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      Characterization of efficient xylanases from industrial-scale pulp and paper wastewater treatment microbiota

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          Abstract

          Xylanases are widely used enzymes in the food, textile, and paper industries. Most efficient xylanases have been identified from lignocellulose-degrading microbiota, such as the microbiota of the cow rumen and the termite hindgut. Xylanase genes from efficient pulp and paper wastewater treatment (PPWT) microbiota have been previously recovered by metagenomics, assigning most of the xylanase genes to the GH10 family. In this study, a total of 40 GH10 family xylanase genes derived from a certain PPWT microbiota were cloned and expressed in Escherichia coli BL21 (DE3). Among these xylanase genes, 14 showed xylanase activity on beechwood substrate. Two of these, PW-xyl9 and PW-xyl37, showed high activities, and were purified to evaluate their xylanase properties. Values of optimal pH and temperature for PW-xyl9 were pH 7 and 60 ℃, respectively, while those for PW-xyl37 were pH 7 and 55 ℃, respectively; their specific xylanase activities under optimal conditions were 470.1 U/mg protein and 113.7 U/mg protein, respectively. Furthermore, the Km values of PW-xyl9 and PW-xyl37 were determined as 8.02 and 18.8 g/L, respectively. The characterization of these two xylanases paves the way for potential application in future pulp and paper production and other industries, indicating that PPWT microbiota has been an undiscovered reservoir of efficient lignocellulase genes. This study demonstrates that a metagenomic approach has the potential to screen efficient xylanases of uncultured microorganisms from lignocellulose-degrading microbiota. In a similar way, other efficient lignocellulase genes might be identified from PPWT treatment microbiota in the future.

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          MEGA7: Molecular Evolutionary Genetics Analysis Version 7.0 for Bigger Datasets.

          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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            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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              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
                lyh224@163.com
                tianlinmin@163.com
                yongjunwei@zzu.edu.cn
                Journal
                AMB Express
                AMB Express
                AMB Express
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                2191-0855
                19 January 2021
                19 January 2021
                2021
                : 11
                : 19
                Affiliations
                [1 ]GRID grid.207374.5, ISNI 0000 0001 2189 3846, Key Laboratory of Advanced Drug Preparation Technologies, Ministry of Education, School of Pharmaceutical Sciences, , Zhengzhou University, ; Zhengzhou, People’s Republic of China
                [2 ]GRID grid.207374.5, ISNI 0000 0001 2189 3846, College of Public Health, , Zhengzhou University, ; Zhengzhou, Henan 450001 People’s Republic of China
                [3 ]GRID grid.258164.c, ISNI 0000 0004 1790 3548, Department of Food Science and Engineering, , Jinan University, ; Guangzhou, 510632 People’s Republic of China
                Article
                1178
                10.1186/s13568-020-01178-1
                7815853
                33464408
                0a170e63-6204-452f-99b1-ff91e9f91b11
                © The Author(s) 2021

                Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 29 December 2020
                : 31 December 2020
                Funding
                Funded by: National Natural Science Foundation of China
                Award ID: 31800079
                Award Recipient :
                Categories
                Original Article
                Custom metadata
                © The Author(s) 2021

                Biotechnology
                metagenome,xylanase,gh10 family,xylan,pulp and paper wastewater
                Biotechnology
                metagenome, xylanase, gh10 family, xylan, pulp and paper wastewater

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