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In silico genome mining provides easy access to secondary metabolite biosynthetic gene clusters (BGCs) encoding the biosynthesis of many bioactive compounds, which are the basis for many important drugs used in human medicine. However, the association between BGCs and other functions encoded in the genomes of producers have remained elusive. Here, we present a systems biology workflow that integrates genome mining with a detailed pangenome analysis for detecting genes associated with a particular BGC. We analyzed 3,889 enterobacterial genomes and found 13,266 BGCs, represented by 252 distinct BGC families and 347 additional singletons. A pangenome analysis revealed 88 genes putatively associated with a specific BGC coding for the colon cancer-related colibactin that code for diverse metabolic and regulatory functions. The presented workflow opens up the possibility to discover novel secondary metabolites, better understand their physiological roles, and provides a guide to identify and analyze BGC associated gene sets. [ABSTRACT FROM AUTHOR]

Many drugs are derived from small molecules produced by microorganisms and plants, so-called natural products. Natural products have diverse chemical structures, but the biosynthetic pathways producing those compounds are often organized as biosynthetic gene clusters (BGCs) and follow a highly conserved biosynthetic logic. This allows for the identification of core biosynthetic enzymes using genome mining strategies that are based on the sequence similarity of the involved enzymes/genes. However, mining for a variety of BGCs quickly approaches a complexity level where manual analyses are no longer possible and require the use of automated genome mining pipelines, such as the antiSMASH software. In this review, we discuss the principles underlying the predictions of antiSMASH and other tools and provide practical advice for their application. Furthermore, we discuss important caveats such as rule-based BGC detection, sequence and annotation quality and cluster boundary prediction, which all have to be considered while planning for, performing and analyzing the results of genome mining studies. [ABSTRACT FROM AUTHOR]

Actinomycetes are excellent sources for novel bioactive compounds, which serve as potential drug candidates for antibiotics development. While industrial efforts to find and develop novel antimicrobials have been severely reduced during the past two decades, the increasing threat of multidrug-resistant pathogens and the development of new technologies to find and produce such compounds have again attracted interest in this field. Based on improvements in whole-genome sequencing, novel methods have been developed to identify the secondary metabolite biosynthetic gene clusters by genome mining, to clone them, and to express them in heterologous hosts in much higher throughput than before. These technologies now enable metabolic engineering approaches to optimize production yields and to directly manipulate the pathways to generate modified products. [ABSTRACT FROM AUTHOR]

Actinomycetes are one of the most valuable sources of natural products with industrial and medicinal importance. After more than half a century of exploitation, it has become increasingly challenging to find novel natural products with useful properties as the same known compounds are often repeatedly re-discovered when using traditional approaches. Modern genome mining approaches have led to the discovery of new biosynthetic gene clusters, thus indicating that actinomycetes still harbor a huge unexploited potential to produce novel natural products. In recent years, innovative synthetic biology and metabolic engineering tools have greatly accelerated the discovery of new natural products and the engineering of actinomycetes. In the first part of this review, we outline the successful application of metabolic engineering to optimize natural product production, focusing on the use of multi-omics data, genome-scale metabolic models, rational approaches to balance precursor pools, and the engineering of regulatory genes and regulatory elements. In the second part, we summarize the recent advances of synthetic biology for actinomycetal metabolic engineering including cluster assembly, cloning and expression, CRISPR/Cas9 technologies, and chassis strain development for natural product overproduction and discovery. Finally, we describe new advances in reprogramming biosynthetic pathways through polyketide synthase and non-ribosomal peptide synthetase engineering. These new developments are expected to revitalize discovery and development of new natural products with medicinal and other industrial applications. [ABSTRACT FROM AUTHOR]

We report the complete genome sequence of Amycolatopsis japonica MG417-CF17 T (=DSM 44213 T ) which was identified as the producer of ( S , S )- N , N ′-ethylenediaminedisuccinic acid during a screening for phospholipase C inhibitors. The genome of A. japonica MG417-CF17 T consists of two replicons: the chromosome (8,961,318 bp, 68.89% G + C content) and the plasmid pAmyja1 (92,539 bp, 68.23% G + C content), encoding a total of 8422 protein coding genes. Analysis of the sequence data revealed 30 clusters encoding the biosynthesis of secondary metabolites. [ABSTRACT FROM AUTHOR]