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To accelerate the shift to bio-based production and overcome complicated functional implementation of natural and artificial biosynthetic pathways to industry relevant organisms, development of new, versatile, bio-based production platforms is required. Here we present a novel yeast-based platform for biosynthesis of bacterial aromatic polyketides. The platform is based on a synthetic polyketide synthase system enabling a first demonstration of bacterial aromatic polyketide biosynthesis in a eukaryotic host.

Recently described rhizolutin and collinolactone isolated from Streptomyces Gö 40/10 share the same novel carbon scaffold. Analyses by NMR and X‐Ray crystallography verify the structure of collinolactone and propose a revision of rhizolutin's stereochemistry. Isotope‐labeled precursor feeding shows that collinolactone is biosynthesized via type I polyketide synthase with Baeyer–Villiger oxidation. CRISPR‐based genetic strategies led to the identification of the biosynthetic gene cluster and a high‐production strain. Chemical semisyntheses yielded collinolactone analogues with inhibitory effects on L929 cell line. Fluorescence microscopy revealed that only particular analogues induce monopolar spindles impairing cell division in mitosis. Inspired by the Alzheimer‐protective activity of rhizolutin, we investigated the neuroprotective effects of collinolactone and its analogues on glutamate‐sensitive cells (HT22) and indeed, natural collinolactone displays distinct neuroprotection from intracellular oxidative stress. [ABSTRACT FROM AUTHOR]

Medicinal plants are a prolific source of natural products with remarkable chemical and biological properties, many of which have considerable remedial benefits. Numerous medicinal plants are suffering from wildcrafting, and thus biotechnological production processes of their natural products are urgently needed. The plant Aster tataricus is widely used in traditional Chinese medicine and contains unique active ingredients named astins. These are macrocyclic peptides showing promising antitumor activities and usually containing the highly unusual moiety 3,4-dichloroproline. The biosynthetic origins of astins are unknown despite being studied for decades. Here we show that astins are produced by the recently discovered fungal endophyte Cyanodermella asteris. We were able to produce astins in reasonable and reproducible amounts using axenic cultures of the endophyte. We identified the biosynthetic gene cluster responsible for astin biosynthesis in the genome of C. asteris and propose a production pathway that is based on a nonribosomal peptide synthetase. Striking differences in the production profiles of endophyte and host plant imply a symbiotic cross-species biosynthesis pathway for astin C derivatives, in which plant enzymes or plant signals are required to trigger the synthesis of plant-exclusive variants such as astin A. Our findings lay the foundation for the sustainable biotechnological production of astins independent from aster plants. [ABSTRACT FROM AUTHOR]

Streptomycetes serve as major producers of various pharmacologically and industrially important natural products. Although CRISPR-Cas9 systems have been developed for more robust genetic manipulations, concerns of genome instability caused by the DNA double-strand breaks (DSBs) and the toxicity of Cas9 remain. To overcome these limitations, here we report development of the DSB-free, single-nucleotide-resolution genome editing system CRISPR-BEST (CRISPR-Base Editing SysTem), which comprises a cytidine (CRISPR-cBEST) and an adenosine (CRISPRaBEST) deaminase-based base editor. Specifically targeted by an sgRNA, CRISPR-cBEST can efficiently convert a C:G base pair to a T:A base pair and CRISPR-aBEST can convert an A:T base pair to a G:C base pair within a window of approximately 7 and 6 nucleotides, respectively. CRISPR-BEST was validated and successfully used in different Streptomyces species. Particularly in nonmodel actinomycete Streptomyces collinus Tü365, CRISPR-cBEST efficiently inactivated the 2 copies of kirN gene that are in the duplicated kirromycin biosynthetic pathways simultaneously by STOP codon introduction. Generating such a knockout mutant repeatedly failed using the conventional DSB-based CRISPR-Cas9. An unbiased, genome-wide off-target evaluation indicates the high fidelity and applicability of CRISPR-BEST. Furthermore, the system supports multiplexed editing with a single plasmid by providing a Csy4-based sgRNA processing machinery. To simplify the protospacer identification process, we also updated the CRISPy-web (https://crispy.secondarymetabolites.org), and now it allows designing sgRNAs specifically for CRISPR-BEST applications. [ABSTRACT FROM AUTHOR]

Covering: up to February, 2018 This review briefly introduces and summarizes current knowledge about the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated (Cas) – CRISPR/Cas system and how it was engineered to become one of the most important and versatile genome editing techniques that are currently revolutionizing the whole field of molecular biology. It aims to highlight and discuss the applications and remaining challenges of CRISPR/Cas (mainly focusing on CRISPR/SpCas9)-based genome editing in natural product discovery. The organisms covered include bacteria such as Streptomyces, Corynebacteria, and Myxobacteria; filamentous fungi such as Aspergillus, Beauveria, and Ganoderma; microalgae; and some plants. As closing remarks, the prospects of using CRISPR/Cas in natural product discovery will be discussed. [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]

Highlights • Microorganisms are a prolific source of highly bioactive compounds. • Omics approaches to unveil biosynthetic gene clusters encoding new natural product. • Use multi-omics tools to study the regulation of natural products biosynthesis. Natural products produced by microorganisms represent the main source of bioactive molecules. The development of high-throughput (omics) techniques have importantly contributed to the renaissance of new antibiotic discovery increasing our understanding of complex mechanisms controlling the expression of biosynthetic gene clusters (BGCs) encoding secondary metabolites. In this context this review highlights recent progress in the use and integration of 'omics' approaches with focuses on genomics, transcriptomics, proteomics metabolomics meta-omics and combined omics as powerful strategy to discover new antibiotics. [ABSTRACT FROM AUTHOR]

Abstract: Natural products of bacteria and fungi are the most important source for antimicrobial drug leads. For decades, such compounds were exclusively found by chemical/bioactivity-guided screening approaches. The rapid progress in sequencing technologies only recently allowed the development of novel screening methods based on the genome sequences of potential producing organisms. The basic principle of such genome mining approaches is to identify genes, which are involved in the biosynthesis of such molecules, and to predict the products of the identified pathways. Thus, bioinformatics methods and tools are crucial for genome mining. In this review, a comprehensive overview is given on programs and databases for the identification and analysis of antibiotic biosynthesis gene clusters in genomic data. [Copyright &y& Elsevier]

Lanthipeptides are a class of ribosomally synthesised and post-translationally modified peptide (RiPP) natural products from the bacterial secondary metabolism. Their name is derived from the characteristic lanthionine or methyl-lanthionine residues contained in the processed peptide. Lanthipeptides that possess an antibacterial activity are called lantibiotics. Whereas multiple tools exist to identify lanthipeptide gene clusters from genomic data, no programs are available to predict the post-translational modifications of lanthipeptides, such as the proteolytic cleavage of the leader peptide part or tailoring modifications based on the analysis of the gene cluster sequence. antiSMASH is a software pipeline for the identification of secondary metabolite biosynthetic clusters from genomic input and the prediction of products produced by the identified clusters. Here we present a novel antiSMASH module using a rule-based approach to combine signature motifs for biosynthetic enzymes and lanthipeptide-specific cleavage site motifs to identify lanthipeptide clusters in genomic data, assign the specific lanthipeptide class, predict prepeptide cleavage, tailoring reactions, and the processed molecular weight of the mature peptide products. [ABSTRACT FROM AUTHOR]

A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard., Chemistry and Chemical Biology

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]