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 B 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 B 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^*

^*Corresponding author for this work

Aarhus University

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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/.

Original language	English
Journal	Nucleic Acids Research
Volume	51
Issue number	D1
Pages (from-to)	D603–D610
Number of pages	8
ISSN	0305-1048
DOIs	https://doi.org/10.1093/nar/gkac1049
Publication status	Published - 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, Z. L., van Santen, J. A., Selem-Mojica, N., Tørring, T., Zaroubi, L., Alanjary, M., Aleti, G., Aguilar, C., Al-Salihi, S. A. A., Augustijn, H. E., ... Medema, M. H. (2023). MIBiG 3.0: a community-driven effort to annotate experimentally validated biosynthetic gene clusters. Nucleic Acids Research, 51(D1), D603–D610. https://doi.org/10.1093/nar/gkac1049

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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/.",

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year = "2023",

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, vol. 51, no. D1, pp. D603–D610. https://doi.org/10.1093/nar/gkac1049

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 B

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

Y1 - 2023

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/.

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

ER -

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

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