iTP-seq: a scalable profiling workflow to characterize bacterial translation landscapes in vitro

Uneven translation rates resulting from mRNA context, tRNA abundance, nascent amino acid sequence or various external factors play a key role in controlling the expression level and folding of the proteome. Inverse toeprinting coupled to next-generation Sequencing (iTP-seq) is a scalable in vitro method for characterizing Bacterial translation landscapes, complementary to ribosome profiling (Ribo-seq), a widely used method for determining transcriptome-wide protein synthesis rates in vivo. In iTP-seq, ribosome-protected mRNA fragments known as inverse toeprints are generated by using RNase R, a highly processive 3' to 5' RNA exonuclease. Deep Sequencing of these fragments reveals the position of the leading ribosome on each mRNA with codon resolution, as well as the full upstream coding regions translated by these ribosomes. Consequently, the method requires no a priori knowledge of the translated sequences, enabling work with fully customizable transcript libraries rather than previously sequenced genomes. As a standardized framework for inverse toeprint generation, amplification and Sequencing, iTP-seq can be used in combination with different types of libraries, in vitro translation conditions and data-analysis pipelines tailored to address a range of biological questions. Here, we present a robust protocol for iTP-seq and show how it can be integrated into a broader workflow to enable the study of context-dependent translation inhibitors, such as Antibiotics. The time required to complete this workflow is ~10 d, and the workflow can be carried out by an experienced molecular biologist, with data analysis also requiring a working knowledge of command-line tools and Python scripts.