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SID 5 Final Project Report

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Proof copy 6

Note 1In line with the Freedom of Information Act 2000, Defra aims to place the results of its completed research projects in the public domain wherever possible. The SID 5 (Final Research Report form) is designed to capture the information on the results and outputs of Defra-funded research in a format that is easily publishable through the Defra website. A SID 5 must be completed for all projects.

A SID 5A form will also have to be completed where a project is paid on a monthly basis or against quarterly invoices. No SID 5A is required where payments are made at milestone points. When a SID 5A is required, no SID 5 form will be accepted without the accompanying SID 5A.

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Project identification

1. Defra Project code RG0126

2. Project title Strategies for risk assessment, minimising the environmental impact of fungal disease suppressing GM bacteria and plants on non-target species

3. Name and address of contractor

Prof. M. J. Bailey & Dr T.M Timms-WilsonNERCCEH-OxfordMansfield RoadOxford          Postcode OX1 3SR

54. Total Defra project costs £ £437,985

5. Project: start date........... 01 April 2002

end date............ 30 September 2005

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6. It is Defra’s intention to publish this form. Please confirm your agreement to do so...................................................................................YES NO When preparing SID 5s contractors should bear in mind that Defra intends that they be made public. They should be written in a clear and concise manner and represent a full account of the research project which someone not closely associated with the project can follow.

Defra recognises that in a small minority of cases there may be information, such as intellectual property or commercially confidential data, used in or generated by the research project, which should not be disclosed. In these cases, such information should be detailed in a separate annex (not to be published) so that the SID 5 can be placed in the public domain. Where it is impossible to complete the Final Report without including references to any sensitive or confidential data, the information should be included and this section completed. NB: only in exceptional circumstances will Defra expect contractors to give a "No" answer.

In all cases, reasons for withholding information must be fully in line with the Freedom of Information Act 2000 and (prior to January 2005) the Code of Practice on Access to Government Information.

If you have answered NO, please explain why the Final report should not be released into public domain

Note – We anticipate that the findings will be published in peer review journals. If release of the report compromises this position then a further discussion will be needed between Defra and the contractors. However I don’t believe this will be an issue.

Executive Summary7. The executive summary must not exceed 2 sides in total of A4 and should be understandable to the

intelligent non-scientist. It should cover the main objectives, methods and findings of the research, together with any other significant events and options for new work.

To explore the potential impacts of genetically modified organisms (GMOs) on soil ecosystems we have studied model systems that combine a well described plant associated bacterium (Pseudomonas fluorescens SBW25) modified to produce the antifungal compound phenazine-1-carboxylic acid (Bailey et al., 2003a,b; Timms-Wilson et al, 2000) and a chitinase producing tobacco plant (Shi 1999). These GM-bacteria and GM-plants carry novel antifungal compounds for the suppression of fungal phytopathogens and provide ideal systems with which to assess impact on microbial ecosystem function in agricultural soils. Methods have been applied to monitor changes in succession, activity, biomass and diversity in the mycorrhizal and rhizobacterial community in response to GM-Biological Control Agent (GM-BCA) inocula and chitinase producing plants. The fate and impact of the phenazine (PHZ) producing inocula were compared in the rhizospheres of three crop plants, wheat, pea and sugar beet, and findings compared to the rhizosphere response of tobacco modified for the de novo expression of chitinase and plants treated with metalaxyl. Field and controlled glasshouse investigations were undertaken to establish the natural background variation and response for all plant types. Consent was granted by the Secretary of State for Combine molecular community finger-printing methods (Single Sub-Unit ribosomal RNA gene directed PCR-DGGE) to assess changes in community diversity and ecosystem function of the rhizosphere microbiota and mycorrhizal fungi associated with crop plants, that may result from the application of bacterial GM-BCA and a transgenic plant. Evaluate and compare the impact to non-target organisms caused by a fungicide (metalaxyl) when compared to bacteria and plants modified to express antifungal compounds (phenazine and chitinase respectively) for the control of fungal phytopathogens. Determine whether a genetic biocontainment strategy [the niche directed expression of the introduced antifungal genes (e.g. phenazine)] would be effective or necessary if perturbation to the ecosystem were identified following the release of GM-BCAs. Provide science based advice to assist the regulatory authorities when considering applications for the open environmental release of genetically modified organisms for crop protection.

Basic MethodologiesPrevious investigations demonstrated that P. fluorescens SBW25 was a typical representative of common plant associated bacteria. SBW25 effectively colonises roots and leaves of a variety of plants following seed inoculation, has moderate plant growth promoting properties and is non-pathogenic. To evaluate whether genetically modified bacteria constitute a risk to the environment this bacterium was genetically modified to carry ecologically functional genes. Genes for the synthesis of a common anti-fungal compound, phenazine, were isolated from a closely relative, Pseudomonas species (2-79) and inserted as a single copy in the chromosome of SBW25. The modified variant, 23.10, was highly effective in colonising plant roots and reducing infection caused by fungal plant pathogens (Timms-Wilson et al., 2000). Variants such as these are common candidates for use in the biological control of fungal diseases of field and glasshouse grown crop plants (Gladorf et al., 2001). We therefore established a series of

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experiments to assess whether impact or perturbation could be observed to soil function and the natural biota of plant roots. Studies were undertaken in three different crop plants, pea, sugar beet and wheat under open field conditions and in mesocosms. Mesocosms allow replication and plant growth in natural field soils under controlled laboratory and glasshouse conditions that simulate field conditions. The following parameters were measured for plants inoculated with the bacterium genetically modified for the de novo expression of phenazine with findings compared to the controls of untreated plants and plants treated with the unmodified wild type SBW25. In addition limited studies were undertaken to determine whether tobacco plants modified to express another antifungal compound, chitinase, alone or in the presence of the GM-BCA affect the normal soil microbiota. Investigations were also compared to the use of a chemical fungicide, metalaxyl. Replicate samples were collected from individual plants grown in field soils over a single growing season. Culturable population counts for soil and root microbiota. Populations were estimated using serial dilutions of the sampled root rhizosphere. Estimates of total culturable aerobic, bacterial heterotrophs, pseudomonads, introduced inocula and fungal propagules were made. Community level physiological profiling (CLPP). The commercially available BIOLOG system which evaluates the ability of a mixed population of microbes to degrade a range of carbon substrates, was used to assess the metabolic potential and functionality of the sampled microbial community (Ellis et al., 1995).Denaturing gradient gel electrophoresis (DGGE). Total community fingerprint. Molecular methods were applied to assess the relative diversity of the “total” microbial community. The method is commonly applied to compare bacterial and fungal diversity based on variation in 16S and 18S ribosomal RNA genes that reflect phylogenetic associations (Kowalchuk et al., 1997; Griffiths et al., 2000). The combined use of gene amplification using the Polymerase Chain Reaction (PCR) and the physical separation of all the amplified individual genetic variants of the targeted genes by DGGE allows a “bar-code” or fingerprint of each sample to be produced. These fingerprints reveal differences in population distribution and relative abundance allowing treatment effects to be measured. Additional approaches were evaluated in an attempt to improve resolution to assess the fate and impact of the introduced bacteria, these included flow cytometry to measure total and active cells in samples, enzymology and quantitative estimates of root colonisation by mycorrhizal fungi.

A number of field and mesocosm (simulated field) experiments were undertaken. In all cases samples were collected from the rhizosphere, the area directly associated with the root surface from which loosely adhering soil had been removed. This provided a reliable source of biological material and a specialised habitat where plant-microbe interactions are the strongest and subject to less abiotic variation when compared to bulk soil. The rhizosphere is considered a more relevant habitat for analysis than the bulk soil (Lilley et al., 2006). Experiments were established to:1. Assess the background and monitor changes in microbial community structure and function in three

crop species grown under field conditions at each key plant growth stage (life-history analysis) to allow between plant/ within season comparisons. Parallel studies confirmed the suitability of mesocosm studies as a surrogate for field work.

2. Mesocosm assessments of the impact of fungal disease suppressing GM bacteria, disease suppressing GM plants and the fungicide metalaxyl. Data produced were essential for risk assessment evaluations required when seeking consent for the open field release of GMOs.

3. In 2004 an open field release experiment was conducted in collaboration with Rothamsted Research to monitor the impact of disease suppressing GM bacteria on community diversity and ecosystem function of rhizosphere microbiota of spring wheat under agricultural conditions.

Findings: The methods proved to be effective and were highly reproducible. In all systems studied using different inocula, soils and plants no direct or lasting adverse affects were

recorded when GM treatment was were compared to wild-type or untreated controls. The greatest differences in the activity and diversity of soil and rhizosphere microbiota were recorded

between plant types and the growth phase of the plants (seedling to mature/harvest). Demonstrating the significant impact of growth stage and plant root exudates on microbial succession in the rhizosphere. The plant genotype selects a specific microflora from the soil. The introduction of a high density of inocula or inocula expressing a fungicide had little observable impact on ecosystem function and diversity when compared to the wild type control. Plant biomass was unaffected by treatment.

Findings from mesocosm (large scale pot based systems) and field based experiments were broadly comparable, demonstrating the potential of well planned and executed pot based experiments for predicting field performance and a mechanism for safety assessment of the potential environmental impact for these types of genetically modified organisms on the plant habitat.

Microbial communities in productive soils are highly complex and diverse. The resilience of the “soil community” is a clear reflection of the ability of component populations to respond and adapt to variable biotic and abiotic selective pressures.

Soil communities exhibit considerable functional redundancy with a range of taxonomically distinct bacteria able to undertake similar functions. As reflected in the reproducible but distinct selection of microbial communities observed for the different plant species.

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Attempts to refine techniques to target only the active component by vital staining and Fluorescence Activated Cell Sorting proved to be no more discriminatory in the rhizosphere when compared to the related PCR-DGGE analysis of the total sample. The developed method was however effective in identifying the limited numbers of metabolically active bacteria in more seriously perturbed bulk soils (Whiteley et al, 2004). Our studies demonstrated that the great majority of cells at the plant surface are metabolically active. Collaborative studies demonstrate that up to 70% of all isolated cells can be grown on standard microbiological agars (in contrast to less than 1% from bulk soils). This important observation confirms the importance of plant directed selection of a specialised and active biota in the rhizosphere dominated by copiotrophic (and predominately culturable) proteobacteria allowing an accurate evaluation of perturbation and impact.

Direct PCR-DGGE was the method of choice and was refined to target total diversity with universal primers and group specific primers to target sub-populations represented by the α-proteobeacteria, the γ-proteobacteria and total fungal community. The γ-proteobacteria diversity assessments allowed evaluation of potential impact of bacteria most closely related to the pseudomonad inocula based on the assumption that perturbation may be reflected in this community due to competition and niche exclusion resulting from the high density input “inocula effect”.

To advance these studies and provide a more direct evaluation of impact, based on soil microbial quality and activity, key functional groups need to be identified. The approach taken and data provided in this detailed study confirms the resilience and diversity of soil ecosystems and outlines suitable approaches in the safety evaluation of genetically modified bacteria used in plant growth promotion. The rhizosphere provides a suitable target habitat to evaluate the potential impact of GMOs. This investigation provides a critical assessment of methodologies. We demonstrated that following the release of GM-bacteria or plants that impacts are low and even when engineered to carry an ecologically functional trait, antifungal activity (phenazine and chitinase respectively), they have little discernable or lasting impact on the diversity, community succession or function of non-pathogenic, beneficial indigenous fungi or bacteria in the target habitat of the rhizosphere.

Key points1. The rhizosphere is a highly selective environment supporting extremely robust microbial populations.

Plant species enrichment of rhizosphere micro-organisms differs between growth stages and plant type. The plant has a more direct effect on the diversity, relative abundance and function of indigenous microbial communities than seasonal effects in bulk soil.

2. The plant effect is greater than the impact of bacterial inocula with or without novel antifungal activity.3. Molecular approaches and measures of activity provide sensitivity and accuracy for assessing soil

microbial community diversity and function.4. Transient displacement was recorded in fluorescent pseudomonads, the indigenous bacterial

populations most closely related to the inocula. The application of inocula revealed limited effects upon the microbial physiology; initial impacts were also recorded on microbial diversity. Natural succession of component microbial populations in the rhizosphere of pea, wheat and sugar beet was not adversely affected following inoculation of the WT and GM-BCA.

5. The bacterial inocula, the “inocula effect” resulted in an observable immediate response in the metabolic profile (physiological profile) of seedling rhizosphere communities compared to that that observed for the fungicide of chitinase producing plants. This impact was transient and did not influence or perturb natural succession as plants matured.

6. The combined use of GM-BCA on a GM-plant (chitinase) did not produce an additional or compounded increase in measured perturbation. The use of Metalaxyl-M in these experiments revealed a small cumulative effect on bacterial, but not fungal physiological activity. Overall microbial diversity was not affected.

7. Rhizosphere ecosystem responses to the application of genetically modified organisms were case specific, and dependant upon the engineered functional trait, the plant species and the soil characteristics being assessed. Pea responses were greater than those of wheat, whereas sugar beet rhizospheres’ showed little or no response to the introduced GM.

8. A deliberate field release of wild type and phenazine-1-carboxylate (natural bacterial antifungal compound) producing P. fluorescens SBW25 to wheat was conducted in 2004. As predicted the inocula colonised the emerging plants but declined (cfu/ g root material) as plant matured. The inocula did not persist in soils. No specific or lasting perturbation was observed to the diversity and function of the soil/rhizosphere biota and plants developed normally. No significant impact of GM over wild type inocula was observed. Plant biomass was unaffected by treatment.

Scientific Report8. The Scientific Report should be no longer than 20 sides of A4 and include:

the scientific objectives as set out in the SID 3 (original application form);

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the extent to which the objectives set out in the SID 3 have been met; details of methods used and the results obtained, including statistical analysis (if appropriate); a discussion of the results and their reliability; the main implications of the findings; possible future work; and any action resulting from the research (e.g. IP, Knowledge Transfer).

Published papers, or details of any other outputs (e.g. presentations), should also be annexed to the SID 5, together with other relevant information which cannot be accommodated within the recommended maximum of 20 pages.

INTRODUCTIONOver the last decade considerable research effort has been directed at the study and assessment of the use of genetically modified bacteria and plants in agriculture. Whilst considerable benefits have been identified for the control of disease, increase in crop yield, the expression of vitamins and the reduction in the use of herbicides and insecticides, concerns remain of the wider ecological impact that transgenic organisms may have on soil ecosystem function and biodiversity. Risk assessment and impact evaluation need to consider subtle environmental effects that may result from the use of GMOs. In many parts of the world, outside the European arena, bacterial inocula have been developed for the suppression of fungal-phytopathogens, and a range of crop plants have also been modified which express novel genes for the commercial control of foliar and rhizosphere fungal infections. With the development of transgenic micro-organisms and plants that carry these functional traits it is imperative that appropriate and independent investigations are carried out into risk assessment and impact evaluation on the beneficial non-target soil microflora. In this context it is essential that estimates be made as to whether the transfer of novel traits to bacteria or plants extends their habitat range through competition and antagonism. An increase in the spectrum of affected organisms could have severe effects on ecosystem function, particularly non-phytopathogenic fungi typical of the mycorrhizae and soil. Mycorrhizal fungi (MF) play a central role in nutrient cycling and plant health it is essential that studies be undertaken to determine whether GM-BCAs pose an increased risk to the beneficial micro-organisms both in target crops and local vegetation. We will monitor changes in the diversity and function of the metabolically active bacteria and MF in the roots of three crop plants to monitor the impact of a highly rhizocompetent fluorescent pseudomonad modified to express PCA for the enhanced control of damping-off disease. This is one of a very limited number of international studies that compare changes in below ground ecosystem function and diversity to assess the potential for harm of GMOs. This proposal was directed to Roame A (RG01) to inform DEFRA of any “potential impact or harm that may arise from the use and application of genetically modified bacteria and plants released to the environment… to provide plant protection and plant growth promotion by the de novo expression of antifungal compounds”. The main objectives were to extend our current approaches for impact assessments to include field releases of a genetically modified bacterium. This proposal built on a substantial understanding of the genetics and biology of a rhizosphere competent fluorescent pseudomonad, Pseudomonas fluorescens SBW25 that we had modified to express an additional antifungal compound (AFC), phenazine-1-carboxylic acid (PHZ). This genetically modified biological control agent (GM-BCA) protects seedlings from 100x the normal challenge of Pythium ultimum (the causative agent of damping-off disease) when compared to either the wild type P. fluorescens SBW25 (the recipient of the genes) or P. fluorescens 2-79 (the original source of the PHZ biosynthetic pathway, phzABCDEFG). We have evaluated whether the expression of PHZ directly influences the ecosystem function and diversity of non-target, plant beneficial rhizosphere bacteria and mycorrhizal fungi in crop and field margin plants. To optimise the study and to test potential commercial developments in GM-plants, we have also applied molecular and biological measures of rhizosphere function to the study of plants modified to express chitinase in greenhouse based studies. As these AFCs antagonise a different range of fungi it is appropriate to determine, whether alone or together, the plants and bacteria have a greater impact on the non-target biota. In addition we also evaluated the impact of the commercial fungicide metalaxyl. The output from this project will provide input to DEFRA policy “to provide scientific data .. to establish whether any GMO released would pose any discernible risk of harm to the agricultural environment ... and based on sound scientific principles .. affirm the adequacy of risk assessment..” that might result from the future environmental release of GMMs and GMO plants with commercial potential for plant protection and plant growth promotion. SCIENTIFIC OBJETIVES:

1. To evaluate the ecological impact and fate of a rhizocompetent bacteria, Pseudomonas fluorescens SBW25, modified to express phenazine 1-carboxylic acid (PHZ) for the enhanced protection of glasshouse and agricultural crops from fungal disease.

2. Determine how the impact of PHZ producing bacteria compares to the impact of chitinase

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producing plants and the use of a chemical fungicide, metalaxyl.3. Determine whether a biocontainment strategy for the niche directed expression of PHZ reduces

perturbation to ecosystem function. A promoter Ppui3 has been identified in SBW25 that is induced only in the presence of the germinating oospores of Pythium ultimum, the causative agent of damping-off disease.

4. Undertake a small scale, deliberate field release of the genetically modified bacteria (GM-biological control agent, GM-BCA) to test and provide science based advice to the regulatory authorities on the likely environmental impact and suitability of methods for making assessment.

5. Provide science based advice to assist the regulatory authorities when considering applications for the open environmental release of genetically modified organisms for crop protection.

MATERIALS AND METHODSWe have built on our knowledge of the microbial ecology and genetics of plant associated bacteria. Using a model system that combines a well described phenazine producing bacterium and a chitinase producing plant (tobacco) in combination with the use of the selective fungicide Metalaxyl. These GM-bacteria and GM-plants carry novel antifungal compounds for the suppression of fungal phytopathogens and provide ideal systems with which to assess impact on microbial ecosystem function in agricultural soils. We have developed generic methods that facilitate phylogenetic and molecular analyses of the activity of microbial communities. These methods have been applied to determine impact by monitoring changes in succession, activity, biomass and diversity in the mycorrhizal and rhizobacterial community in response to biocontrol inocula and chitinase producing plants.

Plants and planting. Pea (Psium satvium var. quincy), Wheat (Triticum aestivum var. Pena wawa or axona) and Sugar Beet (Beta vulgaris var. amythyst) seeds were used for the appropriate experiments. Sowing densities were equivalent to agricultural conditions as described. Where necessary weeds were controlled in field plots by hand. Irrigation was applied as required to establish the crops. At CEH-Oxford a genetically modified plant with increased antifungal activity was available. The variant, tobacco cultivar Nicotiana tabacum Xanthi-nc had been modified to express a baculovirus Autographa californica multiple nucleopolyhedrovirus (AcMNPV) derived chitinase gene coding sequence under the control of the constitutive cauliflower mosaic (CaMV) 35S promoter (Sui et al, 1987). This plant was effective in the topical control of Verticillium infection. The objective was to evaluate activity and impacts in the rhizosphere of treated and manipulated plants.

Soils and field sites. Pea, Wheat and Sugar Beet mesocosm experiments were conducted in plant pots containing a 1:1 mix of field soil (University of Oxford field station, Wytham) to horticultural compost. Tobacco mesocosm experiments used a 1:1:1 mix of field soil, horticultural compost and top soil. Field sites were located at either University of Oxford field station, Wytham, Oxon, or Rothamsted Research, Harpenden, Herts.

Bacterial strains. Treatments: a rifampicin resistant mutant of Pseudomonas fluorescens SBW25 (WT) and a variant of SBW25, 23.10, which had been genetically modified to carry a constitutively expressed, chromosomally located, single copy of the phenazine-1-carboxylic acid biosynthetic pathway operon (GM-BCA). Treatments were applied to provide 1x 107 bacterial inocula / gram of soil. Controls included water treatment alone.

Fungicide treatment. Commercial fungicide was applied to provide a contrast of conventional methods against which GM treatment could be compared. The soil applied fungicide Syngenta SL567A (Metalaxyl-M 44.7% w/w) was used at the rate 117l/m2 applied in 500ml water/m2 (as per manufacturers instructions) using a watering can bar sprinkler to achieve uniform distribution of treatment. The treatment was applied once at the time of sowing. Concentrations of metalaxyl in surface soil was determined by PerkinElmer Autosystem XL GC equipped with an autosampler and a Turbomass-MS detector. The GC instrument was outfitted with a split/splitless injector and a DB5-MS capillary column (Agilent, Cheshire, UK).

Plant productivity. Plants were separated into phyllosphere (above ground) and rhizosphere (below ground) samples. The phyllosphere portion was washed, oven dried at 65 ºc for 14 days and dry weights determined to reflect general productivity in response to treatment. All root samples were analysed as described below to assess the fate of the GM inocula and to evaluate whether discernable impact could result to below ground microbial diversity and metabolic function following the use of genetically modified bacteria or plants engineered to produce antifungal compounds. When this project began it was at the forefront of the application of molecular analyses for assessing below ground diversity and was unique in that the impact of a biologically functional GM bacterium had been proposed.

Sampling the rhizosphere. Plant roots were sampled and scored against the growth stage (GS) of the plant species in question. GS1 = young seedling; GS2 = growing plant, mid point of rapid growth; GS3 =

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maturing/flowering; GS4 = seed set; GS5 = post harvest. As plants were sampled at different times relative to the time of planting data and comparisons have been made against significant points in the plants life cycle. Individual plants were collected from each treatment plot or mesocosm replicate and analysed separately. In the baseline filed studies and mesocosm studies three plants were analysed per plot (n=3), in the release experiment, 2004, 6 plants were collected from each plot to increase the power of analysis. For sugar beet growth over a single season was followed, where GS4 correlated to the typical point of harvest and GS 5 leaf senescence.At each sampling time plants were gently removed from the soil to maintain the root structure, bagged, and any loosely adhering soil shaken off. The rhizosphere from each individual plant was sampled by mixing 1g root with 5 ml of phosphate buffer saline (PBS), ten 6 mm glass beads in a sterile 50 ml centrifuge tubes and vortexed for 2 min. From this suspension 1 ml aliquots were removed for nucleic acid extraction and 100ul removed for serial 1:10 dilutions to enumerate colony forming units on microbiological agars. For Biolog Community Level Physiological Profiling (CLLP), flow cytometry and where appropriate total cell counts, plant debris was removed and bacterial cells were collected and washed by low speed centrifugation. Samples were also collected from bulk soil surface horizon where plant roots were absent as a control.

Assessment of microbial diversity and activity in the rhizosphere and bulk soil.Culturable population counts. Population densities of plant associated bacteria and fungi were estimated using 1:10 serial dilutions of the suspension derived from soil and root samples. One hundred microlitres of dilutions were plated out onto three media types. Total bacterial densities were estimated with Tryptone Soya Broth Agar (TSBA) (Difco-Oxoid, UK), with the addition of cyclohexamide (0.1 mg ml -1) to suppress fungal growth. Pseudomonad population densities were estimated on Pseudomonad Selective Agar (PSA) (Difco-Oxoid, UK) supplemented with cyclohexamide (0.1 mg ml-1), centrimide (10 g ml-1), fucidin (10 g ml-1), and cephalosporin (50 g ml-1). Fungal population densities were estimated on Potato Dextrose Agar (PDA) (Difco-Oxoid, UK) containing 320 g ml-1 aueromycin™ (Cyanamid, UK) to suppress of bacterial growth. Plates were incubated at 28 C for 2 d. Bacterial colonies forming units (CFU), and Fungal propagule forming units (PFU) were counted.

Flow cytometric analysis -total cell counts. Bacterial cells were separated from soil particles by density centrifugation with Nycodenz (Axis-Shield PoC, Norway), and stained with Sybr Green I (Invetrogen, Netherlands) for cytometric detection on a FACScaliber (Beckton Dickinson, USA).

Flow cytometric analysis -Live Cell counts and sorting of CTC stained “active” cells. An aliquot of the cells collected for total cell counts were also stained using the live cell stain 5-cyano-2,3-ditolyl tetrazolium chloride (CTC) for flow cytometric analysis on a FACScaliber (Beckton Dickinson, USA) (Whiteley et al. 2003). Metabolically active cells fluoresce and can be sorted away from the inactive cells. This approach was applied to determine whether there were clear differences in the relative activity of bacterial populations when compared to the bulk soils and when treatments and plant types were compared by molecular analysis. In addition the approach was taken to determine whether the use of FACS and vital staining would provide a more sensitive and discriminatory method than the direct assessment of diversity of the total sample described below.

Community level physiological profiling (CLPP)- assessment of microbial activity. The 50 ml centrifuge tubes containing soil/PBS mixture were centrifuged at 3000 x g for 5 min before 1 ml of supernatant was diluted into 20 ml 1x PBS. One hundred mictolitres of this dilution were added per well of BIOLOG™-GN2 plates for bacteria and BIOLOG™-FN2 for fungi were incubated at 15C for 7 d. This translates as approximately 6.00 log10 bacteria inoculated per well. These densities are confirmed in total count data. Optical densities (OD) of each well were measured on a Rosys Anthos Lucy I plate reader (Switzerland) at a wavelength of 600 nm. Data were aligned against each of the 95 specific substrates the sampled communities were able utilise. In addition the average well colour was determined as an indicator of relative enzymatic activity for each community. These data provide an index of activity and nutrient utilisation capacity (physiological profiling).

Root staining for arbuscular mycorrhizal abundance and distribution. Soil cores were removed from the field cores using a 1 cm diameter cork borer. Each sample was washed through a 700 µm sieve with distilled water to separate roots from the soil. Roots were stained in trypan blue (0.05% (w/v) trypan blue, 50% (v/v) glycerol, 0.2% (v/v) HCL), and mounted on microscope slides parallel to each other. Microscopy at 200x magnification was used to score mycorrhizal presence/absence.

Extraction of total nucleic acid from environmental samples. DNA extractions were carried out from the pellets collected from the equivalent of 1 ml plant/soil suspension using the BBCTAB protocol (Griffiths et al, 2000) modified to include an additional freeze/thaw lysis step. Extracted total DNA was resuspended in 100 l ddH2O (Yield ~150 ng l-1) and stored at -20 C until analysed

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Molecular assessment of total microbial diversity - Community ribosomal RNA gene fingerprinting by denaturing gradient gel electrophoresis (DGGE). Microbial community diversity was determined by the analysis of 16S and 18S ribosomal RNA gene variation. Purified community DNA was amplified using well described universal and group specific primers. One prime in each pair carried the GC clamp and the DNA amplified by PCR. The GC clamp facilitates the separation of the mixture of different fragments of the targeted “gene” on the basis of the variation in the melting temperature of the double strand. The different melting temperatures result from subtle differences in each fragments sequence. Each sequence is unique to a taxonomic group. The fragments are run on denaturing gels and after staining a clear pattern of individual bands can be seen. The banding represents a “bar-code” or “fingerprint” for a particular sample as they are highly reproducible and reflect the accessible diversity within the sample. The comparison of the pattern of these fingerprints, combined with an estimate of the staining intensity of each band (which is a reflection of the relative abundance of a particular species or group in each sample) provides the estimate for monitoring changes in diversity of the community in response to natural succession or perturbation. The method, first described by Muyzer (Muyzer et al., 1993), has revolutionised microbial ecology and is a universally accepted method.The mixture of PCR fragments were separated by electrophoresis in denaturing polyacrylamide gels using a commercial gel-tank system (Ingeny, Netherlands) and DNA was visualised using Sybr Gold (Invetrogen, Netherlands). Individual gels were digitally scanned and analysed with Phoretix 1D software (Nonlinear Dynamics Inc.), each band represents a different operational taxonomic unit; OTU) and where necessary can be excised from the gel and sequenced to identify the taxonomic identity of the bacteria present in the original sample.

Universal and group specific primers. Universal primers are generally applied to asses the total diversity present in a sample. However group specific primers were also applied to study the diversity and community succession of specific functional groups. This approach provides finer differentiation: Eubacteria for “total” bacterial diversity, -proteobacterial to target an important and abundant groups of soil bacteria common to the soil-rhizosphere of many plants (Janssen 2006; Griffiths et al., 2006; Timms-Wilson et al., 2006) and the Pseudomonad (-proteobacteria) primers to target the bacterial group to which the inoculum belongs. With some caution it is possible to infer certain functional roles for such taxa. For example the acidobacteria, have only been discovered through molecular sequencing and so their functions in the environment are almost entirely unknown. The fact that acidobacteria are difficult to grow in culture, require low nutrients with long incubation times suggests a possible oligotrophic growth strategy compared with the more copiotrophic (and culturable) proteobacteria. Ecologically, it has been postulated from a meta-analysis of soil molecular studies that the ratio of proteobacteria to acidobacteria may be related to the nutrient status of the soil (Smit et al., 2001). Our studies targeted key groups and the relevance of our findings are discussed below both in the contexts of rhizosphere microbial ecology and in the context of determining impacts of GM inocula on soil and related ecosystems. The diversity of key fungal groups was also evaluated using general fungal primers directed at the 18S ribosomal RNA gene.

Sequencing of 16S and 18S DNA fragments. To confirm specification of PCR primer sets, bands were extracted from DGGE gels, purified, amplified by PCR and inserted into cloning vectors for sequencing. Vector inserts were sequenced by the DNA sequencing facility, Dept. of Biochemistry, University of Oxford. The analysis of extracted bands was applied to confirm the precision of the group specific primers used to detect the α and γ proteobacteria. The γ- directed primers were designed to predominantly target pseudomonad species, this allowed the appropriate monitoring of those bacterial populations most closely related to the applied inocula, P. fluorescens SBW25. This tested the assumption that if perturbation were to occur to bacterial populations in the rhizosphere then an effect could occur in the most closely related groups evolved to compete for similar resources (niche specific adaptation).

Statistical analysis of data. Principle component analysis (PCA) allows complex, multivariate data to be scrutinised by the two most variable factors (MVSP software, Kovach computing). Statistical weighting was given to PCA by taking the values of the identified most variable factors and performing a two-tailed, unequal variance T-test. These evaluations were further tested based on Analysis of Similarity (ANOSIM), using the Bray-Curtis distance measure is used to determine whether two groups of multivariate data are significantly related (Past software, University of Oslo). This approach facilitates a more complex comparison of spatial differences and temporal changes in assemblages. We have adopted this approach to detect impacts in those investigations where a sufficiently large number of replicates were possible. Namely the tobacco experiment and critically the open field release. Large replicate numbers allow estimates of true variation which tend to be large in biological samples. A key finding in the initial studies of the three plant natural microbial communities in the field and the mesocosm studies of the three plants plus inocula was that technical constrains limited analysis to n=3, the open field release in 2004 on wheat allowed a sample size of n=18 for CLPP (activity) and plate counts and n=9 for DGGE (diversity) studies.

Presentation of data. A significant quantity of data have been generated which are available on request .

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For ease of presentation we provide only those figures that illustrate key points and findings. An illustration of typical PCR-DGGE profiles is provided in Fig. 1. Fig 2 illustrates the transformed data from PCA plots of total bacterial and fungal diversity (PCR-DGGE profiles) from the rhizospheres of untreated, field grown pea, wheat and sugar beet to demonstrate the plant type effect with time. Figure 3 Illustrates microbial activity based on BIOLOG-CLPP data derived from the GM-tobacco mesocosm studies to contrast metalaxyl and GM-BCA treatment with chitinase expression from the tobacco rhizosphere community. Figures 4- 6 illustrate the detailed findings from the deliberate open field release experiment on wheat where the GM-BCA, the PHZ expressing strain 23.10 was introduced as a seed dressing to wheat: Fig 4– population densities (CFU) comparisons between field and mesocosm grown plants; Fig 5 CLPP assessment over the plant growing season: Fig 6 PCR-DGGE analyses of total, γ and α bacteria and total fungal communities. ANOSIM comparisons are provided as R plots and general trends to compare impacts following treatments: ANOSIM tests the null hypothesis that there is no significant difference between groups of samples (i.e treatment against untreated controls). The difference between treatments at any one sampling point is represented by the value R, where R values range between -1 and 1, with a positive value indicating that differences exist between the groups, a value of 1 indicates that the groups are completely different. R values equal to zero indicate that the groups are identical. Fig 7 mesocosm studies in pea, wheat and sugar beet; Fig 8 Metalaxyl impacts on field grown pea, wheat and sugar beet; Fig 9 GM-tobacco mesocosm studies with bacterial inocula and metalaxyl and Fig 10 the deliberate field release experiment of the GM-BCA to wheat. The absence of large negative values is taken to indicate that robustness of the experimental and sampling design in what is probably a highly stochastic environment.

RESULTS1. Field. Assessment of the natural microbial community structure and function in wheat, pea and

sugar beet grown under field conditions. 1.1 Objective.To evaluate the diversity of bacteria and fungi and make functional biological measures to assess changes in biomass, community diversity and ecosystem function of the rhizosphere microbiota of wheat, pea and sugar beet plants under field conditions. Component 1 also allowed refinement of the methods and testing of their value and utility. To gain a greater understanding of the base line natural conditions the below ground microbiology three plant types were investigated. Diversity and function of the sampled root associated community was investigated throughout a single growing season for pea (Psium satvium var. quincy), wheat (Triticum aestivum var. Pena Wawa) and sugar beet (Beta vulgaris var. amythyst).

1.2 Results.Seed were sown at normal agricultural densities in replicated (n=3 for each crop type) plots of approximately 2.25 m2 and sampled throughout the growing season. Samples were classified as follows. This approach allowed comparisons based on plant developmental stage.

Growth Stage Description

Pea plant age (d)

Wheat plant age

(d)

Sugar beet plant age

(d)GS1 Young seedling 14 12 16GS2 Growing plant, midpoint of rapid growth 30 48 44GS3 Flowering/mature plant 57 76 78

GS4 Fruiting plant, point of harvest (sugar beet tuber expansion) 70 103 99

GS5 Post-harvest plant rhizosphere (sugar beet senescence / point of harvest) 85 132 120

Culturable populations, field grown plants. Culturable population density data shows significant differences in population densities of total bacteria, Pseudomonad or fungi, between plant species. Each plant species selects a unique community with greater activity and density for total bacteria, pseudomonads and fungi when compared to the bulk soil level. (data not shown)

CLPP (microbial community activity and metabolic profiles), field grown plants. In all three plant types, grown under field conditions, the physiological profile for carbon utilisation patterns of bacterial and fungal communities were distinct. Communities separated in respect of plant type. For each plant type microbial communities clustered according to plant growth stage. As a general finding seedling and post harvest rhizosphere communities clustered more closely for any one species. Pea and sugar beet community profiles were more similar to each other than to wheat. (data not shown). These observations illustrate that plant type and the quality of rhizodeposition directly influences the selection and community succession of a specialised root-associated microbial flora.

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DGGE- Molecular assessment of total microbial diversity, field grown plants. (Fig 1; Fig 2) Evaluation of the total diversity of bacteria and fungi in the rhizosphere of the three plants grown in the same soil confirms that each plant selects its own specific community. Data are presented for individual samples (n=3). Seedlings of the three plants have the most similar communities. Diversity is high in all samples as indicated by the 100s of faint bands in the DGGE profiles (Fig 1). In soils the profiles do not appear to change over the growing season (Fig 1a) and only one or two bands appear dominant. Variation between individual replicates is minimal but the profiles or fingerprints of the community changes under the influence of plant development. This is most probably due to changes in the nutrient status of the plant and quality and quantity of root exudates and rhizodeposition. This effect is typical and was observed in all assessments of community diversity irrespective of plant type or treatment. As plants develop, succession in the relative diversity of the microbial community becomes more pronounced with each plant type sustaining its own specialist community. Changes in the relative abundance of OTUs (staining intensity of individual bands) also reflects the selection and adaptive pressures for individual microbial populations. At GS2 a higher degree of variation within growth stages is identified with overlap between pea and wheat data points and separation from sugar beet (Fig 2a). At GS3 the community profile of pea demonstrates higher internal variance in comparison to the wheat and sugar beet profiles. Fungal diversity, determined by 18S PCR-DGGE PCA analysis (Fig 1c: fig 2b) confirms plant specialisation but as with the bacteria the community diversity is greater and more distinct than that of wheat or pea. As the plants mature separation of the community diversity according to plant type is more pronounced.

1.3 Findings Different plant species enrich different bacterial and fungal populations from the indigenous soil

microbial community. The selection effect of plant species on rhizosphere microbiology is dynamic and changes over the life

cycle of a particular plant variety/type. Individual plant species enrichment of the rhizosphere microbiota and differences between plant

growth stage have a greater effect on the diversity and function of indigenous microbial communities than seasonal effects observed in bulk soil.

Total densities of bacteria (CFU) are significantly greater than those found in the bulk soil, and independent of plant type.

The relative activity of the sampled microbial community varied between plant species. This may reflect differences in the rate and quality of rhizodeposition (C, N etc). In pea and sugar beet, activity was lowest in young and post harvest plants. In wheat microbial activity was almost 50% higher in seedlings when compared to al other growth stages.

2. Mesocosm. Assessment of the natural microbial community structure and function in wheat, pea and sugar beet grown under mesocosm conditions & evaluation of potential impact on microbial community diversity and ecosystem function in the rhizosphere of wheat, pea and sugar beet plants, resulting from the application of bacterial biocontrol agents.

2.1 Objective.To compare the rhizosphere microbiology and function of mesocosm grown plants propagated in field soil with field grown plants (1. above); and assess the effect of the inoculation of Pseudomonas fluorescens SBW25 (WT) and Pseudomonas fluorescens 23.10 (GM) upon the ecosystem function and diversity of non-target, plant beneficial rhizosphere bacterial and mycorrhizal communities.

2.2 Results.General observations. Comparisons between the background bacterial population density and diversity of field or mesocosm grown plants were broadly similar. This general observation supported the use of mesocosms as a means of assessing the potential performance and impact of GM-inocula or GM plants on soil microbes and rhizosphere function when plants were grown in similar soils.

Culturable populations, Mesocosms. In all plant species the same general trends were observed. The population densities for bacteria (CFU) remain relatively stable with no observable influence of growth stage or treatment. Similarly, no significant differences between growth stages were observed for the total pseudomonad population densities. As predicted the pseudomonad populations at seedling and the early stages of plant development, in the treated plants, is dominated by the inocula. The relative proportion of inocula within the total pseudomonad community declines with plant development in response to out competition by the indigenous pseudomonads. Fungal populations remain stable regardless of treatment or plant growth stage. Data for mesocosm grown wheat plants are included in Fig 4b. Fig 4 compares the rhizosphere microbiology for wheat plants grown at Rothamsted Research (section 6) and wheat plants grown in mesocoms containing Wytham field soil.

CLPP (microbial community activity and metabolic profiles), Mesocosms. For Wheat and Pea

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PCA comparisons show distinct patterns that correlate primarily to plant growth stage, independent of treatment. Direct comparative analyses reveal an inocula effect against the water only control. Overall the expression of PHZ has no significant lasting impact when compared to the wild type control. In sugar beet greater overlap between CLPP profiles was observed between each growth stage. At GS4 treatments for each plant are not significantly different from the control (Fig7).

DGGE- Molecular assessment of total microbial diversity, Mesocosms. The general trends in untreated controls for the mesocosm grown plants were broadly similar to those for field grown studies described above. The data presented in Fig 1B illustrates the findings of treatment and different community analysis for pea seedlings. Images of DGGE-Gels or PCA analysis of DGGE gels or CLPP profile assessments are not included. In general terms the impact of wild type or PHZ producing inocula is similar and reflects the relative survival of the inocula. Pea impacts were greater than wheat with little or no effect observed when inocula (Wt or GM) were compared to untreated control. The inocula effect was evident in young plants, but the trend towards untreated control as each of the plants matured was evident. No last impact was observed.

Analysis within individual growth stages for wheat shows that at GS1 there is high variance within treatments coincident with germination and inocula effects. At GS2 through 4 the treatments loosely cluster. Group specific -proteobacteria DGGE analysis of all growth stages also reveals a strong growth stage effect dependent on plant type. Analysis at individual growth stages shows that at GS1 the GM treatment separates from the water control with the WT treatment overlapping both the GM treatment and the water control. At GS2 and beyond there were no significant differences between treatments. Group specific γ-proteobacteria DGGE revealed individual growth stage effects due to the impact of the inocula on closely related groups. At GS1 and 2 there are distinct separation of treatments coincident with the high relative abundance of inocula (Fig 4b) as the plants mature the inocula density declines. The natural succession within the community does not appear to be affected. Total fungal diversity based on 18S DGGE analysis shows a progressive shift in community structure with subsequent plant growth stages. At GS1 and 2 the WT and water control are similar to each other with separation from the GM treatment. At GS3 and GS4 the WT and GM cluster away from the water control further illustrating the inocula effect. However the expression of the antifungal compound by the GM does not appear to affect the fungal community when compared to the non-expressing wild type.For pea, bacterial diversity is clustered to each growth stage with no relation to treatments. Analysis within individual growth stages shows that at GS1 the treatments had no distinct separation from each other. At GS2 separation of the WT and GM from the water control is observed. At GS3 the GM treatment is separated from the WT and water control which cluster together. The -proteobacteria DGGE analysis of all growth stages show only growth stage separation. For the group specific γ-proteobacteria DGGE analysis there is no discernable separation of growth stages or treatments. Analysis within individual growth stages reveals inocula effects separating GM from WT and water control. Fungal 18S DGGE analysis shows partial separation of data with growth stages. Analysis at individual growth stages shows that at GS1 WT treatment separates from both GM and the water control. At GS2 there is distinct separation of WT and GM from water control and at GS3 all treatments cluster separately. Sugar Beet total bacterial diversity showed no distinct separation between growth stage or treatment. Analysis within individual growth stages reveal a minor but transient separation at GS1 within the α-proteobacteria with a minor separation of the GM-BCA observed for the γ-proteobacteria. Fungal 18S DGGE analysis of all growth stages shows there are no dominating effects on community structure by treatments or growth stages. Analysis at individual growth stages indicated that at GS1 through 3 there is no distinct clustering of treatments.

Plant productivity. No significant differences between treated/untreated plants were recorded.

2.3 Findings The impact on indigenous bacterial and fungal communities after the inoculation of the WT and GM-

BCA bacteria is small, at best transient and varies depending on plant type and age. Inocula successfully colonise the rhizosphere in each plant species. WT and GM (PHZ producing) pseudomonad inocula influence the physiology profiles of the

indigenous bacterial community. The inocula effect is expected as they can represent up to 10% of the total community.

The percentage of the pseudomonad population represented by the inocula declines with plant age due to competition.

Observed responses by the indigenous bacterial and fungal communities are different depending upon plant species.

The community is dominated by aerobic heterotrophs whose activity varies with plant type.

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Rhizodepostion is assumed to be the driver of selection, colonisation and local adaptation, The impact on subsections of the indigenous bacterial communities as a result of the inocula is, as

expected, most obvious on the pseudomonad populations. Histological assessment of mychorrizal infection of roots did not differ between treatments. Plant species and growth stage has a more significant effect on bacterial and fungal community

structure and function than the inocula tested.

3. Assessment of genetic biocontainment strategy. 3.1 Objective.

In earlier investigations we identified an inducible promoter (Piup3) present in the fluorescent pseudomonad isolate 54/96 that was induced in the presence of germinating oospores from Pythium spp (Timms-Wilson et al, 2000). The objective was to replace the constitutive Ptac promoter that controlled the expression of the PHZ operon chromosomally located in the SBW25 derivative, 23.10, described elsewhere in this report. Under the control of the inducible promoter de novo synthesis of PHZ would only occur only in the presence of plants under the threat of infection. This “biocontainment” strategy was attractive as it would minimise unnecessary release of a functional antifungal compound. This was considered highly appropriate if and where an impact or measure of harm was identified with the constitutive strain, 23.10.

3.2 Results. Following the detailed glasshouse (mesocosm) studies of the fate and impact of 23.10 it was evident that perturbation and impact to the below ground biota was minimal over the growing cycle of the three plants studied. It was therefore agreed with the project officer that glasshouse release and monitoring of the “biocontainment” strain was not essential to the success of the project and that remaining effort should concentrate on the open field release and refinement of the impact evaluations.

4. Comparative assay of the impact of fungicide (Metalaxyl-M) use upon biomass, community diversity and ecosystem function of the rhizosphere microbiota associated with wheat, pea and sugar beet plants under field conditions.

4.1 Objective.To assess the effect of the application of Metalaxyl-M upon the ecosystem function and diversity of non-target, plant beneficial rhizosphere bacteria and mycorrhizal fungi in the rhizosphere of field grown wheat, pea and sugar beet. Fungicide (Syngenta SL567A) was applied at commercially recommended rates directly to the soil once at the time of sowing.

4.2 Results.When total bacterial and fungal densities (CFU) were compared no treatment effects were observed indicating that the chemical fungicide had no direct effect when compared with untreated plant controls. Culturable population comparisons for all the major comparators, CLPP, bacterial and fungal diversity of the rhizosphere communities for the three plant species against the untreated control were evaluated (Fig 8). A limited effect was observed on the soil fungi for all plant species, interestingly the histological evaluation of mycorrhizal infection in pea and wheat plants revealed that in wheat the extent of mycorrhizal infection was significantly higher in fungicide treated plants at GS1. This may reflect a reduction in competition from indigenous fungi and the specificity of the chemical fungicide for certain types of fungi. Although a more pronounced effect on total bacterial diversity was seen, little or no effect on bacterial community physiology profiles was recorded (Fig 8).

Persistence of the fungicide. By GC-MS analysis Metalaxyl was detected in soil 48 days (GS2) following application.

Plant productivity. No significant differences were observed between treated/untreated plants.

4.3 Findings Metalaxyl-M is a highly selective fungicide and effects beyond its target organisms appear limited. Significant differences due to the application of Metalaxyl-M were observed in the 16S and 18S

community profiles of all three plant types. Metalaxyl treatment increased mycorrhizal association in wheat seedlings. Plant species and growth stage are the major factors driving bacterial and fungal community structure

and function.

5. Mesocosm assessments of the impact of fungal disease suppressing GM bacteria and disease suppressing GM tobacco plants on biomass, community diversity and ecosystem function of the rhizosphere microbiota.

5.1 ObjectiveTo assess the effect of the application of Metalaxyl-M, Pseudomonas fluorescens SBW25 (WT) and

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Pseudomonas fluorescens 23.10 (GM) upon the ecosystem function and diversity of non-target, plant beneficial rhizosphere bacteria and mycorrhizal fungi in the rhizosphere of chitinase producing GM tobacco (Nicotiana tabacum Xanthi) grown under glasshouse conditions. This investigation was conducted to determine whether a synergistic or cumulative impact would result from a combination of treatments with the potential to reduce fungal infections in plants.

5.2 ResultsCulturable populations (CFU). Tobacco cultivar Nicotiana tabacum Xanthi-nc, a glasshouse virus indicator, was genetically modified with a baculovirus Autographa californica multiple nucleopolyhedrovirus (AcMNPV) derived chitinase gene expressed under the control of the “constitutive” cauliflower mosaic (CaMV) 35S promoter. Tobacco plants and chitinase producing tobacco plants were grown in mesocosms under controlled conditions. No significant differences between treatments and the control (water treated, non-chitinase producing plant) were observed in treated and untreated tobacco plants. The bacterial inocula colonised the rhizosphere of the tobacco variants, with population densities declining with age. Trends for the culturable component were similar to those observed for the other plants described above.

CLPP (microbial community activity and metabolic profiles). ANOSIM of data shows that in comparison with the control (water treated, non-chitinase producing plant) significant differences are observed for all treatment/plant types, at all growth stages (GS1 through 5) for tobacco with greater impacts observed for the chitinase producing variant (Fig 9). Differences appear to be in direct proportion to the accumulation of treatments for both fungal and bacterial communities. The combination of de novo chitinase production by the plant and de novo phenazine expression by the bacterial inocula having the greatest impact. The community profile of the parental tobacco line treated with the GM-BCA was significantly different from the parental line treated to fungicide or the wild type alone. However no obvious differences in community diversity were observed following DGGE analysis (data not shown) of the treatments. Chitinase production had an effect that was highly variable between replicates, however a cumulative effect was evident for multiple treatments. Despite the clear indication that treatment has an impact on the activity of the rhizosphere community of tobacco the effects observed were less than those for plant age (Fig 3.1) when compared to fungicide or bacterial inocula (Fig.3.2) or indeed the de novo expression of chitinase (Fig 3.3).

Mycorrhizal infection. No significant differences were observed between treatments.

Plant productivity. No significant differences in plant biomass were observed.

5.3 Findings The production of chitinase in plant tissue has a significant effect upon the physiology of the microbial

community in the plant rhizosphere. The production of chitinase in plant tissue does not significantly alter the 16S or 18S community

fingerprints of rhizosphere microorganisms. Combining chitinase production with GM inocula increased the observed impact, but the effect was

less than that observed for the different growth stages of the plant. Growth stage has the greatest impact on the diversity and function of tobacco rhizosphere microbial

communities.

6. Assessment of the impact of disease suppressing GM bacteria on biomass, community diversity and ecosystem function of the rhizosphere microbiota of spring wheat under agricultural conditions.

The deliberate field release of a GM bacterium6.1 Objectives.

To assess the effect of the inoculation of Pseudomonas fluorescens SBW25 (WT) and Pseudomonas fluorescens 23.10 (GM) upon the ecosystem function and diversity of non-target, plant beneficial rhizosphere bacteria and mycorrhizal fungi in the rhizosphere spring wheat (Triticum aestivum var. Axona) under agricultural conditions.

Plants, site and inoculation. The field release experiment was undertaken within the boundary of a barley field which had been fallow following harvest and ploughing. Triticum aestivum, var. Axona was drilled by hand at a density of 350 seed per meter squared. Three plots of four square meters were sown for each treatment. Bacterial inocula were prepared in the laboratory under standard conditions and washed free of nutrients prior to resuspension. Treatments included the rifampicin resistant wild type P. fluorescens SBW25 and its variant 23.10 that constitutively produced the antifungal compound PHZ. In total 2.5 x 1011 cfu of bacterial inocula were applied per square meter directly to the soil surface, an equivalent volume of water alone was included as the untreated control. Irrigation was provided by

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rotating overhead sprinkler bars as per standard agricultural practice. Weeds were suppressed/removed by manual hoeing.

Sampling rationale Samples were taken at days: 0d (bulk soil, at application of bacteria); 25d (growth stage (GS1); 67d (GS2); 88d (GS3); 105d (GS4) and 122d (GS5:stubble - post harvest). Randomised samples of individual plants were collected from each plot based on pre-determined coordinates from the original planting grid. Nine plants from each plot were dissected so that the above ground portions could be used to index dry weights of the plants. Rhizosphere material was analysed following the removal of loosely adhering soil as described.

6.2 Results.Culturable populations in wheat, deliberate field release (Fig 4.1,2,3a). Total bacterial population densities show no significant differences due to inocula. Pseudomonad population densities demonstrate significant differences based upon the application of WT inocula at GS1 and 5, and GM inocula at GS2 in comparison to the water control. The inocula represent a large proportion of the pseudomonad community at GS1, this proportion decreases by approximately two orders of magnitude by GS3. GS3 through 5 show a stabilisation of the number of inocula pseudomonad present. The WT inocula persist at significantly higher densities than the GM inocula at GS3 and 5. This difference had not been observed in all previous laboratory and mesocosm investigations. No obvious explanation has been found to account for this apparent different field performance.

CLPP (microbial community activity and metabolic profiles) in wheat, deliberate field release. (Fig 5). Community physiological profiles for bacteria clustered against plant growth stage (Fig 5.1, 5.2), no treatment effects were visible. ANOSIM of data within each growth stage (fig 10) show minor differences when compared to the water control which indicates limited or minor inocula effects. The findings were similar in the fungal CLPP assessments (Fig 5.3, 5.4).

DGGE- Molecular assessment of microbial diversity in wheat, deliberate field release. (Fig 6). For all assessments of bacterial community diversity and succession the influence of plant age was significantly greater than the impact of wild type or phenazine producing inocula (Fig 6.1. 6.2, 6.3). For the total and two bacterial groups investigated (α and γ) the trend in diversity over the growing season was clustering with respect to plant development stage with a clear reversion at harvest to the pattern recorded at seedling. Individual, within growth stage comparisons show no clear clustering based upon treatment (Fig 10).

18S DGGE PCA plots over the growing season indicate some growth stage clustering as the plant develops away from the distinct separation observed at GS1 (Fig 6.4).

Plant productivity. Dry weight of growth stage samples and harvest fresh weight of plot areas shows no significant differences between treated/untreated plants.

6.3 Findings The inocula colonised and survived in the rhizosphere of field grown spring wheat (Triticum aestivum

var. Axona). However, population densities were not as high as those achieved in microcosm experiments under environmentally controlled conditions with Wheat (Triticum aestivum var. Pena Wawa). The effect is not due to difference in the plant genotype (variety), but demonstrates the variation and challenges that result from field experimentation.

The WT inocula persists at higher levels than the GM inocula. The applications of both WT and GM inocula have transient impacts on the physiology of the plant

rhizosphere microbial community. But this is less than the plant growth stage effects. No significant change was observed in the microbial diversity following the release of the bacterial

inocula. The effect of bacterial inocula is small in relation to plant growth stage effect. Growth stage is the major factor in driving bacterial and fungal community structure and function.

DISCUSSIONEnvironmental concerns and human health considerations have driven the development of alternatives to agricultural chemicals. Certain naturally occurring bacterial strains have the effect of reducing the incidence of plant disease and promoting plant growth. Many Bacillus and Pseudomonas based biocontrol inoculants have been commercially developed and marketed in the US (Mark et al., 2006). Monitoring the impact of an introduced organism (such as biocontrol inocula) upon an environment requires careful assessment of the factors upon which the introduction is likely to have an effect. Because it is not feasible to monitor all components of a soil ecosystem for their response, monitoring is concentrated upon organisms whose demise is thought to result in the loss of soil function and are therefore indicative of a negative effect (Lilley 2006). Soil nutrient cycling is dependant upon the

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successful functioning of the rhizosphere. Loss or negative perturbation of these functions is the primary concern relating to the use of biocontrol inocula engineered for the expression of anti fungal compounds.

Methodological considerations. In this project we have applied methods suitable for large-scale sampling and analysis of microbial taxonomic and functional diversity. The analysis of bacterial and fungal community structures, using DNA technologies that target ribosomal RNA (rRNA) sequences, can profile whole communities and detect microbes absent from the limited populations isolated using traditional culturing methods (Lilley et al., 2006). Microbial functional diversity is assayed using a variety of methods, notably community level physiological profiling (CLPP). Here, soil samples are assayed for the use of 95 environmentally relevant carbon sources by the isolated bacteria or fungi. Transgenic and non-transgenic alfalfa have shown a clear separation of bacterial CLPP (Tesfaye et al., 2003), with the rhizosphere bacteria of the transgenic alfalfa using significantly more substrates and having a greater functional diversity than bacteria from the untransformed control. CLPP is a popular technique in soil ecology and it frequently provides information that can be related to changes in the soil habitat, although it is unclear whether this information can indicate true changes in soil function. Both traditional and molecular techniques can detect many of the perturbations in rhizosphere soil community; however it should be remembered that there is no direct relationship between these perturbations and the detection of negative effects.A significant drawback of total nucleic acid based approaches for PCR-DGGE is that they do not necessarily represent the microbial community that is “active”. It is possible that subtle changes in the functional microbial community will be hidden by the legacy of superseded communities. RNA-Stable Isotope Probing (SIP) (Manefield et al., 2002) and Live Cell Staining (CTC cell sorting) (Whiteley et al., 2003) provide the researcher with tools that allow the investigation of active, functional communities. In this study CTC cell sorting was investigated as a means to increase the sensitivity of nucleic acid based techniques to subtle impacts on active, functional micro organisms. This approach consists of four principle steps: (i) the separation of bacterial cells from rhizosphere material by density centrifugation, (ii) the staining of active cells with CTC, (iii) the counting and collection of stained cells by flow cytometry, (iv) the nucleic acid extraction and subsequent PCR-DGGE of the active community. Due to the high relative activity of bacterial cells isolated with the method applied, which targets the community at the root surface or in close contact with the roots, it was not possible to differentiate active from inactive cells. Essentially the vast majority were active, indicative of the rhizosphere effect. Therefore this approach was not continued as it added little refinement, it is worth noting that the method is effective in evaluating gross perturbations to microbial communities in bulk soils (Whiteley et al., 2003)Analysis of the microbial community as defined by PCR-DGGE is an established method in environmental microbiology (Figure 1A). To extend the power of DGGE analyses to resolve the complex and diverse bacterial communities’ additional primer sets were deployed to provide finer differentiation of the various taxonomic groups present in the rhizosphere sample. The sequence divergence and the taxonomic relationship between bacterial species and genera is large in the 16S ribosomal RNA operon. We have applied three levels of differentiation (Figure 1B). The advantage is that we can focus on sub-sets within the total community and provide a higher level of resolution. Eubacteria for “total” diversity (Whiteley & Bailey 2000), -proteobacterial (Gomes 2001) to target an important and abundant group of soil bacteria common to the soil-rhizosphere of many plants, and the Pseudomonad (γ-proteobacteria) primers (Windmer 1998) to target the bacterial group to which the inoculum belongs. The diversity of key fungal groups was evaluated (Figure 1C) with general fungal primers directed at the 18S ribosomal RNA gene (Kowalchuk 1997). It should be noted however that there are limitations with the DGGE system not only with the number samples that can be simultaneously analysed, but also in the quality of the differentiation possible in high diversity mixed communities. As rapid systems become more common place we recommend that future investigations should make use of either Terminal-Restriction Fragment Length Polymorphism Analysis (TR-FLP) (Liu 1997), or where available the use of phylogenetic “Chips” to which sampled nucleic acid can be hybridized and a total community and relative abundance assessment can be made. Clearly advantageous but at considerable cost.

A baseline understanding. Our early studies into the nominal fluctuations in plant driven rhizosphere dynamics of plants grown under field conditions indicated that the components driving both the diversity and physiology of the observed microbiota are plant species and plant growth stage. Figure 2 demonstrates the plant driven separation of DGGE data based upon Principle Component Analysis (PCA). Similarly Viebahn et al (2005) observed the effect of plant species upon rhizosphere ascomycete communities when subjected to a crop rotation of wheat and potato. These observations enforce the importance of understanding the affect of the host plant in studies addressing the impact of bacterial inoculums to plant surfaces.

To make our studies broadly applicable three plant species were chosen as host plants to the bacterial inocula:

Wheat: Monocotyledon, simple rooting pattern, no secondary thickening of tissue with minimal structural changes associated with growth stage.

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Pea: Dicotyledon, with branched rooting pattern, known and agronomically important microbial associations.Sugar Beet: Dicotyledon, with simple tap root dominated root structure that thickens during maturation. Does not form mycorrhizal associations.

These plant types provide a broadly representative basis upon which to build our knowledge of plant driven rhizosphere community diversity and function.

Laboratory and glasshouse based mesocosm assays. Application of the wild type pseudomonas and phenazine-1-carboxylic acid producing GM derivative resulted in successful colonisation of the rhizosphere by the two bacteria in all plants studied, confirming previous studies (Timms-Wilson 2000, 2004). The survival of the introduced inocula demonstrated the characteristic trait of previous inoculation studies, with decline of population densities over time (Hirsch 1994, Thompson 1995, Glandorf 2001, Leeflang 2002, Timms-Wilson 2004). The impact of the inocula on the indigenous culturable microbial community densities were identified as very minor and transient based on the microbial carrying capacity of the crop plant. The only major perturbations identified were represented by the displacement of a large proportion of the indigenous Pseudomonads by the inoculum. Analysis of Biolog CLPP provided a representation of the metabolic potential of the rhizosphere communities, and identified that there were significant responses in the rhizosphere communities’ resultant from the GM inocula in wheat, pea and sugar beet, and resultant from the wild type inocula in wheat and sugar beet. The robustness of soil microbial communities to sustained inputs was demonstrated by a simple re-application assay where soil was re-planted with wheat seeds and re-inoculated at 5 week (growth stage 2) intervals with inocula as described above. No difference in impact was recorded in these sequential exposure experiments above or different from this seen for single inputs confirming the lack of a cumulative or additive response (data not shown).The impact on community structures, identified by DGGE, again confirmed clustering based upon plant species and growth stage and within individual growth stages by treatment. A comprehensive study to ascertain whether it is possible to increase the perturbances observed due to bacterial inocula by their application to a GM anti-fungal tobacco plant. The tobacco cultivar had been transformed by Agrobacterium tumefaciens vector carrying AcMNVP chitinase coding gene, transformed plants were shown to have fewer symptoms of brown spot disease (Shi et al, 1999). Quantitative measures of differences were required for this assay. Data demonstrated small increases in perturbance caused by the combination of GM bacteria and GM plant when compared to wild-type plant with GM inocula or GM plant with no inocula. Similarly an increase in perturbation was observed when Metalaxyl-M fungicide was applied to chitinase producing tobacco.

Fungicide affects compared to Biocontrol affects. Two experiments were devised to assess the impact of a commercially available highly specific fungicide. The fungicide chosen was Metalaxyl-M because of its specificity to fungi of the Peronosporales which are responsible for late blight, downy mildew, damping off, and stem and fruit rot of crop plants. The GM biocontrol bacteria that we have used for this study is known to inhibit damping off disease, it was therefore felt that Metalaxyl-M would be of comparative importance. Few studies have been undertaken to assess the effect of Metalaxyl-M fungicide application at recommended dosage levels upon non-target micro-organisms. Monkeidje (2002) demonstrated that the soil microbial population densities and enzymatic systems were the most sensitive indicators of change due to the application of Metalaxyl at varying concentration, implying that our methodologies are highly suited to the detection of effects caused by this fungicide. The first experiment undertaken under field conditions showed that at manufacturer’s application rates the minor effects of the fungicide were observed in bacterial and fungal community diversity profiles of the crops grown, with some effect noticed in physiological profiles of wheat and pea only. The largest effect was recorded in the bacterial rhizosphere community of the pea crop. Plant productivity did differ between treated and control plants. However in the mesocosm experiment, differences in bacterial CLPP for the fungicide treated plants were observed using tobacco plants.

The value of mesocosm investigations. By ensuring that mesocosm studies used plant growth media containing field soil, we have been able to closely reproduce the rhizosphere bacterial and fungal population dynamics of wheat, pea and sugar beet plants. The population densities of the inocula colonising the rhizosphere in mesocosm studies reflected the differential carrying capacity of the individual crop species observed in the field. These population densities are indicative of the Wytham field soil, with pea supporting the densest populations and sugar beet the least. Another study focusing on these three plant species in a different soil type identified a different pattern of rhizosphere colonisation abilities (Timms-Wilson 2004). It is, therefore, important to understand that soil and plant type influence the rhizosphere communities (Grayston 1998, Marschner 2001, Buyer 2002, Girvin 2003). Responses relating to the application of bacteria or fungicide showed variation dependant not only upon plant species but soil type. These findings indicate that great care must be taken in the design of mesocosm experiments as to the specific soil, treatment and plant species to which the results relate.

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The field release. Figure 4 demonstrates typical culturable population densities recorded in the wheat investigations under field and mesocosm conditions. Different patterns of rhizosphere colonisation abilities can be accounted for by differences in soil types. Figure 5 demonstrates bacterial BIOLOG CLPP data from field grown wheat treated with GM inocula, having been analysed with Principle Components. The complexity of the graph is due to the sample size employed (n=16). The arrow in Figure 5.1 indicates the overall movement of data with growth stages 1 through 5. Figures 5.2 through 5.4 demonstrate data indicated on the basis of the three treatments at the first three growth stages, further analysis of data at these growth stages indicated that at each growth stage the GM treatment data were significantly different to the water control and wild type treatment. Figure 6 shows PCA transformed DGGE data from eubacterial; alpha- and gamma- proteobacterial; and fungal communities labelled by growth stage or treatment. These figures clearly demonstrate that treatment effects are disguised by plant growth stage. It is necessary to visualise data at individual growth stages in order to identify any clustering based upon treatment affect.

Treatment effects upon plant productivity. No loss of plant productivity was recorded from any of our experiments, although differences rhizosphere community diversity and metabolic activity were detected. Changes in community structure and physiological profile were not always associated with the abundance in the rhizosphere of the biocontrol agent; findings akin to those of Bankhead et al. (2004) that used related biocontrol bacterium. As no gross impacts on plant productivity were observed it is possible to conclude that no negative effect upon rhizosphere function was caused. Our results compare well with similar studies into the affects of Pseudomonas biocontrol strains. A recent publication by Mark et al (2006) indicated that seven authors reported minor shifts in rhizosphere microbial diversity following the introduction of inocula (Glandorf et al 2001, Bakker et al 2002, Viebahn et al 2003, Resca et al 2001, Shaukat et al 2003, Girlanda et al 2001 and Beyler et al 1999). However, impacts on the metabolic or physiological traits of the rhizosphere were not commonly reported. As with our studies none of these investigations identified or reported lasting or significant perturbations which translated into deleterious consequences for plant productivity, plant yield or soil function.

SUMMARYThe studies conducted as a part of this Defra contract provided substantial quantities of relevant data necessary to investigate the complexity of soil biology. The overall purpose was to develop and test approaches that assessed whether the use of GM bacteria inocula and/or GM-plants impacts on the microbial diversity and function in the rhizosphere. In all systems studied using different inocula, soils and plants no adverse affect was recorded when GM inocula were compared to wild type inocula. The greatest differences in the soil and rhizosphere microbiota were recorded between plant type and the growth phase of the plants. Findings from mesocosm (large scale pot based systems) and field based experiments were comparable, demonstrating the potential of well planned and executed pot based experiments for predicting field performance and a mechanism for safety assessment of these types of genetically modified organisms. This study also evaluated the techniques and methods available for recording the impact and assessing potential perturbation in a given microbial habitat such as the rhizosphere. Traditional microbiological methods (e.g. colony counts on growth media) were compared with molecular based methods that target the total community (e.g. PCR-DGGE) and methods that measure relative activity (CLPP). Each approach provides valid data that facilitate direct comparison. The benefit of related assessments is that they provide sensitivity and suitable contrast when limited or no impact is recorded. The study confirms that soil is a complex environment that supports an extensive diversity of micro-organisms. In the course of this study we were one of the first groups to demonstrate that the plant is highly selective for the types of bacteria and fungi that are able to colonise their roots (Timms-Wilson et al., 2004). Each plant type and variety selects for and establishes a typical but distinguishable microflora when grown in the same soil. Succession in the rhizosphere microbial community was also observed in response to changes in plant metabolism as plants mature. These findings confirm the critical importance of root exudates (rhizodeposition) in selecting specific bacteria and fungal communities that directly influence plant health and productivity. Under the systems tested minor impacts were recorded. The detailed analyses of key sub-groups with the diverse microbial community did not reveal any lasting effects. Microbial communities in productive soils are highly complex and diverse. The resilience of the “soil community” is a clear reflection of the ability of component populations to respond and adapt to variable biotic and abiotic selective pressures. As a consequence the communities exhibit considerable functional redundancy with a range of taxonomically distinct bacteria able to undertake similar functions. This is perhaps reflected in the reproducible but distinct selection of microbial communities observed in the different plant species. To advance these studies and potentially provide a more direct evaluation of impact, based on soil microbial quality and activity, key functional groups need to be identified. Greater understanding may be required. However the approach taken and data provided in this study confirms the resilience and

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diversity of soil ecosystems and outlines suitable approaches in the safety evaluation of genetically modified bacteria used in plant growth promotion. Molecular tools for the study of microbial community diversity and function have advanced rapidly since the turn of the century. This report demonstrates the value and specificity provided by the use of community fingerprinting relative diversity. More specific probes allowed major taxonomic groups to be studied in greater detail. Even at higher resolution impact or effect was difficult to measure.The comparison of methods allowed a comprehensive assessment of techniques to compare genetic and physiological signatures. Each had merit and each should be selected to meet the purpose of the evaluation. The user must decide. It is apparent that molecular methods are main stream and a valuable tool for assessing diversity and relative activity. Functional assessments need comparative systems and as high throughput methods for determining genotype and metabolic activity improve it will be possible to target key groups. This investigation is timely in this regard and provides a critical assessment of methodologies. We demonstrate that following the deliberate field release of GM-bacteria biological and ecological impacts are low in soils communities. And even when engineered to carry an ecologically functional trait, antifungal activity, the impact of the bacterial inocula was at best marginal and only transiently affected closely related competitors. The inocula had no lasting discernable impact on non-pathogenic, beneficial indigenous fungi or bacteria in the target habitat of the rhizosphere. It should be remembered that the phenazine operon was isolated from a soil bacterium and is a common trait found in most agricultural soils. It is therefore likely that local adaptations and selection has taken place already. This highlights the need to understand the ecology and source of both vectors and the traits used in genetically modified organisms when predicting and devising methods for evaluating efficacy and impact.

Key points1. The rhizosphere is a highly selective environment supporting extremely robust microbial populations.

Plant species enrichment of rhizosphere micro-organisms differs between growth stages and has a more direct effect on the diversity, relative abundance and function of indigenous microbial communities than seasonal effects in bulk soil.

2. The plant effects are greater than the impact of bacterial inocula with or without novel antifungal activity.

3. Molecular approaches and measures of activity provide sensitivity and accuracy for assessing soil microbial community diversity and function.

4. Transient displacement was recorded in fluorescent pseudomonads, the indigenous bacterial populations most closely related to the inocula. The application of inocula revealed limited effects upon the microbial physiology; initial impacts were also recorded on microbial diversity. Natural succession of component microbial populations in the rhizosphere of pea, wheat and sugar beet was not adversely affected following inoculation of the WT and GM-BCA.

5. The bacterial inocula, the “inocula effect” resulted in an observable immediate response in the metabolic profile (physiological profile) of seedling rhizosphere communities compared to that observed for the fungicide of chitinase producing plants. This impact was transient and did not influence or perturb natural succession as plants matured.

6. The combined use of GM-BCA on a GM-plant (chitinase) did not produce an additional or compounded increase in measured perturbation. The use of Metalaxyl-M in these experiments revealed a small cumulative effect on bacterial, but not fungal physiological activity. Overall, microbial diversity was not affected.

7. Rhizosphere ecosystem responses to the application of genetically modified organisms were case specific, and dependant upon the engineered functional trait, the plant species and soil characteristics being assessed. Pea responses were greater than those of wheat, whereas sugar beet rhizospheres showed little or no response to the introduced GM.

8. A deliberate field release of wild type and phenazine-1-carboxylate (natural bacterial antifungal compound) producing P. fluorescens SBW25 to wheat was conducted in 2004. As predicted the inocula colonised the emerging plants but declined (cfu/ g root material) as plant matured. The inocula did not persist in soils. No specific or lasting perturbation was observed to the diversity and function of the soil/rhizosphere biota and plants developed normally. No significant impact of GM over wild type inocula was observed. Plant biomass was unaffected by treatment.

Acknowledgements: We would like to express our thanks to the staff at Rothamsted Research Harpenden for their support and expert assistance with the field release experiments. And to Defra and CEH for funding this research

References to published material9. This section should be used to record links (hypertext links where possible) or

references to other published material relating to or generated by this project.

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References:Bailey, M.J., I.P Thompson & T.M Timms-Wilson. 2003a. Phyllosphere Microbial Diversity. Encyclopaedia of Plants & Crop Science. (ed.) Goodman, R.M. Marcel-Dekker, Madison.Bailey, M.J., Timms-Wilson, T.M. and Lilley, A.K. 2003b. Considerations for the use of functional markers and field release of genetically engineered micro-organisms to soils and plants. In: Molecular Microbial Ecology Manual. Akkermans, A., de Bruijn, F., Kowalchuk, G., Head, I., van Elsas, J. (eds) Klewer Academic Press. Bakker, P.A., D.C. Glandorf, M. Viebahn, T.W. Ouwens, E. Smit, P.K. Leeflang, K. Wernars, L.S. Thomashow, J.E. Thomas-Oates and L.C. van Loon. 2002. Effects of Pseudomonas putida modified to produce phenazine-1-carboxylic acid and 2,4-diacetylphloroglucinaol on the microflora of field grown wheat. Antonie Van Leeuwenhoek. 81: 617-624.Bankhead, S.B., B.B. Landa, E. Lutton, D.M. Weller, B.B. McSpadden Gardener. 2004. Minimal changes in rhizobacterial population structure following root colonization by wild type and transgenic biocontrol strains. FEMS Microbiology Ecology. 49:307-318.Beyler, M., C. Keel, P. Michaux and D. Haas. 1999. Enhanced production of indole-3-acetic acid by a genetically modified strain of Pseudomonas fluorescens CHA0 affect root growth of cucumber, but does not improve protesction of the plant against Pythium root rot. FEMS Microbiology Ecology 28: 225-233Buyer, J. S., D. P. Roberts, and E. Russek-Cohen. 2002. Soil and plant effects on microbial community structure. Canadian Journal of Microbiology 48:955-964.Ellis, R.J., Thompson, I.P. and Bailey, M.J. 1995. Metabolic profiling as a means of characterising plant-associated microbial communities. FEMS Microbiology Ecology 16, 9-18.Girlanda, M., S. Perroto, Y. Moenne-Loccoz, R. Bergero, A. Lazzari, G. Defago, P. Bonfante and A.M. Luppi. 2001. Impact of biocontrol Pseudomonas fluorescens CHA0 and a genetically modified derivative on the diversity of culturable fungi in the cucumber rhizosphere. Applied Environmental Microbiology. 67:1851-1864.Girvan, M. S., J. Bullimore, J. N. Pretty, A. M. Osborn, and A. S. Ball. 2003. Soil type is the primary determinant of the composition of the total and active bacterial communities in arable soils. Applied and Environmental Microbiology 69:1800-1809.Glandorf, D. C. M., P. Verheggen, T. Jansen, J. W. Jorritsma, E. Smit, P. Leeflang, K. Wernars, L. S. Thomashow, E. Laureijs, J. E. Thomas-Oates, P. Bakker, and L. C. Van Loon. 2001. Effect of genetically modified Pseudomonas putida WCS358r on the fungal rhizosphere microflora of field-grown wheat. Applied and Environmental Microbiology 67:3371-3378.Gomes, N. C. M., H. Heuer, J. Schonfeld, R. Costa, L. Mendonca-Hagler, and K. Smalla. 2001. Bacterial diversity of the rhizosphere of maize (Zea mays) grown in tropical soil studied by temperature gradient gel electrophoresis. Plant and Soil 232:167-180.Grayston, S. J., S. Q. Wang, C. D. Campbell, and A. C. Edwards. 1998. Selective influence of plant species on microbial diversity in the rhizosphere. Soil Biology & Biochemistry 30:369-378.Griffiths, R.I., Whiteley, A.S., O’Donnell, A.G. and Bailey, M.J. (2000). A rapid method for the co-extraction of DNA and RNA from natural environments for the analysis of rDNA and rRNA based microbial community composition. Applied Environmental Microbiology 66, 5488-5491. Griffiths, R.I., Whiteley, A.S., O’Donnell, A.G. and Bailey, M.J. (2003) Influence of depth, sampling time and rhizodeposition on bacterial community structure in an upland grassland soil. FEMS Microbiology Ecology 43, 35-44. Griffiths, R,I., Bailey, M.J. and Whiteley, A.S. (2006). The functions and components of soil biota at the micro scales. Soil Biology and Biochemistry, In Press.Hirsch, P. R., and J. D. Spokes. 1994. Survival and dispersion of genetically modified rhizobia in the field and genetic interactions with native strains. FEMS Microbiology Ecology 15:147-159.Janssen, P.H. 2006. Identifying the dominant soil bacterial taxa in libraries of 16S rRNA and 16S rRNA Genes. Appl. Environ. Microbiol. 72, 1719-1728:Kowalchuk, G. A., S. Gerards, and J. W. Woldendorp. 1997. Detection and characterization of fungal infections of Ammophila arenaria (marram grass) roots by denaturing gradient gel electrophoresis of specifically amplified 18S rDNA. Applied and Environmental Microbiology 63:3858-3865.Leeflang, P., E. Smit, D. C. Glandorf, E. J. van Hannen, and K. Wernars. 2002. Effects of Pseudomonas putida WCS358r and its genetically modified phenazine producing derivative on the Fusarium population in a field experiment, as determined by 18S rDNA analysis. Soil Biology and Biochemistry 34:1021-1025.Lilley, A.K., M.J. Bailey, C. Cartwright, S.L Turner, P.R. Hirsch. 2006. Life in earth: the impact of GM plants on soil ecology?. Trends in Biotechnology. 24:9-14.Liu, W., T.L. Marsh, H. Cheng, and L.J. Forney. 1997. Characterization of Microbial Diversity by Determining Restriction Fragment Length Polymorphisms of Genes Encoding 16S rRNA. Applied and Environmental Microbiology. 63:4516-4522Manefield, M.,A.S. Whiteley, R.I. Griffiths, M.J. Bailey. 2002 RNA stable isotope probing, a novel means of linking microbial community function to phylogeny. Applied and Environmental Microbiology. 68:5367-5373.Mark, G.L., J.P. Morrisey, P. Higgins and F. O’Gara. 2006. Molecular-based strategies to exploit

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Pseudomonas biocontrol strains for environmental biotechnology applications. FEMS Microbiological Ecology. 56:167-177.Marschner, P., C. H. Yang, R. Lieberei, and D. E. Crowley. 2001. Soil and plant specific effects on bacterial community composition in the rhizosphere. Soil Biology and Biochemistry. 33:1437-1445.Moeseneder, M.M., J.M. Arrieta, G. Muyzer, C. Winter, and G.J. Herndi. 1999. Optimisation of Terminal- Restriction Length Polymorphism Analysis for Complex Marine Bacterioplankton Communities and Comparison with Denaturing Gradient Gel Electrophoresis. Applied and Environmental Microbiology. 65:3518-3525Monkiedje, A., M. Olusoji Ilori, M. Spieller. 2002. Soil quality changes resulting from the application of the fungicides mefenoxam and metalaxyl to a sandy loam. Soil Biology and Biochemistry. 34:1939-1948. Muyzer, G., Dewaal, E.C. and Uitterlinden, A.G. 1993. Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16s rRNA.. Applied and Environmental Microbiology 59, 695-700.Resca, R., M. Basaglia, S. Poggiolini, et al. 2001. An integrated approach for the evaluation of biological control of the complex Polymyxa betae/Beet necrotic yellow vein virus, by means of seed inoculation. 232: 215-226Shaukat, S.S. and I.A. Siddiqui. 2003. Impact of biocontrol agents Pseudomonas fluorescens CHA0 and its genetically modified derivatives on the diversity of culturable fungi in the rhizosphere of mungbean. Journal of Applied Microbiology. 95: 1039-1049.Shi, J., C.J. Thomas, L.A King, C.R. Hawes, R.D. Possee, M.L. Edwards, D. Pallett, J.I Cooper. 1999 The expression of a baculovirus-derived chitinase gene increased resistance of tobacco cultivars to brown spot (Alternaria alternate). Annals of Applied Biology 136: 1-8.Smit, E., et al. 2001. Diversity and Seasonal Fluctuations of the Dominant Members of the Bacterial Soil Community in a Wheat Field as Determined by Cultivation and Molecular Methods. Applied and Environmental Microbiology 67, 2284-2291.Tesfaye, M. et al. 2003. Influence of enhanced malate dehydrogenase expression by alfalfa on diversity of rhizobacteria and soil nutrient availability. Soil Biol. Biochem. 35:1103–1113. Thompson, I. P., R. J. Ellis, and M. J. Bailey. 1995. Autecology of a genetically modified fluorescent pseudomonad on sugar beet. FEMS Microbiology Ecology 17:1-13. Timms-Wilson, T. M., R. J. Ellis, A. Renwick, D. J. Rhodes, D. V. Mavrodi, D. M. Weller, L. S. Thomashow, and M. J. Bailey. 2000. Chromosomal insertion of phenazine-1-carboxylic acid biosynthetic pathway enhances efficacy of damping-off disease control by Pseudomonas fluorescens. Molecular Plant-Microbe Interactions 13:1293-1300.Timms-Wilson, T.M., Ellis, R.J. and Bailey, M.J. 2000. Immuno-capture differential display method (IDDM) for the detection of environmentally induced promoters in rhizobacteria. Journal Microbiological Methods 41, 77-84.Timms-Wilson, T. M., K. Kilshaw, and M. J. Bailey. 2004. Risk assessment for engineered bacteria used in biocontrol of fungal disease in agricultural crops. Plant and Soil 266:57-67.Timms-Wilson, T,M., Griffiths, R.I., Whiteley, A.S. and Bailey, M.J. (2006). Detection of active bacterial populations in soil. In: Modern Soil Microbiology, Marcel-Dekker. Vol2 Chapt 15.Viebahn, M., R. Doornbos, K. Wernars, L.C. van Loon, E. Smit, and P.A.H.M. Bakker. 2005. Ascomycete communities in the rhizosphere of field grown wheat are not affected by introductions of genetically modified Pseudomonas putida WCS358r. Environmental microbiology. 7: 1775-1785.Whiteley, A. S., and M. J. Bailey. 2000. Bacterial community structure and physiological state within an industrial phenol bioremediation system. Applied and Environmental Microbiology 66:2400-2407.Whiteley, A.S., R.I Griffiths, M.J. Bailey. 2003. Analysis of the microbial functional diversity within water-stressed soil communities by flow cytometric analysis and CTC+ cell sorting. Journal of Microbiological Methods. 54: 257-267. Widmer, F., R. J. Seidler, P. M. Gillevet, L. S. Watrud, and G. D. Di Giovanni. 1998. A highly selective PCR protocol for detecting 16S rRNA genes of the genus Pseudomonas (sensu stricto) in environmental samples. Applied and Environmental Microbiology 64:2545-53Winding, A. 1994. Fingerprinting bacterial soil communities using Biolog microtitre plates. In K. Ritz, J. Dighton, and K. E. Giller (ed.), Beyond the biomass, First ed. John Wiley and Sons, Chichester.

Works relating to or generated by this study:Bailey, M.J., T.M Timms-Wilson & A.K. Lilley. 2003. Considerations for the use of functional markers and field release of genetically engineered micro-organisms to soils and plants. In: Molecular Microbial Ecology Manual. Akkermans, A., de Bruijn, F., Kowalchuk, G., Head, I., van Elsas, J. (eds) Klewer Academic Press. Lilley, A.K, M.J. Bailey, M. Barr, K. Kilshaw, T.M. Timms-Wilson, M.J. Day, S.J. Norris, T.H. Jones & H.C.J. Godfray. 2003. Population dynamics and gene transfer in genetically modified bacteria in a model mesocosm. Molecular Ecology. 12:3097-3107.Bailey, M.J., I.P. Thompson & T.M Timms-Wilson. 2003. Phyllosphere Microbial Diversity. Encyclopaedia of Plants & Crop Science. (ed.) Goodman, R.M. Marcel-Dekker, Madison.

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Griffiths, R.I., Whiteley, A.S., O’Donnell, A.G. and Bailey, M.J. (2003) Influence of depth, sampling time and rhizodeposition on bacterial community structure in an upland grassland soil. FEMS Microbiology Ecology 43, 35-44. Timms-Wilson, T.M., K. Kilshaw & M.J. Bailey. 2004. Risk assessment for engineered bacteria used in biocontrol of fungal disease in agricultural crops. Soil Biology and Biochemistry 226:57-67.Timms-Wilson, T,M., R.I. Griffiths, A.S. Whiteley & M.J. Bailey. 2006. Detection of active bacterial populations in soil. In: Modern Soil Microbiology, Marcel-Dekker. Vol2 Chapt 15.Timms-Wilson, T.M., C. Moon, D. Arnold and A.J. Spiers. 2006. A survey of biofilm formation and cellulose expression amongst soil and plant-associated pseudomonads. In Microbial Ecology of Aerial Plant Surfaces. CABI, In press.Unde, S., D. Arnold, S. Giddens, C. Moon, T.M. Timms-Wilson, A. Spiers. 2006 Biofilm formation and cellulose expression amongst Pseudomonas spp. Environmental isolates, Environmental Microbiol, In press.Timms-Wilson, T.M., K. Smalla, T.I. Goodall A. Houlden, V. Gallego and M.J. Bailey. 2006. Microbial diversity in the phyllosphere and rhizosphere of field grown crop plants-microbial specialization at the plant surface. Phyllosphere book CABI, In Press.Hails, R.S. and Timms-Wilson, T.M. 2006. Genetically modified organisms as invasive species? In: Biological Invasions ed. By W. Nentwig, Springer. In Press.Lilley, A.K., M.J. Bailey, C. Cartwright, S.L Turner, P.R. Hirsch. 2006. Life in earth: the impact of GM plants on soil ecology?. Trends in Biotechnology. 24:9-14.

In addition during the period of this award Drs Bailey and Timms-Wilson gave a number of keynote talks, seminars, invited presentations and both oral and poster contributions at national and international meetings relating to this important investigation.

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