Investigating the Spread of Antimicrobial Drug-Resistant Microorganisms in Dairy Sheep Farms: A Follow-Up Study
by
, , ,
Antonia Mataragka
1,*,
Nikolaos Tzimotoudis
2,
Alexandros Mavrommatis
3,
Eleni Tsiplakou
3
,
Andrianna Symeonidou
1,
Maria Kotsikori
1,
George Zervas
3 and
John Ikonomopoulos
1 1
Laboratory of Anatomy and Physiology of Farm Animals, Department of Animal Science, School of Animal Biosciences, Agricultural University of Athens, Iera Odos 75, GR-11855 Athens, Greece
2
Laboratory of Microbiology, Hellenic Army Biological Research Center, GR-15236 Athens, Greece
3
Laboratory of Nutritional Physiology and Feeding, Department of Animal Science, School of Animal Biosciences, Agricultural University of Athens, Iera Odos 75, GR-11855 Athens, Greece
*
Author to whom correspondence should be addressed.
Appl. Sci. 2023, 13(14), 8165; https://0-doi-org.brum.beds.ac.uk/10.3390/app13148165
Submission received: 8 June 2023
/
Revised: 7 July 2023
/
Accepted: 12 July 2023
/
Published: 13 July 2023
(This article belongs to the Special Issue Detection and Control of Foodborne and Waterborne Pathogenic Bacteria)
Abstract
:Recently, we investigated the spread of antimicrobial drug-resistant (AMR) microorganisms in five dairy sheep farms in Greece to identify indicators for improved field surveillance. The high percentage of samples of feeds and milk positive to Escherichia coli and Staphylococci, including AMR isolates, recorded in this previous study generated the interest to further investigate the parameters likely to affect positivity of these certain indicators in the same farms. For this reason, 76 samples were collected, comprising milk collected from the raw milk tank (n = 5), swabs from milking shells (n = 48), feeds (n = 6), and home-grown feeds (n = 17). Samples were processed for the detection of the pathogens mentioned above and the assessment of AMR using conventional microbiology and the polymerase chain reaction. The overall percentage of positive samples was 71.1%. The percentage of isolates that were characterised as AMR of those detected was 27.8% (30% Staphylococci, 21.4% E. coli). The results indicate that AMR testing in milking shell swabs is advisable for improving AMR stewardship and should be regarded as complimentary to testing samples from the raw milk tank, because these may not depict the microbial burden of milking shells. Furthermore, the spread and antimicrobial resistance of tested bacteria in feeds are characterised by considerable variability and should therefore be assessed longitudinally.
1. Introduction
Monitoring animal health is recognised as a factor of key significance in improving antimicrobial stewardship [1]. To this direction, in-farm surveillance using indicators of the spread of antimicrobial drug resistance (AMR) can prove significant in improving animal health and welfare, and in effect, public health protection. Interestingly, the relevant information available in connection with dairy sheep is limited. Recently, we investigated the spread of AMR bacteria in five dairy sheep farms in Greece to identify indicators for improved field surveillance [2]. This investigation, which was to the best of our knowledge, the first to be conducted on this subject, relied on the detection of two common foodborne pathogens that have proven suitable for monitoring AMR transfer between animals and humans, namely Staphylococcus aureus and E. coli [3]. The study farms, referred to as Farms A–E, were selected based on location, accessibility, size (small, medium, large), breeding practice (indoor intensive, semi-intensive, and semi-extensive), and the availability of reliable farm records, which was confirmed onsite through a method of inspection and personal interview. That certain investigation concluded that the spread of AMR isolates in the study population is considerable. This finding was clearly reflected in milk, particularly with regards to the AMR and multidrug-resistant (MDR) S. aureus that was detected in samples collected both from the udder and the bulk milk tank. Notably, the latter proved suitable for the cost-effective assessment of AMR, dispensing with the need to collect samples from individual animals. The assessment that was conducted to assess potential sources of the AMR spread within farms was targeted to bedding, faeces, drinking water, and feeds. The latter, particularly the samples collected from the farms’ feeders, were found positive to E. coli, which was identified in several cases as AMR or MDR, at a percentage that was statistically significantly higher compared to all other types of samples (b = 3.602; p-value < 0.01). Notably, the presence of AMR isolates of S. aureus in feeds was found to increase the probability of milk positivity to AMR S. aureus by 3.25 times, which was regarded as indicative that feeds may be a factor of key significance in the spread of AMR inside the farm [2].
Based on the findings reported above, it was considered advisable to further our previous investigation to the parameters likely to affect AMR positivity of milk and feeds in the study farms to identify potential indicators of their spread and improve field surveillance.
2. Materials and Methods
In total, 76 samples were collected, consisting of milk (n = 53) and feeds (n = 23) from Farms A to E (Table 1). Sample collection was performed between June and August 2021, i.e., one year after our previous investigation [2].
In connection with milk, we collected 5 samples from the farms’ raw milk tanks (1 from each of the Farms A–E) and 48 swabs (12 from each farm, excluding Farm B, which applies manual milking) from the interior surface of the shells (teatcups) of each milking machine, after routine disinfection. Four (n = 4) of the swabs collected from each farm were taken from the bottom of different shells, and the rest (n = 8) from the area close to the shell’s ring.
With regards to feeds, this investigation was focused to own home-grown feeds stored in each farm’s respective storage (n = 6, 1 in Farms A, B, D, and E, and 2 from Farm C), and to those of the ingredients produced by the respective farms (n = 17, 3 from Farm A, 1 from Farm B, 6 from Farm C, 3 from Farm D, and 4 from Farm E) (Table 1).
Samples were processed for the detection of E. coli, S. aureus, and coagulase-negative Staphylococci (CoNS), as well as the assessment of drug resistance, using conventional microbiology and the polymerase chain reaction (PCR), as previously described [2]. In brief, sample processing for the isolation of targeted pathogens was conducted based on standard procedures using a 7% sheep blood agar base (Oxoid Ltd., Basingstoke, UK) for milk samples, MacConkey agar (Oxoid Limited, UK) for milk and feed samples, and Baird-Parker agar (Oxoid Limited, UK) for feed samples. Colonies phenotypically consistent with Staphylococci and E. coli were subcultured on Plate Count Agar (PCA, Oxoid Limited, UK) or Tryptone Soya Agar (TSA, Oxoid Limited, UK) and Tryptone Bile Xglucuronide agar (TBX agar, Oxoid Limited, UK), respectively. Selected colonies were tested with PCR targeting the tuf gene for Staphylococcus spp., the nuc gene for S. aureus and the rfbE gene for E. coli [2].
Staphylococci isolates were tested for susceptibility to cefoxitin (FOX: 30 μg), clindamycin (DA: 2 μg), erythromycin (ERY: 15 μg), gentamicin (CN: 10 μg), norfloxacin (NOR: 10 μg), penicillin G (P: 1 unit), tetracycline (TE: 30 μg), and trimethoprim-sulphamethoxazole (SXT: 25 μg). The isolates of E. coli were tested for susceptibility to amoxicil-lin-clavulanic acid (AMC: 30 μg), ampicillin (AM: 10 μg), cefotaxime (CTX: 5 μg), cefoxitin (FOX: 30 μg), ceftazidime (CAZ: 10 μg), ciprofloxacin (CIP: 5 μg), gentamicin (CN: 10 μg), meropenem (MEM: 10 μg), and trimethoprim-sulphamethoxazole (SXT: 25 μg).
Isolates were characterised as AMR if not susceptible to at least one of the antimicrobials recommended by the European Committee on Antimicrobial Susceptibility Testing, at a concentration corresponding to the determined breakpoint [4], and as MDR when non-susceptible to at least one agent from three antimicrobial categories [5].
3. Results
The examined pathogens were found in 54 (71.1%) of the 76 tested samples. S. aureus, CoNS and E. coli were detected in 14.5% (11 of 76), 38.2% (29 of 76) and 18.4% (14 of 76) of the samples, respectively. In 3 cases (3.9%, 3 of 76), which corresponded to samples collected from milking shells, the result of the analysis was positive for both E. coli and CoNS. The percentage of positive samples in the study farms was 88.2% in Farm A (15 of 17), 33.3% in Farm B (1 of 3), 66.7% (14 of 21) in Farm C, 88.2% in Farm D (15 of 17), and 50% (9 of 18) in Farm E. The lowest percentage of samples positive to E. coli was recorded in Farm B (0%, 0 of 3), whereas the highest was recorded in Farm D (29.5%, 5 of 17). The relevant percentages recorded for Staphylococci was 33.3% (1 of 3) in Farm B and 76.5% (13 of 17) in Farm A (Table 1).
The percentage of isolates of the study pathogens that were characterised as AMR of those detected was 27.8% (15 of 54), corresponding to 30% (12 of 40) of Staphylococci [33.3% (4 of 12) S. aureus, 66.7% (8 of 12) CoNS] and 21.4% (3 of 14) of E. coli. None (n = 0) of the 3 E. coli AMR isolates and 6 of the 12 AMR Staphylococci isolates were characterised as MDR (50%) [25% (1 of 4) S. aureus, 62.5% (5 of 8) CoNS]. All the AMR Staphylococci isolates (100%, 12 of 12) and 2 of the 3 (66.7%) AMR E. coli isolates were detected in the milking shells. The other AMR E. coli isolate was detected in a sample of feed (33.3%, 1 of 3). The number of AMR Staphylococci isolates of the total number of Staphylococci detected per farm was 1 of 13 (7.7%) in Farm A, 0 of 1 (0%) in Farm B, 4 of 9 (44.4%) in Farm C, 6 of 10 (60%) in Farm D, and 1 of 7 (14.3%) in Farm E. The relevant percentages with regards to E. coli were 2 of 2 (100%) in Farm A, and 1 of 2 (50%) in Farm E (Table 2 and Table 3). The number of MDR Staphylococci isolates of the total number of those characterised as AMR per farm was 1 of 1 (100%) in Farm A, 1 of 4 (25%) in Farm C, 4 of 6 (66.7%) in Farm D, and 0 of 1 (0%) in Farm E. None of the E. coli AMR isolates were characterised as MDR (Table 2 and Table 3).
4. Discussion
As mentioned above, the interest for this study was generated by the findings of our previous investigation, which resulted in a high percentage of positive samples of feeds and milk to the targeted pathogens, including AMR and MDR isolates. Therefore, this investigation aimed to conduct a more thorough analysis of the certain types of samples, which in connection to feeds, referred additionally to the analysis of their ingredients produced by the respective farmers. With regards to milk, the analysis was targeted to the raw milk tank, which had proven a reliable sampling point for in-farm monitoring [2], and the milking machines that may provide favourable conditions for the formation of biofilms exhibiting strong resistance to antibiotics and antiseptics [6,7].
The analysis of the samples collected from the milk tank and the milking shells was positive to E. coli in only 3 of the samples that were tested (5.7%, 3 of 53). These three samples were swabs from milking machines: two from Farm A and one from Farm D (Table 1). Considering that the detection of the certain pathogen implies faecal contamination, the small percentage of E. coli-positive samples of this category (samples of milk tank and swabs of milking shells) can be considered an indication of good hygiene for Farms C and E. To the contrary of E. coli, Staphylococci were detected in all the samples collected from the milk tank (three farms positive to S. aureus and two to CoNS), a finding that can be considered consistent with staphylococcal mastitis being a common problem in the study farms, and the certain sampling point (milk tank) being suitable for its routine monitoring [2]. Another finding that further supports the proposed correlation between mastitis and positivity of milk to Staphylococci was that positive results were recorded for the same group of pathogens in the milking shell swabs, in all farms that use milking machines (Farms A, C, D, and E). Comparing these results to those from the milk tank, with regards both to the pathogens detected and the AMR profile, concludes that they are not consistent, which indicates that milking machines are infected with pathogens that do not always appear in the milk tank (Table 2 and Table 3). This finding could be associated with the milking machines providing a substrate which favours formation of microbial biofilms, harbouring pathogens that are less likely to be detected in other sites within the farm [8]. Notably, only 1 of the 14 (7.1%) AMR isolates of all the study pathogens that were detected in milk (Staphylococci and E. coli) appeared in the milk tank; the rest (92.9%, 13 of 14) were detected in the milking shells (Table 1 and Table 2). Based on the above, AMR testing in samples collected from the milking shells is rendered advisable for improving in-farm AMR monitoring and complimentary to that conducted in samples of milk. In support of this, it is perhaps worth reporting that the analysis conducted in the milking shells concluded to MDR isolates in 6 of the 12 AMR Staphylococci-positive samples (50%). Notably, 4 of the 6 MDR Staphylococci isolates (66.7%) were detected in one farm (Farm D), which hosted 50% (6 of 12) of all the detected AMR Staphylococci isolates. This can be considered to constitute a strong indication of poor antimicrobial stewardship in the certain farm, for which, as mentioned above, positivity of a milking shell swab to E. coli was proposed as an indication of poor hygiene.
In corroborating the use of milking sells as a sampling point to assess AMR emergence within a farm, it is perhaps worth referring to a CoNS AMR isolate in Farm A, which was not detected in the samples collected from the milk tank and was the only AMR Staphylococcus isolate detected to be resistant to cefoxitin, hence potentially being of particular significance in terms of animal and public health protection [9,10].
The analysis of the samples of feeds and of their ingredients provided positive results for E. coli in Farms C–E, and for Staphylococci in Farm A. The certain category of samples (feeds and their ingredients) was negative to the targeted pathogens only in Farm B (Table 2 and Table 3). Contrary to our previous investigation that indicated heavy contamination of feeds with AMR isolates of the targeted pathogens, in this study, the positivity of the certain indicator was negligible, with only one positive E. coli isolate in Farm E. In speculating the cause of the improved AMR profile of the feeds tested in this study compared to those of our previous one, it is worth noting that to avoid seasonal positivity variations, sample collection was conducted in both studies between June and August. In the year that passed between the previous study and this investigation, the study farms were instructed to adopt measures to improve storage conditions of feeds, including infrastructure improvements for better ventilation and pest control. These suggestions were followed to a level that cannot fully justify the inconsistency between the two studies.
5. Conclusions
Based on the above, it would be safer to conclude that the findings reported in this study and our previous study [2] indicate that the spread and AMR emergence of the targeted pathogens in feeds are parameters of considerable variability and should therefore be assessed longitudinally.
Author Contributions
Conceptualization, J.I., A.M. (Alexandros Mavrommatis), E.T. and G.Z.; methodology and analysis, A.M. (Antonia Mataragka), J.I., N.T. and A.M. (Alexandros Mavrommatis); investigation, A.M. (Antonia Mataragka), J.I., N.T., A.M. (Alexandros Mavrommatis), E.T., A.S., M.K. and G.Z.; resources, E.T., G.Z. and J.I.; data curation, A.M. (Alexandros Mavrommatis), A.M. (Antonia Mataragka), E.T. and J.I.; writing—original draft preparation and writing—review and editing, A.M., J.I., N.T., A.M. (Alexandros Mavrommatis), A.S. and M.K.; visualization, supervision, and project administration, J.I., E.T. and G.Z. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding.
Institutional Review Board Statement
Not applicable.
Informed Consent Statement
Not applicable.
Data Availability Statement
Not applicable.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Food and Agriculture Organization. Drivers, Dynamics and Epidemiology of Antimicrobial Resistance in Animal Production. 2016. Available online: http://www.fao.org/3/i6209e/i6209e.pdf (accessed on 23 March 2023).
- Tzimotoudis, N.; Mataragka, A.; Mavrommatis, A.; Malesios, C.; Anastasiadi, V.; Galanis, D.; Timofte, D.; Zendri, F.; de Carvalho Ferreira, H.C.; Wauters, E.; et al. Antimicrobial Drug Resistance in Sheep Farms in Greece: Assessment of the Current Situation and Investigation Towards Improving Surveillance and Control. Acta Sci. Vet. Sci. 2022, 4, 173–186. [Google Scholar] [CrossRef]
- Ma, F.; Xu, S.; Tang, Z.; Li, Z.; Zhang, L. Use of antimicrobials in food animals and impact of transmission of antimicrobial resistance on humans. Biosaf. Health 2021, 3, 32–38. [Google Scholar] [CrossRef]
- The European Committee on Antimicrobial Susceptibility Testing. Breakpoint Tables for Interpretation of MICs and Zone Diameters. Version 13.0. 2023. Available online: http://www.eucast.org (accessed on 10 May 2023).
- Magiorakos, A.P.; Srinivasan, A.; Carey, R.B.; Carmeli, Y.; Falagas, M.E.; Giske, C.G.; Harbarth, S.; Hindler, J.F.; Kahlmeter, G.; Olsson-Liljequist, B.; et al. Multidrug resistant, extensively drug-resistant and pandrug-resistant bacteria: An international expert proposal for interim standard definitions for acquired resistance. Clin. Microbiol. Infect. 2012, 18, 268–281. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Bremer, P.J.; Fillery, S.; McQuillan, A.J. Laboratory scale Clean-In-Place (CIP) studies on the effectiveness of different caustic and acid wash steps on the removal of dairy biofilms. Int. J. Food Microbiol. 2006, 106, 254–262. [Google Scholar] [CrossRef] [PubMed]
- Jahid, I.K.; Ha, S.D. The Paradox of Mixed-Species Biofilms in the Context of Food Safety. Compr. Rev. Food Sci. Food Saf. 2014, 13, 990–1011. [Google Scholar] [CrossRef]
- Weber, M.; Liedtke, J.; Plattes, S.; Lipski, A. Bacterial community composition of biofilms in milking machines of two dairy farms assessed by a combination of culture-dependent and -independent methods. PLoS ONE 2019, 14, e0222238. [Google Scholar] [CrossRef] [PubMed]
- CLSI. Performance Standards for Antimicrobial Susceptibility Testing, 30th ed.; CLSI Supplement M100; Clinical and Laboratory Standards Institute: Wayne, PA, USA, 2020. [Google Scholar]
- Naccache, S.N.; Callan, K.; Burnham, C.A.; Wallace, M.A.; Westblade, L.F.; Dien Bard, J. Evaluation of Oxacillin and Cefoxitin Disk Diffusion and Microbroth Dilution Methods for Detecting mecA-Mediated β-Lactam Resistance in Contemporary Staphylococcus epidermidis Isolates. J. Clin. Microbiol. 2019, 57, e00961-19. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Table 1.
The total (T) number of samples tested per type, in Farms A–E, and the percentage of samples that reacted positively to either or both (B) of E. coli (Ec) and Staphylococci (St), i.e., S. aureus (denoted with an asterisk) and coagulase-negative Staphylococci (CoNS).
Table 1.
The total (T) number of samples tested per type, in Farms A–E, and the percentage of samples that reacted positively to either or both (B) of E. coli (Ec) and Staphylococci (St), i.e., S. aureus (denoted with an asterisk) and coagulase-negative Staphylococci (CoNS).
| Type of Sample | Farm A | Farm B | Farm C | Farm D | Farm E | Total | |||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| T | St | Ec | B | T | St | Ec | B | T | St | Ec | B | T | St | Ec | B | T | St | Ec | B | T | St | Ec | B | Sum Positive | |
| Milk tank | 1 | 1 | - | - | 1 | 1 * | - | - | 1 | 1 * | - | - | 1 | 1 * | - | - | 1 | 1 | - | - | 5 | 2 + 3 * | - | - | 5 |
| Outer shell 1 | 8 | 7 | 1 | 1 | - | - | - | - | 8 | 5 | - | - | 8 | 2 + 4 * | 1 | 1 | 8 | 5 | - | - | 32 | 19 + 4 * | 2 | 2 | 25 |
| Inner shell 1 | 4 | 4 | 1 | 1 | - | - | - | - | 4 | 3 * | - | - | 4 | 2 + 1 * | - | - | 4 | 1 | - | - | 16 | 7 + 4 * | 1 | 1 | 12 |
| Concentrated feed | 1 | - | - | - | 1 | - | - | - | 2 | - | 2 | - | 1 | - | 1 | - | 1 | - | 1 | - | 6 | - | 4 | - | 4 |
| Maize | 1 | - | - | - | 1 | - | - | - | 1 | - | - | - | 1 | - | 1 | - | 1 | - | 1 | - | 5 | - | 2 | - | 2 |
| Rapeseed | 1 | 1 | - | - | - | - | - | - | 1 | - | - | - | - | - | - | - | 1 | - | - | - | 3 | 1 | - | - | 1 |
| Soybean meal | 1 | - | - | - | - | - | - | - | 1 | - | 1 | - | - | - | - | - | 1 | - | - | - | 3 | - | 1 | - | 1 |
| Sunflower seed cake | - | - | - | - | - | - | - | - | 1 | - | - | - | - | - | - | - | - | - | - | - | 1 | - | - | - | - |
| Cottonseed cake | - | - | - | - | - | - | - | - | 1 | - | 1 | - | - | - | - | - | - | - | - | - | 1 | - | 1 | - | 1 |
| Wheat bran | - | - | - | - | - | - | - | - | 1 | - | 1 | - | - | - | - | - | 1 | - | - | - | 2 | - | 1 | - | 1 |
| Alfalfa hay pellet | - | - | - | - | - | - | - | - | - | - | - | - | 2 | - | 2 | - | - | - | - | - | 2 | - | 2 | - | 2 |
| Total | 17 | 13 76.5% | 2 11.8% | 2 11.8% | 3 | 1 33.3% | 0 | 0 | 21 | 9 42.8% | 5 23.8% | 0 | 17 | 10 58.3% | 5 29.5% | 1 5.9% | 18 | 7 38.3% | 2 11.1% | 0 | 76 | 29 + 11 * 52.6% | 14 18.4% | 3 3.9% | 54 71.1% |
1. Samples collected from the ring (outer) or the bottom (inner) of the milking shell.
Table 2.
Antibiotic resistance of the AMR Staphylococci isolates (S. aureus and CoNS) that were detected per type of sample (the asterisk denotes those positive to S. aureus), indicating the relevant antibiotics and the isolates characterised as MDR.
Table 2.
Antibiotic resistance of the AMR Staphylococci isolates (S. aureus and CoNS) that were detected per type of sample (the asterisk denotes those positive to S. aureus), indicating the relevant antibiotics and the isolates characterised as MDR.
| Farm | Positive Samples per Type | Antibiotic 2 | MDR | |||||||
|---|---|---|---|---|---|---|---|---|---|---|
| P | FOX | ERY | DA | SXT | NOR | CN | TE | |||
| A | Milk tank | |||||||||
| Outer shell 1 1 | ||||||||||
| Outer shell 2 | ||||||||||
| Outer shell 3 | + | + | + | + | ||||||
| Outer shell 4 | ||||||||||
| Outer shell 5 | ||||||||||
| Outer shell 7 | ||||||||||
| Outer shell 8 | ||||||||||
| Inner 1 shell 1 | ||||||||||
| Inner shell 2 | ||||||||||
| Inner shell 3 | ||||||||||
| Inner shell 4 | ||||||||||
| Rapeseed | ||||||||||
| Total Farm A | 0 of 13 | 1 of 13 | 0 of 13 | 0 of 13 | 0 of 13 | 0 of 13 | 1 of 13 | 1 of 13 | 1 of 13 | |
| B | Milk tank * | |||||||||
| Total Farm B | 0 of 1 | 0 of 1 | 0 of 1 | 0 of 1 | 0 of 1 | 0 of 1 | 0 of 1 | 0 of 1 | 0 of 1 | |
| C | Milk tank * | + | ||||||||
| Outer shell 1 | + | |||||||||
| Outer shell 2 | + | |||||||||
| Outer shell 5 | ||||||||||
| Outer shell 6 | ||||||||||
| Outer shell 8 | ||||||||||
| Inner shell 1 * | ||||||||||
| Inner shell 2 * | ||||||||||
| Inner shell 3 * | + | + | + | + | ||||||
| Total Farm C | 2 of 9 | 0 of 9 | 1 of 9 | 1 of 9 | 0 of 9 | 0 of 9 | 0 of 9 | 2 of 9 | 1 of 9 | |
| D | Milk tank * | |||||||||
| Outer shell 1 | + | + | + | + | ||||||
| Outer shell 2 * | + | |||||||||
| Outer shell 3 * | ||||||||||
| Outer shell 4 * | ||||||||||
| Outer shell 5 | + | + | + | + | ||||||
| Outer shell 7 * | ||||||||||
| Inner shell 1 | + | + | + | + | ||||||
| Inner shell 2 | + | + | + | + | ||||||
| Inner shell 4 * | + | |||||||||
| Total Farm D | 0 of 10 | 0 of 10 | 3 of 10 | 4 of 10 | 0 of 10 | 0 of 10 | 1 of 10 | 6 of 10 | 4 of 10 | |
| E | Milk tank | |||||||||
| Outer shell 1 | ||||||||||
| Outer shell 3 | ||||||||||
| Outer shell 5 | + | |||||||||
| Outer shell 6 | ||||||||||
| Outer shell 7 | ||||||||||
| Inner shell 4 | ||||||||||
| Total Farm E | 0 of 7 | 0 of 7 | 1 of 7 | 0 of 7 | 0 of 7 | 0 of 7 | 0 of 7 | 0 of 7 | 0 of 7 | |
| Total | 2 of 40 5% | 1 of 40 2.5% | 5 of 40 12.5% | 5 of 40 12.5% | 0 of 40 0% | 0 of 40 0% | 2 of 40 5% | 9 of 40 22.5% | 6 of 40 15% | |
1 Samples collected from the ring (outer) or the bottom (inner) of the milking shell. 2 P: penicillin; FOX: cefoxitin; ERY: erythromycin; DA: clindamycin; SXT: trimethoprim-sulphamethoxazole; NOR: norfloxacin; CN: gentamicin; TE: tetracycline.
Table 3.
Antibiotic resistance of the E. coli isolates that were detected per type of sample, indicating the relevant antibiotics and the isolates characterised as MDR.
Table 3.
Antibiotic resistance of the E. coli isolates that were detected per type of sample, indicating the relevant antibiotics and the isolates characterised as MDR.
| Farm | Positive Samples per Type | Antibiotic 2 | MDR | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| SXT | CN | CIP | AM | AMC | FOX | CAZ | MEM | CTX | |||
| A | Outer shell 1 3 | + | |||||||||
| Inner shell 1 | + | ||||||||||
| Total Farm A | 0 of 2 | 1 of 2 | 0 of 2 | 0 of 2 | 1 of 2 | 0 of 2 | 0 of 2 | 0 of 2 | 0 of 2 | 0 of 2 | |
| C | Concentrated Feed 1 | ||||||||||
| Concentrated Feed 2 | |||||||||||
| Cottonseed cake | |||||||||||
| Soybean meal | |||||||||||
| Wheat bran | |||||||||||
| Total Farm C | 0 of 5 | 0 of 5 | 0 of 5 | 0 of 5 | 0 of 5 | 0 of 5 | 0 of 5 | 0 of 5 | 0 of 5 | 0 of 5 | |
| D | Outer shell 3 | ||||||||||
| Concentrated Feed | |||||||||||
| Maize | |||||||||||
| Alfalfa hay pellet 1 | |||||||||||
| Alfalfa hay pellet 2 | |||||||||||
| Total Farm D | 0 of 5 | 0 of 5 | 0 of 5 | 0 of 5 | 0 of 5 | 0 of 5 | 0 of 5 | 0 of 5 | 0 of 5 | 0 of 5 | |
| E | Concentrated Feed | + | |||||||||
| Maize | |||||||||||
| Total Farm E | 1 of 2 | 0 of 2 | 0 of 2 | 0 of 2 | 0 of 2 | 0 of 2 | 0 of 2 | 0 of 2 | 0 of 2 | 0 of 2 | |
| Total | 1 of 14 7.1% | 1 of 14 7.1% | 0 of 14 0% | 0 of 14 0% | 1 of 14 7.1% | 0 of 14 0% | 0 of 14 0% | 0 of 14 0% | 0 of 14 0% | 0 of 14 0% | |
1 Samples collected from the ring (outer) or the bottom (inner) of the milking shell. 2 SXT: trimethoprim-sulphamethoxazole; CN: gentamicin; CIP: ciprofloxacin; AM: ampicillin; AMC: amoxicillin-clavulanic acid; FOX: cefoxitin; CAZ: ceftazidime; MEM: meropenem; CTX: cefotaxime.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Mataragka, A.; Tzimotoudis, N.; Mavrommatis, A.; Tsiplakou, E.; Symeonidou, A.; Kotsikori, M.; Zervas, G.; Ikonomopoulos, J. Investigating the Spread of Antimicrobial Drug-Resistant Microorganisms in Dairy Sheep Farms: A Follow-Up Study. Appl. Sci. 2023, 13, 8165. https://0-doi-org.brum.beds.ac.uk/10.3390/app13148165
AMA Style
Mataragka A, Tzimotoudis N, Mavrommatis A, Tsiplakou E, Symeonidou A, Kotsikori M, Zervas G, Ikonomopoulos J. Investigating the Spread of Antimicrobial Drug-Resistant Microorganisms in Dairy Sheep Farms: A Follow-Up Study. Applied Sciences. 2023; 13(14):8165. https://0-doi-org.brum.beds.ac.uk/10.3390/app13148165
Chicago/Turabian StyleMataragka, Antonia, Nikolaos Tzimotoudis, Alexandros Mavrommatis, Eleni Tsiplakou, Andrianna Symeonidou, Maria Kotsikori, George Zervas, and John Ikonomopoulos. 2023. "Investigating the Spread of Antimicrobial Drug-Resistant Microorganisms in Dairy Sheep Farms: A Follow-Up Study" Applied Sciences 13, no. 14: 8165. https://0-doi-org.brum.beds.ac.uk/10.3390/app13148165
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
