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      Two carbapenem-resistant ST1:ST231:KL1:OCL1 Acinetobacter baumannii strains recovered in Tehran, Iran, carry AbaR31 in the chromosome and AbaR4 and Tn aphA6 in a RepAci6 plasmid

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          Abstract

          Objectives

          To analyse the context of genes conferring antibiotic resistance in two carbapenem-resistant Acinetobacter baumannii isolates recovered in Tehran, Iran.

          Methods

          The antibiotic resistance phenotype for 28 antibiotics was determined using disc diffusion. The whole genome sequences of ABH008 and ABS200 were determined using the Illumina HiSeq X Ten platform. Resistance genes were identified using ResFinder and multilocus sequence types were determined using the Oxford and Institut Pasteur schemes.

          Results

          Isolates ABH008 and ABS200, recovered in 2012 and 2013, respectively, in two different Tehran hospitals, belong to the common global clone 1 lineage, ST1 IP and ST231 OX. They are resistant to sulfamethoxazole, tetracycline, gentamicin, amikacin, third-generation cephalosporins and carbapenems. Despite being isolated in different hospitals, phylogenetic analysis indicated they are closely related. Consistent with this, both isolates carry catA1, sul1, aacC1 and aadA1 in a novel variant of the AbaR3-type resistance island, named AbaR31. Both isolates are resistant to amikacin and carbapenems owing to aphA6 and oxa23, respectively. The oxa23 gene is located in the AbaR4 resistance island, and aphA6 in Tn aphA6, and both mobile elements are in an ∼90 kbp plasmid encoding the putative RepAci6 replication initiation protein. Resistance to third-generation cephalosporins is due to the acquisition by homologous recombination of a 5 kb DNA segment that contains ISAba1- ampC from a ST623 strain.

          Conclusions

          The resistance gene complements of ABH008 and ABS200 were found in AbaR31 and a plasmid that encodes RepAci6. The close genetic relationship of ABH008 and ABS200, despite each being recovered from different hospitals, indicates transmission between the two hospitals.

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          Most cited references26

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          Multidrug-resistant, extensively drug-resistant and pandrug-resistant bacteria: an international expert proposal for interim standard definitions for acquired resistance.

          Many different definitions for multidrug-resistant (MDR), extensively drug-resistant (XDR) and pandrug-resistant (PDR) bacteria are being used in the medical literature to characterize the different patterns of resistance found in healthcare-associated, antimicrobial-resistant bacteria. A group of international experts came together through a joint initiative by the European Centre for Disease Prevention and Control (ECDC) and the Centers for Disease Control and Prevention (CDC), to create a standardized international terminology with which to describe acquired resistance profiles in Staphylococcus aureus, Enterococcus spp., Enterobacteriaceae (other than Salmonella and Shigella), Pseudomonas aeruginosa and Acinetobacter spp., all bacteria often responsible for healthcare-associated infections and prone to multidrug resistance. Epidemiologically significant antimicrobial categories were constructed for each bacterium. Lists of antimicrobial categories proposed for antimicrobial susceptibility testing were created using documents and breakpoints from the Clinical Laboratory Standards Institute (CLSI), the European Committee on Antimicrobial Susceptibility Testing (EUCAST) and the United States Food and Drug Administration (FDA). MDR was defined as acquired non-susceptibility to at least one agent in three or more antimicrobial categories, XDR was defined as non-susceptibility to at least one agent in all but two or fewer antimicrobial categories (i.e. bacterial isolates remain susceptible to only one or two categories) and PDR was defined as non-susceptibility to all agents in all antimicrobial categories. To ensure correct application of these definitions, bacterial isolates should be tested against all or nearly all of the antimicrobial agents within the antimicrobial categories and selective reporting and suppression of results should be avoided. © 2011 European Society of Clinical Microbiology and Infectious Diseases. No claim to original US government works.
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            NCBI prokaryotic genome annotation pipeline

            Recent technological advances have opened unprecedented opportunities for large-scale sequencing and analysis of populations of pathogenic species in disease outbreaks, as well as for large-scale diversity studies aimed at expanding our knowledge across the whole domain of prokaryotes. To meet the challenge of timely interpretation of structure, function and meaning of this vast genetic information, a comprehensive approach to automatic genome annotation is critically needed. In collaboration with Georgia Tech, NCBI has developed a new approach to genome annotation that combines alignment based methods with methods of predicting protein-coding and RNA genes and other functional elements directly from sequence. A new gene finding tool, GeneMarkS+, uses the combined evidence of protein and RNA placement by homology as an initial map of annotation to generate and modify ab initio gene predictions across the whole genome. Thus, the new NCBI's Prokaryotic Genome Annotation Pipeline (PGAP) relies more on sequence similarity when confident comparative data are available, while it relies more on statistical predictions in the absence of external evidence. The pipeline provides a framework for generation and analysis of annotation on the full breadth of prokaryotic taxonomy. For additional information on PGAP see https://www.ncbi.nlm.nih.gov/genome/annotation_prok/ and the NCBI Handbook, https://www.ncbi.nlm.nih.gov/books/NBK174280/.
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              Is Open Access

              Rapid phylogenetic analysis of large samples of recombinant bacterial whole genome sequences using Gubbins

              The emergence of new sequencing technologies has facilitated the use of bacterial whole genome alignments for evolutionary studies and outbreak analyses. These datasets, of increasing size, often include examples of multiple different mechanisms of horizontal sequence transfer resulting in substantial alterations to prokaryotic chromosomes. The impact of these processes demands rapid and flexible approaches able to account for recombination when reconstructing isolates’ recent diversification. Gubbins is an iterative algorithm that uses spatial scanning statistics to identify loci containing elevated densities of base substitutions suggestive of horizontal sequence transfer while concurrently constructing a maximum likelihood phylogeny based on the putative point mutations outside these regions of high sequence diversity. Simulations demonstrate the algorithm generates highly accurate reconstructions under realistically parameterized models of bacterial evolution, and achieves convergence in only a few hours on alignments of hundreds of bacterial genome sequences. Gubbins is appropriate for reconstructing the recent evolutionary history of a variety of haploid genotype alignments, as it makes no assumptions about the underlying mechanism of recombination. The software is freely available for download at github.com/sanger-pathogens/Gubbins, implemented in Python and C and supported on Linux and Mac OS X.
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                Author and article information

                Journal
                JAC Antimicrob Resist
                JAC Antimicrob Resist
                jacamr
                JAC-Antimicrobial Resistance
                Oxford University Press
                2632-1823
                September 2021
                07 August 2021
                07 August 2021
                : 3
                : 3
                : dlab112
                Affiliations
                [1 ] Division of Microbiology, Department of Pathobiology, School of Public Health, Tehran University of Medical Sciences , Tehran, Iran
                [2 ] The iThree institute, University of Technology Sydney , Ultimo, NSW, Australia
                Author notes
                Author information
                https://orcid.org/0000-0002-3614-7261
                Article
                dlab112
                10.1093/jacamr/dlab112
                8346695
                34377981
                e82efbc2-f047-4107-9157-e7fb65df73c4
                © The Author(s) 2021. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 15 March 2021
                : 06 July 2021
                Page count
                Pages: 5
                Funding
                Funded by: Australian Research Council (ARC) DECRA fellowship;
                Award ID: DE200100111
                Funded by: Tehran University of Medical Sciences, DOI 10.13039/501100004484;
                Award ID: 41448
                Funded by: Academy of Science for Developing World (TWAS);
                Award ID: 11-119 RG/PHA/AS_C-UNESCO FR:3240262646
                Categories
                Brief Report
                AcademicSubjects/MED00740
                AcademicSubjects/MED00290
                AcademicSubjects/MED00230

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