Mapping prokaryotic translatomes with ribosome profiling and its derivative approaches

Ribosome profiling (Ribo-seq) is a powerful technique that has been widely used to study and globally annotate translatomes, including small open reading frames (sORFs). The method has enabled the detection of novel translated sORFs in the model organism Escherichia coli and in several other prokaryotes. However, for many bacterial and archaeal species this information is still lacking. To gain insights into the translatomes and hidden world of small proteins (≤ 50-100 amino acids), we have been adapting and optimizing Ribo-seq approaches for diverse prokaryotes. For this purpose, we have established conventional as well as optimized new Ribo-seq derivates based on specific translation inhibitors to detect translation initiation and translation termination sites (TIS and TTS). Furthermore, we have developed several computational tools to aid in the analysis of our datasets. Among these tools are the HRIBO pipeline, which processes raw data and performs metagene profiling analysis, ORF prediction, differential expression analysis, and ORFBounder, which automatically identifies peaks for TIS and TTS libraries.

We have applied such Ribo-seq profiling approaches and bioinformatics analyses to several species, including Haloferax volcanii, the plant symbiont Sinorhizobium meliloti, [CS1] and the human pathogens Campylobacter jejuni and Helicobacter pylori. The approaches, together with independent mass spectrometry and western blot validation, expanded the number of small proteins in the different organisms. Additionally, to gain insights into potential sORF functions, we have also generated Ribo-seq datasets under different growth and stress conditions. Moreover, future aims and challenges will involve applying Ribo-seq to anaerobic bacteria from the microbiota or mixtures of organisms, such as during host interaction. Additionally, we created RIBOBASE, an online repository of prokaryotic transcriptomic and translatomic datasets that facilitates the visualization, sharing of data online and direct access to the data. Altogether, our experimental and computational approaches will be beneficial for both current and future research on small proteins in prokaryotes.