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  1. bookVolume 66 (2022): Edizione 4 (December 2022)
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Analysis of antimicrobial resistance and genetic correlations of Escherichia coli in dairy cow mastitis

Ke Li,
Ke Li,
Mingyuan Hou,
Mingyuan Hou,
Lin Zhang,
Lin Zhang,
Mengyue Tian,
Mengyue Tian,
Ming Yang,
Ming Yang,
Li Jia,
Li Jia,
Yanyan Liang,
Yanyan Liang,
Dongmin Zou,
Dongmin Zou,
Ruonan Liu e
Ruonan Liu e
Yuzhong Ma
Yuzhong Ma
Pubblicato online: 04 Nov 2022
Volume & Edizione: Volume 66 (2022) - Edizione 4 (December 2022)
Pagine: 571 - 579
Ricevuto: 23 Mar 2022
Accettato: 28 Sep 2022
Journal of Veterinary Research's Cover Image
Journal of Veterinary Research
Dettagli della rivista
License
Formato
Rivista
eISSN
2450-8608
Prima pubblicazione
30 Mar 2016
Frequenza di pubblicazione
4 volte all'anno
Lingue
Inglese
Introduction

Dairy cow mastitis is a disease that is common on more than one continent and causes a decline in milk production and quality, leading to significant economic losses in the dairy industry (36). Escherichia coli is an important mammary pathogen in the environment of dairy farms and is closely associated with severe inflammatory symptoms (15). Currently, antibiotics are widely used to prevent and treat dairy cow mastitis. In the United States of America, it has been estimated that more than 80% of the total administered volume of antibiotics was used in animal production activities (14). Although the usage of antimicrobials usually brings positive effects, the problem of antimicrobial resistance (AMR) has also emerged (18). A nationwide study was conducted in China to determine the extent of AMR in common mastitis pathogens (including E. coli) infecting dairy herds and the study showed its increasing prevalence (9). Antimicrobial resistance reduced the cure rates of cow mastitis and posed a grave threat to public health and animal welfare (42).

Antimicrobial-resistant bacteria often harbour antibiotic resistance genes, which is proven to be a driving factor in drug resistance (39). These bacteria can spread among different hosts, which transduce antibiotic resistance genes to strains which may in some cases already possess certain drug resistance, leading to the emergence of multi-drug-resistant (MDR) bacteria (35).

As a clonally structured population, E. coli was classified into different phylogenetic groups and clonal complexes (CCs) by multilocus sequence typing (MLST) (23). By comparing database sequence records with the MLST results, specific housekeeping genes of E. coli were indicated to denote different STs; such a comparison was considered a reliable molecular typing method to explore the genetic correlations of microbial populations (24). Recent epidemiological investigations suggested that the antibiotic resistance of E. coli strains exhibited diversity in different microbial populations. It also brought more challenges to the prevention and treatment of dairy cow mastitis in veterinary clinics (32). In the face of the growing problem of antibiotic resistance and the potential threat to human health, it is necessary to analyse the antibiotic resistance of different E. coli populations. The objectives of the study were to understand the current state of antimicrobial resistance and the genetic characteristics of E. coli strains from dairy cow mastitis and to provide information helpful for the rational use of antibiotics in clinics.
Material and Methods

Sample collection and E. coli isolation. Between June 2019 and October 2021, 196 mastitis milk samples were collected from different dairy farms located in Xushui, Qingyuan, Quyang, and Mancheng in northern China. The criteria defining clinical mastitis were local pain in the mammary gland area accompanied by severe or general signs of inflammation, including swelling of the udder, tenderness to touch, fever, and depression (30, 40). Following convention, the teat was disinfected with 2% iodine tincture and 75% ethanol and the three initial streams were forestripped. Milk samples were aseptically collected in sterile tubes immediately. The samples were put on ice and sent to the laboratory within 4 h. A 10 μL volume of milk was aerobically cultured at 37℃ for 12 h in blood agar (Aobox, Beijing, China) with 5% sheep blood. Primary identification of the E. coli isolates was based on the characteristics of a Gram stain and growth on Eosin-Methylene Blue (EMB) Agar (Solarbio, Beijing, China). The 16S rDNA of all isolates was amplified in a PCR using 27F (5ʹ-AGAGTT TGATCMTGGCTCAG-3ʹ) and 1492R (5ʹ-TACGGY TACCTTGTTACGACTT-3ʹ) universal primers (37). The reaction procedures were as follows: 300 s at 95℃ followed by 35 cycles of 30 s at 95℃, 30 s at 57℃ and 60 s at 72℃. The PCR products were sequenced by Shanghai Sangon Biotech Co., Ltd (China) and compared with the sequences logged in GenBank. The confirmed E. coli isolates were stored in 25% sterile glycerol at −80℃.

Antimicrobial susceptibility test of E. coli isolates. Susceptibility to antimicrobial agents was determined by the Kirby–Bauer method as described by the Clinical Laboratory Standards Institute (CLSI) guidelines (11). Confirmed isolates of E. coli were tested for susceptibility to 13 antimicrobial agents commonly used in China. The preparations included beta-lactams, aminoglycosides, macrolides, tetracyclines, sulfonamides and quinolones; the selection was ampicillin (AMP, 10 μg), amoxicillin (AMX, 10 μg), ceftriaxone (CRO, 30 μg), cefazolin (CFZ, 30 μg), gentamicin (GEN, 10 μg), streptomycin (STR, 10 μg), neomycin (NER, 30 μg), amikacin (AMI, 30 μg), erythromycin (EM, 15 μg), doxycycline (DOX, 30 μg), trimethoprim-sulfamethoxazole (SXT, 25 μg), ciprofloxacin (CIP, 5 μg) and enrofloxacin (ENR, 5 μg). The antimicrobial agents were purchased from the China Institute of Veterinary Drugs Control. Multidrug resistance (MDR) was defined as resistance to three or more classes of antibiotics. Escherichia coli ATCC 25922 was used as a reference strain.

DNA extraction. A single colony from a fresh bacterial culture on EMB Agar was picked and inoculated into 5 mL of fresh Luria–Bertani broth and incubated with shaking for 12 h. Extraction of DNA was achieved using the DNA Quick extraction kit (Tiangen, Beijing, China) following the manufacturer’s instructions. All DNA preparation concentrations were measured using a Nanodrop ND-2000 spectrophotometer (ThermoFisher Scientific, Waltham, MA, USA) and adjusted to be approximately 100 ng/mL. The DNA extracts were stored at −20℃.

MLST and phylogenetic group. One pair of primers for each of the adk, fumC, gyrB, icd, mdh, purA and recA housekeeping genes was designed utilising data from a public MLST database (https://pubmlst.org/data) and then used in a PCR (43). The reaction procedure was as follows: initial denaturation at 94℃ for 5 min, 35 cycles of denaturation at 94℃ for 45 s, annealing at different temperatures for 45 s (Table 1), extension at 72℃ for 60 s, and final extension at 72℃ for 7 min. The products were sequenced by Shanghai Sangon Biotech Co., Ltd. The sequences of housekeeping genes were processed by BioEdit (https://www.bioedit.com) to obtain the housekeeping gene number and they were submitted to the Achtman online database (http://enterobase.warwick.ac.uk/species/index/ecoli) for comparison. Each isolate’s ST was acquired from the database. A minimum spanning tree was built using the goeBURST algorithm in Phyloviz1.0 software (http://www.phyloviz.net) (38). Subsequently, the sequences were further trimmed and concatenated (3,370 bp) to conduct molecular phylogenetic analysis using the maximum likelihood method in MEGA 7.0. Bootstrapping with 1,000 replicates was applied to estimate the reliability of the phylogenetic tree. The tree was visualised with iTOL online software (https://itol.embl.de) to analyse the distribution of drug resistance genes and resistance phenotype in the E. coli isolates.

Primer sequences, product sizes, annealing temperature and references used for the PCR in the study

Gene Primer sequence (5′–3′) Product size (bp) Annealing temperature (℃) Reference or GenBank accession no.
blaTEM ATAAAATTCTTGAAGACGAAA GACAGTTACCAATGCTTAATC 643 53 (25)
blaSHV TTTGTCGCTTCTTTACTCGCCTTTA GCCAGATCCATTTCTATCATGCCTA 198 56 DQ247972
blaOXA TCAACTTTCAAGATCGCA GTGTGTTTAGAATGGTGA 591 53 (25)
aac(2') ACTGTGATGGGATACGCGTC CTCCGTCAGCGTTTCAGCTA 482 54 (26)
aacA4 CTTCAGGATGGCAAGTTGGT TCATCTCGTTCTCCGCTCAT 286 55 (26)
aadA CTGGAGGTCACTGTCGTGC CCGTGGATTGCCAAAGGTC 274 55 X68089
erm(B) AAAACTTACCCGCCATACCA TTTGGCGTGTTTCATTGCTT 126 53 MN461246
erm(C) GCTCGTGTCATTTCTGGGAGT AGCCTAGCAGCCATTTCTATC 375 53 GQ483470
tet(A) CGGAGCAGAAACAAGAAAGCG GGATCAGGACCGGATACACCAT 345 57 (26)
tet(B) CATTAATAGGCGCATCGCTG TGAAGGTCATCGATAGCAGG 391 53 (26)
sul1 GCCTGGAACTGCTGCTGATGC TCGCCTGCCAAACCGAACTCT 314 59 (27)
sul2 GCGCTCAAGGCAGATGGCATT GCGTTTGATACCGGCACCCGT 793 57 (27)
qnrB GATCGTGAAAGCCAGAAAGG ACGATGCCTGGTAGTTGTCC 513 55 (25)
adk ATTCTGCTTGGCGCTCCGGG CCGTCAACTTTCGCGTATTT 583 54 (20)
fumC TCACAGGTCGCCAGCGCTTC GTACGCAGCGAAAAAGATTC 806 54 (20)
gyrB TCGGCGACACGGATGACGGC ATCAGGCCTTCACGCGCATC 911 60 (20)
icd ATGGAAAGTAAAGTAGTTGTTCCGGCACA GGACGCAGCAGGATCTGTT 878 54 (20)
mdh ATGAAAGTCGCAGTCCTCGGCGCTGCTGGCGG TTAACGAACTCCTGCCCCAGAGCGATATCTTTCTT 932 60 (20)
purA CGCGCTGATGAAAGAGATGA CATACGGTAAGCCACGCAGA 816 54 (20)
recA CGCATTCGCTTTACCCTGACC TCGTCGAAATCTACGGACCGGA 780 58 (20)

Detection of antimicrobial resistance genes. Genes were detected by PCR with resistance to the following antimicrobials: beta-lactams (blaTEM, blaSHV and blaOXA), aminoglycosides (aac(2'), aacA4 and aadA), macrolides (erm(B) and erm(C)), tetracyclines (tet(A) and tet(B)), sulfonamides (sul1 and sul2) and quinolones (qnrB) (1, 2, 28, 44). The reaction procedure of PCR was as follows: initial denaturation at 94℃ for 5 min, 30 cycles of denaturation at 94℃ for 30 s, annealing at different temperatures for 30 s (Table 1), extension at 72℃ for 30 s, and final extension at 72℃ for 10 min. PCR products were visualised by 1% agarose gel electrophoresis.

Statistical analysis. The chi-squared test and Pearson’s correlation coefficient were used to compare the correlations between an isolate’s resistance to a particular antibiotic and the isolate’s possession of the corresponding resistance gene. The significance level was set at P < 0.05 for statistical procedures. All analyses were conducted using SPSS 21.0 (SPSS Inc., Chicago, IL, USA).
Results

Isolates. Overall, 40 (20.41%) E. coli isolates from the 196 tested milk samples were culture-positive. The isolation rates of E. coli in Xushui, Qingyuan, Quyang and Mancheng were 22.22% (16/72), 24.14% (7/29), 17.86% (5/28) and 17.91% (12/67), respectively.

Antimicrobial susceptibility testing. The results of the susceptibility test were interpreted according to the criteria of the CLSI (Table 2). Antimicrobial susceptibility tests showed that most of the isolates were resistant to CFZ (77.5%), SXT (55.0%) and AMP (52.5%). In contrast, most isolates were susceptible to AMI (95.0%), CIP (82.5%) and GEN (67.5%). In addition, some E. coli isolates were classified as intermediate susceptible to EM (52.5%), NER (37.5%), and ENR (27.5%) (Table 2). For analysis, intermediate susceptibility was considered as resistance (7). In this study, 29 (72.5%) MDR E. coli strains were detected. The most common antimicrobial resistance profile was AMP-AMX-CRO-CFZ-GEN-STR-NER-EM-DOX-SXT-CIP-ENR (n = 4, 13.8%). Resistance to eight antibacterial drugs was the most common occurrence of multiple resistance (n = 6, 20.7%) (Table 3).

Susceptibility of 40 E. coli strains to 13 antibiotics commonly used in China

Antibiotic Distribution of E. coli strains (number of strains/%) Decision criteria/Diameter of inhibitory zone (mm)
R1 I S R I S
Ampicillin 21/52.5% 6/15.0% 13/32.5% ≤13 14–16 ≥17
Amoxicillin 18/45.0% 3/7.5% 19/47.5% ≤13 14–17 ≥18
Ceftriaxone 19/47.5% 1/2.5% 20/50.0% ≤19 20–23 ≥24
Cefazolin 31/77.5% 8/20.0% 1/2.5% ≤19 20–22 ≥23
Gentamicin 13/32.5% 0 27/67.5% ≤12 13–14 ≥15
Streptomycin 12/30.0% 5/12.5% 23/57.5% ≤11 12–14 ≥15
Neomycin 1/2.5% 15/37.5% 24/60.0% ≤11 12–16 ≥17
Amikacin 1/2.5% 1/2.5% 38/95.0% ≤14 15–16 ≥17
Erythromycin 17/42.5% 21/52.5% 2/5.0% ≤13 14–22 ≥23
Doxycycline 14/35.0% 5/12.5% 21/52.5% ≤10 11–13 ≥14
Trimethoprim- sulfamethoxazole 22/55.0% 0 18/45.0% ≤12 13–16 ≥17
Ciprofloxacin 7/17.5% 0 33/82.5% ≤15 16–20 ≥21
Enrofloxacin 6/5.0% 11/27.5% 23/57.5% ≤15 16–23 ≥24

R – resistant; I – intermediate; S – susceptible

Sequence types, resistance phenotypes and resistance genes in 40 E. coli strains

ID Location MLST Resistance phenotypes Resistance genes
1 Xushui ST10 AMP-AMX-CRO-CFZ-GEN-STR-EM-DOX-SXT-ENR aadA, qnrB
2 Xushui ST10 AMP-AMX-CRO-CFZ-GEN-STR-NER-EM-DOX-SXT-CIP-ENR aadA, tet(B)
3 Xushui ST359 AMP-AMX-CRO-CFZ-GEN-STR-NER-EM-DOX-SXT-CIP-ENR blaSHV, aadA
4 Xushui ST10 CFZ-EM aadA, tet(B), sul2
5 Xushui ST10 AMP-AMX-CRO-CFZ-STR-NER-EM-DOX-SXT-CIP-ENR aadA, sul2
6 Xushui ST1585 AMP-AMX-CRO-CFZ-GEN-STR-NER-EM-DOX-SXT-CIP-ENR aacA4, aadA
7 Xushui ST359 AMP-AMX-CRO-CFZ-GEN-STR-NER-AMI-EM-DOX-SXT-CIP-ENR blaSHV, blaOXA, aadA
8 Xushui ST359 AMP-AMX-CRO-CFZ-GEN-NER-EM-DOX-SXT-ENR blaOXA, aacA4, aadA
9 Xushui ST359 AMP-AMX-CRO-CFZ-GEN-STR-EM-DOX-SXT-CIP-ENR blaSHV, blaOXA, aadA, tet(B)
10 Xushui ST10 CFZ-EM aadA, sul2
11 Xushui ST10 CFZ-EM aadA, tet(B), sul2
12 Xushui ST359 AMP-AMX-CRO-CFZ-GEN-NER-EM-SXT-ENR blaOXA, aadA, sul2
13 Xushui ST1125 AMP-AMX-CRO-CFZ-STR-SXT aadA, tet(B)
14 Xushui ST1585 AMP-AMX-CRO-CFZ-EM-DOX-SXT-ENR blaSHV, aadA, tet(B)
15 Xushui ST327 AMP-AMX-CRO-CFZ-EM-DOX-ENR aadA, tet(B)
16 Xushui ST937 AMP-AMX-CRO-CFZ-STR-EM-SXT-ENR aadA, tet(B)
17 Qingyuan ST10717 AMP-CFZ-STR-NER-EM-DOX-SXT aac(2ʹ), aadA, erm(B), tet(A), tet(B)
18 Qingyuan ST942 CFZ-NER-EM-DOX erm(B), tet(A), sul1, sul2
19 Qingyuan ST446 AMP-CFZ-GEN-STR-NER-EM-DOX-SXT aac(2ʹ), aadA, erm(B), tet(A), tet(B)
20 Qingyuan ST1310 AMP-AMX-CRO-CFZ-GEN-STR-NER-AMI-EM aac(2ʹ), erm(B), tet(A), tet(B), sul2
21 Qingyuan ST515 AMP-AMX-CRO-CFZ-STR-EM-DOX-SXT-ENR aac(2ʹ), erm(B), tet(A), sul1
22 Qingyuan ST48 AMP-CFZ-NER-EM aac(2ʹ), erm(B), tet(A), tet(B), sul1
23 Qingyuan ST10 CFZ-NER-EM aac(2ʹ), tet(A), sul2
24 Quyang ST1252 AMP-AMX-CRO-CFZ-STR-EM-SXT-ENR aac(2ʹ), erm(B), tet(A), tet(B)
25 Quyang ST1079 AMP-CFZ-EM tet(A), tet(B)
26 Quyang ST154 CFZ aac(2ʹ), erm(B), tet(A), tet(B), sul2
27 Quyang ST1585 AMP-AMX-CRO-CFZ-GEN-STR-NER-EM-DOX-SXT-CIP-ENR aadA, erm(B)
28 Quyang ST1167 AMP-AMX-CRO-CFZ-STR-NER-EM-DOX-SXT aadA, erm(B), tet(A)
29 Mancheng ST1610 AMP-CFZ-EM aac(2ʹ), tet(A)
30 Mancheng ST10 NER-EM aac(2ʹ), tet(A), sul1, sul2
31 Mancheng ST2741 CFZ-EM aac(2ʹ), aadA, tet(A), tet(B)
32 Mancheng ST2741 CFZ-EM aac(2ʹ), tet(A), tet(B)
33 Mancheng ST48 AMP-CFZ-GEN-STR-EM-DOX-SXT-ENR aac(2ʹ), aadA, erm(B), tet(A), tet(B), sul1
34 Mancheng ST10 AMP-AMX-CRO-CFZ-EM-DOX-SXT-ENR aac(2ʹ), erm(B), tet(A), tet(B), sul1, sul2
35 Mancheng ST906 AMP-AMX-CRO-CFZ-EM-SXT aac(2ʹ), tet(A), tet(B)
36 Mancheng ST48 CFZ-EM aac(2ʹ), aadA, erm(B), tet(B), sul1, qnrB
37 Mancheng ST48 CFZ-EM erm(B), tet(B), sul1
38 Mancheng ST48 CFZ-EM aadA, erm(B), tet(B), sul1
39 Mancheng ST906 CFZ-EM aac(2ʹ), tet(B)
40 Mancheng ST48 AMP-AMX-CFZ-GEN-EM-DOX-SXT aadA, erm(B), sul1

AMP – ampicillin; AMX – amoxicillin; CRO – ceftriaxone; CFZ – cefazolin; GEN – gentamicin; STR – streptomycin; NER – neomycin; AMI – amikacin; EM – erythromycin; DOX – doxycycline; SXT – trimethoprim-sulfamethoxazole; CIP – ciprofloxacin; ENR – enrofloxacin

Antimicrobial resistance genes. In the present study, 40 strains (100.0%) of E. coli with resistance genes were detected, and the genes detected most frequently were the aminoglycoside resistance gene, aadA (n = 25, 62.5%), the tetracycline resistance genes, tet(B) (n = 24, 60.0%) and tet(A), (n = 18, 45.0%) and the macrolide resistance gene, erm(B) (n = 16, 40.0%). Resistance genes to beta-lactams or macrolides, blaTEM and erm(C), were not detected in this study (Table 3).

The associations of resistance genes and the corresponding antibiotics. The relationship between resistance genes and the corresponding antibiotics of E. coli strains was evaluated (Table 4). The results showed that four kinds of antimicrobials, namely amoxicillin (AMX), ceftriaxone (CRO), gentamicin (GEN), and streptomycin (STR), correlated positively with their corresponding resistance genes in E. coli strains (P < 0.05).

Pearson’s correlation coefficients (r) of resistance genes and corresponding antibiotics

Resistance gene Antimicrobials
AMP AMX CRO CFZ GEN STR NER AMI EM DOX SXT CIP ENR
blaSHV 0.231 0.317 0.333 0.053 - - - - - - - - -
blaOXA −0.114 0.248 0.124 −0.059 - - - - - - - - -
aac(2ʹ) - - - - −0.27 3 −0.12 5 −0.083 0.035 - - - - -
aacA4 - - - - 0.331 0.035 0.281 −0.053 - - - - -
aadA - - - - 0.427 0.353 0.105 −0.059 - - - - -
erm(B) - - - - - - - - −0.04 7 - - - -
tet(A) - - - - - - - - - −0.156 - - -
tet(B) - - - - - - - - - −0.347 - - -
sul1 - - - - - - - - - - - 0.174 - -
sul2 - - - - - - - - - - - 0.343 - -
qnrB - - - - - - - - - - - −0.106 0.035

AMP – ampicillin; AMX – amoxicillin; CRO – ceftriaxone; CFZ– cefazolin; GEN– gentamicin; STR – streptomycin; NER – neomycin;

AMI – amikacin; EM – erythromycin; DOX – doxycycline; SXT – trimethoprim-sulfamethoxazole; CIP – ciprofloxacin; ENR – enrofloxacin Pearson’s correlation coefficients (r) shown in bold are significant at P < 0.05

A positive r indicates a positive association between the two variables, whereas a negative r indicates a negative association

- represents antimicrobials without corresponding antibiotic resistance genes

MLST and phylogenetic analyses. Nineteen STs were identified among all the 40 strains, of which the most prevalent was ST10 (n = 9, 22.5%), followed by ST48 (n = 6, 15.0%), ST359 (n = 5, 12.5%) and ST1585 (n = 3, 7.5%); 13 STs presented only once. No new STs were found in this study (Table 3). Five major nodes comprising 14 E. coli isolates were found by minimum spanning tree analysis of all ST types. Based on the single-locus variant level, 40 E. coli strains were classified as five clonal complexes (CC10, CC154, CC359, CC446 and CC906) and their main sequence types were ST10, ST154, ST359, ST446 and ST906, respectively. There was only one pair of allelic differences between neighbouring ST types in these clonal complexes (Fig. 1).

Fig. 1

Full minimum spanning tree using the goeBURST algorithm (n = 40). Each square represents a single sequence type (ST), and the circumference is proportional to the number of isolates within each ST. Grey regions represent a clonal complex. The numbers above the lines (1–5) represent the number of different alleles between the two ST types. The major nodes are indicated by in olive green

The evolutionary tree demonstrated a close genetic relationship between strains in the same clonal complex, such as CC154 (purple area, Fig. 2) and CC446 (yellow area, Fig. 2). The strains in CC10 (blue area, Fig. 2) were distributed in different clusters of the evolutionary tree, while ST48 strains were more distantly related to ST10 and ST1585 strains (Fig. 2). By antimicrobial resistance analysis, it was shown that there were differences in drug resistance profile and gene carriage in the same ST or CC strains. For example, two E. coli strains in CC446 (ID17 and ID19) (Fig. 2) had similar drug resistance profiles and carried a similar number of resistance genes, and the five ST359 strains (ID3, ID7, ID8, ID9 and ID12) (Fig. 2) also matched each other in the same manner. The reverse trend was found for two strains in CC154 (ID26 and ID28) (Fig. 2) and six ST10 strains (ID1, ID10, ID11, ID23, ID30 and ID34) (Fig. 2): compared with the other strains in the same CC group or the same ST type, these strains showed remarkable differences in their drug resistance profiles and numbers of antimicrobial resistance genes (Fig. 2).

Fig. 2

Molecular phylogenetic and antimicrobial resistance analysis of 40 E. coli isolates. The evolutionary tree was inferred using the maximum likelihood method based on the Tamura–Nei model. The bootstrap consensus tree inferred from 1,000 replicates was taken to represent the evolutionary history of the taxa analysed. The branches of the evolutionary tree were named with ID, location, and ST type of E. coli isolates. The same clonal complexes were highlighted in the same colour area. The height of the blue bar graph on the periphery of the evolutionary tree represents the number of drug-resistant genes (2, 3, 4, 5, 6) carried by E. coli isolates. The diameter of different antibiotic inhibition zones (6–34 mm) was displayed as a heat map where red represents high-resistance diameters (trending to susceptible) and blue represents low-resistance diameters (trending to resistant)
Discussion

Escherichia coli is a primary environmental bacterium that can cause mastitis in dairy cow herds. A previous review indicated that dairy cows with mastitis caused by E. coli generally showed severe clinical signs such as redness, swelling, pain, and fever, and that even death could result from the disease (10). In response to coliform mastitis outbreaks or the threat of them in cattle herds, large amounts of antibiotics have been used worldwide. The overuse of antibiotics is severe in China. Statistically, more than 23% of antibiotics used in the world for food animal production were used in China, and the proportion is projected to increase to 30% in 2030 (5, 34). This questionable practice has led to the emergence of AMR in E. coli strains. Unfortunately, the adverse effects of antimicrobial resistance in bacteria have not attracted enough attention in livestock production (31). There are complicated genetic relationships among E. coli strains because of the clonal complex. Exploring these can provide helpful information to better understand the rules of antimicrobial resistance in a region. Therefore, it is constructive to analyse the perspective for E. coli antimicrobial resistance on dairy farms from the starting point of the phylogenetic community.

In this study, the isolation rate of E. coli in milk samples in the northern China region was 20.41%, which was higher than that of previous reports (7.8%) (6). Such a difference might be related to sample sizes, regional differences and detection methods. The results of susceptibility testing showed that the proportion of MDR strains was as high as 72.5%, which is higher than the 40% rate reported in milk samples from Egypt (31) but lower than the 87.8% reported in the Middle East (41). As was recently reported by Cheng et al. (9), MDR E. coli in bovine mastitis is a problem in sizeable Chinese dairy herds. Most E. coli strains exhibited broad resistance to the beta-lactam antibiotics cefazolin (77.5%), ampicillin (52.5%), ceftriaxone (47.5%) and amoxicillin (45.0%), whereas the opposite situation was seen for neomycin (2.5%) and amikacin (2.5%) which are aminoglycoside antibiotics. In comparison, a study on the antimicrobial susceptibility of nine udder pathogens isolated from bovine clinical mastitis milk in Europe showed a higher resistance rate to ampicillin and tetracycline and a lower one to the beta-lactam antibiotics amoxicillin/clavulanic acid and cefazolin (12). We found apparent differences in antimicrobial consumption patterns between Europe and China (13), reflecting a combination of factors including pharmaceutical marketing strategies, veterinarian prescription patterns, governmental guidelines for proper antimicrobial use and farm economic benefit in different regions (33). Therefore, we inferred that our finding arose from the inappropriate use of antibiotics on the farms in the investigated region. Moreover, we found that resistance had emerged to gentamicin that was hitherto usually effective, which could be explained by the long-term use of this antibiotic in dairy herds (19).

There are many mechanisms of antimicrobial resistance in bacteria. In most cases, the presence of antimicrobial resistance genes strongly correlated with resistant phenotypes (3, 22), and a genetic origin aggravates the problem of antimicrobial resistance (21) because antimicrobial resistance genes can be transmitted both vertically and horizontally by plasmid, transposon and integrator in bacterial populations. This study found that more than half of the isolates carried the aadA and tet(B) genes and none carried the blaTEM and erm(C) genes, which is consistent with a previous study conducted in the north-eastern region of Jordan demonstrating the relatively high rate of E. coli of carriage of these resistance genes (17). To investigate the effects of difference in resistance gene distribution on antibiotic resistance in E. coli strains (8), we analysed correlations between antibiotics and corresponding resistance genes of E. coli isolates. The results showed that resistance to amoxicillin and ceftriaxone was correlated positively with resistance genes to beta-lactams (Table 4). This association is considered the main reason for the widespread resistance of E. coli to beta-lactam antibiotics on the regions’ farms: although a large number of beta-lactam resistance genes were not detected, this trend could be the result of carriage of other genes of resistance to beta-lactams and also attributable to other complicated resistance mechanisms, such as extended-spectrum beta-lactamase production (4). Furthermore, some E. coli strains show no association between the antibiotics they resist and the corresponding resistance genes. Liu et al. (22) reported that most antibiotic resistance genes showed no correlations with their corresponding/non-corresponding antibiotics in conferring the expected resistance except the tet(A) resistance gene in bacteria from river drinking-water sources. Our results are only partially consistent with these findings. Perhaps environmental selection pressure affects the diversity and dissemination of antimicrobial resistance in E. coli strains (22, 27). In a further study, the relationship between the antimicrobial resistance of E. coli and various environmental factors needs to be clarified.

Multilocus sequence typing is a robust and reproducible method for analysing genetic relationships in population genetics and is frequently used in molecular epidemiological investigations (29). In this experiment, 40 E. coli strains were divided into 19 STs and 5 CCs. Most of the strains with the same ST type or CC had similar genetic relationships, which is in line with the with the previous study (43) and is evident in the minimum spanning tree and phylogenetic tree (Figs 1 and 2). Interestingly, unlike other CCs in the phylogenetic tree, ST48 strains have a distant relationship with other ST strains in CC10. However, there is only a pair of housekeeping genes’ (adk) difference between ST48 and ST10 strains on the minimum spanning tree, and we speculate that this phenomenon is caused by the difference in the adk sequence (38). We also input the heat map of antimicrobial susceptibility and the number of resistance genes into the phylogenetic tree and found that the molecular characteristics were very different in the same CCs or in the same ST strains; this is consistent with reports that the antimicrobial sensitivity of E. coli differs greatly from region to region (16). We attribute the polymorphism of E. coli molecular characteristics to differences in the environment’s hygiene level, farm management model and antibiotic use on dairy farms in different regions.

In conclusion, the present study elucidated the molecular characteristics of antimicrobial resistance and genetic correlations of E. coli from mastitic dairy cows in northern China. The farms in our study area were contaminated with MDR E. coli, which could have been caused by the inappropriate use of antibiotics. The high detection rates of MDR isolates and the differences in resistance suggested that measures should be taken to reduce the risk to animal food safety and human health, such as the use of only those antimicrobials which are prudent having regard to the AMR E. coli and genotypes on northern Chinese dairy farms.

Fig. 1

Full minimum spanning tree using the goeBURST algorithm (n = 40). Each square represents a single sequence type (ST), and the circumference is proportional to the number of isolates within each ST. Grey regions represent a clonal complex. The numbers above the lines (1–5) represent the number of different alleles between the two ST types. The major nodes are indicated by in olive green
Full minimum spanning tree using the goeBURST algorithm (n = 40). Each square represents a single sequence type (ST), and the circumference is proportional to the number of isolates within each ST. Grey regions represent a clonal complex. The numbers above the lines (1–5) represent the number of different alleles between the two ST types. The major nodes are indicated by in olive green

Fig. 2

Molecular phylogenetic and antimicrobial resistance analysis of 40 E. coli isolates. The evolutionary tree was inferred using the maximum likelihood method based on the Tamura–Nei model. The bootstrap consensus tree inferred from 1,000 replicates was taken to represent the evolutionary history of the taxa analysed. The branches of the evolutionary tree were named with ID, location, and ST type of E. coli isolates. The same clonal complexes were highlighted in the same colour area. The height of the blue bar graph on the periphery of the evolutionary tree represents the number of drug-resistant genes (2, 3, 4, 5, 6) carried by E. coli isolates. The diameter of different antibiotic inhibition zones (6–34 mm) was displayed as a heat map where red represents high-resistance diameters (trending to susceptible) and blue represents low-resistance diameters (trending to resistant)
Molecular phylogenetic and antimicrobial resistance analysis of 40 E. coli isolates. The evolutionary tree was inferred using the maximum likelihood method based on the Tamura–Nei model. The bootstrap consensus tree inferred from 1,000 replicates was taken to represent the evolutionary history of the taxa analysed. The branches of the evolutionary tree were named with ID, location, and ST type of E. coli isolates. The same clonal complexes were highlighted in the same colour area. The height of the blue bar graph on the periphery of the evolutionary tree represents the number of drug-resistant genes (2, 3, 4, 5, 6) carried by E. coli isolates. The diameter of different antibiotic inhibition zones (6–34 mm) was displayed as a heat map where red represents high-resistance diameters (trending to susceptible) and blue represents low-resistance diameters (trending to resistant)

Pearson’s correlation coefficients (r) of resistance genes and corresponding antibiotics

Resistance gene Antimicrobials
AMP AMX CRO CFZ GEN STR NER AMI EM DOX SXT CIP ENR
blaSHV 0.231 0.317 0.333 0.053 - - - - - - - - -
blaOXA −0.114 0.248 0.124 −0.059 - - - - - - - - -
aac(2ʹ) - - - - −0.27 3 −0.12 5 −0.083 0.035 - - - - -
aacA4 - - - - 0.331 0.035 0.281 −0.053 - - - - -
aadA - - - - 0.427 0.353 0.105 −0.059 - - - - -
erm(B) - - - - - - - - −0.04 7 - - - -
tet(A) - - - - - - - - - −0.156 - - -
tet(B) - - - - - - - - - −0.347 - - -
sul1 - - - - - - - - - - - 0.174 - -
sul2 - - - - - - - - - - - 0.343 - -
qnrB - - - - - - - - - - - −0.106 0.035

Susceptibility of 40 E. coli strains to 13 antibiotics commonly used in China

Antibiotic Distribution of E. coli strains (number of strains/%) Decision criteria/Diameter of inhibitory zone (mm)
R1 I S R I S
Ampicillin 21/52.5% 6/15.0% 13/32.5% ≤13 14–16 ≥17
Amoxicillin 18/45.0% 3/7.5% 19/47.5% ≤13 14–17 ≥18
Ceftriaxone 19/47.5% 1/2.5% 20/50.0% ≤19 20–23 ≥24
Cefazolin 31/77.5% 8/20.0% 1/2.5% ≤19 20–22 ≥23
Gentamicin 13/32.5% 0 27/67.5% ≤12 13–14 ≥15
Streptomycin 12/30.0% 5/12.5% 23/57.5% ≤11 12–14 ≥15
Neomycin 1/2.5% 15/37.5% 24/60.0% ≤11 12–16 ≥17
Amikacin 1/2.5% 1/2.5% 38/95.0% ≤14 15–16 ≥17
Erythromycin 17/42.5% 21/52.5% 2/5.0% ≤13 14–22 ≥23
Doxycycline 14/35.0% 5/12.5% 21/52.5% ≤10 11–13 ≥14
Trimethoprim- sulfamethoxazole 22/55.0% 0 18/45.0% ≤12 13–16 ≥17
Ciprofloxacin 7/17.5% 0 33/82.5% ≤15 16–20 ≥21
Enrofloxacin 6/5.0% 11/27.5% 23/57.5% ≤15 16–23 ≥24

Primer sequences, product sizes, annealing temperature and references used for the PCR in the study

Gene Primer sequence (5′–3′) Product size (bp) Annealing temperature (℃) Reference or GenBank accession no.
blaTEM ATAAAATTCTTGAAGACGAAA GACAGTTACCAATGCTTAATC 643 53 (25)
blaSHV TTTGTCGCTTCTTTACTCGCCTTTA GCCAGATCCATTTCTATCATGCCTA 198 56 DQ247972
blaOXA TCAACTTTCAAGATCGCA GTGTGTTTAGAATGGTGA 591 53 (25)
aac(2') ACTGTGATGGGATACGCGTC CTCCGTCAGCGTTTCAGCTA 482 54 (26)
aacA4 CTTCAGGATGGCAAGTTGGT TCATCTCGTTCTCCGCTCAT 286 55 (26)
aadA CTGGAGGTCACTGTCGTGC CCGTGGATTGCCAAAGGTC 274 55 X68089
erm(B) AAAACTTACCCGCCATACCA TTTGGCGTGTTTCATTGCTT 126 53 MN461246
erm(C) GCTCGTGTCATTTCTGGGAGT AGCCTAGCAGCCATTTCTATC 375 53 GQ483470
tet(A) CGGAGCAGAAACAAGAAAGCG GGATCAGGACCGGATACACCAT 345 57 (26)
tet(B) CATTAATAGGCGCATCGCTG TGAAGGTCATCGATAGCAGG 391 53 (26)
sul1 GCCTGGAACTGCTGCTGATGC TCGCCTGCCAAACCGAACTCT 314 59 (27)
sul2 GCGCTCAAGGCAGATGGCATT GCGTTTGATACCGGCACCCGT 793 57 (27)
qnrB GATCGTGAAAGCCAGAAAGG ACGATGCCTGGTAGTTGTCC 513 55 (25)
adk ATTCTGCTTGGCGCTCCGGG CCGTCAACTTTCGCGTATTT 583 54 (20)
fumC TCACAGGTCGCCAGCGCTTC GTACGCAGCGAAAAAGATTC 806 54 (20)
gyrB TCGGCGACACGGATGACGGC ATCAGGCCTTCACGCGCATC 911 60 (20)
icd ATGGAAAGTAAAGTAGTTGTTCCGGCACA GGACGCAGCAGGATCTGTT 878 54 (20)
mdh ATGAAAGTCGCAGTCCTCGGCGCTGCTGGCGG TTAACGAACTCCTGCCCCAGAGCGATATCTTTCTT 932 60 (20)
purA CGCGCTGATGAAAGAGATGA CATACGGTAAGCCACGCAGA 816 54 (20)
recA CGCATTCGCTTTACCCTGACC TCGTCGAAATCTACGGACCGGA 780 58 (20)

Sequence types, resistance phenotypes and resistance genes in 40 E. coli strains

ID Location MLST Resistance phenotypes Resistance genes
1 Xushui ST10 AMP-AMX-CRO-CFZ-GEN-STR-EM-DOX-SXT-ENR aadA, qnrB
2 Xushui ST10 AMP-AMX-CRO-CFZ-GEN-STR-NER-EM-DOX-SXT-CIP-ENR aadA, tet(B)
3 Xushui ST359 AMP-AMX-CRO-CFZ-GEN-STR-NER-EM-DOX-SXT-CIP-ENR blaSHV, aadA
4 Xushui ST10 CFZ-EM aadA, tet(B), sul2
5 Xushui ST10 AMP-AMX-CRO-CFZ-STR-NER-EM-DOX-SXT-CIP-ENR aadA, sul2
6 Xushui ST1585 AMP-AMX-CRO-CFZ-GEN-STR-NER-EM-DOX-SXT-CIP-ENR aacA4, aadA
7 Xushui ST359 AMP-AMX-CRO-CFZ-GEN-STR-NER-AMI-EM-DOX-SXT-CIP-ENR blaSHV, blaOXA, aadA
8 Xushui ST359 AMP-AMX-CRO-CFZ-GEN-NER-EM-DOX-SXT-ENR blaOXA, aacA4, aadA
9 Xushui ST359 AMP-AMX-CRO-CFZ-GEN-STR-EM-DOX-SXT-CIP-ENR blaSHV, blaOXA, aadA, tet(B)
10 Xushui ST10 CFZ-EM aadA, sul2
11 Xushui ST10 CFZ-EM aadA, tet(B), sul2
12 Xushui ST359 AMP-AMX-CRO-CFZ-GEN-NER-EM-SXT-ENR blaOXA, aadA, sul2
13 Xushui ST1125 AMP-AMX-CRO-CFZ-STR-SXT aadA, tet(B)
14 Xushui ST1585 AMP-AMX-CRO-CFZ-EM-DOX-SXT-ENR blaSHV, aadA, tet(B)
15 Xushui ST327 AMP-AMX-CRO-CFZ-EM-DOX-ENR aadA, tet(B)
16 Xushui ST937 AMP-AMX-CRO-CFZ-STR-EM-SXT-ENR aadA, tet(B)
17 Qingyuan ST10717 AMP-CFZ-STR-NER-EM-DOX-SXT aac(2ʹ), aadA, erm(B), tet(A), tet(B)
18 Qingyuan ST942 CFZ-NER-EM-DOX erm(B), tet(A), sul1, sul2
19 Qingyuan ST446 AMP-CFZ-GEN-STR-NER-EM-DOX-SXT aac(2ʹ), aadA, erm(B), tet(A), tet(B)
20 Qingyuan ST1310 AMP-AMX-CRO-CFZ-GEN-STR-NER-AMI-EM aac(2ʹ), erm(B), tet(A), tet(B), sul2
21 Qingyuan ST515 AMP-AMX-CRO-CFZ-STR-EM-DOX-SXT-ENR aac(2ʹ), erm(B), tet(A), sul1
22 Qingyuan ST48 AMP-CFZ-NER-EM aac(2ʹ), erm(B), tet(A), tet(B), sul1
23 Qingyuan ST10 CFZ-NER-EM aac(2ʹ), tet(A), sul2
24 Quyang ST1252 AMP-AMX-CRO-CFZ-STR-EM-SXT-ENR aac(2ʹ), erm(B), tet(A), tet(B)
25 Quyang ST1079 AMP-CFZ-EM tet(A), tet(B)
26 Quyang ST154 CFZ aac(2ʹ), erm(B), tet(A), tet(B), sul2
27 Quyang ST1585 AMP-AMX-CRO-CFZ-GEN-STR-NER-EM-DOX-SXT-CIP-ENR aadA, erm(B)
28 Quyang ST1167 AMP-AMX-CRO-CFZ-STR-NER-EM-DOX-SXT aadA, erm(B), tet(A)
29 Mancheng ST1610 AMP-CFZ-EM aac(2ʹ), tet(A)
30 Mancheng ST10 NER-EM aac(2ʹ), tet(A), sul1, sul2
31 Mancheng ST2741 CFZ-EM aac(2ʹ), aadA, tet(A), tet(B)
32 Mancheng ST2741 CFZ-EM aac(2ʹ), tet(A), tet(B)
33 Mancheng ST48 AMP-CFZ-GEN-STR-EM-DOX-SXT-ENR aac(2ʹ), aadA, erm(B), tet(A), tet(B), sul1
34 Mancheng ST10 AMP-AMX-CRO-CFZ-EM-DOX-SXT-ENR aac(2ʹ), erm(B), tet(A), tet(B), sul1, sul2
35 Mancheng ST906 AMP-AMX-CRO-CFZ-EM-SXT aac(2ʹ), tet(A), tet(B)
36 Mancheng ST48 CFZ-EM aac(2ʹ), aadA, erm(B), tet(B), sul1, qnrB
37 Mancheng ST48 CFZ-EM erm(B), tet(B), sul1
38 Mancheng ST48 CFZ-EM aadA, erm(B), tet(B), sul1
39 Mancheng ST906 CFZ-EM aac(2ʹ), tet(B)
40 Mancheng ST48 AMP-AMX-CFZ-GEN-EM-DOX-SXT aadA, erm(B), sul1

Ahmed A.M., Furuta K., Shimomura K., Kasama Y., Shimamoto T.: Genetic characterization of multidrug resistance in Shigella spp. from Japan. J Med Microbiol 2006, 55, 1685–1691, doi: 10.1099/jmm.0.46725-0. Ahmed A.M. Furuta K. Shimomura K. Kasama Y. Shimamoto T. Genetic characterization of multidrug resistance in Shigella spp from Japan. J Med Microbiol 2006 55 1685 1691 10.1099/jmm.0.46725-017108272Apri DOISearch in Google Scholar

Ahmed A.M., Motoi Y., Sato M., Maruyama A., Watanabe H., Fukumoto Y., Shimamoto T.: Zoo animals as reservoirs of gram-negative bacteria harboring integrons and antimicrobial resistance genes. Appl Environ Microbiol 2007, 73, 6686–6690, doi: 10.1128/aem.01054-07. Ahmed A.M. Motoi Y. Sato M. Maruyama A. Watanabe H. Fukumoto Y. Shimamoto T. Zoo animals as reservoirs of gram-negative bacteria harboring integrons and antimicrobial resistance genes Appl Environ Microbiol 2007 73 6686 6690 10.1128/aem.01054-07Apri DOISearch in Google Scholar

Ai W., Zhou Y., Wang B., Zhan Q., Hu L., Xu Y., Guo Y., Wang L., Yu F., Li X.: First Report of Coexistence of blaSFO-1 and blaNDM-1β-Lactamase Genes as Well as Colistin Resistance Gene mcr-9 in a Transferrable Plasmid of a Clinical Isolate of Enterobacter hormaechei. Front Microbiol 2021, 18, 12, 676113, doi: 10.3389/fmicb.2021.676113. Ai W. Zhou Y. Wang B. Zhan Q. Hu L. Xu Y. Guo Y. Wang L. Yu F. Li X. First Report of Coexistence of blaSFO-1 and blaNDM-1β-Lactamase Genes as Well as Colistin Resistance Gene mcr-9 in a Transferrable Plasmid of a Clinical Isolate of Enterobacter hormaechei Front Microbiol 2021 18 12 676113 10.3389/fmicb.2021.676113825296534220761Apri DOISearch in Google Scholar

Alam M.Z., Aqil F., Ahmad I., Ahmad S.: Incidence and transferability of antibiotic resistance in the enteric bacteria isolated from hospital wastewater. Braz J Microbiol 2013, 44, 799–806, doi: 10.1590/s1517-83822013000300021. Alam M.Z. Aqil F. Ahmad I. Ahmad S. Incidence and transferability of antibiotic resistance in the enteric bacteria isolated from hospital wastewater Braz J Microbiol 2013 44 799 806 10.1590/s1517-83822013000300021391019224516448Apri DOISearch in Google Scholar

Antimicrobial Resistance Collaborators: Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet 2022, 399, 629–655, doi: 10.1016/S0140-6736(21)02724-0. Antimicrobial Resistance Collaborators Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis Lancet 2022 399 629 655 10.1016/S0140-6736(21)02724-0884163735065702Apri DOISearch in Google Scholar

Aslam N., Khan S., Usman T., Ali T.: Phylogenetic genotyping, virulence genes and antimicrobial susceptibility of Escherichia coli isolates from cases of bovine mastitis. J Dairy Res 2021, 88, 78–79, doi: 10.1017/S002202992100011X. Aslam N. Khan S. Usman T. Ali T. Phylogenetic genotyping, virulence genes and antimicrobial susceptibility of Escherichia coli isolates from cases of bovine mastitis J Dairy Res 2021 88 78 79 10.1017/S002202992100011X33622442Apri DOISearch in Google Scholar

Bahadori M., Motamedifar M., Derakhshandeh A., Firouzi R., Motamedi Boroojeni A., Alinejad M., Naziri Z.: Genetic relatedness of the Escherichia coli fecal population and strains causing urinary tract infection in the same host. MicrobiologyOpen 2019, 8, e00759, doi: 10.1002/mbo3.759. Bahadori M. Motamedifar M. Derakhshandeh A. Firouzi R. Motamedi Boroojeni A. Alinejad M. Naziri Z. Genetic relatedness of the Escherichia coli fecal population and strains causing urinary tract infection in the same host MicrobiologyOpen 2019 8 e00759 10.1002/mbo3.759656212730358940Apri DOISearch in Google Scholar

Cai W., Fu Y., Zhang W., Chen X., Zhao J., Song W., Li Y., Huang Y., Wu Z., Sun R., Dong C., Zhang F.: Synergistic effects of baicalein with cefotaxime against Klebsiella pneumoniae through inhibiting CTX-M-1 gene expression. BMC Microbiol 2016, 16, 181, doi: 10.1186/s12866-016-0797-1. Cai W. Fu Y. Zhang W. Chen X. Zhao J. Song W. Li Y. Huang Y. Wu Z. Sun R. Dong C. Zhang F. Synergistic effects of baicalein with cefotaxime against Klebsiella pneumoniae through inhibiting CTX-M-1 gene expression BMC Microbiol 2016 16 181 10.1186/s12866-016-0797-1497766027502110Apri DOISearch in Google Scholar

Cheng J., Qu W., Barkema H.W., Nobrega D.B., Gao J., Liu G., De Buck J., Kastelic J.P., Sun H., Han B.: Antimicrobial resistance profiles of 5 common bovine mastitis pathogens in large Chinese dairy herds. J Dairy Sci 2019, 102, 2416–2426, doi: 10.3168/jds.2018-15135. Cheng J. Qu W. Barkema H.W. Nobrega D.B. Gao J. Liu G. De Buck J. Kastelic J.P. Sun H. Han B. Antimicrobial resistance profiles of 5 common bovine mastitis pathogens in large Chinese dairy herds J Dairy Sci 2019 102 2416 2426 10.3168/jds.2018-1513530639013Apri DOISearch in Google Scholar

Cheng W., Han S.: Bovine mastitis: risk factors, therapeutic strategies, and alternative treatments – A review. Asian-Australas J Anim Sci 2020, 33, 1699–1713, doi: 10.5713/ajas.20.0156. Cheng W. Han S. Bovine mastitis: risk factors, therapeutic strategies, and alternative treatments – A review Asian-Australas J Anim Sci 2020 33 1699 1713 10.5713/ajas.20.0156764907232777908Apri DOISearch in Google Scholar

Clinical and Laboratory Standards Institute: VET08: Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals, Fourth Edition. CLSI, Wayne, PA, 2018. Clinical and Laboratory Standards Institute VET08: Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals, Fourth Edition CLSI, Wayne, PA 2018Search in Google Scholar

El Garch F., Youala M., Simjee S., Moyaert H., Klee R., Truszkowska B., Rose M., Hocquet D., Valot B., Morrissey I., de Jong A., VetPath Study Group: Antimicrobial susceptibility of nine udder pathogens recovered from bovine clinical mastitis milk in Europe 2015–2016: VetPath results. Vet Microbiol 2020, 245, 108644, doi: 10.1016/j.vetmic.2020.108644. El Garch F. Youala M. Simjee S. Moyaert H. Klee R. Truszkowska B. Rose M. Hocquet D. Valot B. Morrissey I. de Jong A. VetPath Study Group Antimicrobial susceptibility of nine udder pathogens recovered from bovine clinical mastitis milk in Europe 2015–2016: VetPath results Vet Microbiol 2020 245 108644 10.1016/j.vetmic.2020.10864432456822Apri DOISearch in Google Scholar

European Medicines Agency.: Second ESV AC Report. European Surveillance of Veterinary Antimicrobial Consumption Report (ESV AC). Sales of veterinary antimicrobial agents in 19 EU/EEA countries in 2010, 2018. European Medicines Agency. Second ESV AC Report. European Surveillance of Veterinary Antimicrobial Consumption Report (ESV AC). Sales of veterinary antimicrobial agents in 19 EU/EEA countries in 2010 2018Search in Google Scholar

Gelband H., Miller-Petrie M., Pant S., Gandra S., Levinson J., Barter D., White A., Laxminarayan R.: The state of the world’s antibiotics. Center for Disease Dynamics, Economics & Policy, Washington, D.C., 2015. Gelband H. Miller-Petrie M. Pant S. Gandra S. Levinson J. Barter D. White A. Laxminarayan R. The state of the world’s antibiotics. Center for Disease Dynamics, Economics & Policy Washington, D.C 2015Search in Google Scholar

Ghanbarpour R., Oswald E.: Phylogenetic distribution of virulence genes in Escherichia coli isolated from bovine mastitis in Iran. Res Vet Sci 2010, 88, 6–10, doi: 10.1016/j.rvsc.2009.06.003. Ghanbarpour R. Oswald E. Phylogenetic distribution of virulence genes in Escherichia coli isolated from bovine mastitis in Iran Res Vet Sci 2010 88 6 10 10.1016/j.rvsc.2009.06.00319580980Apri DOISearch in Google Scholar

Holmer I., Salomonsen C., Jorsal S., Astrup L., Jensen V., Høg B., Pedersen K.: Antibiotic resistance in porcine pathogenic bacteria and relation to antibiotic usage. BMC Vet Res 2019, 15, 449, doi: 10.1186/s12917-019-2162-8. Holmer I. Salomonsen C. Jorsal S. Astrup L. Jensen V. Høg B. Pedersen K. Antibiotic resistance in porcine pathogenic bacteria and relation to antibiotic usage BMC Vet Res 2019 15 449 10.1186/s12917-019-2162-8690720831829171Apri DOISearch in Google Scholar

Ismail Z., Abutarbush S.: Molecular characterization of antimicrobial resistance and virulence genes of Escherichia coli isolates from bovine mastitis. Vet World 2020, 13, 1588–1593, doi: 10.14202/vetworld.2020.1588-1593. Ismail Z. Abutarbush S. Molecular characterization of antimicrobial resistance and virulence genes of Escherichia coli isolates from bovine mastitis Vet World 2020 13 1588 1593 10.14202/vetworld.2020.1588-1593752293833061231Apri DOISearch in Google Scholar

Iwano H., Inoue Y., Takasago T., Kobayashi H., Furusawa T., Taniguchi K., Fujiki J., Yokota H., Usui M., Tanji Y., Hagiwara K., Higuchi H., Tamura Y.: Bacteriophage ΦSA012 Has a Broad Host Range against Staphylococcus aureus and Effective Lytic Capacity in a Mouse Mastitis Model. Biology 2018, 7, 8, doi: 10.3390/biology7010008. Iwano H. Inoue Y. Takasago T. Kobayashi H. Furusawa T. Taniguchi K. Fujiki J. Yokota H. Usui M. Tanji Y. Hagiwara K. Higuchi H. Tamura Y. Bacteriophage ΦSA012 Has a Broad Host Range against Staphylococcus aureus and Effective Lytic Capacity in a Mouse Mastitis Model Biology 2018 7 8 10.3390/biology7010008587203429315249Apri DOISearch in Google Scholar

Kimera Z., Mshana S., Rweyemamu M., Mboera L., Matee M.: Antimicrobial use and resistance in food-producing animals and the environment: an African perspective. Antimicrob Resist Infect Control 2020, 9, 37, doi: 10.1186/s13756-020-0697-x. Kimera Z. Mshana S. Rweyemamu M. Mboera L. Matee M. Antimicrobial use and resistance in food-producing animals and the environment: an African perspective Antimicrob Resist Infect Control 2020 9 37 10.1186/s13756-020-0697-x705306032122406Apri DOISearch in Google Scholar

Levin-Reisman I., Ronin I., Gefen O., Braniss I., Shoresh N., Balaban N.Q.: Antibiotic tolerance facilitates the evolution of resistance. Science 2017, 355, 826–830, doi: 10.1126/science.aaj2191. Levin-Reisman I. Ronin I. Gefen O. Braniss I. Shoresh N. Balaban N.Q. Antibiotic tolerance facilitates the evolution of resistance Science 2017 355 826 830 10.1126/science.aaj219128183996Apri DOISearch in Google Scholar

Li Y., Yang L., Fu J., Yan M., Chen D., Zhang L.: Genotyping and high flux sequencing of the bacterial pathogenic elements - integrons. Microb Pathog 2018, 116, 22–25, doi: 10.1016/j.micpath.2017.12.073. Li Y. Yang L. Fu J. Yan M. Chen D. Zhang L. Genotyping and high flux sequencing of the bacterial pathogenic elements - integrons Microb Pathog 2018 116 22 25 10.1016/j.micpath.2017.12.07329306009Apri DOISearch in Google Scholar

Liu Y., Chen Y., Feng M., Chen J., Shen W., Zhang S.: Occurrence of antibiotics and antibiotic resistance genes and their correlations in river-type drinking water source, China. Environ Sci Pollut Res Int 2021, 28, 42339–42352, doi: 10.1007/s11356-021-13637-8. Liu Y. Chen Y. Feng M. Chen J. Shen W. Zhang S. Occurrence of antibiotics and antibiotic resistance genes and their correlations in river-type drinking water source, China Environ Sci Pollut Res Int 2021 28 42339 42352 10.1007/s11356-021-13637-833813699Apri DOISearch in Google Scholar

Maiden M.C., Bygraves J.A., Feil E., Morelli G., Russell J.E., Urwin R., Zhang Q., Zhou J., Zurth K., Caugant D.A., Feavers I.M., Achtman M., Spratt B.G.: Multilocus sequence typing: a portable approach to the identification of clones within populations of pathogenic microorganisms. Proc Natl Acad Sci USA 1998, 95, 3140–3145, doi: 10.1073/pnas.95.6.3140. Maiden M.C. Bygraves J.A. Feil E. Morelli G. Russell J.E. Urwin R. Zhang Q. Zhou J. Zurth K. Caugant D.A. Feavers I.M. Achtman M. Spratt B.G. Multilocus sequence typing: a portable approach to the identification of clones within populations of pathogenic microorganisms Proc Natl Acad Sci USA 1998 95 3140 3145 10.1073/pnas.95.6.3140197089501229Apri DOISearch in Google Scholar

Maiden M.C., Jansen van Rensburg M.J., Bray J.E., Earle S.G., Ford S.A., Jolley K.A., McCarthy N.D.: MLST revisited: the gene-by-gene approach to bacterial genomics. Nat Rev Microbiol 2013, 11, 728–736, doi: 10.1038/nrmicro3093. Maiden M.C. Jansen van Rensburg M.J. Bray J.E. Earle S.G. Ford S.A. Jolley K.A. McCarthy N.D. MLST revisited: the gene-by-gene approach to bacterial genomics Nat Rev Microbiol 2013 11 728 736 10.1038/nrmicro3093398063423979428Apri DOISearch in Google Scholar

Martínez J.L.: Antibiotics and antibiotic resistance genes in natural environments. Science 2008, 321, 365–367, doi: 10.1126/science.1159483. Martínez J.L. Antibiotics and antibiotic resistance genes in natural environments Science 2008 321 365 367 10.1126/science.115948318635792Apri DOISearch in Google Scholar

Mather A.E., Denwood M.J., Haydon D.T., Matthews L., Mellor D.J., Coia J.E., Brown D.J., Reid S.W.: The prevalences of Salmonella genomic island 1 variants in human and animal Salmonella typhimurium DT104 are distinguishable using a Bayesian approach. PLoS One 2011, 6, e27220, doi: 10.1371/journal.pone.0027220. Mather A.E. Denwood M.J. Haydon D.T. Matthews L. Mellor D.J. Coia J.E. Brown D.J. Reid S.W. The prevalences of Salmonella genomic island 1 variants in human and animal Salmonella typhimurium DT104 are distinguishable using a Bayesian approach PLoS One 2011 6 e27220 10.1371/journal.pone.0027220322067722125606Apri DOISearch in Google Scholar

Natarajan M., Kumar D., Mandal J., Biswal N., Stephen S.: A study of virulence and antimicrobial resistance pattern in diarrhoeagenic Escherichia coli isolated from diarrhoeal stool specimens from children and adults in a tertiary hospital, Puducherry, India. J Health Popul Nutr 2018, 37, 17, doi: 10.1186/s41043-018-0147-z. Natarajan M. Kumar D. Mandal J. Biswal N. Stephen S. A study of virulence and antimicrobial resistance pattern in diarrhoeagenic Escherichia coli isolated from diarrhoeal stool specimens from children and adults in a tertiary hospital, Puducherry, India J Health Popul Nutr 2018 37 17 10.1186/s41043-018-0147-z604586430005599Apri DOISearch in Google Scholar

Navajas-Benito E.V., Alonso C.A., Sanz S., Olarte C., Martínez-Olarte R., Hidalgo-Sanz S., Somalo S., Torres C.: Molecular characterization of antibiotic resistance in Escherichia coli strains from a dairy cattle farm and its surroundings. J Sci Food Agric 2017, 97, 362–365, doi: 10.1002/jsfa.7709. Navajas-Benito E.V. Alonso C.A. Sanz S. Olarte C. Martínez-Olarte R. Hidalgo-Sanz S. Somalo S. Torres C. Molecular characterization of antibiotic resistance in Escherichia coli strains from a dairy cattle farm and its surroundings J Sci Food Agric 2017 97 362 365 10.1002/jsfa.770926969806Apri DOISearch in Google Scholar

Núñez-Samudio V., Pecchio M., Pimentel-Peralta G., Quintero Y., Herrera M., Landires I.: Molecular Epidemiology of Escherichia coli Clinical Isolates from Central Panama. Antibiotics 2021, 10, 899, doi: 10.3390/antibiotics10080899. Núñez-Samudio V. Pecchio M. Pimentel-Peralta G. Quintero Y. Herrera M. Landires I. Molecular Epidemiology of Escherichia coli Clinical Isolates from Central Panama Antibiotics 2021 10 899 10.3390/antibiotics10080899838862134438949Apri DOISearch in Google Scholar

Oliveira L., Ruegg P.L.: Treatments of clinical mastitis occurring in cows on 51 large dairy herds in Wisconsin. J Dairy Sci 2014, 97, 5426–5436, doi: 10.3168/jds.2013-7756. Oliveira L. Ruegg P.L. Treatments of clinical mastitis occurring in cows on 51 large dairy herds in Wisconsin J Dairy Sci 2014 97 5426 5436 10.3168/jds.2013-775624997660Apri DOISearch in Google Scholar

Ombarak R.A., Zayda M.G., Awasthi S.P., Hinenoya A., Yamasaki S.: Serotypes, Pathogenic Potential, and Antimicrobial Resistance of Escherichia coli Isolated from Subclinical Bovine Mastitis Milk Samples in Egypt. Jpn J Infect Dis 2019, 72, 337–339, doi: 10.7883/yoken.JJID.2018.538. Ombarak R.A. Zayda M.G. Awasthi S.P. Hinenoya A. Yamasaki S. Serotypes, Pathogenic Potential, and Antimicrobial Resistance of Escherichia coli Isolated from Subclinical Bovine Mastitis Milk Samples in Egypt Jpn J Infect Dis 2019 72 337 339 10.7883/yoken.JJID.2018.53831061360Apri DOISearch in Google Scholar

Osman K.M., Kappell A.D., Elhadidy M., ElMougy F., El-Ghany W.A.A., Orabi A., Mubarak A.S., Dawoud T.M., Hemeg H.A., Moussa I.M.I., Hessain A.M., Yousef H.M.Y.: Poultry hatcheries as potential reservoirs for antimicrobial-resistant Escherichia coli: A risk to public health and food safety. Sci Rep 2018, 8, 5859, doi: 10.1038/s41598-018-23962-7. Osman K.M. Kappell A.D. Elhadidy M. ElMougy F. El-Ghany W.A.A. Orabi A. Mubarak A.S. Dawoud T.M. Hemeg H.A. Moussa I.M.I. Hessain A.M. Yousef H.M.Y. Poultry hatcheries as potential reservoirs for antimicrobial-resistant Escherichia coli: A risk to public health and food safety Sci Rep 2018 8 5859 10.1038/s41598-018-23962-7589558329643424Apri DOISearch in Google Scholar

Patel S., Wellington M., Shah R., Ferreira M.: Antibiotic Stewardship in Food-producing Animals: Challenges, Progress, and Opportunities. Clin Ther 2020, 42, 1649–1658, doi: 10.1016/j.clinthera.2020.07.004. Patel S. Wellington M. Shah R. Ferreira M. Antibiotic Stewardship in Food-producing Animals: Challenges, Progress, and Opportunities Clin Ther 2020 42 1649 1658 10.1016/j.clinthera.2020.07.004743444932819723Apri DOISearch in Google Scholar

Qiao M., Ying G., Singer A., Zhu Y.: Review of antibiotic resistance in China and its environment. Environ Int 2018, 110, 160–172, doi: 10.1016/j.envint.2017.10.016. Qiao M. Ying G. Singer A. Zhu Y. Review of antibiotic resistance in China and its environment Environ Int 2018 110 160 172 10.1016/j.envint.2017.10.01629107352Apri DOISearch in Google Scholar

Rossolini G.M., Arena F., Pecile P., Pollini S.: Update on the antibiotic resistance crisis. Curr Opin Pharmacol 2014, 18, 56–60, 10.1016/j.coph.2014.09.006 Rossolini G.M. Arena F. Pecile P. Pollini S. Update on the antibiotic resistance crisis Curr Opin Pharmacol 2014 18 56 60 10.1016/j.coph.2014.09.00625254623Apri DOISearch in Google Scholar

Seegers H., Fourichon C., Beaudeau F.: Production effects related to mastitis and mastitis economics in dairy cattle herds. Vet Res 2003, 34, 475–491, doi: 10.1051/vetres:2003027. Seegers H. Fourichon C. Beaudeau F. Production effects related to mastitis and mastitis economics in dairy cattle herds Vet Res 2003 34 475 491 10.1051/vetres:200302714556691Apri DOISearch in Google Scholar

Song X., Wu H., Yin Z., Lian M., Yin C.: Endophytic Bacteria Isolated from Panax ginseng Improves Ginsenoside Accumulation in Adventitious Ginseng Root Culture. Molecules 2017, 22, 837, doi: 10.3390/molecules22060837. Song X. Wu H. Yin Z. Lian M. Yin C. Endophytic Bacteria Isolated from Panax ginseng Improves Ginsenoside Accumulation in Adventitious Ginseng Root Culture Molecules 2017 22 837 10.3390/molecules22060837615262428545250Apri DOISearch in Google Scholar

Souto A.C., Bonfietti L.X., Ferreira-Paim K., Trilles L., Martins M., Ribeiro-Alves M., Pham C.D., Martins L., Dos Santos W., Chang M., Brito-Santos F., Santos D.C., Fortes S., Lockhart S.R., Wanke B., Melhem M.S., Lazéra M.S., Meyer W.: Population Genetic Analysis Reveals a High Genetic Diversity in the Brazilian Cryptococcus gattii VGII Population and Shifts the Global Origin from the Amazon Rainforest to the Semi-arid Desert in the Northeast of Brazil. PLoS Negl Trop Dis 2016, 10, e0004885, doi: 10.1371/journal.pntd.0004885. Souto A.C. Bonfietti L.X. Ferreira-Paim K. Trilles L. Martins M. Ribeiro-Alves M. Pham C.D. Martins L. Dos Santos W. Chang M. Brito-Santos F. Santos D.C. Fortes S. Lockhart S.R. Wanke B. Melhem M.S. Lazéra M.S. Meyer W. Population Genetic Analysis Reveals a High Genetic Diversity in the Brazilian Cryptococcus gattii VGII Population and Shifts the Global Origin from the Amazon Rainforest to the Semi-arid Desert in the Northeast of Brazil PLoS Negl Trop Dis 2016 10 e0004885 10.1371/journal.pntd.0004885498698027529479Apri DOISearch in Google Scholar

Sukumar S., Roberts A.P., Martin F.E., Adler C.J.: Metagenomic Insights into Transferable Antibiotic Resistance in Oral Bacteria. J Dent Res 2016, 95, 969–976, doi: 10.1177/0022034516648944. Sukumar S. Roberts A.P. Martin F.E. Adler C.J. Metagenomic Insights into Transferable Antibiotic Resistance in Oral Bacteria J Dent Res 2016 95 969 976 10.1177/002203451664894427183895Apri DOISearch in Google Scholar

Suojala L., Simojoki H., Mustonen K., Kaartinen L., Pyörälä S.: Efficacy of enrofloxacin in the treatment of naturally occurring acute clinical Escherichia coli mastitis. J Dairy Sci 2010, 93, 1960–1969, doi: 10.3168/jds.2009-2462. Suojala L. Simojoki H. Mustonen K. Kaartinen L. Pyörälä S. Efficacy of enrofloxacin in the treatment of naturally occurring acute clinical Escherichia coli mastitis J Dairy Sci 2010 93 1960 1969 10.3168/jds.2009-246220412909Apri DOISearch in Google Scholar

Tartor Y., Abd El-Aziz N., Gharieb R., El Damaty H., Enany S., Soliman E., Abdellatif S., Attia A., Bahnass M., El-Shazly Y., Elbediwi M., Ramadan H.: Whole-Genome Sequencing of Gram-Negative Bacteria Isolated From Bovine Mastitis and Raw Milk: The First Emergence of Colistin mcr-10 and Fosfomycin fosA5 Resistance Genes in Klebsiella pneumoniae in Middle East. Front Microbiol 2021, 12, 770813, doi: 10.3389/fmicb.2021.770813. Tartor Y. Abd El-Aziz N. Gharieb R. El Damaty H. Enany S. Soliman E. Abdellatif S. Attia A. Bahnass M. El-Shazly Y. Elbediwi M. Ramadan H. Whole-Genome Sequencing of Gram-Negative Bacteria Isolated From Bovine Mastitis and Raw Milk: The First Emergence of Colistin mcr-10 and Fosfomycin fosA5 Resistance Genes in Klebsiella pneumoniae in Middle East Front Microbiol 2021 12 770813 10.3389/fmicb.2021.770813869298734956131Apri DOISearch in Google Scholar

Wang D., Wang Z., Yan Z., Wu J., Ali T., Li J., Lv Y., Han B.: Bovine mastitis Staphylococcus aureus: antibiotic susceptibility profile, resistance genes and molecular typing of methicillin-resistant and methicillin-sensitive strains in China. Infect Genet Evol 2015, 31, 9–16, doi: 10.1016/j.meegid.2014.12.039. Wang D. Wang Z. Yan Z. Wu J. Ali T. Li J. Lv Y. Han B. Bovine mastitis Staphylococcus aureus: antibiotic susceptibility profile, resistance genes and molecular typing of methicillin-resistant and methicillin-sensitive strains in China Infect Genet Evol 2015 31 9 16 10.1016/j.meegid.2014.12.03925582604Apri DOISearch in Google Scholar

Wirth T., Falush D., Lan R., Colles F., Mensa P., Wieler L H., Karch H., Reeves P. R., Maiden M.C., Ochman H., Achtman M.: Sex and virulence in Escherichia coli: an evolutionary perspective. Mol Microbiol 2006, 60, 1136–1151, doi: 10.1111/j.1365-2958.2006.05172.x. Wirth T. Falush D. Lan R. Colles F. Mensa P. Wieler L H. Karch H. Reeves P. R. Maiden M.C. Ochman H. Achtman M. Sex and virulence in Escherichia coli: an evolutionary perspective Mol Microbiol 2006 60 1136 1151 10.1111/j.1365-2958.2006.05172.x155746516689791Apri DOISearch in Google Scholar

Zhang A., Wang H., Tian G., Zhang Y., Yang X., Xia Q., Tang J., Zou L.: Phenotypic and genotypic characterisation of antimicrobial resistance in faecal bacteria from 30 Giant pandas. Int J Antimicrob Agents 2009, 33, 456–460, doi: 10.1016/j.ijantimicag.2008.10.030. Zhang A. Wang H. Tian G. Zhang Y. Yang X. Xia Q. Tang J. Zou L. Phenotypic and genotypic characterisation of antimicrobial resistance in faecal bacteria from 30 Giant pandas Int J Antimicrob Agents 2009 33 456 460 10.1016/j.ijantimicag.2008.10.03019168331Apri DOISearch in Google Scholar

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