Dr José C Jiménez-López

Malek Shams

Tony Campillo

Céline Lavire

Daniel Muller

Xavier Nesme

Ludovic Vial

Jose C Jimenez-Lopez

T Campillo1

C Lavire1

M Shams1

J F Pothier3

J Pulawska4

Rapid and efficient methods to isolate, type strains and determine species of Agrobacterium spp. in pure culture and complex environments

Avant-propos

Je voudrais tout d'abord cordialement remercier les membres du jury, pour avoir accepté d'évaluer mes travaux de thèse, et en particulier P. Simonet et C. Manceau qui ont fait le rapport sur ce mémoire, Y. Dessaux qui a apporté son expertise sur la biologie d'Agrobacterium, C. Lavire et X. Nesme qui m'ont encadré durant ce travail et Y. Moenne-Loccoz directeur de l'UMR 5557 qui m'a accepté dans l'unité. Je remercie aussi les membres de mon comité de pilotage de thèse, F. Hommais, T. Pommier et D. Muller. Mes plus sincères remerciements vont à mes collègues qui m'ont activement aidé durant ce travail. J. Reynaud qui a co-encadré ce travail avant son départ en retraite. J. Pothier pour les études Maldi-TOF et B. Duffy qui m'a accueilli pour cela à Agroscope à Wadenswill pour un stage de recherche dans le cadre de l'action COST 873, ainsi que P. Portier qui nous a gentiment fournit les souches d'A. vitis incluses dans cette étude

Résumé

Les bactéries du genre Agrobacterium forment un ensemble taxonomiquement diversifié composé de nombreuses espèces, présent dans la plupart des sols et dans la rhizosphère des plantes. Les agrobactéries sont le plus souvent anodines voire stimulatrices de la croissance des plantes mais celles qui hébergent un plasmide Ti induisent la maladie de la galle du collet à de nombreuses plantes d'intérêt agronomique. Les plasmides Ti peuvent se transmettre par conjugaison aux autres agrobactéries qui deviennent à leur tour pathogènes. Ainsi, du point de vue écologique comme du point de vue épidémiologique, il est impératif de connaître la diversité des populations d'agrobactéries du sol, hôtes potentiels des plasmides Ti. Dans ce contexte, nous avons dans notre travail de thèse d'une part donné l'état actuel des connaissances sur la taxonomie du genre Agrobacterium, et nous avons fait une revue des méthodes d'isolement et de typage de ces bactéries. D'autre part, nous avons cherché à mettre au point des méthodes d'identification rapides et fiables des différentes espèces. Une première méthode est basée sur la technique MALDI-TOF MS. Elle permet d'identifier facilement les espèces de bactéries cultivées mais la méthode n'est pas assez résolutive pour typer des souches et encore moins la présence de plasmides Ti dans les isolats. Nous avons alors développé des amorces de PCR spécifiques de chaque espèces [START_REF]tumefaciens C58 {recA-G8-4} '185 A. tumefaciens DC07-004 {recA-G8-4} '321 A. tumefaciens LMG 75[END_REF], pour le genre Agrobacterium et la famille Rhizobiaceae. Ces amorces se sont révélées efficaces pour identifier les bactéries cultivées mais aussi pour détecter leur présence dans des communautés microbiennes. Nous avons ensuite utilisé ces outils pour étudier la répartition des agrobactéries à l'échelle d'un pays, d'une station et entre sols nus et sols rhizosphériques en utilisant soit des isolats soit des ADN métagénomiques extraits des différents environnements. Enfin, nous avons montré que le clonage-séquençage ou le séquençage à haut débit d'amplicons obtenus à partir d'ADN de communautés microbiennes nous permettaient de connaître facilement et avec une grande profondeur la diversité des populations d'agrobactéries.

Les outils que nous avons développés sont fiables et faciles d'accès. Ils permettront d'étudier l'effet des facteurs de l'environnement sur la structure génétique des populations d'Agrobacterium pour répondre, par exemple, à la question de l'effet sélectif des plantes sur les espèces d'agrobactéries du sol recrutées dans la rhizosphère.

General Introduction

Agrobacterium are Alphaproteobacteria common in most soils that closely interact with plants in two respects. Firstly, and as a general trait of the whole taxon, they are rhizospheric bacteria saprophytically living in the root environment (i.e. rhizosphere) of numerous plants.

Rhizospheric interactions are generally considered to be of commensal type with no detrimental effect to the plant, but in most instances they are likely beneficial to plants (Hao et al., 2011). For evident agronomic purposes it is thus worthwhile to explore the genetic diversity of agrobacteria of potentially important plant growth-promoting rhizobacteria (PGPR). Nevertheless, it is not yet known if the PGPR ability is a general trait among Agrobacterium or just a strain-or speciesspecific trait. Such a study requires an expert knowledge of the Agrobacterium taxonomy.

Secondly, when they harbor a dispensable Ti plasmid (i.e. tumor inducing plasmid), agrobacteria are plant pathogens able to cause the crown gall disease to most dicots and gymnosperms and some monocots (Pitzscke & Hirt, 2010). Ti plasmids are conjugative and can easily spread in indigenous soil agrobacteria. As a result transconjugant agrobacteria become in turn pathogenic, contributing both to disease spread and perennial soil contaminations. An epidemiological survey of crown gall thus also requires expert determination of the Agrobacterium taxonomy. However, the Agrobacterium taxonomy was historically based upon pathogenicity, while in modern bacterial taxonomy, the criteria to delineate taxa include genomic and phylogenetic informations. This recently brought considerable modifications to the Agrobacterium nomenclature that need to be clearly explicited.to base ecological works on most recent advances. In parallele, a point about biochemical and molecular methods set up to establish the taxonomic status of agrobacteria is required.

Agrobacteria are considered as common soil and rhizosphere inhabitants. However, to our knowledge, there is no exhaustive data about biotic or abiotic factors that influence their presence in particular environments. Our hypothesis is that determining factors that are shaping agrobacterial population genetic structures will have important issues for crown gall control itself. Indeed finding factors that limit the survival of agrobacteria and especially of the Ti plasmid harboring ones may provide us new ways to control perennial soil contaminations by pathogenic agrobacteria. As we will show later, indigenous agrobacterial populations are composites, generally with several species and strains per species. It is however difficult to extensively assess the taxonomic status of Agrobacterium populations by standard microbial approaches which are expensive and time-consuming. Hence, we were setting up affordable methods that will allow the simultaneous, rapid and accurate identification of numerous agrobacterial isolates and/or undoubtly detect Agrobacterium species directly in their common biotopes, soil, root and tumors, without bacterial isolations.

In a first part, the present thesis establishes the state of the art about the current agrobacterial taxonomy (Chapter 1-1), and current methods to isolate, type strains and determine species of Agrobacterium (Chapter 1-2). In a second part, we present development and evaluation of new tools for large scale Agrobacterium biodiversity studies. First, we evaluated the usefulness of MALDI-TOF MS technology as a high throughput tool to characterize and classify agrobacteria (Chapter 2-1). Then we set up a recA-based PCR method to accurately and exhaustively assess agrobacterial diversity either of isolated agrobacteria or directly in various biotopes (Chapters 2-2). We applied standard biochemical, and recA-based and Ti plasmidbased identification/detection methods to study the prevalence of pathogenic and non-pathogenic (i.e. Ti plasmid-free) agrobacteria at the country and local scales (Chapter 2-3). Finally, we tested whether analyzing the internal composition of recA amplicons could be a way to directly assess the micro-diversity of agrobacterial populations using cloning sequencing or pyrosequencin approaches. The later methodology was applied to establish the actual field diversity of Agrobacterium and to evaluate whether plant genotypes differentially select agrobacteria in their root systems, providing first data upon biotic factors shaping the population structure of agrobacteria (Chapter 2-4).

Summary

Crown gall, caused by bacteria belonging to different species of the genus Agrobacterium, is one of the most serious diseases affecting nursery production of fruit trees and nuts. From a practical point of view, determination if the soil of fields designated for nursery plantations is free from tumour-inducing agrobacteria is very important. During the infection process, after transfer of bacterial DNA to the plant cell, the presence of bacteria is no longer required for gall development. Therefore, infections caused by Agrobacterium remain difficult to detect although many methods are available for diagnosis of crown gall and identification of agrobacteria. In the present minireview, methods for isolation, identification and detection of tumorigenic agrobacteria developed within COST873 are described and ready-touse protocols based on both classical and molecular methods are provided.

The full paper is given in annexe 2.

First and as mentioned in chapter 1.1, Agrobacterium are soil and rhizospheric bacteria. The population size of agrobacteria in soil has been estimated to vary between 103 and 10 7 CFU/g [START_REF] Bouzar | Isolation of different Agrobacterium biovars from a natural oak savanna and tallgrass prairie[END_REF][START_REF] Bouzar | Correlative association between resident plasmids and the host chromosome in a diverse Agrobacterium soil population[END_REF][START_REF] Burr | Populations of Agrobacterium in vineyard and non vineyard soils and grape roots in vineyards and nurseries[END_REF][START_REF] Schroth | Biology and control of Agrobacterium tumefaciens[END_REF].

Additionally, seasonal fluctuations of the total agrobacterial population were observed, with higher population size during spring and summer than during fall and winter (Krimi et al., 2002).

Apart from diseased foci, the great majority of soil agrobacteria are not pathogenic [START_REF] Bouzar | Isolation of different Agrobacterium biovars from a natural oak savanna and tallgrass prairie[END_REF][START_REF] Vogel | Relationship between spatial and genetic distance in Agrobacterium spp. in one cubic centimeter of soil[END_REF][START_REF] Pulawska | Development of a semi-nested PCR based method for sensitive detection of tumorigenic Agrobacterium in soil[END_REF]Costechareyre et al., 2010;Shams et al., 2012). However some soils were found to be permissive to agrobacteria and to crown gall in turn. These soils allowed the long term persistency of pathogenic agrobacteria for several decades, rendering the soils inappropriate for the culture of susceptible crops [START_REF] Krimi | Seasonal fluctuations and long-term persistence of pathogenic populations of Agrobacterium spp. in soils[END_REF]Rhouma et al., 2007).

Agrobacterium can also be isolated from areas never exploited agriculturally. [START_REF] Bouzar | Isolation of different Agrobacterium biovars from a natural oak savanna and tallgrass prairie[END_REF] reported biovar 2 strains isolated in natural oak savanna and tallgrass prairie. D 'Hondt et al. (2004) found bacteria closely related to A. tumefaciens complex (biovar 1) in deeply buried sediments of the eastern Pacific Ocean, while [START_REF] Süss | Widespread distribution and high abundance of Rhizobium radiobacter within Mediterranean subsurface sediments[END_REF] showed that bacteria of the same taxon -with a rrs closely related to those of G2 and G9 of A. tumefaciens2 -are widespread in Mediterranean sediments, and could be isolated from up to 200,000-year-old marine sapropels.

Remarkably, members of Agrobacterium were also isolated from human clinical samples.

Agrobacterium infections in humans are frequently associated with the use of plastic catheters or with immunocompromising diseases like HIV [START_REF] Edmont | Agrobacterium radiobacter: a recently recognized opportunistic pathogen[END_REF][START_REF] Landron | Central venous catheter-related infection due to Agrobacterium radiobacter: a report of 2 cases[END_REF]. None of these strains carried a Ti/Ri plasmid. Studies on these strains showed that they belonged to A. pusense -genomovar G2 of the A. tumefaciens complex 3 - (Panday et al., 2011).

Diversity of agrobacteria is a general question, which can be analyzed from different point of views, such as genomic or plasmidic, genomic and plasmidic together, or diversity studies regarding host specificity. In chapter 1.1 and 1.2 different techniques to isolate, type and discriminate strains of Agrobacterium have been presented. Some techniques are available and are used since many years to assess agrobacterial diversity, others are quite new. Depending on classification method used, studies about Agrobacteirum can consider strain, species or biovar level and are useful to answer different kind of questioning. Current techniques are divided into those that grossly identify agrobacteria at the biovar level and those that operate very fine discriminations at the strain/isolate level. We asked which technique was the most used and at which taxonomic level Agrobacterium diversity was mostly studied. Table 1-3-1 summarized methods used and taxonomic assignation obtained from some of the publications dealing with Agrobacterium biodiversity studies. Hereafter some interesting results obtained using those methods are highlighted. [START_REF] Nesme | Population heterogeneity of Agrobacterium tumefaciens in galls of Populus L. from a single nursery[END_REF][START_REF] Michel | Identification of different Agrobacterium strains isolated from the same forest nursery[END_REF][START_REF] Nesme | Chromosomal and pTi genotypes of Agrobacterium strains isolated from Populus tumors in two nurseries[END_REF] PCR-RFLP of the 16S+ITS serological, biochemical, DNA-DNA hybridization DNA-DNA hybridization

Strain Strain Strain

Fruit trees [START_REF] Michel | Identification of different Agrobacterium strains isolated from the same forest nursery[END_REF][START_REF] Albiach | Plasmid heterogeneity in Spanish isolates of Agrobacterium tumefaciens from thirteen different hosts[END_REF]Pulawska et al., 1998[START_REF] Ridé | Characterization of plasmidborne and chromosome-encoded traits of Agrobacterium biovar 1, 2, and 3 strains from France[END_REF][START_REF] Peluso | Physiological, biochemical and molecular analyses of an Italian collection of Agrobacterium tumefaciens strains[END_REF][START_REF] Pulawska | Genetic diversity of Agrobacterium strains determined by RAPD and gyrB gene sequence analysis[END_REF]Pulawska et al., 2012 [START_REF] Miller | Leaf, stem, crown, and root galls induced in Chrysanthemum by Agrobacterium tumefaciens[END_REF][START_REF] Bush | Characterization of an unusual new Agrobacterium tumefaciens strain from Chrysanthemum morifolium Ram[END_REF][START_REF] Vaudequin-Dransart | Novel Ti plasmids in Agrobacterium strains isolated from fig tree and chrysanthemum tumors and their opinelike molecules[END_REF][START_REF] Ogawa | Highly tumorigenic Agrobacterium tumefaciens strain from crown gall tumors of chrysanthemum[END_REF][START_REF] Kawaguchi | Multiplex PCR for the identification of Agrobacterium biovar 3 strains[END_REF] [START_REF] Bouzar | A new Agrobacterium strain isolated from aerial tumors on Ficus benjamina L[END_REF][START_REF] Vaudequin-Dransart | Novel Ti plasmids in Agrobacterium strains isolated from fig tree and chrysanthemum tumors and their opinelike molecules[END_REF][START_REF] Zoina | Characterization of agrobacteria from weeping fig (Ficus benjamina)[END_REF][START_REF] Raio | Chromosomal and plasmid diversity of Agrobacterium strains isolated from Ficus benjamina tumors[END_REF] [START_REF] Alconero | Crown gall of peaches from Maryland, South Carolina, and Tennessee and problems with biological control[END_REF], on fruit trees in Greece [START_REF] Panagopoulos | Characteristics of Greek Isolates of Agrobacterium tumefaciens (E. F. Smith & Townsend) Conn[END_REF], Hungary (Süle 1978) andSpain (Lopez et al. 1988). However, in some areas and on some hosts, biovar 1 predominated, as with pecan in the USA [START_REF] Bouzar | Crown gall on pecan: A survey of Agrobacterium strains and potential for biological control in Georgia[END_REF] or Australia and New Zealand (Keane et al. 1970). Biovar 2 members were found to be homogenous group (Mougel et al., 2002;Popoff et al., 1984) and conversely, the highest diversity was observed within strains of biovar 1 (Pu awska et al. 2012).

Biodiversity and genomic studies.

RAPD analysis of tumorigenic agrobacteria isolated from tumors on fruit trees in six nurseries in Poland showed a high heterogeneity of bacteria. No correlation between genetic diversity and geographical origin, or host plant was found. Although some bacteria were isolated from the same nursery and the same species of host plant at the same time, they showed different RAPD patterns. The RAPD patterns generated with 5 RAPD primers were so diverse that it was possible to find a unique DNA fingerprint for each strain tested [START_REF] Pulawska | Genetic diversity of Agrobacterium strains determined by RAPD and gyrB gene sequence analysis[END_REF]. Similar observations were made by [START_REF] Llop | Tracking Agrobacterium strains by a RAPD system to identify single colonies from plant tumors[END_REF]. When looking at smaller environments, a high diversity of agrobacterial population could still be found. Differences in agrobacterial populations have indeed been observed on an area as small as 1cm 3 of an agricultural soil [START_REF] Vogel | Relationship between spatial and genetic distance in Agrobacterium spp. in one cubic centimeter of soil[END_REF]. Out of 55 isolates, 42 different ribotypes dispatched into 3 genomovars (G1, G4 and G8) of the A. tumefaciens complex were found by using the 16S + ITS PCR-RFLP [START_REF] Vogel | Relationship between spatial and genetic distance in Agrobacterium spp. in one cubic centimeter of soil[END_REF].

Epidemiological investigations combining genomic and plasmidic studies.

Isolates from a given host species usually show high biochemical and genetic diversity. For example, rose isolates belonged to biovars 1 or 2 with a nearly equal occurrence of succinamopine and nopaline Ti plasmids. They could be further subclassified into several chromosomal and Ti plasmid groups using PCR-RFLP analysis (Pionnat et al., 1999).

Chromosomal and Ti plasmid diversity was also observed among poplar isolates [START_REF] Nesme | Population heterogeneity of Agrobacterium tumefaciens in galls of Populus L. from a single nursery[END_REF][START_REF] Nesme | Chromosomal and pTi genotypes of Agrobacterium strains isolated from Populus tumors in two nurseries[END_REF]. PCR-RFLP of chromosomal (16S plus the 16S-232S intergenic regions) and Ti plasmid regions of 41 Agrobacterium strains from various origins showed that Ti plasmids belonging to the same PCR-RFLP group were found in strains with different chromosomal backgrounds and conversely different Ti plasmids were harbored by strains of the same chromosomal group (Ponsonnet and Nesme, 1994). A. vitis, the cause of crown gall on grapevine is an exception. In a study based on 16S-23S intergenic spacer region, a collection of 76 A. vitis isolates was analyzed and direct correspondence between chromosomal information and opine type of Ti plasmid was found [START_REF] Otten | Phylogenetic relationships between Agrobacterium vitis isolates and their Ti plasmids[END_REF]. This correspondence suggests a strong epidemiological link between analyzed strains. The same observation was made by [START_REF] Palacio-Bielsa | Chromosomal and Ti plasmid characterization of tumorigenic strains of three Agrobacterium species isolated from grapevine tumours[END_REF] on Spanish A. vitis isolates. It can be hypothesized that the reason for such diverse combinations of chromosomal background and Ti plasmid type in the case of biovar 1 and 2 and A. larrymoorei strains, which is the opposite of the more homogenous structure of A.

vitis population, could be the result of very different pathosystems. A. vitis strains are systemic and they have little chance of contact with a large and diverse pool of Agrobacterium strains and in consequence, of accessory plasmids. Such a phenomenon is the opposite for biovar 1 and 2 involved in common crown galls on fruit trees, as the tumor surface is largely in contact with soil where a large pool of Agrobacterium and plasmid diversity can be found. Furthermore, tumors are opine-rich environments that must facilitate conjugation and thus modification, of the progeny plasmid content.

Conclusion

Identification at the strain/isolate level was found to be very relevant for epidemiological investigations because finding the same strains in different crown gall outbreaks is a clue that those outbreaks are epidemiologically related. However identification at the strain/isolate level is often too detailed for agro-ecological studies. Indeed, the environmental diversity of agrobacterial strains is so huge that finding the same strains in different environment is a rare event except of course in the case of epidemics as mentioned above. Although new techniques are available, most studies still focus on classical biochemical method that only give results at the biovar level. However this level is not informative enough, especially for biovar 1 that is more diverse than other taxa within Agrobacterium. Hence, except for biovar 3 (i.e. A. vitis) that is infeodated to vine and found only in association with this plant, biovars 1 and 2 are so common that they are consistently found in almost all environments. Biovar typing is therefore of limited interest to elucidate factors that shape agrobacterial population genetic structures. The reason why it is still often used may be linked to the lack of affordable techniques that could be used to extensively analyze agrobacterial diversity at wide scale and at different taxonomic levels.

Fine typing of agrobacteria strains is an absolute prerequisite to assess the environmental diversity of agrobacteria for epidemiological and agro-ecological investigations especially to determine the epidemic or endemic status of crown gall outbreaks. As a reminding point, current techniques were divided into those who that grossly identify agrobacteria at the biovar level and those that operate very fine discriminations at the strain/isolate level. Methodologies delineating bacteria at the biovar level are not accurate enough for that purposes. Indeed, except for biovar 3 (i.e. A. vitis) that is infeodated to vine and therefore found only in association with this plant, biovars 1 and 2 are so common that they are consistently found in almost all environments (Chapter 1-3). Biovar typing is therefore of limited interest to elucidate factors that shape agrobacterial population genetic structures. At the opposite, the identification at the strain/isolate level was found to be very relevant for epidemiological investigations because finding the same strains is different crown gall outbreaks is a clue that those outbreaks are epidemiologically related (Chapter 1-3; Ponsonnet et al., 1994;Pionnat et al., 1999). However, in contrast, identification at the strain/isolate level is often too detailed for agro-ecological studies. Indeed, the environmental diversity agrobacterial strain is generally so huge that finding the same strains in different environment is a rare event except of course in the case of epidemics as described above. In this respect, the MLSA approach developed by Costechareyre (thesis 2009) for agrobacteria is relevant methodology to define the strain, species and genus status of any agrobacterial isolates. However, sequencing of housekeeping genes is labor-intensive, timeconsuming, and impractical for high-throughput investigations. Thus, there is still a valuable need of simplified and rapid approach to perform mass agrobacterium identification.

Whole-cell matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) is an emerging technology (Fig. 2-3-1) in microbial diagnostics [START_REF] Krader | Identification of archaea and some extremophilic bacteria using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry[END_REF][START_REF] Sauer | Classification and identification of bacteria by mass spectrometry and computational analysis[END_REF]. Identity is based on unique mass/charge ratio (m/z) fingerprints of proteins, which are ionized using short laser pulses directed to bacterial cells obtained from a single colony embedded in a matrix. After desorption, ions are accelerated in vacuum by a high electric potential and separated on the basis of the time taken to reach a detector, which is directly proportional to the mass-to-charge ratio of an ion. This technique has been shown to deliver reproducible protein mass fingerprints starting from an aliquot of a single bacterial colony within minutes and without any prior separation, purification, or concentration of samples. Whole-cell MALDI-TOF MS is a reliable technique across broad conditions (e.g., different growth media, cell growth states), with limited variability in mass-peak signatures -26 -within a selected mass range (2,000 < m/z < 20,000) that does not affect reliability of identification [START_REF] Lay | MALDI-TOF mass spectrometry of bacteria[END_REF]. MALDI-TOF MS profiles primarily represent ribosomal proteins, which are the most abundant cellular proteins and are synthesized under all growth conditions [START_REF] Ryzhov | Characterization of the protein subset desorbed by MALDI from whole bacterial cells[END_REF]. However, this approach is not informative as it relies upon the availability of a reference database. Current databases are weighted to clinical taxa [START_REF] Bessède | Identification of Campylobacter species and related organisms by matrix associated laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry[END_REF][START_REF] Stephan | Rapid genus-and species-specific identification of Cronobacter spp. by matrix-assisted laser desorption ionization-time of flight mass spectrometry[END_REF] and only a few references are available for plant-associated and environmental bacteria [START_REF] Sauer | Classification and identification of bacteria by mass spectrometry and computational analysis[END_REF][START_REF] Rezzonico | Whole cell MALDI-TOF mass spectrometry application for rapid identification and clustering analysis of Pantoea species[END_REF][START_REF] Wensing | Identification of the corn pathogen Pantoea stewartii by mass spectrometry of whole cell extracts and its detection with novel PCR primers[END_REF] . -27 -

In this chapter, we evaluated the usefulness of MALDI-TOF MS technology as a high throughput tool to characterize and classify agrobacteria. For this aim, strains covering all Agrobacterium species known so far as well as outgroup strains belonging to the Rhizobiaceae family were analyzed using the whole cell MALDI-TOF MS approach. To evaluate the quality of the taxonomic assignation done by the method, the MALDI-TOF MS data clustering was compared to the recA phylogeny done with the same strains. In addition, we evaluated whether the technique was able to provide information about strain pathogenicity by looking for consistant and remarkable differences between MALDI-TOF MS patterns of a standard pathogenic strain (C58) and its plasmid free derivatives.

Material and Method

Bacterial strains and growth conditions

A total of 114 strains covering all the genomic species richness of the genus Agrobacterium known so far as well as 4 outgroup strains belonging to the Rhizobiaceae family were investigated with whole-cell MALDI-TOF MS with 1 to 19 strains per species (Table 2-1-1). A special emphasis was given to A. vitis, with a selection of 19 strains done by P. Portier on the basis of their recA diversity. Along to the standard pathogenic strain C58, C58 derivative cured of pTiC58 and pAtC58 plasmids or containing other Ti plasmids were included in the analysis (Table 2-1-2). Bacteria were grown on MG agar (Ophel and Kerr, 1990) and LPG agar medium (yeast extract, 5 g/L; Bacto peptone, 5 g/L; glucose, 10 g/L) at 28°C for 42-50 h.

IC MALDI-TOF analysis

Colonies harvested on LPG plates were directly smeared onto target spots of a polished ground steel 48-position MALDI-TOF MS sample target (Industrietechnik mab AG, Basel, Switzerland)

with two distinct spot per strain using a blind random spotting design. Each spot was then overlaid with 1 l of a saturated solution of sinapinic acid (SA -49508, Sigma-Aldrich, Buchs, Switzerland) in 60% acetonitrile (154601, Sigma-Aldrich, Buchs, Switzerland) -0.3% trifluoroacetic acid (T6508, Sigma-Aldrich, Buchs, Switzerland), and air-dried for some minutes at room temperature. Senegal ND recA-Aun-1 a genomovar G1 to G9 were named according to the nomenclature of Mougel et al.(2002) Culture collections providing strains are abbreviated in the strain names as CFBP (Collection Française de Bactéries associées aux Plantes), CIP (Collection de l'Institut Pasteur), ICPB (International Collection of Phytopathogenic Bacteria), LMG (Collection of the Laboratorium voor Microbiologie en Microbiele Genetica), NCPPB (National Collection of Plant Pathogenic Bacteria), NCPPB (National Collection of Plant Pathogenic Bacteria). Superscript T following strain designation indicate the type strain of a species. b N/A, information not available. c Genomospecies determined by AFLP as described by [START_REF] Portier | Identification of genomic species in Agrobacterium biovar 1 by AFLP genomic markers[END_REF]. ND, not determined. d Allele code as established by Costechareyre et al. (2010)+A. vitis + Acc. Numbers Protein mass fingerprints were obtained using an AXIMA Confidence MALDI-TOF Mass Spectrometry (Shimadzu-Biotech Corp., Kyoto, Japan), with a detection in the linear, positive mode at a laser frequency of 50 Hz and within a mass range from 2,000-20,000 Daltons. The acceleration voltage was 20 kV, and the extraction delay time was 200 ns. MALDI-TOF MS spectra were the average of at least four replicate measurements using slides prepared at least in two different instances. Protein mass fingerprints were determined using 100 different laser direction and at least 10 laser shots per direction, then averaged and processed to provide a single raw spectrum using the Launchpad v2.8 software (Shimadzu-biotech, Kyoto, Japan). The software was also used for peak processing using the following settings: the Advanced Scenario was chosen from the Parent Peak Cleanup menu, Peak Width was set to 80 channels, Smoothing Filter Width to 50 channels, Baseline Filter Width to 500 channels and Threshold Apex was chosen as the peak detection method. For the Threshold Apex Peak Detection, the Threshold Type was set to Dynamic, the Threshold Offset to 0.020 mV and the Threshold Response Factor pTiC58 pAtC58 AW137 and DC07-004 are strains found to be exactly similar to C58 by MLSA using 8 housekeeping genes, received respectively as a laboratory strain from Ghent University or as a recent isolate from a Tunisian soil (Costechareyre et al., 2010). to 1.2. Each target plate was externally calibrated using spectra of reference strain Escherichia coli DH5 alpha. Processed spectra were reduced to the 150 most intensive peaks with an ad hoc PERL script written by J.F. Pothier, V. Pflüger, B. Duffy (unpublished), and exported as peak lists with m/z values and signal intensity in the ASCII format. A binary matrix was then generated using the SARAMIS™ (Spectral ARchive And Microbial Identification System, AnagnosTec, Potsdam-Golm, Germany) SuperSpectrum tool. Peak lists were trimmed to a mass range of 2-20 kDa. Peak lists were binned and average masses were calculated using the SARAMIS™ SuperSpectrum tool with an error of 800 ppm. Final consensus spectra for each strain were generated with a customized VBA script (J.F. Pothier, V. Pflüger, B. Duffy, unpublished) by eliminating masses present within fewer than half of the replicate measurements. Multivariate cluster analysis using the UPGMA algorithm with Dice coefficient was performed in PAST v2.14 (Hammer et al., 2001) and the resulting dendrogram was visualized with FigTree v1.3.1.

For clustering, a dendogram was constructed using strain consensus spectra selecting peaks that were found in at least half of 4 independent measurements, with the weighted pair-group average (UPGMA) clustering algorithm with the Dice coefficient. Similarity distances are expressed as percentage. The tree topology robustness was evaluated using the 1000 bootstrap resembling of peak values.

Results

Relevant growth medium for efficient agrobacteria detection using MALDI-TOF MS

To assess the growth condition influence on spectra, we compared results obtained using two standard growth media. There was a good cell multiplication for all strains on MG agar in both 24 and 48 hours of culture, while Agrobacterium vitis as well as Rhizobium strains had a very slower growth using LPGA (data not shown). Spectra were however clearer and more readable using LPG than MG medium, likely because polysaccharides intensely produced with the MG medium were blurring the peak spectra (data not shown). The best informative spectra that allowed unambiguous Agrobacterium identification used in further studies were obtained using 24-hour old colonies grown in LPG plate.

Agrobacterium species identification using MALDI-TOF MS

With the conditions described above, a typical MALDI-TOF MS spectrum of agrobacteria contained about 150 peaks between 2,000 and 20,000 Da, with the highest intensity peaks found between 4,000 and 20,000 Da. Spectra displayed high overall levels of similarity within species (not shown), but slightly different patterns between different species as exemplified Fig. 2-1-2. MALDI-TOF MS spectrum similarity analysis showed that agrobacteria belonging to the same species gathered in single clusters in all instances (Fig. 2-1-3). Rare mis-classifications occurred however. In all instances, they concerned mis-named strains. A definitive and fully conclusive dendrogram is thus currently in progress and will be delivered soon (draft given in Fig. 2

-1-3').
Result overall showed the potential interest of the methodology to rapidly identify agrobacterial isolates. However, within homogenous species clusters, strains with the same recA allele were -33 -frequently found to be intermingled with other allele, showing that the method is inappropriate in delineating agrobacteria at the strain/isolate level. -36 -

Plasmid content assessment using MALDI-TOF MS

To discriminate pathogenic agrobacteria from non-pathogenic bacteria (i.e. Ti plasmid containing vs. Ti plasmid free), we used different derivatives of the standard pathogenic strain C58. Derivatives have an identical chromosomal background but differ in their plasmid content (Table 2-1-2). MALDI-TOF MS spectra of Ti plasmid free derivatives were however intermingled those of C58 (Fig. 2-1-3). Analyses were also performed with agrobacteria incubated with ferulic acid in order to induce Ti plasmid virulence genes and thus stimulate the production of typical Ti plasmid protein, but no more marked differences were obtained (data not shown). Taken together, these results indicated that with the current experimental conditions, the MALDI-TOF MS technology did not allow the identification of pathogenic strains.

Discussion

Whole cell fingerprinting by MALDI-TOFMS is an emerging and powerful technique for rapid identification of bacteria. In the present study, the IC MALDI-TOF MS analysis was able to separate most Agrobacterium species (Fig. 2-1-3). The segregation showed the same level of accuracy as recA sequencing, DNA-DNA hybridization or AFLP methodologies and was more sensitive than either morpho-biochemical tests or 16S rRNA gene sequencing approaches. MALDI-TOF MS is set up generally at a range between 2 and 20 kDa of biomolecules in order to obtain the stable and strong signal to noise ratio. This size range is dominated by ribosomal proteins which ionize well and provide accurate spectra [START_REF] Stevenson | Evaluation of Matrix-Assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry for Identification of Clinically Important Yeast Species[END_REF][START_REF] Wieser | MALDI-TOF MS in microbiological diagnostics-identification of microorganisms and beyond (mini review)[END_REF]. Ribosomal proteins are less influenced by culture conditions allowing MALDI-TOF MS to be consistently used to differentiate some bacterial species (Claydon et al. 1996;Demirev et al. 1999;Fenselau and Demirev 2001). Interestingly, Agrobacterium species not distinguishable using 16S rRNA sequencing technique (Mougel et al., 2002) were accurately identified and classified in closed but completely separated clades as exemplified with genomovars G8 and G6 member. By the same way, genomovars G4 and G2 that have shown identical 16S rRNA sequences are grouped in close species clusters using the MALDI-TOF MS technique. The methodology still require improvements for some species such as A. rubi and A. larrymoorei, but it was found to be a promising tool for mass species identification of agrobacteria.

The MALDI-TOF MS technique has been reported to fail in identifying species that have very similar ribosomal proteins such as Shigella spp. and Escherichia coli, or Streptococcus pneumoniae and members of the S. oralis/mitis group [START_REF] Wieser | MALDI-TOF MS in microbiological diagnostics-identification of microorganisms and beyond (mini review)[END_REF]. In our opinion, it is -37 -likely because the later so-called different species are not readily different genomic species, contrary to the bona fide species of Agrobacterium analyzed in the present study. The present work offers us a great chance to utilize the MALDI-TOF MS technology for the species identification of single isolates and indeed for extensive agrobacterial population studies.

The protein mass fingerprints can be used to generate a Superspectrum by identifying specific mass peaks for each Agrobacterium species. Comparison of these protein mass fingerprints allows the definition of a set of markers present in fingerprints of all strains from a given species.

Even thought subsets of masses are shared within different Agrobacterium species, a combination of discriminatory signals is thought to provide unique Agrobacterium species signatures. As ribosomal protein mass can be inferred from the bioinformatic analysis of sequenced genomes, such an analysis is currently attempted by our collaborators (J. Pothier and Valentin Pflüger), using genome sequence of members of all A. tumefaciens species done by the Agrobacterscope(http://www.cns.fr/agc/microscope/about/collabprojects.php?P_id=51&wwwpk gdb=8f9fc33c35a024a8f6bf12ea71d7ff4d).

The MALDI-TOF MS technique is however not precise enough to discriminate strains within a species. Furthermore, and unfortunately, we did not found specific spectra for Ti plasmid even in presence of Ti plasmid protein production stimulator (Ferulic acid). We nevertheless, wander if the methodology can still be improved for this purpose.

In conclusion, results presented in this work clearly showed that MALDI-TOF MS is a reliable and rapid method for agrobacteria species identification, comparable to what is obtainable with housekeeping gene sequencing. The technology is moreover more rapid and affordable than MLSA. Indeed, by using this methodology, it is possible to prepare over 100 bacterial cell extracts and to analyze them in an 8 h working day, a number which could significantly be increased when coupled to process automation. Cell extracts themselves can be stored in ethanol for months without significant loss in spectrum quality. This in turn could allow pooling much larger numbers of samples. MALDI-TOF MS thus open a new and very useful way for diversity and ecological studies applicable to analysis of large populations of isolates allowing the differentiation of strains, species and genera of agrobacteria. Finally, we are hopeful to use MALDI-TOF MS on meta-proteome samples obtained from different environments instead of just pure isolate identification, as it had been used by [START_REF] Ziegler | In Situ Identification of Plant-Invasive Bacteria with MALDI-TOF MassSpectrometry[END_REF]. It would then allow us to analyze composite communities of bacteria and understand their microbial construction in a near future.

-43 -Agrobacteria are members of the Alphaproteobacteria subclass that is common in almost all soils where they closely interact with plants in two respects. Firstly, and as a primary trait, agrobacteria generally live saprophytically in the vicinity of plant roots. This rhizospheric interaction is commensal and has no detrimental effects on plants. It may even be beneficial to plants by promoting plant growth [START_REF] Hao | Genome sequence and mutational analysis of plant-growth-promoting bacterium Agrobacterium tumefaciens CCNWGS0286 isolated from a zinc-lead mine tailing[END_REF]. Secondly, it is well known that agrobacteria are plant pathogens that can cause crown gall disease in most dicots, gymnosperms and some monocots. However, the pathogenicty of agrobacteria is only the consequence of the acquisition of a Ti (i.e. tumor-inducing) plasmid. Fortunately for agriculture, indigenous soil agrobacteria populations are generally Ti plasmid free and most soils are uncontaminated and thus suitable for growing crops susceptible to crown gall, such as stone and pip fruit trees, raspberry, rose, poplar, etc. However, pathogenic agrobacteria may be fortuitously introduced with diseased plant material in any soils that may become contaminated. Contamination can be caused by introduced pathogenic strains. Alternatively, as Ti plasmids are conjugative, they can be easily transferred to indigenous soil agrobacteria that in turn become pathogenic, contributing to disease spread and perennial soil contamination (Krimi et al,. 2002;Costechareyre et al., 2010). Even for crown gall epidemiology, it is thus necessary to gain further insight into the ecology of actual and potential Ti plasmid reservoirs such as agrobacteria in their primary habitats, soils and rhizospheres.

As explained above, agrobacteria is a term used to describe bacteria based on a functional trait (i.e. their actual or potential pathogenicity). It is not a valid taxonomic term. According to the latest taxonomic proposals, agrobacteria are now divided into two genera: Agrobacterium and Rhizobium (Costechareyre et al., 2010;[START_REF] Lindström | International Committee on Systematics of Prokaryotes. Subcommittee on the taxonomy of Agrobacterium and Rhizobium: Minutes of the meeting, 7 September 2010[END_REF]Shams et al., 2012). In this revised nomenclature, biovar 2 agrobacteria (as defined by Keane et al., 1970) are now grouped into Rhizobium rhizogenes, while other agrobacteria are grouped into the genus Agrobacterium, now defined as a monophyletic taxon. The monophyletic Agrobacterium genus currently includes: A. vitis, A. rubi, A. larrymoorei, A. skierniewicense, A. sp. NCPPB 1650, likely Allorhizobium undicola, and a cluster of several genomic species corresponding to biovar 1 agrobacteria. Biovar 1 genomic species are collectively called the Agrobacterium tumefaciens complex, and individually called genomovar G1, G2, G3, G4, G5, G6, G7, G8, G9, G13 and G14. We added G14 to the collection of Agrobacterium tumefaciens genomic species after the recent description of a novel species in biovar 1 by Pu awska et al. (2012). Only some of these genomic species have been given a Latin epithet: pusense for G2 (Panday et al., 2011), radiobacter for G4, fabrum for G8 [START_REF] Lassalle | Genomic species are ecological species as revealed by comparative genomics in Agrobacterium tumefaciens[END_REF] and nepotum for G14 (Pu awska et al., -44 -2012). R. skierniewicense, recently described by Pu awska et al. ( 2012), is a close relative of A. rubi and A. larrymoorei outside the A. tumefaciens complex and is called A. skierniewicense in this paper according to the present Agrobacterium genus definition.

Agrobacterium genomic species were initially determined by DNA-DNA hybridizations (Popoff et al., 1984), but easier methodologies were proposed to achieve the same goal. Alternative methodologies also provide access to the infra-specific diversity required for population genetic studies. Among the methodologies, AFLP [START_REF] Vos | AFLP: a new technique for DNA fingerprinting[END_REF] was found to be useful for delineating Agrobacterium genomic species (Mougel et al., 2002), but the method is not dedicated for the rapid identification of a novel isolate. Standard method based upon 16S rRNA gene (rrs) analyses is insufficient to distinguish Agrobacterium species, since several ones exhibit identical rrs ( Mougel et al., 2002). On the contrary, we showed that recA gene sequencing can discriminate Agrobacterium species and also revealed the presence of numerous recA alleles within most species (Costechareyre et al., 2010). Sequencing this gene is now therefore routinely done to give a first idea of the species and allele status of novel isolates. The availability of numerous sufficiently long sequences of recA alleles offers scope for the development of specific primers to identify each Agrobacterium species, the Agrobacterium genus and the Rhizobiaceae family. We think that designing primers targeting specific taxa would permit identification of target taxa by a fast and inexpensive approach. To assess the diversity of numerous populations so as to elucidate ecological factors that shape their genetic structures, we proposed to set up a PCR-based approach to evaluate the species and allelic diversity of agrobacterial populations based on individual sequences present in recA amplicons obtained from complex communities.

The present study was aimed at developing species-, genus-and family-specific recA-based PCR primers suitable: i) for rapid identification of genomic species of Agrobacterium spp. and ii) to assess the allelic and species diversity of indigenous communities of Agrobacterium and Rhizobiaceae.

Materials and Methods

Bacteria

The Rhizobium and Agrobacterium strains used in this study listed in Table 2-2-1 are available at CFBP (Collection Française de Bactéries associées aux Plantes, INRA, Angers, France, http://www-intranet.angers.inra.fr/cfbp/). Agrobacteria isolated from an environmental community were obtained from a Poaceae rhizosphere at La-Côte-Saint-André (LCSA, Isère, France) using selective media amended with potassium tellurite and cycloheximide, as previously described [START_REF] Mougel | Novel tellurite-amended media and specific chromosomal and Ti plasmid probes for direct analysis of soil populations of Agrobacterium biovars 1 and 2[END_REF]Shams et al., 2012). All strains were routinely grown on mannitol glutamate (MG) medium (Ophel and Kerr, 1990) at 28°C and stored at -80°C in glycerol.

DNA extraction

Pure culture genomic DNAs were extracted from bacteria grown overnight at 28°C in MG broth using the NucleoSpin® Tissue kit (Macherey-Nagel GmbH & Co., UK). Metagenomic soil DNA was extracted according to instructions of the PowerSoil® DNA isolation kit (Mo Bio, Carlsbad, CA, US). DNA sample quantity and quality were determined with NanoDrop 2.5.4. (NanoDrop Technologies, Wilmingon, DE) and after electrophoresis in 1% agarose gel (Euromedex, Souffelweyersheim, France).

Primer design and PCR reactions

Degenerated primers F2898 5'-TAA TAC GAC TCA CTA TAG GGT CTT TGC GKC TCG TAG AGG AYA-3' and F2899 5'-ATT AAC CCT CAC TAA AGG GAT GCA GGA AGC GGT CGG CRA TSA G-3' designed by Costechareyre et al. (2010) were used to amplify and sequence a 1028-bp recA region spanning from position 13 to 1040 of Atu1874 (recA) in C58. PCR were performed at 57°C for A. tumefaciens species, but for bacteria outside this complex the annealing temperatures required adjustments As several strains may have the same recA allele, only one with a long sequence was arbitrarily selected as recA allele reference strain. Reference strains were made available when possible at CFBP (Collection Française de Bactéries associées aux Plantes, INRA, Angers, France) or at LMG (Laboratorium voor Microbiologie, Ghent University, Belgium). Species assignments were done using standard genomic methods (DNA/DNA hybridization, AFLP, complete genome sequence analysis) or phylogenetic analyses performed with at least two different genes, except for strains indicated by # which were assigned using only recA sequences. T indicates species type-strains. Large recA were obtained from complete genome sequences. * indicates strains used to prepare the synthetic community. Position indicates the primer position in the complete recA sequence of C58 (Atu1874). Taxon indicates the target taxon specifically amplified with primer sets. bp, amplicon length in base pairs. °C, annealing temperature.

Specific primers listed in

Primer specificity and analysis of complex communities

Primer specificity was tested on DNA of strains representing all recA alleles of target species indicated in Table 2-2-1 and one representative of other species, and then in conditions mimicking the presence of several species in template DNAs. Firstly, to check the ability of primers to specifically amplify the target species even in the presence of other species, template

DNAs were prepared by vigorously mixing 30 ng DNA of one strain per species for all species, including the target. Secondly, and conversely, to check the absence of amplification in the absence of the target species, template DNAs were prepared by mixing 30 ng DNA of one strain per species for all species except the target.

The synthetic community was prepared by mixing 23 strains harboring readily different recA alleles (Table 2-2-1). For this purpose, 2 ml of overnight cultures of each strain were adjusted to an OD 600 of 0.5, mixed by vortexing and maintained on ice to stop growth until DNA extraction as described above. Further PCRs were performed using 30 ng of this composite DNA as template.

PCR product cloning, sequencing and sequence analysis

PCR products were cloned into the pGEM-T easy vector as indicated by the manufacturer (Promega, Madison, USA) and clones were sequenced by Biofidal (Villeurbanne, France) using M13 forward and reverse universal primers. PCR products were sequenced by Genoscreen (Lille, France).

Bellerophon software was used to detect and eliminate chimera as described by Huber et al.

( 2004), with the Kimura correction and a 200 bp sliding window. Sequences were then compared to a locally curated recA sequence database made with the accessions given Table 2-2-1 in order to assign each sequence to the closest recA allele.

Results

The present study was aimed at designing primers in the conserved recA gene to identify agrobacteria and related bacteria at different taxonomic levels, including all known Agrobacterium species (eleven within and five outside of the A. tumefaciens complex) plus the close relative species Allorhizobium undicola, the Agrobacterium genus and the Rhizobiaceae family. We thus first attempted to obtain the most exhaustive view of recA diversity in Agrobacterium spp. Indeed, since the work of Costechareyre et al. (2010) describing 50 recA alleles amongst 14 species in Agrobacterium spp., two new species (A. skierniewicense, A. nepotum) have been described and 27 new strains with novel recA alleles have been found

(Table 2-2-1)
. By visual inspection of 77 aligned Agrobacterium allele sequences, we then designed sets of specific primers for all species as well as for superior taxa (Table 2-2-2).

Species-specific primers

Species-specific primers similarity analysis performed with blastn in GenBank showed that all primer sets likely amplify only their target taxon. Moreover, all agrobacteria that belonged to a particular species were recognized and amplified using relevant species-specific primers, thus generating amplicons of expected lengths. For instance, G2 delivered a 633 bp amplicon with G2-specific primers with all G2 agrobacteria irrespective of their recA allele, while no amplification was obtained with these primers using non-target DNAs (Fig. 2-1-1). In addition, with all species-specific primer sets, no amplification occurred in the absence of target DNAs, even when template DNAs consisted of mixtures of DNAs of different but closely related species (Fig. 2-1-2). Finally, we verified that no aspecific amplifications (i.e. amplicons of unexpected length) were obtained when using a DNA mixture mimicking a complex community formed by the pooling of 23 different strains belonging to different Agrobacterium and Rhizobium species

(Table 2-2-1; Fig. 2-2-3
). This indicated that the primer set specificities are conserved even in the presence of numerous non-target but closely related alleles in template DNAs, as consistently occurs in environmental communities.

Agrobacterium-and Rhizobiaceae-specific primers

Using a moderately stringent temperature (52°C), Agrobacterium-specific primers F8360-F8361 amplified a fragment of expected length (453 bp) with all isolates of the A. tumefaciens complex, A. sp. NCPPB 1650, A. rubi, A. skierniewicense and A. larrymoorei (with the exception of AF3.10, recA-Ala-1 allele) as well as with the close relative species Allorhizobium undicola (Fig.

2-2-4A

). Amplifications were reliably obtained at 52°C in spite of the occurrence of a mismatch between one primer and recA alleles such as recA-G6-1, recA-G7-11, recA-G9-2, recA-Ala-2, recA-Ala-4. recA-Ala-1 with an antepenultimate mismatch at 3' required a lower annealing temperature for reliable amplifications (data not shown). Conversely, no amplifications were obtained with A. vitis or other Rhizobiaceae isolates that all showed at least four mismatches with primers (Fig. 2-2-4A).

Rhizobiaceae-specific primers F7386-F7387 amplified a fragment of the expected length (779 bp) with all tested Rhizobiaceae species except A. undicola, while no amplification was obtained with any Gammaproteobacteria, Betaproteobacteria or other Alphaproteobacteria families (Fig.

2-2-4A and data not shown). As a final confirmation, sequences of PCR products obtained with pure culture DNAs always matched the template strain sequences (data not shown).

Species and infra-specific diversity of complex communities

Determining the internal species and allele diversity of complex amplicons would be a way to characterize the actual diversity of complex communities. To evaluate the usefullness of Agrobacterium-or Rhizobiaceae-specific primers to assess the allelic and species diversity of indigenous communities of Agrobacterium and Rhizobiaceae we first made a synthetic community of known allele composition (i.e. 23 different strains with alleles perfectly and non perfectly matching primer sequences). We then used a cloning-sequencing approach to decypher the allele diversity of amplicons obtained using Agrobacterium-or Rhizobiaceae-specific primers .

M G1 1 2 3 4 5 G3 G4 G5 G6 G7 G8 G9 G13 Aru T-

bp

G2

-53 - PCRs were performed with species-specific primers using a complex synthetic community DNA as template ( 1) or the DNA of a representative of target species as positive control (2) or without DNA as negative control (3). Species-specific primers used are specified above wells. The list of DNAs used as positive controls are presented in Fig. 2-2-1. The composition of synthetic community is indicated Table 2-2-2. M, 1kb+ Invitrogen DNA marker.

For Agrobacterium-and Rhizobiaceae-specific primers, respectively, 47 and 41 colonies were selected and sequenced. Unexpected sequences matching none of the alleles of the initial community were obtained and suspected as chimera sequences. Consequently, out of the 47 sequences obtained with Agrobacterium-specific primers, 18 sequences (38%) were identified as chimeras by Bellerophon software and removed from subsequent analyses. The 29 remaining sequences were divided into 14 alleles among the 20 potentially amplifiable by the Agrobacterium-specific primer set comprising recA-G6-1 and recA-G9-2, two alleles containing primer mismatches (Table 2-2-4). At the species level, 9 species out of the 12 present in different amounts in the initial community were detected, indicating the relevance of this primer set for analyzing both allelic and species diversities of Agrobacterium communities.

Out of the 41 sequences obtained with Rhizobiaceae-specific primers, 12 sequences (29%) were identified as chimeras. The 29 remaining sequences were divided into 17 alleles among the 23 that were amplifiable by the Rhizobiaceae-specific primer set. Ultimately, eleven species divided into three genera were detected. This indicates that this primer set is relevant for analyzing the allele, species and genus diversity of a Rhizobiaceae community.

Diversity analysis of an environmental community

In order to test whether primers targeting Agrobacterium or Rhizobiaceae can be used to assess the agrobacterial diversity of an environmental community, we used the direct approach based on the cloning and sequencing of amplicons obtained with metagenomic DNA extracted from the whole bacterial community of a wild Poaceae rhizosphere and compared results obtained with the standard microbiological approach. From the 30 sequences of 779 bp obtained with Rhizobiaceae-specific primers, 11 (34%) were identical and showed almost total identity with recA-G8-1 (Fig. 2 number of bacterial colonies isolated from the community (Isolation), of cloned fragments (Cloning-sequencing) or of positive amplification out a total of six assays (Direct PCR) done with the community metagenomic DNA. nt, not tested. Cloning-sequencing was done with F7386-F7387 or F8360-F8361 primer sets that specifically amplify Rhizobiaceae or Agrobacterium spp., respectively. Direct PCRs were done with the species-specific primers described in Table 2.

Presence of Agrobacterium species in the community was then investigated by direct PCR using species-specific primers with metagenomic DNA. As expected from the microbiological and cloning-sequencing results presented above, G1 and G8 were repeatedly detected in this way (Table 5). The microbiological approach has already pointed the presence of a G4 isolate, which is confirmed by visualisation of a positive signal with G4 specific primers. However, the method also revealed the probable presence of G2, G6 and G7 in this community, whereas they were not detected by the standard microbiological or by cloning-sequencing approaches based on primers for superior taxa. No amplification was obtained with other tested species-specific primers (G3, G5, G9, G13).

Discussion

To achieve our dual objective of rapid agrobacterial species identification and agrobacterial diversity assessment in complex environments, we designed recA based PCR primers with specificities at different taxonomic levels. The housekeeping recA gene has been established as a useful target for the identification of species inside closely related taxa (e.g. Rhizobiaceae, Burkoldheria cepacia complex, Brucella spp; [START_REF] Gaunt | Phylogenies of atpD and recA support the small subunit rRNA-based classification of rhizobia[END_REF], Payne et al. 2006, Scholz et al. 2008). Costechareyre et al. (2010) showed that recA gene sequencing can discriminate Agrobacterium species, contrary to 16S rDNA sequences (Mougel et al. 2002).

-58 - B., Bradyrhizobium;Rh., Rhodoposeudomonas Az., Azorhizobium;R., Rhizobium;E., Ensifer;Avi, Agrobacterium vitis;Aun, Allorhizobium undicola;Aru, A. rubi;1650, A. sp.;Ask, A. skierniewicense; G1 to G14, A. tumefaciens genomovars; G14, A. nepotum; G4, A. radiobacter; G2, A. pusense; G8, A. fabrum. Double arrow indicates Rhizobiaceae potentially amplifiable with Rhizobiaceae-specific primers F7386-F7387. Single arrow indicates the main species subset amplified using Agrobacterium-specific primers F8360-F8361. Numbers indicates clade probabilities. Branch length unit: number of substitutions per nucleotidic site.

recA-G8-1 J0-7 CN68 CN70 CN71 CN73 CN74 CN80 CN82 CN93 CN92 CN89 CN53 recA-G6-1 NCPPB 925 1.00 recA-G9-1 Hayward 0362 recA-G2-1 LMG 146 recA-G13-1 CFBP 6927 recA-G14-1 LMG 26435 T recA-G1-1 TT111 recA-G5-1 CIP 107445 recA-G4-2 LMG 140 T recA-G3-1 CIP 107443 recA-G7-1 RV3 CN52 CN56 recA-Ask-1 LMG 26191 T recA-1650-1 CN94 recA-Aru-1 LMG 17935 T CN81 CN87 CN59
Reliable taxonomic identification would require further investigations such as the sequencing of other housekeeping genes, as proposed with the multi-locus sequencing analysis (MLSA) approach (Gevers et al., 2005). Actually, taxonomic identification based on a single gene could be incorrect in case of horizontal gene transfer (HGT) between strains of different species (a strain readily belonging to a given species may have acquired a foreign recA allele).

Nevertheless, in our hands, MLSA and comparisons of complete genomes reliably showed us that recA was not prone to interspecies HGT within the Agrobacterium tumefaciens complex (unpublished results). We are thus reasonably confident about the taxonomic assignations of agrobacteria when recA was used alone. Moreover, thanks to its stability within species, recA is a good candidate to detect the presence of agrobacterial species in composite communities. We assumed that having a positive amplification signal with given primer sets is an easy and efficient way to have a first idea of the taxonomic status of any novel Agrobacterium isolate.

Designing of species-specific primers was possible thanks to the availability of numerous recA sequences longer than those usually found in databases (mostly from MLSA sequence data).

Indeed, MLSA analysis generally delivered ca. 450-500 bp fragments matching the 45-550 region of recA in C58, while the present study showed that relevant regions for the designed specific primers were often outside of this region (Table 2). Furthermore, perfect specific amplifications were obtained using species-specific primers, providing a novel way for rapid and accurate identification of Agrobacterium species.

Primers designed for superior taxa enabled amplification of most species that were usually classified within Agrobacterium spp. or Rhizobiaceae. The so-called Agrobacterium-specific primers were found to be able to amplify almost all Agrobacterium species except A. vitis, while it allowed the amplification of Allorhizobium undicola. This illustrates the close relatedness of the later species and might be an argument to include Allorhizobium undicola in the genus Agrobacterium since this inclusion is still a pending question [START_REF] Lindström | International Committee on Systematics of Prokaryotes. Subcommittee on the taxonomy of Agrobacterium and Rhizobium: Minutes of the meeting, 7 September 2010[END_REF]. As -60 -a consequence, it is likely that primers F8360 and F8361 target a very large subset of Agrobacterium spp. and only Agrobacterium spp. as shown by results obtained with DNA extracted both from synthetic and environmental community (Table 2-2-4 and2-2-5). The Rhizobiaceae-specific primers allowed amplifying recA sequences from available isolates of Agrobacterium, Ensifer and Rhizobium species (Table 2-2-5). A. undicola was not amplified by these primers. However, they amplify all other Rhizobiaceae members tested in this study.

Moreover using those primers on metagenomic DNA from an unknown community allowed us to detect sequences of Rhizobiaceae family members and no sequences of other family (Figure 5). This shows that Agrobacterium and Rhizobiaceae-specific primers could be useful tools to study more easily Agrobacterium and Rhizobiaceae biodiversity in complex environments, i.e. without standard microbiology methods requiring strains isolation and biochemical typing tests.

All primer sets were found to be relevant for the identification of the taxonomic status of bacteria at the family (Rhizobiaceae), genus (Agrobacterium) or species levels of bacteria in pure culture, but also for simply detecting the presence of agrobacteria in composite environmental DNAs as shown with the known synthetic community or the unknown environmental community (Table 2-2-4 and2-2-5). Notably, primers designed for superior taxa allowed us to consistently detect the presence of Rhizobiaceae and Agrobacterium spp. in all the soils we have tested to date. This was verified in the present study for the French LCSA soil (Table 2-2-5), but also for 66 soils sampled at 16 locations from northern to the middle of Tunisia, within orchards, oasis and uncultivated semi-desert stands (data not shown).

The cloning-sequencing approach revealed that G8 agrobacteria prevailed over all other Agrobacterium or Rhizobiaceae species at LCSA, but species specific primers also showed the occurrence of several other species (Table 2-2-5). This was a confirmation of previous microbiological inspections that reliably led to the isolation of G1, G4, G8 and G2 and G7 agrobacteria at LCSA [START_REF] Vogel | Relationship between spatial and genetic distance in Agrobacterium spp. in one cubic centimeter of soil[END_REF]and unpublished results). Thus, species specific primers could be useful to point the presence at low density of particular Agrobacterium species in environmental samples. However, the agrobacterial taxonomic diversity assessment was more rapidly obtained by analyzing the allele content of amplicons obtained with primers targeting superior taxa (Tables 2-2-5). Hence, this approach also revealed that recA-G8-1 was the dominant allele in this rhizosphere. This was in complete agreement with previous microbiological studies that showed the frequent presence in this soil of agrobacteria such as J-07 that had a typical recA-G8-1 allele [START_REF] Vogel | Relationship between spatial and genetic distance in Agrobacterium spp. in one cubic centimeter of soil[END_REF]Cosechareyre et al., 2010). Finally, the prevalence of G8 noted in the present study suggested that G8 agrobacteria were preferentially recruited in a particular rhizosphere. This kind of analyses used at larger scale could help deciphering the ecology of the different agrobacterial species such as finding factors that control the preferential recruitments of Agrobacterium species by particular rhizospheres.

In conclusion, the microbiological approach used so far to identify Agrobacterium species is hard to use for exhaustive investigations of the species composition of bacterial communities. Thanks to the recA specific primers designed in the present study, it is now possible to achieve an accurate and rapid first identification of all Agrobacterium species in both pure cultures and complex environments. Coupled with a cloning-sequencing approach, primers targeting superior taxa will allow investigation of agrobacterial and Rhizobiaceae microdiversity in the different biotopes they inhabit, including bulk and rhizosphere soils, tumors or even legume nodules for the purposes of thorough ecological, agroecological and epidemiological studies.

Agrobacteria are considered as common soil and rhizosphere inhabitants. However, to our knowledge, there is no exhaustive data about their actual presence in a large variety of soils (Chapter 1-3). The same question could be addressed to the presence of Ti plasmid harboring agrobacteria. Indeed, it is not known whether pathogenic or Ti plasmid-free agrobacteria are present everywhere or if biotic or abiotic factors may influence their presence in particular environments. Answering to this question may have important issues for crown gall control itself because finding factors that limit the survival of agrobacteria and especially of the Ti plasmid harboring ones may provide us new ways to control perennial soil contaminations by pathogenic agrobacteria.

In this chapter we thus addressed the question of the presence of i) agrobacteria and ii) Ti plasmids in soils at the country and local scales. For this purpose, we sampled soils in various locations in Tunisia consisted of agronomic and non-agronomic soils as well as soils collected in extreme condition such as salty and semi-arid areas that had or had not known history of crown gall.

Material and methods

Soil sampling and processing.

To look for the presence of agrobacteria, 16 stations located from northern to the middle of Tunisia have been arbitrarily selected. Sampled stations consisted of orchard, oasis and uncultivated semi-desert plots (Fig. 2-3-1), with 1 to 10 different sampling points per station for a total of 66 (Table 2-3-1). A special focus was given to the governmental fruit tree nursery located at Chbika (Kairouan governorate) in which one plot (Chbika-1) has repeatedly been reported to be infested by crown gall [START_REF] Rhouma | Plasmid and chromosomal diversity of a Tunisian collection of Agrobacterium tumefaciens strains[END_REF]Costechareyre et al., 2010

) (Fig. 2-3- 1').
GPS coordinates recorded for each sampling point were transformed into decimal degrees using the on-line service http://www.toutimages.com/google_gps/sis_gps.htm. Soil samples (ca. 40 g per point) were collected in the 5-10 cm superficial soil layers in sterile Falcon tubes, sealed and stored at greenhouse temperature (25°C) up to construction of individual soil microcosmes in the following weeks. Microcosmes consisted of sterile glass tubes containing 1.3 g perlite filled with ca. 20 g soil, and one germinated seed of Medicago truncatula ecotype Jemalong line A17.

Before sowing, seeds had been surface sterelized with hypochlorite, scalpel scarified, vernalized at 4°C during 48 h then overnight germinated on sterile agar plate at 25°C in the dark.

International, Lunel Viel, France) just after sowing were incubated in a growth chamber for three weeks at 28°C and 70% of humidity and a 16/8 day/night regime, with irrigations once a week with 1 ml of nutrient solution. After 3 weeks, microcosmes containing seedlings at the 2 leaf stage (Fig. 23-2) were treated to separate bulk from rhizosphere soils. For each microcosme, soil was divided into bulk and rhizosphere soil compartments. Bulk soil compartments consisted of visually root free soil fractions and rhizosphere soil compartments consisted of soil fractions tightly adhering to roots. The later compartments were obtained by removing non-adherent soil particules of roots by vigorous manual shaking. Bulk soils (ca. 1 g) as well as shaken root systems were suspended into 1 ml sterile water under agitation for 2 hours.

Soil suspension aliquots were used to isolate agrobacteria, while remaining aliquots deprived of root were centrifuged at 4000 g for 10 min to obtain soil pellets for subsequent soil metagenomic -71 -DNA extractions. Agrobacterium tumefaciens complex bacteria were isolated using the elective 1A-Te medium as described by [START_REF] Mougel | Novel tellurite-amended media and specific chromosomal and Ti plasmid probes for direct analysis of soil populations of Agrobacterium biovars 1 and 2[END_REF]. The bona fide Agrobacterium status of isolates was done using biochemical methods described Chapter 1-1. Metagenomic DNAs were extracted from soil samples using the PowerSoil® DNA isolation kit (Mo Bio, Carlsbad, CA, US).

Primers and PCR conditions.

Primers used to detect and identify agrobacteria were defined Chapter 2-2, while primers F14 and F749 used to detect Ti plasmids were described Chapter 1-1. PCRs were carried out as described in these chapters

Statistics

Chi square statistics were calculated on-line at http://marne.u707.jussieu.fr/biostatgv/?module =tests/chideux

Results

Agrobacterium prevalence in Tunisian soils.

Presence of agrobacteria in soils was first assessed by PCR using Agrobacterium specific primers with sample metagenomic DNAs. Positive amplifications were obtained for all the 132 samples that included equal numbers (66) of bulk and rhizospheric soils. This molecular detection was confirmed by the isolation of A. tumefaciens bacteria from all samples. Using species specific primers, we found that isolates gave positive PCR results either with G4 or G7 specific primers, 97/132 or 35/132, respectively, with no cross reactions with other primer sets as expected. There were more G4 than G7 isolates, but the two species were equally distributed in bulk and rhizosphere soil samples (Chi square=0.039; N=132; df=1; p-value=0.843), indicating no effect of biotope compartment upon A. tumefaciens species relative frequency (Table 2-3-2).

A more exhaustive analysis of the agrobacterial diversity in soils was performed using speciesspecific primers with metagenomic DNAs of the Chbika-1 station. All samples yielded easily visible bands of expected sizes using G4 and G7 specific primers as well as faint bands with A.

larrymoorei and A. vitis (Fig. 2-3-3) specific primers. Conversely, no amplifications were obtained using G1, G2, G3, G5, G6, G8, G9, G13, G14 specific prime414r sets in any samples (data not shown).

Presence of Ti plasmids in different Tunisian soils.

We looked for the presence of Ti plasmids by performing PCRs with primers F14 and F749, that permit the amplification of 432 or 384 bp fragment of the vir regions of nopaline or octopine and agrocine-mannopine type Ti plasmids, respectively (Chapter 1-1). No amplifications were obtained with Agrobacterium isolates, but bands of ca. 432 bp were obtained with 36/132 metagenomic DNAs. Amplifications occurred equally in bulk and rhizosphere soil samples (Chi square=1.375; N=132; df=1; p-value=0.241), indicating no effect of biotope compartment upon Ti plasmid harboring bacteria distribution (Table 2-3-3). Moreover, Ti plasmids were generally detected in both the bulk and the rhizosphere soils of the same sampling points, indicating a high level of reliability of the detection for a given sampling point corresponding to a single microcosme (data not shown). In summary, vir ampli were obtained in 12/16 Tunisian locations (Table 2-3-4). The greatest numbers of detection were obtained at Chbika-1, that was known to be severely contaminated by pathogenic agrobacteria. However, there was not detection at Oudna-2 which is a station where large crown gall tumors were easily visible in the close vicinity of sampling points. Conversely, Ti plasmids were detected with soils of Motbasta and Tozeur-1 that were both non-agronomic soils from a salty and a semi-arid area, respectively.

M T-TG1 ° TG1 TG2 ° TG2 TG3 ° TG3 TG4 ° TG4 TG5 ° TG5 TG6 ° TG6 TG7 ° TG7 TG8 ° TG8 TG9 ° TG9 TG10 ° TG10 K309

Discussion

In this chapter we addressed the question of the presence of agrobacteria and Ti plasmids in soils at a large scale. Taken together, our result showed that agrobacteria and especially members of the A. tumefaciens complex were present in all Tunisian soils we investigated. This result is remarkable and partly unexpected because some sampled soils were non-agronomic ones -74 -collected in extreme environments such as arid and salty areas (Table 2-3-4). It is certainly too early to claim that agrobacteria are present in every soils on earth. Nevertheless, the present study showed us that we now have the suitable microbiological and metagenomic methodologies to perform extensive Agrobacterium prevalence studies.

Only G4 and G7 agrobacteria were isolated from Tunisian soils in the present study. This result was surprising because other species were very likely present in numerous soils, at least at Chbika-1 as previously described by [START_REF] Rhouma | Plasmid and chromosomal diversity of a Tunisian collection of Agrobacterium tumefaciens strains[END_REF] and Costechareyre et al. (2010). As an hypothesis, we wander if the unique presence of G4 and G7 amongst isolates could be an artifact due to faster growth speeds of G4 and G7 over other species. It is thus our further aim to compare growth speeds of Agrobacterium species on 1A-Te medium. Nevertheless, the fact that we got so numerous isolates of the same species in very different locations offered us the opportunity to address the novel question of the presence of unique strains of agrobacteria (of G4 or of G7) at a country scale. We unfortunately didn't have time to do this analysis, but this investigation would be easily amenable because we have both the availability of numerous isolates belonging to the same species in various locations and the suitable methodology to answer the question of Tunisian G4 or G7 strain uniqueness. For this purpose, the recA sequencing currently in progress would offer a first indication. Nevertheless, MLSA will be preferable in order to know whether G4 and G7 isolates belong to single clonal complex or to markedly different strains. This population genetic information would help us to understand if G4 and G7 agrobacteria have spread over all Tunisia or if their dispersal was limited to sampling points of the same stations. We expect having soon these results because it would be help us in understanding how long agrobacterial strain actually spread out of stations.

We found no Ti plasmid harboring agrobacteria among isolates, confirming that Ti plasmid-free, non-pathogenic agrobacteria are dominant in soils. Conversely, we detected Ti plasmid signature in many soil community DNAs. However, those so-called Ti plasmid-specific primers indeed detected vir homologous sequences in non-agronomic soils that had no reported history of crown gall infestations and conversely not in visually crown gall infested orchards (Table 2-3-4). The biological relevance of those results is questionable. In a one hand, if F14-F749 primers did amplify only Ti plasmid sequences, the lack of detection in crown gall infested stations might have been caused either by a low density of Ti plasmid-free agrobacteria that was below the PCR detection threshold, either because primers did not match the particular Ti plasmids that caused the visible crown galls. In any cases, if primers readily detected Ti plasmids, results would suggest a wide dispersal of pathogenic agrobacteria in numerous soils. This is an unexpected and surprising result that absolutely requires additional investigations for definitive conclusions. To answer this question, we need to isolate pathogenic agrobacteria from from stations that provided unexpected results, but we unfortunately didn't have the opportunity to perform these investigations. In the other hand, F14-F749 primers might simply have targeted homologous vir regions outside Ti plasmids. Indeed, performing blastn with the F14-F749 amplified vir region of C58 in GenBank, showed us that part of this region has a strong homology also with non-Ti plasmids such as a vir region of plasmid p42a in Rhizobium etli that matches significantly with F749, or as the symbiotic island of Mesorhizobium loti that matches F14 (data not shown). It is thus very likely that vir homologous regions occurred by chance in soils. Hence, we assume that results obtained with F14-F749 primers just provided a presumptive indication upon the presence of Ti plasmids in soils. Detecting other Ti plasmid-specific regions is therefore required to ascertain such a presence. Conserved T-DNA regions might be used for this purpose, targeting for instance the oncogene region as early proposed by Ponsonnet and Nesme (1994) and Pionnat et al. (1999). Indeed, in our opinion, the PCR amplification of a single region can't be a definitive method to ascertain the presence of Ti plasmid in environmental samples. Moreover, especially when investigation are undertaken for forensic purposes, isolation of viable pathogenic agrobacteria from suspect areas are required to definitively confirm the first indications given by PCR. In fine, pathogenicity testing on indicator plants is the ultimate and definitive clue for the presence of viable and pathogenic agrobacteria. Nonetheless, direct PCRs remain faster. To gain in significance, we propose thus to use multiplex PCRs targeting vir plus other Ti plasmidspecific regions to achieve trustable Ti plasmid detection.

As a general feature, the present analysis showed us that bulk and rhizosphere soils of the same sampling points mostly led to the isolation of the same Agrobacterium species (Table 2-3-2) or the same detection of Ti plasmid (Table 2-3-3). This could lead us to suggest that there was no selective plant effect upon the recruitment of Agrobacterium species or of Ti plasmid harboring bacteria in rhizospheres. This suggestion is however questionable. In our opinion, the absence of bulk vs. rhizosphere effect might be caused by a failure in our sampling procedure. Indeed, we collected bulk and rhizosphere soils in the same microcosmes and not in independent test tubes.

It is thus very likely that cross contaminations between the two compartments might occur.

Actually, in those relatively small test tubes, root systems were rather developed (Fig. 2-3-2) and leaved us little chance to well select really root free soil fractions. However, if there is no real taxon density distributions that followed an exponential decrease model in which ranked taxa decreased according to a 1/2 ratio (Table 2-4-1).

Agrobacterium communities.

Metagenomic DNAs used to evaluate the Agrobacterium species in a standard field plot was those of Chbika- Sequencing and data processing.

The Roche 454™ Genome Sequencer FLX™ System, with FLX Titanium chemistry was used to sequence pooled recA PCR products with MID labelling according to manufacturer's instructions. For this purpose, samples were 5'-labeled during PCR using forward primers consisted of the FLX adapter A, a sample specific barcode (MID) and the Agrobacterium specific recA sequence F8360 defined Chapter 2-3-2, and a reverse primer consisted of the FLX adapter B and the Agrobacterium specific recA sequence F8361 defined Chapter 2-3-2:

forward primer: 5' -CCATCTCACCCTGCGTGTCTCCGACTCGAAGCTCGGTTCCAATGAAA-3' reverse primer: 5' -CCTATCCCCTGTGTGCCTTGGCAGTCTCAGGCTTGCGCAGCGCCTGGCT-3' Sequencings were done using FLX slides for pools of 24 or 48 samples by Genoscreen (Lille, France). Raw sequence data were cleaned and denoised using the mothur v.1.25.0 pipeline (http://www.mothur.org.), authorizing 1 error in barcode (bdiffs=) and 2 errors in primer (pdiffs=2), aligned against recA sequences of the fungene data base and cleaned of chimera retrieved with the Uchime module of mothur.

Data treatment and statistics

Cleaned sequences were classified in operational taxonomic units (OTUs) according to their best identity hit (Imax) with an exhaustive Rhizobiaceae recA database that essentially corresponded to those given in Percentage confidence intervals were calculated on-line at http://ww3.ac-poitiers.fr/math/prof/ resso/ cali/ic_phrek.html#sommaire.

Results

Diversity of synthetic communities.

The first aim of the present study was to evaluate whether the pyrosequencing technology applied to analyze the sequence feature composition of recA amplicons would provide relevant data to analyze the microdiversity of Agrobacterium spp. In a first step, we used synthetic communities to evaluate the methodology abilities and limits. In the second step, the methodology was used to analyze the diversity of field Agrobacterium communities and to test whether plant genotypes had a selective effect upon this diversity.

A great majority of sequence features obtained with synthetic communities were readily assigned to species that were used to construct synthetic communities since only 13/9195 (1.3‰) displayed less than 95% identity with any introduced species and were thus classified in the "undetermined Agrobacterium class" class (Table 2-4-2). This class was not an homogenous OTU, since it grouped unclassified sequences. Most of unclassified sequence features branched indeed at different places of the Agrobacterium phylogenic tree. These sequences were "single singletons" that occurred only once in a single synthetic community. Even if no experimental data supports our assumption, we assumed that "single singletons" resulted by chance from stochastic errors occurring during PCR and/or sequencing and constituted the background noise of the methodology. Due to this background noise, the methodology could lead to false detections of species that were readily absent in communities. For this reason, species occurring as single singletons in an analysis were considered as falsely detected and removed of subsequent community analyses.

At the infra-specific level, 6196 sequence features (67%) were assigned to one of the introduced alleles by using the 0-1% divergence criterion (Table 2-4-2). Conversely, numerous sequences were not assigned to any introduced allele even if they were could be assigned to introduce species. This showed a severe limit of the methodology, which confidently allowed the assignation of sequence features at the species level but difficultly at the allele level. In further studies, we only investigated the species status revealed by sequence features.

Comparisons of observed and expected occurrence of species in synthetic communities.

As a general feature, there was a rather good agreement between observed and expected species frequency distributions (Fig. 2-4-1). This was particularly verified for the most dominant species that actually dominated in all communities. Discrepancies occurred however with A. rubi, A. larrymoorei, A. sp. 1650 and A. undicola thar were poorly or not detected at all. Control PCRs using the community DNAs with primers targeting the same recA region showed that A. rubi and A. sp. 1650 were present. A. larrymoorei was not amplified as expected. Nevertheless, for unknown reasons, A. undicola also failed to amplify with these primers, but was detected by using A. undicola specific primers defined in Chapter 2-2. This suggested that the lack of A.

undicola sequences was caused by an unexpected mutation but was not related to a particular limitation of the method. Except these particular cases, the species distribution shapes were grossly the same between introduced and analyzed community, showing that the approach could be used to give a snapshot of the Agrobacterium species distribution in a community. Finally, as a rule of thumb, species of the A. tumefaciens complex were always detected if a minimum of 4 sequence features were expected.

Agrobacterium diversity assessment in a model field plot.

Amplicons obtained with metagenomic DNAs of the Chbika-1 station (Cf. Chapter 2-3) delivered sequences that generally matched with known Agrobacterium species (Table 2-4-3), but an important set of sequences found in the sample TG9-BS did not match with any known Agrobacterium or Rhizobium species. These unclassified sequences were almost identical and showed a best identity of 87% with A. sp. 1650, suggesting they originate from the same species closely related but different of presently known Agrobacterium. As a result, the "unclassified

Agrobacterium" class corresponded to a bona fide OTU. Similarly, the "undetermined Rhizobium" was an OTU for a single Rhizobium species related to R. loessense. These OTUs were kept in further analyses. Statistical analyses including principal component analysis (PCA) performed to compare bulk and rhizosphere soils (i.e. soil compartment), or to analyze effect of sample field geographic positions, showed that these parameters had no significant effect on sample species contents (data not shown). This result indicated indeed that the 19 samples were independent replicates of the Chbika-1 community.

From those analyses, the Agrobacterium species richness of Chbika-1 consisted in 13

Agrobacterium and 1 Rhizobium species. The number of species detected per sample varied from 1 to 6. Conversely, species were detected in only one sample for six species (undertermined Rhizobium, A. sp. 1650, A. undicola, G3, G6, G9), while G14 was detected in 12/19 samples (Table 2-4-3). The latter species was the most prevalent in the Chbika-1 station. Simulations

showed that dominant and sub-dominant species found in more than one samples were obtained by analyzing ca. 10 samples in average (data not shown). As a consequence, a good estimate of In the present setting up of recA amplicon pyrosequencing for the purpose of Agrobacterium microdiversity analysis, we verified that the methodology provided a relevant snapshot of the Agrobacterium community composition. Inherent limits of the methodology however allowed us to obtain relevant informations at the species but not at the allele levels. The methodology allowed detecting a species when at least 4 recA sequences were expected, while sequencing error could provide false sequences occurring as singleton. Thus, we proposed to consider a species as being readily present only at least 4 sequences of this species were detected.

Applied to environmental communities, the methodology revealed us the presence of up to 14 species in the model station of Chbika-1. While most species detected through the amplicon sequencing approach had been already detected by standard microbiology or by the cloningsequencing approach (Chapter 2-3), the most frequent species revealed by amplicon pyrosequencing was G14, a species never found previously. Investigations using G14-speciufic primers did not confirm the occurrence of this species in the Chbika-1 metagenomic DNA. We -89 -have no reasonable explanations for this strong discrepancy, leading us to consider cautiously the present Chbika-1 analysis.

Using various approaches, we did not find differences in the Agrobacterium species content of between bulk and rhizosphere soils in Chbika-1 (Chapter 2-3 and 2-4). This was very likely due to our compartment separation procedure that was used "bulk soils" that were harvested in the close vicinity of roots. Conversely, the compartment separation procedure used by A. Zancarini with M. truncatula was more stringent, and a clear difference between bulk and rhizosphere soils was thus obtained with her DNAs (Fig. 2-4-3). A third compartment, consisted of washed root tissue was also considered by A. Zancarini, but no significant differences were detected between these two plant relate compartment. Thanks two those DNAs, we were able to show that plant genotypes displayed significant different abilities toward the recruitment of Agrobacterium species. To our knowledge, this is the first report of such a plant effect upon the recruitment of very closely related bacterial species by very closely related plant genotypes. This finding is in agreement with the result of Zancarinbi et al. ( 2012), who showed clear community differences between the same M. truncatula genotypes using a taxonomically less resolutive but more general 16S based approach. The effect of different plants on agrobacterial diversity leads to forming different agrobacteria community in each rhizosphere depending on needs, completion, advantages or difficulties for each bacterial species. It conducts to preferential population formations in different rhizospheres, but also to differences according to soils. As showed by P. [START_REF] Portier | Sélection d'écotypes bactériens pathogènes et non-pathogènes par la plante en relation avec la différentiation en espèces génomiques chez Agrobacterium spp[END_REF], the rhizosphere of Medicago truncatula (Jemalong A17) was more favorable to G8 and G4 than to G1 members when grown in the French soil of La-Côte-Saint-André (LCSA).

Presently, in the soil of Mas d'Imbert, G8 members were found in the Jemalong rhizospher but it was sub-dominant compared to G1 and G4. As a consequence, question remains pending whether the plant selective effect found in the present study is caused by marked Agrobacteriumspecific traits or by characteristic traits of the sole agrobacterial strains present in Mas d'Imbert.

In conclusion, the recA amplicon-pyrosequencing approach is very promising tool to analyze environmental Agrobacterium species diversity. It allows the simultaneous and high throughput deliverance of relevant taxonomic data requested to study biotic and abiotic factors that are shaping agrobacterial populations. Amongst, the very promising way of research, the methodolology will permit to more clearly show how plant root systems is influencing this community.

microbiological and metagenomic methodologies to perform extensive Agrobacterium prevalence studies, to determine where and in which extent Agrobacterium is present everywhere.

From biodiversity studies on colonies isolated from Tunisian soils, only G4 and G7 agrobacteria were detected. This result was surprising because other species were very likely present in numerous soils, at least at Chbika-1 as previously described by [START_REF] Rhouma | Plasmid and chromosomal diversity of a Tunisian collection of Agrobacterium tumefaciens strains[END_REF] and Costechareyre et al. (2010). The unique presence of G4 and G7 amongst isolates could be an artifact due to faster growth speeds of G4 and G7 over other species. The question of Agrobacterium species growth speeds on 1A-Te medium should be addressed for all species as it could also have modified our view of Agrobacterium population diversity. This could explain some differences we obtained comparing biodiversity studies that were culture-dependant or culture-independent (chapters 2-2, 2-3 and 2-4 for A. tumefaciens G14). Interetingly, the fact that we got numerous isolates of the same species in very different locations is offering us the opportunity to address the novel question of the presence of unique strains of agrobacteria (of G4 or of G7) at a country scale. Information about the presence of a given strain at a country scale has great consequences for epidemilogical studies. Of course, reliable taxonomic identifications require further investigations such as the sequencing of other housekeeping genes, as proposed with the multi-locus sequencing analysis (MLSA) approach (Gevers et al., 2005;Costechareyre, 2008). Indeed, taxonomic identification based on a single gene could be incorrect in case of horizontal gene transfer (HGT) between strains of different species (a strain readily belonging to a given species may have acquired a foreign recA allele). Nevertheless, recA was not prone to interspecies HGT within the Agrobacterium tumefaciens complex. We are thus reasonably confident about the taxonomic assignations of agrobacteria when recA was used alone. Anyway, MLSA will be added in order to know whether G4 and G7 isolates belong to single clonal complexes or to markedly different strains. This population genetic information would help us to understand how far agrobacterial strain actually spread out of local stations such as tree nurseries.

Most species detected through the amplicon sequencing approach had been already detected by standard microbiology or by the cloning-sequencing approaches. The most frequent species revealed by amplicon pyrosequencing at Chbika-1 was G14, a species never found previously.

As mentioned above, we have no reasonable explanations for this strong discrepancy between isolation and metagenomic analysis especially for the present Chbika-1 samples. Concerning the -94 -isolation method, it is extremely important to go back to stations and look for G14 isolates using specific-primers. We propose here to use both isolation and metagenomic methods by keeping selective media at 28°C during the selection of well isolated agrobacteria in order to have metagenomic stocks for subsequent analyses. Metagenomic stocks must be later analysed using species-specific at first, or if needed by Agrobacterium-specific primers. This technique can assure us to have all of possible collected and grown agrobacteria on a plate that were selected or no via isolation methods.

The recA amplicon-pyrosequencing approach allowed us to show that plant genotypes displayed significant different abilities to recruit different species of Agrobacterium. This is the first report of a differential recruitment of Agrobacterium species by so closely related closely related plant genotypes. This finding is a complement and in agreement with results of Zancarini et al. (2012), who showed clear community differences between the same M. truncatula genotypes using a taxonomically less resolutive -but more general-16S rDNA based approach. The effect of different plants on agrobacterial diversity leading to forming different agrobacteria community in each rhizosphere depends on ecological needs, advantages or difficulties of each bacterial species. The soil itself is also strongly influencing the interaction between two partners (plant and bacteria), leading to tripartite interaction. [START_REF] Portier | Identification of genomic species in Agrobacterium biovar 1 by AFLP genomic markers[END_REF] showed that the rhizosphere of Medicago trucatula (Jemalong A17) was more favorable to G8 and G4 than to G1 members when grown in the soil of La-Côte-Saint-André. However, from our present study, with the soil of Mas d'Imbert, G8 members were detected in the rhizosphere of Jemalong but this latter species was sub-dominant compared to G1 and G4. Those results may have been influenced by different methods used in the two studies, microbial approaches via isolation and metagenomic approaches. As a consequence, question remains pending whether the plant selective effect found in the present study is caused by marked Agrobacterium-specific traits or by characteristic traits of the sole agrobacterial strains present in Mas d'Imbert.

We found no Ti plasmid harboring agrobacteria among isolates, confirming that Ti plasmid-free agrobacteria are prevalent in all tested soils. Conversely, we detected Ti plasmid signature in many soil community DNAs. However, those so-called Ti plasmid-specific primers indeed detected vir homologous sequences in non-agronomic soils that had no reported history of crown gall infestations and conversely not in visually crown gall infested orchards. In any cases, if primers readily detected Ti plasmids, results would suggest a wide dispersal of pathogenic agrobacteria in numerous soils. This is an unexpected and surprising result that absolutely -95 -requires additional investigations for definitive conclusions. We need therefore to isolate pathogenic agrobacteria from stations to ascertain this result by testing the pathogenicity of those newly isolated agrobacteria. Nevertheless, this unexpected result could be an indication that vir (1994) and Pionnat et al. (1999). In fine, pathogenicity testing on indicator plants is the ultimate and definitive clue for the presence of viable and pathogenic agrobacteria. Nonetheless, direct PCRs remain faster. To gain in significance, we propose thus to use multiplex PCRs targetting vir plus other Ti plasmid-specific regions to achieve trustable Ti plasmid detection.

In conclusion, we have reviewed the Agrobacterium taxonomy and the methods used to isolate, type strains and determine species of Agrobacterium. This has highlighted the need to improve and develop new tools that would be valuable to perform large scale studies on Agobacterium populations. Tools were thus developped for studing isolates (MALDI-TOF MS and recA primers) but also to asses Agrobacterium diversity from metagenomic DNAs. Coupled with a cloning-sequencing approach, primers targeting superior taxa allow easy and affordable investigations of Agrobacterium and Rhizobiaceae microdiversity. The recA ampliconpyrosequencing approach was found very promising to assess the environmental diversity of Agrobacterium populations. Alternatively, we could indeed imagine that sequencing the whole metagenomic DNA is a better and richer alternative providing much more information about the role of abiotic and biotic factors, since this approach is thought to provide the real genomic diversityof an ecosystem. Nevertheless, the complete DNA sequencing of a soil is still expensive and would require a lot of times for analysis... for perhaps lesser results concerning our interested object! Indeed, due to the extreme abundance of metagenomic data it is likely that relevant informations concerning only a target taxon-such as Agrobacterium spp.-would be very highly diluted and thus less accessible than with targeted approaches such as those developped in -96 -the present thesis. Indeed, with this limited approach, we were able to evaluate the Agrobacteirum diversity from a model field soil of Tunisian and from rhizospheres allowing us to draw new hypothesis about Agrobacterium prevalence in soils. Those results need to be confirmed by studies at larger scales. The technology for simultaneous and high throughput deliverance of relevant taxonomic data requested to study biotic and abiotic factors that are shaping agrobacterial populations is now available. Amongst, results obtained during our thesis, the plant genotype effect upon the differential recruitment of agrobacteria in root systems appears us a promising way for further researches in Agrobacterium agro-ecology.

Assessing the diversity of agrobacterial populations

Figure 2 - 1 - 1 .

 211 Figure 2-1-1. Sequence of identification by MALDI-TOF mass spectrometry of a bacterial colony in a clinical microbiology laboratory. (Photographs: Olivier Gaillot, Laboratoire de bactériologie-hygiène, CHRU de Lille)

Figure 2 - 1 - 2 .

 212 Figure 2-1-2. Typical MALDI-TOF MS spectra of Agrobacterium species. A. tumefaciens ICPB TT111 (G1), A. tumefaciens CIP 497-74 (G2), A. tumefaciens CIP 107443 (G3), A. tumefaciens Kerr 14 (G4) and A. tumefaciens CIP 107444 (G5. Absolute intensity of ions (mV) is shown on the y axis and the masses (in Daltons) of the ions are shown on the x axis. The m/z values represent mass-to-charge ratios. The biomarker masses identified in this work are indicated with vertical dashed lines.

Figure

  Figure 2-1-3'. Similarity analysis of whole cell MALDI-TOF MS protein mass fingerprints for strains of Agrobacterium species and related taxa. C58 and C58 derivatives were in red, and Ti plasmid free C58 derivative were in bold. G1-G9, A. tumefaciens genomic species. Corrected version.

Figure 2 - 2 - 1 .

 221 Figure 2-2-1. Specificity of G2-specific primers F6786-F6790.PCRs were performed with template DNAs extracted from strains that had different G2 recA alleles or from other species. G1, TT111; 1, Bernaerts L2/2/1 (recA-G2-1); 2, Bernaerts M 2/1 (recA-G2-2); 3, CIP 497-74 (recA-G2-3); 4, CIP 28-75 (recA-G2-4); 5, CIP 43-76 (recA-G2-5); G3, CIP 107443; G4, B6; G5, CIP 107445; G6, NCPPB 925; G7, RV3; G8, C58; G9, Hayward 0362; G13, PGF 01-22; Aru, A rubi LMG 17935 T ; T-, negative control; M, 1 kb+ Invitrogen DNA marker.

Figure 2 -

 2 Figure 2-2-2. Specificity of amplification with species-specific primers. PCRs were performed with species-specific primers and DNA mixtures containing (1) or not containing (2) target species DNAs or without DNA (3). Species-specific primers used are specified on the figure. DNAs used for DNA mixture preparation were extracted from TT111 (G1 species), Bernaerts L2/2/1 (G2); CIP 107443 (G3); B6 (G4); CIP 107445 (G5); NCPPB 925 (G6); RV3 (G7); C58 (G8); Hayward (G9); PGF 01-22 (G13); M, 1kb+ Invitrogen .

Figure 2 -

 2 Figure 2-2-3. Absence of aspecific amplification in the presence of a composite DNA using species-specific primers.PCRs were performed with species-specific primers using a complex synthetic community DNA as template[START_REF]tumefaciens Zutra 3/1 {recA-G7-3[END_REF] or the DNA of a representative of target species as positive control (2) or without DNA as negative control (3). Species-specific primers used are specified above wells. The list of DNAs used as positive controls are presented in Fig.2-2-1. The composition of synthetic community is indicated Table 2-2-2. M, 1kb+ Invitrogen DNA marker.

Figure 2 -

 2 Figure 2-2-4. Range of species amplified using Agrobacterium-specific primers F8360-F8361 (A) or Rhizobiaceace-specific primers F7386-F7387 (B). G1, TT111; G2, CIP 497-74; G3, CIP 107443; G4, B6; G5, CIP 107445; G6, NCPPB 925; G7, RV3; G8, C58; G9, Hayward 0362; G13, PGF 01-22; Ala, Fb33 (A. larrymoorei); Aru, LMG 17935 (A. rubi ); Ask, Ch11 (A. skierniewicense); 1650, NCPPB 1650 (A. sp); Avi, K309 T (A.vitis); Aun, ORS 992 (A.undicola); Rrh, K84 (R.rhizogenes); Rle, A34 (R. leguminosarum); Ret, CFN 42 T (R.etli); Eme, RM1021 (E.meliloti); Mhu, Mesorhizobium huakuii; Azo, B510 (Azospirillum sp.); Pse, A1032 (Pseudomonas sp.); T-, negative control; M, 1kb+ Invitrogen DNA marker.

Figure 2 -

 2 Figure 2-2-5. Phylogenetic position of recA sequence features delivered by cloning-sequencing of an amplicon obtained using Rhizobiaceae-specific primers F7386-F7387 with an environmental DNA extracted from a Poaceae rhizosphere community.The maximum-likelihood method (ln(L)=-15771.8, 1101 sites, GTR 4 rate classes) was used to analyze recA sequences obtained by cloning-sequencing (red) or from GenBank selecting one sequence per Rhizobiaceae species (black). B., Bradyrhizobium; Rh., Rhodoposeudomonas Az., Azorhizobium; R., Rhizobium; E., Ensifer; Avi, Agrobacterium vitis; Aun, Allorhizobium undicola; Aru, A. rubi; 1650, A. sp.; Ask, A. skierniewicense; G1 to G14, A. tumefaciens genomovars; G14, A. nepotum; G4, A. radiobacter; G2, A. pusense; G8, A. fabrum. Double arrow indicates Rhizobiaceae potentially amplifiable with Rhizobiaceae-specific primers F7386-F7387. Single arrow indicates the main species subset amplified using Agrobacterium-specific primers F8360-F8361. Numbers indicates clade probabilities. Branch length unit: number of substitutions per nucleotidic site.

Figure 2 - 3 - 1 .

 231 Figure 2-3-1. Location of soils selected for assessing the agrobacterial diversity at a country scale. A) Location on the Tunisian map. red, selected locations; green, Chbika (Kairouan governorate). B) GPS coordinates (decimal degrees) of locations.

Figure 2 -

 2 Figure 2-3-2. Medicago truncatula genotype Jemalong A17 seedlings after 3 weeks of growth.

Figure 2 -

 2 Figure 2-3-3. PCR amplification in metagenomic DNA from Chbika using A. vitis-specific primers (G0004-G0005). °, Bulk soil; , rhizopsheric soil; T-, negative control; K309T, A. vitis; M, 1kb + Invitrogen DNA marker.

Figure 2 - 4 - 1 .

 241 Figure 2-4-1. Observed and expected occurrence of Agrobacterium species in synthetic communities as given by multiplex pyrosequencing of a recA amplicon. Expected (red). Observed (blue). Axis: Agrobacterium species. Ordinate: log of sequence occurrence in amplicons. Bars indicate the 5% confidence interval for expected data.

  primers do not target only Ti plasmids. Of course, Ti plasmid detection in metagenomic condition is risky and it is shown clearly by Yakabe et al. (2012). Indeed, vir genes have homologous in many plasmids especially in Rhizobiaceae. Due to this homology and also to horizontal gene transfer (HGT) between plasmids it is likely that vir primers might sometime hybridize non-Ti plasmids. Alternatively, designing new conserved primers targeting other Ti plasmid-specific regions would allow the unambiguously detection of pTi from genomic DNA, as it is made for strain with MLSA technique. Conserved T-DNA regions might be used for this purpose, targeting for instance the oncogene region as early proposed by Ponsonnet and Nesme

RESUME

  Les bactéries du genre Agrobacterium forment un ensemble taxonomiquement diversifié composé de nombreuses espèces, présent dans la plupart des sols et dans la rhizosphère des plantes. Les agrobactéries sont le plus souvent anodines voire stimulatrices de la croissance des plantes mais celles qui hébergent un plasmide Ti induisent la maladie de la galle du collet à de nombreuses plantes d'intérêt agronomique. Les plasmides Ti peuvent se transmettre par conjugaison aux autres agrobactéries qui deviennent à leur tour pathogènes. Ainsi, du point de vue écologique comme du point de vue épidémiologique, il est impératif de connaître la diversité des populations d'agrobactéries du sol, hôtes potentiels des plasmides Ti. Dans ce contexte, nous avons dans notre travail de thèse d'une part repréciser l'état actuel des connaissances sur la taxonomie du genre Agrobacterium, et nous avons fait une revue des méthodes d'isolement et de typage de ces bactéries. D'autre part, nous avons cherché à mettre au point des méthodes d'identification rapides et fiables des différentes espèces. Une première méthode est basée sur la technique MALDI-TOF MS. Elle permet d'identifier facilement les espèces de bactéries cultivées mais la méthode n'est pas assez résolutive pour typer des souches et encore moins la présence de plasmides Ti dans les isolats. Nous avons alors développé des amorces de PCR spécifiques de chaque espèces (17), pour le genre Agrobacterium et la famille Rhizobiaceae. Ces amorces se sont révélées efficaces pour identifier les bactéries cultivées mais aussi pour détecter leur présence dans des communautés microbiennes. Nous avons ensuite utilisé ces outils pour étudier la répartition des agrobactéries à l'échelle d'un pays, d'une station et entre sols nus et sols rhizosphériques en utilisant soit des isolats soit des ADN métagénomiques extraits des différents environnements. Enfin, nous avons montré que le clonage-séquençage ou le séquençage à haut débit d'amplicons obtenus à partir d'ADN de communautés microbiennes nous permettaient de connaître facilement et avec une grande profondeur la diversité des populations d'agrobactéries. Les outils que nous avons développés sont fiables et faciles d'accès. Ils permettront d'étudier l'effet des facteurs de l'environnement sur la structure génétique des populations d'Agrobacterium pour répondre, par exemple, à la question de l'effet sélectif des plantes sur les espèces d'agrobactéries du sol recrutées dans la rhizosphère. d'espèces, identification, détection, biodiversité des agrobactériés INTITULET ET ADRESSE DU LABORATOIRE Ecologie Microbienne, UMR CNRS 5557 / USC INRA 1364 Université Claude Bernard Lyon 1, 16 rue R. Dubois, F-69622 Villeurbanne cedex, France

Table 1 -3-1. Agrobacterium diversity studies and taxonomic level of identification. Host Plant or Soil Work Technique °Taxonomic determination °

 1

		Otten et al., 1996	16S-23S intergenic spacer region	Strain
	Grapevines	Ridé et al., 2000	Phenotypic tests, Plasmid typing	Biovar
	Vitis Vinifera	Szegedi and Bottka, 2002	PCR on; Polygalacturonase primers and PTi	Biovar
		Kawaguchi et al., 2005	Multiplex PCR (16S rDNA+VirC1-VirC2)	Biovar
		Kawaguchi et al., 2008	rep-PCR, MLSA, Serological tests	Strain
		Palacio-Bielsa et al., 2009	16S rRNA sequencing, PCR on Ti Plasmid	Strain
		Kawaguchi, 2011	MLSA	Strain
	Poplar
	Ppoulus (Leuce section)

Table 2 -1-1. Strains and species used in this study.

 2

	Strain designation a	Other designation(s) a	Country b	AFLP c	recA allele d
	A. tumefaciens genomovar G1
	ICPB TT111	CFBP 5767/LMG 196	USA	G1	recA-G1-1
	S377	CFBP 5768/LMG 326	N/A	G1	recA-G1-1
	ATCC 4720	CFBP 5493/LMG 182	USA	G1	recA-G1-1
	NCPPB 396	CFBP 5765/LMG 176	Germany	G1	recA-G1-2
	CFBP 5771		France	G1	recA-G1-2
	S56	CFBP 5491/LMG 321	N/A	G1	recA-G1-3
	S4	CFBP 5492/LMG 318	N/A	G1	recA-G1-3
	CFBP 5622		France	G1	recA-G1-4
	CFBP 2712		France	G1	recA-G1-5
	CFBP 2517		France	G1	recA-G1-6
	CFBP 7067		France	ND	recA-G1-7
	CFBP 7064		France	ND	recA-G1-8
	CFBP 7066		France	ND	recA-G1-9
	Fb243	CFBP 5479	Italy	G1	recA-G1-10

A. tumefaciens genomovar G2 (A. pusense)

	Zutra F/1	CFBP 5877/LMG 296	Israel		G6	recA-G6-1
	AR125			Tunisia		G6	recA-G6-1
	A. tumefaciens genomovar G7
	RV3	CFBP 5500/LMG 317	N/A		G7	recA-G7-1
	NCPPB 1641	CFBP 5502/LMG 228	UK		G7	recA-G7-2
	Zutra 3/1	CFBP 6999/LMG 198	Israel		G7	recA-G7-3
	DC07-042	CFBP 7274		Tunisia		ND	recA-G7-3
	AR78 OR GF78	CFBP 7001		Tunisia		G7	recA-G7-4
	AR29	CFBP 7125		Tunisia		G7	recA-G7-5
	AR94	CFBP 7127		Tunisia		G7	recA-G7-6
	AR92	CFBP 7124		Tunisia		G7	recA-G7-7
	AR118	CFBP 7129		Tunisia		G7	recA-G7-8
	CH6	CFBP 7198		Tunisia		ND	recA-G7-9
	DC07-029	CFBP 7200		Tunisia		ND	recA-G7-10
	A. tumefaciens genomovar G8 (A. fabrum)
	ICPB TT9	CFBP 5504/LMG 64		USA		G8	recA-G8-1
	T37	CFBP 5503/LMG 332	USA		G8	recA-G8-1
	J-07	CFBP 5773		France		G8	recA-G8-1
	Mushin 6	CFBP 6550/LMG 201	Australia		G8	recA-G8-1
	LMG 75	CFBP 6549		USA		G8	recA-G8-2
	Bernaerts L2/2/1 LMG 46	CFBP 5875/LMG 146 CFBP 6554	Belgium USA	ND	G8	recA-G2-1 recA-G8-3
	Bernaerts M 2/1 C58 *	CFBP 5876/LMG 147 CFBP 1903/LMG 287 Belgium USA	G2	G8	recA-G2-2 recA-G8-4
	CIP 497-74 AW137	CFBP 5494/CFBP 2884 LMG R-10181	France	N/A	G2	G8	recA-G2-3 recA-G8-4
	CIP 28-75 DC07-004	CFBP 5495 CFBP 7272	France	Tunisia	G2	ND	recA-G2-4 recA-G8-4
	CIP 43-76 MKS-01	CFBP 5496	France	France	G2	ND	recA-G2-5 recA-G8-5
	MKS-03		France		ND		recA-G2-7
	A. tumefaciens genomovar G9
	A. tumefaciens genomovar G3 Hayward 0362	CFBP 5507/LMG 26		Australia		G9	recA-G9-1
	CIP 107443 Hayward 0363	CFBP 6623/CIP 493-74 CFBP 5506/LMG 27	France	Australia	G3	G9	recA-G3-1 recA-G9-2
	CIP 107442	CFBP 6624/CIP 111-78	France		G3		recA-G3-2
	A. tumefaciens genomovar G13
	A. tumefaciens genomovar G4 (A. radiobacter) PGF 01-22 CFBP 6927		France		G13	recA-G13-1
	B6*	CFBP 2413/LMG 187	USA		G4		recA-G4-1
	CIP 67-1	Strain B6 at CIP	USA		G4		recA-G4-1
	ATCC 4452	CFBP 5766/LMG 181	USA		G4		recA-G4-1
	DC07-012	CFBP 7273	Tunisia	ND		recA-G4-1
	ATCC 4718	CFBP 5764/LMG 139	USA		G4		recA-G4-2
	ATCC 19358 T	CFBP 5522/LMG 140	N/A		G4		recA-G4-2
	CFBP 5621		France		G4		recA-G4-2
	LMG 340	CFBP 5769/ICPB TT11	USA		G4		recA-G4-2
	LMG 62	CFBP 5763/ICPB TR6	N/A		G4		recA-G4-2
	CFBP 5627		France		G4		recA-G4-2
	CFBP 2514		Spain		G4		recA-G4-2
	Kerr 14	CFBP 5761/LMG 15	Australia	G4		recA-G4-3
	Hayward 0322	CFBP 5770/LMG 1687	Australia	G4		recA-G4-3
	Myr3	CFBP 7128	Tunisia	G4		recA-G4-4
	AR9	CFBP 7126	Tunisia	G4		recA-G4-5
	CH14	CFBP 7199	Tunisia	ND		recA-G4-6
	A. tumefaciens genomovar G5
	CIP 107445	CFBP 6625/CIP 291-77	France		G5		recA-G5-1
	CIP 107444	CFBP 6626/CIP 120-78	France		G5		recA-G5-2
	A. tumefaciens genomovar G6
	NCPPB 925	CFBP 5499/LMG 225	South Africa	G6		recA-G6-1
		-29 -

A. tumefaciens genomovar G14 (A. nepotum) C3

	A. vitis
	K309 T	CFBP 5523/LMG 8750	Australia	A. vitis	recA-Avi-1
	AV08.155	CFBP 7224	France		ND	recA-Avi-1
	AV07.004	CFBP 7196	France		ND	recA-Avi-2
	AV08.011	CFBP 7228	France		ND	recA-Avi-3
	AV07.006	CFBP-LABO12945	France		ND	recA-Avi-4
	S4	CFBP2660	Hungary	ND	recA-Avi-5
	AV07.175	CFBP 7217	France		ND	recA-Avi-6
	AV07.147	CFBP 7216	France		ND	recA-Avi-7
	AV08.120	CFBP 7222	France		ND	recA-Avi-8
	AV08.017	CFBP 7218	France		ND	recA-Avi-9
	AV08.022	CFBP 7219	France		ND	recA-Avi-10
	AV08.007	CFBP-LABO13296	France		ND	recA-Avi-11
	AV08.013	CFBP-LABO13297	France		ND	recA-Avi-12
	AV08.214	CFBP-LABO13298	France		ND	recA-Avi-13
	AV09.020	CFBP-LABO13300	France		ND	recA-Avi-15
	AV07.018	CFBP-LABO13295	France		ND	recA-Avi-16
	AV08.172	CFBP-LABO13074	France		ND	recA-Avi-17
	AV08.260	CFBP-LABO13299	France		ND	recA-Avi-20
	Agrobacterium sp.
	NCPPB 1650	CFBP 4470	South Africa	ND	recA-1650-1
	CH11		Poland		ND	recA-CH11
	81K		Poland		ND	ND
	Rhizobium rhizogenes
	LMG 150 T	CFBP 2408/CFBP 5520	N/A		R. rhizogenes	recA-Rrh-1
	K84	CFBP 1937/LMG 138	Australia	R. rhizogenes	recA-Rrh-1
	Rhizobium etli CFN42 T	LMG 17827	Mexico	ND	recA-Ret-1
	Ensifer meliloti 1021		N/A		ND	recA-Eme-1
	Rhizobium undicola ORS 991	LMG 11874
	.4.1			Poland		G14	recA-G14-1
	A. larrymoorei
	AF 3.10 T	CFBP 5473/LMG 21410	USA		A. larrymoorei	recA-Ala-1
	Fb33	CFBP 5476		Italy		ND	recA-Ala-2
	Fb23	CFBP 5475		Italy		ND	recA-Ala-2
	Fb72	CFBP 5477		Italy		ND	recA-Ala-2
	LT4	CFBP 5480		Italy		ND	recA-Ala-3
	NL7	CFBP 5481		The Netherlands	ND	recA-Ala-4
	NL25	CFBP 5482		The Netherlands	ND	recA-Ala-4
	NL360D	CFBP 5483		The Netherlands	ND	recA-Ala-4
	A. rubi
	LMG 17935 T	CFBP 5509/CFBP 6448	USA		A. rubi	recA-Aru-1
	TR2	CFBP 999		USA		ND	recA-Aru-1
	LMG 294			N/A		ND	recA-Aru-2
		-30 -

Table 2 -1-2. C58 derivatives used to test plasmid content effect upon MALDI-TOF MS spectra.

 2

	C58 derivatives	Ti plasmid content	At plasmid content
	C58	pTiC58	pAtC58
	C58C1	No Ti plasmid	pAtC58
	CFBP 1896	pTiH100alpha	pAtC58
	CFBP 1897	pTiR10C21	pAtC58
	CFBP 1898	pTiA66	pAtC58
	GMI 9023	No Ti plasmid	NoAt plasmid
	UIA5	No Ti plasmid	No At plasmid
	AB 150	pTiC58	pAtC58
	AB 152	pTiC58	pAtC58
	AB 153	pTiC58	pAtC58
	AW137	pTiC58	pAtC58
	DC07-004

Table 2 -2-1. recA alleles of Agrobacterium spp. and related taxa used to design specific PCR primers. Allele name Allele reference strain CFBP / LMG n° Accession n° Length recA allele description Agrobacterium tumefaciens genomovar G1

 2

	recA-G1-1	ICPB TT111 *	CFBP 5767 / LMG 196	FM164286	969	Costechareyre et al., 2010
	recA-G1-2	CFBP 5771 *		FM164294	969	Costechareyre et al., 2010
	recA-G1-3	S56	CFBP 5491 / LMG 321	FM164289	969	Costechareyre et al., 2010
	recA-G1-4	CFBP 5622		FM164291	969	Costechareyre et al., 2010
	recA-G1-5	CFBP 2712		FM164292	969	Costechareyre et al., 2010
	recA-G1-6	CFBP 2517		FM164293	969	Costechareyre et al., 2010
	recA-G1-7	CFBP 7067		FM164295	969	Costechareyre et al., 2010
	recA-G1-8	CFBP 7064		FM164297	969	Costechareyre et al., 2010
	recA-G1-9	CFBP 7066		FM164298	969	Costechareyre et al., 2010
	recA-G1-10 Fb243 #	CFBP 5479	deposit in progress	966	This study
	recA-G1-11 H13-3	not available	AGROH133_07016 1092	Wibberg et al;, 2011
	recA-G1-12 Foundi	in progress at CFBP	deposit in progress	1092	This study
	recA-G1-13 5A	not available	AGVZ00000000	1092	Hao et al., 2012
	recA-G1-14 R-46040	not available	FR772678	550	De Meyer et al. (2011)
	A. tumefaciens genomovar G2 (A. pusense)
	recA-G2-1	Bernaerts L2/2/1	CFBP 5875 / LMG 146	FM164299	969	Costechareyre et al., 2010
	recA-G2-2	Bernaerts M 2/1	CFBP 5876 / LMG 147	FM164300	969	Costechareyre et al., 2010
	recA-G2-3	CIP 497-74 *	CFBP 5494 / CFBP 2884	FM164301	969	Costechareyre et al., 2010
	recA-G2-4	CIP 28-75 *	CFBP 5495	FM164302	969	Costechareyre et al., 2010
	recA-G2-5	CIP 43-76	CFBP 5496	FM164303	969	Costechareyre et al., 2010
	recA-G2-6	MKS-02 #	in progress at CFBP	deposit in progress	936	This study
	recA-G2-7	MKS-03 #	in progress at CFBP	deposit in progress	953	This study
	recA-G2-8	AGR20 #	in progress at CFBP	deposit in progress	969	This study
	A. tumefaciens genomovar G3
	recA-G3-1	CIP 107443 *	CFBP 6623 / CIP 493-74	FM164304	969	Costechareyre et al., 2010
	recA-G3-2	CIP 107442 *	CFBP 6624 / CIP 111-78	FM164305	969	Costechareyre et al., 2010
	A. tumefaciens genomovar G4 (A. radiobacter)
	recA-G4-1	B6 *	CFBP 2413 / LMG 187	FM164306	969	Costechareyre et al., 2010
	recA-G4-2	ATCC 19358 T	CFBP 5522 / LMG 140	FM164311	969	Costechareyre et al., 2010
	recA-G4-3	Kerr 14 *	CFBP 5761 / LMG 15	FM164309	969	Costechareyre et al., 2010
	recA-G4-4	Myr3	CFBP 7128	FM164334	969	Costechareyre et al., 2010
	recA-G4-5	AR9	CFBP 7126	FM164335	969	Costechareyre et al., 2010
	recA-G4-6	CH14	CFBP 7199	FN432354	969	Costechareyre et al., 2010
	A. tumefaciens genomovar G5
	recA-G5-1	CIP 107445 *	CFBP 6625	FM164317	969	Costechareyre et al., 2010
	recA-G5-2	CIP 107444 *	CFBP 6626	FM164318	969	Costechareyre et al., 2010
	recA-G5-3	F2	not available	AFSD00000000	1092	Li et al., 2011

. tumefaciens genomovar G14 (A. nepotum)

	A. skierniewicense
	recA-Ask-1	Ch11 T		CFBP 7420 / LMG 26191	HE610311	869	This study
	A. sp
	recA-1650-1 NCPPB 1650	CFBP 4470 / LMG 230	FN813466	896	Costechareyre et al., 2010
	A. vitis
	recA-Avi-1	K309 T *	CBP 5523 / LMG 8750	FR847962	957	This study
	recA-Avi-2	S4		not available	CP000633	1089	Slater et al., 2009
	recA-Avi-3	NKZ-2		not available	AB543861	437	Kawaguchi, 2011
	recA-Avi-4	IS552-1	not available	AB543847	437	Kawaguchi, 2011
	recA-Avi-5	G-Ag-67	not available	AB543860	437	Kawaguchi, 2011
	recA-Avi-6	UK-2		not available	AB543845	437	Kawaguchi, 2011
	recA-Avi-7	MAFF 211677	not available	AB543837	437	Kawaguchi, 2011
	recA-Avi-8	ARK-2		not available	AB608984	437	Kawaguchi, unpublished
	recA-Avi-9	VAR06-30	not available	AB285087	437	Kawaguchi, 2011
	Allorhizobium undicola
	recA-Aun-1 ORS 992 T	CFBP 6719 / LMG 11875	HE610313	760	This study
	Rhizobium rhizogenes
	recA-Rrh-1	K84 *		CFBP 1937	CP000628	1086	Slater et al., 2009
	R. leguminosarum
	recA-Rleg	3841 T		LMG 14904	AM236080	1095	Young et al., 2006
	R. etli
	recA-Ret-1	CFN42 T	LMG 17827	CP000133	1089	González et al., 2006
	Ensifer meliloti
	recA-Sme-1 RM 1021 *	LMG 4251	AL591688	1086	Galibert et al., 2001
	recA-G14-1 C3.4.1	in progress at CFBP	HE610312		740	This study
	recA-G14-2 AGR18 #	in progress at CFBP	deposit in progress	969	This study
	recA-G14-3 AGR19 #	in progress at CFBP	deposit in progress	969	This study
	A. larrymoorei
	recA-Ala-1	AF 3.10 T *	CFBP 5473	FN432355		966	Costechareyre et al., 2010
	recA-Ala-2	Fb33	CFBP 5476	FN432393		966	Costechareyre et al., 2010
	recA-Ala-3	LT4	CFBP 5480	FN813464		957	Costechareyre et al., 2010
	recA-Ala-4	NL7	CFBP 5481	FN813465		948	Costechareyre et al., 2010
	A. rubi
	recA-Aru-1	TR3 T *	CBP 5509 / LMG 17935	AM182122		498	Martens et al., 2007
	recA-Aru-2	Braun EU6	LMG 294	deposit in progress	852	This study
				-48 -

Table 2

 2

	-2-2 were designed by visual inspection of recA allele
	sequences aligned with BioEdit software (version 7.0.9.0). The level of specificity of each
	primer against currently known sequences was checked on line at NCBI
	(http://www.ncbi.nlm.nih.gov/) on the nucleotide collection (nr/nt) database with blastn
	(somewhat similar sequences) using 7 as word size.
	Standard PCRs were carried out in a 30 l reaction volume containing 2.4 mM MgCl 2 , 0.4 mM
	(each) dNTPs, 1U of Taq DNA polymerase (Invitrogen, France), 1 M of each primer and 30 ng

of DNA template. The optimal annealing temperatures of each primer set given in Table 2-2-2 were determined after running gradient PCRs using the Biometra TGradient Thermocycler. After

Table 2 -2-2. Species-, Agrobacterium-and Rhizobiaceae-specific primer sets. Forward primer Position Reverse primer Position Taxon bp °C Primer sets experimentally validated with target and non-target pure culture DNA and complex DNA mixtures

 2

	F7386	AGCAAGGCACTGGAAGCGG	49-67 F7387 CCATACATGATGTCGAATTC	808-827 Rhizobiaceae	779	52
	F8360	AGCTCGGTTCCAATGAAA	113-130 F8361 GCTTGCGCAGCGCCTGGCT	547-565 Agrobacterium	453	52
	F6782	CGTGGTTGAAGTAGAGACCA	132-151 F6786 TTTTCACGCCCCTGCCCCA	926-944 Genomovar G1	813	60
	F6790	TGACGCCGAACATGCGCTT	312-330 F6786 TTTTCACGCCCCTGCCCCA	926-944 Genomovar G2	633	67
	F8232	CGTTCGGCAAGGGATCGATC	89-108 F8227 CCGCGGCGTCAGTGCCGCG	471-489 Genomovar G3	401	65
	F8533	GCGTTCCGGTGCGGTTGATG	432-451 F8827 CACCTGCTTGAAGGGCGGA	789-807 Genomovar G4	511	60
	F8232	CGTTCGGCAAGGGATCGATC	89-108 F8228 AGCGTATCGGTGATTTCGAGG 408-428 Genomovar G5	290	60
	F8392	TATCGCGCTCGGTATCGGT	177-195 F8229 AGTCGACCACGAGCACGTCC	447-466 Genomovar G6	442	65
	F6788	TGGCATTGCAGACCATTGCC	257-276 F8413 CGAACGGACGCATAGAAC	681-698 Genomovar G7	502	60
	F6784	CGGTTGACGTTCTTGTCATCGAT 443-465 F6786 TTTTCACGCCCCTGCCCCA	926-944 Genomovar G8	502	60
	F8359	CTGCGCAAGCTGACGGCT	556-573 F8230 CACGCCGAGATCGACCAAC	852-870 Genomovar G9	315	65
	F8232	CGTTCGGCAAGGGATCGATC	231-249 F8231 GGACTTGGAGATCGAGGCT	570-588 Genomovar G13	358	60
	Primer

sets experimentally validated with target and non-target pure culture DNA

	F9033	GGTATCGGCGGTTTGCCGCG	187-206 F9034 TCTTGACGACCTTGACACG	760-778 Genomovar G14	592	67
	F9186	TTTCCACAGGGTCTCTCAGT	152-171 F9187 TCTCGCCTTCGATTTCCGCA	489-508 A. larrymoorei	357	60
	G0009	GTTCCAATGAAAGTATCGTC	119-138 G0001 GAAGACCCGGAAGGCTATCA 513-532 A. rubi	414	57
	G0006	CGGTAAGACAACGCTCGCT	243-261 G0007 CGCGTGTCTGGTTACCGACG	744-763 A. sp. 1650	530	60
	F9190	TGAGGTCGAGACCGTTTCTACA 138-159 G0008 CTTCGGGCGAACCGTAGGAA 636-655 A. skierniewicense 518	60
	G0002	TGAAAAGGTCGTGGAGATCGAT 126-147 G0003 TCAGTGCTGCAACGGAGTCA	462-481 A. undicola	356	60
	G0004	GATATCGCGCTCGGCATTGGT	175-195 G0005 CCTTCGATTTCAGCTTTCG	485-503 A. vitis	329	55

Table 5 . Agrobacterial species detected in an environmental community according to detection methods.

 5

	Detected species	Isolation	Cloning-sequencing	Direct PCR
			Rhizobiaceae	Agrobacterium
	A. tumefaciens G1	3	0	3	4/6
	A. tumefaciens G2	0	0	0	3/6
	A. tumefaciens G3	0	0	0	0/6
	A. tumefaciens G4	1	0	0	3/6
	A. tumefaciens G5	0	0	0	0/6
	A. tumefaciens G6	0	0	0	5/6
	A. tumefaciens G7	0	0	0	4/6
	A. tumefaciens G8	1	11	44	3/6
	A. tumefaciens G9	0	0	0	0/6
	A. tumefaciens G13	0	0	0	0/6
	Other Agrobacterium sp.	0	8	0	nt
	Rhizobium spp.	2	11	0	nt
	Numbers indicate the

-2-5). No other sequences gathered within the A. tumefaciens recA cluster. Seven sequences significantly gathered in the recA cluster grouping A. rubi, A. sp. NCPPB 1650, A. skierwienense and A. larrymoorei. All of these sequences were of bona fide Agrobacterium species but they were not from the A. tumefaciens species complex. Outside the Agrobacterium genus cluster, eight recA sequences gathered significantly with the cluster including Ensifer species, R. herbae and R. giardini, and three gathered with other Rhizobium species such as R. tubonenese, R. leguminosarum, or R. rhizogenes. As expected, none gathered outside of Rhizobiaceae. This clearly showed that all sequences obtained from an amplicon performed with Rhizobiaceae-specific primers could be readily assigned as bona fide Rhizobiaceae bacteria. In addition, as a remarkable biological result, with 62% of the sequences, G8 recA clearly dominated in the Rhizobiaceae community

Table 2 -3-1. Location of Tunisian samples used in this study.

 2

	Name	Station	Latitude	Longitude	Altitude
	TA1	OUDNA-1	36°38'06,0	10°07'41,0	60
	TA2	OUDNA-1	36°38'05,7	10°07'41,5
	TB1	OUDNA-2	36°37'03,4	10°08'39,1	65
	TB2	OUDNA-2	36°37'03,2	10°08'38,8
	TB3	OUDNA-2	36°37'02,3	10°08'36,1	64
	TB4	OUDNA-2	36°37'00,5	10°08'37,6	60
	TB5	OUDNA-2	36°37'00,9	10°08'40,7
	TB6	OUDNA-2	36°37'01,8	10°08'42,5	76
	TB7	OUDNA-2	36°37'03,4	10°08'41,7	73
	TB8	OUDNA-2	36°37'12,2	10°08'36,7
	TC1	ENFIDHA	36°06'06,4	10°23'12,2	21
	TC2	ENFIDHA	36°06'06,2	10°23'11,7	14
	TC3	ENFIDHA	36°06'06,2	10°23'10,9
	TD1	KONDAR	35°59'48,2	10°18'51,6	26
	TD2	KONDAR	35°59'47,2	10°18'51,4	25
	TD3	KONDAR	35°59'46,4	10°18'51,1	27
	TE1	MOTBASTA	35°46'47,6	10°08'05,6	31
	TE2	MOTBASTA	35°46'47,5	10°08'05,0	39
	TE3	MOTBASTA	35°46'47,2	10°08'04,1
	TF1	CHBIKA-1	35°37'04,8	09°55'05,3	131
	TG1	CHBIKA-1	35°37'04,5	09°55'05,4	130
	TG2	CHBIKA-1	35°37'05,0	09°55'05,7
	TG3	CHBIKA-1	35°37'05,6	09°55'06,1	125
	TG4	CHBIKA-1	35°37'06,2	09°55'06,6	124
	TG5	CHBIKA-1	35°37'06,8	09°55'07,0	127
	TG6	CHBIKA-1	35°37'05,4	09°55'08,2	122
	TG7	CHBIKA-1	35°37'05,6	09°55'07,5	124
	TG8	CHBIKA-1	35°37'05,8	09°55'06,7	125
	TG9	CHBIKA-1	35°37'05,9	09°55'06,0	125
	TG10	CHBIKA-1	35°37'06,2	09°55'05,1
	TH1	CHBIKA-2	35°37'05,0	09°55'03,6	125
	TH2	CHBIKA-2	35°37'05,6	09°55'01,9	126
	TH3	CHBIKA-2	35°37'06,6	09°54'59,4	127
	TH4	CHBIKA-2	35°37'04,0	09°55'00,0	125
	TH5	CHBIKA-2	35°37'07,2	09°55'02,0	124
	TI1	CHBIKA-3	35°37'07,3	09°54'46,3	130
	TI2	CHBIKA-3	35°37'07,8	09°54'46,1	124
	TI3	CHBIKA-3	35°37'08,6	09°54'45,8	131
	TI4	CHBIKA-3	35°37'08,4	09°54'45,5	125
	TI5	CHBIKA-3	35°37'12,7	09°54'45,3	130
	TI6	CHBIKA-3	35°37'12,6	09°54'44,8	127
	TJ1	CHBIKA-4	35°37'03,5	09°55'06,0	105
	TJ2	CHBIKA-4	35°37'03,1	09°55'07,5	132
	TJ3	CHBIKA-4	35°37'02,0	09°55'08,3	125
	TJ4	CHBIKA-4	35°37'01,0	09°55'09,5	130
	TK1	TAOUS	34°56'08,9	10°37'00,5	124
	TK2	TAOUS	34°56'07,7	10°37'00,5	112
	TK3	TAOUS	34°56'06,0	10°37'00,0	124
	TL1	MEZZOUNA	34°34'33,6	09°49'45,8	157
	TL2	MEZZOUNA	34°34'33,7	09°49'47,0	159
	TL3	MEZZOUNA	34°34'35,1	09°49'46,4	155
	TL4	MEZZOUNA	34°34'35,1	09°49'46,4
	TM1	TOZEUR-1	33°58'16,8	08°06'39,8	32

Table 2 -3-2. Number of isolates per Agrobacterium species Tunisian soils according to biotope compartments.

 2

	Biotope	Genomovar	Genomovar
		G4	G7	Total
	BS	48	18	66
	RS	49	17	66
	Total	97	35	132
	BS, bulk soil; RS, rhizopshere soil. Species identifications of bacterial isolates were done according to PCR results
	using G4 or G7 specific primers defined Chapter 2-2.

Table 2 -3-3. Distribution of Ti plasmid in Tunisian soils according to sampled biotopes.

 2

	Biotope	Vir+	Vir-	Total
	BS	21	45	66
	RS	15	51	66
	Total	36	96	132

BS, bulk soil; RS, rhizopsheric soil. Ti plasmid presence in metagenomic DNAs were inferred from PCR results using Ti plasmid sspecific primers described Chapter 1-1.

Table 2 -3-4. PCR based Ti plasmid detection in Tunisian soils.

 2

	Location	Soil characteristic	pTi ratio	sampling point
	Oudna-1	non agronomic soil	0/2
	Oudna-2	crown galled cherry orchard	0/9
	Enfidha	ploughed fallow soil (after cereal)	1/3	TC2
	Kondar	common olive orchard	1/3	TD2
	Motbasta	non agronomic salty soil	1/3	TE1
	Chbika-1	ploughed contaminated plot	7/11	TG1,2,3,5,6,7,8,10
	Chbika-2	ploughed plot	1/5	TH3
	Chbika-3	stone fruit tree nursery plot	1/6	TI5
	Chbika-4	olive orchard plot	3/4	TJ1,2,4
	Taous	olive orchard	1/3	TL2
	Mezzouna	stone fruit orchard	1/4	TK2
	Tozeur-1	non agronomic semi-arid soil	1/1	TM1
	Chott-El-Gharsa	non agronomic soil in arid zone	0/3
	Tozeur-2	hotel park soil	1/3	TN1
	Chebika oasis	oasis soil	2/4	T01,3
	Tozeur 3	palm tree orchard	0/3
	pTi ratio, Ti plasmid detection number per sampling point number.

  1 described Chapter 2-3. Metagenomic DNAs used to test the plant genotype effect upon Agrobacterium species recruitment in rhizospheres were a kind gift of A. Zancarini and C. Mougel (INRA, Dijon, France), who prepared DNAs as explained in Zancarini et al. (2012). Selected genotypes were two Algerian ecotypes DZA 045-6, DZA 315-16 and the standard line Jemalong A17. Plants were grown in a silt-clay loam soil from Mas d'Imbert (France). Investigated compartments were bulk and rhizosphere soils, and root tissues.

Table 2

 2 100%, in the corresponding recA allele. Imax data were used to consctruct a contingency table giving the number of sequences per OTU of each sample.

	-3-1 using anl analysis pipeline set up by A. Chosson. If Imax < 90%,
	sequences were classified in the "unclassified Rhizobium" OTU class; if 90% Imax < 94%, in

Table 2 -4-4. Agrobacterium species occurrence in Medicago truncatula genotypes.

 2

	Sample Agrob 1650	G1	G3 G4	G8	G13 G14 Total
	211-R	0	0	1029	0	0	0	0	0	1029
	211-SR	0	0	1167	0	17	120	0	5	1309
	212-R	0	0	1004	0	18	0	0	358	1380
	212-SR	0	0	919	0	0	15	0	102	1036
	213-R	0	0	709	0	0	0	0	0	709
	213-SR	0	0	1462	0	33	21	0	3	1519
	217-R	0	0	752	0	18	36	0	0	806
	217-SR	0	0	417	34 141	29	0	0	621
	218-R	0	0	920	0	0	0	0	0	920
	218-SR	0	0	1597	0	2	58	0	0	1657
	219-R	0	0	950 428 25	0	0	167	1570
	219-SR	1	0	669	57	43	52	0	6	828
	235-R	0	0	217	0	170	0	0	202	589
	235-SR	0	0	127	45 126	0	0	25	323
	236-R	0	0	875	0	84	0	0	0	959
	236-SR	0	0	1029	0	339	0	0	153	1521
	237-R	0	0	2	0	355	0	0	0	357
	237-SR	0	0	426	0	141	31	0	165	763
	613S-N	2	0	3	2	490	5	1	4	507
	615S-N	111	0	962	0	0	1227	0	0	2300
	616S-N	0	0	0	249	0	0	652	0	901
	618S-N	0	8	1	0	0	0	0	835	844
	211, 212, 213: replicates of DZA 045-6. 217, 218, 219: replicates of DZA 315-16. 235, 236, 237: replicates of
	Jemalong A17.

R: root tissue; SR: rhizosphere soil; N: bulk soil of Mas d'Imbert.

exemplified by works ofPonsonnet (1994) Structure génétique des populations d'Agrobacterium. Apport à l'écologie des plasmids Ti. Thèse de doctorat, Université Claude Bernard Lyon 1.

taxonomic indications determined by ourself using nucleotide accessions provided in the cited paper.

id.

This study was done in collaboration with J. Pothier and B. Duffty in the frame of the European COST 873 action.

Microcosmes irrigated with 1 ml of sterile nutrient solution (N/P/K: 18/6/26 , Soluplant, Duclos

Acknowledgment

This work was supported by the EcoGenome project of Agence Nationale de la Recherche (grant number ANR-08-BLAN-0090). M.S. was supported by a CNRS contract in the framework of EcoGenome. The authors would like to thank R. Mhamdi and J. Pu awska for providing novel strains of novel species, P. Portier at CFBP (http://www-intranet.angers.inra. fr/cfbp/) for strain repository, and the translator Dr D. Manley for reading the manuscript and providing suggestions.

, Vial L. 1,2,3 , Chapulliot D. 1,2,3,4 , Nesme X. 1,2,3,4 , Lavire C.

Summary

Agrobacteria are common soil bacteria that interact with plants as commensals, plant growth promoting rhizobacteria or alternatively as pathogens. Understanding factors that shape their populations is a prerequisite for ecological studies. Indigenous agrobacterial populations are composites, generally with several species and strains per species. It would, however, be hard to thoroughly assess such diversity by standard microbial approaches. We therefore developed a recA-based PCR approach to accurately identify and specifically detect agrobacteria at various taxonomic levels. Specific primers were designed for the 16 bona fide genomic Agrobacterium species presently known, including 11 species of the Agrobacterium tumefaciens complex (G1-G9, G13 and G14), A. larrymoorei, A. rubi, A. skierniewicense, A. sp. 1650, and A. vitis, and for the close relative Alllorhizobium undicola. Specific primers were also designed for superior taxa, Agrobacterium spp. and the Rhizobiaceace family. Primer specificities were assessed with target and non-target pure culture DNAs as well as with DNAs extracted from composite agrobacterial communities. In addition, we showed that the amplicon cloning-sequencing approach used with Agrobacterium-specific or Rhizobiaceae-specific primers is a way to assess the agrobacterial diversity of an indigenous agrobacterial population. Hence, the Agrobacterium-specific primers designed in the present study enabled the first accurate and rapid identification of all Agrobacterium species, as well as their direct detection in environmental samples. Analysis of recA-amplicon compositions thus provides a way to accurately and exhaustively assess agrobacterial diversity in various biotopes for ecological, agro-ecological and epidemiological studies. amplified from this rhizosphere, while no R. rhizogenes sequences (e.g. biovar 2 agrobacteria) were found.

Table 2-2-3 -------------------F6786-F6790 -+ -------------------F8227-F8232 --+ ------------------F8533-F8827 ---+ -----------------F8228-F8232 ----+ ----------------F8229-F8392 -----+ ---------------F6788-F8413 ------+ ------------- ----------+ ---------G0009-G0001 ------------+ --------G0006-G0007 -------------+ -------F9190-G0008 --------------+ ------G0002-G0003 ---------------+ -----G0004-G0005 ----------------+ ----G1 to G9, G13 and G14 indicate species of the A. tumefaciens complex. Ala, A. larrymoorei;A r u , A. rubi;A s p , NCPPB 1650; Aun, A. undicola;A v i , A. vitis;R r h , R. Rhizogenes;R e t , R. etli;R l e , R. leguminosarum;E m e , E. meliloti. For PCRs performed with annealing temperatures indicated in Table 2: +, yielded a fragment of the expected length with all alleles described; (+), yielded a fragment of the expected length with all alleles described except for AF3.10 (recA-Ala-1) that required a lower temperature for reliable amplifications; -, no amplification.

In a second step, screening for particular recA alleles in the metagenomic DNA was performed using the cloning-sequencing approach with Agrobacterium-specific primers. From the 47 sequences obtained 44 (93.6%) were identical and showed 100% identity with recA-G8-1 (or recA-G8-3 because these two alleles are identical in the short 453 bp region targeted by F8360 and F8361), one was identical to recA-G1-7, and two were identical to recA-G1-14. All sequences obtained are in agreement with primers specificities. Notably, Bellerophon detected no chimera among the recA sequence sets obtained from this community (probably because the environmental communities were far less diversified than the synthetic one tested above and thus less prone to chimera formation). recA-G2-4 Agrobacteria isolated from the rhizosphere using the A. tumefaciens-elective 1A-Te medium of [START_REF] Mougel | Novel tellurite-amended media and specific chromosomal and Ti plasmid probes for direct analysis of soil populations of Agrobacterium biovars 1 and 2[END_REF] were first presumptively assigned as G1 bacteria, G4 and G8 using speciesspecific primers described in Table 2. Amplicon sequencings then confirmed these previous species assignments, and allowed us to identify the presence of alleles recA-G1-6, recA-G4-2 and recA-G8-5 amongst isolates (data not shown).

Chapter 2-3

Assessing the presence of agrobacteria and Ti plasmids in soil at a country scale.

compartment difference, the two samples of a given microcosme should be considered as simple replicates of the same soil community. If so, results however showed a high reliability of results obtained with two independent metagenomic DNAs extracted from the same community sampled corresponding to the microcosme scale.

Chapter 2-4

Assessing the pyrosequencing approach to analyze Agrobacterium microdiversity 5 In preceding chapters, we showed that analyzing the sequence composition of amplicons obtained from composite communities is a way to determine their taxonomic compositions. In these works, internal amplicon compositions were analyzed using the cloning-sequencing approach. The method was found relevant as it revealed the actual composition of synthetic communities of known taxonomic composition (Chapter 2-3). This methodology is nevertheless limited by the number of clones that can be reasonably sequenced for a given, community (i.e. 50-100 at the best), hampering therefore the comparison of multiple communities.

Conversely, the new genome sequencing (NGS) technologies provide thousands of reads in a single run. Coupled with multiplexing NGSs allowed the simultaneous sequencing of numerous pooled samples and noticeably of pooled amplicons. NGSs therefore offer the scope for the development of affordable high throughput analysis of multiple communities. The present limit of NGSs is the maximum length of DNA fragment that can be sequenced. Indeed, sequence features must be long enough to carry enough evolutive informations for subsequent phylogenetic treatments. In this respect, the best methodology to date is the pyrosequencing technology with Titanium chemistry that permits the sequencing of DNA fragments of 450 bp.

Hence, we designed Agrobacterium specific primers F8360 and F8361 described Chapter 2-2 precisely taking into account this technical constraint.

In the present work, we aimed at setting up and assessing the pyrosequencing approach to analyse agrobacterial microdiversity. For this purpose: i) we analyzed the sequence composition of amplicons obtained with communities of known taxonomic compositions; ii) we then used the approach to deliver an exhaustive investigation of a field agrobacterial community (i.e. Chbika-1) and to test whether plant genotypes had an effect upon agrobacteria recruited in rhizospheres.

Material and methods

Synthetic communities

To construct synthetic communities of known species allelic compositions, suspensions of overnight bacterial culture in standard LPG adjusted to the same OD 600 of 0.6 were assembled in defined quantities. These quantities were chosen in order to construct two kind of communities distinguished by their patterns of taxon density distribution. A first set, namely communities CS1 and CS2, were constructed with taxon densities distributed according to a "broken stick" model in which a small number of taxa strongly dominated numerous other taxa present at low and equivalent frequencies. A second set, namely communities CS3 and CS4, were constructed with the Agrobacterium species diversity for a field such as Chbika-1 would be obtained by analyzing the composition of 9 amplicons that could be obtained by sequencing three independent pools of three amplicons for each. A. tumefaciens G1 to G13, genomospecies of the Agrobacterium tumefaciens species complex (Lindström and Young, 2012).

-85 -

Plant genotype effect upon the Agrobacterium diversity of root inhabiting bacterial communities.

Height species were detected in the soil metagenomics DNA of Mas d'Imbert used to grow M. truncatula genotypes (Table 2-4-4). Five species dominated in plant compartments over the bulk soil, but no significant differences were observed between Rhizosphere soil and soil tissue communities. Later data were thus assembled in subsequent analyses. The Agrobacterium species relative abundance significantly varied according to plant genotypes (Fig. 2-4-3). G1 was preferentially recruited in the root systems of Algerian ecotypes DZA 045-6 and DZA 315-16, while these genotypes poorly recruited GA members. Conversely, Jemalong A17, recruited equivalent amounts of G1 and G4. This suggested that Jemalong A17 was more tolerant than Algerian ecotypes toward the recruitment of G4 members. Sample plots TG1 to TG10, with bulk (BS) or rhizosphere (RS) soils were as described Chapter 2-4. Agro: "unclassified Agrobacterium" sequences detected at TG9-BS had the same sequence with a best identity of 87% with A. sp. 1650, forming a single OTU for a single bona fide Agrobacterium species. Rhizo: "unclassified Rhizobium" sequences detected at TG8-BS had the same sequence with a best identity of 88% with R. loessense, forming a single OTU for a single bona fide Rhizobium species -87 -

Discussion

The pyrosequencing technology allowed us to sequence numerous individual PCR fragments of composite PCR products obtained with metagenomic DNAs extracted from complex communities. In this approach each individual pyrosequence was assumed to arise from a single cell and the relative number of fragments with identical sequences is assumed to be a measure of the relative abundance of cells harboring this sequence in the part of the community whose recA was amplifiable with the concerned primers. While, the pyrosequencing technology allowed to deliver huge numbers of individual sequences, it is however unnecessary to have huge numbers of sequences to analyze the species and allelic diversity of a taxon of limited extent such as Agrobacterium spp. Conversely, we needed to analyze and compare numerous communities.

Thus, we pooled and sequenced together numerous samples individually identified by tags (i.e.

MIDs).

Discussion and Perspectives

The genus Agrobacterium encompasses several species and several strains within species that are now clearly named using a novel nomenclature reviewed in chapter 1.1. In each population different techniques have been used to recognize their members. In the present experimental work, we have adapted several methodologies that have been set up by other researchers. We have also amended different techniques or developed new techniques to rapid and accurate identification of agrobacteria. We also studied aspects of agrobacterial life such as pathogenicity at a country scale or the role of plants on the composition of agrobacterial population.

To identify and study agrobacteria diversity, a set of efficient procedures is now available that can be used on pure culture isolates as well as on agrobacteria directly in soil microbiomes. These methodologies are necessary to unmask the ecologies of Agrobacterium species that usually live sympatrically in soils (Voget at al., 2003;Costechareyre et al., 2010).

We also used this methodology to look for a novel environmental strain of genomovar G8 in order to verify whether such a novel strain actually harbour the species-specific genes of this species. This was my contribution to the paper of Lasalle et al. (2011) given in annexe 3. We verified indeed that strain MKS-01, a novel isolate from LCSA assigned to G8 thanks to our G8specific primers harbored a novel recA allele (recA-G8-5), and had indeed the predicted G8specific genes in its genome. More generally, we are expecting that these knowledge will now allow us to differentially manage agrobacterial species in soils to decrease the crown gall disease impact as well as to stimulate agrobacteria having potential PGPR effects.

Among techniques that could be used for rapid identification of agrobacterial isolates, MALDI-TOF MS was evaluated and found to be suitable to delineate all Agrobacterium species.

By using this technique, we could identify Agrobacterium species undistinguishable by 16S rRNA sequencing. However the methodology still requires improvements, and the construction of a database that could allow the identification of mass peaks specific for each Agrobacterium species (i.e. a set of markers present in fingerprints of all strains from a given species). The MALDI-TOF MS technique is however not precise enough to discriminate strains within a species, and is thus not suitable for epidemiological studies. Unfortunately again, we did not found specific spectra for Ti plasmid even in presence of Ti plasmid protein production stimulator (Ferulic acid). We nevertheless think that this methodology can still be improved for this purpose. Results presented in this work showed that MALDI-TOF MS is a reliable and rapid method for agrobacterial identification at the species level, comparable to what is obtainable with housekeeping gene sequencing. This implies the implementation of a database and of course that laboratories have bought the MALDI-TOF apparatus. However those analyses can be externalize to companies or plate-form facilities owning this tehnology and expertise. Hence, MALDI-TOF MS open a new and very useful way for diversity and ecological studies applicable to analysis of large populations of isolates allowing the differentiation of species and genera of agrobacteria.

To achieve our dual objective of rapid agrobacterial species identification and agrobacterial diversity assessment in complex environments, we designed recA based-PCR primers with specificities at different taxonomic levels. This was possible thanks to the availability of numerous recA sequences longer than those usually found in databases (mostly from MLSA sequence data). Indeed, MLSA analysis generally delivered ca. 450-500 bp fragments which are not enough long to find suitable regions for primer designing. Such designing was also possible because recA allele sequences belonging to a given species show enough diversity among and great differences with other agrobacteria. Moreover, primers designed for superior taxa enabled the amplification of most species that were usually classified within Agrobacterium spp. or Rhizobiaceae members.

The microbiological approach used so far to identify Agrobacterium species is difficult to use for exhaustive investigations of the species composition of bacterial communities. Thanks to recA specific primers, it is now possible to achieve accurate and rapid first identifications of all Agrobacterium species in both pure cultures and complex environments. In chapter 2-3, we addressed the question of the presence of agrobacteria and Ti plasmids in soils at large scales.

Taken together, our results showed that agrobacteria and especially members of the A.

tumefaciens complex were present in all Tunisian soils we investigated so far. This result is remarkable and partly unexpected because some sampled soils were non-agronomic ones collected in extreme environments such as arid and salty areas. It is certainly too early to claim that agrobacteria are present in every soils on earth. However, as mentioned in chapter 1.3, bacteria closely related to A. tumefaciens complex were found in exotic samples such as deeply buried sediments of the eastern Pacific Ocean [START_REF] D'hondt | Distributions of microbial activities in deep subseafloor sediments[END_REF] or up to 200,000-year-old marine sapropels [START_REF] Süss | Widespread distribution and high abundance of Rhizobium radiobacter within Mediterranean subsurface sediments[END_REF]). The present study showed that we now have the suitable