Evaluation of virulence factors profiles and antimicrobials resistance of Escherichia coli isolated from bulk tank milk and raw milk filters

Dell'Orco, Francesca; Gusmara, C.; Loiacono, Monica; Gugliotta, Theo; Albonico, F.; Mortarino, Michele; Zecconi, A.

doi:10.1016/j.rvsc.2018.12.011

Cited by 25 publications

(22 citation statements)

References 27 publications

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“…coli from bulk tank milk from both conventional and organic farms had low resistance rates and relative frequencies of resistance combinations. Low presence of AR in commensal E. coli (non-clinical E. coli isolates) from bulk tank milk has been previously reported [58,59]. Low use of antibiotics in dairy cattle [51,60] might result in low AR in the bacteria in milk.…”

Section: Discussionmentioning

confidence: 99%

Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017

et al. 2021

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Recent findings on Antibiotic Resistance (AR) have brought renewed attention to the comparison of data on AR from human and animal sectors. This is however a major challenge since the data is not harmonized. This study performs a comparative analysis of data on resistance combinations in Escherichia coli (E. coli) from different routine surveillance and monitoring systems for human and different animal populations in Germany. Data on E. coli isolates were collected between 2014 and 2017 from human clinical isolates, non-clinical animal isolates from food-producing animals and food, and clinical animal isolates from food-producing and companion animals from national routine surveillance and monitoring for AR in Germany. Sixteen possible resistance combinations to four antibiotics—ampicillin, cefotaxime, ciprofloxacin and gentamicin–for these populations were used for hierarchical clustering (Euclidian and average distance). All analyses were performed with the software R 3.5.1 (Rstudio 1.1.442). Data of 333,496 E. coli isolates and forty-one different human and animal populations were included in the cluster analysis. Three main clusters were detected. Within these three clusters, all human populations (intensive care unit (ICU), general ward and outpatient care) showed similar relative frequencies of the resistance combinations and clustered together. They demonstrated similarities with clinical isolates from different animal populations and most isolates from pigs from both non-clinical and clinical isolates. Isolates from healthy poultry demonstrated similarities in relative frequencies of resistance combinations and clustered together. However, they clustered separately from the human isolates. All isolates from different animal populations with low relative frequencies of resistance combinations clustered together. They also clustered separately from the human populations. Cluster analysis has been able to demonstrate the linkage among human isolates and isolates from various animal populations based on the resistance combinations. Further analyses based on these findings might support a better one-health approach for AR in Germany.

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Section: Discussionmentioning

confidence: 99%

Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017

et al. 2021

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“…In summary, considering the different matrices, sequencing depths and microbial enrichment methods evaluated in this study, milk filters treated with MolYsis kit and sequenced to a depth of 60 M PE reads appeared to be the more suitable samples to obtain a deep taxonomic and AMR gene content profiling of the milk production environment evaluated; nevertheless, the increasing of costs and time spent manipulating the samples must be taken into account. The analysis of milk filters to investigate the microbiome and to identify the presence of foodborne pathogens or AMR genes has already proved to be a useful tool (Murphy et al, 2005;Sonnier et al, 2018;Dell'Orco et al, 2019). In-line filters can filter milk from approximately 150 cows, catching debris, large particles of organic material, and foreign objects.…”

Section: Discussionmentioning

confidence: 99%

Detection of Antimicrobial Resistance Genes in the Milk Production Environment: Impact of Host DNA and Sequencing Depth

et al. 2020

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Over the past decades, antimicrobial resistance (AMR) has been recognized as one of the most serious threats to public health. Although originally considered a problem to human health, the emerging crisis of AMR requires a "One Health" approach, considering human, animal, and environmental reservoirs. In this regard, the extensive use of antibiotics in the livestock production systems to treat mastitis and other bacterial diseases can lead to the presence of AMR genes in bacteria that contaminate or naturally occur in milk and dairy products, thereby introducing them into the food chain. The recent development of high-throughput next-generation sequencing (NGS) technologies is improving the fast characterization of microbial communities and their functional capabilities. In this context, whole metagenome sequencing (WMS), also called shotgun metagenomic sequencing, allows the generation of a vast amount of data which can be interrogated to generate the desired evidence, including the resistome. However, the amount of host DNA poses a major challenge to metagenome analysis. Given the current absence of literature concerning the application of WMS on milk to detect the presence of AMR genes, in the present study, we evaluated the effect of different sequencing depths, host DNA depletion methods and matrices to characterize the resistome of a milk production environment. WMS was conducted on three aliquots of bulk tank milk and three aliquots of the in-line milk filter collected from a single dairy farm; a fourth aliquot of milk and milk filter was bioinformatically subsampled. Two commercially available host DNA depletion methods were applied, and metagenomic DNA was sequenced to two different sequencing depth. Milk filters proved to be the most suitable matrices to evaluate the presence of AMR genes; besides, the pre-extraction host DNA depletion method was the most efficient approach to remove host reads. To our knowledge, this is the first study to evaluate the limitations posed by the host DNA in investigating the milk resistome with a WMS approach, confirming the circulation of AMR genes in the milk production environment.

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“…E. coli from bulk tank milk from both conventional and organic farms had low resistance rates and relative frequencies of resistance combinations. Low presence of AR in commensal E. coli (non-clinical E. coli isolates) from bulk tank milk has been previously reported (58,59). Low systemic use of antibiotics in dairy cattle (51,60) might result in low AR in the bacteria in milk.…”

Section: Discussionmentioning

confidence: 95%

Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017

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Eckmanns

Kaspar

et al. 2020

Preprint

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Recent findings on Antibiotic Resistance (AR) have brought renewed attention to the comparison of data on AR from human and animal sectors. This is however, a major challenge since the data is not harmonized. This study performs a comparative analysis of data on resistance combinations in Escherichia coli (E. coli) from different routine surveillance and monitoring systems for human and different animal populations in Germany. Data on E. coli isolates were collected between 2014 and 2017 from human clinical isolates, non-clinical animal isolates from food-producing animals and food, and clinical animal isolates from food-producing and companion animals from national routine surveillance and monitoring for AR in Germany. Sixteen possible resistance combinations to four antibiotics - ampicillin, cefotaxime, ciprofloxacin and gentamicin – for these populations were used for hierarchical clustering (Euclidian and average distance). All analyses were performed with the software R 3.5.1 (Rstudio 1.1.442). Data of 333,496 E. coli isolates and forty-one different human and animal populations were included in the cluster analysis. Three main clusters were detected. Within these three clusters, all human populations (intensive care unit (ICU), general ward and outpatient care) showed similar relative frequencies of the resistance combinations and clustered together. They demonstrated similarities with clinical isolates from different animal populations and most isolates from pigs from both non-clinical and clinical isolates. Isolates from healthy poultry demonstrated similarities in relative frequencies of resistance combinations and clustered together. However, they clustered separately from the human isolates. All isolates from different animal populations with low relative frequencies of resistance combinations clustered together and likewise separately from the human populations. Cluster analysis has been able to demonstrate the linkage among human isolates and isolates from various animal populations based on the resistance combinations. Further analyses based on these findings might promote a better one-health approach for AR in Germany.

show abstract

Evaluation of virulence factors profiles and antimicrobials resistance of Escherichia coli isolated from bulk tank milk and raw milk filters

Cited by 25 publications

References 27 publications

Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017

Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017

Detection of Antimicrobial Resistance Genes in the Milk Production Environment: Impact of Host DNA and Sequencing Depth

Cluster analysis of resistance combinations in Escherichia coli from different human and animal populations in Germany 2014-2017

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