Eriko Takano

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

Abstract Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products. At the enzyme level, active sites of key biosynthetic enzymes are now pinpointed through a curated pattern-matching procedure and Enzyme Commission numbers are assigned to functionally classify all enzyme-coding genes. Additionally, chemical structure prediction has been improved by incorporating polyketide reduction states. Finally, in order for users to be able to organize and analyze multiple antiSMASH outputs in a private setting, a new XML output module allows offline editing of antiSMASH annotations within the Geneious software.

antiSMASH: rapid identification, annotation and analysis of secondary metabolite biosynthesis gene clusters in bacterial and fungal genome sequences

Bacterial and fungal secondary metabolism is a rich source of novel bioactive compounds with potential pharmaceutical applications as antibiotics, anti-tumor drugs or cholesterol-lowering drugs. To find new drug candidates, microbiologists are increasingly relying on sequencing genomes of a wide variety of microbes. However, rapidly and reliably pinpointing all the potential gene clusters for secondary metabolites in dozens of newly sequenced genomes has been extremely challenging, due to their biochemical heterogeneity, the presence of unknown enzymes and the dispersed nature of the necessary specialized bioinformatics tools and resources. Here, we present antiSMASH (antibiotics & Secondary Metabolite Analysis Shell), the first comprehensive pipeline capable of identifying biosynthetic loci covering the whole range of known secondary metabolite compound classes (polyketides, non-ribosomal peptides, terpenes, aminoglycosides, aminocoumarins, indolocarbazoles, lantibiotics, bacteriocins, nucleosides, beta-lactams, butyrolactones, siderophores, melanins and others). It aligns the identified regions at the gene cluster level to their nearest relatives from a database containing all other known gene clusters, and integrates or cross-links all previously available secondary-metabolite specific gene analysis methods in one interactive view. antiSMASH is available at http://antismash.secondarymetabolites.org.

antiSMASH 2.0—a versatile platform for genome mining of secondary metabolite producers

Microbial secondary metabolites are a potent source of antibiotics and other pharmaceuticals. Genome mining of their biosynthetic gene clusters has become a key method to accelerate their identification and characterization. In 2011, we developed antiSMASH, a web-based analysis platform that automates this process. Here, we present the highly improved antiSMASH 2.0 release, available at http://antismash.secondarymetabolites.org/. For the new version, antiSMASH was entirely re-designed using a plug-and-play concept that allows easy integration of novel predictor or output modules. antiSMASH 2.0 now supports input of multiple related sequences simultaneously (multi-FASTA/GenBank/EMBL), which allows the analysis of draft genomes comprising multiple contigs. Moreover, direct analysis of protein sequences is now possible. antiSMASH 2.0 has also been equipped with the capacity to detect additional classes of secondary metabolites, including oligosaccharide antibiotics, phenazines, thiopeptides, homo-serine lactones, phosphonates and furans. The algorithm for predicting the core structure of the cluster end product is now also covering lantipeptides, in addition to polyketides and non-ribosomal peptides. The antiSMASH ClusterBlast functionality has been extended to identify sub-clusters involved in the biosynthesis of specific chemical building blocks. The new features currently make antiSMASH 2.0 the most comprehensive resource for identifying and analyzing novel secondary metabolite biosynthetic pathways in microorganisms.

Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters.

Although biosynthetic gene clusters (BGCs) have been discovered for hundreds of bacterial metabolites, our knowledge of their diversity remains limited. Here, we used a novel algorithm to systematically identify BGCs in the extensive extant microbial sequencing data. Network analysis of the predicted BGCs revealed large gene cluster families, the vast majority uncharacterized. We experimentally characterized the most prominent family, consisting of two subfamilies of hundreds of BGCs distributed throughout the Proteobacteria; their products are aryl polyenes, lipids with an aryl head group conjugated to a polyene tail. We identified a distant relationship to a third subfamily of aryl polyene BGCs, and together the three subfamilies represent the largest known family of biosynthetic gene clusters, with more than 1,000 members. Although these clusters are widely divergent in sequence, their small molecule products are remarkably conserved, indicating for the first time the important roles these compounds play in Gram-negative cell biology.

A complex role for the γ-butyrolactone SCB1 in regulating antibiotic production in Streptomyces coelicolor A3(2)

Many streptomycetes produce extracellular γ‐butyrolactones. In several cases, these have been shown to act as signals for the onset of antibiotic production. Synthesis of these molecules appears to require a member of the AfsA family of proteins (AfsA is required for A‐factor synthesis of the γ‐butyrolactone A‐factor and consequently for streptomycin production in Streptomyces griseus). An afsA homologue, scbA, was identified in Streptomyces coelicolor A3(2) and was found to lie adjacent to a divergently transcribed gene, scbR, which encodes a γ‐butyrolactone binding protein. Gel retardation assays and DNase I footprinting studies revealed DNA binding sites for ScbR at − 4 to − 33 nt with respect to the scbA transcriptional start site, and at − 42 to − 68 nt with respect to the scbR transcriptional start site. Addition of the γ‐butyrolactone SCB1 of S. coelicolor resulted in loss of the DNA‐binding ability of ScbR. A scbA mutant produced no γ‐butyrolactones, yet overproduced two antibiotics, actinorhodin (Act) and undecylprodigiosin (Red), whereas a deletion mutant of scbR also failed to make γ‐butyrolactones and showed delayed Red production. These phenotypes differ markedly from those expected by analogy with the S. griseus A‐factor system. Furthermore, transcription of scbR increased, and that of scbA was abolished, in an scbR mutant, indicating that ScbR represses its own expression while activating that of scbA. In the scbA mutant, expression of both genes was greatly reduced. Addition of SCB1 to the scbA mutant induced transcription of scbR, but did not restore scbA expression, indicating that the deficiency in scbA transcription in the scbA mutant is not solely due to the inability to produce SCB1, and that ScbA is a positive autoregulator in addition to being required for γ‐butyrolactone production. Overall, these results indicate a complex mechanism for γ‐butyrolactone‐mediated regulation of antibiotic biosynthesis in S. coelicolor.

Transcriptional regulation of the redD transcriptional activator gene accounts for growth-phase-dependent production of the antibiotic undecylprodigiosin in Streptomyces coelicolor A3(2)

Transcription of redD, the activator gene required for production of the red‐pigmented antibiotic undecylprodigiosin by Streptomyces coelicolor A3(2), showed a dramatic increase during the transition from exponential to stationary phase. The increase in redD expression was followed by transcription of redX, a biosynthetic structural gene, and the appearance of the antibiotic in the mycelium, and coincided with the intracellular appearance of ppGpp. However, ppGpp production elicited either by nutritional shift‐down of, or addition of serine hydroxamate to, exponentially growing cultures had no stimulatory effect on redD transcription. The presence of redD on a multicopy plasmid resulted in elevated levels of the redD transcript and production of redX and undecylprodigiosin during exponential growth; the normal growth‐phase‐dependent production of undecylprodigiosin appeared to be mediated entirely through the redD promoter, which shows limited similarity to the consensus sequence for the major class of eubacterial promoters.

Computational tools for the synthetic design of biochemical pathways

As the field of synthetic biology is developing, the prospects for de novo design of biosynthetic pathways are becoming more and more realistic. Hence, there is an increasing need for computational tools that can support these efforts. A range of algorithms has been developed that can be used to identify all possible metabolic pathways and their corresponding enzymatic parts. These can then be ranked according to various properties and modelled in an organism-specific context. Finally, design software can aid the biologist in the integration of a selected pathway into smartly regulated transcriptional units. Here, we review key existing tools and offer suggestions for how informatics can help to shape the future of synthetic microbiology.

Stationary-phase production of the antibiotic actinorhodin in Streptomyces coelicolor A3(2) is transcriptionally regulated

Production of actinorhodin, a polyketide antibiotic made by Streptomyces coelicolor A3(2), normally occurs only in stationary‐phase cultures. S1 nuclease protection experiments showed that transcription of actII‐ORF4, the activator gene required for expression of the biosynthetic structural genes, increased dramatically during the transition from exponential to stationary phase. The increase in actII‐ORF4 expression was followed by transcription of the biosynthetic structural genes actIII and actVI‐ORF1, and by the production of actinorhodin. The presence of actII‐ORF4 on a multicopy plasmid resulted in enhanced levels of actII‐oRF4 mRNA, and transcription of actIII and actinorhodin production during exponential growth, suggesting that actinorhodin synthesis in rapidly growing cultures is normally limited only by the availability of enough of the activator protein. bldA, which encodes a tRNALeuUUA that is required for the efficient translation of a single UUA codon in the actII‐ORF4 mRNA, was transcribed throughout growth. Moreover, translational fusions of the 5prime; end of actII‐ORF4 that included the UUA codon to the ermE reporter gene demonstrated the presence of functional bldA tRNA in young, exponentially growing cultures and no increase in the efficiency of translation of UUA codons, relative to UUG codons, was observed during growth. The normal growth‐phase‐dependent production of actinorhodin in the liquid culture conditions used in these experiments appears to be mediated at the transcriptional level through activation of the actII‐ORF4 promoter.

The stringent response in Streptomyces coelicolor A3(2).

The stringent response was elicited in the antibiotic producer Streptomyces coelicolor A3(2) either by amino acid depletion (nutritional shiftdown) or by the addition of serine hydroxamate; both led to increased levels of ppGpp and to a reduction in transcription from the four promoters of the rrnD rRNA gene set. Analysis of untreated batch cultures revealed elevated ppGpp levels at the end of exponential growth, preceding the onset of antibiotic production. The effect of provoking the stringent response on antibiotic production in exponentially growing cultures was assessed by S1 nuclease mapping of actIII, an early gene of the actinorhodin biosynthetic cluster. Expression of act III occurred after nutritional shiftdown, but not after treatment with serine hydroxamate. Although the need for ppGpp in triggering antibiotic production remains equivocal, ppGpp synthesis atone does not appear to be sufficient to initiate secondary metabolism in S. coelicolor A3(2).

antiSMASH 4.0-improvements in chemistry prediction and gene cluster boundary identification

Abstract Many antibiotics, chemotherapeutics, crop protection agents and food preservatives originate from molecules produced by bacteria, fungi or plants. In recent years, genome mining methodologies have been widely adopted to identify and characterize the biosynthetic gene clusters encoding the production of such compounds. Since 2011, the ‘antibiotics and secondary metabolite analysis shell—antiSMASH’ has assisted researchers in efficiently performing this, both as a web server and a standalone tool. Here, we present the thoroughly updated antiSMASH version 4, which adds several novel features, including prediction of gene cluster boundaries using the ClusterFinder method or the newly integrated CASSIS algorithm, improved substrate specificity prediction for non-ribosomal peptide synthetase adenylation domains based on the new SANDPUMA algorithm, improved predictions for terpene and ribosomally synthesized and post-translationally modified peptides cluster products, reporting of sequence similarity to proteins encoded in experimentally characterized gene clusters on a per-protein basis and a domain-level alignment tool for comparative analysis of trans-AT polyketide synthase assembly line architectures. Additionally, several usability features have been updated and improved. Together, these improvements make antiSMASH up-to-date with the latest developments in natural product research and will further facilitate computational genome mining for the discovery of novel bioactive molecules.