Rate-limiting steps in yeast protein translation

Macroevolutionary changes in natural selection on codon usage reflects evolution of the tRNA pool across a budding yeast subphylum

Across taxonomical domains, synonymous codons of an amino acid are found to be used at unequal frequencies within genes. This codon usage bias (CUB) is highly variable across species. Genome-wide CUB reflects a balance between adaptive and non-adaptive microevolutionary processes within a species. Variation in microevolutionary processes results in across-species variation in CUB. As CUB is tightly linked to important molecular and biophysical processes, it is critical to understand how changes to these processes are linked to changes in microevolutionary processes. We employed a population genetics model to quantify natural selection and mutation biases on a per-codon basis across the Saccharomycotina budding yeast subphylum. We found that the strength of natural selection and mutation biases varied significantly between closely related yeasts. Across-species variation in natural selection reflected the evolution of tRNA gene copy number. Additionally, we found evidence that changes to tRNA modification expression can contribute to changes in natural selection across species independent of changes to tGCN. Both lines of evidence support the link between the evolution of the tRNA pool and natural selection in codon usage through changes in the translation efficiency of a codon. Furthermore, we found that changes to tGCN often reflected changes to genome-wide GC%, suggesting changes to the tRNA pool reflect changes to mutation bias. Our work establishes how changes in microevolutionary processes impact changes in molecular mechanisms, ultimately shaping the macroevolutionary variation of a trait.

Significance statement

Codon usage bias (CUB) - the non-uniform usage of synonymous codons - is a feature of all genomes and varies across closely related species. Differences in CUB imply differences in the underlying microevolutionary processes (natural selection, mutation bias) driving CUB. CUB is hypothesized to be tightly linked to key molecular processes, particularly mRNA translation. We used a population genetics model to quantify natural selection and mutation bias on a per-codon basis across 327 budding yeasts. We found high variability in the microevolution of CUB and showed that changes in natural selection were correlated with the evolution of the tRNA pool. Our work establishes how variation in molecular mechanisms relates to variation in microevolution, shaping variation in a trait across species.

Macroevolutionary divergence of gene expression driven by selection on protein abundance

The regulation of messenger RNA (mRNA) and protein abundances is well-studied, but less is known about the evolutionary processes shaping their relationship. To address this, we derived a new phylogenetic model and applied it to multispecies mammalian data. Our analyses reveal (i) strong stabilizing selection on protein abundances over macroevolutionary time, (ii) mutations affecting mRNA abundances minimally impact protein abundances, (iii) mRNA abundances evolve under selection to align with protein abundances, and (iv) mRNA abundances adapt faster than protein abundances owing to greater mutational opportunity. These conclusions are supported by comparisons of model parameters with independent functional genomic data. By decomposing mutational and selective influences on mRNA-protein dynamics, our approach provides a framework for discovering the evolutionary rules that drive divergence in gene expression.

Structural Basis for the Improved RNA Clamping of Amidino-Rocaglates to eIF4A1

Eukaryotic initiation factor 4A-1 (eIF4A1) is an ATP-dependent RNA helicase that unwinds 5'-UTR mRNA secondary structures to facilitate cap-dependent translation initiation. Rocaglates, a class of natural products typified by rocaglamide A (RocA), possess antineoplastic and anti-infectious activity mediated by their interaction with eIF4A1. Rocaglates inhibit cap-dependent translation initiation by "clamping" eIF4A1 onto polypurine RNA, which impedes ribosome scanning. A novel class of rocaglate derivatives, amidino-rocaglates (ADRs) which feature an amidine ring fused to the rocaglate core, is particularly effective at promoting eIF4A1-RNA-clamping compared to other rocaglate congeners. Herein, we present the X-ray crystal structure of an ADR in complex with eIF4A1, the nonhydrolyzable ATP ground-state mimic adenylyl-imidodiphosphate (AMPPNP), and poly r(AG)5 RNA refined to 1.69 Å resolution. The binding pose and interactions of the ADR with eIF4A1 do not differ substantially from those of RocA, prompting an investigation of the basis for enhanced target engagement. Computational modeling suggests that the rigidified ADR scaffold is inherently preorganized in an eIF4A1-RNA binding-competent conformation, thereby avoiding entropic penalties associated with RocA binding. This study illustrates how conformational rigidification of the rocaglate scaffold can be leveraged to improve potency for the development of rocaglates as potential anticancer and anti-infectious agents.

Cellular translational enhancer elements that recruit eukaryotic initiation factor 3

Translation initiation is a highly regulated process that broadly affects eukaryotic gene expression. Eukaryotic initiation factor 3 (eIF3) is a central player in canonical and alternative pathways for ribosome recruitment. Here, we have investigated how direct binding of eIF3 contributes to the large and regulated differences in protein output conferred by different 5'-untranslated regions (5' UTRs) of cellular mRNAs. Using an unbiased high-throughput approach to determine the affinity of budding yeast eIF3 for native 5' UTRs from 4252 genes, we demonstrate that eIF3 binds specifically to a subset of 5' UTRs that contain a short unstructured binding motif, AMAYAA. eIF3-binding mRNAs have higher ribosome density in growing cells and are preferentially translated under certain stress conditions, supporting the functional relevance of this interaction. Our results reveal a new class of translational enhancers and suggest a mechanism by which changes in core initiation factor activity enact mRNA-specific translation programs.

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.

Exploring the dynamics of messenger ribonucleoprotein-mediated translation repression

Translational control is crucial for well-balanced cellular function and viability of organisms. Different mechanisms have evolved to up- and down-regulate protein synthesis, including 3' untranslated region (UTR)-mediated translation repression. RNA binding proteins or microRNAs interact with regulatory sequence elements located in the 3' UTR and interfere most often with the rate-limiting initiation step of translation. Dysregulation of post-transcriptional gene expression leads to various kinds of diseases, emphasizing the significance of understanding the mechanisms of these processes. So far, only limited mechanistic details about kinetics and dynamics of translation regulation are understood. This mini-review focuses on 3' UTR-mediated translational regulation mechanisms and demonstrates the potential of using single-molecule fluorescence-microscopy for kinetic and dynamic studies of translation regulation in vivo and in vitro.

Reversing the relative time courses of the peptide bond reaction with oligopeptides of different lengths and charged amino acid distributions in the ribosome exit tunnel

The kinetics of the protein elongation cycle by the ribosome depends on intertwined factors. One of these factors is the electrostatic interaction of the nascent protein with the ribosome exit tunnel. In this computational biology theoretical study, we focus on the rate of the peptide bond formation and its dependence on the ribosome exit tunnel electrostatic potential profile. We quantitatively predict how oligopeptides of variable lengths can affect the peptide bond formation rate. We applied the Michaelis-Menten model as previously extended to incorporate the mechano-biochemical effects of forces on the rate of reaction at the catalytic site of the ribosome. For a given pair of carboxy-terminal amino acid substrate at the P- and an aminoacyl-tRNA at the A-sites, the relative time courses of the peptide bond formation reaction can be reversed depending on the oligopeptide sequence embedded in the tunnel and their variable lengths from the P-site. The reversal is predicted to occur from a shift in positions of charged amino acids upstream in the oligopeptidyl-tRNA at the P-site. The position shift must be adjusted by clever design of the oligopeptide probes using the electrostatic potential profile along the exit tunnel axial path. These predicted quantitative results bring strong evidence of the importance and relative contribution of the electrostatic interaction of the ribosome exit tunnel with the nascent peptide chain during elongation.

Understanding the regulation of protein synthesis under stress conditions

Protein synthesis regulation primarily occurs at translation initiation, the first step of gene translation. However, the regulation of translation initiation under various conditions is not fully understood. Specifically, the reason why protein production from certain mRNAs remains resistant to stress while others do not show such resilience. Moreover, why is protein production enhanced from a few transcripts under stress conditions, whereas it is decreased in the majority of transcripts? We address them by developing a Monte Carlo simulation model of protein synthesis and ribosome scanning. We find that mRNAs with strong Kozak contexts exhibit minimal reduction in translation initiation rate under stress conditions. Moreover, these transcripts exhibit even greater resilience to stress when the scanning speed of 43S ribosome subunit is slow, albeit at the cost of reduced initiation rate. This implies a trade-off between initiation rate and the ability of mRNA to withstand stress. We also show that mRNAs featuring an upstream ORF can act as a regulatory switch. This switch elevates protein production from the main ORF under stress conditions; however, minimal to no proteins are produced under the normal condition. Because, in stress, a larger fraction of 43S ribosomes bypasses the upstream ORF due to its weak Kozak context. This, in turn, increases the number of scanning ribosomes reaching the main ORF, whose strong Kozak context can convert them into 80S ribosomes, even under stress conditions. This switching allows an efficient use of cellular resources by producing proteins when they are required. Thus, our computational study provides valuable insights into our understanding of stress-responsive translation-initiation.

Single-molecule tracking reveals dynamic regulation of ribosomal scanning

How eukaryotic ribosomes traverse messenger RNA (mRNA) leader sequences to search for protein-synthesis start sites remains one of the most mysterious aspects of translation and its regulation. While the search process is conventionally described by a linear "scanning" model, its exquisitely dynamic nature has restricted detailed mechanistic study. Here, we observed single Saccharomyces cerevisiae ribosomal scanning complexes in real time, finding that they scan diverse mRNA leaders at a rate of 10 to 20 nt s-1. We show that specific binding of a protein to its mRNA leader sequence substantially arrests scanning. Conversely, impairing scanning-complex guanosine 5'-triphosphate hydrolysis results in native start-site bypass. Our results illustrate an mRNA-centric, kinetically controlled regulatory model where the ribosomal pre-initiation complex amplifies a nuanced energetic landscape to regulate scanning and start-site selection fidelity.

eIF4A1 enhances LARP1-mediated translational repression during mTORC1 inhibition

Eukaryotic translation initiation factor (eIF)4A-a DEAD-box RNA-binding protein-plays an essential role in translation initiation. Recent reports have suggested helicase-dependent and helicase-independent functions for eIF4A, but the multifaceted roles of eIF4A have not been fully explored. Here we show that eIF4A1 enhances translational repression during the inhibition of mechanistic target of rapamycin complex 1 (mTORC1), an essential kinase complex controlling cell proliferation. RNA pulldown followed by sequencing revealed that eIF4A1 preferentially binds to mRNAs containing terminal oligopyrimidine (TOP) motifs, whose translation is rapidly repressed upon mTORC1 inhibition. This selective interaction depends on a La-related RNA-binding protein, LARP1. Ribosome profiling revealed that deletion of EIF4A1 attenuated the translational repression of TOP mRNAs upon mTORC1 inactivation. Moreover, eIF4A1 increases the interaction between TOP mRNAs and LARP1 and, thus, ensures stronger translational repression upon mTORC1 inhibition. Our data show the multimodality of eIF4A1 in modulating protein synthesis through an inhibitory binding partner and provide a unique example of the repressive role of a universal translational activator.

Synonymous codon substitutions modulate transcription and translation of a divergent upstream gene by modulating antisense RNA production

Synonymous codons were originally viewed as interchangeable, with no phenotypic consequences. However, substantial evidence has now demonstrated that synonymous substitutions can perturb a variety of gene expression and protein homeostasis mechanisms, including translational efficiency, translational fidelity, and cotranslational folding of the encoded protein. To date, most studies of synonymous codon-derived perturbations have focused on effects within a single gene. Here, we show that synonymous codon substitutions made far within the coding sequence of Escherichia coli plasmid-encoded chloramphenicol acetyltransferase (cat) can significantly increase expression of the divergent upstream tetracycline resistance gene, tetR. In four out of nine synonymously recoded cat sequences tested, expression of the upstream tetR gene was significantly elevated due to transcription of a long antisense RNA (asRNA) originating from a transcription start site within cat. Surprisingly, transcription of this asRNA readily bypassed the native tet transcriptional repression mechanism. Even more surprisingly, accumulation of the TetR protein correlated with the level of asRNA, rather than total tetR RNA. These effects of synonymous codon substitutions on transcription and translation of a neighboring gene suggest that synonymous codon usage in bacteria may be under selection to both preserve the amino acid sequence of the encoded gene and avoid DNA sequence elements that can significantly perturb expression of neighboring genes. Avoiding such sequences may be especially important in plasmids and prokaryotic genomes, where genes and regulatory elements are often densely packed. Similar considerations may apply to the design of genetic circuits for synthetic biology applications.

Pleiotropic effects of PAB1 deletion: Extensive changes in the yeast proteome, transcriptome, and translatome

Cytoplasmic poly(A)-binding protein (PABPC; Pab1 in yeast) is thought to be involved in multiple steps of post-transcriptional control, including translation initiation, translation termination, and mRNA decay. To understand both the direct and indirect roles of PABPC in more detail, we have employed mass spectrometry to assess the abundance of the components of the yeast proteome, as well as RNA-Seq and Ribo-Seq to analyze changes in the abundance and translation of the yeast transcriptome, in cells lacking the PAB1 gene. We find that pab1Δ cells manifest drastic changes in the proteome and transcriptome, as well as defects in translation initiation and termination. Defects in translation initiation and the stabilization of specific classes of mRNAs in pab1Δ cells appear to be partly indirect consequences of reduced levels of specific initiation factors, decapping activators, and components of the deadenylation complex in addition to the general loss of Pab1's direct role in these processes. Cells devoid of Pab1 also manifested a nonsense codon readthrough phenotype indicative of a defect in translation termination. Collectively, our results indicate that, unlike the loss of simpler regulatory proteins, elimination of cellular Pab1 is profoundly pleiotropic and disruptive to numerous aspects of post-transcriptional regulation.

Translation elongation as a rate limiting step of protein production

The impact of synonymous codon choice on protein output has important implications for understanding endogenous gene expression and design of synthetic mRNAs. Synonymous codons are decoded at different speeds, but simple models predict that this should not drive protein output. Instead, translation initiation should be the rate limiting step for production of protein per mRNA, with little impact of codon choice. Previously, we used a neural network model to design a series of synonymous fluorescent reporters and showed that their protein output in yeast spanned a seven-fold range corresponding to their predicted translation elongation speed. Here, we show that this effect is not due primarily to the established impact of slow elongation on mRNA stability, but rather, that slow elongation further decreases the number of proteins made per mRNA. We combine simulations and careful experiments on fluorescent reporters to show that translation is limited on non-optimally encoded transcripts. Using a genome-wide CRISPRi screen, we find that impairing translation initiation attenuates the impact of slow elongation, showing a dynamic balance between rate limiting steps of protein production. Our results show that codon choice can directly limit protein production across the full range of endogenous variability in codon usage.

Calibrated ribosome profiling assesses the dynamics of ribosomal flux on transcripts

Ribosome profiling, which is based on deep sequencing of ribosome footprints, has served as a powerful tool for elucidating the regulatory mechanism of protein synthesis. However, the current method has substantial issues: contamination by rRNAs and the lack of appropriate methods to measure ribosome numbers in transcripts. Here, we overcome these hurdles through the development of "Ribo-FilterOut", which is based on the separation of footprints from ribosome subunits by ultrafiltration, and "Ribo-Calibration", which relies on external spike-ins of stoichiometrically defined mRNA-ribosome complexes. A combination of these approaches estimates the number of ribosomes on a transcript, the translation initiation rate, and the overall number of translation events before its decay, all in a genome-wide manner. Moreover, our method reveals the allocation of ribosomes under heat shock stress, during aging, and across cell types. Our strategy of modified ribosome profiling measures kinetic and stoichiometric parameters of cellular translation across the transcriptome.

Current limitations in predicting mRNA translation with deep learning models

BACKGROUND

The design of nucleotide sequences with defined properties is a long-standing problem in bioengineering. An important application is protein expression, be it in the context of research or the production of mRNA vaccines. The rate of protein synthesis depends on the 5' untranslated region (5'UTR) of the mRNAs, and recently, deep learning models were proposed to predict the translation output of mRNAs from the 5'UTR sequence. At the same time, large data sets of endogenous and reporter mRNA translation have become available.

RESULTS

In this study, we use complementary data obtained in two different cell types to assess the accuracy and generality of currently available models for predicting translational output. We find that while performing well on the data sets on which they were trained, deep learning models do not generalize well to other data sets, in particular of endogenous mRNAs, which differ in many properties from reporter constructs.

CONCLUSIONS

These differences limit the ability of deep learning models to uncover mechanisms of translation control and to predict the impact of genetic variation. We suggest directions that combine high-throughput measurements and machine learning to unravel mechanisms of translation control and improve construct design.

OTUD6 deubiquitination of RPS7/eS7 on the free 40 S ribosome regulates global protein translation and stress

Ribosomes are regulated by evolutionarily conserved ubiquitination/deubiquitination events. We uncover the role of the deubiquitinase OTUD6 in regulating global protein translation through deubiquitination of the RPS7/eS7 subunit on the free 40 S ribosome in vivo in Drosophila. Coimmunoprecipitation and enrichment of monoubiquitinated proteins from catalytically inactive OTUD6 flies reveal RPS7 as the ribosomal substrate. The 40 S protein RACK1 and E3 ligases CNOT4 and RNF10 function upstream of OTUD6 to regulate alkylation stress. OTUD6 interacts with RPS7 specifically on the free 40 S, and not on 43 S/48 S initiation complexes or the translating ribosome. Global protein translation levels are bidirectionally regulated by OTUD6 protein abundance. OTUD6 protein abundance is physiologically regulated in aging and in response to translational and alkylation stress. Thus, OTUD6 may promote translation initiation, the rate limiting step in protein translation, by titering the amount of 40 S ribosome that recycles.

Thermal adaptation in plants: understanding the dynamics of translation factors and condensates

Plants, as sessile organisms, face the crucial challenge of adjusting growth and development with ever-changing environmental conditions. Protein synthesis is the fundamental process that enables growth of all organisms. Since elevated temperature presents a substantial threat to protein stability and function, immediate adjustments of protein synthesis rates are necessary to circumvent accumulation of proteotoxic stress and to ensure survival. This review provides an overview of the mechanisms that control translation under high-temperature stress by the modification of components of the translation machinery in plants, and compares them to yeast and metazoa. Recent research also suggests an important role for cytoplasmic biomolecular condensates, named stress granules, in these processes. Current understanding of the role of stress granules in translational regulation and of the molecular processes associated with translation that might occur within stress granules is also discussed.

Enrichment of rare codons at 5' ends of genes is a spandrel caused by evolutionary sequence turnover and does not improve translation

Previously, Tuller et al. found that the first 30-50 codons of the genes of yeast and other eukaryotes are slightly enriched for rare codons. They argued that this slowed translation, and was adaptive because it queued ribosomes to prevent collisions. Today, the translational speeds of different codons are known, and indeed rare codons are translated slowly. We re-examined this 5' slow translation 'ramp.' We confirm that 5' regions are slightly enriched for rare codons; in addition, they are depleted for downstream Start codons (which are fast), with both effects contributing to slow 5' translation. However, we also find that the 5' (and 3') ends of yeast genes are poorly conserved in evolution, suggesting that they are unstable and turnover relatively rapidly. When a new 5' end forms de novo, it is likely to include codons that would otherwise be rare. Because evolution has had a relatively short time to select against these codons, 5' ends are typically slightly enriched for rare, slow codons. Opposite to the expectation of Tuller et al., we show by direct experiment that genes with slowly translated codons at the 5' end are expressed relatively poorly, and that substituting faster synonymous codons improves expression. Direct experiment shows that slow codons do not prevent downstream ribosome collisions. Further informatic studies suggest that for natural genes, slow 5' ends are correlated with poor gene expression, opposite to the expectation of Tuller et al. Thus, we conclude that slow 5' translation is a 'spandrel'--a non-adaptive consequence of something else, in this case, the turnover of 5' ends in evolution, and it does not improve translation.

Depletion of cap-binding protein eIF4E dysregulates amino acid metabolic gene expression

Protein synthesis is metabolically costly and must be tightly coordinated with changing cellular needs and nutrient availability. The cap-binding protein eIF4E makes the earliest contact between mRNAs and the translation machinery, offering a key regulatory nexus. We acutely depleted this essential protein and found surprisingly modest effects on cell growth and recovery of protein synthesis. Paradoxically, impaired protein biosynthesis upregulated genes involved in the catabolism of aromatic amino acids simultaneously with the induction of the amino acid biosynthetic regulon driven by the integrated stress response factor GCN4. We further identified the translational control of Pho85 cyclin 5 (PCL5), a negative regulator of Gcn4, that provides a consistent protein-to-mRNA ratio under varied translation environments. This regulation depended in part on a uniquely long poly(A) tract in the PCL5 5' UTR and poly(A) binding protein. Collectively, these results highlight how eIF4E connects protein synthesis to metabolic gene regulation, uncovering mechanisms controlling translation during environmental challenges.

TIR predictor and optimizer: Web-tools for accurate prediction of translation initiation rate and precision gene design in Saccharomyces cerevisiae

Translation initiation is the primary determinant of the rate of protein production. The variation in the rate with which this step occurs can cause up to three orders of magnitude differences in cellular protein levels. Several mRNA features, including mRNA stability in proximity to the start codon, coding sequence length, and presence of specific motifs in the mRNA molecule, have been shown to influence the translation initiation rate. These molecular factors acting at different strengths allow precise control of in vivo translation initiation rate and thus the rate of protein synthesis. However, despite the paramount importance of translation initiation rate in protein synthesis, accurate prediction of the absolute values of initiation rate remains a challenge. In fact, as of now, there is no available model for predicting the initiation rate in Saccharomyces cerevisiae. To address this, we train a machine learning model for predicting the in vivo initiation rate in S. cerevisiae transcripts. The model is trained using a diverse set of mRNA transcripts, enabling the comparison of initiation rates across different transcripts. Our model exhibited excellent accuracy in predicting the translation initiation rate and demonstrated its effectiveness with both endogenous and exogenous transcripts. Then, by combining the machine learning model with the Monte-Carlo search algorithm, we have also devised a method to optimize the nucleotide sequence of any gene to achieve a specific target initiation rate. The machine learning model we've developed for predicting translation initiation rates, along with the gene optimization method, are deployed as a web server. Both web servers are accessible for free at the following link: ajeetsharmalab.com/TIRPredictor. Thus, this research advances our fundamental understanding of translation initiation processes, with direct applications in biotechnology.

What, where, and how: Regulation of translation and the translational landscape in plants

Translation is a crucial step in gene expression and plays a vital role in regulating various aspects of plant development and environmental responses. It is a dynamic and complex program that involves interactions between mRNAs, transfer RNAs, and the ribosome machinery through both cis- and trans-regulation while integrating internal and external signals. Translational control can act in a global (transcriptome-wide) or mRNA-specific manner. Recent advances in genome-wide techniques, particularly ribosome profiling and proteomics, have led to numerous exciting discoveries in both global and mRNA-specific translation. In this review, we aim to provide a "primer" that introduces readers to this fascinating yet complex cellular process and provide a big picture of how essential components connect within the network. We begin with an overview of mRNA translation, followed by a discussion of the experimental approaches and recent findings in the field, focusing on unannotated translation events and translational control through cis-regulatory elements on mRNAs and trans-acting factors, as well as signaling networks through 3 conserved translational regulators TOR, SnRK1, and GCN2. Finally, we briefly touch on the spatial regulation of mRNAs in translational control. Here, we focus on cytosolic mRNAs; translation in organelles and viruses is not covered in this review.

Evolving precision: rRNA expansion segment 7S modulates translation velocity and accuracy in eukaryal ribosomes

Ribosome-enhanced translational miscoding of the genetic code causes protein dysfunction and loss of cellular fitness. During evolution, open reading frame length increased, necessitating mechanisms for enhanced translation fidelity. Indeed, eukaryal ribosomes are more accurate than bacterial counterparts, despite their virtually identical, conserved active centers. During the evolution of eukaryotic organisms ribosome expansions at the rRNA and protein level occurred, which potentially increases the options for translation regulation and cotranslational events. Here we tested the hypothesis that ribosomal RNA expansions can modulate the core function of the ribosome, faithful protein synthesis. We demonstrate that a short expansion segment present in all eukaryotes' small subunit, ES7S, is crucial for accurate protein synthesis as its presence adjusts codon-specific velocities and guarantees high levels of cognate tRNA selection. Deletion of ES7S in yeast enhances mistranslation and causes protein destabilization and aggregation, dramatically reducing cellular fitness. Removal of ES7S did not alter ribosome architecture but altered the structural dynamics of inter-subunit bridges thus affecting A-tRNA selection. Exchanging the yeast ES7S sequence with the human ES7S increases accuracy whereas shortening causes the opposite effect. Our study demonstrates that ES7S provided eukaryal ribosomes with higher accuracy without perturbing the structurally conserved decoding center.

Single-molecule RNA-FISH analysis reveals stochasticity in reactivation of latent HIV-1 regulated by Nuclear Orphan Receptors NR4A and cMYC

HIV-1 eradication strategies require complete reactivation of HIV-1 latent cells by Latency Reversing Agents (LRA). Current methods lack effectiveness due to incomplete proviral reactivation. We employed a single-molecule RNA-FISH (smRNA-FISH) and FISH-Quant analysis and found that proviral reactivation is highly variable from cell-to-cell, stochastic, and occurs in bursts and waves, with different kinetics in response to diverse LRAs. Approximately 1-5% of latent cells exhibited stochastic reactivation without LRAs. Through single-cell RNA-seq analysis, we identified NR4A3 and cMYC as extrinsic factors associated with stochastic HIV-1 reactivation. Concomitant with HIV-1 reactivation cMYC was downregulated and NR4A3 was upregulated in both latent cell lines and primary CD4+ T-cells from aviremic patients. By inhibiting cMYC using SN-38, an active metabolite of irinotecan, we induced NR4A3 and HIV-1 expression. Our results suggest that inherent stochasticity in proviral reactivation contributes to cell-to-cell variability, which could potentially be modulated by drugs targeting cMYC and NR4A3.

Harnessing anti-inflammatory pathways and macrophage nano delivery to treat inflammatory and fibrotic disorders

Targeting specific organs and cell types using nanotechnology and sophisticated delivery methods has been at the forefront of applicative biomedical sciences lately. Macrophages are an appealing target for immunomodulation by nanodelivery as they are heavily involved in various aspects of many diseases and are highly plastic in their nature. Their continuum of functional "polarization" states has been a research focus for many years yielding a profound understanding of various aspects of these cells. The ability of monocyte-derived macrophages to metamorphose from pro-inflammatory to reparative and consequently to pro-resolving effectors has raised significant interest in its therapeutic potential. Here, we briefly survey macrophages' ontogeny and various polarization phenotypes, highlighting their function in the inflammation-resolution shift. We review their inducing mediators, signaling pathways, and biological programs with emphasis on the nucleic acid sensing-IFN-I axis. We also portray the polarization spectrum of macrophages and the characteristics of their transition between different subtypes. Finally, we highlighted different current drug delivery methods for targeting macrophages with emphasis on nanotargeting that might lead to breakthroughs in the treatment of wound healing, bone regeneration, autoimmune, and fibrotic diseases.

Ribosomal mutations enable a switch between high fitness and high stress resistance in Listeria monocytogenes

Multiple stress resistant variants of Listeria monocytogenes with mutations in rpsU encoding ribosomal protein RpsU have previously been isolated after a single exposure to acid stress. These variants, including L. monocytogenes LO28 variant V14 with a complete deletion of the rpsU gene, showed upregulation of the general stress sigma factor Sigma B-mediated stress resistance genes and had a lower maximum specific growth rate than the LO28 WT, signifying a trade-off between stress resistance and fitness. In the current work V14 has been subjected to an experimental evolution regime, selecting for higher fitness in two parallel evolving cultures. This resulted in two evolved variants with WT-like fitness: 14EV1 and 14EV2. Comparative analysis of growth performance, acid and heat stress resistance, in combination with proteomics and RNA-sequencing, indicated that in both lines reversion to WT-like fitness also resulted in WT-like stress sensitivity, due to lack of Sigma B-activated stress defense. Notably, genotyping of 14EV1 and 14EV2 provided evidence for unique point-mutations in the ribosomal rpsB gene causing amino acid substitutions at the same position in RpsB, resulting in RpsB22Arg-His and RpsB22Arg-Ser, respectively. Combined with data obtained with constructed RpsB22Arg-His and RpsB22Arg-Ser mutants in the V14 background, we provide evidence that loss of function of RpsU resulting in the multiple stress resistant and reduced fitness phenotype, can be reversed by single point mutations in rpsB leading to arginine substitutions in RpsB at position 22 into histidine or serine, resulting in a WT-like high fitness and low stress resistance phenotype. This demonstrates the impact of genetic changes in L. monocytogenes' ribosomes on fitness and stress resistance.

The impact of multiple abiotic stresses on ns-LTP2.8 gene transcript and ns-LTP2.8 protein accumulation in germinating barley (Hordeum vulgare L.) embryos

Abiotic stresses occur more often in combination than alone under regular field conditions limiting in more severe way crop production. Stress recognition in plants primarily occurs in the plasma membrane, modification of which is necessary to maintain homeostasis in response to it. It is known that lipid transport proteins (ns-LTPs) participate in modification of the lipidome of cell membranes. Representative of this group, ns-LTP2.8, may be involved in the reaction to abiotic stress of germinating barley plants by mediating the intracellular transport of hydrophobic particles, such as lipids, helping to maintain homeostasis. The ns-LTP2.8 protein was selected for analysis due to its ability to transport not only linear hydrophobic molecules but also compounds with a more complex spatial structure. Moreover, ns-LTP2.8 has been qualified as a member of pathogenesis-related proteins, which makes it particularly important in relation to its high allergenic potential. This paper demonstrates for the first time the influence of various abiotic stresses acting separately as well as in their combinations on the change in the ns-LTP2.8 transcript, ns-LTP2.8 protein and total soluble protein content in the embryonal axes of germinating spring barley genotypes with different ns-LTP2.8 allelic forms and stress tolerance. Tissue localization of ns-LTP2.8 transcript as well as ns-LTP2.8 protein were also examined. Although the impact of abiotic stresses on the regulation of gene transcription and translation processes remains not fully recognized, in this work we managed to demonstrate different impact on applied stresses on the fundamental cellular processes in very little studied tissue of the embryonal axis of barley.

Riboformer: a deep learning framework for predicting context-dependent translation dynamics

Translation elongation is essential for maintaining cellular proteostasis, and alterations in the translational landscape are associated with a range of diseases. Ribosome profiling allows detailed measurements of translation at the genome scale. However, it remains unclear how to disentangle biological variations from technical artifacts in these data and identify sequence determinants of translation dysregulation. Here we present Riboformer, a deep learning-based framework for modeling context-dependent changes in translation dynamics. Riboformer leverages the transformer architecture to accurately predict ribosome densities at codon resolution. When trained on an unbiased dataset, Riboformer corrects experimental artifacts in previously unseen datasets, which reveals subtle differences in synonymous codon translation and uncovers a bottleneck in translation elongation. Further, we show that Riboformer can be combined with in silico mutagenesis to identify sequence motifs that contribute to ribosome stalling across various biological contexts, including aging and viral infection. Our tool offers a context-aware and interpretable approach for standardizing ribosome profiling datasets and elucidating the regulatory basis of translation kinetics.

METTL16 promotes liver cancer stem cell self-renewal via controlling ribosome biogenesis and mRNA translation

BACKGROUND

While liver cancer stem cells (CSCs) play a crucial role in hepatocellular carcinoma (HCC) initiation, progression, recurrence, and treatment resistance, the mechanism underlying liver CSC self-renewal remains elusive. We aim to characterize the role of Methyltransferase 16 (METTL16), a recently identified RNA N6-methyladenosine (m6A) methyltransferase, in HCC development/maintenance, CSC stemness, as well as normal hepatogenesis.

METHODS

Liver-specific Mettl16 conditional KO (cKO) mice were generated to assess its role in HCC pathogenesis and normal hepatogenesis. Hydrodynamic tail-vein injection (HDTVi)-induced de novo hepatocarcinogenesis and xenograft models were utilized to determine the role of METTL16 in HCC initiation and progression. A limiting dilution assay was utilized to evaluate CSC frequency. Functionally essential targets were revealed via integrative analysis of multi-omics data, including RNA-seq, RNA immunoprecipitation (RIP)-seq, and ribosome profiling.

RESULTS

METTL16 is highly expressed in liver CSCs and its depletion dramatically decreased CSC frequency in vitro and in vivo. Mettl16 KO significantly attenuated HCC initiation and progression, yet only slightly influenced normal hepatogenesis. Mechanistic studies, including high-throughput sequencing, unveiled METTL16 as a key regulator of ribosomal RNA (rRNA) maturation and mRNA translation and identified eukaryotic translation initiation factor 3 subunit a (eIF3a) transcript as a bona-fide target of METTL16 in HCC. In addition, the functionally essential regions of METTL16 were revealed by CRISPR gene tiling scan, which will pave the way for the development of potential inhibitor(s).

CONCLUSIONS

Our findings highlight the crucial oncogenic role of METTL16 in promoting HCC pathogenesis and enhancing liver CSC self-renewal through augmenting mRNA translation efficiency.

Decoding stoichiometric protein synthesis in E. coli through translation rate parameters

E. coli is one of the most widely used organisms for understanding the principles of cellular and molecular genetics. However, we are yet to understand the origin of several experimental observations related to the regulation of gene expression in E. coli. One of the prominent examples in this context is the proportional synthesis in multiprotein complexes where all of their obligate subunits are produced in proportion to their stoichiometry. In this work, by combining the next-generation sequencing data with the stochastic simulations of protein synthesis, we explain the origin of proportional protein synthesis in multicomponent complexes. We find that the estimated initiation rates for the translation of all subunits in those complexes are proportional to their stoichiometry. This constraint on protein synthesis kinetics enforces proportional protein synthesis without requiring any feedback mechanism. We also find that the translation initiation rates in E. coli are influenced by the coding sequence length and the enrichment of A and C nucleotides near the start codon. Thus, this study rationalizes the role of conserved and nonrandom features of genes in regulating the translation kinetics and unravels a key principle of the regulation of protein synthesis.

C-Terminal Domain Controls Protein Quality and Secretion of Spider Silk in Tobacco Cells

The remarkable mechanical strength and extensibility of spider dragline silk spidroins are attributed to the major ampullate silk proteins (MaSp). Although fragmented MaSp molecules have been extensively produced in various heterologous expression platforms for biotechnological applications, complete MaSp molecules are required to achieve instinctive spinning of spidroin fibers from aqueous solutions. Here, a plant cell-based expression platform for extracellular production of the entire MaSp2 protein is developed, which exhibits remarkable self-assembly properties to form spider silk nanofibrils. The engineered transgenic Bright-yellow 2 (BY-2) cell lines overexpressing recombinant secretory MaSp2 proteins yield 0.6-1.3  µg L-1 at 22 days post-inoculation, which is four times higher than those of cytosolic expressions. However, only 10-15% of these secretory MaSp2 proteins are discharged into the culture media. Surprisingly, expression of functional domain-truncated MaSp2 proteins lacking the C-terminal domain in transgenic BY-2 cells increases recombinant protein secretion incredibly, from 0.9 to 2.8 mg L-1 per day within 7 days. These findings demonstrate significant improvement in the extracellular production of recombinant biopolymers such as spider silk spidroins using plant cells. In addition, the results reveal the regulatory roles of the C-terminal domain of MaSp2 proteins in controlling their protein quality and secretion.

Quantification of elongation stalls and impact on gene expression in yeast

Ribosomal pauses are a critical part of cotranslational events including protein folding and localization. However, extended ribosome pauses can lead to ribosome collisions, resulting in the activation of ribosome rescue pathways and turnover of protein and mRNA. While this relationship has been known, there has been little exploration of how ribosomal stalls impact translation duration at a quantitative level. We have taken a method used to measure elongation time and adapted it for use in Saccharomyces cerevisiae to quantify the impact of elongation stalls. We find, in transcripts containing Arg CGA codon repeat-induced stalls, a Hel2-mediated dose-dependent decrease in protein expression and mRNA level and an elongation delay on the order of minutes. In transcripts that contain synonymous substitutions to nonoptimal Leu codons, there is a decrease in protein and mRNA levels, as well as similar elongation delay, but this occurs through a non-Hel2-mediated mechanism. Finally, we find that Dhh1 selectively increases protein expression, mRNA level, and elongation rate. This indicates that distinct poorly translated mRNAs will activate different rescue pathways despite similar elongation stall durations. Taken together, these results provide new quantitative mechanistic insight into the surveillance of translation and the roles of Hel2 and Dhh1 in mediating ribosome pausing events.

Arabidopsis eIF4E1 protects the translational machinery during TuMV infection and restricts virus accumulation

Successful subversion of translation initiation factors eIF4E determines the infection success of potyviruses, the largest group of viruses affecting plants. In the natural variability of many plant species, resistance to potyvirus infection is provided by polymorphisms at eIF4E that renders them inadequate for virus hijacking but still functional in translation initiation. In crops where such natural resistance alleles are limited, the genetic inactivation of eIF4E has been proposed for the engineering of potyvirus resistance. However, recent findings indicate that knockout eIF4E alleles may be deleterious for plant health and could jeopardize resistance efficiency in comparison to functional resistance proteins. Here, we explored the cause of these adverse effects by studying the role of the Arabidopsis eIF4E1, whose inactivation was previously reported as conferring resistance to the potyvirus clover yellow vein virus (ClYVV) while also promoting susceptibility to another potyvirus turnip mosaic virus (TuMV). We report that eIF4E1 is required to maintain global plant translation and to restrict TuMV accumulation during infection, and its absence is associated with a favoured virus multiplication over host translation. Furthermore, our findings show that, in the absence of eIF4E1, infection with TuMV results in the production of a truncated eIFiso4G1 protein. Finally, we demonstrate a role for eIFiso4G1 in TuMV accumulation and in supporting plant fitness during infection. These findings suggest that eIF4E1 counteracts the hijacking of the plant translational apparatus during TuMV infection and underscore the importance of preserving the functionality of translation initiation factors eIF4E when implementing potyvirus resistance strategies.

Bioinformatic Analysis Reveals the Role of Translation Elongation Efficiency Optimisation in the Evolution of Ralstonia Genus

Translation efficiency modulates gene expression in prokaryotes. The comparative analysis of translation elongation efficiency characteristics of Ralstonia genus bacteria genomes revealed that these characteristics diverge in accordance with the phylogeny of Ralstonia. The first branch of this genus is a group of bacteria commonly found in moist environments such as soil and water that includes the species R. mannitolilytica, R. insidiosa, and R. pickettii, which are also described as nosocomial infection pathogens. In contrast, the second branch is plant pathogenic bacteria consisting of R. solanacearum, R. pseudosolanacearum, and R. syzygii. We found that the soil Ralstonia have a significantly lower number and energy of potential secondary structures in mRNA and an increased role of codon usage bias in the optimization of highly expressed genes' translation elongation efficiency, not only compared to phytopathogenic Ralstonia but also to Cupriavidus necator, which is closely related to the Ralstonia genus. The observed alterations in translation elongation efficiency of orthologous genes are also reflected in the difference of potentially highly expressed gene' sets' content among Ralstonia branches with different lifestyles. Analysis of translation elongation efficiency characteristics can be considered a promising approach for studying complex mechanisms that determine the evolution and adaptation of bacteria in various environments.

Comprehensive quantitative modeling of translation efficiency in a genome-reduced bacterium

Translation efficiency has been mainly studied by ribosome profiling, which only provides an incomplete picture of translation kinetics. Here, we integrated the absolute quantifications of tRNAs, mRNAs, RNA half-lives, proteins, and protein half-lives with ribosome densities and derived the initiation and elongation rates for 475 genes (67% of all genes), 73 with high precision, in the bacterium Mycoplasma pneumoniae (Mpn). We found that, although the initiation rate varied over 160-fold among genes, most of the known factors had little impact on translation efficiency. Local codon elongation rates could not be fully explained by the adaptation to tRNA abundances, which varied over 100-fold among tRNA isoacceptors. We provide a comprehensive quantitative view of translation efficiency, which suggests the existence of unidentified mechanisms of translational regulation in Mpn.

Translation factor and RNA binding protein mRNA interactomes support broader RNA regulons for posttranscriptional control

The regulation of translation provides a rapid and direct mechanism to modulate the cellular proteome. In eukaryotes, an established model for the recruitment of ribosomes to mRNA depends upon a set of conserved translation initiation factors. Nevertheless, how cells orchestrate and define the selection of individual mRNAs for translation, as opposed to other potential cytosolic fates, is poorly understood. We have previously found significant variation in the interaction between individual mRNAs and an array of translation initiation factors. Indeed, mRNAs can be separated into different classes based upon these interactions to provide a framework for understanding different modes of translation initiation. Here, we extend this approach to include new mRNA interaction profiles for additional proteins involved in shaping the cytoplasmic fate of mRNAs. This work defines a set of seven mRNA clusters, based on their interaction profiles with 12 factors involved in translation and/or RNA binding. The mRNA clusters share both physical and functional characteristics to provide a rationale for the interaction profiles. Moreover, a comparison with mRNA interaction profiles from a host of RNA binding proteins suggests that there are defined patterns in the interactions of functionally related mRNAs. Therefore, this work defines global cytoplasmic mRNA binding modules that likely coordinate the synthesis of functionally related proteins.

Clearing the slate: RNA turnover to enable cell state switching?

The distribution of mRNA in tissue is determined by the balance between transcription and decay. Understanding the control of RNA decay during development has been somewhat neglected compared with transcriptional control. Here, we explore the potential for mRNA decay to trigger rapid cell state transitions during development, comparing a bistable switch model of cell state conversion with experimental evidence from different developmental systems. We also consider another potential role for large-scale RNA decay that has emerged from studies of stress-induced cell state transitions, in which removal of mRNA unblocks the translation machinery to prioritise the synthesis of proteins that establish the new cell state.

spotter: a single-nucleotide resolution stochastic simulation model of supercoiling-mediated transcription and translation in prokaryotes

Stochastic simulation models have played an important role in efforts to understand the mechanistic basis of prokaryotic transcription and translation. Despite the fundamental linkage of these processes in bacterial cells, however, most simulation models have been limited to representations of either transcription or translation. In addition, the available simulation models typically either attempt to recapitulate data from single-molecule experiments without considering cellular-scale high-throughput sequencing data or, conversely, seek to reproduce cellular-scale data without paying close attention to many of the mechanistic details. To address these limitations, we here present spotter (Simulation of Prokaryotic Operon Transcription & Translation Elongation Reactions), a flexible, user-friendly simulation model that offers highly-detailed combined representations of prokaryotic transcription, translation, and DNA supercoiling. In incorporating nascent transcript and ribosomal profiling sequencing data, spotter provides a critical bridge between data collected in single-molecule experiments and data collected at the cellular scale. Importantly, in addition to rapidly generating output that can be aggregated for comparison with next-generation sequencing and proteomics data, spotter produces residue-level positional information that can be used to visualize individual simulation trajectories in detail. We anticipate that spotter will be a useful tool in exploring the interplay of processes that are crucially linked in prokaryotes.

Algorithm for optimized mRNA design improves stability and immunogenicity

Messenger RNA (mRNA) vaccines are being used to combat the spread of COVID-19 (refs. 1-3), but they still exhibit critical limitations caused by mRNA instability and degradation, which are major obstacles for the storage, distribution and efficacy of the vaccine products4. Increasing secondary structure lengthens mRNA half-life, which, together with optimal codons, improves protein expression5. Therefore, a principled mRNA design algorithm must optimize both structural stability and codon usage. However, owing to synonymous codons, the mRNA design space is prohibitively large-for example, there are around 2.4 × 10632 candidate mRNA sequences for the SARS-CoV-2 spike protein. This poses insurmountable computational challenges. Here we provide a simple and unexpected solution using the classical concept of lattice parsing in computational linguistics, where finding the optimal mRNA sequence is analogous to identifying the most likely sentence among similar-sounding alternatives6. Our algorithm LinearDesign finds an optimal mRNA design for the spike protein in just 11 minutes, and can concurrently optimize stability and codon usage. LinearDesign substantially improves mRNA half-life and protein expression, and profoundly increases antibody titre by up to 128 times in mice compared to the codon-optimization benchmark on mRNA vaccines for COVID-19 and varicella-zoster virus. This result reveals the great potential of principled mRNA design and enables the exploration of previously unreachable but highly stable and efficient designs. Our work is a timely tool for vaccines and other mRNA-based medicines encoding therapeutic proteins such as monoclonal antibodies and anti-cancer drugs7,8.

On the Decoupling of Evolutionary Changes in mRNA and Protein Levels

Variation in gene expression across lineages is thought to explain much of the observed phenotypic variation and adaptation. The protein is closer to the target of natural selection but gene expression is typically measured as the amount of mRNA. The broad assumption that mRNA levels are good proxies for protein levels has been undermined by a number of studies reporting moderate or weak correlations between the two measures across species. One biological explanation for this discrepancy is that there has been compensatory evolution between the mRNA level and regulation of translation. However, we do not understand the evolutionary conditions necessary for this to occur nor the expected strength of the correlation between mRNA and protein levels. Here, we develop a theoretical model for the coevolution of mRNA and protein levels and investigate the dynamics of the model over time. We find that compensatory evolution is widespread when there is stabilizing selection on the protein level; this observation held true across a variety of regulatory pathways. When the protein level is under directional selection, the mRNA level of a gene and the translation rate of the same gene were negatively correlated across lineages but positively correlated across genes. These findings help explain results from comparative studies of gene expression and potentially enable researchers to disentangle biological and statistical hypotheses for the mismatch between transcriptomic and proteomic data.

Evolutionary barriers to horizontal gene transfer in macrophage-associated Salmonella

Horizontal gene transfer (HGT) is a powerful evolutionary force facilitating bacterial adaptation and emergence of novel phenotypes. Several factors, including environmental ones, are predicted to restrict HGT, but we lack systematic and experimental data supporting these predictions. Here, we address this gap by measuring the relative fitness of 44 genes horizontally transferred from Escherichia coli to Salmonella enterica in infection-relevant environments. We estimated the distribution of fitness effects in each environment and identified that dosage-dependent effects across different environments are a significant barrier to HGT. The majority of genes were found to be deleterious. We also found longer genes had stronger negative fitness consequences than shorter ones, showing that gene length was negatively associated with HGT. Furthermore, fitness effects of transferred genes were found to be environmentally dependent. In summary, a substantial fraction of transferred genes had a significant fitness cost on the recipient, with both gene characteristics and the environment acting as evolutionary barriers to HGT.

A simple geometrical model of the electrostatic environment around the catalytic center of the ribosome and its significance for the elongation cycle kinetics

The central function of the large subunit of the ribosome is to catalyze peptide bond formation. This biochemical reaction is conducted at the peptidyl transferase center (PTC). Experimental evidence shows that the catalytic activity is affected by the electrostatic environment around the peptidyl transferase center. Here, we set up a minimal geometrical model fitting the available x-ray solved structures of the ribonucleic cavity around the catalytic center of the large subunit of the ribosome. The purpose of this phenomenological model is to estimate quantitatively the electrostatic potential and electric field that are experienced during the peptidyl transfer reaction. At least two reasons motivate the need for developing this quantification. First, we inquire whether the electric field in this particular catalytic environment, made only of nucleic acids, is of the same order of magnitude as the one prevailing in catalytic centers of the proteic enzymes counterparts. Second, the protein synthesis rate is dependent on the nature of the amino acid sequentially incorporated in the nascent chain. The activation energy of the catalytic reaction and its detailed kinetics are shown to be dependent on the mechanical work exerted on the amino acids by the electric field, especially when one of the four charged amino acid residues (R, K, E, D) has previously been incorporated at the carboxy-terminal end of the peptidyl-tRNA. Physical values of the electric field provide quantitative knowledge of mechanical work, activation energy and rate of the peptide bond formation catalyzed by the ribosome. We show that our theoretical calculations are consistent with two independent sets of previously published experimental results. Experimental results for E.coli in the minimal case of the dipeptide bond formation when puromycin is used as the final amino acid acceptor strongly support our theoretically derived reaction time courses. Experimental Ribo-Seq results on E. coli and S. cerevisiae comparing the residence time distribution of ribosomes upon specific codons are also well accounted for by our theoretical calculations. The statistical queueing time theory was used to model the ribosome residence time per codon during nascent protein elongation and applied for the interpretation of the Ribo-Seq data. The hypo-exponential distribution fits the residence time observed distribution of the ribosome on a codon. An educated deconvolution of this distribution is used to estimate the rates of each elongation step in a codon specific manner. Our interpretation of all these results sheds light on the functional role of the electrostatic profile around the PTC and its impact on the ribosome elongation cycle.

Highly efficient cellular expression of circular mRNA enables prolonged protein expression

A major problem with mRNA therapeutics is the limited duration of protein expression due to the short half-life of mRNA. New approaches for generating highly stable circular mRNA in vitro have allowed increased duration of protein expression. However, it remains difficult to genetically encode circular mRNAs in mammalian cells, which limits the use of circular mRNA in cell-derived therapeutics. Here we describe the adaptation of the Tornado (Twister-optimized RNA for durable overexpression) system to achieve in-cell synthesis of circular mRNAs. We identify the promoter and internal ribosomal entry site (IRES) that result in high levels of protein expression in cells. We then show that these circular mRNAs can be packaged into virus-like particles (VLPs) thus enabling prolonged protein expression. Overall, these data describe a platform for synthesis of circular mRNAs and how these circular mRNAs can markedly enhance the ability of VLPs to function as a mRNA delivery tool.

The one-message-per-cell-cycle rule: A conserved minimum transcription level for essential genes

The inherent stochasticity of cellular processes leads to significant cell-to-cell variation in protein abundance. Although this noise has already been characterized and modeled, its broader implications and significance remain unclear. In this paper, we revisit the noise model and identify the number of messages transcribed per cell cycle as the critical determinant of noise. In yeast, we demonstrate that this quantity predicts the non-canonical scaling of noise with protein abundance, as well as quantitatively predicting its magnitude. We then hypothesize that growth robustness requires an upper ceiling on noise for the expression of essential genes, corresponding to a lower floor on the transcription level. We show that just such a floor exists: a minimum transcription level of one message per cell cycle is conserved between three model organisms: Escherichia coli, yeast, and human. Furthermore, all three organisms transcribe the same number of messages per gene, per cell cycle. This common transcriptional program reveals that robustness to noise plays a central role in determining the expression level of a large fraction of essential genes, and that this fundamental optimal strategy is conserved from E. coli to human cells.

The one-message-per-cell-cycle rule: A conserved minimum transcription level for essential genes

The inherent stochasticity of cellular processes leads to significant cell-to-cell variation in protein abundance. Although this noise has already been characterized and modeled, its broader implications and significance remain unclear. In this paper, we revisit the noise model and identify the number of messages transcribed per cell cycle as the critical determinant of noise. In yeast, we demonstrate that this quantity predicts the non-canonical scaling of noise with protein abundance, as well as quantitatively predicting its magnitude. We then hypothesize that growth robustness requires an upper ceiling on noise for the expression of essential genes, corresponding to a lower floor on the transcription level. We show that just such a floor exists: a minimum transcription level of one message per cell cycle is conserved between three model organisms: Escherichia coli, yeast, and human. Furthermore, all three organisms transcribe the same number of messages per gene, per cell cycle. This common transcriptional program reveals that robustness to noise plays a central role in determining the expression level of a large fraction of essential genes, and that this fundamental optimal strategy is conserved from E. coli to human cells.

Broad anti-pathogen potential of DEAD box RNA helicase eIF4A-targeting rocaglates

Inhibition of eukaryotic initiation factor 4A has been proposed as a strategy to fight pathogens. Rocaglates exhibit the highest specificities among eIF4A inhibitors, but their anti-pathogenic potential has not been comprehensively assessed across eukaryotes. In silico analysis of the substitution patterns of six eIF4A1 aa residues critical to rocaglate binding, uncovered 35 variants. Molecular docking of eIF4A:RNA:rocaglate complexes, and in vitro thermal shift assays with select recombinantly expressed eIF4A variants, revealed that sensitivity correlated with low inferred binding energies and high melting temperature shifts. In vitro testing with silvestrol validated predicted resistance in Caenorhabditis elegans and Leishmania amazonensis and predicted sensitivity in Aedes sp., Schistosoma mansoni, Trypanosoma brucei, Plasmodium falciparum, and Toxoplasma gondii. Our analysis further revealed the possibility of targeting important insect, plant, animal, and human pathogens with rocaglates. Finally, our findings might help design novel synthetic rocaglate derivatives or alternative eIF4A inhibitors to fight pathogens.

Direct and indirect consequences of PAB1 deletion in the regulation of translation initiation, translation termination, and mRNA decay

Cytoplasmic poly(A)-binding protein (PABPC; Pab1 in yeast) is thought to be involved in multiple steps of post-transcriptional control, including translation initiation, translation termination, and mRNA decay. To understand these roles of PABPC in more detail for endogenous mRNAs, and to distinguish its direct effects from indirect effects, we have employed RNA-Seq and Ribo-Seq to analyze changes in the abundance and translation of the yeast transcriptome, as well as mass spectrometry to assess the abundance of the components of the yeast proteome, in cells lacking the PAB1 gene. We observed drastic changes in the transcriptome and proteome, as well as defects in translation initiation and termination, in pab1Δ cells. Defects in translation initiation and the stabilization of specific classes of mRNAs in pab1Δ cells appear to be partly indirect consequences of reduced levels of specific initiation factors, decapping activators, and components of the deadenylation complex in addition to the general loss of Pab1's direct role in these processes. Cells devoid of Pab1 also manifested a nonsense codon readthrough phenotype indicative of a defect in translation termination, but this defect may be a direct effect of the loss of Pab1 as it could not be attributed to significant reductions in the levels of release factors.

Dysregulation of amino acid metabolism upon rapid depletion of cap-binding protein eIF4E

Protein synthesis is a crucial but metabolically costly biological process that must be tightly coordinated with cellular needs and nutrient availability. In response to environmental stress, translation initiation is modulated to control protein output while meeting new demands. The cap-binding protein eIF4E-the earliest contact between mRNAs and the translation machinery-serves as one point of control, but its contributions to mRNA-specific translation regulation remain poorly understood. To survey eIF4E-dependent translational control, we acutely depleted eIF4E and determined how this impacts protein synthesis. Despite its essentiality, eIF4E depletion had surprisingly modest effects on cell growth and protein synthesis. Analysis of transcript-level changes revealed that long-lived transcripts were downregulated, likely reflecting accelerated turnover. Paradoxically, eIF4E depletion led to simultaneous upregulation of genes involved in catabolism of aromatic amino acids, which arose as secondary effects of reduced protein biosynthesis on amino acid pools, and genes involved in the biosynthesis of amino acids. These futile cycles of amino acid synthesis and degradation were driven, in part, by translational activation of GCN4, a transcription factor typically induced by amino acid starvation. Furthermore, we identified a novel regulatory mechanism governing translation of PCL5, a negative regulator of Gcn4, that provides a consistent protein-to-mRNA ratio under varied translation environments. This translational control was partial dependent on a uniquely long poly-(A) tract in the PCL5 5' UTR and on poly-(A) binding protein. Collectively, these results highlight how eIF4E connects translation to amino acid homeostasis and stress responses and uncovers new mechanisms underlying how cells tightly control protein synthesis during environmental challenges.

Riboformer: A Deep Learning Framework for Predicting Context-Dependent Translation Dynamics

Translation elongation is essential for maintaining cellular proteostasis, and alterations in the translational landscape are associated with a range of diseases. Ribosome profiling allows detailed measurement of translation at genome scale. However, it remains unclear how to disentangle biological variations from technical artifacts and identify sequence determinant of translation dysregulation. Here we present Riboformer, a deep learning-based framework for modeling context-dependent changes in translation dynamics. Riboformer leverages the transformer architecture to accurately predict ribosome densities at codon resolution. It corrects experimental artifacts in previously unseen datasets, reveals subtle differences in synonymous codon translation and uncovers a bottleneck in protein synthesis. Further, we show that Riboformer can be combined with in silico mutagenesis analysis to identify sequence motifs that contribute to ribosome stalling across various biological contexts, including aging and viral infection. Our tool offers a context-aware and interpretable approach for standardizing ribosome profiling datasets and elucidating the regulatory basis of translation kinetics.

spotter : A single-nucleotide resolution stochastic simulation model of supercoiling-mediated transcription and translation in prokaryotes

Stochastic simulation models have played an important role in efforts to understand the mechanistic basis of prokaryotic transcription and translation. Despite the fundamental linkage of these processes in bacterial cells, however, most simulation models have been limited to representations of either transcription or translation. In addition, the available simulation models typically either attempt to recapitulate data from single-molecule experiments without considering cellular-scale high-throughput sequencing data or, conversely, seek to reproduce cellular-scale data without paying close attention to many of the mechanistic details. To address these limitations, we here present spotter (Simulation of Prokaryotic Operon Transcription & Translation Elongation Reactions), a flexible, user-friendly simulation model that offers highly-detailed combined representations of prokaryotic transcription, translation, and DNA supercoiling. In incorporating nascent transcript and ribosomal profiling sequencing data, spotter provides a critical bridge between data collected in single-molecule experiments and data collected at the cellular scale. Importantly, in addition to rapidly generating output that can be aggregated for comparison with next-generation sequencing and proteomics data, spotter produces residue-level positional information that can be used to visualize individual simulation trajectories in detail. We anticipate that spotter will be a useful tool in exploring the interplay of processes that are crucially linked in prokaryotes.