Roxane Roquigny

Julia Mougin

Cédric Le Bris

Maryse Bonnin-Jusserand

Périne Doyen

Thierry Grard
email: thierry.grard@univ-littoral.fr

Characterization of the marine aquaculture microbiome: a seasonal survey in a seabass farm

Keywords: seabass farm microbiomes, biofilms, tank water, 16S rRNA gene sequencing, Vibrionaceae

Vibriosis is a recurrent disease in marine aquaculture environments. Monitoring the dynamics of bacterial populations in several compartments of the aquaculture infrastructure is of paramount importance to understand the occurrence of the disease. In the present study, the fish farm, located in the north of France, is a flow-through system where the tanks are supplied by two water inlets. Water from breeding tanks, and inlets and the biofilms in the tanks were sampled weekly in a seabass farm for 7 months. DNA was extracted from 477 samples to sequence the variable V4-V5 region of the 16S rRNA gene and analyze the sequences using the QIIME2 platform. Proteobacteria (54.52 %) and Bacteroidetes (26.85 %) composed more than 80% of the phylum diversity. Alpha-and beta-diversity indicators showed that bacterial communities were more diverse in samples from biofilms and tanks than in samples from water inlets. Some families were specific to one compartment, e.g. ammoniumoxidizing bacteria in biofilms, whereas Vibrionaceae family isolates were mostly found in tank water samples. Taxa were determined up to the species level for the Vibrionaceae. Besides, all six determined genera of Vibrionaceae were identified, with mostly Vibrio and Photobacterium isolates detected in almost all samples. Vibrionaceae persisted over time in the biofilms. Our results suggest

Introduction

Over the past decade, aquaculture mass production has increased worldwide [START_REF] Ahmed | Global aquaculture productivity, environmental sustainability, and climate change adaptability[END_REF].

European seabass (Dicentrarchus labrax, L.) is one of the most farmed aquaculture species produced with a production about 191,000 t in 2016 (FAO, 2005(FAO, -2020)). Aquaculture is a fast-growing sector whose growth is limited by several challenges. There are geographic factors, such as the availability of water and land, as well as environmental factors such as the pollution of coastal zones [START_REF] Ahmed | Toolbox Approaches Using Molecular Markers and 16S rRNA Gene Amplicon Data Sets for Identification of Fecal Pollution in Surface Water[END_REF]. Disease outbreaks remain one of the main challenges, responsible for severe fish losses, leading to the loss of billions of dollars every year [START_REF] Lafferty | Infectious Diseases Affect Marine Fisheries and Aquaculture Economics[END_REF].

Belonging to Gammaproteobacteria, the Vibrionaceae family is composed of six well-identified genera and more than 140 species [START_REF] Thompson | Biodiversity of Vibrios[END_REF]. It is one of the most predominant bacterial groups in marine environments with a worldwide distribution [START_REF] Mursidi | Vibriosis in Fish: A Review on Disease Development and Prevention[END_REF][START_REF] Thompson | Biodiversity of Vibrios[END_REF]. Several Vibrionaceae species have been identified as pathogens of farmed aquatic animals. Specifically, the Vibrio, Photobacterium and Aliivibrio genera are responsible for vibriosis [START_REF] Mursidi | Vibriosis in Fish: A Review on Disease Development and Prevention[END_REF]. Lethargy, skin lesions and hemorrhagic septicemia characterize affected fish [START_REF] Mursidi | Vibriosis in Fish: A Review on Disease Development and Prevention[END_REF]. On the one hand, global warming stimulates the occurrence of the repeated vibriosis outbreaks in farming systems [START_REF] Travers | Influence of temperature and spawning effort on Haliotis tuberculata mortalities caused by Vibrio harveyi: an example of emerging vibriosis linked to global warming[END_REF][START_REF] Vezzulli | Effects of Global Warming on Vibrio Ecology[END_REF]. On the other hand, biofilm formation enhances the virulence and the persistence of Vibrionaceae and some other species, partly due to horizontal gene transfer of potential virulence genes [START_REF] Abe | Biofilms: hot spots of horizontal gene transfer (HGT) in aquatic environments, with a focus on a new HGT mechanism[END_REF][START_REF] Faruque | Transmissibility of cholera: In vivo-formed biofilms and their relationship to infectivity and persistence in the environment[END_REF][START_REF] Karunasagar | Biofilm formation by Vibrio harveyi on surfaces[END_REF]. [START_REF] Michaud | Phylogenetic characterization of the heterotrophic bacterial communities inhabiting a marine recirculating aquaculture system[END_REF] found that most of the detected potential pathogens (e.g. Vibrio spp., Erwinia spp. and Coxiella spp.) are associated with the biofilter biofilms in a recirculating aquaculture system (RAS) for rearing seabass. Multispecies biofilms are therefore considered as a reservoir for potential pathogenic and antibiotic-resistant bacteria [START_REF] King | Identification of Bacterial Pathogens in Biofilms of Recirculating Aquaculture Systems[END_REF]. Moreover, [START_REF] Kotob | The impact of co-infections on fish: a review[END_REF] indicated that the relationships between microorganisms determine whether opportunistic pathogens proliferate and become virulent. Next-generation sequencing (NGS) technologies are one way to consider the importance of all species for a better understanding of the development of disease outbreaks and the fragile equilibrium within microbiomes.

Despite the development of aquaculture, most studies still mainly focus on microbiota of the reared species' organs [START_REF] Larsen | Characterization of the gut microbiota of three commercially valuable warmwater fish species[END_REF]. One study investigating the microbiome of the shrimp gut and tank water samples from two shrimp farms showed that microbial diversity was lower in the shrimp gut than in the tank water [START_REF] Zoqratt | Microbiome analysis of Pacific white shrimp gut and rearing water from Malaysia and Vietnam: implications for aquaculture research and management[END_REF]. Another recent study investigated the skin and gill microbiomes of seabass and seabream from a fish farm [START_REF] Rosado | Characterization of the skin and gill microbiomes of the farmed seabass (Dicentrarchus labrax) and seabream (Sparus aurata)[END_REF] and attested that the diversity of microbiomes was tissue-specific within and between species. Nevertheless, both studies detected potential pathogens such as Vibrio spp., which can lead to disease outbreaks in case of a shift in bacterial abundance (e.g. dysbiosis). Studies dealing with the microbial composition from biofilms and water in the tanks mainly involve RAS [START_REF] Michaud | Phylogenetic characterization of the heterotrophic bacterial communities inhabiting a marine recirculating aquaculture system[END_REF][START_REF] Wang | Intestinal microbiota of healthy and unhealthy Atlantic salmon Salmo salar L. in a recirculating aquaculture system[END_REF][START_REF] Wietz | Effects of seawater ozonation on biofilm development in aquaculture tanks[END_REF], but other studies have investigated temporal variations of bacterioplankton and the seasonal dynamics of bacterial and microeukaryotic plankton communities, e.g. in a semi-intensive European seabass aquaculture system [START_REF] Duarte | Bacterial and microeukaryotic plankton communities in a semi-intensive aquaculture system of sea bass (Dicentrarchus labrax): A seasonal survey[END_REF][START_REF] Martins | Seasonal patterns of bacterioplankton composition in a semi-intensive European seabass (Dicentrarchus labrax) aquaculture system[END_REF]. The seasonal studies showed that changes in environmental variables influence the overall microbial communities.

In this context, we conducted a seasonal survey from April to October 2018 in a seabass farm in the North of France. Every year, this farm undergoes economic losses due to vibriosis outbreaks during summer. The aim of this study was to characterize the marine fish farm microbiomes and to determine the dynamics of bacterial populations in the different compartments of the aquaculture infrastructure.

The objective was particularly to understand if Vibrio species get into the tanks during summer through the water inlets or if they persist throughout the year as biofilms. Studying the microbial composition can help understand the recurrence of vibriosis during summer. We therefore sampled biofilms and the water from the tanks and the inlets. The V4-V5 variable region of the 16S rRNA gene was amplified and then sequenced using an Illumina MiSeq platform. To our knowledge, this is the first study to carry out a weekly seasonal survey for 7 months on a fish farm with a comparison of microbial composition between water inlets, tank water and biofilms in the tanks.

Materials and methods

Sampling campaign

The experiments were conducted from April to October 2018 for 31 weeks, in Aquanord Ichtus sea farm (Gravelines, France). The fish farm installation and process have been described in the year 2018 IFREMER annual report [START_REF] Antajan | Surveillance écologique du site de production électronucléaire de Gravelines, novembre 2017 -octobre 2018[END_REF]. Briefly, the fish farm is a flow-through system where the tanks are supplied by two water inlets. The "cold-water" inlet supplies tanks with water from the surrounding local seawater. The "hot-water" inlet supplies tanks with seawater coming from the hotwater discharge canal of a nuclear power system. Several parameters, such as temperature, salinity, conductivity, pH and dissolved oxygen, were measured in the upper surface of the water of each compartment (Table S1). During the sampling campaign, no acute vibriosis outbreak occurred and fish losses remained low and stable. Fishes had been vaccinated with an autovaccine, as per annual routine, to fight against vibriosis. Fish density fluctuated from 20,000 to 30,000 individuals per breeding tank.

The water capacity of each tank was 75 m 3 , with a water-column of 1.3 m. The tanks had a mean fish load of 48.13 kg of fish.m -3 . Every week, 1 L of water was collected 20 cm below the water surface, in a sterilized bottle, in triplicate from the three tanks and the two water inlets. The 15 water bottles were kept on ice during the transport to the laboratory and filtered within 2 h. Nitrocellulose filters of 0.45 µm pore size (Sartorius, Goettingen, Germany) were used and then frozen at -80°C in Luria-Bertoni (LB) broth medium supplemented with NaCl (LBS)/20% glycerol. The filtration stage has been optimized for maximum recovery of the bacterial community using a larger volume of water and larger pore size. The pore size was determined based on the high turbidity of the tank water due to suspended organic material. Moreover, to mimic the biofilm formation occurring on the walls of aquaculture tanks, we used the same concrete material to manufacture the pieces of concrete that were immersed (20 cm below the surface of the water), collected and brought back to the laboratory. Three pieces of concrete were not immersed and were considered as blanks (hereafter named B0), whereas samples immersed 2 h in the tanks were named 0B. Every two weeks, pieces of concrete were collected in triplicate from the three same tanks as the water samples. The nine pieces of concrete, still immersed in the water, were maintained on ice during the transport and until processing at the laboratory. Each piece of concrete was swabbed on a defined surface (of 2.34 cm²) with two cotton swabs as previously done by [START_REF] Mougin | Adhesion to stainless steel surfaces and detection of viable but non cultivable cells of Vibrio parahaemolyticus and Vibrio cholerae isolated from shrimps in seafood processing environments: Stayin' alive?[END_REF] and swabs were stored at -80°C in an LBS/20% glycerol medium.

DNA extraction

Filter and swab samples were thawed and vortexed for 3 min to retrieve bacteria. Filters and swabs were discarded and the samples were centrifuged at 8000 × g for 10 min. Supernatants were removed and 25 mL or 3 mL of physiological water were added for samples from water or biofilm, respectively. After a brief vortex, the samples were centrifuged again (8000 × g for 10 min) and supernatants were removed. The pellets were resuspended in 2 mL of physiological water, and briefly vortexed. Samples were then centrifuged (8000 × g for 10 min) for the third time and the supernatants were discarded.

The DNA from each pellet was extracted using the DNeasy PowerBiofilm Kit (Qiagen, Hilden, Germany) following the manufacturer's protocol. The DNA purity was assessed on a Denovix DS-11 spectrophotometer (Clinisciences, Nanterre, France) and DNA concentration was measured using the Qubit TM dsDNA HS Assay Kit on a Qubit 3.0 fluorometer (Invitrogen, Carlsbad, CA, USA). The quantity of extracted DNA was normalized to 5 ng.µL -1 in Tris HCL (10 mM, pH 8.5) for the subsequent PCR assays and stored at -20°C. The 477 aliquots and the three negative control samples (composed of nuclease-free water) were used for metagenomic 16S rRNA gene sequencing. Hereafter samples were named tank water (W), cold-water inlet (CW), hot-water inlet (HW) and biofilm (B) samples depending on their compartment of origin. In the results, the sampling week is indicated before the compartment letter, e.g. sample named 8B came from swabbed biofilms at week 8.

PCR amplification, library preparation, 16S rRNA gene amplicon sequencing

A two-step PCR was performed according to 16S metagenomic sequencing library preparation protocol from Illumina. The first PCR step was carried out in duplicate. The amplicon primers 515F-Y/926R targeted the V4-V5 variable region of the 16S rRNA gene and were purchased from TIB MOLBIOL (Syntheselabor GmbH, Germany). The primers coupled with Illumina Reads adapters 515F-Y 5'-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGGTGYCAGCMGCCGCGGTAA-3' and 926R 5'-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGCCGYCAATTYMTTTRAGTTT-3' resulted in an amplicon of around 480 bp [START_REF] Parada | Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples[END_REF][START_REF] Quince | Removing Noise From Pyrosequenced Amplicons[END_REF]. PCR reactions were carried out in a final volume of 25 µL using 0.5 µL of each amplicon primer (10 µM), 2.5 µL of DNA (5 ng.µL -1 ) and 12.5 µL of 2X Platinum TM Green Hot Start Master Mix (Life Technologies SAS, Thermofisher Scientific, Villepinte, France). The PCR program was as follows: 94°C for 2 min followed by 30 cycles of a 94°C denaturation step for 45 s, a 50°C annealing step for 60 s and a 72°C elongation step for 90 s [START_REF] Raut | Bacterial community response to a preindustrial-to-future CO2 gradient is limited and soil specific in Texas Prairie grassland[END_REF].

Dual indices were attached during the second step PCR, using the Illumina Nextera XT Index Kits v2 (Illumina, Paris, France). PCR reaction was carried out in a final volume of 50 µL using 5 µL of previously purified amplicon, 5 µL of each Nextera XT Index and 25 µL of 2X Platinum TM Green Hot Start Master Mix. PCR program started with 94°C for 2 min followed by 8 cycles with a denaturation step of 94°C for 45 s, an annealing step of 59°C for 60 s and an elongation step of 72°C for 90 s. After each PCR step, PCR products were purified using Agencourt AMPure XP beads (Beckman Coulter, Life Sciences, Villepinte, France) and were verified using electrophoresis on a 1% agarose gel. The expected amplicon size was around 500 bp long. Final product purity was assessed with a Denovix Spectrophotometer and final product concentration was measured using the Qubit TM dsDNA HS Assay Kit on a Qubit 3.0 fluorometer. The quantity of each sample was normalized to 4 nM in TrisHCL (10mM, pH 8.5) and then 5µL of diluted DNA from each library were mixed.

Following the Illumina protocol, pooled library was denatured, diluted to a final concentration of 4 pM, combined with 10% PhiX (Illumina) and loaded using MiSeq reagent v3 kits (600 cycles, 2 × 300 bp) as recommended by the manufacturer. Finally, five sequencing runs of 96 samples each were sequenced as paired-end reads using an Illumina MiSeq platform (Illumina).

Sequence analyses

Sequences were generated in demultiplexed fastq files and analyzed using the quantitative insights into microbial ecology 2 (QIIME2; release 2019.10) open-source platform [START_REF] Bolyen | Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2[END_REF][START_REF] Caporaso | QIIME allows analysis of high-throughput community sequencing data[END_REF]. In each run, a total of 47,746,767 sequences were processed using DADA2 pipeline [START_REF] Callahan | DADA2: Highresolution sample inference from Illumina amplicon data[END_REF][START_REF] Martin | Cutadapt removes adapter sequences from high-throughput sequencing reads[END_REF]. Briefly, paired-end sequences were trimmed to 240 bp, filtered, denoised, merged and chimeras were discarded, resulting in 20,134,001 dereplicated sequences (42.2%), (Table S2). The DADA2 pipeline gave five amplicon sequence variant (ASV) tables, which listed the number of times each exact ASV was observed in each sample [START_REF] Callahan | Exact sequence variants should replace operational taxonomic units in marker-gene data analysis[END_REF]. The five tables were merged and technical triplicates grouped using the sum function. The combined table was filtered to exclude singletons and technical negative control samples. Taxonomy was assigned using a naive Bayes classifier trained on the 99_otus SILVA 132-release database [START_REF] Altschul | Basic local alignment search tool[END_REF][START_REF] Bokulich | Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2's q2-feature-classifier plugin[END_REF][START_REF] Edgar | Search and clustering orders of magnitude faster than BLAST[END_REF][START_REF] Pedregosa | Scikit-learn: Machine learning in Python[END_REF][START_REF] Quast | The SILVA ribosomal RNA gene database project: improved data processing and web-based tools[END_REF][START_REF] Wang | Naïve Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy[END_REF]. The table with taxonomic assignments was filtered a second time to exclude sequences assigned with mitochondria and chloroplast identification. Thus, analyses were subsequently performed on 159 samples, with 17,243,983 sequences clustered into 147,640 ASVs.

Then, we chose a rarefaction depth of 29,725 sequences (27.41% of total retained sequences), which was the lowest read number. All samples were included in the beta-diversity analysis, without need to favor the rarest sequences. The values of the alpha-diversity indicators are detailed in Table S3. Chao1 and Shannon indices were selected to evaluate richness and evenness across sampling weeks and compartments [START_REF] Chao | Nonparametric estimation of the number of classes in a population[END_REF][START_REF] Shannon | The mathematical theory of communication[END_REF]. Two phylogenetic measures of beta-diversity were also selected and visualized in EMPeror [START_REF] Vázquez-Baeza | EMPeror: a tool for visualizing highthroughput microbial community data[END_REF]. The unweighted UniFrac distance was used as a qualitative measure based on the presence/absence of different considered taxa. The weighted UniFrac distance was used as a quantitative measure based on the relative abundance of taxa (Lozupone andKnight, 2005, Lozupone et al., 2011). The phylogeny pipeline was previously applied to the data using MAFFT [START_REF] Katoh | MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability[END_REF], MASK [START_REF] Lane | S/23S rRNA sequencing[END_REF] and FastTree [START_REF] Price | FastTree 2 -Approximately Maximum-Likelihood Trees for Large Alignments[END_REF] algorithms. Alpha-diversity statistical significances were tested using a Kruskal-Wallis test for pairwise comparisons [START_REF] Kruskal | Use of Ranks in One-Criterion Variance Analysis[END_REF]. Statistical significance of beta-diversity distances was analyzed using a PERMANOVA test (999 permutations).

Data availability

All sequences generated in this study are available in the NCBI sequence read archive under the Bioproject accession number PRJNA613386.

Results

Sequencing and classification

During the weekly sampling campaign from April to October 2018, total DNA from 477 samples from water or biofilm samples were extracted. Illumina MiSeq sequenced amplicons of the V4-V5 variable region of the16S rRNA gene using the paired-end method and high quality sequences were obtained and processed. All technical triplicates were combined, leading to 159 samples subsequently analyzed and split into two datasets (Table S4). The water dataset was composed of 110 water samples from hot-and cold-water inlets and from the three breeding tanks for 22 weeks. The second dataset was composed of 48 biofilm samples from the three breeding tanks for 16 weeks and the non-immersed blank (B0). The mean number of sequences per sample obtained in biofilm samples was 140,286 and 94,271 in water samples. The number of sequences ranged from 29,725for the hot-water inlet sample at week 4 (4HW), to 315,298 for the biofilm sample from the second tank at week 24 (24B2). More than 17 million high quality sequences were thus processed with a mean of 108,453 sequences per sample. Each sequence was labeled, generating 147,640 ASVs. After a rarefaction process, taxonomy assignment was applied using the SILVA 132 database and the bacterial compositions were studied at different taxonomic levels.

Bacterial composition

Taxonomic identification

At the phylum level (Fig. 1), results attributed 94.38% of microbial diversity, all sampling dates and compartments (biofilm or water samples) combined, to six major phyla: Proteobacteria, Bacteroidetes, Verrucomicrobia, Planctomycetes, Chloroflexi and Thaumarchaeota. Proteobacteria and Bacteroidetes represented more than 80% of the diversity with 54.52% and 26.85%, respectively. Moreover, Gamma-, Alpha-and Deltaproteobacteria were the three main classes composing the Proteobacteria phylum with 55.88%, 37.20% and 6.82%, respectively. Secondly, because the phylum taxonomic level did not distinguish among samples, we preferred the family taxonomic level. Thus, the taxonomy of water samples was assigned based on 1,291 ASVs at the family level, whereas biofilm samples were taxonomically identified from 1,009 ASVs (Table S4).

Composition across both datasets across time

Water dataset

The samples from the water dataset were separated into three compartments: the cold-water inlet (Fig. 2A), the hot-water inlet (Fig. 2B) and tank water samples (Fig. 3). The samples of the three tanks at the same sampling date for tank water were combined. No significant differences were observed between tanks at each week according to the pairwise comparisons of the diversity indices with the Kruskal-Wallis test. From April to October, bacterial compositions were obtained from 22 sampling weeks. The major phyla represented in water dataset were Proteobacteria, Bacteroidetes and Verrucomicrobia. Among them, Vibrionaceae, Rhodobacteraceae, Flavobacteriaceae and Rubritaleaceae were the most frequently observed families. The relative abundance of the bacterial families seemed more similar between cold-and hot-water inlets samples than with the tank water samples, particularly for Vibrionaceae. In fact, the relative abundance of Vibrionaceae barely reached 5% in either water inlet sample (Fig. 2A,2B), whereas it reached 50% in tank water samples, with the highest abundances for 18W, 24W and 28W (Fig. 3). Inversely, the relative abundance of Rhodobacteraceae and Flavobacteriaceae accounted for around 20% of the bacterial communities for each water inlet across time, and their abundance fluctuated more drastically in tank water samples from around 20% at week 0 to barely 10% at week 30. To a lesser extent, the SAR, Halieaceae, Desulfobulbaceae, Pirellulaceae and Cyanobiaceae families were specifically detected in samples from hot-and cold-water inlets and Colwelliaceae were mostly observed in tank water samples.

Biofilm dataset

As in the tank water samples, the biofilm samples from the three tanks at the same sampling date were combined. No significant differences were observed between tanks at each week according to the pairwise comparisons of the diversity indices using the Kruskal-Wallis test. The biofilm dataset was composed of the blank samples (three non-immersed pieces of concrete, named B0) and the samples from the tanks during 16 sampling weeks (Fig. 4). The blank B0 was mostly represented by specific phyla and families that were not identified in the other samples. The Actinobacteria, Firmicutes and Cyanobacteria phyla and the Burkholderiaceae family were only detected in the B0 samples, and no Planctomycetes were identified. At week 0, after 2 h immersion, the 0B biofilm sample already harbored more Flavobacteriaceae (20.38%), Vibrionaceae (14.84%), Rhodobacteraceae (7.02%), Colwelliaceae (2.74%) and Saprospiraceae (4.30%) than the B0 sample. These relative abundances observed were quite similar to the proportions observed in 0W, i.e. in the tank water samples from the same sampling week. Proteobacteria, Bacteroidetes and Verrucomicrobia were represented in the biofilm dataset, as in the water dataset. Results also brought to light the presence of Planctomycetes, Chloroflexi and Thaumarchaeota. Among these phyla, Flavobacteriaceae, Rhodobacteraceae, Saprospiraceae, Rubritelaceae, Pirellulaceae, Vibrionaceae, Halieaceae and Rubinisphaeraceae were the most common families observed across time in biofilm samples. Three other families, Nitrosomonadaceae (from less than 0.01% in 2B to 1.71% in 30B), Nitrosopumilaceae (from less than 0.01% in 2B to 8.14% in 30B) and Nitrospiraceae (from less than 0.01% in 2B to 1.20% in 30B) were increasingly present over time at the expense of the Flavobacteriaceae (from 37.89 % in 2B to 23.23 % in 30B). All together, the phyla, Planctomycetes, Chloroflexi and Thaumarchaeota appeared to be specific to biofilm samples and their relative abundance increased over time.

Analyses of alpha-and beta-diversity

Comparison of alpha-diversity indices

Significant differences were always observed when comparing mean values of alpha-diversity indices between datasets. The biofilm dataset had significantly the greatest diversity than the water dataset both with the richness indicator Chao1 (H=13.87, p-value < 0.001) and the richness/evenness indicator Shannon (H=70.32, p-value < 0.001).

More specifically, there were no differences in richness between the bacterial communities of tank water and biofilm samples, whereas the latter were significantly richer than samples from either water inlet (p-value < 0.001, Fig. 5A). The Chao1 values revealed that tank water samples harbored as many bacterial communities as biofilm samples, but both compartments had more bacterial communities than either water inlet. Shannon's index values were significantly different between biofilm, water inlet and tank water samples (p-value < 0.001, Fig. 5B), this latter compartment being also significantly different from cold-water inlet samples (p-value < 0.05, Fig. 5B). Hot-water inlet samples did not show differences with tank water samples or cold-water inlet samples. Shannon's index, based on richness and evenness, estimated that the microbiome was richer in biofilm samples than in other compartments, meaning that there were more bacterial communities and their presence was more evenly distributed. The bacterial communities were also richer and more evenly distributed in the tank water samples than in the cold-water inlet samples. Some significant differences were observed when comparing the mean values of Shannon's index between sampling weeks within tank water samples or biofilm samples. Concerning tank water samples (Fig. 5C, p-value < 0.05), at weeks 16, 19 and 26 (16W, 19W, 26W Fig. 3), Shannon's index values showed that the bacterial communities in tank water samples were more diverse and evenly distributed than at weeks 2 and 28 (2W, 28W, Fig. 3). Regarding the biofilm samples (Fig. 5D, pvalue < 0.05), except for week 2 (2B, Fig. 4), none of the bacterial communities were significantly different regarding their richness and evenness.

Alpha-diversity results indicated that the bacterial communities were more numerous and evenly distributed within the biofilm samples than in the tank water samples. Both communities from biofilm and tank water samples were more numerous and evenly distributed than communities from either water inlet.

Comparison of beta-diversity

We used a principal coordinate analysis (PCoA) to compare each microbiome sample with every other sample in each dataset (water and biofilm) and each compartment (hot-and cold-water inlets, tank water and biofilm). The qualitative comparison of microbiomes (Fig. 6A) based on presence or absence of considered taxa showed that two major axes explained almost 15% of the beta-diversity of all samples. Along these axes, samples from both water inlets could be grouped together, as well as biofilm samples on one end and tank water samples on the other end. The weighted UniFrac distance greatly increased the ability to discriminate samples by compartment (Fig. 6B). Moreover, the two main axes accounted for almost 50% of the variance. PERMANOVA analyses for both beta-diversity UniFrac distances tested if the hypothesis that one compartment was different from another was correct. Thus, compartments were statistically different between another by both the unweighted (R 2 = 0.14, p < 0.001) and the weighted UniFrac (R 2 =0.46, p < 0.001) distances.

The comparison between both UniFrac distances on the same data showed that the relative abundance of taxa in our samples was more compartment-discriminating than the presence/absence of different considered taxa, whereas presence/absence better dissociated the samples from each other.

Detection and identification of the Vibrionaceae family

The study of the distribution of the Vibrionaceae family was performed on sequences identified by genus within this taxonomic level. Almost 15% of all sequences were identified as Vibrionaceae, namely 2,575,816 sequences (Table S4), 90% of which (2,343,502 sequences) came from the water dataset. Six different already identified genera and two other groups defined as uncultured and unassigned were determined within the Vibrionaceae family (Table 1). Vibrio spp. (1,796,843 sequences), Photobacterium spp. (404,774 sequences), Aliivibrio spp. (328,413 sequences) and Enterovibrio spp. (29,895 sequences) were the most identified ASVs. Moreover, Shannon's index was applied to Vibrionaceae within the tank water samples (Fig. 7). Significant differences were observed for 19W and 20W samples (both in August) compared with samples from 0W to 10W (except 6W) and from 26W to 30W. During these two weeks in August, the mean temperature was 20.5°C (+/-0.19°C) and pH ranged from 7.24 to 7.40 (Table S1).

Discussion

Here, we conducted a seasonal survey in the North of France, from April to October 2018 in a seabass farm that undergoes repeated summer outbreaks of vibriosis. Although no acute vibriosis outbreak occurred during this survey, the characterization of the microbiomes from the marine aquaculture environment was of paramount importance to evaluate and monitor the bacterial communities and their potential interactions over time. Specifically, the characterization of the Vibrionaceae population dynamics in the various aquaculture compartments shed light on which compartments (water inlets, water tank and biofilm) may be a source or a reservoir of Vibrionaceae. Using Illumina MiSeq technology targeting the V4-V5 variable region of the 16S rRNA gene, we detected and identified the bacterial communities through a weekly sampling campaign. The presence of Vibrionaceae was ubiquitous and detected in all samples (Table 1). Despite a common microbiome shared between all samples, alpha-diversity indices were significantly different between sample compartments (Fig. 5A,5B).

Common microbiome composition

A common microbiome was detected in samples from all compartments. This commonality is likely due to the source of the water used to supply the tanks in water and in which the pieces of concrete were immersed. Taking all the results together, the Proteobacteria (54.52 %) and Bacteroidetes (26.85 %) phyla formed the main components of the microbiomes from the water and biofilm compartments (Fig. 1). These phyla have already been detected in a seabass farm [START_REF] Duarte | Bacterial and microeukaryotic plankton communities in a semi-intensive aquaculture system of sea bass (Dicentrarchus labrax): A seasonal survey[END_REF] and were also predominant in the seabass skin microbiome [START_REF] Chiarello | High diversity of skin-associated bacterial communities of marine fishes is promoted by their high variability among body parts, individuals and species[END_REF][START_REF] Pimentel | Bacterial communities 16S rDNA fingerprinting as a potential tracing tool for cultured seabass Dicentrarchus labrax[END_REF][START_REF] Rosado | Characterization of the skin and gill microbiomes of the farmed seabass (Dicentrarchus labrax) and seabream (Sparus aurata)[END_REF]. Moreover, Gamma-, Alphaproteobacteria and Bacteroides appear to be the first classes to form a biofilm in a RAS [START_REF] Wietz | Effects of seawater ozonation on biofilm development in aquaculture tanks[END_REF].

A core microbiome analysis (data not shown) revealed that Vibrionaceae (Vibrio genus, Table 1), Rhodobacteraceae (with the Loklanella, Sulfitobacter, Planktotalea genera), Rhizobiaceae, Flavobacteriaceae and Saprospiraceae were the families (belonging to the Proteobacteria and Bacteroidetes phyla) shared among all samples. These results were also consistent with those of [START_REF] Wang | Intestinal microbiota of healthy and unhealthy Atlantic salmon Salmo salar L. in a recirculating aquaculture system[END_REF], who found that genera from the Saprospiraceae, Flavobacteriaceae and Rhodobacteraceae families were shared between RAS tank water and the RAS biofilter. Moreover, Flavobacteriaceae and Rhodobacteraceae have also been reported in association with zooplankton, notably because of their respective capacities to participate in the carbon cycle by degrading highmolecular-weight organic matter, and to contribute to biofilm formation [START_REF] De Corte | Metagenomic insights into zooplankton-associated bacterial communities[END_REF].

Overall microbiota differences between sampling compartments

The alpha-and beta-diversity indices used in this study (Chao1, Shannon, unweighted and weighted UniFrac distances) highlighted differences in the bacterial composition between the compartments and between samples within each compartment (Fig. 5, Fig. 6). The biofilm samples and tank water samples harbored the most diverse bacterial populations compared with the water inlet samples (Fig. 5A,5B). These observations could be partly explained by the presence of seabass in the tanks. The Colwelliaceae family was more abundant in the tank water samples than in the water inlet samples (Fig. 2, Fig. 3). [START_REF] Pimentel | Bacterial communities 16S rDNA fingerprinting as a potential tracing tool for cultured seabass Dicentrarchus labrax[END_REF] highlighted that the accumulation of uneaten feed in the tank generate anoxic areas, where the genus Colwellia could be found and contribute to anaerobic processes. Otherwise, previous studies have shown that biofilm communities are distinct from other microbial communities, for example in raw water [START_REF] Luo | Microbial community structures in a closed raw water distribution system biofilm as revealed by 454-pyrosequencing analysis and the effect of microbial biofilm communities on raw water quality[END_REF]. The increasing presence of the Nitrosomonadaceae, Nitrospiraceae and Nitrosopumilaceae families appeared to be specific to the biofilm samples (Fig. 4). In fact, these three families are involved in nitrification processes and are known as ammonium-oxidizing bacteria and ammonium-oxidizing archaea [START_REF] Rurangwa | Microorganisms in recirculating aquaculture systems and their management[END_REF]. [START_REF] Luo | Microbial community structures in a closed raw water distribution system biofilm as revealed by 454-pyrosequencing analysis and the effect of microbial biofilm communities on raw water quality[END_REF] revealed that the presence of Firmicutes and Nitrospiraes spp. in microbial biofilms improves the quality of the raw water by dissolving oxygen and modifying nitrogen levels.

Planctomycetes, such as Pirellulaceae (Fig. 4), also participate in ammonium oxidation in anaerobic conditions [START_REF] Schreier | Microbial diversity of biological filters in recirculating aquaculture systems[END_REF]. The presence of these bacterial populations in a biofilm is crucial because they oxidize ammonia and nitrite into less toxic compounds, such as nitrates [START_REF] Rurangwa | Microorganisms in recirculating aquaculture systems and their management[END_REF]. Moreover, our results showed that bacterial populations composing biofilm established between the 2 hours immersion and the second sampling week. Bacterial communities on the non-immersed blank disappeared after just 2 h of immersion, as manifested by the Actinobacteria, Cyanobacteria and Firmicutes families. Firmicutes have been found in bacterial communities from RAS biofilters or in biofilms in raw water distribution systems [START_REF] Luo | Microbial community structures in a closed raw water distribution system biofilm as revealed by 454-pyrosequencing analysis and the effect of microbial biofilm communities on raw water quality[END_REF][START_REF] Schreier | Microbial diversity of biological filters in recirculating aquaculture systems[END_REF]. These families have often been observed in various inhabited areas, such as utensils or on stones [START_REF] Ng | Microorganisms meet solid minerals: interactions and biotechnological applications[END_REF]. The populations unique to biofilms changed rapidly, despite the presence and constancy of families common to all compartments. Our results showed that Planctomycetes, Chloroflexi and Thaumarchaeota phyla as being specific to biofilm samples.

During this seasonal campaign, the cold-water inlet underwent the most temperature changes (from 9.08°C to 21.1°C), due to warmer waters in the summer, but no major differences in bacterial communities were observed in this compartment. The water temperature in the tanks was maintained approximately constant by mixing in variable proportions the hot-and cold-water inlets (from 17.97°C to 21.17°C). Nevertheless, the bacterial communities did not change with the slightly higher temperatures during summer (Fig. 5C,5D). Moreover, a Spearman correlation test was performed between all physical parameters (temperature, pH, oxygen, salinity and conductivity) measured in the tanks, the diversity indicators (Chao1 and Shannon from tank water and biofilm samples) and the relative abundance of Vibrionaceae (from the tank water and biofilm samples). No significant association was revealed between evenness and richness variations from the tank water and biofilm samples and temperature, oxygen, salinity or conductivity considered independently. A negative correlation was revealed only between pH and both diversity indicators in biofilm samples. Bacterial communities of biofilm samples appeared more diverse when the pH was lower. The pH variation ranged from 6.35 to 7.97 during the sampling campaign (Table S1). The pH decrease may be linked to the nitrification process occurring in biofilm samples. Finally, the relative abundance of Vibrionaceae from water tank samples correlated negatively with pH and oxygen levels in the tanks, whereas the relative abundance of Vibrionaceae from biofilm samples correlated positively with the temperature in the tanks. Then the temperature rising seemed promote Vibrionaceae proliferation in biofilm samples and their role as reservoir in case of dysbiosis.

Potential pathogens detected

We then focused on the Vibrionaceae family in tank water samples, because this compartment contained more Vibrionaceae than the other compartments. Our results suggested that biofilms may be a reservoir of Vibrionaceae, and tank water seemed amenable to its proliferation. A lower Shannon index was indeed obtained (18W, 24W and 28W, Fig. 5C) when the Vibrionaceae were most abundant (18W, 24W and 28W, Fig. 3). The balance between bacterial communities was thus disturbed, because one bacterial population had proliferated in particular. Among the Vibrionaceae family, four genera were frequent, in order of importance: Vibrio, Photobacterium, Aliivibrio and Enterovibrio. More precisely, the species level determination identified Vibrio ponticus, Vibrio aestivus, Vibrio sinaloensis and Vibrio anguillarum, as well as Photobacterium damselae subsp. damselae, Photobacterium swingsii, Photobacterium gaetbulicola Gung47, Photobacterium rosenbergii, and Photobacterium damselae subsp. piscicida, and Aliivibrio fischeri and Enterovibrio nigricans (Table 1). Most pathogenic Vibrio species, such as Vibrio harveyi or Vibrio vulnificus, were not identified, although we expected to find V. harveyi since it has already been identified as major pathogens in this aquaculture infrastructure [START_REF] Mougin | Development of a mreB-targeted real-time PCR method for the quantitative detection of Vibrio harveyi in seawater and biofilm from aquaculture systems[END_REF]. The Vibrionaceae population more than doubled during the sampling campaign (20% at 0W and 50% at 28W, Fig. 3). The peaks of diversity were reached at weeks 19 and 20 (during August), suggesting that all genera were present and in stable proportions (Fig. 7). Despite this variation, the equilibrium between genera remained relatively stable throughout the sampling weeks.

Our results revealed that the water from the tanks contained Vibrionaceae and may be sufficiently rich in bacteria to harbor pathogens and their antagonistic members. Some studies have indeed reported that Roseobacter spp. (family Rhodobacteraceae) may establish antagonistic activity against Vibrionaceae and particularly against V. anguillarum [START_REF] Balcázar | Phylogenetic characterization and in situ detection of bacterial communities associated with seahorses (Hippocampus guttulatus) in captivity[END_REF][START_REF] Hjelm | Seasonal Incidence of Autochthonous Antagonistic Roseobacter spp. and Vibrionaceae Strains in a Turbot Larva (Scophthalmus maximus) Rearing System[END_REF]).

Among the Flavobacteriaceae, Polaribacter is an opportunist common fish farm bacteria colonizing an already weakened fish and has already been detected in the core microbiome of seabass and seabream [START_REF] Rosado | Characterization of the skin and gill microbiomes of the farmed seabass (Dicentrarchus labrax) and seabream (Sparus aurata)[END_REF]. Our results showed that increases in Rhodobacteraceae and Flavobacteriaceae were associated with decreases in Vibrionaceae. The absence of acute vibriosis outbreaks during the campaign suggests that there is an equilibrium between pathogenic Vibrionaceae and the other antagonistic bacterial communities. It would be relevant to study the putative antagonistic activity between sampled Vibrionaceae, Rhodobacteraceae and Flavobacteriaceae. Simultaneously, identification and detection of biofilm microbiomes now makes it possible to investigate the capacity of horizontal gene transfer of the different species and to investigate antibiotic resistance. Despite the presence of potential pathogens, there were no disease outbreaks; therefore, the vaccination campaign appears to have worked. In the present study, no sampling was carried out directly on fish firstly for ethical reasons and secondly because the main objective was to consider the aquaculture compartments. Nevertheless, future studies should compare our results with fish microbiomes to confirm the efficiency of vaccination. Finally, our results demonstrated the importance of simultaneously studying all bacterial communities.

Conclusion

In conclusion, this is the first study to compare bacterial communities from several water compartments and from biofilms in an aquaculture farm over time with a seven-month weekly sampling campaign. Proteobacteria and Bacteroidetes, which are common phyla in water ecosystems, were abundant. The diversity of bacterial communities differed within compartments, although there were no significant correlations with water quality parameters. Biofilm samples contained higher bacterial diversity than water samples and tank water samples were richer than samples from water inlets. The proportion of Vibrionaceae was high in tank water samples. All six genera composing the Vibrionaceae family were identified. The natural environment seemed to be a source of Vibrionaceae, which found a favorable environment to develop and then persist in biofilms in the aquaculture system. In the future, we plan to investigate the antagonistic effects between Vibrionaceae and other already present bacteria to design solutions such as probiotics use to monitor bacterial populations and promote sustainable aquaculture. Moreover, the aquaculture environment can be monitored using a metatranscriptomic analysis. The bacterial populations detected can be linked to the primary and secondary metabolic functions observed, such as virulence. Unassigned families or those that did not reach a minimum of 1% in at least one sample were grouped in the "Others" category.

Figure 1 :

 1 Figure 1: The six most abundant phyla (from all samples, over all sampling times), representing 94.38% of all sequences. The number above each bar indicates the percentage of each phylum. The percentage of each class of Proteobacteria is shown in the blue donut chart.

Figure 2 :

 2 Figure2: Bar plots of relative abundance (%) of bacterial families throughout the 30 sampling weeks composing A) the cold-water inlet samples, B) the hot-water inlet samples. Bacterial families are grouped by phylum with the second color scale on the top. Families unassigned or that did not reach a minimum of 3% in at least one sample were grouped in the "Others" category.

Figure 3 :

 3 Figure3: Bar plots of relative abundance (%) of bacterial families composing the tank water samples throughout the 30 sampling weeks. Bacterial families are grouped by phylum with the second color scale on the top. Families unassigned or that did not reach a minimum of 3% in at least one sample were grouped in the "Others" category.

Figure 4 :

 4 Figure 4: Bar plots of relative abundance (%) of bacterial families across biofilm samples across sampling weeks. Bacterial families are grouped by phylum and by family (color scale on the right).

Figure 5 :

 5 Figure 5: Mean values and standard deviations of Chao1 (A) and Shannon (B, C, D) alpha-diversity indices plotted by compartment (A, B) or by sampling week for tank water samples (C) and for biofilm samples (D). All purple and gray box plots respectively represent tank water samples and biofilm samples from the three breeding tanks. Blue and red box plots correspond to cold-and hotwater inlet samples, respectively. Kruskal-Wallis tests for pairwise comparisons were carried out and different letters indicate significant differences.

Figure 6 :

 6 Figure 6: Beta-diversity of the 159 samples. (A) Unweighted UniFrac and (B) weighted UniFrac distances were analyzed and plotted using principal coordinates analysis (PCoA). Each point represents a microbiome sample (composed of 29,725 sequences corresponding to the rarefaction depth). Rings and stars distinguish the water dataset from the biofilm dataset, respectively. Blue and red colors correspond to cold-and hot-water inlet samples, respectively, whereas the three shades of purple indicate the water or biofilm samples from the three breeding tanks. The brown star indicates the B0 sample.

Figure 7 :

 7 Figure 7: Mean values and standard deviations of Shannon alpha-diversity index of the Vibrionaceae family, plotted by sampling week for tank water samples. Kruskal-Wallis tests for pairwise comparisons were carried out and different letters indicate significant differences.

Table 1 :

 1 Number of sequences identified, using the SILVA 132 database, in the Vibrionaceae family and number of samples

	Taxonomy of Vibrionaceae detected

Acknowledgements

Authors wish to thank Aquanord-Ichtus as a contributor to this project, especially Guillaume Tielie, Anabelle Duhamel and Céline Doyen. Authors want to thank Dominique Hervio-Heath for her advice on sequencing targets. We would also like to thank the Hauts-de-France Regional Council and ULCO (PhD funding for Julia Mougin); and the CPER 2014-2020 MARCO project (post-doctoral funding for Roxane Roquigny).

Funding

This work was supported by the French government, IFREMER and the Hauts-de-France Regional Council as part of the CPER 2018-2019 MARCO project.

This work was also supported by the Hauts-de-France Regional Council and ULCO, which provided funding for Julia Mougin's PhD studies.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Sandrine Petry
email: sandrine.petry@anses.fr

Corinne Sévin

Sofia Kozak

Nathalie Foucher

Claire Laugier

Maud Linster

Marie-France Breuil

Marie-Capucine Dupuis

Aymeric Hans

Fabien Duquesne

Jackie Tapprest

Relationship between rifampicin resistance and RpoB substitutions of Rhodococcus equi strains isolated in France

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

Rhodococcus equi is a soil-dwelling and facultative intracellular bacterium that causes severe to fatal pulmonary and extrapulmonary pyrogranulomatous infections in animals and humans [START_REF] Prescott | Rhodococcus equi: an animal and human pathogen[END_REF][START_REF] Vázquez-Boland | Rhodococcus equi: the many facets of a pathogenic actinomycete[END_REF]. While affecting a variety of animal species, R. equi is a major pathogen in the horsebreeding industry, R. equi infections being endemic on many stud farms worldwide [START_REF] Von Bargen | Molecular and infection biology of the horse pathogen Rhodococcus equi[END_REF]. The virulence of equine R. equi strains is related to the presence of host-associated plasmid pVAPA [START_REF] Letek | Evolution of the Rhodococcus equi vap pathogenicity island seen through comparison of host-associated vapA and vapB virulence plasmids[END_REF][START_REF] Macarthur | Comparative genomics of Rhodococcus equi virulence plasmids indicates host-driven evolution of the vap pathogenicity island[END_REF][START_REF] Ocampo-Sosa | Molecular epidemiology of Rhodococcus equi based on traA, vapA, and vapB virulence plasmid markers[END_REF][START_REF] Takai | Association between a large plasmid and 15-to 17-Kilodalton antigens in virulent Rhodococcus equi[END_REF]. Together with porcine pVAPB and ruminant pVAPN, equine pVAPA plasmids can be found in R. equi strains isolated from humans (4-6,8), consistent therefore with a zoonotic source of infection [START_REF] Vázquez-Boland | The pathogenic actinobacterium Rhodococcus equi: what's in a name?[END_REF]. Following its introduction in 1967, rifampicin has become a mainstay therapy in the treatment of various diseases, including tuberculosis, methicillin-resistant Staphylococcus aureus infections and Neisseria meningitidis infections [START_REF] Alifano | Rifampicin-resistance, rpoB polymorphism and RNA polymerase genetic engineering[END_REF]. It is furthermore recommended as an alternative treatment for infections caused by tick-borne pathogens Borrelia burgdorferi and Anaplasma phagocytophilum [START_REF] Alifano | Rifampicin-resistance, rpoB polymorphism and RNA polymerase genetic engineering[END_REF], and is also part of the multi-drug therapy used to treat leprosy [START_REF] Maymone | Leprosy: treatment and management of complications[END_REF]. Since the 1980s, rifampicin has been used in combination with a macrolide such as erythromycin or, more recently, azithromycin or clarithromycin, as the standard recommended treatment for foals infected with R. equi [START_REF] Giguère | Treatment of infections caused by Rhodococcus equi[END_REF][START_REF] Hillidge | Use of erythromycin-rifampin combination in treatment of Rhodococcus equi pneumonia[END_REF][START_REF] Sweeney | Rhodococcus equi pneumonia in 48 foals: response to antimicrobial therapy[END_REF]. The rifampicin-macrolide combination has reduced foal mortality but has also led to the emergence of R. equi resistance. The first observations of rifampicin resistance [START_REF] Fines | Characterization of mutations in the rpoB gene associated with rifampin resistance in Rhodococcus equi isolated from foals[END_REF][START_REF] Kenney | Development of reactive arthritis and resistance to erythromycin and rifampin in a foal during treatment for Rhodococcus equi pneumonia[END_REF][START_REF] Takai | Emergence of rifampin-resistant Rhodococcus equi in an infected foal[END_REF] and a progressive development of resistance to both rifampicin and erythromycin [START_REF] Kenney | Development of reactive arthritis and resistance to erythromycin and rifampin in a foal during treatment for Rhodococcus equi pneumonia[END_REF] were reported in the 1990s. An alarming situation has recently been observed in Kentucky, USA [START_REF] Burton | Macrolide-and rifampin-resistant Rhodococcus equi on a horse breeding farm, Kentucky, USA[END_REF][START_REF] Giguère | Determination of the prevalence of antimicrobial resistance to macrolide antimicrobials or rifampin in Rhodococcus equi isolates and treatment outcome in foals infected with antimicrobial-resistant isolates of R equi[END_REF][START_REF] Giguère | Antimicrobial Resistance in Rhodococcus equi[END_REF][START_REF] Huber | Prevalence and risk factors associated with emergence of Rhodococcus equi resistance to macrolides and rifampicin in horse-breeding farms in Kentucky, USA[END_REF][START_REF] Huber | Emergence of Resistance to Macrolides and Rifampin in Clinical Isolates of Rhodococcus equi from Foals in Central Kentucky, 1995 to 2017[END_REF], where rifampicin and erythromycin resistance has increased by 13.8% and 12.9% respectively between the 1995-2006 and 2007-2017 periods [START_REF] Huber | Emergence of Resistance to Macrolides and Rifampin in Clinical Isolates of Rhodococcus equi from Foals in Central Kentucky, 1995 to 2017[END_REF] due to a specific R. equi clone that carries a chromosomal mutation and a mobile element conferring this dual resistance to respectively, rifampicin and macrolides [START_REF] Álvarez-Narváez | Clonal Confinement of a Highly Mobile Resistance Element Driven by Combination Therapy in Rhodococcus equi[END_REF].

The primary mechanism of resistance to rifampicin consists from substitutions that alter residues of the rifampicin-binding pocket on the β-subunit of the RNA polymerase (RpoB), resulting in a decreased affinity for rifampicin. Substitutions that confer rifampicin resistance are typically located in three distinct clusters, I to III, of RpoB and in particular at three sites located in cluster I: Asp516, His526, and Ser531 (Escherichia coli numbering) [START_REF] Alifano | Rifampicin-resistance, rpoB polymorphism and RNA polymerase genetic engineering[END_REF][START_REF] Jin | Mapping and sequencing of mutations I the Escherichia coli rpoB gene that lead to rifampicin resistance[END_REF]. For R. equi, at least 15 different substitutions at five sites in cluster I -Ser509, Gln513, Asp516, His526, and Ser531 -have been reported [START_REF] Fines | Characterization of mutations in the rpoB gene associated with rifampin resistance in Rhodococcus equi isolated from foals[END_REF][START_REF] Álvarez-Narváez | Clonal Confinement of a Highly Mobile Resistance Element Driven by Combination Therapy in Rhodococcus equi[END_REF][START_REF] Asoh | Emergence of rifampin-resistant Rhodococcus equi with several types of mutations in the rpoB gene among AIDS patients in northern Thailand[END_REF][START_REF] Boyen | Acquired antimicrobial resistance in equine Rhodococcus equi isolates[END_REF][START_REF] Liu | Appearance of multidrug-resistant virulent Rhodococcus equi clinical isolates obtained in China[END_REF][START_REF] Riesenberg | MICs of 32 antimicrobial agents for Rhodococcus equi isolates of animal origin[END_REF][START_REF] Huber | The novel and transferable erm (51) gene confers macrolides, lincosamides and streptogramins B (MLSB) resistance to clonal Rhodococcus equi in the environment[END_REF]. Substitutions at His526 and Ser531 confer the highest levels of rifampicin resistance [START_REF] Giguère | Antimicrobial Resistance in Rhodococcus equi[END_REF].

Apart from two French reports on the rifampicin resistance of equine R. equi strains [START_REF] Fines | Characterization of mutations in the rpoB gene associated with rifampin resistance in Rhodococcus equi isolated from foals[END_REF][START_REF] Duchesne | In vitro antimicrobial susceptibility of equine clinical isolates from France, 2006-2016[END_REF], very few data are available in France, a major European horse-breeding country.

Nevertheless, according to Duchesne's study [START_REF] Duchesne | In vitro antimicrobial susceptibility of equine clinical isolates from France, 2006-2016[END_REF], which found that only 1.7% of the R. equi strains isolated from 2006 to 2016 were rifampicin-resistant, the French situation could be much less alarming than in Kentucky, USA. In this context, our objective was to study the rifampicin resistance of R. equi strains isolated from infected horses over a 20-year period (1998 to 2018) in order to determine the relationship between the rifampicin susceptibility tested using the disc diffusion (DD) and broth macrodilution (BMD) methods, rpoB gene sequencing and multilocus sequence typing (MLST).

Materials and methods

Bacterial strains, culture media and growth conditions

From 1995 to 2018, 1949 R. equi strains were isolated during bacteriological analyses performed at the ANSES Laboratory for Animal Health in Normandy on samples collected during equine necropsies or epidemiological surveys on stud farms. Among these strains, 20 were non-susceptible to rifampicin and none to erythromycin. Forty R. equi strains from the ANSES collection were used in this study, including the 20 strains non-susceptible to rifampicin. The strains susceptible to rifampicin were not randomly selected but to reflect the diversity of the collection (Table 1). The 40 strains studied were maintained using cryobeads (AES or BioMérieux) at -80°C. They were confirmed as R. equi by their colony morphology on Columbia CNA agar with 5% sheep blood (BioMérieux) and by PCRs to detect the presence of the plasmid vapA gene [START_REF] Makrai | Characterization of Virulence Plasmids and Serotyping of Rhodococcus equi Isolates from Submaxillary Lymph Nodes of Pigs in Hungary[END_REF] and the chromosomal choE gene [START_REF] Ladrón | Rapid identification of Rhodococcus equi by a PCR assay targeting the choE gene[END_REF][START_REF] Duquesne | Development of a multilocus sequence typing scheme for Rhodococcus equi[END_REF]. If the vapA PCR result proves negative, plasmid-positive and plasmid-negative strains are distinguished after a PCR targeting the traA gene coding a protein of the conserved conjugal transfer machinery of Rhodococcus species plasmids [START_REF] Ocampo-Sosa | Molecular epidemiology of Rhodococcus equi based on traA, vapA, and vapB virulence plasmid markers[END_REF]. R. equi ATCC 33701 was used as a rifampicin-susceptible reference strain.

In vitro antibiotic susceptibility testing

Antibiotic susceptibility was determined using the standard DD method on Mueller-Hinton agar supplemented with 5% lysed horse blood (Oxoid) and 20 µg/ml β-nicotinamide adenine dinucleotide (β-NAD) (ThermoFisher Scientific) according to the 2019 Antibiogram Committee of the French Society for Microbiology (CASFM) guideline [START_REF]Comité de l'Antibiogramme de la Société Française de Microbiologie[END_REF]. Discs (Oxoid) containing 5 µg oxacillin, 500 µg gentamicin, 500 µg streptomycin, [START_REF] Fines | Characterization of mutations in the rpoB gene associated with rifampin resistance in Rhodococcus equi isolated from foals[END_REF] 1. In this study, intermediate and resistant strains were grouped together in the non-susceptible strain population so as to indicate that they were no longer wild-type strains.

Rifampicin MICs were determined using the BMD method with a Mueller-Hinton broth supplemented with 5% lysed horse blood (Oxoid) and 20 µg/ml β-NAD (ThermoFisher Scientific) according to the 2019 CASFM guideline for slow-growing bacteria including Streptococcus spp. and Corynebacterium spp. [START_REF]Comité de l'Antibiogramme de la Société Française de Microbiologie[END_REF]. The protocol was performed as previously described [START_REF] Courvalin | Antibiogramme. Détermination des concentrations minimales inhibitrices et bactericides en milieu liquide[END_REF]. Results were recorded as the lowest concentrations of rifampicin that inhibited visible growth of R. equi.

DNA extraction

The NucleoSpin ® Tissue kit (Macherey-Nagel) was used for DNA extraction according to the manufacturer's instructions for hard-to-lyse bacteria in the support protocol for bacteria.

rpoB sequencing

The 827-bp rpoB partial gene was amplified and sequenced as previously described [START_REF] Riesenberg | MICs of 32 antimicrobial agents for Rhodococcus equi isolates of animal origin[END_REF]. The rpoB gene fragment studied comprises the three distinct clusters I, II, and III identified by Jin and Gross [START_REF] Jin | Mapping and sequencing of mutations I the Escherichia coli rpoB gene that lead to rifampicin resistance[END_REF] in E. coli where amino acid substitutions leading to rifampicin resistance were typically located; this was different from the fragment studied by MLST. The RpoB amino acid sequences from amino acids 477 to 705 (E. coli numbering) were deduced and compared to the RpoB amino acid sequence of the rifampicin-susceptible R. equi 103S (GenBank accession no. CBH49657) used as a wild-type reference. The RpoB amino acid sequences of the 40 R. equi strains studied can be found under GenBank accession nos. MT363641 to MT363680.

MLST and phylogenetic tree

The seven housekeeping genes (gapdh, tpi, mdh, icl, rpoB, recA, and adk) were amplified and sequenced as previously described [START_REF] Duquesne | Development of a multilocus sequence typing scheme for Rhodococcus equi[END_REF]. The Rhodococcus MLST website (https://pubmlst.org/rhodococcus/) sited at the University of Oxford [START_REF] Jolley | Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications[END_REF] was used to assign the allele numbers and the sequence types (STs) after having previously trimmed to equivalent lengths all the sequences of each individual MLST locus like on the Rhodococcus MLST website. For each unique ST, sequences of the seven MLST loci were concatenated, giving a 4017-bp in-frame sequence. Concatenated sequences were aligned and a phylogenetic tree drawn up using the MEGA software version 7.0 (39) via the maximum likelihood method based on the Tamura-Nei model. Support for internal nodes was estimated using the nonparametric bootstrap method with 1000 replications. The tree was rooted with the ST06-concatenated sequences of the Rhodococcus sp. MBE 538 strain as the outgroup, extracted from the Rhodococcus MLST website.

Results

The 40 R. equi strains studied were from 27 horses, with one strain per animal except for horses no. 11 (three strains) and no. 25 (12 strains) (Table 1). They were confirmed as R. equi by PCR (positive choE PCR results) and the equine pVAPA plasmid was detected by PCR in 38 of them (positive traA and vapA PCR results). The two plasmidless strains (negative traA and vapA PCR results) were both isolated in 1998, strain #39 from the lung of animal no. 25, and strain #40 from the faeces of the same animal two days before its death and necropsy; interestingly, 11 pVAPA strains (#27 to #37) (Table 1) were isolated from different organs of this same animal (no. 25).

General susceptibility study

The susceptibility of the 40 strains to 11 antibiotics was determined by DD (Table 2). All 40 were susceptible to gentamicin, streptomycin, erythromycin, azithromycin, clarithromycin, and enrofloxacin but non-susceptible to lincomycin and oxacillin, except one strain susceptible to lincomycin. About half of the strains were also non-susceptible to spiramycin (45.0%), rifampicin (50.0%) and trimethoprim-sulfamethoxazole (57.5%). A focus on rifampicin susceptibility determined by DD and BMD is presented in Table 1. The 20 strains classified by DD as susceptible to rifampicin (inhibition zone diameters of 30-36 mm) had MICs ≤ 4 µg/ml, while the 20 strains classified by DD as non-susceptible to rifampicin (inhibition zone diameters of 7-24 mm) had MICs ≥ 8 µg/ml. The strains that were not susceptible to rifampicin were isolated between 1998 and 2018 from nine equids of widely varying breed, sex, age, and sample source.

RpoB sequence analysis

RpoB amino acid sequences encompassing positions 477 to 705 (E. coli numbering) were obtained for the 40 strains and the R. equi ATCC 33701. Fourteen different RpoB amino acid sequences, designated RpoB profiles I to XIV, were observed, including the wild-type RpoB (GenBank accession no. CBH49657) (39) of the rifampicin-susceptible R. equi 103S (Table 1 and Fig. 2). RpoB profile I corresponded to the wild-type sequence. It was found in ten strains with MICs of 0.5 to 1 µg/ml and characterised by DD as susceptible to rifampicin, and in the rifampicin-susceptible R. equi ATCC 33701. RpoB profiles II to XIV differed from the wildtype sequence by the presence of one to five substitutions per profile, for a total of nine different substitutions at five sites in cluster I (Thr508Ala, Asp516Val, Asp516Tyr, His526Asn, His526Asp, and Ser531Leu) and three sites outside clusters I, II, and III (Thr491Ser, Tyr653Asn, and Asn678His) (Fig. 2). RpoB profiles II to VIII were found in ten strains with MICs of 0.5 to 4 µg/ml and characterised by DD as susceptible to rifampicin, while RpoB profiles IX to XIV were found in 20 strains with MICs of 8 to 1024 µg/ml and characterised by DD as non-susceptible to rifampicin (Table 1 and Fig. 2).

The comparative analysis of in vitro rifampicin susceptibility testing and RpoB substitutions shows that: (i) substitutions outside clusters I to III and the Thr508Ala substitution in cluster I do not appear to confer rifampicin resistance because they were found in both strains that are susceptible and strains that are not susceptible to rifampicin by DD and with MICs of 0.5 to 512 µg/ml. They were observed in a single substitution for six strains found by DD to be susceptible to rifampicin with MICs ≤ 2 µg/ml or in RpoB profiles with multiple substitutions; (ii) the Asp516Tyr (MIC, 8 µg/ml), Ser531Leu (MIC, 16-256 µg/ml), and His526Asp (MIC, 512-1024 µg/ml) substitutions appear to confer rifampicin resistance because they were found by DD only in strains non-susceptible to rifampicin with MICs ≥ 8 µg/ml, as a single substitution or in RpoB profiles with multiple substitutions not appearing to confer rifampicin resistance; (iii) the His526Asn substitution was observed in a single substitution (RpoB profile VIII) in strain #34, which was found by DD to be susceptible to rifampicin but with a MIC of 4 µg/ml suggesting it might actually be considered as having some degree of resistance; (iv) the Asp516Val substitution was observed together with multiple other substitutions apparently unrelated to rifampicin resistance (RpoB profile VIII) in strain #35, found by DD to be susceptible to rifampicin with a MIC of 1 µg/ml (Fig. 2 and Fig. 3).

MLST analysis

MLST analysis was used to investigate a possible association between RpoB profiles and STs.

The 40 strains and the R. equi ATCC 33701 were divided into nine existing STs and ST43 representing a novel ST in the Rhodococcus MLST website. ST24 (n = 19), ST1 (n = 5), ST19

(n = 5), and ST16 (n = 4) were the most prevalent STs; ST19 and ST24 may nevertheless be artificially enlarged by the presence of several strains isolated from a single animal, since in all cases, only one ST was found per animal (Table 1). The ST distribution in the phylogenetic tree showed two distinct phylogenetic clusters: one (ST7 and ST10) with both strains from Mayotte (a French overseas island in the Indian Ocean), and one with the R. equi ATCC 33701 from Ontario (Canada) and the 38 strains from metropolitan France (Fig. 1). No association was observed between RpoB profiles and dominant ST1, ST19, and ST24, or even the Mayotte and Normandy clusters. It is noteworthy that ST16 was found only in strains found by DD to be susceptible to rifampicin with wild-type RpoB profile I or RpoB profile VI in which case the Thr491Ser substitution did not appear to confer rifampicin resistance.

Several strains isolated from a single animal could be considered to represent a single clone when pVAPA, MLST, rifampicin susceptibility and RpoB sequencing results were identical. Thus, two clones were characterised among the three strains from animal no. 11, strains #19 and #21 giving the same results; likewise, six clones were characterised among the 12 strains from animal no. 25, strains #27, #28, #30, #31, #32, and #37 giving the same results (Fig. 2).

Discussion

This study reports the presence of nine French cases of rifampicin resistance in horses infected by R. equi between 1998 and 2018. The 20 R. equi strains recovered from these cases and found to exhibit resistance to rifampicin correspond to 1% of the R. equi ANSES collection built up between 1995 and 2018 from equine samples collected during necropsies or environmental samples from stud farms. These strains were all susceptible to macrolides. This report is in accordance with a recent French study [START_REF] Duchesne | In vitro antimicrobial susceptibility of equine clinical isolates from France, 2006-2016[END_REF] which revealed that 1.7% of the R. equi strains isolated between 2006 and 2016 were rifampicin-resistant, and 1.7% erythromycin-resistant according to the data presented. Thus, the French situation appears to differ from that in Kentucky, USA, where rifampicin and macrolide resistance has considerably increased over the past two decades [START_REF] Giguère | Determination of the prevalence of antimicrobial resistance to macrolide antimicrobials or rifampin in Rhodococcus equi isolates and treatment outcome in foals infected with antimicrobial-resistant isolates of R equi[END_REF][START_REF] Giguère | Antimicrobial Resistance in Rhodococcus equi[END_REF][START_REF] Huber | Prevalence and risk factors associated with emergence of Rhodococcus equi resistance to macrolides and rifampicin in horse-breeding farms in Kentucky, USA[END_REF][START_REF] Huber | Emergence of Resistance to Macrolides and Rifampin in Clinical Isolates of Rhodococcus equi from Foals in Central Kentucky, 1995 to 2017[END_REF][START_REF] Burton | Macrolide-and rifampin-resistant Rhodococcus equi on a horse breeding farm, Kentucky, USA[END_REF], and is associated with both the density of animals and the number of animals treated with antimicrobials [START_REF] Huber | Prevalence and risk factors associated with emergence of Rhodococcus equi resistance to macrolides and rifampicin in horse-breeding farms in Kentucky, USA[END_REF]. Whatever the case, as rifampicin is a mainstay of treatment for various human diseases [START_REF] Alifano | Rifampicin-resistance, rpoB polymorphism and RNA polymerase genetic engineering[END_REF], the isolation of an equine rifampicin-resistant R. equi strain must be managed in order to avoid zoonotic transmission.

As no clinical breakpoints are available for application of DD and BMD methods to R. equi, rifampicin inhibition zone diameters were interpreted in keeping with Staphylococcus spp. and Streptococcus spp. breakpoints approved by the 2013 CASFM guideline (35) and rifampicin MICs were compared to DD and rpoB sequencing results. The interpretative results of inhibition zone diameters and MICs are consistent with each other, the 20 strains found by DD to be non-susceptible to rifampicin all having MICs with higher values than the 20 strains found by DD to be susceptible to rifampicin. The consistency of results was also observed between rifampicin susceptibility testing and rpoB sequencing. All the strains found by DD to be non-susceptible to rifampicin systematically had a substitution at one of the three sites -Asp516, His526, and Ser531 -in cluster I that are frequently encountered and confer rifampicin resistance [START_REF] Alifano | Rifampicin-resistance, rpoB polymorphism and RNA polymerase genetic engineering[END_REF][START_REF] Jin | Mapping and sequencing of mutations I the Escherichia coli rpoB gene that lead to rifampicin resistance[END_REF]. However, 20% of these strains also showed one to four additional substitutions (outside clusters I to III and Thr508Ala in cluster I) apparently not involved in rifampicin resistance. The clinical significance of this finding needs to be further explored.

Our results support previous reports highlighting the fact that certain substitutions in RpoB are more likely to confer high-level resistance [START_REF] Fines | Characterization of mutations in the rpoB gene associated with rifampin resistance in Rhodococcus equi isolated from foals[END_REF][START_REF] Giguère | Antimicrobial Resistance in Rhodococcus equi[END_REF][START_REF] Álvarez-Narváez | Clonal Confinement of a Highly Mobile Resistance Element Driven by Combination Therapy in Rhodococcus equi[END_REF][START_REF] Riesenberg | MICs of 32 antimicrobial agents for Rhodococcus equi isolates of animal origin[END_REF][START_REF] Huber | The novel and transferable erm (51) gene confers macrolides, lincosamides and streptogramins B (MLSB) resistance to clonal Rhodococcus equi in the environment[END_REF]. Indeed, in this study, highlevel resistance was correlated with the presence of His526Asp (MIC, 512-1024 µg/ml; nine strains) or Ser531Leu (MIC, 16-256 µg/ml; ten strains), while low-level resistance was correlated with the presence of Asp516Tyr (MIC, 8 µg/ml; one strain). His526Asp and Ser531Leu had already been described in rifampicin-resistant R. equi strains [START_REF] Boyen | Acquired antimicrobial resistance in equine Rhodococcus equi isolates[END_REF][START_REF] Liu | Appearance of multidrug-resistant virulent Rhodococcus equi clinical isolates obtained in China[END_REF][START_REF] Riesenberg | MICs of 32 antimicrobial agents for Rhodococcus equi isolates of animal origin[END_REF], and when comparative data were present in the same study, the MICs were higher for His526Asp than for Ser531Leu [START_REF] Fines | Characterization of mutations in the rpoB gene associated with rifampin resistance in Rhodococcus equi isolated from foals[END_REF][START_REF] Riesenberg | MICs of 32 antimicrobial agents for Rhodococcus equi isolates of animal origin[END_REF]. However, the Ser531Leu substitution was previously observed in R. equi strains with high-level rifampicin resistance of 128 µg/ml [START_REF] Riesenberg | MICs of 32 antimicrobial agents for Rhodococcus equi isolates of animal origin[END_REF] or with low-level rifampicin resistance of 8 µg/ml [START_REF] Fines | Characterization of mutations in the rpoB gene associated with rifampin resistance in Rhodococcus equi isolated from foals[END_REF][START_REF] Riesenberg | MICs of 32 antimicrobial agents for Rhodococcus equi isolates of animal origin[END_REF]. Substitutions in other regions of RpoB than the clusters I to III or other mechanisms of rifampicin resistance may explain this finding and even the presence of rare rifampicin resistant R. equi strains with no substitution in the clusters I to III of RpoB [START_REF] Riesenberg | MICs of 32 antimicrobial agents for Rhodococcus equi isolates of animal origin[END_REF]. To our knowledge, Asp516Tyr has never been described before in R. equi but was previously described in rifampicin-resistant Mycobacterium tuberculosis strains [START_REF] Ohno | Relationship between rifampin MICs for and rpoB mutations of Mycobacterium tuberculosis strains isolated in Japan[END_REF][START_REF] Cavusoglu | In-vitro activity of rifabutin against rifampicin-resistant Mycobacterium tuberculosis isolates with known rpoB mutations[END_REF].

Regarding the 20 strains found by DD to be susceptible to rifampicin, 50% showed no substitution in RpoB amino acid sequences 477 to 705, and 40% showed only substitutions not appearing to confer rifampicin resistance. As concerns the remaining 10%, strains #34 and #35 had one substitution in cluster I (with additional substitutions outside clusters I to III in the case of strain #35) -His526Asn and Asp516Val respectively. These have previously been described in R. equi strains as leading to low-level rifampicin resistance of 1-8 µg/ml [START_REF] Fines | Characterization of mutations in the rpoB gene associated with rifampin resistance in Rhodococcus equi isolated from foals[END_REF][START_REF] Boyen | Acquired antimicrobial resistance in equine Rhodococcus equi isolates[END_REF][START_REF] Riesenberg | MICs of 32 antimicrobial agents for Rhodococcus equi isolates of animal origin[END_REF]. Both strains were isolated respectively from animal no. 25 during which ten other strains were also isolated, all being found by DD to be non-susceptible to rifampicin and with MICs of 8 to 1024 µg/ml. In this context, strains #34 and #35 should be considered nonsusceptible to rifampicin and we propose that ≥ 32 mm should be used as a breakpoint for susceptibility instead of ≥ 29 mm for a 30-μg rifampicin disc (Fig. 3). However, our findings do not allow us to propose breakpoints for rifampicin MICs obtained by the BMD method. S ≤ 1 µg/ml and R ≥ 4 µg/ml have already been reported in the literature for R. equi and correspond to CLSI interpretative criteria for Staphylococcus aureus [START_REF] Berghaus | Comparison of Etest, disk diffusion, and broth macrodilution for in vitro susceptibility testing of Rhodococcus equi[END_REF], which is probably the most consistent with our DD and rpoB sequencing results.

In this study, the nine horses concerned with the isolation of rifampicin non-susceptible strains were distributed throughout the phylogenetic tree of R. equi species based on MLST sequences (Fig. 1) and no association was observed between the rifampicin resistance and dominant ST1, ST19 and ST24 (or any other information on horses, like the year of collection) (Fig. 1). These findings suggest a non-clonal dissemination of rifampicin resistant strains in France contrary to what has been observed from equine R. equi strains isolated in the USA [START_REF] Álvarez-Narváez | Comparing PFGE, MLST, and WGS in monitoring the spread of macrolide and rifampin resistant Rhodococcus equi in horse production[END_REF]. It should however be noted that MLST results generated with next generation sequencing (NGS) had resulted in a better detection of this clonality than Sanger sequencing [START_REF] Álvarez-Narváez | Comparing PFGE, MLST, and WGS in monitoring the spread of macrolide and rifampin resistant Rhodococcus equi in horse production[END_REF]. In our context, it is unlikely that NGS-MLST would have allowed us to conclude differently.

In conclusion, this study reports nine French cases of rifampicin resistance in horses infected by R. equi between 1995 and 2018. The relationship between rifampicin susceptibility tested using both DD and BMD methods, and the substitutions observed in RpoB amino acid sequences 477 to 705 (E. coli numbering) revealed the presence of substitutions that were correlated with high-level (His526Asp, Ser531Leu), low-level (Asp516Tyr), and low or borderline-level (His526Asn and Asp516Val) rifampicin resistance, the Asp516Tyr substitution having never been previously described in R. equi. We observed that the standard DD method widely used in clinical laboratories may miss isolates with RpoB substitutions, such as strains #34 and #35 with substitutions His526Asn and Asp516Val respectively.

Further studies are needed to define specific R. equi clinical breakpoints for rifampicin and macrolides used in combination to treat R. equi infections.

Haenni for discussions on antibiotic resistance (ANSES, Lyon Laboratory). We also wish to thank Delphine Libby-Claybrough, professional translator and native English speaker, for her editorial assistance. The ANSES Laboratory for Animal Health, Normandy site, is a member of the equine research scientific interest group "GIS Centaure" and the authors are grateful to the Regional Council of Normandy for providing an excellent scientific and work environment. previously reported as correlated with low-level rifampicin resistance, and observed respectively in the strain #34 (susceptible to rifampicin by DD with a MIC of 4 µg/ml) and in the strain #35 (susceptible to rifampicin by DD with a MIC of 1 µg/ml). Both strains were isolated from the animal no. 25 during which ten other strains were also isolated, all being non-susceptible to rifampicin by DD with MICs of 8 to 1024 µg/ml. b Same animal (no. 25) but different sample sources; the strain from the faeces was isolated two days before necropsy.

c From the atypical outbreak of R. equi infections in adult ponies on Mayotte in 2012 [START_REF] Tapprest | Major outbreak of rhodococcosis in adult equidae[END_REF]. d PCR and MLST results extracted from Duquesne et al. [START_REF] Duquesne | Development of a multilocus sequence typing scheme for Rhodococcus equi[END_REF]. +, detected; -, not detected; ND, not determined.

e No virulence plasmid was detected. f 30-µg rifampicin inhibition zone diameters (mm) and rifampicin MICs (µg/ml) were determined respectively by DD and BMD.

g The rifampicin susceptibility of the reference ATCC 33701 and 103S strains was taken from the literature [START_REF] Fines | Characterization of mutations in the rpoB gene associated with rifampin resistance in Rhodococcus equi isolated from foals[END_REF][START_REF] Letek | The Genome of a Pathogenic Rhodococcus: Cooptive Virulence Underpinned by Key Gene Acquisitions[END_REF].

Fig. 1 .

 1 Fig. 1. Phylogenetic tree of R. equi species based on MLST sequences. The maximum likelihood phylogenetic tree was based on the alignment of 4017-bp concatenated DNA sequences of the seven MLST loci for 37 R. equi STs recorded in the Rhodococcus MLST database (https://pubmlst.org/rhodococcus/) and the new one, ST43, obtained in this study. The tree was rooted with the ST06-concatenated sequences of the Rhodococcus sp. MBE 538 strain as the outgroup, extracted from the Rhodococcus MLST database. The bootstrap values were calculated from 1000 replications. The black arrows represent the STs of the 40 strains studied and R. equi ATCC 33701. The RpoB profiles I to XIV are indicated after the black arrows with in parentheses the number of horses concerned; the year of collection was indicated when animals were concerned with the isolation of rifampicin non-susceptible strains. a , His526Asp or Ser531Leu correlated with high-level rifampicin resistance; b , Asp516Tyr correlated with low-level rifampicin resistance; c , His526Asn or Asp516Val

Fig. 2 .

 2 Fig. 2. Schematic positions of RpoB substitutions in the 40 R. equi strains studied. A: Map of the E. coli RpoB with the location of rifampicin cluster I (507 to 533), II (563 to 572), and III (687). B: Distribution of substitutions observed in RpoB amino acid sequences 477 to 705 (E. coli numbering). Fourteen RpoB amino acid sequences, artificially named RpoB profiles I to XIV, were observed, including the wild-type RpoB (GenBank accession no. CBH49657). The rifampicin MICs determined by BMD are indicated.

Fig. 3 .

 3 Fig. 3. Distribution of rifampicin inhibition zone diameters and MICs as determined by respectively disc diffusion and broth macrodilution methods. Vertical solid lines represent the interpretative zone diameter breakpoints for Staphylococcus spp. and Streptococcus spp. (35) and the vertical dotted line represents a proposed interpretative susceptible zone diameter breakpoint for R. equi. The strain frequency per square is not represented; one square may contain the results from one to seven strains. The amino acid substitutions observed in RpoB cluster I are indicated. S, susceptible; R, resistant.

513b

  Breakpoints for azithromycin and clarithromycin are the same as for erythromycin. 514 c Approved by the CASFM (35) for Staphylococcus spp. and Streptococcus spp.

515d

  The indicator of resistance was defined as the ratio between the number of non-susceptible 516 strains and the total number of strains (n=40). Their confidence intervals (CI) were calculated 517 using the exact binomial method. to DD results. b new substitutions reported in this study. Strain ID in the study Rifampicin MIC (µg/ml) RpoB profile ATCC 33701 and 103S (accession no. CBH49657) ND a I (wild type) #04, #05, #06, #09, #15, #16, #22, #26, #38, #39 0#03, #07, #08, #19, #21, #29, #20, #27, #28, #30, #31, #32, #37 128 -1024 XIV

Acknowledgements

The authors are grateful to Maud Bernez-Romand, Clarisse Brocquevieille, Benoit Ecolivet, and Armand Pontin for technical assistance, Aurélie Merlin for discussions on the R