| Literature DB >> 35040117 |
E M Parker1, M Valcanis2, L J Edwards3, P Andersson2, D F Mollenkopf1, T E Wittum1.
Abstract
Food for human and animal consumption can provide a vehicle for the transfer of pathogenic and antimicrobial-resistant bacteria into the food chain. We investigated the antimicrobial susceptibility of 453 Salmonella isolates collected from raw feed components, equipment and finished feed from 17 commercial feed mills in Australia between 2012 and 2021. Previous studies have found Salmonella prevalence and the diversity of Salmonella serotypes are greatest in the raw feed components. We, therefore, hypothesised that we would find a greater proportion of antimicrobial-resistant Salmonella isolates in the raw feed components compared to other sample types. We found that of 453 isolates tested, 356 (0.80) were susceptible to all antimicrobials tested, 49 (0.11) were nonsusceptible to streptomycin only and 48 (0.11) were resistant to two or more antimicrobials. Of the 48 antimicrobial-resistant isolates, 44 were found in feed milling equipment, two in raw feed components and two in finished feed. Statistical analysis, using a logistic regression with random effects model, found that the population-adjusted mean probability of detecting antimicrobial-resistant Salmonella isolates from feed milling equipment of 0.39, was larger than the probability of detecting resistant isolates in raw feed components 0.01, (P < 0.001) and in finished feed, 0.11, (P = 0.006). This propensity for antimicrobial-resistant bacteria to colonise feed milling equipment has not been previously reported. Further studies are required to understand the ecology of antimicrobial-resistant Salmonella in the feed milling environment.Entities:
Keywords: animal feed; antibiotics; antimicrobial resistance; feed mill; food safety; public health
Mesh:
Substances:
Year: 2022 PMID: 35040117 PMCID: PMC9304270 DOI: 10.1111/avj.13146
Source DB: PubMed Journal: Aust Vet J ISSN: 0005-0423 Impact factor: 1.343
Probability of antimicrobial susceptible, nonsusceptible and resistant Salmonella isolates recovered from Australian feed mills
| Antimicrobial susceptibility testing result | Number of | Probability 95% confidence interval |
|---|---|---|
| Susceptible | 356 | 0.79 (0.75–0.82) |
| Nonsusceptible to streptomycin only | 49 | 0.11 (0.08–0.14) |
| Resistant to two or more antimicrobials | 48 | 0.11 (0.08–0.13) |
| Total | 453 |
Probability of antimicrobial‐resistant Salmonella isolates by sample type from Australian feed mills
| Sample type | Number of isolates | Number of resistant | Probability (95% confidence interval) |
|---|---|---|---|
| Raw material | 228 | 2 | 0.01 (0.00–2.1) |
| Equipment | 124 | 44 | 0.36 (0.27–0.44) |
| Finished feed | 101 | 2 | 0.02 (0.0–0.05) |
| Total | 453 | 48 | 0.11 (7.8–13.4) |
Figure 1The feed processing chain. Forty‐four antimicrobial‐resistant Salmonella isolates were from environmental swabs of equipment in the post heat treatment area of the mill.
Antimicrobial resistance patterns for antimicrobial‐resistant Salmonella isolates representing six serotypes with phenotypic resistance to antimicrobials recovered from Australian feed mills
| Serotype | Sample type | Mill no. | Year |
| Resistance patterns |
|---|---|---|---|---|---|
| Anatum | Equipment | 2 | 2019 | 1 | ACCtSuTTmSp (nsS) |
| Number of isolates = 32 | Equipment | 2 | 2018 | 1 | ACSuTmSp (nsST) |
| Number AMR = 16 | Equipment | 5 | 2015 | 8 | ACSuTTmSp (nsC, 3 x nsS) |
| Equipment | 5 | 2015 | 1 | CTSu | |
| Equipment | 4 | 2018–19 | 3 | CtSpSuTTm (nsS) | |
| Equipment | 1 | 2018 | 1 | CtSpSuTTm | |
| Equipment | 1 | 2020 | 1 | SuT (nsS) | |
| Mbandaka | Equipment | 7 | 2015 | 1 | AGSSpSuTTM |
| Number of isolates = 35 | Equipment | 7 | 2015 | 1 | AGSpSuTm |
| Number AMR = 16 | Equipment | 7 | 2015 | 1 | ASpSuTTm |
| Feed | 7 | 2016 | 1 | AAzCSSpSuTTm | |
| Equipment | 7 | 2012 | 1 | SpSuTTm | |
| Equipment | 5 | 2018 | 2 | ASuT (nsCp) | |
| Equipment | 1 | 2015 | 1 | SpSuTTm | |
| Equipment | 6 | 2015 | 8 | SpSuTTm | |
| Singapore | Canola meal | 3 | 2014 | 1 | SSpSuT |
| Number of isolates = 13 | Meat meal | 3 | 2015 | 1 | SSpSuT |
| Number AMR = 11 | Equipment | 3 | 2016–19 | 9 | SSpSuT |
| Subsp. I ser. 4,[5],12:i:‐ | Equipment | 3 | 2019 | 1 | ASSuT |
| Number of isolates = 2 | Equipment | 5 | 2020 | 1 | ASSuT |
| Number AMR = 2 | |||||
| Orion | Feed | 6 | 2020 | 1 | SSuTSp |
| Number of isolates = 57 | |||||
| Number AMR = 1 | |||||
| Senftenberg | Equipment | 2 | 2020 | 1 | ACSuTTmSp (nsSCp) |
| Number of isolates = 24 | |||||
| Number AMR = 1 | |||||
| Worthington | Equipment | 6 | 2018 | 1 | SuTTmSp |
| Number of isolates = 2 | |||||
| Number AMR = 1 |
A, ampicillin; Az, azithromycin, C, chloramphenicol; Cp, ciprofloxacin; Ct, trimethoprim‐sulphathiazole (co‐trimoxazole); G, gentamicin; ns, nonsusceptible; S, streptomycin; Sp, spectinomycin; Su, sulphathiozole; T, tetracycline; Tm, trimethoprim.
Mills 1 to 5 are RAM mills, Mills 6 and 7 are non‐RAM mills.
Results of the multivariable logistic regression with random effects model to assess the odds of detection of an antimicrobial‐resistant salmonella isolate from raw material, equipment and finished feed in Australian feed mills
| Variable | Coefficient | P‐value | Population adjusted predicted probability (95% CI) |
|---|---|---|---|
| β0 | −6.47 (−8.70 to 4.26) | <0.001 | |
| Sample type | |||
| Raw materials | 0A | 0.01 (0.00–0.04) | |
| Equipment | 5.74B (3.91–7.56) | <0.001 | 0.39 (0.19–0.60) |
| Finished feed | 3.03C (0.72–5.34) | 0.004 | 0.11 (0.00–0.27) |
| Mill site | Residual intraclass correlation (95% CI) | ||
| Variance | 5.08 (1.45–17.56) | 0.61 (0.31–0.84) | |
Coefficients within variables with different superscripts, (A, B or C), differ (P < 0.05).
P‐value based on the likelihood ratio chi square test statistic.
β the logistic regression model intercept.
CI, Confidence interval.