Whole genome sequencing to study antimicrobial resistance and RTX virulence genes in equine Actinobacillus isolates
Veterinary Research volume 54, Article number: 33 (2023)
Actinobacillus equuli is mostly associated with disease in horses and is most widely known as the causative agent of sleepy foal disease. Even though existing phenotypic tools such as biochemical tests, 16S rRNA gene sequencing, and Matrix Assisted Laser Desorption Ionization Time of Flight Mass Spectrometry (MALDI-TOF MS) can be used to identify members of the Actinobacillus genus, these methods struggle to differentiate between certain species and do not allow strain, virulence, and antimicrobial susceptibility typing. Hence, we performed in-depth analysis of 24 equine Actinobacillus isolates using phenotypic identification and susceptibility testing on the one hand, and long-read nanopore whole genome sequencing on the other hand. This allowed to address strain divergence down to the whole genome single nucleotide polymorphism (SNP) level. While lowest resolution was observed for 16S rRNA gene classification, a new multi-locus sequence typing (MLST) scheme allowed proper classification up to the species level. Nevertheless, a SNP-level analysis was required to distinguish A. equuli subspecies equuli and haemolyticus. Our data provided first WGS data on Actinobacillus genomospecies 1, Actinobacillus genomospecies 2, and A. arthritidis, which allowed the identification of a new Actinobacillus genomospecies 1 field isolate. Also, in-depth characterization of RTX virulence genes provided information on the distribution, completeness, and potential complementary nature of the RTX gene operons within the Actinobacillus genus. Even though overall low prevalence of acquired resistance was observed, two plasmids were identified conferring resistance to penicillin-ampicillin-amoxicillin and chloramphenicol in one A. equuli strain. In conclusion our data delivered new insights in the use of long-read WGS in high resolution identification, virulence gene typing, and antimicrobial resistance (AMR) of equine Actinobacillus species.
Actinobacillus species are Gram-negative bacteria, causing different diseases in several animals, including swine, cattle, and horses . Even though Actinobacillus equuli (A. equuli) is most frequently associated with disease in horses, also other Actinobacillus species, such as A. suis , A. arthritidis , Actinobacillus genomospecies 1 [3,4,5] and Actinobacillus genomospecies 2 [3, 6] have been occasionally described in equine samples. Nomenclature changes and the fact that it is very difficult to differentiate some of these species with standard biochemical tests, 16S rRNA gene sequencing, and/or MALDI-TOF MS, make it hard to interpret final identification in previously and currently published reports. Actinobacillus equuli is an important cause of septicemia in foals (sleepy foal disease) and is inflicted as primary or secondary pathogen in lower respiratory tract diseases, peritonitis, and meningitis in adult horses [1, 7, 8]. Also, it has been occasionally linked with infections in pigs, rabbits, and humans [1, 9,10,11,12]. The A. equuli species contains 2 subspecies, i.e. A. equuli subspecies equuli and A. equuli subsp. haemolyticus . Both subspecies can cause disease in horses, even though A. equuli subsp. haemolyticus has been associated more with severe respiratory disease. This is thought to be because of the A. equuli toxin (Aqx), a member of the repeats-in toxin (RTX) family, which is encoded by the aqx genes in A. equuli subsp. haemolyticus strains only and contributes to the haemolytic characteristic of this subspecies . A. equuli infections are feared by both horse owners and veterinarians due to the high mortality rate of such infections.
Actinobacillus equuli affected neonatal foals should be treated aggressively with antimicrobial therapy and supportive care. Both in foals and adult horses, various antimicrobial agents are used for treatment, but beta-lactam antibiotics, often combined with aminoglycosides are most frequently applied. Even though there are some reports on antimicrobial resistance in A. equuli , antimicrobial susceptibility data are still scarce or limited to specific cases or antimicrobial agents [7, 16, 17], while there seem to be no published data on genetic determinants at all .
To study bacterial antimicrobial resistance (AMR) and virulence, whole genome sequencing (WGS) has become affordable and of great interest in the field of microbiology. As exemplified for many other bacterial species in both human and veterinary medicine, the use of WGS data allows to study strain relatedness via phylogenetic inference, to perform virulence gene typing, and identify AMR associated mediators [19,20,21,22,23,24,25]. Many of these genes are located on mobile genetic elements (MGEs), such as plasmids, integrons, and transposons [26,27,28]. These MGEs are considered one of the most important drivers in the dissemination of AMR within and cross species and/or genus level. Within and across the genus of Actinobacillus, various plasmids have previously been described as important mediators of AMR [29, 30], but data are largely absent for equine species. The availability of new sequencing methodologies, such as third generation long-read nanopore sequencing (Oxford Nanopore Technologies (ONT)), allowed to use this technique in the generation of complete circular and accurate bacterial whole genomes and plasmids. Therefore, the goal of current study was to evaluate the overall genomic relatedness, a new MLST scheme, and distribution of RTX genes within the genus Actinobacillus sensu stricto, along with determining the in vitro susceptibility of well-identified recent equine Actinobacillus isolates in relation to genetic resistance mechanisms.
Materials and methods
Actinobacillus isolates and reference/type strains
Twenty-four Actinobacillus isolates were obtained from independent clinically affected horses during the period of 2008–2017, except for strains 3873 and 3874 that were isolated from the same animal on different occasions. The isolates were presumptively identified as A. equuli by colony morphology and standard biochemical methods, including haemolysis on sheep blood agar . Identification was also obtained with MALDI-TOF MS (Bruker Daltonik GmbH, Bremen, Germany) using the direct transfer method and α‐cyano‐4‐hydroxycinnamic acid as matrix, according to manufacturer’s guidelines and compared with the Bruker Daltonik database containing 8468 mean spectra projections. We considered identifications with a log score value > 2.0 to be reliable at the species level. Considering that equine Actinobacillus species may not be easily distinguished, even with MALDI-TOF MS or 16S rRNA gene sequencing [32, 33], further identification based on WGS data was performed, as described below. Pure cultures of all isolates were stored at −80 °C for further analysis. For WGS, A. equuli subsp. equuli type strain CCUG 2041T was included as an internal control for long-read sequencing quality validation, as genomic data of this strain have been published before and are available at NCBI (accession CP007715.1). Additionally, A. equuli subsp. haemolyticus type strain CCUG 19799T, A. arthritidis type strain CCUG 24862T, Actinobacillus genomospecies 1 reference strains CCUG 22229 and CCUG 22231, and Actinobacillus genomospecies 2 reference strain CCUG 15571 , were subjected to WGS to assist in the whole genome phylogenetic inference of Actinobacillus species, as no or scarce genomic data for these species were available at the time this manuscript was prepared.
Extraction of high molecular weight DNA and long-read whole genome sequencing
All clinical Actinobacillus strains (n = 24) and CCUG type/reference strains (n = 6) were grown and subjected to DNA extraction. All colonies from a fresh overnight culture were resuspended in 250 μL dPBS (Gibco) and subjected to high-molecular weight (HMW) DNA isolation using the ZymoBIOMICS DNA MiniPrep Kit (Zymo Research), following manufacturers’ instructions. Resulting HMW DNA was subjected to quantification and quality assessment on a NanoDrop Spectrophotometer after which samples with lowered quality (A260/A230 < 1.7) were cleaned using CleanNGS (CleanNA) magnetic beads. High-quality HMW DNA was used in a rapid long-read sequencing library preparation (SQK-RBK-004; ONT) using 400 ng input per sample and multiplexing up to 12 samples on a R9.4.1 flow cell (ONT). All samples were sequenced for 48 h, and data were collected as raw fast5 files in the MinKNOW software (ONT). All data were basecalled using the Bonito R&D basecaller (v0.4.0; ONT) with the firstname.lastname@example.org model on the Ghent University HPC Tier 2 GPU cluster Joltik using 1× GPU (NVIDIA Volta V100 32 GB). Draft genomes were assembled using canu (v2.0 ), followed by read mapping and polishing using minimap2 (v2.20 ) and medaka (v1.5.0; ONT), respectively. Completeness and accuracy of final consensus genomes was assessed using Kraken2 , ribosomal multi-locus sequence typing (rMLST) , QUAST (v5.0.2. ), and CheckM (v1.1.0 ). Genome completeness was evaluated against the 589 Actinobacillus spp. marker sets (18 genomes with 1004 marker genes). When all 1004 marker genes were identified, a completeness of 100% was reported. A genome QC report and associated NCBI accession numbers can be found in Additional files 1 and 2.
Phylogenetic analysis of Actinobacillus species
Complete and high-quality Actinobacillus species genomes were used in a whole genome single nucleotide polymorphism (SNP)-based analysis using csi phylogeny  including all available unique whole genomes of Actinobacillus spp. from NCBI (n = 72 accessed on 29/03/2022). Due to high divergence within the Actinobacillus genus, a subset of these genomes (n = 53) was kept for downstream analysis, excluding A. minor, A. indolicus, “A. porcitonsillarum”, A. succinogenes, A. porcinus, A. delphinicola, A. seminis, and A. sp. GY-402, along with genome duplicates (n = 10). Thus, a focus will be maintained on Actinobacillus sensu stricto. The A. equuli subsp. equuli strain CCUG 2041T (CP007715.1) was used as reference strain in both analyses. Also, sequences from the 16S rRNA gene were extracted. Since no MLST scheme is currently available for any Actinobacillus species, potential MLST genes (adk (adenylate kinase), atpG (ATP FOF1 synthase subunit gamma), deoD (purine nucleoside phosphorylase), zwf (glucose-6-phosphate dehydrogenase), recA (recombinase A), mdh (malate dehydrogenase), and pgi (glucose-6-phosphate isomerase)) were extracted from the genomes based on existing MLST schemes from other Pasteurellaceae members [41,42,43,44,45]. An overview of the generation of our new MLST scheme is given in Additional file 3. The new Actinobacillus spp. MLST scheme will be hosted on pubmlst.org . Subsequently, the aligned SNPs (csi phylogeny output), 16S rRNA gene allele 1, and concatenated MLST genes were used in maximum likelihood (ML) phylogenetic analyses, using IQ-TREE with the GTR + I + R substitution model and 1000 ultrafast bootstraps (-bb) (v1.6.1; ).
Antimicrobial susceptibility testing
Antimicrobial susceptibility testing was performed using the agar dilution assay , using Mueller Hinton agar supplemented with 5% defibrinated sheep blood, since preliminary testing showed that growth in cation–adjusted Mueller Hinton broth was difficult to interpret. An overview of the tested antimicrobials can be found in Table 1. Plates were incubated at 35 °C (± 2 °C) for 20–24 h in 5% CO2 enriched atmosphere, due to the fastidious and capnophilic nature of the Actinobacillus genus in general. Staphylococcus aureus ATCC 29213 and Escherichia coli ATCC 25922 were used as quality control strains for all antibiotics tested, while for amoxicillin-clavulanic acid testing additionally Escherichia coli ATCC 35218 was used. Since no wild type cut-off values are available for A. equuli (EUCAST, 2022), the ECOFF was determined using the “Normalized Resistance Interpretation (NRI)” method (Bioscand AB, Täby, Sweden) [49, 50], following manufacturers’ instructions. When the standard deviation of the normal distribution of wild type MIC values exceeds 1.2 log2, the outcome can only result in a tentative estimate of the ECOFF and one can only speak of the “putative wild type group”.
Evaluation of molecular mechanisms of virulence and antimicrobial resistance
Virulence and AMR genes were identified with abricate (v1.0.1)  using the virulence factor database (VFDB) , the comprehensive AMR database (CARD) , and a novel RTX toxin database (n = 1389), which was composed of RTX toxin and RTX toxin-related protein sequences obtained from NCBI (accessed on 21/02/2023) limited to the family of Pasteurellaceae and removal of sequences that were classified as “partial”. Sequences with a sequence homology of at least 60% amino acid identity and 80% coverage were searched for and reported. A complete overview can be found in Additional file 4. In addition, all genomes were annotated using prokka (v1.14.6; ), after which all hemolysin-associated genes were extracted and verified in BLASTX (v2.13.0 +). Next to genomes, also plasmids were searched for, analyzed, and manually annotated using open reading frame (ORF) finder (NCBI) and an experimental nr_clustered_blast (NCBI) with default settings. Classification and mobilization potential of identified plasmids was done using the mob-suite (v3.1.0; ). All clinical strains were tested for the presence of two identified plasmids using PCR. Based on the obtained plasmid sequences, two primer sets (available in Additional file 5) were generated and used for each plasmid in a OneTaq PCR reaction using following thermocycler conditions: initial denaturation at 94 °C for 30 s, 30 cycles of 94 °C for 30 s, 59 °C for 30 s, and 68 °C for 2 min, followed by a final extension at 68 °C for 5 min, using the strain in which the plasmids were originally detected as positive control. After amplification, DNA was visualized on a 1.5% agarose gel and sequenced as described above.
Identification and phylogenetic analysis of Actinobacillus species
All clinical isolates were identified as either A. equuli or A. suis using MALDI-TOF MS with score values > 2.00, except for one isolate. First and second-best score were often not of the same species, and score values > 2.00 for both A. equuli and A. suis were frequently observed within one strain. Isolate 3216 showed the best match with A. pleuropneumoniae (score value = 2.03) in the MALDI-TOF database and a second best hit with A. lignieresii (score value = 1.90). From the WGS data, all ribosomal gene sequences were used to perform a rMLST species identification (pubMLST) which identified all isolate species as A. equuli (20–90%), except for isolate 3216 that showed highest support (60%) with A. lignieresii (Additional file 2).
First, sequencing accuracy of the long-read only assembly was assessed by comparing the newly obtained genome with the available CCUG 2041T (CP007715.1) genomes, showing a 99.999% genome accuracy (Q50). A mean genome completeness of 98.7% (± 3.2%) was obtained for the genomes. This is in line with completeness statistics of all available NCBI WGS data (98.7% (± 3.8%)). Hence, the currently obtained genomic data represent highly accurate and complete genomes. To assess the potential use of the 16S rRNA gene and putative MLST scheme for identification and classification of Actinobacillus species, specific sequences were extracted from the genomes and used for phylogenetic inferences (Figures 1A and B). Our data was also supplemented with all available Actinobacillus spp. genomes (n = 62 after duplicate removal). Importantly, eight Actinobacillus species showed low whole genome nucleotide overlap with the A. equuli reference. These included “A. porcitonsillarum” (13%), A. minor (12%), A. indolicus (8%), A. porcinus (5%), A. seminis (3%) A. succinogenes (3%), Actinobacillus sp. GY-402 (3%), and A. delphinicola (2%) (Additional file 1). Due to this high genetic divergence and the significant drop in genomic overlap, these species were excluded from further analyses, which limits our main analysis to the genus Actinobacillus sensu stricto.
As shown in Figure 1A, the 16S rRNA gene sequence tree does not allow proper distinction of the A. equuli species from A. suis (purple), A. arthritidis (light green), and Actinobacillus genomospecies 2 (dark green). While all other species clearly clustered within a separate clade, little 16S rRNA gene specific mutations contributed to the divergence of the A. lignieresii and A. pleuropneumoniae clades, preventing proper classification. On the other side, our new MLST genes adk, atpG, deoD, zwf, recA, mdh, and pgi were concatenated, which allowed proper distinction of all Actinobacillus species. The strain 3216 clustered together with the Actinobacillus genomospecies 1 strains in both 16S rRNA gene and MLST trees. While this new MLST-based tree allowed proper clustering of all species included in this study, no subspecies resolution for A. equuli subsp. equuli and A. equuli subsp. haemolyticus could be obtained. Based on the MLST scheme, the A. equuli reference strain CCUG 2041T (CP007715.1) clustered within the A. equuli clade. The highest classification resolution could be obtained with the SNP-based WGS phylogenetic analysis (Figure 1C). This allowed to classify all strains, except strain 3216, to the A. equuli species with the highest accuracy and resolution. Within the A. equuli species, clear distinction could be made between 2 clades. The first clade contained seven non-haemolytic isolates (strains in green) and previously published genomic data of the (non-haemolytic) A. equuli reference strain NCTC 9435 (LR134486). The second clade contained 14 haemolytic (strains in red) and two non-haemolytic isolates and previously published genomic data of the A. equuli subsp. haemolyticus reference strain CCUG 19799T. Remarkably, even though both previously published genomes and the currently obtained genome of reference strain CCUG 2041T (CP007715.1) clustered closely together, this cluster seemed to be only distantly related to both current clinical isolates and other Actinobacillus equuli reference strains NCTC 9435 and CCUG 19799T. As summarized in Additional file 1, the reference strain shared 91.8% (± 0.8%) and 86.4% (± 0.7%) of its genome with the strains belonging to A. equuli subsp. equuli and A. equuli subsp. haemolyticus, respectively. Interestingly, based on the MLST analysis, the clade of the A. lignieresii species (orange) was wrongly placed within the A. pleuropneumoniae clade when compared to the SNP-based tree (Figure 1C). Hence, the SNP-based tree provided the highest resolution of classification and identification for all Actinobacillus species. Noteworthy, as seen in the horizontal distances between each A. equuli strain and other Actinobacillus species and the high divergence of the excluded Actinobacillus species, the Actinobacillus genus is represented by highly divergent species within and between different clades (Figure 1C and Additional file 1).
Identification of haemolysis-associated genes within the Actinobacillus genus
Based on the WGS data, all non-haemolytic isolates, and the A. equuli reference strains NCTC 9435 and NCTC 8529 lacked all four A. equuli specific RTX operon proteins (AqxCABD) (Figure 2; green). All other A. equuli isolates (n = 16) and the A. equuli subsp. haemolyticus reference strain CCUG 19799T had a complete RTX operon (Aqx(CABD)) embedded within their genomes (Figure 2; red). Noteworthy, strain 798 and 1812 showed no clear haemolysis when studied on blood agar plates. Nevertheless, none of the RTX operon proteins were absent or showed deviating amino acid identities. Interestingly, the aqxD gene was identified in all A. equuli subps. haemolyticus, A. suis, A. urea, and A. vicugnae strains, belonging to the same phylogenetic clade. In the A. vicugnae strain also the ApxI(CAB) proteins were identified. In all A. suis strains, an incomplete ApxI(CAB) operon and partial ApxII(CA) operon was found (Figure 2).
While genes encoding the RTX proteins were widely detected in all A. pleuropneumoniae (ApxI, ApxII, ApxIII, and ApxIV operons or combinations), also Actinobacillus genomospecies 1 isolate 3216 and both Actinobacillus genomospecies 1 reference strains CCUG 22229 and CCUG 22231, showed the presence of the A. pleuropneumoniae associated ApxI(CABD) operon, with an ApxIA protein showing a mean 70.5% (± 0.1%) amino acid homology. For the A. lignieresii strain NCTC4191, an ApxI(CAD) operon was identified, which was not found in the NCTC4189T strain. In some of the excluded Actinobacillus species, also RTX operon genes were identified. Interestingly, all tree A. lignieresii strains, showed the presence of an ApxIV protein. In “A. porcitonsillarum” 9953L55 and A. minor 202, a complete ApxI(CABD) operon was present. While these were absent in the NM305T strain, this strains genome showed the presence of an LktB protein from Mannheimia haemolytica with 71% protein homology. In the case of A. seminis NCTC1051T and A. porcinus NM319T, an ApxIIIA protein was detected within their genomes. In the former, A. seminis NCTC1051T, also conserved Pasteurella aerogenes-derived PaxB and PaxD proteins were identified. A complete overview of the RTX protein distribution within the Actinobacillus genus is given in Additional file 6.
Antimicrobial susceptibility testing
The results of the antimicrobial susceptibility testing, including the results of the quality control strains, are presented in Table 1. The distribution of the MIC values of most antimicrobial agents showed a unimodal distribution in the A. equuli isolates, except for penicillin, ampicillin, and chloramphenicol. Additionally, MIC values for the (potentiated; i.e., strengthen the antimicrobial effect of sulphonamides with the addition of trimethoprim) sulphonamides were spread out over a very wide MIC range. This wide distribution may have caused the NRI method to possibly falsely assign part of the strains as having acquired resistance towards sulfisoxazole, while for the trimethoprim/sulfamethoxazole combination only a putative wild-type population could be described. For penicillin, ampicillin, and chloramphenicol, only isolate 3887 was identified as a non-wild-type isolate, using the ECOFF as determined by the NRI method. The MIC values of the Actinobacillus genomospecies 1 strain 3216 were within the wild-type ranges of the A. equuli strains and no genetic resistance determinants were observed using the WGS data, suggesting this isolate also did not acquire resistance to any veterinary relevant antimicrobial agent.
Again, WGS data were used to evaluate the presence of antimicrobial resistance associated genes. Analysis of the sequencing data showed that all strains showed the presence of the global regulator crp gene within the genome. Genomic presence of the multidrug resistance transporter msbA gene was shown in 53% (16/30) of the clinical strains. Though, none of these could be correlated with observed phenotypic acquired resistance. Interestingly, the A. equuli subsp. haemolyticus strain 3887 showed the presence of two plasmids carrying various antimicrobial resistance genes. As shown in Figure 3, the class A beta-lactamase ROB-1, the aminoglycoside 3-phosphatase APH(3'')-Ib and chloramphenicol O-acetyltransferase catIII were identified on two different plasmids, named A. equuli pROB3887 (4615 bp) and pAPH-CAT3887 (2947 bp), respectively (Figures 3A and B). Further annotation of the latter showed the presence of a truncated dihydropteroate synthase sul2 gene (17.7% coverage; Figure 3B; blue). In-depth characterization showed closest matches with the pB1000 plasmid from Haemophilus influenzae strain BB1053 (GU080065) and pMHSCS1 plasmid from Mannheimia haemolytica (AJ249249), respectively. While the pROB3887 plasmid was considered mobilizable, the pAPH-CAT3887 plasmid was classified as non-mobilizable, possibly due to the truncation of the MobA mobilization protein in the 2947 bp plasmid. To validate the presence/absence of this plasmid in any other strains, all other strains were screened for these plasmids using a targeted multiplex PCR, showing no detection in any other of the currently targeted strains.
The present study provides new insights in the genetic diversity and presence of RTX virulence genes of the Actinobacillus genus. While focussing on equine clinical strains, also novel phenotypic and genetic data on acquired resistance in A. equuli were obtained. In general, identification of A. equuli is considered difficult due to its close relationship to A. suis [32, 56]. The use of the 16S rRNA gene was compared to a new MLST and whole genome SNP, showing that 16S rRNA gene sequencing was indeed least reliable in differentiating Actinobacillus species, while whole genome SNP analysis performed best. The use of 16S rRNA gene sequencing was also shown to not provide sufficient resolution and lack of specificity in previous research on Bacillus and Actinobacillus species [56, 57]. Interestingly, the Actinobacillus genomospecies 1 clade could be properly distinguished from other Actinobacillus species using the 16S rRNA gene only. This was not the case for A. suis and Actinobacillus genomospecies 2 which clustered amongst A. equuli strains. Here a putative new MLST scheme was used based on previously published schemes for Pasteurellaceae [41, 45]. The inclusion of the adk (adenylate kinase), atpG (ATP FOF1 synthase subunit gamma), deoD (purine nucleoside phosphorylase), zwf (glucose-6-phosphate dehydrogenase), recA (recombinase A), mdh (malate dehydrogenase), and pgi (glucose-6-phosphate isomerase) genes allowed to distinguish A. equuli from other Actinobacillus species, though it did not support the distinction between A. equuli subsp. equuli and A. equuli subsp. haemolyticus. This was only possible when using the SNP-based phylogenetic inference . Even though A. equuli and A. suis might be separated by detection of specific virulence genes (apx/aqx), sequencing certain housekeeping genes (e.g., infB), or by biochemical tests such as fermentation of D(-)-mannitol and cellobiose and β-glucosidase production, these tests are not always easy to interpret [58,59,60]. Over the years improvements to these tests have been made , still biochemical tests are progressively replaced by faster and easier techniques such as MALDI-TOF MS in diagnostic laboratories [33, 62]. MALDI-TOF MS, however, was not able to unequivocally identify all clinical strains as Actinobacillus equuli and did not support further subspecies classification. Albeit, both subspecies were included in initial versions of the Bruker Biotyper 3.0 database . In the most recent version of the Bruker Biotyper database that was used in this study, the software highlights that the species A. equuli, A. lignieresii, A. pleuropneumoniae, and A. suis have highly similar 16S rRNA gene and MALDI-TOF MS spectra. Therefore, distinguishing these species remains difficult. Interestingly, one of the clinical strains (3216) could not be correctly identified at all using MALDI-TOF MS, but this is mainly because Actinobacillus genomospecies 1 is not represented in the Bruker database. In addition, using the rMLST analysis, the closest match for strain 3216 was A. lignieresi (60%). Hence, we supplemented current data with other Actinobacillus species, including Actinobacillus genomospecies 1, Actinobacillus genomospecies 2, and A. arthritidis for which reference/type strains were sequenced. To the authors knowledge these are the first whole genome sequences available for these species. This allowed to classify the 3216 strain to Actinobacillus genomospecies 1 as it showed closest phylogenetic relation to the two Actinobacillus genomospecies 1 type strains, based on 16S rRNA gene, a putative MLST scheme, and whole genome SNP phylogenetic inferences. Of note, both MALDI-TOF MS and pubMLST showed close matches to the A. lignieresii species, which seemed to be the closest related species within the SNP-based tree (Figure 1C). First genome sequences of Actinobacillus genomospecies 1, Actinobacillus genomospecies 2, and A. arthritidis represented distinct clades within the Actinobacillus genus. The ability to identify and classify these lesser-known bacterial species is important as they have been linked to arthritis, stomatitis, and septicemia in horses [3, 13, 33]. Even though sequencing represents an interesting tool, existing databases (e.g. rMLST on pubMLST) also exhibit limitations if no closely linked species are present. Hence, lowered sequencing costs and new methodologies will encourage the availability of more divergent bacterial species, even from unculturable isolates from metagenomics sequencing [63,64,65].
It is generally accepted that A. suis strains carry ApxI(CABD) and ApxII(CA) proteins, while A. equuli subsp. haemolyticus isolates carry the Aqx(CABD) operon encoding the Aqx toxin and A. equuli subsp. equuli do not carry any RTX member toxins [66,67,68]. Indeed, this was confirmed in our study, where a clear distinction between the A. equuli subsp. haemolyticus and A. equuli subsp. equuli could be made with the presence/absence of the complete Aqx(CABD) operon. For the A. suis strains, incomplete ApxI(CAB) and ApxII(CA), operons were identified. These are thought to be complemented by the presence of the Aqx(D) protein. Within the A. pleuropneumoniae population, various ApxIV variants were identified, which was limited to this species and its phylogenetically close relative, A. liqnieresii. Also, the AqxD protein was identified in all genomes of A. equuli subsp. haemolyticus, A. suis, A. ureae, and A. vicugnae. The wider distribution of the AqxD protein suggests a putative other functional role within these species. Indeed, RTX exoproteins represent a highly diverse family, with its most studied function linked to enzymatic cytotoxins in a wide variety of bacteria, including various members of the Enterobacteriaceae and Pasteurellaceae. In addition, RTX proteins have been described to be hydrolytic enzymes with protease/lipase activity (e.g., Serratia and Pseudomonas), bacteriocin activity and nodulation (e.g., Rhizobium and Agrobacterium), and motility in Cyanobacteria . Though, its exact role(s) in diverse bacterial species, including Actinobacillus species, remains to be elucidated. This might also be the case for the identified LktB and PaxD/PaxB proteins in A. minor and A. seminis, respectively. As described before, a wide variety of RTX toxin clusters have been identified in different Actinobacillus species . For A. pleuropneumoniae four different clusters (ApxI-IV) have been described . Our data shows the occurrence of these four major RTX clusters associated with their genomic clades. While complete ApxI(CABD) and ApxIII(CABD) operons were identified in previously sequenced A. pleuropneumoniae strains, no complete ApxII(CABD) operons were found. Also, most A. pleuropneumoniae strains harbour one or more incomplete RTX operons. Even though RTX genes from E. coli and B. pertussis were shown to be complementary in vitro, the complementary character for Actinobacillus species should be further elucidated . Interestingly, our newly sequenced Actinobacillus genomospecies 1 strains also showed the presence of a complete ApxI(CABD) operon. Though, substantial mutations at the protein level were observed in the ApxI(A) protein. The absence of any of the RTX operons in the Actinobacillus genomospecies 2 reference strain is supported by previous phenotypic observations in an Actinobacillus genomospecies 2 strain isolated in Japan . Overall, we conclude that sequencing-based methods contribute to a better understanding of the complete toxin landscape. It provides information on the completeness and potential complementary nature of the RTX gene operons without the need of species-specific primer sets.
Considering there are no veterinary clinical breakpoints for A. equuli  and that the therapeutic result is also strongly dependent on the stage of infection, the lack of acquired resistance does not guarantee a successful therapy . On the other hand, the presence of acquired resistance can indeed hamper the in vivo efficacy of the antimicrobial agent. However, only for penicillin, ampicillin, and chloramphenicol, a remarkable increase in MIC values of 10 times above the highest MIC values of isolates belonging to the wild-type population was observed for isolate 3887. For oxacillin, the MIC value of isolate 3887 was merely twice as high as the highest MIC value of the rest of the tested population. This is probably due to the plasmid-encoded blaROB-1 resistance mechanism that was observed in this isolate, which is commonly found among Pasteurellaceae and induces primarily resistance towards beta-lactamase susceptible penicillins . It was therefore concluded that, even though the current collection of isolates is relatively small, there was no acquired resistance towards veterinary relevant antimicrobial agents in current equine A. equuli population, except for one isolate exhibiting acquired resistance towards beta-lactamase sensitive penicillins and chloramphenicol. Even though the anamnesis data joining the resistant strain were limited and could not be traced, various treatment periods with penicillin were described, which might be in line with the acquired beta-lactam resistance as observed using both MIC testing and WGS. While the blaROB-1 gene was identified on a plasmid, named pROB3887, resistance markers against aminoglycosides (aph(3″)-Ib), and chloramphenicol (catIII) were present on a different plasmid (pAPH-CAT3887). Both plasmids were previously described in different Pasteurellaceae genera, of which similar plasmids carried a sul2 and aminoglycoside aph(3″)-Ib gene. These genes are often observed together in Actinobacillus, Pasteurella, and Mannheimia species . Also the blaROB-1 beta-lactamase gene was shown to be widely occurring on plasmids within the family of Pasteurellaceae and sometimes collocated with sul2 and aph(3″)-Ib .
In conclusion, our data highlight the added value of long-read nanopore WGS on the identification, virulence gene typing, and antimicrobial resistance testing of equine Actinobacillus equuli isolates at the highest resolution. Next to the availability of new WGS data on Actinobacillus genomospecies 1, Actinobacillus genomospecies 2, and A. arthritidis, our data allowed to deliver in-depth characterization of the genomic landscape of RTX-associated genes within the Actinobacillus genus. Furthermore, we identified two A. equuli specific plasmids, carrying various AMR genes which contribute to acquired AMR and dissemination of resistance in the Pasteurellaceae family.
Availability of data and materials
All data generated or analysed during this study are included in this published article and its supplementary information files.
Rycroft AN, Garside LH (2000) Actinobacillus species and their role in animal disease. Vet J 159:18–36
Henderson B, Diaz M, Martins C, Kenney D, Baird JD, Arroyo LG (2020) Valvular endocarditis in the horse: 20 cases (1993–2020). Can Vet J 61:1290–1294
Christensen H, Bisgaard M, Angen O, Olsen JE (2002) Final classification of Bisgaard taxon 9 as Actinobacillus arthritidis sp. nov. and recognition of a novel genomospecies for equine strains of Actinobacillus lignieresii. Int J Syst Evol Microbiol 52:1239–1246
Donahue JM, Sells SF, Bolin DC (2006) Classification of Actinobacillus spp isolates from horses involved in mare reproductive loss syndrome. Am J Vet Res 67:1426–1432
Kokotovic B, Angen Ø, Bisgaard M (2011) Genetic diversity of Actinobacillus lignieresii isolates from different hosts. Acta Vet Scand 53:6
Murakami M, Shimonishi Y, Hobo S, Niwa H, Ito H (2016) First isolation of Actinobacillus genomospecies 2 in Japan. J Vet Med Sci 78:701–703
Matthews S, Dart AJ, Dowling BA, Hodgson JL, Hodgson DR (2001) Peritonitis associated with Actinobacillus equuli in horses: 51 cases. Aust Vet J 79:536–539
Pusterla N, Jones MEB, Mohr FC, Higgins JK, Mapes S, Jang SS, Samitz EM, Byrne BA (2008) Fatal pulmonary hemorrhage associated with RTX toxin producing Actinobacillus equuli subspecies haemolyticus infection in an adult horse. J Vet Diagn Invest 20:118–121
Layman QD, Rezabek GB, Ramachandran A, Love BC, Confer AW (2014) A retrospective study of equine actinobacillosis cases: 1999–2011. J Vet Diagn Invest 26:365–375
Moyaert H, Decostere A, Baele M, Hermans K, Tavernier P, Chiers K, Haesebrouck F (2007) An unusual Actinobacillus equuli strain isolated from a rabbit with Tyzzer’s disease. Vet Microbiol 124:184–186
Schröttner P, Schultz J, Rudolph W, Gunzer F, Thrümer A, Fitze G, Jacobs E (2013) Actinobacillus equuli ssp. Haemolyticus in a semi-occlusively treated horse bite wound in a 2-year-old girl. GMS Ger Med Sci 11:1–6
Ward CL, Wood JLN, Houghton SB, Mumford JA, Chanter N (1998) Actinobacillus and Pasteurella species isolated from horses with lower airway disease. Vet Rec 143:277–279
Christensen H, Bisgaard M, Olsen JE (2002) Reclassification of equine isolates previously reported as Actinobacillus equuli, variants of A. equuli, Actinobacillus suis or Bisgaard taxon 11 and proposal of A. equuli subsp. equuli subsp. nov. and A. equuli subsp. haemolyticus subsp. nov. Int J Syst Evol Microbiol 52:1569–1576
Kuhnert P, Berthoud H, Straub R, Frey J (2003) Host cell specific activity of RTX toxins from haemolytic Actinobacillus equuli and Actinobacillus suis. Vet Microbiol 92:161–167
Ensink JM, van Klingeren B, Houwers DJ, Klein WR, Vulto AG (1993) In-vitro susceptibility to antimicrobial drugs of bacterial isolates from horses in The Netherlands. Equine Vet J 25:309–313
Thomas E, Thomas V, Wilhelm C (2006) Antibacterial activity of cefquinome against equine bacterial pathogens. Vet Microbiol 115:140–147
Nielsen SS, Bicout DJ, Calistri P, Canali E, Drewe JA, Garin-Bastuji B, Gonzales Rojas JL, Schmidt CG, Herskin M, Michel V, Miranda Chueca MA, Padalino B, Pasquali P, Roberts HC, Sihvonen LH, Spoolder H, Stahl K, Velarde A, Viltrop A, Winckler C, Dewulf J, Guardabassi L, Hilbert F, Mader R, Baldinelli F, Alvarez J (2021) Assessment of animal diseases caused by bacteria resistant to antimicrobials: horses. EFSA J 19:12
Michael GB, Bossé JT, Schwarz S (2018) Antimicrobial resistance in Pasteurellaceae of veterinary origin. Microbiol Spectr 6:3
Bokma J, Vereecke N, De Bleecker K, Callens J, Ribbens S, Nauwynck H, Hasebrouck F, Theuns S, Boyen F, Pardon B (2020) Phylogenomic analysis of Mycoplasma bovis from Belgian veal, dairy and beef herds. Vet Res 51:121
De Witte C, Vereecke N, Theuns S, De Ruyck C, Vercammen F, Bouts T, Boyen F, Nauwynck H, Haesebrouck F (2021) Presence of broad-spectrum beta-lactamase-producing Enterobacteriaceae in zoo mammals. Microorganisms 9:4
Cardenas-Alvarez MX, Restrepo-Montoya D, Bergholz TM (2022) Genome-wide association study of Listeria monocytogenes isolates causing three different clinical outcomes. Microorganisms 10:1934
Brynildsrud O, Bohlin J, Scheffer L, Eldholm V (2016) Rapid scoring of genes in microbial pan-genome-wide association studies with Scoary. Genome Biol 17:238
Ceric O, Tyson GH, Goodman LB, Mitchell PK, Zhang Y, Prarat M, Cui J, Peak L, Scaria J, Antony L, Thomas M, Nemser SH, Anderson R, Thachil AJ, Franklin-Guild RJ, Slavic D, Bommineni YR, Mohan S, Sanchez S, Wilkes R, Sahin O, Hendrix GK, Lubbers B, Reed D, Jenkins T, Roy A, Paulsen D, Mani R, Olsen K, Pace L, Pulido M et al (2019) Enhancing the one health initiative by using whole genome sequencing to monitor antimicrobial resistance of animal pathogens: Vet-LIRN collaborative project with veterinary diagnostic laboratories in United States and Canada. BMC Vet Res 15:130
Marin C, Marco-Jiménez F, Martínez-Priego L, De Marco-Romero G, Soriano-Chirona V, Lorenzo-Rebenaque L, D’auria G (2022) Rapid oxford nanopore technologies MinION sequencing workflow for Campylobacter jejuni identification in broilers on site—a proof-of-concept study. Animals 12:2065
Chen L, Li H, Chen T, Yu L, Guo H, Chen L, Chen Y, Chen M, Zhao J, Yan H, Zhou L, Wang W (2018) Genome-wide DNA methylation and transcriptome changes in Mycobacterium tuberculosis with rifampicin and isoniazid resistance. Int J Clin Exp Pathol 11:3036–3045
Dimitriu T (2022) Evolution of horizontal transmission in antimicrobial resistance plasmids. Microbiology 168:001214
Blair JMA, Webber MA, Baylay AJ, Ogbolu DO, Piddock LJV (2015) Molecular mechanisms of antibiotic resistance. Nat Rev Microbiol 13:42–51
Boueroy P, Wongsurawat T, Jenjaroenpun P, Chopjitt P, Hatrongjit R, Jittapalapong S, Kerdsin A (2022) Plasmidome in mcr-1 harboring carbapenem-resistant enterobacterales isolates from human in Thailand. Sci Rep 12:19051
Bossé JT, Durham AL, Rycroft AN, Kroll JS, Langfor PR (2009) New plasmid tools for genetic analysis of Actinobacillus pleuropneumoniae and other Pasteurellaceae. Appl Environ Microbiol 75:6124–6131
Matter D, Rossano A, Sieber S, Perreten V (2008) Small multidrug resistance plasmids in Actinobacillus porcitonsillarum. Plasmid 59:144–152
Quinn PJ, Carter ME, Markey BK, Carter GR (1994) Clinical veterinary microbiology. Wolfe/Mosby, London
Montagnani C, Pecile P, Moriondo M, Petricci P, Becciani S, Chiappini E, Indolfi G, Rossolini GM, Azzari C, de Martino M, Galli L (2015) First human case of meningitis and sepsis in a child caused by Actinobacillus suis or Actinobacillus equuli. J Clin Microbiol 53:1990–1992
Christensen H, Bisgaard M (2004) Revised definition of Actinobacillus sensu stricto isolated from animals: A review with special emphasis on diagnosis. Vet Microbiol 99:13–30
Koren S, Walenz BP, Berlin K, Miller JR, Bergman NH, Phillipy AM (2017) Canu: Scalable and accurate long-read assembly via adaptive κ-mer weighting and repeat separation. Genome Res 27:722–736
Li H (2018) Minimap2: Pairwise alignment for nucleotide sequences. Bioinformatics 34:3094–3100
Wood DE, Salzberg SL (2014) Kraken: Ultrafast metagenomic sequence classification using exact alignments. Genome Biol 15:R46
Jolley KA, Bliss CM, Bennett JS, Bratcher HB, Brehony C, Colles FM, Wimalarathna H, Harrison OB, Sheppard SK, Cody AJ, Maiden MCJ (2012) Ribosomal multilocus sequence typing: Universal characterization of bacteria from domain to strain. Microbiology 158:1005–1015
Mikheenko A, Prjibelski A, Saveliev V, Antipov D, Gurevich A (2018) Versatile genome assembly evaluation with QUAST-LG. Bioinformatics 34:i142–i150
Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW (2015) CheckM: Assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res 25:1043–1055
Kaas RS, Leekitcharoenphon P, Aarestrup FM, Lund O (2014) Solving the problem of comparing whole bacterial genomes across different sequencing platforms. PLoS ONE 9:e104984
Nedergaard S, Jensen AB, Haubek D, Nørskov-Lauritsen N (2021) Multilocus sequence typing of Aggregatibacter actinomycetemcomitans competently depicts the population structure of the species. Microbiol Spectr 9:e0108521
Davies RL, MacCorquodale R, Reilly S (2004) Characterisation of bovine strains of Pasteurella multocida and comparison with isolates of avian, ovine and porcine origin. Vet Microbiol 99:145–158
Petersen A, Christensen H, Kodjo A, Weiser GC, Bisgaard M (2009) Development of a multilocus sequence typing (MLST) scheme for Mannheimia haemolytica and assessment of the population structure of isolates obtained from cattle and sheep. Infect Genet Evol 9:626–632
Meats E, Feil EJ, Stringer S, Cody AJ, Goldstein R, Kroll JS, Popovic T, Spratt BG (2003) Characterization of encapsulated and noncapsulated Haemophilus influenzae and determination of phylogenetic relationships by multilocus sequence typing. J Clin Microbiol 41:1623–1636
Mullins MA, Register KB, Brunelle BW, Aragon V, Galofré-Mila N, Bayles DO, Jolley KA (2013) A curated public database for multilocus sequence typing (MLST) and analysis of Haemophilus parasuis based on an optimized typing scheme. Vet Microbiol 162:899–906
Jolley KA, Bray JE, Maiden MCJ (2018) Open-access bacterial population genomics: BIGSdb software, the PubMLST.org website and their applications [version 1; referees: 2 approved]. Wellcome Open Res 3:1–20
Chernomor O, Von Haeseler A, Minh BQ (2016) Terrace Aware Data Structure for Phylogenomic Inference from Supermatrices. Syst Biol 65:997–1008
CLSI (2018) Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals - VET01 5th edit.
Kronvall G (2010) Normalized resistance interpretation as a tool for establishing epidemiological MIC susceptibility breakpoints. J Clin Microbiol 48:4445–4452
Interpretation NR Normalized Resistance Interpretation (NRI). http://www.bioscand.se/nri/
Abricate (Seemann T). https://github.com/tseemann/abricate
Chen L, Zheng D, Liu B, Yang J, Jin Q (2016) VFDB 2016: Hierarchical and refined dataset for big data analysis - 10 years on. Nucleic Acids Res 44:D694–D697
Jia B, Raphenya AR, Alcock B, Waglechner N, Guo P, Tsang KK, Lago BA, Dave BM, Peireira S, Sharma AN, Doshi S, Courtot M, Lo R, Williams LE, Frye JG, Elsayegh T, Sardar D, Westman EL, Pawlowski C, Johnson TA, Brinkman FSL, Wrigth GD, McArthur AG (2017) CARD 2017: Expansion and model-centric curation of the comprehensive antibiotic resistance database. Nucleic Acids Res 45:D566–D573
Seemann T (2014) Prokka: rapid prokaryotic genome annotation. Bioinformatics 30:2068–2069
Robertson J, Nash JHE (2018) MOB-suite: software tools for clustering, reconstruction and typing of plasmids from draft assemblies. Microb genomics 4:8
Maul C, Suchowski M, Klose K, Antov V, Pfeffer M, Schwarz B (2020) Detection of Actinobacillus equuli ssp equuli in piglets with purulent polyarthritis and tendovaginitis. Tierarztl Prax Ausgabe G Grosstiere - Nutztiere 48:51–58
Fox GE, Wisotzkey JD, Jurtshuk P (1992) How close is close: 16S rRNA sequence identity may not be sufficient to guarantee species identity. Int J Syst Bacteriol 42:166–170
Blackall PJ, Bisgaard M, Mckenzie RA (1997) Characterisation of Australian isolates of Actinobacillus capsulatus, Actinobacillus equuli, Pasteurella caballi and Bisgaard Taxa 9 and 11. Aust Vet J 75:52–55
Lentsch RH, Wagner JE (1980) Isolation of Actinobacillus lignieresii and Actinobacillus equuli from laboratory rodents. J Clin Microbiol 12:351–354
Ashhurst-Smith C, Norton R, Thoreau W, Peel MM (1998) Actinobacillus equuli septicemia: An unusual zoonotic infection. J Clin Microbiol 36:2789–2790
Dousse F, Thomann A, Brodard I, Korczak BM, Schlatter Y, Kuhnert P, Miserez R, Frey J (2008) Routine phenotypic identification of bacterial species of the family Pasteurellaceae isolated from animals. J Vet Diagn Invest 20:716–724
Kuhnert P, Bisgaard M, Korczak BM, Schwendener S, Christensen H, Frey J (2012) Identification of animal Pasteurellaceae by MALDI-TOF mass spectrometry. J Microbiol Methods 89:1–7
Jin H, You L, Zhao F, Li S, Ma T, Kwok L, Xu H, Sun Z (2022) Hybrid, ultra-deep metagenomic sequencing enables genomic and functional characterization of low-abundance species in the human gut microbiome. Gut Microbes 14:2021790
Sereika M, Petriglieri F, Bygh Nymann Jensen T, Sannikov A, Hoppe M, Nielsen PH, Marshall IPG, Schramm A, Albertsen M (2023) Closed genomes uncover a saltwater species of Candidatus Electronema and shed new light on the boundary between marine and freshwater cable bacteria. ISME J. https://doi.org/10.1038/s41396-023-01372-6
Moss EL, Maghini DG, Bhatt AS (2020) Complete, closed bacterial genomes from microbiomes using nanopore sequencing. Nat Biotechnol 38:701–707
Frey J (1995) Virulence in Actinobacillus pleuropneumoniae and RTX toxins. Trends Microbiol 3:257–261
Frey J, Bosse JT, Chang YF, Cullen JM, Fenwick B, Gerlach GF, Gygi D, Haesebrouck F, Inzana TJ, Jansen R, Kamp EM, Macdonald J, Maclnnes JI, Nicolet J, Rycroft AN, Segers RPAM, Smits MA, Stenbaek E, Struck DK, van den Bosch JF, Willson PJ, Young R (1993) Actinobacillus pleuropneumoniae RTX-toxins: Uniform designation of haemolysins, cytolysins, pleurotoxin and their genes. J Gen Microbiol 139:1723–1728
Benavente C, Fuentealba I (2012) Actinobacillus suis and Actinobacillus equuli, emergent pathogens of septic embolic nephritis, a new challenge for the swine industry. Arch Med Vet 44:99–107
Linhartová I, Bumba L, Mašín J, Basler M, Osicka R, Kamanová J, Procházková K, Adkins I, Hejnová-Holubová J, Sadílková L, Morová J, Sebo P (2010) RTX proteins: a highly diverse family secreted by a common mechanism. FEMS Microbiol Rev 34:1076–1112
Berthoud H, Frey J, Kuhnert P (2002) Characterization of Aqx and its operon: The hemolytic RTX determinant of Actinobacillus equuli. Vet Microbiol 87:159–174
Frey J (2019) RTX toxins of animal pathogens and their role as antigens in vaccines and diagnostics. Toxins (Basel) 11:719
CLSI (2018) Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals - VET08 4th edit.
Scott Weese J (2008) Antimicrobial resistance in companion animals. Anim Health Res Rev 9:169–176
Chang YF, Ma DP, Bai HQ, Young R, Struck DK, Shin SJ, Lein DH (1992) Characterization of plasmids with antimicrobial resistant genes in Pasteurella haemolytica A1. Mitochondrial DNA 3:89–97
The matrix-assisted laser desorption/ionization time-of-flight mass spectrometer was financed by the Research Foundation-Flanders (FWO-Vlaanderen) as part of Hercules Project G0H2516N (grant no. AUGE/15/05). N.V. is funded by a grant from the Flemish Agency for Innovation and Entrepreneurship (Baekeland Mandate HBC.2020.2889).
None of the authors of this paper has a financial or personal relationship with other people or organisations that could inappropriately influence or bias the content of the paper. ST is co-founder and co-owner of PathoSense BV. NV is an employee at PathoSense BV.
Handling editor: Marcelo Gottschalk
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Additional file 1. Overview of used WGS data for Actinobacillus spp. strains, including accessions, genome QC, and excluded strains based on divergence.
Additional file 2. Overview of rMLST analysis results for all used WGS genomes. Whenever percentages do not add up to 100%, not all ribosomal gene sequences could be proper classified or identified in the used genome.
Additional file 4. Overview of identified RTX and RTX toxin-related proteins from all used WGS genomes. Percentages represent protein homologies.
Actinobacillus genus. An ML tree (1000 ultrafast bootstraps) highlighting phenotypic (orange) haemolysis of new Actinobacillus strains in relation to haemolysis-associated genes embedded within all available Actinobacillus sp. genomes, including RTX protein hits across the Pasteurellaceae family. Colour code (yellow-magenta) represents amino acid identity of the identified proteins as compared to the NCBI RTX protein hits. Only hits with amino acid similarity above 60% and 80% coverage are shown, and RTX-like proteins were excluded. A complete overview can be found in Additional file 4.
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Vereecke, N., Vandekerckhove, A., Theuns, S. et al. Whole genome sequencing to study antimicrobial resistance and RTX virulence genes in equine Actinobacillus isolates. Vet Res 54, 33 (2023). https://doi.org/10.1186/s13567-023-01160-2