MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters

Barbara R Terlouw; Kai Blin; Jorge C Navarro-Muñoz; Nicole E Avalon; Marc G Chevrette; Susan Egbert; Sanghoon Lee; David Meijer; Michael J J Recchia; Zachary L Reitz; Jeffrey A van Santen; Nelly Selem-Mojica; Thomas Tørring; Liana Zaroubi; Mohammad Alanjary; Gajender Aleti; César Aguilar; Suhad A A Al-Salihi; Hannah E Augustijn; J Abraham Avelar-Rivas; Luis A Avitia-Domínguez; Francisco Barona-Gómez; Jordan Bernaldo-Agüero; Vincent A Bielinski; Friederike Biermann; Thomas J Booth; Victor J Carrion Bravo; Raquel Castelo-Branco; Fernanda O Chagas; Pablo Cruz-Morales; Chao Du; Katherine R Duncan; Athina Gavriilidou; Damien Gayrard; Karina Gutiérrez-García; Kristina Haslinger; Eric J N Helfrich; Justin J J van der Hooft; Afif P Jati; Edward Kalkreuter; Nikolaos Kalyvas; Kyo Bin Kang; Satria Kautsar; Wonyong Kim; Aditya M Kunjapur; Yong-Xin Li; Geng-Min Lin; Catarina Loureiro; Joris J R Louwen; Nico L L Louwen; George Lund; Jonathan Parra; Benjamin Philmus; Bita Pourmohsenin; Lotte J U Pronk; Adriana Rego; Devasahayam Arokia Balaya Rex; Serina Robinson; L Rodrigo Rosas-Becerra; Eve T Roxborough; Michelle A Schorn; Darren J Scobie; Kumar Saurabh Singh; Nika Sokolova; Xiaoyu Tang; Daniel Udwary; Aruna Vigneshwari; Kristiina Vind; Sophie P J M Vromans; Valentin Waschulin; Sam E Williams; Jaclyn M Winter; Thomas E Witte; Huali Xie; Dong Yang; Jingwei Yu; Mitja Zdouc; Zheng Zhong; Jérôme Collemare; Roger G Linington; Tilmann Weber; Marnix H Medema

doi:10.1093/nar/gkac1049

MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters

Barbara R Terlouw, Kai Blin, Jorge C Navarro-Muñoz, Nicole E Avalon, Marc G Chevrette, Susan Egbert, Sanghoon Lee, David Meijer, Michael J J Recchia, Zachary L Reitz, Jeffrey A van Santen, Nelly Selem-Mojica, Thomas Tørring, Liana Zaroubi, Mohammad Alanjary, Gajender Aleti, César Aguilar, Suhad A A Al-Salihi, Hannah E Augustijn, J Abraham Avelar-RivasLuis A Avitia-Domínguez, Francisco Barona-Gómez, Jordan Bernaldo-Agüero, Vincent A Bielinski, Friederike Biermann, Thomas J Booth, Victor J Carrion Bravo, Raquel Castelo-Branco, Fernanda O Chagas, Pablo Cruz-Morales, Chao Du, Katherine R Duncan, Athina Gavriilidou, Damien Gayrard, Karina Gutiérrez-García, Kristina Haslinger, Eric J N Helfrich, Justin J J van der Hooft, Afif P Jati, Edward Kalkreuter, Nikolaos Kalyvas, Kyo Bin Kang, Satria Kautsar, Wonyong Kim, Aditya M Kunjapur, Yong-Xin Li, Geng-Min Lin, Catarina Loureiro, Joris J R Louwen, Nico L L Louwen, George Lund, Jonathan Parra, Benjamin Philmus, Bita Pourmohsenin, Lotte J U Pronk, Adriana Rego, Devasahayam Arokia Balaya Rex, Serina Robinson, L Rodrigo Rosas-Becerra, Eve T Roxborough, Michelle A Schorn, Darren J Scobie, Kumar Saurabh Singh, Nika Sokolova, Xiaoyu Tang, Daniel Udwary, Aruna Vigneshwari, Kristiina Vind, Sophie P J M Vromans, Valentin Waschulin, Sam E Williams, Jaclyn M Winter, Thomas E Witte, Huali Xie, Dong Yang, Jingwei Yu, Mitja Zdouc, Zheng Zhong, Jérôme Collemare, Roger G Linington, Tilmann Weber, Marnix H Medema

Institut for Bio- og Kemiteknologi - Industrial Biotechnology - Gustav Wieds Vej 10D

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review

267 Citationer (Scopus)

Abstract

With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.

Originalsprog	Engelsk
Artikelnummer	gkac1049
Tidsskrift	Nucleic Acids Research
Vol/bind	51
Nummer	D1
Sider (fra-til)	D603-D610
Antal sider	8
ISSN	0305-1048
DOI	https://doi.org/10.1093/nar/gkac1049
Status	Udgivet - jan. 2023

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Terlouw, B. R., Blin, K., Navarro-Muñoz, J. C., Avalon, N. E., Chevrette, M. G., Egbert, S., Lee, S., Meijer, D., Recchia, M. J. J., Reitz, ZL., van Santen, JA., Selem-Mojica, N., Tørring, T., Zaroubi, L., Alanjary, M., Aleti, G., Aguilar, C., Al-Salihi, S. A. A., Augustijn, HE., ... Medema, MH. (2023). MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters. Nucleic Acids Research, 51(D1), D603-D610. Artikel gkac1049. https://doi.org/10.1093/nar/gkac1049

@article{236ca9a57fdb4308b6eab9a15b5d0adf,

title = "MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters",

abstract = "With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.",

keywords = "Biosynthetic Pathways/genetics, Genome, Genomics, Multigene Family",

author = "Terlouw, \{Barbara R\} and Kai Blin and Navarro-Mu{\~n}oz, \{Jorge C\} and Avalon, \{Nicole E\} and Chevrette, \{Marc G\} and Susan Egbert and Sanghoon Lee and David Meijer and Recchia, \{Michael J J\} and Zachary L Reitz and Jeffrey A van Santen and Nelly Selem-Mojica and Thomas T{\o}rring and Liana Zaroubi and Mohammad Alanjary and Gajender Aleti and C{\'e}sar Aguilar and Al-Salihi, \{Suhad A A\} and Hannah E Augustijn and J Abraham Avelar-Rivas and Luis A Avitia-Dom{\'i}nguez and Francisco Barona-G{\'o}mez and Jordan Bernaldo-Ag{\"u}ero and Bielinski, \{Vincent A\} and Friederike Biermann and Thomas J Booth and Victor J Carrion Bravo and Raquel Castelo-Branco and Fernanda O Chagas and Pablo Cruz-Morales and Chao Du and Katherine R Duncan and Athina Gavriilidou and Damien Gayrard and Karina Guti{\'e}rrez-Garc{\'i}a and Kristina Haslinger and Helfrich, \{Eric J N\} and van der Hooft, \{Justin J J\} and Afif P Jati and Edward Kalkreuter and Nikolaos Kalyvas and Kyo Bin Kang and Satria Kautsar and Wonyong Kim and Aditya M Kunjapur and Yong-Xin Li and Geng-Min Lin and Catarina Loureiro and Louwen, \{Joris J R\} and Louwen, \{Nico L L\} and George Lund and Jonathan Parra and Benjamin Philmus and Bita Pourmohsenin and Pronk, \{Lotte J U\} and Adriana Rego and Devasahayam Arokia Balaya Rex and Serina Robinson and L Rodrigo Rosas-Becerra and Eve T Roxborough and Michelle A Schorn and Darren J Scobie and Kumar Saurabh Singh and Nika Sokolova and Xiaoyu Tang and Daniel Udwary and Aruna Vigneshwari and Kristiina Vind and Vromans, \{Sophie P J M\} and Valentin Waschulin and Sam E Williams and Jaclyn M Winter and Thomas E Witte and Huali Xie and Dong Yang and Jingwei Yu and Mitja Zdouc and Zheng Zhong and J{\'e}r{\^o}me Collemare and Roger G Linington and Tilmann Weber and Marnix H Medema",

year = "2023",

month = jan,

doi = "10.1093/nar/gkac1049",

language = "English",

volume = "51",

pages = "D603--D610",

journal = "Nucleic Acids Research",

issn = "0305-1048",

publisher = "Oxford University Press",

number = "D1",

}

Terlouw, BR, Blin, K, Navarro-Muñoz, JC, Avalon, NE, Chevrette, MG, Egbert, S, Lee, S, Meijer, D, Recchia, MJJ, Reitz, ZL, van Santen, JA, Selem-Mojica, N, Tørring, T, Zaroubi, L, Alanjary, M, Aleti, G, Aguilar, C, Al-Salihi, SAA, Augustijn, HE, Avelar-Rivas, JA, Avitia-Domínguez, LA, Barona-Gómez, F, Bernaldo-Agüero, J, Bielinski, VA, Biermann, F, Booth, TJ, Carrion Bravo, VJ, Castelo-Branco, R, Chagas, FO, Cruz-Morales, P, Du, C, Duncan, KR, Gavriilidou, A, Gayrard, D, Gutiérrez-García, K, Haslinger, K, Helfrich, EJN, van der Hooft, JJJ, Jati, AP, Kalkreuter, E, Kalyvas, N, Kang, KB, Kautsar, S, Kim, W, Kunjapur, AM, Li, Y-X, Lin, G-M, Loureiro, C, Louwen, JJR, Louwen, NLL, Lund, G, Parra, J, Philmus, B, Pourmohsenin, B, Pronk, LJU, Rego, A, Rex, DAB, Robinson, S, Rosas-Becerra, LR, Roxborough, ET, Schorn, MA, Scobie, DJ, Singh, KS, Sokolova, N, Tang, X, Udwary, D, Vigneshwari, A, Vind, K, Vromans, SPJM, Waschulin, V, Williams, SE, Winter, JM, Witte, TE, Xie, H, Yang, D, Yu, J, Zdouc, M, Zhong, Z, Collemare, J, Linington, RG, Weber, T & Medema, MH 2023, 'MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters', Nucleic Acids Research, bind 51, nr. D1, gkac1049, s. D603-D610. https://doi.org/10.1093/nar/gkac1049

MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters. / Terlouw, Barbara R; Blin, Kai; Navarro-Muñoz, Jorge C et al.
I: Nucleic Acids Research, Bind 51, Nr. D1, gkac1049, 01.2023, s. D603-D610.

Publikation: Bidrag til tidsskrift/Konferencebidrag i tidsskrift /Bidrag til avis › Tidsskriftartikel › Forskning › peer review

TY - JOUR

T1 - MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters

AU - Terlouw, Barbara R

AU - Blin, Kai

AU - Navarro-Muñoz, Jorge C

AU - Avalon, Nicole E

AU - Chevrette, Marc G

AU - Egbert, Susan

AU - Lee, Sanghoon

AU - Meijer, David

AU - Recchia, Michael J J

AU - Reitz, Zachary L

AU - van Santen, Jeffrey A

AU - Selem-Mojica, Nelly

AU - Tørring, Thomas

AU - Zaroubi, Liana

AU - Alanjary, Mohammad

AU - Aleti, Gajender

AU - Aguilar, César

AU - Al-Salihi, Suhad A A

AU - Augustijn, Hannah E

AU - Avelar-Rivas, J Abraham

AU - Avitia-Domínguez, Luis A

AU - Barona-Gómez, Francisco

AU - Bernaldo-Agüero, Jordan

AU - Bielinski, Vincent A

AU - Biermann, Friederike

AU - Booth, Thomas J

AU - Carrion Bravo, Victor J

AU - Castelo-Branco, Raquel

AU - Chagas, Fernanda O

AU - Cruz-Morales, Pablo

AU - Du, Chao

AU - Duncan, Katherine R

AU - Gavriilidou, Athina

AU - Gayrard, Damien

AU - Gutiérrez-García, Karina

AU - Haslinger, Kristina

AU - Helfrich, Eric J N

AU - van der Hooft, Justin J J

AU - Jati, Afif P

AU - Kalkreuter, Edward

AU - Kalyvas, Nikolaos

AU - Kang, Kyo Bin

AU - Kautsar, Satria

AU - Kim, Wonyong

AU - Kunjapur, Aditya M

AU - Li, Yong-Xin

AU - Lin, Geng-Min

AU - Loureiro, Catarina

AU - Louwen, Joris J R

AU - Louwen, Nico L L

AU - Lund, George

AU - Parra, Jonathan

AU - Philmus, Benjamin

AU - Pourmohsenin, Bita

AU - Pronk, Lotte J U

AU - Rego, Adriana

AU - Rex, Devasahayam Arokia Balaya

AU - Robinson, Serina

AU - Rosas-Becerra, L Rodrigo

AU - Roxborough, Eve T

AU - Schorn, Michelle A

AU - Scobie, Darren J

AU - Singh, Kumar Saurabh

AU - Sokolova, Nika

AU - Tang, Xiaoyu

AU - Udwary, Daniel

AU - Vigneshwari, Aruna

AU - Vind, Kristiina

AU - Vromans, Sophie P J M

AU - Waschulin, Valentin

AU - Williams, Sam E

AU - Winter, Jaclyn M

AU - Witte, Thomas E

AU - Xie, Huali

AU - Yang, Dong

AU - Yu, Jingwei

AU - Zdouc, Mitja

AU - Zhong, Zheng

AU - Collemare, Jérôme

AU - Linington, Roger G

AU - Weber, Tilmann

AU - Medema, Marnix H

PY - 2023/1

Y1 - 2023/1

N2 - With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.

AB - With an ever-increasing amount of (meta)genomic data being deposited in sequence databases, (meta)genome mining for natural product biosynthetic pathways occupies a critical role in the discovery of novel pharmaceutical drugs, crop protection agents and biomaterials. The genes that encode these pathways are often organised into biosynthetic gene clusters (BGCs). In 2015, we defined the Minimum Information about a Biosynthetic Gene cluster (MIBiG): a standardised data format that describes the minimally required information to uniquely characterise a BGC. We simultaneously constructed an accompanying online database of BGCs, which has since been widely used by the community as a reference dataset for BGCs and was expanded to 2021 entries in 2019 (MIBiG 2.0). Here, we describe MIBiG 3.0, a database update comprising large-scale validation and re-annotation of existing entries and 661 new entries. Particular attention was paid to the annotation of compound structures and biological activities, as well as protein domain selectivities. Together, these new features keep the database up-to-date, and will provide new opportunities for the scientific community to use its freely available data, e.g. for the training of new machine learning models to predict sequence-structure-function relationships for diverse natural products. MIBiG 3.0 is accessible online at https://mibig.secondarymetabolites.org/.

KW - Biosynthetic Pathways/genetics

KW - Genome

KW - Genomics

KW - Multigene Family

UR - https://www.scopus.com/pages/publications/85146851279

U2 - 10.1093/nar/gkac1049

DO - 10.1093/nar/gkac1049

M3 - Journal article

C2 - 36399496

SN - 0305-1048

VL - 51

SP - D603-D610

JO - Nucleic Acids Research

JF - Nucleic Acids Research

IS - D1

M1 - gkac1049

ER -