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      Charting the complexity of the activated sludge microbiome through a hybrid sequencing strategy

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          Abstract

          Background

          Long-read sequencing has shown its tremendous potential to address genome assembly challenges, e.g., achieving the first telomere-to-telomere assembly of a gapless human chromosome. However, many issues remain unresolved when leveraging error-prone long reads to characterize high-complexity metagenomes, for instance, complete/high-quality genome reconstruction from highly complex systems.

          Results

          Here, we developed an iterative haplotype-resolved hierarchical clustering-based hybrid assembly (HCBHA) approach that capitalizes on a hybrid (error-prone long reads and high-accuracy short reads) sequencing strategy to reconstruct (near-) complete genomes from highly complex metagenomes. Using the HCBHA approach, we first phase short and long reads from the highly complex metagenomic dataset into different candidate bacterial haplotypes, then perform hybrid assembly of each bacterial genome individually. We reconstructed 557 metagenome-assembled genomes (MAGs) with an average N50 of 574 Kb from a deeply sequenced, highly complex activated sludge (AS) metagenome. These high-contiguity MAGs contained 14 closed genomes and 111 high-quality (HQ) MAGs including full-length rRNA operons, which accounted for 61.1% of the microbial community. Leveraging the near-complete genomes, we also profiled the metabolic potential of the AS microbiome and identified 2153 biosynthetic gene clusters (BGCs) encoded within the recovered AS MAGs.

          Conclusion

          Our results established the feasibility of an iterative haplotype-resolved HCBHA approach to reconstruct (near-) complete genomes from highly complex ecosystems, providing new insights into “complete metagenomics”. The retrieved high-contiguity MAGs illustrated that various biosynthetic gene clusters (BGCs) were harbored in the AS microbiome. The high diversity of BGCs highlights the potential to discover new natural products biosynthesized by the AS microbial community, aside from the traditional function (e.g., organic carbon and nitrogen removal) in wastewater treatment.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s40168-021-01155-1.

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          Most cited references60

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          Prokka: rapid prokaryotic genome annotation.

          T Seemann (2014)
          The multiplex capability and high yield of current day DNA-sequencing instruments has made bacterial whole genome sequencing a routine affair. The subsequent de novo assembly of reads into contigs has been well addressed. The final step of annotating all relevant genomic features on those contigs can be achieved slowly using existing web- and email-based systems, but these are not applicable for sensitive data or integrating into computational pipelines. Here we introduce Prokka, a command line software tool to fully annotate a draft bacterial genome in about 10 min on a typical desktop computer. It produces standards-compliant output files for further analysis or viewing in genome browsers. Prokka is implemented in Perl and is freely available under an open source GPLv2 license from http://vicbioinformatics.com/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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            CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes

            Large-scale recovery of genomes from isolates, single cells, and metagenomic data has been made possible by advances in computational methods and substantial reductions in sequencing costs. Although this increasing breadth of draft genomes is providing key information regarding the evolutionary and functional diversity of microbial life, it has become impractical to finish all available reference genomes. Making robust biological inferences from draft genomes requires accurate estimates of their completeness and contamination. Current methods for assessing genome quality are ad hoc and generally make use of a limited number of “marker” genes conserved across all bacterial or archaeal genomes. Here we introduce CheckM, an automated method for assessing the quality of a genome using a broader set of marker genes specific to the position of a genome within a reference genome tree and information about the collocation of these genes. We demonstrate the effectiveness of CheckM using synthetic data and a wide range of isolate-, single-cell-, and metagenome-derived genomes. CheckM is shown to provide accurate estimates of genome completeness and contamination and to outperform existing approaches. Using CheckM, we identify a diverse range of errors currently impacting publicly available isolate genomes and demonstrate that genomes obtained from single cells and metagenomic data vary substantially in quality. In order to facilitate the use of draft genomes, we propose an objective measure of genome quality that can be used to select genomes suitable for specific gene- and genome-centric analyses of microbial communities.
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              QUAST: quality assessment tool for genome assemblies.

              Limitations of genome sequencing techniques have led to dozens of assembly algorithms, none of which is perfect. A number of methods for comparing assemblers have been developed, but none is yet a recognized benchmark. Further, most existing methods for comparing assemblies are only applicable to new assemblies of finished genomes; the problem of evaluating assemblies of previously unsequenced species has not been adequately considered. Here, we present QUAST-a quality assessment tool for evaluating and comparing genome assemblies. This tool improves on leading assembly comparison software with new ideas and quality metrics. QUAST can evaluate assemblies both with a reference genome, as well as without a reference. QUAST produces many reports, summary tables and plots to help scientists in their research and in their publications. In this study, we used QUAST to compare several genome assemblers on three datasets. QUAST tables and plots for all of them are available in the Supplementary Material, and interactive versions of these reports are on the QUAST website. http://bioinf.spbau.ru/quast . Supplementary data are available at Bioinformatics online.
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                Author and article information

                Contributors
                liulei94@foxmail.com
                yulinwang605@gmail.com
                elly.yu.yang@gmail.com
                wangdp@grandomics.com
                wonderland@cuhk.edu.hk
                zhengcm@sustech.edu.cn
                zhangt@hku.hk
                Journal
                Microbiome
                Microbiome
                Microbiome
                BioMed Central (London )
                2049-2618
                15 October 2021
                15 October 2021
                2021
                : 9
                : 205
                Affiliations
                [1 ]GRID grid.194645.b, ISNI 0000000121742757, Environmental Microbiome Engineering and Biotechnology Laboratory, , The University of Hong Kong, ; Hong Kong SAR, China
                [2 ]GRID grid.263817.9, ISNI 0000 0004 1773 1790, State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, , Southern University of Science and Technology, ; Shenzhen, China
                [3 ]GRID grid.263817.9, ISNI 0000 0004 1773 1790, School of Environmental Science and Engineering, , Southern University of Science and Technology, ; Shenzhen, China
                [4 ]GRID grid.459813.2, Nextomics Biosciences Institute, ; Wuhan, China
                [5 ]GRID grid.10784.3a, ISNI 0000 0004 1937 0482, Department of Chemical Pathology, , The Chinese University of Hong Kong, ; Hong Kong SAR, China
                Author information
                http://orcid.org/0000-0003-1148-4322
                Article
                1155
                10.1186/s40168-021-01155-1
                8518188
                34649602
                76d27b56-3597-4922-810b-5df67021f425
                © 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/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 12 May 2021
                : 1 September 2021
                Funding
                Funded by: university grants committee
                Award ID: GRF17206120
                Award Recipient :
                Funded by: National Natural Science of Foundation of China
                Award ID: 41890852
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                long-read metagenomics,nanopore long reads,complete genomes,highly complex metagenomes,activated sludge microbiome,haplotype-resolved

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