Detection and repository optimization of fragmentation spectra from biological signals in metabolomics studies

Abstract

Metabolomics has gained prominence in the field of omics. It offers the possibility of phenotypic understanding at the molecular level, covering different areas of knowledge. From the experimental approach based on Mass Spectrometry (MS), untargeted metabolomics presents itself in a very promising way, because it has the capacity to reveal new Natural Products (NP) of pharmacological interest. It is estimated that 60% of drugs currently registered have a natural product involved in their development. In this sense, the potential for discovering new bioactives from the marine microbiome, through untargeted metabolomics, is enormous, given the extension and environmental diversity of the Brazilian coast. Despite technological advances, the difficulty in discriminating a biological signal from noise in data obtained in experiments with an untargeted approach is a bottleneck in the application of the technique to the NP area. In this sense, this project aims to develop a robust experimental platform for distinguishing between biological signal and noise in MS, allowing the creation of spectra catalogs in marine microbial communities. Therefore, from extracts of microbial models, reproducible biological signals will be selected for further detection and fragmentation in LC-MS/MS experiments. Tools for inspection and selection of high-quality spectra will be created, as well as their link between the genes annotated in the target biological system. The preliminary results presented in this proposal demonstrate that this is a feasible, viable and promising project. The project will be developed at the Computational Chemo-Biology Laboratory (CCBL) and at the Natural and Synthetic Products Research Center (NPPNS), under the supervision of Dr. Ricardo Roberto da Silva and Prof. Dr. Norberto Peporine Lopes. CCBL has a research grant in Support of Young Researchers (17/18922-2). We will also count on the support of the NPPNS through the Thematic grant 2020/02207-5. In addition, we have the direct collaboration of Profa. Dr. Letícia Lotufo, who will work on the project with both technical and practical issues (Thematic 15/17177-6). (AU)