Bacterial antimicrobial resistance (AMR) is constantly evolving and horizontal gene transfer through plasmids plays a major role. The identification of plasmid characteristics and their association ...with different bacterial hosts provides crucial knowledge that is essential to understand the contribution of plasmids to the transmission of AMR determinants. Molecular identification of plasmid and strain genotypes elicits a distinction between spread of AMR genes by plasmids and dissemination of these genes by spread of bacterial clones. For this reason several methods are used to type the plasmids, e.g. PCR-based replicon typing (PBRT) or relaxase typing. Currently, there are 28 known plasmid types in Enterobacteriaceae distinguished by PBRT. Frequently reported plasmids IncF, IncI, IncA/C, IncL (previously designated IncL/M), IncN and IncH are the ones that bear the greatest variety of resistance genes. The purpose of this review is to provide an overview of all known AMR-related plasmid families in Enterobacteriaceae, the resistance genes they carry and their geographical distribution.
The mobile colistin resistance gene mcr-1 has been identified worldwide in human and animal sources, while its occurrence in the environment is still largely unknown. The aim of this study was to ...investigate the presence of mcr-1 -harbouring Enterobacteriaceae in water samples obtained from rivers and waste water treatment plants in the area of Barcelona, Spain.
The presence of mcr-1 was detected by PCR. Bacterial identification was performed via MALDI-TOF MS. Resistance to colistin was determined by a broth dilution method. The epidemiological relationship between the positive isolates was assessed with PFGE and ST was determined by MLST. Plasmid characterization was performed by transformation experiments, antimicrobial susceptibility testing and incompatibility group PCR.
Thirty MDR isolates bearing mcr-1 , 29 Escherichia coli (ST632 and ST479) and 1 Klebsiella pneumoniae (ST526), were identified in sewage from two different waste water treatment plants, whereas the gene was not found in river water. All isolates, including the K. pneumoniae , harboured bla CTX-M-55 and bla TEM-1 . mcr-1 was in all cases associated with an IncI2 plasmid, which only conferred resistance to colistin. mcr-1 was harboured by two predominant E. coli clones that were found in both waste water treatment plants.
This study showed a high occurrence of mcr-1 in the sewage of Barcelona, mainly due to the dissemination of two E. coli pulsotypes that are circulating in the population. The presence of mcr-1 in the environment is a cause for concern, and suggests high prevalence of mcr-1 in the community.
Abstract
Improvements in cost and speed of next generation sequencing (NGS) have provided a new pathway for delivering disease diagnosis, molecular typing, and detection of antimicrobial resistance ...(AMR). Numerous published methods and protocols exist, but a lack of harmonisation has hampered meaningful comparisons between results produced by different methods/protocols vital for global genomic diagnostics and surveillance. As an exemplar, this study evaluated the sensitivity and specificity of five well-established in-silico AMR detection software where the genotype results produced from running a panel of 436
Escherichia coli
were compared to their AMR phenotypes, with the latter used as gold-standard. The pipelines exploited previously known genotype–phenotype associations. No significant differences in software performance were observed. As a consequence, efforts to harmonise AMR predictions from sequence data should focus on: (1) establishing universal minimum to assess performance thresholds (e.g. a control isolate panel, minimum sensitivity/specificity thresholds); (2) standardising AMR gene identifiers in reference databases and gene nomenclature; (3) producing consistent genotype/phenotype correlations. The study also revealed limitations of in-silico technology on detecting resistance to certain antimicrobials due to lack of specific fine-tuning options in bioinformatics tool or a lack of representation of resistance mechanisms in reference databases. Lastly, we noted user friendliness of tools was also an important consideration. Therefore, our recommendations are timely for widespread standardisation of bioinformatics for genomic diagnostics and surveillance globally.
Abstract
Objectives
Farm-level quantification of antimicrobial usage (AMU) in pig farms.
Methods
In a cross-sectional study, AMU data on group treatments administered to a single batch of fattening ...pigs from birth to slaughter (group treatment data) and antimicrobials purchased during 1 year (purchase data) were collected at 180 pig farms in nine European countries. AMU was quantified using treatment incidence (TI) based on defined (DDDvet) and used (UDDvet) daily doses and defined (DCDvet) and used (UCDvet) course doses.
Results
The majority of antimicrobial group treatments were administered to weaners (69.5% of total TIDDDvet) followed by sucklers (22.5% of total TIDDDvet). AMU varied considerably between farms with a median TIDDDvet of 9.2 and 7.1 for a standardized rearing period of 200 days based on group treatment and purchase data, respectively. In general, UDDvet and UCDvet were higher than DDDvet and DCDvet, respectively, suggesting that either the defined doses were set too low or that group treatments were often dosed too high and/or administered for too long. Extended-spectrum penicillins (31.2%) and polymyxins (24.7%) were the active substances most often used in group treatments, with the majority administered through feed or water (82%). Higher AMU at a young age was associated with higher use in older pigs.
Conclusions
Collecting farm-level AMU data of good quality is challenging and results differ based on how data are collected (group treatment data versus purchase data) and reported (defined versus used daily and course doses).
Abstract
Objectives
To control the emerging threat of antimicrobial resistance, international policy appeals for appropriate monitoring of antimicrobial usage (AMU) at supranational, species and farm ...level. The aim of this study was to quantify AMU in broilers at farm and flock level in nine European countries.
Methods
Antimicrobial treatment data of one flock and purchased antimicrobials over one year were collected at 181 European broiler farms. Afterwards AMU was quantified using treatment incidence (TI) per 100 days based on Defined Daily Dose (DDDvet), Defined Course Dose (DCDvet) or Used Daily Dose (UDDvet) values. Total AMU at flock level was obtained by summing the TIDDDvet of all treatments in the sampled flock (TIDDDvetFl*).
Results
The median TIDDDvetFl* was 9.0 (95% CI 5.5–10.8), meaning that broilers were treated with antimicrobials during 9% of their rearing period. TIDDDvetFl* varied considerably within and between countries. However, in every country at least one untreated flock was present. Average TIDDDvetFl* at country level ranged from 3.3 to 36.7. Polymyxins, extended-spectrum aminopenicillins and fluoroquinolones were the most used antimicrobials, accounting for 26%, 26% and 18% of total AMU, respectively. Twenty-six percent of the farms started a treatment on day 1 of production, and 49% of overall AMU was administered within the first week.
Conclusions
Results show that rearing broilers without AMU is feasible. However, a huge variation in AMU in terms of amount, moment of administration and antimicrobial classes was observed. This shows that there is still ground to be covered when it comes to AMU on broiler farms.
Broiler chickens are among the main livestock sectors worldwide. With individual treatments being inapplicable, contrary to many other animal species, the need for antimicrobial use (AMU) is ...relatively high. AMU in animals is known to drive the emergence and spread of antimicrobial resistance (AMR). High farm biosecurity is a cornerstone for animal health and welfare, as well as food safety, as it protects animals from the introduction and spread of pathogens and therefore the need for AMU. The goal of this study was to identify the main biosecurity practices associated with AMU in broiler farms and to develop a statistical model that produces customised recommendations as to which biosecurity measures could be implemented on a farm to reduce its AMU, including a cost-effectiveness analysis of the recommended measures. AMU and biosecurity data were obtained cross-sectionally in 2014 from 181 broiler farms across nine European countries (Belgium, Bulgaria, Denmark, France, Germany, Italy, the Netherlands, Poland and Spain). Using mixed-effects random forest analysis (Mix-RF), recursive feature elimination was implemented to determine the biosecurity measures that best predicted AMU at the farm level. Subsequently, an algorithm was developed to generate AMU reduction scenarios based on the implementation of these measures. In the final Mix-RF model, 21 factors were present: 10 about internal biosecurity, 8 about external biosecurity and 3 about farm size and productivity, with the latter showing the largest (Gini) importance. Other AMU predictors, in order of importance, were the number of depopulation steps, compliance with a vaccination protocol for non-officially controlled diseases, and requiring visitors to check in before entering the farm. K-means clustering on the proximity matrix of the final Mix-RF model revealed that several measures interacted with each other, indicating that high AMU levels can arise for various reasons depending on the situation. The algorithm utilised the AMU predictive power of biosecurity measures while accounting also for their interactions, representing a first step toward aiding the decision-making process of veterinarians and farmers who are in need of implementing on-farm biosecurity measures to reduce their AMU.
As in other bacterial pathogens, the virulence determinants of
Listeria species are clustered in genomic islands scattered along the chromosome. This review summarizes current knowledge about the ...structure, distribution and role in pathogenesis of
Listeria virulence loci. Hypotheses about the mode of acquisition and evolution of these loci in this group of Gram-positive bacteria are presented and discussed.
We assessed the role of the actin‐polymerizing protein, ActA, in host cell invasion by Listeria monocytogenes. An in frame ΔactA mutant was constructed in a hyperinvasive strain of prfA* genotype, in ...which all genes of the PrfA‐dependent virulence regulon, including actA, are highly expressed in vitro. Loss of ActA production in prfA* bacteria reduced entry into Caco‐2, HeLa, MDCK and Vero epithelial cells to basal levels. Reintroduction of actA into the ΔactA prfA* mutant fully restored invasiveness, demonstrating that ActA is involved in epithelial cell invasion. ActA did not contribute to internalization by COS‐1 fibroblasts and Hepa 1‐6 hepatocytes. Expression of actA in Listeria innocua was sufficient to promote entry of this non‐invasive species into epithelial cell lines, but not into COS‐1 and Hepa 1‐6 cells, indicating that ActA directs an internalization pathway specific for epithelial cells. Scanning electron microscopy of infected Caco‐2 human enterocytes suggested that this pathway involves microvilli. prfA* bacteria, but not wild‐type bacteria (which express PrfA‐dependent genes very weakly in vitro) or prfA*ΔactA bacteria, efficiently invaded differentiated Caco‐2 cells via their apical surface. Microvilli played an active role in the phagocytosis of the prfA* strain, and actA was required for their remodelling into pseudopods mediating bacterial uptake. Thus, ActA appears to be a multifunctional virulence factor involved in two important aspects of Listeria pathogenesis: actin‐based motility and host cell tropism and invasion.
PDF
