Bacterial Diversity in the Rhizosphere of AVP1 Transgenic Cotton (Gossypium Hirsutum L.) and Wheat (Triticum Aestivum L.)

Bacterial Diversity in the Rhizosphere of AVP1 Transgenic Cotton (Gossypium hirsutum L.) and Wheat (Triticum aestivum L.)

Muhammad Arshad

2016

Department of Biotechnology Pakistan Institute of Engineering & Applied Sciences Nilore-45650 Islamabad, Pakistan

Reviewers and Examiners

Foreign Reviewers 1. Dr. Dittmar Hahn Department of Biology, Texas State University, 601 University Drive San Marcos, Fax +1 (512) 245 8713 Telephone: +1 (512) 245 3372 E-mail Address: [email protected] 2. Dr. Philippe Normad Microbial Ecology Laboratory, UMR CNRS 5557, F-69622 Villeurbanne Cedex Telephone: 33 (0)4-7243-1377 E-mail Address: [email protected] University of Arkansas, 3. Dr. Katharina Pawlowski Stockholm University Mailing Address: SE-106 91 Stockholm, Sweden Telephone (With Country Code): +46 8 16 37 72 E-mail Address: [email protected] Thesis Examiners

1. Dr. Asghari Bano, Department of Biosciences university of Wah cant Telephone # 03129654341 E-mail Address: [email protected]

2. Dr. Muhammad Arshad Department of Botany, PMAS AAU, Murree Road, Rawalpindi Telephone: 051-9062207 E-mail Address: [email protected] 3. Dr. Amer Jamil, Molecular Biochemistry Lab, Dept. of Chemistry and Biochemistry, University of Agriculture Faisalabad Telephone: 41-9201104 E-mail Address: [email protected]

Head of the Department (Name): Prof. Dr. Shahid Mansoor, S.I.

Signature with date: ______

Thesis Submission Approval

This is to certify that the work contained in this thesis entitled Bacterial Diversity in the Rhizosphere of AVP1 Transgenic Cotton (Gossypium hirsutum L.) and Wheat (Triticum aestivum L.), was carried out by Muhammad Arshad, and in my opinion, it is fully adequate, in scope and quality, for the degree of M. Phil leading to Ph.D. Furthermore, it is hereby approved for submission for review and thesis defense.

Supervisor: ______Name: Dr. Muhammad Sajjad Mirza Date: 27 December, 2016 Place: NIBGE, Faisalabad

Co-Supervisor: ______Name: Dr. Shaheen Asad Date: 27 December, 2016 Place: NIBGE, Faisalabad

Head, Department of Biotechnology: ______Name: Dr. Shahid Mansoor (S.I) Date: 27 December, 2016 Place: NIBGE, Faisalabad

Bacterial Diversity in the Rhizosphere of AVP1 Transgenic Cotton (Gossypium hirsutum L.) and Wheat (Triticum aestivum L.)

Muhammad Arshad

Submitted in partial fulfillment of the requirements for the degree of Ph.D.

2016

Department of Biotechnology Pakistan Institute of Engineering and Applied Sciences Nilore-45650 Islamabad, Pakistan

Dedications

My Parents

My innocent kids

Muhammad and Anaya

Acknowledgements

Nothing is deserving of worship except “ALMIGHTY ALLAH”, all praises for Him, Who is the entire source of all knowledge and wisdom endowed to mankind. He guides the way and gives me courage to complete this work. I offer my humblest gratitude from deep sense of heart to the Holy Prophet, MUHAMMAD (Peace be Upon Him) Who is, forever source of guidance and knowledge for humanity.

I am very grateful to my PhD supervisor Dr. Muhammad Sajjad Mirza, Deputy Chief Scientist, NIBGE Faisalabad for his professional and technical guidance, scientific discussions and suggestions, keen interest in completion of this task and moral support during whole period of research and compilation of thesis. I also pay thanks to my foreign supervisor Professor Dr. Johan Leaveau at Plant Pathology Department University of California Davis CA, USA for his kind and technical support and valuable contribution during my visit to the host lab for six month fellowship. I will appreciate Mr. Gurdeep Rastogi, my senior colleague and Mr. Jan Tech, lab in charge at Pathology Lab, University of California Davis CA, USA.

I would also like to appreciate and acknowledge the efforts of Dr. Shahid Mansoor (S.I.), Director (NIBGE), and Dr. Suhail Hameed (Exe. Director NIBGE) for maintaining the honor of this institute among other research organizations of Pakistan. I would like to acknowledge Dr. Shaheen Asad (co-superviser) and Dr. Nasir A saeed Principle Scientists at NIBGE, Faisalabad, for providing all plant material. I would like to appreciate Mr. Muhammad Arshad Senior Scientist at NIBGE and Mr. Masood Anwar for their cooperation during this course of study.

I am also indebted to my lab colleagues Dr. Muther Mansoor Qaisrani, Dr. Muhammad Tahir and Mr. Ahmad Zaheer for their help in learning research techniques and theoretical discussions. I am also thankful to Mr. Muhammad Ahmad and Muhammad Imran technicians at Microbial Ecology Lab, NIBGE, Faisalabad, for the kind help in conducting lab and field experiments. The help from Dr. Farooq

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Latif (DCS) and Dr. Ghulam Rasul (PS), at NIBGE, Faisalabad for analysis of organic acids and phytohormones on HPLC is thankfully acknowledged.

Special thanks are due to my parents who waited a long time. I am especially thankful to my wife Aisha Arshad who suffered my long absence at home brought up my beloved kids Muhammad and Anaya with full care and provided me the spiritual and moral support during this long period of study, research work and in thesis writing.

Many friends have helped me stay sane through these difficult years. Particularly, I am thankful to Dr. Atif Iqbal, Dr. Asif Habib Dr. Ikram Anwar and Sohail Mehmood Kareemi. Their support and care helped me to overcome setbacks and stay focused on my graduate study. I greatly value their friendship and I deeply appreciate their belief in me. I have no words to pay sincerest thanks to my friends for their help, encouragement and great friendship that made easier for me to overcome difficulties in all hard times.

At the end, I would like to acknowledge Higher Education Commission, Pakistan, for providing me funds for my doctoral research in Pakistan and University of California, Davis CA USA. Without this financial support I might not be able to focus on my research.

Muhammad Arshad

Declaration of Originality

I hereby declare that the work accomplished in this thesis is the result of my own research carried out in Soil & Environmental Biotechnology Division (NIBGE). This thesis has not been published previously nor does it contain any material from the published resources that can be considered as the violation of international copyright law. Furthermore, I also declare that I am aware of the terms ‘copyright’ and ‘plagiarism’, and if any copyright violation was found out in this work I will be held responsible of the consequences of any such violation.

______(Muhammad Arshad)

27 December, 2016 NIBGE, Faisalabad.

Copyrights Statement

The entire contents of this thesis entitled Bacterial Diversity in the Rhizosphere of AVP1 Transgenic Cotton (Gossypium hirsutum L.) and Wheat (Triticum aestivum L.) by Muhammad Arshad are an intellectual property of Pakistan Institute of Engineering & Applied Sciences (PIEAS). No portion of the thesis should be reproduced without obtaining explicit permission from PIEAS.

Table of Contents

Dedications ...... ii Acknowledgements ...... iii Declaration of Originality ...... v Copyrights Statement ...... vi Table of Contents ...... vii List of Figures ...... xi List of Tables ...... xiv Abstract ...... xvii List of Publications and Patents ...... xix List of Abbreviations and Symbols...... xx 1. Introduction ...... 1 1.1 Genetically Modified Crops ...... 1 1.2 Use of AVP1 Gene to Develop Transgenic Plants ...... 2 1.3 Bacterial Diversity in Rhizosphere of Genetically Modified Plants ...... 4 1.4 Plant Growth Promoting Rhizobacteria (PGPR) ...... 5 1.4.1 Mode of Action of PGPR ...... 5 1.4.2 Nitrogen Fixation ...... 6 1.4.3 Biological Nitrogen Fixation (BNF) ...... 8 1.4.4 Diversity of Diazotrophic Bacteria ...... 9 1.4.5 The Domain Archea ...... 9 1.4.6 Phosphorus Mineralization by Microbes for Plant Growth Promotion .. 11 1.4.7 Phytohormone Production by PGPR for Plant Growth Promotion ...... 12 1.4.8 PGPR as Biofertilizers ...... 14 1.5 Effect of Transgenic Plants in Rhizosphere Environment ...... 15 1.5.1 Effect of Transgenic Plants on Soil Microorganisms ...... 15 1.6 Diversity of Culturable and Non-Culturable Bacteria in the Rhizosphere ...... 18 1.6.1 16S rRNA Gene as a Tool for Studying Diversity of Culturable and Non- Culturable Bacteria ...... 18 1.6.2 Bacterial Diversity by Pyrosequencing Analysis of 16S rRNA Gene .... 19 1.6.3 Functional Genes for Bacterial Identification and Detection ...... 23

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1.6.4 nifH Metagenomics: A Tool to Study the Diversity of Diazotrophic Bacteria ...... 23 1.6.5 Real Time PCR: A Gene Quantification Approach to Study the Abundance of nif H and 16s rRNA Gene ...... 24 2. Materials and Methods ...... 27 2.1 Isolation of Bacteria from the Rhizosphere of Cotton and Wheat ...... 27 2.1.1 Isolation of Diazotrophic Bacteria by Enrichment Culture Technique .. 25 2.2 Morphological Characterization of Bacteria ...... 28 2.2.1 Colony and Cell Morphology ...... 28 2.2.2 Culture Preservation...... 28 2.3 Phosphorus Solubilization ...... 28 2.3.1 Qualitative Assay for Phosphorus Solubilization by Bacteria ...... 28 2.3.2 Quantitative Estimation of Phosphate Solubilization by Bacteria ...... 28 2.3.3 Extraction and Quantification of Organic Acids Produced By Bacteria in Pikovskaya Medium...... 29 2.4 Indole Acetic Acid Production by Bacterial Isolates ...... 31 2.4.1 Colorimetric Estimation of IAA by Salkowski's Reaction (Spot Test) .. 31 2.4.2 Quantification of IAA Production ...... 30 2.5 Identification of Bacterial Isolates by 16R rRNA Gene Sequence Analysis ...... 31 2.5.1 DNA Extraction from Pure Cultures of Bacterial Isolates...... 31 2.5.2 Identification of Bacterial Isolates ...... 31 2.6 Plant Inoculation Experiments ...... 32 2.6.1 Soil Analysis and Plant Material...... 32 2.6.2 Bacterial Inoculum Preparation ...... 32 2.6.3 Quick Screening of Bacterial Isolates in Sterilized Sand ...... 32 2.6.4 Bacterial Inoculation of Cotton and Wheat Plants Grown In Earthen Pots ...... 33 2.6.5 Bacterial Inoculation of Wheat Plants Grown in Micro-Plots ...... 33 2.6.6 Statistical Analysis ...... 34 2.7 Estimation of Bacterial Population ...... 34 2.7.1 Bacterial Population by Counting Colony Forming Units (cfu/g of soil) ...... 34 2.7.2 Bacterial Population by Counting Most Probable Number (MPN) ...... 34 2.7.3 Real Time PCR ...... 34 2.8 Extraction and Quantification of Root Exudates from the Rhizosphere ...... 35 2.9 Diversity of Diazotrophic Bacteria in the Rhizosphere of Transgenic and Non- transgenic Plants of Cotton and Wheat ...... 36

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2.9.1 PCR Amplification of nifH Gene from Soil DNA ...... 36 2.9.2 Cloning of nifH Gene and Sequencing Reactions...... 36 2.9.3 Phylogenetic Analysis ...... 37 2.10 Bacterial Diversity in the Rhizosphere of AVP1 Transgenic Cotton and Wheat by Pyrosequencing Analysis ...... 37 2.10.1 16S rRNA Gene Amplification for Pyrosequencing ...... 37 2.10.2 Analysis of the Pyrosequencing Data ...... 37 3. Results ...... 39 3.1 Isolation of Bacteria from the Rhizosphere of AVP1 Transgenic Cotton ...... 39 3.2 Isolation of Bacteria from the Rhizosphere of AVP1 Transgenic Wheat ...... 39 3.3 Identification of Bacterial Isolates by 16S rRNA Gene Sequence Analysis ...... 42 3.4 Quantification of IAA Production by Bacterial Isolates ...... 51 3.5 Phosphate Solubilization ...... 54 3.5.1 Qualitative Assay for Phosphate Solubilization by Bacterial Strains ..... 54 3.5.2 Quantitative Assay for Phosphate Solubilization by Bacterial Strains ... 54 3.6 Quantification of Organic Acid Production by Bacteria in Pikovskaya Medium Used for Studying Phosphate Solubilization ...... 55 3.7 Bacterial Inoculation of Cotton Plants ...... 60 3.7.1 Experiment 1 (year 2009) ...... 60 3.7.2 Experiment 2 (Year 2010) ...... 64 3.7.3 Experiment 3 (year 2011) ...... 67 3.8 Bacterial Inoculation of Wheat Plants ...... 71 3.8.1 Experiment 1 (year 2009) ...... 71 3.8.2 Experiment 2 (year 2011-2012) ...... 75 3.8.3 Experiment 3 (2012-2013) ...... 78 3.9 Bacterial Population ...... 81 3.9.1 Real Time PCR Quantification of 16S rRNA and nif H genes from Rhizospheric Soil ...... 84 3.9.2 Detection of Root Exudates in the Rhizosphere of AVP1 Transgenic Cotton and Wheat ...... 86 3.10 Diversity of Diazotrophic Bacteria Determined by PCR Amplification of Partial nifH gene from Soil DNA ...... 89 3.11 Bacterial Diversity by Pyrosequencing of 16S rRNA Gene...... 105 3.11.1 16S rRNA Gene Sequences, Processing and Taxonomic Analysis .... 107 3.11.2 Bacterial Diversity in Cotton Rhizosphere ...... 107 3.11.3 Abundance of Bacterial Classes in Cotton Rhizosphere Soil ...... 107 3.11.4 Abundance of Bacterial Genera in the Rhizosphere of Cotton ...... 108

3.12 Bacterial Diversity in Wheat Rhizosphere ...... 118 3.12.1 Abundance of Bacterial Classes in Wheat Rhizosphere Soil ...... 118 3.12.2 Abundance of Bacterial Genera in the Rhizosphere Wheat ...... 118 4. Discussion ...... 128 4.1 Conclusion and Future Perspectives ...... 144 5. References ...... 145

List of Figures

Figure 1-1 The role of intracellular plant growth promoting rhizobacteria (iPGPR) and extracellular plant growth promoting rhizobacteria (ePGPR) in soil ecosystem...... 6 Figure 1-2 A sketch of nitrogen cycle showing the conversion of atmospheric nitrogen into available forms...... 7 Figure 1-3 Schematic representation of 16S rRNA gene annotated with variable regions (V1 to V9) of 16S rRNA ...... 21 Figure 1-4 16S rRNA gene with three distinct variable regions and primers ...... 21 Figure 1-5 Schematic representation of progress of enzymatic reaction in pyrosequencing ...... 22 Figure 3-6 Isolation of bacteria on nutrient agar medium by serial dilution method ...... 39 Figure 3-7 Genomic DNA extracted from bacterial isolates...... 43 Figure 3-8 16S rRNA gene amplified from bacterial isolates...... 43 Figure 3-9 Phylogenetic tree showing the phylogenetic relationship of different strains of genus Bacillus and Paenibacillus...... 46 Figure 3-10 Phylogenetic tree showing the phylogenetic relationship of the Brevibacillus strains...... 47 Figure 3-11 Phylogenetic tree showing the phylogenetic relationship of the Arthrobacter strain ...... 48 Figure 3-13 Phylogenetic tree showing the phylogenetic relationship of Azospirillum strain ...... 50 Figure 3-16 Plate assay for detection of phosphorus solubilization by bacterial isolates on Pikovskaya medium supplemented with insoluble tri-calcium phosphate (TCP) ...... 55 Figure 3-17: Organic acid production (µg/mL) by bacterial isolates in pure culture. Bacterial cultures were grown for two weeks in Pikovskaya medium containing insoluble tri-calcium phosphate...... 59 Figure 3-18 Bacterial inoculation experiments on cotton plants conducted in different years in growth room...... 60 Figure 3-19 Effect of bacterial inoculation on growth of cotton plants (transgenic and non-transgenic) ...... 61 Figure 3-20 Effect of bacterial inoculation on root and shoot dry weights of transgenic and non-transgenic plants ...... 63 Figure 3-21 AVP1 transgenic cotton plants grown under controlled conditions in earthen pots ...... 65

Figure 3-22 Effect of bacterial inoculation on shoot dry weight, and yield (lint+seed) of transgenic and non-transgenic plants ...... 67 Figure 3-23 Bacterial inoculation of AVP1 transgenic and non–transgenic cotton grown under controlled conditions in earthen pots ...... 68 Figure 3-24 Effect of bacterial inoculation on root dry weight, and yield (lint+seed) of transgenic and non-transgenic plants ...... 70 Figure 3-25 Bacterial inoculation experiments on wheat plants conducted in different years ...... 71 Figure 3-26 Effect of bacterial inoculation on growth of AVP1 transgenic wheat plants grown in jars filled with sterilized sand ...... 72 Figure 3-27 Effect of bacterial inoculation on shoot dry weight, and root dry weight of transgenic and non-transgenic wheat plants ...... 74 Figure 3-28 Effect of bacterial inoculation on growth of AVP1 transgenic and non- transgenic wheat grown in micro-plots under natural conditions...... 75 Figure 3-29 transgenic and non-transgenic wheat plants grown in micro-plots ...... 77 Figure 3-30 Effect of bacterial inoculation on growth of AVP1 transgenic and non- transgenic wheat grown in micro-plots under natural conditions...... 78 Figure 3-31 Effect of bacterial inoculation on straw weight, and grain weight of transgenic and non-transgenic wheat plants ...... 80 Figure 3-32 Bacterial population (log cfu/g soil) on nutrient agar in the rhizosphere of transgenic and non-transgenic cotton at 30, 60 and 90 days after sowing (DAS) ...... 82 Figure 3-33 Bacterial population (log cfu/g soil) on nutrient agar in the rhizosphere of transgenic and non-transgenic wheat at 30, 60 and 90 days after sowing (DAS) ...... 82 Figure 3-34 Bacterial population of diazotrophs (log MPN/g soil in NFM) in the rhizosphere of transgenic and non-transgenic cotton at 30, 60 and 90 days after sowing (DAS) ...... 83 Figure 3-35 Bacterial population diazotrophs (log MPN/g soil in NFM) in the rhizosphere of transgenic and non-transgenic wheat at 30, 60 and 90 days after sowing (DAS) ...... 83 Figure 3-36 Real time quantification of 16S rRNA and nifH gene from rhizosphere of AVP1 transgenic cotton and wheat ...... 86 Figure 3-37 Organic acid production in rhizosphere of AVP1 transgenic and non- transgenic cotton and wheat...... 88 Figure 3-38 Amplification of nifH gene from soil DNA extracted from AVP1 transgenic and non-transgenic cotton (A) and wheat (B) ...... 90 Figure 3-39 transgenic (A) and non-transgenic cotton (B)...... 92 Figure 3-40 Distribution of diazotrophic bacteria in the rhizosphere of AVP1 transgenic (A) and non-transgenic wheat (B) ...... 98 Figure 3-41 Phylogenic tree constructed from nifH gene sequences retrieved from AVP1 transgenic and non-transgenic cotton ...... 103

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Figure 3-42 Phylogenic tree constructed from nifH gene sequences of AVP1 transgenic and non-transgenic wheat ...... 104 Figure 3-43 DNA extracted from the rhizosphere soil of cotton and wheat ...... 105 Figure 3-44 PCR amplification of 16S rRNA gene from the rhizosphere of AVP1- transgenic and non-transgenic cotton (A) and wheat (B) using barcoded primers ...... 106 Figure 3-45 Abundance of bacterial phyla in the rhizosphere of AVP1 transgenic and non-transgenic cotton...... 112 Figure 3-46 16S rRNA sequences belonging to different bacterial classes reterieved from the rhizosphere of AVP1 transgenic and non-transgenic cotton 113 Figure 3-47 Bacterial genera detected in the rhizosphere of AVP1 transgenic and non-transgenic cotton ...... 115 Figure 3-48 Abundance of important PGPR genera in the rhizosphere of AVP1 transgenic and non-transgenic cotton rhizosphere ...... 117 Figure 3-49 Abundance of 16S rRNA sequences of different bacterial phyla in the rhizosphere of AVP1 transgenic and non-transgenic wheat ...... 121 Figure 3-50 Abundance of 16S rRNA sequences belonging to different bacterial classes dominant in wheat rhizosphere of AVP1 transgenic and non- transgenic wheat...... 122 Figure 3-51 Bacterial genera detected only in the rhizosphere of AVP1 transgenic and non-transgenic wheat ...... 124 Figure 3-52 Abundance and comparison of PGPR detected in AVP1 transgenic and non-transgenic rhizosphere of wheat...... 126

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List of Tables

Table 1.1 Global area of biotech crops in mega countries in 2014 ...... 3 Table 1.2 Categorization of PGPR on the bases of their action mechanism ...... 6 Table 1.3 Important nitrogen fixing bacteria residing in rhizosphere of different crops plants ...... 10 Table 1.4 Effect of transgenic plants on structure and functions of soil microorganisms and their communities ...... 16 Table 1.5 Sequences of PCR primers for amplification of 16S rRNA gene ...... 22 Table 2.6 Primer sequence with titanium adopter sequence ...... 38 Table 2.7 Soil samples with barcodes name and sequences ...... 38 Table 3.8 Colony and cell morphology of the bacterial strains isolated from the rhizosphere of AVP1 transgenic and non-transgenic cotton ...... 40 Table 3.9 Colony and cell morphology of the bacterial strains isolated from the rhizosphere of AVP1 transgenic and non-transgenic wheat ...... 41 Table 3.10 Identification of bacterial isolates from rhizosphere of AVP1 transgenic and non-transgenic cotton by 16S rRNA gene sequence analysis ...... 44 Table 3.11 Identification of bacterial isolates from rhizosphere of AVP1 transgenic and non-transgenic wheat rhizosphere by 16S rRNA gene sequence analysis ...... 45 Table 3.12 Quantification of IAA produced by bacterial strains isolated from cotton ...... 53 Table 3.13 Quantification of IAA produced by bacterial strains isolated from wheat ...... 54 Table 3.14 Quantification of P solublization by bacterial isolates from cotton ..... 56 Table 3.15 Quantification of P solubilization by bacterial isolates from wheat .... 56 Table 3.16 Quantification of organic acid production (µg/mL) by bacterial isolates in the growth medium used for P-solubilization ...... 58 Table 3.17 Effect of bacterial inoculation on growth of AVP1 transgenic (A) and non-transgenic cotton (B) grown in sterilized sand under controlled conditions (year 2009) ...... 62 Table 3.18 Effect of bacterial inoculation on growth of AVP1 transgenic (A) and non-transgenic cotton plants (B) grown in earthen pots under controlled conditions (Year 2010)...... 66 Table 3.19 Effect of bacterial inoculation on growth of AVP1 (A) transgenic and non-transgenic cotton (B) grown in earthen pots under controlled conditions ...... 69

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Table 3.20 Effect of bacterial inoculation on growth of AVP1 transgenic (A) and non-transgenic wheat (B) grown in sterilized sand under controlled conditions ...... 73 Table 3.21 Effect of PGPR strains on yield and growth parameters of transgenic (A) and non-transgenic wheat (B) grown in micro-plots during 2011-2012 ...... 76 Table 3.22 Effect of PGPR strains on yield and growth parameters of transgenic (A) and non-transgenic wheat (B) grown in micro plots during 2012-2013 ...... 79 Table 3.23 Relative gene abundance (copy number) of bacterial 16S rRNA and nif H genes in the rhizospheric soil revealed by real time PCR ...... 85 Table 3.24 Detection of organic acids produced* as root exudates in rhizosphere of AVP1 transgenic and non-transgenic cotton and wheat ...... 87 Table 3.25 Diversity of diazotrophic bacterial sequences in the rhizosphere of AVP1 transgenic and non-transgenic cotton...... 91 Table 3.26 Identification of culturable diazotrophic bacterial sequences in the rhizosphere of AVP1 transgenic cotton ...... 93 Table 3.27 dentification of culturable diazotrophic bacteria detected in the rhizosphere of non-transgenic cotton ...... 94 Table 3.28 List of uncultured diazotrophic bacteria from AVP1 transgenic cotton rhizosphere ...... 95 Table 3.29 List of uncultured diazotrophic bacterial sequences from non-transgenic cotton rhizosphere ...... 96 Table 3.30 Diversity of diazotrophic bacteria in the rhizosphere of AVP1 transgenic and non-transgenic wheat ...... 97 Table 3.31 Identification of culturable diazotrophic bacterial sequences in the rhizosphere of AVP1 transgenic wheat ...... 99 Table 3.32 Identification of culturable diazotrophic bacteria detected in the rhizosphere of non-transgenic wheat ...... 100 Table 3.33 List of uncultured diazotrophic bacteria from AVP1 transgenic wheat rhizosphere ...... 101 Table 3.34 List of uncultured diazotrophic bacteria from AVP1 transgenic wheat rhizosphere ...... 102 Table 3.35 16S rRNA sequences retrieved from rhizosphere of AVP1 transgenic cotton and wheat with non-transgenic control ...... 109 Table 3.36 Abundance of 16S rRNA sequences belonging to different phyla in the rhizosphere of AVP1 transgenic and non-transgenic cotton ...... 108 Table 3.37 Abundance of 16S rRNA sequences of different bacterial genera (Top 50 genera) retrieved from transgenic and non-transgenic cotton ...... 113 Table 3.38 Bacterial genera detected only in the rhizosphere of transgenic cotton ...... 116

Table 3.39 Sequences of important PGPR genera detect in the rhizosphere of AVP1 transgenic and non-transgenic cotton...... 116 Table 3.40 Abundance of 16S rRNA sequences of different bacterial phyla in the rhizosphere of AVP1 transgenic and non-transgenic wheat ...... 120 Table 3.41 Abundance of 16S rRNA sequences belonging to different bacterial genera (Top 50 genera) retrieved from the rhizosphere of AVP1 transgenic and non-transgenic wheat ...... 122 Table 3.42 Bacterial genera detected only in the rhizosphere of transgenic wheat ...... 125 Table 3.43 Sequences of important PGPR genera detect in the rhizosphere of AVP1 transgenic and non-transgenic wheat ...... 125

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Abstract

Present study was conducted to compare diversity of bacteria in the rhizosphere of AVP1 transgenic cotton and AVP1 transgenic wheat with non-transgenic plants of both the crops. Over-expression of the H+pyrophosphatase (H+PPase) AVP1 results in salt and water stress tolerance. For studying the diversity of culturable bacteria, 12 strains were isolated from cotton and 14 strains were purified from wheat and identified by 16S rRNA gene sequence analysis. After initial screening of the isolates on the bases of phytohormone production and phosphate solubilization in pure culture as well as plant growth promotion in short term experiments in sand culture, the efficient strains were used as inoculants for plants grown in non-sterilized soil. Risk assessment studies indicated no significant difference of bacterial populations in the rhizosphere of transgenic and non-transgenic plants as determined by log cfu/g soil, MPN and copy number of 16S rRNA and nifH genes. However, bacterial populations were variable at different plant growth stages of both cotton and wheat. Using soil DNA, diversity of diazotrophs and rhizospheric communities was assessed by sequence analysis of PCR- amplified nifH gene and 16S rRNA genes, respectively. nifH sequences belonging to well-known diazotrophic genera i.e Anabaena, Azospirillum, Bradyrhizobium and Pseudomonas were abundant and common in the rhizosphere of AVP1 transgenic and non-transgenic plants of cotton and wheat. A fraction of uncultured diazotrophs were also detected in the rhizosphere of cotton and wheat. From the rhizosphere of cotton (transgenic and non-transgenic) total 190249 sequences of 16S rRNA gene were retrieved by pyrosequencing analysis which indicated 127747 sequences of bacteria, 8128 sequences of Archaea and 22964 sequences of unclassified bacteria. All the 19 bacterial phyla detected on the basis of 16S rRNA gene sequencing were represented in the rhizosphere of both transgenic and non-transgenic cotton plants. From wheat rhizosphere total 156282 sequences were obtained by pyrosequencing analysis of 16S rRNA gene which indicated 128006 sequences of bacteria, 7928 sequences of Archea and 21568 sequences of unclassified bacteria. All the 18 bacterial phyla detected on the basis of 16S rRNA gene sequencing were represented in the rhizosphere of both the

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transgenic and the non-transgenic wheat. In the present study comparison of the number of sequences retrieved from transgenic and non-transgenic plants of cotton and wheat indicated that all major bacterial groups (phyla) were represented in the rhizosphere of both type of plants (transgenic and non-transgenic) and point to safe use of transgenic plants.

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List of Publications and Patents

 Journal Publications Muhammad Arshad, Muhammad Arshad, Johan Leveaue, Shaheen Asad, Asma Imran, Muhammad Sajjad Mirza. 2015. Culturable Bacterial Population in the Rhizosphere of AVP1 Transgenic and non-transgenic Cotton and Growth Promotion by Inoculated Strains of Arthrobacter, Azospirillum and Brevibacillus. (JCR 2014) (ISSN: 1018-7081)

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List of Abbreviations and Symbols

ºC Degree centigrade µL Micro litre µm Micro meter 10X 10 times ABA Abscisic acid ACC- 1-aminocyclopropane-1-carboxylate deaminase deaminase

ANOVA Analysis of variance ARA Acetylene reduction assay ATP Adenosine triphosphate AVP1 Vacuolar proton-pyrophosphatase from Arabidopsis BLAST Basic local alignment search tool BNF Biological nitrogen fixation Bt cotton Bacillus thuringiensis transgenic cotton cfu Colony forming units cm Centimeter CRD Completely randomized design DAP Di-ammonium phosphate DAS Days after sowing GA Gluconic acid GFP Green fluorescent protein GMOs Genetically modified organisms GMPs Genetically modified plants HCN Hydrogen cyanide HPLC High performance liquid chromatography IAA Indole-3-acitic acid LB Luria Bertani

MPN Most probable number N Nitrogen 15N Isotope of nitrogen with atomic

N2 Atmospheric nitrogen NCBI National Center for Biotechnology Information NFM Nitrogen free malate NTC Non-transgenic cotton NTW Non-transgenic wheat P Phosphorus PGPR Plant growth promoting rhizobacteria PSB Phosphate solubilizing bacteria RCBD Randomized complete block design TC Transgenic cotton TCP Tri-calcium phosphate TW Transgenic wheat

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1. Introduction

1.1 Genetically Modified Crops Genetic modification of plants, microbes and animals to incorporate useful traits is a powerful technology for the development of sustainable agricultural systems. Genetically modified plants (GMPs) with a wide variety of traits have been developed. Most GMPs developed to date can be grouped into eight main categories: (i) resistance to herbicides, (ii) resistance to pests, (iii) resistance to pathogens, (iv) resistance to environmental stress, (v) altered root exudates, (vi) plants with altered composition, (vii) ability to produce pharmaceutical or industrial compounds and (viii) elimination of pollutants [1]. The first genetically modified plant was produced in 1982, using an antibiotic-resistant tobacco plants [2]. The first field trials of genetically engineered plants occurred in France and the USA in 1986, when herbicide resistant tobacco plants were engineered [3]. In 1987, Plant Genetic Systems (Ghent, Belgium) was the first company to develop genetically engineered (tobacco) plants with insect tolerance by expressing genes encoding for insecticidal proteins from Bacillus thuringiensis (Bt) [4].

The first genetically modified crop approved for sale in the U.S., in 1994, was the Flavr Savr Tomato, which was modified for its longer shelf life. GM technology has addressed some of the most serious concerns of world agriculture and GM technology can be applied to some of the specific problems of agriculture, indicating the potential for benefits. Biotechnology has revolutionized crop improvement by producing GM crops with enhanced availability and utilization of important traits. Transgenic crops containing insect-resistance genes from Bacillus thuringiensis have made it possible to reduce significantly the amount of insecticide applied on cotton [4]. Other insecticidal proteins have been discovered including lectins, protease inhibitors, antibodies, wasp and spider toxins, microbial insecticides and insect peptide hormones [3].

One of the major technologies that led to the “Green Revolution” was the development of high-yielding semi-dwarf wheat varieties. Crops have been developed that have an inbuilt resistance to biotic and abiotic stress i.e rice yellow mottle virus (RYMV) devastates rice in Africa by destroying the majority of the crop. “Genetic 1. Introduction immunization” was done by creating transgenic rice plants that were resistant to RYMV [98]. Numerous other examples could be given i.e blight resistant potatoes and rice bacterial leaf blight, plants modified to overproduce citric acid in roots and provide better tolerance to aluminum in acid soils. The transgenic rice exhibiting an increased production of beta carotene as a precursor to vitamin A and may be a useful tool to help treat the problem of vitamin A deficiency in young children living in the tropics. Plant genetic engineering technology is now being widely used for “biopharming”, or production of pharmaceuticals in plants. (Text on crop plants with foreign has also been given in Table 1.4).

1n 2010, 8 insect resistant Bt. and 1 hybrid cotton varieties were officially approved by government of Pakistan. In Pakistan 2014 was the fifth year of commercialization of Bt. crop with the area 2.9 million hectares. With the increase in land area under transgenic crops (Table 1.1) concerns have been raised over the potential detrimental effects of genetically modified plants on human health, environment and non-target organisms including soil microbial communities. The major concerns are the possibility of creating invasive plant species, the unintended consequences of transgene flow to indigenous plants and microorganisms and development of ‘super’ pests [6].

1.2 Use of AVP1 Gene to Develop Transgenic Plants

Salinity limits the plant growth affecting 20% of the world’s irrigated lands [7].The harmful effects of salt on plants are a result of (i) water deficit that results from the relatively high solute concentrations in soil and (ii) excessive sodium (Na+) concentrations in the cytoplasm. Excessive Na+ in the cytoplasm changes ion ratios that disturbs critical biochemical processes and also increases plasma membrane injury [9, 10]. Accumulation of compatible solutes and reduction of sodium ions in the cytoplasm are two common mechanisms in plants to deal with the injury. Plants reduce excessive Na+ in the cytoplasm by (i) excluding Na+ from cells using the Na+/H+ antiporter located in the plasma membrane; and by pumping Na+ into vacuoles using Na+/H+ antiporter located in the tonoplast [11].

1. Introduction

Table 1.1 Global area of biotech crops in mega countries in 2014 [8].

Rank Country Area (million Biotech Crops hectares) 1. USA 73.1 Maize, soybean, cotton, canola, sugar beet, alfalfa, papaya, squash 2. Brazil 42.2 Soybean, maize, cotton 3. Argentina 24.3 Soybean, maize, cotton 4. Canada 11.6 Canola, maize, soybean, sugar beet

5. India 11.6 Cotton 6. China 3.9 Cotton, papaya, poplar, tomato, sweet pepper 7. Paraguay 3.9 Soybean, maize, cotton 8. Pakistan 2.9 Cotton 9. South Africa 2.7 Maize, soybean, cotton 10. Uruguay 1.6 Soybean, maize

The compartmentalization of Na+ into vacuoles provides an efficient mechanism for avoiding the toxic effects of Na+ in the cytosol. The transport of Na+ into vacuoles is mediated by vacuolar Na+ /H+ antiporters that are driven by the electrochemical gradient of protons. The proton-motive force generated by the vacuolar ATPase (V- ATPase) and vacuolar pyrophosphatase (V-PPase) can drive secondary transporters, such as the Na+/H+ antiporter and Ca2+/H+ antiporter, as well as organic acids, sugars, and other compound transporters to maintain cell turgor [12]. The vacuolar H+-PPase is a single subunit protein located in the vacuolar membrane [13]. It pumps H+ from the cytoplasm into vacuoles with P Pi-dependent H+ transport activity. Theoretically, over- expression of H+-PPase should enhance the ability to form the pH gradient between the cytoplasm and vacuoles, resulting in a stronger proton-motive force for the Na+/H+ antiporter, Ca2+/H+ antiporter, and other secondary transporters. The accumulation of cations, such as Na+, in vacuoles could increase the osmotic pressure of plants, while reducing the toxic effects of these cations [14].

The transcription and translation of AVP1 and P-ATPases (Arabidopsis H+- ATPase’s, AHAs), normally expressed in roots showed that low Pi increases transcript and protein abundance of AVP1 and P-ATPase in Arabidopsis [14, 15]. Another

1. Introduction phenotype of AVP1 i.e AtAVP1OX plants exhibited enhanced growth, enhanced rhizosphere acidification, larger shoot formation and Pi uptake when grown on solid Pi-deficient medium. Roots of different lines i.e AtAVP1OX, LeAVP1DOX and OsAVP1DOX have higher K+ contents and thus exude greater amounts of organic acids when compared with control plants. Transgenic tomatoes over-expressing the E229D gain-of-function mutant (AVP1D) of the Arabidopsis H+-pyrophosphatase (LeAVP1DOX) develop more robust root systems and are resistant to imposed soil water deficits [16].

Over-expression of the H+pyrophosphatase (H+PPase) AVP1 resulted in salt and water stress tolerant Arabidopsis plants [14]. The tolerance was initially explained by an enhanced uptake of ions into their vacuoles. Presumably, the greater AVP1 activity in vacuolar membranes provides increased vacuolar H+ to drive the secondary active uptake of toxic (i.e. sodium) and nontoxic ions into the vacuole. The resulting decline in vacuolar osmotic potential may trigger water uptake, permitting plants to survive under conditions of low soil water potentials [15]. Significantly, further characterization of these AVP1 overexpressing plants revealed an enhancement of their root development, with obvious implications for their ability to withstand drought [16]. These results suggest that the H+PPase AVP1 is a potential target for genetic engineering of root systems in agriculturally important crop plants.

1.3 Bacterial Diversity in Rhizosphere of Genetically Modified Plants Rhizosphere is the rooting zone of plants and includes the roots, soil attached to the roots, and the adjacent soil under the influence of the roots [17]. Microorganisms are also considered as important component of the rhizosphere and contribute to ecological fitness of their host plant. Soil microbes are involved in important process that might occur in the rhizosphere including plant growth promotion, plant protection, pathogenesis, production of antibiotics, cycling of carbon, nitrogen and sulfur [18, 19]. Bacteria represent one of the three domains in the phylogenetic tree of life comprised of Archaea, Bacteria and Eukarya [20]. Bacterial diversity generally refers to the genetic diversity which is the amount and distribution of genetic information within the

1. Introduction bacterial communities. Total number of species present (species richness) and distribution of individuals among the species (evenness) are the functions of diversity.

1.4 Plant Growth Promoting Rhizobacteria (PGPR) The term ‘rhizobacteria’ is used to describe the soil bacteria (PGPR) that competitively colonize plants and stimulate growth by utilizing plant beneficial traits and by reducing plant diseases [21]. PGPR constitute the key part of rhizosphere biota by successfully establishing in the rhizosphere due to their adaptability in a wide variety of environments, faster growth, and their ability to metabolize a wide range of compounds [22]. Most rhizospheric bacteria establish an inoffensive interaction with the host plants exhibiting no visible effect on the growth and overall physiology of the host [23]. In negative interactions, the phytopathogenic rhizobacteria produce phytotoxic substances such as hydrogen cyanide or ethylene and negatively influence the growth and physiology of the plants. PGPRs on the other hand exert a positive effect on plant growth by diverse mechanisms such as solubilization of nutrients, nitrogen fixation, and production of phytohormones [24-26]. PGPR can be further classified into extracellular plant growth promoting rhizobacteria (ePGPR), present in the rhizosphere, on the rhizoplane or in the spaces between the cells of root cortex and intracellular plant growth promoting rhizobacteria (iPGPR) generally located inside the specialized nodular structures of root cells [27]. A large number of PGPR like Azospirillum, Azotobacter, Bacillus, Enterobacter, Pseudomonas, Klebsiella and Paenibacillus have been isolated from rhizosphere of various crops and their plant growth promoting traits have been studied [28-32].

1.4.1 Mode of Action of PGPR

PGPR promote plant growth directly by utilizing mechanisms like biological nitrogen fixation, phytohormone production e.g auxins, mineral solubilization or indirectly by employing mechanisms basically related to biocontrol and include antibiotic production, siderophores production to chelate available Fe in the rhizosphere, synthesis of extracellular enzymes to hydrolyze the cell wall of fungal pathogens and competition for niches within the rhizosphere [33, 34]. On the bases of their action mechanism application of PGPR can be generalized into three broad categories i.e. Biofertilizers, Biopesticides and Phytostimulators (Table 1.2).

1. Introduction

Table 1.2 Categorization of PGPR on the bases of their action mechanism

PGPR category Mechanism of action Reference Biofertilizers Biological nitrogen fixation. Solubilization [32, 35] of Phosphorus. Production of plant growth regulators e.g (IAA). Biopesticides Promote plant growth indirectly by [32,35] controlling growth of phyto-pathogens. Production of antibiotics, siderophores, HCN, hydrolytic enzymes acquired and induced systemic resistance.

Phytostimulators Production of phytohormones such as [36, 37] indole acetic acid, gibberellic acid, cytokinins and ethylene

Figure 1-1 The role of intracellular plant growth promoting rhizobacteria (iPGPR) and extracellular plant growth promoting rhizobacteria (ePGPR) in soil ecosystem. 1.4.2 Nitrogen Fixation

Nitrogen (N) is one of the major plant nutrients, required for cellular synthesis of vital biomolecules like enzymes, proteins, nucleic acids (DNA and RNA) and chlorophyll

[38]. More than 78% of nitrogen is present in the atmosphere in the gaseous N2 form which is unavailable to the plants. Plants utilize only fixed forms of nitrogen e.g + - ammonium (NH4 ) and nitrate (NO3 ) for growth. In the biogeochemical nitrogen cycle

1. Introduction

+ the conversion of atmospheric N2 into NH4 ammonium ions is driven by nitrogen - fixation process, which in turn is converted into nitrate (NO3 ) through nitrification process and finally returns to the atmosphere in gaseous nitrogen oxides and nitrogen gas by denitrification process (Figure 1-2). The maintenance and replenishing of fixed N as ammonium is essentially required for the formation of N containing compounds in the living cells of all life forms.

The conversion of the atmospheric nitrogen into available forms takes place by (i) Industrial nitrogen fixation at high temperature and pressure to produce chemical N fertilizers. (ii) Conversion of N2 into oxides of nitrogen in the atmosphere by natural lightening (iii) Biological nitrogen fixation (BNF) i.e the conversion of N2 to NH4+ by diazotrophic prokaryotes.

Figure 1-2 A sketch of nitrogen cycle showing the conversion of atmospheric nitrogen into available forms.

1. Introduction

1.4.3 Biological Nitrogen Fixation (BNF)

In biological nitrogen fixation process, gaseous nitrogen from the atmosphere is reduced to ammonia, by the enzyme nitrogenase [39]. The process of molecular nitrogen fixation is found in phylogenetically diverse groups of prokaryotic organisms, the bacteria and archea, including aerobic, microaerophilic, facultative, and strictly anaerobic microorganisms [40]. This biochemical reaction of dinitrogen conversion into ammonium is highly energy expensive and it requires a significant amount of reducing power, along with energy from ATP [41].

Nitrogenase - + N2 + 8e + 16 ATP + 16 H2O 2NH3 + H2 +16 ADP + 16 Pi + 8H

An enzyme complex called ‘nitrogenase’ found in prokaryotes catalyzes the conversion of atmospheric dinitrogen (N2) in biological fixation process. Nitrogenase enzyme is highly conserved in its role and structure among diverse prokaryotes [42]. The nitrogenase system is composed of two subunits of metallo-proteins. The subunit I or dinitrogenase is larger component which performs nitrogen reduction and also referred as MoFe-protein or component I. The molecular weight of componentI is 220 to 250 kD. Subunit II or component II, is the smaller component and known as dinitrogenase reductase with molecular weight of 60-70 kD. Dinitrogenase reductase pairs ATP hydrolysis to inter-protein electron transport and is composed of two similar subunits encoded by nifH gene. Among nitrogen fixers, nif genes differ in their structural organization. For example in gamma and alpha proteobacteria nifHDK operon is responsible for transcription. In slow growing symbiotic associations nifH and nifDK are separate operons by which transcription is associated [42].

NifH genes have been highly conserved through evolution [43]. This great conservation of nifH genes provides a valuable molecular tools to examine phylogenetic distributions and biological nitrogen fixation in the environment [44, 45]. The nifH gene has one of the largest non-ribosomal database sequences of diverse culturable as well as uncultivated microorganisms from the environment [42]. The nifH gene provides phylogenetic uniqueness that allows construction of trees of relatedness for diazotrophic organisms. In order to analyze biological processes in specific ecosystems without cultivation, nifH gene markers have been employed. nifH

8 1. Introduction genes have been amplified by PCR from environmental samples as well as from pure cultures [45-47].

1.4.4 Diversity of Diazotrophic Bacteria

Several diazotrophic bacteria occur as free-living bacteria in the environment while others (e.g. Rhizobium, Frankia) can induce root-nodules on legumes and non- legumes and live as symbiotic entophytes. The common example of symbiotic relationship between bacteria and plant is Rhizobium-legume symbiosis. A special structure called ‘nodule’ is induced on roots of legumes (chickpea, lentil and other plants) by rhizobia. Free-living diazotrophic bacteria have been isolated from the rhizosphere, rhizoplane and interior of the roots of grasses, cereals and food crops like wheat, rice, maize and sugarcane [48-50]. Free-living nitrogen fixing bacteria are known to colonize rhizosphere of important crops and belonged to different genera (Table 1.3).

1.4.5 The Domain Archea

Archaea are the third domain in the phylogenetic tree of life alongside Bacteria and Eucarya [51, 52] and were considered as an assemblage of extremophilic organisms without a major role in the earth ecosystems. The numbers of known taxa within the Archaea are expanding and include diazotrophs as well. The Archaea are distributed over two main phylogenetic branches based on 16S rRNA sequence comparisons, the Euryarchaeota and the Crenarchaeota [52]. The Euryarchaeota contain the methanogens, the halophiles, and some extreme thermophiles, while the Crenarchaeota contain most of the extreme thermophiles. Within the Archaea, nitrogen fixation has been found only in the methanogenic Euryarchaeota, however, within the methanogens, nitrogen fixation is widespread [53]. M. thermolithotrophicus is the only organism demonstrated to fix nitrogen at 60°C or above. In the Methanobacteriales, nitrogen fixation has been demonstrated for Methanobacterium bryantii [54]. Diazotrophic 15 growth, N2 incorporation, or acetylene reduction has been reported for a number of methanogens. The discovery of Archaea in oceanic plankton has triggered a huge number of studies [55, 56]. These studies presented that Archaea are abundant and diverse group of microorganisms in whole biosphere with a significant impact on nutrient cycling [57]. Evidence for autotrophic growth of some phylotypes of

9 1. Introduction

Thaumarchaeota has been provided in soil [58]. Cultivation of novel archaeal strains and culture-independent techniques in molecular biology have played an instrumental role for recognizing and characterizing novel archaeal metabolisms and for estimating their environmental impact that archaea are important players in carbon and nitrogen cycling.

Table 1.3 Important nitrogen fixing bacteria residing in rhizosphere of different crops plants

Genus PGPR activity Host References

IAA N2 P fixation solubil ization

Azospirillum √ √ wheat, rice, maize, [59] sugarcane and other graminous plants

Acetobacter √ Sugarcane, sugarcane, [60] cotton wood Acinetobacter √ sugarcane, cowpea [61]

Achromobacter √ √ sugarcane [62]

Azotobacter √ √ √ rice [63]

Agrobacterium √ √ sugarcane [64]

Alcaligenes √ wetland rice [65]

Azoarcus √ kallar grass [66]

Bacillus √ √ rice,cowpea, mangrove [67]

Burkholderia √ √ rice, sugarcane, grasses [68]

Enterobacter √ √ √ rice, sugarcane, grasses [69]

Paenibacillus √ √ rice,cowpea, mangrove [70]

Pseudomonas √ √ √ wheat, sugarcane, [64] grasses, mangrove

Rhizobium √ √ legumes, peas, cow pea, [71]

Zoogloea √ √ √ kallar grass [66]

10 1. Introduction

1.4.6 Phosphorus Mineralization by Microbes for Plant Growth Promotion

Phosphorus (P) is the second most important element after nitrogen that plant requires. This element being structural component of the nucleic acids, proteins and phospholipids is involved in important biological processes such as cell division, photosynthesis, biological oxidations and transfer of energy and nutrient uptake by plants [72]. Primarily soil phosphorus originates from weathering of soil minerals such as apatite. Addition of P in soil also occurs from fertilizer application, agricultural -2 4 - waste, plant residues, or bio-solids. Orthophosphate ions (HPO4 and H2 PO ) are produced when apatite breaks down, organic residues are decomposed, or fertilizer P sources are dissolved.

All phosphorus taken up by plants comes from phosphorus dissolved in the soil solution. The amount of soluble phosphorus in the soil solution is very low, as most of phosphorus is insoluble and thus unavailable to plants. The type of P-bearing minerals that form in soil is highly dependent on soil pH. Soluble P, originating from any source, reacts very strongly with Fe and Al to form insoluble Fe and Al phosphates in acidic soils and with Ca to form insoluble Ca phosphates in alkaline soils. Recent interest generated in finding P solubilizing microorganisms that solubilize the phosphate present in soil is mainly due to the rising costs of phosphorus fertilizers. Therefore, phosphate solubilizing rhizospheric bacteria offer a very attractive opportunity to increase the bioavailability of phosphorus to plants [73]. Several reports have examined the ability of different bacterial species to solubilize insoluble inorganic phosphate compounds [74].

Plants and microorganisms use phosphatase enzyme to mineralize (hydrolyze) organic P for uptake. Increased activity of phosphatases occurs in response to P deficiency as part of P starvation responses [75]. Solubilization of phosphate due to the production of organic acids by microbes is considered a major mechanism for P solubilization [76]. The mineral phosphate solubilizing bacteria use root exudates e.g. sugars as carbon source to form organic acids. A number of organic acids like malic, glyoxalic, succinic, fumaric, tartaric, alpha keto butyric, oxalic, citric, 2-ketogluconic and gluconic acid have been detected in cell-free supernatant growth medium of bacteria [77]. The amount and type of the organic acids produced varies with the

11 1. Introduction microorganism. Organic acids produced by phosphate solubilizing bacteria are used to lower pH of the medium. Due to existence of equilibrium between anions and protons, the protons are consumed in the dissolution of the phosphorus [78].

Chelation of cations has also been implicated in phosphate solubilizing. Chelation involves the formation of two or more coordinate bonds between an anionic or polar molecule and a cation, resulting in a ring structure complex [79]. Organic acid anions, with oxygen containing hydroxyl and carboxyl groups, have the ability to form stable complexes with cations such as Al3+, Ca2+, Fe2+ and Fe3+ and, that are often bound with phosphate in poorly solubilized forms [80].

1.4.7 Phytohormone Production by PGPR for Plant Growth Promotion

Phytohormone production is a well-established phenomenon that contributes to plant growth promotion by PGPR [32, 81]. Phytohormones are small singling molecules used by the plants for their growth and development in variable developmental and environmental conditions. Plant growth promoting abilities of PGPR are often related to the production of these growth regulators [82]. Several bacterial genera have been reported for the production of phytohormones (IAA) including Azospirillum, Acetobacter, Achromobacter, Azotobacter, Bacillus, Enterobacter, Pseudomonas, Rhizobium, and Xanthomonas [83, 84]. Phenyl acetic acid (PAA) is an auxin-like molecule, derived from amino acid metabolism and is known for its weak auxin activity. Based on its aromatic structure, it was speculated that PAA might be derived from phenylalanine. Azospirillum have been reported for the production phytohormones, like indole-3-acetic acid and more specifically PAA [57]. PAA could only be identified in supernatant extracts from Azospirillum brasilense cultures grown in LB medium PAA has been demonstrated to display growth-inhibitory activity towards Gram-negative bacteria (including P. syringae and E. coli), Gram- positive bacteria (including Bacillus subtilis and Staphylococcus aureus) [364,365,367]. A high degree of similarity between IAA biosynthesis pathways in plants and bacteria has been noticed and its role in plant-microbe interaction has been studied. Tryptophan has been identified as a main precursor for IAA biosynthesis pathways in bacteria. Five different pathways for biosynthesis of IAA have been identified.

12 1. Introduction

(i) Indole-3-acetamide (IAM) pathway

(ii) Indole-3-pyruvate (IPyA)

(i) Tryptamine (TAM) pathway

(ii) Tryptophan side-chain oxidase (TSO)

(iii) Indole-3-acetonitrile (IAN)

The best characterized pathway in bacteria is IAM pathway with two step reactions. In first step tryptophan-2-monooxygenase (iaaM) converts trptophan into IAM. In the second step IAM hydrolase encoded by iaaH converts IAM into indole-3- acetic acid (1AA). The genes iaaM and iaaH have been cloned and characterized from various bacteria, such as Agrobacterium, Bradyrhizobium, Pseudomonas, Pantoea and Rhizobium [85, 86]. Indole-3-pyruvate (IPyA pathway) pathway has been identified in a number of bacterial genera including Azospirillum, Bradyrhizobium, Cyanobacteria and Rhizobium. The first step is transamination of tryptopan into indole-3-pyruvate. In the next step indole-3- acetic acid is decarboxylated into indole-3-acetaldehyde. In the last step this aldehyde intermediate is oxidized into indole-3-acetic acid [87]. Insertional inactivation of the pathway resulted in a lower IAA production e.g. up to 90% reduction in Azospirillum brasilense [88] indicating the importance of the IPyA pathway in auxin production. In bacteria, the tryptamine (TAM) pathway has been identified in Bacillus by identification of tryptophan decarboxylase activity [88] and in Azospirillum by detection of the conversion of exogenous tryptamine to IAA [89]. A bacterial tryptophan-independent pathway could be demonstrated in Azospirillum brasilense by feeding experiments with labeled precursors. This pathway is predominant in case no tryptophan is supplied to the medium [88].

IAA-mediated ethylene production could increase root biomass, root hair number and consequently the root surface area. Involvement of PGPR formulated cytokinins, showed increase in root initiation, cell division, cell enlargement and increase in root surface area of crop plants through enhanced formation of lateral and adventitious roots [36, 37]. Although ethylene is essential for normal growth and development in plants, at high concentration it can be harmful as it induces defoliation and other cellular processes that may lead to reduced crop performance. Thus, rhizobacteria assist in diminishing the accumulation of ethylene levels and re-establish

13 1. Introduction a healthy root system needed to cope with environmental stress. The primary mechanism includes the destruction of ethylene via enzyme ACC deaminase. Rhizosphere bacteria such as Achromobacter, Azospirillum, Bacillus, Enterobacter, Pseudomonas and Rhizobium have been reported with ACC deaminase activity [22, 27]. IAA-mediated ethylene production could increase root biomass, root hair number and consequently the root surface area of PGPR inoculated tomato plants [17]. Involvement of PGPR formulated cytokinins have also been observed in root initiation, cell division, cell enlargement and increase in root surface area of crop plants [36,37]

1.4.8 PGPR as Biofertilizers

Application of PGPR strains as Biofertilizers is increasing due to high price of chemical fertilizers which are being used extensively in agricultural system. PGPR have been continuously used to enhance the plant growth, seed emergence and overall yield of crops in different agro-ecosystems. Bio-inoculant application of nitrogen fixing bacteria such as Azospirillum, Azotobacter, Acinetobacter, Bacillus, Burkholderia, Enterobacter and Pseudomonas resulted in increased plant growth and yield of various crops [24].

Inoculation of rice varieties with Pseudomonas strain K1 showed an increase in shoot biomass and grain yield over that of non-inoculated control plants [66]. Growth responses of wheat after the inoculation with rhizobacteria suggested that the growth of wheat basically depends on a number of factors like plant genotype, nature of PGPR inoculants as well as environmental conditions [90]. A balanced nutrition of various crops such as sorghum, barley, black gram, soybean and wheat can be achieved by inoculation of these plants with diazotrophic and p-solubilizing bacteria in combination rather than single microbe inoculation [91, 92]. Co-inoculation of Enterobacter and rhizobia resulted in improved growth and yield of chickpea [93, 94]. Co-inoculation of Bradyrhizobium with plant growth promoting rhizobacteria (PGPR) enhanced the nodulation and root and shoot growth in mung bean [95].

The use of microbial preparations for increasing crop production has become common practice in many countries including Pakistan. Several types of biofertilizers are being produced commercially by public research organizations as well as private sector. NIBGE is providing biofertilizer (Bio-power) for almost all major crops

14 1. Introduction including wheat, rice, sugarcane, maize and leguminous crops. This product is based on different consortia of beneficial bacteria and primarily contains a combination of nitrogen fixers, P-solubilizer and IAA producers.

1.5 Effect of Transgenic Plants in Rhizosphere Environment In countries where GMO technology has been accepted, the land area planted for commercial production of transgenic plants is increasing every year [96]. The effects of transgenic plants on the soil and ecosystem function should be carefully evaluated before the release of any transgenic plant variety. Biosafety studies on plants should include the study of their effects on soil organisms [97]. Plants are known to have a profound effect on the abundance, diversity and activity of soil microorganisms living in close proximity with their roots in a soil zone defined as the rhizosphere [98]. Bacteria inhabiting the rhizosphere, also referred as rhizobacteria, are responsible for numerous functions including nutrient cycling and decomposition, which can significantly influence vegetation dynamics [99]. Among these, plant growth- promoting rhizobacteria represent one of the best-characterized functional group of rhizobacteria known for playing a significant role in plant health and plant development [100, 101]. As it can be assumed that any significant impact of plant genetic transformation might alter these fundamental microbial processes, rhizobacteria have been defined as good indicator organisms and have been studied to assess the general impact of GMPs on the soil environment [102].

1.5.1 Effect of Transgenic Plants on Soil Microorganisms

Different transgenes, with expression of novel plant proteins, can potentially alter diversity and abundance of rhizobacteria by direct release of novel proteins into the rhizosphere through plant root exudation or enhance production and release [103]. Some unintentional effects on specific pests or pathogens may be carefully investigated. Similarly risk to alter non-targeted rhizobacteria may be evaluated [104]. It has been reported that Bt-recombinant DNA and expressed Cry proteins were released in soils through root exudation and plant tissue decomposition where they remained intact and chemically active for extended periods of time [105, 106]. T4 lysozyme a common transgene protein, is not only present in root exudates but it maintains biological activity after entering the soil [107]. Root system architecture, composition of root exudates and their quantity, and ability of soil nutrient utilization are crops or cultivar-related

15 1. Introduction factors which can be used as determinant in plant and rhizobacterial interactions [108]. Different studies presenting the effects of transgenic plants on soil micro-organisms have been summarized in Table 1.4.

Table 1.4 Effect of transgenic plants on structure and functions of soil microorganisms and their communities

Plant Transgenic trait Effect on soil biota Reference Cotton Insect resistance Significant stimulation in [105] (cry1ac) growth of culturable bacteria and fungi with change in substrate utilization. (CrylAc and CpTI ) No apparent impact on [109] microorganism populations in rhizosphere soil Wheat Pathogen Variation in cultivable [110] Resistance rhizospheric community (Root rot resistance Chromosome S-615) Rice Insect resistance No persistent effect on soil [111] (Cry1Ab) enzymatic activities (Cry1Ca) No obvious adverse effects on the growth of Chlorella pyrenoidosa.

Maize (i) Insect resistance No significant differences in [111] (cry1Ab) earthworm, micro-rthropods, nematodes and protozoan May affect AMF under [112] different environmental conditions Significant changes occurred [113] in the abundances (revealed [114] by qPCR) of ammonia- oxidizing bacterial and archaeal communities (ii)Herbicide No effect of transgenic maize [115] resistance was observed on genetic (pat) diversity of bacterial communities in rhizospheric samples.

16 1. Introduction

Potato (i) Insect resistance Altered CLPP pattern of [116] (Invertebrate pest microbial community in control conA and transgenic rhizosphere GNA lections) (ii) Expressing the Transgenic potato plant [107] phage T4 lysozyme roots showed high gene bactericidal activity against Bacillus subtilis adsorbed artificially on potato roots as compared to non- transgenic plants (iii) T4 lysozyme No difference in growth of [117] producing plant lines bacterial communities was DL4 and DL5 observed between the rhizosphere of transgenic potato and non-transgenic potato varieties. Soybean Herbicide resistance Incidence of Fusarium [118] (Glufosinate tolerant (soilborne pathogen) on EPSPS) transgenic soybean roots was greater within 1 week after the application of glyphosate as compared to non-transgenic isoline. Alfalfa Organic acid Qualitative changes in the [119] expression abundance of bacterial (a nodule-enhanced phylogenetic groups between malate rhizosphere soils of dehydrogenase) transgenic and untransformed alfalfa. Tobacco Expression of Numbers of collembella [120] proteinase inhibitor I colonies associated with (cryIIIA. Bacillus transgenic tobacco litter are thuringiensis less as compared with non- var.tenebrionis (Bt.) transgenic litter. Whereas nematode population is high in transgenic litter as Rape (i)Herbicide Rhizosphere and root interior [122] resistance microbial populations (Glufosinate associated with a transgenic tolerant) (pat) canola have altered CLPP and fatty acid methyl ester (FAME) profiles compared to

17 1. Introduction

the profiles of a non- transgenic counterpart.

(ii)Herbicide From root interior and rhizosphere [123] resistance fewer Arthrobacter, Bacillus, (pat) Micrococcus and Variovorax isolates, and more Flavobacterium and Pseudomonas isolates were found in the root interior of Quest compared to Excel or Parkland. The bacterial root-endophytic community of the transgenic cultivar, Quest exhibited a lower diversity compared to Excel or Parkland. Arabidopsis No effect on E. coli populations [124] thaliana

1.6 Diversity of Culturable and Non-Culturable Bacteria in the Rhizosphere Biosphere is dominated by microorganisms but only 0.1-10% microorganisms are culturable while the vast majority remains uncultured [125]. Microbial diversity and community structure cannot be described precisely without having the information about non-cultured microorganisms in a particular environment [126]. Cell- independent molecular approach for studying the microbial population and community structure inhabiting in environmental samples on the basis of 16S rRNA gene sequence analysis has explored a new perspective in microbial ecology [47, 127]. These “metagenomics” studies are based on DNA isolated from environment and harbor the genome of the entire population in the environment “Metagenome”. These studies help in understanding of the community structure and the metabolic potential of a community [125, 128]. These metagenomic studies helped in the detection and identification of genes involved in production of antibiotics, anticancer agents, industrial enzymes and the enzymes involved in bio-degradation of heavy metals [129, 130]. Soil microbial diversity and community structure depends upon various factors i.e soil pH, temperature, moisture contents, nature and amount of root exudates, crop rotations, soil nutrient status and agricultural practices [131-134].

18 1. Introduction

1.6.1 16S rRNA Gene as a Tool for Studying Diversity of Culturable and Non-Culturable Bacteria

Bacteria are usually identified using phenotypic techniques that are mainly based on production of enzymes and metabolism of carbohydrates. A number of biochemical and morphological methods have been employed for identification of bacteria [135]. These methodologies are based on chromogenic enzymatic reactions and are available in commercial kits (BioLog Inc, Hayward, CA, USA; API20E and API ZYM systems by Vitek, Inc, St. Lois, MO, USA). Bacterial identification on the bases of intrinsic antibiotic resistance [136, 137], fluorescent antibody techniques, polyacrylamide gel electrophoresis of total protein [138] and fatty acid analysis [139], have been used. DNA based genotypic methods DNA-DNA hybridization, DNA-RNA hybridization, use of random or specific primers in PCR, RFLP (Restriction Fragment Length Polymorphism) have also been used successfully for identification of bacteria. Ribosomes are important component of protein synthesis machinery in all living cells including bacteria. A bacterial ribosome is composed of multiple ribosomal proteins and three ribosomal RNAs i.e 23S rRNA, 16S rRNA and 5S rRNA. The genes that encode for RNAs are organized in the genome as rrn operon and multiple rrn operons in a bacterial genome.

The first bacterial 16S rDNA containing 1524 nucleotides (GenBank accession no.J01859) was sequenced in 1972 by Ehresmann and his colleagues for Escherichia coli [140]. The nucleotide sequences among various bacteria are highly conserved, the conservation and divergence reflect bacterial evolution and each bacterial species has its unique 16S rDNA sequences [141]. With the invention of polymerase chain reaction (PCR) technology, 16S rDNA sequencing became a tool for bacterial phylogeny studies. Partial or complete 16S rDNA can be amplified by PCR. Conserved regions of 16S rDNA allow design of highly conserved primers for nearly universal amplification of most bacterial species [106, 142]. The nucleotide sequences of the amplicons are determined, compared with a database, yield homology matches and consequent identification of a particular bacterium. It is the variable regions of 16S rDNA that give discriminatory power (Figure 1-3). The longer sequences reads give more accurate identification, however, at least even 200 bp may yield meaningful results. Universal PCR primers are chosen as complementary to the conserved regions most commonly

19 1. Introduction near the ends of the gene. The sequence of the variable region in between is used for the comparative taxonomy [143] and these primers are used to amplify the 16S rRNA gene (Table 1.5). Presently universal primer pairs are available for amplification of partial or full length amplification of 16S rRNA gene [144-146]. There are multiple public and private databases available, such as GenBank, Ribosomal Database Project (RDP).

1.6.2 Bacterial Diversity by Pyrosequencing Analysis of 16S rRNA Gene

Traditional molecular techniques like DNA finger printing, cloning, and Sanger’s sequencing cover only a single aspect either bacterial communities in number of soils or bacterial diversity in few soil samples. The less tiresome and most efficient technique to study the bacterial community structure and composition on the basis of 16S rRNA sequence analysis in soil is molecular pyrosequencing. This new technique enables us to study the depth as well as width of the soil samples [129, 147]. Pyrosequencing provides a huge amount of parallel sequences obtained from a single DNA as compared to traditional methodology like cloning. Pyrosequencing is a bioluminometric DNA sequencing technique based on sequencing by synthesis [148]. This technique relies on the real-time detection of inorganic pyrophosphate (PPi) released on successful incorporation of nucleotides during DNA synthesis (Figure 1-5).

20 1. Introduction

Figure 1-3 Schematic representation of 16S rRNA gene annotated with variable regions (V1 to V9) of 16S rRNA

Figure 1-4 16S rRNA gene with three distinct variable regions and primers [149].

21 1. Introduction

Table 1.5 Sequences of PCR primers for amplification of 16S rRNA gene*

Primer name Sequence (5'-3') Reference 27F AGAGAGTTTGATCCTGGCTCAG [150] 1492R ATTAGATACCCNGGTAG [151]

PA AGACTTTGATCCTGCTCAG [144]

PH AAGGAGGTGATCCAGCCGCA [144] 338F ACTCCTACGGGAGGCAGCAG [152] 533R CCAGCAGCCGCGGTAAT [153]

787F AGGATTAGATACCCTGGTA [154] 530F TAAAACTYAAAKGAATTGACGGG [155] 355R ACTGCTGCSYCCCGTAGGAGT CT [155] 1100R YAA CGA GCG CAA CCC [156] 1100R GGGTTNCGNTCGTTG [157]

*http://bioinfo.unice.fr/454/454_analyses_of_diversity.html PPi is immediately converted to adenosine triphosphate (ATP) by ATP sulfurylase, and the level of generated ATP is sensed by luciferase producing photons. Unused ATP and deoxynucleotide are degraded by the nucleotide degrading enzyme apyrase. The presence or absence of PPi, and therefore the incorporation or non-incorporation of each nucleotide added, is ultimately assessed on the basis of whether or not photons are detected [158].

Figure 1-5 Schematic representation of progress of enzymatic reaction in pyrosequencing DNA template with hybridized primer and four enzymes involved in pyrosequncing are added to a well of a micro-titer plate. The four nucleotides are added step wise, and incorporation is followed using the enzyme ATP sulfurylase and luciferase. The unincorporated nucleotides of each addition are continuously degraded by apyrase allowing addition of subsequent nucleotide.

22 1. Introduction

1.6.3 Functional Genes for Bacterial Identification and Detection

Functional genes with conserved nucleotide sequences have a supportive role in bacterial identification and phylogenetic grouping of bacteria. For identification and phylogenetic studies of diazotrophic bacteria, nifH is the most commonly used gene after 16S rRNA. This gene encodes for components of nitrogenase enzyme responsible for nitrogen fixation. The amplification and sequencing of this gene helps in grouping of nitrogen fixing bacteria [159-162]. Some PGPR also possess 1-aminocyclopropane- 1-carboxylic acid (ACC) deaminase gene that controls the plant ethylene level and results in enlargement of root system. Amplification of ACC deaminase gene in PCR is also used as supportive tool for identification and grouping of PGPR [163, 164]. PCR amplification and sequence analysis of genes like gdh (encodes membrane glucose dehydrogenase) and pqqE (a gene having a role in P-solubilization) have also been used to determine relatedness of specific bacterial groups [165].

1.6.4 nifH Metagenomics: A Tool to Study the Diversity of Diazotrophic Bacteria

The nifH gene, that encodes the iron protein subunit of nitrogenase, is often used as a biomarker gene to assess the diversity of nitrogen fixing organisms in various environments. This gene is conserved among diazotrophs, and it provides a good phylogenetic correlation between nif H and the 16S rRNA gene [45, 166]. Bacterial diversity on the basis of nifH gene amplification and sequencing of soil DNA has been investigated from rhizosphere of mangrove forest of China [167] amazon rain forest [168], oak-hornbeam forest (Chor-bush Forest) near Cologne, Germany [169], soils from France and Senegal [170], Douglas ﬁr forest in USA [171] and rice rhizosphere at Kyushu University Farm, Japan [172].

Polymerase chain reaction (PCR) of the nifH gene combined with cloning and sequencing gives information on the diazotrophic composition in an environment. Numerous PCR primers targeting the nifH genes have been designed with different range of specificity, from “universal” covering different diazotrophic taxa [170, 173, 174]. Using the nifH gene as a molecular marker in natural environments provides evidence for potential nitrogen fixation [175]. nifH gene is the most thoroughly studied among the genes of the nif operon, with an extensive collection of sequences in the data

23 1. Introduction bank obtained from both cultured and uncultivated microorganisms from multiple environments [172, 176, 177]. Cultivation-independent studies using clone library analyses [177], denaturing gradient gel electrophoresis (DGGE) [178] and terminal or complete restriction fragment length polymorphism (RFLP) methods [170] have already shown the great diversity of nifH genes in natural environments. Despite this extent of knowledge, little is known about the assemblage of nitrogen fixing communities in the complex soil environment [179].

1.6.5 Real Time PCR: A Gene Quantification Approach to Study the Abundance of nif H and 16s rRNA Gene

Real-time PCR (Quantitative PCR or Q-PCR) is widely used in microbial ecology, to determine gene abundance or transcript numbers present in specific environmental samples. Target specificity of any Q-PCR assay is determined by the selected primers that allow the quantification of taxonomic or functional gene markers present in a mixed community. Q-PCR is a robust, sensitive, and highly reproducible method to quantitatively track phylogenetic and functional gene changes under varying environmental and experimental conditions. Q-PCR provides data sets that describe the abundance of specific bacteria or genes to compare other quantitative environmental data sets. The importance of Q-PCR is increasing in microbial ecology as it provides understanding about the roles and contributions of particular microbial and functional groups within ecosystem functioning [180]. Real-time PCR monitors amplicons production during each PCR cycle using a fluorescent probe that emits fluorescence during the reaction as an indicator of the extent of amplification of the target [181]. The fluorescent signal is directly proportional to the amplification of the target (number of new copies made). The equipment monitors the signal’s increase until it reaches the exponential level, which determines the threshold cycle. By definition, the threshold cycle is the first cycle in which there is a significant increase in fluorescence above the background or a specified threshold value. Through threshold cycle measurement, comparative quantification analysis allows the determination of the concentration of target amplicons. The higher the starting DNA copy number, the quicker (fewer cycles) the amplicons threshold is reached. SYBR Green I, a dye that intercalates non- specifically to all double- stranded DNA, is a good and simple choice for real-time PCR. Standardized in house protocols allow confirmation of the desired product

24 1. Introduction

(amplicons) from primer-dimer or non-specific amplification by melting curve analyses. The melting curve, generated by the real-time PCR equipment, is a plot of fluorescence versus temperature, when performed with an intercalating dye such as SYBR Green I. The melting temperature of a specific DNA sequence, which is a function of the number of base pairs and % GC content, is defined as the temperature at which 50% of the DNA is in double-stranded form and 50% is in single-stranded form. The need to quantify microbial populations is a pressing one in many areas of microbial ecology. The first applications of Q-PCR in microbial ecology were reported in 2000 to target 16S rRNA genes [182, 183] determined the spatial and temporal quantitative differences in the distributions of Synechococcus, Prochlorococcus and archaea in marine waters [184] quantified archaeal 16S rRNA gene numbers within samples from a deep sea hydrothermal vent effluent, hot spring water and from freshwater sediments. By targeting highly conserved regions of the 16S rRNA gene, Q- PCR assays have been designed to quantify ‘total’ bacterial (and/or archaeal) numbers while targeting of taxa-specific sequences within hypervariable regions within the gene enables quantification of sequences. Q-PCR has also been applied to quantify functional genes within the environment. By targeting functional genes that encode enzymes in key metabolic or catabolic pathways and genetic potential for a particular microbial function within a particular environment can be assessed. To understand microbial functioning in the environment it is essential to know what genes are present and the diversity of these genes to determine their abundance and distribution within the environment. Quantification of functional genes involved in ammonia oxidation [185], nitrate reduction and denitrification [186], sulphate reduction [187], methanogenesis [188] and methane oxidation [189] have been investigated.

Pakistan falls into arid and semi-arid climatic conditions and agriculture in the country is mainly dependent on the scanty and unpredictable rainfall. Therefor irrigation water is considered as the most important limiting factor for crop production (368, 369). High salt concentrations in soil are also major factor contributing to low crop production as significant portion of agricultural lands has been wasted due to salinity. Different approaches have been used for crop improvement which include the development of transgenic plants. Transgenic crops e.g AVP1 transgene, engineered to tolerate drought and salinity could significantly increase yields for many developing countries. However legal issues related to the release of transgenes for cultivation is in

25 1. Introduction the country have to be resolved that transgene is “Biosafe”. Biosafty of the AVP1 transgenic cotton and wheat has to be investigated and the present study was designed to study any effects of transgenes on indigenous bacterial populations.

The main objective of the present study was the risk assessment of soil environment by comparing the diversity of PGPR from rhizosphere of transgenic and non-transgenic plants (cotton and wheat). We isolated and identified plant growth promoting rhizobacteria from the rhizosphere and after characterization, plant growth promotion ability of bacterial strains was assessed by inoculating transgenic as well as non-transgenic plants of wheat and cotton. The bacterial strains that showed positive growth promotion were considered as biofertilizer of cotton and wheat plants, respectively. Bacterial population in the rhizosphere of transgenic and non-transgenic plants (cotton and wheat) was studied by cfu/g and MPN count on different growth media and by real time quantification of nifH and 16S rRNA gene directly amplified from soil DNA. Moreover, bacterial diversity in the rhizosphere of transgenic as well as non-transgenic plants was investigated by 16S rRNA and nifH sequence analysis using culture-independent techniques.

2. Materials and Methods

2.1 Isolation of Bacteria from the Rhizosphere of Cotton and Wheat Soil samples were collected from rhizosphere of transgenic and non-transgenic cotton and wheat plants that were grown separately in green house under controlled conditions. The representative soil samples along with some fine roots were collected and stored at 4°C and used for further studies. These rhizosphere soil samples were used for preparation of 10X serial dilutions up to 10-5 in saline solution (0.89% NaCl). From each dilution (10-3 to10-5), 100µL were spread on nutrient agar plates [190] and Pikovskaya agar plates [191]. The plates were incubated at 30°C for 24 hours to 72 hours. Bacterial colonies were counted on the bases of difference in their morphology. From Pikovskaya agar plates the colonies with clear halo zone were considered positive for phosphorus solubilization. Pure bacterial colonies were obtained by continuous streaking on fresh plates containing respective growth medium.

2.1.1 Isolation of Diazotrophic Bacteria by Enrichment Culture Technique Fresh root pieces (8-10 cm long) with adhering soil were added to 1 mL semi-solid NFM medium in 1.5 ml eppendorf tubes [192]. After two days, 50 µL from each tube were transferred to new eppendorf tubes containing fresh semi-solid NFM. This procedure was repeated five to six times. Each time bacterial growth was observed under microscope. A full loop with growth medium from eppendorf was streaked on nutrient agar plates. These bacteria were further purified by repeated sub-culturing on nutrient agar.

2. Materials and Methods

2.2 Morphological Characterization of Bacteria 2.2.1 Colony and Cell Morphology Single colonies from purified bacterial culture were transferred to nutrient agar broth. A single colony was streaked on fresh agar plate and incubated for 24 hours. Colony morphology (i.e. color, shape, margins) was observed under light microscope (Labophot-2 Nikon, Japan). Bacterial cell morphology and motility were studied by taking a drop of bacterial suspension on a glass slide by mixing a drop of sterilized deionized water and adjusting a cover slip on it. Cell morphology and shape were recorded under the microscope (Microscope, LaboPhot 2 Nikon, Japan)

2.2.2 Culture Preservation

Purified bacterial isolates were grown in LB broth at 28oC for 48hours and preserved in glycerol (20%) at -80°C.

2.3 Phosphorus Solubilization 2.3.1 Qualitative Assay for Phosphorus Solubilization by Bacteria Bacterial isolates selected from Pikovskaya medium were grown in LB broth medium at 30oC for 48hours with shaking (300rpm). From this culture 50µL were spotted on Pikovskaya agar plates [192]. These plates were sealed with para-film and incubated at 30°C for 2 weeks. Bacterial colonies with clear halo zone formation were selected and considered as positive strains for phosphate solubilization.

2.3.2 Quantitative Estimation of Phosphate Solubilization by Bacteria

Quantitative estimation of phosphorus solubilization by bacteria was done by molybdate blue color method [193]. Bacterial isolates were grown in 100 mL conical flask containing 50 mL of Pikovskaya broth medium (pH 7), supplemented with tri- calcium phosphate (5 g.L-1) as insoluble P source [191]. These cultures were grown at 30°C on a shaker (150 rpm) for 15 days. Bacterial growth was transferred to 50 mL clean falcon tubes. Cell-free supernatant was harvested by centrifugation at 5000 rpm for 10 minutes (Biofuge Primo, thermoelectron Corporation, Germany). The supernatant was filtered through 0.45 µm filter (Orange Scientific GyroDisc CA-PC, Belgium) and O.D was recorded at 882 nm on a spectrophotometer (Camspec M350 double beam UV visible, UK). Solubilized phosphate was determined by preparing

28 2. Materials and Methods standard curve of known concentration of KH2PO4 (2, 4, 6, 8, 10, 12 ppm) using Regent A, and Reagent B.

For preparation of regent A, 12.0 g of ammonium paramolybdate [(NH4)

Mo4O2.4H2O] was dissolved in 250 mL of distilled water. Potassium antimony tartrate solution was prepared separately by dissolving 0.290 g of Potassium antimony tartrate in 100 mL of distilled water. Both solutions were added to 1.0 L of 5N H2SO4, mixed thoroughly and 2L volume was made by adding distilled water. Reagent A was stored in Pyrex glass volumetric flask in dark. For preparation of reagent B, 1.056 g of ascorbic acid was dissolved in 200 mL of Reagent A. Reagent B was prepared fresh every time when required.

For preparation of stock solution, 0.439 of KH2PO4 was dissolved in 500 mL of distilled water, thoroughly shaken in volumetric flask and diluted to 1.0 L by distilled water. Five drops of toluene were added to stop microbial activity. This stock solution containing 100 ppm soluble phosphorous was diluted to make 2, 4, 6, 8, 10, 12, 14, 16 and 20 ppm solution of soluble P for spectrophotometer analysis. Two mL of these solutions and 4.0 mL of reagent B were mixed and diluted with distilled water up to 25 mL. Blue color developed within approximately 10 minutes. A blank solution was also prepared by adding 4.0 mL of reagent B into 21 mL of distilled water. Optical density of these solutions was measured on spectrophotometer (Camspec M350-Double Beam UV-Visible Spectrophotometer, 39 UK) at 882 nm.

A graph was plotted between optical density and concentration (ppm) of standard solution. Same procedure was repeated for filtered cell-free supernatants of bacterial cultures for measuring P solubilization.

2.3.3 Extraction and Quantification of Organic Acids Produced By Bacteria in Pikovskaya Medium Organic acids produced by bacterial cultures in Pikovskaya medium were extracted by mixing the cell-free supernatant with equal volume of ethyl acetate. Ethyl acetate was evaporated to dryness. Organic acids were re-suspended in 1.5 mL of methanol and filtered through 0.2 µm filters (Orange Scientific Gyro Disc CA-PC, Belgium). The samples were analyzed on HPLC PERKIN ELMER series 200 with 20 µL auto- sampler PE NELSON 900 series interface, PE NELSON 600 series link and PERKIN ELMER NCI 900 Network Chromatography interface using Diode-array detector at

29 2. Materials and Methods

210 nm and their UV spectra (190-400 nm), Microgaurd cation-H Precolumn. Aminex HPx-87H analytical column was used for separation. Sulfuric acid (0.001 N) was used as mobile phase with flow rate of 0.3 mL/minute. Solutions (100 µg/mL) of acetic acid, citric acid, malic acid, succinic acid, gluconic acid, lactic acid and oxalic acid were used as standard. Peak area and retention time of samples were compared with standards for quantification of organic acids [79].

2.4 Indole Acetic Acid Production by Bacterial Isolates 2.4.1 Colorimetric Estimation of IAA by Salkowski's Reaction (Spot Test) To determine indole acetic acid (IAA) production, bacterial cultures were grown at 30°C in LB medium supplemented with tryptophan (100 mg/L). After incubation for five days, cultures were centrifuged at 5,000 rpm for 10 minutes to obtain cell-free supernatant and pH was adjusted to 2.8 with HCl (1N). Salkowski’s reagent (1.0 mL of 0.5M FeCl3, 30 mL of conc. H2SO4 and 50 mL dH2O) was prepared for qualitative analysis of IAA. Different standards of IAA (1000, 100 and 10 µg/mL) were prepared. Equal volumes of cell-free supernatant, and Salkowski’s reagent (e.g. 250 µL of each) were mixed. Development of pink color indicated the IAA producing ability of bacterial strain.

2.4.2 Quantification of IAA Production

For quantification of indol-3-acetic acid (IAA) production, cell-free culture medium was obtained by centrifugation at 5000 rpm for 15 minutes. After adjusting 2.8 pH with HCl (IN) extraction was done with equal volumes of ethyl acetate [194]. This mixture was evaporated to dryness and re-suspended in 1 mL of ethanol. The samples were analyzed on HPLC (Varian Pro star) using UV detector and C -18 column. Methanol: acetic acid: water (30:1:70 v/v/v) was used as a mobile phase at the rate of 1.0 mL/min. Pure indole -3-acetic acid (1000 µg/mL) was used as standard. Computer software (Varian) was used to compare the retention time and peak area.

30 2. Materials and Methods

2.5 Identification of Bacterial Isolates by 16R rRNA Gene Sequence Analysis 2.5.1 DNA Extraction from Pure Cultures of Bacterial Isolates For identification of bacterial isolates by PCR amplified 16S rRNA gene sequence analysis, DNA from pure bacterial cultures was extracted by CTAB method with minor modifications [195]. Single bacterial colony from nutrient agar plates was inoculated to nutrient broth (5 mL) grown for 24 hours at 30°C with continuous shaking on shaker 150 rpm (Kuhner shaker, Switzerland). Cultures were centrifuged at 10,000 rpm for 2 minutes to pellet down bacterial cells. These cell pellets were re-suspended in 567 µL TE buffer (Tris, EDTA, pH 8). Bacterial cell lysis was done by adding 30µL of 10% (w/v) SDS (sodium dodycyle thiosulphate), followed by incubation at 37°C for one hour. After incubation, 100 μL NaCl 5M and 80 μL of CTAB [Cetyl trimethyl ammonium bromide; 10% CTAB/0.7 M NaCl] were added, mixed thoroughly and kept at 65oC for 10 minutes. The lysate was centrifuged at 10,000 rpm for 10 minutes. The supernatant was extracted twice with 780 µL chloroform/isoamyl alcohol (24:1). It was followed by extraction with 780 µL of phenol/chloroform/isomyl alcohol (25:24:1). The supernatant was incubated at -20°C for 30 min, after adding 20 µL of Na acetate (3M, pH 5.2) and 1mL of absolute ethanol. DNA was then precipitated by centrifugation at 13,000 rpm for 20 minutes. Washing of DNA pallet was done with 70% ethanol before drying under vacuum. The DNA pellet was dissolved in 100 µL double distilled deionized water and stored at -20° C for further use.

2.5.2 Identification of Bacterial Isolates

16S rRNA gene of bacterial isolates from cotton and wheat was amplified by PCR using conserve primers PA and PH [144]. PCR amplification was performed in a total volume of 25 µL, containing 1 µL template DNA of 40 ng/µL concentration, 2.5 μL 10X Taq polymerase buffer, 0.5 μL 10 mM dNTPs, 2 μL of 25 mM MgCl2, 1 μM each of primer and 0.2 units of Taq DNA polymerase. PCR was performed in a thermal cycler (Eppendorf, Germany). Conditions for PCR were 95°C for 5 minutes, followed by 30 cycles (95°C for 1 minute, 52°C for 1 minute, 72°C for 3 minutes) and final extension at 72°C for 10 minutes. PCR reactions were analyzed by 1% (w/v) agarose gel electrophoresis in 1X TAE buffer and visualized under UV light after staining with ethidium bromide (0.2-0.5 μg/mL). The gel was run at 50V for one hour with 1kb DNA

31 2. Materials and Methods ladder (Fermentas, Germany) as a size marker. The desired bands were eluted from the gel. PCR products were purified with QIA quick PCR purification kit (QIAGEN, USA) according to the manufacturer instructions and sent for sequencing to Macrogen Korea. The obtained sequences of 16S rRNA were trimmed (Bio-Edit 7.1) and identified through BLAST search at NCBI (National Centre for Biotechnology Information) (www.ncbi.nlm.nhi.gov). These sequences were deposited to GenBank EMBL and accession numbers were obtained. The sequences that showed closely related homology and few others sequences including type strains of related genera were downloaded as FASTA file format. These sequences were subjected to multiple alignment by CLUSTAL W [196] and phylogenetic analysis (NJ) outlined by [197] was performed using software MEGA6. The bootstrap replicate (BS) values of > 50% or greater represent well supported nodes and thus only those were retained.

2.6 Plant Inoculation Experiments 2.6.1 Soil Analysis and Plant Material AVP1 transgenic and non-transgenic cotton plants were provided by Gene Transformation Lab, NIBGE. The soil (sandy loam soil, total N: 0.007%, available N: 0.0044%, available P: 1.85ppm, pH: 8.4, EC: 3.15 m/S, organic matter 0.006%) used in all inoculation studies was collected from experimental fields of NIBGE.

2.6.2 Bacterial Inoculum Preparation

For inoculation of plants (cotton and wheat) bacterial cultures were grown in LB agar broth (50 ml) at 30ºC for 48h and centrifuged at 4000 for 10 min to get the cell pellet. The cell pellet was washed with 0.8% saline solution and re-suspended in 100 ml saline. One ml of bacterial culture (≃109 cfu/ml) was applied directly near to the root system.

2.6.3 Quick Screening of Bacterial Isolates in Sterilized Sand

For quick screening of the bacterial isolates for plant growth promotion, cotton and wheat seedlings were grown in sterilized sand for 40 days. The seeds were surface sterilized with sodium hypo-chloride for 5 min and then washed with sterilized water. Plastic jars (200 cm3) were used to grow seedlings and three seedlings of cotton and five seedlings of wheat were maintained in each jar with five replicates and were kept in growth room under controlled environment at 12 -25°C with average daylight of 10-

32 2. Materials and Methods

12 hours. One mL of Hoagland solution (1/8 strength) was provided twice a week as nutrient source.

2.6.4 Bacterial Inoculation of Cotton and Wheat Plants Grown In Earthen Pots Seeds of cotton (transgenic and non-transgenic, variety Coker) and wheat plants (transgenic and non-transgenic, variety Sehar 2006) were surface-sterilized with 0.1% (NaOCl) for 5 minutes, followed by washing in sterilized distilled water. The seeds were grown in earthen pots (radius 24cm, 32cm depth) containing non-sterilized field soil and watered at alternated days. The plants were kept in green house under controlled conditions of light, temperature and humidity (28° C, photoperiod of 16/8 h light/dark, with light flux density approximately 1600 lux and 65% relative humidity). Three plants of cotton and five plants of wheat were maintained in each pot with three replicates. To each pot 1.8 g each of urea and DAP (equivalent to the recommended dose for cotton and wheat ) was applied. Plants were harvested at maturity (~180 days) and data of different agronomic parameters was recorded. For measuring the cumulative root length, plant roots were separated and washed in water and spread on a transparent polyethylene sheet. The sheet with roots was put on the desktop scanner which scanned the roots and created a computer image of the roots. The root length were measured on the P-IV IBM computer and scanner by using root image analysis programme (Washington State University Research Foundation programme, Washington state university, USA).

2.6.5 Bacterial Inoculation of Wheat Plants Grown in Micro-Plots

After the pot experiment the isolates were inoculated to wheat plants in micro-plots (1.2m x 1.2m) in net house with natural conditions of temperature and moisture. Non- transgenic plants of same variety were grown as a control. Experiments were laid out in Randomized Complete Block Design (RCBD) with three replicates. The plant to plant distance was kept 18 cm and row to row 36 cm distance was maintained. Nitrogen as urea, phosphorus as single super phosphate (SSP) and potassium as KCl @ 80% of recommended fertilizer doses (recommended doses for NPK are 120, 100 and 70 kg ha-1, respectively) was applied to plants. Seed inoculation was done as described in previous section. Plant dry weight was measured after oven drying at 65o C till constant weight and grain yield was determined after harvesting.

33 2. Materials and Methods

2.6.6 Statistical Analysis

Data collected from pot and micro-plot experiments were analyzed statistically by analysis of variance [198] technique, using the statistix (version 8.1) software. One way ANOVA was applied in pot experiment data as well as in micro plots experiments. Least significant difference test (Fisher’s LSD) at 5% probability was used to compare the differences among treatments means.

2.7 Estimation of Bacterial Population 2.7.1 Bacterial Population by Counting Colony Forming Units (cfu/g of soil) For estimation of bacterial populations, soil samples from rhizosphere of transgenic and non-transgenic plants of cotton grown during 2012 and from wheat experiments conducted during 2011-12, were collected. These soil samples were collected at different plant growth stages i.e 30, 60 and 90 days after sowing (DAS). Plant growth conditions like fertilizers, irrigation, growth conditions have been mentioned above (see 2.6.4). Plants were uprooted carefully and soil adhering to the roots was collected. Rhizosphere soil (1.0 g) was added to 9 mL saline solution (0.89%) and used for preparation of 10X serial dilutions up to 10-5. From each dilution, 100 µl soil suspension was spread on nutrient agar plates. The agar plates were incubated at 30°C for 2-6 days and colony forming units (cfu/g) were counted.

2.7.2 Bacterial Population by Counting Most Probable Number (MPN)

Diazotrophic bacteria were estimated by the most probable number (MPN) method. Collected soil samples (cotton and wheat rhizosphere) were suspended and serially diluted in sterile water. Aliquots (100 µL) of each dilution was inoculated to eppendorf tubes (5 replicates) containing semi-solid NFM (100µL) and incubated 28°C for 15 days. After incubation bacterial growth was observed under microscope and growth positive eppendorf tubes were used for determination of MPN [194].

34 2. Materials and Methods

2.7.3 Real Time PCR

DNA Extraction from Soil Rhizosphere

Soil samples were collected from the rhizosphere of AVP1 transgenic cotton and wheat plants as well as non-transgenic controls plants, grown during 2012 and 2011-12, respectively. Three plants from each pot were uprooted, soil attached to the roots was separated and composite sample was prepared by mixing 5g of soil from each treatment. Total 8 soil samples were prepared for DNA isolation. Two sub samples (0.5g) from this composite sample were used for DNA extraction by Fast DNA Spin kit for Soil by FastPrep® instrument (MP Biomedicals, USA). Genomic DNA extracted from soil was used for further studies (nifH and pyrosequencing analysis)

Quantification of 16S rRNA and nifH Genes from Soil DNA by Real Time PCR

Quantification of 16S rRNA and nifH gene in soil DNA was carried out in a Bio-Rad CFX96 real-time PCR system (Bio-Rad Laborat ories, Hercu les CA). For 16S rRNA gene amplification primers (534f/783r) and for nifH gene amplification (polF/polR) were used. The 10 μL reaction volume contained 10 ng of DNA template, 5μL of SsoFast™ EvaGreen® Supermix (Bio-Rad) and 1 μL of each primer (12.5 µM stock). Real-time PCR reaction conditions included an initial 3 minute enzyme activation at 95 °C, followed by 40 cycles of 5S denaturation at 95 °C and 5S elongation at 53°C for amplification of 16S rRNA gene with (534f/783r) and 54°C for nifH gene (polF/ploR). For standard preparations, PCR products of strain Pseudomonas syrangae for 16S rRNA and Rhizobium for nifH standards were used. PCR products were purified by gel electrophoresis and quantified in a NanoDrop 2000 spectrophotometer (Thermo Fisher Scienti fic Inc. Wilmington, DE). Target copy numbers were estimated from soil samples. It was done by using standard curves that were generated from 10-fold dilutions of PCR products in triplicate. The absolute copy numbers in the standards were calculated based on DNA concentrations and size of PCR products. For calculation 660 g mol−1 average molecular mass of a double-stranded DNA molecule was considered [199]. All real-time PCR reactions on soil samples were performed in duplicate and mean values were estimated for each DNA sample. Melt-curve analysis of the PCR products was performed at the end of each real-time run. No DNA template controls were included in every run.

35 2. Materials and Methods

2.8 Extraction and Quantification of Root Exudates from the Rhizosphere Rhizosphere soil samples were collected from AVP1 transgenic cotton (2012) and wheat (2011-12) rhizosphere. Falcon tubes containing 30 ml of sterilized distilled water were weighed, then soil attached with the roots was added in these tubes. Weight of these tubes (soil+roots attached) was noted. The tubes with samples were placed on a shaker at 200 rpm for 30 minutes and then centrifuged at 5000 rpm for 10 minutes. Supernatants were collected into new Falcon tubes. This supernatant was concentrated up to 1.5 mL in a concentrator (eppendorf Concentrator 5301, Germany) and filtered through 0.2 µm filter (Orange Scientific GyroDisc CA -PC, Belgium). Samples were analyzed on HPLC PERKIN ELMER with the same conditions that were used for detection of organic acid from pure cultures [79].

2.9 Diversity of Diazotrophic Bacteria in the Rhizosphere of Transgenic and Non-transgenic Plants of Cotton and Wheat 2.9.1 PCR Amplification of nifH Gene from Soil DNA PCR amplification of nifH gene was done from soil DNA extracted from cotton and wheat rhizosphere (described in 2.7.3). Purified DNA was obtained by incubating DNA with RNaseA (Promega Corporation, Madison, WI) at 37° for 10 minutes with final concentration 100 µg/mL. A 360 bp fragment of the nifH gene was amplified by using a pair of primers nif H F and nif H R [200]. Reaction mixture was prepared in 25µL volume containing 12.5µL GoTaq®Green Master Mix (Promega, WI), 2 μL of template DNA, and 1μL of each forward and reverse primer from 12.5 μM stocks. PCR conditions consisted of an initial denaturation at 95 °C for 3 minutes, followed by 35 cycles of 94 °C for 45 seconds, 53 °C for 60 seconds, and 72 °C for 60 seconds, and a final elongation at 72 °C for 10 minutes. PCR products were purified using High Pure PCR Cleanup Micro Kit (Roche Applied Science, USA). Required amplified product was confirmed by visualizing on 1.2% agarose gel with 1 kb marker.

2.9.2 Cloning of nifH Gene and Sequencing Reactions

PCR products were cloned using the TOPO TA Cloning kit (Invitrogen Corporation, Carlsbad, CA) according to manufacturer’s instructions. Clone libraries were

36 2. Materials and Methods constructed in vector pCR2.1-TOPO and positive clones were selected (randomly 30 clones from each library) and sequencing was performed using the BigDye Terminator v3.1 Cycle sequencing kit (Applied Biosystems, Rotkreuz, Switzerland) with M13 forward primer. Sequencing was done on ABIPRISM 3700 DNA Analyzer (Applied Biosystems).

2.9.3 Phylogenetic Analysis

To determine the distribution of nifH and 16S rRNA gene among transgenic cotton and wheat rhizosphere soil, all sequencing data were blast searched at NCBI data bank. Sequence alignment was done on CLUSTER X with all strains from this study and other closely related sequences derived from GenBank data base [201]. To analyze all these sequences Maximum likelihood (ML) was adopted as described by [202]. Bootstrap value of 50 or greater was kept as representative [203].

2.10 Bacterial Diversity in the Rhizosphere of AVP1 Transgenic Cotton and Wheat by Pyrosequencing Analysis 2.10.1 16S rRNA Gene Amplification for Pyrosequencing DNA extracted from soil samples (Table 7) was used in a PCR with primers PYRO799f and 1492r [204] to amplify bacterial 16S rRNA gene sequences. ‘PYRO799f ’ is a derivative of 799f [153] containing a 16S rRNA gene conserved region, a unique barcode and a binding site for the pyrosequencing primer (Table 6). Each PCR reaction was carried out in a 50µL reaction volume containing 50 to 100 ng of template DNA, 25 picomoles each of primer PYRO799f and 1492r, 0.1 µM of each dNTP, 1x Ex Taq PCR buffer (Tak ara Bio Inc, Mountain view CA), and 1.5 units of high fidelity TaKaRa Ex Taq enzyme (Takara Bio Inc). PCR conditions were as follows: denaturation at 95°C for 5 minutes, 30 cycles at 95°C for 45 seconds, 55°C for 45 seconds, and 72°C for 2 minutes, followed by a 10 minutes elongations at 72°C. PCR reactions were run on a 1% agarose gel and bacterial amplicons with the expected size of 0.7 kb were recovered using a Qiaquick Gel Extraction Kit (Qiagen, Valencia, CA). Pyrosequencing was performed on these amplicons using standard titanium chemistry. Sequences were processed through the custom length and quality filters at CAGE and binned by barcode. In order to minimize the effects of sequencing errors, reads that were of atypical length (<200 or >650 bp) or had ≥ 1 nucleotide mismatch in the primer

37 2. Materials and Methods or barcode sequence were excluded from the analysis. Only reads with an average quality threshold value of ≥ 20 were considered to be qualified for further analysis.

2.10.2 Analysis of the Pyrosequencing Data

From each data set representing a single sample on the bases of attached barcode DNA, sequences were picked up randomly as follows. Original FASTA file with all sequences were opened in a text file. All eight treatments were separated on the bases of different attached barcodes and considered as Sequence ID file in the FASTA SEQUENCE SELECTION module at the Ribosomal Database Project's (RDP’s) Pyrosequencing Pipeline (http://pyro.cme.msu.edu). These FATSA files were used as input into RDP Classifier [205]. Using an 80% confidence threshold, the resulting hierarchy was downloaded as a text file and imported into Microsoft Excel for quantification of the contribution of individual taxa (phylum, class, order, family, or genus) to the total population. From Microsoft Excel staked bar graphs were constructed to compare diversity among the treatments on phylum and genera level. Separate stake bar graphs was drawn among the resident and rare genera among the treatments.

38 2. Materials and Methods

Table 2.6 Primer sequence with titanium adopter sequence

Name Titanium A Adaptor Barcode Primer sequence 454 Primer A: CCATCTCATCCCTGC Barcode PYRO799F:AACMGG GTGTCTCCGACTCAG ATTAGATACCCKG

454 Primer B: CCTATCCCCTGTGTG No barcode 1492R:TACGGYTACC CCTTGGCAGTCTCAG TTGTTACGACTT

Table 2.7 Soil samples with barcodes name and sequences

No. Soil sample Barcode Name Barcode Sequence 1 TC1 TFA35 GTCAACTG 2 NTC1 TFA36 GTGTCACA 3 TC2 TFA37 TAATCGCG 4 NTC2 TFA38 TACCGCTT 5 TW1 TFA39 TAGGATCC 6 NTW1 TFA40 TCACACAG 7 TW2 TFA41 TCCAAGCA 8 NTW2 TFA42 TCGAGTTG

3. Results

3.1 Isolation of Bacteria from the Rhizosphere of AVP1 Transgenic Cotton Soil samples were collected from the rhizosphere of transgenic and non-transgenic cotton grown in green house during the year 2011. A total of 12 bacterial isolates were purified on nutrient agar plates (Table 3.8). Among these, seven isolates were purified from AVP1 transgenic cotton plants and five were isolated from non-transgenic cotton plants.

3.2 Isolation of Bacteria from the Rhizosphere of AVP1 Transgenic Wheat AVP1 transgenic wheat plants along with non-transgenic wheat plants were grown in micro-plots in a net house under natural conditions during 2010-11. A total of 14 isolates were purified from rhizospheric soil on nutrient agar plates (Table 3.9). Among these, nine bacterial isolates were purified from AVP1 transgenic wheat and five isolates from non-transgenic wheat.

Figure 3-6 Isolation of bacteria on nutrient agar medium by serial dilution method

3. Results

Table 3.8 Colony and cell morphology of the bacterial strains isolated from the rhizosphere of AVP1 transgenic and non-transgenic cotton

Isolate Host Colony Cell morphology morphology 1. NTW1 Non-transgenic Small, yellow Short rods Cotton irregular margins 2. NTC-2NF Non-transgenic Small, yellow Motile short rods Cotton smooth margins 3. NTC-7 Non-transgenic Pinkish white, Plump rods with empty Cotton small wrinkled space margins 4. NTC-4 Non-transgenic Off white, large, Medium size rods Cotton irregular margins 5. AC Non-transgenic White, circular, Medium size motile Cotton flat, undulated rods margins 6. D-4 Transgenic Yellow, medium Very motile short rods Cotton size, smooth margins 7. B-alpha Transgenic Pure white, small, Medium sized rods Cotton round margins with few shorter cells

8. TN4-3NF Transgenic Irregular, milky Thin short rods Cotton white , gummy 9. A5 Transgenic Medium size, Large cells motile Cotton transparent irregular shape 10. Azo-BM31 Transgenic Pink, small, Small rods, highly Cotton smooth margins motile 11. CC Transgenic Yellowish, small Small rods Cotton convex surface 12. DC Transgenic White, large Thin rods, slightly Cotton motile

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Table 3.9 Colony and cell morphology of the bacterial strains isolated from the rhizosphere of AVP1 transgenic and non-transgenic wheat

Isolate Host Colony morphology Cell morphology 1. NTC-1NF Non-transgenic Medium size, cream color Very short, motile rods wheat round margins 2. NTC-11 Non-transgenic Light brown color, Short rods, slightly wheat wrinkled margins motile 3. WP1 Non-transgenic White large colonies, Thin rods, motile wheat irregular, wrinkled margins, 4. WP3 Non-transgenic Brown, large, smooth Small cells, vey motile wheat margins 5. WP8 Non-transgenic White, medium size, Thin rods, slightly wheat wrinkled margins motile 6. A6 Transgenic Large colonies, transparent, Medium size cells, wheat wrinkled margins joined together to form long rods 7. WN1 Transgenic Light yellow, small Very short, motile rods wheat 8. WN2 Transgenic Off white, very small Short rods, motile wheat 9. WT2 Transgenic Small size, brown, Very short, motile rods wheat transparent, smooth margins 10. WP2 Transgenic Medium size, white, Shiny, thin rods wheat smooth margins 11. NFM-2 Transgenic Small size, off-white, Motile rods wheat smooth margins 12. AZ Transgenic Medium size, light yellow, Small cells, motile wheat smooth margins 13.Azo-BM31 Transgenic Pinkish white, smooth Short rods, motile wheat margins, small size 14. WC Transgenic Off white, small size, dry Motile short rods wheat irregular margins

42 3. Results

3.3 Identification of Bacterial Isolates by 16S rRNA Gene Sequence Analysis Genomic DNA was extracted from pure cultures for the amplification of 16S rRNA gene using conserved primers (Figure 3-7). Bacterial identification by 16S rRNA sequence analysis indicated that bacterial strains isolated from the rhizosphere of AVP1 transgenic and non-transgenic cotton belonged to seven genera i.e Agrobacterium, Arthrobacter, Azospirillum, Bacillus (7,strains), Brevibacillus, Pseudomonas, and Rhizobium (Table 3.10). The isolates from AVP1 transgenic and non-transgenic wheat rhizosphere belonged to genera Achromobacter (2 strains), Actinobacteria, Advenella, Alcaligenese, Arthrobacter, Bacillus (4 strains), Bervibacterium, Pseudomonas (2 strains) and Rhizobium (Table 3.11).

Phylogenetic trees were constructed using 16S rRNA gene sequences of the bacterial isolates along with related sequences in the NCBI data base. Phylogenetic trees were constructed by using 16S rRNA gene sequences of bacterial isolates from AVP1 transgenic cotton and wheat and also from representative non-transgenic. Phylogenetic relationships of different strains of genus Bacillus (strain WP8 and WP2 isolated from AVP1 transgenic wheat) and Paenibacillus (NTC-7 isolated from non- transgenic cotton) were studied on the basis of 16S rRNA gene sequences (Figure 3- 11). Three major clusters were observed in this tree. Bacillus sp. strain WP8 and WP3 clustered with other Bacillus sp. taken from the Gene Bank. Paenibacillus sp. strain NTC-7 clustered with Paenibacillus edaphicus. Bacterial isolate Achromobacter strain AZ clustered with other Achromobacter sp. and uncultured Achromobacter (Figure 3- 14). Phylogenetic analysis of different isolates belonging to genus Pseudomonas (Pseudomonas strain D4 isolated from AVP1 transgenic cotton and WP3 isolated from transgenic wheat) showed three major clusters (Figure 3-15). Pseudomonas strain WP3 clustered with Pseudomonas straminea and Pseudomonas sp. strain D4 established cluster with other Pseudomonas strains reported from a variety of environments.

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1 2 3 4 5

1000 bp Genomic DNA extracted from bacterial pure cultures

Figure 3-7 Genomic DNA extracted from bacterial isolates. Lane 1, 1kb DNA ladder; Lane 2, isolate Wp3; Lane 3, isolate Bα; Lane 4, isolate D4;

Lane 5, isolate WN1. 3 000 bp 1 2 3 4 5 6

1500b 1000p bp bp 16S rDNA (PCR product)

250 bp

Figure 3-8 16S rRNA gene amplified from bacterial isolates. Lane 1, 1kb ladder; Lane 2, -ve control; Lane 3, isolate Wp3; Lane 4, isolate Bα; Lane 5, isolate D4; Lane 6, isolate WN1.

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Table 3.10 Identification of bacterial isolates from rhizosphere of AVP1 transgenic and non-transgenic cotton by 16S rRNA gene sequence analysis

Isolate Closest match in Sequence Accession NCBI similarity (%) No. 1. NTW1 Agrobacterium tumefaciens 98 HE995808 (KC107786.1)

2. B-α Arthrobacter oxydanse 99 HE995801 (KC934793.1)

3. Azo-BM31 Azospirillum brasilense 99 HE995805 (KC920689.1)

4. A-5 Bacillus aryabhattai 100 HE995809 (KM507162.1)

5. AC Bacillus sp. 100 HE995812 (JX232168.1)

6. CC Bacillus idriensis 99 HE995804 (KM036073.1)

7. NTC-4 Bacillus licheniformis 99 HE995806 (KP713760.1)

8. DC Bacillus subtilis 100 HE995811 (JX232168.1)

9. TN4-3NF Brevibacillus laterosporus 100 HE995803 (KF973294.1)

10. NTC-7 Paenibacillus sp. 99 HE995807 (EU570250.1)

11. D-4 Pseudomonas sp. 98 HE995802 (D88526.1)

12. NTC-2NF Rhizobium sp. 100 HE995810 (KF731646.1)

Bacterial cultures were grown in nutrient broth and DNA was extracted from pure culture. 16S rRNA gene was amplified by PCR.

45 3. Results

Table 3.11 Identification of bacterial isolates from rhizosphere of AVP1 transgenic and non-transgenic wheat rhizosphere by 16S rRNA gene sequence analysis Isolate Closest match in NCBI Sequence similarity Accession (%) No

1. A6 Achromobacter sp. (HQ448952.1) 97 HE995801

2. AZ Achromobacter sp. (KM461115.1) 100 HE995802

3. NTC-1NF Advenella sp. (KM191133) 100 HE995812

4. WC Alcaligenes sp. (LM655389.1) 100 HE995804

5. NTC-11 Arthrobacter sp. (EU135627.1) 100 HE995805

6. Azo-BM30 Azospirillum sp. (NR118484.1) 100 HE995809

7. WP1 Bacillus safensis (LC015558.1) 100 HE995806

8. WP2 Bacillus pumilus (KM924441.1) 100 HE995807

9. WP8 Bacillus pumilus (KP224308) 100 HE995808

10. NFM-2 Brevibacterium sp. (HQ622520.2) 100 HE995811

11. WN1 Microbacterium sp. (KP301095.1) 99 HE995803

12. WT2 Pseudomonas putida (AM131104.1) 100 HE995813

13. WP3 Pseudomonas putida (KP313537) 100 HE995814

14. WN2 Rhizobium sp. (GU060510.1) 100 HE995815

Bacterial cultures were grown in nutrient broth and DNA was extracted from pure culture. 16S rRNA gene was amplified by PCR

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E coil (HM194886)

Figure 3-9 Phylogenetic tree showing the phylogenetic relationship of different strains of genus Bacillus and Paenibacillus. Phylogenetic tree (Neighbor-Joining method) showing the phylogenetic relationship of different strains of genus Bacillus (strain WP8 and WP3 isolated from AVP1 transgenic wheat) and Paenibacillus (NTC-7 isolated from non-transgenic cotton) on the basis of 16S rRNA gene sequences. Amplified 16S rRNA gene fragment from the isolated strains of Bacillus sp. strain WP8, WP3, and Paenibacillus sp. strain NTC-7 ( ) were sequenced and BLAST searched through NCBI database. Closely related obtained from NCBI databank and sequence of type strains ( ) were used and aligned using CLUSTAR W. Distances were computed using the Jukes-Cantor method. The bootstrap replicates (BS) values of 50% or greater represent well supported nodes and thus only those were retained. E. coli (HM194886) was taken as an out group.

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Figure 3-10 Phylogenetic tree showing the phylogenetic relationship of the Brevibacillus strains. Phylogenetic tree (Neighbor-Joining method) showing the phylogenetic relationship of the Brevibacillus strain TN4-3NF ( ) based on the sequences of the 16S rRNA gene. Amplified 16S rRNA gene fragment from the isolated strain Brevibacillus strain TN4- 3NF (transgenic cotton) was sequenced and BLAST searched through NCBI database. 16S rRNA gene sequences from the current study along with those of the closely related sequences obtained from NCBI databank and sequence of type strains ( ) were used and aligned using CLUSTAR W. Distances were computed using the Jukes-Cantor method. Numbers above the nodes represent maximum likelihood bootstrap support above 50%.

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Figure 3-11 Phylogenetic tree showing the phylogenetic relationship of the Arthrobacter strain Phylogenetic tree (Neighbor-Joining method) showing the phylogenetic relationship of the Arthrobacter strain B-α ( ) based on the sequences of the 16S rRNA gene. Amplified 16S rRNA gene fragment from the isolated strains Arthrobacter strain B-α was sequenced and BLAST searched through NCBI database. Closely related sequences and sequence of type strains ( ) were obtained from NCBI databank and aligned using CLUSTAR W. Distances were computed using the Jukes-Cantor method. The bootstrap replicates (BS) values of 50% or greater represent well supported nodes.

49 3. Results

Figure 3-12 Phylogenetic tree showing the phylogenetic relationship of genus Agrobacterium and genus Rhizobium Phylogenetic tree (Neighbor-Joining method) showing the phylogenetic relationship of genus Agrobacterium (strain NTW1) and genus Rhizobium (strain NTC-2NF isolated from non-transgenic cotton) on the basis of 16S rRNA gene sequences. Amplified 16S rRNA gene fragment from the isolated strains Agrobacterium strain NTW1 and Rhizobium strain NTC-2NF ( ) were sequenced and BLAST searched through NCBI database. Closely related sequences and sequence of type strains ( ) were obtained from NCBI databank and aligned using CLUSTAR W. Distances were computed using the Jukes-Cantor method. The bootstrap replicates (BS) values of 50% or greater represent well supported nodes. E. coli (HM194886) was taken as out group.

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Figure 3-13 Phylogenetic tree showing the phylogenetic relationship of Azospirillum strain Phylogenetic tree (Neighbor-Joining method) showing the phylogenetic relationship of Azospirillum strain BM31 isolated from AVP1 transgenic cotton on the basis of 16S rRNA gene sequences. Amplified 16S rRNA gene fragment from the isolated strain of Azospirillum strain BM31 ( ) were sequenced and BLAST searched through NCBI database. Closely related sequences and sequences of type strain ( ) were downloaded and aligned using CLUSTAR W. Distances were computed using the Jukes-Cantor method. The bootstrap replicates (BS) values of 50% or greater represent well supported nodes. E. coli (HM194886) was taken as out group.

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(HM19486)

Figure 3-14 Phylogenetic tree showing the phylogenetic relationship of genus Achromobacter Phylogenetic tree (Neighbor-Joining method) showing the phylogenetic relationship of genus Achromobacter (strain AZ isolated from AVP1 transgenic wheat) on the basis of 16S rRNA gene sequences. Amplified 16S rRNA gene fragment from the isolated strain Achromobacter sp. strain AZ sequenced ( ) and BLAST searched through NCBI database. Closely related sequences and sequences of type strain ( ) were downloaded and aligned using CLUSTAR W and distances were computed using the Jukes-Cantor method. The bootstrap replicates (BS) values of 50% or greater represent well supported nodes. E. coli (HM194886) was taken as out group.

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Figure 3-15 Phylogenetic tree showing the phylogenetic relationship of genus Pseudomonas Phylogenetic tree (Neighbor-Joining method) showing the phylogenetic relationship of genus Pseudomonas (strain D4 isolated from AVP1 transgenic cotton and strain WP3 isolated from AVP1 transgenic wheat) on the basis of 16S rRNA gene sequences. Amplified 16S rRNA gene fragment from the isolated strains Pseudomonas sp. strain D4 and WP3 were sequenced and BLAST searched through NCBI database Closely related sequences and sequences of type strain ( ) were downloaded and aligned using CLUSTAR W and distances were computed using the Jukes-Cantor method. The bootstrap replicates (BS) values of 70% or greater represent well supported nodes. E. coli (HM194886) was taken as out group. The bootstrap replicates (BS) values of 50% or greater represent well supported nodes. Pseudomonas stutzeri (U26416.1) was taken as out group.

53 3. Results

3.4 Quantification of IAA Production by Bacterial Isolates Phytohormone (IAA) production by bacterial isolates was determined on HPLC by using standard methods. The isolates obtained from rhizosphere of cotton and wheat were grown in LB broth medium supplemented with tryptophan as a precursor for IAA biosynthesis. Among the bacterial isolates from cotton, maximum amount of IAA (29.01 µg/mL) was determined in the growth medium of Bacillus sp. strain NTC-4, followed by Agrobacterium strain NTW1 which produced 22.54 µg/mL of IAA in the medium (Table 3.12). Bacillus sp. strain AC, DC and Bacillus sp. strain CC showed relatively less production of IAA. Among the bacterial isolates from wheat rhizosphere, maximum IAA production (19.88 µg/mL) was observed in the growth medium of Arthrobacter sp. strain NTC-11 (19.6 µg/mL), followed by Brevibacterium sp. strain NFM-2 (15.70 µg/mL) and Achromobacter sp. strain A6 (11.01 µg/mL) (Table 3.13)

Table 3.12 Quantification of IAA produced by bacterial strains isolated from cotton

IAA production* No. Bacterial strains (µg/mL)

1. Agrobacterium sp. strain NTW1 22.54 ± 3.3 2. Arthrobacter sp. strain Bα 10.06 ± 2.5 3. Azospirillum sp. strain Azo-BM31 12.3 ± 0.4 4. Bacillus sp. strain NTC-4 29.01 ± 5.5 5. Bacillus sp. strain AC 2.12 ± 0.2 6. Bacillus sp. strain CC 1.31 ± 0.2 7. Bacillus sp. strain A5 6.04 ± 0.1 8. Bacillus sp. strain DC 2.9 ± 0.1 9. Brevibacillus sp. strain TN4-3NF 11.25 ± 2.8 10. Paenibacillus sp. strain NTC-7 12.06 ± 1.2 11. Pseudomonas sp. strain D4 15.68 ± 1.4 12. Rhizobium sp. strain NTC-2NF 8.86 ± 2.2 *Bacterial cultures were grown for two weeks in LB medium containing tryptophan as precursor of IAA. The values given are an average of 3 replicates.

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Table 3.13 Quantification of IAA produced by bacterial strains isolated from wheat

No. Bacterial Strains IAA production* ( µg/mL) 1. Achromobacter sp. strain A6 11.21±1.43 2. Achromobacter sp. strain AZ 5.71±0.8 3. Alkaligense sp. strain WC 0.64±0.26 4. Arthrobacter sp. strain NTC-11 19.88±3.2 5. Advenella sp. strain NTC-1NF 7.86±1.2 6. Azospirillum sp. strain BM30 9 ±0.1 7. Bacillus sp. strain WP1 1.02±0.2 8. Bacillus sp. strain WP2 10.01±0.3 9. Bacillus sp. strain WP8 0.41±0.1 10. Brevibacterium sp. strain NFM-2 15.70±0.14 11. Microbacterium sp. strain WN1 4.64±0.6 12. Pseudomonas sp. strain WP3 9.18±1.25 13. Pseudomonas sp. strain WT2 8.01±2.11 14. Rhizobium sp. strain WN2 6.42±0.4 *Bacterial cultures were grown for two weeks in LB medium containing tryptophan as precursor of IAA. The values given are an average of 3 replicates. 3.5 Phosphate Solubilization 3.5.1 Qualitative Assay for Phosphate Solubilization by Bacterial Strains Phosphate solubilization by bacterial isolates was studied on Pikovskaya agar plates containing insoluble tri-calcium phosphate (TCP). Clear halo zone formation around bacterial colonies indicated phosphate solubilization by bacteria in pure culture (Figure 3-16). These halo zones were observed around bacterial colonies after one week incubation.

3.5.2 Quantitative Assay for Phosphate Solubilization by Bacterial Strains Bacterial strains that showed growth or clear halo zone on Pikovskaya agar plates were selected for quantification of phosphate solubilization by spectrophotometric method. Among the bacterial isolates from cotton rhizosphere, maximum P-solubilization activity was observed in Arthrobacter sp. Bα (46.02 µg/mL), followed by Pseudomonas sp. D4 (42.05 µg/mL) whereas minimum P-solubilization activity was recorded among Bacillus sp. strain DC (1.32 µg/mL) and Bacillus sp. strain CC (4.52 µg/mL) (Table 3.14). Among the bacterial isolates from wheat rhizosphere, maximum P-solubilization activity (122 µg/mL) was showed by Pseudomonas sp. strain WP3, followed by

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Achromobacter sp. strain A6 (33.5 µg/mL). Brevibacterium strain NFM2, and Bacillus strains EC and WP1 did not show any P-solubilization activity (Table 3.15).

B-α NT.N4- NTC

Halo- Halo-

WP1

WP8 Halo-

zone Figure 3-16 Plate assay for detection of phosphorus solubilization by bacterial isolates on Pikovskaya medium supplemented with insoluble tri- calcium phosphate (TCP)

56 3. Results

Table 3.14 Quantification of P solublization by bacterial isolates from cotton

Serial# Bacterial Strains Available P* (µg/mL) 1. Agrobacterium sp. strain NTW1 1.96 ± 0.4 2. Arthrobacter sp. strain B-α 46.02 ± 5.2 3. Bacillus sp. strain A-5 12.34 ± 0.6 4. Bacillus sp. strain AC 5.01 ± 0.4 5. Azospirillum sp. strain Azo-BM31 41.01 ± 1.7 6. Bacillus sp. strain CC 4.52 ± 1.2 7. Bacillus sp. strain NTC-4 9.08 ± 2.2 8. Bacillus sp. strain DC 1.32 ± 2.2 9. Brevibacillus sp. strain TN4-3NF 33.50 ± 1.2 10. Paenibacillus sp. strain NTC-7 14.08 ± 3.4 11. Pseudomonas sp. strain D4 42.05 ± 4.6 12. Rhizobium sp. strain NTC-2NF 6.94 ± 0.4

Table 3.15 Quantification of P solubilization by bacterial isolates from wheat

Serial #. Bacterial Strains Available P* (µg/mL)

1. Achromobacter sp. strain A6 33.5 ± 4.1 2. Achromobacter sp. strain AZ 7.4 ± 4.2 3. Alkaligense sp. strain WC 5.6 ± 0.5 4. Arthrobacter sp. strain NTC-11 27.0 ± 6.5 5. Advenella sp. strain NTC-1NF 2.5 ± 0.2 6. Azospirillum sp. strain Azo-BM30 27.1 ± 1.9 7. Bacillus sp. strain WP2 17.5 ± 1.4 8. Bacillus sp. strain WP8 22.0 ± 4.6 9. Microbacterium sp. strain WN1 26.0 ± 3.5 10. Pseudomonas sp. strain WP3 112.0 ± 3.7 11. Pseudomonas sp. strain WT2 17.0 ± 5.4 12. Rhizobium sp. strain WN2 26.2 ± 1.8 *Bacterial cultures were grown for two weeks in Pikovskaya growth medium (pH 7) containing insoluble tri-calcium phosphate as insoluble phosphorus source. The values given are an average of 3 replicates. No P solubilization was detected in pure culture of Brevibacterium sp. strain NFM-2, and Bacillus strains EC and WP1.

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3.6 Quantification of Organic Acid Production by Bacteria in Pikovskaya Medium Used for Studying Phosphate Solubilization Production of organic acids like acetic acid, citric acid, gluconic acid, lactic acid, malic acid, oxalic acid and succinic acid by bacterial cultures was detected on HPLC in Pikovskaya medium supplemented with sucrose as carbon source. Among these acids acetic acid, citric acid, gluconic acid, lactic acid, malic acid, oxalic acid and succinic acid were detected in the growth medium (Table 3.16). Among the tested strains, Pseudomonas strain WP3 isolated from AVP1 transgenic wheat showed maximum amount of acetic acid (38.21 µg/mL) production. Among the isolates from AVP1 transgenic cotton tested in this study Pseudomonas strain D4 showed maximum amount of citric acid (13.87 µg/mL) production. Lactic acid and succinic acid were detected relatively in low amounts. Oxalic acid was detected only in the pure cultures of Paenibacillus strain NTC-7(1.02 µg/mL) and Bacillus strain WP8 (0.02 µg/mL) in low amounts. Azospirillum strains BM31, Brevibacillus strain TN4-3NF isolated from AVP1 transgenic cotton and Paenibacillus strain NTC-7 isolated from non-transgenic cotton showed relatively higher amounts of all organic acids.

58 3. Results

Table 3.16 Quantification of organic acid production (µg/mL) by bacterial isolates in the growth medium used for P-solubilization Bacterial strains Acetic Citric Malic Lactic Gluconic Succinic acid acid acid Acid Acid Acid Achromobacter strain A6 12.54±1.2 4.3±2.01 ND* 2.31±1.9 ND* ND*

Agrobacterium strain NTW1 18.8±4.1 0.6±0.04 0.2±0.06 ND* 09±0.12 0.21±0.1

Arthrobacter strain B-α 19.05±3.8 7.0±1.2 ND* 0.3±0.03 0.1±0.04 0.21±0.02

Azospirillum strain BM31 18.02±08 6.5±1.5 2.08±09 2.5±1.1 4.56±0.1 0.9±0.12

Azospirillum strain BM30 8.74±0.8 5.6±0.8 ND* 3.1± 1.7 2.45±0.89 1.78±0.4

Bacillus strain A-5 5.1±1.4 8.3±2.8 ND* 0.2±0.12 ND* 1.4±0.02

Bacillus strain NTC-4 7.05±1.9 4.3±1.6 ND* 0.3±0.10 ND* ND*

Bacillus strain WP8 32.85±8 9.5±3.6 1.2±0.5 2.6±1.52 3.41±2.0 ND*

Brevibacillus strain TN4- 14.84±5.4 6.5±1.5 0.02±0.08 0.4±0.20 0.6±0.02 2.24±0.35 3NF Microbacterium strain WN1 12.04±2.5 4.6±2.3 0.07±0.02 0.65±0.5 1.45±1.2 0.03±0.05

Paenibacillus strain NTC-7 14.56±4.3 7.9± 1.2 3.1±1.07 4.5±1.8 1.2±0.89 1.35±0.04

Pseudomonas strain D4 14.25±4.0 13.8±2.4 ND* 3.2±2.31 ND* ND*

Pseudomonas strain WP3 38.21±8 12.4±3.5 ND* 4.6±2.46 2.1±0.05 ND*

Pseudomonas strain WT2 11.0±2.6 3.6±1.27 1.2±0.12 0.71±0.8 1.25±1.25 0.31±0.02

Rhizobium strain WN2 9.65±0.8 5.8±0.95 ND* 2.2± 1.9 2.35±0.45 ND*

*Organic acids by bacteria in Pikovskaya medium were quantified on HPLC and given values (µg/mL) in the Table are an average of 3 replicates with standard deviation *ND= Not detected.

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Figure 3-17 Organic acid production (µg/mL) by bacterial isolates in pure culture. Bacterial cultures were grown for two weeks in Pikovskaya medium containing insoluble tri-calcium phosphate. NTW1=Agrobacterium strain NTW1; B-α=Arthrobacter strain B-α; A5=Bacillus strain A-5; NTC4=Bacillus strain NTC-4; TN4-3NF=Brevibacillus strain TN4-3NF; NTC7=Paenibacillus strain NTC-7; D4=Pseudomonas strain; WN1= Microbacterium strain WN1; WP3=Pseudomonas strain WP3; WP8=Bacillus strain WP8; A6=Achromobacter strain A6; WT2= Pseudomonas strain WT2; WN2= Rhizobium strain WN2; BM31= Azospirillum strain BM31; BM30= Azospirillum strain BM30

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3.7 Bacterial Inoculation of Cotton Plants A series of experiments (Figure 3-18) during different years were conducted to evaluate the effect of PGPR cotton plants. For quick screening of bacterial isolates, seedlings were grown in small plastic jars filled with sterilized sand. These experiments were performed with AVP1 transgenic cotton along with non-transgenic plants as control. Transgenic and non-transgenic plants used in these experiments belonged to the same event and generation. Transgenic plants were confirmed by PCR amplification of the AVP1 gene by Gene Transformation Group, NIBGE and PCR positive plants were used for data collection.

Cotton plant inoculation experiments

2009 Sand Culture (Sterilized sand)

2011 Pot Experiment (Non-sterilized soil)

Pot Experiment (Non-sterilized soil) 2012

Figure 3-18 Bacterial inoculation experiments on cotton plants conducted in different years in growth room. 3.7.1 Experiment 1 (year 2009) Effect of Bacterial Inoculation on Growth of AVP1 Transgenic and Non–Transgenic Cotton Grown in Sterilized Sand For quick screening of bacterial strains for their growth promotion ability, a short term experiment was conducted in sterile sand under controlled conditions (Figure 3-19). In the present study 8 bacterial isolates selected on the bases of high IAA production and phosphate solubilizing ability, were used as single-strain inoculants for AVP1 transgenic and non-transgenic cotton. These strains were tested for their growth promotion potential in short-term experiments using sterilized sand. Sub-sets of bacterial strains showing significant improvement in growth of cotton plants in sand culture were applied as inoculum in pot experiment using field soil. Bacterial isolates Agrobacterium strain NTW1, Arthrobacter strain Bα, Azospirillum strain BM31, Bacillus strain NTC-4, Bacillus strain A5, Brevibacillus strain TN4-3NF, Paenibacillus

61 3. Results strain TNC-7 and Pseudomonas strain D4 were tested (Table 3.17). Plants were harvested after 40 days of sowing and data on cumulative root length, root dry weight and shoot dry weight were recorded. A significant (P≤ 0.05) improvement in growth parameters of inoculated transgenic plants was recorded over non-inoculated control plants (Table 3.17A; Figure 3-20). Among the transgenic plants, inoculated strains showed significant improvement of cumulative root length, root dry weight and shoot dry weight over non-inoculated control. Maximum increase in root length, root dry weight and shoot dry weight of transgenic cotton plants was recorded in the treatments inoculated with Arthrobacter strain Bα, Bacillus strain NTC-4, Brevibacillus strain TN4-3NF and Pseudomonas strain D4. Maximum increase in root length (24%) and root dry weight (22.1%) of transgenic plants was shown by inoculation of Arthrobacter strain Bα. No significant effect was observed on the shoot dry weight and root dry weight of transgenic plants inoculated with Agrobacterium strain NTW1. Inoculation of non-transgenic plants with the same set of bacterial strains showed that there was no significant effect of inoculation on the root dry weight of non-transgenic plants. A significant (P≤ 0.05) impact on cumulative root length and shoot dry weight was recorded among non-transgenic plants inoculated with Arthrobacter strain Bα, Azospirillum strain BM31, Brevibacillus strain TN4-3NF and Pseudomonas strain D4. Maximum increase in root length (24%) was recorded on inoculation of Azospirillum strain BM31 and maximum shoot dry weight (26.7%) was shown by inoculation of Pseudomonas strain D4.

Inoculated transgenic cotton plants Non-inoculated

Figure 3-19 Effect of bacterial inoculation on growth of cotton plants (transgenic and non-transgenic)

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Table 3.17 Effect of bacterial inoculation on growth of AVP1 transgenic (A) and non-transgenic cotton (B) grown in sterilized sand under controlled conditions (year 2009) A

Transgenic cotton Cumulative root Root dry Shoot dry weight (g) Treatment length (cm) weight (g)

Control (Non-inoculated) 21.79 C 0.529C 2.098 D Agrobacterium strain NTW1 24.63 B 0.532C 2.160 CD Arthrobacter strain Bα 27.05 A 0.657A 2.448 B Azospirillum strain BM31 23.65 BC 0.582B 2.474 B Bacillus strain NTC-4 26.95A 0.687A 2.484 B Bacillus strain A5 23.65 BC 0.620B 2.244 C Brevibacillus strain TN4-3NF 26.20 AB 0.623B 2.528 B Paenibacillus strain TNC-7 25.08 AB 0.624B 2.110 D Pseudomonas strain D4 26.84 A 0.631B 2.652 A LSD(P≤ 0.05)B 2.83 0.071 0.24

Non-transgenic cotton Cumulative root Root dry Shoot dry weight Treatment length (cm) weight (g) (g)

Control (Non-inoculated) 20.20C 0.50 2.30D Agrobacterium strain NTW1 25.30AB 0.49 2.24D Arthrobacter strain Bα 25.90AB 0.51 2.89AB Azospirillum strain BM31 26.26A 0.67 2.87AB Bacillus strain NTC-4 25.00AB 0.67 2.60C Bacillus strain.A5 22.15BC 0.63 2.32D Brevibacillus strain TN4-3NF 23.10ABC 0.48 2.75BC Paenibacillus strain TNC-7 22.00BC 0.51 2.34D Pseudomonas strain D4 23.60ABC 0.53 2.94A LSD(P≤ 0.05) 1.12 NS 0.31

Values in same column sharing the same letter do not differ significantly (P≤ 0.05) according to Fisher’s LSD, (n=3). Three seeds were grown in plastic jars containing sterilized sand and 1.0 mL bacterial cultures (≃ 109cfu/mL) were inoculated to seedlings after emergence. Three seedlings were maintained in each jar. Values are an average of five replications.

63 3. Results

T.Root Dry weight (g) NT.Root Dry weight (g)

T.Shoot Dry weight (g) NT.Shoot Dry weight (g)

2.5

Weight (g) Weight 1.5

0.5

Treatment

Figure 3-20 Effect of bacterial inoculation on root and shoot dry weights of transgenic and non-transgenic plants Control = non-inoculated, T= AVP1 transgenic cotton; NT= Non-transgenic cotton; NTW1= Inoculated with Agrobacterium strain NTW1; Bα= Inoculated with Arthrobacter strain Bα; NTC-4= Inoculated with Bacillus strain NTC-4; A5= Inoculated with Bacillus strain A5; TN4-3NF = Inoculated with Brevibacillus strain TN4-3NF; TNC-7= Inoculated with Paenibacillus strain TNC-7; D4 = Inoculated with Pseudomonas strain D4

64 3. Results

3.7.2 Experiment 2 (Year 2010) Effect of Bacterial Inoculation on Growth of AVP1 Transgenic and Non–Transgenic Cotton Grown Under Controlled Conditions in Earthen Pots

Promising bacterial strains showing plant growth promotion in short term experiments in sand culture were selected and used as inoculum for cotton plants grown in earthen pots. Pots were filled with non-sterilized soil collected from NIBGE experimental field area. Arthrobacter strain Bα, Azospirillum strain BM31, Bacillus strain NTC-4, Brevibacillus strain TN4-3NF and Pseudomonas strain D4 were used as single strain inocula for transgenic and non-transgenic cotton plants (Table 3.18)

Among the inoculated plants, transgenic plants inoculated with Pseudomonas strain D4 showed an increase in shoot dry weight (13.7%), root dry weight (8.7%), root length (28.5%), and yield (11.19%), over non-inoculated control. Moreover, inoculation of transgenic plants with Brevibacillus strain TN4-3NF also showed the improvement of shoot dry weight (12.9%), root dry weight (8.3%) and root length (18.5%) (Table 18A). Inoculation of bacterial strains showed non-significant effect on cotton boll production (no. of bolls). Maximum increase in yield of transgenic cotton plant was recorded on inoculation with Brevibacillus strain TN4-3NF (11.2%) and Pseudomonas strain D4 (9.6%).

Non-transgenic plants inoculated with Arthrobacter strain Bα, Pseudomonas strain D4, and Bacillus strain NTC-4, showed increase in shoot dry weight which was 13%, 14.0% and 13.8.6%, respectively. Non-transgenic plants showed non-significant effect of inoculated strains on yield except Pseudomonas strain D4 and Arthrobacter strain Bα. Inoculation with Pseudomonas strain D4 and Arthrobacter strain Bα resulted in 22 % and 23% increase in yield of non-transgenic plants, respectively (Table 3.18B).

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Inoculated transgenic plant Non-Inoculated transgenic plant inoculated Figure 3-21 AVP1 transgenic cotton plants grown under controlled conditions in transgenic plant earthen pots

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Table 3.18 Effect of bacterial inoculation on growth of AVP1 transgenic (A) and non-transgenic cotton plants (B) grown in earthen pots under controlled conditions (Year 2010). A

Transgenic cotton Treatments Cumulative Root dry Shoot dry No. bolls Yield (g) root length weight (g) weight (g) per plant (Lint+seed) (cm) Control (Non-inoculated) 31.553 C 4.090B 19.14B 17.66 38.01B Arthrobacter strain Bα 41.38A 4.41A 21.56A 20.33 37.41B Azospirillum strain BM31 34.94B 4.36A 19.78B 15.00 38.01B Bacillus strain NTC-4 40.70A 4.40A 21.51A 19.33 38.45B Brevibacillus strain 39.19A 4.43A 21.62A 18.85 42.37A TN4-3NF Pseudomonas strain D4 40.60A 4.45A 21.77A 20.66 41.67A LSD(P≤ 0.05) 2.17 0.09 0.46 NS 2.05

Non-transgenic cotton

Treatments Cumulative Root dry Shoot dry No. bolls Yield (g) root length weight (g) weight (g) per plant (Lint+seed) (cm) Control (Non-inoculated) 34.74C 4.030C 19.05B 15.00B 36.25B

Arthrobacter strain Bα 35.27BC 4.556A 21.56A 16.33AB 44.64A

Azospirillum strain BM31 35.83ABC 4.040C 19.78B 14.00B 37.40B

Bacillus strain NTC-4 37.28AB 4.183BC 21.67A 16.66AB 38.61AB

Brevibacillus strain 34.58C 4.243B 21.54A 17.66AB 40.56AB TN4-3NF Pseudomonas strain D4 37.77A 4.523A 21.77A 19.00A 44.37A

LSD(P≤ 0.05) 0.98 0.08 0.35 1.73 3.08

Values in same column sharing same letter do not differ significantly (P≤ 0.05) according to Fisher’s LSD, (n=3). Three seeds were grown in each pot containing non-sterilized soil and one plant was maintained in each pot till maturity. 1.0 mL bacterial cultures (≃109cfu/mL) were inoculated to seeds at the time of sowing.

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T.Shoot Dry Weight (g) NT.Shoot Dry Weight (g) T.Yield (lint +seed) NT.Yield (lint +seed)

Weight (g) Weight 20

10 C Bα BM31 NTC-4 TN4- D4 3NF

Treatment Figure 3-22 Effect of bacterial inoculation on shoot dry weight, and yield (lint+seed) of transgenic and non-transgenic plants T=AVP1 transgenic plants; NT= non-transgenic plants; C = Non-inoculated control. Bα = Inoculated with Arthrobacter strain Bα, BM 31= Inoculated with Azospirillum brasilense strain BM31, NTC-4= Inoculated with Bacillus strain NTC-4, TN4.3NF= Inoculated with Brevibacillus strains TN4-3NF, D4= Inoculated with Pseudomonas strain D4 3.7.3 Experiment 3 (year 2011) Effect of Bacterial Inoculation on Growth of AVP1 Transgenic and Non–Transgenic Cotton Grown In Earthen Pots under Controlled Conditions A pot experiment was conducted to study the effect of PGPR strains that were tested as inoculum previously i.e year 2010. Bacterial strains Arthrobacter strain Bα, Azospirillum strain BM31, Bacillus strain NTC-4, Brevibacillus strain TN4-3NF, Pseudomonas strain D4 were used for inoculation of transgenic and non-transgenic cotton plants. Inoculation with Arthrobacter strain Bα resulted in increased cumulative root length (7.4%), shoot dry weight (8.9%), root dry weight (21.6%), and yield (24.5%) of transgenic cotton plants over non-inoculated control. In this experiment inoculation with Pseudomonas strain D4 resulted in increased cumulative root length (7.9%), shoot dry weight (11.5%), root dry weight (21.8%) and yield (23%) of transgenic cotton plants over control (Table 3.19A). Brevibacillus strain TN4-3NF also showed a significant impact on cumulative root length (7.9%) and root dry weight (21%) of inoculated plants as compared to non-inoculated control. Bacillus strain NTC- 4 did not show any significant impact on the growth of transgenic plants. The same

68 3. Results isolates were applied to non-transgenic plants to study their performance as inoculants (Table 19B). Inoculation of non-transgenic plants with Brevibacillus strain TN4-3NF and Pseudomonas strain D4 resulted in the improvement of all growth parameters studied. Two inoculated strains i.e Bacillus strain NTC-4 and Azospirillum strain BM31 did not show any improvement of plant growth (yield).

Non-transgenic plants AVP1 transgenic plants

AVP1transgenic and non-transgenic cotton under controlled conditions

Inoculated Inoculated Inoculated Inoculated Non-inoculated Arthrobacter Azospirillum Pseudomonas Brevibacillus Bα BM31 D4 TN4-3NF

AVP1 transgenic AVP1 transgenic plants inoculated with different bacterial strains non-inoculated

Figure 3-23 Bacterial inoculation of AVP1 transgenic and non–transgenic cotton grown under controlled conditions in earthen pots

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Table 3.19 Effect of bacterial inoculation on growth of AVP1 (A) transgenic and non-transgenic cotton (B) grown in earthen pots under controlled conditions A

Transgenic cotton Cumulative Root Shoot Yield Treatment root length dry wt. dry wt. (Lint + (cm) (g) (g) seed) Control (Non-inoculated) 53.50D 8.04B 22.00C 9.24C Arthrobacter strain Bα 57.40A 9.78A 23.96AB 11.81AB Azospirillum strain BM31 55.73B 8.31B 23.59AB 10.98AB Bacillus strain NTC-4 54.41C 8.16B 22.26BC 10.57BC Brevibacillus strain TN4- 56.35AB 9.74A 22.43BC 9.51C 3NF Pseudomonas strain D4 57.76A 9.80A 24.54A 11.95A LSD(P≤ 0.05) 0.69 1.4 0.92 0.40

B Non-transgenic Treatment Cumulative Root dry Shoot Yield root length wt. (g) dry (Lint + (cm) wt.(g) seed) Control (Non-inoculated) 45.00D 7.04C 20.07D 10.66B 24.08A Arthrobacter strain Bα 48.33DC 7.88B 12.10A B 23.02B Azospirillum strain BM31 49.30C 7.61B 11.68AB C Bacillus strain NTC-4 52.33BC 7.15C 22.59C 10.68B Brevibacillus strain TN4- 54.43A 8.62A 24.98A 12.28A 3NF Pseudomonas strain D4 55.10A 7.85B 22.32C 12.54A LSD(P≤ 0.05) 3.81 0.43 0.52 1.33 Values in same column sharing the same letter do not differ significantly (P≤ 0.05) according to Fisher’s LSD, (n=3). Five seeds were grown in each pot containing non-sterilized soil and three plants were maintained till maturity. 1.0 mL bacterial cultures (≃109cfu/mL) were inoculated to seedlings after emergence. Three seedlings were maintained in each pot with five replicates.

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T.Yield (lint +seed) NT.Yield (lint +seed) T.Shoot Dry Weight (g) NT.Shoot Dry Weight (g)

10 Weight (g) Weight

Treatment

Figure 3-24 Effect of bacterial inoculation on root dry weight, and yield (lint+seed) of transgenic and non-transgenic plants T=AVP1 transgenic plants; NT= non-transgenic plants; C = Non-inoculated control. Bα = Inoculated with Arthrobacter strain Bα, BM 31= Inoculated with Azospirillum strain BM31, NTC-4= Inoculated with Bacillus strain NTC-4, TN4.3NF= Inoculated with Brevibacillus strains TN4-3NF, D4= Inoculated with Pseudomonas strain D4.

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3.8 Bacterial Inoculation of Wheat Plants A series of experiments during different years were conducted to evaluate the effect of PGPR bacterial strains on wheat plants (Figure 3-25). For quick screening of bacterial isolates, wheat plants were grown in small plastic jars filled with sterilized sand. Efficient PGPR strains were selected to be used as inoculum in micro-plots under natural conditions. These experiments were performed with AVP1 transgenic wheat along with non-transgenic plants as control. Transgenic and non-transgenic plants used in these experiments belonged to the same event and generation. Transgenic plants were confirmed by PCR amplification of the AVP1 gene by Gene Transformation Lab (NIBGE). Transgenic plants were confirmed by PCR amplification of the AVP1 gene. All data on plant growth parameters were collected from PCR positive plants.

Wheat plant inoculation experiments

2009 Sand Culture (Sterilized sand)

Micro-plot Experiment (Non-sterilized soil) 2010 -11

2011 -12 Micro-plot Experiment (Non-sterilized soil)

Figure 3-25 Bacterial inoculation experiments on wheat plants conducted in different years 3.8.1 Experiment 1 (year 2009) Effect of Bacterial Inoculation on Growth of AVP1 Transgenic and Non–Transgenic Wheat Seeds Grown in Sterilized Sand under Controlled Conditions Bacterial isolates from the rhizosphere of AVP1 transgenic and non-transgenic wheat were inoculated to wheat seedlings grown in plastic jars filled with sterilized sand. The plants were harvested 40 days after sowing. Bacterial isolates Achromobacter strain A6, Arthrobacter strain NTC-11, Azospirillum strain BM30, Bacillus strain WP2, Bacillus strain WP8, Brevibacterium strain NFM-2, Microbacterium strain WN1, and Pseudomonas strain WP3 and were used as single strain inoculant for transgenic and non-transgenic wheat plants (Table 3.20). Inoculation of AVP1 transgenic plants with PGPR resulted in the growth improvement of wheat plants as indicated by an increase in cumulative root length and dry weight of shoots and roots (Table 3.20A). Among the

72 3. Results tested strains, five strains i.e Achromobacter strain A6, Arthrobacter strain NTC-11, Azospirillum strain BM30, Microbacterium strain WN1 and Pseudomonas strain WP3 showed an increase in all the growth parameters of transgenic plants over non- inoculated control. Maximum increase in cumulative root length (22.1%), shoot dry weight (10.5%) and root dry weight (23 %) over control plants was recorded in the plants inoculated with Pseudomonas strain WP3. Inoculation with Arthrobacter strain NTC-11 and Microbacterium strain WN1 resulted an increase (18.1% and 23 %, respectively) in root dry weight over non-inoculated plants. The inoculation with Azospirillum strain BM30 increased cumulative root length of plant (17.4 %) and Achromobacter strain A6 increased root dry weight (21.5%) of AVP1 transgenic plants over control. Among the bacterial inoculum tested for non-transgenic wheat plants, no significant improvement of cumulative root length was recorded. Maximum increase in shoot dry weight was recorded over control plants inoculated with Achromobacter strain A6, Arthrobacter strain NTC-11 and Pseudomonas strain WP3. Maximum increase (6%) in root dry weight of non-transgenic plants was recorded in plants inoculated with Pseudomonas strain WP3 (Table 3.20B).

Figure 3-26 Effect of bacterial inoculation on growth of AVP1 transgenic wheat

plants grown in jars filled with sterilized sand

Table 3.20 Effect of bacterial inoculation on growth of AVP1 transgenic (A) and non-transgenic wheat (B) grown in sterilized sand under controlled conditions A

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Transgenic wheat Cumulative Root dry Shoot dry Treatment root length weight (g) weight (g) (cm) Control (Non-inoculated) 22.91D 0.65B 2.56B Achromobacter strain A6 26.89ABC 0.79A 2.81A Arthrobacter strain NTC-11 27.97A 0.77A 2.82A Azospirillum strain BM30 26.95ABC 0.68B 2.57B Bacillus strain WP2 22.85D 0.68B 2.62B Bacillus strain WP8 26.52ABC 0.63B 2.65B Brevibacterium sp. strain NFM-2 25.06CD 0.72AB 2.63B Microbacterium strain WN1 27.91AB 0.64B 2.75A Pseudomonas strain WP3 27.99A 0.80A 2.83A LSD(P≤ 0.05) 2.88 0.092 0.14 Values in a column sharing same letter do not differ significantly (P≤ 0.05) according to Fisher’s LSD, (n=3). Five seeds of wheat were grown in plastic jars containing sterilized sand and 1.0 mL bacterial cultures (≃ 109cfu/mL) were inoculated to seedlings after emergence. Three seedlings were maintained in each jar with five replicates.

Non–transgenic wheat Cumulative Root dry Shoot dry Treatment root length weight (g) weight (g) Control (Non-inoculated) 24.64 0.70CD 2.54DE Achromobacter strain A6 26.14 0.71CD 2.82A Arthrobacter strain NTC-11 26.04 0.82AB 2.80AB Azospirillum strain BM30 23.04 0.72CD 2.81AB Bacillus strain WP2 25.44 0.75BC 2.72BC Bacillus strain WP8 23.24 0.70CD 2.57DE Brevibacterium sp. strain NFM-2 22.64 0.81AB 2.53E Microbacterium strain WN1 22.44 0.72CD 2.73AB Pseudomonas strain WP3 26.13 0.88A 2.81AB LSD(P≤ 0.05) N.S 0.083 0.14

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T.Root Dry wt (g) NT. Root dry wt T.Shoot dry wt (g) NT.Shoot dry wt (g)

2.5

1.5 Weight (g) 1

0.5

0 C A6 NTC-11 BM30 WP2 WP8 NFM-2 WN1 WP3

Treatments

Figure 3-27 Effect of bacterial inoculation on shoot dry weight, and root dry weight of transgenic and non-transgenic wheat plants Control= Non-inoculated; T= AVP1 transgenic cotton; NT= Non-transgenic cotton A6= Inoculated with Achromobacter strain A6; NTC-11= Inoculated with Arthrobacter strain NTC-11; BM30= Inoculated with Azospirillum strain BM30; WP2= Inoculated with Bacillus strain WP2; WP8= Inoculated with Bacillus strain WP8; NFM-2= Inoculated with Brevibacterium strain NFM-2; WN1= Inoculated with Microbacterium strain WN1; WP3= Inoculated with Pseudomonas strain WP3

75 3. Results

3.8.2 Experiment 2 (year 2011-2012) Effect of bacterial inoculation on AVP1 transgenic and non-transgenic wheat grown in micro-plots Bacterial strains which showed efficient plant growth promotion in sand culture were selected for use as inoculum of wheat in micro-plots. To evaluate the performance of bacterial strains on growth of AVP1 transgenic and non-transgenic wheat, micro-plot experiments were designed in a net house of NIBGE under natural (light and temperature) conditions (Figure 3-28). In this experiment, Achromobacter strain A6, Arthrobacter strain NTC-11, Microbacterium strain WNI, Azospirillum strain BM30 and Pseudomonas strain WP3 were used as single-strain inoculum. Plants were harvested at maturity and data on different plant growth parameters (cumulative root length, root dry weight, straw and grain weight) were recorded. Data analysis showed a significant (<0.05) effect of inoculated strains on both transgenic and non-transgenic plants as compared to non-inoculated control plants. Transgenic plants inoculated with Arthrobacter strain NTC-11, Azospirillum strain BM30 and Pseudomonas strain WP3 showed significant (<0.05) increase in root length and root dry weight. Inoculation of Arthrobacter strain NTC-11 showed maximum increase in the straw dry weight (8.1%) over control and maximum increase in grain weight (8.2%) over control was noted in the plants inoculated with Pseudomonas strain WP3. Inoculation of non-transgenic wheat plant with Arthrobacter strain NTC-11, resulted in a maximum increase of cumulative root length, straw weight and grain weight. All inoculated strains showed significant improvement of straw weight and grain weight (Table 3.21).

Figure 3-28 Effect of bacterial inoculation on growth of AVP1 transgenic and non-transgenic wheat grown in micro-plots under natural conditions.

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Table 3.21 Effect of PGPR strains on yield and growth parameters of transgenic (A) and non-transgenic wheat (B) grown in micro-plots during 2011-2012 A

Transgenic wheat Treatment Cumulative Root dry Straw Grain root length (cm) weight(g) weight (g) weight (g)

Control (Non-inoculated) 22.05C 1.45C 656.67E 565.00C Achromobacter strain A6 23.15BC 1.48C 677.00C 563.67C Arthrobacter strain NTC-11 27.15A 1.67A 705.33A 594.33B Microbacterium strain WNI 25.98AB 1.63B 669.67D 530.67D Azospirillum strain BM30 27.16A 1.68A 692.00B 600.33B Pseudomonas strain WP3 27.37A 1.67A 676.67C 611.67A LSD(P≤ 0.05) 3.6 0.02 6.74 8.64

Transgenic wheat Treatment Cumulative root Root dry Straw Grain length (cm) weight(g) weight (g) weight (g)

Control (Non-inoculated) 22.66B 1.48C 636.0C 539.33 C Achromobacter strain A6 23.83B 1.67 A 666.6B 562.00 B Arthrobacter strain NTC-11 27.02 A 1.43C 687.6A 585.67 A Microbacterium strain WNI 25.43AB 1.66AB 668.0B 556.00 B Azospirillum strain BM30 24.06B 1.55BC 665.6B 558.67 B Pseudomonas strain WP3 23.40 B 1.54C 659.0B 560.33 B LSD(P≤ 0.05) 22.83 0.12 11.66 7.27 Wheat seeds were sown in Micro-plots (1.2mx1.2m) maintaining RXR distance 23 cm and PXP distance15cm. Values are an average of 3 replications.

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T.Grain weight (g) NT.Grain weight (g) T.Straw weight (g) NT.Straw weight (g)

800 700 600 500 400 300 Weight (g) 200 100 0 C A6 NTC-11 WN1 BM30 WP3 Treatments

Figure 3-29 Effect of bacterial inoculation on straw weight, and grain weight of transgenic and non-transgenic wheat plants grown in micro-plots C= Non-inoculated; T=AVP1 transgenic wheat, NT= Non-transgenic wheat, A6= Inoculated with Achromobacter strain A6; NTC-11= Inoculated with Arthrobacter strain NTC-11; WN1= Inoculated with Microbacterium strain WN1; BM30= Inoculated with Azospirillum strain BM30; WP3= Inoculated with Pseudomonas strain WP3

78 3. Results

3.8.3 Experiment 3 (2012-2013) Effect of Bacterial Inoculation on AVP1 Transgenic and Non-Transgenic Wheat Grown in Micro-Plots

The experiment was conducted in cemented micro plots (1.2m X 1.2m) to evaluate the effects of bacterial inoculation on AVP1 transgenic and non-transgenic wheat (Figure 3-30). The bacterial inocula included Achromobacter strain A6, Arthrobacter strain NTC-11, Pseudomonas strain WP3, Azospirillum lipoferum strain BM30 and Microbacterium strain WNI. Among the inoculated treatments of transgenic plants, inoculation with four strains i.e Achromobacter strain A6, Arthrobacter strain NTC-11, Pseudomonas strain WP3 and Azospirillum lipoferum strain BM30 resulted in a significant increase in cumulative root length. Maximum increase in straw weight (12% over control) grain weight (9%over control) was recorded in plants inoculated with Pseudomonas strain WP3. (Table 3.22A). Inoculation with three strains (Arthrobacter strain NTC-11, Azospirillum strain BM30 and Pseudomonas strain WP3) showed a significant increase in root dry weight of non-transgenic plants. Maximum increase in straw weight was recorded in the plants inoculated with Achromobacter strain A6, Azospirillum strain BM30, Pseudomonas strain WP3 and Microbacterium strain WNI. Inoculation of non-transgenic plants with Arthrobacter strain NTC-11 and Microbacterium strain WNI resulted in a maximum increase in grain dry weight which was 18.9% and 17.7%, respectively over non-inoculant control (Table 3.22B).

Figure 3-30 Effect of bacterial inoculation on growth of AVP1 transgenic and non-transgenic wheat grown in micro-plots under natural conditions.

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Table 3.22. Effect of PGPR strains on yield and growth parameters of transgenic (A) and non-transgenic wheat (B) grown in micro plots during 2012-2013 A

Transgenic wheat Treatment Cumulative Root dry Straw Grain root length weight(g) weight weight (g) (cm) (g)

Control (Non-inoculated) 20.06B 2.21C 555.6C 404.6D

Achromobacter strain A6 23.28A 2.47AB 556.6 C 415.0C

Arthrobacter strain NTC-11 23.33A 2.58A 659.6A 461.6A

Microbacterium strain WNI 20.66B 2.63A 566.6C 417.0C

Azospirillum strain BM30 22.00A 2.39B 614.6B 413.6C

Pseudomonas strain WP3 23.21A 2.49AB 635.0B 450.3B

LSD(P≤ 0.05) 2.68 0.15 20.7 8.35

Non-transgenic wheat Treatment Cumulative root Root dry Straw Grain length (cm) weight weight weight(g) (g) (g)

Control (Non-inoculated) 19.09C 2.36C 529.6B 389.3C

Achromobacter strain A6 21.33AB 2.56AB 536.6B 412.0B

Arthrobacter strain NTC-11 22.66A 2.60A 603.3A 435.6A

Microbacterium strain WNI 19.33BC 2.43BC 625.0A 406.0B

Azospirillum strain BM30 21.00AB 2.66A 638.3A 410.3B

Pseudomonas strain WP3 22.43AB 2.64A 629.0A 408.6B

LSD(P≤ 0.05) 0.26 0.14 37.56 7.27 Wheat seeds were sown in micro-plots (1.2mx1.2m) maintaining RXR distance 23 cm and PXP distance15cm. Values are an average of 3 replications.

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T.Grain weight (g) NT.Grain weight(g)

T.Straw weight (g) NT.Straw weight (g)

700

600

500

400

300 Weight (g) 200 NT.Straw… T.Straw… 100 NT.Grain… T.Grain… 0 C A6 NTC-11 WN1 BM30 WP3 Treatments

Figure 3-31 Effect of bacterial inoculation on straw weight, and grain weight of transgenic and non-transgenic wheat plants T.C= Transgenic wheat non-inoculated, NTC= Non-transgenic wheat non-inoculated; A6= Inoculated with Achromobacter A6; NTC-11=Inoculated with Arthrobacter strain NTC-11; WN1=Inoculated with Microbacterium strain WNI; BM30=Inoculated with Azospirillum strain BM30. WP3=Inoculated with Pseudomonas strainWP3

81 3. Results

3.9 Bacterial Population Bacterial population (log cfu/g of soil) in the rhizosphere of transgenic and non- transgenic plants of cotton and wheat was estimated on growth media at 30, 60 and 90 days after sowing (DAS). Soil samples were collected from the rhizosphere of cotton and wheat plants (transgenic and non-transgenic) grown during 2012 and 2011-2012, respectively. General bacterial population (cfu) was estimated by serial dilution method on nutrient agar plates and diazotrophic bacterial population was estimated by MPN (most probable number) using NFM (semi-solid) medium.

Data showed that bacterial populations (cfu/g soil) were not statistically different in the rhizosphere of transgenic and non-transgenic plants of cotton and wheat, however a shift in bacterial population was recorded at different growth stages. In cotton rhizosphere, maximum bacterial population (5.63 log cfu/g soil) was recorded at 90 DAS among the transgenic cotton plants as compared to 60 and 30 DAS. From wheat rhizosphere, maximum bacterial population (6.42 log cfu/g soil) was recorded at 60 DAS among transgenic wheat plants as compared to 30 and 90 DAS.

Diazotrophic bacterial population (MPN) did not show any significant difference in cotton rhizosphere (transgenic and non-transgenic). However, in wheat rhizosphere, a shift in bacterial population was recorded at 30 and 60 DAS. In wheat rhizosphere, maximum bacterial population i.e 5.3 log MPN/g soil in transgenic wheat and 4.8 log MPN/g soil were recorded in non-transgenic wheat at 60DAS.

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5.8 5.7 A A 5.6 B B 5.5

5.4 C C

5.3 Logcfu/g soil 5.2 5.1 5 30 DAS 60 DAS 90 DAS Transgenic Cotton Non-transgenic

Figure 3-32 Bacterial population (log cfu/g soil) on nutrient agar in the rhizosphere of transgenic and non-transgenic cotton at 30, 60 and 90 days after sowing (DAS)

6.6

6.5 A A B 6.4 B 6.3 C C

6.2 Log cfu/g soil Logcfu/g

6.1

6 30 DAS 60 DAS 90 DAS

Transgenic Wheat Non-transgenic

Figure 3-33 Bacterial population (log cfu/g soil) on nutrient agar in the rhizosphere of transgenic and non-transgenic wheat at 30, 60 and 90 days after sowing (DAS)

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8.0

7.0 A A 6.0

5.0

4.0 MPN /g of soil (log values) (log soil of /g MPN 3.0 30.DAS 60.DAS 90.DAS Transgenic cotton Non-transgenic

Figure 3-34 Bacterial population of diazotrophs (log MPN/g soil in NFM) in the rhizosphere of transgenic and non-transgenic cotton at 30, 60 and 90 days after sowing (DAS)

8 7 A 6 A A A 5 C C 4 3 2 1 0 30 DAS 60 DAS 90 DAS Transgenic wheat Non-transgenic

Figure 3-35 Bacterial population diazotrophs (log MPN/g soil in NFM) in the rhizosphere of transgenic and non-transgenic wheat at 30, 60 and 90 days after sowing (DAS)

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3.9.1 Real Time PCR Quantification of 16S rRNA and nif H genes from Rhizospheric Soil Abundance of 16S rRNA and nif H genes was determined by real time PCR from the rhizosphere soil samples collected at different growth stages (35 and 90 DAS). The soil samples were collected in two replicates from rhizosphere of cotton (transgenic and non-transgenic) plants during the year 2012 and from wheat (transgenic and non- transgenic) plants grown during 2011-12. These samples were divided into two group’s i.e Group A and Group B. Each sample was given a specific ID that represents its source i.e TC for transgenic cotton, NTC for non-transgenic cotton whereas ‘TW’ for transgenic wheat and ‘NTW’ for non-transgenic wheat.

In Group A, that belonged to cotton rhizospheric soil samples collected during the year 2011, maximum copy number log 6.39 copies/g soil of 16S rRNA gene was recovered in sample TC (transgenic cotton) collected at 90 DAS, followed by log 6.36 copies/g soil in sample NTC (non-transgenic cotton) collected at 90 DAS. A relatively lower copy number 16S rRNA gene was recorded in samples which were collected at 35 DAS. nifH gene abundance data showed that population of diazotrophic bacteria was maximum i.e log 5.85 copies/g soil in non-transgenic cotton soil sample (NTC) at 35 DAS and it was minimum in transgenic cotton rhizosphere at 35 DAS (Table 3.23).

The group B, belonged to rhizospheric soil samples from wheat rhizosphere grown during 2009-10. Highest copy number (log 6.79 copies/g soil) of 16S rRNA gene was estimated in non-transgenic wheat at 90 DAS whereas relatively low copy number (log 6.54.79 copies/g soil) was observed in transgenic wheat rhizosphere at 90 DAS. Population of diazotrophic bacteria indicated by copy number of nif H, was highest (5.84 copies/g soil) in transgenic wheat at 35 DAS and slightly low in non-transgenic wheat at 35 DAS. A low copy number of nifH was observed in both transgenic and non- transgenic wheat at 90 DAS (Table 3.23).

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Table 3.23 Relative gene abundance (copy number) of bacterial 16S rRNA and nif H genes in the rhizospheric soil revealed by real time PCR

Cotton

Samples Sample.ID Sampling 16S rRNA gene nif H gene time copies/ g of soil copies/ g of soil (log values) (log values) * Group. A T-C 35 DAS 6.04 ± 0.30 5.66 ± 1.72 NT-C 35 DAS 6.22 ± 1.02 5.85 ± 2.90 T-C 90 DAS 6.39 ± 0.99 5.41 ± 1.70 NT-C 90 DAS 6.367 ± 2.1 5.39 ± 2.68 Wheat

Sample.ID Sampling 16S rRNA gene nif H gene time copies/ g of soil copies/ g of soil (log values) (log values) ** Group. B T-W 35 DAS 6.54 ± 0.48 5.94 ± 0.98 NT-W 35 DAS 6.63 ± 0.87 5.83 ± 1.60 T-W 90 DAS 6.62 ± 2.14 5.26 ± 1.32 NT-W 90 DAS 6.79 ± 1.51 5.16 ± 2.61 *: Group A includes soil samples from AVP1 transgenic (TC) and non-transgenic cotton (NT-C) rhizosphere, collected at different days after sowing (DAS) during 2011. **:Group B includes soil samples from AVP1 transgenic(TW) and non-transgenic wheat (NT-W) rhizosphere collected at different days after sowing (DAS) during 2009- 10. Given values are an average of three replicates with standard deviation

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Figure 3-36 Real time quantification of 16S rRNA and nifH gene from rhizosphere of AVP1 transgenic cotton and wheat TC= AVP1 transgenic cotton; NTC= Non-transgenic cotton, TW= AVP1 transgenic wheat; NTW=Non-transgenic wheat 3.9.2 Detection of Root Exudates in the Rhizosphere of AVP1 Transgenic Cotton and Wheat Organic acids (acetic acid, citric acid, malic acid and oxalic acid) produced as root exudates in the rhizosphere of AVP1 transgenic cotton and wheat were also investigated. The soil samples were collected in two replicates from rhizosphere of cotton (transgenic and non-transgenic) plants during the year 2012 and from wheat (transgenic and non-transgenic) plants grown during 2011-12. Maximum amount of acetic acid (8.89 µg/mL) was detected in transgenic cotton rhizosphere. Malic acid was detected in smaller amounts in all soil samples. A difference was observed in the production of oxalic acid that was relatively higher in transgenic cotton rhizosphere (6.72 µg/mL) whereas in non-transgenic cotton rhizosphere it was present relatively in low amounts (3.84 µg/mL). Over all transgenic rhizosphere soil showed a relatively higher amounts of organic acid production as compared to non-transgenic rhizosphere.

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Table 3.24. Detection of organic acids produced* as root exudates in rhizosphere of AVP1 transgenic and non-transgenic cotton and wheat A

Treatment Acetic acid Oxalic Acid Citric acid Malic acid

1. Transgenic 8.89 ± 1.30A 6.72 ± 2.31A 2.06 ± 0.71A 0.73± .05A cotton

2. Non-transgenic 8.15 ± 1.12B 3.84 ± 1.20B 1.99 ± 0.45B 0.71± 0.04A cotton LSD (P ≤ 0.05) 0.03 0.02 0.01 N.S

Treatment Acetic acid Oxalic Acid Citric acid Malic acid

3. Transgenic 8.62 ± 1.60A 5.43 ± 2.2A 2.18 ± 0.95A 0.94± 0.01A wheat

4. Non-transgenic 8.25 ± 2.14B 3.27 ± 1.5B 2.16 ± 0.20A 0.98± 0.02B wheat LSD (P ≤ 0.05) 0.04 0.02 NS 0.02

*Cotton (2012) and wheat (2011-12) plants were uprooted with adhering soil in three replicates. Roots along with attached soil were washed to extract the roots exudates. Extract was analyzed on HPLC to determine the organic acids present in exudates. Values are an average of three replicates with standard deviation.

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Malic acid

9 Citric acid 8

7 Oxalic Acid 6

5 Acetic acid

4 Organicacid (µg/mL) 3

2 Acetic acid Oxalic Acid 1 Citric acid Malic acid 0 TC NTC TW NTW

Treatments

Figure 3-37 Organic acid production in rhizosphere of AVP1 transgenic and non- transgenic cotton and wheat T.C= Transgenic cotton rhizosphere soil; NT.C= Non-transgenic cotton rhizosphere soil; T.W= Transgenic wheat rhizosphere soil; NT.W= Non-transgenic wheat rhizosphere soil.

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3.10 Diversity of Diazotrophic Bacteria Determined by PCR Amplification of Partial nifH gene from Soil DNA Diversity of diazotrophic bacteria from the rhizosphere of AVP1 transgenic cotton and wheat was determined by PCR amplification of partial nifH gene (~360bp) from DNA directly extracted from the rhizosphere soil. Four clone libraries (TC, NTC, TW, NTW) of nifH gene were constructed and 50 clones from each library were selected randomly and sequenced. On the bases of sequence length and sequence quality 159 clones (TC=41/50, NTC=39/50, TW=38/50, NTW=34/50) provided enough sequence information required for comparison at NCBI databank. In all four clone libraries, sequence related to non-culturable diazotrophic bacteria were high constituting about 78% in TC, 74% in NTC, 78% in TW, and 79% in NTW (Figure 3-39, 3-40).

From the clone library ‘TC’ belonging to diazotrophic bacteria in the rhizosphere of AVP1 transgenic cotton plants, 41 readable sequences were obtained which showed 82% of library coverage. Among 41 readable sequences, 32 sequences (82%) showed homology with non-culturable diazotrophic bacterial sequences and 9 sequences (22%) with culturable diazotrophic bacteria in the databank. Among culturable diazotrophic bacteria 7% sequences showed homology with Anabaena, 2% with Azoarcus sp., 2% with Azospirillum, 5% with Azotobacter chroococcum, 2% with Bradyrhizobium japonicum and 2 % with Pseudomonas sp. (Figure 3-39)

Library ‘NTC’ contained sequences of diazotrophic bacteria retrieved from non-transgenic cotton rhizosphere. In this library 39 readable sequences were obtained with library coverage of 78%. Among these readable sequences, 29 sequences (74%) showed homology with non-culturable diazotrophic bacteria, 10 sequences (26%) showed homology with culturable diazotrophic bacteria in the databank (Figure 3-39). Among culturable diazotrophic bacteria, 5% sequences showed homology with Anabaena, 3% with Azohydromonas, 3% with Azospira restricta, 3% with Azospirillum brasilence, 8% with Bradyrhizobium japonicum, 3 % with Pseudomonas sp. and 3% with Zoogloea oryzae. (Table 3.25)

Library ‘TW’ contained sequences from rhizosphere of AVP1 transgenic wheat. In this library there were 38 readable sequences with library coverage 78%. Among readable sequences 29 sequences (76%) showed homology with non-culturable diazotrophic bacteria and 9 sequences (24%) with culturable diazotrophic bacteria.

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Among these culturable bacteria 10% sequences showed homology with Agrobacterium, 3% with Azospirillum, 5% Bradyrhizobium, 3% with Pseudomonas, and 3% Rhizobium.

Library ‘NTW’ contained sequences from the rhizosphere of non-transgenic wheat. This library contained 34 readable sequences with 68% library coverage. In these readable sequences 27sequences (79%) showed homology with non-culturable diazotrophic bacteria and 7 sequences (21%) showed homology with culturable diazotrophic bacteria. Among culturable diazotrophic bacteria 3% sequences showed homology with Agrobacterium, 3% with Azospirillum, 12% with Pseudomonas and 3% with Zoogloea. (Table 3.30)

Figure 3-38 Amplification of nifH gene from soil DNA extracted from AVP1 transgenic and non-transgenic cotton (A) and wheat (B) Figure A: Lane 1 1kb marker, Lane 2 -Ve control, Lane 3 transgenic cotton (TC1), Lane 4 non-transgenic cotton (NTC1), Lane 5 transgenic cotton (TC2), Lane 6 non- transgenic cotton (NTC2). Figure B: Lane 1 1kb marker, Lane 2 -Ve control, Lane 3 transgenic wheat (TW1) , Lane 4 non-transgenic wheat (NTW1), Lane 5 transgenic wheat (TW2), Lane 6 non- transgenic wheat (NTW2),

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Table 3.25 Diversity of diazotrophic bacterial sequences in the rhizosphere of AVP1 transgenic and non-transgenic cotton

Description AVP1 transgenic cotton Non-transgenic cotton (TC library) (NTC library) A. Total clone sequences 41 39

B. (i) Non-culturable diazotrophs 32 (78%) 29 (74%)

(ii) Culturable diazotrophs 9 (22%) 10 (26%)

C. (i) Anabaena sp. 3 (7%) 2 (5%)

(ii) Azoarcus sp. 1 (2%) 0

(iii) Azohydromonas australica 0 1 (3%)

(iv) Azospira restricta 0 1 (3%)

(iv) Azospirillum zeae 1 (3%) 1 (2%)

(iv) Azotobacter chroococcum 1 (3%) 0

(iv) Bradyrhizobium japonicum 1 (2%) 3 (8%)

(iv) Pseudomonas stutzri 1 (3%) 1 (3%)

(iv) Zoogloea oryzae 0 1 (2%)

TC’ and ‘NTC’ nifH gene libraries constructed from amplified nifH gene from rhizosphere of AVP1 transgenic and non-transgenic cotton, respectively.

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Figure 3-39 Distribution of diazotrophic bacterial sequences in the rhizosphere of AVP1 transgenic (A) and non-transgenic cotton (B).

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Table 3.26 Identification of culturable diazotrophic bacterial sequences in the rhizosphere of AVP1 transgenic cotton

No. Sequence IDa Closest match Sequence Origin References & Accession in NCBI similarity No. (%) 1 P1- 18 Anabaena sp. 99 Rice paddies Un-published (LN736030.1) (HM063719.1) (India) 2 P1- 15 Anabaena sp. 92 [206] (LN736031.1) (AJ716235.1)

3 P3-13 Anabaena sp. 97 [207] (LN736032.1) (JN1624601.1)

4 P1- 14 Azospirillum zea 94 Zea mays [207] (LN736033.1) (JN162478.1) (India)

5 P1- 22 Azotobacter 97 Agricultural unpublished (LN736034.1) chroococcum soil (EF634050.1) (Italy)

6 P3- 3 Azoarcus 86 Kallar grass [208] (LN736035.1) (AY6010541) (China)

7 P3- 4 Bradyrhizobium 87 Radish [209] (LN736036.1) Japonicum paddy soil (HQ3356861) (Nether land) 8 P1-6 Pseudomonas 73 [211] (LN736037.1) stutzri (CP000304.1)

Identification by NCBI BLASTN of nif H sequences obtained from the rhizosphere of AVP1 transgenic cotton grown in controlled condition. a:Sequence ID represents the clones obtained from nifH gene library ‘’TC’’

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Table 3.27 Identification of culturable diazotrophic bacteria detected in the rhizosphere of non-transgenic cotton

No. Sequence IDa Closest match in Sequence Originc References & Accession NCBI similarity No. (%) 1 P2- 11 Azohydromonas 99 Saline alkaline [210] (LN736038.1) australica soil India (JN162460.1) 2 P2- 3 Azospirillum 99 Aquatic [211] (LN736039.1) brasilense terrestrial (EU048106.1) environments. Brazil 3 P2- 7 Pseudomonas sp. 89 Pulp and paper Unpublished (LN736040.1) (HM063793.1) wastewater China 4 P2-4 Zoogloea oryzae 89 Rice paddy soil [209] (LN736041.1) (HQ335686.1) in Tokyo 5 P2-14 Azospira restricta 89 Ground water Unpublished (LN736042.1) (HQ190167.1) China 6 P3- 13 Azoarcus, 86 [177] (LN736043.1) (AY6010541) 7 P2-26 Bradyrhizobium 93 Radish paddy [212] (LN736044.1) japonicum soils (EF583593.1) 8 P2-23 Bradyrhizobium 92 Sweden Unpublished (LN736045.1) japonicum china (GQ289562.1) 9 P4-11 Bradyrhizobium 92 Unpublished (LN736046.1) japonicum china (GQ289582.1) 10 P4-20 Anabaena sp. 93 Variety Unpublished (LN736047.1) (L04598.1) environment 11 P4-7 Anabaena sp. 96 china [213] (LN736048.1) (L04499.1) a:Sequence ID represents the clones obtained from nifH gene library ‘’NTC’’

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Table 3.28 List of uncultured diazotrophic bacteria from AVP1 transgenic cotton rhizosphere

# Clone Acc. No Source*

1 P3-5 KH744001.1 2 P3-30 KH744002.1 saline alkaline soil 3 P3-20 KH744003.1

4 P3-12 KH744004.1 5 P3-14 KH 744005.1 6 P3-16 KH 744006.1 cotton rhizospheric soil 7 P1-11 KH 744007.1 8 P1-29 KH 744008.1 soils 9 P1-1 KH 744009.1 10 P1-20 KH 744010.1 11 P3-6 KH 744011.1 paddy soil from China 12 P3-15. KH 744012.1 Marine sediments 13 P1-30 KH 744013.1 Oryza-root tissues 14 P3-19 KH 744014.1 Tea plants 15 P3-29 KH 744015.1 Bioremediation soil 16 P3-7 KH 744016.1 17 P3-21 KH 744017.1 Forest soil 18 P1-2 KH 744018.1 Thick mudflat sediment. 19 P1-23. KH 744019.1 Soybeans . 20 P3-23 KH 744020.1 Leaf surface 21 P3-24 KH 744021.1 22 P1-25 KH 744022.1 Indian Punjab soil 23 P3-9 KH 744023.1 California soil 24 P1-26 KH 744024.1 Rhizosphere 25 P1-19 KH 744025.1 Sea water 26 P3-1 KH 744026.1 27 P3-8 KH 744027.1 28 P1-16 KH 744028.1 29 P1-28 KH 744029.1 Microbial mat of salted soil 30 P1-5 KH 744030.1 Salt marsh elevation 31 P1-21 KH 744031.1 Chesapeake bay *Uncultured diazotrophic source already reported in databank

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Table 3.29 List of uncultured diazotrophic bacterial sequences from non- transgenic cotton rhizosphere

# Clone Acc. No Source* 1 P4-9 KH744032.1 cotton rhizosphere 2 P2-1 KH744033.1 3 P4-9 KH744034.1 4 P2-2 KH744035.1 alkaline soil sorghum 5 P4-28 KH744036.1 6 P4-2 KH744037.1 7 P4-15 KH744038.1 8 P4-12 KH744039.1 salt marsh soils 9 P4-22 KH744040.1 soil 10 P2-12 KH744041.1 11 P2-8 KH744042.1 12 P4-17 KH744043.1 alkaline soils 13 P2-28 KH744044.1 14 P4-25 KH744045.1 15 P2-16 KH744046.1 rice filed 16 P4-13 KH744047.1 paddy soils 17 P4-8 KH744048.1 18 P2-6 KH744049.1 roots of Oryza sative 19 P2-22 KH744050.1 20 P4-1 KH744051.1 21 P4-16 KH744052.1 Kollumerwaard bulk soil 22 P4-19 KH744053.1 23 P4-18 KH744054.1 24 P2-5 KH744055.1 Baltic sea 25 P2-9 KH744056.1 Turf grass soil 26 P4-30 KH744057.1 Forest soil 27 P2-15 KH744058.1 Salted pond microbial mat 28 P4-10 KH744059.1 Cotton rhizosphere 29 P2-20 KH744060.1 *Uncultured diazotrophic source already reported in databank

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Table 3.30 Diversity of diazotrophic bacteria in the rhizosphere of AVP1 transgenic and non-transgenic wheat

Description AVP1 transgenic Non-transgenic Wheat Wheat (TCW) (NTW) A. Total clone sequences 38 (79%) 34 (76%)

B. (i) Non-culturable diazotrophs 29 (76%) 27 (79%)

(ii) Culturable diazotrophs 9 (24%) 7 (21%)

C. (i) Agrobacterium tumefaciens 4 (8%) 1 (3%)

(ii) Azospirillum sp. 1 (3%) 1 (3%)

(iii) Bradyrhizobium japonicum 2 (5%) 0

(iv) Pseudomonas sp. 1 (3%) 4 (12%)

(v) Rhizobium sp. 1 (3%) 0

(vi) Zoogloea sp. 0 1 (3%)

TCW’ and ‘NTW’ nifH gene libraries constructed from amplified nif H gene from rhizosphere of AVP1 transgenic and non-transgenic wheat, respectively.

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Figure 3-40 Distribution of diazotrophic bacteria in the rhizosphere of AVP1 transgenic (A) and non-transgenic wheat (B)

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Table 3.31 Identification of culturable diazotrophic bacterial sequences in the rhizosphere of AVP1 transgenic wheat

No. Sequence ID Closest match in Sequence Origin References & Accession NCBI similarity No. (%)

1 P7-26 Rhizobium 99 "agricultural Un-published gallicum soil" Italy (LM794549.1) (EF634041.1)

2 P7-27 Pseudomonas sp. 98 sugarcane Un-published rhizosphere (LM794550.1) (FJ822997.1) from china

3 P7-29 Agrobacterium 98 sugarcane [214] tumefaciens rhizosphere (LM794551.1) from china (FJ822995.1)

4 P5-22 Azospirillum spp. 95 china Un-published

(LM794552.1) (GU256447.1)

5 P7-3 Pseudomonas sp. 95 sugarcane in Un-published china (LM794553.1) (FJ822997.1)

6 P5-28 Azospirillum 94 cereal crops [215] brasilense grown in (LM794554.1) Greece (GQ161230.1)

7 P5-6 Azospirillum 93 China [216] brasilense (LM794555.1) (GQ161230.1)

8 P5-14 Bradyrhizobium 90 "reddish paddy [217] japonicum soil (LM794556.1) (GQ289577.1)

9 P5-12 Bradyrhizobium 86 "reddish paddy Un-published japonicum soil (LM794557.1) (GQ289567.1) Identification by NCBI BLASTN of nif H sequences obtained from the rhizosphere of AVP1 transgenic and non-transgenic wheat grown in controlled condition. Sequence ID represents the clones obtained from nifH gene library ‘’TW’’

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Table 3.32 Identification of culturable diazotrophic bacteria detected in the rhizosphere of non-transgenic wheat

No. Sequence IDa Closest match in Sequence Origin References & Accession NCBI similarity No. (%) 1 P8-4 Azotobacter 99 Diazotrophic [218] (LM794522.1) chroococcum strain study (M73020.1) 2 P6-13 Azospirillum zea 95 Field-grown [48] (LM794523.1) (FR669146.1) barley, oat, and wheat

3 P6-14 Pseudomonas sp. 96 Sugarcane Unpublished (LM794524.1) (FJ822997.1) rhizosphere soil from china

4 P6-16 Pseudomonas sp. 97 Sugarcane Unpublished (LM794525.1) (FJ822997.1) rhizosphere soil from china

5 P8-14 Pseudomonas sp. 99 sugarcane unpublished (LM794526.1) (FJ822997.1) rhizosphere soil from china

6 P6-5 Zoogloea oryza 87 rice paddy soil [219] (LM794527.1) (AB201045.1) 7 P8-26 Pseudomonas sp. 96 sugarcane unpublished (LM794528.1) (FJ822997.1) rhizosphere soil from china

a:Sequence ID represents the clones obtained from nifH gene library ‘’NTW’’

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Table 3.33: List of uncultured diazotrophic bacteria from AVP1 transgenic wheat rhizosphere

No. Clone Acc. No Source* 1 P5-3 LM794520.1 Roots of rice 2 P7-24 LM794521.1 paddy soil china 3 P5-23 LM794523.1 4 P7-22 LM794524.1 Agricultural soil Switzerland 5 P7-7 LM794526.1 Root and stem of field- grown maize 6 P7-25 LM794527.1 "Saline-alkaline soil" 7 P7-1 LM794528.1 8 P5-4 LM794530.1 Free living diazotroph of soil 9 P7-14 LM794531.1 "Saline-alkaline soil" 10 P5-16 LM794533.1 "Kollumerwaard bulk soil"

11 P7-20 LM794534.1 soil neatherland 12 P5-26 LM794535.1 13 P7-13 LM794537.1 14 P7-19 LM794538.1 15 P5-9 LM794540.1 16 P5-25 LM794541.1 17 P7-2 LM794542.1 18 P7-17 LM794544.1 19 P7-21 LM794545.1 20 P5-7 LM794547.1 21 P5-17 LM794548.1 22 P7-6 LM794549.1 23 P5-15 LM794551.1 Free living diazotroph of soil 24 P5-27 LM794552.1 Montipora flabellata 25 P5-30 LM794554.1 Microbial mat on sandy 26 P7-9 LM794555.1 intertidal beach

27 P7-30 LM794556.1 28 P5-8 LM794558.1 Colombian Amazon Region 29 P5-1 LM794559.1 Malaysian soil 30 P5-19 LM794561.1 Mudflat mesocosms 31 P5-20 LM794562.1 "hot spring" *Uncultured diazotrophic source already reported in databank

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Table 3.34 List of uncultured diazotrophic bacteria from AVP1 transgenic wheat rhizosphere

Clone Acc.No Source* 1 P6-12 LM794563.1 Paddy soil in china with long term organic 2 P6-3 LM794565.1 management 3 P8-29 LM794566.1 4 P8-1 LM794568.1 Lelystad bulk soil" The Netherlands 5 P8-9 LM794569.1 Kollumerwaard bulk soil" 6 P8-2 LM794570.1 7 P8-7 LM794572.1 8 P6-23 LM794573.1 9 P6-7 LM794575.1 10 P8-16 LM794576.1 11 P8-28 LM794577.1 12 P8-3 LM794579.1 Falls Lake, North Carolina" 13 P8-17 LM794580.1 Rice roots 14 P8-5 LM794582.1 15 P6-21 LM794583.1 16 P6-20 LM794584.1 Rhizospheric soil of sorghum" 17 P8-10 LM794586.1 Bioremediated soil at Zhongyuan oil field 18 P6-18 LM794587.1 Turfgrass established soil" 19 P6-24 LM794589.1 Rice roots 20 P8-19 LM794590.1 Chesapeake Bay, Station 2, surface" 21 P6-1 rhizospheric soil of sorghum" LM794591.1 22 P6-22 LM794593.1 Tea plantation soil 23 P8-8 LM794594.1 Sandy intertidal beach 24 P6-8 LM794596.1 25 P6-2 LM794597.1 Soil Mexico 26 P6-25 LM794598.1 Soil 27 P8-25 LM794600.1 Thick mudflat sediment" *Uncultured diazotrophic source already reported in databank

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Sequences from AVP1

transgenic Cotton Group I

Sequences from non- transgenic cotton

Group II

Group III

Group IV

Group V

Figure 3-41 Phylogenic tree constructed from nifH gene sequences retrieved from AVP1 transgenic and non-transgenic cotton

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Sequences from AVP1 transgenic wheat

Sequences from non-transgenic wheat

Group I

Group II

Group III

Group IV

Group V

Figure 3-42 Phylogenic tree constructed from nifH gene sequences of AVP1 transgenic and non-transgenic wheat

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3.11 Bacterial Diversity Revealed by Pyrosequencing of 16S rRNA Gene Amplified from Soil DNA Diversity of culturable and uncultured bacteria from the rhizosphere of AVP1 transgenic and non-transgenic cotton and wheat plants was investigated by amplification and sequence analysis of 16S rRNA gene from soil DNA. Rhizosphere soil samples were collected from AVP1 transgenic cotton and wheat along with non-transgenic plants as their control from inoculation experiments conducted during 2012 (cotton) and 2010- 12 (wheat), respectively

Soil DNA was extracted from 4 rhizosphere soil samples i.e rhizospheric soil from AVP1 transgenic cotton, non-transgenic cotton, AVP1 transgenic wheat and non- transgenic wheat (Figure 43). DNA was extracted in two replicates of each rhizosphere soil sample and total 8 samples were processed. 16S rRNA gene was amplified from these 8 soil DNA samples (Figure 44) by using a forward primer ‘454 Primer A’ (799F with an adapter sequence and specific barcode sequence) with 8 different barcodes for all 8 soil DNA samples. ‘454PrimerB’ (1492R with a specific adaptor sequence) were used as a reverse primer

1 2 3 4 5

3000 bp

1000 bp Genomic DNA from soil

Figure 3-43 DNA extracted from the rhizosphere soil of cotton and wheat Lane 1, 1kb marker; Lane 2, soil DNA from transgenic cotton rhizosphere; Lane 3, soil DNA from non-transgenic cotton rhizosphere; Lane 4, soil DNA from transgenic wheat rhizosphere; Lane 5, soil DNA from non-transgenic wheat rhizosphere

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1 2 3 4 5 A

700 bp PCR product 700 (Partial 16S rRNA gene)

1 2 3 4 5

700 bp 700 PCR product (16S rRNA gene)

Figure 3-44 PCR amplification of 16S rRNA gene from the rhizosphere of AVP1-transgenic and non-transgenic cotton (A) and wheat (B) using barcoded A: Lane 1, 1kb marker; Lane 2, +Ve control; Lane 3, -Ve control, Lane 4, transgenic cotton (TC1) Lane 5, non-transgenic cotton (NTC1), Lane 6, transgenic cotton (TC2), Lane 7, non-transgenic cotton (NTC2) B: Lane 1, 1kb marker; Lane 2, +Ve control; Lane 3, -Ve control, Lane 4, transgenic wheat (TW1) Lane 5, non-transgenic wheat (NTW1), Lane 6, transgenic wheat (TW2), Lane 7, non-transgenic wheat (NTW2) 3.11.1 Barcoded Pyrosequencing of 16S rRNA Gene, DNA Sequence Processing and Taxonomic Analysis From 8 soil DNA samples, 16S rRNA gene sequences covering V5, V6, and V7 were amplified with PCR and pyrosequencing of these barcoded amplicons was performed. The obtained sequences were analyzed through the Ribosomal Database Project (RDP) pyrosequencing pipeline (http://pyro.cme.msu.edu). A total of 346531 roots/sequences were obtained from all soil samples, with an average of 43316±14500 roots per sample (Table 3.31). All these roots/sequences according to the individual sample treatment were assigned hierarchy view at 80% confidence threshold. Collectively, 255753 sequences of 16S rRNA gene were related to bacteria, 31137±2840 sequences related to Archaea, 44532 sequences belonged to unclassified bacteria (Table 3.35)

3.11.2 Bacterial Diversity in Cotton Rhizosphere Among the retrieved sequences 127747 sequences of 16S rRNA were related to bacteria, 8128 were related to Archaea and 22964 belonged to unclassified bacteria. Among these sequences on an average 47242±3690 sequences were detected in the

107 3. Results rhizosphere of AVP1 transgenic cotton and about 47882±3198 sequences were detected from non-transgenic cotton rhizosphere. All the 19 bacterial phyla detected on the basis of 16S rRNA gene sequencing were represented in the rhizosphere of both transgenic and non-transgenic cotton plants. In the rhizosphere of AVP1 transgenic cotton plants, sequences of Proteobacteria were most abundant (16188 ± 3282 sequences), followed by Crenarchaeota (14205 ± 2551 sequences) and Firmicutes (4103 ± 1820 sequences). Sequences of the same three phyla were also abundant in the rhizosphere of non- transgenic plants as 14914 ± 2527 sequences belonged to Proteobacteria, followed by 17390 ± 782 sequences of Crenarchaeota and 5651 ± 3885 sequences related to Firmicutes (Table 3.36). Further analysis of retrieved 16S rRNA sequences indicated occurrence bacterial genera in the rhizosphere of transgenic and non-transgenic cotton.

3.11.3 Abundance of Bacterial Classes in Cotton Rhizosphere Soil 16S rRNA sequences belonging to bacterial classes were found in cotton rhizosphere soil. Among these classes on an average 42±4 were detected in transgenic cotton rhizosphere and 38±07 classes were detected in non-transgenic rhizosphere soil. Majority of classes were common in both the soils (transgenic and non-transgenic rhizosphere). Results showed that in AVP1 transgenic cotton rhizosphere sequences belonged to bacterial class Thermoprotei were most abundant (36%), followed by Alpha-proteobacteria (16%), Beta-proteobacteria ( 6%), Gamma-proteobacteria (11%), Actinobacteria (10%), Bacilli (10%), Delta-proteobacteria (5%), Sphingobacteria(4%), Acidobacteria (1%) and Clostridia (1%). In non-transgenic cotton rhizosphere sequences belonging to bacterial class ‘Thermoprotei’ were also most abundant (43%), followed by Alphaproteobacteria (13%), Betaproteobacteria (7%), Gammaproteobacteria (11%), Actinobacteria (4%), Bacilli (13%), Delta-proteobacteria (4%), Sphingobacteria (3%), Acidobacteria GP3(1%) and Clostridia (1%)(Figure 3-46)

3.11.4 Abundance of Bacterial Genera in the Rhizosphere of Cotton Data analysis at genus level showed that in transgenic cotton rhizosphere bacterial sequences related to 344±5 genera were found and sequences related to 321±12 genera were detected in non-transgenic cotton rhizosphere soil. Among these, sequences of 240 genera were commonly detected in transgenic and non-transgenic rhizosphere. This indicated that majority of detected genera were common in both root systems i.e transgenic and non-transgenic cotton rhizosphere (Table 3.37). 16S rRNA sequences

108 3. Results related to 60 genera were found only in the rhizosphere of transgenic cotton (Table 3.38) and 16S rRNA sequences related to 33 genera were found only in the rhizosphere of non-transgenic cotton. Bacterial genera that have been reported as PGPR were also detected in the rhizosphere of transgenic and non-transgenic wheat (Table 3.39). Comparison of the number of sequences retrieved from transgenic and non-transgenic plants belonging to specific groups indicated quantitative differences but all major bacterial groups were present in the rhizosphere of both type of plants.

109 3. Results

Table 3.35 16S rRNA sequences retrieved from rhizosphere of AVP1 transgenic cotton and wheat with non-transgenic control

Unclassified Unclassif Bacterial No. of Total Treatment Roots bacterial ied roots sequences phyla genera sequences 1. TC1a 49852 47 34938 5887 19 348 (2012) 2. NTC1b 50144 64 32158 5415 23 330 (2012) 3. TC2c 44633 49 33734 6838 21 340 (2012) 4.NTC2d 45620 66 26917 4824 20 312 (2012) Total (cotton) 190249 226 127747 22964 99 1330 5. TW1e 45318 62 34353 6027 21 310 (2011-12) 6. NTW1f 40456 31 33640 5108 20 315 (2011-12) 7. TW2g 36637 30 31654 6272 18 276 (2011-12) 8. NTW2h 33871 25 28359 4161 20 298 (2011-12) Total (wheat) 156282 148 128006 21568 79 1199 *Numbers in each row represent the abundance of sequences at different hierarchal levels of bacterial domain mentioned in each column a =TC1, transgenic cotton. b=NTC1, non-transgenic cotton, (collected during 2012) c=TC2, transgenic cotton, d =NTC2 non-transgenic cotton (collected during 2012) e=TW1 transgenic wheat f=NTW1 non-transgenic wheat (collected during 2011-12) g=TW2 transgenic wheat h= NTW2 non-transgenic wheat (collected during 2011-12)

110 3. Results

Table 3.36 Abundance of 16S rRNA sequences belonging to different phyla in the rhizosphere of AVP1 transgenic and non-transgenic cotton

No. Phylum Sequences retrieved from Sequences retrieved AVP1 transgenic cotton from non-transgenic rhizosphere cotton rhizosphere

1 Proteobacteria 16188 ± 3282 14914 ± 2527

2 Crenarchaeota 14205 ± 2551 17390 ± 782

3 Firmicutes 4103 ± 1820 5651 ± 3885

4 Unclassified bacteria 5887 ± 1590 5415 ± 1027

5 Actinobacteria 3819 ± 1156 1783 ± 161

6 Bacteroidetes 2349 ± 632 1844 ± 397

7 Acidobacteria 1036 ± 475 824 ± 84

8 Planctomycetes 692 ± 842 5140 ± 7172

9 Chloroflexi 572 ± 340 259 ± 9

10 Euryarchaeota 440 ± 283 3787 ± 4646

11 Verrucomicrobia 379 ± 62 404 ± 97

12 Nitrospira 352 ± 12 218 ± 245

13 Armatimonadetes 267.5 ± 303 50 ± 18

14 Gemmatimonadetes 247 ± 77 259 ± 37

15 Deinococcus thermus 128 ± 72 94 ± 10

16 Chlamydiae 76 ± 14 72 ± 6

17 Incertaesedis 42 ± 6 122 ± 158

18 Chlorobi 5 ± 3 2 ± 2

19 Elusimicrobia 2 ± 1 61 ± 83

DNA extracted from rhizosphere soil AVP1 transgenic and non-transgenic cotton was used for pyrosequencing analysis of 16S rRNA gene. Given numbers are average of 2 replicates.

111 3. Results

unclassified_Bacteria

55000 Verrucomicrobia

TM7 50000 Unclassified Bacteria Proteobacteria 5887 5415 45000 Planctomycetes

Nitrospira 40000 Proteobacteria Gemmatimonadetes 14914

35000 16188 Firmicutes No. of Phyla of No. Euryarchaeota 30000 Elusimicrobia

25000 5651 4103 Fermicutes Deinococcus-Thermus

Crenarchaeota 20000 Crenarchaeota Chloroflexi 15000 14205 17390 Chlorobi

10000 Chlamydiae Bacteroidetes 2349 5000 1844 Armatimonadetes 3819 1783 0 Actinobacteria AVP1 transgenic Non-transgic cotton Cotton Acidobacteria

Figure 3-45 Abundance of bacterial phyla in the rhizosphere of AVP1 transgenic and non-transgenic cotton.

112 3. Results

Figure 3-46 16S rRNA sequences belonging to different bacterial classes reterieved from the rhizosphere of AVP1 transgenic and non-transgenic cotton

Table 3.37 Abundance of 16S rRNA sequences of different bacterial genera (Top 50 genera) retrieved from transgenic and non-transgenic cotton

No. Genera Sequences detected Sequences detected in in the rhizosphere the rhizosphere of non- of transgenic cotton transgenic cotton 1 Bacillus 2221 3043 2 Steroidobacter 600 435 3 Cellvibrio 426 629 4 Lysobacter 410 95 5 Incertae sedis 388 442 6 Solirubrobacter 372 196 7 Niastella 363 264 8 Pseudoxanthomonas 360 224 9 Nitrospira 355 388 10 Microvirga 333 345 11 Gemmatimonas 302 233 12 Ohtaekwangia 298 186 13 Pseudomonas 291 439 14 Ensifer 254 185

113 3. Results

15 Paenibacillus 230 291 16 Arthrobacter 201 106 17 Devosia 184 95 18 Nitrosospira 180 204 19 Sphingomonas 180 188 20 Cystobacter 171 56 21 Tumebacillus 165 153 22 Dongia 157 125 23 Truepera 156 84 24 Acidobacteria 140 175 25 Streptomyces 139 46 26 Flavobacterium 124 56 27 Rubrobacter 115 58 28 Flavisolibacter 108 126 29 Nocardioides 104 22 30 Pontibacter 102 78 31 Chitinophaga 101 3 32 Amaricoccus 100 41 33 Marmoricola 97 50 34 Acidovorax 93 11 35 Skermanella 90 94 36 Rhizobium 80 132 37 Syntrophobacter 79 108 38 Altererythrobacter 78 49 39 Bryobacter 76 91 40 Arenimonas 72 226 41 Legionella 72 49 42 Rubellimicrobium 71 63 43 Phenylobacterium 66 57 44 Aquicella 64 39 45 Mesorhizobium 55 45 46 Hydrogenophaga 54 83 47 Ammoniphilus 53 112 48 Vasilyevaea 53 21 49 Armatimonadetes 49 58 50 Serpens 48 75

114 3. Results

Figure 3-47 Bacterial genera detected in the rhizosphere of AVP1 transgenic and non-transgenic cotton

Table 3.38 Bacterial genera detected only in the rhizosphere of transgenic cotton

115 3. Results

No. Bacterial genera Sequences detected in the rhizosphere of AVP1 transgenic cotton

1 Pseudofulvimonas 31

2 Serratia 22

3 Azospirillum 14

4 Rhizobacter 13

5 Cellulosimicrobium 4

6 Croceicoccus 4

7 Gemmata 4

8 Microlunatus 4

9 Oxobacter 4

10 Armatimonadetes 3

Table 3.39: Sequences of important PGPR genera detect in the rhizosphere of AVP1 transgenic and non-transgenic cotton

Genera Transgenic Cotton Non-Transgenic Cotton Bacillus 2221 3043 Pseudoxanthomonas 360 224 Pseudomonas 291 439 Paenibacillus 230 291 Arthrobacter 201 106 Flavobacterium 124 56 Rhizobium 80 132 Mesorhizobium 55 45 Bradyrhizobium 48 48 Brevundimonas 40 16 Microbacterium 22 9 Azohydromonas 15 34 Azoarcus 5 4 Burkholderia 1 2

116 3. Results

1000 Transgenic Cotton 900 Non-Transgenic Cotton 800 2221 700 3043 600 500 439 360 400 291 291 300

224 230 201 Genera Abundance Genera 200 132 106 80 100 55 40 45 16 5 4 0

Figure 3-48 Abundance of important PGPR genera in the rhizosphere of AVP1 transgenic and non-transgenic cotton rhizosphere

117 3. Results

3.12 Bacterial Diversity in Wheat Rhizosphere From wheat rhizosphere (transgenic and non-transgenic) total 156282 sequences were obtained by pyrosequencing analysis of 16S rRNA gene. Among these sequences 128006 sequences were related to bacteria, 7928 were Archeal sequences, and 21568 sequences belonged to unclassified bacteria. Among these sequences, on an average 40977±6138 sequences were detected in the rhizosphere of AVP1 transgenic wheat and about 37163±4656 sequences from non-transgenic wheat rhizosphere. All the 18 bacterial phyla detected on the basis of 16S rRNA gene sequencing were represented in the rhizosphere of transgenic and non-transgenic wheat. In the rhizosphere of AVP1 transgenic wheat Proteobacteria were most abundant (14327±3653 sequences), followed by Crenarchaeota (9938±2921) and Firmicutes (6957±1724) sequences. Sequences of Proteobacteria (13180±2784), Crenarchaeota (6580±1436) and Firmicutes (8328±1257) were also abundant in the rhizosphere of non-transgenic wheat as Crenarchaeota (Table 3.40).

3.12.1 Abundance of Bacterial Classes in Wheat Rhizosphere Soil Sequences belonging to bacterial classes were found in wheat rhizosphere soil. Among these sequences related to 44±2 bacterial classes were found in transgenic wheat rhizosphere and sequences related to 42±0.7 bacterial classes were found in non- transgenic wheat rhizosphere soil. Sequences belonging to majority of the classes (94.84%) were common in both the soils. In AVP1 transgenic wheat, Thermoprotei were most abundant (30%), followed by Alpha-proteobacteria (12%), Beta- proteobacteria (7%), Gamma-proteobacteria (8%), Actinobacteria (5%), Bacilli (18%), Delta-proteobacteria (10%), Sphingobacteria (5%), Acidobacteria GP3 (3%) and Clostridia (2%). In non-transgenic wheat rhizosphere sequences of bacterial class ‘thermoprotei’ were also most abundant (21%), followed by Alpha-proteobacteria (14%), Beta-proteobacteria (8%), Gamma-proteobacteria (8%), Actinobacteria (8%), Bacilli (24%), Delta-proteobacteria (9%), Sphingobacteria (4%), Acidobacteria GP3(3%) and Clostridia (1%) (Figure.3-50)

3.12.2 Abundance of Bacterial Genera in the Rhizosphere Wheat In the present study 16S rRNA sequences related to 293±24 genera were found in the rhizosphere of AVP1 transgenic wheat and in the rhizosphere of non-transgenic wheat sequences related to 306±12 genera were detected. Among these 233±24 genera were

118 3. Results common in the rhizosphere of both transgenic and non-transgenic wheat (Table 3.41). Sequences of few genera were found only in the rhizosphere of AVP1 transgenic wheat (Table 3.42). Bacterial genera that have been reported as PGPR were also detected in the rhizosphere of transgenic and non-transgenic wheat (Table 3.43). Comparison of the number of sequences retrieved from transgenic and non-transgenic plants belonging to specific groups indicated quantitative differences but all major bacterial groups were present in the rhizosphere of both type of plants.

119 3 Results

Table 3.40 Abundance of 16S rRNA sequences of different bacterial phyla in the rhizosphere of AVP1 transgenic and non-transgenic wheat

No. Phylum Sequences retrieved Sequences retrieved from AVP1 transgenic from non-transgenic Wheat rhizosphere wheat rhizosphere 1 Proteobacteria 14327±3653 13180±2784

2 Crenarchaeota 9938±2921 6580±1436

3 Firmicutes 6957±1724 8328±1257

4 Unclassified bacteria 6027±1203 5108±445

5 Bacteroidetes 1997±1005 1790±489

6 Acidobacteria 1820±989 1489±750

7 Actinobacteria 1640±945 2469±125

8 Euryarchaeota 904±435 198±57

9 Verrucomicrobia 569±253 504±165

10 Nitrospira 357±125 187±23

11 Chloroflexi 243±15 209±15

12 Chlamydiae 110±25 32±06

13 Gemmatimonadetes 96±17 116±25

14 Planctomycetes 64±05 55±04

15 Armatimonadetes 41±18 37±17

16 Incertaesedis 37±11 29±05

17 Deinococcus-Thermus 32±09 60±08

18 Chlorobi 27±07 38±14

DNA extracted from rhizosphere soil AVP1 transgenic and non-transgenic wheat was used for pyrosequencing analysis of 16S rRNA gene. Given numbers are average of 2 replicates.

120 3 Results

Verrucomicrobia 50000 unclassified_Bacteria

TM7 45000

Unclassified Bacteria Proteobacteria 6027 40000 Planctomycetes

5108 Nitrospira 35000 Proteobacteria Gemmatimonadetes 14327 30000

No. of Phyla of No. Firmicutes 13180 Euryarchaeota 25000 Deinococcus-Thermus

20000 6957 Firmicutes Crenarchaeota 8328 Chloroflexi 15000

Chlorobi 9938 10000 6580 Chlamydiae Crenarchaeota Bacteroidetes 5000 Armatimonadetes

0 Actinobacteria AVP1 transgenic Non-transgenic wheat Wheat Acidobacteria

Figure 3-49: Abundance of 16S rRNA sequences of different bacterial phyla in the rhizosphere of AVP1 transgenic and non-transgenic wheat

7 00

121 3 Results

Figure 3-50 Abundance of 16S rRNA sequences belonging to different bacterial classes dominant in wheat rhizosphere of AVP1 transgenic and non-transgenic wheat Table 3.41 Abundance of 16S rRNA sequences belonging to different bacterial genera (Top 50 genera) retrieved from the rhizosphere of AVP1 transgenic and non-transgenic wheat

No. Genera Sequences detected Sequences detected in in the rhizosphere the rhizosphere of of transgenic wheat non-transgenic wheat 1 Bacillus 3207 4738 2 Steroidobacter 794 761 3 Paenibacillus 490 418 4 Methanosarcina 458 40 5 Azotobacter 417 370 6 Nitrospira 344 181 7 Ohtaekwangia 338 295 8 Bryobacter 322 267 9 Sphingomonas 282 141 10 Flavisolibacter 281 262 11 Skermanella 235 318 12 Dongia 207 126 13 Microvirga 180 212 14 Niastella 176 226 15 Methanobacterium 174 44 16 Clostridium sensu stricto 153 85 17 Mesorhizobium 133 132 18 Armatimonadetes 114 45 19 Arthrobacter 113 93

122 3 Results

20 Solirubrobacter 111 165 21 Anaeromyxobacter 103 97 22 Armatimonadetes 99 76 23 Cystobacter 98 35 24 Devosia 97 96 25 Gemmatimonas 96 116 26 Haliangium 88 188 27 Armatimonadetes 79 82 28 Ammoniphilus 72 113 29 Peredibacter 68 43 30 Ensifer 68 54 31 Marmoricola 64 84 32 Altererythrobacter 55 120 33 Lysobacter 54 103 34 Armatimonadetes 53 88 35 Streptomyces 49 100 36 Parachlamydia 47 10 37 Falsibacillus 46 53 38 Pontibacter 45 93 39 Crossiella 44 21 40 Caldilinea 41 59 41 Armatimonadetes 40 23 42 Nannocystis 39 29 43 Geosporobacter 38 21 44 Bradyrhizobium 38 44 45 Nocardioides 37 49 46 Armatimonadetes 37 28 47 Acetivibrio 37 25 48 Sporacetigenium 34 28 49 Nitrosospira 34 5 50 Conexibacter 34 43

123 3 Results

Figure 3-51 Bacterial genera detected only in the rhizosphere of AVP1 transgenic and non-transgenic wheat

124 3 Results

Table 3.42 Bacterial genera detected only in the rhizosphere of transgenic wheat

16S rRNA sequences belonging to Genera transgenic wheat 1 Nocardioides 37 2 Cellulosilyticum 6 3 Acrocarpospora 4 4 Chondromyces 4 5 Rickettsia 4 6 Coxiella 3 7 Desertibacter 3 8 Methano- brevibacter 3 9 Aeribacillus 2 10 Amnibacterium 2

Table 3.43 Sequences of important PGPR genera detect in the rhizosphere of AVP1 transgenic and non-transgenic wheat

Genera Transgenic Cotton Non-Transgenic Cotton Arthrobacter 113 93 Aspromonas 1 1 Azoarcus 16 30 Azospirillum 14 21 Azotobacter 417 370 Azotobacter 417 370 Bacillus 3207 4738 Bradyrhizobium 38 44 Brevibacillus 18 7 Brevibacillus 18 7 Mesorhizobium 133 132 Paenibacillus 490 418 Paenibacillus 490 418 Pseudomonas 12 14 Rhizobium 16 37 *genera that have been reported as PGPR of different crops

125 3 Results

PGPR of Wheat Rhizosphere

1000 AVP1-transgenic Wheat 900 3 Non-Transgenic Wheat 800 207 700 4 338 600 490 500 418 417 400 370

300 PGPR AbundancePGPR 200 133 132 113 93 100 3844 30 37 187 16 16 1421 1214 0

Figure 3-52 Abundance and comparison of PGPR detected in AVP1 transgenic and non-transgenic rhizosphere of wheat.

126

4. Discussion

For the development of sustainable agricultural systems, genetic engineering offers genetic modifications of crop plants to incorporate useful traits. There is an increase in the adoptability and cultivation of genetically modified crops [220]. However the use of genetically modified crops requires well defined risk assessment prior to adoption in any agricultural system [221]. These risks include the impact of genetically modified plants on soil-associated microbial communities as plants are known to have a profound effect on the abundance, diversity and activity of soil microorganisms living in close proximity with their roots in a soil zone called the rhizosphere [222].

Present study was conducted to evaluate the diversity of bacteria in the rhizosphere of AVP1 transgenic cotton and AVP1 transgenic wheat as well as non- transgenic plants of both the crops. Studies conducted include determination of bacterial diversity by isolation of bacteria from rhizosphere of transgenic and non- transgenic plants, impact of PGPR strains on growth of cotton and wheat plants, estimation of bacterial population in the rhizosphere of transgenic and non-transgenic plants (cotton & wheat) at different plant growth stages on bacterial growth medium as well as by real time PCR. Furthermore diversity of diazotrophic bacteria was investigated by PCR amplification, cloning and sequencing of nifH gene using soil DNA. Finally bacterial diversity was determined by pyrosequencing analysis of 16S rRNA gene from soil DNA.

Bacteria were isolated from AVP1 transgenic cotton and AVP1 transgenic wheat along with their non-transgenic control plants. On different growth media total 26 isolates were obtained which included 12 isolates from cotton and 14 isolates from wheat rhizosphere. These isolates were identified on the bases of 16S rRNA gene comparison with closely related sequences reported in the databank (NCBI). Bacterial strains belonging to genera Arthrobacter (strain Bα), Azospirillum (strain BM31), Bacillus (strains A5, CC and DC), Brevibacillus (strain TN4-3NF) and Pseudomonas (strain D4) were isolated from AVP1 transgenic cotton rhizosphere and Agrobacterium (strain NTW1), Bacillus (strains NTC-7, NTC-4 and AC) and Rhizobium (strain NTC-

4. Discussion

2NF) from non-transgenic cotton. Bacterial strains belonging to genera Bacillus were most common in both transgenic and non-transgenic cotton rhizosphere. The bacterial isolates from AVP1 transgenic wheat rhizosphere belonged to genera Achromobacter (strains A6 and AZ), Alcaligenese (strain WC), Bacillus (strain WP2), Brevibacterium (strain NFM-2) and Pseudomonas (strain WT2). Bacterial strains belonging to genera Arthrobacter (strain NTC-11), Bacillus (strain WP2), Advenella (strain NTC-1NF) and Pseudomonas (strain WP3) were isolated only from non-transgenic wheat. Bacterial strains belonging to genera Achromobacter, Bacillus and Pseudomonas were common in both AVP1 transgenic and non-transgenic wheat rhizosphere.

Bacterial strains isolated and identified in the present study have been found in soil, mostly as residents of plant roots. The Achromobacter strains (family Alcaligenaceae) have been isolated from wheat and maize [223, 224]. Colonization of Achromobacter species in sunflower rhizosphere under drought conditions conferred tolerance to water stress [225]. Agrobacterium has been found as soil bacterium [175] and in association with the roots of cotton and many other crop plants [226]. Isolation and identification of different bacterial strains belonging to genus Arthrobacter has been reported from the rhizosphere of various crops [67]. Arthrobacter species are known to have a considerable ability to survive during severe drought conditions. A stress tolerant phosphate solubilizer Arthrobacter strain has been isolated from tomato rhizosphere [227, 228]. From cotton rhizosphere of the Indian soil, the strains belonging to genera Azospirillum, Arthrobacter and Bacillus have been isolated [229]. Isolation of Azospirillum strains has often been reported from cereal crops but isolations from cotton have also been made [230]. Isolation of Azospirillum strains from the rhizosphere of wheat, rice and sugarcane has been reported previously from the same soil as used in the present study [25, 223, 231]. Bacterial strains related to genera Bacillus colonize the cotton root zone and affect the plant growth by adopting different mechanisms [109, 232]. The present study indicated that the strains of Bacillus are colonize in the rhizosphere of AVP1 transgenic and non-transgenic plants of cotton and wheat more frequently as compared to the other rhizospheric bacteria. Occurrence of Bacillus in the rhizosphere of cotton has been reported in Pakistani soil. Several studies proved the presence and abundance of Bacillus genera in the rhizosphere of various crops [233, 234]. Studies on bacterial diversity of transgenic tobacco showed that Bacillus were commonly present in transgenic and non-transgenic rhizosphere

128 4. Discussion

[235]. Brevibacillus has been established as a new genus by reclassification of the Bacillus brevis group of species in the genus Bacillus [236]. Brevibacillus strains present in soil are known to play role in bioremediation and biocontrol in cotton rhizosphere [237]. Presence of bacterial strains belonging to genus Paenibacillus has been shown in the rhizosphere of cotton [238, 239]. High efficiency in host root colonization of plant rhizosphere by Pseudomonads have been reported resulting in improved crop yield [240, 241]. Advenella have been isolated from tea and rice rhizosphere as a phytase producing bacteria for their plant growth promoting activities [242]. Rhizobia are known generally to invade the root systems of legumes to form nodules but as free-living bacteria are also an integral part of rhizosphere biota exhibiting successful rhizosphere colonization [243, 244].

Production of IAA by the bacterial isolates purified from cotton and wheat was investigated in pure culture. It has been found that not only plants but bacteria and fungi are also able to synthesize IAA [245]. IAA synthesized by bacteria play a major role in root growth, cell elongation, tissue differentiation, plant growth promotion and responses to light and gravity [246]. In the present study, IAA production was detected in the pure culture of Achromobacter strain A6, Agrobacterium strain NTW1, Arthrobacter NTC-11, Azospirillum strains BM31, Bacillus strain A5 and NTC-7, Pseudomonas strain D4 and WT2. Achromobacter strains isolated from different crops like wheat, brassica, maize, and canola have been shown to produce IAA [247-249]. Agrobacterium can induce root formation in some plants due to production of natural plant growth promoting substances (IAA) [250]. Arthrobacter strains have been reported for IAA production under stress conditions [251]. Many strains of Azospirillum produce IAA in considerable amounts that favors the plant growth [252]. Studies on Pseudomonas sp. have suggested that these bacteria are able to synthesize IAA [253]. The treatment of seeds or cuttings with Agrobacterium, Pseudomonas and many other bacterial genera induced root formation of some plants because of natural auxin production by bacteria [254]. Moreover, IAA can also be a signaling molecule in bacteria and therefore can have a direct effect on bacterial physiology [255]. It has been estimated that more than 80% of bacteria isolated from the rhizosphere can produce plant growth regulator IAA [75, 243].

Phosphate solubilization by bacteria is an important mechanism utilized for plant growth promotion [256]. In the present study, phosphate solubilization activity of

129 4. Discussion bacterial isolates was studied in Pikovskaya medium supplemented with tri-calcium rock phosphate as sole source of phosphorus. Among the tested strains, efficient phosphorus solubilization was shown by Achromobacter strains A6, Arthrobacter strains Bα and NTC-11, Azospirillum strain BM31, Bacillus strain WP8, and Pseudomonas strains WP3 and D4. Phosphate solubilization activity has been reported in several genera of PGPR including Arthrobacter, Achromobacter, Bacillus, and Pseudomonas [22, 223, 257]. Agrobacterium and some other genera isolated from the temperate countries have the ability to solubilize phosphorous [258]. Phosphate solubilization ability of different strains of Arthrobacter has been reported from subtropical soils [75]. Arthrobacter strains as stress tolerant phosphate solubilizing rhizobacteria have been isolated from tomato rhizosphere soil [259]. Pseudomonas strains enhanced productivity in rice crop by phosphate solubilization [260, 261].

Rhizospheric bacteria secrete organic acids like acetic acid, citric acid and gluconic acid to lower the pH of medium that affects the phosphorous solubilization ability of bacteria [262, 263]. Similar studies showed the involvement of organic acids produced by different PGPR in mobilization of P in the rhizosphere [32, 264]. In the present study Achromobacter strain A6, Agrobacterium strain NTW1, Azospirillum strain BM31, Bacillus strains (AC, CC, and DC), Brevibacillus strain TN4-3NF, Paenibacillus NTC-7 and Rhizobium strain NTC-2NF showed production of organic acids in pure culture. Among the detected acids, acetic acid was detected relatively in higher amounts as compared to the other acids. Production of acetic acid by different PGPR strains from the same soil has already been reported [257]. Maximum acetic acid production was shown by Pseudomonas strain WP3, followed by Bacillus strain WP8, Arthrobacter strain Bα and Azospirillum strain BM31. Similar studies indicated that Arthrobacter, Azospirillum and Bacillus produce organic acids in pure culture for phosphate solubilization [75, 265].

Use of PGPR with the aim of improving nutrient availability and plant growth promotion has been studied during past couple of decades [266, 267]. In the present study 8 bacterial isolates showing high IAA and phosphorus solubilization ability were used as single-strain inoculants for AVP1 transgenic and non-transgenic cotton. For quick screening in short-term experiments (40 days duration), bacterial isolates were tested as inoculants for plants in sterilized sand and the tested strains included Agrobacterium strain NTW1, Arthrobacter strain Bα, Azospirillum strain BM31,

130 4. Discussion

Bacillus strain NTC-4, Bacillus strain A5, Brevibacillus strain TN4-3NF, Paenibacillus strain TNC-7 and Pseudomonas strain D4.The inoculated transgenic and non- transgenic plants showed significant improvement of most of the growth parameters recorded in the study. Maximum increase in root length (24%) and root dry weight (22.1%) of transgenic plants was shown by inoculation of Arthrobacter strain Bα. Maximum increase in root length (24%) of non-transgenic plants was recorded on inoculation of Azospirillum strain BM31. No significant effect was observed on the shoot dry weight and root dry weight of transgenic and non-transgenic plants inoculated with Agrobacterium strain NTW1 and Paenibacillus strain TNC-7. Therefore, Arthrobacter strain Bα, Azospirillum strain BM31, Bacillus strain NTC-4, Brevibacillus strain TN4-3NF, and Pseudomonas strain D4, were selected for further inoculation of cotton plants (transgenic and non-transgenic) in non-sterilized soil.

These selected strains were used as inoculum in pot experiment during 2011 and experiment was repeated again during 2012. During 2011, maximum increase in yield of transgenic cotton plant was recorded on inoculation with Brevibacillus strain TN4-3NF (11.2%) and Pseudomonas strain D4 (9.6%) over non-inoculated control. Non-transgenic plants did not show any significant effect on yield except Pseudomonas strain D4 and Arthrobacter strain Bα which showed 22 % and 23% increase, respectively in yield of non-transgenic plants. During 2012, inoculation of transgenic plants with Arthrobacter strain Bα and Pseudomonas strain D4 resulted in increased cumulative root length (7.4%, 7.9%), shoot dry weight (8.9%, 11.5%), root dry weight (21.6%, 21.8%), and yield (24.58%, 23%) of transgenic cotton plants over control. Inoculation of non-transgenic plants with Brevibacillus strain TN4-3NF and Pseudomonas strain D4 resulted in the improvement of all growth parameters studied. Arthrobacter strain Bα, Azospirillum strain BM31, Bacillus strain NTC-4 Brevibacillus strain TN4-3NF and Pseudomonas strain D4 were efficient in growth promotion of transgenic plants as well as non-transgenic plants and therefore, qualified as effective PGPR strains of cotton. Bacterial strains belonging to these genera have been reported to be the integral parts of rhizosphere biota exhibiting successful rhizosphere colonization and beneficial effect on growth of crop plants [81, 83, 268, 269]. Arthrobacter are extremely common in soils and often constitute more than one-half of the total bacterial population [270]. It has been reported that co-inoculation of plants with Arthrobacter sp. Bacillus and Pseudomonas could alleviate the adverse effects of

131 4. Discussion soil salinity [271]. The Azospirillum genus is able to colonize more than a hundred plant species and known to significantly improve plant growth, development, and productivity under agronomic conditions [272]. Increase in the growth of root hairs and number of lateral roots of cotton has been observed in greenhouse conditions [273]. Azospirillum inoculation increased plant height, dry weight and nitrogen content by increasing N uptake in cotton [274]. It has been reported that in cotton root association, Azospirillum is capable of producing antibacterial and antifungal compounds, siderophores and growth regulating substances [275]. Species of Bacillus are common inhabitants among the resident microflora of various species of plants including cotton, where they play an important role in plant protection and growth promotion [276, 277]. In another study cotton and some other crops raised with inoculation of commercial product of Bacillus were effective against soil borne pathogens [278]. Growth promotion of transgenic (Bt) cotton due to inoculation with Bacillus and Arthrobacter strains has been reported recently [279]. Members of the genus Brevibacillus have received considerable attention as potential inoculants due to their ability to survive under stressful conditions by endospore formation [279, 280]. Brevibacillus spp. isolated from sugarcane rhizosphere have shown plant growth-promoting potential in in vitro experiments [281] and also on germination of eggplant and pepper grown under organic amendments and in greenhouse conditions [282]. Pseudomonas spp. are ubiquitous bacteria in agricultural soils and have many traits that make them well suited as PGPR. Specific strains of the Pseudomonas group used as seed inoculants on crop plants (potato, radish, sunflower and sugar beet) caused statistically significant yield improvement in field tests [283]. It has been reported that inoculation of cotton plants with Pseudomonas spp. resulted in improved growth parameters as has been observed in the present study [284].

For wheat inoculation studies bacterial strains were tested as single-strain inoculants in sterilized sand for quick screening in short-term experiments (40 days duration) Achromobacter strain A6, Arthrobacter strain NTC-11, Azospirillum strain BM30, Bacillus strain WP2, Bacillus strain WP8, Brevibacterium strain NFM-2, Microbacterium strain WN1, and Pseudomonas strain WP3 were used as single strain inoculants for transgenic and non-transgenic wheat plants. Among the tested strains, five strains i.e Achromobacter strain A6, Arthrobacter strain NTC-11, Azospirillum strain BM30, Microbacterium strain WN1 and Pseudomonas strain WP3 showed an

132 4. Discussion increase in all the growth parameters of transgenic plants. Maximum increase in cumulative root length (22.1%), shoot dry weight (10.5%) and root dry weight (23 %) was recorded in the plants inoculated with Pseudomonas strain WP3 over non- inoculated control plants. Among the bacterial inocula tested for non-transgenic wheat plants, no significant improvement of cumulative root length was recorded. Maximum increase in shoot dry weight was recorded over control plants inoculated with Achromobacter strain A6 Arthrobacter strain NTC-11 and Pseudomonas strain WP3. Efficient bacterial strains (Achromobacter strain A6, Arthrobacter strain NTC-11, Microbacterium strain WNI, Azospirillum strain BM30 and Pseudomonas strain WP3) were studied in two experiments conducted during 2010-11 and 2011-12 in micro-plots under natural conditions. Data analysis of both experiments showed a significant effect of inoculated strains on both transgenic and non-transgenic plants as compared to non- inoculated control plants. However, Arthrobacter strain NTC-11, Pseudomonas strain WP3 and Azospirillum strain BM30 were more efficient strains compared with Achromobacter strain A6, and Microbacterium strain WNI. During 2010-11, inoculation of Arthrobacter strain NTC-11 showed maximum increase in the straw dry weight (8.1 %) and maximum increase in grain weight (8.2 %) was noted in the plants inoculated with Pseudomonas strain WP3. All inoculated strains showed significant improvement of straw weight and grain weight of wheat grown in micro-plots. In the experiments Achromobacter strain A6, Arthrobacter strain NTC-11, Azospirillum strain BM30 and Pseudomonas strain WP3 were identified as efficient PGPR strains for wheat. The bacterial inoculants tested in this study have frequently been used to promote growth of wheat and other crop plants [109, 285]. Arthrobacter spp., Achromobacter spp., and Bacillus spp., were previously isolated from rhizosphere of wheat and reported as dinitrogen fixers [286]. Isolation and characterization of Achromobacter strains from wheat and maize has been reported [223, 248]. Inoculation of Achromobacter sp. has been reported to confer tolerance to salt and water stresses to tomato, sunflower and pepper [60, 287, 288]. The inoculation of maize seeds with the strains of Achromobacter and Arthrobacter caused a significant increase in the shoot and root dry matter of different cultivars [289]. Co-inoculation of wheat with Arthrobacter and Bacillus strains could alleviate the adverse effects of soil salinity on wheat growth [228]. Seed inoculations of wheat with Azospirillum and Bacillus significantly increased the grain and straw yield [290]. Beneficial effects of Azospirillum on wheat yield in field and greenhouse conditions have been reported [79,

133 4. Discussion

257, 291]. In another study, Azospirillum strains obtained from wheat roots showed a consistent positive effect on the yield of different wheat cultivars [292]. Recently growth promotion of wheat by phosphate solubilizing Azospirillum has been reported from Pakistan [257]. Microbacterium has been reported to occur as endophyte of different crop plants playing important ecological roles [293, 294]. Pseudomonas, Bacillus and Microbacterium strains increased root growth of wheat when applied as inoculum [295]. There are many reports on the occurrence of Pseudomonas spp. in the rhizosphere of wheat [123, 296-298].

The use of genetically modified or transgenic plants has a great potential for sustainable agriculture. However an increase in the adoptability and cultivation of genetically modified crops demands well-defined risk assessment [160]. These risk assessment studies are essentially required because some transgenic plants (insect resistant) are known to change rhizosphere environment through root exudates, which consequently affects the growth of microorganisms in the rhizosphere [299]. In the present study bacterial populations in the rhizosphere of AVP1 transgenic and non- transgenic cotton and wheat were compared at different growth stages. Bacterial population (cfu/g soil) were estimated on nutrient agar medium at three crop developmental stages i.e 30, 60, and 90 DAS of cotton and wheat. In the present study no significant difference was observed in bacterial population in the rhizosphere of transgenic and non-transgenic rhizosphere soils at all three growth stages. Similar to these results, no difference was observed in growth of bacterial communities between the rhizosphere of transgenic potato and non-transgenic potato varieties [117]. Also, no effect of transgenic maize has been observed on diversity of culturable bacterial communities in rhizospheric soil samples [115]. Studies on culturable bacterial population showed that B. thuringiensis toxins present in transgenic corn (Zea mays) rhizosphere did not change culturable microbial communities [300]. The diversity of rhizosphere bacteria of transgenic, herbicide-resistant corn was not different from that of the corresponding non-transgenic variety [301].

In the present study bacterial population varied significantly with the crop development stage. In cotton rhizosphere maximum bacterial populations i.e 5.63 (log cfu/g soil) and 5.58 (log cfu/g soil) were recorded at 90 DAS among transgenic and non-transgenic plants, respectively. In the rhizosphere of wheat, maximum bacterial populations i.e 6.42 (log cfu/g soil) and 6.40 (log cfu/g soil) were recorded at 60 DAS

134 4. Discussion in transgenic and non-transgenic plants, respectively and relatively low cfu/g soil were detected at 30 DAS and 90 DAS. Population of diazotrophic bacteria in the rhizosphere of transgenic and non-transgenic plants of cotton and wheat was observed in semi-solid nitrogen-free malate (NFM) medium. Data showed that there was no statistically significant difference among diazotrophic population (MPN) in the rhizosphere of transgenic and non-transgenic plants of cotton and wheat at different stages except in wheat rhizosphere at 90 DAS which was relatively higher compared with other growth stages. This difference in bacterial population may be the effect of qualitative and quantitative difference of substrates released by plant roots by exudation at different developmental stages [302].

In the present study, real time PCR was used to quantify microbial populations in the rhizosphere of cotton and wheat. Abundance of 16S rRNA and nifH genes in rhizosphere was determined by real time PCR from the soil samples collected from AVP1 transgenic and non-transgenic plants at different plant developmental stages (35 DAS and 90 DAS). In cotton rhizospheric soil samples, more copy number of 16S rRNA gene were recovered in AVP1 transgenic cotton (log 6.39 copies/g of soil), at 90 DAS and in non-transgenic cotton log 6.36 copies/g of soil of 16S rRNA gene at 90 DAS than at 35 DAS. These results showed that bacterial population was low at early stage of cotton (35 DAS) and it increased with the crop development and was highest at 90 DAS. Abundance of nifH gene was determined to estimate population of diazotrophic bacteria in the rhizosphere. In the rhizosphere of transgenic and non- transgenic cotton log 5.66 and log 5.85 nifH copies/g of soil were detected, respectively. At 90 DAS, nifH sequences detected in the rhizosphere of transgenic and non- transgenic cotton plants were log 5.41 and log 5.39 nifH copies/g of soil, respectively. In the rhizosphere of transgenic and non-transgenic wheat relatively higher copy number of 16S rRNA and nifH genes were detected at 35 DAS compared with 90 DAS. Rhizosphere microbial communities are known to be affected by several factors including plant growth stages [303]. Previous studies indicated that the rhizosphere population decreases as a plant matures [304], where as other study showed that microbial diversity increases with plant age [302]. In our study generally similar or very close copy number of 16S rRNA and nifH gene in transgenic and non-transgenic plants showed that the shift in bacterial population is an independent function of plant without any influence of foreign gene (AVP1) incorporated into transgenic plants. A significant

135 4. Discussion but not persistent change in the abundance of bacterial and archaeal communities determined by real time PCR has been observed [305]. It has been reported that that the changes in the microbial community structure associated with genetically modified plants were temporary and did not persist into the next season [122]. Another study showed that the abundance and diversity of nitrogen-fixing bacteria tended to increase with duration of organic management but the highest number of nifH gene copies was observed in the rhizosphere and bulk soil of 5 years organic management [306].

Organic acids have been hypothesized to perform many functions in soil including root nutrient acquisition, mineral weathering, microbial chemotaxis and metal detoxification. Organic acids as root exudates are released into the rhizosphere as a result of rhizodeposition and play a major role in the maintenance of root-soil and root-microbe contacts [79, 307]. Information on the content and composition of organic acids and sugars in exudates of various crops is limited and has a very fragmented character. A study on tomato plant exudates showed that citric acid was the major organic acid in root exudates. Malic acid and succinic acid were also detected however, their levels were dependent on the plant age. The percentage of malic acid decreased between the seedling and root stage, whereas the opposite occurred with succinic acid, which became a major organic acid between growth stages of tomato plant. In another study cucumber and sweet pepper rhizosphere citric acid, malic acid and succinic acid were present in substantial amounts, although the levels and timing was different among various crops [121].

In the present study organic acids (acetic acid, citric acid, malic acid, lactic acid, gluconic acid and succinic acid) produced as root exudates in soil solution collected from rhizosphere of transgenic and non-transgenic plants of cotton and wheat were assayed. To detect a particular acid from concentrated soil solution standards of six acids were used (production of these six acids were also assayed from pure culture of different bacterial strains). However, in soil solution only acetic acid, citric acid, malic acid and lactic acids were detected in comparable amounts. Gluconic acid and succinic acid were also detected in soil solution but there concentration were quite low (0.0002- 0.0004 μg/mL). Among the organic acids detected in soil solution, acetic acid was detected in relatively higher amounts, followed by oxalic acid and citric acid. Production of different organic acids (Acetic acid, Oxalic Acid, Citric acid, Malic acid) were analyzed statistically that showed significant difference of organic acids

136 4. Discussion production in soil solution of AVP1 transgenic and non-transgenic plants (cotton and wheat). Production of Acetic acid, Oxalic Acid and Citric acid was significant among AVP1 transgenic cotton plants plans as compared to non-transgenic plants. However production of Malic acid was non-significant among transgenic and non-transgenic cotton plants. AVP1 transgenic wheat plants showed significant production of Acetic acid, Oxalic Acid and Malic acid as compared to non-transgenic plants. Citric acid production was non-significant among transgenic and non-transgenic wheat plants. In the present study, maximum amount of acetic acid (8.89 µg/mL) was detected in the soil solution of transgenic cotton plants. Oxalic acid was the second dominant acid detected in soil solution and relatively higher amounts were detected in the soil solution of transgenic cotton and wheat plants as compared to non-transgenic plants soil solutions. The presence of organic acids in the rhizosphere of different crops has been reported previously [307, 308] and it has been found that rate of root exudates released by the plant roots influence microbial biota and activity in rhizosphere [309].

Culture-independent molecular methods are being applied for the assessment of diazotrophic diversity by amplifying, cloning and sequencing of the nifH gene from environmental DNA samples [310, 311]. Diazotrophic diversity on the basis of nifH gene amplification and sequencing of soil DNA from rhizosphere of mangrove forest of China [312], oak-hornbeam forest (Chorbush Forest) Germany [169], soil from France and Senegal [170], Douglas fir forest in USA [313] and rice rhizosphere at Kyushu University Farm, Japan [172] has been reported. In the present study diversity of diazotrophic bacteria in rhizosphere of AVP1 transgenic cotton and wheat was explored by sequence analysis of nifH gene from soil DNA. Data analysis showed that sequences related to Anabaena, Azospirillum, Bradyrhizobium and Pseudomonas were common in AVP1 transgenic and non-transgenic cotton whereas nifH sequences of Zoogloea, Azohydromonas and Azospira were detected only in non-transgenic cotton rhizosphere soil samples. Common genera in AVP1 transgenic and non-transgenic wheat were Agrobacterium, Azospirillum, Bradyrhizobium and Pseudomonas, however sequences related to Zoogloea were detected only in non-transgenic wheat rhizosphere. These results indicated that diverse diazotrophs community exist in the rhizosphere of transgenic and non-transgenic plants that can be isolated and used as inoculants to enhance the crop productivity [314]. In the present study representatives of bacterial genera Agrobacterium, Azospirillum, Pseudomonas and Rhizobium were present

137 4. Discussion among isolates and no isolate representing Azoarcus, Bradyrhizobium and Zoogloea was obtained. Strains of Azospirillum; Azotobacter, Bacillus, Pseudomonas, Rhizobium and Zoogloea and some other genera have been reported as non-symbiotic diazotrophs of crop farming systems in Pakistan and elsewhere [25, 49, 315, 316]. The genus Azospira was described by Reinhold-Hurek & Hurek [159] to accommodate a lineage of nitrogen-fixing bacteria phenotypically differentiated from other strains originally assigned to the genus Azoarcus [317]. The genus Azospira includes a single validly published species, Azospira oryzae, strains of which have been isolated from surface- sterilized roots of Kallar grass collected from Pakistan as well as from resting stages (sclerotia) of a basidiomycete [318].

Our results showed that in all four clone libraries constructed from transgenic cotton (TC), non-transgenic cotton (NTC), transgenic wheat (TW), non-transgenic wheat (NTW), sequences related to non-cultured diazotrophic bacteria were abundant and constituted about 78% in TC, 74% in NTC, 78% in TW, and 79% in NTW of total detected sequences. Sequences of uncultured diazotrophic bacteria detected in the present study have already been reported from cotton rhizosphere, alkaline soils, and mostly were from agricultural soils (unpublished results reported at NCBI data bank). Many authors have already described sequences corresponding to diverse unidentified diazotrophs [45, 170]. These non-cultivated diazotrophs may be the dominant nitrogen- fixing organisms in soil systems [319]. In our study 14 uncultured diazotrophic sequences showed homology with uncultured sequences from saline alkaline soils of The Netherlands, 5 uncultured sequences showed homology with the sequences that have been reported from cotton rhizosphere of India. Uncultured bacterial nifH sequences showing homology with sequences reported from paddy soils of china, agricultural soil Switzerland, root of sugarcane from Indian Punjab, leaf surface of tropical plants and from soil of California USA were also detected. Some sequences of uncultured diazotrophic bacteria from AVP1 transgenic and non-transgenic wheat rhizosphere showed homology with diazotrophic communities of Dutch soil which have been extensively studied for seasonal variation in the diversity and abundance of diazotrophic communities [209]. Other uncultured sequences showed homology with uncultured database (NCBI) sequences from sugarcane rhizosphere of China, rhizosphere of cereal crops of Greece and Agricultural soil of Italy. In the present study majority of the retrieved sequences of culturable as well as non-culturable bacteria were

138 4. Discussion commonly present in the transgenic and non-transgenic plants pointing to no significant effect of transgenic plants on diazotrophic communities. Persistence of nitrogen fixing bacteria without any effect of transgenic has also been reported [320].

In the present study, pyrosequencing analysis of 16S rRNA gene directly amplified from rhizosphere soil DNA of AVP1 transgenic cotton and wheat along with non-transgenic plants were carried out to compare bacterial diversity. Sequences related to 19 bacterial phyla were detected in AVP1 transgenic and non-transgenic cotton and sequences related to 18 bacterial phyla were detected in AVP1 transgenic and non- transgenic wheat. In cotton and wheat root system, Actinobacteria, Acidobacteria, Bacteroidetes, Crenarchaeota, Proteobacteria and Firmicutes were most dominant among the detected phyla. The detection of these phyla has been reported through metagenomic studies in different soils [321, 322]. Data analysis showed that in cotton rhizosphere, sequences related to Actinobacteria, Acidobacteria, Proteobacteria and Firmicutes were more abundant in transgenic plants except Crenarchaeota which were dominant among non-transgenic plants. However in wheat rhizosphere, sequences related to Acidobacteria, Bacteroidetes, Crenarchaeota and Proteobacteria were relatively more abundant in transgenic wheat rhizosphere and sequences related to Actinobacteria and Firmicutes were dominant in the rhizosphere of non-transgenic plants. Major phyla detected in present study have been reported in a variety of environments. Proteobacteria phylum is metabolically versatile and genetically diverse, comprising the largest fraction of the bacterial community in soil ecosystems including the rhizosphere [323]. Dominant populations of Actinobacteria have been reported on maize roots in a tropical soil [324]. It was also found that members of the Bacteroidetes group constituted dominant populations in the rhizosphere of maize and canola. Members of these bacterial groups are capable of degrading complex macromolecules, thus contributing to the turnover of carbon, nitrogen and phosphorus [325]. Further analysis of the sequences showed that a total number of 80±05 and 88±06 bacterial classes were found in cotton and wheat rhizosphere, respectively. In our study bacterial classes alpha, beta and gamma Proteobacteria belonging to phylum Proteobacteria were most abundant, followed by Thermoprotei and Bacilli. The members of the classes of Proteobacteria have been well -known for their role in agriculture, possessing several plant growth promoting mechanisms including phytohormones, siderophore, phosphate solubilization and nitrogen fixation [326,

139 4. Discussion

327]. Dominant members of Proteobacteria classes in our study were in accordance with other studies on bacterial diversity in maize rhizosphere [328]. Second abundant bacterial class was Thermoprotei, belonging to phylum Crenarchaeota. The Crenarchaeota have been classified as a phylum of the Archaea kingdom. Initially, the Crenarchaeota were thought to be sulfur-dependent extremophiles but recent studies have indicated that Crenarchaeota may be the most abundant archaea in the marine environment. Until recently all cultured Crenarchaeota had been considered as “thermophilic” or “hyper-thermophilic” organisms, some of which have the ability to grow at up to 113 °C. These Archea have been detected in agricultural soil in various studies [329, 330].

Data analysis at genus level showed that in transgenic cotton rhizosphere bacterial sequences related to 344±5 genera were found and sequences related to 321±12 genera were detected in non-transgenic cotton rhizosphere soil. Among these, sequences of 240 genera were commonly detected in transgenic and non-transgenic rhizosphere. This indicated that majority of detected genera were common in both root systems i.e transgenic and non-transgenic cotton rhizosphere. Data showed that 16S rRNA sequences of Bacillus were the most abundant in transgenic (2221 sequences) and non-transgenic cotton (3043 sequences), followed by Steroidobacter, Cellvibrio, Lysobacter and Rubrobacter. Steroidobacter genus belonging to the order Rhizobiales has been reported as an agar-degrading bacterium recently isolated from soil collected from a vegetable cropping field [331]. Cellvibrio, a genus of Pseudomonadaceae, is a nitrogen-fixing bacterium isolated from the rhizosphere soils treated with manure [332]. The genus Lysobacter is grouped in the family Xanthomonadaceae, belonging to the Gamma-Proteobacteria, found in soil and water habitats [333]. Several members of Lysobacter are known as biological control agents against soil borne phyto- pathogens such as Rhizoctonia solani, Thielaviopsis basicola [334]. Studies have suggested that beneficial bacteria belonging to Lysobacter probably play an important role for soil suppressiveness and plant growth [335, 336]. Our data showed that the relative abundance of Lysobacter was is much higher in the rhizosphere of transgenic cotton. 16S rRNA gene sequences related to Rubrobacter spp. have been recovered from moderate, terrestrial environments [337, 338]. The type strain of Niastella has been isolated from soil cultivated with Korean ginseng. Sequences related to bacterial genera known for PGPR like Bradyrhizobium, Pseudomonas, Rhizobium,

140 4. Discussion

Streptomyces, Serratia, and Azospirillum were frequently detected in the present study [252, 339].

In this study, 16S rRNA sequences related to 60 genera were detected only in AVP1 transgenic cotton rhizosphere. Pseudofulvimonas, Serratia, Azospirillum, and Rhizobacter were most abundant genera detected only in the rhizosphere of transgenic cotton. 16S rRNA sequences related to 33 genera were found only in the rhizosphere of non-transgenic cotton. Among them the most abundant were Brachybacterium, Glycomyces, Actinomycetospora, Aeromicrobium, and Achromobacter. Brachybacterium is able to degrade anthracene very efficiently and could serve as better candidate for bioremediation [340]. It has also been isolated from oil contaminated soils [341]. Glycomyces, Actinomycetospora and Aeromicrobium belonging to actinomycetes, have been isolated from soil in different regions of the world [342]. Aeromicrobium strains have been isolated from an alkaline soil [343]. Actinobacteria are ideal candidates for developing microbial inoculants for use in agriculture production system as phosphate solubilizers [342]. Actinomycetes are more widespread and important in soil [344].The genus Fulvimonas was described by Mergaert et al. [345] with a single species Fulvimonas soli which has been isolated from soil [345]. Members of the Actinobacteria, Rubrobacter and xylanophilus (phylum Actinobacteria) are widespread in soils throughout the world. Nitrosomonas are ammonia-oxidizing bacteria belonging to the phylum Proteobacteria were detected and have been reported for bioremidation. Microvirga, a root nodule symbiotic bacterium was isolated from cowpea grown in semi-arid Brazil [346]. It has been isolated from rice field soil in China [347]. Novel aerobic bacterium Gemmatimonas was isolated from an anaerobic and aerobic sequential batch reactor for wastewater treatment [348]. Other genera detected in cotton rhizosphere include Pseudoxanthomonas, a bio- surfactant producing bacterium with high emulsifying activity, Hydrogenophaga, is being used in bioreduction of vanadium (V) in groundwater [349] and Skermanella strains have been purified from a sand sample collected from the desert of Xinjiang, China [350].

In the present study 16S rRNA sequences related to 293±24 genera were found in the rhizosphere of AVP1 transgenic wheat and in the rhizosphere of non-transgenic wheat sequences related to 306±12 genera were detected. Among these 233±24 genera were common in the rhizosphere of both transgenic and non-transgenic wheat. Among

141 4. Discussion the dominant bacterial genera detected maximum sequences of Bacillus were recorded. Bacterial sequences related to 42 genera were found only in the rhizosphere of transgenic wheat in which Cellulosilyticum and chondromyces were abundant. 16S rRNA sequences related to 63 genera were found only in the rhizosphere of non- transgenic wheat where Nocardioides and Nonomuraea genera were most abundant. Cellulosilyticum has been detected from an anaerobic ethanol-producing cellulolytic bacterial consortium from hot springs basin with agricultural residues and energy crops [351]. The genuine habitat of the genus Chondromyces is soil, as long as the pH is slightly acid to slightly alkaline but is frequently found on the dung of herbivorous animals, on decaying plant material and on the bark of trees and occasionally they have also been found on the surface of plant leaves [352]. The genus Nonomuraea is a rare actinomycete taxon with a long taxonomic history. The genus is less known among the rare actinomycete genera as its taxonomic position was revised several times. It can be found in diverse ecological niches, while most of its member species were isolated from soil samples [353]. Nocardioides sp. widely distributed in agricultural soils degrades a range of herbicides [354]. A ‘strange’ genus detected from wheat rhizosphere was Haliangium, belong to family Haliangiaceae and represents a unique myxobacterial taxon occupying a novel and distinct phylogenetic cluster. To date, there is no valid standing nomenclature to classify the monotypic genus Haliangium. So far, all members of this taxon were isolated from marine environment and currently the only known application is the production of novel biologically active compounds [355]. Falsibacillus has been isolated from coastal regions and from rhizosphere soil of a medical plant [356]. Bryobacter aggregatus has been proposed to accommodate three strains of slowly growing, chemo-organotrophic bacteria isolated from acidic Sphagnum peat bogs [357]. Comparison of the number of sequences retrieved from transgenic and non-transgenic plants belonging to specific groups indicated quantitative differences but all major bacterial groups were present in the rhizosphere of both type of plants. Pyrosequencing data generated in the present study showed that important PGPR genera like Arthrobacter, Azopsirillum, Azoarcus, Bacillus, Paenibacillus, Mesorhizobium, Bradyrhizobium, and Pseudomonas were detected in all soil samples. However bacterial genera Azohydromonas, Brevundimonas, Burkholderia Pseudoxanthomonas, Microbacterium and Rhizobium were present only with cotton root system where as bacterial genera Azotobacter, Azospirillum, Brevibacillus and Rhizobium were detected in wheat root system only. In the present study, bacterial

142 4. Discussion sequences related to genera Azoarcus, Azohydromonas, Bradyrhizobium and Mesorhizobium were frequently detected but representatives of these could not be isolated from soil as pure culture. Therefore, potential of these genera for plant growth promotion could not be explored. Similarly cloning and sequencing of nifH gene amplified from soil showed the presence of well-known diazotrophic genera like Azotobacter, Azoarcus, Bradyrhizobium and Zoogloea in the rhizosphere but could not be isolated as pure culture. On the other hand, representative of the diazotrophic bacterial genera Arthrobacter, Paenibacillus, Brevibacillus and Enterobacter were could not detected by nifH gene sequencing, however pyrosequencing analysis of 16S rRNA gene revealed the presence of these and many other important PGPR genera.

In the present study, bacterial sequences that showed homology with uncultured bacteria were also detected in both nifH and 16S rRNA gene sequencing. Data showed that nifH sequences of uncultured nitrogen-fixing bacteria retrieved by the culture- independent approach (nifH gene cloning and sequencing) were more than > 70% of the total detected sequences. Similarly pyrosequencing of 16S rRNA gene showed that approximately 20% sequences were related to uncultured bacteria. Presence of uncultured bacterial sequences have been reported from different environments depending upon the technique used for detection [358, 359]. A fraction of uncultured bacterial sequences from the rhizosphere of different potato cultivars has been reported [360]. Presence of uncultured bacterial communities has also been shown in the rhizosphere of healthy and diseased wheat plants [361]. Uncultured rhizobacterial communities in glyphosate-tolerant cotton rhizosphere were variable among transgenic and non-transgenic plants [362]. The uncultured bacteria detected in the present study as well as other studies simply indicates that the laboratory culturing techniques presently being used are unable to grow these bacteria due to the lack of critical information about specific biology of micro-organisms. It is expected that many ‘uncultured’ bacteria will be isolated and used not only for plant growth promoting but also for other useful purposes.

4.1 Conclusion and Future Perspectives Based on estimation of bacterial populations and bacterial diversity assessed in the present study, it was found that AVP1 gene did not adversely affect soil enzymatic properties and soil micro-flora. The present study supports introduction of AVP1-

143 4. Discussion transgenic wheat in agricultural systems in the country as no adverse effects were observed on indigenous bacterial communities.

In the present study, bacterial sequences related to several well-known PGPR like genera Azoarcus, Azotobacter, Acinetobacter and Enterobacter were detected in the rhizosphere but the same could not be isolated from soil as pure culture. Future studies may focus on isolation of these important genera using selective growth media and optimum growth conditions and explored for their PGPR potential. Soil DNA-based studies also indicated presence of bacterial like Steroidobacter, Streptomyces, Micromonospora, Lysobacter, Rubrobacter, Pseudoxanthomonas Rhodococcus, Fulvimonas and Nitrosomonas which have been reported for important biological activities like bio-remediation of heavy metals, degradation of cholestrol and rubber, production of pharmaceutical agents and antibiotic producing activity. Future studies may be directed to isolate and utilize these bacteria for bio-remediation of contaminated soils and for production of useful bio-molecules. Efficient PGPR identified in the present study may be utilized as single-strain inocula or in different combinations in extensive field trials before final recommendation for commercial biofertilizer production for cotton and wheat.

144

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