| Grant number: | 20/07710-7 |
| Support type: | Regular Research Grants |
| Duration: | April 01, 2021 - March 31, 2023 |
| Field of knowledge: | Physical Sciences and Mathematics - Chemistry - Organic Chemistry |
| Principal researcher: | Camila Manoel Crnkovic |
| Grantee: | Camila Manoel Crnkovic |
| Home Institution: | Faculdade de Ciências Farmacêuticas (FCF). Universidade de São Paulo (USP). São Paulo , SP, Brazil |
| Assoc. researchers: | Alessandra S. Eustaquio ; Frederico José Gueiros Filho ; José Angelo Lauletta Lindoso |
| Associated scholarship(s): | 21/02751-0 - Building and screening a chemical library of extracts from cyanobacteria, BP.TT |
Abstract
Natural products are an important source of pharmaceuticals and chemical probes. The discovery of new natural products is challenged by the inherent complexity of biological extracts and by the increasing rates of rediscovery of known compounds. Expanding source diversity and improving chemical prospection approaches are critical to enhance the discovery of new natural products. Cyanobacteria are a taxonomically diverse phylum of microorganisms known to produce secondary metabolites with biotechnological potential. The chemistry of cyanobacteria remains largely underexplored, representing a promising source of unprecedented scaffolds. In creating natural product libraries, prefractionating extracts has been shown to enhance screening performance. Furthermore, metabolomics and genomics offer solutions for the analysis of complex biological samples. We propose the chemical prospection of cyanobacterial strains using a standardized pipeline improved by metabolomics and genomics to identify promising natural products. The pipeline will include large-scale cultivation, lyophilization, extraction, and prefractionation for the development of a chemical library that will be tested for antiproliferative, antibacterial, and antileishmanial activities. We propose the integration of mass spectrometry-based metabolomics and genome mining to aid sample prioritization, preliminary dereplication, and compound identification. A relational data management system will be implemented to store and document research records. (AU)