Unravelling the complexity of microbial gene regulatory networks

• Grant number: 19/15675-0
• Support Opportunities: Research Projects - Thematic Grants
• Duration: April 01, 2020 - March 31, 2022
• Field of knowledge: Biological Sciences - Microbiology - Applied Microbiology
• Principal Investigator: Rafael Silva Rocha
• Grantee: Rafael Silva Rocha
• Host Institution: Faculdade de Medicina de Ribeirão Preto (FMRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
• Associated researchers: María Eugenia Guazzaroni
• Associated scholarship(s): 20/14630-0 - Microbial characterization in a hospital environment using the MinION sequencing platform, BP.IC

Abstract

Gene regulatory networks (GRNs) are the central control units determining the dynamics of living systems to changing environmental conditions. The recent advances in genomics and systems biology approaches have allowed the investigation of GRNs in at a resolution with no precedents. Yet, GRNs are combinatorial, where multiple signaling pathways acts together to control the large diversity of genes from each organism, and we still lack mechanistic understanding on how these complex systems at the molecular scale. This understanding is crucial for the generation of novel engineered organisms for biomedical and biotechnological application, one of the major goals of Synthetic Biology field. In this sense, in this current project will focus on the investigation of the molecular mechanism of combinatorial gene regulation in complex regulatory networks in microorganisms. In this sense, we will combine a wide number of experimental setups and computational tools to investigate the designing principles in GRNs in bacteria and yeast. Through the course of this project, we will use the knowledge generated here to construct novel expression systems aiming their use in biotechnologically relevant applications. For this, we will implement cutting edge technologies for the automatic construction synthetic GRNs, high-throughput experimental validation and the novel computational tools for data analysis. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

KIKUTI MANCILIO, LUCCA BONJY; RIBEIRO, GUILHERME AUGUSTO; RODRIGUES DE ALMEIDA, ERICA JANAINA; VIANA DE SIQUEIRA, GUILHERME MARCELINO; ROCHA, RAFAEL SILVA; GUAZZARONI, MARIA-EUGENIA; DE ANDRADE, ADALGISA RODRIGUES; REGINATTO, VALERIA. Adding value to lignocellulosic byproducts by using acetate and p-coumaric acid as substrate in a microbial fuel cell. INDUSTRIAL CROPS AND PRODUCTS, v. 171, NOV 1 2021. (18/05454-3, 19/25432-7, 18/15528-4, 14/50945-4, 18/12471-1, 19/15675-0, 15/04309-1)

BORELLI, TIAGO CABRAL; LOVATE, GABRIEL LENCIONI; SCARANELLO, ANA FLAVIA TONELLI; RIBEIRO, LUCAS FERREIRA; ZARAMELA, LIVIA; PEREIRA-DOS-SANTOS, FELIPE MARCELO; SILVA-ROCHA, RAFAEL; GUAZZARONI, MARIA-EUGENIA. Combining Functional Genomics and Whole-Genome Sequencing to Detect Antibiotic Resistance Genes in Bacterial Strains Co-Occurring Simultaneously in a Brazilian Hospital. ANTIBIOTICS-BASEL, v. 10, n. 4, APR 2021. (19/00390-0, 15/04309-1, 19/06672-7, 16/18827-7, 19/15675-0, 18/18158-3)

MONTEIRO, LUMMY MARIA OLIVEIRA; SARAIVA, JOAO PEDRO; TOSCAN, RODOLFO BRIZOLA; STADLER, PETER F.; SILVA-ROCHA, RAFAEL; DA ROCHA, ULISSES NUNES. redicTF: prediction of bacterial transcription factors in complex microbial communities using deep learnin. ENVIRONMENTAL MICROBIOME, v. 17, n. 1, FEB 8 2022. (19/15675-0, 18/21133-2, 16/19179-9)