Strategies for mining fungal natural products

Fungi are well known for their ability to produce a multitude of natural products. On the one hand their potential to provide beneficial antibiotics and immunosuppressants has been maximized by the pharmaceutical industry to service the market with cost-efficient drugs. On the other hand identification of trace amounts of known mycotoxins in food and feed samples is of major importance to ensure consumer health and safety. Although several fungal natural products, their biosynthesis and regulation are known today, recent genome sequences of hundreds of fungal species illustrate that the secondary metabolite potential of fungi has been substantially underestimated. Since expression of genes and subsequent production of the encoded metabolites are frequently cryptic or silent under standard laboratory conditions, strategies for activating these hidden new compounds are essential. This review will cover the latest advances in fungal genome mining undertaken to unlock novel products.     

Genome mining for ribosomally synthesized natural products

In recent years, the number of known peptide natural products that are synthesized via the ribosomal pathway has rapidly grown. Taking advantage of sequence homology among genes encoding precursor peptides or biosynthetic proteins, in silico mining of genomes combined with molecular biology approaches has guided the discovery of a large number of new ribosomal natural products, including lantipeptides, cyanobactins, linear thiazole/oxazole-containing peptides, microviridins, lasso peptides, amatoxins, cyclotides, and conopeptides. In this review, we describe the strategies used for the identification of these ribosomally synthesized and posttranslationally modified peptides (RiPPs) and the structures of newly identified compounds. The increasing number of chemical entities and their remarkable structural and functional diversity may lead to novel pharmaceutical applications.     

Phylogeny-guided (meta)genome mining approach for the targeted discovery of new microbial natural products

Genomics-based methods are now commonplace in natural products research. A phylogeny-guided mining approach provides a means to quickly screen a large number of microbial genomes or metagenomes in search of new biosynthetic gene clusters of interest. In this approach, biosynthetic genes serve as molecular markers, and phylogenetic trees built with known and unknown marker gene sequences are used to quickly prioritize biosynthetic gene clusters for their metabolites characterization. An increase in the use of this approach has been observed for the last couple of years along with the emergence of low cost sequencing technologies. The aim of this review is to discuss the basic concept of a phylogeny-guided mining approach, and also to provide examples in which this approach was successfully applied to discover new natural products from microbial genomes and metagenomes. I believe that the phylogeny-guided mining approach will continue to play an important role in genomics-based natural products research.     

Novel bioactive natural products from bacteria via bioprospecting,genome mining and metabolic engineering

For over seven decades, bacteria served as a valuable source of bioactive natural products some of which were eventually developed into drugs to treat infections, cancer and immune system-related diseases. Traditionally, novel compounds produced by bacteria were discovered via conventional bioprospecting based on isolation of potential producers and screening their extracts in a variety of bioassays. Over time, most of the natural products identifiable by this approach were discovered, and the pipeline for new drugs based on bacterially produced metabolites started to run dry. This mini-review highlights recent developments in bacterial bioprospecting for novel compounds that are based on several out-of-the-box approaches, including the following: (i) targeting bacterial species previously unknown to produce any bioactive natural products, (ii) exploring non-traditional environmental niches and methods for isolation of bacteria and (iii) various types of ‘genome mining’ aimed at unravelling genetic potential of bacteria to produce secondary metabolites. All these approaches have already yielded a number of novel bioactive compounds and, if used wisely, will soon revitalize drug discovery pipeline based on bacterial natural products.     

Gifted microbes for genome mining and natural product discovery

Actinomycetes are historically important sources for secondary metabolites (SMs) with applications in human medicine, animal health, and plant crop protection. It is now clear that actinomycetes and other microorganisms with large genomes have the capacity to produce many more SMs than was anticipated from standard fermentation studies. Indeed ~90 % of SM gene clusters (SMGCs) predicted from genome sequencing are cryptic under conventional fermentation and analytical analyses. Previous studies have suggested that among the actinomycetes with large genomes, some have the coding capacity to produce many more SMs than others, and that strains with the largest genomes tend to be the most gifted. These contentions have been evaluated more quantitatively by antiSMASH 3.0 analyses of microbial genomes, and the results indicate that many actinomycetes with large genomes are gifted for SM production, encoding 20–50 SMGCs, and devoting 0.8–3.0 Mb of coding capacity to SM production. Several Proteobacteria and Firmacutes with large genomes encode 20–30 SMGCs and devote 0.8–1.3 Mb of DNA to SM production, whereas cultured bacteria and archaea with small genomes devote insignificant coding capacity to SM production. Fully sequenced genomes of uncultured bacteria and archaea have small genomes nearly devoid of SMGCs.     

A mass spectrometry-guided genome mining approach for natural product peptidogenomics

Peptide natural products show broad biological properties and are commonly produced by orthogonal ribosomal and nonribosomal pathways in prokaryotes and eukaryotes. To harvest this large and diverse resource of bioactive molecules, we introduce here natural product peptidogenomics (NPP), a new MS-guided genome-mining method that connects the chemotypes of peptide natural products to their biosynthetic gene clusters by iteratively matching de novo tandem MS (MS(n)) structures to genomics-based structures following biosynthetic logic. In this study, we show that NPP enabled the rapid characterization of over ten chemically diverse ribosomal and nonribosomal peptide natural products of previously unidentified composition from Streptomycete bacteria as a proof of concept to begin automating the genome-mining process. We show the identification of lantipeptides, lasso peptides, linardins, formylated peptides and lipopeptides, many of which are from well-characterized model Streptomycetes, highlighting the power of NPP in the discovery of new peptide natural products from even intensely studied organisms.     

Discovery of a new peptide natural product by Streptomyces coelicolor genome mining

Analyses of microbial genome sequences reveal numerous examples of gene clusters encoding proteins typically involved in complex natural product biosynthesis but not associated with the production of known natural products. In Streptomyces coelicolor M145 there are several gene clusters encoding new nonribosomal peptide synthetase (NRPS) systems not associated with known metabolites. Application of structure-based models for substrate recognition by NRPS adenylation domains predicts the amino acids incorporated into the putative peptide products of these systems, but the accuracy of these predictions is untested. Here we report the isolation and structure determination of the new tris-hydroxamate tetrapeptide iron chelator coelichelin from S. coelicolor using a genome mining approach guided by substrate predictions for the trimodular NRPS CchH, and we show that this enzyme, which lacks a C-terminal thioesterase domain, together with a homolog of enterobactin esterase (CchJ), are required for coelichelin biosynthesis. These results demonstrate that accurate prediction of adenylation domain substrate selectivity is possible and raise intriguing mechanistic questions regarding the assembly of a tetrapeptide by a trimodular NRPS.     

Automated correction of genome sequence errors

By using information from an assembly of a genome, a new program called AutoEditor significantly improves base calling accuracy over that achieved by previous algorithms. This in turn improves the overall accuracy of genome sequences and facilitates the use of these sequences for polymorphism discovery. We describe the algorithm and its application in a large set of recent genome sequencing projects. The number of erroneous base calls in these projects was reduced by 80%. In an analysis of over one million corrections, we found that AutoEditor made just one error per 8828 corrections. By substantially increasing the accuracy of base calling, AutoEditor can dramatically accelerate the process of finishing genomes, which involves closing all gaps and ensuring minimum quality standards for the final sequence. It also greatly improves our ability to discover single nucleotide polymorphisms (SNPs) between closely related strains and isolates of the same species.     

Automated bacterial genome analysis and annotation

More than 300 bacterial genome sequences are publicly available, and many more are scheduled to be completed and released in the near future. Converting this raw sequence information into a better understanding of the biology of bacteria involves the identification and annotation of genes, proteins and pathways. This processing is typically done using sequence annotation pipelines comprised of a variety of software modules and, in some cases, human experts. The reference databases, computational methods and knowledge that form the basis of these pipelines are constantly evolving, and thus there is a need to reprocess genome annotations on a regular basis. The combined challenge of revising existing annotations and extracting useful information from the flood of new genome sequences will necessitate more reliance on completely automated systems.     

A System for Automated Bacterial (genome) Integrated Annotation--SABIA

A web-based software suite, SABIA (System for Automated Bacterial Integrated Annotation), is described that provides a comprehensive computational support for the assembly and annotation of whole bacterial genomes from the data derived from sequencing projects. AVAILABILITY: Both SABIA and supplementary materials are available at http://www.sabia.lncc.br     

Applied techniques for mining natural proteasome inhibitors

In eukaryotic cells, the ubiquitin–proteasome-system (UPS) is responsible for the non-lysosomal degradation of proteins and plays a pivotal role in such vital processes as protein homeostasis, antigen processing or cell proliferation. Therefore, it is an attractive drug target with various applications in cancer and immunosuppressive therapies. Being an evolutionary well conserved pathway, many pathogenic bacteria have developed small molecules, which modulate the activity of their hosts' UPS components. Such natural products are, due to their stepwise optimization over the millennia, highly potent in terms of their binding mechanisms, their bioavailability and selectivity. Generally, this makes bioactive natural products an ideal starting point for the development of novel drugs. Since four out of the ten best seller drugs are natural product derivatives, research in this field is still of unfathomable value for the pharmaceutical industry. The currently most prominent example for the successful exploitation of a natural compound in the UPS field is carfilzomib (Kyprolis®), which represents the second FDA approved drug targeting the proteasome after the admission of the blockbuster bortezomib (Velcade®) in 2003. On the other hand side of the spectrum, ONX 0914, which is derived from the same natural product as carfilzomib, has been shown to selectively inhibit the immune response related branch of the pathway. To date, there exists a huge potential of UPS inhibitors with regard to many diseases. Both approved drugs against the proteasome show severe side effects, adaptive resistances and limited applicability, thus the development of novel compounds with enhanced properties is a main objective of active research. In this review, we describe the techniques, which can be utilized for the discovery of novel natural inhibitors, which in particular block the 20S proteasomal activity. In addition, we will illustrate the successful implementation of a recently published methodology with the example of a highly potent but so far unexploited group of proteasome inhibitors, the syrbactins, and their biological functions. This article is part of a Special Issue entitled: Ubiquitin–Proteasome System. Guest Editors: Thomas Sommer and Dieter H. Wolf.     

Automated genome sequence analysis and annotation.

MOTIVATION: Large-scale genome projects generate a rapidly increasing number of sequences, most of them biochemically uncharacterized. Research in bioinformatics contributes to the development of methods for the computational characterization of these sequences. However, the installation and application of these methods require experience and are time consuming. RESULTS: We present here an automatic system for preliminary functional annotation of protein sequences that has been applied to the analysis of sets of sequences from complete genomes, both to refine overall performance and to make new discoveries comparable to those made by human experts. The GeneQuiz system includes a Web-based browser that allows examination of the evidence leading to an automatic annotation and offers additional information, views of the results, and links to biological databases that complement the automatic analysis. System structure and operating principles concerning the use of multiple sequence databases, underlying sequence analysis tools, lexical analyses of database annotations and decision criteria for functional assignments are detailed. The system makes automatic quality assessments of results based on prior experience with the underlying sequence analysis tools; overall error rates in functional assignment are estimated at 2.5-5% for cases annotated with highest reliability ('clear' cases). Sources of over-interpretation of results are discussed with proposals for improvement. A conservative definition for reporting 'new findings' that takes account of database maturity is presented along with examples of possible kinds of discoveries (new function, family and superfamily) made by the system. System performance in relation to sequence database coverage, database dynamics and database search methods is analysed, demonstrating the inherent advantages of an integrated automatic approach using multiple databases and search methods applied in an objective and repeatable manner. AVAILABILITY: The GeneQuiz system is publicly available for analysis of protein sequences through a Web server at http://www.sander.ebi.ac. uk/gqsrv/submit     

Bioprospecting microbial metagenome for natural products

Mining of natural sources for new secondary metabolites has a successful history, which is reflected by the fact that over 50% of all drugs, currently on the market, are derived from natural products. Bacteria are one of the most important sources of bioactive natural products destined for drug discovery. However, less than 1% of the microorganisms observed in different habitats have been cultivated and characterized. To explore the genomic and functional diversity of the vast majority of the microbial world, novel methods were introduced, which are based on analysis of a DNA isolated from environmental communities. Metagenomics represents a strategy offering access to the genetic information present in uncultured bacteria by screening of libraries constructed from DNA isolated from different habitats. Functional- and sequence-driven screens are the major approaches employed to mine metagenomic libraries. This review aims to highlight discoveries in this area and discusses the possible future directions of the field.     

Antifungal natural products

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Integrons: natural tools for bacterial genome evolution

Integrons were first identified as the primary mechanism for antibiotic resistance gene capture and dissemination among Gram-negative bacteria. More recently, their role in genome evolution has been extended with the discovery of larger integron structures, the super-integrons, as genuine components of the genomes of many species throughout the gamma-proteobacterial radiation. The functional platforms of these integrons appear to be sedentary, whereas their gene cassette contents are highly variable. Nevertheless, the gene cassettes for which an activity has been experimentally demonstrated encode proteins related to simple adaptive functions and their recruitment is seen as providing the bacterial host with a selective advantage. The widespread occurrence of the integron system among Gram-negative bacteria is discussed, with special focus on the super-integrons. Some of the adaptive functions encoded by these genes are also reviewed, and implications of integron-mediated genome evolution in the emergence of novel bacterial species are highlighted.     

MbtH homology codes to identify gifted microbes for genome mining

Advances in DNA sequencing technologies have made it possible to sequence large numbers of microbial genomes rapidly and inexpensively. In recent years, genome sequencing initiatives have demonstrated that actinomycetes with large genomes generally have the genetic potential to produce many secondary metabolites, most of which remain cryptic. Since the numbers of new and novel pathways vary considerably among actinomycetes, and the correct assembly of secondary metabolite pathways containing type I polyketide synthase or nonribosomal peptide synthetase (NRPS) genes is costly and time consuming, it would be advantageous to have simple genetic predictors for the number and potential novelty of secondary metabolite pathways in targeted microorganisms. For secondary metabolite pathways that utilize NRPS mechanisms, the small chaperone-like proteins related to MbtH encoded by Mycobacterium tuberculosis offer unique probes or beacons to identify gifted microbes encoding large numbers of diverse NRPS pathways because of their unique function(s) and small size. The small size of the mbtH-homolog genes makes surveying large numbers of genomes straight-forward with less than ten-fold sequencing coverage. Multiple MbtH orthologs and paralogs have been coupled to generate a 24-mer multiprobe to assign numerical codes to individual MbtH homologs by BLASTp analysis. This multiprobe can be used to identify gifted microbes encoding new and novel secondary metabolites for further focused exploration by extensive DNA sequencing, pathway assembly and annotation, and expression studies in homologous or heterologous hosts.     

Bioinformatics tools for genome mining of polyketide and non-ribosomal peptides

Microbial natural products have played a key role in the development of clinical agents in nearly all therapeutic areas. Recent advances in genome sequencing have revealed that there is an incredible wealth of new polyketide and non-ribosomal peptide natural product diversity to be mined from genetic data. The diversity and complexity of polyketide and non-ribosomal peptide biosynthesis has required the development of unique bioinformatics tools to identify, annotate, and predict the structures of these natural products from their biosynthetic gene clusters. This review highlights and evaluates web-based bioinformatics tools currently available to the natural product community for genome mining to discover new polyketides and non-ribosomal peptides.     

Biocommunication and natural genome editing

The biocommunicative approach investigates communication processes within and among cells, tissues, organs and organisms as sign-mediated interactions, and nucleotide sequences as code, i.e. language-like text, which follows in parallel three kinds of rules: combinatorial (syntactic), context-sensitive (pragmatic), and content-specific (semantic). Natural genome editing from a biocommunicative perspective is competent agent-driven generation and integration of meaningful nucleotide sequences into pre-existing genomic content arrangements and the ability to (re-)combine and (re-)regulate them according to context-dependent (i.e. adaptational) purposes of the host organism.