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      Phage selection restores antibiotic sensitivity in MDR Pseudomonas aeruginosa

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          Abstract

          Increasing prevalence and severity of multi-drug-resistant (MDR) bacterial infections has necessitated novel antibacterial strategies. Ideally, new approaches would target bacterial pathogens while exerting selection for reduced pathogenesis when these bacteria inevitably evolve resistance to therapeutic intervention. As an example of such a management strategy, we isolated a lytic bacteriophage, OMKO1, (family Myoviridae) of Pseudomonas aeruginosa that utilizes the outer membrane porin M (OprM) of the multidrug efflux systems MexAB and MexXY as a receptor-binding site. Results show that phage selection produces an evolutionary trade-off in MDR P. aeruginosa, whereby the evolution of bacterial resistance to phage attack changes the efflux pump mechanism, causing increased sensitivity to drugs from several antibiotic classes. Although modern phage therapy is still in its infancy, we conclude that phages, such as OMKO1, represent a new approach to phage therapy where bacteriophages exert selection for MDR bacteria to become increasingly sensitive to traditional antibiotics. This approach, using phages as targeted antibacterials, could extend the lifetime of our current antibiotics and potentially reduce the incidence of antibiotic resistant infections.

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          Most cited references47

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          MUSCLE: multiple sequence alignment with high accuracy and high throughput.

          We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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            RAxML-VI-HPC: maximum likelihood-based phylogenetic analyses with thousands of taxa and mixed models.

            RAxML-VI-HPC (randomized axelerated maximum likelihood for high performance computing) is a sequential and parallel program for inference of large phylogenies with maximum likelihood (ML). Low-level technical optimizations, a modification of the search algorithm, and the use of the GTR+CAT approximation as replacement for GTR+Gamma yield a program that is between 2.7 and 52 times faster than the previous version of RAxML. A large-scale performance comparison with GARLI, PHYML, IQPNNI and MrBayes on real data containing 1000 up to 6722 taxa shows that RAxML requires at least 5.6 times less main memory and yields better trees in similar times than the best competing program (GARLI) on datasets up to 2500 taxa. On datasets > or =4000 taxa it also runs 2-3 times faster than GARLI. RAxML has been parallelized with MPI to conduct parallel multiple bootstraps and inferences on distinct starting trees. The program has been used to compute ML trees on two of the largest alignments to date containing 25,057 (1463 bp) and 2182 (51,089 bp) taxa, respectively. icwww.epfl.ch/~stamatak
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              Bacteriophage resistance mechanisms.

              Phages are now acknowledged as the most abundant microorganisms on the planet and are also possibly the most diversified. This diversity is mostly driven by their dynamic adaptation when facing selective pressure such as phage resistance mechanisms, which are widespread in bacterial hosts. When infecting bacterial cells, phages face a range of antiviral mechanisms, and they have evolved multiple tactics to avoid, circumvent or subvert these mechanisms in order to thrive in most environments. In this Review, we highlight the most important antiviral mechanisms of bacteria as well as the counter-attacks used by phages to evade these systems.
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                Author and article information

                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group
                2045-2322
                26 May 2016
                2016
                : 6
                : 26717
                Affiliations
                [1 ]Department of Ecology and Evolutionary Biology, Yale University , New Haven, CT 06520, USA
                [2 ]School of Natural Sciences, University of California Merced , Merced, CA, 95343, USA
                [3 ]E. coli Genetic Stock Center, Department of Molecular, Cellular and Developmental Biology, Yale University , New Haven, CT 06520, USA
                [4 ]Department of Microbial Pathogenesis, Yale School of Medicine , New Haven, CT 06520, USA
                [5 ]Department of Surgery, Yale School of Medicine , New Haven, CT 06520, USA
                [6 ]Program in Microbiology, Yale School of Medicine , New Haven, CT 06520, USA
                Author notes
                Article
                srep26717
                10.1038/srep26717
                4880932
                27225966
                8a059e58-224d-49a7-8cf3-502d734a176f
                Copyright © 2016, Macmillan Publishers Limited

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 07 March 2016
                : 05 May 2016
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