Research Project
10233828
Abstract: Discovery and characterization of new toxins Microcystis and other cyanobacteria commonly found in cyanobacterial harmful algal blooms (cHABs) harbor numerous gene clusters that encode the biosynthesis of diverse and unknown natural products. This project will test the hypothesis that these gene clusters are responsible for production of variety of unknown toxins and bioactive compounds that threaten human and environmental health yet remain invisible to current methods commonly used to assess water quality. The goal is to identify novel toxins and their specific genetic pathways for biosynthesis and regulation through the study of both pure cultures and consortia of uncultured microorganisms. Genomes will be assembled from metagenomes and from representative cultures of dominant bloom-forming cyanobacterial species. High-throughput bioinformatic mining of genomes and metagenomes will identify and prioritize targets for manual curation and structure prediction. In parallel to these gene-based studies, analysis of cultures and field samples will be analyzed via (i) high-throughput screening for a variety of bioactivities at the U-M Center for Chemical Genomics, and (ii) metabolomics studies (conducted by Wilhelm and Boyer groups), and (iii) assessment of potential biological targets relating to human disease. Taken together, results on the genetic/biochemical novelty and abundance and expression of genes in Lake Erie blooms will be used to identify high-priority gene clusters for further biochemical studies via heterologous biosynthetic pathway expression in genetically tractable host organisms. A next-generation graph database will be developed to facilitate the synthesis and integrated queries of genetic, experimental, and environmental data. This project directly addresses two research priorities listed in the COHH3 RFA: (1) discovery of new toxins, (2) interrogation of how climate change impacts toxic algal blooms. A broader outcome will be the development of a versatile and high throughput approach to identify natural products from varied sources of secondary metabolite gene clusters through the integration of breakthrough technologies in high throughput metagenomics and bioinformatics with experimental and analytical laboratory approaches. This research project will be carried out by three labs that have a track record of close collaboration. It will be tightly integrated into the activities of the proposed center, drawing on infrastructure and resources provide by the center and providing a number of unique capabilities to the center.
