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      Transporter characterisation reveals aminoethylphosphonate mineralisation as a key step in the marine phosphorus redox cycle

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          Abstract

          The planktonic synthesis of reduced organophosphorus molecules, such as alkylphosphonates and aminophosphonates, represents one half of a vast global oceanic phosphorus redox cycle. Whilst alkylphosphonates tend to accumulate in recalcitrant dissolved organic matter, aminophosphonates do not. Here, we identify three bacterial 2-aminoethylphosphonate (2AEP) transporters, named AepXVW, AepP and AepSTU, whose synthesis is independent of phosphate concentrations (phosphate-insensitive). AepXVW is found in diverse marine heterotrophs and is ubiquitously distributed in mesopelagic and epipelagic waters. Unlike the archetypal phosphonate binding protein, PhnD, AepX has high affinity and high specificity for 2AEP ( Stappia stellulata AepX K d 23 ± 4 nM; methylphosphonate K d 3.4 ± 0.3 mM). In the global ocean, aepX is heavily transcribed (~100-fold> phnD) independently of phosphate and nitrogen concentrations. Collectively, our data identifies a mechanism responsible for a major oxidation process in the marine phosphorus redox cycle and suggests 2AEP may be an important source of regenerated phosphate and ammonium, which are required for oceanic primary production.

          Abstract

          Here the authors show that 2-aminoethylphosphonate (2AEP) mineralisation is widespread in the global ocean, operating independently of exogenous inorganic phosphate concentration. They propose 2AEP may be a major route for the regeneration of phosphate required to support marine primary production.

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          IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era

          Abstract IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.
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            Interactive Tree Of Life (iTOL) v4: recent updates and new developments

            Abstract The Interactive Tree Of Life (https://itol.embl.de) is an online tool for the display, manipulation and annotation of phylogenetic and other trees. It is freely available and open to everyone. The current version introduces four new dataset types, together with numerous new features. Annotation options have been expanded and new control options added for many display elements. An interactive spreadsheet-like editor has been implemented, providing dataset creation and editing directly in the web interface. Font support has been rewritten with full support for UTF-8 character encoding throughout the user interface. Google Web Fonts are now fully supported in the tree text labels. iTOL v4 is the first tool which supports direct visualization of Qiime 2 trees and associated annotations. The user account system has been streamlined and expanded with new navigation options, and currently handles >700 000 trees from more than 40 000 individual users. Full batch access has been implemented allowing programmatic upload and export of trees and annotations.
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              The Perseus computational platform for comprehensive analysis of (prote)omics data.

              A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.
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                Author and article information

                Contributors
                I.lidbury@sheffield.ac.uk
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                27 July 2021
                27 July 2021
                2021
                : 12
                : 4554
                Affiliations
                [1 ]GRID grid.7372.1, ISNI 0000 0000 8809 1613, School of Life Sciences, University of Warwick, Gibbet Hill Road, ; Coventry, UK
                [2 ]GRID grid.11835.3e, ISNI 0000 0004 1936 9262, Department of Molecular Biology and Biotechnology, , University of Sheffield, ; Sheffield, UK
                [3 ]GRID grid.511332.7, ISNI 0000 0004 4659 2945, Nanotemper Technologies GmbH, Flößergasse 4, ; Munich, Germany
                [4 ]GRID grid.9435.b, ISNI 0000 0004 0457 9566, School of Agriculture, Policy, and Development, University of Reading, Earley Gate, Whiteknights, ; Reading, UK
                [5 ]GRID grid.11835.3e, ISNI 0000 0004 1936 9262, Department of Animal and Plant Sciences, , University of Sheffield, ; Sheffield, UK
                Author information
                http://orcid.org/0000-0003-3093-4245
                http://orcid.org/0000-0002-0367-4276
                http://orcid.org/0000-0003-3080-3448
                http://orcid.org/0000-0002-5182-3643
                http://orcid.org/0000-0002-6241-3551
                http://orcid.org/0000-0002-4329-0699
                http://orcid.org/0000-0001-7190-315X
                Article
                24646
                10.1038/s41467-021-24646-z
                8316502
                34315891
                74c0311d-727d-46d2-b0ec-50c57a1b6dec
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 10 December 2020
                : 29 June 2021
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