Noncoding RNAs, including regulatory RNAs (sRNAs), are instrumental in regulating gene expression in pathogenic bacteria, allowing them to adapt to various stresses encountered in their host environments. Staphylococcus aureus is a well-studied model for RNA-mediated regulation of virulence and pathogenicity, with sRNAs playing significant roles in shaping S. aureus interactions with human and animal hosts. By modulating the translation and/or stability of target mRNAs, sRNAs regulate the synthesis of virulence factors and regulatory proteins required for pathogenesis. Moreover, perturbation of the levels of RNA modifications in two other classes of noncoding RNAs, rRNAs, and tRNAs, has been proposed to contribute to stress adaptation. However, the study of how these various factors affect translation regulation has often been restricted to specific genes, using in vivo reporters and/or in vitro translation systems. Genome-wide sequencing approaches offer novel perspectives for studying RNA-dependent regulation. In particular, ribosome profiling methods provide a powerful resource for characterizing the overall landscape of translational regulation, contributing to a better understanding of S. aureus physiopathology. Here, we describe protocols that we have adapted to perform ribosome profiling in S. aureus.

It is generally believed that the regulation of gene expression involves protein translation occurring before RNA transcription. Therefore, it is crucial to investigate protein translation and its regulation. Recent advancements in biological sciences, particularly in the field of omics, have revolutionized protein translation research. These studies not only help characterize changes in protein translation during specific biological or pathological processes but also have significant implications in disease prevention and treatment. In this review, we summarize the latest methods in ribosome-based translation omics. We specifically focus on the application of fluorescence imaging technology and omics technology in studying overall protein translation. Additionally, we analyze the advantages, disadvantages, and application of these experimental methods, aiming to provide valuable insights and references to researchers studying translation.

Investigation of translation in rare cell types or subcellular contexts is challenging due to large input requirements for standard approaches. Here, we present \"nanoRibo-seq\" an optimized approach using 102- to 103-fold less input material than bulk approaches. nanoRibo-seq exhibits rigorous quality control features consistent with quantification of ribosome protected fragments with as few as 1,000 cells. We compare translatomes of two closely related cortical neuron subtypes, callosal projection neurons (CPN) and subcerebral projection neurons (SCPN), during their early postnatal development. We find that, while translational efficiency is highly correlated between CPN and SCPN, several dozen mRNAs are differentially translated. We further examine upstream open reading frame (uORF) translation and identify that mRNAs involved in synapse organization and axon development are highly enriched for uORF translation in both subtypes. nanoRibo-seq enables investigation of translational regulation of rare cell types in vivo and offers a flexible approach for globally quantifying translation from limited input material.

The processing, membrane targeting and folding of newly synthesized polypeptides is closely linked to their synthesis at the ribosome. A network of enzymes, chaperones and targeting factors engages ribosome-nascent chain complexes (RNCs) to support these maturation processes. Exploring the modes of action of this machinery is critical for our understanding of functional protein biogenesis. Selective ribosome profiling (SeRP) is a powerful method for interrogating co-translational interactions of maturation factors with RNCs. It provides proteome-wide information on the factor\'s nascent chain interactome, the timing of factor binding and release during the progress of translation of individual nascent chain species, and the mechanisms and features controlling factor engagement. SeRP is based on the combination of two ribosome profiling (RP) experiments performed on the same cell population. In one experiment the ribosome-protected mRNA footprints of all translating ribosomes of the cell are sequenced (total translatome), while the other experiment detects only the ribosome footprints of the subpopulation of ribosomes engaged by the factor of interest (selected translatome). The codon-specific ratio of ribosome footprint densities from selected over total translatome reports on the factor enrichment at specific nascent chains. In this chapter, we provide a detailed SeRP protocol for mammalian cells. The protocol includes instructions on cell growth and cell harvest, stabilization of factor-RNC interactions, nuclease digest and purification of (factor-engaged) monosomes, as well as preparation of cDNA libraries from ribosome footprint fragments and deep sequencing data analysis. Purification protocols of factor-engaged monosomes and experimental results are exemplified for the human ribosomal tunnel exit-binding factor Ebp1 and chaperone Hsp90, but the protocols are readily adaptable to other co-translationally acting mammalian factors.

During protein biosynthesis, ribosomes bind to messenger (m)RNA, locate its protein-coding information, and translate the nucleotide triplets sequentially as codons into the corresponding sequence of amino acids, forming proteins. Non-coding mRNA features, such as 5\' and 3\' untranslated regions (UTRs), start sites or stop codons of different efficiency, stretches of slower or faster code and nascent polypeptide interactions can alter the translation rates transcript-wise. Most of the homeostatic and signal response pathways of the cells converge on individual mRNA control, as well as alter the global translation output. Among the multitude of approaches to study translational control, one of the most powerful is to infer the locations of translational complexes on mRNA based on the mRNA fragments protected by these complexes from endonucleolytic hydrolysis, or footprints. Translation complex profiling by high-throughput sequencing of the footprints allows to quantify the transcript-wise, as well as global, alterations of translation, and uncover the underlying control mechanisms by attributing footprint locations and sizes to different configurations of the translational complexes. The accuracy of all footprint profiling approaches critically depends on the fidelity of footprint generation and many methods have emerged to preserve certain or multiple configurations of the translational complexes, often in challenging biological material. In this review, a systematic summary of approaches to stabilize translational complexes on mRNA for footprinting is presented and major findings are discussed. Future directions of translation footprint profiling are outlined, focusing on the fidelity and accuracy of inference of the native in vivo translation complex distribution on mRNA.

Ribosome profiling (Ribo-seq) can potentially provide detailed information about ribosome position on transcripts and estimates of protein translation levels in vivo. Hsp90 chaperones, which play a critical role in stress tolerance, have characteristic patterns of differential expression under nonstressed and heat shock conditions. By analyzing published Ribo-seq data for the Hsp90 chaperones in S. cerevisiae, we find wide-ranging artifacts originating from \"multimapping\" reads (reads that cannot be uniquely assigned to one position), which constitute ~25% of typical S. cerevisiae Ribo-seq datasets and ~80% of the reads from HEK293 cells. Estimates of Hsp90 protein production as determined by Ribo-seq are reproducible but not robust, with inferred expression levels that can change 10-fold depending on how multimapping reads are processed. The differential expression of Hsp90 chaperones under nonstressed and heat shock conditions creates artificial peaks and valleys in their ribosome profiles that give a false impression of regulated translational pausing. Indeed, we find that multimapping can even create an appearance of reproducibility to the shape of the Hsp90 ribosome profiles from biological replicates. Adding further complexity, this artificial reproducibility is dependent on the computational method used to construct the ribosome profile. Given the ubiquity of multimapping reads in Ribo-seq experiments and the complexity of artifacts associated with multimapping, we developed a publicly available computational tool to identify transcripts most at risk for multimapping artifacts. In doing so, we identify biological pathways that are enriched in multimapping transcripts, meaning that particular biological pathways will be highly susceptible to multimapping artifacts.