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Self-resistance guided genome mining uncovers new topoisomerase inhibitors from myxobacteria.

ABSTRACT: There is astounding discrepancy between the genome-inscribed production capacity and the set of known secondary metabolite classes from many microorganisms as detected under laboratory cultivation conditions. Genome-mining techniques are meant to fill this gap, but in order to favor discovery of structurally novel as well as bioactive compounds it is crucial to amend genomics-based strategies with selective filtering principles. In this study, we followed a self-resistance guided approach aiming at the discovery of inhibitors of topoisomerase, known as valid target in both cancer and antibiotic therapy. A common host self-defense mechanism against such inhibitors in bacteria is mediated by so-called pentapeptide repeat proteins (PRP). Genes encoding the biosynthetic machinery for production of an alleged topoisomerase inhibitor were found on the basis of their collocation adjacent to a predicted PRP in the genome of the myxobacterium Pyxidicoccus fallax An d48, but to date no matching compound has been reported from this bacterium. Activation of this peculiar polyketide synthase type-II gene cluster in the native host as well as its heterologous expression led to the structure elucidation of new natural products that were named pyxidicyclines and provided an insight into their biosynthesis. Subsequent topoisomerase inhibition assays showed strong affinity to - and inhibition of - unwinding topoisomerases such as E. coli topoisomerase IV and human topoisomerase I by pyxidicyclines as well as precise selectivity, since E. coli topoisomerase II (gyrase) was not inhibited at concentrations up to 50 ?g ml-1.

SUBMITTER: Panter F

PROVIDER: S-EPMC5982219 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

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Self-resistance guided genome mining uncovers new topoisomerase inhibitors from myxobacteria.

Panter Fabian F Krug Daniel D Baumann Sascha S Müller Rolf R

Chemical science 20180503 21

There is astounding discrepancy between the genome-inscribed production capacity and the set of known secondary metabolite classes from many microorganisms as detected under laboratory cultivation conditions. Genome-mining techniques are meant to fill this gap, but in order to favor discovery of structurally novel as well as bioactive compounds it is crucial to amend genomics-based strategies with selective filtering principles. In this study, we followed a self-resistance guided approach aiming ...[more]

PMID: 29910943

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Project description:BACKGROUND: Topoisomerase I (TOP1) is a nuclear enzyme that catalyzes the relaxation of supercoiled DNA during DNA replication and transcription. TOP1 is the molecular target of camptothecin and related drugs such as irinotecan and SN38 (irinotecan's active metabolite). Irinotecan is widely used as an anti-cancer agent in the treatment of metastatic colon cancer. However, its efficacy is often limited by the development of resistance. METHODS: We previously established several SN38 resistant HCT116-derived clones to study the mechanisms underlying resistance to SN38. Here, we investigated whether resistance to SN38 in these cell lines could be linked to the presence of TOP1 mutations and changes in its expression and activity. Functional analyses were performed on these cell lines challenged with SN38 and we specifically monitored the double strands breaks with ?H2AX staining and replication activity with molecular combing. RESULTS: In SN38 resistant HCT116 clones we identified three new TOP1 mutations, which are located in the core subdomain III (p.R621H and p.L617I) and in the linker domain (p.E710G) and are packed together at the interface between these two domains. The presence of these TOP1 mutations in SN38 resistant HCT116 cells did not modify TOP1 expression or intrinsic activity. Conversely, following challenge with SN38, we observed a decrease of TOP1-DNA cleavage complexes and a reduction in double-stranded break formation). In addition, we showed that SN38 resistant HCT116 cells present a strong decrease in the SN38-dependent asymmetry of replication forks that is characteristic of SN38 sensitive HCT116 cells. CONCLUSIONS: These results indicate that the TOP1 mutations are involved in the development of SN38 resistance. We hypothesize that p.L617, p.R621 and p.E710 TOP1 residues are important for the functionality of the linker and that mutation of one of these residues is sufficient to alter or modulate its flexibility. Consequently, linker fluctuations could have an impact on SN38 binding by reducing the enzyme affinity for the drug.

Project description:Fungal secondary metabolites are a rich source of valuable natural products, and genome sequencing has revealed a proliferation of predicted biosynthetic gene clusters in the genomes. However, it is currently an unfeasible task to characterize all biosynthetic gene clusters and to identify possible uses of the compounds. Therefore, a rational approach is needed to identify a short list of gene clusters responsible for producing valuable compounds. To this end, several bioactive clusters include a resistance gene, which is a paralog of the target gene inhibited by the compound. This mechanism can be used to identify these clusters. We have developed the FRIGG (fungal resistance gene-directed genome mining) pipeline for identifying this type of biosynthetic gene cluster based on homology patterns of the cluster genes. In this work, the FRIGG pipeline was run using 51 Aspergillus and Penicillium genomes, identifying 72 unique families of putative resistance genes. The pipeline also identified the previously characterized resistance gene inpE from the fellutamide B cluster, thereby validating the approach. We have successfully developed an approach to identify putative valuable bioactive clusters based on a specific resistance mechanism. This approach will be highly useful as an ever-increasing amount of genomic data becomes available; the art of identifying and selecting the right clusters producing novel valuable compounds will only become more crucial. IMPORTANCE Species belonging to the Aspergillus genus are known to produce a large number of secondary metabolites; some of these compounds are used as pharmaceuticals, such as penicillin, cyclosporine, and statin. With whole-genome sequencing, it became apparent that the genetic potential for secondary metabolite production is much larger than expected. As an increasing number of species are whole-genome sequenced, thousands of secondary metabolite genes are predicted, and the question of how to selectively identify novel bioactive compounds from this information arises. To address this question, we have created a pipeline to predict genes involved in the production of bioactive compounds based on a resistance gene hypothesis approach.

Dataset Information

Self-resistance guided genome mining uncovers new topoisomerase inhibitors from myxobacteria.

Publications

Self-resistance guided genome mining uncovers new topoisomerase inhibitors from myxobacteria.

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