In recent years novel single-cell sequencing methods have allowed an in-depth analysis of the diversity of cell types and states in a wide range of organisms. Due to the continuous optimization of experimental and computational methods by many research groups, it is now possible to sequence the transcriptomes of thousands to millions of individual cells. Albeit an exciting development, transcription only covers the first step in the central dogma. The second step, the process of translation, is currently much harder to explore in single cells. Despite recent progress in detecting proteins by mass spectrometry with single-cell resolution, it remains a major challenge to measure translation in individual cells. Building upon existing ribosome profiling protocols, our laboratory recently majorly increased the sensitivity of these assays allowing ribosome profiling in single cells. Integrated with a machine learning approach, this method achieves single-codon resolution in individual cells. Using human cell lines, we validated this method by demonstrating that limitation for a particular amino acid causes ribosome pausing at a subset of the codons representing this amino acid. Interestingly, this pausing was only observed in a sub-population of cells correlating to its cell-cycle state underscoring the importance of single-cell resolution. We were also able to observe ribosome pausing events in rare primary enteroendocrine cells. The detection of ribosome pausing provides the first basis for monitoring translation in single cells using sequencing-based approaches. However, currently no methods exist to determine the translation efficiency in single cells and to correlate translation efficiency to tRNA levels and its modifications, RNA bound proteins, and m6A methylation of mRNA, all major regulatory mechanisms of translation. The overarching goal of this proposal is to develop these technologies and demonstrate the utility of these new methods in biologically relevant contexts. The proposal is focussed around the following objectives: (i) to integrate single-cell ribosomal profiling with transcriptomics to quantify translation efficiencies; (ii) to develop a method to detection tRNA levels and their modifications and integrate this information with the ribosomal profiles of the same cell; (iii) to develop a single-cell sequencing method to detect RNA-bound proteins and integrate this with single-cell ribosomal profiling; (iv) to develop a single-cell sequencing technology to detect m6A methylation in mRNA and integrate these data with single-cell ribosomal profiling.
