skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Top-Down Genomic Surveillance Approach To Investigate the Genomic Epidemiology and Antibiotic Resistance Patterns of Enterococcus faecium Detected in Cancer Patients in Arkansas
Control of hospital-associated Enterococcus faecium infection is a strenuous task due to the difficulty of identifying transmission routes and the persistence of this nosocomial pathogen despite the implementation of infection control measures that have been successful with other important nosocomial pathogens. This study provides a comprehensive analysis of over 100 E. faecium isolates collected from 66 cancer patients at the University of Arkansas for Medical Sciences (UAMS) between June 2018 and May 2019. In the top-down approach used in this study, we employed, in addition to the 106 E. faecium UAMS isolates, a filtered set of 2,167 E. faecium strains from the GenBank database to assess the current population structure of E. faecium species and, consequently, to identify the lineages associated with our clinical isolates. We then evaluated the antibiotic resistance and virulence profiles of hospital-associated strains from the species pool, focusing on antibiotics of last resort, to establish an updated classification of high-risk and multidrug-resistant nosocomial clones. Further investigation of the clinical isolates collected from UAMS patients using whole-genome sequencing analytical methodologies (core genome multilocus sequence typing [cgMLST], core single nucleotide polymorphism [coreSNP] analysis, and phylogenomics), with the addition of patient epidemiological data, revealed a polyclonal outbreak of three sequence types occurring simultaneously in different patient wards. The integration of genomic and epidemiological data collected from the patients increased our understanding of the relationships and transmission dynamics of the E. faecium isolates. Our study provides new insights into genomic surveillance of E. faecium to assist in monitoring and further limiting the spread of multidrug-resistant E. faecium.  more » « less
Award ID(s):
1946391
PAR ID:
10498146
Author(s) / Creator(s):
Date Published:
Journal Name:
Microbiology spectrum
ISSN:
2165-0497
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. null (Ed.)
    Abstract Background VREfm is a major cause of Hospital Acquired Infection in the United States. We analyzed all the VREfm infections that occurred in our institution between 2018 and 2019 using Whole Genome Sequencing (WGS) to understand epidemiological relationship between previously unidentified clusters. In this study we describe a cluster in our hematology oncology unit. Methods A total of 109 discrete VREfm isolates from 66 patients were analyzed. VREfm isolates used in this study were identified from positive blood and urine cultures. Genomic deoxyribonucleic acid (DNA) was extracted from pure cultures. The purity and integrity of extracted DNA were determined using appropriate assays. Library construction and sequencing were conducted and Multi Locust Sequence Typing (MLST) obtained (image 1). Phylogenomic tree was plotted using the Interactive Tree of Life (image 2). Image 1 - methods Image 2 - Tree of Life Results Total of 7 clusters were identified. Here we describe one cluster (image 3) with the highest genetic similarity which showed maximum difference of 5 Single Nucleotide Polymorphisms (zero between patient 1 and 2, image 4). The cluster is composed of 24 clinical strains of VREfm from 6 patients, over a 9 month time period (Image 5). All patients had hematologic malignancies; 4/6 patients had received recent chemotherapy and 5/6 patients were neutropenic. 4 patients were admitted in a single unit (labelled E7), 1 patient was on a sister unit (labelled F7); and 1 patient was in the cancer infusion center. All patients had central venous access placed by radiology at the time of diagnosis of infection and had visited our outpatient infusion center multiple times during this time frame. Image 3 - Close look at cluster 1 Image 4 - Dendrogram of 106 isolates performed with coreSNP(Single Nucleotide Polymorphisms) pairwise distances. • Dendogram shows different patients (same color for isolates that belong to the same patient) and the patient numbers. • Besides the patient number, the number of largest number SNPS that separate those isolates is shown. • Branches represent the number of coreSNPs that differ strains from that branch. As you see isolates from cluster 1 differ in a maximum of 5 SNPs but isolates of patient 1 and patient 2 differ in 0 SNPs between them. Cluster 1 is represented by a green square. Image 5 - Time period of infections Conclusion The prolonged period in our cluster argues in favor of an environmental niche in the hospital unit. We are unable to elucidate pattern of transmission in a cluster of infections without knowing patient colonization of VREfm; because we are likely looking at the tip of the iceberg when analyzing infected cases. It is difficult to ascribe causality to any one of these exposures without concomitant surveillance cultures of environment and personnel. Retrospective WGS is of limited value in infection control. We now have third generation sequencing with the MinION device to do real time sequencing with which we also validated some of our samples. Disclosures Atul Kothari, MD, Ansun Biopharma (Consultant) 
    more » « less
  2. Abstract Objective:Whole genome sequencing (WGS) can help identify transmission of pathogens causing healthcare-associated infections (HAIs). However, the current gold standard of short-read, Illumina-based WGS is labor and time intensive. Given recent improvements in long-read Oxford Nanopore Technologies (ONT) sequencing, we sought to establish a low resource approach providing accurate WGS-pathogen comparison within a time frame allowing for infection prevention and control (IPC) interventions. Methods:WGS was prospectively performed on pathogens at increased risk of potential healthcare transmission using the ONT MinION sequencer with R10.4.1 flow cells and Dorado basecaller. Potential transmission was assessed via Ridom SeqSphere+ for core genome multilocus sequence typing and MINTyper for reference-based core genome single nucleotide polymorphisms using previously published cutoff values. The accuracy of our ONT pipeline was determined relative to Illumina. Results:Over a six-month period, 242 bacterial isolates from 216 patients were sequenced by a single operator. Compared to the Illumina gold standard, our ONT pipeline achieved a mean identity score of Q60 for assembled genomes, even with a coverage rate as low as 40×. The mean time from initiating DNA extraction to complete analysis was 2 days (IQR 2–3.25 days). We identified five potential transmission clusters comprising 21 isolates (8.7% of sequenced strains). Integrating ONT with epidemiological data, >70% (15/21) of putative transmission cluster isolates originated from patients with potential healthcare transmission links. Conclusions:Via a stand-alone ONT pipeline, we detected potentially transmitted HAI pathogens rapidly and accurately, aligning closely with epidemiological data. Our low-resource method has the potential to assist in IPC efforts. 
    more » « less
  3. BackgroundAntimicrobial resistance is a growing concern in canineStaphylococcus pseudintermediusdermatitis. Treatment with rifampicin (RFP) is considered only in meticillin‐resistant and multidrug‐resistantS. pseudintermedius(MDR‐MRSP). Hypothesis/ObjectivesTo determine an optimal RFP dosing for MDR‐MRSP treatment without induction of RFP resistance and identify causal mutations for antimicrobial resistance. Methods and materialsTime–kill assays were performed in a control isolate and three MDR‐MRSP isolates at six clinically relevant concentrations [32 to 1,024 × MIC (the minimum inhibitory concentration)]. Whole‐genome resequencing and bioinformatic analysis were performed in the resistant strains developed in this assay. ResultsThe genomic analysis identified nine antimicrobial resistance genes (ARGs) in MDR‐MRSP isolates, which are responsible for resistance to seven classes of antibiotics. RFP activity against all four isolates was consistent with a time‐dependent and bacteriostatic response. RFP resistance was observed in six of the 28 time–kill assays, including concentrations 64 × MIC in MDR‐MRSP1 isolates at 24 h, 32 × MIC in MDR‐MRSP2 at 48 h, 32 × MIC in MDR‐MRSP3 at 48 h and 256 × MIC in MDR‐MRSP3 at 24 h. Genome‐wide mutation analyses in these RFP‐resistant strains discovered the causal mutations in the coding region of therpoBgene. Conclusions and clinical relevanceA study has shown that 6 mg/kg per os results in plasma concentrations of 600–1,000 × MIC ofS. pseudintermedius. Based on our data, this dose should achieve the minimum MIC (×512) to prevent RFP resistance development; therefore, we recommend a minimum daily dose of 6 mg/kg for MDR‐MRSP pyoderma treatment when limited antibiotic options are available. 
    more » « less
  4. Health care–associated infections due to multidrug-resistant organisms (MDROs), such as methicillin-resistant Staphylococcus aureus (MRSA) and Clostridioides difficile (CDI), place a significant burden on our health care infrastructure. Screening for MDROs is an important mechanism for preventing spread but is resource intensive. The objective of this study was to develop automated tools that can predict colonization or infection risk using electronic health record (EHR) data, provide useful information to aid infection control, and guide empiric antibiotic coverage. We retrospectively developed a machine learning model to detect MRSA colonization and infection in undifferentiated patients at the time of sample collection from hospitalized patients at the University of Virginia Hospital. We used clinical and nonclinical features derived from on-admission and throughout-stay information from the patient’s EHR data to build the model. In addition, we used a class of features derived from contact networks in EHR data; these network features can capture patients’ contacts with providers and other patients, improving model interpretability and accuracy for predicting the outcome of surveillance tests for MRSA. Finally, we explored heterogeneous models for different patient subpopulations, for example, those admitted to an intensive care unit or emergency department or those with specific testing histories, which perform better. We found that the penalized logistic regression performs better than other methods, and this model’s performance measured in terms of its receiver operating characteristics-area under the curve score improves by nearly 11% when we use polynomial (second-degree) transformation of the features. Some significant features in predicting MDRO risk include antibiotic use, surgery, use of devices, dialysis, patient’s comorbidity conditions, and network features. Among these, network features add the most value and improve the model’s performance by at least 15%. The penalized logistic regression model with the same transformation of features also performs better than other models for specific patient subpopulations. Our study shows that MRSA risk prediction can be conducted quite effectively by machine learning methods using clinical and nonclinical features derived from EHR data. Network features are the most predictive and provide significant improvement over prior methods. Furthermore, heterogeneous prediction models for different patient subpopulations enhance the model’s performance. 
    more » « less
  5. Insertion sequences (ISs) and other transposable elements are associated with the mobilization of antibiotic resistance determinants and the modulation of pathogenic characteristics. In this work, we aimed to investigate the association between ISs and antibiotic resistance genes, and their role in the dissemination and modification of the antibiotic-resistant phenotype. To that end, we leveraged fully resolved Enterococcus faecium and Enterococcus faecalis genomes of isolates collected over 5 days from an inpatient with prolonged bacteraemia. Isolates from both species harboured similar IS family content but showed significant species-dependent differences in copy number and arrangements of ISs throughout their replicons. Here, we describe two inter-specific IS-mediated recombination events and IS-mediated excision events in plasmids of E. faecium isolates. We also characterize a novel arrangement of the ISs in a Tn1546-like transposon in E. faecalis isolates likely implicated in a vancomycin genotype–phenotype discrepancy. Furthermore, an extended analysis revealed a novel association between daptomycin resistance mutations in liaSR genes and a putative composite transposon in E. faecium , offering a new paradigm for the study of daptomycin resistance and novel insights into its dissemination. In conclusion, our study highlights the role ISs and other transposable elements play in the rapid adaptation and response to clinically relevant stresses such as aggressive antibiotic treatment in enterococci. 
    more » « less