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      ε 2-Phages Are Naturally Bred and Have a Vastly Improved Host Range in Staphylococcus aureus over Wild Type Phages

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          Abstract

          Due to the rapid spread of antibiotic resistance, and the difficulties of treating biofilm-associated infections, alternative treatments for S. aureus infections are urgently needed. We tested the lytic activity of several wild type phages against a panel of 110 S. aureus strains (MRSA/MSSA) composed to reflect the prevalence of S. aureus clonal complexes in human infections. The plaquing host ranges (PHR) of the wild type phages were in the range of 51% to 60%. We also measured what we called the kinetic host range (KHR), i.e., the percentage of strains for which growth in suspension was suppressed for 24 h. The KHR of the wild type phages ranged from 2% to 49%, substantially lower than the PHRs. To improve the KHR and other key pharmaceutical properties, we bred the phages by mixing and propagating cocktails on a subset of S. aureus strains. These bred phages, which we termed evolution-squared (ε 2) phages, have broader KHRs up to 64% and increased virulence compared to the ancestors. The ε 2-phages with the broadest KHR have genomes intercrossed from up to three different ancestors. We composed a cocktail of three ε 2-phages with an overall KHR of 92% and PHR of 96% on 110 S. aureus strains and called it PM-399. PM-399 has a lower propensity to resistance formation than the standard of care antibiotics vancomycin, rifampicin, or their combination, and no resistance was observed in laboratory settings (detection limit: 1 cell in 10 11). In summary, ε 2-phages and, in particular PM-399, are promising candidates for an alternative treatment of S. aureus infections.

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          SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing.

          The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.
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            CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database

            Abstract The Comprehensive Antibiotic Resistance Database (CARD; https://card.mcmaster.ca) is a curated resource providing reference DNA and protein sequences, detection models and bioinformatics tools on the molecular basis of bacterial antimicrobial resistance (AMR). CARD focuses on providing high-quality reference data and molecular sequences within a controlled vocabulary, the Antibiotic Resistance Ontology (ARO), designed by the CARD biocuration team to integrate with software development efforts for resistome analysis and prediction, such as CARD’s Resistance Gene Identifier (RGI) software. Since 2017, CARD has expanded through extensive curation of reference sequences, revision of the ontological structure, curation of over 500 new AMR detection models, development of a new classification paradigm and expansion of analytical tools. Most notably, a new Resistomes & Variants module provides analysis and statistical summary of in silico predicted resistance variants from 82 pathogens and over 100 000 genomes. By adding these resistance variants to CARD, we are able to summarize predicted resistance using the information included in CARD, identify trends in AMR mobility and determine previously undescribed and novel resistance variants. Here, we describe updates and recent expansions to CARD and its biocuration process, including new resources for community biocuration of AMR molecular reference data.
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              ResFinder 4.0 for predictions of phenotypes from genotypes

              Abstract Objectives WGS-based antimicrobial susceptibility testing (AST) is as reliable as phenotypic AST for several antimicrobial/bacterial species combinations. However, routine use of WGS-based AST is hindered by the need for bioinformatics skills and knowledge of antimicrobial resistance (AMR) determinants to operate the vast majority of tools developed to date. By leveraging on ResFinder and PointFinder, two freely accessible tools that can also assist users without bioinformatics skills, we aimed at increasing their speed and providing an easily interpretable antibiogram as output. Methods The ResFinder code was re-written to process raw reads and use Kmer-based alignment. The existing ResFinder and PointFinder databases were revised and expanded. Additional databases were developed including a genotype-to-phenotype key associating each AMR determinant with a phenotype at the antimicrobial compound level, and species-specific panels for in silico antibiograms. ResFinder 4.0 was validated using Escherichia coli (n = 584), Salmonella spp. (n = 1081), Campylobacter jejuni (n = 239), Enterococcus faecium (n = 106), Enterococcus faecalis (n = 50) and Staphylococcus aureus (n = 163) exhibiting different AST profiles, and from different human and animal sources and geographical origins. Results Genotype–phenotype concordance was ≥95% for 46/51 and 25/32 of the antimicrobial/species combinations evaluated for Gram-negative and Gram-positive bacteria, respectively. When genotype–phenotype concordance was <95%, discrepancies were mainly linked to criteria for interpretation of phenotypic tests and suboptimal sequence quality, and not to ResFinder 4.0 performance. Conclusions WGS-based AST using ResFinder 4.0 provides in silico antibiograms as reliable as those obtained by phenotypic AST at least for the bacterial species/antimicrobial agents of major public health relevance considered.
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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Pharmaceuticals (Basel)
                Pharmaceuticals (Basel)
                pharmaceuticals
                Pharmaceuticals
                MDPI
                1424-8247
                02 April 2021
                April 2021
                : 14
                : 4
                : 325
                Affiliations
                [1 ]PhagoMed Biopharma GmbH, Leberstrasse 20, A-1110 Vienna, Austria; david.saez@ 123456phagomed.com (D.S.M.); Zehra.visram@ 123456phagomed.com (Z.V.); Michele.mutti@ 123456phagomed.com (M.M.); Marcela.restrepo@ 123456phagomed.com (M.R.-C.); susana.hartmann@ 123456phagomed.com (S.H.); kremers.ana@ 123456gmail.com (A.I.K.); Lenka.tisakova@ 123456phagomed.com (L.T.)
                [2 ]Leibniz Institute DSMZ—German Collection of Microorganisms and Cell Cultures, Inhoffenstraße 7B, 38124 Braunschweig, Germany; susanne_schertler@ 123456web.de (S.S.); jow12@ 123456dsmz.de (J.W.)
                [3 ]Bactrace Biotec AG, Neherstr. 1, 81675 Munich, Germany; b.kalali@ 123456bactrace.com
                [4 ]Leibniz Institute of Photonic Technology (IPHT), 07745 Jena, Germany; stefan.monecke@ 123456leibniz-ipht.de (S.M.); Ralf.Ehricht@ 123456leibniz-ipht.de (R.E.)
                [5 ]Institute of Medical Microbiologye and Hygiene, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Fiedlerstr. 42, D-01307 Dresden, Germany
                [6 ]InfectoGnostics Research Campus Jena, 07743 Jena, Germany
                [7 ]Institute of Physical Chemistry, Friedrich-Schiller University, 07743 Jena, Germany
                [8 ]Department of Fundamental Microbiology, University Lausanne, CH-1015 Lausanne, Switzerland; gregory.resch@ 123456unil.ch
                Author notes
                Author information
                https://orcid.org/0000-0003-3567-6919
                https://orcid.org/0000-0002-1691-7396
                https://orcid.org/0000-0002-6840-2810
                https://orcid.org/0000-0002-2891-0888
                https://orcid.org/0000-0002-6612-0043
                https://orcid.org/0000-0003-2341-4591
                https://orcid.org/0000-0002-8077-6559
                Article
                pharmaceuticals-14-00325
                10.3390/ph14040325
                8065394
                33918287
                5663332d-70f5-4c27-afec-9eb42d4cf10a
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 29 January 2021
                : 23 February 2021
                Categories
                Article

                phage therapy,phage breeding,phage training,homologous recombination,host range,antimicrobial resistance,phage cocktail,s. aureus,mrsa,mssa

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