Proteomics reveal cap-dependent translation inhibitors remodel the translation machinery and translatome

Disruption of protein synthesis can be a useful therapeutic target in conditions where excessive or aberrant protein production contributes to disease. Examples include unchecked protein production and cellular growth in cancer, and the production of viral proteins that propagate infection or result in direct damage to host cells. One strategy is to inhibit protein translation by prevent the interaction of the cellular machinery that generates the protein, the ribosome, to the molecules that provides the instruction for producing the protein, the mRNA. Current pharmaceuticals that can disrupt this process are being testing in clinical trials, including the class of drugs known as rocaglates, however the system-wide effects of these drugs are poorly understood. In a recent study by Ho and colleagues, researchers used LC-MS/MS to examine the influence of a rocaglate member Silverstrol on the cellular proteome and translatome to determine how far reaching the effects of these drugs are on the process of protein production. The study used a powerful combination of chemical labelling, at both the protein and peptide level, as well as organelle enrichment to interrogate specific cellular responses to this potentially important class of drugs, showing that their effects go far beyond the initial stages of connecting the instructions to the machinery. This paper is an excellent example of a cross-disciplinary collaboration that combines advanced techniques in cellular biology with expertise in mass spectrometry to capture the “translational landscape” during a highly important cellular event.

How was BSI General Proteomics service used?

Translatome analysis was completed using a method known as TMT-pSILAC (tandem mass tag-pulse stable isotope labelling with amino acids in cell culture). In this experiment, human cell lines were grown with media containing “light” amino acids for 7 days to achieve a baseline proteome, treated with a translation inhibitor (Silverstrol), then switched to growth in media containing a “heavy” isotope for the final 8 hours to label all newly synthesized proteins. In this way, the changes in protein production in response to the experimental treatment can be clearly identified. In the BSI laboratory the SILAC samples that had been treated with the Inhibitor (or vehicle control) were digested into peptides, labelled with tandem mass tags (TMT), combined, fractionated, and then assessed by LC-MS/MS. Importantly, each TMT tag generates a unique reporter mass that can be identified during MS1 to allow for relative quantification of individual peptides across samples. This means that the same peptide from multiple samples can be measured in the same isolation window, removing any run-run variation, and increasing the accuracy the relative abundance measurements. Combining all the TMT-labelled samples and then chromatographically separating them into 44 independent fractions meant the complexity of each fraction of the sample was reduced, allowing for increased peptide identification overall.

In a separate experiment that focused on identifying changes to active translation factors following treatment with the inhibitor, human cell lines were subjected to the pulse SILAC protocol as described above, exposed to the translation inhibitor Silverstrol, but also treated with a chemical that arrests protein production for the final 10 minutes of the experiment. The sample was lysed and then the translation machinery, i.e., the ribosomes, where isolated. In the BSI laboratory, the samples were digested, TMT-labeled, and fractionated to improve relative comparisons and overall identification rates. This experiment allowed for the identification of “factors that are actively engaged in productive translation” to determine changes in translational machinery and ribosomal engagement.

All LC-MS/MS and data analysis was completed with PEAKS as part of General Proteomics Service offered by BSI.

How was PEAKS used?

MS data was analyzed using PEAKS X+ software. SILAC and TMT induced modifications were accounted for using variable and fixed modifications during the database search workflow. The PEAKS X+ quantification module (PEAKS Q) was used for calculations of relative abundance for TMT labelled peptides. Data exported from PEAKS X+ was fully compatible with downstream enrichment analysis using freely available tools including Database for Annotation, Visualization and Integrated Discovery (DAVID).

J. David Ho, Tyler A. Cunningham, Paola Manara, Caroline A. Coughlin, Artavazd Arumov, Evan R. Roberts, Ashanti Osteen, Preet Kumar, Daniel Bilbao, Jonathan R. Krieger, Stephen Lee, and Jonathan H. Schatz. Proteomics reveal cap-dependent translation inhibitors remodel the translation machinery and translatome. Cell Reports. 2021; 37: 109806. doi:10.1016/j.celrep.2021.109806

Abstract

Tactical disruption of protein synthesis is an attractive therapeutic strategy, with the first-in-class eIF4A-targeting compound zotatifin in clinical evaluation for cancer and COVID-19. The full cellular impact and mechanisms of these potent molecules are undefined at a proteomic level. Here, we report mass spectrometry analysis of translational reprogramming by rocaglates, cap-dependent initiation disruptors that include zotatifin. We find effects to be far more complex than simple “translational inhibition” as currently defined. Translatome analysis by TMT-pSILAC (tandem mass tag-pulse stable isotope labeling with amino acids in cell culture mass spectrometry) reveals myriad upregulated proteins that drive hitherto unrecognized cytotoxic mechanisms, including GEF-H1-mediated anti-survival RHOA/JNK activation. Surprisingly, these responses are not replicated by eIF4A silencing, indicating a broader translational adaptation than currently understood. Translation machinery analysis by MATRIX (mass spectrometry analysis of active translation factors using ribosome density fractionation and isotopic labeling experiments) identifies rocaglate-specific dependence on specific translation factors including eEF1ε1 that drive translatome remodeling. Our proteome-level interrogation reveals that the complete cellular response to these historical “translation inhibitors” is mediated by comprehensive translational landscape remodeling.