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      Complete Genome Sequence of Methylosinus sp. Strain C49, a Methane-Oxidizing Bacterium Harboring phaABC Genes for Polyhydroxyalkanoate Synthesis

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          Abstract

          We report a complete genome sequence of Methylosinus sp. strain C49, a methane-oxidizing bacterium (MOB) in the class Alphaproteobacteria, isolated from MOB-enriched biomass. The genome encodes the functional genes for methane oxidation ( pmoA) and polyhydroxyalkanoate (PHA) biosynthesis ( phaABC). Deciphering the genome will help research toward PHA production by MOB.

          ABSTRACT

          We report a complete genome sequence of Methylosinus sp. strain C49, a methane-oxidizing bacterium (MOB) in the class Alphaproteobacteria, isolated from MOB-enriched biomass. The genome encodes the functional genes for methane oxidation ( pmoA) and polyhydroxyalkanoate (PHA) biosynthesis ( phaABC). Deciphering the genome will help research toward PHA production by MOB.

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          KofamKOALA: KEGG Ortholog assignment based on profile HMM and adaptive score threshold

          Takuya Aramaki, Romain Blanc-Mathieu, Hisashi Endo … (2019)
          Abstract Summary KofamKOALA is a web server to assign KEGG Orthologs (KOs) to protein sequences by homology search against a database of profile hidden Markov models (KOfam) with pre-computed adaptive score thresholds. KofamKOALA is faster than existing KO assignment tools with its accuracy being comparable to the best performing tools. Function annotation by KofamKOALA helps linking genes to KEGG resources such as the KEGG pathway maps and facilitates molecular network reconstruction. Availability and implementation KofamKOALA, KofamScan and KOfam are freely available from GenomeNet (https://www.genome.jp/tools/kofamkoala/). Supplementary information Supplementary data are available at Bioinformatics online.
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            Performance of neural network basecalling tools for Oxford Nanopore sequencing

            Ryan Wick, Louise Judd, Kathryn E. Holt (2019)
            Background Basecalling, the computational process of translating raw electrical signal to nucleotide sequence, is of critical importance to the sequencing platforms produced by Oxford Nanopore Technologies (ONT). Here, we examine the performance of different basecalling tools, looking at accuracy at the level of bases within individual reads and at majority-rule consensus basecalls in an assembly. We also investigate some additional aspects of basecalling: training using a taxon-specific dataset, using a larger neural network model and improving consensus basecalls in an assembly by additional signal-level analysis with Nanopolish. Results Training basecallers on taxon-specific data results in a significant boost in consensus accuracy, mostly due to the reduction of errors in methylation motifs. A larger neural network is able to improve both read and consensus accuracy, but at a cost to speed. Improving consensus sequences (‘polishing’) with Nanopolish somewhat negates the accuracy differences in basecallers, but pre-polish accuracy does have an effect on post-polish accuracy. Conclusions Basecalling accuracy has seen significant improvements over the last 2 years. The current version of ONT’s Guppy basecaller performs well overall, with good accuracy and fast performance. If higher accuracy is required, users should consider producing a custom model using a larger neural network and/or training data from the same species. Electronic supplementary material The online version of this article (10.1186/s13059-019-1727-y) contains supplementary material, which is available to authorized users.
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              Enrichment, isolation and some properties of methane-utilizing bacteria.

              R Whittenbury, K. Phillips, J. Wilkinson (1970)
              Article 0 comments Cited 261 times – based on 0 reviews     Review now
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                Author and article information

                Contributors
                J. Cameron Thrash: Role: Editor
                Journal
                Journal ID (nlm-ta): Microbiol Resour Announc
                Journal ID (iso-abbrev): Microbiol Resour Announc
                Journal ID (hwp): ga
                Journal ID (pmc): mra
                Journal ID (publisher-id): MRA
                Title: Microbiology Resource Announcements
                Publisher: American Society for Microbiology (1752 N St., N.W., Washington, DC )
                ISSN (Electronic): 2576-098X
                Publication date (Electronic): 2 July 2020
                Publication date Collection: July 2020
                Volume: 9
                Issue: 27
                Electronic Location Identifier: e00113-20
                Affiliations
                [a ]Department of Chemical Engineering, Tokyo University of Agriculture and Technology, Koganei, Tokyo, Japan
                [b ]Global Innovation Research Institute, Tokyo University of Agriculture and Technology, Fuchu, Tokyo, Japan
                University of Southern California
                Author notes
                Address correspondence to Toshikazu Suenaga, suenagat@ 123456go.tuat.ac.jp , or Akihiko Terada, akte@ 123456cc.tuat.ac.jp .

                Citation Yasuda S, Suenaga T, Terada A. 2020. Complete genome sequence of Methylosinus sp. strain C49, a methane-oxidizing bacterium harboring phaABC genes for polyhydroxyalkanoate synthesis. Microbiol Resour Announc 9:e00113-20. https://doi.org/10.1128/MRA.00113-20.

                Author information
                https://orcid.org/0000-0002-9258-6912
                Article
                Publisher ID: MRA00113-20
                DOI: 10.1128/MRA.00113-20
                PMC ID: 7330232
                PubMed ID: 32616630
                SO-VID: b81bd571-9dbc-4281-b4fc-20098d9b28b2
                Copyright © Copyright © 2020 Yasuda et al.
                License:

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

                History
                Date received : 5 February 2020
                Date accepted : 7 June 2020
                Page count
                Figures: 1, Tables: 1, Equations: 0, References: 13, Pages: 3, Words: 1571
                Funding
                Funded by: MEXT | Japan Society for the Promotion of Science (JSPS), https://doi.org/10.13039/501100001691;
                Award ID: 17H01893
                Award Recipient :
                Funded by: MEXT | Japan Society for the Promotion of Science (JSPS), https://doi.org/10.13039/501100001691;
                Award ID: 19K21555
                Award Recipient :
                Funded by: Tokyo University of Agriculture and Technology (TUAT), https://doi.org/10.13039/501100009518;
                Award Recipient :
                Categories
                Subject: Genome Sequences
                Custom metadata
                cover-date July 2020

                Data availability:

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