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      Broad-range lytic bacteriophages that kill Staphylococcus aureus local field strains

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          Abstract

          Staphylococcus aureus is a very successful opportunistic pathogen capable of causing a variety of diseases ranging from mild skin infections to life-threatening sepsis, meningitis and pneumonia. Its ability to display numerous virulence mechanisms matches its skill to display resistance to several antibiotics, including β-lactams, underscoring the fact that new anti- S. aureus drugs are urgently required. In this scenario, the utilization of lytic bacteriophages that kill bacteria in a genus -or even species- specific way, has become an attractive field of study. In this report, we describe the isolation, characterization and sequencing of phages capable of killing S. aureus including methicillin resistant (MRSA) and multi-drug resistant S. aureus local strains from environmental, animal and human origin. Genome sequencing and bio-informatics analysis showed the absence of genes encoding virulence factors, toxins or antibiotic resistance determinants. Of note, there was a high similarity between our set of phages to others described in the literature such as phage K. Considering that reported phages were obtained in different continents, it seems plausible that there is a commonality of genetic features that are needed for optimum, broad host range anti-staphylococcal activity of these related phages. Importantly, the high activity and broad host range of one of our phages underscores its promising value to control the presence of S. aureus in fomites, industry and hospital environments and eventually on animal and human skin. The development of a cocktail of the reported lytic phages active against S. aureus–currently under way- is thus, a sensible strategy against this pathogen.

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          Most cited references52

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          GeneMarkS: a self-training method for prediction of gene starts in microbial genomes. Implications for finding sequence motifs in regulatory regions.

          J Besemer (2001)
          Improving the accuracy of prediction of gene starts is one of a few remaining open problems in computer prediction of prokaryotic genes. Its difficulty is caused by the absence of relatively strong sequence patterns identifying true translation initiation sites. In the current paper we show that the accuracy of gene start prediction can be improved by combining models of protein-coding and non-coding regions and models of regulatory sites near gene start within an iterative Hidden Markov model based algorithm. The new gene prediction method, called GeneMarkS, utilizes a non-supervised training procedure and can be used for a newly sequenced prokaryotic genome with no prior knowledge of any protein or rRNA genes. The GeneMarkS implementation uses an improved version of the gene finding program GeneMark.hmm, heuristic Markov models of coding and non-coding regions and the Gibbs sampling multiple alignment program. GeneMarkS predicted precisely 83.2% of the translation starts of GenBank annotated Bacillus subtilis genes and 94.4% of translation starts in an experimentally validated set of Escherichia coli genes. We have also observed that GeneMarkS detects prokaryotic genes, in terms of identifying open reading frames containing real genes, with an accuracy matching the level of the best currently used gene detection methods. Accurate translation start prediction, in addition to the refinement of protein sequence N-terminal data, provides the benefit of precise positioning of the sequence region situated upstream to a gene start. Therefore, sequence motifs related to transcription and translation regulatory sites can be revealed and analyzed with higher precision. These motifs were shown to possess a significant variability, the functional and evolutionary connections of which are discussed.
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            Fast algorithms for large-scale genome alignment and comparison.

            We describe a suffix-tree algorithm that can align the entire genome sequences of eukaryotic and prokaryotic organisms with minimal use of computer time and memory. The new system, MUMmer 2, runs three times faster while using one-third as much memory as the original MUMmer system. It has been used successfully to align the entire human and mouse genomes to each other, and to align numerous smaller eukaryotic and prokaryotic genomes. A new module permits the alignment of multiple DNA sequence fragments, which has proven valuable in the comparison of incomplete genome sequences. We also describe a method to align more distantly related genomes by detecting protein sequence homology. This extension to MUMmer aligns two genomes after translating the sequence in all six reading frames, extracts all matching protein sequences and then clusters together matches. This method has been applied to both incomplete and complete genome sequences in order to detect regions of conserved synteny, in which multiple proteins from one organism are found in the same order and orientation in another. The system code is being made freely available by the authors.
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              An Integrated Pipeline for de Novo Assembly of Microbial Genomes

              Remarkable advances in DNA sequencing technology have created a need for de novo genome assembly methods tailored to work with the new sequencing data types. Many such methods have been published in recent years, but assembling raw sequence data to obtain a draft genome has remained a complex, multi-step process, involving several stages of sequence data cleaning, error correction, assembly, and quality control. Successful application of these steps usually requires intimate knowledge of a diverse set of algorithms and software. We present an assembly pipeline called A5 (Andrew And Aaron's Awesome Assembly pipeline) that simplifies the entire genome assembly process by automating these stages, by integrating several previously published algorithms with new algorithms for quality control and automated assembly parameter selection. We demonstrate that A5 can produce assemblies of quality comparable to a leading assembly algorithm, SOAPdenovo, without any prior knowledge of the particular genome being assembled and without the extensive parameter tuning required by the other assembly algorithm. In particular, the assemblies produced by A5 exhibit 50% or more reduction in broken protein coding sequences relative to SOAPdenovo assemblies. The A5 pipeline can also assemble Illumina sequence data from libraries constructed by the Nextera (transposon-catalyzed) protocol, which have markedly different characteristics to mechanically sheared libraries. Finally, A5 has modest compute requirements, and can assemble a typical bacterial genome on current desktop or laptop computer hardware in under two hours, depending on depth of coverage.
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                Author and article information

                Contributors
                Role: Investigation
                Role: Investigation
                Role: Investigation
                Role: InvestigationRole: Methodology
                Role: Data curationRole: Formal analysis
                Role: Data curationRole: Formal analysisRole: InvestigationRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Funding acquisitionRole: MethodologyRole: ResourcesRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                25 July 2017
                2017
                : 12
                : 7
                : e0181671
                Affiliations
                [1 ] Laboratorio de Microbiología Molecular, Facultad de Ciencias Médicas, Universidad Nacional de Rosario, Rosario, Santa Fe, Argentina
                [2 ] EEA Rafaela, Instituto Nacional de Tecnología Agropecuaria (INTA), Rafaela, Santa Fe, Argentina
                [3 ] Bioinformatics Program, Universidad Nacional de Rosario, Rosario, Santa Fe, Argentina
                Cairo University, EGYPT
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0003-4180-9677
                Article
                PONE-D-17-16472
                10.1371/journal.pone.0181671
                5526547
                28742812
                fb491dea-43ba-4fbe-be58-15a2ee0a2936
                © 2017 Abatángelo 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
                : 28 April 2017
                : 5 July 2017
                Page count
                Figures: 8, Tables: 3, Pages: 22
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100006668, Fondo para la Investigación Científica y Tecnológica;
                Award ID: PICT START UP 1406
                Award Recipient :
                This work was supported by PICT START UP 1406; http://www.agencia.mincyt.gob.ar/frontend/agencia/fondo/foncyt.
                Categories
                Research Article
                Biology and Life Sciences
                Organisms
                Viruses
                Bacteriophages
                Biology and Life Sciences
                Organisms
                Bacteria
                Staphylococcus
                Staphylococcus Aureus
                Biology and Life Sciences
                Microbiology
                Medical Microbiology
                Microbial Pathogens
                Bacterial Pathogens
                Staphylococcus
                Staphylococcus Aureus
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Pathogens
                Microbial Pathogens
                Bacterial Pathogens
                Staphylococcus
                Staphylococcus Aureus
                Biology and Life Sciences
                Genetics
                Genomics
                Microbial Genomics
                Viral Genomics
                Biology and Life Sciences
                Microbiology
                Microbial Genomics
                Viral Genomics
                Biology and Life Sciences
                Microbiology
                Virology
                Viral Genomics
                Research and Analysis Methods
                Database and Informatics Methods
                Biological Databases
                Genomic Databases
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Genomic Databases
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Genomic Databases
                Biology and Life Sciences
                Computational Biology
                Comparative Genomics
                Biology and Life Sciences
                Genetics
                Genomics
                Comparative Genomics
                Biology and Life Sciences
                Computational Biology
                Genome Analysis
                Biology and Life Sciences
                Genetics
                Genomics
                Genome Analysis
                Research and Analysis Methods
                Database and Informatics Methods
                Bioinformatics
                Sequence Analysis
                Sequence Alignment
                Biology and Life Sciences
                Molecular Biology
                Molecular Biology Techniques
                Molecular Biology Assays and Analysis Techniques
                Molecular Biology Display Techniques
                Phage Display
                Research and Analysis Methods
                Molecular Biology Techniques
                Molecular Biology Assays and Analysis Techniques
                Molecular Biology Display Techniques
                Phage Display
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