M Joël Pothier

Rapporteur Mme

Céline Lavire

Rapporteure M Jean-Philippe

Examinateur Galaud

Emmanuelle Mme

Lauber

Julien S Luneau

Aude Cerutti

Brice Roux

Sébastien Carrère

Marie-Françoise Jardinaud

Antoine Gaillac

Carine Gris

Emmanuelle Lauber

Richard Berthomé

Matthieu Arlat

Alice Boulanger
email: alice.boulanger@inrae.fr

Laurent D Noël
email: laurent.noel@inrae.fr

Maël Baudin

Olivier Bouchez

Jonas François

Jayashree Ray

Babil Torralba

Jennifer D Lewis

Adam M Deutschbauer

Xanthomonas campestris transcriptome inside cauliflower hydathodes reveals virulence strategies and physiological adaptation during the biotrophic infection stage

Keywords: Xanthomonas campestris, hydathode, cauliflower, transcriptome, hrp gene cluster, type III effector, type III secretion, hrpG, regulon RB-TnSeq, Xanthomonas, Fitness, Brassica oleracea, Hydathodes

Pathogens causing diseases on crop plants represent a threat to agriculture and indirectly to the environment through the use of pesticides. Xanthomonas campestris pv. campestris (Xcc) is a seed-transmitted vascular pathogen causing black rot disease on cultivated and wild Brassicaceae. Hydathodes are plant organs localized at leaf margins which are preferentially used by Xcc to enter the plant tissues and initiate systemic infections. This study presents the transcriptomic status of Xcc three days after entry into cauliflower hydathodes. Despite the absence of visible plant tissue alterations and a bacterial biotrophic lifestyle, Xcc deeply modified the expression of over 800 of its genes including a striking repression of chemotaxis and motility functions. Xcc full repertoire of virulence factors was not yet activated but the RB expression of the 95-gene HrpG regulon, including the type three secretion machinery important for suppression of plant immunity, was induced. A number of metabolic adaptations such as catabolism of plant compounds, transport functions, sulfur and phosphate metabolism were upregulated transcriptionally without significant bacterial stress responses being observed. These transcriptomic observations give information about the nutritional and stress status of bacteria during the biotrophic infection stages and help to decipher the adaptive strategy of Xcc to the hydathode environment.

Importance

Xanthomonas campestris pv. campestris (Xcc) bacteria cause important damages in the cultivated Brassicaceae including both fresh market and processing Brassica and impose strong sanitary restrictions to the Brassica seed industry. The question of how such pathogens adapt and prosper in plant environments is an essential question to optimize our agricultural practices and to limit the spread and incidence of the disease. In this study, we report the pathogen transcriptome at early stages when the bacterial population is low. To this end, we optimized both RNA extraction and enrichment methods to capture Xcc transcriptome inside hydathodes, the leaf plant organs preferentially infected by Xcc in field conditions. These transcriptomic data captured bacterium physiological status at the first encounter of plant inner tissues and enable to generate a new list of candidate genes potentially involved in bacterial pathogenicity and adaptation to the plant environment.

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Introduction

Xanthomonas campestris pv. campestris (Xcc) is a seed-transmitted vascular pathogen causing black rot disease on Brassicaceae. This bacterium has a complex lifestyle composed of both epiphytic and endophytic stages (Vicente and Holub, 2013) which have been studied by molecular genetics since the 80's (Daniels et al., 1984). Xcc epiphytic life is associated with environmental stresses such as UV or dehydration and relies, for instance, on the production of protective pigments or xanthan exopolysaccharides (EPS). Upon favorable conditions, Xcc will gain access into the plant inner tissues via wounds or hydathodes (Cerutti et al., 2017).

Hydathodes are plant organs localized at the leaf margin mediating guttation. Hydathodes are classically composed of an epidermis with water pores resembling stomata and an inner lose parenchyma called epithem irrigated by numerous xylem vessels [START_REF] Cerutti | Mangroves in the Leaves: Anatomy, Physiology, and Immunity of Epithemal Hydathodes[END_REF]. These specific structures offer an ecological niche for pathogenic bacteria and a rapid access to xylem vessels leading to systemic vascular infections (Cerutti et al., 2017). However, only few pathogens have been demonstrated to colonize this niche and the conditions driving hydathode infection are poorly understood [START_REF] Cerutti | Mangroves in the Leaves: Anatomy, Physiology, and Immunity of Epithemal Hydathodes[END_REF]. While a pre-invasive immunity limiting Xcc entry through water pores could not be evidenced, a post-invasive immunity was described inside the epithem (Cerutti et al., 2017). This is best revealed by the inability of a bacterial type III secretion (T3S) mutant to multiply in the epithem and to initiate vascular infections. The Hrp (hypersentive response and pathogenicity) T3S system is responsible for the secretion and translocation of type III effector (T3E) proteins inside plant cells where they interfere with plant physiology and suppress plant immunity.

Once inside hydathodes, Xcc will adapt to this new niche and first adopt a biotrophic lifestyle: bacteria will multiply intercellularly between epithem cells without causing visible tissue alterations as observed until three days post infection (dpi) of cauliflower hydathodes (Cerutti et al., 2017). A switch to a necrotrophic behaviour is then observed, resulting in the almost complete digestion of the epithem at 6 dpi and bacterial vascularization. Systemic infection reaching the flowers will cause seed colonization and transmission to seedlings [START_REF] Darsonval | Adhesion and Fitness in the Bean Phyllosphere and Transmission to Seed of Xanthomonas fuscans subsp. fuscans. MPMI 22[END_REF]Dutta et al., 2014).

During infection, Xcc feeds on guttation fluid, xylem sap or plant tissues. This process can be facilitated by high affinity nutrient transport systems such as TonB-dependent transporters (TBDT) for mineral (e.g iron) or carbohydrate nutrition {e.g. sucrose, Blanvillain et al., 2007)and to a large repertoire of plant cell wall degrading enzymes secreted through the type two secretion (T2S) system. Such metabolic adaptations need to be finely coordinated throughout the infectious cycle. Master regulators include the rpf-DSF (Diffusible Signal Factor) quorum sensing system and sensors of nutrient availability and metabolic activity. Xcc genome encodes more than 50 two-component systems that allow bacterial cells to respond appropriately to diverse extracellular stimuli encountered during its life cycle such as oxidative stress, oxygen levels, pH, temperature and plant signals [START_REF] Qian | Genome-Scale Mutagenesis and Phenotypic Characterization of Two-Component Signal Transduction Systems in Xanthomonas campestris pv. campestris ATCC 33913[END_REF]. Among them, some are well known to play a major role in virulence such as the response regulator HrpG which is, with the transcription regulator HrpX, the master regulator of the T3S regulon (Noël et al., 2001;[START_REF] Wang | The decoy Substrate of a pathogen effector and a pseudokinase specify pathogen-induced modified-Self recognition and immunity in plants[END_REF][START_REF] Zhang | Analysis of HrpG regulons and HrpG-interacting proteins by ChIP-seq and affinity proteomics in Xanthomonas campestris[END_REF]. Most transcriptomic studies in Xcc or other

R

Xanthomonas species were performed so far in vitro focusing on specific regulons of the hrpG and hrpX genes in hrp-inducing medium, the prc protease gene, the DSF-mediated quorum sensing gene or the gum genes responsible for xanthan production (Schmidtke et al., 2012;Jalan et al., 2013;Liu et al., 2013;[START_REF] Zhang | Comparative Transcriptome Profiling Reveals Different Expression Patterns in Xanthomonas oryzae pv. oryzae Strains with Putative Virulence-Relevant Genes[END_REF][START_REF] An | The PAS domain-containing histidine kinase RpfS is a second sensor for the diffusible signal factor of Xanthomonas campestris[END_REF][START_REF] Alkhateeb | Genome wide transcription start sites analysis of Xanthomonas campestris pv. campestris B100 with insights into the gum gene cluster directing the biosynthesis of the exopolysaccharide xanthan[END_REF]Kim et al., 2016;Liao et al., 2016;Noh et al., 2016;[START_REF] Chen | Melatonin Treatment Inhibits the Growth of Xanthomonas oryzae pv. oryzae[END_REF]Li et al., 2019). Only few in planta transcriptomic analyses were performed on Xanthomonas (Lee et al., 2017;Li et al., 2019;Liao et al., 2019;Gétaz et al., 2020) and all at late stages of infection and/or in comparison to in vitro-grown bacteria. Our knowledge of in planta gene expression and regulation thus remains elusive and technically challenging especially at early steps of infection, when bacterial populations are low. Such in planta transcriptomics approaches would help identify new pathogenic behaviors and adaptation to the host during the infection process and in the different tissues colonized. Such approaches are also good descriptors of the environmental conditions and stresses imposed by the host to the bacterial pathogen (Nobori et al., 2018).

In this study, we compared the transcriptome of Xcc inside cauliflower hydathodes at 4

or 72 hours after inoculation, i.e. during the biotrophic stage of infection, in order to determine Xcc adaptative transcriptomic responses and access the environmental conditions met by this bacterial pathogen inside plant tissues.

Materials and methods

Bacterial strains, plasmids and growth conditions

The list of strains and plasmids used in this study is provided in Table S1. Xanthomonas campestris pv. campestris reference strain 8004 is a spontaneous rifampicin-resistant derivative of strain NCPPB 1145 isolated from cauliflower in Sussex (UK, 1958) (Daniels et al., 1984).

The 8004::hrpG* E44K mutant constitutively expresses the hrpG regulon [START_REF] Guy | xopAC-triggered immunity against Xanthomonas depends on Arabidopsis receptor-like cytoplasmic kinase genes PBL2 and RIPK[END_REF].

All deletion mutants were constructed in the Xcc 8004::GUS-GFP background (Cerutti et al., 2017). Xcc was cultivated in MOKA rich 4 g.l -1 Yeast extract, 8 g.l -1 Casamino acids, 1 mM MgSO4 and 2 g.l -1 K2HPO4; Blanvillain et al., 2007) at 28°C under agitation at 200 rpm or on MOKA-agar plates. E. coli strains TG1 and pRK2073 were cultivated on LB-agar or in liquid LB medium at 37°C under agitation.

Mutagenesis and complementations

In-frame deletion mutants of Xcc were achieved using double recombination with derivatives of the suicide plasmid pK18mobSacB as described [START_REF] Schäfer | Small mobilizable multi-purpose cloning vectors derived from the Escherichia coli plasmids pK18 and pK19: selection of defined deletions in the chromosome of Corynebacterium glutamicum[END_REF] sequences. Because XC_2711 is located at the end of the pstCAB operon, it does not contain any ribosome-binding site (RBS) in its immediate upstream region, thus preventing correct translation of the transcript. This led us to construct the pK18_compR3_RBS plasmid by adding the RBS from the pK18-GUS-GFP plasmid (Cerutti et al., 2017), downstream the pTac promoter. All plasmids were conjugated into Xcc 8004::GUS-GFP derivatives by triparental mating with the E. coli TG1 carrier and pRK2073 helper strains as described [START_REF] Figurski | Replication of an origin-containing derivative of plasmid RK2 dependent on a plasmid function provided in trans[END_REF][START_REF] Ditta | Broad host range DNA cloning system for gram-negative bacteria: construction of a gene bank of Rhizobium meliloti[END_REF]Cerutti et al., 2017). Deletions and insertions were verified RL by PCR. The sequences of oligonucleotides used to construct deletion and complementation plasmids are listed in Table S2.

Plant growth conditions

Brassica oleracea var botrytis cv. Clovis F1 (cauliflower) were grown under greenhouse conditions. Four-weeks-old plants were transferred to a growth chamber (9 h light; 22°C; 70% relative humidity) one day before inoculations.

Preparation of biological samples used for RNA sequencing

Xcc strains were grown in vitro in MOKA medium to mid exponential phase, harvested by filtration as described [START_REF] Wang | The decoy Substrate of a pathogen effector and a pseudokinase specify pathogen-induced modified-Self recognition and immunity in plants[END_REF] and stored at -80°C. Hydathodes from the first three cauliflower leaves were inoculated by continuous or transient dipping as described (Cerutti et al., 2017) using 0.01% of SILWET-L77® (DE SANGOSSE). For continuous dipping, leaves were dipped in a bacterial suspension for 4 hours in a covered small greenhouse and immediately harvested. For transient dipping, after inoculation, plants were watered, placed in a small greenhouse, covered for a day and a half and harvested 72 hours post inoculation. To collect hydathodes, leaves were briefly rinsed twice in sterile distilled water and dried on a paper towel prior to harvesting. At least 1000 hydathodes were macrodissected per condition with a 1.5 mm diameter punch. Collected tissues were immediately placed in a RNA Protect Bacteria Reageant® (Quiagen™, 2:1 (v/v) of RNA Protect and RNAse free water). After three minutes sonication in a waterbath, the supernatant was recovered and centrifuged for 10 minutes at 5000g. The pellet was stored at -80°C. Three independent biological replicates were performed.

In order to verify that in both conditions hydathodes contain an equivalent amount of bacteria, infection efficiency after 4 hpi and 72 hpi was checked by determining bacterial populations in 24 and 30 individual hydathodes, respectively in three independent experiments (Figure S1).

RNA extractions, ribodepletion and sequencing

RNA extraction was essentially performed as previously described (Sallet et al., 2013).

After RNA extraction with the mirVana Isolation Kit (Ambion®, Life Technologies™), RNA integrity was assessed using the RNA Nano 6000 Assay Kit for the Bioanalyzer 2100 system. S3) as described (Sallet et al., 2013). Oligocapture was performed following the manufacturer instructions as described (Sallet et al., 2013). After ethanol precipitation, residual oligonucleotides were removed with Turbo DNAse (Ambion®, Invitrogen™). Quality of RNA samples and ribosomal and other-RNA depletion were analysed using a Fragment Analyzer-AATI (Advanced Analytical) on the GeT-PlaGe platform (Genotoul, Toulouse, France). RNAs were then separated into short (<200 nt) and long (>200 nt) RNA fractions using Zymo

Research RNA Clean & ConcentratorTM-5 columns (Proteigene). Oriented sequencing was carried out on in vitro-grown Xcc by Fasteris SA (Geneva, Switzerland) as described (Sallet et al., 2013). For small RNA fraction, the Small RNA Sequencing Alternative v1.5 Protocol (Illumina) was used, starting with ca. 500 ng RNAs that were treated with tobacco acid pyrophosphatase to remove triphosphate at 5' transcript ends and purified on acrylamide gel before and after the adaptor ligation step. For large RNAs, a fragmentation step by zinc during 8 min was included after the Illumina procedure. The size of selected inserts was 20-120 nt for short RNA libraries and 50-120 nt for long RNA libraries. Libraries were sequenced either in single end (small RNA fraction) or in paired end (Large RNA fraction) on an Illumina HiSeq 2000 platform. Raw sequence data were submitted to the Sequence Read Archive (SRA) database (Accession SRP280320).

For samples prepared from infected tissues, oriented paired end RNA sequencing was carried out on the GeT-PlaGe platform (Genotoul, Toulouse, France) using an Illumina HiSeq et al., 2006).

Infection of hydathodes and measurement of bacterial population

For hydathode infection, the second true leaf of cauliflower plants was dip-inoculated in a bacterial suspension at 10 8 cfu/mL in 1mM MgCl2 containing 0.5% (v/v) Tween 80. In order to determine Xcc populations in single hydathodes, hydathodes were collected at 3 or 6 days post-inoculation by macrodissection with a 1.5 mm-diameter punch. 8 hydathodes were sampled per leaf and individually placed in 200 µL of 1mM MgCl2. After bead-assisted grinding at 30 Hz for 2 min using a Retsch MM400 grinder, 5-µL droplets of serial dilutions were spotted on MOKA 30 µg/mL pimaricin plates in three technical replicates and incubated at 28°C for two to three days. Individual colonies were then counted and the mean of the three technical replicates was calculated to estimate the infection level of each hydathode.

Experiments were performed on three plants per condition and in three independent biological replicates. Significance of differences observed in bacterial population quantifications and bacterial pathogenicity assays was assessed using the non-parametric Kruskal-Wallis test with = 0.05.

RM

Results

Improved annotation of Xcc strain 8004 genome based on a large transcriptomic dataset

Transcriptomic analyses are intrinsically dependent on the proper structural annotation of genes. In order to improve annotation of Xcc strain 8004 using experimental expression data, we produced the transcriptome of two nearly isogenic strains grown in MOKA medium: wild type 8004 and strain 8004::hrpG* which expresses the constitutive active variant E44K of HrpG [START_REF] Guy | xopAC-triggered immunity against Xanthomonas depends on Arabidopsis receptor-like cytoplasmic kinase genes PBL2 and RIPK[END_REF]; see later for comparative analysis of the HrpG regulon). Total RNAs were extracted from exponentially growing bacteria and subjected to ribodepletion using a custom oligonucleotide set optimized to bind Xanthomonas ribosomal RNAs [START_REF] Wang | The decoy Substrate of a pathogen effector and a pseudokinase specify pathogen-induced modified-Self recognition and immunity in plants[END_REF]. At this step, RNAs were separated based on their size with a cutoff of ca. 200 bases. While the large RNA fractions were subjected to single end strand-specific sequencing, the smaller RNAs protected with a 5' triphosphate group in the small fraction were subjected to paired end strandspecific sequencing in order to map precisely transcriptional start sites and distinguish small RNAs from degradation products of larger RNA molecules. Those 12 libraries (Two genotypes, two RNA fractions, three biological replicates) were used to refine the annotation of the genome. More than 1724 transcriptional starts (5' UTRs) and 1246 3' UTRs could be experimentally defined (Table 1). In particular, determination of 5' UTRs modified predicted translational start site for 1164 CDS. Additionally, 753 small ncRNAs were evidenced. These results highlight the importance of experimentally-supported genome annotations and offer improved resources for the genetic characterization of Xcc and the functional analysis of its transcriptome.

Xcc transcriptome remodeling at early stages of hydathode infection:

To obtain a proxy of the physiological status of Xcc at the early step of plant leaf infection, we performed RNA sequencing on bacteria re-isolated from cauliflower hydathodes 72 hours after a rapid dip inoculation of an attached leaf. This 72 hpi timepoint corresponds to a biotrophic phase of the infection where bacteria are still limited to the epithem apoplastic spaces and where the epithem does not present detectable cellular alterations (Cerutti et al., 2017). For any transcriptomic analysis, the choice of the reference condition is most critical.

Here, we determined that after 4 hours of continuous immersion of a detached leaf in the RS bacterial suspension, ca. 10 5 cfu per hydathode are detected, similarly to the bacterial titers measured at 72 hpi (Figure S1). Thus, the 4 hpi and 72 hpi conditions allow the narrow comparison of two bacterial populations both in contact with the epithem tissue for 4 and 72 hours, respectively. Other observations suggest the relevance of the 4 hpi timepoint as a reference in planta condition: comparison of in vitro (MOKA rich medium) and in planta (4 and 72 hpi) RNAseq results for wild-type Xcc strain 8004 using Euclidean distance calculations

shows that the RNAseq samples obtained from hydathodes at 4 hpi cluster with the 72 hpi samples rather than those obtained in MOKA (Figure S2). Also, the expression of 14 genes belonging to the HrpG regulon was already induced at 4 hpi (Figure 1, Table S4) indicating that bacterial cells extracted in this condition were in contact with plant tissue. Finally, among the 1,356 differentially-expressed genes (DEGs) between the 72 hpi and MOKA conditions (Table S4), 711 were already differentially expressed at 4 hpi compared to MOKA. These results suggest that the transcriptomic impact of inoculum preparation (from MOKA to 1mM

MgCl2) can be masked by the choice of the 4 hpi timepoint in order to focus the analysis solely on bacterial adaptation to the plant environment.

Our in planta analysis revealed that during the first days of hydathodes colonization, Xcc massively reshaped its transcriptome (Figure 1, Table S4, Table S5). Indeed, 18 % of Xcc CDS undergo a transcriptional reprogramming during hydathode infection with 828 DEGs after 72 hpi in comparison to 4 hpi. We observe that 18 Biological Processes, such as catabolism, stress response and transport, were enriched in up-regulated genes. On the other hand, 13 GOterms were found enriched among down regulated genes, with a strong over-representation of motility and chemotaxis categories (Table 2).

Xcc adopts a sedentary lifestyle inside hydathodes

Most genes involved in flagellar biosynthesis, type IV pilus biosynthesis and chemotaxis are strongly repressed 72 hpi when bacteria are localized into hydathodes. Motility and chemotaxis are key components of pathogenicity, especially for plant pathogens (Matilla and Krell, 2018). However, some previous studies have shown that Xcc could be an exception.

Indeed, Xcc seems to not be flagellated when grown in xylem fluids and that the motile form of Xcc cells seems to be less efficient in disease development on cauliflower and radish (Kamoun and Kado, 1990). These observations suggest a probable fitness cost of motility apparatus production during infection. To investigate the importance of motility in disease development,

we have constructed deletion mutants in key genes for either type IV pilus synthesis ( pilE and pilA) or for flagellar synthesis ( fliC, fliQ). Different combinations of these mutants were tested for in vitro motility (Figure S3), pathogenicity (Figure S4) and hydathode colonization (Figure 2). As expected, no strong effect of these mutations was observed neither on disease symptoms development nor on hydathode colonization. These results, together with the heavy repression observed in hydathodes, strongly suggest that motility is a process that could be detrimental for the bacterium during plant tissue colonization.

The hrpG regulon is activated and required at early steps of infection

Data mining also showed that the expression of the hrpG gene, as well as the T3SS compomponents and T3E, are induced during hydathodes infection. This observation prompted us to (i) confirm that hrpG is important for hydathodes infection and (ii) precisely identify the set of genes controlled by hrpG. We constructed the 8004 hrpG mutant and show that it presents a reduced multiplication in hydathodes (Figure 2) and is avirulent on cauliflower after wound inoculation (Figure S4). Both phenotypes are complemented by inserting an hrpG overexpression construct in 8004 hrpG chromosome. On the other hand, the hrpG* gain-offunction mutation did not affect the multiplication of Xcc in cauliflower hydathodes (Figure 2)

nor its pathogenicity after wound inoculation as compared to the wild-type strain. This suggests that HrpG functionality in planta is retained and that in vitro studies with this mutant are legitimate. We also confirm the observation made in the close relative Xanthomonas euvesicatoria (Noël et al., 2001) that the 8004::hrpG* strain presents a reduced extracellular activity on milk plates (Figure S5).

To identify the set of genes under the control of HrpG in Xcc, we explored the transcriptome of the 8004::hrpG* and 8004 strains. The newly annotated genome was used to map reads obtained from both strains after growth in MOKA rich medium (Table S6). Analysis of the HrpG regulon identified 95 differentially expressed genes (DEGs, Log2(fold change) 2

or -2, FDR adjusted p-value < 0.05) distributed across the genome or grouped within the 23kb hrp gene cluster (25 DEGs out of 95, Table S4). To objectively investigate the cellular processes affected in our subset of DEGs, we performed a Gene Ontology (GO-term) enrichment test. Among the 85 genes with an increased expression in strain 8004::hrpG*, 43 M possess a predicted PIP box in their promoter region (Table S4). The PIP box is a cis-DNA motif allowing the induction of gene expression by the HrpX transcriptional regulator which is under direct positive regulation by HrpG (Koebnik et al., 2006). As expected, 43 of the 95 DEGs correspond to genes involved in T3SS and T3Es, underlying the enrichment in the secretion GO term among genes upregulated in hrpG* background (Table 3, Table S5). From the 30 T3Es encoded by Xcc 8004, only 18 were significantly induced in the 8004::hrpG* strain.

Of the other 56 DEGs, 26 encode proteins with unknown function and 19 enzymes, many of which are predicted to degrade proteins or carbohydrates. Interestingly, most genes belonging to this HrpG regulon are similarly regulated into hydathodes after 72 hpi (Figure 1). Among the 95 genes belonging to the HrpG regulon, 25 (out of 25) and 24 (out of 30) genes coding for the T3S system and T3E proteins, respectively, were induced at 72 hpi (Table S4 andS5), meaning that HrpG is activated at this early stage of infection. As mentioned previously, it is also worth noting that 14 genes are over-expressed in hydathodes at 4 hpi in comparison to the MOKA condition, thus hinting at the rapid adaptive response deployed by Xcc at the first encounter with host tissues. These results indicate that, though essential for pathogenicity, the HrpG regulon involves a very limited number of genes (95 out of 6162) which represents a very partial view of Xcc transcriptomic adaptations to "in planta" conditions.

Metabolic adaptations of Xcc inside hydathodes highlight some nutritional properties of the plant environment

Among the 31 GO terms significantly affected at transcriptomic level a third are involved in metabolism, indicating that Xcc undergoes an important metabolic adaptation inside the hydathode.

Modification of the expression profile of genes encoding plant cell wall degrading enzymes Regarding sugar catabolism, we observe an increase in the transcription of genes involved in the catabolism of cellulose, a major compound of plant primary cell wall. Yet, increased expression of other plant cell wall degrading enzymes genes is not observed at 72 hpi, consistently with the absence of visible degradation of cell walls in the epithem (Cerutti et al., 2017). Among the 43 genes encoding degradative enzymes in Xcc strain 8004 (da Silva et al., M 2002), 10 have an increased and 10 have a reduced expression at 72 hpi, respectively (Table S5). Expression of either xps or xcs genes encoding type II secretion systems involved in secretion of those enzymes is not induced at 72 hpi suggestive of a biotrophic lifestyle for at least three days post infection.

Lignin is another major component of plant cell walls and a source of aromatic compounds.

Interestingly, the expression of XC_3426 and XC_3427 genes coding for protocatechuate (PCA) 4;5-dioxygenase subunits is increased 6-and 8-fold at 72 hpi, respectively. PCA is a lignin degradation product [START_REF] Brown | Biophysical Analyses of Designed and Selected Mutants of Protocatechuate 3,4-Dioxygenase[END_REF] which can be further catabolized by PCA dioxygenases to enter the tricarboxylic acid (TCA) cycle (Wang et al., 2015c). While XC_3426

and XC_3427 relevance for pathogenicity remains unknown, XC_0375 to XC_0383 genes cluster encoding 3-and 4-hydroxybenzoate degrading enzymes are needed for full virulence of Xcc in radish (Wang et al., 2015c) suggesting that degradation plant phenolic compounds is a key issue inside plant tissues.

Expression of transporter genes is deeply remodeled in planta

Broad expression changes can be observed in transporter genes since 49 out of 210 genes involved in transport are differentially expressed at 72 hpi (Table A, Table SE). Those transporters belong to MFS, ABC and TonB dependent Transporters (TBDT) families. TBDTs have been shown to be involved in iron and carbohydrates polymers uptake with high affinity in Xcc (Blanvillain et al., 2007;[START_REF] Boulanger | Identification and Regulation of the N-Acetylglucosamine Utilization Pathway of the Plant Pathogenic Bacterium Xanthomonas campestris pv. campestris[END_REF]Déjean et al., 2013). 14 out of 48 TBDT genes are differentially expressed: 7 show an increased expression at 72 hpi and 7 with a decreased activity. Among those, some have no clear known function, but the ones identified to be induced by polygalacturonate (PGA) (Blanvillain et al., 2007) are all repressed into hydathodes (Table S5). The two TBDT genes XC_3205 and XC_2512 known to be positively regulated by HrpG and HrpX (Blanvillain et al., 2007) are also induced at 72 hpi.

Interestingly, the absence of the fur regulon and its iron high affinity TBDT transporters (XC_0167, XC_3463, XC_2846, XC_1341, XC_1108 XC_0924-0925, XC_0642, XC_4249, XC_0558 and XC_4249) in our dataset indicates that iron might not be limiting at this stage of the infection of the hydathodes.

Upregulation of two pathways important for sulfur assimilation in hydathodes

In contrast to iron, induction of genes important for sulfur transport and assimilation is observed at 72hpi in hydathodes: the operon encoding the ABC sulfate transporter CysPUWA (XC_3292 to XC_3295) and the operon encoding an assimilatory sulfate reduction pathway leading to sulfide production (XC_0990 to XC_0994) are induced by ca. 6-and 20-fold, respectively (Table S5). Sulfide is then used for cysteine and methionine biosynthesis. Sulfur metabolism including sulfur-containing amino acids, sulfur compounds, or sulfate have been shown to be involved in different virulence factor production, as in xanthan production (Garcı a-Ochoa et al., 2000) or T3SS induction (Schulte and Bonas, 1992). Yet, a deletion of the entire cysPUWA operon ( XC_3292-95) in Xcc strain 8004 did not significantly affect bacterial multiplication in neither hydathodes after dip-inoculation nor disease symptoms development after wound inoculation in cauliflower (Figure 2, Figure S4). Thus, sulfate import through the CysPUWA system is not required, indicating that either sulfur is not limiting for bacterial growth in hydathodes or that sulfur might be acquired through other import pathways such as the taurine import system. For instance, E. coli responds to sulfate or cysteine starvation by expressing the ssuABCDE and tauABCD operons which are involved in the uptake of alkanesulfonate and desulfonation of the organosulfonates and for the uptake and desulfonation of taurine, respectively. While ssuABCDE can be found in other Xanthomonas such as Xanthomonas citri (Pereira et al., 2015), it is absent in Xcc strain 8004. TauABCD homologues are encoded by genes of the locus XC_3454 to XC_3460 (Figure S6) with XC_3454, XC_3459 and XC_3456 being highly similar to E. coli TauB, TauC and a predicted taurine dioxygenase, respectively.

Interestingly, expression of these genes (locus XC_3454 to XC_3460) is increased at 72 hpi suggesting a possible implication of this pathway in sulfur assimilation in planta.

Phosphate uptake machinery is rate limiting for Xcc multiplication inside hydathodes Increased expression of the genes encoding the PstSCAB high-affinity transporter system (genes XC_2708 to XC_2711, Table S4) involved in active inorganic phosphate (Pi) import upon phosphate starvation suggests that Pi might be limiting inside hydathodes. This system is known to be activated in various conditions in bacteria (Lamarche et al., 2008), including during ML plant colonization (Pegos et al., 2014;Moreira et al., 2015). For instance, phosphate uptake by Xanthomonas citri is essential for pathogenicity on citrus. In order to test if phosphate acquisition upon phosphate starvation is important for Xcc strain 8004 during hydathode colonization, we have deleted XC_2711 (pstB) and XC_3272 (which encodes an homologue of the PhoB response regulator of Pi starvation response in E. coli; [START_REF] Yang | Genome-Wide PhoB Binding and Gene Expression Profiles Reveal the Hierarchical Gene Regulatory Network of Phosphate Starvation in Escherichia coli[END_REF]Gardner and McCleary, 2019). Results obtained demonstrated that pstB, unlike phoB, is important for hydathode colonization (Figure 2) and that both pstB and phoB mutants were not affected in symptoms development by direct inoculation into xylem vessels (Figure S4). These results demonstrate that Pi might be limiting for the growth during early infection stages but not for the pathogenicity into xylem vessels. Similar to Pi, expression of genes important for nitrogen assimilation such as those involved in uptake of nitrite and nitrate and their reduction to ammonia (XC_2175 to XC_2178) are induced at 72 hpi in hydathodes, further stressing the importance of Xcc mineral nutritional needs in planta. S4). Finally, expression of some genes of the gum operon (XC_1658 to XC_1673) implicated in the production of the xanthan exopolysaccharides (EPS) are induced by 4-to 5-fold at 72 hpi. Xanthan is a well-known protectant against environmental stresses and toxic compounds and a suppressor of plant immunity (Kakkar et al., 2015). All together these data seem to indicate that Xcc cells face nutritional, osmotic and environmental stresses in hydathodes,

Limited stress responses in planta

Discussion

Xcc life cycle depends on Xcc adaptation to various plant environments (e.g. seeds, leaf surface, hydathodes, xylem, mesophyll, debris). This work provides the first analysis of transcriptional changes that Xcc undergoes upon plant infection and hydathode colonization, including the regulation of various metabolic and virulence pathways (Figure 3), and informs about the environmental conditions faced by Xcc inside hydathodes.

Xcc adopts a sedentary biotrophic lifestyle inside hydathodes

Xcc is known to be a necrotroph causing black rot disease. However, the physiological snapshot obtained by RNAseq at 72 hpi in hydathodes suggests that Xcc rather behaves as a biotroph since the epithem is intact (Cerutti et al., 2017) and many genes coding for degradative enzymes, T2SS and most catabolic pathways of sugar polymers and carbohydrates were expressed at basal levels. We also observed that the constitutive activation of the HrpG regulon recapitulating part of the in planta condition at 72 hpi is associated with the repression of protease genes expression and a reduced extracellular protease activity. Carbon and nitrogen needs of Xcc could be supported in planta by the continuous xylem sap flow in the epithem and/or by the energy stored during bacterial growth into rich medium prior to plant inoculation.

Furthermore, the expression of multiple virulence-associated genes such as those involved in quorum sensing, iron uptake or motility was also reduced at 72 hpi in hydathodes. Motility has been shown to be an essential virulence trait for many bacterial pathogens [START_REF] Chaban | The flagellum in bacterial pathogens: For motility and a whole lot more[END_REF].

Yet, Xcc motility mutants fliC and flic-pliA-pliE were not affected in pathogenicity which could be expected considering that, inside hydathodes, Xcc strongly repressed the expression of over 84 (out of 94) genes important for chemotaxis, twitching (Type 4 pilus) and swimming Interestingly, an increase in the expression of genes important for twitching motility and adhesion was observed in Xcc grown in vitro in xylem sap (Dugé de [START_REF] De Bernonville | Transcriptional reprogramming and phenotypical changes associated with growth of Xanthomonas campestris pv. campestris in cabbage xylem sap[END_REF].

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Xylem sap corresponds to the environment met by Xcc immediately after leaving the hydathode.

These observations suggest a possible biphasic infectious process with the reactivation of the motility and other virulence-associated genes at late infection stages. Further transcriptomic analyses of virulence gene expression throughout the entire infectious cycles would be needed to support such an hemibiotrophic lifecycle of Xcc or other Xanthomonas species.

Stealthiness of Xcc inside hydathodes and neutralization of plant immune responses

The observed repression of chemotaxis, twitching and swimming motility also suggests that those functions are dispensable once inside hydathodes or even detrimental to successfully settle in planta. For instance, production of bacterial peptide flg22 from the flagellar FliC protein is a well-known PAMP (pathogen-associated molecular pattern) recognized by the FLS2 receptor and a potent elicitor of basal plant immunity which restricts pathogen growth in planta (Gómez-Gómez and Boller, 2000). While flg228004 peptide is not recognized by Arabidopsis FLS2 [START_REF] Sun | Within-Species Flagellin Polymorphism in Xanthomonas campestris pv campestris and Its Impact on Elicitation of Arabidopsis FLAGELLIN SENSING2-Dependent Defenses[END_REF]Guy et al., 2013b), we cannot exclude that other FliC peptides, flagellar proteins or pili proteins from Xcc strain 8004 could act as PAMPs in Brassicaceae. In the absence of an Xcc strain constitutively expressing those genes, we were not able to test such hypotheses. Xcc stealthiness could also be acquired by limiting bacterial multiplication until an efficient suppression of immunity has been achieved. Such suppression could be mediated by the T3E proteins whose expression depends on the HrpG regulator. In contrast to a wild-type Xcc strain, a T3S system mutant caused hydathode browning and necrosis at 48 hpi and had a reduced multiplication at 72 hpi (Cerutti et al., 2017). These results

indicate that hydathode immune responses can be effective against bacterial pathogens and that their suppression by Xcc T3S system and its T3E proteins is required for successful infection.

It would thus be most interesting to refine our observations by finely monitoring plant immune responses throughout the infection.

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Inference of environmental conditions inside hydathodes based on Xcc transcriptomic behaviour

Compared to in vitro-grown Xcc, transcriptomic changes are already observed as early as 4 hpi with the increased expression of 14 genes belonging to HrpG regulon (Table S4). These genes could participate in the transition from in vitro to in planta growth such as gene XC_2566

coding for an extracellular function (ECF) sigma factor which importance for this transcriptional switch should be tested. Those transcriptomic signatures can also be used to infer the metabolic and physiological status of Xcc inside hydathodes and the nutritional properties of the epithem. For instance, the epithem environment, in which Xcc proliferates, is likely not limiting for assimilable iron since the corresponding uptake machinery is not expressed. In contrast, both the low-affinity phosphate inorganic transport (Pit) and the high-affinity phosphate-specific transport (Pst) systems, known to be important for the uptake of inorganic phosphate (Pi) in Xanthomonas, are upregulated at 72 hpi [START_REF] Willsky | Characterization of two genetically separable inorganic phosphate transport systems in Escherichia coli[END_REF]Moreira et al., 2015). Similar to Xac (Moreira et al., 2015), the Pst system is needed for in planta growth of Xcc. These results demonstrate that Xcc not only faces Pi starvation inside hydathodes but that Pi availability also limits Xcc proliferation in this tissue. Very low Pi concentrations are indeed found in guttation fluids of several plant species such as barley (Nagai et al., 2013) and are correlated with expression of genes coding for plant high affinity Pi transporters such as AtPHT1;4 in hydathodes even under Pi sufficient conditions (Misson et al., 2004). These observations suggest that an active competition between the plant and Xcc for access to Pi might occur in the epithem. Similar to Pi, Xcc transcriptome at 72 hpi also suggests that sulfur and nitrogen are present in low amounts requiring the upregulation of dedicated uptake systems.

Yet, it remains unclear whether these elements are limiting for growth of Xcc inside hydathodes.

Exposure to stresses is also unveiled by the transcriptomic upregulation of many genes involved in responses to general stress (e.g. gum genes) and especially osmotic stress. However, it remains uncertain whether this potential osmotic stress is intrinsic of the epithemal environment or whether it is caused by active plant immune responses. For instance, we could not evidence significant signs of oxidative stresses classically associated with strong plant immune responses. Therefore, Xcc seems to adapt rapidly to the low concentrations of nutrients found in the epithem and to endure limited stress maybe due to the continuous flow of fluids inside hydathodes which renews nutrient supplies and dilutes potential antibacterial compounds.

Perspectives

While informative, such global transcriptomic studies provide an averaged picture of the population, ignoring the spatial and temporal differences occurring in planta between attached vs. planctonic cells or between cells which entered hydathodes early vs. late after inoculation. The phenotypic heterogeneity often observed in bacterial pathogens is therefore ignored here [START_REF] Weigel | Phenotypic heterogeneity: a bacterial virulence strategy[END_REF]). To answer this limitation, single cell transcriptomic protocols are becoming available [START_REF] Darsonval | Adhesion and Fitness in the Bean Phyllosphere and Transmission to Seed of Xanthomonas fuscans subsp. fuscans. MPMI 22[END_REF]Wang et al., 2015b;[START_REF] Chen | Tools for Genomic and Transcriptomic Analysis of Microbes at Single-Cell Level[END_REF][START_REF] Kim | A Genome-Scale Co-Functional Network of Xanthomonas Genes Can Accurately Reconstruct Regulatory Circuits Controlled by Two-Component Signaling Systems[END_REF] but their use to describe the transcriptomes of in planta-grown bacteria still remains highly challenging. SR

Bacterial pathogenicity assays

Pathogenicity of Xcc strains was tested by wound inoculation of the second true leaf of cauliflower plants by wounding the main vein with a needle dipped in an Xcc suspension at 10 8 cfu/mL. Symptoms were evaluated according to a disease index scale at 7 and 10 dpi (Figure S4) Experiments were performed on five plants per condition and in three independent biological replicates. Significance of differences observed bacterial pathogenicity assays was assessed using the non-parametric Kruskal-Wallis test with = 0.05.

Motility assays

Xcc cells grown overnight in MOKA were washed by centrifugation (4000 x g, 5 min) and resuspended in sterile water. 2-µl bacterial suspensions adjusted at 10 8 cfu/mL were spotted on swimming plates {0.03% Bacto peptone, 0.03% yeast extract, 0.3% agar, \Su, 2016 #8143} and incubated 48 h at 28°C. White halos expanding from the colonies indicate the strains' ability to perform flagellar motility.

Protease activity assay on milk plates

10 % skimmed milk stock solution was first autoclave for 10 min and used to pour 0.5 % skimmed milk MOKA plates supplemented with 30µg/mL pimaricin. Each plate contains 15 mL of medium. Extracellular protease activity of Xcc strains was tested by spotting 5 L of an overnight culture adjusted to 4.10 8 cfu/mL. Plates were incubated at 28 °C and imaged 24 hour post inoculation. Diameters of colonies and halos of degradation were measured. Protease activity was calculated as followed: PrA = [ (r halo ) 2 -(r colo ) 2 ]/ [ (r colo ) 2 ] with "r" corresponding to the radius.

Measurement of exopolysaccharide production

Extracellular EPS production was measured as described {Vojnov, 1998 #8147}. Briefly, an overnight growth of each strain in MOKA was used to inoculate 20 mL of MOKA supplemented with 50µg/mL of rifampicin at 2.10 7 cfu/mL. After 24 hours of growth 12 mL of culture was centrifuged 15 min at 6500 g. EPS present in supernatant were ethanol precipitated.

Then, bacterial and EPS pellets were dried for 8 hours at 65°C before being weighed. EPS production corresponds to the ratio of dry weight EPS on dry weight bacterial cells.

Growth measurements in vitro

In vitro growth curves were generated using a FLUOStar Omega apparatus (BMG Labtech, Offenburg, Germany) using 96-well flat-bottom microtiter plates (Greiner) with 200 µL of bacterial suspensions. After an overnight preculture in MOKA rich medium, cells were harvested by centrifugation at 9500 g for 4 minutes, washed and resuspended in MME minimal medium (K2HPO4 10.5 g/L, KH2PO4 4.5 g/L, (NH4)2SO4 1 g/L MgSO4 0.12g/L, casamino acids 0.15 g/L) [START_REF] Arlat | Xanthomonas campestris Contains a Cluster of hrp Genes Related to the Larger hrp Cluster of Pseudomonas solanacearum[END_REF]. Bacterial suspensions inoculated at an optical density at 600 nm (OD600) of 0.15 were prepared in MME and MOKA media. For each experiment, four replicates coming from two independent precultures were performed. The microplates were shaken continuously at 700 rpm using the linear-shaking mode. Each experiment was repeated three times and a representative experiment was shown. b Percentage of unique hits to the genes of Brassica oleracea nuclear and mitochondrial genomes and Brassica rapa chloroplastic genome.

BL

Supplemental Figures:

B

Supplemental Tables

c Percentage of unique hits to the genes of Xcc strain 8004.

d Sequence Read Archive accession number

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Introduction

Crop production, for both food and feed, is at the core of our alimentation. However, pests and pathogens are a constant threat and often cause significant yield losses. The search for new control strategies then relies on our understanding of host-pathogen interactions.

Therefore, the identification and characterization of molecular determinants of pathogens fitness are of great interest and provide new targets for the development of disease management solutions.

Xanthomonas bacteria cause disease on more than 400 plant species and are responsible for tremendous losses on various economically important crops worldwide. Among them, Xanthomonas campestris pv. campestris (Xcc), the causal agent of the black rot disease, represents the most damageable bacterial pathogen of Brassica crops (e.g. cauliflower, cabbage,

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mustard, radish etc.; Vicente and Holub, 2013). Transmissible by seeds, Xcc survives as an epiphyte and enters the plant by leaf organs called hydathodes. Hydathodes are nephron-like structures located at the extremity of xylem sap conducting vessels that mediate the plant guttation process, allowing the release of excess root pressure in the leaf and presumably filtering sap content (Cerutti et al., 2017;[START_REF] Cerutti | Mangroves in the Leaves: Anatomy, Physiology, and Immunity of Epithemal Hydathodes[END_REF]. Xcc exploits the hydathodes pores located at the leaf margin to sneak into its host and initiate the infection. After a six-day long biotrophic homing step, Xcc adopts a necrotrophic behavior and destroys the epithemal tissue of hydathodes. By doing so, Xcc gains access to xylem vessels and exploits the plant vasculature to spread systemically within the plant.

Xcc deploys an arsenal of virulence factors to successfully infect the host plant, including two secretion systems that are essential for pathogenicity: while the type II secretion system (T2SS) exports enzymes such as plant cell wall degrading enzymes to the extracellular space, the type III secretion system (T3SS) enables the translocation of effector proteins into the host cells to suppress immune responses and hijack host metabolism [START_REF] Büttner | Regulation and secretion of Xanthomonas virulence factors[END_REF]. In addition, Xcc produces exopolysaccharides (xanthan) and lipopolysaccharides that protect the cell against environmental stresses and support biofilm formation. Quorum sensing coordinates bacterial behavior, including biofilm dispersal, and is required for disease as well.

Furthermore, Xcc possesses a wide range of two-components systems that ensure perception of environmental signals and mounting of adequate adaptive responses (Qian et al., 2008b).

Altogether, these traits contribute to the fitness of the bacterium during the infection. However, while previous studies have investigated in depth the virulence factors deployed by Xcc to implement its pathogenic lifestyle at late stages of infection, very few looked at the finer fitness determinants involved in the early steps of plant infection [START_REF] An | Mechanistic insights into host adaptation, virulence and epidemiology of the phytopathogen Xanthomonas[END_REF]Timilsina et al., 2020). A recent transcriptomic study on the early infection steps revealed that Xcc colonization of hydathodes is associated with sedentarization, activation of pathogenicity determinants and induction of high-affinity transporters for nutrient uptake (e.g. phosphate, sulfate, nitrate;

Luneau et al., in prep). Nevertheless, transcriptome profiling only provides genes expression levels without evaluating their contribution to bacterial fitness.

With the rise of New Generation Sequencing technologies, transposon insertion site sequencing tools have been developed to address the question of bacterial fitness at the genomic scale [START_REF] Cain | A decade of advances in transposon-insertion sequencing[END_REF][START_REF] Van Opijnen | Transposon Insertion Sequencing, a Global Measure of Gene Function[END_REF]. Here, we propose to use Randomly

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Barcoded Transposon insertion site Sequencing (RB-TnSeq) to identify the genetic bases underlying the adaptation of Xcc to the environments it colonizes within the host. RB-TnSeq allows, via the inoculation of a saturated library of barcoded transposon-mutagenized bacteria, to evaluate gene importance for fitness at very high-throughput [START_REF] Wetmore | Rapid quantification of mutant fitness in diverse bacteria by sequencing randomly bar-coded transposons[END_REF].

Focusing on the early interactions between Xcc and its host could prove useful to understand the factors underlying the emergence of epidemics and develop appropriate control strategies.

In this study, we screened and successfully identified genes contributing to Xcc fitness in hydathodes, xylem sap and synthetic media. In addition, we investigated several candidate genes and characterized the "hypothetical protein"-encoding gene XC_3388. We show that this protein acts as a major regulator of adaptation and pathogenicity in Xcc and that it is likely contributing to fitness into hydathodes through social behavior within the bacterial population.

Results

Construction of a saturated library of Xcc transposon-insertion mutants identifies essential genes.

In order to screen for genes involved in the adaptation of Xanthomonas campestris pv.

campestris strain 8004 to its environment, we first constructed a saturated library of randomly barcoded insertion mutants (RB-TnSeq) using a mariner transposon. High-throughput TnSeq analysis allowed the mapping of each insertion site to Xcc genome and their association to a unique barcode. This large-scale mutagenesis ultimately resulted in the obtention of 241,284 well mapped individual mutants, each carrying a barcode. However, after filtering out chimeric reads and non-unique DNA barcodes, and computationally removing insertions located outside the body of the gene (central 10% -90% of the coding sequence), we selected 109,885 mutants for fitness analysis (see Methods). Also, because insertions are performed using a mariner transposon, mutations only occur at TA dinucleotide sites in the genome (Figure 1a). We identified 51,853 out of 77,299 potential TA insertion sites in Xcc 8004 genome to be successful recipients of a transposon insertion, thus resulting in the large saturation of the genome (one insertion every 100 bp in average). Overall, our library contains mutants with at least one insertion mapped for 4,186 out of 4,617 with 3,674 genes included in our computational analyses (ie. genes that have at least one insertion with a unique barcode in the body of the gene).

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Among the 431 genes that do not contain an insertion, 33 do not carry a TA site in their sequence and could not have been included in our study, while 125 do not have mutations within the body of the gene. Because of the high saturation of insertions, we supposed that mutations did occur in the other 273 genes but resulted in a lethal outcome. Consequently, we hypothesized that our genome-wide mutagenesis identified 273 essential genes in Xcc strain 8004 (Table S1). We performed a Gene Ontology enrichment analysis which highlighted that core cellular functions related to DNA replication, translation (tRNA metabolism and ribosome assembly), cell envelope (cell wall organization, peptidoglycan and fatty acids biosynthesis)

and cell morphogenesis (cell shape, cell division) were significantly enriched in this subset of essential genes (Figure 1b). Nucleoside metabolism is also strongly affected in mono-and poly-phosphate purine and pyrimidine pathways. Regarding amino acids, only the lysine biosynthesis pathway seems essential for Xcc growth in the rich medium used to build the library.

RB-TnSeq fitness analysis identifies 172 genes required for Xcc multiplication in hydathodes.

Xcc is one of the few plant pathogens known to be able to enter the host via hydathodes pores. Since it is the first environment encountered by the bacterium in the plant, hydathodes are a particularly meaningful compartment to study through the scope of bacterial fitness.

Because the apoplasm of hydathodes is filled with nutrient-depleted xylem sap, we hypothesized that Xcc encounter specific environmental conditions during the early infection process, including poor nutrient availability, osmotic stress and plant defenses that they need to overcome to establish successfully (Luneau et al., in prep). To determine which genes contribute to Xcc fitness in hydathodes, we performed a genome-wide screening using our RB-TnSeq library.

Due to the anatomy of the hydathodes, we expected that the tight entry points and the constrained space inside the tissue would act as a strong bottleneck in the inoculation process (Cerutti et al., 2017). Conveniently, thanks to the barcode feature of our library, the retrieval of individual infected hydathodes allowed us to precisely count the number of different Xcc mutant strains that enter the hydathodes during the inoculation procedure (Figure 2a; see Methods). We observed that an average of 35,000 bacterial strains could be inoculated within individual hydathodes during a single infection event. While this result was a prerequisite for estimating the number of hydathode samples needed to perform the screening in the best conditions, it also informs us on the capacity of hydathodes to host a massive population of Xcc during infections. Cauliflower hydathodes each display an average of 30 pores (Cerutti et al., 2017) which suggests that around 1,200 bacteria can enter each of the hydathode pores. This evaluation indicates that, under natural conditions, entry into hydathodes does not constitute a biological bottleneck. However, in the frame of the RB-TnSeq screening, this bottleneck effect strongly limits the inoculation to only a subset of the library mutants in the same microenvironment. In order to overcome a potential bias and obtain reproducible results, we sampled over 1,600 hydathodes from around 100 plants per biological replicate (Figure S1).

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Previous work had demonstrated that Xcc infection remains contained into the cauliflower hydathodes for 6 days before entering the xylem vessels (Cerutti et al., 2017). We therefore chose to study the fitness of Xcc mutants after 3 and 6 days of hydathodes colonization, with the hope to decouple hydathodes early infection processes and adaptive responses in a settled population. We could identify 172 genes as directly contributing to Xcc fitness into hydathodes (Table S2). Almost all the genes found to be important at 3 dpi were also found at 6 dpi (Figure 2b). A large majority of the genes were sorted out by our RB-TnSeq screening because the associated mutants displayed a loss of fitness. A GO terms enrichment analysis revealed that functions related to the biosynthesis of cofactors, purine (Inosine Monophosphate), LPS and multiple amino acids were significantly associated with Xcc fitness in hydathodes. We also identified phosphate uptake and gluconeogenesis as statistically enriched pathways.

In order to go beyond the descriptive value of our dataset, we constructed 12 in-frame deletion mutants on candidate genes that we wanted to investigate further (Table 1). To validate the results of the large-scale fitness assay, the phenotype of these 12 mutants was assessed by a competition assay where each mutant was co-inoculated in a 1:1 ratio against the wild-type strain. At 6 dpi, Competitive Indexes (CI) values obtained in dip-inoculated hydathodes were well correlated with the RB-TnSeq data (Spearman correlation coefficient r = 0.75, p-value = 0.0044; Figure 3a). This observation validates the RB-TnSeq screening results and allows the extrapolation of descriptive loss of fitness into functional importance of mutated genes. We also evaluated the ability of our set of mutants to generate disease symptoms by wound inoculation on cauliflower (Figure 3b). We could show that the hisH (XC_2377) mutant, auxotrophic for histidine, the citM (XC_0810) mutant, devoid of citrate transporter, and PhaE-PhbC (XC_1958/XC_1959) mutant, impaired in the biosynthesis of the polyhydroxyalkanoate energy storage compound, displayed both a loss of fitness in the hydathodes and a defect in pathogenicity. Notably, two putative transcriptional regulators, XC_0449 and XC_1431, as well as two genes without any predicted functions, XC_3253 and XC_3388, were strongly affected in pathogenicity. This is particularly interesting because it emphasizes the strength of the RB-TnSeq approach to identify genes crucial for bacterial fitness without any a priori on their function or biological role.

Metabolic adaptation is a key fitness determinant for Xcc into plant-associated environments

We then hypothesized that a xylem-dwelling bacterium such as Xcc is adapted to its vascular lifestyle, in particular from the nutrition standpoint. Therefore, we also investigated the genetic basis of Xcc adaptation to the xylem environment. However, because the inoculation of the xylem vessels by piercing-like methods imposes a very strong bottleneck, we decided to use xylem sap as a proxy for this environment. Xylem sap can be easily collected from cauliflower (Dugé de [START_REF] De Bernonville | Transcriptional reprogramming and phenotypical changes associated with growth of Xanthomonas campestris pv. campestris in cabbage xylem sap[END_REF] and the large amounts gathered allowed us to grow the RB-TnSeq library in flasks (ex-planta). We identified 53 genes as key fitness determinants of Xcc in xylem sap. While 11 are specific to this condition, 42 were also found to be required for hydathodes colonization at 6 dpi (Figure 2b; Table S3). Interestingly, we managed to identify 19 genes as commonly important for Xcc fitness in all three plant-

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( " associated conditions investigated here (hydathodes 3 dpi, 6 dpi and xylem sap; Figure 2b; Table S4). Only purine (Inosine monophosphate) biosynthesis as well as vitamins (NADH and Folate) and TCA cycle-related pathways are found in all cases. While this might seem revealing, these quasi-essential functions are also impacted in vitro and are therefore not specifically interesting for the study of in planta fitness (Figure S3). Nevertheless, we sorted out ppGpp metabolism as specifically important in our screening in xylem sap, suggesting that Xcc faces adverse conditions that require a stringent response. We did not detect a strong metabolic signature of Xcc adaptation into xylem sap as compared to hydathodes. Remarkably, it was the opposite: biosynthesis of almost all amino acids (except cysteine, methionine, proline and valine) were required for Xcc optimal multiplication into the hydathode compartment but were presumably not limiting in xylem sap (Table S5). Only mutants on the proline biosynthesis pathway showed a significant and specific fitness defect in xylem sap.

TnSeq vs. RNAseq: two sides of the same story

A recent study in our group investigated the physiology of Xcc in hydathodes using a transcriptomic approach (Luneau et al., in prep). We saw that over 800 genes are deregulated in Xcc between early infection (4 hours post inoculation; hpi) and later settlement of the bacteria in the plant (3 days post inoculation). Because we identified overlapping pathways associated with Xcc lifestyle in the hydathodes using our RB-TnSeq approach, such as phosphate uptake and regulation of virulence factors, we decided to compare the transcriptomic response of Xcc in hydathodes to the RB-TnSeq results obtained here. We observed a complete lack of correlation between the RB-TnSeq results obtained at 6 dpi into the hydathodes and the change in genes expression between 4 hpi and 3 dpi (Figure S3). In fact, only 10 genes could be identified as differentially expressed in RNAseq and important for the competitive fitness of Xcc in hydathodes by RB-TnSeq. Here, we confirm the previous observations of [START_REF] Helmann | Genome-wide identification of Pseudomonas syringae genes required for fitness during colonization of the leaf surface and apoplast[END_REF] that both approaches are totally uncorrelated when studying a plant pathogen. One explanation is that they measure different aspects of bacterial physiology: while RNAseq captures a snapshot of the population's transcriptome at a given time of infection, RB-TnSeq compiles the history of individual cells over the whole infection period. The other reason is that RB-TnSeq looks at the direct contribution of each gene on bacterial fitness while RNAseq only

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describes their expression level. Therefore, transcriptomic profiling by RNAseq and fitness assessment by RB-TnSeq are complementary approaches to study the same question.

RB-TnSeq in hydathodes quantifies the cost of virulence and identifies new putative regulators of pathogenicity

It is widely considered that virulence factors expressed by bacterial pathogens are important for their fitness in the host in the sense that they are critical to the colonization of this special niche. However, our experimental RB-TnSeq data shows that only a few genes identified as important for Xcc fitness in the hydathodes are related to virulence functions [START_REF] He | Comparative and functional genomics reveals genetic diversity and determinants of host specificity among reference strains and a large collection of Chinese isolates of the phytopathogen Xanthomonas campestris pv. campestris[END_REF]; Figure S5). We see that genes involved in EPS biosynthesis and T2SS contribute to Xcc fitness, but none of the T3SS machinery components or Type III effectors, nor quorum sensing signal biosynthesis genes came out of the screen. However, we observe a gain of fitness in mutants associated with major regulators of virulence factors including the hrpG and hrpX transcriptional activator of the T3SS and the rpfC and rpfG genes encoding the two-component system involved in quorum sensing signal perception, as well as many transcriptional regulators involved in adaptive responses to the environment such as xibR (iron metabolism), ravR (response to oxygen tension), hpaR (extracellular proteases production), vemR (motility and exopolysaccharides production) and clp (exopolysaccharides and extracellular enzymes production) (Table 2).

Table 2 | Genes for which RB-TnSeq mutants displayed a gain of fitness during hydathodes infection

TnSeq approaches are prone to such counterintuitive results as they evaluate the fitness of individual cells in a population context. In particular, mutations associated with the production of public goods -resources secreted in the extracellular space that are available to

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the whole population -can be subject to cross-complementation at the population level. Thus, while inactivation of individual genes may not allow the detection of fitness loss in a mixed population, mutation of the regulators suppresses the cost of expressing the set of virulence factors and sometimes results in an apparent gain of fitness. This cheater-like behavior is generally visible in dense bacterial populations. In our case, Xcc cells are confined and tightlypacked within hydathodes, which, in the light of our data, suggests (i) that hydathodes constitute a conducive environment for cheater-like behavior and (ii) that RB-TnSeq can finely quantify the cost of virulence during Xcc infection.

A closer look into the mutants displaying a gain of fitness in hydathodes revealed that 3 out of the 13 genes have not been characterized. Though XC_0522 is predicted to be a XREfamily transcriptional regulator, the functions of XC_3388 and XC_RS10905 remain elusive as they are annotated as encoding a "hypothetical protein" and a "stress-induced protein" respectively. However, due to their phenotype in hydathodes, we hypothesize that these 3 genes encode regulators of adaptation and/or pathogenicity. Among them, the XC_3388 mutant shows a strong decrease in its ability to trigger disease symptoms and a rough phenotype on plates (Figure 3b). Consequently, we chose to focus our attention on understanding its role in Xcc physiology and fitness. We performed multiple functional validation assays to explore the consequence of XC_3388 deletion on Xcc and investigated motility, EPS production, extracellular enzyme secretion and in vitro growth (Figure 4). In addition to the loss of pathogenicity, the XC_3388 mutant is hyper-motile on swimming plates and displays lower extracellular amylase activity. Additional metabolic fingerprinting on Biolog plates showed that the XC_3388 mutant is affected in metabolism of glucose, glutamate, maltose and arbutin.

Subsequent evaluation of growth on these carbon sources confirmed the deregulation of metabolic pathways, adding to the pleiotropic role of this putative regulator (Figure S5).

Protein sequence analysis by BLAST revealed that XC_3388 is well-conserved within the gamma-proteobacteria genomes (> 25% identity on at least 50% sequence length). However, the only domain predicted in the sequence of XC_3388 is the domain of unknown function DUF1631 for which no information is available. Based on its wide impact on Xcc physiology and the fact that it was identified by RB-TnSeq with the same gain-of-fitness phenotype as major regulators, we conclude that XC_3388 is a novel regulator of virulence and adaptation in Xcc.

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Discussion

RB-TnSeq captures the importance of genes with unknown functions and provides new targets for pathogens control

The RB-TnSeq method is gaining in popularity thanks to its ability to screen at the genome-wide scale and provide phenotypic information about individual gene contribution to bacterial fitness. [START_REF] Price | Mutant phenotypes for thousands of bacterial genes of unknown function[END_REF] exploited this feature to investigate the adaptive value of each gene from over 30 ecologically distant bacterial strains in multiple conditions. By measuring the contribution of each gene to specific conditions, they could produce co-fitness relationships and associate a functional relevance to 11,000 uncharacterized genes. Here, we chose to investigate the role of the conserved XC_3388 hypothetical protein and could show that it is a major regulator of adaptation and pathogenicity in Xcc. It was very recently shown that major pathogenicity regulators could be targeted by plant defense mechanisms to block the infection inside the bacterial cell. Indeed, (Wang et al., 2020) demonstrated that the sulforaphane secondary compound of Arabidopsis thaliana covalently modifies a residue of the HrpS T3SS activator in Pseudomonas syringae to impair disease development. In addition, [START_REF] Singla-Rastogi | Plant Small RNA Species Direct Gene Silencing in Pathogenic Bacteria as well as Disease Protection[END_REF] recently showed that plants direct small RNAs against pathogenic bacteria in a strategy called Antibacterial Gene Silencing (AGS). AGS against P. syringae triggered RNA interference in the production of the HrpL T3SS activator and significantly reduced the severity of disease symptoms. Expanding our knowledge of bacterial cell processes could therefore initiate the development of new biotechnology-derived control strategies against specific pathogens. In the same fashion, the list of essential genes that we provide for Xcc constitute an asset for the design of new antimicrobial compounds.

Amino acid biosynthesis is required for optimal fitness in plant-associated environments but each pathosystem is different

The main objective of this study was to identify bacterial fitness determinants involved in Xanthomonas adaptation to the in planta lifestyle. Using RB-TnSeq as a genome-wide screening method, we showed that over 180 genes are required for Xcc to fully thrive in hydathodes and xylem sap. The most represented function that we found to be important was amino acid biosynthesis. Consistently with previous TnSeq studies on plant pathogens, we 5M sorted out auxotrophic mutants as strongly affected in fitness. This observation suggests that certain metabolic pathways such as the biosynthesis of histidine are crucial for in planta fitness.

Consequently, we can hypothesize that the apoplastic plant tissue environment is nutrient limited and that bacteria exploit to the best of their abilities the available sources of nutrients to sustain their growth. The same hypothesis was formulated by Helmann and colleagues (2019) who found that tryptophan, histidine and leucine/isoleucine/valine pathways mutants are limited in their growth during Pseudomonas syringae colonization of the bean leaf mesophyll.

Interestingly they identified proline as an important biosynthetic pathway in leaf mesophyll, which we identified in xylem sap but not in hydathodes. On the other hand, [START_REF] Royet | Identification by Tn-seq of Dickeya dadantii genes required for survival in chicory plants[END_REF] identified the sulfur-containing amino acids methionine and cysteine as important requirements during Dickeya dadantii infection of chicory, which neither our study nor Helmann's did.

Therefore, all these TnSeq results suggest that, even though amino acids are key cellular components, the needs of pathogenic bacteria are different and likely depend on their own metabolic capacities as well as the nutrient availability within the tissues of their host.

While it was recently shown that vascularization of phytopathogenic bacteria only relies on the presence of a single cellobiohydrolase (Gluck-Thaler et al., 2020), hydathodes and xylem appear to be very different environments for which Xcc is adapted, at least from the nutrition standpoint. It could be argued that restarting the cultures in fresh xylem sap during the RB-TnSeq assay renewed the availability of nutritional compounds and thus prevented the detection of fitness defects in auxotrophic mutants. However true this remark is, it is important to keep in mind that the xylem environment in planta is characterized by a strong flux of sap which maintains a constant provisioning of nutrients [START_REF] Brodersen | Functional Status of Xylem Through Time[END_REF]. We therefore conclude that the ability of Xcc to thrive in both hydathodes and xylem is a hallmark of its ability to adapt to the environments it colonizes during plant infection. Previous work on cabbage showed that xylem sap carries amino acids, organic acids and sugars in the low millimolar range and that most of these compounds are actively consumed by Xcc (Dugé de Bernonville et al., 2014).

However, there is no clear correlation between the abundance of amino acids or their utilization and the importance of biosynthetic genes for Xcc fitness in xylem sap. In the future, investigating the metabolomic composition of guttation fluids and xylem sap are needed to understand what is really available for Xcc in the cauliflower leaf. This would complement the current efforts spent on the reconstruction of bacterial metabolic networks and ultimately help comprehend the dynamics of plant infection by phytopathogenic bacteria [START_REF] Kim | A Genome-Scale Co-Functional Network of Xanthomonas Genes Can Accurately Reconstruct Regulatory Circuits Controlled by Two-Component Signaling Systems[END_REF][START_REF] Gerlin | Genome-Scale Investigation of the Metabolic Determinants Generating Bacterial Fastidious Growth[END_REF].

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Detection of cheaters highlights the ability of RB-TnSeq to investigate single strain fitness in a population context

An important observation of our study is the population behavior of the pool of Xcc mutants during hydathodes infection. Indeed, we could not detect any alteration of fitness in T3SS mutants. We suggested that this apparently intact fitness phenotype was in fact the consequence of cross-complementation at the population level. In a situation where a mutant defective in the production of a public good is surrounded by individuals carrying the WT phenotype, the producers mask the phenotype of the non-producer. This complementation in trans can then be seen as a problem for the evaluation of the fitness of individual mutants.

However, it is a unique chance to study the real importance of genes for bacterial fitness in a population context. It is then normal to miss on the typical public goods such as quorum sensing signal production or T3SS-mediated immunity suppression that are shared between members of the community. Here, we obtain two interesting outcomes: (i) amino acids identified as required for fitness cannot be obtained by cross-feeding between Xcc individuals and (ii)

mutants for costly processes that can be shared behave like cheaters and display a gain of fitness. This is the case for the transcriptional activators of the costly T3SS, hrpG and hrpX, for which mutants benefit from the cooperators without experiencing the cost of production as described for Salmonella typhimurium [START_REF] Sturm | The Cost of Virulence: Retarded Growth of Salmonella Typhimurium Cells Expressing Type III Secretion System 1[END_REF]. According to the Black Queen Hypothesis, it becomes evolutionarily more advantageous in the short term to lose these costly genes rather than carry them [START_REF] Morris | The Black Queen Hypothesis: Evolution of Dependencies through Adaptive Gene Loss[END_REF]. Nevertheless, in the grand scheme of Xcc life cycle, losing the ability to repress host immunity appears as a weakness to initiate infection into the next host and is likely counter-selected. However, this observation suggests that it would be possible for non-pathogenic strains present in the phyllosphere to co-infect the host along a pathogenic one and take advantage of it to multiply efficiently.

Host and bacterial factors can counter-select cheaters emerging from social cooperative behaviors

Surprisingly, not all shared goods follow the Black Queen Hypothesis. Indeed, we observed a loss of fitness in T2SS-deficient mutants in our TnSeq assay. In Xcc, the T2SS allows the secretion of cell wall degrading enzymes into the environment which produces oligosaccharides-derived carbon sources and facilitates Xcc movement within the host. Given LB the nature of the T2SS, enzymes secreted in the environment are expected to diffuse freely and thus benefit all the individuals of the community. Yet, it seems to be important for individual cells. One possibility would be that an important T2SS substrate is not secreted into the extracellular medium and remains anchored into the outer membrane. This phenomenon has been shown to happen in the Dickeya dadantii phytopathogen, wherein the PnlH outer membrane protein is exported through the TAT pathway but remains associated with the outer envelope of the cell [START_REF] Ferrandez | Novel mechanism of outer membrane targeting of proteins in Gram-negative bacteria[END_REF]. Another explanation could be the limited diffusion of either the enzymes or the degradative products in the medium.

Moreover, there is a growing amount of results showing the importance of spatiotemporal heterogeneity in the dynamics of microbial populations [START_REF] Ackermann | A functional perspective on phenotypic heterogeneity in microorganisms[END_REF][START_REF] Friesen | Social Evolution and Cheating in Plant Pathogens[END_REF]. The physical environment of the host tissues could therefore play an important role in the viability of cheaters during the infection. While we showed that there is no strong bottleneck at the entry step into hydathodes, we know that Xcc can massively accumulate in the epithem which provides favorable conditions for the multiplication of cheaters. The passage from the hydathodes to the xylem then constitutes a putative bottleneck, in which the structure of the host could be the main driver to control the frequency of cheaters in the population. The same argument applies to mesophyll colonization from xylem vessels at later stages of the infection.

The structural organization of the host tissues also conditions the isolation of bacterial individuals and therefore leads them to challenge their intrinsic fitness. It was for example nicely shown by Rufian and colleagues that Pseudomonas syringae infection of tomato leaves mesophyll counter-selects cheaters at low density but supports them at high density [START_REF] Rufián | Pseudomonas syringae Differentiates into Phenotypically Distinct Subpopulations During Colonization of a Plant Host[END_REF]. Similarly to what we suggest in Xcc, they showed that this opportunistic niche occurring throughout the colonization process allows the expression of phenotypic heterogeneity in an isogenic population. Division of labor, whereby bacterial sub-populations emerge by differentially expressing costly cellular components, could therefore constitute an important adaptive strategy leading Xcc to an increased fitness in hydathodes. This distribution of costly biological processes was observed once in Xcc during xylem colonization, where two subpopulations emerge that differ on their perception of the quorum sensing signals [START_REF] Samal | New insight into bacterial social communication in natural host: Evidence for interplay of heterogeneous and unison quorum response[END_REF]. Interestingly, authors showed that the frequencies of each subpopulation changed during host colonization to favor heterogeneity during early disease stages and became more homogeneous at later stages when densely-packed cells all need to acquire nutrients. It is also worth noting that in the human pathogen Salmonella typhimurium, the expression of an L avirulent T3SS-deficient phenotype is necessary to control the emergence of genetic mutants that could have a deleterious effect on disease progression [START_REF] Diard | Stabilization of cooperative virulence by the expression of an avirulent phenotype[END_REF].

Methods

Bacterial strains and growth media

In this study, we used the Xanthomonas campestris pv. campestris reference strain 8004 (Daniels et al., 1984), a spontaneous rifampicin-resistant derivative of the Xcc NCPPB No. 1145 isolated from cauliflower in Sussex, UK, in 1958, which had its genome sequenced by [START_REF] Qian | Comparative and functional genomic analyses of the pathogenicity of phytopathogen Xanthomonas campestris pv. campestris[END_REF]. We also used the Xcc 8004 GUS-GFP strain constructed by (Cerutti et al., 2017) as a recipient for the RB-TnSeq library and as a genetic background for all the deletion mutants.

The Xcc 8004::GUS*-GFP* variant contains a point mutation inactivating the catalytic sites of both reporter protein as described in Luneau et al. (in press). We cultivated Xcc in MOKA rich medium (4 g.l -1 Yeast extract, 8 g.l -1 Casamino acids, 1 mM MgSO4 and 2 g.l -1 K2HPO4; Blanvillain et al., 2007), MME Glucose poor medium (10.5 g.l -1 K2HPO4, 4.5 g.l -1 KH2PO4, 1 g.l -1 (NH4)2SO4, 1 mM MgSO4, 0.15% (w/v) Casamino acids, 20 mM Glucose; [START_REF] Arlat | Xanthomonas campestris Contains a Cluster of hrp Genes Related to the Larger hrp Cluster of Pseudomonas solanacearum[END_REF] or MME Glucose complemented with DropOut -Leucine/Tryptophan/Histidine supplements instead of casamino acids (10.5 g.l -1 K2HPO4, 4.5 g.l -1 KH2PO4, 1 g.l -1 (NH4)2SO4, 1 mM MgSO4, 0.15% (w/v) DropOut -LTH, 20 mM Glucose) at 28°C under agitation at 200 rpm or on MOKA-agar plates.

To obtain clean deletion mutants, we used the SacB method [START_REF] Schäfer | Small mobilizable multi-purpose cloning vectors derived from the Escherichia coli plasmids pK18 and pK19: selection of defined deletions in the chromosome of Corynebacterium glutamicum[END_REF] and constructed pK18 derivatives containing regions homologous to the genomic sequences upstream and downstream of the gene of interest to be removed by double-recombination. For in trans complementation, we constructed pK18_CompR3 plasmid derivatives to allow the genomic insertion of the complementation cassette in a neutral site between genes XC_1301 and XC_1302 (Luneau et al., in prep). We used the Escherichia coli strain TG1 as carrier for the plasmids and the helper strain pRK2073 to introduce plasmids into Xcc by triparental conjugation [START_REF] Figurski | Replication of an origin-containing derivative of plasmid RK2 dependent on a plasmid function provided in trans[END_REF][START_REF] Ditta | Broad host range DNA cloning system for gram-negative bacteria: construction of a gene bank of Rhizobium meliloti[END_REF]. We grew E. coli strains at 37°C on LB-agar or liquid LB under shaking at 200 rpm. When appropriate, we used the antibiotics rifampicin (50 µg.ml -1 ), kanamycin (50 µg.ml -1 ), spectinomycin (40 µg.ml -1 ) and the fungicide L pimaricin (30 µg.ml -1 ). The lists of strains, plasmids and primers used in this study are presented in Table S6 and Table S7.

Plant material and xylem sap harvest

We used Brassica oleracea var botrytis cv. Clovis F1 cauliflower as a plant host model because of its susceptibility to Xcc infection and the large size of its leaves which display thick hydathodes conveniently visible with the naked eye. We grew plants under greenhouse conditions and used them at 4 weeks after sawing. For all the RB-TnSeq, competition and pathogenicity assays, we inoculated the second true leaf of each plant (second leaf above the cotyledons). We then kept plants in classical growth chambers conditions until completion of the experiment: 9 h light; 22°C; 70% relative humidity. For RB-TnSeq screening of Xcc genes involved in the adaptation to xylem sap, we collected root-pressure exudates from cauliflower as described in Dugé de [START_REF] De Bernonville | Transcriptional reprogramming and phenotypical changes associated with growth of Xanthomonas campestris pv. campestris in cabbage xylem sap[END_REF]. Briefly, we decapitated the cauliflower stem above the cotyledons, rinsed with distilled water and manually collected the excreted fluids (here called xylem sap). Though we discarded the two first rounds of collection to avoid plant debris contamination, we sampled xylem sap throughout the day, pooling the samples of multiple plants altogether and immediately storing them at -20°C.

Construction of the RB-TnSeq library and transposon insertion site sequencing

We constructed the RB-TnSeq barcoded transposon insertion library by (i) conducting transposon mutagenesis using a barcoded mariner transposon library and (ii) performing the mapping of transposon insertion sites as well as barcode association, as previously described [START_REF] Wetmore | Rapid quantification of mutant fitness in diverse bacteria by sequencing randomly bar-coded transposons[END_REF]. The E. coli WM3064 donor library containing the barcoded mariner plasmid, pKMW3, was recovered from a glycerol stock in LB kanamycin containing 300 M diaminopimelic acid (DAP) and conjugated into Xcc 8004::GUS-GFP overnight on MOKA plates containing DAP. The many separate conjugations were then resuspended as a single pooled mixture and spread on MOKA kanamycin plates for selecting mutants. Over 590,000 kanamycin-resistant Xcc colonies were pooled for the library. All colonies were resuspended in L5 250 mL MOKA kanamycin, diluted to a starting OD600 0.2 and grown at 28 °C with shaking to OD600 1.0. Finally, 250 L 80% glycerol was added to 1-mL aliquots and frozen at -80 °C.

Fitness screening in hydathodes

The RB-TnSeq library is kept as aliquots at -80°C. For each biological replicate, we fully melted a single 2 ml-aliquot of the library and grew the culture overnight at 28°C with shaking at 200 rpm in 125 ml of MOKA medium. We washed twice the culture by serial centrifugation (6,000

x g, 10 min) and resuspension cycles in MgCl2 1mM. After measurement of OD600, we pelleted 10 9 Xcc cells by centrifugation at 13,000 x g for 5 min and stored them at -80°C to be used as T0 samples. From the rest of the washed suspension, we adjusted the Xcc inoculum to OD600 = 0.1 (10 8 cfu/ml) in MgCl2 1mM + 0.5% v/v Tween 80 and we performed hydathodes inoculation by dipping cauliflower leaves for 15 s inside the bacterial suspension (Cerutti et al., 2017).

Because infection of the hydathodes relies on the guttation process, we placed plants in growth chamber conditions and covered them with a mini-greenhouse lid to reach 100% relative humidity during 24h. We then removed the lids and allowed the infection to proceed for 3 or 6 days. After incubation, we retrieved Xcc populations by macro-dissection of hydathodes (16 per leaf) using a 1.5 mm-diameter Biopsy Punch (Miltex®, Electron Microscopy Sciences). In total, we collected around 1,650 hydathodes for each of the four biological replicates. During sampling, hydathodes were placed in MgCl2 1mM to be later bead-grinded for 2 min at 30 Hz.

We performed DNA extraction using the Promega Wizard® Genomic DNA Purification Kit but we included an additional protein degradation step by incubating the samples with 400 µg/ml of proteinase K at 37°C for 1h before protein precipitation. Samples were stored at -80°C until preparation for barcode sequencing.

Fitness screening in vitro: Xylem sap & synthetic media

Similarly to the screening in planta, we prepared a culture of the RB-TnSeq library from stored aliquots, grew it in MOKA for 4 hours at 28°C with 200 rpm agitation and washed it twice in MgCl2 1mM. Again, we pelleted 10 9 Xcc cells by centrifugation at 13,000 x g for 5 min and stored them at -80°C to be used as T0 samples. From the rest of the washed suspension, we LL adjusted the Xcc inoculum to OD600 = 0.05 (5.10 7 cfu/ml) in 10 ml of either 0.22 µm-filtrated cauliflower xylem sap, MOKA rich medium, MME + Glucose poor medium or MME -Casa + Glucose + DropOut -LTH. We incubated all cultures at 28°C under agitation at 200 rpm.

Because the differences in fitness become more noticeable over time, it is important to keep in mind that the clarity of RB-TnSeq results depends on the number of generations. Therefore, we allowed bacterial growth to go up to 6-7 generations in all media. However, except in MOKA rich medium, Xcc growth could not attain such a number of generations before reaching the stationary phase. We therefore chose to restart cultures at the end of the exponential phase by centrifugation (6,000 x g, 5 min) and resuspension of the whole population in a larger volume of fresh medium at OD600 = 0.05. At the end of the growth, we pelleted 10 9 Xcc cells by centrifugation at 13,000 x g for 5 min and stored the pellets at -80°C until DNA extraction (same protocol as before).

Barcode sequencing and calculation of gene fitness

Barcode sequencing, mapping, and analysis to calculate the relative abundance of barcodes was done using the TnSeq methodology and computation pipeline developed by [START_REF] Wetmore | Rapid quantification of mutant fitness in diverse bacteria by sequencing randomly bar-coded transposons[END_REF]; the code is available at https://bitbucket.org/berkeleylab/feba/. For each experiment, fitness values for each gene are calculated as a log2 ratio of relative barcode abundance after library growth in a given condition divided by relative abundance in the time0 sample. Fitness values are normalized across the genome so the typical gene has a fitness value of 0. Fitness values from sequencing replicates were averaged for each experiment.

Fitness data analysis

We considered genes to be important for Xcc fitness when the mutants were strongly affected, i.e. |f| > 1 and when this phenotype was deemed robust, i.e. |t-score| > 3 [START_REF] Wetmore | Rapid quantification of mutant fitness in diverse bacteria by sequencing randomly bar-coded transposons[END_REF][START_REF] Helmann | Genome-wide identification of Pseudomonas syringae genes required for fitness during colonization of the leaf surface and apoplast[END_REF]. Because we did four independent biological replicates of each screening experiment, we decided to only retain genes that match those criteria in at least three of the four replicates. Such stringent requirements assured us to select robust and biologically relevant phenotypes with good confidence. We performed data mining and graphic representations with LO R version 3.6.3. Enrichment analysis considering gene ontology was then conducted using the topGO package version 2.40.0 using Fischer's test and p-value < 0.01 (Alexa et al., 2006).

Competition assays

We used competition assays to validate the RB-TnSeq screening in planta by co-inoculation of two strains of interest in a 1:1 ratio. We mixed the Xcc strain 8004 GUS*-GFP* (reference strain, hereafter WT*) and deletion mutants in the 8004 GUS-GFP background (challengers)

to assess the fitness of the latter as described in Luneau et al. (in press). Briefly, we inoculated cauliflower hydathodes with the same protocol as for the RB-TnSeq assay except that we adjusted the inoculum suspensions to OD600 = 0.05 for each strain (final OD600 = 0.1) in MgCl2 1mM + 0.5% v/v Tween 80. In order to maximize the throughput of the validation assays, we chose to inoculate only one plant for each of the mixes. We plated inoculation suspensions to use as T0 reference samples as well as 6 dpi samples consisting of 16 pooled and grinded hydathodes. The Competitive Index (CI) of each strain was calculated as the ratio of the relative frequencies of mutant vs. reference strains in the 6 dpi infected sample compared to the T0 inoculum [START_REF] Taylor | Use of phoA gene fusions to identify a pilus colonization factor coordinately regulated with cholera toxin[END_REF]Macho et al., 2007). Hence, we consider a CI > 1 as a gain of fitness of the mutant compared to the WT* reference strain and a CI < 1 as a loss of fitness. We performed 4 independent biological replicates of the competition assays for all strains tested.

Pathogenicity assays

We evaluated bacterial aggressiveness of the mutant strains by piercing-inoculation in the midrib of cauliflower leaves using a needle dipped in a Xcc inoculum adjusted at OD600 = 0.1.

We assessed disease progression at 7 and 10 days post-inoculation according to the annotation scale presented in Luneau et al. (in prep). We performed pathogenicity assays in three independent biological replicates of five individual plants each. Significance of differences observed in symptoms severity was assessed using the non-parametric Kruskal-Wallis test with = 0.05.

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Motility

Overnight cultures of Xcc in MOKA were washed by centrifugation (4,000 x g; 5 min) and resuspended in sterile water. 2-µl of bacterial suspensions adjusted at 10 8 cfu/mL were spotted on swimming plates (0.03% Bacto peptone, 0.03% yeast extract, 0.3% agar; [START_REF] Su | Characterization of the GntR family regulator HpaR1 of the crucifer black rot pathogen Xanthomonas campestris pathovar campestris[END_REF] and incubated 48 h at 28°C. Ability to perform flagellar motility was assessed by the presence and size of white halos expanding from the colonies.

Extracellular enzymes activity assay on plates

Extracellular enzymatic assays of Xcc strains were tested by spotting 5 L of an overnight culture adjusted to 4.108 cfu/mL on plates containing 15-mL of different phenotypic agarcontaining media. Plates were incubated at 28 °C and imaged 24 hours post inoculation.

Diameters of colonies and halos of degradation were measured to calculate enzymatic activity

as follows: PrA = [ (rhalo)2-(rcolo)2]/ [ (rcolo)2]
with "r" corresponding to the radius. Each experiment was biologically replicated at least three times. For protease activity assays, Xcc' cells were spotted on 0.5 % skimmed milk MOKA plates supplemented with 30 µg/mL pimaricin (Luneau et al., in prep). For Amylase activity assays Xcc cells were spotted on 0.125 % potato starch (prolabo, VWR) MOKA plates supplemented with 30 µg/mL pimaricin. After a 24h incubation step at 28°C and colonies diameter measurement, bacterial cells were washed using distilled water and plates were stained using lugol solution until a strong blue coloration and starch degradation halo appeared.

Measurement of exopolysaccharide production

Extracellular EPS production was measured as described (Luneau et al., in prep). Briefly, an overnight growth of each strain in MOKA was used to inoculate 20 mL of MOKA supplemented with 50 µg/mL of rifampicin at 2.10 7 cfu/mL. After 24 hours of growth, 12 mL were centrifuged for 15 min at 6,500 x g. EPS present in the supernatant were precipitated with ethanol. Bacterial and EPS pellets were dried for 8 hours at 65°C before being weighed. EPS production corresponds to the ratio of dry weight EPS on dry weight bacterial cells.

LR

Carbon and nitrogen substrates phenotyping

Metabolic properties of WT and mutant strains were characterized using Omnilog-Biolog were analyzed using the R opm script as previously described (Vaas et al., 2012;Vaas et al., 2013).

Growth measurements in vitro

In vitro growth curves were generated using a FLUOStar Omega apparatus (BMG Labtech, Offenburg, Germany) and 96-well flat-bottom microtiter plates (Greiner) with 200 µL of bacterial suspensions. After an overnight preculture in MOKA rich medium, cells were harvested by centrifugation at 9,500 x g for 4 minutes, washed and resuspended in MME minimal medium. Bacterial suspensions inoculated at an optical density at 600 nm (OD600) of 0.15 were prepared in MME or MME supplemented with either glucose, glutamate, maltose or arbutin at 20 mM and MOKA media. For each experiment, we performed 4 replicates coming from 2 independent precultures. The microplates were shaken continuously at 700 rpm using the linear-shaking mode. Each experiment was repeated 3 times and a representative experiment is shown.

Conclusion

We identified over 180 genes as key fitness determinants that Xanthomonas campestris pv.

campestris requires to efficiently thrive into hydathodes and xylem sap. A further investigation of 12 genes validated our RB-TnSeq approach and uncovered the importance of uncharacterized LM genes for the regulation of adaptive traits during host infection. We also retrieved major regulators of adaptation and pathogenicity and hypothesize that they are involved in social cooperative behaviors at the population level. In particular, we characterized the role of the XC_3388 hypothetical protein in the physiology of Xcc and show that it is a novel regulator of adaptation and pathogenicity. We also provide a list of 300 essential genes in Xcc which reinforces our understanding of fundamental cell processes. Complementary studies in leaf mesophyll tissue will enable the generation of a multi-environment map of genetic fitness determinants and thus address the questions of tissue specificity. Ultimately, it will deliver considerable insights into the dynamics of adaptive processes during the infection cycle of this major Xanthomonas pathogen.

ON

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Table S5 | Amino acid biosynthesis pathways are required for Xcc fitness in the host plant and in vitro media. Amino acids biosynthesis pathways required for Xcc fitness are indicated with (++) when all the genes of the pathway are important or (+) when only few genes are important, according to the BioCyc database. [Abstract] Competition assays are a simple phenotyping strategy that confront two bacterial strains to evaluate their relative fitness. Because they are more accurate than single-strain growth assays, competition assays can be used to highlight slight differences that would not otherwise be detectable.

Amino acids

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In the frame of host-pathogens interactions, they can be very useful to study the contribution of individual bacterial genes to bacterial fitness and lead to the identification of new adaptive traits. Here we describe how to perform such competition assay by taking the example of the model phytopathogenic bacterium

Xanthomonas campestris pv. campestris during infection of the mesophyll of its cauliflower host. This phenotypic assay is based on the use of a Competitive Index (CI) that compares the relative abundance of co-inoculated strains before and after inoculation. Since multiplication is a direct proxy for bacterial fitness, the evolution of the ratio between both strains in the mixed population is a direct way to assess differences of fitness in a given environment. In this protocol, we exploit the blue staining of GUSexpressing bacteria to count blue vs. white colonies on plates and estimate the competitiveness of the strains of interest in plant mesophyll.

Keywords: Competitive Index, Competition assay, Fitness, Mesophyll, Xanthomonas, Cauliflower, GUS,

Brassica oleracea

[Background] Over the years, topics of ecology and evolution have been increasingly important when studying host-microbe interactions. In addition to simply assessing the virulence of bacterial pathogens, matters of fitness and adaptation to the environment are now being addressed. Recently, large-scale high-throughput screening tools, such as RB-TnSeq (Randomly-Barcoded Transposon insertion site Sequencing), have been developed to efficiently identify the genetic determinants of bacterial fitness.

RB-TnSeq relies on the co-inoculation of a library of mutagenized bacteria, all carrying a unique barcode, to simultaneously evaluate the contribution of each gene to bacterial survival and growth [START_REF] Wetmore | Rapid quantification of mutant fitness in diverse bacteria by sequencing randomly bar-coded transposons[END_REF]. Such studies result in the identification of genes putatively implicated in bacterial adaptation to the host that then need to be confirmed by reverse genetics using simpler fitness assays.

Early on, it was proposed that competition assays could be used as an answer to this need. Typically, such competition assays are performed by co-inoculating two strains in a 1:1 ratio into a given environment and following the evolution of this ratio over time. If one of the strains grows more than the other, it is considered as more fit (in this specific environment) than its counterpart. The main limiting factor is then to be able to count separately the two mixed populations. A quite straight forward solution here is to use discriminating markers such as antibiotic resistances to count the abundance of each strain after plating on selective medium. Differential antibiotic resistances have been widely used in coinoculation assays (Macho et al., 2007 and2010;[START_REF] Feng | A Xanthomonas uridine 5'-monophosphate transferase inhibits plant immune kinases[END_REF] but it is known that such resistances often carry a strong cost of fitness that could interfere in studies that involve fine fitness mechanisms.

Also, they require to plate the samples twice, once on each selective medium, which can introduce a bias in the evaluation of the strains relative frequencies. Fluorescent markers provide an alternative to antibiotics but require costly imaging equipment [START_REF] Perrier | Spontaneous mutations in a regulatory gene induce phenotypic heterogeneity and adaptation of Ralstonia solanacearum to changing environments[END_REF]. Here we describe a visual blue/white screening using the enzymatic properties of the beta-glucuronidase (GUS) enzyme. The assay is then performed by co-inoculating a GUS-expressing strain in competition with a non-tagged strain: after plating on medium containing X-gluc (the substrate of the GUS enzyme), colonies of tagged bacteria will turn blue while the others will remain white. A similar Bio-protocol had been proposed before using LacZ as a marker in the Vibrio cholerae animal pathogen [START_REF] Fu | Infant rabbit colonization competition assays[END_REF]. However, even though the concept is similar, we feel that a detailed protocol for plant inoculations is very much needed.

Here, we chose the bacterial phytopathogen Xanthomonas campestris pv. campestris (Xcc) as a model to illustrate this protocol. Xcc is particularly interesting because it has the specificity to infect multiple organs and tissues of its cauliflower host (Brassica oleracea pv. botrytis cv. Clovis). After entry through the hydathodes, Xcc spreads through the xylem sap-conducting vessels and colonizes the leaf mesophyll of its host where it causes the typical symptoms of the Black rot disease (Vicente and Holub, 2013;[START_REF] An | Mechanistic insights into host adaptation, virulence and epidemiology of the phytopathogen Xanthomonas[END_REF]. We recently performed an RB-TnSeq screening on Xcc during cauliflower infection (unpublished data) that ultimately led us to set up a competition assay. In this protocol, we describe how this competition assay can be performed in the plant leaf mesophyll. We take the example of the well-described hrpX (transcriptional activator of the Type III Secretion System), hrcV (Type III Secretion System component) and xopAC (Type III Effector) mutants that display contrasted fitness phenotypes when confronted with the Xcc 8004 wild-type strain in planta. This protocol provides a basis that can be adapted for other plant compartments such as hydathodes or xylem as well as in vitro studies.

Availability of such protocol is particularly relevant given the number of plant pathogens that enter through and thrive into their host leaves.

Materials and Reagents With this system, the two challenged strains carry and express the GUS-GFP cassette, but only one of them will actually appear as tagged. We thus remove the possibility of a fitness cost associated with the cassette while still being able to differenciate the two mixed strains. 2. Centrifuge 2 ml of bacterial preculture for 5 min at 6,000 rpm (i.e., 3.3 x g) and wash twice in 1 mM MgCl2. Resuspend in 1 mM MgCl2 and measure OD600nm.

3. Prepare 1 ml of bacterial suspension in a 2-ml tube so that for each strain OD600nm = 0.1 final (i.e., 1 x 10 8 cfu/ml, note: this estimation has to be verified when working with other species by plating on solid medium) in 1 mM MgCl2.

4. Dilute each suspension to 1/100 in a 5-ml tube to obtain a final inoculum at OD600nm = 0.001 (i.e., 1 x 10 6 cfu/ml) in 5 ml of 1 mM MgCl2. For the WT* reference strain, prepare 10 ml of suspension at OD600nm = 0.001 as it will be used in all mixes.

5. Mix 2 ml of WT* suspension with 2 ml of each of the strains to test in another 5-ml tube (so that each mixed strain is at 5 x 10 5 cfu/ml but the final concentration of the inoculum is 1 x 10 6 cfu/ml).

B. Inoculation 1. Using a blunt syringe, filled with one milliliter of bacterial suspension, infiltrate the mesophyll of the 2 nd true leaf of cauliflower (for pictures of the procedure, see [START_REF] Cohn | Assays to Assess Virulence of Xanthoonas axonopodis pv. manihotis on Cassava[END_REF]. A large enough area should be infiltrated in order to later be able to sample a 6-mm leaf disc without taking any of the tissues damaged by the syringe. Typically, up to seven separate spots can be infiltrated on the same cauliflower leaf, thus allowing the inoculation of multiple strains or mixes on the same leaf. In this case, be careful to well separate infiltration areas to exclude crosscontamination.

2. Circle the infiltrated area on the lower side of the leaf to mark the infected tissue for later sampling.

3. Place the plants in the growth chamber and water them appropriately. 2. Perform serial 1/10 dilutions (10 µl in 90 µl of 1 mM MgCl2) using a multichannel pipette.

3. Take 100 µl of dilution 10 -3 and spread out them on round 92-mm MOKA plates containing the appropriate antibiotics (i.e., Rifampicin 50 µg/ml here) and fungicide (i.e., Pimaricin 30 µg/ml here) as well as X-Gluc 200 µM. In our case, spreading is performed by shaking using 4-mm glass beads until homogeneous repartition of the suspension.

4. Incubate 4-5 days at 28 °C to allow bacterial growth and blue staining of GUS-expressing colonies.

5. Count blue and white colonies, e.g., using a hand-held colony counter, to determine the ratio of mixed strains at T0. This is necessary for proper normalization during later calculation of the CI (see Data analysis section).

D. Sampling, plating and counting of relative frequencies in mixed populations after incubation 1. Three days after inoculation, sample mesophyll tissues by punching out a 6-mm leaf disc in the infiltrated area defined by the marker label and placing it in 200 µl of 1 mM MgCl2.

2. Grind leaf samples using 4-mm glass beads in 2-ml tubes (2 beads per tube) using the beadsassisted grinder for 2 min at 30 Hz.

3. Centrifuge shortly (five seconds) the tubes containing the ground material to gather it at the bottom.

4. Transfer 100 µl of ground tissue in a 96-well plate with conical bottom.

5. Proceed as described in Steps C2 to C5. However, because each strain displays a different phenotype and to ensure the presence of colonies from both strains, plate 50 µl of dilutions 10 -2 and 10 -3 .

Note: Classically, we advise to collect bacterial titers by counting the plates displaying between 30 and 300 colonies. However, because competition assays require to finely determine the number of CFU for each of the mixed strains, we recommend to count plates where there are at least 100 colonies for mix-inoculated samples.

Data analysis

For reproducibility purposes, experiments should be performed in at least four biological replicates.

A biological replicate is defined as a replication of complete experimental procedure with fresh buffers, fresh bacterial cells suspension prepared from cells grown on new solid medium and new batches of plants. Results of competition assays are displayed as a Competitive Index (CI), which is defined as the ratio of the relative abundance of mutant over WT* strain after incubation normalized by the relative abundance of mutant over WT* strain in the inoculum [START_REF] Taylor | Use of phoA gene fusions to identify a pilus colonization factor coordinately regulated with cholera toxin[END_REF]; Here, we used the Xcc 8004::GUS-GFP ΔhrpX, ΔhrcV and ΔxopAC mutants as an example for this protocol. These three strains are Type III Secretion System-related mutants that exhibit contrasted fitness in planta [START_REF] Feng | A Xanthomonas uridine 5'-monophosphate transferase inhibits plant immune kinases[END_REF][START_REF] Guy | xopAC-triggered immunity against Xanthomonas depends on Arabidopsis receptor-like cytoplasmic kinase genes PBL2 and RIPK[END_REF]Wang et al., 2015). Competitive indices of these three strains when co-inoculated with the WT* strain are shown in Figure 1. Xcc 8004::GUS-GFP is a negative control whose fitness should be the same as the WT* reference strain (i.e., CI ~ 1). Strains with CI < 1 are considered less fit than the WT strain in the mesophyll environment.

We used four independent biological replicates of one plant sample each. The plot was generated using the ggplot2 package of the R software [START_REF] Wickham | ggplot2: elegant graphics for data analysis[END_REF]; https://github.com/tidyverse/ggplot2).

We purposely set a log10-based scale to stretch out low CI values that would be hardly differentiable otherwise. Statistical treatment of the data was also achieved with R using the Kruskal-Wallis test.

Groups identified as significantly different (P < 0.05) are displayed using the letters 'a', 'b' and 'c' in Figure 1A. (Goodman and Novacky, 1994; Balint Kurti, 2019)

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Figure 1 |

 1 Figure 1 | Les plantes sont en interactions avec leur environnement biotique et abiotique. Les facteurs abiotiques comme les épisodes de températures extrêmes, de sécheresse et de carence en nutriments sont source de stress pour les plantes. Les plantes subissent aussi des stress biotiques comme les attaques de ravageurs, d'herbivores, de microorganismes pathogènes (bactéries, virus, champignons) ou par compétition avec d'autres plantes. L'ensemble de ces interactions impose des stress sur la plante avec des conséquences variées selon le stade de développement.

Figure 2 |Figure 3 |

 23 Figure 2 | Les bactéries du genre Xanthomonas sont des phytopathogènes d'intérêt agronomique majeur. Xanthomonas campestris pv. campestris A) cultivé sur milieu riche et B) observé en microscopie électronique. Exemples de symptômes causés par les Xanthomonas : C) Xanthomonas campestris pv. campestris sur le chou, D) Xanthomonas oryzae pv. oryzicola et E) Xanthomonas oryzae pv. oryzae sur le riz, F) Xanthomonas citri pv. citri sur les agrumes, G) Xanthomonas axonopodis pv. manihotis sur le manioc, H) Xanthomonas vasicola pv. musacearum sur la banane, I) Xanthomonas phaseoli pv. phaseoli sur le haricot et J) Xanthomonas fragariae sur la fraise. Photos A) & B) adaptées de Vicente & Holub, 2013 ; C) An et al., 2019 ; G) Mansfield et al., 2012 ; Le reste des photos sont issues de https://gd.eppo.int, courtoisie de D) T.W. Mew, IRRI, Los Baños (PH), H) M. M. Shimwela, Tanzania Agricultural Research Institute, Maruku, Tanzania, I) Ebrahim Osdaghi, J) U. Mazzucchi, Università di Bologna (IT).

Figure 4 |

 4 Figure 4 | Structure anatomique et fonction de guttation des hydathodes chez le chou. A) Hydathodes de chou-fleur vus en microscopie électronique (barre d'échelle = 500 µm). Surface B) d'un pore de l'hydathodes et C) d'un stomate de chou-fleur après inoculation par trempage transitoire dans une suspension de Xcc (barre d'échelle = 10 µm). La structure externe a l'air similaire avec un pore et deux cellules de garde. Noter l'abondance de bactéries au niveau du pore de l'hydathode mais absentes du stomate. D) Photo d'une feuille de chou-fleur présentant des gouttelettes de guttation au niveau des hydathodes (Photo : Alice Boulanger, LIPM). E) Observation en Normarsky d'un hydathode clarifié. Noter les ramifications et l'abondance de terminaisons des vaisseaux du xylème dans l'hydathode (barre d'échelle = 200 µm). po : pore de l'hydathode. Les images A), B), C) et E) sont issues de Cerutti et al., 2017.

Figure 5 |

 5 Figure 5 | Xcc développe un comportement biotrophe puis nécrotrophe dans les hydathodes. A) Représentation schématique d'un hydathode infecté à 3 et 6 jours post-inoculation par Xcc. L'épiderme est en vert clair, les pores son en vert foncé, l'épithème est en jaune, les vaisseaux du xylème sont en orange et les bactéries sont en bleu (adapté de Cerutti et al., 2019). B) Vue d'ensemble d'un hydathode de chou-fleur 3 jours après inoculation : les bactéries occupent les espaces intercellulaires mais les tissus ne semblent pas endommagés (barre d'échelle = 50 µm). C) Grossissement de la zone encadrée en B) (barre d'échelle = 10 µm). D) Vue d'ensemble d'un hydathode de chou-fleur 6 jours après inoculation montrant des tissus complètement dégradés (barre d'échelle = 50 µm). E) Grossissement de la zone encadrée en D) (barre d'échelle = 20 µm). p : parenchyme ; cp : parenchyme cortical ; xv : vaisseaux du xylème ; e : épiderme (Cerutti et al., 2017).

Figure 6 |

 6 Figure 6 | Xcc colonise abondamment les vaisseaux du xylème conduisant à une infection systémique. Dynamique de l'infection d'une feuille de chou-fleur par la souche Xcc LMG568::lux suivi par bioluminescence : A) Xcc est confiné dans les hydathodes à 3 jours post-inoculation (dpi) puis se propage progressivement dans le réseau du xylème à 6 dpi (B & C), 7 dpi (D) et 8 dpi (E). F) Xcc se déplace dans les vaisseaux et est retrouvé dans la tige au niveau de l'inter-noeud au-dessus de la feuille inoculée (+1) ainsi que dans les vaisseaux et les hydathodes de la feuille du noeud +1. Inoculation réalisée avec la souche Xcc 8004::GUS-GFP visible en bleu dans les tissus grâce à la coloration GUS. Par microscopie confocale, on localise Xcc G) en surface des hydathodes et H) sous les pores à 3dpi et I) dans les vaisseaux du xylème de la feuille à 6 dpi. po : pore de l'hydathode ; xv : vaisseaux du xylème. Toutes les images sont issues de Cerutti et al., 2017.

Figure 7 |

 7 Figure 7 | Xcc infecte le mésophylle foliaire. A) Schéma représentatif d'une coupe transversale de feuille. Le mésophylle correspond à la zone centrale contenue entre l'épiderme supérieur et l'épiderme inférieur, c'est-àdire à la fois le parenchyme palissadique et le parenchyme lacuneux (adapté de Vorholt, 2012). B) Symptômes typiques de la nervation noire des brassicacées causée par Xcc : chlorose et nécrose en forme de V émanant de la marge de la feuille. Des points de nécrose sont visibles le long des nervures là où Xcc ressort des vaisseaux et colonise le mésophylle du chou (Mansfield et al., 2012).

Figure 8 |

 8 Figure 8 | Les systèmes à deux composants perçoivent l'environnement et assurent la transduction du signal. A) Schéma fonctionnel d'un système à deux-composants (TCS) typique. Lors de la fixation du substrat sur le domaine de ligation extracellulaire du senseur, le domaine kinase intracellulaire s'autophosphoryle sur un résidu histidine en hydrolysant l'ATP. L'activation du senseur histidine kinase entraîne le transfert du groupe phosphoryl sur le régulateur de réponse qui s'active à son tour (adapté de Jacob-Dubuisson et al., 2018). B) Modèle de régulation de la physiologie bactérienne par les TCS connus et caractérisés chez les Xanthomonas (Pandey et al., 2016).

Figure 9 |Figure 10 |

 910 Figure 9 | Les transporteurs actifs assurent l'import de nutriments dans la cellule. A) Modèle dynamique d'un transporteur ABC. Le substrat est pris en charge par la protéine de liaision au niveau périplasmique et acheminé au niveau des deux domaines transmembranaires. L'hydrolyse de l'ATP au niveau des sous-unités ABC fournit l'énergie pour changer la conformation du complexe et permet le relargage cytoplasmique du substrat (Rees et al., 2009). B) Modèle du système d'import du phosphate et de sa régulation chez Xanthomonas. Le phosphate inorganique (Pi) est importé dans le périplasme grâce à la porine OprO. Lorsque le phosphate est abondant ([Pi] > 4 µM), l'absorption du phosphate est assurée par le transporteur basse affinité PitA. Dans ces conditions, les système haute-affinité PstSCAB n'est pas nécessaire : la transduction du signal par le TCS PhoBR est bloquée par l'interaction directe entre PhoU et le senseur PhoR qui empêche l'autophosphorylation par le domaine histidine kinase. En situation de carence en phosphate ([Pi] < 4 µM), l'acquisition du phosphate par PitA n'est plus suffisante et le système PstSCAB prend le relais. La protéine PhoX prend en charge le phosphate inorganique périplasmique et l'achemine jusqu'au transporteur ABC formé par le système Pst. Dans cette situation, PhoR est libérée et assure le phospho-relais auprès du régulateur de réponse PhoB qui agit comme facteur de transcription en activant directement l'expression des gènes sous son contrôle, dont l'opéron pstSCAB. La dualité des systèmes d'import Pit / Pst permet aux bactéries de s'adapter aux concentrations du milieu environnant et de maintenir l'homéostasie du phosphate au niveau intracellulaire. OM : membrane externe ; IM : Membrane interne ; Pi : phosphate inorganique ; X : PhoX ; U : PhoU ; A : PstA ; B : PstB ; C : PstC ; S : PstS.

Figure 11 |

 11 Figure 11 | Xcc déploie un arsenal de facteurs de virulence lors de l'infection. Les adhésines (fimbriae & pilus de Type IV) contribuent à l'adhésion des bactéries et constitue le biofilm avec les EPS et LPS. Xcc est également capable de sécréter des enzymes de dégradation de la paroi cellulaire et des protéines effectrices via le T2SS et le T3SS respectivement. Le CWDE perturbe la paroi cellulaire végétale et les protéines effectrices, une fois transférées dans le cytoplasme végétal, sont capables de moduler la physiologie végétale et de bloquer les défenses végétales. EPS: exopolysaccharide, LPS: lipopolysaccharide, T2S: Système de sécrétion de type II, T3S: Système de sécrétion de type III, OM: membrane externe, IM: membrane interne. CW: paroi cellulaire et PM: membrane plasmique. Adapté de Büttner et Bonas, 2010.

Figure 12 |

 12 Figure 12 | Structure des systèmes de sécrétion chez Xanthomonas. Les Xanthomonas possèdent six types de systèmes de sécrétion pour l'export de molécules vers le milieu extracellulaire. Le T2SS et le T5SS sécrètent des protéines après import dans le périplasme par les systèmes Sec ou TAT alors que le T3SS, le T4SS et le T6SS assurent la translocation de protéines dans la cellule hôte. Vésicules de la membrane externe (OMV); membrane interne (IM); membrane externe (OM). D'après Büttner & Bonas, 2010.

Figure 13 |

 13 Figure13| Xanthomonas utilise le T3SS pour injecter des effecteurs dans la cellule hôte et manipuler sa physiologie. L'injection d'effecteurs par le T3SS conduit à la modulation de plusieurs processus biologiques au sein de la cellule de l'hôte. Bien que les cibles de la plupart des effecteurs restent inconnues, certains altèrent la signalisation et la mise en place des réponses immunitaires, les mécanismes de recyclage tels que l'autophagie ou le protéasome, la modulation de l'expression génique, la synthèse des protéines, le trafic vésiculaire, l'homéostasie des phytohormones ou encore la dynamique du cytosquelette. Figure adaptée de la thèse de Manuel Gonzalez-Fuente.

Figure 14 |Figure 15 |

 1415 Figure 14 | Le quorum sensing régule la dynamique de formation et de dispersion des biofilms. La formation de biofilm est initiée par l'adhésion de bactéries à une surface. La production de la matrice extracellulaire, en particulier la sécrétion d'EPS, contrôlée par le DSF conduit à l'établissement d'un biofilm dense, protecteur des bactéries. Après croissance de la population bactérienne, l'accumulation du DSF conduit à la dispersion du biofilm par expression d'enzymes de dégradation et une réactivation de la mobilité. Adapté de Rumbaugh & Sauer, 2020.

Figure 16 |

 16 Figure 16 | Principe du TnSeq. A) Génération d'une banque de mutants par insertion aléatoire de transposon dans le génome. Chaque bactérie reçoit un évènement d'insertion de manière à saturer complètement et uniformément le génome à l'échelle de la population. Les flèches indiquent les sites d'insertion et leur longueur indique le nombre de reads lors du séquençage. Les cadres ouverts de lecture sont représentés par des rectangles de couleur selon leur importance (rouge : essentiel ; vert : non-essentiel ; violet : important). B) Une fois la banque générée, les mutants sont cultivés dans les conditions d'intérêt. Les gènes importants pour la croissance dans ce milieu sont retrouvés moins fréquemment selon leur contribution à la fitness bactérienne. C) Le nombre de reads pour chaque insertion est évalué par séquençage haut-débit. L'abondance relative des mutants est mesurée avant et après chaque expérience (van Opijnen & Levin, 2020).

Figure 17 |

 17 Figure 17 | Principe du RB-TnSeq. A) (Haut) Les vecteurs de livraison de transposon Tn5 et mariner sont convertis en vecteurs RB-TnSeq en clonant des millions de code-barres ADN uniques (N20) flanqués de sites d'amorçage PCR communs (U1 et U2) près du bord de la répétition inversée du transposon (IR). (En bas) Un transpososome à code-barres aléatoires a été généré en amplifiant d'abord par PCR le gène de résistance à la kanamycine avec des oligonucléotides contenant des IR Tn5 et la région de code-barres d'ADN aléatoire, puis en ajoutant la transposase Tn5. Les trois systèmes peuvent être utilisés pour muter les bactéries par électroporation ou (pour les vecteurs Tn5 et mariner) par conjugaison. Indépendamment du système ou de la méthode de délivrance, le but est de générer une grande population de transposons mutants de telle sorte que chaque souche contienne un codebarre ADN unique. B) Une banque de mutants de transposon barcodés au hasard est caractérisée en utilisant un protocole similaire au HITS ou au TraDIS. Ici, nous nous référons à ce protocole de manière générique par «TnSeq». Pour le TnSeq, l'ADN génomique est fragmenté, réparé et ligaturé avec des adaptateurs Illumina Y. Les fragments d'ADN contenant le transposon sont enrichis par PCR à l'aide d'une amorce spécifique de l'adaptateur Y et d'une seconde amorce spécifique du transposon. Le code-barre d'ADN et le site d'insertion du transposon sont identifiés en une seule étape de séquençage Illumina de 150 nucléotides. Les résultats TnSeq se présentent sous la forme d'un tableau des code-barres et des sites d'insertion de transposon associés. C) (Haut) Pour le BarSeq, les code-barres d'ADN sont amplifiés par PCR à l'aide d'oligonucléotides qui se lient aux régions U1 et U2 communes. Les deux oligonucléotides contiennent des séquences adaptatrices pour le séquençage Illumina. L'un des oligonucléotides contient un indice d'expérimentation et permet le multiplexage de plusieurs expériences de BarSeq sur une seule ligne de séquençage Illumina. (En bas) Les tests d'évaluation de la competitivité des mutants sont effectués en comparant l'abondance des code-barres d'ADN par BarSeq avant (temps zéro) et après (condition) la croissance sélective. Dans cet exemple simple, le gène associé au code-barre 2 a une fitness réduite; le gène associé au code-barre 3 a une meilleur fitness. D'après Wetmore et al., 2015.

  . Sequences flanking the deletion were PCR amplified from Xcc strain 8004 genomic DNA, introduced into pK18mobSacB by Gibson assembly (Gibson et al., 2009) and verified by sequencing. Genetic complementation was performed by genomic integration of a cassette containing each gene under the control of a constitutive pTac promoter at a neutral locus situated between XC_1301 and XC_1302. Gene fragments encompassing the predicted translational start site were PCR amplified from Xcc strain 8004 genomic DNA and cloned by Gibson assembly into plasmid pK18_CompR3, a pK18mobSacB derivative containing a pTac promoter region and a T7 terminator region from pCZ1016 (Déjean et al., 2013) flanked by XC_1301 and XC_1302

  suggests a rapid adaptation of Xcc to the plant environment Surprisingly, there are few transcriptional changes for genes associated with transcription, translation, replication, TCA cycle or amino acid biosynthesis between 4 and 72 hpi. However, these functions are already strongly repressed comparing 4 hpi with MOKA conditions meaning that adaptation to the plant environment requires a rapid slowdown in cellular division and core-metabolism. Other stress-responsive genes have their expression induced in planta such as base excision repair and nucleotide excision repair systems, trehalose production pathways, superoxide dismutases and chaperone proteins. In addition, expression of the ABC transporter system OpuB-ABC (XC_0173 to XC_0174; Hoffmann et al., 2018) and the choline degradation pathway (XC_0760 to XC_0761;[START_REF] Wargo | Homeostasis and Catabolism of Choline and Glycine Betaine: Lessons from Pseudomonas aeruginosa[END_REF], both involved in osmoprotection, are induced 72 hpi suggesting that bacteria face an osmotic shock in the apoplast of the epithem cells (Figure3, Table

(

  flagellum) motility. Repression of chemotaxis and motility has also been reported at early rice infection stages in Xanthomonas oryzae pv. oryzicola(Xoc; Liao et al., 2019) while twitching motility and quorum sensing were both activated at later infection stages and important for virulence of Xanthomonas oryzae pv. oryzae(Xoo; Lee et al., 2017) and Xac(Li et al., 2019).

12 GuySSallet

 12 Figurski DH, Helinski DR (1979) Replication of an origin-containing derivative of plasmid RK2 dependent on a plasmid function provided in trans. PNAS 76: 1648-1652

Figure 1 :

 1 Figure 1: Xanthomonas campestris undergoes a massive transcriptomic reprogramming during hydathodes infection. (A) Genome-wide expression profile of Xcc in hydathodes at 72 hpi versus 4 hpi. Each point represents a gene for which the change in expression level is given as the log2 fold change (Log2FC) between 72 hpi and 4 hpi into hydathodes. Genes considered significantly differentially expressed (DEGs) are represented in red if induced or in blue if repressed between the two timepoints. Non DEGs are colored in grey. Genes under the control of the HrpG regulator (ie. found differentially expressed in the 8004::hrpG* vs 8004 dataset) and found differentially expressed at 72 hpi vs 4 hpi in hydathodes are colored in dark red (up-regulated) and dark blue (down-regulated). (B) Venn diagram showing the total number of DEGs (|Log2FC| 2; FDR 0.05) obtained after growth of the Xcc 8004 WT strain in MOKA-rich medium as compared to either the 8004::hrpG* mutant in MOKA and the WT strain after 4 hours or 72 hours in hydathodes.

Figure 2 :

 2 Figure 2: Xanthomonas colonization of hydathodes. Bacterial multiplication of Xcc 8004 wild-type strain (WT), deletion mutants and complemented strains in individual hydathodes 3 and 6 days after dip-inoculation of the second true leaf of 4 weeks-old cauliflower plants. The box plot representations are showing the impact of (A) mutations in the T3SS hrpG regulator, (B) mutations in phosphate and sulfate transport genes and (C) mutations in motility genes over Xcc multiplication into hydathodes. Each point of the plot represents the population extracted from one hydathode. At least 8 hydathodes were sampled on one leaf per plant and three plants were used per experiment, though not all hydathodes were infected. Results from at least three independent experiments were pooled and a total of at least 50 infected hydathodes were counted for each strain. Letters indicate statistically different groups obtained from the Kruskal-Wallis test on all data points for each strain with an error = 0.05.

Figure 3 :

 3 Figure 3: Schematic representation of Xcc main transcriptomic responses happening during the early steps of hydathode infection. Genes corresponding to blue and red objects are repressed and induced between 4 and 72 hpi, respectively. Genes corresponding to grey objects are not differentially expressed. T3SS: type three secretion system; T3E: type three effector; T2SS: type two secretion system; LPS: lipopolysaccharide; PCWDE: Plant cell wall degrading enzymes; T4P: type four pilus. Figure drafted using biorender (https://app.biorender.com).

Figure S1 :

 S1 Figure S1: Measure of hydathode population in the two conditions used for RNAseq. The number of Xcc colony forming units (CFU) per hydathode was determined after 4 hours of continuous immersion (4 hpi) or 72 hours after transient dipping (72 hpi) for 24 or 30 individual hydathodes respectively in three independent biological replicates. Each point represents the population extracted from one hydathode. Box plots represent the pooled results obtained for three independent experiments.

Figure S2 :

 S2 Figure S2: RNAseq samples clustering. The heatmap shows the Euclidean distances between samples as calculated from the variance-stabilizing data transformation of the count data.

Figure S3 :

 S3 Figure S3: Swimming motility is reduced in type IV pilus and flagellum mutants in Xcc. To confirm the loss of flagellar motility in the mutants tested in patho-assays, we assayed their ability to move in 0.3% agar swimming plates. 2 µL of bacterial suspensions adjusted to 10 8 cfu/mL were spotted on swimming plates and pictures were taken after 48 hours of incubation at 28°C. Deletion mutants affected in key components of the type IV pilus (A), flagellum (B), and hrpG regulator (C). The experiment was repeated three times independently using five plates each time.Strains: 1. WT; 2. fliC; 3. fliC::fliC; 4. pilA pilE; 5. pilA pilE fliC; 6. pilA pilE fliC::fliC; 7. fliQ; 8. fliQ::fliQ; 9. hrpG; 10. hrpG::hrpG; 11. hrpG*

Figure S5 :

 S5 Figure S5: Phenotypic characterization of hrpG mutants. (A) EPS production assays were performed on 24h growth of either 8004::GUS-GFP strain (WT), HrpG* and DhrpG strains in rich MOKA medium. Production was normalized on dry weight bacteria. Histogram represents the average of results obtained for three independent replicates. (B) On the left, representative pictures of protease activity assay on plate are shown for each tested strain. The histogram represents the average of protease activity measured, as described in the supplemental Material and Methods section, for three independent replicates.

Figure S6 :

 S6 Figure S6: Synteny of genes involved in two transport systems in Xcc.Alignment was performed based on protein Blast using the SyntTax tool (https://archaea.i2bc.paris-saclay.fr/synttax/). (A) Comparison of genetic organization of the locus involved in the pst system between Xcc strain 8004, Xcc strain ATTC33913, Xac strain 306 et E. coli K12 strain MG1655 using XC_3456 as reference and "Best match" and a minimal threshold normalized BLAST bit score set at 30% as parameters. (B) Comparison of genetic organization of the locus involved in Tau system between Xcc strain 8004, Xcc strain ATTC33913, Xac strain 306 et E. coli K12 strain MG1655 using XC_2711 as reference and "Best match" and a minimal threshold normalized BLAST bit score set at 30% as parameters.

Figure S7 :

 S7 Figure S7: Growth of Xcc wild-type and mutant strains in (A) MME minimal medium and (B) MOKA rich medium. After overnight growth in complete medium, cells were harvested, washed, and resuspended in MME or MOKA. The error bars indicate the standard deviations obtained from 4 technical replicates. The experiments were repeated 3 times and similar results were obtained.

Figure 1 |

 1 Figure 1 | An RB-TnSeq library of Xcc mutants to screen for fitness determinants in vitro and in planta. a) The RB-TnSeq library is composed of Xcc 8004::GUS-GFP derived transposon-insertion mutants carrying 20 bprandom barcodes (N20). (1) To evaluate the competitive fitness of the pool of Xcc mutants, the T0 population is inoculated into either hydathodes, xylem sap or in vitro media and evolved for multiple generations. (2) After DNA extraction, both T0 and evolved population samples are (3) analyzed by barcode sequencing to measure the relative abundance of each mutant strain. (4) Comparison of relative abundance in the two populations assesses the impact of genes inactivation on bacterial fitness and precisely quantifies the contribution of each gene to Xcc fitness. (Created with BioRender.com) b) List of key biological processes found enriched among essential genes of Xcc according to the Gene Ontology classification. Red bars indicate the number of genes found to be essential in each GO category. Light red bars show the total number of genes annotated in each category.

Figure 2 |

 2 Figure 2 | RB-TnSeq identifies over 180 genes contributing to Xcc fitness in hydathodes and xylem sap. a) Number of barcodes recovered 3 days after hydathodes inoculation with the RB-TnSeq library. The bottleneck was estimated based on 4 biological replicates (n = 24 hydathodes each). The dashed line indicates the mean of the 4 replicates. b) Venn diagram showing the overlap between genes contributing to Xcc fitness in hydathodes at 3 or 6 dpi and in xylem sap. c) Representation of the genome wide fitness phenotype of Xcc mutants after 6 days in the hydathodes. Red dots represent the genes that we consider to be directly involved in Xcc fitness (for details see Methods section).

Figure 3 |

 3 Figure 3 | Functional validation confirms the importance of selected candidate genes for Xcc fitness and pathogenicity. a Correlation between competition assays performed by challenging Xcc deletion mutants of candidate genes with the WT* strain and the RB-TnSeq data in hydathodes at 6 dpi. Spearman correlation coefficient and the associated p-value are indicated on the graph. b Pathogenicity assays in cauliflower leaves shows a diversity of phenotypes associated to the loss of genes contributing to Xcc fitness in hydathodes. Statistically significant differences are indicated according the Kruskal-Wallis test (***: p-value < 0.001).

Figure 4 |

 4 Figure 4 | Mutation of XC_3388 leads to a pleiotropic deregulation of biological processes in Xcc. a Evaluation of exopolysaccharides (EPS) production by Xcc 8004, the XC_3388 mutant and the XC_3388::XC_3388 complemented strain. b Evaluation of amylase activity in Xcc 8004, the XC_3388 mutant and the XC_3388::XC_3388 complemented strain is obtained by quantifying the size of the degradation halo visible on plates as shown in the pictures. c Metabolic fingerprinting profiles of Xcc 8004 and the XC_3388 mutant obtained with the Biolog PM1 plates (carbon sources). Each row shows the kinetics of metabolization for each individual compound. Numbers (1) and (2) indicate differences in glucose and glutamic acid metabolization respectively. d Photos of the plate motility assay used to investigate flagellar swimming abilities of Xcc 8004, the XC_3388 mutant and the fliC non-motile flagellin mutant.

  technology. Carbon and nitrogen sources utilization were assayed using Biolog phenotype microarray plates PM1, PM2A and PM3B (PM; Biolog, Hayward CA) according to the manufacturer's protocol. Xcc cells were grown in rich MOKA medium overnight at 28°C. Cells were collected and resuspended in IF-0 (for PM1 and PM2A) or IF-0 20mM glucose (for PM3B) supplemented with 1× Biolog Redox Dye Mix H, at initial optical density (OD600nm) of 0.08 for plates inoculation (100 µl/well). Incubation time was 72 h in the Omnilog instrument (Biolog, Hayward, CA) at 28°C. Two to three independent replicates were performed. Results

Figure S2 |

 S2 Figure S2 | RB-TnSeq results in vitro. a Genome-wide gene fitness assessment in MME Glucose DropOut -LTH medium.Genes related to the biosynthesis of Leucine, Histidine and Tryptophan are highlighted. We observe the expected loss of fitness of auxotrophic mutants in a medium lacking these three amino acids. This confirms the proper behavior of the Xcc RB-TnSeq library and the good quality of the readout for the evaluation of gene fitness. b Screening of Xcc genes important for in vitro growth identified quasi-essential genes and allowed us to exclude genes that are not specific to the plant-associated environments tested.

Figure S3 |

 S3 Figure S3 | Absence of correlation between Xcc RNAseq and RB-TnSeq data in hydathodes. We compared the fitness score associated with each gene in hydathodes at 6 dpi with the level of differential expression between 4 hours and 3 days post-inoculation in cauliflower hydathodes (Luneau et al., in prep). The red line shows the linear regression model ; R 2 : Pearson correlation coefficient.

10 .

 10 Brassica oleracea var. botrytis cv. Clovis F1 (Vilmorin) Note: Plants are grown under greenhouse conditions and used at 4 weeks after sawing. All inoculations were performed using the second true leaf (second leaf above the cotyledons). After inoculation, plants are kept in classical growth chamber conditions: 9 h light; 22 °C; 70% relative humidity. Xanthomonas campestris pv. campestris (Xcc) strain 8004::GUS-GFP (WT hereafter; Cerutti et al., 2017) and variants: Xcc 8004::GUS*-GFP* (WT* hereafter, carrying the point mutations Y468A and Y66A inactivating the catalytic sites of the β-glucuronidase and GFP proteins respectively); Xcc 8004::GUS-GFP ΔhrpX; Xcc 8004::GUS-GFP ΔhrcV; Xcc 8004::GUS-GFP ΔxopAC Note: With concerns to the cost of fitness related to the constitutive expression of the GUS-GFP cassette, we decided to create the non-functional version of the cassette for our reference strain.

1 .

 1 -protocol.org/exxxx Bio-protocol 10(xx): exxxx. DOI:10.21769/BioProtoc.xxxx C. Plating of the inoculation suspensions and counting of the initial relative frequencies in mixed populations Transfer 100 µl of inoculation suspension into a 96-well plate with conical bottom.

Figure 1 .

 1 Figure 1. Competition assay of Xcc 8004::GUS-GFP strain and related mutants in cauliflower mesophyll. All competition assays were performed by co-inoculating the Xcc 8004::GUS*-GFP* reference strain with Xcc 8004::GUS-GFP derivatives in a 1:1 ratio. Mesophyll discs were sampled at 3 days post-inoculation. A. Graphical representation of competition assays results. Strains showing CI ~ 1 are considered as fit as the WT strain while strains with CI < 1 are considered less fit than the WT strain in the mesophyll environment. Horizontal bars show the median for four

5 MBBLMLFigure 1 |Figure 2 |Figure 3 |

 5123 Figure 1 | Symptômes de collapse observés en réponse à l'infiltration des souches de Xcc disponibles dans l'équipe. Deux groupes se dégagent avec (I) des souches provoquant un collapse rapide visible à 1 dpi et (II) des souches qui présentent le même profil que la 8004 avec un collapse complet à 3 dpi. Chaque souche a été inoculée sur 2 plantes, le résultat de chaque plante est présenté dans une colonne à chaque jour d'observation. 0 : Aucun symptôme ; SC : Début de collapse avec seulement quelques points éparpillés dans la zone infiltrée ; C : Collapse de toute la zone infiltrée ; D : Décoloration de la zone infiltrée qui nécrose et présente un aspect « papier à cigarette ».

Figure 4 |

 4 Figure 4 | XopJ6 est un facteur d'avirulence reconnu par la paire de récepteurs RRS1/RPS4 chez Arabidopsis thaliana. Symptômes visibles à 10 dpi (en haut) après inoculation par piqûre de feuilles d'Arabidopsis thaliana Ws-0 sauvage (WT) ou du mutant rrs1-rps4 (inoculum à 10 8 CFU/ml). Les photos sont représentatives de la sévérité des symptômes observés sur 24 feuilles issus de 3 réplicas biologiques indépendants. Populations bactériennes (en bas) à 0 dpi (en gris) et 3 dpi (en noir) dans les feuilles d'A. thaliana des mêmes génotypes après infiltration d'une suspension bactérienne à 10 5 CFU/ml. Les boxplots représentent les données obtenues au cours de 3 réplicas biologiques avec 17 échantillons à 0 dpi et 27 échantillons à 3 dpi. Les lettres indiquent les groupes statistiquement différents selon le test de Kruskal-Wallis (p-value < 0.01). Résultats produits par Emmanuelle Lauber et figure adaptée de la thèse de Manuel González-Fuente (LIPM).

Figure 5 |

 5 Figure 5 | La présence de XopJ6 chez Xcc entraine un collapse rapide du mésophylle foliaire du chou-fleur Clovis F1. Le mésophylle du chou-fleur Clovis F1 a été inoculé par infiltration avec une suspension à 10 8 CFU/ml de A) la souche CN06 contenant ou non xopJ6, B) la souche 8004 contenant les différents varients alléliques de xopJ6 et C) les souches CN06 et CN06 xopJ6 portant le plasmide pLAFR6 vide (pLA-0), avec xopJ6 (pLA-J6) ou avec popP2 (pLA-PopP2).

Figure 6 |

 6 Figure 6 | XopJ6 limite la multiplication de Xcc dans les hydathodes du chou-fleur. Les populations bactériennes dans les hydathodes de Clovis F1 ont été dénombrées à 3 dpi (n = 36) après inoculation par trempage dans une suspension ajustée à 10 8 CFU/ml. La fitness de la souche sauvage CN06 est améliorée chez le mutant CN06 xopJ6 et retrouvée chez la souche complémentée CN06 xopJ6::xopJ6. Les lettres représentent les groupes statistiquement différents selon le test de Kruskal-Wallis (p-value < 0.05). Résultats obtenus par Emmanuelle Lauber (LIPM).

Figure 7 |

 7 Figure 7 | XopJ6 contribue à la multiplication de Xcc dans le mésophylle du chou-fleur. Les populations bactériennes dans le mésophylle foliaire de Clovis F1 ont été dénombrées à 0 dpi (n = 18) puis à 3 dpi (n = 27) après inoculation par infiltration avec un inoculum ajusté à 10 5 CFU/ml. A) La souche sauvage 8004 et les souches complémentées avec les différents variants de XopJ6 ne présentent pas de différence significative après 3 jours de croissance in planta. B) La fitness de la souche sauvage CN06 est affectée chez le mutant CN06 xopJ6 et restaurée chez la souche complémentée CN06 xopJ6::xopJ6. Les lettres représentent les groupes statistiquement différents selon le test de Kruskal-Wallis (p-value < 0.05).

Figure 8 |

 8 Figure 8 | XopJ6 ne semble pas être reconnu chez les autres Brassicacées d'intérêt testées. Deux jours postinoculation les symptômes de collapse sec observés chez Clovis F1 ne sont pas visibles chez les autres Brassicacées infiltrées avec un inoculum ajusté à 10 8 CFU/ml. Il semblerait donc que Clovis F1 soit le seul à pouvoir reconnaître la présence de XopJ6. Résultats représentatifs de deux réplicas biologiques avec 3 échantillons par souche.

Figure 1 |

 1 Figure 1 | Goulots d'étranglement potentiellement rencontrés par Xcc lors de la colonisation du xylème. L'entrée de Xcc dans les hydathodes au niveau des pores n'impose pas de sélection sur le nombre d'individus fondateurs. Les étapes de vascularisation, de propagation entre vaisseaux du xylème et de sortie des vaisseaux sont des sites putatifs de goulot d'étranglement. Figure adaptée de Cerutti et al., 2019.

  *4 " D > )*" 0 @> )--) )2 > )F @> ! > D!" -@A> "-2F= .> )40 2 @ > ! G> "* )-

  ADNc synthesis, 3' adenylation). During the fragmentation step, the RNA were cut in fragments of 120 to 210 bases. Raw sequence data were submitted to the Sequence Read Archive (SRA) database (Accession SRP280329).

	package pheatmap version 1.0.12 (Raivo Kolde (2015). pheatmap: Pretty Heatmaps. R package
	version 1.0.8. https://CRAN.R-project.org/package=pheatmap) on sample to sample Euclidean
	distances. Fitted generalized linear models (GLM) with a design matrix Multiple factor
	(biological repetition and factor of interest) were designed for further analyses. The Cox-Reid
	profile-adjusted likelihood (CR) method in estimating dispersions was then used. Differentially
	Reannotation of Xcc strain 8004 genome sequence expressed genes (DEG) were called using the generalized linear model (GLM) likelihood ratio
	test using a False Discovery Rate (FDR; Benjamini and Yekutieli, 2001) adjusted q-value <
	Annotation of X. campestris pv. campestris strain 8004 genome was performed using 0.05. Clustering on filtered DEG (q-value < 0.05 in at least on biological condition) was
	EuGene-PP (Sallet et al., 2013; EuGene-PP v1.0, eugene-4.1c) with SRP280320 RNA libraries generated with heatmap.2 function as available in the gplots Bioconductor package version
	and X. campestris pv. campestris strains 8004, ATCC33913 and B100 public annotations 3.0.1. (Warnes et al., 2016). gplots: Various R Programming Tools for Plotting Data. R package
	version 3.0.1. (https://CRAN.Rproject.org/package=gplots) using Ward's minimum variance
	clustering method on Euclidean. Enrichment analysis considering gene ontology was then
	conducted using the topGO package version 2.40.0 (Alexa
	Mapping of RNA sequencing reads was performed on Xcc strain 8004 genome sequence
	(Qian et al., 2005, Genbank accession number CP000050.1} which was reannotated and when
	appropriate on sequences of Brassica oleracea nuclear genome (Brassica_oleracea.v2.1.31;
	Accession GCA_000695525.1), Brassica oleracea mitochondrial genome (accession
	NC_016118.1) and Brassica rapa chloroplastic genome (BRARA_CHL, accession
	NC_040849.1). Parameters used were the following: matches allow no gap, a minimum length
	of 40 nucleotides for single-end mRNA librairies and no more than one mismatch, a minimum
	length of 18 nucleotides for single-end smallRNA libraries and no mismatch and a minimum
	length of 60 nucleotides for single-end mRNA librairies with a maximum of 5 mismatches. We
	kept only the best alignments for each read or pair of reads. Reads mapping at two different
	positions with the same best scores were not considered.
	Differentially expressed genes were detected with EdgeR Bioconductor package version
	3.30.3 (Robinson et al., 2010). Genes with no counts across all libraries were discarded prior to
	further analysis. Normalization was performed using TMM (trimmed mean of M-values)
	method (Robinson and Oshlack, 2010). Quality control plots of normalized data sets and
	reproducibility of biological repeats (Figure S2) were generated by principal component
	analysis using Ade4 version1.7-15 package (Dray, 2007) and heatmaps obtained with the
	RR

3000 platform. Oriented RNA libraries were prepared with TrueSep™ Stranded mRNA Sample Prep Kit (Illumina®). Subsequent steps of sequencing were performed according to the RN manufacturer instructions (RNA fragmentation, GCA_000012105.1,GCA_000007145.1 and GCA_000070605.1, respectively. This new annotation is available at https://dx.doi.org/10.25794/reference/id52ofys.

Analysis of RNA sequencing results and statistical analysis

Table 1 : Impact of transcriptomic data on the de novo annotation of Xcc 8004 genome RNAseq data used a All genes mRNA b rRNA c operon tRNA d Other ncRNA e

 1

	5'	3'	Reference	Accession
	UTR f	UTR g		Number

b Protein coding sequence c Ribosomal RNA d Tranfer RNA e Non coding RNA f 5' untranslated region g 3' untranslated region SM

Table 2 : GO terms of biological processes enriched among Xcc genes differentially expressed in hydathodes, 4 hpi vs 72 hpi.

 2

	GO.ID	Term	Annotated a Significant b Expected c	Adjusted
						p-value
	Upregulated
	GO:0006073	cellular glucan metabolic	19	11	1,89	1.8 10 -8
		process
	GO:0055114	oxidation-reduction process	399	74	39,78	8.9 10 -8
	GO:0070814	hydrogen sulfide biosynthetic	5	5	0,5	9.5 10 -6
		process
	GO:0005992 e	trehalose biosynthetic process	5	5	0,5	9.5 10 -6
	GO:0006950	response to stress	123	25	12,26	0.00063
	GO:0019344	cysteine biosynthetic process	6	4	0,6	0.00123
	GO:0009251	glucan catabolic process	11	5	1,1	0.00263
	GO:0043649	dicarboxylic acid catabolic	7	4	0,7	0.00265
		process
	GO:0044247	cellular polysaccharide	8	4	0,8	0.00361
		catabolic process
	GO:0009306	protein secretion	46	11	4,59	0.00435
	GO:0043623	cellular protein complex	18	6	1,79	0.00612
		assembly
	GO:0006457	protein folding	18	6	1,79	0.00612
	GO:0098661	inorganic anion transmembrane	15	5	1,5	0.01230
		transport
	GO:0098869	cellular oxidant detoxification	30	7	2,99	0.02468
	GO:0044419	interspecies interaction between	12	4	1,2	0.02506
		organisms
	GO:0005975	carbohydrate metabolic process	201	39	20,04	0.03559
	GO:0006817	phosphate ion transport	8	3	0,8	0.03753
	GO:0016311	dephosphorylation	33	7	3,29	0.04006
	Downregulated
	GO:0006935	chemotaxis	44	36	3,12	< 10 -30
	GO:0097588	archaeal or bacterial-type	23	23	1,63	9.4 10 -28
		flagellum-dependent cell
		motility
	GO:0007165	signal transduction	175	51	12,4	1.7 10 -22

a Number of genes annotated for a given GO term b Number of differentially regulated genes among the genes annotated for a given GO term c Expected number of differentially regulated genes if no significant enrichment e Terms for which all annotated genes are differentially regulated are highlighted in bold BB

Table 3 : GO terms enrichment among Xcc genes belonging to the HrpG regulon.

 3

	GO.ID	Term	Annotated a Significant b Expected c	Adjusted
						p-values
		BIOLOGICAL PROCESS
	Upregulated
	GO:0002790	peptide secretion	46	9	0,91	1.5 10 -7
	GO:0009306	protein secretion	46	9	0,91	1.5 10 -7
	GO:0032940	secretion by cell	47	9	0,93	1.8 10 -7
	GO:0046903	secretion	47	9	0,93	1.8 10 -7
	GO:0015031	protein transport	81	10	1,61	2.5 10 -6
	GO:0008104	protein localization	85	10	1,69	3.9 10 -6
	GO:0015833	peptide transport	85	10	1,69	3.9 10 -6
	GO:0045184	establishment of protein	85	10	1,69	3.9 10 -6
		localization
	GO:0042886	amide transport	86	10	1,71	4.3 10 -6
	GO:0033036	macromolecule localization	96	10	1,91	1.2 10 -5
	GO:0071705	nitrogen compound transport	120	10	2,38	8.6 10 -5
	GO:0071702	organic substance transport	142	10	2,82	0.00035
	GO:0044419	interspecies interaction between	12	3	0,24	0.00143
		organisms
	GO:0051704	multi-organism process	21	3	0,42	0.00763
	Downregulated
	GO:0000272	polysaccharide catabolic	27	3	0,08	5.6 10 -5
		process
	GO:0009057	macromolecule catabolic	58	3	0,18	0.00057
		process
	GO:0016052	carbohydrate catabolic process	61	3	0,19	0.00066
	GO:0005976	polysaccharide metabolic	64	3	0,2	0.00076
		process
	GO:0005975	carbohydrate metabolic process	201	4	0,63	0.00198
		MOLECULAR FUNCTION
	Upregulated
	GO:0016301	kinase activity	176	8	2,71	0.0046
	GO:0001067	regulatory region nucleic acid	27	3	0,42	0.0077
		binding

a Number of genes annotated for a given GO term b Number of differentially regulated genes among the genes annotated for a given GO term c Expected number of differentially regulated genes if no significant enrichment B Supplemental Material and Methods

Table S1 : List of strains and vectors used in this study Strain or Plasmid Relevant characteristics Reference or source Xanthomonas campestris pv. campestris

 S1

	8004::GUS-GFP phoB	phoB (XC_3272) deletion mutant,	This study
		constitutive GUS and GFP expression; Rif R
	8004::GUS-GFP phoB::phoB	phoB complemented mutant, constitutive	This study
		GUS and GFP expression; Rif R
	E. coli
	TG1	supE thi-1 (lac-proAB) (mcrB-hsdSM)5	Stratagene
	8004	Wild-type, spontaneous Rifampicin-(rk -mk -) [F´ traD36 proAB lacI q Z M15]	(Daniels et al., 1984)
	DH5	resistant mutant of NCPPB 1145; Rif R F -recA lacZ DM15	Bethesda Research
	8004::hrpG*	hrpGE44K mutant derivative, constitutive hrp	(Guy et al., 2013b) Laboratory
	Plasmids	gene expression; Rif R
	8004::GUS-GFP pRK2073	Wild-type, constitutive GUS and GFP Spec R ; Strep R expression; Rif R Helper plasmid for triparental mating;	(Cerutti et al., 2017) (Leong et al., 1982)
	8004::GUS-GFP hrpG pK18mobSacB	hrpG (XC_3077) deletion mutant, edition; Kan R constitutive GUS and GFP expression; Rif R Suicide vector in Xcc used for genome	This study (Schäfer et al., 1994)
	8004::GUS-GFP hrpG::hrpG pK18_XC3077_AmAv	hrpG complemented mutant, constitutive GUS and GFP expression; Rif R XC_3077 deletion construct; Kan R	This study This study
	8004::GUS-GFP hrpG* pK18_XC2245_AmAv	hrpGE44K mutant derivative, constitutive hrp XC_2245 deletion construct; Kan R	This study This study
	pK18_XC1058_AmAv	gene expression, constitutive GUS and GFP expression; Rif R XC_1058 deletion construct; Kan R	This study
	pK18_XC1626_AmAv	XC_1626 deletion construct; Kan R	This study
	8004::GUS-GFP fliC	fliC (XC_2245) deletion mutant, constitutive	This study
	pK18_XC2272_AmAv	GUS and GFP expression; Rif R XC_2272 deletion construct; Kan R	This study
	8004::GUS-GFP fliC::fliC pK18_XC2711_AmAv	fliC complemented mutant, constitutive XC_2711 deletion construct; Kan R	This study This study
		GUS and GFP expression; Rif R
	8004::GUS-GFP pilA pilE pK18_XC3272_AmAv	pilA (XC_1058) pilE (XC_1626) double XC_3272 deletion construct; Kan R	This study This study
	pK18_compR3	deletion mutant, constitutive GUS and GFP complementation, pTac promoter; Kan R expression; Rif R pK18mobSacB derivative use for genomic	This study
	8004::GUS-GFP pilA pilE fliC pilA (XC_1058) pilE (XC_1626) fliC (XC_2245) triple deletion mutant, pK18_Comp_XC3077 XC_3077 overexpression construc; Kan R	This study This study
	pK18_Comp_XC2245_5UTR	constitutive GUS and GFP expression; Rif R XC_2245 overexpression construct; Kan R	This study
	8004::GUS-GFP pK18_Comp_XC2272	pilA pilE fliC triple deletion mutant XC_2272 overexpression construct; Kan R	This study This study
	pilA pilE fliC::fliC	complemented with fliC, constitutive GUS
	pK18_Comp_XC3272	and GFP expression; Rif R XC_3272 overexpression construct; Kan R	This study
	8004::GUS-GFP fliQ pK18_compR3_RBS	fliQ (XC_2272) deletion mutant, pK18mobSacB derivative use for genomic	This study This study
		constitutive GUS and GFP expression; Rif R complementation, pTac promoter with
		ribosome-binding site added; Kan R
	8004::GUS-GFP fliQ::fliQ pK18_CompRBS_XC2711	fliQ complemented mutant, constitutive GUS and GFP expression; Rif R XC_2711 overexpression construct; Kan R	This study This study
	Rif: Rifampicin; Kan: Kanamycin
	8004::GUS-GFP pstB	pstB (XC_2711) deletion mutant,	This study
		constitutive GUS and GFP expression; Rif R
	8004::GUS-GFP pstB::pstB	pstB complemented mutant, constitutive	This study
		GUS and GFP expression; Rif R

Table S2 : Sequences of oligonucleotides used for construction of deletion and complementation plasmids

 S2

	XC_3077	Left	Rev Fwd	XC_1058AvAm pK18_CompR3_X	GAGCTTTGATTACGGAGCCGCCGCTTC CGAATTCGAGCTCCGTCGACAAGCTCTGT
	Locus name	Position Direction Name C3077_Fwd	Sequence (5'-3') GATCAGTGTAAAACCATTTTGC TGTGCTCAGTTCCATGGTCTG
		Right Right	Fwd Rev	XC_1058AmAv pK18_CompR3_X	GCAAAATGGTTTTACACTGATCGAAGC GTTTAAACCGCATGCATCGCAAGCTTCAG
	Plasmids construction		C3077_Rev	GGCGGCTCCGTAATCAAAGCTC CAAGCTGCGGTGCGATTGACC
	XC_1301 XC_2245	Right Left	Fw Rev Fwd	pK18_Am1301 pK18_1058Av pK18_Comp_XC2 245_5UTR_Fwd	GAGTCGACCTGCAGGCATGCAAGCTACT CGAATTCGAGCTCCGTCGACAAGCTCTA TGTAAAACGACGGCCAGTGCCAAGCTCA ATCGCACGTGATGGAGCGCTGG GAATAGTAGTCCCGGAGCCGTTG AAGGTTCCCAGAGCATCG
	XC_1626	Left Left Right	Rev Fwd Rev	MCS_Am1301 pK18_1626Am pK18_Comp_XC2 245_out_Rev	GTAAAACGACGGCCAGTGCCAAGCTCAG GTTTAAACCGCATGCATCGCAAGCTGCTC TATGATGTCGGCGCAAAAACTGCAGGGC AAGGCCGTTGTGGCGACTCGGC GATGGTGATCGGACATTGAGCC TAGCGTTGCTGTGACG
	XC_1302 XC_2272	Right Left	Rev Rev Fwd	pK18_Av1302 XC_1626AvAm pK18_CompR3_X C2272_Fwd	GCCAGTCTTTACATCACCAACAGTCAC CGAATTCGAGCTCCGTCGACAAGCTGCA GAGTCGACCTGCAGGCATGCAAGCTGGC TATGGCGCCTGGGAAATCGGCC GCCCCCTAACTGCTTGCAAGAAC CCGCACTTGCATCAGCACTCC
		Left Right Right	Fw Fwd Rev	MCS_Av1302 XC_1626AmAv pK18_CompR3_X C2272_Rev	GTTCTTGCAAGCAGTTAGGGGGCGTGA GTTTAAACCGCATGCATCGCAAGCTCTAC TACGCGCAGCGTGACCGCTACACTTGCT GTGGTGATCAGCGGGCCGCAGC CTGTTGGTGATGTAAAGACTGGC CCGATCAGATGCGGAATGC
	pTac-T7 MCS region XC_2711	Right Left	Fw Rev Fwd	Am1301_MCS pK18_1626Av pK18_CompRBS_ XC2711_Fwd	GAGTCGACCTGCAGGCATGCAAGCTCAG GCTCTAGAGGATCTCGACCAAGCTATGA AGCGCCGAGTCGCCACAACGGCCTTGC CCTGCAGTTTTTGCGCCGACATC ACAGCAACTGGTCCGCAGGGTG CTGACCTTTCTTTCCGGACG
	XC_2272	Left Left Right	Rev Fwd Rev	Av1302_MCS pK18_2272Am pK18_CompRBS_ XC2711_Rev	GTAAAACGACGGCCAGTGCCAAGCTATG CGTTTAAACCGCATGCATCGCAAGCTTCA GCGCTGCGGCCCGCTGATCACCACAGC AAGTGTAGCGGTCACGCTGCGCG GGGGACCCCGAAGCAGAACAGC GCCGAAGCGGCCGGTGATG
	RBS XC_3272	Right Left	Fw Rev Fwd	CompR3_RBSup XC_2272AvAm pK18_CompR3_X C3272_Fwd	TCCATCAGCGCGTGCCGCTACCCGATA CGAATTCGAGCTCCGTCGACAAGCTCGT CGGATCCGAATTCGAGCTCCGTCGACAA GCTGAATTAATTCGGATCCCTC ATCCACAAGACGGTGACCAGGCC AGTCTACTGGCGACCATCC
		Left Right Right	Rev Fwd Rev	XC_2272AmAv pK18_CompR3_X CompR3 _RBSdw CGCGTTTAAACCGCATGCATCGCAAGCTT TGGCCTGGTCACCGTCTTGTGGATTATC GTTTAAACCGCATGCATCGCAAGCTTCAG GGTCGAGATCCTCTAGAGCTC GGGTAGCGGCACGCGCTGATGG C3272_Rev GTGGCCGAGGAGAAACGGTAG
	Deletion		Rev	pK18_2272Av	AGAGTCGACCTGCAGGCATGCAAGCTTA GCTGTCCACCAGCAACGCGATC
	XC_3077 XC_2711	Left Left	Fwd Fwd	pK18_3077Am pK18_2711Am	GTAAAACGACGGCCAGTGCCAAGCTCGG GTAAAACGACGGCCAGTGCCAAGCTGCT TCCACCTGTAATTACAAGAGC GTACGTGATGCAGACCG
			Rev Rev	XC_3077AvAm XC_2711AvAm	CTCAGCAAGCTGCGGTGCGATTGACGT GCAGGCCTACATCAGCCGAAGCGGCTT
					CATTCGCAGCGGCGTCCATCAC GGCGTTTTGGAGATCGTTC
		Right Right	Fwd Fwd	XC_3077AmAv XC_2711AmAv	GTGATGGACGCCGCTGCGAATGACGTC GAACGATCTCCAAAACGCCAAGCCGCT
					AATCGCACCGCAGCTTGCTGAG TCGGCTGATGTAGGCCTGC
			Rev Rev	pK18_3077Av pK18_2711Av	GAGTCGACCTGCAGGCATGCAAGCTGTA GAGTCGACCTGCAGGCATGCAAGCTGGA
					CGGCGAGAGCCCGAAGCAG ATTGAGTGCGATCGAGCGCTTG
	XC_2245 XC_3272	Left Left	Fwd Fwd	pK18_2245Am pK18_3272Am	GTAAAACGACGGCCAGTGCCAAGCTCGC GTAAAACGACGGCCAGTGCCAAGCTGCT TCAAGACCACCTTGTCGTCGAT TCGATGCGCTGCTGAAGC
			Rev Rev	XC_2245AvAm XC_3272AvAm	GCTGTGACGCTGCCGATTACTGCAGCA GGCATCAGGTGGCCGAGGAGAAACGG GCGACATTACGTTGGTGTTGATTACCT GTG TCATCGACGATCAGGATGCG
		Right	Fwd	XC_3272AmAv	CGCATCCTGATCGTCGATGACCGTTTCT
		Right	Fwd	XC_2245AmAv	AATCAACACCAACGTAATGTCGCTGCT CCTCGGCCACCTGATGCC
					GCAGTAATCGGCAGCGTCACAGCAACG
			Rev	pK18_3272Av	C GAGTCGACCTGCAGGCATGCAAGCTGCC
					TTGTTGAACCACTGCAC
			Rev	pK18_2245Av	GAGTCGACCTGCAGGCATGCAAGCTCCG
	Complementation			AGCTGGTGGTGGTGGCGGTAAA
	XC_1058	Left	Fwd	pK18_1058Am	GTAAAACGACGGCCAGTGCCAAGCTGAG
					CATGTTCGCGTTGCGAGCAGG
				L O

Table S3 : Sequences of oligonucleotides used for oligocapture of plant RNAs

 S3

	18S_559_LNA Bo01051s080_29_LNA	TG{C}CCT{C}CAATGGAT{C}CTC{G}TTA GTAA{C}CCAT{G}CTAT{A}CTC{C}CAGG
	Name	Sequence (5'-3') a
	18S_258_LNA Bo01051s080_127_LNA	AT{C}ATGAA{T}CATCAG{A}GCAA{C}GG GGTTCAA{G}AACG{C}AAG{G}TGT{C}CC
	Nuclear ribosomal RNA
	18S_1147_LNA Bo01051s080_517_LNA	TTC{C}TTTAAGTT{T}CAG{C}CTTG{C}G CTA{G}AAGCAG{C}CA{C}CCTTG{A}AAG
	28S_2844_LNA	CTC{C}CGA{C}AATTTCAA{G}CA{C}TCT
	18S_1412_LNA Bo01051s080_709_LNA	GG{C}CATAGTC{C}CTCTAA{G}AA{G}CC CGGTA{C}CAAAT{C}GAG{G}CAA{A}CTC
	28S_3090_LNA	GT{G}TTT{C}AA{G}ACGGGTCGAA{T}GG
	28S_843_LNA Bo01051s080_812_LNA	GCCAA{C}ACAA{T}AGGA{T}CGAA{A}TC GAAG{C}TTAT{C}CCCCA{C}CGT{C}TCA
	28S_3345_LNA	C{C}TATACCCAAGT{C}AGA{C}GAA{C}G
	5,8S_2159_LNA a Bases under brackets refer to locked nucleic acid (LNA)-modified bases ACA{C}CAA{G}TATCGCA{T}TT{C}GCT
	28S_3660_LNA	T{C}TTAAT{C}GAC{C}AACACC{C}TTTG
	Choroplastic ribosomal RNA
	28S_3889_LNA	G{C}TACTA{C}CAC{C}AAGATCTG{C}AC
	Bo0151s070_23S_10_LNA	A{C}AGCTT{C}GGCA{G}ATCG{C}TTAGC
	28S_4534_LNA	CCTA{C}ATTGTT{C}CATC{G}AC{C}AGA
	Bo01051s070_23S_256_LNA	CAAG{G}GGTA{G}TA{C}AGGAATA{T}TC
	28S_4803_LNA	GGA{C}CATC{G}CAATG{C}TTTGT{T}TT
	Bo01051s070_23S_832_LNA	AGA{C}AGTG{C}CCA{G}ATCGT{T}ACGC
	28S_5082_LNA	GT{C}ATTTCA{C}AAAGTCG{G}ACT{A}G
	Bo01051s070_23S_974_LNA	CCTT{C}TTCG{C}CTT{C}CA{C}CTAAGC
	28S_5399_LNA	GA{T}AGG{C}CACG{C}TTTCACGG{T}TC
	Other plant RNA
	28S_5772_LNA	CG{G}ATTCTGA{C}TTAGA{G}GCG{T}TC
	BRARA_CHL_psbA_43_LNA	GTTAT{C}CAGTTA{C}AGAA{G}C{G}ACC
	28S_5693_LNA	GA{C}CAATTGT{G}CGAA{T}CAACG{G}T
	BRARA_CHL_psbA_199_LNA	GTTT{C}TGGAT{C}T{C}TTCTTTA{C}GG
	28S_6158_LNA	AA{G}TTGG{G}AATT{C}GTTAAG{G}AGC
	BRARA_CHL_psbA_506_LNA	GATT{C}CTA{G}AGG{C}ATACCAT{C}AG
	28S_2474_LNA	TGA{T}ATGCT{T}AAA{C}TCAGC{G}GGT
	BRARA_CHL_psbA_745_LNA	CCA{A}AATAA{C}CGTGA{G}CAG{C}TAC
	28S_2707_LNA	CCAAA{C}AACCCGA{C}TC{G}TAGA{C}A
	BRARA_CHL_psbA_829_LNA	CAA{A}TACCTA{C}TAC{C}GGC{C}AAGC
	28S_4147_LNA	TT{T}CCAG{G}GTGGG{C}AGG{C}TGTTA
	BRARA_CHL_psbA_932_LNA	CA{G}CC{C}AAGTATT{A}ATAACA{C}GTC
	18S_70_LNA	GTT{C}ATA{C}TTA{C}ACATGCATG{G}C
	BRARA_CHL_rbcL_4_LNA	G{C}TTTAGT{C}TCT{G}TTTGTGGT{G}A
	18S_174_LNA	GCA{C}GTATT{A}GCT{C}TAGAA{T}TAC
	BRARA_CHL_rbcL_188_LNA	C{C}ACA{C}AGTTGTC{C}ATGTA{C}CAG
	18S_383_LNA	AT{C}GAA{C}CCTAATTCT{C}CGT{C}AC
	BRARA_CHL_rbcL_731_LNA	CA{T}CATTT{C}TTCG{C}ATGTA{C}CCG
	18S_1792_LNA	CG{G}AAA{C}CTTGTTACGA{C}TT{C}TC
	BRARA_CHL_rbcL_1032_LNA	CAT{C}GCG{C}AG{T}AAATCAA{C}AAAG
	18S_1677_LNA	ATT{C}AATCG{G}TAG{G}AGCGA{C}GGG
	BRARA_CHL_rbcL_1395_LNA	CGAT{G}GTTGG{G}AA{G}TTAAAT{G}TG
		N R M

Table S6 : Properties of RNAseq libraries from Xcc strain 8004 wild-type and derivatives grown in vitro or harvested from cauliflower hydathodes Strain Condition Biological replicates Number of raw reads Uniquely mapped reads Xcc & Brassica (%) a Hits Brassica genes (%) b Hits Xcc genes (%) c Accession d

 S6

	8004	MOKA	3	22 503 680	93,58 %	-	94,72 %	SRR12603737
				31 781 601	88,67 %	-	94,49 %	SRR12603738, SRR12603725
				29 317 932	88,54 %	-	94,21 %	SRR12603739, SRR12603726
	8004::hrpG*	MOKA	3	21 746 450	95,87 %	-	93,58 %	SRR12603727
				14 282 665	94,84 %	-	94,11 %	SRR12603728
				15 932 094	95,08 %	-	94,57 %	SRR12603729
	8004	Cauliflower	3					SRR12603813,
		hydathodes		158 422 507	33,42 %	62,45 %	13,32 %	SRR12603814,
		4 hpi						SRR12603815
								SRR12603810,
				150 271 178	23,49 %	66,21%	10,63 %	SRR12603811,
								SRR12603812
								SRR12603804,
				173 591 985	41,15 %	67,94 %	10,12 %	SRR12603805,
								SRR12603806
	8004	Cauliflower	3					SRR12603816,
		hydathodes		164 579 058	38,59 %	55,19 %	16,40 %	SRR12603817,
		72 hpi						SRR12603818
								SRR12603801,
				163 894 181	38,47 %	52,56 %	27,27 %	SRR12603802,
								SRR12603803
								SRR12603807,
				143 337 188	27,63 %	73,48 %	1,61 %	SRR12603808,
								SRR12603809

a Percentage of raw reads mapped uniquely to the sequences of Xcc strain 8004 chromosome (Genbank accession number CP000050.1), Brassica oleracea nuclear and mitochondrial genomes (Accession GCA_000695525.1, NC_016118.1) and Brassica rapa chloroplastic genome (BRARA_CHL, accession NC_040849.1).

Table 1 | List of genes selected for validation of the RB-TnSeq data

 1

Table S2 | 172 genes contribute to Xcc fitness during hydathodes colonization.

 S2

	XC_3263	XCC8004_a40901 endopeptidase La	-0,75	-2,06	-0,45	-0,64	-0,99	-0,53
	XC_1868 XC_3271	XCC8004_a23231 hypothetical protein XCC8004_a41141 peptidase	-0,55 -0,85	-1,17 -1,17	-0,06 -0,08	-0,39 -0,17	-0,40 -0,18	-0,05 -0,35
	XC_1869 XC_3272	XCC8004_a23251 acetylornithine carbamoyltransferase XCC8004_a41161 transcriptional regulator PhoB	-1,75 -0,97	-3,53 -2,29	-0,01 0,02	0,08 -0,07	0,04 -0,12	-0,42 0,04
	Gene 8004 XC_1871 XC_3273 XC_1872 XC_3282	locus_tag XCC8004_a23271 argininosuccinate synthase Predicted Function XCC8004_a41171 histidine kinase XCC8004_a23281 acetylornithine deacetylase XCC8004_a41271 amidophosphoribosyltransferase	Hyd 3dpi -1,70 -0,02 -1,94 -2,05	Hyd 6dpi -3,08 -1,04 -3,11 -3,80	Xylem sap -0,10 0,04 0,13 -0,03	MME Glucose DropOut -LTH -0,37 0,02 0,09 -2,77	MME Glucose -0,30 -0,01 0,20 -1,07	-0,48 0,00 MOKA -0,70 -3,28
	XC_0007 XC_1873 XC_3299	XCC8004_a00091 tetratricopeptide repeat domain protein XCC8004_a23291 acetylglutamate kinase XCC8004_a41451 Putative secreted protein	-0,69 -2,17 -1,05	-1,05 -3,09 -0,96	-0,19 -0,30 -0,34	-0,03 -0,25 -0,21	0,14 -0,03 -0,29	-0,22 -0,07 -0,30
	XC_0012 XC_1875 XC_3313	XCC8004_a00161 pyridoxamine 5'-phosphate oxidase XCC8004_a23311 N-acetyl-gamma-glutamyl-phosphate reductase XCC8004_a41641 phospho-2-dehydro-3-deoxyheptonate aldolase	-0,70 -2,03 -0,60	-1,94 -3,57 -1,35	-0,01 -0,01 0,06	0,01 -0,12 0,09	-0,11 0,07 -2,35	0,27 -0,18 -0,46
	XC_0031 XC_1876 XC_3314	XCC8004_a00421 glutamate synthase XCC8004_a23321 argininosuccinate lyase XCC8004_a41651 disulfide bond formation protein B	-1,45 -1,46 -1,53	-2,76 -3,52 -1,97	-0,12 0,08 -1,92	0,07 0,06 -2,43	-0,11 0,03 -2,29	-0,23 -0,64 -2,05
	XC_0032 XC_1880 XC_3388	XCC8004_a00431 glutamate synthase large subunit XCC8004_a23361 glutamate-5-semialdehyde dehydrogenase XCC8004_a42701 DUF1631 domain-containing protein	-1,31 -0,32 0,36	-2,61 -1,17 1,28	0,01 -0,02 -0,60	0,03 -0,05 -0,89	-0,15 -0,19 -1,22	-0,22 -1,26 -0,35
	XC_0100 XC_1906 XC_3439	XCC8004_a01281 aromatic amino acid aminotransferase XCC8004_a23681 rifampin ADP-ribosyl transferase XCC8004_a43301 4-hydroxythreonine-4-phosphate dehydrogenase	-1,82 -1,09 -0,37	-2,85 -1,09 -1,19	-0,85 -0,37 -0,03	-1,93 -0,46 -0,11	-3,06 -0,33 -0,27	-1,55 -0,48 -0,05
	XC_0143 XC_1927 XC_3526	XCC8004_a01841 1,4-alpha-glucan branching protein GlgB XCC8004_a23941 tetratricopeptide repeat protein XCC8004_a44361 dimethylmenaquinone methyltransferase	-1,93 -1,41 -0,89	-2,66 -2,47 -1,12	-0,08 0,21 -0,11	-0,15 0,15 -0,30	-0,08 0,39 -0,55	-0,08 0,44 -0,05
	XC_0186 XC_1928 XC_3544	XCC8004_a02321 cardiolipin synthase XCC8004_a23951 lipopolysaccharide biosynthesis protein XCC8004_a44581 serine hydroxymethyltransferase	-0,43 -2,24 -1,16	-1,58 -2,94 -2,63	-0,52 0,43 -0,20	-0,65 0,15 -1,36	-0,81 0,07 -2,48	-0,70 0,54 -3,99
	XC_0196 XC_1929 XC_3563	XCC8004_a02471 ammonium transporter XCC8004_a23961 multidrug MFS transporter XCC8004_a44801 general secretion pathway protein GspD	-0,51 -1,93 -0,77	-1,20 -2,30 -1,20	0,07 0,34 -0,08	0,01 -0,03 -0,19	-0,05 -0,16 -0,27	-0,01 0,67 -0,70
	XC_0198 XC_1952 XC_3566	XCC8004_a02501 nitrogen regulation protein NR(I) XCC8004_a24221 phosphoenolpyruvate synthase XCC8004_a44851 general secretion pathway protein GspL	-1,01 -0,65 -1,08	-1,14 -1,71 -1,51	-0,07 -0,01 -0,02	-0,08 -0,18 -0,19	-0,75 -0,01 -0,34	-0,22 -3,27 -0,85
	XC_0213 XC_1958 XC_3567	XCC8004_a02681 preprotein translocase subunit SecB XCC8004_a24301 PHA synthase subunit XCC8004_a44861 general secretion pathway protein GspK	-1,72 -1,99 -0,80	-2,14 -2,95 -1,43	-1,19 0,10 -0,06	-1,36 0,31 -0,30	-1,68 0,44 -0,38	-0,75 -0,77 -0,73
	XC_0329 XC_1959 XC_3572	XCC8004_a04001 DUF1852 domain-containing protein XCC8004_a24311 poly-beta-hydroxybutyrate polymerase XCC8004_a44911 general secretion pathway protein GspF	-1,15 -1,79 -0,50	-1,28 -3,27 -1,59	-0,01 0,03 -0,37	0,13 0,22 -0,19	0,15 0,43 -0,23	-0,64 -0,90 -0,91
	XC_0356 XC_1977 XC_3578	XCC8004_a04481 dihydroxy-acid dehydratase XCC8004_a24701 glucose-6-phosphate dehydrogenase XCC8004_a44991 phosphoribosylformylglycinamidine synthase	-1,38 -0,92 -2,25	-3,62 -1,11 -3,47	-0,05 -0,25 -0,10	0,18 -1,80 -3,21	0,01 -2,47 -1,66	0,12 -0,13 -3,55
	XC_0399 XC_0400 XC_2059 XC_3605	XCC8004_a05011 8-amino-7-oxononanoate synthase XCC8004_a05021 biotin synthase XCC8004_a25301 DUF4189 domain-containing protein XCC8004_a25851 MULTISPECIES: hypothetical protein XCC8004_a45331 conserved protein involved in carbohydrate biosynthesis	-0,30 -1,28 -0,95 -1,76 -1,18	-1,47 -3,31 -1,19 -2,26 -1,60	0,00 -0,04 -0,03 -0,56 0,45	-0,34 -1,97 -0,03 -0,75 -0,01	-0,15 -2,46 0,03 -1,15 -0,35	-0,02 -0,55 -0,02 -1,45 0,89
	XC_0447 XC_0449 XC_0467 XC_0473 XC_0483 XC_0484 XC_0486 XC_0509 XC_0522 XC_0657 XC_0714 XC_2103 XC_3608 XC_2208 XC_3609 XC_2218 XC_3612 XC_2228 XC_3613 XC_2252 XC_3627 XC_2272 XC_3630 XC_2333 XC_3634 XC_2335 XC_3696 XC_2354 XC_3718 XC_2364 XC_3745 XC_2375 XC_3760	XCC8004_a05731 dihydroorotate dehydrogenase XCC8004_a05761 MarR family transcriptional regulator XCC8004_a06001 phosphoribosylaminoimidazole-succinocarboxamide synthase XCC8004_a06071 anthranilate synthase component I XCC8004_a06201 anthranilate phosphoribosyltransferase XCC8004_a06211 indole-3-glycerol-phosphate synthase XCC8004_a06231 transcriptional regulator XCC8004_a06601 phosphoribosylamine--glycine ligase XCC8004_a06761 XRE family transcriptional regulator XCC8004_a08411 putative exported protein XCC8004_a09141 peptidase S41 XCC8004_a26461 Fe/S biogenesis protein NfuA XCC8004_a27231 stress-induced protein XCC8004_a45401 phosphomannomutase XCC8004_a27671 voltage-gated chloride channel protein XCC8004_a45411 mannose-1-phosphate guanyltransferase XCC8004_a27781 Clp protease ClpX XCC8004_a45451 glucose-1-phosphate thymidylyltransferase XCC8004_a27921 c-di-GMP phosphodiesterase XCC8004_a45461 dTDP-glucose 4,6-dehydratase XCC8004_a28231 chemotaxis protein CheY XCC8004_a45631 GDP-D-mannose dehydratase XCC8004_a28471 flagellar biosynthetic protein FliR XCC8004_a45671 glycosyl transferase XCC8004_a29211 hybrid sensor histidine kinase/response regulator XCC8004_a45741 glycosyl transferase XCC8004_a29231 cation tolerance protein CutA XCC8004_a46551 putative exported protein XCC8004_a29431 iron transporter FeoB XCC8004_a46791 alanine racemase XCC8004_a29541 D-3-phosphoglycerate dehydrogenase XCC8004_a47121 amino acid transporter XCC8004_a29661 imidazole glycerol phosphate synthase XCC8004_a47281 sigma-54-dependent Fis family transcriptional regulator	-1,11 -1,52 -1,67 -1,62 -1,93 -2,08 1,13 -2,35 0,19 -0,25 -1,12 -0,42 1,23 -0,94 -0,95 -3,34 -1,36 -1,82 0,03 -1,33 0,34 -2,52 1,38 -1,37 1,25 -1,38 1,64 -2,68 -0,25 -3,43 -0,36 -0,47 -1,94 0,75	-1,27 -2,15 -2,97 -3,00 -3,91 -4,80 2,28 -3,26 1,06 -1,04 -1,31 -1,20 1,24 -1,03 -2,12 -4,75 -1,76 -1,82 1,04 -1,88 1,06 -2,40 1,56 -1,96 2,34 -2,34 3,12 -3,23 -1,20 -3,65 -1,98 -1,01 -3,06 1,06	-0,90 0,11 -0,30 -0,03 0,02 -0,03 0,29 -0,14 0,04 0,06 -0,24 -0,06 0,28 0,17 0,02 0,27 -0,28 0,28 0,01 0,31 -0,10 0,29 0,02 0,23 0,25 0,46 0,21 -0,61 -0,34 -0,21 0,18 -0,35 -0,14 0,30	-0,55 -0,22 -3,51 -0,03 -0,28 -0,19 0,19 -3,18 -0,05 -0,10 -1,11 -0,04 0,02 -0,68 -0,05 -2,82 -0,31 0,13 0,05 0,08 -0,28 -0,14 0,02 -0,36 -0,07 0,06 0,06 -0,21 -0,67 -0,35 -0,15 -0,19 -0,22 0,02	-0,52 -0,24 -1,89 -2,92 -4,23 -5,09 0,24 -3,05 0,04 0,04 -1,90 -0,06 0,02 -0,64 0,00 -4,65 -0,96 -0,12 0,12 0,01 -0,42 -0,12 0,07 -0,46 -0,28 -0,20 -0,12 0,62 -0,65 -3,96 -2,54 -0,41 -3,45 0,18	-0,45 -0,44 -3,53 -0,06 0,04 -0,18 0,78 -3,25 0,15 -0,02 -0,22 0,11 -2,46 1,23 -4,80 0,01 0,95 -1,01 0,95 -0,06 0,35 0,36 0,15 0,24 0,58 0,73 -0,70 0,50 -3,29 -0,93 -0,22 -2,48 -0,31 1,14
	XC_0753 XC_0754 XC_2376 XC_3813 XC_0764 XC_3814 XC_0800 XC_0805 XC_0810 XC_0814 XC_0833 XC_0834 XC_0836 XC_0837 XC_0838 XC_0840 XC_2524 XC_2377 XC_3815 XC_3886 XC_2378 XC_3896 XC_2379 XC_3937 XC_2380 XC_3938 XC_2386 XC_3939 XC_2389 XC_4008 XC_2407 XC_4041 XC_2465 XC_4281	XCC8004_a09561 iron dicitrate transport regulator FecR XCC8004_a09571 N-acetylglucosamine-6-phosphate deacetylase XCC8004_a29671 1-(5-phosphoribosyl)-5-[(5-phosphoribosylamino) methylideneamino] imidazole-4-carboxamide XCC8004_a47981 CDP-glycerol glycerophosphotransferase XCC8004_a09681 thiol:disulfide interchange protein XCC8004_a47991 lipopolysaccharide biosynthesis protein isomerase XCC8004_a10101 aminotransferase XCC8004_a10161 amylosucrase XCC8004_a10221 citrate transporter XCC8004_a10281 ABC transporter substrate-binding protein XCC8004_a10491 isopropylmalate isomerase XCC8004_a10501 3-isopropylmalate dehydratase XCC8004_a10531 3-isopropylmalate dehydrogenase XCC8004_a10561 2-isopropylmalate synthase XCC8004_a10591 acetolactate synthase catalytic subunit XCC8004_a31621 protein-L-isoaspartate O-methyltransferase XCC8004_a10571 threonine dehydratase XCC8004_a48001 polymerase XCC8004_a29681 imidazole glycerol phosphate synthase subunit XCC8004_a48851 beta-glucosidase HisH XCC8004_a48971 protoheme IX farnesyltransferase XCC8004_a29691 imidazoleglycerol-phosphate dehydratase XCC8004_a49561 protein CapI XCC8004_a29701 histidinol-phosphate aminotransferase XCC8004_a49571 dolichol-phosphate mannosyltransferase XCC8004_a29711 histidinol dehydrogenase XCC8004_a49581 membrane protein XCC8004_a29771 threonine synthase XCC8004_a50461 hypothetical protein XCC8004_a29801 aspartate kinase XCC8004_a50911 shikimate dehydrogenase XCC8004_a30021 MULTISPECIES: hypothetical protein XCC8004_a30741 glucose-6-phosphate isomerase XCC8004_a54181 ParA family protein	-2,55 -2,58 -1,48 -1,77 -1,66 -2,35 -0,94 -1,40 -0,38 -0,38 -1,60 -1,60 -2,38 -0,65 -1,04 -1,05 -0,69 -2,26 -2,08 -2,71 -0,89 -0,84 -1,04 -0,87 -2,44 -0,97 -0,89 -0,57 -1,15 -1,56 -1,01 -2,38 -2,28 -1,19	-4,28 -3,14 -3,55 -3,46 -2,52 -3,29 -2,41 -1,17 -1,38 -1,38 -4,03 -2,97 -3,66 -1,93 -3,30 -1,51 -2,23 -2,73 -4,04 -3,55 -3,53 -1,12 -2,65 -1,63 -2,42 -1,55 -2,50 -1,31 -2,59 -1,91 -3,35 -3,08 -2,76 -1,37	0,00 0,10 0,04 0,10 -0,12 0,28 0,10 0,00 0,08 -0,01 0,03 0,01 -0,17 -0,01 -0,05 -0,43 -0,01 0,09 0,20 -0,10 -0,15 -0,60 -0,10 -0,07 -0,01 -0,13 -0,07 0,02 -0,10 -0,34 0,04 -0,19 -0,35 -0,49	0,00 0,28 -0,18 -0,02 -0,17 -0,18 -0,20 -0,06 0,09 -0,22 -0,30 -0,07 -0,02 -0,03 0,12 -1,42 0,04 -0,02 0,18 -1,20 0,13 -0,83 0,00 -0,06 -0,06 -0,12 0,07 0,05 -0,13 -0,06 0,03 -0,27 -0,09 -1,04	-0,09 0,22 -4,53 -0,05 -0,20 -0,45 -3,91 0,11 0,17 -0,02 -4,76 -3,78 -4,52 -1,90 -0,49 -1,09 -0,37 -0,25 -4,30 -1,03 -4,46 -0,78 -4,88 0,10 -3,61 -0,08 0,09 0,16 -0,05 0,37 0,06 -2,87 -0,18 -0,94	-0,34 -1,73 -0,09 -2,79 -2,24 -0,70 -0,90 -0,21 -0,10 -0,12 -0,03 -0,15 -0,35 0,27 -0,13 -0,58 0,07 0,58 0,04 -1,82 -0,27 -0,22 -0,03 -1,60 0,12 -1,01 -0,03 -0,76 -0,07 -0,57 -0,02 -1,04 -1,86 -0,18
	XC_0841 XC_2643	XCC8004_a10601 ketol-acid reductoisomerase XCC8004_a33121 3-phosphoshikimate 1-carboxyvinyltransferase	-1,28 -1,53	-3,48 -4,01	-0,04 -0,32	0,01 -0,24	0,01 -2,76	0,40 -2,54
	XC_0972 XC_2644	XCC8004_a12331 glyceraldehyde-3-phosphate dehydrogenase XCC8004_a33131 chorismate mutase	-2,01 -1,61	-2,70 -3,52	-0,08 -0,04	-0,26 -0,18	-1,92 -0,46	-2,27 -1,25
	XC_0976 XC_2645 XC_1015 XC_2667	XCC8004_a33141 MFS transporter XCC8004_a12381 phosphoglycerate kinase XCC8004_a12811 thiazole synthase XCC8004_a33411 chromosome segregation protein SMC	-1,11 -1,08 -0,47 -0,55	-1,85 -2,56 -1,11 -1,63	-0,15 -0,03 -0,05 -0,57	-0,01 -0,24 0,25 -0,75	-2,03 -2,34 -0,47 -0,76	-2,46 -2,49 -0,02 -0,61
	XC_1050 XC_2678	XCC8004_a13341 histidine kinase XCC8004_a33551 carbonate dehydratase	-1,19 -2,03	-2,94 -2,99	-0,38 -2,12	-0,98 -2,07	-0,58 -0,59	-0,16 -2,48
	XC_1067 XC_2708	XCC8004_a13571 NAD synthetase XCC8004_a33911 phosphate-binding protein	-1,63 -1,09	-2,12 -2,16	-1,03 0,01	-0,73 -0,29	-2,43 0,08	-2,62 0,02
	XC_1078 XC_2709 XC_1113 XC_2710	XCC8004_a33921 phosphate ABC transporter permease XCC8004_a13701 trehalose-phosphatase XCC8004_a14101 TonB-dependent receptor XCC8004_a33931 phosphate ABC transporter permease	-1,72 -1,05 -0,46 -1,32	-1,59 -3,25 -1,94 -2,28	0,18 0,17 0,09 0,06	-1,89 0,02 -0,05 0,10	-4,53 0,06 -0,02 0,01	-0,39 -0,01 0,10 -0,01
	XC_1134 XC_2711	XCC8004_a14341 potassium transporter Kup XCC8004_a33941 phosphate ABC transporter ATP-binding protein	-1,87 -1,37	-2,28 -2,12	-0,53 -0,02	0,02 -0,01	-0,29 0,14	-1,73 0,01
	XC_1175 XC_1225 XC_2768 XC_2827	XCC8004_a14901 glycosyl transferase XCC8004_a15571 XCC8004_a34661 membrane protein adenosylmethionine-8-amino-7-oxononanoate aminotransferase XCC8004_a35451 MarR family transcriptional regulator	-1,15 -2,20 -0,86 0,73	-1,47 -2,55 -1,76 1,61	0,43 -0,52 -0,07 0,27	0,11 -0,66 -0,54 -0,02	0,00 -0,44 -0,42 0,04	0,87 -0,57 -0,08 0,41
	XC_1235 XC_1307 XC_2847	XCC8004_a15711 beta-lactamase XCC8004_a16551 nucleotide-binding protein XCC8004_a35711 right-handed parallel beta-helix repeat-containing protein	-0,42 -1,92 -2,47	-1,36 -1,38 -5,03	0,10 -0,09 -0,07	0,11 -0,08 -0,03	0,27 -0,13 -0,04	0,05 -0,84 -1,55
	XC_1311 XC_2848	XCC8004_a16591 RNA polymerase sigma54 factor XCC8004_a35721 asparagine synthase B	-1,31 -0,81	-1,65 -1,93	-0,17 0,26	-0,06 -0,54	-0,10 -4,52	0,50 0,19
	XC_1324 XC_2956 XC_3076	XCC8004_a16731 XCC8004_a36941 5'-methylthioadenosine phosphorylase Phosphoribosylformylglycinamidine cyclo-ligase (AIR synthase) XCC8004_a38371 DNA-binding protein	0,20 -3,02 0,29	-1,13 -3,92 1,71	0,05 0,03 0,00	-0,28 -3,14 -0,04	-0,18 -1,28 -0,11	-0,15 -3,42 0,13
	XC_1328 XC_3077	XCC8004_a16771 mannose-1-phosphate guanylyltransferase XCC8004_a38401 transcriptional regulator	-0,74 0,76	-1,26 1,75	0,17 0,01	0,24 -0,19	0,33 -0,03	-1,09 -0,02
	XC_1404 XC_3083	XCC8004_a17601 phosphoglyceromutase XCC8004_a38471 cytochrome o ubiquinol oxidase subunit I	-2,28 -0,60	-2,26 -1,12	-0,01 -0,47	0,38 -0,81	-0,82 -0,93	-2,20 -0,04
	XC_1431 XC_3114	XCC8004_a17891 TetR family transcriptional regulator XCC8004_a38881 polyketide cyclase	-0,98 -3,27	-2,05 -3,66	0,09 -0,69	-0,19 -0,18	-0,48 0,52	-0,05 -0,76
	XC_1567 XC_3121 XC_1575 XC_3195 XC_1577 XC_3196	XCC8004_a38951 septum formation inhibitor XCC8004_a19511 chorismate synthase XCC8004_a39871 membane protease HflC XCC8004_a19601 tryptophan synthase subunit beta XCC8004_a19631 tryptophan synthase alpha chain XCC8004_a39881 membrane protein	-1,11 -0,17 -2,57 -1,21 -2,95 -0,67	-2,84 -1,65 -3,96 -1,31 -4,28 -1,12	-0,36 -0,28 -0,02 -0,07 -0,08 -0,25	-0,06 -0,36 -0,01 -0,75 -0,04 -0,63	-2,58 0,12 -4,45 -0,74 -2,58 -0,79	-1,64 -0,59 -0,13 -0,22 0,09 -0,19
	XC_1613 XC_3210	XCC8004_a20101 N5-carboxyaminoimidazole ribonucleotide mutase XCC8004_a40081 3-methylitaconate isomerase	-4,25 -0,58	-4,86 -1,28	-0,50 -0,92	-5,11 -0,74	-2,46 -0,67	-4,73 -1,19
	XC_1614 XC_3251	XCC8004_a20111 phosphoribosylaminoimidazole carboxylase XCC8004_a40601 3-deoxy-D-manno-octulosonic acid kinase	-1,75 -1,63	-4,26 -3,00	-0,10 -0,31	-3,30 -0,02	-2,68 0,21	-3,50 -0,77
	XC_1658 XC_1659 XC_3252	XCC8004_a20841 polysaccharide biosynthesis protein GumB XCC8004_a20861 polysaccharide biosynthesis protein GumC XCC8004_a40611 lipopolysaccharide heptosyltransferase family protein	-2,06 -1,30 -2,52	-2,63 -2,64 -3,09	0,30 0,15 0,09	-0,99 -0,25 -0,24	-2,66 -1,90 -0,50	-0,63 -0,76 -2,97
	XC_1681 XC_3253	XCC8004_a21101 Putative secreted protein XCC8004_a40621 hypothetical protein	-1,45 -1,62	-1,38 -4,05	-0,33 0,05	-0,54 -0,16	-0,55 -0,63	-0,45 -3,08
	XC_1782	XCC8004_a22241 membrane protein	-0,71	-2,09	-1,97	-2,09	-1,83	-1,13
	XC_1783	XCC8004_a22261 magnesium transporter	-0,61	-1,59	-0,32	-0,42	-0,54	-0,69
	XC_1821	XCC8004_a22691 beta-ketoacyl-ACP reductase	-1,37	-3,08	0,17	0,34	0,55	-0,75
			OR OM OS

Table S3 | Genes important for Xcc growth in xylem sap but not in hydathodes. Table S4 | Genes contributing to Xcc fitness in both hydathodes and xylem sap

 S3

	$ %	$ %$&'()	*			*
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Table S6 | List of strains and plasmids used in this study Strain or Plasmid Relevant characteristics Reference or source Xanthomonas campestris pv. campestris

 S6

	pRK2073		Helper plasmid for triparental mating; Spec R ; Strep R Leong et al., 1982
	pK18mobSacB		Suicide vector in Xcc used for genome edition;		Schäfer et al., 1994
			Kan R
	Biosynthesis Alanine 8004 strain derivative; constitutive GUS and GFP Hyd 3dpi Hyd 6dpi XS DO-LTH MME + + + pK18mobsacB used for genomic insertion; Kan R Luneau et al., in prep MME Glucose Cerutti et al., 2017 + Asparagine + + + expression; Rif R pK18_XC0143_AmAv 8004::GUS-GFP pK18_compR3 pK18mobSacB derivative for deletion of XC_0143; This study Aspartic acid + + + + RB-TnSeq library 8004::GUS-GFP transposon-insertion mutants ; Kan R This study Arginine ++ 8004::GUS-GFP XC_0143 (glgB1) deletion mutant, constitutive GUS This study Kan R Rif R ; Kan R pK18_XC0449_AmAv pK18mobSacB derivative for deletion of XC_0449; This study	MOKA	Essential genes ?	Hyd only + +	Hyd + XS +	XS only
	Cysteine pK18_XC0555_AmAv XC_0143	and GFP expression; Rif R pK18mobSacB derivative for deletion of XC_0555;		This study
	8004::GUS-GFP	Glutamine XC_0449 deletion mutant, constitutive GUS and + Kan R		This study
	Glycine pK18_XC0810_AmAv XC_0449	+ pK18mobSacB derivative for deletion of XC_0810; + GFP expression; Rif R	+	This study	+	+
	8004::GUS-GFP	Glutamic acid XC_0555 deletion mutant, constitutive GUS and + Kan R		This study		+	+
	Histidine pK18_XC1113_AmAv XC_0555	++ pK18mobSacB derivative for deletion of XC_1113; GFP expression; Rif R	++ This study		+
	8004::GUS-GFP	Isoleucine XC_0810 (citM) deletion mutant, constitutive GUS ++ Kan R		This study		+
	Lysine pK18_XC1431_AmAv XC_0810 Leucine 8004::GUS-GFP XC_1113 pK18_XC1958-59_AmAv pK18mobSacB derivative for deletion of XC_1958-and GFP expression; Rif R pK18mobSacB derivative for deletion of XC_1431; ++ XC_1113 (bfeA) deletion mutant, constitutive GUS Kan R and GFP expression; Rif R	This study ++ This study This study		YES	+
	8004::GUS-GFP	Phenylalanine XC_1431 deletion mutant, constitutive GUS and + ++ + 59; Kan R	+	This study	+	+
	Methionine GFP expression; Rif R pK18_XC2377_AmAv XC_1431 pK18mobSacB derivative for deletion of XC_2377;		This study
	8004::GUS-GFP	Serine	+ XC_1958-59 (phaE-phcC) deletion mutant, + + Kan R	+	This study		+
	Proline Tryptophan XC_2377 (hisH) deletion mutant, constitutive GUS ++ ++ Kan R constitutive GUS and GFP expression; Rif R pK18_XC2620_AmAv 8004::GUS-GFP XC_1958-59 pK18mobSacB derivative for deletion of XC_2620;	+ ++ This study This study		+	+
	Threonine and GFP expression; Rif R pK18_XC3076_AmAv XC_2377 pK18mobSacB derivative for deletion of XC_3076; ++ Tyrosine + + + 8004::GUS-GFP XC_2620 deletion mutant, constitutive GUS and Kan R XC_2620 GFP expression; Rif R pK18_XC3253_AmAv pK18mobSacB derivative for deletion of XC_3253;	+	This study This study This study	+	+
	8004::GUS-GFP		XC_3076 (hrpX) deletion mutant, constitutive GUS Kan R		This study
	XC_3076 pK18_XC3388_AmAv	and GFP expression; Rif R pK18mobSacB derivative for deletion of XC_3388;		This study
	8004::GUS-GFP		glgB1 (XC_3253) deletion mutant, constitutive GUS Kan R	This study
	XC_3253 pK18_comp_XC3388	and GFP expression; Rif R pK18_compR3 derivative used for		This study
	8004::GUS-GFP		glgB1 (XC_3388) deletion mutant, constitutive GUS complementation of XC_3388; Kan R	This study
	XC_3388		and GFP expression; Rif R
	8004::GUS-GFP		XC_3388 complemented mutant, constitutive GUS		This study
	XC_3388:: XC_3388	and GFP expression; Rif R
	8004::GUS-GFP fliC	fliC (XC_2245) deletion mutant, constitutive GUS		Luneau et al., in prep
			and GFP expression; Rif R
	E. coli
	TG1		supE thi-1 (lac-proAB) (mcrB-hsdSM)5 (rk -mk -	Stratagene
			) [F´ traD36 proAB lacI q Z M15]
	Plasmids
			N

Valine N

Table 1 | Symptômes de collapse observés chez tous les mutants d'effecteurs de type III de Xcc 8004.

 1 Tous les mutants présentent un profil similaire à la souche sauvage 8004 avec un collapse complet à 3 dpi. Chaque souche a été inoculée sur 2 plantes, le résultat de chaque plante est présenté dans une colonne à chaque jour d'observation. 0 : Aucun symptômes ; SC : Début de collapse avec seulement quelques points éparpillés dans la zone infiltrée ; C : Collapse de toute la zone infiltrée.

	Nom du gène	ID du gène (Xcc 8004)

"0 Annexe | Liste des souches et plasmides construits pour l'étude du coût de virulence et de l'hétérogénéité phénotypique chez Xcc

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Liste des oligos utilisés pour l'étude de l'hétérogénéité phénotypique chez Xcc

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Acknowledgments

AC and JL were funded by a PhD grant from the French Ministry of Higher Education, Research and Innovation. BR, AC and LDN were funded by grants from the Agence Nationale de la Recherche XANTHOMIX (ANR-2010-GENM-013-02), Xopaque (ANR-10-JCJC-1703-01) and NEPHRON (ANR-18-CE20-0020-01). We are grateful to Stéphanie Bolot for management and early analysis of the Xanthomix dataset. JL, EL, AB and LDN were funded by the XBOX (ANR-19-CE20-JCJC-0014-01) project. The Laboratoire des Interactions Plantes-Microorganismes is part of the French Laboratory of Excellence project (TULIP ANR-10-LABX-41; ANR-11-IDEX-0002-02). All authors benefited from the COST action CA16107 EuroXanth. Acknowledgment This work was supported by a PhD grant from the French Ministry of National Education and Research to JSL. JSL, LDN, EL and AB are supported by the ANR (ANR-19-CE20-0014-01). LIPM is part of the French Laboratory of Excellence project (TULIP ANR-10-LABX-41; ANR-11-IDEX-0002-02).

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Competing interests

There are no competing interests.

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