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      Dogs Leaving the ICU Carry a Very Large Multi-Drug Resistant Enterococcal Population with Capacity for Biofilm Formation and Horizontal Gene Transfer

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      PLoS ONE
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          Abstract

          The enterococcal community from feces of seven dogs treated with antibiotics for 2–9 days in the veterinary intensive care unit (ICU) was characterized. Both, culture-based approach and culture-independent 16S rDNA amplicon 454 pyrosequencing, revealed an abnormally large enterococcal community: 1.4±0.8×10 8 CFU gram −1 of feces and 48.9±11.5% of the total 16,228 sequences, respectively. The diversity of the overall microbial community was very low which likely reflects a high selective antibiotic pressure. The enterococcal diversity based on 210 isolates was also low as represented by Enterococcus faecium (54.6%) and Enterococcus faecalis (45.4%). E. faecium was frequently resistant to enrofloxacin (97.3%), ampicillin (96.5%), tetracycline (84.1%), doxycycline (60.2%), erythromycin (53.1%), gentamicin (48.7%), streptomycin (42.5%), and nitrofurantoin (26.5%). In E. faecalis, resistance was common to tetracycline (59.6%), erythromycin (56.4%), doxycycline (53.2%), and enrofloxacin (31.9%). No resistance was detected to vancomycin, tigecycline, linezolid, and quinupristin/dalfopristin in either species. Many isolates carried virulence traits including gelatinase, aggregation substance, cytolysin, and enterococcal surface protein. All E. faecalis strains were biofilm formers in vitro and this phenotype correlated with the presence of gelE and/or esp. In vitro intra-species conjugation assays demonstrated that E. faecium were capable of transferring tetracycline, doxycycline, streptomycin, gentamicin, and erythromycin resistance traits to human clinical strains. Multi-locus variable number tandem repeat analysis (MLVA) and pulsed-field gel electrophoresis (PFGE) of E. faecium strains showed very low genotypic diversity. Interestingly, three E. faecium clones were shared among four dogs suggesting their nosocomial origin. Furthermore, multi-locus sequence typing (MLST) of nine representative MLVA types revealed that six sequence types (STs) originating from five dogs were identical or closely related to STs of human clinical isolates and isolates from hospital outbreaks. It is recommended to restrict close physical contact between pets released from the ICU and their owners to avoid potential health risks.

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          eBURST: inferring patterns of evolutionary descent among clusters of related bacterial genotypes from multilocus sequence typing data.

          The introduction of multilocus sequence typing (MLST) for the precise characterization of isolates of bacterial pathogens has had a marked impact on both routine epidemiological surveillance and microbial population biology. In both fields, a key prerequisite for exploiting this resource is the ability to discern the relatedness and patterns of evolutionary descent among isolates with similar genotypes. Traditional clustering techniques, such as dendrograms, provide a very poor representation of recent evolutionary events, as they attempt to reconstruct relationships in the absence of a realistic model of the way in which bacterial clones emerge and diversify to form clonal complexes. An increasingly popular approach, called BURST, has been used as an alternative, but present implementations are unable to cope with very large data sets and offer crude graphical outputs. Here we present a new implementation of this algorithm, eBURST, which divides an MLST data set of any size into groups of related isolates and clonal complexes, predicts the founding (ancestral) genotype of each clonal complex, and computes the bootstrap support for the assignment. The most parsimonious patterns of descent of all isolates in each clonal complex from the predicted founder(s) are then displayed. The advantages of eBURST for exploring patterns of evolutionary descent are demonstrated with a number of examples, including the simple Spain(23F)-1 clonal complex of Streptococcus pneumoniae, "population snapshots" of the entire S. pneumoniae and Staphylococcus aureus MLST databases, and the more complicated clonal complexes observed for Campylobacter jejuni and Neisseria meningitidis.
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            NHSN annual update: antimicrobial-resistant pathogens associated with healthcare-associated infections: annual summary of data reported to the National Healthcare Safety Network at the Centers for Disease Control and Prevention, 2006-2007.

            To describe the frequency of selected antimicrobial resistance patterns among pathogens causing device-associated and procedure-associated healthcare-associated infections (HAIs) reported by hospitals in the National Healthcare Safety Network (NHSN). Data are included on HAIs (ie, central line-associated bloodstream infections, catheter-associated urinary tract infections, ventilator-associated pneumonia, and surgical site infections) reported to the Patient Safety Component of the NHSN between January 2006 and October 2007. The results of antimicrobial susceptibility testing of up to 3 pathogenic isolates per HAI by a hospital were evaluated to define antimicrobial-resistance in the pathogenic isolates. The pooled mean proportions of pathogenic isolates interpreted as resistant to selected antimicrobial agents were calculated by type of HAI and overall. The incidence rates of specific device-associated infections were calculated for selected antimicrobial-resistant pathogens according to type of patient care area; the variability in the reported rates is described. Overall, 463 hospitals reported 1 or more HAIs: 412 (89%) were general acute care hospitals, and 309 (67%) had 200-1,000 beds. There were 28,502 HAIs reported among 25,384 patients. The 10 most common pathogens (accounting for 84% of any HAIs) were coagulase-negative staphylococci (15%), Staphylococcus aureus (15%), Enterococcus species (12%), Candida species (11%), Escherichia coli (10%), Pseudomonas aeruginosa (8%), Klebsiella pneumoniae (6%), Enterobacter species (5%), Acinetobacter baumannii (3%), and Klebsiella oxytoca (2%). The pooled mean proportion of pathogenic isolates resistant to antimicrobial agents varied significantly across types of HAI for some pathogen-antimicrobial combinations. As many as 16% of all HAIs were associated with the following multidrug-resistant pathogens: methicillin-resistant S. aureus (8% of HAIs), vancomycin-resistant Enterococcus faecium (4%), carbapenem-resistant P. aeruginosa (2%), extended-spectrum cephalosporin-resistant K. pneumoniae (1%), extended-spectrum cephalosporin-resistant E. coli (0.5%), and carbapenem-resistant A. baumannii, K. pneumoniae, K. oxytoca, and E. coli (0.5%). Nationwide, the majority of units reported no HAIs due to these antimicrobial-resistant pathogens.
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              Genomics of Actinobacteria: tracing the evolutionary history of an ancient phylum.

              Actinobacteria constitute one of the largest phyla among bacteria and represent gram-positive bacteria with a high G+C content in their DNA. This bacterial group includes microorganisms exhibiting a wide spectrum of morphologies, from coccoid to fragmenting hyphal forms, as well as possessing highly variable physiological and metabolic properties. Furthermore, Actinobacteria members have adopted different lifestyles, and can be pathogens (e.g., Corynebacterium, Mycobacterium, Nocardia, Tropheryma, and Propionibacterium), soil inhabitants (Streptomyces), plant commensals (Leifsonia), or gastrointestinal commensals (Bifidobacterium). The divergence of Actinobacteria from other bacteria is ancient, making it impossible to identify the phylogenetically closest bacterial group to Actinobacteria. Genome sequence analysis has revolutionized every aspect of bacterial biology by enhancing the understanding of the genetics, physiology, and evolutionary development of bacteria. Various actinobacterial genomes have been sequenced, revealing a wide genomic heterogeneity probably as a reflection of their biodiversity. This review provides an account of the recent explosion of actinobacterial genomics data and an attempt to place this in a biological and evolutionary context.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                19 July 2011
                : 6
                : 7
                : e22451
                Affiliations
                [1 ]Department of Diagnostic Medicine and Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, Kansas, United States of America
                [2 ]Medical Biofilm Research Institute, Lubbock, Texas, United States of America
                [3 ]Department of Entomology, Kansas State University, Manhattan, Kansas, United States of America
                University of Birmingham, United Kingdom
                Author notes

                Conceived and designed the experiments: LZ. Performed the experiments: AG SED LZ. Analyzed the data: AG SED LZ. Contributed reagents/materials/analysis tools: LZ. Wrote the paper: AG LZ.

                Article
                PONE-D-11-03008
                10.1371/journal.pone.0022451
                3139645
                21811613
                9d632233-a86e-42f9-8567-209da37ebc01
                Ghosh et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 10 February 2011
                : 28 June 2011
                Page count
                Pages: 13
                Categories
                Research Article
                Biology
                Microbiology
                Bacterial Pathogens
                Gram Positive
                Bacteriology
                Microbial Ecology
                Medicine
                Epidemiology
                Infectious Disease Epidemiology
                Infectious Diseases
                Public Health
                Veterinary Science
                Veterinary Diseases
                Veterinary Bacteriology
                Zoonotic Diseases
                Veterinary Medicine
                Small Animal Care
                Veterinary Hospitals
                Veterinary Microbiology

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                Uncategorized

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