Development of a high-throughput protocol for testing an RNA Switch Library for training a Machine Learning Model

• Grant number: 25/02907-0
• Support Opportunities: Scholarships abroad - Research Internship - Doctorate
• Start date: July 01, 2025
• End date: March 31, 2026
• Field of knowledge: Biological Sciences - Genetics - Molecular Genetics and Genetics of Microorganisms
• Principal Investigator: Danielle Biscaro Pedrolli
• Grantee: Guilherme Engelberto Kundlatsch
• Supervisor: Beatrix Suß
• Host Institution: Faculdade de Ciências Farmacêuticas (FCFAR). Universidade Estadual Paulista (UNESP). Campus de Araraquara. Araraquara , SP, Brazil
• Institution abroad: Technische Universität Darmstadt (TU Darmstadt), Germany
• Associated to the scholarship: 23/02133-0 - Development and optimization of RNA switches for transcriptional control applying machine learning, BP.DR

Abstract

Toehold switches are synthetic elements designed to detect the presence of an RNA trigger and regulate gene expression at the translational level. They have versatile applications as biosensors, enzyme screening tools, and regulatory components for metabolic engineering. Recently, transcriptional toehold switches have been developed, but they remain in the early stages of research and exhibit low sensitivity to triggers. This study aims to optimize this new class of switches using machine learning. In previous stages of this research, a streamlined protocol for evaluating in vitro transcription using the fluorescent RNAs Broccoli and Mango III was developed, along with a methodology for optimizing biological parts through machine learning. Both approaches were validated through the development of optimized transcription terminators. This exchange aims to leverage the expertise and automation tools available at the partner institution to construct a library of transcriptional switches, applying the previously developed methods for subsequent optimization through machine learning. Beyond advancing the development of transcriptional toehold switches, this project seeks to create a software tool that other researchers can use to design RNA switches.