Limited Genetic Diversity of blaCMY-2-Containing IncI1-pST12 Plasmids from Enterobacteriaceae of Human and Broiler Chicken Origin in The Netherlands
by
, , ,
Evert P.M. den Drijver
1,2,*,†, 
Joep J.J.M. Stohr
1,2,†,
Jaco J. Verweij
1,
Carlo Verhulst
2,
Francisca C. Velkers
3,
Arjan Stegeman
3,
Marjolein F.Q. Kluytmans-van den Bergh
4,5,6,
Jan A.J.W. Kluytmans
2,4,6 and
i---Health Study Group
1 1
Microvida, Laboratory for Medical Microbiology and Immunology, Elisabeth-TweeSteden Hospital, 5000 AS Tilburg, The Netherlands
2
Microvida, Laboratory for Microbiology, Amphia Hospital, 4818 CK Breda, The Netherlands
3
Faculty of Veterinary Medicine, Department of Farm Animal Health, Utrecht University, 3584 CL Utrecht, The Netherlands
4
Department of Infection Control, Amphia Hospital, 4818 CK Breda, The Netherlands
5
Amphia Academy Infectious Disease Foundation, Amphia Hospital, 4818 CK Breda, The Netherlands
6
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, 3508 GA Utrecht, The Netherlands
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Microorganisms 2020, 8(11), 1755; https://doi.org/10.3390/microorganisms8111755
Submission received: 27 October 2020
/
Revised: 6 November 2020
/
Accepted: 7 November 2020
/
Published: 8 November 2020
(This article belongs to the Special Issue Control and Detection of Multiple Antibiotic Resistant Pathogens)
Abstract
:Distinguishing epidemiologically related and unrelated plasmids is essential to confirm plasmid transmission. We compared IncI1–pST12 plasmids from both human and livestock origin and explored the degree of sequence similarity between plasmids from Enterobacteriaceae with different epidemiological links. Short-read sequence data of Enterobacteriaceae cultured from humans and broilers were screened for the presence of both a blaCMY-2 gene and an IncI1–pST12 replicon. Isolates were long-read sequenced on a MinION sequencer (OxfordNanopore Technologies). After plasmid reconstruction using hybrid assembly, pairwise single nucleotide polymorphisms (SNPs) were determined. The plasmids were annotated, and a pan-genome was constructed to compare genes variably present between the different plasmids. Nine Escherichia coli sequences of broiler origin, four Escherichia coli sequences, and one Salmonella enterica sequence of human origin were selected for the current analysis. A circular contig with the IncI1–pST12 replicon and blaCMY-2 gene was extracted from the assembly graph of all fourteen isolates. Analysis of the IncI1–pST12 plasmids revealed a low number of SNP differences (range of 0–9 SNPs). The range of SNP differences overlapped in isolates with different epidemiological links. One-hundred and twelve from a total of 113 genes of the pan-genome were present in all plasmid constructs. Next generation sequencing analysis of blaCMY-2-containing IncI1–pST12 plasmids isolated from Enterobacteriaceae with different epidemiological links show a high degree of sequence similarity in terms of SNP differences and the number of shared genes. Therefore, statements on the horizontal transfer of these plasmids based on genetic identity should be made with caution.
1. Introduction
Antimicrobial resistance in Gram-negative bacteria is a worldwide growing public health problem [1,2]. The gut is an important reservoir for resistant Gram-negative bacteria, both in humans and livestock [3,4]. Antimicrobial resistance in livestock has been suggested as a potential source for resistance in humans, with a growing number of studies published on this potential transmission route for antimicrobial resistance mechanisms in Gram-negative bacteria [5,6,7]. AmpC beta-lactamase-production is an example of these mechanisms as a potential source for 3rd generation cephalosporin resistance in Gram-negative bacteria [8].
Plasmids are an important vector for antimicrobial resistance dissemination with genes for various resistance mechanisms (e.g., AmpC beta-lactamase genes) being located on these mobile genetic elements. Incompatibility group I1 (IncI1) plasmids of the plasmid sequence type (pST) 12 have been associated with the spread of blaCMY-2, which is the most common AmpC beta-lactamase gene [9,10,11]. Recent studies show that the sequence of IncI1 plasmids is highly conserved [12,13,14,15,16]. Most studies to date are based on short-read sequence mechanisms [13,14,16]. However, it remains challenging to study plasmid transmission using short-read sequencing data alone. Repeated sequences, often shared between plasmid and chromosomal DNA, hinder the assembly of the bacterial genome from short-read data, often resulting in contigs of which the origin, either plasmid or chromosomal, cannot be resolved [17]. This limits the interpretation of plasmid transmission by not providing accurate prediction of the total plasmid sequence. Recently, a combination of short- and long-read sequence data provided an accurate analysis, such as shown in a recent study on IncI1 plasmids of pST3 and pST7 [15]. Everything considered, the amount of studies using combined short- and long-read sequencing data of IncI1-pST12 plasmids from human and livestock origin is still limited. The transmission of antimicrobial resistant bacteria within and between domains is predominantly based on the comparison of bacterial chromosome. However, when only typing the bacterial chromosome, the transmission of resistance gene-containing plasmids can go undetected. Although plasmid replicon typing combined with pMLST data can be useful to monitor the spread of plasmids through populations, more accurate distinguishing of related from non-related plasmids based on molecular characteristics (e.g., number of single nucleotide polymorphisms (SNP) differences) is essential for using sequence data to detect plasmid transmission. We hypothesize that a combination of short- and long-read sequence data of blaCMY-2 containing IncI1–pST12 plasmids reveal highly conserved plasmid sequencing, which complicates distinguishing plasmid transmission between epidemiologically related and unrelated isolates. The objective of the current study is to determine the relatedness between IncI1–pST12 plasmids of epidemiologically related and unrelated Enterobacteriaceae isolates from humans and livestock, and we explore the possibility of accurately distinguishing related from unrelated samples based on plasmid sequencing data alone.
2. Materials and Methods
2.1. Collection of Isolates
2.1.1. AmpC E. coli Isolates from i-4-1-Health Dutch-Belgian Cross-Border Project
As part of the i-4-1-Health project, human and broiler samples were collected as described by Kluytmans-van den Bergh et al. [18]. After vortexing, the nylon-flocked swabs in 2 mL Cary–Blair medium (FecalSwab®, Copan Italy, Brescia, Italy) were plated on a blood agar plate (growth control, performed since 2011), and the liquid Cary–Blair medium was mixed in tryptic soy broth (TSB) and incubated for 18–24 h (35–37 °C). Broths were subcultured on an AmpC selective MacConkey agar containing cefotaxime and cefoxtin (1 and 8 mg/mL, respectively) on half the plate and ceftazidime and cefoxitin (1 and 8 mg/mL, respectively) on the other half of the plate (Mediaproducts, Groningen, Germany) [19]. For all oxidase-negative isolates that grew on either side of the selective agar plates, species identification was performed by automated mass spectrometry systems (VitekMS, bioMérieux, Marcy l’Etoile, France). Susceptibility testing was performed using Vitek 2 (bioMérieux, Marcy l’Etoile, France). The presence of AmpC in all oxidase-negative isolates was phenotypically confirmed using the D68C AmpC & ESBL Detection Set (Mastdiscs, Mastgroup Ltd., Bootle, UK) and interpreted according to the manufacturer’s instructions. All phenotypically confirmed isolates were sequenced using an Illumina MiSeq sequencer (Illumina, San Diego, CA, USA). DNA isolation and sequencing were performed as described by Coolen et al. [20]. De novo assembly and error correction were performed using SPAdes version 3.9.1 [21].
2.1.2. AmpC E. coli Isolates from Amphia Prevalence Screening
pampC gene containing E. coli isolates were selected from a prevalence screening, which had been performed in the Amphia hospital described by Den Drijver et al. [22]. Rectal swabs taken from hospital patients were pre-enriched using selective TSB containing cefotaxime (0.25 mg/L) and vancomycin (8 mg/L) and subsequently cultured on a MacConkey agar plate containing cefotaxime (1 mg/L) or a MacConkey double agar plate containing cefotaxime and cefoxtin (1 and 8 mg/mL, respectively) on half the plate and ceftazidime and cefoxitin (1 and 8 mg/mL, respectively) on the other half of the plate (Mediaproducts, Groningen) [19]. For all oxidase-negative isolates that grew on either side of the selective agar plates, species identification was performed by automated mass spectrometry systems (VitekMS, bioMérieux, Marcy l’Etoile, France). Susceptibility testing was performed using Vitek 2 (bioMérieux, Marcy l’Etoile, France). The presence of AmpC in all oxidase-negative isolates was phenotypically confirmed using the D68C AmpC & ESBL Detection Set (Mastdiscs, Mastgroup Ltd., Bootle, UK) and interpreted according to the manufacturer’s instructions. All phenotypically confirmed isolates were sequenced in the University of Groningen Medical Center (UMCG) using MiSeq (Illumina, San Diego, CA, USA) and assembled with CLC Genomics Workbench 9.0, 9.0.1 or 9.5.2 (Qiagen, Hilden, Germany) as was previously described in more detail by Kluytmans-van den Bergh et al. [23].
2.1.3. pAmpC-encoding Clinical Isolates from Elisabeth-Tweesteden Hospital
Suspected pampC gene containing E. coli isolates from blood cultures were selected retrospectively from our laboratory database based upon the presence of a phenotype (cefoxitin minimal inhibitory concentration (MIC) > 8 mg/L and/or cefotaxime MIC ≥ 1mg/L and/or ceftazidime MIC ≥ 1mg/L. One Salmonella enterica serotype Kentucky isolate from a fecal sample was selected from our laboratory database based upon the presence of an AmpC suspected phenotype (cefoxitin MIC > 8 mg/L and/or cefotaxime MIC ≥ 1mg/L and/or ceftazidime MIC ≥ 1mg/L). The isolates were recultured from deep frozen samples on blood agar and identified using the MALDI-TOF MS (BD Diagnostic Systems, Sparks, MD, USA). Susceptibility testing was performed using a Phoenix Automated Microbiology System (BD Diagnostic Systems, Sparks, MD, USA). The isolates were sequenced using an Illumina MiSeq sequencer (Illumina, San Diego, CA, USA). DNA isolation and sequencing were performed as described by Coolen et al. [20]. De novo assembly and error correction were performed using SPAdes version 3.9.1 [21].
2.2. Whole-Genome Bioinformatics Analysis of Short-Read Sequencing Data
The presence of acquired resistance genes was identified by uploading assembled genomes to the ResFinder web service of the Center for Genomic Epidemiology (version 3.1) [24]. The presence of plasmid replicons and the typing of a specific IncI plasmid was performed using pMLST (version 2.0) [25]. The genomes were selected based on a 100% match to blaCMY-2 and IncI-pST12. Typing of a specific multi locus sequence type (MLST) was performed using the MLST web service of the Center for Genomic Epidemiology (version 2.0), and fim typing was performed using FimTyper (version 1.0), Center for Genomic Epidemiology [26,27].
2.3. Long-Read Sequencing and Hybrid Assembly
No more than two isolates of the same flock or patient belonging to the same MLST were selected for further long-read sequencing.
All isolates were long-read sequenced on a MinION sequencer using the FLO-MIN106D flow cell and the Rapid Barcoding Sequencing Kit SQK RBK004 according to the standard protocol provided by the manufacturer (Oxford Nanopore Technologies, Oxford, UK). A hybrid assembly of long-read and short-read sequence data was performed using Unicycler v.0.8.4 [28]. Whole-genome MLST (wgMLST) (core and accessory genome) was performed for all isolates using Ridom SeqSphere+, version 4.1.9 (Ridom, Münster, Germany). Species-specific wgMLST typing schemes were used as described previously [23]. The pairwise genetic difference between isolates of the same species was calculated by dividing the total number of allele differences by the total number of shared alleles from the typing scheme present in both sequences, using a pairwise ignoring missing values approach. Genetic relatedness was determined using the thresholds for wgMLST-based genetic distance of 0.0095, as described previously [23].
2.4. Plasmid Analysis
The genomes created using the hybrid assembly were uploaded to the online bioinformatics tools ResFinder v.2.1, VirulenceFinder v.1.2 and PlasmidFinder v.1.2. (Center for Genomic Epidemiology, Technical University of Denmark, Lingby, Denmark) [24,25,29]. Circular components created by the hybrid assembly that were smaller than 1000 kb and that contained an IncI1-pST12 plasmid replicon and a blaCMY-2 gene were extracted from the assembly graph using BANDAGE v0.8.1. [30]. All extracted plasmid components were annotated using Prokka v1.13.3 [31]. Using snippy v4.4.59 (https://github.com/tseemann/snippy), the number of single nucleotide polymorphisms (SNPs) was determined between the extracted plasmid components using a blaCMY-2 gene containing IncI1–pST12 plasmid extracted from the GenBank (accession number: MH472638.1) as reference [12]. A pan-genome was constructed, and a gene presence or absence was determined for all extracted plasmid components using roary v3.12 [32]. All extracted plasmids consisting of a single circular contig were aligned using GView 1.7 [33] and progressiveMAUVE v2.4.0 to detect possible rearrangements [34]. If a hypervariable region is identified, the sequence of this region and its flanking regions are extracted using biopython v1.37. Moreover, segments (A, B, C, D) and flanking genes (PilV and rci) of a previously described hypervariable shufflon region of the IncI1 replicon containing plasmids (GenBank accession nr: AB027308.1) were BLAST searched in the extracted hypervariable regions [35,36].
2.5. Classification of Pairwise Comparisons
Pairwise comparisons of assembled plasmids were classified according to the known epidemiological link between the isolates: (i) same sample; (ii) same ward/flock but different sample; (iii) same location (hospital or farm) but different ward/flock and sample; (iv) same domain (human or broiler) but different location, ward/flock and sample; and (v) no known epidemiological link, i.e., different domain, location, ward/floc, and sample.
2.6. Ethical Statement
The I-4-1-Healt study was judged to be beyond the scope of the Dutch Medical Research Involving Human Subjects Act and the Belgian Law on Experiments on Humans, dated 7 May 2004. Written or verbal informed consent for data collection and taking a fecal, perianal, or gastrointestinal stoma swab for microbiological culture is obtained from all participants or their legal representatives. For the veterinary domain, approval by an animal welfare body is not required. All human data are anonymized, i.e., data cannot be directly or indirectly related to their source. Data on institutions and farms are pseudonymized, i.e., identifying information is replaced by a code, and a key file that links this code to the identifying information is kept separate from the research data.
3. Results
3.1. Isolate Characteristics
A total of 2508 human cases from four different hospitals and 119 broilers from 14 different farms were screened for the presence of plasmid encoded AmpC genes, e.g blaCMY-2 (Table S1). In 107 isolates, an AmpC phenotype was confirmed based on the D68C AmpC & ESBL Detection Set. Sixteen of 107 isolates contained both an IncI1 pST12 and a blaCMY-2 gene (Table S1). Based upon the above-mentioned selection criteria, fourteen isolates were included for long-read sequencing analysis, i.e., thirteen E. coli and one Salmonella enterica, serotype Kentucky (Table 1). Nine of the E. coli isolates were from one broiler farm; the other isolates were from human origin. The E. coli isolates included five different MLSTs and fim types. Based on wgMLST analysis, four different clusters could be identified (Figure 1, Table 1, and Table S2). Additional information regarding antimicrobial resistance phenotype and genotype of the included isolates is provided in Table S3.
3.2. Plasmid Analysis
In the hybrid assembly of fourteen sequences, both the IncI1–pST12 replicon gene and blaCMY-2 gene were located on a single circular contig ranging in size from 98,410 to 98,999 bp. No additional antimicrobial resistance or virulence genes were detected on any of the extracted plasmids. The number of SNP’s detected between the fourteen plasmids ranged from zero to nine SNPs (Table 2). When comparing the plasmids extracted from the selected isolates to a publicly available IncI1–pST12 blaCMY-2 gene-containing plasmid extracted from the GenBank (accession number: MH472638.1), the number of SNPs detected ranged from 0 to 7 (Table 2). A small SNP difference was seen between epidemiologically related strains with a maximum difference of two SNPs. The range of SNP differences overlapped between epidemiologically related and unrelated plasmids (Table 3). The median number of SNP differences of plasmids in a different domain or different location, but the same domain was higher than in the other three pairwise comparison groups.
The total number of genes detected in the fourteen plasmids was 113, of which 112 were detected in all plasmids. One gene was present only in one plasmid (pEC11) and encoded for a hypothetical protein. An alignment of coding regions of the fourteen plasmids revealed no rearrangements between the described plasmids (Figure 2). However, progressive MAUVE alignment of non-coding regions revealed a small highly variable region of 519 to 1096 bp in all plasmids (Figure S1). This hypervariable region and approximately 2125 bp of the flanking sequence were extracted from all plasmids. The genes PilV and rci were detected in the flanking regions of the hypervariable region of all plasmids (Table 4). Moreover, in all plasmids, either one (B) or two (A, B) shufflon segments were detected in the extracted hypervariable region of the various plasmids (Table 4). No rearrangements were detected in any of the other regions.
4. Discussion
The current study included E. coli isolates of various sequence types and a S. enterica isolate, which were from both human and broiler origin. Plasmid analysis based on short- and long-read sequence data of blaCMY-2 containing IncI1-pST12 plasmids from the included isolates revealed a low number of SNP differences and a high number of shared genes between the various plasmids extracted. Despite the tendency of median SNP increase from epidemiologically related to unrelated plasmids, the range in number of SNPs detected overlapped between every classified epidemiological link in the current study. A small SNP difference was seen between epidemiologically related strains with a maximum difference of two SNPs. Furthermore, only one gene was variably present between the different plasmids, and no rearrangements were observed apart from a small, highly variable region. This area is the formerly described highly variable shufflon region at the C-terminal end of the PilV protein [35,36].
A high degree of similarity between IncI1–pST12 plasmids was previously reported [12,13,14,16]. However, all of the studies either contained only plasmids extracted from one E. coli sequence type (ST131) [12] or the included plasmids were primarily of poultry origin [14]. All of the studies used either gene presence/absence-based or SNP-based analysis, but not both, possibly missing subtle differences between various plasmids. Shirakawa et al. used a combination of short-read sequence data of different blaCMY-2-containing plasmids from Japanese poultry and human origin, together with plasmid sequence data retrieved from the National Center for Biotechnology Information nucleotide database (https://www.ncbi.nlm.nih.gov/) to perform an extensive plasmid comparative analysis. Their clustering analysis showed a high similarity among the IncI1–pST12 plasmids as well; however, this study did not provide further detail on the SNP differences of possible rearrangements within the plasmid sequences. Moreover, these studies predominately used in silico reference-based plasmid reconstructions of short-read sequence data rather than performing a hybrid assembly of both short- and long-read sequence data. A recent study by Valcek et al. on IncI1–pST3 and IncI1–pST7 plasmids showed that using combined long-read and short-read sequencing data improves the accuracy of a full plasmid analysis, e.g., of rearrangements [15]. The current study is the first study describing plasmid differences using both gene presence/absence-based and SNP-based analysis. Moreover, rearrangements between the different plasmids could be detected such as those shown in the hypervariable region, which were missed in previous studies based on only short-read sequences.
Several studies have described outbreaks with blaCMY-2-harboring Enterobacteriaceae [37,38,39,40]. Since the blaCMY-2 is predominantly located on plasmids, horizontal transfer of the plasmid in an outbreak can go undetected if only typing of the bacterial chromosome is performed. Distinguishing epidemiologically related and unrelated plasmids is essential to confirm plasmid transmission in an outbreak. Therefore, statements on the horizontal transfer of these plasmids based on genetic identity should be made with caution. However, given the conservation of the IncI1–pST12 plasmids, they could instead be used as a tool to monitor the speed and breadth of spread of these plasmids through populations, either different in place of origin or bacterial host.
The current study is the first to explore blaCMY-2-containing IncI1–pST12 plasmids from related and unrelated isolates, using combined short- and long-read sequencing data. Moreover, this study includes isolates from different species, sequence types, and domains, both from human and broiler origin. Two different comparison techniques, either gene presence/absence and SNP differences, were used. Furthermore, combining long-read and short-read sequence data provided full plasmid analysis, including the presence of rearrangements.
By combining the isolate collections from three different studies, we screened a relatively large amount of human and broiler cases. However, due to low prevalence of blaCMY-2 in the Netherlands, our sample size remained relatively small. This results in the main limitation of the current study, as the small sample size precludes the use of statistical test and caution must be applied, as the findings should be confirmed in a study with a larger sample size. Preferably, such a study should include isolates of different species, sequence types, and origin of isolation containing IncI1–pST12 plasmids. Furthermore, the current study only included plasmids of broilers isolated in one farm; therefore, other plasmids of veterinary origin should be added in future studies to confirm our findings.
In conclusion, IncI1–pST12 plasmids of epidemiologically related and unrelated Enterobacteriaceae of both human and broiler origin in the current explorative study show a high degree of sequence similarity in terms of SNP differences and the number of shared genes.
Supplementary Materials
Supplementary materials can be found at https://www.mdpi.com/2076-2607/8/11/1755/s1, Tables S1–S3, and Figure S1.
Author Contributions
Conceptualization, E.P.M.d.D., J.J.J.M.S., J.J.V. and J.A.J.W.K.; methodology, E.P.M.d.D. and J.J.J.M.S.; software, J.J.J.M.S.; formal analysis, E.P.M.d.D. and J.J.J.M.S.; investigation, E.P.M.d.D., J.J.J.M.S., C.V. and F.C.V.; resources, J.J.V., A.S., M.F.Q.K.-v.d.B. and J.A.J.W.K.; data curation, E.P.M.d.D. and J.J.J.M.S.; writing—original draft preparation, E.P.M.d.D. and J.J.J.M.S.; writing—review and editing, J.J.V., C.V., F.C.V., A.S., M.F.Q.K.-v.d.B. and J.A.J.W.K.; visualization, J.J.J.M.S.; supervision, J.J.V. and J.A.J.W.K.; project administration, M.F.Q.K.-v.d.B. and J.A.J.W.K.; funding acquisition, J.A.J.W.K. All authors have read and agreed to the published version of the manuscript.
Funding
The i-4-1-Health project was financed by the Interreg V Flanders-The Netherlands program, the cross-border cooperation program with financial support from the European Regional Development Fund (ERDF). Additional financial support was received from the Dutch Ministry of Health, Welfare and Sport, the Dutch Ministry of Economic Affairs, the Province of Noord-Brabant, the Belgian Department of Agriculture and Fisheries, the Province of Antwerp and the Province of East-Flanders. Selective and non-selective agar plates, ETEST® strips and VITEK® 2 AST cards were provided by bioMérieux (Marcy l’Etoile, France); FecalSwabs® and tryptic soy broths are provided by Copan Italy (Brescia, Italy). The authors were free to publish the results from the project without interference from the funding bodies, bioMérieux or Copan Italy.
Acknowledgments
We are grateful to the collaborators from the participating laboratories, hospitals, and livestock farms for their contribution to the collection of the microbiological and epidemiological data. i-4-1-Health Study Group. Lieke van Alphen (Maastricht University Medical Center+, Maastricht, The Netherlands), Nicole van den Braak (Avans University of Applied Sciences, Breda, The Netherlands), Caroline Broucke (Agency for Care and Health, Brussels, Belgium), Anton Buiting (Elisabeth-TweeSteden Hospital, Tilburg, The Netherlands), Liselotte Coorevits (Ghent University Hospital, Ghent, Belgium), Sara Dequeker (Agency for Care and Health, Brussels, Belgium and Sciensano, Brussels, Belgium), Jeroen Dewulf (Ghent University, Ghent, Belgium), Wouter Dhaeze (Agency for Care and Health, Brussels, Belgium), Bram Diederen (ZorgSaam Hospital, Terneuzen, The Netherlands), Helen Ewalts (Regional Public Health Service Hart voor Brabant, Tilburg, The Netherlands), Herman Goossens (University of Antwerp, Antwerpen, Belgium and Antwerp University Hospital, Antwerp, Belgium), Inge Gyssens (Hasselt University, Hasselt, Belgium), Casper den Heijer (Regional Public Health Service ZuidLimburg, Heerlen, The Netherlands), Christian Hoebe (Maastricht University Medical Center+, Maastricht, The Netherlands and Regional Public Health Service Zuid-Limburg, Heerlen, Casper Jamin (Maastricht University Medical Center+, Maastricht, The Netherlands), Patricia Jansingh (Regional Public Health Service Limburg Noord, Venlo, The Netherlands), Jan Kluytmans (Amphia Hospital, Breda, the Netherlands and University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands), Marjolein Kluytmans-van den Bergh (Amphia Hospital, Breda, the Netherlands and University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands), Stefanie van Koeveringe (Antwerp University Hospital, Antwerp, Belgium), Sien De Koster (University of Antwerp, Antwerp, Belgium), Christine Lammens (University of Antwerp, Antwerp, Belgium), Isabel Leroux-Roels (Ghent University Hospital, Ghent, Belgium), Hanna Masson (Agency for Care and Health, Brussel, Belgium), Ellen Nieuwkoop (Elisabeth-TweeSteden Hospital, Tilburg, The Netherlands), Anita van Oosten (Admiraal De Ruyter Hospital, Goes, The Netherlands), Natascha Perales Selva (Antwerp University Hospital, Antwerp, Belgium), Merel Postma (Ghent University, Ghent, Belgium), Stijn Raven (Regional Public Health Service West-Brabant, Breda, The Netherlands), Veroniek Saegeman (University Hospitals Leuven, Leuven, Belgium), Paul Savelkoul (Maastricht University Medical Center+, Maastricht, The Netherlands), Annette Schuermans (University Hospitals Leuven, Leuven, Belgium), Nathalie Sleeckx (Experimental Poultry Centre, Geel, Belgium), Arjan Stegeman (Utrecht University, Utrecht, The Netherlands), Tijs Tobias (Utrecht University, Utrecht, The Netherlands), Paulien Tolsma (Regional Public Health Service Brabant Zuid-Oost, Eindhoven, The Netherlands), Jacobien Veenemans (Admiraal De Ruyter Hospital, Goes, The Netherlands), Dewi van der Vegt (PAMM Laboratory for Pathology and Medical Microbiology, Veldhoven, The Netherlands), Francisca Velkers (Utrecht University, Utrecht, The Netherlands), Martine Verelst (University Hospitals Leuven, Leuven, Belgium), Carlo Verhulst (Amphia Hospital, Breda, The Netherlands), Pascal De Waegemaeker (Ghent University Hospital, Ghent, Belgium), Veronica Weterings (Amphia Hospital, Breda, The Netherlands), Clementine Wijkmans (Regional Public Health Service Hart voor Brabant, Tilburg, The Netherlands), Patricia Willemse-Smits (Elkerliek Hospital, Helmond, The Netherlands), Ina Willemsen (Amphia Hospital, Breda, The Netherlands).
Conflicts of Interest
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
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Figure 1.
Neighbor-joining tree representing the whole-genome multi locus sequence type (wgMLST) analysis of the different E. coli isolates included in the study. Isolates belonging to the same clonal clusters are represented in the identical colors.
Figure 1.
Neighbor-joining tree representing the whole-genome multi locus sequence type (wgMLST) analysis of the different E. coli isolates included in the study. Isolates belonging to the same clonal clusters are represented in the identical colors.
Figure 2.
GView alignment of the various plasmid sequences. Each arrow represents a coding sequence and not necessarily transcriptional direction; gene names are depicted as generated by prokka.
Figure 2.
GView alignment of the various plasmid sequences. Each arrow represents a coding sequence and not necessarily transcriptional direction; gene names are depicted as generated by prokka.
Table 1.
Descriptive characteristics of fourteen IncI1–pST12 and blaCMY-2 containing isolates.
| Isolate | Species | Multilocus ST a | wgMLST Cluster | Fim | Origin | Sample Location | Flock or Ward | Sample Source | Month and Year of Isolation | Accession No. |
|---|---|---|---|---|---|---|---|---|---|---|
| EC1 | E. coli | ST665 | 1 | fimH30 | Broiler | Farm 1 | Flock 1 | Fecal swab 1 | Nov 2017 | ERS4591617 |
| EC2 | E. coli | ST665 | 1 | fimH30 | Broiler | Farm 1 | Flock 1 | Fecal swab 2 | Nov 2017 | ERS4591618 |
| EC3 | E. coli | ST665 | 1 | fimH30 | Broiler | Farm 1 | Flock 2 | Fecal swab 3 | Nov 2017 | ERS4591619 |
| EC4 | E. coli | ST665 | 1 | fimH30 | Broiler | Farm 1 | Flock 2 | Fecal swab 4 | Nov 2017 | ERS4591620 |
| EC5 | E. coli | ST665 | 1 | fimH30 | Broiler | Farm 1 | Flock 3 | Fecal swab 5 | Nov 2017 | ERS4591621 |
| EC6 | E. coli | ST665 | 1 | fimH30 | Broiler | Farm 1 | Flock 3 | Fecal swab 6 | Nov 2017 | ERS4591622 |
| EC7 | E. coli | ST86 | 2 | fimH289 | Broiler | Farm 1 | Flock 3 | Fecal swab 5 | Nov 2017 | ERS4591623 |
| EC8 | E. coli | ST86 | 2 | fimH289 | Broiler | Farm 1 | Flock 3 | Fecal swab 7 | Nov 2017 | ERS4591624 |
| EC9 | E. coli | ST6856 | fimH71 | Broiler | Farm 1 | Flock 3 | Fecal swab 6 | Nov 2017 | ERS4591625 | |
| EC10 | E. coli | ST131 | 3 | fimH22 | Human | Hospital 1 | Ward 1 | Blood 1 | Oct 2013 | ERS4591626 |
| EC11 | E. coli | ST131 | 3 | fimH22 | Human | Hospital 2 | Ward 1 | Blood 2 | Jul 2014 | ERS4591627 |
| EC12 | E. coli | ST973 | 4 | fimH95 | Human | Hospital 3 | Ward 1 | Rectal swab 1 | Dec 2017 | ERS4591628 |
| EC13 | E. coli | ST973 | 4 | fimH95 | Human | Hospital 3 | Ward 2 | Rectal swab 2 | Dec 2017 | ERS4591629 |
| SE1 | Salmonella enteritidis | - | - | Human | Primary care unit | n.a. | Feces | Aug 2018 | ERS4591630 |
a Multilocus Sequence Type (ST) according to Enterobase (http://enterobase.warwick.ac.uk/).
Table 2.
Number of single nucleotide polymorphisms (SNPs) detected between the 14 extracted plasmids and GenBank reference plasmid MH472638.1.
Table 2.
Number of single nucleotide polymorphisms (SNPs) detected between the 14 extracted plasmids and GenBank reference plasmid MH472638.1.
| pEC1 | pEC2 | pEC3 | pEC4 | pEC5 | pEC6 | pEC7 | pEC8 | pEC9 | pEC10 | pEC11 | pEC12 | pEC13 | pSE1 | MH472638.1 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| pEC1 | 0 | 2 | 2 | 2 | 2 | 2 | 3 | 3 | 3 | 3 | 3 | 9 | 8 | 6 | 2 |
| pEC2 | 2 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 7 | 6 | 4 | 0 |
| pEC3 | 2 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 7 | 6 | 4 | 0 |
| pEC4 | 2 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 7 | 6 | 4 | 0 |
| pEC5 | 2 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 7 | 6 | 4 | 0 |
| pEC6 | 2 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 7 | 6 | 4 | 0 |
| pEC7 | 3 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 2 | 2 | 8 | 7 | 5 | 1 |
| pEC8 | 3 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 2 | 2 | 8 | 7 | 5 | 1 |
| pEC9 | 3 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 2 | 2 | 8 | 7 | 5 | 1 |
| pEC10 | 3 | 1 | 1 | 1 | 1 | 1 | 2 | 2 | 2 | 0 | 0 | 8 | 7 | 5 | 1 |
| pEC11 | 3 | 1 | 1 | 1 | 1 | 1 | 2 | 2 | 2 | 0 | 0 | 8 | 7 | 5 | 1 |
| pEC12 | 9 | 7 | 7 | 7 | 7 | 7 | 8 | 8 | 8 | 8 | 8 | 0 | 1 | 5 | 7 |
| pEC13 | 8 | 6 | 6 | 6 | 6 | 6 | 7 | 7 | 7 | 7 | 7 | 1 | 0 | 4 | 6 |
| pSE1 | 6 | 4 | 4 | 4 | 4 | 4 | 5 | 5 | 5 | 5 | 5 | 5 | 4 | 0 | 4 |
| MH472638.1 | 2 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 7 | 6 | 4 | 0 |
Table 3.
Median and range of SNP differences in pairwise comparisons per epidemiological link.
| SNP Differences | |||
|---|---|---|---|
| n of Pairwise Comparisons | Median | Range | |
| Same sample | 2 | 1 | 1 |
| Same flock, different sample | 10 | 0.5 | 0–2 |
| Same location, different ward/flock | 25 | 1 | 0–3 |
| Same domain, different location | 9 | 5 | 0–8 |
| Different domain | 45 | 4 | 1–9 |
Table 4.
Shufflon segments in variable regions of the different plasmids included (direction: ′5–′3).
Table 4.
Shufflon segments in variable regions of the different plasmids included (direction: ′5–′3).
| Plasmid | Shufflon Segments | |||
|---|---|---|---|---|
| pEC1 | PilV | A | B | rci |
| pEC2 | PilV | A | B | rci |
| pEC3 | PilV | A | B | rci |
| pEC4 | PilV | B | rci | |
| pEC5 | PilV | B | rci | |
| pEC6 | PilV | A | B | rci |
| pEC7 | PilV | B | rci | |
| pEC8 | PilV | A | B | rci |
| pEC9 | PilV | A | B | rci |
| pEC10 | PilV | A | B | rci |
| pEC11 | PilV | B | A | rci |
| pEC12 | PilV | B | rci | |
| pEC13 | PilV | B | rci | |
| pSE1 | PilV | B | rci | |
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Drijver, E.P.M.d.; Stohr, J.J.J.M.; Verweij, J.J.; Verhulst, C.; Velkers, F.C.; Stegeman, A.; Bergh, M.F.Q.K.-v.d.; Kluytmans, J.A.J.W.; Group, i.---H.S. Limited Genetic Diversity of blaCMY-2-Containing IncI1-pST12 Plasmids from Enterobacteriaceae of Human and Broiler Chicken Origin in The Netherlands. Microorganisms 2020, 8, 1755. https://doi.org/10.3390/microorganisms8111755
AMA Style
Drijver EPMd, Stohr JJJM, Verweij JJ, Verhulst C, Velkers FC, Stegeman A, Bergh MFQK-vd, Kluytmans JAJW, Group i---HS. Limited Genetic Diversity of blaCMY-2-Containing IncI1-pST12 Plasmids from Enterobacteriaceae of Human and Broiler Chicken Origin in The Netherlands. Microorganisms. 2020; 8(11):1755. https://doi.org/10.3390/microorganisms8111755
Chicago/Turabian StyleDrijver, Evert P.M. den, Joep J.J.M. Stohr, Jaco J. Verweij, Carlo Verhulst, Francisca C. Velkers, Arjan Stegeman, Marjolein F.Q. Kluytmans-van den Bergh, Jan A.J.W. Kluytmans, and i---Health Study Group. 2020. "Limited Genetic Diversity of blaCMY-2-Containing IncI1-pST12 Plasmids from Enterobacteriaceae of Human and Broiler Chicken Origin in The Netherlands" Microorganisms 8, no. 11: 1755. https://doi.org/10.3390/microorganisms8111755
APA StyleDrijver, E. P. M. d., Stohr, J. J. J. M., Verweij, J. J., Verhulst, C., Velkers, F. C., Stegeman, A., Bergh, M. F. Q. K. -v. d., Kluytmans, J. A. J. W., & Group, i. ---H. S. (2020). Limited Genetic Diversity of blaCMY-2-Containing IncI1-pST12 Plasmids from Enterobacteriaceae of Human and Broiler Chicken Origin in The Netherlands. Microorganisms, 8(11), 1755. https://doi.org/10.3390/microorganisms8111755
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