IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites

ABSTRACT In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.g...

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Autores principales:	Michalis Hadjithomas, I-Min Amy Chen, Ken Chu, Anna Ratner, Krishna Palaniappan, Ernest Szeto, Jinghua Huang, T. B. K. Reddy, Peter Cimermančič, Michael A. Fischbach, Natalia N. Ivanova, Victor M. Markowitz, Nikos C. Kyrpides, Amrita Pati
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2015
Materias:	Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/af361eacc5134f4c8014f632c2e40e70
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spelling	oai:doaj.org-article:af361eacc5134f4c8014f632c2e40e702021-11-15T15:41:26ZIMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites10.1128/mBio.00932-152150-7511https://doaj.org/article/af361eacc5134f4c8014f632c2e40e702015-09-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mBio.00932-15https://doaj.org/toc/2150-7511ABSTRACT In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of “big” genomic data for discovering small molecules. IMG-ABC relies on IMG's comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC's focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in Alphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMPORTANCE IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG's extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world.Michalis HadjithomasI-Min Amy ChenKen ChuAnna RatnerKrishna PalaniappanErnest SzetoJinghua HuangT. B. K. ReddyPeter CimermančičMichael A. FischbachNatalia N. IvanovaVictor M. MarkowitzNikos C. KyrpidesAmrita PatiAmerican Society for MicrobiologyarticleMicrobiologyQR1-502ENmBio, Vol 6, Iss 4 (2015)
institution	DOAJ
collection	DOAJ
language	EN
topic	Microbiology QR1-502
spellingShingle	Microbiology QR1-502 Michalis Hadjithomas I-Min Amy Chen Ken Chu Anna Ratner Krishna Palaniappan Ernest Szeto Jinghua Huang T. B. K. Reddy Peter Cimermančič Michael A. Fischbach Natalia N. Ivanova Victor M. Markowitz Nikos C. Kyrpides Amrita Pati IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites
description	ABSTRACT In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of “big” genomic data for discovering small molecules. IMG-ABC relies on IMG's comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC's focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in Alphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMPORTANCE IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG's extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world.
format	article
author	Michalis Hadjithomas I-Min Amy Chen Ken Chu Anna Ratner Krishna Palaniappan Ernest Szeto Jinghua Huang T. B. K. Reddy Peter Cimermančič Michael A. Fischbach Natalia N. Ivanova Victor M. Markowitz Nikos C. Kyrpides Amrita Pati
author_facet	Michalis Hadjithomas I-Min Amy Chen Ken Chu Anna Ratner Krishna Palaniappan Ernest Szeto Jinghua Huang T. B. K. Reddy Peter Cimermančič Michael A. Fischbach Natalia N. Ivanova Victor M. Markowitz Nikos C. Kyrpides Amrita Pati
author_sort	Michalis Hadjithomas
title	IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites
title_short	IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites
title_full	IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites
title_fullStr	IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites
title_full_unstemmed	IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites
title_sort	img-abc: a knowledge base to fuel discovery of biosynthetic gene clusters and novel secondary metabolites
publisher	American Society for Microbiology
publishDate	2015
url	https://doaj.org/article/af361eacc5134f4c8014f632c2e40e70
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IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites

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