Comprehensive translational profiling and STE AI uncover rapid control of protein biosynthesis during cell stress.

Translational control is important in all life, but it remains a challenge to accurately quantify. When ribosomes translate messenger (m)RNA into proteins, they attach to the mRNA in series, forming poly(ribo)somes, and can co-localize. Here, we computationally model new types of co-localized ribosomal complexes on mRNA and identify them using enhanced translation complex profile sequencing (eTCP-seq) based on rapid in vivo crosslinking. We detect long disome footprints outside regions of non-random elongation stalls and show these are linked to translation initiation and protein biosynthesis rates. We subject footprints of disomes and other translation complexes to artificial intelligence (AI) analysis and construct a new, accurate and self-normalized measure of translation, termed stochastic translation efficiency (STE). We then apply STE to investigate rapid changes to mRNA translation in yeast undergoing glucose depletion. Importantly, we show that, well beyond tagging elongation stalls, footprints of co-localized ribosomes provide rich insight into translational mechanisms, polysome dynamics and topology. STE AI ranks cellular mRNAs by absolute translation rates under given conditions, can assist in identifying its control elements and will facilitate the development of next-generation synthetic biology designs and mRNA-based therapeutics.

Targeting the ribosome to treat multiple myeloma.

The high rates of protein synthesis and processing render multiple myeloma (MM) cells vulnerable to perturbations in protein homeostasis. The induction of proteotoxic stress by targeting protein degradation with proteasome inhibitors (PIs) has revolutionized the treatment of MM. However, resistance to PIs is inevitable and represents an ongoing clinical challenge. Our first-in-human study of the selective inhibitor of RNA polymerase I transcription of ribosomal RNA genes, CX-5461, has demonstrated a potential signal for anti-tumor activity in three of six heavily pre-treated MM patients. Here, we show that CX-5461 has potent anti-myeloma activity in PI-resistant MM preclinical models in vitro and in vivo. In addition to inhibiting ribosome biogenesis, CX-5461 causes topoisomerase II trapping and replication-dependent DNA damage, leading to G2/M cell-cycle arrest and apoptotic cell death. Combining CX-5461 with PI does not further enhance the anti-myeloma activity of CX-5461 in vivo. In contrast, CX-5461 shows synergistic interaction with the histone deacetylase inhibitor panobinostat in both the Vk∗MYC and the 5T33-KaLwRij mouse models of MM by targeting ribosome biogenesis and protein synthesis through distinct mechanisms. Our findings thus provide strong evidence to facilitate the clinical development of targeting the ribosome to treat relapsed and refractory MM.