Introduction

Years of misuse and overuse of antibiotics in the livestock and poultry industry have resulted in many irreversible changes, not only in the animal production sector but also in the everyday life of each human. Extensive, uncontrolled antibiotic use results in the presence of low, sub-inhibitory concentrations in the tissues and guts of treated animals (Lim et al. 2020) and the environment (Khan et al. 2013). The mechanisms of action of sublethal levels of antibiotics on bacteria are described in detail by Andersson and Hughes (2014). In food-producing animals, antibiotic use affects the functions of enteric bacteria and can temporarily increase antibiotic resistance in the fecal microbiome (Chee-Sanford et al. 2009; Broom 2017). The chronic application of such sub-therapeutic doses favors the selection of antibiotic-resistant bacteria (ARB) by promoting their growth or introducing de novo mutations. The resistance mechanism of a particular ARB depends on its harbored antibiotic resistance genes (ARGs). The majority of ARG transmission occurs via horizontal gene transfer (HGT), whereby mobile genetic elements (MGEs), such as plasmids or transposons coding for ARG, are exchanged between bacterial species, even those not closely related (Redondo-Salvo et al. 2020).

Escherichia coli is classified as a rod‐shaped, non-sporulating, facultatively anaerobic Gram‐negative bacteria belonging to the family Enterobacteriaceae. This species mainly lives in the lower intestinal tract of warm‐blooded animals, including livestock and poultry, and is often excreted into the environment with urine and feces. In addition to being a widespread gut commensal of vertebrates, E. coli is also a versatile pathogen, killing more than two million humans annually through intraintestinal and extraintestinal diseases (Tenaillon et al. 2010). The presence of E. coli in the natural environment has long been considered an indicator of recent fecal contamination (Anjum et al. 2021), but many studies show that many strains can survive and proliferate in such conditions and be incorporated into indigenous microbial communities (Jang et al. 2017; Marano et al. 2020).

The presence of E. coli and other commensal bacteria in the animals’ gut can be beneficial. Some help animals to digest complex molecules, which cannot otherwise be assimilated, thus producing vitamin K or certain B vitamins essential for the host; others prevent gut colonization by competing with harmful microorganisms, i.e., by consuming available nutrients, occupying physical space, and producing substances such as bacteriocins that inhibit the growth of pathogens. They can also play an essential role in the development and regulation of the immune system by stimulating it and helping it to differentiate between harmful and non-harmful organisms (Tenaillon et al. 2010; Abt and Pamer 2014; Hanning and Diaz-Sanchez 2015).

However, some strains of E. coli can be pathogenic, causing severe diseases in humans and animals. Infection with pathogenic E. coli strain can manifest in enteric or diarrheal disease, urinary tract infections, and meningitis or sepsis. The intestinal symptoms may be caused by EIEC (enteroinvasive E. coli), EHEC (enterohaemorrhagic E. coli), ETEC (enterotoxigenic E. coli), EPEC (enteropathogenic E. coli), DAEC (diffusely adherent E. coli), and EAEC (enteroaggregative E. coli) (Kaper et al. 2004). The most common extraintestinal E. coli infection is urinary tract infection, caused by UPEC (uropathogenic E. coli); however, the pathotype MNEC (meningitis-associated E. coli), responsible for meningitis and sepsis, is becoming increasingly prevalent. EPEC, EHEC, and ETEC can also cause animal disease using the same virulence factors present in human strains and colonization factors unique to animals. The avian pathogenic E. coli (APEC) is an additional animal pathotype, causing extraintestinal infections of poultry, primarily respiratory infections, pericarditis, and septicemia (Kaper et al. 2004).

The aim of the study was to examine the population of E. coli strains isolated from poultry (from intensive rearing facilities) feces. Based on the results of antibiotic susceptibility testing and plasmid profile characteristics, the most prevalent strains were subjected to sequencing with NovaSeq 6000 (Illumina) and MinIon (Oxford Nanopore) platforms for full plasmid structure recovery. Two representative multi-drug resistance (MDR) E. coli isolates were found to harbor three resistance plasmids (R-plasmids) that had not previously been reported in Poland: pECmdr13.3 (IncX1), pECmdr13.2, and pECmdr14.1 (IncC). These were found to carry genes coding for resistance to tetracyclines, aminoglycosides, β-lactams, sulfonamides, fluoroquinolones, and phenicol; the last two were accompanied by mercury resistance.

Materials and methods

Isolation of E. coli strains

Chicken waste was collected from a commercial chicken meat production facility located in the central part of Poland (Masovian district). The samples were taken from two points in the production chain: CM, chicken manure from laying hens, and CL, chicken litter from broilers. Sampling details were described previously by Błażejewska et al. (2022). Samples of chicken litter and manure (0.1 kg per sampling point) were collected from 10 locations for each waste type: the former in the chicken coop and the latter under the cages. The samples were then divided by type and pooled into one representative sample for each type for further analysis. All polled collections were taken in triplicate. The farm owners agreed to manure sampling.

The collected samples were transported to the laboratory in a refrigerator, stored at 4 °C, and processed within 24 h. To isolate antibiotic-resistant E. coli strains, the manure sample was first enriched in Luria Bertani broth (Biomaxima, Lublin, Poland) by adding 1 g of feces to 9 mL of liquid medium. The cultures were incubated at 30 °C and 37 °C for 24 h and 48 h, respectively. After incubation, the bacterial suspensions were diluted (10−1, 10−2, and 10−3), and 100 µL of undiluted sample and each dilution were plated on Eosin Methylene Blue agar (Biomaxima, Lublin, Poland) and MacConkey agar (Biomaxima, Lublin, Poland) supplemented with imipenem (16 mg/L) (Merck, Darmstadt, Germany) to search for carbapenem resistance phenotype; the same dilutions were also asdded to Eosin Methylene Blue agar and MacConkey agar both supplemented with cefotaxime (4 mg/L) (Merck, Darmstadt, Germany) for the extended-spectrum beta-lactamase phenotype (Tacconelli et al. 2018). Each isolation was performed as three biological replicates, followed by three technical ones.

The plates were incubated for 24 h at 37 °C to select animal pathogens and 30 °C for environmental strains. Next, 24 to 48 colonies showing the morphology of the intended bacteria were taken and subjected to three consecutive streaks to get pure colonies. The pure cultures were stored in PBS/glycerol stocks (20% v/v) for further analysis.

The susceptibility profiles of E. coli strains

The antibiotic susceptibility profiles of isolated strains were determined by The Kirby–Bauer test (Biemer 1973). For phenotype characterization, the following antibiotic disks were used: imipenem (β-lactam) (IMP, 10 µg), ciprofloxacin (fluoroquinolone) (CIP, 5 µg), cefotaxime (cephalosporin) (CTX, 5 µg), and gentamicin (aminoglycoside) (CN, 10 µg) (OXOID, USA). The inhibition zones were measured according to EUCAST recommendations, i.e., after incubation for 18 h at 37 °C. Strains with different antibiotic susceptibility profiles, indicated by the bacterial growth inhibition zone differing by approximately + / − 2 mm in diameter around at least one antibiotic disk, were considered non-repetitive and chosen for further research. The presence of E. coli was confirmed by MALDI-TOF MS/MS (matrix-assisted laser desorption/ionization system equipped with a time-of-flight mass spectrometer) (Bielen et al. 2024).

The analyses were performed in an external medical laboratory (ALAB Laboratoria Sp. z o. o., Warsaw, Poland), according to a standard diagnostic procedure. Identification was performed by aligning the peaks to the best-matching reference data. The resulting log score was classified as follows: ≥ 2.3, highly probable species; between 2.0 and 2.3, certain genus and probable species; between 1.7 and 2.0, probable genus; and < 1.7, non-reliable identification. Next, antibiotic susceptibility testing was performed with Vitek2 Compact equipment (BioMerieux, Marcy-l’Étoile, France) (Hogan et al. 2019). Based on the results, strains were classified as sensitive (S), resistant (R), or intermediate (I). The AST-N331 susceptibility card was used.

Strains with the same resistance profile and origin were considered clones. The plasmid profile of non-repetitive strains was determined in three ways: (1) Plasmid DNA was isolated with a commercially available Plasmid Mini kit (A&A Biotechnology, Gdynia, Poland), (2) rapid alkaline lysis for the isolation of plasmid DNA (Birnboim and Doly 1979), (3) plasmid visualization by Eckhardt electrophoresis (Eckhardt 1978). Plasmid DNA with similar profiles was additionally differentiated by digestion with the BamHI and HindIII restriction enzymes (NEB, Ipswich, MA, USA). The digestion was performed according to the manufacturer’s recommendation. Strains with different profiles were chosen for sequencing.

DNA extraction and sequencing

Genomic DNA from bacterial strains was isolated using a Genomic Mini kit (A&A Biotechnology, Gdynia, Poland). The DNA concentration was measured using a Qubit fluorometer and a dsDNA High Sensitivity Assay Kit (Thermo Fisher Scientific, Waltham, MA, USA), and purity was determined by measuring the A260/A280 absorbance ratio with a NanoDrop spectrophotometer (Thermo Fisher, Waltham, MA, USA). Only samples with concentrations higher than 10 ng/µL and an A260/A280 ratio ranging from 1.8 to 2.0 were analyzed. DNA samples were stored at − 20 °C for further use. The DNA samples were isolated in triplicate.

Genomic DNA sequencing on Oxford Nanopore MinION

Libraries were prepared from 500 ng of DNA samples after mechanical fragmentation by the syringe-based method (0.4 × 20 mm needle, 1-mL glass syringe, 200 µL) and purification by solid-phase reversible immobilization with Kapa Pure Beads (Roche, cat. no. 07983298001, elution for 10 min at 37 °C). Native Barcoding method was applied (Oxford Nanopore, cat. no. SQK-NBD112.24, Version: NBE_9134_v112_revE_01Dec2021). The NanoPore MINIon MkB1 R10.4 flow cell and reagents (cat. no. FLO-MIN112) were used for sequencing with standard procedures. Guppy software (version 6.1.2, –flowcell FLO-MIN112 –kit SQK-NBD112-24 options) was applied for basecalling.

Genomic DNA sequencing on Illumina NovaSeq 6000

Briefly, 100 ng of genomic DNA was fragmented to 300 bp by ultrasonication (S220 Covaris, duty factor 10%, peak incident power 140, cycles per burst 200, treatment time 80 s) and subjected to library construction with the KAPA Hyper Prep Kit (Roche, cat. no. 07962363001), according to the manufacturer’s protocol, with five cycles of amplification; however, TruSeq DNA UD Index adapters were used (Illumina, cat. no. 20020590). Libraries were size-selected in a two-step SPRI method and with a sample-to-reagent volume ratio of (1) step—1:0.75 and (2) step—1:0.85 using Kapa HyperPure Beads (Roche, cat. no. 07983298001). Sequencing was performed using pair-end 2 × 100 cycle mode on the Illumina NovaSeq 6000 system (NovaSeq 6000 S1 Reagent Kit v1.5 200 cycles Illumina, cat. no. 20028317; 0.5% of the PhiX control library, Illumina, cat. no. FC-110–3001) and the standard clustering procedure.

Genome assembly and data analysis

Initial sequence quality metrics for Illumina data were obtained using FASTQC v.0.12.0 (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) (Andrews 2010) and subjected to quality trimming using fastp v.0.23.2 (Chen et al. 2018). Nanopore reads were quality filtered with NanoFilt v.2.8.0, discarding reads below 1 kb and QV < 12 (De Coster et al. 2018), and residual adapters were removed using Porechop v.0.2.4 (https://github.com/rrwick/Porechop). The quality of the final long-read dataset was evaluated using NanoPlot v. 1.41.6 (De Coster et al. 2018).

Long-read assembly was performed using Trycycler v.0.5.3 pipeline (Wick et al. 2017). Nanopore reads were initially assembled using four long-read assemblers: Flye v2.9, Unicycler v0.4.8, Raven v1.8.1, and Miniasm v0.3-r179. The resulting assemblies were then reconciled and circularized, and a consensus sequence was generated, which underwent further polishing with medaka_consensus (https://github.com/nanoporetech/medaka). The long-read assembled contigs were further polished with short Illumina reads using polypolish (https://github.com/rrwick/Polypolish) v. 0.5.0 (Wick et al. 2017) and POLCA v. 4.0.5 (Zimin et al. 2017). Finally, all of the sequence errors and misassemblies were manually corrected using SeqMan software v. 9.1 (DNAStar) to obtain a complete nucleotide sequence for the bacterial genome.

The annotation of consensus sequences was performed using Bakta (Schwengers et al. 2021). Plasmid replicon sequences were searched against the PLSDB database (https://ccb-microbe.cs.uni-saarland.de/plsdb/). ARGs were identified and localized in the genomic sequences using abricate (https://github.com/tseemann/abricate). Mobile genetic element detection was performed using mobileelementfinder (Johansson et al. 2021), and the ARG-associated mobilome was characterized using VRprofile2 (Wang et al. 2022).

The plasmid sequences were visualized using SnapGene Viewer software (SnapGene® software from Dotmatics; available at snapgene.com).

Results

E. coli strain selection

Selective media were used to isolate 62 bacterial strains exhibiting growth characteristics of E. coli: 51 strains were identified on Eosin Methylene Blue (EMB) Agar and 11 on MacConkey agar. Of all isolated bacteria, 23 were identified as E. coli by MALDI-TOF MS/MS analysis: of these, 20 strains were isolated on EMB agar, three on MacConkey agar, 13 from chicken manure (CM), and 10 from chicken litter (CL). All bacteria strains were isolated on agar plates supplemented with cefotaxime. No strains resistant to imipenem were identified. All strains were subjected to antibiotic susceptibility profile determination by Vitek 2 Compact: the results are listed in Table S1. Isolates exhibiting similar antibiotic susceptibility profiles were grouped, and their plasmidic profiles were determined. After comparing the plasmidic profiles within the groups, the representative bacterial strains were chosen for plasmid structure determination by total DNA sequencing.

Genomes sequencing and assembly

High-quality genome sequence assemblies for the selected strains were obtained by combining scaffolds from Oxford Nanopore long-read technology (MINIon platform) with Illumina short-read technology (2 × 100 nt in pair-end mode, NovaSeq 6000, approximate 100 × coverage) for quality improvement. The chromosome was successfully assembled, resulting in close to 5 Mb contigs for each strain, and three additional contigs over 40 kb were reconstructed.

Plasmids

Six plasmids belonging to two bacterial isolates were identified (Table 1).

Table 1 Plasmids identified in studied E. coli strains. Plasmids harboring ARGs are marked in gray
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Three of the identified plasmids harbored different ARGs and MGEs (Table 2). The linear structure of the plasmid structures, highlighting the ARGs, MGEs, conjugal transfer genes, transposon transposase genes, heavy metal resistance genes, replication system, integron integrase, and partitioning system elements, is presented in Figs. 1, 2, and 3. Detailed analysis indicated close similarity between the identified plasmids and some bacterial plasmid sequences deposited in the PLSDB plasmid database (https://ccb-microbe.cs.uni-saarland.de/plsdb/); however, there were some differences between them. Plasmid pECmdr13.2 has 133 similar hits, isolated from varied sources located in different regions, plasmid pECmdr13.3 has 18 similar hits, and pECmdr14.1 has 155 similar hits (identity threshold 0.99). None of these plasmids has previously been reported in Poland, but they have been identified in many countries. Although plasmids similar to pECmdr13.2 and pECmdr14.1 have been found in the environment, clinical isolates, and farm animals (cattle, swine, and poultry/birds), plasmids similar to pECmdr13.3 have been identified in the same places but only from poultry. Plasmids that do not confer antibiotic resistance will be characterized further and deposited as a part of an additional project.

Table 2 ARGs, MGEs, integron integrase genes, transposon transposase genes, conjugal transfer system genes, and heavy metal resistance genes
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Fig. 1
figure 1

Linear and circular representation of pECmdr13.2 plasmid; pink-ARGs, red-conjugal transfer genes (TRA), blue-transposon transposase genes (TNP), brown-heavy metal resistance genes, yellow-replication system (REP), green-integron integrase, khaki-partitioning system PAR, gray-mob system (MOB), plum-pilus system (PIL); a name written in quotation marks indicates that the gene function has been assigned based on the homology of the protein it encodes

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Fig. 2
figure 2

Linear and circular representation of pECmdr13.3 plasmid; pink-ARGs, red-conjugal transfer genes (TRA), blue-transposon transposase genes (TNP), brown-heavy metal resistance genes, yellow-replication system (REP), green-integron integrase, khaki-partitioning system (PAR), gray-mob system (MOB), plum-pilus system (PIL); a name given in quotation marks indicates that the gene function has been assigned based on the homology of the protein it encodes

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Fig. 3
figure 3

Linear and circular representation of pECmdr14.1 plasmid; pink-ARGs, red-conjugal transfer genes (TRA), blue-transposon transposase genes (TNP), brown-heavy metal resistance genes, yellow-replication system (REP), green-integron integrase, khaki-partitioning system (PAR), gray-mob system (MOB), plum-pilus system (PIL); a name given in quotation marks indicates that the gene function has been assigned based on the homology of the protein it encodes

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Alignment of ARG-coding sequences and MGE allowed the identification of ARGs located within defined and described MGE, such as IS26, ISEcp1, or “ISclustersTn,” which were in turn situated on the plasmids identified during the study (Fig. 4A–G).

Fig. 4
figure 4

ARGs located within MGE on the identified plasmids: A pECmdr13.2 IS26 (8965 bp) (pink-ARG, blue-transposon transposase genes TNP). B pECmdr13.2 ISclusterTn (18511 bp); pink-ARGs, blue-transposon transposase genes (TNP), green-integron integrase. C pECmdr13.2 ISEcp1 (2731 bp); pink-ARG. D pECmdr13.3 ISclusterTn (14527 bp); pink-ARGs, blue-transposon transposase genes (TNP). E pECmdr14.1 ISclusterTn (14527); pink-ARGs, blue-transposon transposase genes (TNP). F pECmdr14.1 ISEcp1 (2731 bp); pink-ARG. G pECmdr14.1 IS26 (13249 bp); pink-ARGs, blue-transposon transposase genes (TNP)

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A detailed search of the PLSDB provides data on the isolation source, biosample origin, country, and first report of similar plasmids (Table 3), as well as previously reported plasmid host range (Table 4).

Table 3 Region, isolation source, and host biosample of similar plasmids (plasmids identity 0.99)
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Table 4 The host range for similar plasmids (plasmid identity 0.99)
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Discussion

Due to its presence in the veterinary, medical, and natural environment, E. coli is considered a specific vector for the transmission of ARGs, so-called acquired resistance (Zalewska et al. 2021; Męcik et al. 2023). The bacteria found in chicken manure or chicken litter are not limited to E. coli; they often co-isolate with other foodborne bacteria such as Salmonella and Campylobacter spp. (Merchant et al. 2012; Viegas et al. 2012; Błażejewska et al. 2022). This is an important issue since such material is utilized as fertilizer in agriculture globally (Pujiastuti et al. 2018; Błażejewska et al. 2022). These bacteria pose a serious risk of antibiotic resistance transmission between animals, humans, and the environment, i.e., the three links of the One Health concept, and demonstrate considerable survival in water, soil, and crops: the lifespan of pathogenic bacteria ranges from several days to 10 years in soil and from several days to a year on plants (Oliveira et al. 2012; Anokyewaa Appau and Ofori 2024).

The main process responsible for disseminating ARGs is horizontal gene transfer (HGT) (Aminov 2011). The principal route of HGT in bacterial communities is most likely conjugation, and conjugation elements, such as conjugative plasmids, often harbor multiple ARGs (Wozniak and Waldor 2010). In addition, ARGs are often encoded on non-conjugative plasmids, transposons, integrative, and bacteriophages (Abe et al. 2020), whose presence facilitates HGT. HGT is most likely to occur when bacterial density is high, particularly where high numbers of bacteria are present in a given environment, under stress conditions, and selective pressure (Zalewska et al. 2021). Acquired genes may confer adaptive advantages under certain growth or environmental conditions that may contain antimicrobials, xenobiotics, metals, sucrose, and other compounds. Also, abiotic factors may affect conjugal transfer, e.g., the rate of plasmid transfer in the soil varies depending on abiotic factors, such as soil moisture and temperature, pH, and soil type (Aminov 2011). HGT is also affected by genetic diversity in the environment: while high biodiversity may increase the pool of potentially exchangeable genes in the bacterial population, with HGT occurring even between distantly related species, high diversity is considered a barrier to HGT (Klümper et al. 2024).

Antibiotic resistance is undoubtedly associated with resistance plasmids, which spread rapidly through conjugation. Accordingly, plasmids play a significant role in the worldwide dissemination of resistance, including MDR (Partridge et al. 2018; Pinilla-Redondo et al. 2018; San Millan 2018). Therefore, identifying and characterizing R-plasmids and their association with different bacterial hosts is key to understanding the epidemiology and spreading of antibiotic resistance. So far, little information exists on the fully characterized plasmids identified in chicken manure isolates. A suitable example could be the aminoglycoside resistance plasmids (arr-3 and aacA) pRKZ3 (IncQ) and pKANJ7 (IncX), which were isolated from pig and chicken manure (Pu et al. 2019). The present study identified two IncC R-plasmids, pECmdr13.2 and pECmdr14.1, carrying genes for resistance to tetracyclines, aminoglycosides, β-lactams, sulfonamides, and fluoroquinolones and to mercury; in addition, pECmdr14.1 demonstrated resistance to phenicol. The study also identified one IncX1 pECmdr13.3 R-plasmid, carrying genes for resistance to aminoglycosides, β-lactams, tetracyclines, and fluoroquinolones. So far, such plasmids have not been reported in Poland.

Incompatibility Group C (IncC) plasmids have a broad host range; the group can be divided into several types based on differences in sequence arising from homologous recombination events between type 1 and type 2 IncC backbones (Harmer and Hall 2014; Zhang et al. 2020). This variability also results from insertion and deletion events or inversion mechanisms involving IS26 (Ambrose et al. 2018). IncC plasmids occur widely in Gram-negative bacteria and are responsible for transmitting resistance to several different antibiotics, such as aminoglycoside and fluoroquinolone, as well as cephalosporins (blaCMY cephalosporinase genes) and carbapenems (blaNDM carbapenemase genes) which have considerable clinical significance (Shoma et al. 2014; Harmer and Hall 2014; Wasyl et al. 2015; Partridge et al. 2018). In contrast, the IncX plasmids, and their subgroups (IncX1—IncX8), have a narrow spectrum of hosts, including E. coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Salmonella enterica (Dobiasova and Dolejska 2016). These plasmids have been associated with antibiotic resistance to β-lactams, including carbapenems, aminoglycosides, quinolones, tetracyclines, streptomycin, and amphenicols, which are associated with mobile elements, such as insertion sequences, integrons, and transposons (Fang et al. 2018). As shown in Table 2, the plasmids identified in this work have host ranges encompassing pathogenic and opportunistic bacteria capable of living in natural, veterinary, and clinical environments, which further emphasizes the importance of characterizing R-plasmids in these bacteria. Particularly noteworthy is the fact that most of these bacteria are categorized as critical and high-priority on the global priority pathogens list (Tacconelli et al. 2018).

Previous studies found a sulfonamide resistance gene (sul1), a tetracycline resistance gene (tetA), and three aminoglycoside resistance genes (aadA, strA, and strB) in plasmids isolated from chicken manure (Dobiasova and Dolejska 2016; Le Devendec et al. 2016). This is undoubtedly related to antibiotic therapy used in poultry farming: the most frequently administered pharmaceuticals are beta-lactams, macrolides, polymyxins, quinolones, sulfonamides, and tetracyclines (Chauvin et al. 2007). There has been a surge of reports on multidrug-resistant E. coli strains isolated from chicken manure, resistant to β-lactams with ESBL (extended-spectrum beta-lactamase) and AmpC (clinically important β-lactamases; cephalosporinases) phenotypes, which are often also resistant to gentamicin (Zalewska et al. 2021). However, few studies have reported about plasmids coding for both antibiotic and metal resistance genes occurring in bacterial strains isolated from chicken feces. However, one study recently described the presence of ESBL/AmpC and mcr-5-carrying MDR plasmids isolated from E. coli and K. pneumoniae strains in Paraguayan poultry farms (Nesporova et al. 2021). IncHI2 plasmids identified in E. coli isolates from food-producing animals have also been found to carry the antibiotic resistance genes blaCTX-M/oqxAB with aac (6′)-Ib-cr, floR, fosA3, and rmtB, as well as the heavy metal resistance genes pco and sil responsible for increasing the minimal inhibitory concentrations of CuSO4 and AgNO3 (Fang et al. 2016). Previously, similar IncHI2 plasmids carrying tetracycline, trimethoprim, and sulfonamide resistance genes and transposon Tn1696 related to mercury resistance were identified in two MDR S. enterica serovar Typhimurium isolates from Australian food-producing animals (Cain et al. 2010). Another study of E. coli strains from pig slaughterhouses in the UK showed various combinations of resistance to oxytetracycline, streptomycin, sulphonamide, ampicillin, chloramphenicol, trimethoprim–sulfamethoxazole, ceftiofur, amoxicillin–clavulanic acid, aztreonam, and nitrofurantoin, together with resistance to mercury, silver, or copper (merA, merC, and pcoE and silA, silB, and silE genes were detected) (Yang et al. 2020). A similar relationship was found in a 2024 study on the distribution and relationships of ARGs, heavy metal resistance genes, virulence factors, and their transmission mechanisms of an MDR E. coli strain isolated from livestock manure and fertilized soil (Tan et al. 2024).

Therefore, the presence of metal resistance genes and ARGs on the identified plasmids supports their transmission by HGT and subsequent maintenance in the bacterial cell, even in the absence of selection pressure caused by antibiotics. This co-occurrence of genes specifying resistant phenotypes on one MGE is referred to as co-resistance (Baker-Austin et al. 2006; Pal et al. 2017). Such genetic linkage between metal- and antibiotic-resistant traits has been reported on plasmids in Enterobacteriaceae and in other bacteria isolated from other animal feces, soil, or sewage (Summers et al. 1993; Ghosh et al. 2000; Hasman and Aarestrup 2002; Rozwandowicz et al. 2018). It has been shown that metals used in animal feed accumulate and persist in food animals and may impact the development of AMR in primary animal and food production environments (James et al. 2023). Many studies indicate that the spread of AMR introduced through the application of manure to agricultural fields leads to its further spread within the food chain and may pose a risk to human health (Do et al. 2022; Błażejewska et al. 2022; Zalewska et al. 2023, 2024). Such a risk is underlined by the presence of plasmids carrying shared antibiotic and metal resistance in MDR strains of E. coli, a vector known to transmit AMR between One Health sectors: E. coli strains have been found to potentially transfer resistance between humans and chickens (Norizuki et al. 2017).

AMR continues to evolve and spread, with the main mechanism being HGT through plasmids. Therefore, there is a pressing need to identify and characterize R-plasmids and their relationships with different bacterial hosts to understand their involvement in the transfer of AMR determinants. The molecular identification of plasmid genotypes, the transposons and integrons located within them, or other insertion sequences involved in this process would provide a clearer picture of the mechanism of AMR dissemination and its possible range. In turn, the characteristics of their hosts, i.e., the specific strains of bacteria, can improve the prediction of the risk to human and animal health.

Conclusion

The study characterizes three E. coli plasmids (pECmdr13.2, pECmdr13.3, pECmdr14.1) from chicken manure, each carrying ARGs, insertion elements (IS), transposons (Tn26, Tn6196), and a class 1 integron-integrase gene (intI1), common in resistance plasmids from key pathogens, and a mercury resistance operon promoting maintenance without antibiotic pressure. These plasmids confer an MDR phenotype, carry conjugal transfer genes, facilitating HGT, and belong to incompatibility groups IncX1 (narrow host range, Enterobacteriaceae and Pseudomonas spp.) and IncC (broad host range). No such plasmids have been previously reported in Poland, though similar ones have been identified in crucial human pathogens globally, and in natural settings like soil and water. This underscores the urgent need for vigilant monitoring of R-plasmids prevalence in the human, animal, and natural environments and their relationships with different bacterial hosts to understand their involvement in the transfer of AMR determinants.