Comparison of Antibiotic Resistance Profiles of Salmonella Isolates from Retail Meats in Nanchang,China,in Two Periods

Abstract

Salmonella is one of the most important foodborne pathogens. In this article, a total of 160 Salmonella isolates recovered from retail meats in June–July 2018 (before COVID-19 outbreak) and December 2020–April 2021 (after COVID-19 outbreak) in Nanchang, China, were characterized for serotyping, antimicrobial susceptibility, and specific resistance gene screening. The prevalence of Salmonella Typhimurium increased from 5.4% in 2018 to 19.1% in 2021, and Salmonella Enteritidis increased from 3.3% in 2018 to 8.8% in 2021. Compared with those in June–July 2018, Salmonella isolates in December 2020–April 2021 demonstrated a significant increase in resistance to 13 tested antibiotics except for doxycycline and nitrofurantoin (p < 0.05). The Salmonella isolates in December 2020–April 2021 showed a higher presence of plasmid-mediated quinolone resistance genes (qnrA, qnrB, and qnrS), and mutations in the quinolone resistance-determining region (gyrA Asp87Asn, gyrA Asp87Tyr, parC Thr57Ser, and parC Ser80Ile). Whole-genome sequencing was used to analyze four polymyxin B-resistant strains. Some common mutation sites in eptC and micA were found in the four strains. Based on the data in this article, it indicated that antibiotic resistance was facilitated and more gene mutations related to quinolone resistance were developed.

Introduction

S almonella spp. is one of the most prevalent foodborne pathogens that can cause severe infections in humans. Salmonella (S.) enterica subspecies enterica is composed of more than 1500 serotypes (Lamas et al., 2018). Some serovars of S. enterica subspecies enterica (including serovar Typhimurium and serovar Enteritidis) are frequently associated with foodborne disease (Wei et al., 2019; Wu et al., 2021).

Globally, antimicrobial resistance (AMR) in Salmonella isolates has increased over the years and remains an issue of public health concern (Jajere, 2019). Recently, the increasing resistance toward clinically important antimicrobials such as fluoroquinolones and third-generation cephalosporins has become an emerging problem worldwide (Klemm et al., 2018; Kuang et al., 2018). Bacterial strains resistant to at least three classes of antibiotics are defined as multidrug resistant (MDR). MDR Salmonella isolates have been largely found from retail meats in China (Wang et al., 2021; Xu et al., 2020).

The mechanism of AMR in bacteria is complex. For example, quinolone resistance attributes to mutations in the quinolone resistance-determining region (QRDR) and plasmid-mediated quinolone resistance (PMQR) determinants (Hooper and Jacoby, 2015). The most common QRDR mutations have been localized to the amino terminal domains of GyrA or ParC (Campioni et al., 2017). PMQR-encoded resistance is mainly due to the Qnr proteins, including QnrA, QnrS, QnrB, QnrC, QnrD, and QnrVC. These qnr genes generally differ in sequence by 35% or more from each other (Hooper and Jacoby, 2015). Colistin (polymyxin E) and polymyxin B are considered last-line drugs for multidrug-resistant Gram-negative bacteria. Plasmid-mediated polymyxin resistance gene, termed as mcr, was widely disseminated all over the world (Ling et al., 2020). To our knowledge, multiple variants of mcr (mcr1 to mcr10) have been found and became popular (Hussein et al., 2021).

Nanchang is one of the important central cities of China. The information concerning Salmonella in Nanchang is still limited although previous studies have been undertaken in the other districts of China (Sun et al., 2021). Monitoring the AMR of foodborne pathogens is necessary as increasing consumption of disinfectant and antibiotics during the COVID-19 pandemic may have increased AMR (Lobie et al., 2021). Therefore, the aim of this study was to compare the AMR profiles of Salmonella food isolates collected in June–July 2018 (prepandemic) and December 2020–April 2021 (pandemic) in Nanchang, China. The prevalence of some AMR genes (PMQR, QRDR, and mcr) and strain serotypes was also screened. Whole-genome sequencing (WGS) was performed on four polymyxin B-resistant strains to investigate the genotypic characteristics.

Materials and Methods

Sample collection, Salmonella isolation, and identification

Sampling was conducted at two periods, June–July 2018 and December 2020–April 2021. A microbiological monitoring in 2018 summer has been carried out by the Jiangxi General Institute of Testing and Certification Food Testing Institute, as supported by a project. Raw pork and frozen chicken products were initially collected from several supermarkets and open markets in Nanchang, Jiangxi Province, China, during June–July 2018. All the samples were placed on ice and transferred to the laboratory within 2 h after collection. Then Salmonella strains were isolated and identified. To compare the AMR profiles of Salmonella spp. before and after the COVID-19 outbreak, we isolated Salmonella strains from raw pork and frozen chicken products in the same sampling markets during December 2020–April 2021, as supported by another project.

A total of 160 Salmonella strains were isolated by the cultivation methods according to the Chinese National Food Safety Standard (GB 4789.4-2016) and kept at −70°C for long-term storage. Then strains were identified using the VITEK^® 2 COMPACT automated microbial identification system (BioMérieux SA, Marcy l'Etoile, France). Serotyping was performed by slide agglutination using commercial Salmonella O and H antisera (Ningbo Tianrun Bio-pharmaceutical Co., LTD, China).

Jiangxi Institute of Testing is responsible for food safety testing, and there is no need to apply for this qualification for pathogen detection and screening in china.

Antimicrobial susceptibility testing

Antimicrobial susceptibility testing was performed using a broth microdilution method with the Mueller–Hinton medium in 96-well culture plates (CLSI, 2021). The following 15 antimicrobial compounds of eight classes were assessed: ampicillin (AMP), amoxicillin (AM), ceftazidime (CAZ), cefotaxime (CTX), ceftriaxone (CRO), chloramphenicol (CHL), ciprofloxacin (CIP), nalidixic acid (NAL), gentamicin (GEN), tetracycline (TET), sulfisoxazole (SIZ), streptomycin (STR), doxycycline (DOX), polymyxin B, and nitrofurantoin (NIT). Antibiotic drugs were purchased from Shanghai Yuanye Bio-Technology Co., Ltd. Escherichia coli ATCC25922 was used as the quality control strain. The minimum inhibitory concentration (MIC) results were interpreted as susceptible, intermediate, or resistant based on the 2021 Clinical and Laboratory Standards Institute breakpoints and the technical specification on antimicrobial susceptibility tests (WS/T 639-2018, China).

Detection of PMQR and mcr

Genomic DNA was extracted by using a commercial kit (Takara, Japan). PCR was performed using a BIO-RAD T100 cycler (BIO-RAD, USA). The PMQR genes, including qnrA, qnrB, and qnrS, were detected by PCR amplification as previously reported (Robicsek et al., 2006). PCR screening for mcr1 to mcr9 was carried out by simplex PCR as previously described (Borowiak et al., 2020). The PCR mixture included Taq™ DNA Polymerase 0.15 μL (Takara, Japan), 10 × Taq Buffer 2.5 μL, 2.5 mM dNTPMix 2 μL, 1 μL of each primer (10 μmol/L), 1 μL of bacterial DNA template, and distilled water to the final volume of 25 μL.

Detection of QRDR by real-time PCR

The four common QRDR mutations were detected in this study: gyrA Asp87Asn (GAC→AAC), gyrA Asp87Tyr (GAC→TAC), parC Thr57Ser (ACC→AGC), and parC Ser80Ile (AGC→ATC). We developed an SYBR green I-based real-time PCR to detect these mutations as the previous report suggested with some modifications (Baris et al., 2013). Namely, a series of published Salmonella sequences of gyrA and parC were downloaded from the National Center for Biotechnology Information (NCBI) website. Primer pairs were designed to amplify amplicons with specific substitution. To increase the specificity of the reaction, a mismatch at the −2 position of the 3′ end of forward primers was introduced automatically by the online software (PRIMER1: primer design for tetra-primer ARMS-PCR).

Real-time PCR was performed in a total volume of 25 μL containing 12.5 μL of 2 × SYBR Green PCR Master Mix (Wuhan Chuchengzhengmao Science and Engineering co. LTD, China), 0.5 μL of each primer (10 μM), 1 μL of the genomic DNA, and 10.5 μL of distilled water. The real-time PCR was performed using a BIO-RAD CFX 96 Touch cycler under the following conditions: predenaturation for 2 min at 95°C; 40 cycles of denaturation for 10 s at 95°C, annealing for 15 s, and extension for 30 s at 72°C. The primers designed in this study and the annealing temperatures are listed in Table 1.

Table 1.

PCR Primers for Quinolone Resistance-Determining Region Mutation Detection

Primer	Primer sequence (5′-33′)	Annealing temperature (°C)	Size (bp)
parCF Thr57Ser	TGCGATGTCAGAGCTGGGGCTGAACGAGA	61.6	413
parCR Thr57Ser	GGTTGTGCGGCGGGATATCTGTTG
parCF Ser80Ile	TAAGTATCATCCGCACGGCCTCA	56.8	256
parCR Ser80Ile	TAACATCATCGGTTCCTGCATC
gyrAF Asp87Tyr	CGGTGATTCCGCAGTGTGT	56.2	384
gyrAR Asp87Tyr	TGCCCTTCAATGCTGATGTGTT
gyrAF Asp87Asn	TCGTCGATTCCGCAGTGTAT	55.5	385
gyrAR Asp87Asn	TGCCCTTCAATGCTGATGTGTT

The mismatch at the −2 position of the 3′ end of the QRDR primers is underlined and the test substitution of each QRDR gene is highlighted with box.

QRDR, quinolone resistance-determining region.

To validate the specificity of real-time PCR, 10 Salmonella strains performed PCR amplification of the entire gyrA and parC genes and DNA sequencing. Sequence data were analyzed by comparison with QRDR mutations obtained from real-time PCR.

Whole-genome sequencing

Four polymyxin B-resistant strains isolated during December 2020–April 2021 were sent to Shanghai Majorbio Bio-Pharm Technology Co., Ltd to perform WGS by using the PacBio RS II and the Illumina HiSeq X-10 platforms (Majorbio Inc., China). Raw reads were subjected to adapter clipping and quality filtering, and the obtained clean reads were assembled de novo by Unicycler v0.4.7, SPAdes 3.13.0, and GapCloser 1.12 software. Gene prediction was done by RAST 2.0, and AMR genes were identified using ResFinder 4.1 and CARD.

Statistical analysis

Statistical analysis was done by IBM SPSS Statistics 25 software. The chi-square test was used to compare the difference between two groups. Significance was set at p < 0.05 and any difference with p < 0.01 was regarded as highly significant.

Results and Discussion

Serotypes of Salmonella isolated from retail meats

The retail meats taken during June–July 2018 showed a high Salmonella isolation rate (55%). A total of 92 Salmonella were isolated from 167 raw pork and frozen chicken products. The Salmonella isolation rate during December 2020–April 2021 increased to 66.7% (68/102). Actually, seasonal occurrence of Salmonella contamination has been often reported. A higher isolation rate was usually obtained during summer, and a lower isolation rate was obtained during winter. Zdragas et al. (2012) found that the isolation rate of Salmonella in carcasses was 60.4% in summer and 18.7% in winter. Increased prevalence during summer months was positively correlated with the enhanced persistence of Salmonella in warm temperature (Burjaq and Abu-Romman, 2020).

Therefore, in this study, although there was no significant difference in the detection rate of Salmonella between the two periods (p > 0.05), the increase of Salmonella contamination in Nanchang is clearly evident and may pose a foodborne illness risk.

As we used a commercial Salmonella O and H antisera kit, which can only identify the 30 most common serovars of Salmonella in China, 51 strains could not be typed in this study. The left Salmonella isolates were serotyped into 24 distinct serovars (Table 2). In the strains isolated during June–July 2018, 18 serotypes were identified. Salmonella Rissen was the dominant serovar (13.0%), followed by Salmonella Stanleyville (7.6%), Salmonella Essen (6.5%), and Salmonella Weltevreden (6.5%) (Table 2). In the strains isolated during December 2020–April 2021, 12 serotypes were identified. Of these, the predominant serotypes were Salmonella Typhimurium (19.1%), Salmonella Weltevreden (10.3%), and Salmonella Enteritidis (8.8%). Serovars such as Salmonella Typhimurium and Salmonella Enteritidis are frequently associated with foodborne disease (Wei et al., 2019; Wu et al., 2021).

Table 2.

Salmonella Serotypes Identified in the Two Periods

	No. of strains/total tested strains (%)
Salmonella serovar	June–July 2018	December 2020–April 2021
Salmonella Rissen	12/92 (13.0)	0/68 (0)
Salmonella Stanleyville	7/92 (7.6)	5/68 (7.4)
Salmonella Essen	6/92 (6.5)	0/68 (0)
Salmonella Weltevreden	6/92 (6.5)	7/68 (10.3)
Salmonella Typhimurium	5/92 (5.4)	13/68 (19.1)
Salmonella Derby	4/92 (4.3)	0/68 (0)
Salmonella Enteritidis	3/92 (3.3)	6/68 (8.8)
Salmonella Infantis	3/92 (3.3)	0/68 (0)
Salmonella Senftenberg	3/92 (3.3)	0/68 (0)
Salmonella Chester	3/92 (3.3)	0/68 (0)
Salmonella Kentucky	2/92 (2.2)	5/68 (7.4)
Salmonella Agona	2/92 (2.2)	1/68 (1.5)
Salmonella Virchow	2/92 (2.2)	0/68 (0)
Salmonella Riggil	2/92 (2.2)	0/68 (0)
Salmonella Clerkenwell	2/92 (2.2)	0/68 (0)
Salmonella Heidelberg	2/92 (2.2)	0/68 (0)
Salmonella Stratford	1/92 (1.1)	0/68 (0)
Salmonella Regent	1/92 (1.1)	0/68 (0)
Salmonella Reading	0/92 (0)	1/68 (1.5)
Salmonella Emek	0/92 (0)	1/68 (1.5)
Salmonella Dublin	0/92 (0)	1/68 (1.5)
Salmonella Bonn	0/92 (0)	1/68 (1.5)
Salmonella Schwarzengrund	0/92 (0)	1/68 (1.5)
Salmonella Give	0/92 (0)	1/68 (1.5)
Untyped	26/92 (28.3)	25/68 (36.8)

In this study, the prevalence of Salmonella Typhimurium increased from 5.4% in 2018 to 19.1% in 2021, and Salmonella Enteritidis increased from 3.3% in 2018 to 8.8% in 2021. Tang isolated 105 Salmonella strains from 22 farms and 2 markets in the Zhejiang Province and Fujian Province in the eastern part of China (Tang et al., 2022). Only 4 serotypes were isolated in the Fujian Province, of which serotype Weltevreden was isolated only in the Fujian Province. There were 11 serotypes isolated in the Zhejiang Province, among which serotypes Enteritidis, Indiana, Lerum, Mbandaka, Meleagridis, Agona, Corvallis, and Rissen were only isolated in the Zhejiang Province. The prevalent serovars differed in different parts of China.

Antimicrobial susceptibility

During June–July 2018, 79.3% (73/92) of Salmonella were MDR strains, while 100.0% (68/68) of Salmonella isolated during December 2020–April 2021 were MDR strains. It was worth noting that all Salmonella Typhimurium and Salmonella Enteritidis identified in this study are MDR isolates and resistant to at least three classes of antibiotics, indicating the potential high risks. All isolates were resistant to at least one of the tested antibiotics. Compared with June–July 2018, higher resistance rates against all of the tested antibiotics were observed during December 2020–April 2021 (Fig. 1). Except for DOX and NIT, there were significant differences in the resistance rate between the 2 years (p < 0.05) (Fig. 1). The isolates during June–July 2018 showed the highest resistance rate against DOX (92.4%), followed by TET (81.5%) and AMP (66.3%).

FIG. 1.

Distribution of antimicrobial resistance in Salmonella strains isolated from June to July 2018 and from December 2020 to April 2021. The difference in antimicrobial resistance was compared between Salmonella strains. *p < 0.05, **p < 0.01. AM, amoxicillin; AMP, ampicillin; CAZ, ceftazidime; CHL, chloramphenicol; CIP, ciprofloxacin; CRO, ceftriaxone; CTX, cefotaxime; DOX, doxycycline; GEN, gentamicin; NAL, nalidixic acid; NIT, nitrofurantoin; SIZ, sulfisoxazole; STR, streptomycin; TET, tetracycline.

However, the isolates during December 2020–April 2021 exhibited the highest resistance rate against SIZ (97.1%), followed by TET (94.1%) and DOX (94.1%). Low resistance rate was observed for polymyxin B. Only 5 out of 92 (5.4%) isolates during June–July 2018 showed resistance to polymyxin B, and 10 out of 68 (14.7%) isolates during December 2020–April 2021 were resistant to polymyxin B. Our results were in good agreement with some Chinese authors' reports (Li et al., 2022a; Li et al., 2022b; Teng et al., 2022). They isolated Salmonella strains from farms, markets, and companion animals in China and found that most Salmonella isolates were MDR. The antibiotics of the most prevalent resistance were STR, TET, NAL, CIP, and AMP, etc. Tang also found that only 11 out of 105 (10%) isolates were polymyxin E resistant (Tang et al., 2022).

Detection of PMQR and mcr

The previous reports suggested that qnrA, qnrB, and qnrS were the common PMQR genes identified in Chinese retail meats and farm animals (Zhao et al., 2017). Therefore, only qnrA, qnrB, and qnrS were screened in the 93 quinolone-resistant isolates. Only 8 out of 34 (23.5%) quinolone-resistant isolates during June–July 2018 harbored qnrS (Table 3). However, qnrA and qnrB were not detected in the isolates. For quinolone-resistant isolates during December 2020–April 2021, 17 out of 59 (28.8%) harbored at least one PMQR gene. The most frequent PMQR gene was qnrS, which was detected in 25.4% (15/59) of isolates (Table 3). The qnrA gene was detected in 5.1% (3/59) of isolates and the qnrB gene was detected in 3.4% (2/59) of isolates.

Table 3.

Detection Results of Plasmid-Mediated Quinolone Resistance, mcr, and Quinolone Resistance-Determining Region Mutation in Salmonella Isolates

	No. of strains/total tested strains (%)
Detection gene	June–July 2018	December 2020–April 2021
qnrS	8/34 (23.5)	15/59 (25.4)
qnrB	0/34 (0)	3/59 (5.1)
qnrA	0/34 (0)	2/59 (3.4)
gyrA Asp87Asn	0/34 (0)	4/59 (6.8)
gyrA Asp87Tyr	4/34 (11.8)	6/59 (10.2)
parC Thr57Ser	5/34 (14.7)	3/59 (5.1)
parC Ser80Ile	0/34 (0)	1/59 (1.7)
gyrA Asp87Tyr + gyrA Asp87Asn	0/34 (0)	8/59 (13.6)
gyrA Asp87Asn + parC Thr57Ser	7/34 (20.6)	3/59 (5.1)
parC Thr57Ser + parC Ser80Ile	3/34 (8.8)	3/59 (5.1)
gyrA Asp87Asn + gyrA Asp87Tyr + parC Thr57Ser	1/34 (2.9)	5/59 (8.5)
gyrA Asp87Asn + parC Thr57Ser + parC Ser80Ile	7/34 (20.6)	11/59 (18.6)
gyrA Asp87Asn + gyrA Asp87Tyr + parC Thr57Ser + parC Ser80Ile	0/34 (0)	8/59 (13.6)
mcr-1	1/10 (1.0)	0/5 (0)
mcr-2	0/10 (0)	0/5 (0)
mcr-3	0/10 (0)	0/5 (0)
mcr-4	0/10 (0)	0/5 (0)
mcr-5	0/10 (0)	0/5 (0)
mcr-6	0/10 (0)	0/5 (0)
mcr-7	0/10 (0)	0/5 (0)
mcr-8	0/10 (0)	0/5 (0)
mcr-9	0/10 (0)	0/5 (0)

Sampling time represents June–July 2018 and December 2020–April 2021, respectively. Plasmid-mediated quinolone resistance and plasmid-mediated quinolone resistance mutation were screened in the quinolone-resistant isolates. The mcr genes were screened in the polymyxin B-resistant isolates.

The primary mechanism of polymyxin resistance in Gram-negative bacteria involves the modification of lipid A of lipopolysaccharide (LPS), which is a major component of the outer membrane and the initial target of polymyxins. The mcr genes encode for pEtN transferase enzymes, which catalyze the addition of pEtN to the phosphate groups in lipid A. The modification of lipid A results in reduced polymyxin B affinity, thus causing polymyxin B resistance (Nang et al., 2019). The mcr1–mcr9 genes were screened in this study to provide more information regarding mcr dissemination. The mcr genes were rarely identified in the 15 polymyxin B-resistant Salmonella strains in this article. Only one strain was identified to be positive for mcr-1 (Table 3).

QRDR mutations in gyrA and parC genes

We developed a real-time PCR to detect QRDR mutations. Ten Salmonella strains also performed the PCR amplification of the entire gyrA and parC genes. QRDR mutations were obtained by the sequencing data and real-time PCR. The two methods were compared and showed the same results, thus validating the accuracy of real-time PCR. The four common QRDR mutations were then detected for 93 quinolone-resistant isolates in this study by real-time PCR. The majority of quinolone resistant isolates in the study showed a QRDR with mutations. Only 14 strains (7 in 2018 and 7 in 2021) did not show the tested QRDR mutations. Triple mutations (Asp87Asn in gyrA, Thr57Ser and Ser80Ile in parC) were most frequent (Table 3).

The substitutions in gyrA and parC were more common in the isolates during December 2020–April 2021 (52/59, 88%) in comparison with the isolates during June–July 2018 (27/34, 79.4%). Eight isolates recovered during December 2020–April 2021 harbored the tested four point mutations (Table 3). The Salmonella isolates during December 2020–April 2021 showed more genetic mutation diversity.

Whole-genome sequencing

The four polymyxin B-resistant and mcr-negative strains were sequenced and the general features of the genomes are summarized in Table 4. Only strain JXY0409-18 carried an AMR plasmid (NCBI: CP084217.1), which harbored 21 resistance genes including qnrS1. For the other three strains, the resistance genes were located on the chromosomes.

Table 4.

Genome Sequencing Features, Assembly, Common Resistance Genes, and Amino Acid Substitution Results of Salmonella Isolates

	A7	A29–2	A39	JXY0409-18
Plasmid quantity	2	3	2	4
Genome size (bp)	4687652	4897365	4992015	4877564
G + C (%) content	52.22	52.22	52.18	51.78
Sequencing depth	167.47	249.64	267.6	239.6
Number of antibiotic resistance genes	10	19	7	24
Amino acid substitutions in EptC	Glu370Ala	Glu370Ala	Glu370Ala	Glu370Ala
Amino acid substitutions in MicA	Lys91Glu, Thr131Ala, Cys266Arg, Tyr279 His, Tyr290His, Arg292Gly	Lys91Glu, Thr131Ala, Cys228Arg, Ser234Pro, Cys266Arg, Tyr279 His, Arg292Gly	Thr131Ala, Cys228Arg, Ser234Pro, Cys266Arg, Tyr279 His, Tyr290His	Lys91Glu, Thr131Ala, Cys228Arg, Ser234Pro, Cys266Arg, Tyr279 His, Tyr290His, Arg292Gly

Both A7 and A29-2 had a polymyxin-B MIC of 32 μg/mL. A39 had a polymyxin-B MIC of 8 μg/mL. JXY0409-18 exhibited a polymyxin-B MIC of 4 μg/mL. The MIC of ≥4 μg/mL was defined as polymyxin B resistant (CLSI, 2021). Modulation of the two-component regulatory systems PmrA/PmrB and PhoP/PhoQ can affect lipid A modification and also confers resistance to polymyxin B (Sato et al., 2018). In this study, we identified missense mutations in the two-component systems PhoP/PhoQ and PmrA/PmrB. We screened the PhoP/PhoQ- and PmrA/PmrB-regulated genes such as eptA, eptB, eptC, pmrA, pmrB, mgrB, micA, phoP, phoQ, lpxA, lpxC, and lpxD. The four sequenced strains shared several common mutations in the same loci of eptC and micA (Table 4).

Although information is limited, it has been reported that MicA- and EptC-encoded proteins control LPS synthesis and modification (Klein and Raina, 2019). Therefore, the relationship between the mutations in micA and eptC and the resistance enhancement of polymyxin B should be studied further.

Conclusion

There has been growing concerns that COVID-19 might be contributing to AMR (Subramanya et al., 2021). In Nanchang, monitoring foodborne pathogens in the food chain by the official authorities is not continuous and does not include the AMR evaluation. In this study, compared with those during June–July 2018, the antibiotic resistance of Salmonella isolates during December 2020–April 2021 increased and more gene mutations related to resistance were developed. Although the Salmonella strains were isolated from a small time range, our article provided data on the growing resistance of Salmonella isolates from food source. As the cause of antibiotic resistance is multifactorial, the level of the prevalence of antibiotic resistance in the different food chains should be continually monitored. WGS-based prediction of bacterial antibiotic resistance becomes more widespread.

However, the WGS process is currently too slow and expensive and classical PCR-based screening methods are still needed for large samples. The combination of WGS and traditional phenotypic resistance data can produce powerful results to discover new resistance mechanisms.

Footnotes

Authors' Contributions

X.L. was responsible for investigation and interpretation of results. P.Z. was responsible for sample collection and identification. Z.L., L.D., T.Z., X.W., D.M., and Y.Q. contributed to the experiments and data analysis. W.B. was responsible for the conception of the study and supervised the study. R.L. provided funds and wrote the article.

Accession Number(s)

The complete nucleotide sequences of A7, A29-2, A39, and JXY0409-18 have been deposited in the GenBank nucleotide database under accession numbers CP084001.1, CP083731.1, CP084194.1, and CP084216.1, respectively.

Disclosure Statement

We declare that we have no conflicts of interest.

Funding Information

This work was funded by the Jiangxi Quality Supervision and Administration Bureau (Grant Nos. GSJK202104 and GSJK202201).

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