoprotein alcohol dehydrogenase (ADH) template (1yiqA1) with TM-score of 0.800,

which further confirmed the gene ontology (biological, molecular and cellular functions) of

QAU66 GDH resembling that of ADH protein of P. putida (Chen et al., 2002). The structural

homology of GDH of Pseudomonas strains also showed good TM score with already reported

proteins (Figure 3.14). However GDH characterized for Pseudomonas sp. QAU92 showed

similarity with Apo dipeptidyl peptidase with 0.36 TM score, not enough to predict a protein and

possibly contains novel sequences having poor homology with template model.

4.5. Mutagenesis revealed complementary role of pqq and gdh

4.5.1 Role of gdh in plant growth promotion

Several bacteria but with exceptions, secrete organic acid in rhizosphere and

consequently results in phosphate solubilization from insoluble complexes, a form that readily

becomes available to plants (Richardson et al., 2009). This process takes place as result of

oxidation of a carbon source such as glucose or alcohol into gluconic acid either through

membrane bound glucose dehydrogenase (GDH) or alcohol dehydrogenase ADH (Gyaneshwar

et al., 1998; Chen et al., 2002). Generally the Pakistani soil is either calcareous or sodic in

nature, with pH around 8.0 or 10 respectively. Under these conditions, most of the bacterial

isolates that belong to family: Bacillaceae, Enterobacteriacae, Rhizobiaceae or

Pseudomonadaceae (Ahmad et al., 1993) carry out the essential business of phosphate

solubilization. Hence, these types are well placed considering their capability, thus calibrating

the soil pH by 3 to 6 folds.

The screening of isolates revealed most promising phosphate solubilizers based on clear

halo zone formation on Pikovskaya's medium. These isolates belonged to Enterobacter and

Pseudomonas genus. These strains also possessed gdh loci in their genome (Table 3.1). The

capability to bring insoluble phosphate into bioavailable form was revealed by various

rhizosphere bacteria like Bacillus, Enterobacter and Pseudomonas (Richardson et al., 2009) and

this process is due to gdh gene which is conserved in these bacterial families (Tripura et al.,

2007).



The oxidation of glucose into gluconic acid by glucose dehydrogenase (GDH) involves

production of acid in the periplasmic space, hence such organisms render the medium acidic, a

situation just right for the process of phosphate solubilization (Duine et al., 1979). In the present

study this basic rationale was applied to screen those with such a capability. In most of the

strains under study, the pH of the medium dropped from an initial pH value of 7.0 for instance to

4.11 in the case of QAU92. This indirectly depicts the conversion of glucose into gluconic acid

and a possible presence of gdh. Similar study was reported by Moghimi et al. (1978), the

inorganic phosphate solubilized at acidic medium by gdh and gluconic acid released in wheat

roots by rhizobacteria was the main phosphate solubilizing compound.

To endorse this further, the Tn5 derived gdh mutant (QAU90-23) when assessed for its

capacity to solubilize phosphate clearly demonstrated a positive role of gdh in P. putida QAU90.

Furthermore, the above mention gdh mutant could not perform its role in growth promotion in

bean while the wild type was quite capable for it (Figure 3.20). This evidently suggests that

glucose dehydrogenase (GDH) plays an important role in phosphate solubilization and

consequently plant growth promotion. There are only few studies reporting the gdh role in plant

growth promotion, therefore, the present study is one of the few studies probing the role of gdh

in phosphate solubilization and consequently in plant growth promotion.

4.5.2 Multiple roles of PQQ in plants

Although PQQ has been reported in several bacterial genera, there are certain species that

live in anaerobic environments and do not use glucose as carbon source. These bacteria produce

PQQ-dependent GDH but not the PQQ cofactor. The role of PQQ as cofactor is so important that

the GDH enzyme remains inactive (Adamovicz et al., 1991). The majority of Pseudomonas

species (like P. fluorescens) is strictly aerobic in nature and glucose oxidizer (Choi et al., 2008).

Such bacterial strains produce PQQ dependent GDH and thus PQQ remains active in such cases.

The Pseudomonas strains QAU67 and QAU90 in the present study were also strictly aerobic in

nature and glucose oxidizers as revealed in the carbon source utilization test. However

exceptions were also observed for instance, CMR12a utilized ethanol as the carbon source rather

than glucose but QAU92 behaved totally differently and have oxidized glycerol and ethanol

(Figure: 3.24). These strains also have glucose dehydrogenase in their genomes as confirmed by

PCR amplification of gdh genes.



The biochemical characterization has been very useful for evaluation of the bacterial

bionetwork as well as the identification. Furthermore, kits are available for reliable bacterial

identification based on the biochemical analysis and API-20E system has been found suitable for

the identification of enteric bacteria and non-fastidious and Gram-negative rods (Thaochan et al.,

2010). The idea to use API-20E system for the biochemical characterization of pqqC mutant and

wild type strains due to its effectiveness. Deciphering their role through comparing the wild type

and pqqC mutants in biochemical utilization of carbon, nitrogen sources and enzymatic action,

which depicted that PQQ has effect on processes like fermentation and oxidation-reduction

(Figure: 3.23). The analysis also revealed an exceptional case in QAU67. The QAU67-14 mutant

instead of losing its capacity upregulated the process, this could probably be attributed to its

siderophore production.

To an extent, PQQ’s role is connected to the uptake of phosphate via plants, as a cofactor

for rhizobacteria dehydrogenases, the PQQ aids in making the soil and the surrounding

environment acidic (Rodriguez et al., 2001) and consequently more phosphate would be

available to plants. After the pqqC deletion, the mutant strains (P. fluorescens CMR12a-3, P.

putida QAU90-4 and Pseudomonas sp. QAU92-2) lost their ability to solubilize phosphate in

vitro and also their ability to acidify the medium (Figure 3.22). The maximum difference in

acidification of the medium was observed in case of P. putida QAU90 and its pqqC mutant (P.

putida QAU90-4), depicting that the PQQ dependent glucose dehydrogenase (GDH) functioned

in wild type as compared to that in mutants. The present study confirmed that after mutation in

pqq and gdh genes stopped the phosphate solubilization activity and plant growth promotion a by

mutant as compared to wild type strains.

Previously, it was recorded that PQQ enhanced pollen germination in vitro in the plant

species Tulipa, Lilium and Camellia (Xiong et al., 1988, 1990), but the mechanism remains

unclear. The present study provided an evidence that PQQ is a plant growth promoting factor as

evident through comparison of such activity in wild type Pseudomonas strains and loss of such

activity in the pqqC mutants, both in vitro with lettuce as well as in vivo in bean, tomato and rice.

A significant difference (p<0.05) has been revealed for plant height, shoot length, dry weight,

root weight and total number of leaves in the wild type strains with the pqqC mutants (Table 3.7)

and showed that the plant growth promotion is mediated by PQQ. It is anticipated that this will



enrich our present understanding of plant growth promotion mechanism. The PQQ synthesized

from P. fluorescens B16 has been reported as growth promoter in tomato, cucumber, Arabidopsis

and hot pepper (Choi et al., 2008).

PQQ acts as a plant growth promoting factor due to its antioxidant activity. Nonetheless,

it cannot be left out that this effect is indirect because PQQ serves as cofactor for numerous

enzymes, thus promoting the induced systemic resistance and antifungal activity (Choi et al.,

2008). The maximum DPPH scavenging activity was observed for Pseudomonas sp. QAU92 as

compared to its pqqC deletion mutants QU92-2 (Figure 3.25). It was obvious that PQQ showed

the proton-donating capability and assisted as free radical scavenger, acting possibly as primary

antioxidant. PQQ functions to scavenge reactive oxygen species (ROS) as has been reported

previously in Escherichia coli (Misra et al., 2004) and only widely considered.

4.6 The antagonistic activity of PQQ

4.6.1 PQQ’s role in disease control

The P. putida QAU90 and Pseudomonas sp. QAU92 produced biosurfactant

(lipopeptides) also showed biological control of R. solani root rot. Previously Perneel et al.

(2007) reported that P. fluorescens CMR12a produced phenazines and bio-surfactants which

were a vital factor in the biological control of cocoyam root rot, suggesting a strong antagonistic

potential of this bacterial strain towards R. solani. The reduced antifungal capacity and plant

growth promotion might be due to low acid production by the pqqC mutants as compared to wild

type strains and further suggested the possible control of PQQ over such a process.

The pBKminiTn7- gfp2 tagging system revealed successful root colonization in lettuce

by the Pseudomonas CMR12a and QAU92 which colonized the root hair zone of plant. This

clearly indicated the expression of this gene in lettuce roots (Figure 3.30). This system has been

useful in environmental studies, disease control, addressing the gene expression and population

dynamics in plants rhizosphere (Koch et al., 2001). To be an active PGPR, an organism must be

capable of colonizing roots because the organism must establish itself in the rhizosphere at

population densities enough to produce a beneficial effect. The previously reported failures in

plant growth promotion studies under field conditions have often been associated with poor root

colonization (Bloemberg and Lutenberg, 2001). We report here that the plant growth promotion



by pqqC mutants (CMR12a-3 and QAU92-2) maintained the capability to colonize roots which

advocated that additional factors beyond root colonization are involved in plant growth

promotion. These recognize a new plant growth promotion factor PQQ from P. fluorescens

CMR12a and Pseudomonas sp. QAU92, also producing lipopeptides. The root colonization may

be influenced by production of lipopeptides of both strains because rhizosphere competence of

biosurfactant was increased (D’aes et al., 2011). Numerous studies have accredited the

importance of lipopeptides for bacterial motility and root colonization, which are crucial features

of biocontrol agents often the soil borne pathogens (Andersen et al., 2003; Tran et al., 2007,

Perneel et al., 2008).

4.6.2 PQQ role in Induced systemic resistance (ISR)

The first line of plant defense gets activated upon pathogen recognition which results in a

basal level of immunity (Pieterse et al., 2009) and plants can also support a non-specific

systemic resistance response that is operative against future pathogen attack. When PGPR

colonize the host roots, it leads to Induced Systemic Resistance (ISR) (Van Loon et al., 1998).

The expression of pathogenesis related (PR) protein is generally pathogen and host specific. In

rice it has shown infection with C. miyabeanus inducing the transient expression of PR1a. The

expression level of PR1a gene was approximately 47-fold induction by infected control plants

and 41-fold induction by pqqC mutant (P. fluorescens CMR12a-3) plants but only 8-fold

induction recorded by wild type (P. fluorescens CMR12a) at 36 hpi (Figure 3.36).

Studies in rice and Arabidopsis have revealed that rhizobacterial-mediated ISR functions

with components of ethylene (ET) and jasmonic acid (JA) response pathways and are

independent of salicylic acid (SA) (Pieterse et al., 1998; Verhagen et al., 2004; De

Vleesschauwer et al., 2008; De Vleesschauwer and Höfte, 2009). The expression of JA marker

genes JiOsPR10 and JAMYB responded strongly to CMR12a and QAU92 treatment compared to

the pqqC mutant (CMR12a-3 and QAU92). At the same time point and for the same treatment,

the ET-related gene EBP89 showed up-regulation over mock-treated controls and pqqC mutant

(Figure 3.32C). Together these results suggested that pqq genes of CMR12a in LB broth has

resulted in activation of mainly JA and ET pathways while pqq deletion mutant (CMR12a-3)

were unable to activate the hormone up to the level of wild type P. fluorescens CMR12a.



Interestingly, both pqqA and pqqB mutants of E. intermedium lost the bio-control

capability as well as their capacity to upsurge the systemic resistance against Magnaporthe

grisea KI-409, a rice pathogen. This suggested the contribution of PQQ in antifungal activity,

MPS and in elaboration of induced systemic resistance (Han et al., 2008). As clear difference in

expression of ET-related gene EBP89 and JA marker genes JiOsPR10 PR1a gene and JAMYB

between wild type (P. fluorescens CMR12a and Pseudomonas sp. QAU92) and pqqC mutant (P.

fluorescens CMR12a-3and Pseudomonas sp. QAU92-2) strains depicted a fundamental role of

PQQ in induced systemic resistance in rice against C. miyabeanus and in bean against R. solani

root rot.



Conclusions

The morphological and biochemical characterization revealed phenotypic diversity

among isolates. Furthermore, the isolates QAU90 and QAU92 were characterized as

exhibiting good biocontrol, aggressive antagonistic activity, phosphate solubilization,

catalase production, lipopeptides production and plant growth promotion.

The 16S rRNA gene sequencing and the multilocus sequence analysis (MLSA) not only

reliably marked the identification, but also suggested diverse array of bacterial isolates.

Low bootstrap support in the phylogenetic analysis based on the rpoB, rpoD and recA as

well as the 16S rRNA loci suggested that the QAU92 is potentially a novel strain. It also

showed distinct biochemical behavior.

Glucose dehydrogenase (GDH) of Leclercia sp. QAU66 is a main factor in plant growth

promotion being involved in direct oxidation of glucose into gluconic acid.

P. fluorescens CMR12a has shown its extended potential as phosphate solubilizer and

plant growth promotion as compared to other strains, a trait attributed to presence of extra

copies of pqqB and pqqF genes in its operon.

P. fluorescens QAU67 and P. putida QAU90 used glucose as carbon source, depicting

PQQ as the cofactor of glucose dehydrogenase while P. fluorescens CMR12a and

Pseudomonas sp. QAU92 used glycerol and methanol as carbon source depicting PQQ as

cofactor of alcohol dehydrogenase.

Bioinformatics analyses structurally confirmed the catalytic activity of PQQ as ligand to

GDH and elaborated its role in phosphate solubilization.

Bioinformatic also predicted the physico-chemical properties, structure based function

predictions, prediction of functional residues, ligand binding and active site predictions,

homology modeling and functional domains of PQQ dependent glucose dehydrogenase

(GDH).

Mutagenesis revealed the mechanism and role of PQQ dependent glucose dehydrogenase

(GDH) in phosphate solubilization, plant growth promotion and its role in plant disease

control

P. putida QAU90 revealed its role in growth promotion activities of Phaseolus vulgaris

based on itsTn5 based gdh mutant



PQQ plays a pivotal role in phosphate solubilization, antioxidant activity, plant growth

promotion, plant disease control and induced systemic resistance in plants

Results of mutagenesis revealed that PQQ control the function of Glucose

dehydrogenases and PQQ is a novel marker for Pseudomonas identification

Root colonization test of wild type and pqqC mutants suggested PQQ’s role in disease

control of R. solani root rot in bean and lettuce.

The qRT-PCR based gene expression analysis depicted role of PQQ in inducing systemic

resistance (ISR) in rice against C. miyabeanus.



Future recommendations

The Pseudomonas strains may be used as bio-control agents as well as biofertilizer in

areas with low phosphate availability.

The presence of an extra copy of pqqB and pqqF genes in P. fluorescens CMR12a along

with glucose dehydrogenase enabled this strain to act as super phosphate solubilizer. This

hypothesis will further be tested.

All pqq genes will further be probed for their role in PQQ biosynthesis pathway.

The structural model of GDH will further be studied for protein docking analysis.

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Appendix


Appendix A: Collection of samples

Sr. No Common name Botanical name collection Area

Rhizosphere Samples

1

2

Wheat

Maize

Triticum astivum

Zea mays

Gujrat

Multan

2 Cotton Gossypium sp. Multan

3 Pea Pisum sativum Islamabad

4 Cotton Gossypium hirsutum Jakababad

5 Tomato Lycopersicon esculentum Jakababad

6 Rice Oryza sativa Gujranwala

7 Mung Vigna mungo Islamabad

8 Rice Oryza sativa Mianwali

9 Wheat Triticum astivum Gujranwala

10 Worm wood Artemisia sp. Murree

11 Coffee senna Cassia oxidantalis Islamabad

Nodule Samples

1 Mung Vigna mungo Rawalpindi

2 Peanut Arachis hypogaea Rawalpindi

3 Coffee senna Cassia occidentalis Islamabad

4 Sweet alys Alysicarpus bupleurifolius Islamabad

5 Sweet clover Melilotus indicus Islamabad

6 Bur clover Medicago polymorpha Islamabad

7 Trifolium longipes Melilotus polymorpha Islamabad

8 Trefoil Crotalaria medicaginea Islamabad

9 Torki Indigofera linifolia Islamabad

Appendix


Appendix B: List of culture collection used in this study (Plant genomics Lab)

Sr. No Culture

codes Cultures name Source Replicates collection of

1 QAU1 COQ-2 Rhizosphere 3 Islamabad

2 QAU2 6COQ-3 Rhizosphere 3 Islamabad

3 QAU3 2A-4 Rhizosphere 3 Islamabad


5 QAU5 RGQ Rhizosphere 3 Gujranwala

6 QAU6 RGQ-2 Rhizosphere 3 Gujranwala


8 QAU8 2MM Rhizosphere 3 Multan

9 QAU9 Peanut-1 Rhizosphere 3 Rawalpindi

10 QAU10 AB2-1 Rhizosphere 3 Islamabad







17 QAU17 Ar-1 Rhizosphere 3 ayubia

18 QAU18 N-3 Rhizosphere 3 ayubia

19 QAU19 Ar-2 Rhizosphere 3 ayubia

20 QAU20 COQ-3 Rhizosphere 3 Islamabad

21 QAU21 Mung-4 Rhizosphere 3 Rawalpindi

22 QAU22 RIN-2 Rhizosphere 3 Islamabad


24 QAU24 RIN-5 Rhizosphere 3 Islamabad


26 QAU26 3RM Rhizosphere 3 Multan




30 QAU30 COQ Rhizosphere 3 Islamabad

31 QAU31 MUNG-5 Rhizosphere 3 Islamabad

32 QAU32 Mung-1 Rhizosphere 3 Islamabad


34 QAU34 2RM Rhizosphere 3 Multan


36 QAU36 CM-1 Nodules 3 QAU Islamabad

37 QAU37 IL-2 Nodules 3 QAU Islamabad

38 QAU38 CO2-1 Nodules 3 QAU Islamabad


40 QAU40 AB-2 Nodules 3 QAU Islamabad

41 QAU41 CD-1 Nodules 3 QAU Islamabad

42 QAU42 Me-1 Nodules 3 QAU Islamabad

43 QAU43 Me-2 Nodules 3 QAU Islamabad

44 QAU44 N1 New Strain 3 Reference

Appendix


45 QAU45 PRL Strain 3 Reference



48 QAU48 Co1-2 Nodules 3 QAU Islamabad

49 QAU49 Peanut-1 Nodules 3 QAU Islamabad

50 QAU50 MUNG-8 Nodules 3 QAU Islamabad

51 QAU51 MUNG-7 Nodules 3 QAU Islamabad

52 QAU52 Medi-P Nodules 3 QAU Islamabad

53 QAU53 Meli-P Nodules 3 QAU Islamabad

54 QAU54 IL-1 Nodules 3 QAU Islamabad



57 QAU57 MUNG-1 Nodules 3 Rawalpindi





62 QAU62 Cotton-2 Rhizosphere 3 Multan

63 QAU63 Tom-5 Rhizosphere 3 Jaccobabad

64 QAU64 MUNG-4-1 Rhizosphere 3 Islamabad

65 QAU65 1PP Rhizosphere 3 Islamabad

66 QAU66 MUNG-4

Yellow Rhizosphere 3 Islamabad

67 QAU67 3C Rhizosphere 3 Multan

68 QAU68 3MN Rhizosphere 3 Multan

69 QAU69 3MM Rhizosphere 3 Multan

70 QAU70 M.O1-1 Nodules 3 Kaghan

71 QAU71 M.O1-2 Nodules 3 Kaghan

72 QAU72 T.P2-1 Nodules 3 Kaghan



75 QAU75 T.R3-1 Nodules 3 Kaghan




79 QAU79 M.SP5-1 Nodules 3 Kaghan

80 QAU80 M.SP5-2 Nodules 3 Kaghan

81 QAU81 M.A6-1 Nodules 3 Kaghan

82 QAU82 M.A6-2 Nodules 3 Kaghan







Appendix



90 QAU90 GRW-W-1 Rhizosphere 3 Gujranwala

91 QAU91 GRW-W-2 Rhizosphere 3 Gujranwala

92 QAU92 GRT-W-2 Rhizosphere 3 Gujrat

Appendix (C)

LB (LURIA-BERTINI) MEDIUM: (Sambrook and Russell, 2001)

Ingredients Gms / Litre

Tryptone 5.00

Yeast extract 2.50

NaCl 2.50

Agar 5.00

Adjust pH to 7.5 and autoclaved.

Appendix (D)

King's B media (King et al., 1954)


Proteose peptone No.3 20.000

Dipotassium hydrogen phosphate 1.500

Magnesium sulphate. heptahydrate 1.500

Bacto-Agar 20.000

Final pH (at 25°C) 7.2±0 and autoclaved.

Appendix


Appendix (E)

TY (Tryptone Yeast Extract) Medium (g/L); (Beringer, 1974)


Tryptone 5.0

Yeast extract 3.0

CaCl2 0.87

Agar 15.0

Deionized water 1000 ml

Adjust pH 6.8-7.2 and autoclave.

Appendix (F)

Pikovskaya’s medium (Pikovskaya, 1948)


Ca3(PO4)2 5.09

Glucose 10.0

(NH4)2SO4 0.5

NaCl 0.2

MgSO4.7H2O 0.1

KCl 0.2

Yeast Extract 0.5

MnSO4( trace) 0.002

FeSO4 (Fe-EDTA) 0.002

pH 7.7

Agar 20

Bromophenol blue: minor amount

Plate will incubate at 28◦C for 4-7 days.

Appendix


Appendix (G)

Yeast Extract Mannitol (YEM) Medium); (Beck et al., 1993)


Mannitol 10

K2HPO4 0.5

MgSO4.7H2O 0.2

NaCl 0.1

Yeast Extract 0.6

Distilled water 1000mL

pH 6.8-7.0

Congored (0.25%) 10mL/L for agar plates

Agar 1.5-2.0%

Used after autoclave

Appendix (H)

Gram’s staining (Gephardt et al, 1981)

The process involves three steps:

1. Cells are stained with crystal violet dye. Next, a Gram's iodine solution (iodine and

potassium iodide) is added to form a complex between the crystal violet and iodine. This

complex is a larger molecule than the original crystal violet stain and iodine and is

insoluble in water.

2. A decolorizer such as ethyl alcohol or acetone is added to the sample, which dehydrates the

peptidoglycan layer, shrinking and tightening it. The large crystal violet-iodine complex is

not able to penetrate this tightened peptidoglycan layer, and is thus trapped in the cell in

Gram positive bacteria. Conversely, the the outer membrane of Gram negative bacteria is

degraded and the thinner peptidoglycan layer of Gram negative cells is unable to retain the

crystal violet-iodine complex and the color is lost.

3. A counterstain, such as the weakly water soluble safranin, is added to the sample, staining

it red. Since the safranin is lighter than crystal violet, it does not disrupt the purple

coloration in Gram positive cells. However, the decolorized Gram negative cells are stained

red.

Appendix


Appendix (I)

Molecular Biology Reagents and Buffers

TE buffer

10 mM Tris (pH 8.0)

1 mM EDTA (pH 8.0)

10X TBE (Tris Borate EDTA for Gel electrophoresis)

Tris base 108g

Boric acid 55g

0.5M EDTA 40mL

Distilled water 1000ml

Appendix J: List of morphological characters along with character state

Character Character state

Size (Pinpoint, Small, Medium, Large)

Pigmentation (Color of colony)

Form (Circular, Irregular, Rhizoid)

Margin (Circular, Irregular, Wavy, Filamentous)

Elevation (Flat, Raised, Convex)

Appendix


Appendix K: Morphological characterization

Strain ID Colony Morphology a Gram's Staining b

QAU51 T, R, S, C +

QAU53 T, P, S, M, C –

QAU54 T, P, S, C –

QAU56 T, R, S, C, M –

QAU60 T, R, S, C –

QAU62 W, R, D, Cn +

QAU63 W, R, D, C –

QAU64 S, T, C, R –

QAU65 S, O, C, R –

QAU66 S, T, C, R –

QAU67 M, S, O, C, R, –

QAU68 O, R, Cn, D +

QAU69 M, S, O, C, R, –

QAU90 O, M, C, R, –

QAU92 S,O, M, C, R, –

aS (shiny), M (Mucoid), T/W/O (Transparent/ White/ Off-White), C/Cn (Convex/ Concave), R

(Rounded); b + Tested positive, – Tested negative.

Appendix


Appendix L : Assigned NCBI Genbank accession numbers of different genes (16SrRNA,

rpoB, rpoD, recA, gdh and pqqABCDEF)

GenbankIt Genes strains Accession

numbers

BankIt1746551

16SrRNA Pseudomonas putida QAU90 KM251449

BankIt1746553

16SrRNA Pseudomonas sp. QAU92 KM251450

BankIt1746541

rpoB Pseudomonas fluorescens QAU67 KM251440

BankIt1746541

rpoD Pseudomonas fluorescens QAU67 KM251441

BankIt1746541

recA Pseudomonas fluorescens QAU67 KM251442

BankIt1746548

rpoB Pseudomonas putida QAU90 KM251443

BankIt1746548

rpoD Pseudomonas putida QAU90 KM251444

BankIt1746548 recA

Pseudomonas putida QAU90 KM251445

BankIt1746549

rpoB Pseudomonas sp. QAU92 KM251446

BankIt1746549 rpoD Pseudomonas sp. QAU92 KM251447

BankIt1746549 recA

Pseudomonas sp. QAU92 KM251448

BankIt1746536

gdh Pseudomonas sp. CMR12a KM251437

GI:514058043 gdh Leclercia adecarboxylata QAU66 KF156751

BankIt1751430 gdh Pseudomonas fluorescens QAU67 KM360162

BankIt1746538 gdh Pseudomonas putida QAU90 KM251438

BankIt1746540 gdh Pseudomonas sp. QAU92 KM251439

BankIt1746515

pqqB Pseudomonas sp. CMR12a KM251417

BankIt1746515

pqqC Pseudomonas sp. CMR12a KM251418

BankIt1746515 pqqD Pseudomonas sp. CMR12a KM251419

BankIt1746515 pqqE Pseudomonas sp. CMR12a KM251420

Appendix


BankIt1746515 pqqF Pseudomonas sp. CMR12a KM251421

BankIt1746526

pqqB

Pseudomonas fluorescens QAU67

KM251422

BankIt1746526

pqqC Pseudomonas fluorescens QAU67 KM251423

BankIt1746526

pqqD Pseudomonas fluorescens QAU67 KM251424

BankIt1746526 pqqE Pseudomonas fluorescens QAU67 KM251425

BankIt1746529

pqqA Pseudomonas putida QAU90 KM251426

BankIt1746529

pqqB Pseudomonas putida QAU90 KM251427

BankIt1746529

pqqC Pseudomonas putida QAU90 KM251428

BankIt1746529

pqqD Pseudomonas putida QAU90 KM251429

BankIt1746529

pqqE Pseudomonas putida QAU90 KM251430

BankIt1746529 PqqF Pseudomonas putida QAU90 KM251431

BankIt1746533

pqqA Pseudomonas sp. QAU92 KM251432

BankIt1746533

pqqB Pseudomonas sp. QAU92 KM251433

BankIt1746533

pqqC Pseudomonas sp. QAU92 KM251434

BankIt1746533 pqqD Pseudomonas sp. QAU92 KM251435

BankIt1746533 pqqE Pseudomonas sp. QAU92 KM251436

Appendix


Appendix M : The bacterial isolates characterization for antagonistic activities

(−) =

absence; (+) = presence; (+++) = strong activity; PCA, phenazine-1-carboxylate; PCN, phenazine-1-

carboxamide; 1-OH, 1-hydroxy phenazine; PLT, pyoluteorin; Biosurf, biosurfactants; ND, not determined

and quantitative data of antifungal actity mentioned in Table 3.8.

Isolates Biosurf

(Drop

collapse)

Antifungal activity

Siderophores

R. Solani Fusarium Pythium

QAU66

− − − + −

QAU67

− − − − ++

QAU90

+++

+

++

++

−

QAU92

++

++

+

++

−

CMR12a

++ ++

+

++

−

Appendix


Appendix N: Murashige and Skoog (MS) medium (Murashige and Skoog, 1962)

Constituent Final concentration (mg/L)

Major salt

NH4NO3

1650

KNO3

1900

CaCl2 7H2O

440

MgSO4 7H2O

370

KH2PO4

170

Minor salts

KI

0.83

MnSO4 7H2O 22.3

H3BO3

6.2

ZnSO4

8.6

NaMoO4

0.25

CuSO4

0.025

CoCl2

0.025

Iron Source

FeSO4 7H2O

27.8

Na-EDTA 2H2O

37.3

Sucrose 30000

1/2 x Murashige & Skoog (MS) medium (1L)

MS salts with macro- and 2.165 g

Sucrose 10 g

dH2O to 1L

Bacto agar 8g

Autoclave at 121OC for 30 min.

Appendix


Appendix (O); (Eaton et al., 2005)

Peptone water contained

Peptone 7.0 g/l,

Dextrose 5.0 g/l,

Potassium phosphate 5.0 g/l

Kovac’s reagent contained

Para dimethyl aminobenzaldehyde 10 g,

Isoamyl alcohol 150 ml

and Conc. HCl 50 ml

Appendix (P-I) Yeast Peptone Dextrose (YPD) broth medium

Ingredients Grams/Litre

Yeast extract 10.0

Peptone 20.0

Dextrose 20.0

Final pH ( at 25°C) 6.5±0.2

Store prepared media below 8°C, protected from direct light. Store dehydrated powder, in a dry

place, in tightly-sealed containers at 2-25°C.

Appendix (P-II) M-9 nutritional media

10 ul 5X M9 salts,

5 ul 1M CaCl2

50 ul 1M MgSO4

500 µl trace elements and rest of water up to 50 ul

Appendix


Appendix (P-III) Difco™ Potato Dextrose Agar

Approximate Formula grams /Liter

Potato Starch (from infusion) 4.0

Dextrose 20.0

Agar 15.0

Apendix (Q) : Biochemical and physiological characterization of bacterial isolates

Strain ID

IAA

Productiona

Catalase

Productiona

N-acyl

homoserine

lectonea (AHL)

Nitrogenase activitya

QAU51 – – – +

QAU53 – + – +

QAU54 – + – –

QAU56 + – – +

QAU60 – – + +

QAU62 – – – –

QAU63 + + – –

QAU64 + + – –

QAU65 + + – –

QAU66 + + – –

QAU67 + + + –

QAU68 + + – –

QAU69 + + – –

QAU90 + + + –

QAU92 + + – –

aTested positive (+) and Tested Negitive (–)

Appendix


Appendix (R-i): The pqqAEF genes amplification of all bacterial strains; where (L: 1kb Ladder;

Lane 1: pqqE of CMR12a; Lane 2: pqqF of CMR12a; Lane 3: pqqE of QAU90; Lane 4: pqqAB

of QAU90; Lane 5: pqqE of QAU92 and Lane 6: pqqF of QAU90).

Appendix (R-ii): The pqqABE genes amplification of all bacterial strains; where (L: 1kb

Ladder; Lane 1: pqqE of QAU67; Lane 2: pqqAB of CMR12a; Lane 3: pqqAB of QAU92 and

Lane 4: pqqF1 of CMR12a).

Appendix (R-iii): The pqqABEF genes amplification of QAU92 strain; where (L: 1kb Ladder;

Lane 1: pqqAB of QAU92; Lane 2: pqqE of QAU92 and Lane 3: pqqF of QAU92).

Appendix


Appendix (S): The secondary structure prediction of GDH by CSSFP server of (A) Leclercia sp.

QAU66, (B) P. fluorescens CMR12a, (C) P. putida QAU90 and (D) Pseudomonas sp. QAU92.

Different colors representing each part of secondary structure.

Appendix


Appendix (T): MEMPACK cartoons indicate the predicted transmembrane helix or helices with

interactions in GDH protein of P. fluorescens CMR12a (only Helix 1 showed), P. putida QAU90

(only Helix 2 showed) and Pseudomonas sp. QAU92 (only Helix 4 & 5 showed). Helix residues

are indicated as the colored circular nodes. Interactions between residues are indicated by edges.

Helices are oriented to maximize the number of residues with predicted interactions.

Appendix


Appendix (U): PSIPRED tool FFPRED based schematic presentation of secondary structure of

Glucose dehydrogenases (GDH) of all strains (A-D) and position dependent features of

Phosphorylation. The line height of the Phosphorylation features reflects the confidence of the

residue prediction. The blue color represents the α-helix and red color represents the β-strands.

Appendix


Appendix (V): In vitro antagonism activities of Pseudomonas strains against (A-C) Fusarium

solani; (A) P. fluorescens CMR12a, (B) P. putida QAU90 and (C) Pseudomonas sp. QAU92 and

(D-F) Rhizoctonia solani; (D) P. fluorescens CMR12a, (E) P. putida QAU90 and (F)

Pseudomonas sp. QAU92.

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