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

2020 ◽  
Vol 9 (42) ◽  
Author(s):  
Alex J. Mullins ◽  
Cerith Jones ◽  
Matthew J. Bull ◽  
Gordon Webster ◽  
Julian Parkhill ◽  
...  

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.

Author(s):  
Satria A. Kautsar ◽  
Justin J. J. van der Hooft ◽  
Dick de Ridder ◽  
Marnix H. Medema

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.


Metabolites ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 785
Author(s):  
Junyang Wang ◽  
Jens Nielsen ◽  
Zihe Liu

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.


GigaScience ◽  
2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Satria A Kautsar ◽  
Justin J J van der Hooft ◽  
Dick de Ridder ◽  
Marnix H Medema

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.


2019 ◽  
Vol 116 (40) ◽  
pp. 19805-19814 ◽  
Author(s):  
Zachary L. Reitz ◽  
Clifford D. Hardy ◽  
Jaewon Suk ◽  
Jean Bouvet ◽  
Alison Butler

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.


2016 ◽  
Vol 33 (8) ◽  
pp. 1006-1019 ◽  
Author(s):  
Maksym Myronovskyi ◽  
Andriy Luzhetskyy

Transcriptional activation of biosynthetic gene clusters.


2021 ◽  
Author(s):  
Alicia H Russell ◽  
Natalia Miguel Vior ◽  
Edward Steven Hems ◽  
Rodney Lacret ◽  
Andrew William Truman

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...


2020 ◽  
Author(s):  
Alicia H. Russell ◽  
Natalia M. Vior ◽  
Edward S. Hems ◽  
Rodney Lacret ◽  
Andrew W. Truman

ABSTRACTRibosomally synthesised and post-translationally modified peptides (RiPPs) are a structurally diverse class of natural product with a range of bioactivities. Genome mining for RiPP biosynthetic gene clusters (BGCs) is often hampered by poor detection of the short precursor peptides that are ultimately modified into the final molecule. Here, we utilise a previously described genome mining tool, RiPPER, to identify novel RiPP precursor peptides near YcaO-domain proteins, enzymes that catalyse various RiPP post-translational modifications including heterocyclisation and thioamidation. Using this dataset, we identified a novel, diverse and highly conserved family of RiPP BGCs spanning over 230 species of Actinobacteria and Firmicutes. A representative BGC from Streptomyces albus J1074 was characterised, leading to the discovery of streptamidine, a novel-amidine containing RiPP. This highlights the breadth of unexplored natural products with structurally rare features, even in model organisms.


Antibiotics ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 133 ◽  
Author(s):  
Saibin Zhu ◽  
Yanwen Duan ◽  
Yong Huang

Microbial natural product drug discovery and development has entered a new era, driven by microbial genomics and synthetic biology. Genome sequencing has revealed the vast potential to produce valuable secondary metabolites in bacteria and fungi. However, many of the biosynthetic gene clusters are silent under standard fermentation conditions. By rational screening for mutations in bacterial ribosomal proteins or RNA polymerases, ribosome engineering is a versatile approach to obtain mutants with improved titers for microbial product formation or new natural products through activating silent biosynthetic gene clusters. In this review, we discuss the mechanism of ribosome engineering and its application to natural product discovery and yield improvement in Streptomyces. Our analysis suggests that ribosome engineering is a rapid and cost-effective approach and could be adapted to speed up the discovery and development of natural product drug leads in the post-genomic era.


mBio ◽  
2019 ◽  
Vol 10 (4) ◽  
Author(s):  
Loïc Martinet ◽  
Aymeric Naômé ◽  
Benoit Deflandre ◽  
Marta Maciejewska ◽  
Déborah Tellatin ◽  
...  

ABSTRACT Biosynthetic gene clusters (BGCs) are organized groups of genes involved in the production of specialized metabolites. Typically, one BGC is responsible for the production of one or several similar compounds with bioactivities that usually only vary in terms of strength and/or specificity. Here we show that the previously described ferroverdins and bagremycins, which are families of metabolites with different bioactivities, are produced from the same BGC, whereby the fate of the biosynthetic pathway depends on iron availability. Under conditions of iron depletion, the monomeric bagremycins are formed, representing amino-aromatic antibiotics resulting from the condensation of 3-amino-4-hydroxybenzoic acid with p-vinylphenol. Conversely, when iron is abundantly available, the biosynthetic pathway additionally produces a molecule based on p-vinylphenyl-3-nitroso-4-hydroxybenzoate, which complexes iron to form the trimeric ferroverdins that have anticholesterol activity. Thus, our work shows a unique exception to the concept that BGCs should only produce a single family of molecules with one type of bioactivity and that in fact different bioactive molecules may be produced depending on the environmental conditions. IMPORTANCE Access to whole-genome sequences has exposed the general incidence of the so-called cryptic biosynthetic gene clusters (BGCs), thereby renewing their interest for natural product discovery. As a consequence, genome mining is the often first approach implemented to assess the potential of a microorganism for producing novel bioactive metabolites. By revealing a new level of complexity of natural product biosynthesis, we further illustrate the difficulty of estimation of the panel of molecules associated with a BGC based on genomic information alone. Indeed, we found that the same gene cluster is responsible for the production of compounds which differ in terms of structure and bioactivity. The production of these different compounds responds to different environmental triggers, which suggests that multiplication of culture conditions is essential for revealing the entire panel of molecules made by a single BGC.


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