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      Comammox Nitrospira within the Yangtze River continuum: community, biogeography, and ecological drivers

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          Abstract

          The recent discovery of comammox Nitrospira as complete nitrifiers has fundamentally renewed perceptions of nitrogen cycling in natural and engineered systems, yet little is known about the environmental controls on these newly recognized bacteria. Based on improved phylogenetic resolution through successful assembly of ten novel genomes (71–96% completeness), we provided the first biogeographic patterns for planktonic and benthic comammox Nitrospira in the Yangtze River over a 6030 km continuum. Our study revealed the widespread distributions and relative abundance of comammox Nitrospira in this large freshwater system, constituting 30 and 46% of ammonia-oxidizing prokaryotes (AOPs) and displaying 30.4- and 17.9-fold greater abundances than canonical Nitrospira representatives in water and sediments, respectively. Comammox Nitrospira contributed more to nitrifier abundances (34–87% of AOPs) in typical oligotrophic environments with a higher pH and lower temperature, particularly in the plateau (clade B), mountain and foothill (clade A) areas of the upper reach. The dominant position of planktonic comammox Nitrospira was replaced by canonical Nitrospira sublineages I/II and ammonia-oxidizing bacteria from the plateau to downstream plain due to environmental selection, while the dissimilarity of benthic comammox Nitrospira was moderately associated with geographic distance. A substantial decrease (83%) in benthic comammox Nitrospira abundance occurred immediately downstream of the Three Gorges Dam, consistent with a similarly considerable decrease in overall sediment bacterial taxa. Together, this study highlights the previously unrecognized dominance of comammox Nitrospira in major river systems and underlines the importance of revisiting the distributions of and controls on nitrification processes within global freshwater environments.

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          Toward almost closed genomes with GapFiller

          De novo assembly is a commonly used application of next-generation sequencing experiments. The ultimate goal is to puzzle millions of reads into one complete genome, although draft assemblies usually result in a number of gapped scaffold sequences. In this paper we propose an automated strategy, called GapFiller, to reliably close gaps within scaffolds using paired reads. The method shows good results on both bacterial and eukaryotic datasets, allowing only few errors. As a consequence, the amount of additional wetlab work needed to close a genome is drastically reduced. The software is available at http://www.baseclear.com/bioinformatics-tools/.
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            The microbial nitrogen-cycling network

            Nitrogen is an essential component of all living organisms and the main nutrient limiting life on our planet. By far, the largest inventory of freely accessible nitrogen is atmospheric dinitrogen, but most organisms rely on more bioavailable forms of nitrogen, such as ammonium and nitrate, for growth. The availability of these substrates depends on diverse nitrogen-transforming reactions that are carried out by complex networks of metabolically versatile microorganisms. In this Review, we summarize our current understanding of the microbial nitrogen-cycling network, including novel processes, their underlying biochemical pathways, the involved microorganisms, their environmental importance and industrial applications.
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              Stochastic Community Assembly: Does It Matter in Microbial Ecology?

              Understanding the mechanisms controlling community diversity, functions, succession, and biogeography is a central, but poorly understood, topic in ecology, particularly in microbial ecology. Although stochastic processes are believed to play nonnegligible roles in shaping community structure, their importance relative to deterministic processes is hotly debated. The importance of ecological stochasticity in shaping microbial community structure is far less appreciated. Some of the main reasons for such heavy debates are the difficulty in defining stochasticity and the diverse methods used for delineating stochasticity. Here, we provide a critical review and synthesis of data from the most recent studies on stochastic community assembly in microbial ecology. We then describe both stochastic and deterministic components embedded in various ecological processes, including selection, dispersal, diversification, and drift. We also describe different approaches for inferring stochasticity from observational diversity patterns and highlight experimental approaches for delineating ecological stochasticity in microbial communities. In addition, we highlight research challenges, gaps, and future directions for microbial community assembly research.
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                Author and article information

                Contributors
                jinrenni@pku.edu.cn
                Journal
                ISME J
                ISME J
                The ISME Journal
                Nature Publishing Group UK (London )
                1751-7362
                1751-7370
                18 June 2020
                18 June 2020
                October 2020
                : 14
                : 10
                : 2488-2504
                Affiliations
                [1 ]GRID grid.11135.37, ISNI 0000 0001 2256 9319, Key Laboratory of Water and Sediment Sciences, Ministry of Education, College of Environmental Sciences and Engineering, , Peking University, ; 100871 Beijing, China
                [2 ]GRID grid.11135.37, ISNI 0000 0001 2256 9319, Beijing Innovation Center for Engineering Science and Advanced Technology, , Peking University, ; 100871 Beijing, China
                [3 ]GRID grid.261049.8, ISNI 0000 0004 0645 4572, Key Laboratory of Regional Energy Systems Optimization, Resources and Environmental Research Academy, , North China Electric Power University, ; 102206 Beijing, China
                [4 ]GRID grid.262246.6, ISNI 0000 0004 1765 430X, State Key Laboratory of Plateau Ecology and Agriculture, , Qinghai University, ; 810016 Xining, China
                Author information
                http://orcid.org/0000-0002-9114-8347
                Article
                701
                10.1038/s41396-020-0701-8
                7490378
                32555502
                a8e5d3c4-329f-436f-a58f-25d49cd9924f
                © The Author(s) 2020

                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
                : 25 February 2020
                : 2 June 2020
                : 9 June 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001809, National Natural Science Foundation of China (National Science Foundation of China);
                Award ID: 91647211
                Award ID: 51721006
                Award ID: 91647211
                Award ID: 51721006
                Award ID: 91647211
                Award ID: 51721006
                Award ID: 91647211
                Award ID: 51721006
                Award ID: 91647211
                Award ID: 51721006
                Award ID: 91647211
                Award ID: 51721006
                Award ID: 91647211
                Award ID: 51721006
                Award ID: 91647211
                Award ID: 51721006
                Award Recipient :
                Categories
                Article
                Custom metadata
                © International Society for Microbial Ecology 2020

                Microbiology & Virology
                environmental sciences,biogeochemistry,ecology
                Microbiology & Virology
                environmental sciences, biogeochemistry, ecology

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