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      Tundra Soil Viruses Mediate Responses of Microbial Communities to Climate Warming

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          ABSTRACT

          The rise of global temperature causes the degradation of the substantial reserves of carbon (C) stored in tundra soils, in which microbial processes play critical roles. Viruses are known to influence the soil C cycle by encoding auxiliary metabolic genes and infecting key microorganisms, but their regulation of microbial communities under climate warming remains unexplored. In this study, we evaluated the responses of viral communities for about 5 years of experimental warming at two depths (15 to 25 cm and 45 to 55 cm) in the Alaskan permafrost region. Our results showed that the viral community and functional gene composition and abundances (including viral functional genes related to replication, structure, infection, and lysis) were significantly influenced by environmental conditions such as total nitrogen (N), total C, and soil thawing duration. Although long-term warming did not impact the viral community composition at the two depths, some glycoside hydrolases encoded by viruses were more abundant at both depths of the warmed plots. With the continuous reduction of total C, viruses may alleviate methane release by altering infection strategies on methanogens. Importantly, viruses can adopt lysogenic and lytic lifestyles to manipulate microbial communities at different soil depths, respectively, which could be one of the major factors causing the differences in microbial responses to warming. This study provides a new ecological perspective on how viruses regulate the responses of microbes to warming at community and functional scales.

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          Fitting Linear Mixed-Effects Models Usinglme4

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            Cytoscape: a software environment for integrated models of biomolecular interaction networks.

            Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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              RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies

              Motivation: Phylogenies are increasingly used in all fields of medical and biological research. Moreover, because of the next-generation sequencing revolution, datasets used for conducting phylogenetic analyses grow at an unprecedented pace. RAxML (Randomized Axelerated Maximum Likelihood) is a popular program for phylogenetic analyses of large datasets under maximum likelihood. Since the last RAxML paper in 2006, it has been continuously maintained and extended to accommodate the increasingly growing input datasets and to serve the needs of the user community. Results: I present some of the most notable new features and extensions of RAxML, such as a substantial extension of substitution models and supported data types, the introduction of SSE3, AVX and AVX2 vector intrinsics, techniques for reducing the memory requirements of the code and a plethora of operations for conducting post-analyses on sets of trees. In addition, an up-to-date 50-page user manual covering all new RAxML options is available. Availability and implementation: The code is available under GNU GPL at https://github.com/stamatak/standard-RAxML. Contact: alexandros.stamatakis@h-its.org Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                Role: Invited Editor
                Role: Editor
                Journal
                mBio
                mBio
                mbio
                mBio
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                2150-7511
                14 February 2023
                Mar-Apr 2023
                14 February 2023
                : 14
                : 2
                : e03009-22
                Affiliations
                [a ] School of Biological Science and Technology, University of Jinan, Jinan, Shandong Province, China
                [b ] Institute of Marine Science and Technology, Shandong University, Qingdao, Shandong Province, China
                [c ] Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, USA
                [d ] Department of Environmental Science, Policy, and Management, University of California, Berkeley, California, USA
                [e ] School of Civil Engineering and Environmental Sciences, University of Oklahoma, Norman, Oklahoma, USA
                [f ] School of Computer Sciences, University of Oklahoma, Norman, Oklahoma, USA
                [g ] Earth and Environmental Sciences, Lawrence Berkeley National Laboratory, Berkeley, California, USA
                The University of British Columbia
                University of California—Irvine
                Author notes

                Mengzhi Ji and Xiangyu Fan contributed equally to this article. The order of the first two authors was decided based on contributions to the writing and editing of the article.

                The authors declare no conflict of interest.

                Author information
                https://orcid.org/0000-0002-1376-0039
                https://orcid.org/0000-0001-5355-3248
                Article
                03009-22 mbio.03009-22
                10.1128/mbio.03009-22
                10127799
                36786571
                8a12a2ec-2536-48f9-9311-989a911ae3da
                Copyright © 2023 Ji et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 27 October 2022
                : 23 January 2023
                Page count
                supplementary-material: 10, Figures: 7, Tables: 0, Equations: 0, References: 101, Pages: 19, Words: 13589
                Funding
                Funded by: National Natural Science Foundation of China (NSFC), FundRef https://doi.org/10.13039/501100001809;
                Award ID: 31600148
                Award Recipient :
                Funded by: Natural Science Foundation of Shandong Province (Natural Science Foundation of Shandong), FundRef https://doi.org/10.13039/501100007129;
                Award ID: ZR2021MC018
                Award Recipient :
                Categories
                Research Article
                editors-pick, Editor's Pick
                virology, Virology
                Custom metadata
                March/April 2023

                Life sciences
                climate warming,environmental factors,glycoside hydrolases,viral lifestyle,virus-microbe linkage,virus-host linkage

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