Isolation and characterization of the novel bacteriophage vB_SmaS_BUCT626 against Stenotrophomonas maltophilia

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Abstract

<p class="first" id="d3768992e176">Stenotrophomonas maltophilia has been recognized as an emerging global opportunistic pathogen, and it is intrinsically resistant to most antibiotics, which makes the limited choice for treating S. maltophilia infections. Bacteriophage with the proper characterization is considered as a promising alternative treatment option to control S. maltophilia infections. In this study, we isolated a novel Siphoviridae bacteriophage vB_SmaS_BUCT626 with lytic activity against S. maltophilia. Phage vB_SmaS_BUCT626 can lysis 10 of 20 S. maltophilia and was relatively stable at a wide range of temperatures (4-70 °C) and pH values (3.0-13.0) and exhibited good tolerance to chloroform. The genome of phage vB_SmaS_BUCT626 was a 61,662-bp linear double-stranded DNA molecule with a GC content of 56.2%, and contained 100 open-reading frames. It carried no antibiotic resistance, toxin, virulence-related genes, or lysogen-formation gene clusters. Together, these characteristics make phage vB_SmaS_BUCT626, a viable candidate as a biocontrol agent against S. maltophilia infection. </p>

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Sudhir Kumar, Glen Stecher, Koichiro Tamura (2016)

We present the latest version of the Molecular Evolutionary Genetics Analysis (Mega) software, which contains many sophisticated methods and tools for phylogenomics and phylomedicine. In this major upgrade, Mega has been optimized for use on 64-bit computing systems for analyzing larger datasets. Researchers can now explore and analyze tens of thousands of sequences in Mega The new version also provides an advanced wizard for building timetrees and includes a new functionality to automatically predict gene duplication events in gene family trees. The 64-bit Mega is made available in two interfaces: graphical and command line. The graphical user interface (GUI) is a native Microsoft Windows application that can also be used on Mac OS X. The command line Mega is available as native applications for Windows, Linux, and Mac OS X. They are intended for use in high-throughput and scripted analysis. Both versions are available from www.megasoftware.net free of charge.

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

R. C. Edgar (2004)

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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UniProt: the universal protein knowledgebase in 2021

(2020)

Abstract The aim of the UniProt Knowledgebase is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this article, we describe significant updates that we have made over the last two years to the resource. The number of sequences in UniProtKB has risen to approximately 190 million, despite continued work to reduce sequence redundancy at the proteome level. We have adopted new methods of assessing proteome completeness and quality. We continue to extract detailed annotations from the literature to add to reviewed entries and supplement these in unreviewed entries with annotations provided by automated systems such as the newly implemented Association-Rule-Based Annotator (ARBA). We have developed a credit-based publication submission interface to allow the community to contribute publications and annotations to UniProt entries. We describe how UniProtKB responded to the COVID-19 pandemic through expert curation of relevant entries that were rapidly made available to the research community through a dedicated portal. UniProt resources are available under a CC-BY (4.0) license via the web at https://www.uniprot.org/.