Computational Genomics of Specialized Metabolism: from Natural Product Discovery to Microbiome Ecology

ABSTRACT Microbial and plant specialized metabolites, also known as natural products, are key mediators of microbe-microbe and host-microbe interactions and constitute a rich resource for drug development. In the past decade, genome mining has emerged as a prominent strategy for natural product discovery. Initially, such mining was performed on the basis of individual microbial genome sequences. Now, these efforts are being scaled up to fully genome-sequenced strain collections, pangenomes of bacterial genera, and large sets of metagenome-assembled genomes from microbial communities. The Medema research group aims to play a leading role in these developments by developing and applying computational approaches to identify, classify, and prioritize specialized metabolite biosynthetic gene clusters and pathways and to connect them to specific molecules and microbiome-associated phenotypes. Moreover, we are extending the scope of genome mining from microbes to plants, which will allow more comprehensive interpretation of the chemical language between hosts and microbes in a microbiome setting.

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Genomic Assemblies of Members of Burkholderia and Related Genera as a Resource for Natural Product Discovery

Microbiology Resource Announcements ◽

10.1128/mra.00485-20 ◽

2020 ◽

Vol 9 (42) ◽

Author(s):

Alex J. Mullins ◽

Cerith Jones ◽

Matthew J. Bull ◽

Gordon Webster ◽

Julian Parkhill ◽

...

Keyword(s):

Natural Product ◽

Genome Mining ◽

Genomic Analysis ◽

Gene Clusters ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Natural Product Discovery

ABSTRACT The genomes of 450 members of Burkholderiaceae, isolated from clinical and environmental sources, were sequenced and assembled as a resource for genome mining. Genomic analysis of the collection has enabled the identification of multiple metabolites and their biosynthetic gene clusters, including the antibiotics gladiolin, icosalide A, enacyloxin, and cepacin A.

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BiG-SLiCE: A Highly Scalable Tool Maps the Diversity of 1.2 Million Biosynthetic Gene Clusters

10.1101/2020.08.17.240838 ◽

2020 ◽

Cited By ~ 3

Author(s):

Satria A. Kautsar ◽

Justin J. J. van der Hooft ◽

Dick de Ridder ◽

Marnix H. Medema

Keyword(s):

Natural Product ◽

Biological Activities ◽

Genome Mining ◽

Gene Clusters ◽

Genomic Diversity ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Microbial Genomes ◽

Natural Product Discovery ◽

User Friendly

AbstractBackgroundGenome mining for Biosynthetic Gene Clusters (BGCs) has become an integral part of natural product discovery. The >200,000 microbial genomes now publicly available hold information on abundant novel chemistry. One way to navigate this vast genomic diversity is through comparative analysis of homologous BGCs, which allows identification of cross-species patterns that can be matched to the presence of metabolites or biological activities. However, current tools suffer from a bottleneck caused by the expensive network-based approach used to group these BGCs into Gene Cluster Families (GCFs).ResultsHere, we introduce BiG-SLiCE, a tool designed to cluster massive numbers of BGCs. By representing them in Euclidean space, BiG-SLiCE can group BGCs into GCFs in a non-pairwise, near-linear fashion. We used BiG-SLiCE to analyze 1,225,071 BGCs collected from 209,206 publicly available microbial genomes and metagenome-assembled genomes (MAGs) within ten days on a typical 36-cores CPU server. We demonstrate the utility of such analyses by reconstructing a global map of secondary metabolic diversity across taxonomy to identify uncharted biosynthetic potential. BiG-SLiCE also provides a "query mode" that can efficiently place newly sequenced BGCs into previously computed GCFs, plus a powerful output visualization engine that facilitates user-friendly data exploration.ConclusionsBiG-SLiCE opens up new possibilities to accelerate natural product discovery and offers a first step towards constructing a global, searchable interconnected network of BGCs. As more genomes get sequenced from understudied taxa, more information can be mined to highlight their potentially novel chemistry. BiG-SLiCE is available via https://github.com/medema-group/bigslice.

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Synthetic Biology Advanced Natural Product Discovery

Metabolites ◽

10.3390/metabo11110785 ◽

2021 ◽

Vol 11 (11) ◽

pp. 785

Author(s):

Junyang Wang ◽

Jens Nielsen ◽

Zihe Liu

Keyword(s):

Natural Products ◽

Synthetic Biology ◽

Natural Product ◽

Rapid Development ◽

Genome Mining ◽

Gene Clusters ◽

Future Research ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Natural Product Discovery

A wide variety of bacteria, fungi and plants can produce bioactive secondary metabolites, which are often referred to as natural products. With the rapid development of DNA sequencing technology and bioinformatics, a large number of putative biosynthetic gene clusters have been reported. However, only a limited number of natural products have been discovered, as most biosynthetic gene clusters are not expressed or are expressed at extremely low levels under conventional laboratory conditions. With the rapid development of synthetic biology, advanced genome mining and engineering strategies have been reported and they provide new opportunities for discovery of natural products. This review discusses advances in recent years that can accelerate the design, build, test, and learn (DBTL) cycle of natural product discovery, and prospects trends and key challenges for future research directions.

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BiG-SLiCE: A highly scalable tool maps the diversity of 1.2 million biosynthetic gene clusters

GigaScience ◽

10.1093/gigascience/giaa154 ◽

2021 ◽

Vol 10 (1) ◽

Cited By ~ 1

Author(s):

Satria A Kautsar ◽

Justin J J van der Hooft ◽

Dick de Ridder ◽

Marnix H Medema

Keyword(s):

Natural Product ◽

Biological Activities ◽

Genome Mining ◽

Gene Clusters ◽

Genomic Diversity ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Microbial Genomes ◽

Natural Product Discovery ◽

User Friendly

Abstract Background Genome mining for biosynthetic gene clusters (BGCs) has become an integral part of natural product discovery. The >200,000 microbial genomes now publicly available hold information on abundant novel chemistry. One way to navigate this vast genomic diversity is through comparative analysis of homologous BGCs, which allows identification of cross-species patterns that can be matched to the presence of metabolites or biological activities. However, current tools are hindered by a bottleneck caused by the expensive network-based approach used to group these BGCs into gene cluster families (GCFs). Results Here, we introduce BiG-SLiCE, a tool designed to cluster massive numbers of BGCs. By representing them in Euclidean space, BiG-SLiCE can group BGCs into GCFs in a non-pairwise, near-linear fashion. We used BiG-SLiCE to analyze 1,225,071 BGCs collected from 209,206 publicly available microbial genomes and metagenome-assembled genomes within 10 days on a typical 36-core CPU server. We demonstrate the utility of such analyses by reconstructing a global map of secondary metabolic diversity across taxonomy to identify uncharted biosynthetic potential. BiG-SLiCE also provides a “query mode” that can efficiently place newly sequenced BGCs into previously computed GCFs, plus a powerful output visualization engine that facilitates user-friendly data exploration. Conclusions BiG-SLiCE opens up new possibilities to accelerate natural product discovery and offers a first step towards constructing a global and searchable interconnected network of BGCs. As more genomes are sequenced from understudied taxa, more information can be mined to highlight their potentially novel chemistry. BiG-SLiCE is available via https://github.com/medema-group/bigslice.

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The Tripod for Bacterial Natural Product Discovery: Genome Mining, Silent Pathway Induction, and Mass Spectrometry-Based Molecular Networking

mSystems ◽

10.1128/msystems.00160-17 ◽

2018 ◽

Vol 3 (2) ◽

Cited By ~ 14

Author(s):

Daniela B. B. Trivella ◽

Rafael de Felicio

Keyword(s):

Mass Spectrometry ◽

Natural Products ◽

Natural Product ◽

Biosynthetic Pathway ◽

Genome Mining ◽

Chemical Compounds ◽

Gene Clusters ◽

Tandem Mass ◽

Molecular Networking ◽

Natural Product Discovery

ABSTRACT Natural products are the richest source of chemical compounds for drug discovery. Particularly, bacterial secondary metabolites are in the spotlight due to advances in genome sequencing and mining, as well as for the potential of biosynthetic pathway manipulation to awake silent (cryptic) gene clusters under laboratory cultivation. Further progress in compound detection, such as the development of the tandem mass spectrometry (MS/MS) molecular networking approach, has contributed to the discovery of novel bacterial natural products. The latter can be applied directly to bacterial crude extracts for identifying and dereplicating known compounds, therefore assisting the prioritization of extracts containing novel natural products, for example. In our opinion, these three approaches—genome mining, silent pathway induction, and MS-based molecular networking—compose the tripod for modern bacterial natural product discovery and will be discussed in this perspective.

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An Update on Molecular Tools for Genetic Engineering of Actinomycetes—The Source of Important Antibiotics and Other Valuable Compounds

Antibiotics ◽

10.3390/antibiotics9080494 ◽

2020 ◽

Vol 9 (8) ◽

pp. 494

Author(s):

Lena Mitousis ◽

Yvonne Thoma ◽

Ewa M. Musiol-Kroll

Keyword(s):

Genetic Engineering ◽

Genome Mining ◽

Gene Clusters ◽

Biosynthetic Gene ◽

Molecular Tools ◽

Biosynthetic Gene Clusters ◽

Streptomyces Antibioticus ◽

The Past ◽

Bioactive Agents ◽

Valuable Compounds

The first antibiotic-producing actinomycete (Streptomyces antibioticus) was described by Waksman and Woodruff in 1940. This discovery initiated the “actinomycetes era”, in which several species were identified and demonstrated to be a great source of bioactive compounds. However, the remarkable group of microorganisms and their potential for the production of bioactive agents were only partially exploited. This is caused by the fact that the growth of many actinomycetes cannot be reproduced on artificial media at laboratory conditions. In addition, sequencing, genome mining and bioactivity screening disclosed that numerous biosynthetic gene clusters (BGCs), encoded in actinomycetes genomes are not expressed and thus, the respective potential products remain uncharacterized. Therefore, a lot of effort was put into the development of technologies that facilitate the access to actinomycetes genomes and activation of their biosynthetic pathways. In this review, we mainly focus on molecular tools and methods for genetic engineering of actinomycetes that have emerged in the field in the past five years (2015–2020). In addition, we highlight examples of successful application of the recently developed technologies in genetic engineering of actinomycetes for activation and/or improvement of the biosynthesis of secondary metabolites.

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Recent advances in the genome mining of Aspergillus secondary metabolites (covering 2012–2018)

MedChemComm ◽

10.1039/c9md00054b ◽

2019 ◽

Vol 10 (6) ◽

pp. 840-866 ◽

Cited By ~ 16

Author(s):

Jillian Romsdahl ◽

Clay C. C. Wang

Keyword(s):

Aspergillus Terreus ◽

Genome Mining ◽

Gene Clusters ◽

Genetic Identification ◽

Biosynthetic Pathways ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

The Past ◽

Made In

This review covers advances made in genome mining SMs produced by Aspergillus nidulans, Aspergillus fumigatus, Aspergillus niger, and Aspergillus terreus in the past six years (2012–2018). Genetic identification and molecular characterization of SM biosynthetic gene clusters, along with proposed biosynthetic pathways, is discussed in depth.

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Native and engineered promoters in natural product discovery

Natural Product Reports ◽

10.1039/c6np00002a ◽

2016 ◽

Vol 33 (8) ◽

pp. 1006-1019 ◽

Cited By ~ 45

Author(s):

Maksym Myronovskyi ◽

Andriy Luzhetskyy

Keyword(s):

Natural Product ◽

Transcriptional Activation ◽

Gene Clusters ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Natural Product Discovery

Transcriptional activation of biosynthetic gene clusters.

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Discovery and characterisation of an amidine-containing ribosomally-synthesised peptide that is widely distributed in nature

Chemical Science ◽

10.1039/d1sc01456k ◽

2021 ◽

Author(s):

Alicia H Russell ◽

Natalia Miguel Vior ◽

Edward Steven Hems ◽

Rodney Lacret ◽

Andrew William Truman

Keyword(s):

Natural Product ◽

Genome Mining ◽

Gene Clusters ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Wide Range ◽

Modified Peptides

Ribosomally synthesised and post-translationally modified peptides (RiPPs) are a structurally diverse class of natural product with a wide range of bioactivities. Genome mining for RiPP biosynthetic gene clusters (BGCs) is...

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