A new chemical method called Ribo-MaP uses antibiotic molecules as delivery vehicles to chemically tag and sequence the precise locations where ribosomes are actively translating messenger RNA into protein inside living cells. Current methods for monitoring translation—the process by which cells read genetic instructions to build proteins—are powerful but technically demanding. They require lengthy sample preparation steps that can introduce errors and artifacts, limiting their reliability and accessibility. Ribo-MaP bypasses these steps entirely by attaching reactive chemical groups to antibiotics that naturally bind to ribosomes. These probes then modify the RNA nucleotides sitting in the ribosome's active site, and those modifications are read out by standard sequencing. The approach works across diverse organisms—human, bacterial, and yeast cells—because the antibiotic binding site is evolutionarily conserved. If successful, Ribo-MaP could make ribosome profiling as routine as standard gene expression analysis. This would accelerate fundamental discoveries about how cells control protein production—a process that goes wrong in cancer, neurodegeneration, and infectious disease. The method also has commercial potential: companies already offer ribosome profiling as a service, and a simpler, more robust protocol could become the new industry standard. The project is primarily a proof-of-concept for a chemical tool, but the underlying biology it would unlock has broad implications for medicine and biotechnology.
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Translation is an extensively studied and fundamental cellular process that involves decoding mRNAs by ribosomes to produce proteins. Ribosome profiling (Ribo-Seq) is a hugely powerful and popular high-throughput tool for monitoring translation in living cells, revealing new mechanistic insights into translation regulation in diverse organisms. However, current protocols often involve lengthy optimisation and cell processing steps that can be plagued by artifacts. Given these technical challenges, there is a dire need for simpler and more robust ribosome profiling protocols. This motivated us to develop a chemical biology-based approach, which we have named Ribo-MaP, that could greatly simplify ribosome profiling across various model organisms. Our method uses chemical probes attached to well-characterised antibiotics that bind to the same site on the ribosome's decoding centre near the translated mRNA across all studied organisms. We employ these antibiotics as 'carriers' to guide reactive 'warheads' to chemically modify nucleotides associated with actively translated mRNA. The resulting nucleotide modifications can be readily detected and quantified using established high-throughput sequencing and bioinformatics approaches to generate snapshots of ribosome occupancy on mRNAs at nucleotide resolution. Thus, Ribo-MaP has the potential to revolutionise the field by offering a straightforward chemical 'tagging' approach that not only eliminates the need for complex cell processing and ribosome purification steps but also simplifies the entire process. By reducing the technical noise associated with other Ribo-Seq protocols, Ribo-MaP aims to enhance the robustness of ribosome profiling, making it more accessible and easier to implement for research groups studying gene expression. Moreover, the successful development of Ribo-MaP would enable us to address questions about translation regulation that existing Ribo-Seq methods cannot. Objectives: This 15-month project aims to generate proof of principle data to apply for larger-scale funding and patent applications. We will: Design and synthesise antibiotic chemical probes. Based on docking simulations on mRNA-ribosome structures, we will synthesise up to 10 antibiotic chemical probes that have the highest probability of modifying ribosome-bound mRNAs. Test compound reactivity. Translation inhibition and mRNA acylation activities of these derivatives will be tested in vitro using high-throughput cell-free GFP transcription and translation systems. The most promising reagents will be subsequently tested in cell cultures (human, bacteria, and yeast) to establish the optimal reaction conditions. Develop a basic bioinformatics pipeline for the analysis of the sequencing data: Using the preliminary sequencing data, we will establish a Ribo-MaP data analysis pipeline building on existing tools to process the raw data and quantify mRNA nucleotide modification frequencies. This will provide a robust foundation for developing additional machine learning and artificial intelligence approaches that extract biological insights from the data. Given that Ribo-Seq methods are used in drug discovery and offered as a service by companies, our approach is likely to have significant commercial impact. Hence, during the funding period we will also evaluate the intellectual property landscape for Ribo-MaP.
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