Pairs of amino acids at the P- and A-sites of the ribosome predictably and causally modulate translation-elongation rates

Mechanistic Modeling of In Vivo Translation in Escherichia coli Reliably Identifies Well-Adapted and Optimized RNA Sequences

Translation elongation is a multifaceted process that intricately links translational resource availability to the biophysical effects arising from the interaction of mRNA sequences, ribosomes, and nascent polypeptide chains. Optimizing (heterologous) gene expression via codon usage or tRNA preference alone may yield suboptimal outcomes. In this study, we present a comprehensive mechanistic model that accounts for the competition of tRNAs at the ribosomal A-site, internal Shine-Dalgarno sequence interactions, and the decelerating effects of positively charged peptide patches. Our model offers a holistic perspective on the effects of translational elongation, including growth rate-dependent variation in translational rates by 22 to 25% between slow- and fast-growing Escherichia coli cells. We emphasize that endogenous E. coli sequences typically adapt to these effects, particularly in highly expressed genes, where adaptation ensures efficient translation. Conversely, heterologous gene sequences from Saccharomyces cerevisiae are predicted to exhibit lower translational elongation rates by 14 to 70% compared to the homologous isoform. Simulated elongation profiles not only underscore potential sites for translation engineering but also suggest feasible synonymous codon exchanges. The implications of our model extend beyond mere codon usage adaptation and shed light on the key factors influencing translation efficiency (e.g., codons for positively charged amino acids reduced elongation rates by ∼6%). This study provides a nuanced understanding of the intricate dynamics governing translation in E. coli.

Predicting the translation efficiency of messenger RNA in mammalian cells

The degree to which translational control is specified by mRNA sequence is poorly understood in mammalian cells. Here, we constructed and leveraged a compendium of 3,819 ribosomal profiling datasets, distilling them into a transcriptome-wide atlas of translation efficiency (TE) measurements encompassing >140 human and mouse cell types. We subsequently developed RiboNN, a multitask deep convolutional neural network, and classic machine learning models to predict TEs in hundreds of cell types from sequence-encoded mRNA features, achieving state-of-the-art performance (r=0.79 in human and r=0.78 in mouse for mean TE across cell types). While the majority of earlier models solely considered 5' UTR sequence1, RiboNN integrates contributions from the full-length mRNA sequence, learning that the 5' UTR, CDS, and 3' UTR respectively possess ~67%, 31%, and 2% per-nucleotide information density in the specification of mammalian TEs. Interpretation of RiboNN revealed that the spatial positioning of low-level di- and tri-nucleotide features (i.e., including codons) largely explain model performance, capturing mechanistic principles such as how ribosomal processivity and tRNA abundance control translational output. RiboNN is predictive of the translational behavior of base-modified therapeutic RNA, and can explain evolutionary selection pressures in human 5' UTRs. Finally, it detects a common language governing mRNA regulatory control and highlights the interconnectedness of mRNA translation, stability, and localization in mammalian organisms.

A machine learning approach uncovers principles and determinants of eukaryotic ribosome pausing

Nonuniform local translation speed dictates diverse protein biogenesis outcomes. To unify known and uncover unknown principles governing eukaryotic elongation rate, we developed a machine learning pipeline to analyze RiboSeq datasets. We find that the chemical nature of the incoming amino acid determines how codon optimality influences elongation rate, with hydrophobic residues more dependent on transfer RNA (tRNA) levels than charged residues. Unexpectedly, we find that wobble interactions exert a widespread effect on elongation pausing, with wobble-mediated decoding being slower than Watson-Crick decoding, irrespective of tRNA levels. Applying our ribosome pausing principles to ribosome collisions reveals that disomes arise upon apposition of fast-decoding and slow-decoding signatures. We conclude that codon choice and tRNA pools are evolutionarily constrained to harmonize elongation rate with cotranslational folding while minimizing wobble pairing and deleterious stalling.

Cell-type-specific expression of tRNAs in the brain regulates cellular homeostasis

Defects in tRNA biogenesis are associated with multiple neurological disorders, yet our understanding of these diseases has been hampered by an inability to determine tRNA expression in individual cell types within a complex tissue. Here, we developed a mouse model in which RNA polymerase III is conditionally epitope tagged in a Cre-dependent manner, allowing us to accurately profile tRNA expression in any cell type in vivo. We investigated tRNA expression in diverse nervous system cell types, revealing dramatic heterogeneity in the expression of tRNA genes between populations. We found that while maintenance of levels of tRNA isoacceptor families is critical for cellular homeostasis, neurons are differentially vulnerable to insults to distinct tRNA isoacceptor families. Cell-type-specific translatome analysis suggests that the balance between tRNA availability and codon demand may underlie such differential resilience. Our work provides a platform for investigating the complexities of mRNA translation and tRNA biology in the brain.

Monoclonal Antibody Sequence Variants Disguised as Fragments: Identification, Characterization, and Their Removal by Purification Process Optimization

During early stage development of a therapeutic IgG1 monoclonal antibody, high levels of low molecular weight (LMW) peaks were observed by high performance size-exclusion chromatography and capillary electrophoresis. Further characterization of the LMW peak enriched HPSEC fractions using reversed phase liquid chromatography coupled to mass spectrometry showed these LMW species were 47 kDa and 50 kDa in size. However, the measured masses could not be matched to any fragments resulting from peptide bond hydrolysis. To identify these unknown LMW species, molecular characterization methods were employed, including high-throughput sequencing of RNA. Transcriptomic analysis revealed the LMW species were generated by mis-splicing events in the heavy chain transcript, which produced truncated heavy chain products that assembled with the light chain to mimic the appearance of fragments identified by routine purity assays. In an effort to improve product quality, an optimized purification process was developed. Characterization of the process intermediates confirmed removal of both LMW species by the optimized process. Our study demonstrates that deep-dive analytical characterization of biotherapeutics is critical to ensure product quality and inform process development. Transcriptomic analysis tools can help identify the cause of unknown species, and plays a key role in product and process characterization.

Chaperone requirements for de novo folding of Saccharomyces cerevisiae septins

Polymers of septin protein complexes play cytoskeletal roles in eukaryotic cells. The specific subunit composition within complexes controls functions and higher-order structural properties. All septins have globular GTPase domains. The other eukaryotic cytoskeletal NTPases strictly require assistance from molecular chaperones of the cytosol, particularly the cage-like chaperonins, to fold into oligomerization-competent conformations. We previously identified cytosolic chaperones that bind septins and influence the oligomerization ability of septins carrying mutations linked to human disease, but it was unknown to what extent wild-type septins require chaperone assistance for their native folding. Here we use a combination of in vivo and in vitro approaches to demonstrate chaperone requirements for de novo folding and complex assembly by budding yeast septins. Individually purified septins adopted nonnative conformations and formed nonnative homodimers. In chaperonin- or Hsp70-deficient cells, septins folded slower and were unable to assemble posttranslationally into native complexes. One septin, Cdc12, was so dependent on cotranslational chaperonin assistance that translation failed without it. Our findings point to distinct translation elongation rates for different septins as a possible mechanism to direct a stepwise, cotranslational assembly pathway in which general cytosolic chaperones act as key intermediaries.

Hyper-swivel head domain motions are required for complete mRNA-tRNA translocation and ribosome resetting

Translocation of messenger RNA (mRNA) and transfer RNA (tRNA) substrates through the ribosome during protein synthesis, an exemplar of directional molecular movement in biology, entails a complex interplay of conformational, compositional, and chemical changes. The molecular determinants of early translocation steps have been investigated rigorously. However, the elements enabling the ribosome to complete translocation and reset for subsequent protein synthesis reactions remain poorly understood. Here, we have combined molecular simulations with single-molecule fluorescence resonance energy transfer imaging to gain insights into the rate-limiting events of the translocation mechanism. We find that diffusive motions of the ribosomal small subunit head domain to hyper-swivelled positions, governed by universally conserved rRNA, can maneuver the mRNA and tRNAs to their fully translocated positions. Subsequent engagement of peptidyl-tRNA and disengagement of deacyl-tRNA from mRNA, within their respective small subunit binding sites, facilitate the ribosome resetting mechanism after translocation has occurred to enable protein synthesis to resume.

mRNA and tRNA modification states influence ribosome speed and frame maintenance during poly(lysine) peptide synthesis

Ribosome speed is dictated by multiple factors including substrate availability, cellular conditions, and product (peptide) formation. Translation slows during the synthesis of cationic peptide sequences, potentially influencing the expression of thousands of proteins. Available evidence suggests that ionic interactions between positively charged nascent peptides and the negatively charged ribosome exit tunnel impede translation. However, this hypothesis was difficult to test directly because of inability to decouple the contributions of amino acid charge from mRNA sequence and tRNA identity/abundance in cells. Furthermore, it is unclear if other components of the translation system central to ribosome function (e.g., RNA modification) influence the speed and accuracy of positively charged peptide synthesis. In this study, we used a fully reconstituted Escherichia coli translation system to evaluate the effects of peptide charge, mRNA sequence, and RNA modification status on the translation of lysine-rich peptides. Comparison of translation reactions on poly(lysine)-encoding mRNAs conducted with either Lys-tRNA^Lys or Val-tRNA^Lys reveals that that amino acid charge, while important, only partially accounts for slowed translation on these transcripts. We further find that in addition to peptide charge, mRNA sequence and both tRNA and mRNA modification status influence the rates of amino acid addition and the ribosome’s ability to maintain frame (instead of entering the −2, −1, and +1 frames) during poly(lysine) peptide synthesis. Our observations lead us to expand the model for explaining how the ribosome slows during poly(lysine) peptide synthesis and suggest that posttranscriptional RNA modifications can provide cells a mechanism to precisely control ribosome movements along an mRNA.

Ribosome Elongation Kinetics of Consecutively Charged Residues Are Coupled to Electrostatic Force

The speed of protein synthesis can dramatically change when consecutively charged residues are incorporated into an elongating nascent protein by the ribosome. The molecular origins of this class of allosteric coupling remain unknown. We demonstrate, using multiscale simulations, that positively charged residues generate large forces that move the P-site amino acid away from the A-site amino acid. Negatively charged residues generate forces of similar magnitude but move the A- and P-sites closer together. These conformational changes, respectively, increase and decrease the transition state barrier height to peptide bond formation, explaining how charged residues mechanochemically alter translation speed. This mechanochemical mechanism is consistent with in vivo ribosome profiling data exhibiting proportionality between translation speed and the number of charged residues, experimental data characterizing nascent chain conformations, and a previously published cryo-EM structure of a ribosome-nascent chain complex containing consecutive lysines. These results expand the role of mechanochemistry in translation and provide a framework for interpreting experimental results on translation speed.

Quantitative Modeling of Protein Synthesis Using Ribosome Profiling Data

Quantitative prediction on protein synthesis requires accurate translation initiation and codon translation rates. Ribosome profiling data, which provide steady-state distribution of relative ribosome occupancies along a transcript, can be used to extract these rate parameters. Various methods have been developed in the past few years to measure translation-initiation and codon translation rates from ribosome profiling data. In the review, we provide a detailed analysis of the key methods employed to extract the translation rate parameters from ribosome profiling data. We further discuss how these approaches were used to decipher the role of various structural and sequence-based features of mRNA molecules in the regulation of gene expression. The utilization of these accurate rate parameters in computational modeling of protein synthesis may provide new insights into the kinetic control of the process of gene expression.