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. 2025 Mar 23;104(6):105082. doi: 10.1016/j.psj.2025.105082

Strict relationship between phenotypic and plasmid-associated genotypic of multidrug-resistant Escherichia coli isolated from Taihe Black-Boned Silky Fowl farms

Li Zhang a,b,c, Mengjun Ye a,b,c, Yifan Dong a,b,c, Lijuan Yuan a,b,c, Jianjun Xiang a,b,c, Xiren Yu a,b,c, Qiegen Liao a,b,c, Qiushuang Ai a,b,c, Suyan Qiu a,b,c, Dawen Zhang a,b,c,⁎
PMCID: PMC11997332  PMID: 40158280

Abstract

Taihe Black-Boned Silky Fowl (TBSF) is a unique breed in China, characterized by a high concentration of melanin deposited throughout its body. Compared to broiler chickens, many antibiotics exhibit significantly longer withdrawal periods in TBSF. Given that antibiotic exposure is widely recognized as the primary selective pressure driving the persistence and dissemination of antibiotic resistance genes (ARGs) across diverse environments, it is crucial to investigate the occurrence and prevalence of ARGs within TBSF farming systems. In this study, 34 Escherichia coli strains isolated from 22 TBSF farms were subjected to phenotypic and genotypic analyses. The isolates were tested for susceptibility to 28 antimicrobial drugs representing nine antibiotic classes to determine their antimicrobial resistance phenotypes. Draft genome sequences of these E. coli strains were obtained, and the ARGs carried by mobile genetic elements, particularly plasmids, were analyzed for their association with susceptibility phenotype. The genetic context of key ARGs in these E. coli isolates was further characterized. Network analysis was employed to investigate the correlations between ARGs, phenotypes, and drug residues. The results demonstrated that high rates of antimicrobial resistance were observed, with 100 % and 29.4 % of isolates exhibiting resistance to four or more and eight or more antibiotic classes, respectively. According to whole-genome sequencing, a total of 143 ARGs were identified. The antimicrobial resistance phenotypes were consistently correlated with the presence of corresponding ARGs in the 34 E. coli genomes. 100 % of the β-lactams antibiotics resistant mechanism could be attributed to the presence of the resistance gene blaTEM and/or blaOXA-10. Similarly, resistance to tetracyclines, chloramphenicols, aminoglycosides, and fluoroquinolones was fully explained by the presence of tetR and/or tetA, floR and/or cmlA, ant(3’’)-IIa, aph(3’’)-Ib, aph(6)-Id, aac(3)-IId, and aadA, and qnrS and/or mutant gyrA/parC/mdtH. The majority of these key ARGs were found to be plasmid-associated. This study verified and highlighted the prevalent horizontal gene transfer of ARGs in TBSF farms. Factors such as hygiene status, biosecurity measures, and other environmental conditions might play a more significant role than antimicrobial usage in facilitating the horizontal gene transfer of ARGs in TBSF farms. Appropriate measures should be taken to control the transmission and dissemination of these mobile genetic elements associated ARGs and prevent their entry into the human clinical environment from TBSF breeding environment.

Keywords: Escherichia coli, Multidrug resistant, ARGs, Plasmid, Taihe black-boned silky fowl

Introduction

Antimicrobial resistance (AMR) has emerged as a major global health concern, with AMR alone responsible for approximately 1.27 million deaths in 2019 (Antimicrobial Resistance Collaborators, 2022). Identifying the sources and transmission pathways of antibiotic-resistant bacteria across diverse environmental settings continues to present a significant challenge. Mobile genetic elements (MGEs), such as plasmids, transposons, and integrons, have been demonstrated to be perfect vectors for the horizontal gene transfer (HGT) of antibiotic resistance genes (ARGs), with plasmids being particularly significant in this process (Partridge et al., 2018; Rozwandowicz et al., 2018;San Millan et al., 2018). Plasmids can be vertically transmitted within an expanding population of host cells and can also undergo horizontal transfer between bacterial cells via conjugation (Shintani et al., 2015; Zongo et al., 2024). As extrachromosomal elements, plasmids are present in both Gram-negative and Gram-positive bacterial genera. The diversity and adaptation of plasmids in E. coli represent the broader characteristics observed within a significant group of proteobacteria. To date, more than 17 distinct plasmid families have been found in E. coli (de Toro et al., 2014). The World Health Organization (WHO) has classified third-generation cephalosporin-resistant Enterobacterales as critical-priority pathogens, given their substantial threat to public health (World Health Organization, 2024). E. coli, as the type strain of the Enterobacterialses order, serves both as a common commensal and as a pathogen in animals, thereby posing a significant public health concern. The ease of isolation and cultivation of E. coli, together with its significant role in the dissemination of ARGs, makes it an ideal model organism for investigating the spread of ARGs across diverse environments (Arbab et al., 2022).

Livestock, particularly poultry farms, serve as critical reservoirs for the development and dissemination of ARGs, largely due to high stocking densities and the extensive use of antibiotics (Wolfe et al., 2007; Hassell et al., 2019; Scicchitano et al., 2024). In China, poultry farms frequently operate under conditions characterized by limited space and high stocking density. Despite rigorous cleaning and disinfection during the vacancy periods, intensive poultry production farms struggle to maintain optimal microclimate conditions and animal hygiene (Kostadinova et al., 2014). The presence of multi-drug resistant E. coli in poultry poses a substantial public health risk in China, given that chicken meat constitutes a substantial portion of the human diet. According to data from the China Statistical Yearbook, per capita chicken meat consumption increased from 8.9 kg in 2017 to 12.4 kg in 2023, reflecting an annual growth rate of 6.6 percent (National Bureau of Statistics of China, 2024). Taihe Black-Boned Silky Fowl (TBSF) is a distinctive breed of chicken in China, characterized by the extensive melanin deposition throughout its body (Mi et al., 2018). The average rearing period for TBSF on farms is approximately 120 days before slaughter, with some batches even being raised for up to three to five years or even longer. This stands in stark contrast to the 42-day rearing period that is commonly adopted in broiler chicken production. In our previous study, the extremely slow metabolism of enrofloxacin, ciprofloxacin, and trimethoprim in TBSF was observed, with the withdrawal period exceeding 120 days, owing to melanin deposition in TBSF (Yuan et al., 2023).

Antibiotic exposure is widely acknowledged as the predominant selection pressure influencing the evolution, persistence and dissemination of ARGs in both host populations and natural environments (Fournier et al., 2020; Emara et al., 2023). Consequently, the prolonged retention of drug residues observed in TBSF may further exacerbate selective pressures on bacterial communities, potentially promoting the emergence and dissemination of AMR. Despite this concern, there is a conspicuous paucity of research regarding ARGs in the TBSF sector, and the impact of prolonged drug residue on ARGs transmission within the TBSF farming environment remains inadequately understood. To address this knowledge gap, we conducted an extensive and systematic sampling protocol across various types of samples, including soil, feed and feces, from 22 TBSF farms in Taihe, Jiangxi Province, to investigate the epidemiology of ARGs in E. coli. All isolates were subjected to antimicrobial susceptibility testing, and whole-genome sequencing (WGS) was conducted to analyze their genetic profiles. Additionally, we investigated the transmission of ARG-carrying MGEs in E. coli by identifying resistance-associated genetic contexts within genomes and correlating them with the corresponding resistance phenotypes.

Materials and methods

Sampling, bacterial isolation and identification

A total of 74 non-duplicate samples were collected from 22 TBSF farms, as illustrated in Fig. 1. Essential background information for these TBSF farms was provided in Table S1 of the supplemental material. In each farm, one soil sample, one feed sample, and one or two fecal samples were collected. Soil samples were collected from areas adjacent to each sampled poultry house. Within each examined poultry house, fecal samples were collected from five different locations to ensure comprehensive coverage of the house. These samples were then pooled together and combined into a single composite sample weighing more than five grams. Feed samples were collected from the feed plots provided to chickens in the sampled houses at each farm. All samples were aseptically collected in sterile sampling bags (Changde Bkmam Biotechnology Co., LTD.) and transported to the laboratory within 24 h at 4 °C. Each sample was enriched in buffered peptone water for 18 h, followed by plating onto eosin methylene blue agar and incubating at 37 °C for 24 h. Subsequently, three to five colonies exhibiting characteristic of E. coli morphology were chosen for subculturing on eosin methylene blue agar by streak plating to ensure the purity of colonies. Biochemical assays were conducted to identify E. coli isolates, and a single E. coli isolate from each sample was selected for subsequent analysis.

Fig. 1.

Fig 1

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Geographical location of TBSF farms.

Antibiotic susceptibility testing

All E. coli isolates were subjected to antimicrobial susceptibility testing against 28 antibiotics. The Kirby-Bauer disc diffusion method was employed to determine the inhibition zone diameters, and the results were interpreted in accordance with the Clinical and Laboratory Standards Institute document M100 (CLSI, 2022). The reference strain E. coli ATCC25922 was used as a quality control. The antibiotic test panel comprised the following disks with their respective concentrations: ampicillin/sulbactam (10/10 μg), ampicillin (10 μg), amoxicillin (30 μg), cefazoline (30 μg), cefuroxime (30 μg), ceftriaxone (30 μg), imipenem (10 μg), spectinomycin (100 μg), gentamicin (10 μg), kanamycin (30 μg), apramycin (15μg), tetracycline (30 μg), oxytetracycline (30 μg), doxycycline (30 μg), chloramphenicol (30 μg), florfenicol (30 μg), kitasamycin (15μg), tylosin (30 μg), tilmicosin (15 μg), enrofloxacin (10 μg), ciprofloxacin (5 μg), flumequine (30 μg), sulfamethoxazole / trimethoprim (23.75/1.25 μg), sulfadiazine (300 μg), trimethoprim (5 μg), lincomycin (2 μg), polycolistin B (300 IU), and bacitracin (0.04 U). In accordance with the criteria established by Magiorakos et al. (2012), multidrug resistance was defined as resistance to three or more antimicrobial classes.

Whole-genome sequencing and assembly

Genomic DNA was extracted from cells in the logarithmic growth phase using a bacterial DNA extraction kit based on the magnetic beads method (Majorbio, Shanghai, China) following the manufacturer's instructions. Following agarose gel electrophoresis, the concentration and quality of the extracted DNA were measured using a Quantus Fluorometer (Picogreen method). WGS was subsequently performed at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China) using the advanced Illumina novaseq X plus platform.

The raw Illumina reads were subjected to a refinement process in which low-quality and adapter sequences were systematically removed. A paired-end library with an insert size of 400 bp was constructed. Subreads were obtained for de novo assembly using SOAPdenovo v2.04 (Luo et al., 2012). GapCloser v1.12 was used to close gaps that emerged during the scaffolding process performed by SOAPdenovo, leveraging abundant paired relationships of short reads, thereby improving the completeness of the genome sequences. Genes were predicted using Prodigal v.2.6.3. GeneMarkS software v4.3 was used to predict the coding sequences. Barrnap version 0.9, tRNA-scan-SE version 2.0.12, and Infernal version 1.1.4 were used to identify rRNA, tRNA and sRNA, respectively. The predicted coding sequences were translated, and their corresponding functional annotations were completed by blasting genes against the NR (Non-Redundant Protein Sequence), KEGG (Kyoto Encyclopedia of Genes and Genomes), COG (Clusters of Orthologous Groups), and Swiss-Prot databases. MLST of seven housekeeping genes (adk, fumC, gyrB, icd, mdh, purA, and recA) was performed according to the MLST protocol standardized for E. coli (http://mlst.warwick.ac.uk/mlst). Additionally, a phylogenetic analysis was conducted based on 31 single-copy housekeeping genes (dnaG, frr, infC, nusA, pgk, pyrG, rplA, rplB, rplC, rplD, rplE, rplF, rplK, rplL, rplM, rplN, rplP, rplS, rplT, rpmA, rpoB, rpsB, rpsC, rpsE, rpsI, rpsJ, rpsK, rpsM, rpsS, smpB, and tsf) using MEGA software (version 10.1.7).

Identification of MGE-associated ARGs

The prediction of resistance genes from DNA sequences was performed using Diamond v0.8.35, based on the curated data available in the Comprehensive Antibiotic Resistance Database version 3.2.6. Resistance determinants were identified based on stringent criteria, requiring a minimum of 80 % amino acid identity, at least 50 % sequence length identity and a coverage of no less than 50 % when compared to known resistance proteins. The identification of gene islands, insertion sequences, integrons, prophages and transposons was performed using IslandPath-DIMOB version 1.0.0, ISEScan version 1.7.2.1, Integron_Finder version 2, Phigaro version 2.3.0, and TransposonPSI, respectively. PlasFlow version 1.1 was used to predict plasmid sequences from ARG-carrying contigs. The potential for ARGs transmission was evaluated by identifying MGEs located within a span of 10 open reading frames either upstream or downstream of the ARGs in the same contig.

Detection of antibiotics in TBSF samples

In each E. coli-positive TBSF farm, antibiotic residues (including sulfadiazine, florfenicol, tetracycline, oxytetracycline, lincomycin, doxycycline, tilmicosin, enrofloxacin, and ciprofloxacin) in breast meat, feces, eggs, and feed were detected according to the corresponding national standards.

Correlation of drug residues, resistance phenotypes and genotypes

Values were assigned to all items, with a value of 1 designated for positive or resistant items and 0 designated for negative or susceptible items. An E. coli isolate was considered positive for a drug if the presence of that drug was detected in any sample from the farm. Conversely, if the drug was not detected, the isolate was considered negative. The presence of known corresponding resistance genes was considered indicative of positive ARGs in the E. coli isolates. Conversely, the absence of such ARGs was considered indicative of a negative result. Intermediate phenotypes were classified as resistant for the purpose of this analysis. The data were analyzed using the online tools provided by the Majorbio Cloud Platform (https://cloud.majorbio.com/page/tools/).

Accession number(s)

WGS data for all E. coli isolates used in this study were submitted to the National Center for Biotechnology Information (NCBI) under BioProject accession number PRJNA1135707. Accession numbers for individual isolates were provided in Table S2 in the supplemental material.

Results

E. coli isolation and antimicrobial-resistant phenotypes

Among all the collected samples (22 soil samples, 22 feed samples, and 30 fecal samples, including 13 from layers, 9 from hens and 8 from cocks), 34 E. coli strains were successfully isolated from 10 soil samples, 20 fecal samples (including 11 from layers, 6 from hens, and 3 from cocks), and 4 feed samples. The isolation rates of E. coli, from highest to lowest, were as follows: layer feces (11/13), hen feces (6/9), soil (10/22), cock feces (3/8), and feed (4/22) (Fig. 2).

Fig. 2.

Fig 2

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Isolation rate of E. coli in TBSF farms.

All E. coli isolates from TBSF farms were multidrug-resistant strains, with 100 % and 29.4 % of isolates displaying resistance to four or more and eight or more antibiotic classes, respectively (Table S3). All isolates were resistant to tylosin, sulfadiazine, trimethoprim, macrolides, lincomycin and bacitracin, whereas remaining susceptible to cephalosporin (including cefazoline, cefuroxime, and ceftriaxone), imipenem, and polymyxin B. Nearly all strains, with the exception of one fecal sample, were resistant to kitasamycin. The majority of isolates, excluding five fecal samples and two soil samples, exhibited resistance to sulfamethoxazole. The trend of resistance rates among E. coli isolates from fecal samples was broadly consistent with those from environmental samples (feed and soil samples) (Fig. 3). Significantly higher resistance rates to several antibiotics were observed in fecal E. coli isolates compared to environmental E. coli isolates, for example ampicillin (50.0 % vs 28.6 %), amoxicillin (55.0 % vs 28.6 %), spectinomycin (10.0 % vs 0), kanamycin (5.0 % vs 0), tetracycline (65.0 % vs 35.7 %), oxytetracycline (65.0 % vs 35.7 %), enrofloxacin (10 % vs 0), and ciprofloxacin (15 % vs 0).

Fig. 3.

Fig 3

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Antimicrobial resistance to 28 antibiotics of E. coli isolates from TBSF farms. env, including feed and soil samples; AMS, ampicillin/sulbactam; AM, ampicillin; AMX, amoxicillin; CZ, cefazoline; CXM, cefuroxime; CTR, ceftriaxone; IPM, imipenem; SPT, spectinomycin; GM, gentamicin; K, kanamycin; AP, apramycin; TE, tetracycline; OT, oxytetracycline; D, doxycycline; C, chloramphenicol; FON, florfenicol; KI, kitasamycin; TY, tylosin; TIL, tilmicosin; ENR, enrofloxacin; CIP, ciprofloxacin; UB, flumequine; SXT, sulfamethoxazole; SUZ, sulfadiazine; TMP, trimethoprim; LC, lincomycin; PB, polycolistin B; BAC, bacitracin.

Genomic analysis, and ARGs in genomes

In total, 22 known sequence types (ST) based on the seven-gene Achtman scheme were identified. Only one strain possessed novel alleles. Among these STs, ST155 (n = 6, 17.6 %) was the most prevalent (Table S4). MLST analysis revealed the presence of identical STs across samples of different origins. A phylogenetic analysis was also conducted to examine the clonal diversity and phylogenetic relationships among the 34 E. coli isolates (Fig. 4). From these analyses, it was found that there was no significant association between the isolates and their sample sources. These E. coli strains demonstrated the ability to survive in a variety of habitats within TBSF farms.

Fig. 4.

Fig 4

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Phylogenetic tree of 34 E. coli strains using MEGA software (version 10.1.7) based on the housekeeping genes.

To elucidate the genomic basis of antimicrobial resistance phenotypes (ARP) in the E. coli isolates, we investigated the presence of ARGs in their genome sequences. A total of 143 ARGs conferring resistance to all major antibiotic classes were identified via whole-genome sequencing analysis (Table S5). ARGs were detected in all E. coli isolates, including the extended-spectrum beta-lactamase gene blaCTX-M in an E. coli isolate from a fecal sample and the mobile colistin resistance gene mcr-1 in an E. coli isolate from a soil sample. No blaNDM or blaKPC genes were detected, and all strains tested negative for carbapenem-resistant genes. Among the ampicillin and amoxicillin-resistant isolates, the beta-lactamase gene blaTEM was the most prevalent beta-lactamase resistance gene (13 out of 16, 81.2 %). Other beta-lactamase genes, such as blaOXA-10 (3 out of 16, 18.8 %), were also sporadically detected in our study. All tetracycline-resistant strains harbored the tetracycline resistance genes tetA and tetR. Similarly, all florfenicol-resistant strains possessed florfenicol resistance genes, including floR, cmlA, and cfrA. A total of 18 strains exhibited resistance or reduced susceptibility to fluoroquinolones; however, only 8 of these strains harbored the fluoroquinolone resistance gene qnrS in their genomes. In two strains that exhibited resistance to all tested fluoroquinolone drugs, the qnrS gene was absent; however, mutations in the gyrA, parC, and mdtH genes were concurrently observed. Among 19 strains exhibiting resistance or reduced susceptibility to aminoglycosides, the aminoglycoside-resistance genes, including strA (encoding aminoglycoside O-phosphotransferase APH(3′')-Ib), strB(encoding aminoglycoside O-phosphotransferase APH(6)-Ib), aadA(encoding aminoglycoside adenylyltransferase), and aac3-Ⅱ(encoding aminoglycoside N-acetyltransferase AAC(3)-IId), were present either individually or in combination in the majority of these strains (13 out of 19). All strains exhibited resistance to sulfonamides and harbored the integron-encoded dihydrofolate reductase gene dfrA. However, only 11 strains possessed sul genes, which encode sulfonamide-resistant dihydropteroate synthase.

The blaTEM and blaOXA genes have primarily disseminated via plasmids; however, the blaOXA-10 gene was harbored by integrons exclusively in two beta-lactam-resistant isolates. All tetracycline-resistant strains harbored plasmid-associated tetracycline resistance genes tetA and tetR. Similarly, the chloramphenicol and florfenicol resistance genes floR, cmlA, and cfrA, were also detected on various types of plasmids. The aminoglycoside resistant genes aac, aad, strA, and strB were also found to be associated with various types of plasmids. The sulfonamide-resistant dihydropteroate synthase gene sul were all identified on scaffolds that were determined to be part of plasmids.

Genetic environment of plasmid-associated ARGs in E. coli isolates

To further elucidate the genetic mechanisms underlying the dissemination of ARGs, MGEs (including plasmids, gene islands, insert sequences, integrons, prophge, and transposons) were analyzed in the genomes of the isolates. In this study, ARGs associated with major clinically relevant antibiotics were consistently identified on scaffolds determined to be part of plasmids using PlasFlow v1.1 (Table S6).

Among the 13 amoxicillin-resistant E. coli isolates, the blaTEM gene was predicted to be located on various plasmid families, including IncH, IncN, IncF, IncI, IncR, and IncX. The blaTEM gene exhibited the same genetic environment in strains DJF_23 and TR_23, which were isolated from the same farm. This suggested that HGT likely occurred between the fecal and soil niches. In the majority of amoxicillin-resistant strains (8 out of 13), the blaTEM gene was consistently flanked upstream by pinR, a recombinase gene, and was occasionally followed downstream by either a single transposase gene associated with a specific transposon or another recombinase gene. In 5 of the 13 amoxicillin-resistant strains, the sulfonamide resistance gene sul, which encodes dihydropteroate synthase, was consistently identified on scaffolds harboring the blaTEM gene (Fig. 5).

Fig. 5.

Fig 5

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The genetic environment of blaTEM in E. coli isolates.

The floR gene from the majority of chloramphenicol-resistant isolates (5 out of 10) was predicted to be located on IncH plasmids, whereas the remaining isolates were found on IncF (2 out of 10), IncC (1 out of 10), IncX (1 out of 10), and IncN (1 out of 10) plasmids. Among the 10 chloramphenicol-resistant E. coli isolates, strains DJF_23 and TR_23, both isolated from the same farm, possessed the same genetic environment. Additionally, three strains isolated from two fecal samples and a soil sample collected from distinct farms also shared the same genetic environment. In 9 out of 10 chloramphenicol-resistant strains, the floR gene was consistently flanked downstream by dhcR, a LysR family transcriptional regulator gene. Additionally, in 8 out of 10 strains, a dihydropteroate synthase gene was found upstream of floR (Fig. 6).

Fig. 6.

Fig 6

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The genetic environment of floR in E. coli strains.

The tetracycline resistance genes tetA and tetR were consistently co-located in all tetracycline-resistant isolates, with the exception of the strain isolated from a fecal sample. These genes were associated with various plasmid types, including IncH, IncF, IncN, IncP, IncX, and others. Among the 18 tetracycline-resistant E. coli isolates, seven strains isolated from diverse samples collected across different farms shared the same genetic environment. Two strains, isolated from a fecal sample and a soil sample collected from the same farm, shared the same genetic environment. In 14 out of the 18 tetracycline-resistant E. coli isolates, the pecM gene was detected downstream of the tetA gene. Upstream of the pecM gene, a gene called biuH, which encodes an isochorismatase family cysteine hydrolase, was consistently annotated. Downstream of the tetR gene, a gene encoding a transposase protein, which belongs to the drug/metabolite transporter superfamily, was always present (Fig. 7).

Fig. 7.

Fig 7

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The genetic environment of tetA & tetR in E. coli isolates.

Antibiotics residues in TBSF samples

The residues of antibiotics in TBSF samples were analyzed to evaluate the antibiotic usage on the TBSF farms (Table S7). In 19 E. coli - isolated farms, no residue of sulfadiazine was detected. More than five antibiotics were detected in fecal samples from three distinct farms. Specifically, a fecal sample from one farm contained seven antibiotics, whereas two fecal samples from the other two farms each contained five antibiotics. Flufenicol was detected in four fecal samples, one egg sample, and one breast meat sample collected from four farms. The concentrations ranged from a minimum of 0.86 μg/kg to a maximum of 39.68 μg/kg. Tetracycline was detected in three fecal samples at concentrations of 120.58 μg/kg, 8.52 μg/kg, and 6.54 μg/kg, respectively. Oxytetracycline was detected in eight fecal samples and two breast meat samples, with concentrations ranging from 1.93 μg/kg to 3576.79 μg/kg. Another tetracycline drug, doxycycline, was detected in nine fecal samples, four eggs samples, three breast meat samples, and one feed sample collected from 11 farms. The concentrations ranged from 0.97 μg/kg to 4180.67 μg/kg. Lincomycin was detected in five fecal samples and one meat sample, with concentrations ranging from 4.14 μg/kg to 918.03 μg/kg. The macrolide drug timicosin was detected in five meat samples, two fecal samples and one egg samples, with concentrations ranging from 0.11 μg/kg to 8.14 μg/kg. Fluoroquinolones were detected in three meat samples and two fecal samples from only three TBSF farms. Enrofloxacin concentration ranged from 1.21 μg/kg to 10.48 μg/kg, whereas ciprofloxacin concentration ranged from 0.36 μg/kg to 0.75 μg/kg.

Correlation between ARPs, drug residues, and MGE-associated ARGs

In analyzing the ARGs in each E. coli genome, we observed that the genes blaTEM and blaOXA-10 were exclusively identified in β-lactam-resistant isolates, tetR and tetA were present only in tetracycline-resistant isolates, floR and cmlA were found solely in chloramphenicol-resistant isolates, and aminoglycoside resistance genes (aac, aad, strA, and strB) were detected only in aminoglycoside-resistant isolates. The sulfonamide-resistant dihydropteroate synthase genes (sul) were exclusively identified in sulfonamides-resistant isolates. We further analyzed the interactions between drug residues, ARGs, and ARPs using network analysis (Fig. 8). The results indicated that few drug residues in TBSF farms were correlated with ARPs and ARGs. There was a significant correlation between the ARGs and the susceptibility phenotypes to tetracycline, β-lactam, chloramphenicol, sulfonamides, and aminoglycoside antibiotics. Various types of ARGs exhibited interdependent relationships in this study, further supporting the co-transfer of different ARGs was prevalent in TBSF farms.

Fig. 8.

Fig 8

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Network analysis presenting association of the drug residues, ARGs, and ARPs (Spearman coefficient, ρ > 0.5, p < 0.05). D1-D9: drug residues; G_LAC: β-lactams resistant genes; G_CHL: chloramphenicols resistant genes; G_FLU: fluoroquinolones resistant; G_TET: tetracyclines resistant genes; G_AMI: aminoglycosides resistant genes; G_SUL: sulfonamides resistant genes; R_LAC: resistant to β-lactams; R_CHL: resistant to chloramphenicols; R_FLU: resistant to fluoroquinolones; R_TET: resistant to tetracyclines; R_AMI: resistant to aminoglycosides; R_SUL: resistant to sulfonamides.

Discussion

In the present study, the isolation rate of E. coli in layer feces from TBSF farms was the highest, followed by hen feces, soil, cock feces, and feed, while Kwoji et al reported that the highest occurrence (83.3 %) was observed in broiler chicks, whereas the lowest detection rate (54.2 %) was found in layers (Kwoji et al, 2019). This may be attributed to variety of factors influencing the isolation rate of E. coli in chicken farms. For example, running tap water could effectively prevent the contamination of E. coli in the environment (Navab-Daneshmand et al, 2018). Temperature, moisture content, animal presence, sun exposure, antibiotics usage and other factors are also critical determinants influencing E. coli contamination (Capone et al, 2021). The high prevalence of E. coli in layers observed in this study may be attributed to insufficient sanitary conditions in TBSF farm environments (Scheinberg et al, 2017; Soare et al, 2022). Specific factors include the utilization of standing water in tanks instead of running tap water for feeding purposes, the implementation of free-range management rather than intensive farming practices, and insufficient biosecurity protocols, among others. Given that the presence of E. coli in feces is often associated with an increased likelihood of enteric pathogens and/or diarrheal disease, and that the existence of E. coli on farms could potentially impact the downstream segments of the food industry chain (McAuley et al, 2017; Navab-Daneshmand et al, 2018). It is imperative for TBSF farms to implement appropriate management strategies in order to effectively mitigate E. coli cross-contamination.

For several decades, antibiotics were overused as feed additives and therapeutic agents. Consequently, ARGs are prevalent in farms and widely disseminated throughout the animal food chain (McNeece et al., 2014; Wang et al., 2019; Peng et al., 2022; Semedo et al., 2023). Despite the prohibition of antibiotic growth promoters in animal feed (Wang et al., 2020), relevant resistance genes remain prevalent in poultry batches and production. Some researchers suggested the continued prevalence and transmission of corresponding ARGs in animal farms may be attributed to the increased use of therapeutic antimicrobials following the government's prohibition of antibiotic growth promoters (Wen et al., 2022). Furthermore, antibiotics continued to be demonstrated as the most significant and direct selective pressures on bacterial antibiotic resistance (Larsson et al., 2022). In our study, although multidrug-resistant E. coli strains were isolated from various samples in TBSF farms and ARGs associated with different classes of antibiotics were detected in these E. coli genomes, meanwhile, network analysis revealed that few drug residues significantly influenced the ARGs and ARPs. No statistically significant correlation was observed between the drug residues present in the samples and the resistance phenotypes of E. coli strains obtained from those samples. For instance, tetracycline, a broad-spectrum antibiotic, was detected in only three samples in our study, compared with 18 tetracycline-resistant E. coli isolates. Furthermore, the E. coli strain isolated from a tetracycline-residue-positive sample was not resistant to any of the tetracycline antibiotics tested. Network analysis also revealed no significant correlation between tetracycline residues and tetracycline resistance genes. This finding contrasted with other studies that reported a significant correlation between the copy number of tetA gene and the concentrations of residual tetracyclines (Yoshizawa et al., 2020). Therefore, antibiotic residues in the TBSF farm environment may not be the sole major determinant contributing to the dissemination of ARGs.

Numerous studies verified that different types of ARGs exhibit distinct abilities and mechanisms for accumulating and spreading in the environment (Zhu et al., 2020). Some ARGs rapidly decreased in abundance or even disappeared following certain treatments, whereas persistent ARGs were retained or even enriched during particular treatment processes. Examples of such persistent ARGs included those conferring resistance to aminoglycosides, sulfonamides, beta-lactams, quinolones, and multidrug resistance genes (Su et al., 2015; Qian et al., 2016). These persistent ARGs were frequently carried by plasmids and other MGEs, and subsequently transferred to other environments via HGT (Mazhar et al., 2021; Dai et al., 2022). WGS revealed the presence of these persistent ARGs in the 34 E. coli strains examined in this study. The antibiotic resistance profiles of these E. coli strains were largely determined by plasmid-mediated persistent ARGs, particularly blaTEM and blaOXA conferring resistance to β-lactam antibiotics, tetA and tetR conferring resistance to tetracycline antibiotics, floR and cmlA conferring resistance to chloramphenicol antibiotics, qnrS conferring resistance to fluoroquinolone antibiotics, ant(3’’)-IIa, aph(3’’)-Ib, aph(6)-Id, aac(3)-IId, and aadA conferring resistance to aminoglycoside antibiotics, and the sul genes contributing to sulfonamide resistance. These persistent plasmid-associated ARGs were widely prevalent in TBSF breeding environments and contributed to the ARPs of E. coli strains isolated from these environments.

According to WGS, we also discovered that the same plasmid-associated ARGs in different E. coli strains from various samples predominantly shared the same genetic environment. It was evident that ARGs had been extensively disseminated in TBSF farms via HGT, particularly through plasmid-mediated gene dissemination. Plasmids-associated ARGs were identified in a wide range of environments (Che et al., 2019; Wang et al., 2024), and poultry farms were recognized as a major source of contamination and dissemination of antimicrobial resistance (Scicchitano et al., 2024). In our study, the resistance rates of E. coli isolates from feces were significantly higher than those from environmental samples for several types of antibiotics. This finding suggested, to a certain extent, that AMR indeed transferred from poultry farms to their surrounding environments. Previous studies also showed that the most prevalent resistance genes in multi-resistant plasmids harbored by E. coli hosts were those conferring resistance to tetracycline, aminoglycosides, β-lactams, and sulfonamides (Dang et al., 2017). These plasmid-associated ARGs transferred between different strains via conjugation, and stably maintained in both the parental bacteria and transconjugant hosts (Sun et al., 2019). In this study, numerous plasmid-mediated ARGs were found to be shared among several habitats, even in the absence of antibiotic selection pressure. Several factors influenced the transfer and dissemination of plasmid-mediated ARGs between different environments (Bengtsson-Palme et al., 2018; Zhu et al., 2020; Li et al., 2023). Flies, wild birds, dogs, and other animals in or around the farms played a significant role in the transmission of these ARGs due to inadequate biocontainment measures (Nguyen et al., 2015; Wang et al., 2017). Disinfectants also had a significant impact on the abundance and distribution of ARGs in animal farms (Ni et al., 2024). Co-selection of multi-antibiotic resistance in bacteria occurred when the environment was contaminated with heavy metals and microplastics (Imran et al., 2019). In addition to the aforementioned factors, various farm-related factors, including on-farm biosecurity measures, farm staff numbers, and others, also consistently influenced the abundance and transfer of ARGs in livestock and poultry farms (Caffrey et al., 2017; Yang et al., 2022).

In our study, the ARPs were consistently associated with the detection of corresponding ARGs in the E. coli isolates’ genome, specifically those related to β-lactam, tetracycline, chloramphenicol, and fluoroquinolone resistance. In all β-lactam antibiotic-resistant strains, the presence of blaTEM or blaOXA-10 genes, which encoded broad-spectrum β-lactamase found in many Gram-negative bacteria conferred resistance to penicillins and first-generation cephalosporins (Calderón et al., 2021), were responsible for resistance to ampicillin and amoxicillin. In contrast, β-lactam-susceptible strains did not harbor these β-lactam resistance genes. These findings were consistent with other relevant researches. For example, E. coli strains isolated from swine farms exhibited a high degree of concordance between β-lactam resistance phenotypes and the presence of β-lactamase genes (Bonvegna et al., 2022). All tetracycline-resistant strains possessed the tetA and tetR genes, whereas tetracycline-susceptible strains did not. The tetA gene encodes a tetracycline efflux pump protein found in many species of Gram-negative bacteria. The tetR encodes the repressor of the tetracycline resistance element. Its N-terminal region forms a helix-turn-helix structure that binds to DNA. Binding of tetracycline to TetR reduces the repressor's affinity for the promoter/operator sites of the tetracycline resistance gene tetA. Mutations arise within tetR result in reduced affinity for tetracycline. Tetracycline-resistant E. coli strains isolated from broiler meat also harbored the tetA gene (Alam et al., 2023). The floR gene, found in many bacterial species, was a plasmid or chromosome-encoded chloramphenicol exporter gene (Verner-Jeffreys et al., 2017;Shi et al, 2022; Che et al, 2023). All chloramphenicol-resistant strains in this study harbored the floR gene on their plasmids. The detection rate of the floR gene in chloramphenicol-resistance E. coli strains was significantly higher compared to other studies (White et al, 2000). This indicated an increased risk of HGT of the floR gene across TBSF breeding environments. In all fluoroquinolone-resistant strains, the qnrS gene and/or mutant gyrA gene were present. The qnrS gene was a plasmid-mediated gene that encoded a quinolone resistance protein, which protected the antibiotic target site (Kuo et al., 2022). Missense mutations at various positions in gyrA gene conferred differing levels of fluoroquinolone resistance (Liang et al., 2023). In this study, two E. coli strains isolated from fecal samples exhibited resistance to all tested fluoroquinolones, including enrofloxacin, ciprofloxacin, norfloxacin, levofloxacin, moxifloxacin, and flumequine. And both strains harbored missense mutations simultaneously in the gyrA, parC, and mdtH genes, and neither stain possessed the qnrS gene. These findings suggested that E. coli strains in the TBSF farm environment might predominantly enhance their fluoroquinolone resistance through altering antibiotic target proteins and increasing efflux pump efficiency. When missense mutations were detected simultaneously in the gyrA, parC, and mdtH genes within a single strain, the fluoroquinolone resistance level of that strain would be significantly elevated. All E. coli isolates in our study exhibited resistance to macrolides. This intrinsic resistance was attributed to the low permeability of the outer membrane, which limited antibiotic entry into the cells and thereby conferred natural resistance to macrolides (Phuc Nguyen et al., 2009; Dinos et al., 2017; Ma et al., 2024).

Co-transfer of multiple ARGs was frequently observed in this study, for example, the tetracycline resistance gene tetA and tetR, as well as the fluoroquinolone resistance gene qnrS. The backbone of the tetA-carrying plasmid pAsa8, which possesses multiple replicon types including IncN and IncF, harbored several antimicrobial resistance genes, namely tetA, tetR, blaTEM, sul1, dfrA, and ant(3’’)-Ⅱa. This co-transfer phenomenon was frequently observed (Wang et al., 2017; Sun et al., 2021), and was influenced by varying environmental pressures (Hughes et al., 2017). In most aminoglycosides-resistant E. coli strains, aminoglycoside resistance genes were frequently found on MGEs, such as plasmids and introgens, which also carried genes encoding resistance to chloramphenicols, sulfonamides, tetracyclines, and other antibiotics (Table S2). These genes encoding aminoglycoside-modifying enzymes were also found to be associated with extended-spectrum beta-lactamase genes in ESBL-producing E. coli (Alyamani et al., 2017) and other clinical E. coli isolates (Cirit et al., 2019; Qamar et al., 2023). Out of the 34 sulfadiazines-resistant E. coli isolates, 19 harbored either dihydropteroate synthase-encoding gene sul or the dihydrofolate reductase-encoding gene dfrA. WGS analysis demonstrated that the sul and dfrA genes were consistently co-selected with other ARGs in these E. coli isolates, a finding consistent with E. coli strains isolated from other environments (Murase et al., 2022).

Conclusion

The presence of multidrug resistance plasmids in E.coli isolates from TBSF farms highlighted the critical role of poultry as a high-impact reservoir for antibiotic resistance genes. Though no E. coli strains resistant to last-resort antibiotics, including colistin, carbapenems and tigecycline, were detected in the TBSF breeding environments in our study, corresponding resistance genes have been sporadically identified, such as the extended-spectrum beta-lactamase gene blaCTX-M in an E. coli isolate from a fecal sample and the mobile colistin resistance gene mcr-1 in an E. coli isolate from a soil sample. The lack of statistical correlation between drug residues in samples and the resistant phenotypes of E. coli strains raised concerns about the prevalence plasmid-mediated ARGs in TBSF farms. HGT of ARGs was frequently observed across various niches in TBSF farms. In addition to regulating antibiotic use, ensuring farm hygiene and implementing strong biocontainment measures may be the most effective strategies to reduce the HGT frequency of ARGs in TBSF farms. To further evaluate the impact of ARGs dissemination in TBSF farms on human health, additional studies are warranted to investigate the transmission routes of these ARGs and determine whether the exceptionally long drug residue time in TBSF exerts a strong selective pressure that drives the evolution and spread of these ARGs within their breeding environments.

Author contributions

D.Z., L.Z., and M.Y. designed the study. L.Z., Y.D., and Q.L. analyzed data for the work. X.Y. and Q.A. acquired the data. L.Y. and S.Q. verified the data. L.Z. and M.Y. wrote the manuscript. D.Z., S.Q., and Q.A. reviewed it critically.

Declaration of competing interest

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

Acknowledgements

This work was supported by Basic research and Talent training Program of Jiangxi Academy of Agricultural Sciences (Grant No. JXSNKYJCRC 202201), Basic research and Talent training Program of Jiangxi Academy of Agricultural Science (Grant No. JXSNKYJCRC202449), National Major Project for Risk Assessment of Quality and Safety of Agricultural Products (Grant No. GJFP20240302, Grant No. GJFP20230304).

Footnotes

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.psj.2025.105082.

Appendix. Supplementary materials

mmc1.zip (139.9KB, zip)

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