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      High Diversity and Functional Potential of Undescribed “Acidobacteriota” in Danish Wastewater Treatment Plants

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          Abstract

          Microbial communities in water resource recovery facilities encompass a large diversity of poorly characterized lineages that could have undescribed process-critical functions. Recently, it was shown that taxa belonging to “Acidobacteriota” are abundant in Danish full-scale activated sludge wastewater treatment plants (WWTP), and here we investigated their diversity, distribution, and functional potential. “Acidobacteriota” taxa were identified using a comprehensive full-length 16S rRNA gene reference dataset and amplicon sequencing surveys across 37 WWTPs. Members of this phylum were diverse, belonging to 14 families, eight of which are completely uncharacterized and lack type strains. Several lineages were abundant, with relative abundances of up to 5% of the microbial community. Genome annotation and metabolic reconstruction of 50 high-quality “Acidobacteriota” metagenome-assembled genomes (MAGs) from 19 WWTPs showed high metabolic diversity and potential involvement in nitrogen and phosphorus removal and iron reduction. Fluorescence in situ hybridization (FISH) using newly-designed probes revealed cells with diverse morphologies, predominantly located inside activated sludge flocs. FISH in combination with Raman microspectroscopy revealed ecophysiological traits in probe-defined cells from the families Holophagaceae, Thermoanaerobaculaceae, and Vicinamibacteraceae, and families with the placeholder name of midas_f_502, midas_f_973, and midas_f_1548. Members of these lineages had the potential to be polyphosphate-accumulating organisms (PAOs) as intracellular storage was observed for the key compounds polyphosphate and glycogen.

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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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            IQ-TREE: A Fast and Effective Stochastic Algorithm for Estimating Maximum-Likelihood Phylogenies

            Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to find optimal trees, it is not clear whether the best tree is found. Thus, there is need for additional approaches that employ different search strategies to find ML trees and that are at the same time as fast as currently available ML programs. We show that a combination of hill-climbing approaches and a stochastic perturbation method can be time-efficiently implemented. If we allow the same CPU time as RAxML and PhyML, then our software IQ-TREE found higher likelihoods between 62.2% and 87.1% of the studied alignments, thus efficiently exploring the tree-space. If we use the IQ-TREE stopping rule, RAxML and PhyML are faster in 75.7% and 47.1% of the DNA alignments and 42.2% and 100% of the protein alignments, respectively. However, the range of obtaining higher likelihoods with IQ-TREE improves to 73.3-97.1%.
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              BEDTools: a flexible suite of utilities for comparing genomic features

              Motivation: Testing for correlations between different sets of genomic features is a fundamental task in genomics research. However, searching for overlaps between features with existing web-based methods is complicated by the massive datasets that are routinely produced with current sequencing technologies. Fast and flexible tools are therefore required to ask complex questions of these data in an efficient manner. Results: This article introduces a new software suite for the comparison, manipulation and annotation of genomic features in Browser Extensible Data (BED) and General Feature Format (GFF) format. BEDTools also supports the comparison of sequence alignments in BAM format to both BED and GFF features. The tools are extremely efficient and allow the user to compare large datasets (e.g. next-generation sequencing data) with both public and custom genome annotation tracks. BEDTools can be combined with one another as well as with standard UNIX commands, thus facilitating routine genomics tasks as well as pipelines that can quickly answer intricate questions of large genomic datasets. Availability and implementation: BEDTools was written in C++. Source code and a comprehensive user manual are freely available at http://code.google.com/p/bedtools Contact: aaronquinlan@gmail.com; imh4y@virginia.edu Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                22 April 2021
                2021
                : 12
                : 643950
                Affiliations
                Department of Chemistry and Bioscience, Center for Microbial Communities, Aalborg University , Aalborg, Denmark
                Author notes

                Edited by: Bärbel Ulrike Fösel, Helmholtz Zentrum München, Helmholtz-Gemeinschaft Deutscher Forschungszentren, Germany

                Reviewed by: Aharon Oren, Hebrew University of Jerusalem, Israel; Andreas Schramm, Aarhus University, Denmark

                *Correspondence: Per Halkjaer Nielsen, phn@ 123456bio.aau.dk

                Present address: Jannie Munk Kristensen, Division of Microbial Ecology, Center for Microbiology and Environmental Systems Science, University of Vienna, Vienna, Austria

                This article was submitted to Aquatic Microbiology, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2021.643950
                8100337
                33967982
                e1c60b51-f46a-4c3d-9388-00d9e8386b89
                Copyright © 2021 Kristensen, Singleton, Clegg, Petriglieri and Nielsen.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 19 December 2020
                : 29 March 2021
                Page count
                Figures: 6, Tables: 2, Equations: 0, References: 69, Pages: 14, Words: 0
                Funding
                Funded by: Villum Fonden 10.13039/100008398
                Funded by: Teknologi og Produktion, Det Frie Forskningsråd 10.13039/100008393
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                acidobacteriota,metagenomics,fish-probe design,mags,wastewater treatment plants

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