PlantiSMASH: automated identification, annotation and expression analysis of plant biosynthetic gene clusters

ABSTRACTPlant specialized metabolites are chemically highly diverse, play key roles in host-microbe interactions, have important nutritional value in crops and are frequently applied as medicines. It has recently become clear that plant biosynthetic pathway-encoding genes are sometimes densely clustered in specific genomic loci: biosynthetic gene clusters (BGCs). Here, we introduce plantiSMASH, a versatile online analysis platform that automates the identification of candidate plant BGCs. Moreover, it allows integration of transcriptomic data to prioritize candidate BGCs based on the coexpression patterns of predicted biosynthetic enzyme-coding genes, and facilitates comparative genomic analysis to study the evolutionary conservation of each cluster. Applied on 48 high-quality plant genomes, plantiSMASH identifies a rich diversity of candidate plant BGCs. These results will guide further experimental exploration of the nature and dynamics of gene clustering in plant metabolism. Moreover, spurred by the continuing decrease in costs of plant genome sequencing, they will allow genome mining technologies to be applied to plant natural product discovery.The plantiSMASH web server, precalculated results and source code are freely available from http://plantismash.secondarymetabolites.org.

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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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Genomic analysis of siderophore β-hydroxylases reveals divergent stereocontrol and expands the condensation domain family

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1903161116 ◽

2019 ◽

Vol 116 (40) ◽

pp. 19805-19814 ◽

Cited By ~ 8

Author(s):

Zachary L. Reitz ◽

Clifford D. Hardy ◽

Jaewon Suk ◽

Jean Bouvet ◽

Alison Butler

Keyword(s):

Predictive Power ◽

Genome Mining ◽

Genomic Analysis ◽

Gene Clusters ◽

Biosynthetic Gene Cluster ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Peptide Synthetase ◽

Condensation Domain

Genome mining of biosynthetic pathways streamlines discovery of secondary metabolites but can leave ambiguities in the predicted structures, which must be rectified experimentally. Through coupling the reactivity predicted by biosynthetic gene clusters with verified structures, the origin of the β-hydroxyaspartic acid diastereomers in siderophores is reported herein. Two functional subtypes of nonheme Fe(II)/α-ketoglutarate–dependent aspartyl β-hydroxylases are identified in siderophore biosynthetic gene clusters, which differ in genomic organization—existing either as fused domains (IβHAsp) at the carboxyl terminus of a nonribosomal peptide synthetase (NRPS) or as stand-alone enzymes (TβHAsp)—and each directs opposite stereoselectivity of Asp β-hydroxylation. The predictive power of this subtype delineation is confirmed by the stereochemical characterization of β-OHAsp residues in pyoverdine GB-1, delftibactin, histicorrugatin, and cupriachelin. The l-threo (2S, 3S) β-OHAsp residues of alterobactin arise from hydroxylation by the β-hydroxylase domain integrated into NRPS AltH, while l-erythro (2S, 3R) β-OHAsp in delftibactin arises from the stand-alone β-hydroxylase DelD. Cupriachelin contains both l-threo and l-erythro β-OHAsp, consistent with the presence of both types of β-hydroxylases in the biosynthetic gene cluster. A third subtype of nonheme Fe(II)/α-ketoglutarate–dependent enzymes (IβHHis) hydroxylates histidyl residues with l-threo stereospecificity. A previously undescribed, noncanonical member of the NRPS condensation domain superfamily is identified, named the interface domain, which is proposed to position the β-hydroxylase and the NRPS-bound amino acid prior to hydroxylation. Through mapping characterized β-OHAsp diastereomers to the phylogenetic tree of siderophore β-hydroxylases, methods to predict β-OHAsp stereochemistry in silico are realized.

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Expanding the Natural Products Heterologous Expression Repertoire in the Model Cyanobacterium Anabaena sp. Strain PCC 7120: Production of Pendolmycin and Teleocidin B-4

10.26434/chemrxiv.11316098.v1 ◽

2019 ◽

Cited By ~ 1

Author(s):

Patrick Videau ◽

Kaitlyn Wells ◽

Arun Singh ◽

Jessie Eiting ◽

Philip Proteau ◽

...

Keyword(s):

Natural Products ◽

Genome Mining ◽

Gene Clusters ◽

Combinatorial Biosynthesis ◽

Test Case ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Cyanobacterium Anabaena ◽

Anabaena Sp ◽

Pcc 7120

Cyanobacteria are prolific producers of natural products and genome mining has shown that many orphan biosynthetic gene clusters can be found in sequenced cyanobacterial genomes. New tools and methodologies are required to investigate these biosynthetic gene clusters and here we present the use of <i>Anabaena </i>sp. strain PCC 7120 as a host for combinatorial biosynthesis of natural products using the indolactam natural products (lyngbyatoxin A, pendolmycin, and teleocidin B-4) as a test case. We were able to successfully produce all three compounds using codon optimized genes from Actinobacteria. We also introduce a new plasmid backbone based on the native <i>Anabaena</i>7120 plasmid pCC7120ζ and show that production of teleocidin B-4 can be accomplished using a two-plasmid system, which can be introduced by co-conjugation.

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Discovery of Unusual Cyanobacterial Tryptophan-containing Anabaenopeptins by MS/MS Based Molecular Networking

10.20944/preprints202007.0562.v1 ◽

2020 ◽

Author(s):

Subhasish Saha ◽

Germana Esposito ◽

Petra Urajova ◽

Jan Mareš ◽

Daniela Ewe ◽

...

Keyword(s):

Multidisciplinary Approach ◽

Spectroscopic Analysis ◽

Chemical Space ◽

Genome Mining ◽

Gc Content ◽

Gene Clusters ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Hela Cell Lines ◽

Bioactive Secondary Metabolites

Heterocytous cyanobacteria are among the most prolific source of bioactive secondary metabolites, including anabaenopeptins (APTs). A terrestrial filamentous Brasilonema sp. CT11 collected in Costa Rica bamboo forest, as black mat was studied using a multidisciplinary approach: genome mining and HPLC-HRMS/MS coupled with bionformatic analyses. Herein, we report the nearly complete genome consisting 8.79 Mbp with a GC content of 42.4%. Moreover, we report on three novel tryptophane-containing APTs; anabaenopeptin 788 (1), anabaenopeptin 802 (2) and anabaenopeptin 816 (3). Further, the structure of two homologues, i.e., anabaenopeptin 802 (2a) and anabaenopeptin 802 (2b) was determined by spectroscopic analysis (NMR and MS). Both compounds were shown to exert weak to moderate antiproliferative activity against HeLa cell lines. This study also provides the unique and diverse potential of biosynthetic gene clusters and an assessment of the predicted chemical space yet to be discovered from this genus.

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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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antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters

Nucleic Acids Research ◽

10.1093/nar/gkv437 ◽

2015 ◽

Vol 43 (W1) ◽

pp. W237-W243 ◽

Cited By ~ 1265

Author(s):

Tilmann Weber ◽

Kai Blin ◽

Srikanth Duddela ◽

Daniel Krug ◽

Hyun Uk Kim ◽

...

Keyword(s):

Genome Mining ◽

Gene Clusters ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters

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Functional Genome Mining for Metabolites Encoded by Large Gene Clusters through Heterologous Expression of a Whole-Genome Bacterial Artificial Chromosome Library in Streptomyces spp.

Applied and Environmental Microbiology ◽

10.1128/aem.01383-16 ◽

2016 ◽

Vol 82 (19) ◽

pp. 5795-5805 ◽

Cited By ~ 31

Author(s):

Min Xu ◽

Yemin Wang ◽

Zhilong Zhao ◽

Guixi Gao ◽

Sheng-Xiong Huang ◽

...

Keyword(s):

Heterologous Expression ◽

Genome Mining ◽

Gene Clusters ◽

Artificial Chromosome ◽

Functional Screening ◽

Biosynthetic Pathways ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Content Type ◽

Bac Libraries

ABSTRACTGenome sequencing projects in the last decade revealed numerous cryptic biosynthetic pathways for unknown secondary metabolites in microbes, revitalizing drug discovery from microbial metabolites by approaches called genome mining. In this work, we developed a heterologous expression and functional screening approach for genome mining from genomic bacterial artificial chromosome (BAC) libraries inStreptomycesspp. We demonstrate mining from a strain ofStreptomyces rochei, which is known to produce streptothricins and borrelidin, by expressing its BAC library in the surrogate hostStreptomyces lividansSBT5, and screening for antimicrobial activity. In addition to the successful capture of the streptothricin and borrelidin biosynthetic gene clusters, we discovered two novel linear lipopeptides and their corresponding biosynthetic gene cluster, as well as a novel cryptic gene cluster for an unknown antibiotic fromS. rochei. This high-throughput functional genome mining approach can be easily applied to other streptomycetes, and it is very suitable for the large-scale screening of genomic BAC libraries for bioactive natural products and the corresponding biosynthetic pathways.IMPORTANCEMicrobial genomes encode numerous cryptic biosynthetic gene clusters for unknown small metabolites with potential biological activities. Several genome mining approaches have been developed to activate and bring these cryptic metabolites to biological tests for future drug discovery. Previous sequence-guided procedures relied on bioinformatic analysis to predict potentially interesting biosynthetic gene clusters. In this study, we describe an efficient approach based on heterologous expression and functional screening of a whole-genome library for the mining of bioactive metabolites fromStreptomyces. The usefulness of this function-driven approach was demonstrated by the capture of four large biosynthetic gene clusters for metabolites of various chemical types, including streptothricins, borrelidin, two novel lipopeptides, and one unknown antibiotic fromStreptomyces rocheiSal35. The transfer, expression, and screening of the library were all performed in a high-throughput way, so that this approach is scalable and adaptable to industrial automation for next-generation antibiotic discovery.

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Whole-genome sequence of bioactive streptomycete derived from mangrove forest in Malaysia, Streptomyces sp. MUSC 14

Progress In Microbes & Molecular Biology ◽

10.36877/pmmb.a0000195 ◽

2021 ◽

Vol 4 (1) ◽

Author(s):

Hooi-Leng Ser ◽

Loh Teng-Hern Tan ◽

Wen-Si Tan ◽

Wai-Fong Yin ◽

Kok-Gan Chan

Keyword(s):

East Coast ◽

Genetic Manipulation ◽

Genome Mining ◽

Gene Clusters ◽

Peninsular Malaysia ◽

Whole Genome Sequence ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Streptomyces Sp ◽

A Genome

The contribution of streptomycetes to human health is undeniably important and significant, given that these filamentous microbes can produce interesting compounds that can be used to cure deadly infections and even cancer. Isolated from the east coast of Peninsular Malaysia, Streptomyces sp. MUSC 14 has shown significant antioxidant capacity. The current study explores the genomic potential of MUSC 14 via a genome mining approach. The genome size of MUSC 14 is 10,274,825 bp with G + C content of 71.3 %. AntiSMASH analysis revealed a total of nine biosynthetic gene clusters (with more than 80 % similarities to known gene clusters). This information serves as an important foundation for subsequent studies, particularly the purification and isolation of bioactive compounds by genetic manipulation techniques.

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Activation and Identification of a Griseusin Cluster in Streptomyces sp. CA-256286 by Employing Transcriptional Regulators and Multi-Omics Methods

Molecules ◽

10.3390/molecules26216580 ◽

2021 ◽

Vol 26 (21) ◽

pp. 6580

Author(s):

Charlotte Beck ◽

Tetiana Gren ◽

Francisco Javier Ortiz-López ◽

Tue Sparholt Jørgensen ◽

Daniel Carretero-Molina ◽

...

Keyword(s):

Biosynthetic Pathway ◽

Genome Mining ◽

Gene Clusters ◽

Transcriptional Regulators ◽

Biosynthetic Gene ◽

Biosynthetic Gene Clusters ◽

Heterologous Host ◽

Streptomyces Sp ◽

Identification And Characterization

Streptomyces are well-known producers of a range of different secondary metabolites, including antibiotics and other bioactive compounds. Recently, it has been demonstrated that “silent” biosynthetic gene clusters (BGCs) can be activated by heterologously expressing transcriptional regulators from other BGCs. Here, we have activated a silent BGC in Streptomyces sp. CA-256286 by overexpression of a set of SARP family transcriptional regulators. The structure of the produced compound was elucidated by NMR and found to be an N-acetyl cysteine adduct of the pyranonaphtoquinone polyketide 3′-O-α-d-forosaminyl-(+)-griseusin A. Employing a combination of multi-omics and metabolic engineering techniques, we identified the responsible BGC. These methods include genome mining, proteomics and transcriptomics analyses, in combination with CRISPR induced gene inactivations and expression of the BGC in a heterologous host strain. This work demonstrates an easy-to-implement workflow of how silent BGCs can be activated, followed by the identification and characterization of the produced compound, the responsible BGC, and hints of its biosynthetic pathway.

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