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      PBP4 Is Likely Involved in Cell Division of the Longitudinally Dividing Bacterium Candidatus Thiosymbion Oneisti

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          Abstract

          Peptidoglycan (PG) is essential for bacterial survival and maintaining cell shape. The rod-shaped model bacterium Escherichia coli has a set of seven endopeptidases that remodel the PG during cell growth. The gamma proteobacterium Candidatus Thiosymbion oneisti is also rod-shaped and attaches to the cuticle of its nematode host by one pole. It widens and divides by longitudinal fission using the canonical proteins MreB and FtsZ. The PG layer of Ca. T. oneisti has an unusually high peptide cross-linkage of 67% but relatively short glycan chains with an average length of 12 disaccharides. Curiously, it has only two predicted endopeptidases, MepA and PBP4. Cellular localization of symbiont PBP4 by fluorescently labeled antibodies reveals its polar localization and its accumulation at the constriction sites, suggesting that PBP4 is involved in PG biosynthesis during septum formation. Isolated symbiont PBP4 protein shows a different selectivity for β-lactams compared to its homologue from E. coli. Bocillin-FL binding by PBP4 is activated by some β-lactams, suggesting the presence of an allosteric binding site. Overall, our data point to a role of PBP4 in PG cleavage during the longitudinal cell division and to a PG that might have been adapted to the symbiotic lifestyle.

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          NIH Image to ImageJ: 25 years of image analysis

          For the past twenty five years the NIH family of imaging software, NIH Image and ImageJ have been pioneers as open tools for scientific image analysis. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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            The Phyre2 web portal for protein modeling, prediction and analysis.

            Phyre2 is a suite of tools available on the web to predict and analyze protein structure, function and mutations. The focus of Phyre2 is to provide biologists with a simple and intuitive interface to state-of-the-art protein bioinformatics tools. Phyre2 replaces Phyre, the original version of the server for which we previously published a paper in Nature Protocols. In this updated protocol, we describe Phyre2, which uses advanced remote homology detection methods to build 3D models, predict ligand binding sites and analyze the effect of amino acid variants (e.g., nonsynonymous SNPs (nsSNPs)) for a user's protein sequence. Users are guided through results by a simple interface at a level of detail they determine. This protocol will guide users from submitting a protein sequence to interpreting the secondary and tertiary structure of their models, their domain composition and model quality. A range of additional available tools is described to find a protein structure in a genome, to submit large number of sequences at once and to automatically run weekly searches for proteins that are difficult to model. The server is available at http://www.sbg.bio.ic.ac.uk/phyre2. A typical structure prediction will be returned between 30 min and 2 h after submission.
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              SignalP 5.0 improves signal peptide predictions using deep neural networks

              Signal peptides (SPs) are short amino acid sequences in the amino terminus of many newly synthesized proteins that target proteins into, or across, membranes. Bioinformatic tools can predict SPs from amino acid sequences, but most cannot distinguish between various types of signal peptides. We present a deep neural network-based approach that improves SP prediction across all domains of life and distinguishes between three types of prokaryotic SPs.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Antibiotics (Basel)
                Antibiotics (Basel)
                antibiotics
                Antibiotics
                MDPI
                2079-6382
                09 March 2021
                March 2021
                : 10
                : 3
                : 274
                Affiliations
                [1 ]Bacterial Cell Biology & Physiology, Faculty of Science, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands; J.Wang3@ 123456uva.nl
                [2 ]Department of Molecular Biology, Umeå University, SE-901 87 Umeå, Sweden; laura.alvarez@ 123456umu.se (L.A.); felipe.cava@ 123456umu.se (F.C.)
                [3 ]Environmental Cell Biology, University of Vienna, Althanstrasse 14 (UZA I), 1090 Vienna, Austria; bulghes3@ 123456univie.ac.at
                Author notes
                [* ]Correspondence: T.denblaauwen@ 123456uva.nl
                Author information
                https://orcid.org/0000-0003-2429-7542
                https://orcid.org/0000-0002-5403-5597
                Article
                antibiotics-10-00274
                10.3390/antibiotics10030274
                7999549
                8cc7666c-4b23-4ecf-933e-ef9e3c40726d
                © 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
                : 30 January 2021
                : 06 March 2021
                Categories
                Article

                cell division,penicillin binding proteins,peptidoglycan,protein localization,symbiosis

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