A multi-omics reciprocal analysis for characterization of bacterial metabolism

Gabriel Arini ¹ Tiago Cabral Borelli ¹ Elthon Gois Ferreira ¹ Rafael De Felício ² Paula REZENDE-TEIXEIRA ¹ Matheus Pedrino Goncalves ¹ Franciene Rabiço ¹ Guilherme De Siqueira ¹ Luiz Gabriel Souza Mencucini ¹ Henrique Tsuji ¹ Lucas Andrade ¹ Leandro Garrido ¹ Gabriel Padilla ¹ Alberto Gil de la Fuente ³ Mingxun Wang ⁴ Norberto Peporine Lopes ¹ Daniela Trivella ² Leticia Veras Costa Lotufo ¹ María-Eugenia Guazzaroni ¹ Ricardo da Silva ^1*

• ¹ University of São Paulo, São Paulo, Brazil
• ² National Center for Research in Energy and Materials (Brazil), Campinas, São Paulo, Brazil
• ³ Centro de Metabolómica y Bioanálisis (CEMBIO), Boadilla del Monte, Spain
• ⁴ Department of Computer Science & Engineering , Marian and Rosemary Bourns College of Engineering, University of California, Riverside, Riverside, California, United States

Exploiting microbial natural products is a key pursuit of the bioactive compound discovery field. Recent advances in modern analytical techniques have increased the volume of microbial genomes and their encoded biosynthetic products measured by mass spectrometry-based metabolomics. However, connecting multi-omics data to uncover metabolic processes of interest is still challenging. This results in a large portion of genes and metabolites remaining unannotated. Further exacerbating the annotation challenge, databases and tools for annotation and omics integration are scattered, requiring complex computations to annotate and integrate omics datasets. Here we performed a twoway integrative analysis combining genomics and metabolomics data to describe a new approach to characterize the marine bacterial isolate BRA006 and to explore its biosynthetic gene cluster (BGC) content as well as the bioactive compounds detected by metabolomics. We described BRA006 genomic content and structure by comparing Illumina and Oxford Nanopore MinION sequencing approaches. Digital DNA:DNA hybridization (dDDH) taxonomically assigned BRA006 as a potential new species of the Micromonospora genus. Starting from LC-ESI(+)-HRMS/MS data, and mapping the annotated enzymes and metabolites belonging to the same pathways, our integrative analysis allowed us to correlate the compound Brevianamide F to a new BGC, previously assigned to other function.