RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor
RAVEN is a commonly used MATLAB toolbox for genome-scale metabolic model (GEM) reconstruction, curation and constraint-based modelling and simulation. Here we present RAVEN Toolbox 2.0 with major enhancements, including: (i) de novo reconstruction of GEMs based on the MetaCyc pathway database; (ii)...
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description | RAVEN is a commonly used MATLAB toolbox for genome-scale metabolic model (GEM) reconstruction, curation and constraint-based modelling and simulation. Here we present RAVEN Toolbox 2.0 with major enhancements, including: (i) de novo reconstruction of GEMs based on the MetaCyc pathway database; (ii) a redesigned KEGG-based reconstruction pipeline; (iii) convergence of reconstructions from various sources; (iv) improved performance, usability, and compatibility with the COBRA Toolbox. Capabilities of RAVEN 2.0 are here illustrated through de novo reconstruction of GEMs for the antibiotic-producing bacterium Streptomyces coelicolor. Comparison of the automated de novo reconstructions with the iMK1208 model, a previously published high-quality S. coelicolor GEM, exemplifies that RAVEN 2.0 can capture most of the manually curated model. The generated de novo reconstruction is subsequently used to curate iMK1208 resulting in Sco4, the most comprehensive GEM of S. coelicolor, with increased coverage of both primary and secondary metabolism. This increased coverage allows the use of Sco4 to predict novel genome editing targets for optimized secondary metabolites production. As such, we demonstrate that RAVEN 2.0 can be used not only for de novo GEM reconstruction, but also for curating existing models based on up-to-date databases. Both RAVEN 2.0 and Sco4 are distributed through GitHub to facilitate usage and further development by the community (https://github.com/SysBioChalmers/RAVEN and https://github.com/SysBioChalmers/Streptomyces_coelicolor-GEM). |
doi_str_mv | 10.1371/journal.pcbi.1006541 |
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Here we present RAVEN Toolbox 2.0 with major enhancements, including: (i) de novo reconstruction of GEMs based on the MetaCyc pathway database; (ii) a redesigned KEGG-based reconstruction pipeline; (iii) convergence of reconstructions from various sources; (iv) improved performance, usability, and compatibility with the COBRA Toolbox. Capabilities of RAVEN 2.0 are here illustrated through de novo reconstruction of GEMs for the antibiotic-producing bacterium Streptomyces coelicolor. Comparison of the automated de novo reconstructions with the iMK1208 model, a previously published high-quality S. coelicolor GEM, exemplifies that RAVEN 2.0 can capture most of the manually curated model. The generated de novo reconstruction is subsequently used to curate iMK1208 resulting in Sco4, the most comprehensive GEM of S. coelicolor, with increased coverage of both primary and secondary metabolism. This increased coverage allows the use of Sco4 to predict novel genome editing targets for optimized secondary metabolites production. As such, we demonstrate that RAVEN 2.0 can be used not only for de novo GEM reconstruction, but also for curating existing models based on up-to-date databases. Both RAVEN 2.0 and Sco4 are distributed through GitHub to facilitate usage and further development by the community (https://github.com/SysBioChalmers/RAVEN and https://github.com/SysBioChalmers/Streptomyces_coelicolor-GEM).</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1006541</identifier><identifier>PMID: 30335785</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Antibiotics ; Automation ; Bioengineering ; Bioinformatics ; Biologi ; Biological Sciences ; Biology ; Biology and Life Sciences ; Biosynthesis ; Computational Biology - methods ; Computer and Information Sciences ; Computer Simulation ; Constraint modelling ; Databases, Genetic ; Engineering ; Gems ; Gene amplification ; Gene Editing ; Genome editing ; Genomes ; Genomics ; Metabolic networks ; Metabolic Networks and Pathways - genetics ; Metabolism ; Metabolites ; Models, Genetic ; Quality ; Reconstruction ; Research and Analysis Methods ; Secondary metabolites ; Software ; Streptomyces coelicolor ; Streptomyces coelicolor - genetics ; Streptomyces coelicolor - metabolism</subject><ispartof>PLoS computational biology, 2018-10, Vol.14 (10), p.e1006541-e1006541</ispartof><rights>2018 Wang et al. 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This increased coverage allows the use of Sco4 to predict novel genome editing targets for optimized secondary metabolites production. As such, we demonstrate that RAVEN 2.0 can be used not only for de novo GEM reconstruction, but also for curating existing models based on up-to-date databases. 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genetics</subject><subject>Metabolism</subject><subject>Metabolites</subject><subject>Models, Genetic</subject><subject>Quality</subject><subject>Reconstruction</subject><subject>Research and Analysis Methods</subject><subject>Secondary metabolites</subject><subject>Software</subject><subject>Streptomyces coelicolor</subject><subject>Streptomyces coelicolor - genetics</subject><subject>Streptomyces coelicolor - metabolism</subject><issn>1553-7358</issn><issn>1553-734X</issn><issn>1553-7358</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>D8T</sourceid><sourceid>DOA</sourceid><recordid>eNp1Ul1vEzEQPCEQLYV_gMASL7wk-PscHpCiqkClCiQKvFpr315y4XIOtq8l_x6HpFWLQH6wtZ6Z3R1NVT1ndMpEzd6swhgH6Kcb77opo1QryR5Ux0wpMamFMg_vvI-qJymtKC3PmX5cHQkqhKqNOq7Cl_n3s0-ET-lbMidXGBPkrkeSQ-hd-EXaEMkaM7jQd54MmK9D_EEi-jCkHEefuzAQGBoCxENCkvLYbEmpXeaImxzWW4-J-ICFHvoQn1aPWugTPjvcJ9W392dfTz9OLj5_OD-dX0y8ljRPmFfeNd4wPWsZMwwEgnS0oZK2NTUNZ7J2TFPKABtwhmELLbZouFHaGSlOqpd73U0fkj14lSznimrBNdcFcb5HNAFWdhO7NcStDdDZP4UQFxZi7nyPlgIVTkmPraul9n7G61rxWhhXDp_tul3utdI1bkZ3Ty1iQoh-af0S-nUx2Ca0unbegQbrtZlZyTlYkMJYJVyjPKKRLRbVyX9VF-PGltJi3KmVUTjjBf_usPPo1th4HHKE_h7t_s_QLe0iXFnNaVHYrfH6IBDDzxFTtusueex7GDCMxb3SpOaGS1qgr_6C_ttjuUf5GFKK2N4Ow6jdpfiGZXcptocUF9qLu4vckm5iK34Dn2zyHg</recordid><startdate>20181001</startdate><enddate>20181001</enddate><creator>Wang, Hao</creator><creator>Marcišauskas, Simonas</creator><creator>Sánchez, Benjamín J</creator><creator>Domenzain, Iván</creator><creator>Hermansson, Daniel</creator><creator>Agren, Rasmus</creator><creator>Nielsen, Jens</creator><creator>Kerkhoven, Eduard J</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QO</scope><scope>7QP</scope><scope>7TK</scope><scope>7TM</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>K9.</scope><scope>LK8</scope><scope>M0N</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>ADTPV</scope><scope>AOWAS</scope><scope>F1U</scope><scope>ABBSD</scope><scope>D8T</scope><scope>F1S</scope><scope>ZZAVC</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-7475-0136</orcidid><orcidid>https://orcid.org/0000-0002-3593-5792</orcidid><orcidid>https://orcid.org/0000-0002-9955-6003</orcidid><orcidid>https://orcid.org/0000-0001-6093-4110</orcidid><orcidid>https://orcid.org/0000-0003-0770-6383</orcidid><orcidid>https://orcid.org/0000-0002-5322-2040</orcidid></search><sort><creationdate>20181001</creationdate><title>RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor</title><author>Wang, Hao ; Marcišauskas, Simonas ; Sánchez, Benjamín J ; Domenzain, Iván ; Hermansson, Daniel ; Agren, Rasmus ; Nielsen, Jens ; Kerkhoven, Eduard J</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c640t-1c5cbdc8169f1181a3ea4b0d040f708d2147b16001aedab81efafefe82856b843</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Antibiotics</topic><topic>Automation</topic><topic>Bioengineering</topic><topic>Bioinformatics</topic><topic>Biologi</topic><topic>Biological Sciences</topic><topic>Biology</topic><topic>Biology and Life Sciences</topic><topic>Biosynthesis</topic><topic>Computational Biology - methods</topic><topic>Computer and Information Sciences</topic><topic>Computer Simulation</topic><topic>Constraint modelling</topic><topic>Databases, Genetic</topic><topic>Engineering</topic><topic>Gems</topic><topic>Gene amplification</topic><topic>Gene Editing</topic><topic>Genome editing</topic><topic>Genomes</topic><topic>Genomics</topic><topic>Metabolic networks</topic><topic>Metabolic Networks and Pathways - genetics</topic><topic>Metabolism</topic><topic>Metabolites</topic><topic>Models, Genetic</topic><topic>Quality</topic><topic>Reconstruction</topic><topic>Research and Analysis Methods</topic><topic>Secondary metabolites</topic><topic>Software</topic><topic>Streptomyces coelicolor</topic><topic>Streptomyces coelicolor - genetics</topic><topic>Streptomyces coelicolor - metabolism</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Hao</creatorcontrib><creatorcontrib>Marcišauskas, Simonas</creatorcontrib><creatorcontrib>Sánchez, Benjamín J</creatorcontrib><creatorcontrib>Domenzain, Iván</creatorcontrib><creatorcontrib>Hermansson, Daniel</creatorcontrib><creatorcontrib>Agren, Rasmus</creatorcontrib><creatorcontrib>Nielsen, Jens</creatorcontrib><creatorcontrib>Kerkhoven, Eduard J</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Computing Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Biological Science Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - 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Here we present RAVEN Toolbox 2.0 with major enhancements, including: (i) de novo reconstruction of GEMs based on the MetaCyc pathway database; (ii) a redesigned KEGG-based reconstruction pipeline; (iii) convergence of reconstructions from various sources; (iv) improved performance, usability, and compatibility with the COBRA Toolbox. Capabilities of RAVEN 2.0 are here illustrated through de novo reconstruction of GEMs for the antibiotic-producing bacterium Streptomyces coelicolor. Comparison of the automated de novo reconstructions with the iMK1208 model, a previously published high-quality S. coelicolor GEM, exemplifies that RAVEN 2.0 can capture most of the manually curated model. The generated de novo reconstruction is subsequently used to curate iMK1208 resulting in Sco4, the most comprehensive GEM of S. coelicolor, with increased coverage of both primary and secondary metabolism. This increased coverage allows the use of Sco4 to predict novel genome editing targets for optimized secondary metabolites production. As such, we demonstrate that RAVEN 2.0 can be used not only for de novo GEM reconstruction, but also for curating existing models based on up-to-date databases. Both RAVEN 2.0 and Sco4 are distributed through GitHub to facilitate usage and further development by the community (https://github.com/SysBioChalmers/RAVEN and https://github.com/SysBioChalmers/Streptomyces_coelicolor-GEM).</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>30335785</pmid><doi>10.1371/journal.pcbi.1006541</doi><orcidid>https://orcid.org/0000-0001-7475-0136</orcidid><orcidid>https://orcid.org/0000-0002-3593-5792</orcidid><orcidid>https://orcid.org/0000-0002-9955-6003</orcidid><orcidid>https://orcid.org/0000-0001-6093-4110</orcidid><orcidid>https://orcid.org/0000-0003-0770-6383</orcidid><orcidid>https://orcid.org/0000-0002-5322-2040</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Antibiotics Automation Bioengineering Bioinformatics Biologi Biological Sciences Biology Biology and Life Sciences Biosynthesis Computational Biology - methods Computer and Information Sciences Computer Simulation Constraint modelling Databases, Genetic Engineering Gems Gene amplification Gene Editing Genome editing Genomes Genomics Metabolic networks Metabolic Networks and Pathways - genetics Metabolism Metabolites Models, Genetic Quality Reconstruction Research and Analysis Methods Secondary metabolites Software Streptomyces coelicolor Streptomyces coelicolor - genetics Streptomyces coelicolor - metabolism |
title | RAVEN 2.0: A versatile toolbox for metabolic network reconstruction and a case study on Streptomyces coelicolor |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-05T05%3A42%3A21IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=RAVEN%202.0:%20A%20versatile%20toolbox%20for%20metabolic%20network%20reconstruction%20and%20a%20case%20study%20on%20Streptomyces%20coelicolor&rft.jtitle=PLoS%20computational%20biology&rft.au=Wang,%20Hao&rft.date=2018-10-01&rft.volume=14&rft.issue=10&rft.spage=e1006541&rft.epage=e1006541&rft.pages=e1006541-e1006541&rft.issn=1553-7358&rft.eissn=1553-7358&rft_id=info:doi/10.1371/journal.pcbi.1006541&rft_dat=%3Cproquest_plos_%3E2250632626%3C/proquest_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2250632626&rft_id=info:pmid/30335785&rft_doaj_id=oai_doaj_org_article_0a03b54cefb746cc927752738b8b8294&rfr_iscdi=true |