# Emergence and rapid propagation of ST4 Mycoplasma bovis subtype in France and Belgium

Maxime Bruto, Maryne Jaÿ, Stéphanie Lefebvre, Florine Dieu, Marc Saulmont, Nathalie Jarrige, Florence Tardy, Fabien Labroussaa, Claire a M Becker, Chloé Ambroset

► To cite this version:

Maxime Bruto, Maryne Jaÿ, Stéphanie Lefebvre, Florine Dieu, Marc Saulmont, et al.. Emergence and rapid propagation of ST4 Mycoplasma bovis subtype in France and Belgium. Veterinary Journal, 2025, 314, pp.106437. 10.1016/j.tvjl.2025.106437. anses-05523753

HAL Id: anses-05523753

https://anses.hal.science/anses-05523753v1

Submitted on 23 Feb 2026

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons CC BY 4.0 - Attribution - International License
<figure><img src="image_2.png" /></figure>

<figure><img src="image_3.png" /></figure>

Check for
updates

# Emergence and rapid propagation of ST4 *Mycoplasma bovis* subtype in France and Belgium

Maxime Bruto<sup>a</sup>, Maryne Jaÿ<sup>b</sup>, Stéphanie Lefebvre<sup>b</sup>, Florine Dieu<sup>b</sup>, Marc Saulmont<sup>d</sup>, Nathalie Jarrige<sup>c</sup>, Florence Tardy<sup>b,2</sup>, Fabien Labroussaa<sup>b</sup>, Claire A.M. Becker<sup>a,1</sup>, Chloé Ambroset<sup>b,*,1 ID</sup>

## ARTICLE INFO

Keywords:

*Mycoplasma bovis*

Pathogen surveillance

Antimicrobial resistance

Phylogeny

Genomic evolution

## ABSTRACT

*Mycoplasma (M.) bovis* is a major pathogen worldwide involved in bovine respiratory disease with significant economic and welfare impacts. Since the 2000s, the laboratory-based surveillance network Vigimyc has integrated molecular typing of an annual subset of *M. bovis* isolates collected in France, and more recently in Belgium. This study aimed to characterize the epidemiological situation and evolution of *M. bovis* in both countries over the 2018–2024 period. A total of 498 *M. bovis* isolates were characterized using a routine monitoring approach based on *polC* subtyping. We observed the apparent re-emergence and the rapid spread of *polC* st1 isolates since 2019 in France and 2020 in Belgium, accompanied by a concurrent and marked decline of the previously dominant *polC* st2 genotype. To investigate this phenomenon, we performed whole-genome sequencing on 45 *polC* st1 isolates to explore their genetic diversity and evolutionary relationships between strains. Genome-based analyses highlighted that this population was phylogenetically distinct from the older *polC* st1 isolates collected before 2000 and belonged to the ST4 according to the updated PubMLST database. The genetic diversity within these isolates was extremely low in comparison to that observed in the other subtypes, thus highlighting the recent and clonal emergence of this new lineage. In the absence of apparent AMR switch associated with this expansion, as previously observed for the emergence of *polC* st2 population, we identified putative genetic patterns specific to this lineage that may contribute to the fitness and epidemiological success of recent *polC* st1 isolates.

## Introduction

By collecting continuous and reliable information on disease situations, epidemiological surveillance systems aim at limiting the impact of related diseases on human or animal populations (Thrusfield, 2018). Disease surveillance serves as the basis for the detection and rapid evaluation of (re-) emerging diseases or potential outbreaks as well as monitoring the effects of intervention measures (Jebara, 2004). Over the years, advances in diagnostic tools and genomic surveillance of pathogens significantly improved the overall effectiveness of monitoring

programs (Mathijs et al., 2016; Gardy and Loman, 2018). The importance of such surveillance systems was particularly highlighted in the recent SARS-CoV2 pandemic, where surveillance platforms such as Nextstrain (Hadfield et al., 2018) or GISAID (Shu & McCauley, 2017) were essential to keep track of pathogen evolution. The global epidemic of avian influenza in birds (Song et al., 2024), as well as the recent outbreaks of epizootic hemorrhagic disease (EHD) and Bluetongue virus (BTV) in cattle demonstrated their necessity for animal health monitoring as well (Breard et al., 2023; Gondard et al., 2024).

Except for notifiable mycoplasma diseases listed by the WOAH

<footnote><sup>a</sup> Université de Lyon, Anses, VetAgro Sup, UMR Mycoplasmoses Animales, Marcy l'Etoile 69280, France</footnote>

<footnote><sup>b</sup> Université de Lyon, Anses, VetAgro Sup, UMR Mycoplasmoses Animales, Lyon 69007, France</footnote>

<footnote><sup>c</sup> University of Lyon, Anses, laboratoire de Lyon, unité d'Epidémiologie et Appui à la Surveillance, Lyon 69007, France</footnote>

<footnote><sup>d</sup> Regional Animal Health and Identification Association (ARSIA), Ciney, Belgium</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: chloe.ambroset@vetagro-sup.fr (C. Ambroset).</footnote>

<footnote n="1">¹ These authors contributed equally to this work.</footnote>

<footnote n="2">² Current address: Anses, laboratoire de Ploufragan-Plouzané-Niort, unité de Mycoplasmologie, Bactériologie et Résistance aux antibiotiques, 22440 Ploufragan, France.</footnote>
(World Organization of Animal Health) (including the Contagious Bovine Pleuropneumonia, the Contagious Caprine Pleuropneumonia and Contagious agalactia (CA), the surveillance of ruminant mycoplasmoses greatly varies from one country to another. While the monitoring of mycoplasma infections of sheep and goats (i.e. CA) is often overlooked despite recent outbreaks (Johnson et al., 2019; Wagner et al., 2024), several countries have a long surveillance history of *Mycoplasma* (M.) bovis (Aebi et al., 2015; Garcia-Galan et al., 2020; Tardy et al., 2020; Deeney et al., 2021; Haapala et al., 2021, Kinnear et al., 2021). *M. bovis* is a worldwide cattle pathogen mainly involved in bovine respiratory diseases (BRD), arthritis in young cattle and mastitis (Maunsell et al., 2011). First reported in 1961 in the USA, *M. bovis* spread rapidly around the world through international cattle trade or contaminated semen used for insemination (Haapala et al., 2018, Dudek et al., 2020). *M. bovis* is still a major health issue in cattle. In mid-2017, the recent detection of *M.bovis* in New Zealand, a country so far free from this pathogen, resulted in a massive outbreak and led to a huge national eradication program to contain the disease. In France, annual data highlight that *M. bovis* continues to be the most frequently isolated mycoplasma species in cattle (Jay et al., 2021).

The worldwide epidemiosurveillance of *M. bovis* infections relies on different genetic typing approaches, including the updated MLST schemes where all subtypes (ST) are gathered in the pubMLST database (Register et al., 2014, Register et al., 2020) and the *polC* subtyping (st) mainly used in Europe (Becker et al., 2015, Garcia-Galan et al., 2020, 2022, Tardy et al., 2020). In recent years, molecular epidemiology studies using whole genome sequencing (WGS) approaches emerged to track the evolution or emergence of different *M. bovis* lineages (Parker et al., 2016; Bokma et al., 2020; Tardy et al., 2020; Menghwar et al., 2021; Ambroset et al., 2022; Triebel et al., 2023). Comparative genomic studies have shown that population structure of *M. bovis* isolates can be explained by geographical origins or by international trade of cattle (Kumar et al., 2020; Yair et al., 2020; Menghwar et al., 2022; Theze et al., 2023). Despite providing invaluable information on pathogen evolution and phylodynamics, the cost of these WGS approaches remain difficult to sustain.

Vigimyc is a laboratory-based surveillance network focusing on ruminant mycoplasmoses in France since 2003 (Chazel et al., 2010; Jay et al., 2021). Vigimyc scope has been extended recently to Belgium with the participation of ARSIA laboratory. Vigimyc approach relies on identification of mycoplasma positive cultures performed in first-line laboratories from clinical specimens upon request of veterinarians or breeders (Chazel et al., 2010; Jay et al., 2021). Besides AMR surveillance started in 2018 (Jay et al., 2021), the diversity of circulating strains is monitored continuously on a subset of *M. bovis* isolates collected using the *polC* subtyping scheme, based on the sequencing of the *polC* gene, that has been demonstrated to be a useful and cost-effective epidemiological marker. Thanks to this surveillance, we previously demonstrated the existence of three different *polC* subtypes (st) co-circulating in France (Becker et al., 2015). The *polC* subtype 1 (st1), first to be observed before 2000, had a corresponding updated PubMLST subtype ST12. This subtype was progressively replaced after 2000 by a dominant subtype, namely *polC* st2 (updated PubMLST ST8). Interestingly, the apparition of *polC* st2 was associated with antimicrobial resistance (AMR) patterns that differed from older *polC* st1 strains with acquired resistance to all antimicrobial families except fluoroquinolones (FQ) (Gautier-Bouchardon et al., 2014; Khalil et al., 2016, 2017). Initially defined as clonal, this *M. bovis* *polC* st2 French population was later shown to be composed of two different lineages with different epidemic dynamics (Theze et al., 2023). Since 2011, a novel and more diverse *polC* subtype, namely *polC* st3, corresponding to different MLST profiles (ST21-ST134-ST144) has been detected (Becker et al., 2015; Khalil et al., 2016) while *polC* st2 remained steadily dominant. *PolC* st3 isolates showed similar AMR profiles but in vitro studies highlighted that this subtype could acquire more rapidly and conserve mutations in their quinolone resistance-determining regions (QRDR) under selective

pressure leading to resistant phenotypes (Khalil et al., 2016). In Spain, where *polC* st3 is most prevalent, *polC* st3 isolates were shown to be less susceptible to FQ than *polC* st2 (Garcia-Galan et al., 2020).

Surprisingly, an apparent re-emergence (i.e. increase of frequency after a period of absence) of *polC* st1 *M. bovis* strains, once observed in 2014 (Ambroset et al., 2022), appeared to be ongoing since 2019. The present study was conducted to monitor the recent evolution of *M. bovis* isolates collected in the framework of Vigimyc both in France and in Belgium. First, we characterized the epidemiological dynamics, as well as the AMR profiles of the *M. bovis* isolates over the 2018–2024 period through the Vigimyc surveillance network. Then, we sequenced the genomes of a large subset (n = 47) of *polC* st1 strains to genetically characterize this new population and its propagation. Finally, we assessed the phylogenetic relationships of this *polC* st1 population in comparison to the two other subtypes circulating in France, as well as other *polC* st1 isolates worldwide.

## Materials and methods

### Sample collection, culture conditions and DNA extraction

*M. bovis* isolates were collected through Vigimyc surveillance over the 2018–2024 period in France and Belgium, according to the same criteria described by Jay et al. (2021). Briefly, annual selection of *M. bovis* included one isolate only per sampling date and per location, distributed as widely as possible within departments and with diverse associated clinical signs (Table S1). No quantitative clinical data was available for the selected strains. A total of 498 *M. bovis* isolates (364 French and 134 Belgian) identified by membrane filtration dot-immunobinding (Poumarat et al., 1991) were chosen for this study (Table S1). Twenty four old French *M. bovis* isolates, collected over the 1977–1997 period, were used for comparison purpose (Gautier-Bouchardon et al., 2014; Becker et al., 2015). Isolates were grown for ~30 h at 37 °C under 5 % CO₂ in pleuro-pneumonia-like organism (PPLO) broth (Indicia Production, St Genis L'Argentière). Cultures of strains (10⁸ and 10⁹ CFU/mL) were frozen for subsequent Antimicrobial Susceptibility Testing (AST) determination. In parallel, crude extract was used in order to define *polC* subtype (st). Briefly, 20 µL of isolate culture were heated 5 min at 95°C then centrifuged 5 min at 10,000 rpm. Five microliters of supernatant were used as the DNA template for PCR amplification. *M. bovis* isolates selected for sequencing (n = 52) were subsequently cloned by filtration using a 0.22-µm filter and then seeded onto PPLO agar plates. One clone was picked and further subcultured. Genomic DNA (gDNA) was extracted from 4 mL culture using a commercial kit from Lucigen (MasterPure DNA and RNA purification kit, Epicentre) following manufacturer's instructions. The quality and concentration of the gDNA extractions were checked using a Nanodrop spectrophotometer (ThermoFisher) with the following optical densities OD260/280 ≥ 1.8 and OD260/230 ≥ 2 and a Qubit fluorimeter (dsDNA HS assay kit, Thermo Fisher), respectively.

### *polC* and MLST subtyping, genome sequencing, assembly and annotation

For clarity and consistency throughout the paper, 'st' will be used to refer to subtypes obtained using the *polC* subtyping while 'ST' will be used for the updated MLST Register scheme (PubMLST) (Register et al., 2020).

For routine monitoring purpose, *polC* subtyping was done on all 498 isolates as previously reported (Becker et al., 2015). Sanger sequencing was performed at Eurofins genomics and sequence analysis was carried out using Geneious (Geneious Prime; Biomatters, New Zealand, v2023.2.1).

Forty seven *M. bovis* isolates from this study were sequenced using Illumina technology (Nextera XT DNA library preparation kit and Novaseq sequencer). Two *M. bovis* isolates (F12831 and F8428) were also sequenced using Oxford Nanopore Technology (ONT) on a MinION
Flow Cell (R10.4 for F8428 strain and R9.4.1 for F12831). A total of 6 µg and 100 ng of gDNA per isolate were used for ONT and Illumina sequencing, respectively. Both Illumina and ONT sequencing were outsourced at iGenSeq platform (Institut du Cerveau; icm) and at the Bordeaux Genome Transcriptome Facility (PGTB), respectively. Quality control of raw data (FASTQ files for both short and long reads), genome assemblies (draft genomes for short reads and circularized genomes for hybrid assemblies) were performed according to previously published protocols and parameters (Ambroset et al., 2022). All draft assemblies were curated to eliminate all scaffolds with a size below 200 bp. We used the NCBI Prokaryotic Genome Annotation Pipeline (PGAP v2023–10–03.build7061) for genome annotation. Sequence Read Archive (SRA) data were used to re-assemble the five *M. bovis* ST4 genomes previously sequenced (van Engelen et al., 2024) and 23 ST8 genomes previously published (Theze et al., 2023) in order to provide additional genomic data to evaluate the post emergence intra-subtype diversity through SNP analysis (see Bioinformatic analysis section). All sequences and subtypes were retrieved from ncbi and PubMLST databases in december 2024, the 13th. Assembly statistics and genome completeness were computed for the two complete and circularized genomes using QUAST 5.2.0 (Gurevich et al., 2013) and Busco 5.5.0 (Seppey et al., 2019). All these bioinformatics tools and pipelines were run using the IFB-core cluster resources (https://www.france-bioinfomatique.fr/cluster-ifb-core).

Determination of MLST profiles (abbreviated as ST) was performed in PubMLST database (https://pubmlst.org/) following the updated *M. bovis* MLST scheme (Register et al., 2020) for all sequenced genomes used in this study.

Sequences were deposited in public database under bioproject PRJNA1218938.

### Antimicrobial susceptibility testing (AST)

AST was performed on 522 isolates (498 over the 2018–2024 period and 24 over the 1977–1997 period) using the agar dilution method as previously described (Jay et al., 2021) (Table S1). Minimal inhibitory concentrations (MICs) were estimated using defined concentration of different antimicrobials in agar media in order to detect any evolution in MICs distribution over time. Two to five concentrations were tested for each of the following antimicrobial classes: tilmicosin (macrolides), lincomycin (lincosamides), enrofloxacin (fluoroquinolones), oxytetracycline (tetracyclines), spectinomycin (aminoglycosides) and florfenicol (phenicols). All antimicrobials were purchased from Sigma-Aldrich (Sigma-Aldrich, Saint-Quentin-Fallavier).

MICs are expressed in ranges (µg/mL) and interpretation was conducted according to available Tentative Epidemiological Cut-off (TEC-OFF) for *M. bovis* for enrofloxacin and florfenicol (https://mic.eucast.org/) and Pasteurelleceae clinical breakpoints (CLSI, 2015) for the other molecules in the absence of specific breakpoints for veterinary mycoplasmas.

### Bioinformatic analyses

The quantification of SNPs between different genomes was calculated by first aligning each genome sequences to a reference using ska2 (Derelle et al., 2024). Briefly, F9160, F12831, L15762 and L15527 were used as genome reference for ST12, ST4, ST8 and ST21 updated MLST subtype population analysis respectively. For each SNP analysis conducted within a subtype, genomes were selected over the same period of time after their initial detection (i.e. 4 years), to limit the potential bias associated to the natural genetic drift of bacterial genomic sequences overtime. Polymorphism were searched using SNP-sites (Page et al., 2016) and differences were manually counted. Comparative genomics was performed with ppanggolin (v2.1.1) (Gautreau et al., 2020) and default options except for the translation table used (4 instead of 11). Core genes were retrieved with ppanggolin and aligned with mafft

(v7.526) (Katoh and Standley, 2013) and the *-auto* option that automatically defines the most appropriate parameters. The alignments were filtered with Gblocks (Castresana, 2000) and parameters defined to perform a soft filtering (-b3 =10 -b4 =5 -b5 =h). Phylogenetic trees were computed with iqtree (v1.6.12) (Minh et al., 2020) using the general time nucleotide substitution model (GTR), a 4 rate Gamma law (G) and proportion of invariant sites (I) (option -m GTR+G+I). Other parameters were left as default. Visualization of core-phylogenetic tree was done with iTOL (Letunic and Bork, 2007).

## Results

### Apparent emergence of *M. bovis* polC st1 strains in France and Belgium

For surveillance purposes, 498 *M. bovis* isolates (364 French and 134 Belgian) were selected over the 2018–2024 period from the Vigimyc collection and analysed (Fig. 1). Metadata included the geographical origins, the clinical signs and the nature of the specimen when available. All data are provided in Table S1. Clinical signs were mostly related to BRD, that concerned 76 % of French (n = 310) and 74 % of Belgian isolates (n = 99). Other clinical signs comprised arthritis (n = 17 and n = 4), otitis (n = 15 and n = 9) mastitis (n = 2 and n = 10), neurological disease (n = 1 and n = 1) and death (n = 1) for French and Belgian isolates, respectively. Among samples with unreported clinical signs, those of respiratory origin (lung, nasal swab, BALF) were dominant.

On average, subtyping was performed on a representative panel of *M. bovis* isolates collected by Vigimyc in both countries. Indeed analyses were carried out on ~39 % (minimum: 27 % and maximum: 55 % over 2018–2024) and ~49 % (minimum: 31 % and maximum: 57 % over 2019–2024) of the *M. bovis* population annually collected through Vigimyc surveillance in France and Belgium, respectively.

First, no polC st1 subtype was identified on the subset of French *M. bovis* isolates initially performed in 2018 (Fig. 1A). All isolates belonged to polC st2 and polC st3 subtypes with a large proportion of polC st2 (96 %, n = 24). A progressive increase of polC st1 frequency was then observed with 2 % of the samples (n = 1; F12831) in 2019 to62 % (n = 37) in 2024 (Fig. 1A). Consequently, the most prevalent subtype in French samples, namely polC st2, rapidly decreased to reach a proportion of 8 % in 2024 (n = 5). In the meantime, the proportion of polC st3 isolates remained overall stable (~30 % of the population). A similar trend was observed for the *M. bovis* isolates collected in Belgium during the same period (Fig. 1B). While no isolate belonged to the polC st1 in 2018 (n = 8), the frequency increased to 23–24 % in 2020–2021 and peaked the following years (mean ~60 %). Similarly to the French situation, the polC st3 proportion remained stable with around 30 % of isolates, whereas the proportion of polC st2 sharply decreased and represented only 8 % in 2024 (Fig. 1B). From now on, the recent population of polC st1 isolated after 2018 will be named st1new while the polC st1 isolates collected before 2018 will be named st1old.

### The *M. bovis* st1new population is widely distributed with no distinctive clinical profile associated

Overall, the epidemiological situation in the two countries regarding the expansion of these st1new isolates is similar. In France, the first case of st1new re-emergence was collected in 2019 in the Manche department (50) from a cow with respiratory symptoms. Based on the geographical distribution of cases, no link could be established between this particular event and the subsequent isolations of the *M. bovis* st1new population in the following years (Fig. 2A). Indeed, *M. bovis* st1new isolates were recovered from 41 departments out of the 55 covered by the Vigimyc network (Fig. 2A). More isolates appeared to originate from the “Grand-Ouest” area of France which is defined by the region BrTAGne, Pays de la Loire, Basse Normandie and northern part of Nouvelle Aquitaine (up to 9 isolates collected in the department of Vienne, mean=4.1) than from other regions (mean =2.2). However, “Grand-
<figure><img src="image_4.png" /><figcaption>**Fig. 1.** *PolC* subtype (st) proportions of isolates of the Vigimyc network between 2018 and 2024. Yearly *polC* st proportions of the French (A) and Belgium (B) isolates are represented.</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Aggregation of *polC* st1 isolates over the 2018–2024 period in France (A) and in Belgium (B). The small map on the top left shows the French departments or the Belgian provinces covered by the Vigimyc network (dark grey). For the main maps, color graduation highlight the number of bovine in 2020 according to Agreste data for France or in 2021 for Belgium. Black dots show the total number of *polC* st1 strains isolated per department or province over the 2018–2024 period.</figcaption></figure>

Ouest” region is known to host a large percentage of the French cattle population (45 %, Recensement agricole 2020 - Indicateurs: cartes, données et graphiques). The relative proportion of *polC* st1new isolates collected in this region (n = 56) is not different from that of the rest of the country (n = 66). Similarly, st1new isolates were recovered from all five Belgian provinces (Wallonia) covered in the Vigimyc network with isolation events fluctuating between 2 and 19 isolates per province for the whole period (Fig. 2B).

Among the st1new isolates (French n = 132 and Belgian n = 56), 88 % and 80 % were related to BRD. These numbers are similar to the proportions observed inside the whole panel. In the absence of detailed clinical data collected through routine surveillance, the st1new isolates did not appear to be associated with atypical clinical presentations.

*Antimicrobial resistance is not the main driver of the emergence of the st1new M. bovis population*

Historically, the emergence of *M. bovis* *polC* st2 over st1old population isolated before year 2000 was previously demonstrated to be linked to the apparition of novel AMR. Therefore, AST were conducted on all subtyped strains of this study to detect any new AMR profiles in the st1new population that might explain its recent emergence and rapid spread. MICs results obtained for the different isolates are detailed in Table 1. No significant differences in MICs distributions were seen between isolates belonging to the st1new and the *polC* st2 and st3 populations for all antimicrobials, except for spectinomycin. For the latter, a shift towards more sensitive isolates was detected through AMR surveillance (Jay et al. 2021). Indeed, 90 % of the st1new isolates (n = 161) were characterized by low MICs values (≤16 µg/mL, below the *Pas-teurrellaceae* resistant breakpoints for cattle), whereas only 9 % (n = 15) and 49 % (n = 76) of the *polC* st2 and st3 populations had similar MICs
<caption>**Table 1**</caption>

MIC distributions of 5 antimicrobials for *M. bovis* polC st1, st2 and st3 isolates from 2018 to 2024 period collected in France and Belgium and an additional panel of 24 polC st1 isolates collected in France over the 1977–1997 period.

<figure><img src="image_6.png" /></figure>

The number of isolates is shown for each MIC category. The grey color gradation is proportional to the number of isolates with the same MIC value. “/” means no isolate in the corresponding category. The resistant breakpoints for *Pasteurellaceae* (CLSI, 2015) are represented by dashed lines. The tentative ECOFF for *M. bovis* (EUCAST, January 2025) and resistant breakpoint for *Pasteurellaceae* (CLSI, 2015) are represented by a continuous line and double lines respectively. TILM, tilmicosin; SPECTINO, spectinomycin; OXYTETRA, oxytetracycline; FLOR, florfenicol; ENRO, enrofloxacin.

values, respectively (Table 1). A similar phenotype for spectinomycin (i. e. 100% of the population sensitive, n = 24) was also observed for st1old isolates (Table 1). Concerning the other antimicrobials, few noticeable differences between subtypes are worth mentioning. Low MICs values were reported for enrofloxacin for all subtypes with a slight difference of distribution for the *polC* st2 population harboring MICs values mostly comprised between 0.5 and 1 µg/mL (Table 1). However, whatever the subtype considered, all MICs except 4 values remained below the TECOFF (1 µg/mL) and thus belonged to the wild-type population. The distribution of MICs values for florfenicol around 4 µg/mL appeared also different: 51 % of st1new MICs were less than 4 µg/mL compare to 23 % of st2 and 14 % of *polC* st3. However, the majority of florfenicol MICs values remained below the TECOFF (16 µg/mL), being distributed within the wild-type population. Differences observed concerned consecutive MIC ranges were only separated by one dilution step and therefore could not be considered significantly distinct as regards to AST results.

Contradictorily to the similar pattern observed for spectinomycin, a

clear difference was observed between the st1new and st1old populations for tilmicosin. The st1new population was characterized by a clear resistant phenotype (MICs values >1024 µg/mL), also observed in the *polC* st2 and st3 populations. In contrast, the st1old population had low MICs values (<16 µg/mL), consistent with the global sensitive profile towards all antibiotics observed in st1old population.

Recent *M. bovis* polC st1 strains are genetically distinct from historical polC population but related to other *M. bovis* strains isolated in Europe

To assess the genomic diversity of the *polC* st1 population, we sequenced a panel of 45 *M. bovis* polC st1 isolates including st1new isolated between 2019 and 2022 (n = 35) from different French departments and also 6 additional st1old isolated before 2000. Four Belgian isolates collected in 2020 were also included (Table S2). One additional isolate from Algeria (39M3-c3) and collected through a partnership with the University of Batna were also included in this study and sequenced (Oucheriah et al., 2022). All *M. bovis* genomes were
obtained using Illumina sequencing with the exception of the first st1 *polC* isolate newly-identified in 2019, namely F12831, which was sequenced with both Illumina and ONT technologies to provide another complete and circularized reference strain. The genome of isolate F12831 was 1,061,420 bp in size, in coherence with other circularized genomes of *M. bovis* strains, and contained 884 predicted coding sequences (CDS). Typical genomic features of *M. bovis* such as 35 tRNA loci and two sets of rRNA (23S, 16S and 5S) were also identified (Table S3). These characteristics were consistent with general genomic features (size and number of CDSs) of *M. bovis* genomes retrieved in public databases. For the Illumina sequenced population (n = 45), we obtained scaffolds with a mean genome size of 1,054,776 bp (Table S2) and a number of predicted CDS that ranged between 884 and 1151.

Using all the genomes available, we determined the subtype of each isolate according to the updated PubMLST scheme (Register et al., 2020). The sequenced st1 population corresponded to 2 different PubMLST subtypes: the *M. bovis polC* st1old strains and the strain F9160 (isolated in 2014) (Ambroset et al., 2022) belonged to the ST12 whereas all the *polC* st1new strains (F12831 and others) belonged to the ST4. Then, we searched for additional ST4 isolates already identified worldwide amongst the sequences of *M. bovis* genomes publicly available. Among the genome sequences retrieved, 11 *M. bovis* strains belonged to this ST4 subtype including the strain 267780, isolated in 2016 in Israel (Yair et al., 2020), strain 15DD0261 isolated in 2015 in Germany (Triebel et al., 2023) and 9 strains isolated in 2013 from the Netherlands (van Engelen et al., 2024) (Table S2). Amongst the Dutch isolates, only 5 were considered later on in this study as the re-assembly based on the raw data available did not meet our quality criterions. In

addition, the PubMLST database also contained 3 other isolates belonging to ST4 isolated in 2015, 2018 and 2019 in Hungary.

A core genome phylogenetic analysis based on 694 genes was conducted using all the ST12 and ST4 isolates sequenced in this study (Figure S1). This analysis clearly showed that the French and Belgian strains isolated since 2019 clustered together, suggesting a low genetic diversity of the ST4 isolates. Moreover, a separation of ST12 (old isolates) and ST4 (recent isolates) in two different lineages was clearly highlighted.

### Evolutionary dynamic and genetic diversity of the ST4 subtype, toward recent clonal expansion

We sought to better understand the evolutionary history of ST4 in comparison with the other subtypes circulating in France. Another core genome phylogeny analysis was conducted, including all high-quality sequenced *M. bovis* isolates (from all *polC* st) and showed that all ST4 isolates grouped together with ST21-ST134-ST144, corresponding to *polC* st3 isolates, as closest phylogenetic neighbors (Fig. 3A). In comparison, the ST12 was phylogenetically distant from the ST4 but closely related to the ST8 strains (*polC* st2 subtype). The ST4 isolates seem to be separated in two different lineages comprising (i) the French and Belgian isolates characterized in this study and (ii) isolates from other countries. The apparent lack of genetic diversity observed for the French and Belgian isolates highlighted the possibility of a recent clonal expansion of this lineage. We quantified the genetic diversity by computing the SNP numbers present between all the isolates of a particular subtype (Fig. 3B). We observed that among French and Belgian isolates ST4 had

<figure><img src="image_7.png" /><figcaption>**Fig. 3.** Phylogeny and genetic diversity of *M. bovis* subtype circulating in France and ST4 of foreign origins. A. Phylogenetic tree of *M. bovis* isolates based on 599 core genes (639424 positions). Branch support was estimated with SH-like score and black dots indicate branches supported by a score > 0.95. Isolates belonging to ST12 are in blue, ST8 in orange, ST21/ST134/ST144 in green and ST4 in red. B. SNP values of the different French subtypes. For each subtype a single strain was used as reference to calculate SNP values (F9160 for ST12; L15762 for ST8; L15527 for ST21/ST134/ST144; F12831 for ST4). C. Genomic conservation of *M. bovis* isolates using F12831 as reference. Each column represent a gene and each line represent an isolate. When a gene is present, it is represented by a coloured square (the same colour pattern as in A is applied here). When a gene is absent in the isolate, the square is white. Genomic regions of interest are highlighted by a black outer circle.</figcaption></figure>
much less SNPs (mean number = 26.6) than ST12 (mean number = 211.1), ST8 (mean number = 127.2) and ST21-ST134-ST144 (mean number = 260.7) confirming a recent clonal expansion of the ST4 population.

Finally, we also compared the genetic content of the genomes belonging to the four subtypes (Fig. 3C). No specific genes could be found in ST4 that might explain the suggested recent clonal expansion as all the pangenome seems to be shared by at least two other subtypes. However, we could observe three highly dynamic genomic regions (Fig. 3C). These four genetic loci mainly encode for a mycoplasma integrative and conjugative element (MICE), variable surface lipoproteins (vsp), surface antigens bspA and an additional copy of milA, an immunogenic membrane protein (Adamu et al., 2020). In spite of the recent clonal expansion of this lineage, we also noted that within ST4 these regions exhibit a high gene turnover illustrating that antigenic variability evolves rapidly in the field.

Discussion

The surveillance of *M. bovis*, performed through the Vigimyc network over the 2018–2024 period, detected the apparent emergence of *polc* st1 isolates in France and for the first time in Belgium. This subtype was thought to be extinguished in France as no isolate was collected since 2000 with the exception of the strain F9160 isolated in 2014 while *polc* st2 and st3 subtypes were detected (Becker et al., 2015; Becker et al., 2020; Ambroset et al., 2022). *Polc* st1 apparent emergence, first detected in 2019 with an isolate originating from the Northwest of France (Manche), was followed by a rapid spread throughout the country (Fig. 2). A switch in the diversity with a rapid expansion of this *polc* st1 was observed over the 2019–2024 period. In 2024, 62 % of the *M. bovis* isolates analyzed belonged to this subtype and the previously dominant *polc* st2 subtype was decreased to only 8 % (Fig. 1). A similar epidemiological situation was also observed in Belgium even if no records was established prior 2018 for this country. To gain knowledge on the genetic diversity of these novel *polc* st1 *M. bovis* strains, especially in comparison to the historical population, whole genome sequencing of a panel of 45 isolates detected either before 2000 and during the 2018–2024 period was done. In parallel, the first recent *polc* st1 sequence isolated in 2019 (strain F12831) was circularized to provide a trustworthy st1new reference genome for future epidemiological studies. Interestingly, this recent *M. bovis* *polc* st1 population belonged to the ST4 whereas the st1old isolated before 2000 were part of the ST12 subtype according to the updated MLST Register scheme (Register et al., 2020). In contrast to the ST12 isolates, all publicly available ST4 isolates were isolated relatively recently and primarily in Europe. Indeed, the oldest ST4 reference strain was isolated in 2013 in the Netherlands (van Engelen et al., 2024) followed by other isolations in Germany (2015), Hungary (2015–2018) or in countries where *M. bovis* epidemiology is known to be highly influenced by the cattle trade, including Israel (2016) (Yair et al., 2020) and Algeria (2018) (Oucheriah et al., 2022). So far, no reports (Tardy et al., 2020; McAloon et al., 2024) have identified strains belonging to this lineage in north European countries as per UNSD definition. No information is currently available to infer how this ST4 subtype was introduced and spread in Europe. The characterization of the lineage represented by recent ST4 isolates revealed a highly homogenous population with little genetic diversity. This result was strengthened by the very low number of SNPs observed amongst recent ST4 strains and provide additional evidences for the recent emergence of a new clonal population in France and in Belgium.

The emergence of ST4 *M. bovis* population, correlated to the decrease of the ST8 subtype, was intriguing from an epidemiological point of view. In France, the emergence of ST8 isolates in 2000 was associated with a clear switch of AMR profiles (Khalil et al., 2017). AST tests performed on a representative population of each of the subtypes did not reveal any increase in MICs values for any of the antimicrobials tested in the ST4 population. In contrast, almost 90 % of the French and Belgian

ST4 isolates were found susceptible to spectinomycin, whereas the ST8 and ST21-ST134-ST144 populations were globally resistant to the latter. Whatever the subtypes, the distribution of MICs values of Belgian isolates was comparable to those obtained for French isolates with few exceptions. Isolates with higher enrofloxacin MICs (≥2 µg/mL) were only present in Belgian population. On the contrary, isolates with higher florfenicol MICs (≥32 µg/mL) were completely absent in the Belgian population but present in low percentages in French isolates. These fluctuations might reflect the differential use of antimicrobials between the two countries. Interestingly, a study published in 2024 also showed the circulation st1 *polc* isolates in Spain (Corrales et al., 2024) but no PubMLST subtypes are mentioned. However, these Spanish *M. bovis* isolates were characterized by acquired resistance profiles to macro-lides, lincosamides and fluoroquinolones, which suggests that these isolates are different from the ones currently circulating in France and Belgium. Of course, full genome sequences of the Spanish isolates would be necessary to confirm our assumption.

In absence of evidence incriminating AMR as one of the main drivers of the emergence of the ST4 population, the analysis of the core and pan genomes of this population against the other ST8, ST21, ST134 and ST144 subtypes, including ST12, was performed. So far, no clear genetic pattern or specific genes, exclusively present or absent in the ST4 genomes, were identified explaining such an improved fitness. However, some genetic differences were visible in the vsp loci with the presence of different patterns in each of the subtypes. These proteins, known to be highly variable and immunogenic antigens (Beier et al., 1998; Poumarat et al., 1999), may have contributed to the clonal expansion of this new lineage to which the bovine population was naive (Perez-Casal, 2020). Another genomic region included an additional copy of *milA* gene in the ST4 French and Belgian genomes. Indeed, it was previously shown that MilA possesses a lipase activity (Adamu et al., 2020) and may have adhesin properties. Interestingly, the MilA protein is used in ELISA serological diagnostic tests for its immunogenic role (Wawegama et al., 2014). One hydrolase domain associated with the lipase activity was identified in the “original” MilA protein found in all the ST4 genomes collected worldwide while an additional copy of this gene named *milA-like* was only identified amongst the ST4 French and Belgian population. This gene showed homologies with a second domain called TcdA for toxin domain of *Clostridioides difficile* (Voth and Ballard, 2005). Further investigation will be needed to characterize this *milA-like* gene as a candidate virulence factor in *M. bovis*. Additional high-quality genomic sequences of *M. bovis* isolates would be necessary to ease the search for candidate genes involved in this phenomenon. *In vitro* or *in cellulo* competition experiments would be needed to better understand the fitness advantages of the ST4 lineage over the other subtypes.

Overall, this study highlights the importance of maintaining efficient surveillance programs such as the Vigimyc network for the monitoring of *M. bovis*. Additional efforts towards genomic surveillance based on whole genome sequencing should be of prime importance for the future of the Vigimyc network. It would allow the precise monitoring of this new ST4 population through phylodynamics approaches to decipher its evolution and potential diversification in the near future, as well as to infer potential clinical impact in the field (Theze et al., 2023). Ideally, such a surveillance would need to be coordinated at the European level to facilitate the collection of sensitive epidemiological data used to inform and alert surrounding countries of a particular infectious threat.

CRediT authorship contribution statement

**Chloé Ambroset:** Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Methodology, Funding acquisition, Formal analysis, Data curation, Conceptualization. **Maxime Bruto:** Writing – review & editing, Writing – original draft, Visualization, Validation, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. **Maryne Jaŷ:** Writing – review & editing, Writing – original draft, Visualization,
Validation, Methodology, Investigation, Formal analysis, Data curation. **Nathalie Jarrige:** Writing – review & editing, Visualization, Investigation. **Florence Tardy:** Writing – review & editing, Validation, Supervision, Resources, Methodology, Formal analysis, Conceptualization. **Fabien Labroussaa:** Writing – review & editing, Writing – original draft, Supervision, Resources, Funding acquisition. **Claire A.M. Becker:** Writing – review & editing, Writing – original draft, Supervision, Funding acquisition. **Stéphanie Lefebvre:** Writing – review & editing, Investigation. **Florine Dieu:** Writing – review & editing, Investigation. **Marc Saulmont:** Writing – review & editing, Resources, Funding acquisition.

## Funding sources

This work was supported by Anses internal funds allocated to the activities of the Vigimyc epidemiosurveillance network, as well as by a "Impulsion santé globale" grant awarded to Maxime Bruto by VetAgro Sup.

## 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.

## Acknowledgements

The authors thank the former and current members of the Vigimyc team. We thank the team of the IFB Core cluster who provided the access to computational resources for bioinformatics analyses. We also acknowledge Yasmine Oucheriah and Nouzha Heleili from the Batna University in Algeria who kindly authorized the sequencing of the Algerian strain 39M3-c3.

## Appendix A. Supporting information

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.tvjl.2025.106437.

## References

Adamu, J.Y., Wawegama, N.K., Kanci Condello, A., Marenda, M.S., Markham, P.F., Browning, G.F., Tivendale, K.A., 2020. Mycoplasma bovis membrane protein MilA is a multifunctional lipase with novel lipid and glycosaminoglycan binding activity. *Infection and Immunity* 88.

Aebi, M., van den Borne, B.H., Raemy, A., Steiner, A., Pilo, P., Bodmer, M., 2015. Mycoplasma bovis infections in Swiss dairy cattle: a clinical investigation. *Acta Veterinaria Scandinavica* 57, 10.

Ambroset, C., Peticca, A., Tricot, A., Tardy, F., 2022. Genomic features of mycoplasma bovis subtypes currently circulating in France. BMC Genomics 23, 603.

Becker, C.A., Thibault, F.M., Arcangioli, M.A., Tardy, F., 2015. Loss of diversity within mycoplasma bovis isolates collected in France from bovines with respiratory diseases over the last 35years. *Infection Genetics and Evolution*.

Becker, C.A.M., Ambroset, C., Huleux, A., Vialatte, A., Colin, A., Tricot, A., Arcangioli, M. A., Tardy, F., 2020. Monitoring mycoplasma bovis diversity and antimicrobial susceptibility in calf feedlots undergoing a respiratory disease outbreak. *Pathogens* 9.

Beier, T., Hotzel, H., Lynsnyansky, I., Grajetzki, C., Heller, M., Rabeling, B., Yogeved, D., Sachse, K., 1998. Intraspecies polymorphism of vsp genes and expression profiles of variable surface protein antigens (Vsps) in field isolates of mycoplasma bovis. *Veterinary Microbiology* 63, 189–203.

Bokma, J., Vereecke, N., De Bleecker, K., Callens, J., Ribbens, S., Nauwynck, H., Haesebrouck, F., Theuns, S., Boyen, F., Pardon, B., 2020. Phylogenomic analysis of mycoplasma bovis from Belgian veal, dairy and beef herds. *Veterinary Research* 51, 121.

Bread, E., Postic, L., Gondard, M., et al., 2023. Circulation of bluetongue virus serotypes 1, 4, 8, 10 and 16 and epizootic hemorrhagic disease virus in the sultanate of Oman in 2020-2021. *Viruses* 15.

Castresana, J., 2000. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. *Molecular Biology and Evolution* 17, 540–552.

Chazel, M., Tardy, F., Le Grand, D., Calavas, D., Poumarat, F., 2010. Mycoplasmoses of ruminants in France: recent data from The National surveillance network. BMC Veterinary Research 6, 32.

CLSI, 2015. Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated from animals. Clinical and Laboratory Standards Institute, Wayne, PA.

Corrales, J.C., Sanchez, A., Hernandez, X., Amores-Iniesta, J., Esnal, A., de la Fe, C., 2014. A set of multiresistant isolates of mycoplasma bovis subtype ST-1 with a variable susceptibility to quinolones are also circulating in Spain. *Pathogens* 13.

Deeney, A.S., Collins, R., Ridley, A.M., 2021. Identification of mycoplasma species and related organisms from ruminants in england and wales during 2005-2019. BMC Veterinary Research 17, 325.

Derelle, R., von Wachsmann, J., Maklin, T., Hellewell, J., Russell, T., Lalvani, A., Chindelevitch, L., Croucher, N.J., Harris, S.R., Lees, J.A., 2024. Seamless, rapid, and accurate analyses of outbreak genomic data using split k-mer analysis. *Genome Research* 34, 1661–1673.

Dudek, K., Nicholas, R.A.J., Szacawa, E., Bednarek, D., 2020. Mycoplasma bovis Infections-C occurrence, diagnosis and control. *Pathogens* 9.

Garcia-Galan, A., Nouvel, L.X., Baranowski, E., Gomez-Martin A, Sanchez, A., Citti, C., de la Fe, C., 2020. Mycoplasma bovis in spanish cattle herds: two groups of multiresistant isolates predominate, with one remaining susceptible to fluoroquinolones. *Pathogens* 9.

Garcia-Galan, A., Baranowski, E., Hygonenq, M.C., Walch, M., Croville, G., Citti, C., De la Fe, C., Nouvel, L.X., 2022. Genome mosaicism in field strains of mycoplasma bovis as footprints of In-Host horizontal chromosomal transfer. Applied and Environmental Microbiology 88, e0166121.

Gardy, J.L., Loman, N.J., 2018. Towards a genomics-informed, real-time, global pathogen surveillance system. *Nature Reviews Genetics* 19, 9–20.

Gautier-Bouchardon, A.V., Ferre, S., Le Grand, D., Paoli, A., Gay, E., Poumarat, F., 2014. Overall decrease in the susceptibility of mycoplasma bovis to antimicrobials over the past 30 years in France. *PLoS One* 9, e87672.

Gautreau, G., Bazin, A., Gachet, M., et al., 2020. PpanGGOLIN: depicting microbial diversity via a partitioned pangenome graph. *PLoS Computational Biology* 16, e1007732.

Gondard, M., Postic, L., Garin, E., et al., 2024. Exceptional bluetongue virus (BTV) and epizootic hemorrhagic disease virus (EHDV) circulation in France in 2023. *Virus Research* 350, 199489.

Gurevich, A., Saveliev, V., Vyahhi, N., Tesler, G., 2013. QUAST: quality assessment tool for genome assemblies. *Bioinformatics* 29, 1072–1075.

Haapala, V., Pohjanvirta, T., Vahanikkila, N., Halkilaihti, J., Simonen, H., Pelkonen, S., Soveri, T., Simojoki, H., Autio, T., 2018. Semen as a source of mycoplasma bovis mastitis in dairy herds. *Veterinary Microbiology* 216, 60–66.

Haapala, V., Vahanikkila, N., Kulkas, L., Tuunainen, E., Pohjanvirta, T., Autio, T., Pelkonen, S., Soveri, T., Simojoki, H., 2021. Mycoplasma bovis infection in dairy herds-Risk factors and effect of control measures. The Journal of Dairy Science 104, 2254–2265.

Hadfield, J., Megill, C., Bell, S.M., Huddleston, J., Potter, B., Callender, C., Sagulenko, P., Bedford, T., Neher, R.A., 2018. Nextstrain: real-time tracking of pathogen evolution. *Bioinformatics* 34, 4121–4123.

Jay, M., Poumarat, F., Colin, A., Tricot, A., Tardy, F., 2021. Addressing the antimicrobial resistance of ruminant mycoplasmas using a clinical surveillance network. *Frontiers in Veterinary Science* 8, 667175.

Jebara, K.B., 2004. Surveillance, detection and response: managing emerging diseases at national and international levels. *Revue Scientifique et Technique* 23, 709–715.

Johnson, G.C., Fales, W.H., Shoemake, B.M., Adkins, P.R., Middleton, J.R., Williams, F., 3rd, Zinn, M., Mitchell, W.J., Calcutt, M.J., 2019. An outbreak of mycoplasma mycoides subspecies capri arthritis in young goats: a case study. The Journal of Veterinary Diagnostic Investigation 31, 453–457.

Katoh, K., Standley, D.M., 2013. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. *Molecular Biology and Evolution* 30, 772–780.

Khalil, D., Becker, C.A., Tardy, F., 2016. Alterations in the quinolone Resistance- Determining regions and fluoroquinolone resistance in clinical isolates and Laboratory-Derived mutants of *Mycoplasma bovis*: not all genotypes May be equal. *Applied and Environmental Microbiology* 82, 1060–1068.

Khalil, D., Becker, C.A.M., Tardy, F., 2017. Monitoring the decrease in susceptibility to ribosomal RNAs targeting antimicrobials and its molecular basis in clinical *Mycoplasma bovis* isolates over time. *Microbial Drug Resistance* 23, 799–811.

Kinnear, A., Waldner, M., McAllister, T.A., Zaheer, R., Register, K., Jelinski, M., 2021. Application of four genotyping methods to mycoplasma bovis isolates derived from Western Canadian feedlot cattle. *Journal of Clinical Microbiology* 59, e0004421.

Kumar, R., Register, K., Christopher-Hennings, J., et al., 2020. Population genomic analysis of mycoplasma bovis elucidates geographical variations and genes associated with Host-Types. *Microorganisms* 8.

Letunic, I., Bork, P., 2007. Interactive tree of life (iTOL): an online tool for phylogenetic tree display and annotation. *Bioinformatics* 23, 127–128.

Mathijs, E., Vandenbussche, F., Van Borm, S., 2016. Using genomics for surveillance of veterinary infectious agents. *Revue Scientifique Et Technique* 35, 143–157.

Maunsell, F.P., Woolums, A.R., Francoz, D., Rosenbusch, R.F., Step, D.L., Wilson, D.J., Janzen, E.D., 2011. *Mycoplasma bovis* infections in cattle. *Journal of Veterinary Internal Medicine* 25, 772–783.

McAloon, C.I., Farrell, D., Smith, J., et al., 2024. Characterisation and comparison of mycoplasma bovis strain types from Irish and scottish bovine isolates in a global context. *Veterinary Microbiology* 300, 110339.

Menghwar, H., Prysliak, T., Perez-Casal, J., 2021. Phylogeny of mycoplasma bovis isolates from cattle and bison based on multi locus sequence typing and multiple-locus variable-number tandem repeats. *Veterinary Microbiology* 258, 109124.
Menghwar, H., Guo, A., Chen, Y., Lysnyansky, I., Parker, A.M., Prysliak, T., Perez-Casal, J., 2022. A core genome multilocus sequence typing (cgMLST) analysis of mycoplasma bovis isolates. Veterinary Microbiology 273, 109532.

Minh, B.Q., Schmidt, H.A., Chernomor, O., Schrempf, D., Woodhams, M.D., von Haeseler, A., Lanfear, R., 2020. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Molecular Biology and Evolution 37, 1530–1534.

Oucheriah, Y., Heleili, N., Colin, A., Mottet, C., Tardy, F., Becker, C.A.M., 2022. Prevalence of mycoplasma bovis in Algeria and characterisation of the isolated clones. Frontiers in Veterinary Science 9, 910799.

Page, A.J., Taylor, B., Delaney, A.J., Soares, J., Seemann, T., Keane, J.A., Harris, S.R., 2016. SNP-sites: rapid efficient extraction of SNPs from multi-FASTA alignments. Microbial Genomic 2, e000056.

Parker, A.M., Shukla, A., House, J.K., Hazelton, M.S., Bosward, K.L., Kokotovic, B., Sheehy, P.A., 2016. Genetic characterization of Australian mycoplasma bovis isolates through whole genome sequencing analysis. Veterinary Microbiology 196, 118–125.

Perez-Casal, J., 2020. Pathogenesis and virulence of Mycoplasma bovis. Veterinary Clinics of North America: Food Animal Practice 36, 269–278.

Poumarat, F., Perrin, B., Longchambon, D., 1991. Identification of ruminant mycoplasmas by dot immunobinding on membrane filtration (MF dot). Veterinary Microbiology 29, 329–338.

Poumarat, F., Le Grand, D., Solsona, M., Rosengarten, R., Citti, C., 1999. Vsp antigens and vsp-related DNA sequences in field isolates of mycoplasma bovis. FEMS Microbiology Letters 173, 103–110.

Register, K.B., Thole, L., Rosenbush, R.F., Minion, F.C., 2014. Multilocus sequence typing of mycoplasma bovis reveals host-specific genotypes in cattle versus bison. Veterinary Microbiology.

Register, K.B., Lysnyansky, I., Jelinski, M.D., Boatwright, W.D., Waldner, M., Bayles, D. O., Pilo, P., Alt, D.P., 2020. Comparison of two multilocus sequence typing schemes for mycoplasma bovis and revision of the PubMLST reference method. Journal of Clinical Microbiology 58.

Seppey, M., Manni, M., Zdobnov, E.M., 2019. BUSCO: assessing genome assembly and annotation completeness. Methods in Molecular Biology 1962, 227–245.

Shu, Y., McCauley, J., 2017. GISAID: global initiative on sharing all influenza data - from vision to reality. Euro surveillance 22.

Song, X., Tian, J., Li, M., et al., 2024. Epidemiology and biological characteristics of influenza a (H4N6) viruses from wild birds. Emerging Microbes & Infections 13, 2418909.

Tardy, F., Aspan, A., Autio, T., et al., 2020. Mycoplasma bovis in nordic european countries: emergence and dominance of a new clone. Pathogens 9.

Theze, J., Ambroset, C., Barry, S., Masseglia, S., Colin, A., Tricot, A., Tardy, F., Bailly, X., 2023. Genome-wide phylodynamic approach reveals the epidemic dynamics of the main mycoplasma bovis subtype circulating in France. Microbial Genomic 9.

Thrusfield M. (2018) Veterinary epidemiology, fourth edition, p.^pp. 421-456.

Triebel, S., Sachse, K., Weber, M., Heller, M., Diezel, C., Holzer, M., Schnee, C., Marz, M., 2023. De novo genome assembly resolving repetitive structures enables genomic analysis of 35 european mycoplasmopsis bovis strains. BMC Genomics 24, 548.

van Engelen, E., Mars, J., Dijkman, R., 2024. Molecular characterisation of mycoplasma bovis isolates from consecutive episodes of respiratory disease on Dutch veal farms. Veterinary Microbiology 298, 110221.

Voth, D.E., Ballard, J.D., 2005. Clostridium difficile toxins: mechanism of action and role in disease. Clinical Microbiology Reviews 18, 247–263.

Wagner, H., Heller, M., Fawzy, A., et al., 2024. Mycoplasma mycoides subspecies capri, an uncommon mastitis and respiratory pathogen isolated in a German flock of goats. Veterinary Microbiology 290, 109996.

Wawegama, N.K., Browning, G.F., Kanci, A., Marenda, M.S., Markham, P.F., 2014. Development of a recombinant protein-based enzyme-linked immunosorbent assay for diagnosis of mycoplasma bovis infection in cattle. Clinical and Vaccine Immunology 21, 196–202.

Yair, Y., Borovok, I., Mikula, I., Falk, R., Fox, L.K., Gophna, U., Lysnyansky, I., 2020. Genomics-based epidemiology of bovine mycoplasma bovis strains in Israel. BMC Genomics 21, 70.