Antimicrobial Resistance Gene Content Research Articles

Genomic comparison of two Streptococcus suis serotype 1 strains recovered from porcine and human disease cases

Streptococcus suis is a zoonotic pathogen that causes invasive infections in humans and pigs. Although S. suis serotype 2 strains are most prevalent worldwide, other serotypes are also occasionally detected. Herein, we investigated the genomes of two S. suis serotype 1 strains belonging to the clonal complex 1, which were recovered from a human patient and an asymptomatic pig, respectively. The genomes differed in pathotype, virulence-associated gene (VAG) profile, minimum core genome (MCG) typing, and antimicrobial resistance gene content. The porcine serotype 1 strain was sequence type (ST) 237 and MCG1, whereas the human serotype 1 strain was ST105 and MCG ungroupable. Both strains were susceptible to several antibiotics consisting of β-lactams, fluoroquinolones, and chloramphenicol. Resistance to tetracycline, macrolides, and clindamycin was observed, which was attributed to the genes tet(O) and erm(B). Analysis of 99 VAG revealed Hhly3, NisK, NisR, salK/salR, srtG, virB4, and virD4 were absent in both serotype 1. However, the porcine strain lacked sadP (Streptococcal adhesin P), whereas the human strain harbored sadP1. Phylogenetic analysis revealed that human S. suis ST105 strains from Vietnam were genetically the closest to the human serotype 1 strain, whereas porcine S. suis ST11 strains from China and Thailand were genetically the closest to the porcine strain.

Potential influence of antimicrobial resistance gene content in probiotic bacteria on the gut resistome ecosystems.

Antimicrobial resistance (AMR) poses a substantial threat to human health. The commensal bacteria of the gut microbiome were shown to serve as a reservoir of antibiotic resistance genes (ARGs), termed the gut resistome, which has the potential to transfer horizontally to pathogens and contribute to the emergence of drug-resistant bacteria. Namely, AMR traits are generally linked with mobile genetic elements (MGEs), which apart from disseminating vertically to the progeny, may cross horizontally to the distantly related microbial species. On the other hand, while probiotics are generally considered beneficiary to human health, and are therefore widely consumed in recent years most commonly in conjunction with antibiotics, the complexities and extent of their impact on the gut microbiome and resistome have not been elucidated. By reviewing the latest studies on ARG containing commercial probiotic products and common probiotic supplement species with their actual effects on the human gut resistome, this study aims to demonstrate that their contribution to the spread of ARGs along the GI tract merits additional attention, but also indicates the changes in sampling and profiling of the gut microbiome which may allow for the more comprehensive studying of the effects of probiotics in this part of the resistome.

The antibiotic resistome in Escherichia coli isolated from human, food and animal sources.

The aim of this study was to analyze and compare the prevalence and distribution of resistance genes in Escherichia coli genomes isolated from human clinical samples and animal-based foods worldwide. We download from NCBI Pathogen Detection Database the corresponding metadata of the 7123 E. coli genome to access the information about the antimicrobial resistance gene content. The geographic location and the source of isolation were also obtained and compiled with the antimicrobial resistance gene for statistical analysis, results and discussion. Our criteria considered four groups for analyzing the antimicrobial resistance gene distribution. The first group of genomes from invasive clinical human (ICH) samples from countries with Human Development Index (HDI) ≥ 0.850; the second group of ICH from countries with an HDI≤0.849; the third group of animal-based foods (ABF) from countries with HDI≥0.850 and the fourth group of ABFs from countries with HDI≤0.849. The most prevalent genes in the first group were blaCTX-M-134 (96.53%) and blaCTX-M-27 (86.35%). In the second group, ere(A) (95.96%), soxS (94.49%), qepA8 (90.81%), blaCTX-M-15 (85.66%), and fosA3 (80.88%). In the third group, the most frequently detected were aadA12 (98.5%), ant(3") (89.92%), and blaCARB-2 (87.2%). In the fourth group, aadA12 and aac(3)-IV were identified in 100% of the analyzed genomes. It was clear that the use of aminoglycosides in animal production is increasing the selective pressure on micro-organisms in both groups of countries since genes linked to aminoglycoside resistance are related to E. coli from ABF samples. The genomic profile of E. coli from HDI≥0.850 countries indicates a selective pressure aimed at cephalosporins given the high prevalence in both sources.

Epidemiological links and antimicrobial resistance of clinical Salmonella enterica ST198 isolates: a nationwide microbial population genomic study in Switzerland.

Salmonella is a leading cause of foodborne outbreaks and systemic infections worldwide. Emerging multi-drug resistant Salmonella lineages such as a ciprofloxacin-resistant subclade (CIPR) within Salmonella enterica serovar Kentucky ST198 threaten the effective prevention and treatment of infections. To understand the genomic diversity and antimicrobial resistance gene content associated with S. Kentucky in Switzerland, we whole-genome sequenced 70 human clinical isolates obtained between 2010 and 2020. Most isolates belonged to ST198-CIPR. High- and low-level ciprofloxacin resistance among CIPR isolates was associated with variable mutations in ramR and acrB in combination with stable mutations in quinolone-resistance determining regions (QRDRs). Analysis of isolates from patients with prolonged ST198 colonization indicated subclonal adaptions with the ramR locus as a mutational hotspot. SNP analyses identified multiple clusters of near-identical isolates, which were often associated with travel but included spatiotemporally linked isolates from Switzerland. The largest SNP cluster was associated with travellers returning from Indonesia, and investigation of global data linked >60 additional ST198 salmonellosis isolates to this cluster. Our results emphasize the urgent need for implementing whole-genome sequencing as a routine tool for Salmonella surveillance and outbreak detection.

Curation of the AMRFinderPlus databases: applications, functionality and impact

Antimicrobial resistance (AMR) is a significant public health threat. Low-cost whole-genome sequencing, which is often used in surveillance programmes, provides an opportunity to assess AMR gene content in these genomes using in silico approaches. A variety of bioinformatic tools have been developed to identify these genomic elements. Most of those tools rely on reference databases of nucleotide or protein sequences and collections of models and rules for analysis. While the tools are critical for the identification of AMR genes, the databases themselves also provide significant utility for researchers, for applications ranging from sequence analysis to information about AMR phenotypes. Additionally, these databases can be evaluated by domain experts and others to ensure their accuracy. Here we describe how we curate the genes, point mutations and blast rules, and hidden Markov models used in NCBI’s AMRFinderPlus, along with the quality-control steps we take to ensure database quality. We also describe the web interfaces that display the full structure of the database and their newly developed cross-browser relationships. Then, using the Reference Gene Catalog as an example, we detail how the databases, rules and models are made publicly available, as well as how to access the software. In addition, as part of the Pathogen Detection system, we have analysed over 1 million publicly available genomes using AMRFinderPlus and its databases. We discuss how the computed analyses generated by those tools can be accessed through a web interface. Finally, we conclude with NCBI’s plans to make these databases accessible over the long-term.

Diversity of carbapenemase-producing Enterobacterales in England as revealed by whole-genome sequencing of isolates referred to a national reference laboratory over a 30-month period.

Introduction. Increasing numbers of carbapenemase-producing Enterobacterales (CPE), which can be challenging to treat, have been referred to the national reference laboratory in England since the early 2000s.Gap Statement/Aim. Previous studies on CPE in the UK have focussed on localized outbreaks. We applied whole-genome sequencing (WGS) to isolates referred to the national reference laboratory over 30 months to inform our understanding of CPE epidemiology in England.Methodology. The first confirmed CPE from each new patient referred by an English diagnostic laboratory between 1 January 2014 and 30 June 2016 was sequenced on an Illumina HiSeq 2500. Multiple isolates from the same patient were included from either different species or the same species with different carbapenemase genes. The data were analysed using an in-house bioinformatics pipeline that determines species identification, multi-locus sequence typing (MLST) profile and antimicrobial resistance gene content.Results. A total of 2658 non-duplicate CPE were sequenced amongst which three host organisms belonging to diverse sequence types (STs) predominated: Klebsiella pneumoniae (1380/2658, 51.9 %; 177 STs), Escherichia coli (723/2658, 27.2 %; 133 STs) and Enterobacter cloacae (294/2658, 11.1 %; 88 STs). Thirty different carbapenemase gene variants were identified, although bla OXA-48-like (1122/2658, 42.2%), bla NDM (692/2658, 26.0 %), bla KPC (571/2658, 21.5 %), bla VIM (100/2658, 3.8 %) and bla IMP (33/2658, 1.2 %) predominated. ST/carbapenemase gene pairings represented widely distributed high-risk clones or clusters at a regional or hospital level.Conclusion. CPE referred to the national reference laboratory are diverse, suggesting multiple introductions to England and a role for horizontal transfer of carbapenemase genes in English CPE epidemiology.

The promiscuous and highly mobile resistome of Acinetobacter baumannii.

Antimicrobial resistance (AR) is a major global threat to public health. Understanding the population dynamics of AR is critical to restrain and control this issue. However, no study has provided a global picture of the whole resistome of Acinetobacter baumannii , a very important nosocomial pathogen. Here we analyse 1450+ genomes (covering >40 countries and >4 decades) to infer the global population dynamics of the resistome of this species. We show that gene flow and horizontal transfer have driven the dissemination of AR genes in A. baumannii . We found considerable variation in AR gene content across lineages. Although the individual AR gene histories have been affected by recombination, the AR gene content has been shaped by the phylogeny. Furthermore, many AR genes have been transferred to other well-known pathogens, such as Pseudomonas aeruginosa or Klebsiella pneumoniae . Despite using this massive data set, we were not able to sample the whole diversity of AR genes, which suggests that this species has an open resistome. Our results highlight the high mobilization risk of AR genes between important pathogens. On a broader perspective, this study gives a framework for an emerging perspective (resistome-centric) on the genomic epidemiology (and surveillance) of bacterial pathogens.

AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence

Antimicrobial resistance (AMR) is a significant public health threat. With the rise of affordable whole genome sequencing, in silico approaches to assessing AMR gene content can be used to detect known resistance mechanisms and potentially identify novel mechanisms. To enable accurate assessment of AMR gene content, as part of a multi-agency collaboration, NCBI developed a comprehensive AMR gene database, the Bacterial Antimicrobial Resistance Reference Gene Database and the AMR gene detection tool AMRFinder. Here, we describe the expansion of the Reference Gene Database, now called the Reference Gene Catalog, to include putative acid, biocide, metal, stress resistance genes, in addition to virulence genes and species-specific point mutations. Genes and point mutations are classified by broad functions, as well as more detailed functions. As we have expanded both the functional repertoire of identified genes and functionality, NCBI released a new version of AMRFinder, known as AMRFinderPlus. This new tool allows users the option to utilize only the core set of AMR elements, or include stress response and virulence genes, too. AMRFinderPlus can detect acquired genes and point mutations in both protein and nucleotide sequence. In addition, the evidence used to identify the gene has been expanded to include whether nucleotide or protein sequence was used, its location in the contig, and presence of an internal stop codon. These database improvements and functional expansions will enable increased precision in identifying AMR genes, linking AMR genotypes and phenotypes, and determining possible relationships between AMR, virulence, and stress response.

Plasmids shape the diverse accessory resistomes of Escherichia coli ST131.

The human gut microbiome includes beneficial, commensal and pathogenic bacteria that possess antimicrobial resistance (AMR) genes and exchange these predominantly through conjugative plasmids. Escherichia coli is a significant component of the gastrointestinal microbiome and is typically non-pathogenic in this niche. In contrast, extra-intestinal pathogenic E. coli (ExPEC) including ST131 may occupy other environments like the urinary tract or bloodstream where they express genes enabling AMR and host cell adhesion like type 1 fimbriae. The extent to which commensal E. coli and uropathogenic ExPEC ST131 share AMR genes remains understudied at a genomic level, and we examined this here using a preterm infant resistome. We found that individual ST131 had small differences in AMR gene content relative to a larger shared resistome. Comparisons with a range of plasmids common in ST131 showed that AMR gene composition was driven by conjugation, recombination and mobile genetic elements. Plasmid pEK499 had extended regions in most ST131 Clade C isolates, and it had evidence of a co-evolutionary signal based on protein-level interactions with chromosomal gene products, as did pEK204 that had a type IV fimbrial pil operon. ST131 possessed extensive diversity of selective type 1, type IV, P and F17-like fimbriae genes that was highest in subclade C2. The structure and composition of AMR genes, plasmids and fimbriae vary widely in ST131 Clade C and this may mediate pathogenicity and infection outcomes.

Pathogenic Escherichia coli Possess Elevated Growth Rates under Exposure to Sub-Inhibitory Concentrations of Azithromycin.

Antimicrobial resistance (AMR) has been identified by the World Health Organization (WHO) as one of the ten major threats to global health. Advances in technology, including whole-genome sequencing, have provided new insights into the origin and mechanisms of AMR. However, our understanding of the short-term impact of antimicrobial pressure and resistance on the physiology of bacterial populations is limited. We aimed to investigate morphological and physiological responses of clinical isolates of E. coli under short-term exposure to key antimicrobials. We performed whole-genome sequencing on twenty-seven E. coli isolates isolated from children with sepsis to evaluate their AMR gene content. We assessed their antimicrobial susceptibility profile and measured their growth dynamics and morphological characteristics under exposure to varying concentrations of ciprofloxacin, ceftriaxone, tetracycline, gentamicin, and azithromycin. AMR was common, with all organisms resistant to at least one antimicrobial; a total of 81.5% were multi-drug-resistant (MDR). We observed an association between resistance profile and morphological characteristics of the E. coli over a three-hour exposure to antimicrobials. Growth dynamics experiments demonstrated that resistance to tetracycline promoted the growth of E. coli under antimicrobial-free conditions, while resistance to the other antimicrobials incurred a fitness cost. Notably, antimicrobial exposure heterogeneously suppressed bacterial growth, but sub-MIC concentrations of azithromycin increased the maximum growth rate of the clinical isolates. Our results outline complex interactions between organism and antimicrobials and raise clinical concerns regarding exposure of sub-MIC concentrations of specific antimicrobials.

Mortality in Escherichia coli bloodstream infections: antibiotic resistance still does not make it.

Escherichia coli bloodstream infections (BSIs) account for high mortality rates (5%-30%). Determinants of death are unclear, especially since the emergence of ESBL producers. To determine the relative weight of host characteristics, bacterial virulence and antibiotic resistance in the outcome of patients suffering from E. coli BSI. All consecutive patients suffering from E. coli BSI in seven teaching hospitals around Paris were prospectively included for 10 months. E. coli isolates were sequenced using Illumina NextSeq technology to determine the phylogroup, ST/ST complex (STc), virulence and antimicrobial resistance gene content. Risk factors associated with death at discharge or Day 28 were determined. Overall, 545 patients (mean ± SD age 68.5 ± 16.5 years; 52.5% male) were included. Mean Charlson comorbidity index (CCI) was 5.6 (± 3.1); 19.6% and 12.8% presented with sepsis and septic shock, respectively. Portals of entry were mainly urinary (51.9%), digestive (41.9%) and pulmonary (3.5%); 98/545 isolates (18%) were third-generation cephalosporin resistant (3GC-R), including 86 ESBL producers. In-hospital death (or at Day 28) was 52/545 (9.5%). Factors independently associated with death were a pulmonary portal of entry [adjusted OR (aOR) 6.54, 95% CI 2.23-19.2, P = 0.0006], the iha_17 virulence gene (aOR 4.41, 95% CI 1.23-15.74, P = 0.022), the STc88 (aOR 3.62, 95% CI 1.30-10.09, P = 0.014), healthcare-associated infections (aOR 1.98, 95% CI 1.04-3.76, P = 0.036) and high CCI (aOR 1.14, 95% CI 1.04-1.26, P = 0.006), but not ESBL/3GC-R. Host factors, portal of entry and bacterial characteristics remain major determinants associated with mortality in E. coli BSIs. Despite a high prevalence of ESBL producers, antibiotic resistance did not impact mortality. (ClinicalTrials.gov identifier: NCT02890901.).

The impact of sequencing depth on the inferred taxonomic composition and AMR gene content of metagenomic samples

BackgroundShotgun metagenomics is increasingly used to characterise microbial communities, particularly for the investigation of antimicrobial resistance (AMR) in different animal and environmental contexts. There are many different approaches for inferring the taxonomic composition and AMR gene content of complex community samples from shotgun metagenomic data, but there has been little work establishing the optimum sequencing depth, data processing and analysis methods for these samples. In this study we used shotgun metagenomics and sequencing of cultured isolates from the same samples to address these issues. We sampled three potential environmental AMR gene reservoirs (pig caeca, river sediment, effluent) and sequenced samples with shotgun metagenomics at high depth (~ 200 million reads per sample). Alongside this, we cultured single-colony isolates of Enterobacteriaceae from the same samples and used hybrid sequencing (short- and long-reads) to create high-quality assemblies for comparison to the metagenomic data. To automate data processing, we developed an open-source software pipeline, ‘ResPipe’.ResultsTaxonomic profiling was much more stable to sequencing depth than AMR gene content. 1 million reads per sample was sufficient to achieve < 1% dissimilarity to the full taxonomic composition. However, at least 80 million reads per sample were required to recover the full richness of different AMR gene families present in the sample, and additional allelic diversity of AMR genes was still being discovered in effluent at 200 million reads per sample. Normalising the number of reads mapping to AMR genes using gene length and an exogenous spike of Thermus thermophilus DNA substantially changed the estimated gene abundance distributions. While the majority of genomic content from cultured isolates from effluent was recoverable using shotgun metagenomics, this was not the case for pig caeca or river sediment.ConclusionsSequencing depth and profiling method can critically affect the profiling of polymicrobial animal and environmental samples with shotgun metagenomics. Both sequencing of cultured isolates and shotgun metagenomics can recover substantial diversity that is not identified using the other methods. Particular consideration is required when inferring AMR gene content or presence by mapping metagenomic reads to a database. ResPipe, the open-source software pipeline we have developed, is freely available (https://gitlab.com/hsgweon/ResPipe).

Use of online tools for antimicrobial resistance prediction by whole-genome sequencing in methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE).

The antimicrobial resistance (AMR) crisis represents a serious threat to public health and has resulted in concentrated efforts to accelerate development of rapid molecular diagnostics for AMR. In combination with publicly available web-based AMR databases, whole-genome sequencing (WGS) offers the capacity for rapid detection of AMR genes. Here we studied the concordance between WGS-based resistance prediction and phenotypic susceptibility test results for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin-resistant enterococci (VRE) clinical isolates using publicly available tools and databases. Clinical isolates prospectively collected at the University of Pittsburgh Medical Center between December 2016 and December 2017 underwent WGS. The AMR gene content was assessed from assembled genomes by BLASTn search of online databases. Concordance between the WGS-predicted resistance profile and phenotypic susceptibility as well as the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated for each antibiotic/organism combination, using the phenotypic results as gold standard. Phenotypic susceptibility testing and WGS results were available for 1242 isolate/antibiotic combinations. Overall concordance was 99.3%, with a sensitivity, specificity, PPV and NPV of 98.7% (95% CI 97.2-99.5%), 99.6% (95% CI 98.8-99.9%), 99.3% (95% CI 98.0-99.8%) and 99.2% (95% CI 98.3-99.7%), respectively. Additional identification of point mutations in housekeeping genes increased the concordance to 99.4%, sensitivity to 99.3% (95% CI 98.2-99.8%) and NPV to 99.4% (95% CI 98.4-99.8%). WGS can be used as a reliable predicator of phenotypic resistance both for MRSA and VRE using readily available online tools.

Using Machine Learning To Predict Antimicrobial MICs and Associated Genomic Features for Nontyphoidal Salmonella.

Nontyphoidal Salmonella species are the leading bacterial cause of foodborne disease in the United States. Whole-genome sequences and paired antimicrobial susceptibility data are available for Salmonella strains because of surveillance efforts from public health agencies. In this study, a collection of 5,278 nontyphoidal Salmonella genomes, collected over 15 years in the United States, was used to generate extreme gradient boosting (XGBoost)-based machine learning models for predicting MICs for 15 antibiotics. The MIC prediction models had an overall average accuracy of 95% within ±1 2-fold dilution step (confidence interval, 95% to 95%), an average very major error rate of 2.7% (confidence interval, 2.4% to 3.0%), and an average major error rate of 0.1% (confidence interval, 0.1% to 0.2%). The model predicted MICs with no a priori information about the underlying gene content or resistance phenotypes of the strains. By selecting diverse genomes for the training sets, we show that highly accurate MIC prediction models can be generated with less than 500 genomes. We also show that our approach for predicting MICs is stable over time, despite annual fluctuations in antimicrobial resistance gene content in the sampled genomes. Finally, using feature selection, we explore the important genomic regions identified by the models for predicting MICs. To date, this is one of the largest MIC modeling studies to be published. Our strategy for developing whole-genome sequence-based models for surveillance and clinical diagnostics can be readily applied to other important human pathogens.

Clinical features, antimicrobial susceptibility patterns and genomics of bacteria causing neonatal sepsis in a children’s hospital in Vietnam: protocol for a prospective observational study

IntroductionThe clinical syndrome of neonatal sepsis, comprising signs of infection, septic shock and organ dysfunction in infants ≤4 weeks of age, is a frequent sequel to bloodstream infection and mandates...

Virulence Characterisation of Salmonella enterica Isolates of Differing Antimicrobial Resistance Recovered from UK Livestock and Imported Meat Samples.

Salmonella enterica is a foodborne zoonotic pathogen of significant public health concern. We have characterized the virulence and antimicrobial resistance gene content of 95 Salmonella isolates from 11 serovars by DNA microarray recovered from UK livestock or imported meat. Genes encoding resistance to sulphonamides (sul1, sul2), tetracycline [tet(A), tet(B)], streptomycin (strA, strB), aminoglycoside (aadA1, aadA2), beta-lactam (blaTEM), and trimethoprim (dfrA17) were common. Virulence gene content differed between serovars; S. Typhimurium formed two subclades based on virulence plasmid presence. Thirteen isolates were selected by their virulence profile for pathotyping using the Galleria mellonella pathogenesis model. Infection with a chicken invasive S. Enteritidis or S. Gallinarum isolate, a multidrug resistant S. Kentucky, or a S. Typhimurium DT104 isolate resulted in high mortality of the larvae; notably presence of the virulence plasmid in S. Typhimurium was not associated with increased larvae mortality. Histopathological examination showed that infection caused severe damage to the Galleria gut structure. Enumeration of intracellular bacteria in the larvae 24 h post-infection showed increases of up to 7 log above the initial inoculum and transmission electron microscopy (TEM) showed bacterial replication in the haemolymph. TEM also revealed the presence of vacuoles containing bacteria in the haemocytes, similar to Salmonella containing vacuoles observed in mammalian macrophages; although there was no evidence from our work of bacterial replication within vacuoles. This work shows that microarrays can be used for rapid virulence genotyping of S. enterica and that the Galleria animal model replicates some aspects of Salmonella infection in mammals. These procedures can be used to help inform on the pathogenicity of isolates that may be antibiotic resistant and have scope to aid the assessment of their potential public and animal health risk.

Diversity of Plasmids and Antimicrobial Resistance Genes in Multidrug-Resistant Escherichia coli Isolated from Healthy Companion Animals.

The presence and transfer of antimicrobial resistance genes from commensal bacteria in companion animals to more pathogenic bacteria may contribute to dissemination of antimicrobial resistance. The purpose of this study was to determine antimicrobial resistance gene content and the presence of genetic elements in antimicrobial resistant Escherichia coli from healthy companion animals. In our previous study, from May to August, 2007, healthy companion animals (155 dogs and 121 cats) from three veterinary clinics in the Athens, GA, USA area were sampled and multidrug-resistant E. coli (n = 36; MDR, resistance to ≥ 2 antimicrobial classes) were obtained. Of the 25 different plasmid replicon types tested by PCR, at least one plasmid replicon type was detected in 94% (34/36) of the MDR E. coli; four isolates contained as many as five different plasmid replicons. Nine replicon types (FIA, FIB, FII, I2, A/C, U, P, I1 and HI2) were identified with FIB, FII, I2 as the most common pattern. The presence of class I integrons (intI) was detected in 61% (22/36) of the isolates with eight isolates containing aminoglycoside- and/or trimethoprim-resistance genes in the variable cassette region of intI. Microarray analysis of a subset of the MDR E. coli (n = 9) identified the presence of genes conferring resistance to aminoglycosides (aac, aad, aph and strA/B), β-lactams (ampC, cmy, tem and vim), chloramphenicol (cat), sulfonamides (sulI and sulII), tetracycline [tet(A), tet(B), tet(C), tet(D) and regulator, tetR] and trimethoprim (dfrA). Antimicrobial resistance to eight antimicrobials (ampicillin, cefoxitin, ceftiofur, amoxicillin/clavulanic acid, streptomycin, gentamicin, sulfisoxazole and trimethoprim-sulfamethoxazole) and five plasmid replicons (FIA, FIB, FII, I1 and I2) were transferred via conjugation. The presence of antimicrobial resistance genes, intI and transferable plasmid replicons indicate that E. coli from companion animals may play an important role in the dissemination of antimicrobial resistance, particularly to human hosts during contact.