Recent advances in DNA sequencing technologies and a better understanding of natural product biosynthesis provide newfound opportunities to improve the process by which microbial natural products are discovered. The objectives of this research are to establish a series of methodologies by which strains can be quickly assessed for natural product biosynthesis through the analysis of PCR-generated or genome sequence data. The methods will be developed using a model group of marine bacteria belonging to the genus Salinispora and then applied to a large and diverse collection of marine actinomycetes with the aim of discovering structurally diverse, new chemical entities, which will be provided to the NIH Molecular Libraries Small Molecule Repository (MLSMR). The methods include an initial, rapid molecular """"""""fingerprinting"""""""" screen, from which the genetic potential of individual strains can be compared. Sequence-based approaches will then be applied to interpret the biosynthetic richness and novelty of strains with promising fingerprints. These methods will make it possible to predict if the metabolites produced by a strain will be new and how many different compounds in a particular structural class may be produced. Once strains with the greatest genetic potential are identified, detailed chemical studies will be performed. This approach represents a dramatic improvement over traditional paradigms in which large numbers of biosynthetically unknown strains are screened in a limited number of conditions. It will dramatically reduce the isolation of previously discovered compounds, a problem that has long plagued microbial natural product research. This approach provides a culture-independent, genome-level assessment of secondary metabolite biosynthesis as opposed to more traditional methods, which detect only those metabolites produced under a limited set of culture conditions. The methods developed will be broadly applicable to the scientific community and include the creation of a curated sequence database that can be readily downloaded and used to assess genome sequence data for pathways involved in secondary metabolite production. This research has the potential to dramatically increase the rates with which new chemical entities are discovered and made available for biomedical research.
The research presented in this proposal provides a method by which DNA sequence data can be used to dramatically improve the process by which natural products are discovered from microorganisms. It will generate considerable new chemical diversity that can be used for drug discovery research and to study basic biological processes. The methods developed will be made widely available to the research community and thereby have a broad impact on drug discovery and basic biomedical research.
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