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      Lytic archaeal viruses infect abundant primary producers in Earth’s crust

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          Abstract

          The continental subsurface houses a major portion of life’s abundance and diversity, yet little is known about viruses infecting microbes that reside there. Here, we use a combination of metagenomics and virus-targeted direct-geneFISH (virusFISH) to show that highly abundant carbon-fixing organisms of the uncultivated genus Candidatus Altiarchaeum are frequent targets of previously unrecognized viruses in the deep subsurface. Analysis of CRISPR spacer matches display resistances of Ca. Altiarchaea against eight predicted viral clades, which show genomic relatedness across continents but little similarity to previously identified viruses. Based on metagenomic information, we tag and image a putatively viral genome rich in protospacers using fluorescence microscopy. VirusFISH reveals a lytic lifestyle of the respective virus and challenges previous predictions that lysogeny prevails as the dominant viral lifestyle in the subsurface. CRISPR development over time and imaging of 18 samples from one subsurface ecosystem suggest a sophisticated interplay of viral diversification and adapting CRISPR-mediated resistances of Ca. Altiarchaeum. We conclude that infections of primary producers with lytic viruses followed by cell lysis potentially jump-start heterotrophic carbon cycling in these subsurface ecosystems.

          Abstract

          Little is known about viral-host interactions in the continental subsurface. Here, the authors use a combination of metagenomics, fluorescence in situ hybridization, and electron microscopy to show infections of abundant C-fixing subsurface archaea by lytic viruses.

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          Fast gapped-read alignment with Bowtie 2.

          As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.
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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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              The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

              SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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                Author and article information

                Contributors
                alexander.probst@uni-due.de
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                30 July 2021
                30 July 2021
                2021
                : 12
                : 4642
                Affiliations
                [1 ]GRID grid.5718.b, ISNI 0000 0001 2187 5445, Department of Chemistry, Environmental Microbiology and Biotechnology (EMB), Group for Aquatic Microbial Ecology, , University of Duisburg-Essen, ; Essen, Germany
                [2 ]GRID grid.451309.a, ISNI 0000 0004 0449 479X, DOE Joint Genome Institute, ; Berkeley, CA USA
                [3 ]GRID grid.5252.0, ISNI 0000 0004 1936 973X, Plant Development & Electron Microscopy, , Biocenter LMU Munich, ; Planegg-Martinsried, Germany
                [4 ]GRID grid.5560.6, ISNI 0000 0001 1009 3608, Institute for Chemistry and Biology of the Marine Environment (ICBM), , Carl-von-Ossietzky-University Oldenburg, ; Oldenburg, Germany
                [5 ]GRID grid.8148.5, ISNI 0000 0001 2174 3522, Present Address: Department of Biology and Environmental Science, Centre for Ecology and Evolution in Microbial Model Systems (EEMiS), , Linnaeus University, ; Kalmar, Sweden
                Author information
                http://orcid.org/0000-0002-2132-2709
                http://orcid.org/0000-0001-6772-8635
                http://orcid.org/0000-0002-4932-4677
                http://orcid.org/0000-0002-9485-5637
                http://orcid.org/0000-0002-9392-6544
                Article
                24803
                10.1038/s41467-021-24803-4
                8324899
                34330907
                d0d0d3c6-403b-4464-93d5-5853c33d3119
                © 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
                : 5 August 2020
                : 5 July 2021
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                © The Author(s) 2021

                Uncategorized
                microbial ecology,biofilms,virology
                Uncategorized
                microbial ecology, biofilms, virology

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