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      Emergence of Ceftazidime-Avibactam Resistance Due to Plasmid-Borne bla KPC-3 Mutations during Treatment of Carbapenem-Resistant Klebsiella pneumoniae Infections

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          ABSTRACT

          Ceftazidime-avibactam is a novel β-lactam/β-lactamase inhibitor with activity against carbapenem-resistant Enterobacteriaceae (CRE) that produce Klebsiella pneumoniae carbapenemase (KPC). We report the first cases of ceftazidime-avibactam resistance to develop during treatment of CRE infections and identify resistance mechanisms. Ceftazidime-avibactam-resistant K. pneumoniae emerged in three patients after ceftazidime-avibactam treatment for 10 to 19 days. Whole-genome sequencing (WGS) of longitudinal ceftazidime-avibactam-susceptible and -resistant K. pneumoniae isolates was used to identify potential resistance mechanisms. WGS identified mutations in plasmid-borne bla KPC-3 , which were not present in baseline isolates. bla KPC-3 mutations emerged independently in isolates of a novel sequence type 258 sublineage and resulted in variant KPC-3 enzymes. The mutations were validated as resistance determinants by measuring MICs of ceftazidime-avibactam and other agents following targeted gene disruption in K. pneumoniae , plasmid transfer, and bla KPC cloning into competent Escherichia coli . In rank order, the impact of KPC-3 variants on ceftazidime-avibactam MICs was as follows: D179Y/T243M double substitution > D179Y > V240G. Remarkably, mutations reduced meropenem MICs ≥4-fold from baseline, restoring susceptibility in K. pneumoniae from two patients. Cefepime and ceftriaxone MICs were also reduced ≥4-fold against D179Y/T243M and D179Y variant isolates, but susceptibility was not restored. Reverse transcription-PCR revealed that expression of bla KPC-3 encoding D179Y/T243M and D179Y variants was diminished compared to bla KPC-3 expression in baseline isolates. In conclusion, the development of resistance-conferring bla KPC-3 mutations in K. pneumoniae within 10 to 19 days of ceftazidime-avibactam exposure is troubling, but clinical impact may be ameliorated if carbapenem susceptibility is restored in certain isolates.

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          The Sequence Alignment/Map format and SAMtools

          Summary: The Sequence Alignment/Map (SAM) format is a generic alignment format for storing read alignments against reference sequences, supporting short and long reads (up to 128 Mbp) produced by different sequencing platforms. It is flexible in style, compact in size, efficient in random access and is the format in which alignments from the 1000 Genomes Project are released. SAMtools implements various utilities for post-processing alignments in the SAM format, such as indexing, variant caller and alignment viewer, and thus provides universal tools for processing read alignments. Availability: http://samtools.sourceforge.net Contact: rd@sanger.ac.uk
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            Fast and accurate short read alignment with Burrows–Wheeler transform

            Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ∼10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: rd@sanger.ac.uk
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              Is Open Access

              RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

              Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Journal
                Antimicrobial Agents and Chemotherapy
                Antimicrob Agents Chemother
                American Society for Microbiology
                0066-4804
                1098-6596
                March 2017
                March 2017
                : 61
                : 3
                Affiliations
                [1 ]Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
                [2 ]XDR Pathogen Laboratory, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
                [3 ]Public Health Research Institute Tuberculosis Center, New Jersey Medical School, Rutgers University, Newark, New Jersey, USA
                [4 ]VA Pittsburgh Healthcare System, Pittsburgh, Pennsylvania, USA
                Article
                10.1128/AAC.02097-16
                5328542
                28031201
                9387360d-0334-439c-9255-2466a8e85221
                © 2017

                https://journals.asm.org/non-commercial-tdm-license

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