Regulation of translation via mRNA structure in prokaryotes and eukaryotes

RNase P cleavage of pseudoknot substrates reveals differences in active site architecture that depend on residue N-1 in the 5' leader

We show that a small biotin-binding RNA aptamer that folds into a pseudoknot structure acts as a substrate for bacterial RNase P RNA (RPR) with and without the RNase P C5 protein. Cleavage in the single-stranded region in loop 1 was shown to depend on the presence of a RCCA-motif at the 3' end of the substrate. The nucleobase and the 2'hydroxyl at the position immediately 5' of the cleavage site contribute to both cleavage efficiency and site selection, where C at this position induces significant cleavage at an alternative site, one base upstream of the main cleavage site. The frequencies of cleavage at these two sites and Mg2+ binding change upon altering the structural topology in the vicinity of the cleavage site as well as by replacing Mg2+ with other divalent metal ions. Modelling studies of RPR in complex with the pseudoknot substrates suggest alternative structural topologies for cleavage at the main and the alternative site and a shift in positioning of Mg2+ that activates the H2O nucleophile. Together, our data are consistent with a model where the organization of the active site structure and positioning of Mg2+ is influenced by the identities of residues at and in the vicinity of the site of cleavage.

Enhancing mycophenolic acid production in Penicillium brevicompactum through Kozak-optimized 2A peptide multi-gene expression system

Although Penicillium brevicompactum is widely used for industrial mycophenolic acid (MPA) production, research on its metabolic engineering and gene regulation remains limited. Efficient, coordinated expression of multiple genes is crucial for optimizing biosynthetic circuits and metabolic pathways, yet current strategies often suffer from inefficiencies and imbalances. These challenges not only limit the production of the desired metabolic products but can also result in wasted resources and inhibited cell growth. In this study, we optimized the 2A peptide multi-gene expression system in P. brevicompactum by introducing the Kozak sequence. This modification significantly enhanced the transcription of two key genes in the mevalonate (MVA) pathway precursor farnesyl pyrophosphate (FPP): the Acetyl-CoA acetyltransferase gene (ERG10) and the HMG-CoA synthetase gene (ERG13). In the PP-K10K13 strain, the transcription levels of the ERG10 and ERG13 genes increased by 77.02 % and 67.63 %, respectively, compared to the PP-1013 strain, which lacked the Kozak sequence. Consequently, the mycophenolic acid (MPA) production reached 4.30 g/L, representing a 49.31 % increase relative to the wild-type strain (WT). Additionally, observations of the engineered strains incorporating the introduced Kozak sequence showed improved growth, evident in an increase in mycelial dry weight, indicating reduced growth inhibition from metabolic engineering modifications. These results demonstrated that the optimized 2A peptide expression system not only effectively enhanced product synthesis efficiency but also helped restore the normal growth state of the engineered strains. This system is poised to serve as an effective tool for multi-gene expression and further genetic engineering modifications in P. brevicompactum. The study provides a new strategy for constructing more efficient 2A peptide multi-gene expression systems in Penicillium or filamentous fungi in future research endeavors.

Mutation of the LRG1 Rho-GAP gene is responsible for the hyper branching C-variant phenotype in the quorn mycoprotein fungus Fusarium venenatum A3/5

BACKGROUND

Quorn mycoprotein, a protein-rich meat alternative, is produced through large-scale fermentation of the fungus Fusarium venenatum. However, a major challenge during F. venenatum fermentation is the consistent appearance of mutants called colonial variants (C-variants). These C-variants have a highly branched morphology, which ultimately lead to a less desirable final product and early termination of the fermentation process. This study aimed to identify the genetic mutations responsible for C-variant morphology.

RESULTS

We first isolated both C-variant and wild-type strains from commercial fermentation samples and characterised radial growth rates on solid media. Whole genome sequencing facilitated the identification of mutations in a gene called jg4843 in 11 out of 12 C-variant isolates, which were not observed in the wild-type isolates. The jg4843 gene was identified as the ortholog of LRG1, a Rho-GTPase activating protein that regulates the Rho1 signalling pathway affecting fungal growth. Notably, the mutations in jg4843 were primarily located in the RhoGAP domain responsible for LRG1 activity. To confirm the role of these mutations, we used CRISPR/Cas9-mediated homology-directed recombination to introduce the C-variant mutations into the wild-type isolate, which successfully recapitulated the characteristic C-variant morphology.

CONCLUSIONS

This study identified mutations in the LRG1 ortholog jg4843 as the genetic cause of C-variant morphology in commercial fermentation F. venenatum isolates. Understanding this genetic basis paves the way for developing strategies to prevent C-variants arising, potentially leading to more efficient and sustainable production of Quorn mycoprotein.

Increasing recombinant protein production in E. coli via FACS-based selection of N-terminal coding DNA libraries

Here, we present a previously undescribed approach to modify N-terminal sequences of recombinant proteins to increase their production yield in Escherichia coli. Prior research has demonstrated that the nucleotides immediately following the start codon can significantly influence protein expression. However, the impact of these sequences is construct-specific and is not universally applicable to all proteins. Most of the previous research has been limited to selecting from a few rationally designed sequences. In contrast, we used a directed evolution-based methodology, screening large numbers of diversified sequences derived from DNA libraries coding for the N-termini of investigated proteins. To facilitate the identification of cells with increased expression of the target construct, we cloned a GFP gene at the C-terminus of the expressed genes and used fluorescent activated cell sorting (FACS) to separate cells based on their fluorescence. By following this systematic workflow, we successfully elevated the yield of soluble recombinant proteins of multiple constructs up to over 30-fold.

Untranslated region engineering strategies for gene overexpression, fine-tuning, and dynamic regulation

Precise and tunable gene expression is crucial for various biotechnological applications, including protein overexpression, fine-tuned metabolic pathway engineering, and dynamic gene regulation. Untranslated regions (UTRs) of mRNAs have emerged as key regulatory elements that modulate transcription and translation. In this review, we explore recent advances in UTR engineering strategies for bacterial gene expression optimization. We discuss approaches for enhancing protein expression through AU-rich elements, RG4 structures, and synthetic dual UTRs, as well as ProQC systems that improve translation fidelity. Additionally, we examine strategies for fine-tuning gene expression using UTR libraries and synthetic terminators that balance metabolic flux. Finally, we highlight riboswitches and toehold switches, which enable dynamic gene regulation in response to environmental or metabolic cues. The integration of these UTR-based regulatory tools provides a versatile and modular framework for optimizing bacterial gene expression, enhancing metabolic engineering, and advancing synthetic biology applications.

Synthetic translational coupling system for accurate and predictable polycistronic gene expression control in bacteria

Precise and predictable genetic elements are required to address various issues, such as suboptimal metabolic flux or imbalanced protein assembly caused by the inadequate control of polycistronic gene expression in bacteria. Here, we devised a synthetic biopart based on the translational coupling to control polycistronic gene expression. This module links the translation of genes within a polycistronic mRNA, maintaining their expression ratios regardless of coding sequences, transcription rate, and upstream gene translation rate. By engineering the Shine-Dalgarno sequences within these synthetic bioparts, we adjusted the expression ratios of polycistronic genes. We created 41 bioparts with varied relative expression ratios, ranging from 0.03 to 0.92, enabling precise control of pathway enzyme gene expression in a polycistronic manner. This led to up to a 7.6-fold increase in the production of valuable biochemicals such as 3-hydroxypropionic acid, poly(3-hydroxybutyrate), and lycopene. Our work provides genetic regulatory modules for precise and predictable polycistronic gene expression, facilitating efficient protein assembly, biosynthetic gene cluster expression, and pathway optimization.

The role of RNA structural motifs in RNA-lipid raft interaction

Here, we sought to determine the role of specific RNA structural motifs in the interaction of RNA with model lipid vesicles containing liquid-ordered domains (RAFT liposomes). We show that the presence of several small apical loops within RNA structure favors RNA affinity for RAFT liposomes while the increased number of nucleotides within bulges inhibits this affinity. FRET flow cytometry measurements confirmed a modulation of the interaction of RNA with plasma membrane by the presence of specific RNA structural motifs. The analysis of viral RNA fragments revealed that a long double helix at the apical loop increases the affinity of viral RNA to lipid rafts. The analysis of exosomal Y RNAs secreted by nematode parasites showed that the presence of the EXO-motif GGAG is strongly correlated to the presence of small number of large apical loops within RNA structure. These results show that RNA structural motifs can modulate RNA affinity to liquid-ordered membrane lipid raft domains thus suggesting the importance of these motifs both for the mechanism of RNA loading into extracellular vesicles, and for the development of RNA-based lipid biosensors for monitoring of viral RNAs in biofluids and wastewater.

Cis to trans: small ORF functions emerging through evolution

Hundreds of thousands of small open reading frames (smORFs) of less than 100 codons exist in every genome, especially in long noncoding RNAs (lncRNAs) and in the 5' leaders of mRNAs. smORFs are often discarded as nonfunctional, but ribosomal profiling (RiboSeq) reveals that thousands are translated, while characterised smORF functions have risen from anecdotal to identifiable trends: smORFs can either have a cis-noncoding regulatory function (involving low translation of nonfunctional peptides) or full coding function mediated by robustly translated peptides, often having cellular and physiological roles as membrane-associated regulators of canonical proteins. The evolutionary context reveals that many smORFs represent new genes emerging de novo from noncoding sequences. We suggest a mechanism for this process, where cis-noncoding smORF functions provide niches for the subsequent evolution of full peptide functions.

Discovery of paradoxical genes: reevaluating the prognostic impact of overexpressed genes in cancer

Oncogenes are typically overexpressed in tumor tissues and often linked to poor prognosis. However, recent advancements in bioinformatics have revealed that many highly expressed genes in tumors are associated with better patient outcomes. These genes, which act as tumor suppressors, are referred to as "paradoxical genes." Analyzing The Cancer Genome Atlas (TCGA) confirmed the widespread presence of paradoxical genes, and KEGG analysis revealed their role in regulating tumor metabolism. Mechanistically, discrepancies between gene and protein expression-affected by pre- and post-transcriptional modifications-may drive this phenomenon. Mechanisms like upstream open reading frames and alternative splicing contribute to these inconsistencies. Many paradoxical genes modulate the tumor immune microenvironment, exerting tumor-suppressive effects. Further analysis shows that the stage- and tumor-specific expression of these genes, along with their environmental sensitivity, influence their dual roles in various signaling pathways. These findings highlight the importance of paradoxical genes in resisting tumor progression and maintaining cellular homeostasis, offering new avenues for targeted cancer therapy.

Protein binding in an mRNA 5'-UTR sterically hinders translation

Structures in the 5' untranslated regions (UTRs) of mRNAs can physically modulate translation efficiency by impeding the scanning ribosome or by sequestering the translational start site. We assessed the impact of stable protein binding in 5'- and 3'-UTRs on translation efficiency by targeting the MS2 coat protein to a reporter RNA via its hairpin recognition site. Translation was assessed from the reporter RNA when coexpressed with MS2 coat proteins of varying affinities for the RNA, and at different expression levels. Binding of high-affinity proteins in the 5'-UTR hindered translation, whereas no effect was observed when the coat protein was targeted to the 3'-UTR. Inhibition of translation increased with coat protein concentration and affinity, reaching a maximum of 50%-70%. MS2 proteins engineered to bind two reporter mRNA sites had a stronger effect than those binding a single site. Our findings demonstrate that protein binding in an mRNA 5'-UTR physically impedes translation, with the effect governed by affinity, concentration, and sterics.

Deciphering Transcription in Cryptosporidium parvum: Polycistronic Gene Expression and Chromatin Accessibility

Once considered rare in eukaryotes, polycistronic mRNA expression has been identified in kinetoplastids and, more recently, green algae, red algae, and certain fungi. This study provides comprehensive evidence supporting the existence of polycistronic mRNA expression in the apicomplexan parasite Cryptosporidium parvum. Leveraging long-read RNA-seq data from different parasite strains and using multiple long-read technologies, we demonstrate the existence of defined polycistronic transcripts containing 2-4 protein encoding genes, several validated with RT-PCR. Some polycistrons exhibit differential expression profiles, usually involving the generation of internal monocistronic transcripts at different times during development. ATAC-seq in sporozoites reveals that polycistronic transcripts usually have a single open chromatin peak at their 5-prime ends, which contains a single E2F binding site motif. Polycistronic genes do not appear enriched for either male or female exclusive genes. This study elucidates a potentially complex layer of gene regulation with distinct chromatin accessibility akin to monocistronic transcripts. This is the first report of polycistronic transcription in an apicomplexan and expands our understanding of gene expression strategies in this medically important organism.

mRNA vaccine sequence and structure design and optimization: Advances and challenges

Messenger RNA (mRNA) vaccines have emerged as a powerful tool against communicable diseases and cancers, as demonstrated by their huge success during the coronavirus disease 2019 (COVID-19) pandemic. Despite the outstanding achievements, mRNA vaccines still face challenges such as stringent storage requirements, insufficient antigen expression, and unexpected immune responses. Since the intrinsic properties of mRNA molecules significantly impact vaccine performance, optimizing mRNA design is crucial in preclinical development. In this review, we outline four key principles for optimal mRNA sequence design: enhancing ribosome loading and translation efficiency through untranslated region (UTR) optimization, improving translation efficiency via codon optimization, increasing structural stability by refining global RNA sequence and extending in-cell lifetime and expression fidelity by adjusting local RNA structures. We also explore recent advancements in computational models for designing and optimizing mRNA vaccine sequences following these principles. By integrating current mRNA knowledge, addressing challenges, and examining advanced computational methods, this review aims to promote the application of computational approaches in mRNA vaccine development and inspire novel solutions to existing obstacles.

Evaluation of Eukaryotic mRNA Coding Potential

It is widely discussed that eukaryotic mRNAs can encode several functional polypeptides. Recent progress in NGS and proteomics techniques has resulted in a huge volume of information on potential alternative translation initiation sites and open reading frames (altORFs). However, these data are still incomprehensive, and the vast majority of eukaryotic mRNAs annotated in conventional databases (e.g., GenBank) contain a single ORF (CDS) encoding a protein larger than some arbitrary threshold (commonly 100 amino acid residues). Indeed, some gene functions may relate to the polypeptides encoded by unannotated altORFs, and insufficient information in nucleotide sequence databanks may limit the interpretation of genomics and transcriptomics data. However, despite the need for special experiments to predict altORFs accurately, there are some simple methods for their preliminary mapping.

CParty: hierarchically constrained partition function of RNA pseudoknots

MOTIVATION

Biologically relevant RNA secondary structures are routinely predicted by efficient dynamic programming algorithms that minimize their free energy. Starting from such algorithms, one can devise partition function algorithms, which enable stochastic perspectives on RNA structure ensembles. As the most prominent example, McCaskill's partition function algorithm is derived from pseudoknot-free energy minimization. While this algorithm became hugely successful for the analysis of pseudoknot-free RNA structure ensembles, as of yet there exists only one pseudoknotted partition function implementation, which covers only simple pseudoknots and comes with a borderline-prohibitive complexity of O(n5) in the RNA length n.

RESULTS

Here, we develop a partition function algorithm corresponding to the hierarchical pseudoknot prediction of HFold, which performs exact optimization in a realistic pseudoknot energy model. In consequence, our algorithm CParty carries over HFold's advantages over classical pseudoknot prediction in characterizing the Boltzmann ensemble at equilibrium. Given an RNA sequence S and a pseudoknot-free structure G, CParty computes the partition function over all possibly pseudoknotted density-2 structures G∪G' of S that extend the fixed G by a disjoint pseudoknot-free structure G'. Thus, CParty follows the common hypothesis of hierarchical pseudoknot formation, where pseudoknots form as tertiary contacts only after a first pseudoknot-free "core" G and we call the computed partition function hierarchically constrained (by G). Like HFold, the dynamic programming algorithm CParty is very efficient, achieving the low complexity of the pseudoknot-free algorithm, i.e. cubic time and quadratic space. Finally, by computing pseudoknotted ensemble energies, we unveil kinetics features of a therapeutic target in SARS-CoV-2.

AVAILABILITY AND IMPLEMENTATION

CParty is available at https://github.com/HosnaJabbari/CParty.

DDX21 at the Nexus of RNA Metabolism, Cancer Oncogenesis, and Host-Virus Crosstalk: Decoding Its Biomarker Potential and Therapeutic Implications

DDX21, a member of the DEAD-box RNA helicase family, plays a pivotal role in various aspects of RNA metabolism, including ribosomal RNA (rRNA) processing, transcription, and translation. Its diverse functions in cancer progression and viral infections have attracted considerable attention. DDX21 exerts a pivotal function through ribosomal DNA (rDNA) transcription and rRNA processing. DDX21 is involved in different biological processes of mRNA transcription. It interacts with transcription factors, modulates RNA polymerase II elongation, binds R-loops to regulate transcription, and participates in alternative splicing. The elevated expression of DDX21 has been observed in most cancers, where it influences tumorigenesis by affecting ribosome biogenesis, transcription, genome stability, and cell cycle regulation. Additionally, DDX21 plays a key role in the antiviral defense of host by interacting with viral proteins to regulate essential stages of the infection process. This review provides a thorough examination of the biological functions of DDX21, its involvement in cancer progression and viral infections, and its potential as both a biomarker and a therapeutic target. Future studies should aim to clarify the specific mechanisms of the activity of DDX21, advance the development of targeted therapies, and assess its clinical relevance across various cancer types and stages.

Exploring the Use of Alternative Promoters for Enhanced Transgene and sgRNA Expression in Atlantic Salmon Cells

This study facilitates design of expression vectors and lentivirus tools for gene editing of Atlantic salmon. We have characterized widely used heterologous promoters and novel endogenous promoters in Atlantic salmon cells. We used qPCR to evaluate the activity of several U6 promoters for sgRNA expression, including human U6 (hU6), tilapia U6 (tU6), mouse U6 (mU6), zebrafish U6 (zU6), Atlantic salmon U6 (sU6), medaka U6 (medU6), and fugu U6 (fU6) promoters. We also evaluated several polymerase type II (pol II) promoters by luciferase assay. Our results showed that hU6 and tU6 promoters were the most active among all the tested U6 promoters, and heterologous promoters (CMV, hEF1α core) had higher activity compared to endogenous Atlantic salmon promoters sHSP8, sNUC3L, sEF1α. Among endogenous pol II promoters, sEF1α and sHSP8 displayed higher activity than sNUC3L, sHSP703, sHSP7C, sXRCC1L, and sETF. We observed that extending the promoter sequence to include the region up to the start codon (ATG) resulted in a significant increase in expression efficiency for sNUC3L and sEF1α. We also show that mutating the PRDM1 motif will significantly decrease the activity of the sEF1α promoter. The presence of the PRDM1 motif in sHSP8 promoter was also associated with relatively high expression compared to the promoters that naturally lacked this motif, such as sNUC3L. We speculate that this short sequence might be included in other promoters to further enhance the promoter activity, but further experiments are needed to confirm this. Our findings provide valuable insights into the activity of different promoters in Atlantic salmon cells and can be used to facilitate further transgenic studies and improve the efficiency of transgene expression in Atlantic salmon.

DDX RNA helicases: key players in cellular homeostasis and innate antiviral immunity

RNA helicases are integral in RNA metabolism, performing important roles in cellular homeostasis and stress responses. In particular, the DExD/H-box (DDX) helicase family possesses a conserved catalytic core that binds structural features rather than specific sequences in RNA targets. DDXs have critical roles in all aspects of RNA metabolism including ribosome biogenesis, translation, RNA export, and RNA stability. Importantly, functional specialization within this family arises from divergent N and C termini and is driven at least in part by gene duplications with 18 of the 42 human helicases having paralogs. In addition to their key roles in the homeostatic control of cellular RNA, these factors have critical roles in RNA virus infection. The canonical RIG-I-like receptors (RLRs) play pivotal roles in cytoplasmic sensing of viral RNA structures, inducing antiviral gene expression. Additional RNA helicases function as viral sensors or regulators, further diversifying the innate immune defense arsenal. Moreover, some of these helicases have been coopted by viruses to facilitate their replication. Altogether, DDX helicases exhibit functional specificity, playing intricate roles in RNA metabolism and host defense. This review will discuss the mechanisms by which these RNA helicases recognize diverse RNA structures in cellular and viral RNAs, and how this impacts RNA processing and innate immune responses.

Evaluating Performance of Different RNA Secondary Structure Prediction Programs Using Self-cleaving Ribozymes

Accurate identification of the correct, biologically relevant RNA structures is critical to understanding various aspects of RNA biology since proper folding represents the key to the functionality of all types of RNA molecules and plays pivotal roles in many essential biological processes. Thus, a plethora of approaches have been developed to predict, identify, or solve RNA structures based on various computational, molecular, genetic, chemical, or physicochemical strategies. Purely computational approaches hold distinct advantages over all other strategies in terms of the ease of implementation, time, speed, cost, and throughput, but they strongly underperform in terms of accuracy that significantly limits their broader application. Nonetheless, the advantages of these methods led to a steady development of multiple in silico RNA secondary structure prediction approaches including recent deep learning-based programs. Here, we compared the accuracy of predictions of biologically relevant secondary structures of dozens of self-cleaving ribozyme sequences using seven in silico RNA folding prediction tools with tasks of varying complexity. We found that while many programs performed well in relatively simple tasks, their performance varied significantly in more complex RNA folding problems. However, in general, a modern deep learning method outperformed the other programs in the complex tasks in predicting the RNA secondary structures, at least based on the specific class of sequences tested, suggesting that it may represent the future of RNA structure prediction algorithms.

Epigenetic therapy potentiates transposable element transcription to create tumor-enriched antigens in glioblastoma cells

Inhibiting epigenetic modulators can transcriptionally reactivate transposable elements (TEs). These TE transcripts often generate unique peptides that can serve as immunogenic antigens for immunotherapy. Here, we ask whether TEs activated by epigenetic therapy could appreciably increase the antigen repertoire in glioblastoma, an aggressive brain cancer with low mutation and neoantigen burden. We treated patient-derived primary glioblastoma stem cell lines, an astrocyte cell line and primary fibroblast cell lines with epigenetic drugs, and identified treatment-induced, TE-derived transcripts that are preferentially expressed in cancer cells. We verified that these transcripts could produce human leukocyte antigen class I-presented antigens using liquid chromatography with tandem mass spectrometry pulldown experiments. Importantly, many TEs were also transcribed, even in proliferating nontumor cell lines, after epigenetic therapy, which suggests that targeted strategies like CRISPR-mediated activation could minimize potential side effects of activating unwanted genomic regions. The results highlight both the need for caution and the promise of future translational efforts in harnessing treatment-induced TE-derived antigens for targeted immunotherapy.

Optimization of the 5' untranslated region of mRNA vaccines

To investigate the impact of different 5' untranslated regions (UTRs) on mRNA vaccine translation efficiency, five dual-reporter gene expression plasmids with different 5'UTRs were constructed. The corresponding mRNA transcripts were transcribed and capped in vitro. By comparing the expression levels of reporter genes with different 5'UTRs, we identified the 5'UTR associated with the highest expression level. Subsequently, HIVgp145 mRNA vaccines containing various 5'UTRs were constructed and verified. The results demonstrated that mRNA 3 (β-globin 5'UTR) displayed the greatest number of green fluorescence-positive cells and the highest luciferase fluorescence intensity in the reporter gene expression system. Further, among the HIVgp145 mRNA vaccines with different 5'UTRs, mRNA 7 (β-globin 5'UTR) exhibited the highest level of expression. These findings indicate that it is feasible to use the 5'UTR of β-globin in an mRNA vaccine, laying the foundation for animal immunogenicity testing.

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.

Truncated protein isoforms generate diversity of protein localization and function in yeast

Genome-wide measurement of ribosome occupancy on mRNAs has enabled empirical identification of translated regions, but high-confidence detection of coding regions that overlap annotated coding regions has remained challenging. Here, we report a sensitive and robust algorithm that revealed the translation of 388 N-terminally truncated proteins in budding yeast-more than 30-fold more than previously known. We extensively experimentally validated them and defined two classes. The first class lacks large portions of the annotated protein and tends to be produced from a truncated transcript. We show that two such cases, Yap5truncation and Pus1truncation, have condition-specific regulation and distinct functions from their respective annotated isoforms. The second class of truncated protein isoforms lacks only a small region of the annotated protein and is less likely to be produced from an alternative transcript isoform. Many display different subcellular localizations than their annotated counterpart, representing a common strategy for dual localization of otherwise functionally identical proteins. A record of this paper's transparent peer review process is included in the supplemental information.

Effects of mRNA conformational switching on translational noise in gene circuits

Intragenic translational heterogeneity describes the variation in translation at the level of transcripts for an individual gene. A factor that contributes to this source of variation is the mRNA structure. Both the composition of the thermodynamic ensemble, i.e., the stationary distribution of mRNA structures, and the switching dynamics between those play a role. The effect of the switching dynamics on intragenic translational heterogeneity remains poorly understood. We present a stochastic translation model that accounts for mRNA structure switching and is derived from a Markov model via approximate stochastic filtering. We assess the approximation on various timescales and provide a method to quantify how mRNA structure dynamics contributes to translational heterogeneity. With our approach, we allow quantitative information on mRNA switching from biophysical experiments or coarse-grain molecular dynamics simulations of mRNA structures to be included in gene regulatory chemical reaction network models without an increase in the number of species. Thereby, our model bridges a gap between mRNA structure kinetics and gene expression models, which we hope will further improve our understanding of gene regulatory networks and facilitate genetic circuit design.

Codon-optimization in gene therapy: promises, prospects and challenges

Codon optimization has evolved to enhance protein expression efficiency by exploiting the genetic code's redundancy, allowing for multiple codon options for a single amino acid. Initially observed in E. coli, optimal codon usage correlates with high gene expression, which has propelled applications expanding from basic research to biopharmaceuticals and vaccine development. The method is especially valuable for adjusting immune responses in gene therapies and has the potenial to create tissue-specific therapies. However, challenges persist, such as the risk of unintended effects on protein function and the complexity of evaluating optimization effectiveness. Despite these issues, codon optimization is crucial in advancing gene therapeutics. This study provides a comprehensive review of the current metrics for codon-optimization, and its practical usage in research and clinical applications, in the context of gene therapy.

Computational design of mRNA vaccines

mRNA technology has emerged as a successful vaccine platform that offered a swift response to the COVID-19 pandemic. Accumulating evidence shows that vaccine efficacy, thermostability, and other important properties, are largely impacted by intrinsic properties of the mRNA molecule, such as RNA sequence and structure, both of which can be optimized. Designing mRNA sequence for vaccines presents a combinatorial problem due to an extremely large selection space. For instance, due to the degeneracy of the genetic code, there are over 10632 possible mRNA sequences that could encode the spike protein, the COVID-19 vaccines' target. Moreover, designing different elements of the mRNA sequence simultaneously against multiple objectives such as translational efficiency, reduced reactogenicity, and improved stability requires an efficient and sophisticated optimization strategy. Recently, there has been a growing interest in utilizing computational tools to redesign mRNA sequences to improve vaccine characteristics and expedite discovery timelines. In this review, we explore important biophysical features of mRNA to be considered for vaccine design and discuss how computational approaches can be applied to rapidly design mRNA sequences with desirable characteristics.

SparseRNAfolD: optimized sparse RNA pseudoknot-free folding with dangle consideration

MOTIVATION

Computational RNA secondary structure prediction by free energy minimization is indispensable for analyzing structural RNAs and their interactions. These methods find the structure with the minimum free energy (MFE) among exponentially many possible structures and have a restrictive time and space complexity ( O ( n 3 ) time and O ( n 2 ) space for pseudoknot-free structures) for longer RNA sequences. Furthermore, accurate free energy calculations, including dangle contributions can be difficult and costly to implement, particularly when optimizing for time and space requirements.

RESULTS

Here we introduce a fast and efficient sparsified MFE pseudoknot-free structure prediction algorithm, SparseRNAFolD, that utilizes an accurate energy model that accounts for dangle contributions. While the sparsification technique was previously employed to improve the time and space complexity of a pseudoknot-free structure prediction method with a realistic energy model, SparseMFEFold, it was not extended to include dangle contributions due to the complexity of computation. This may come at the cost of prediction accuracy. In this work, we compare three different sparsified implementations for dangle contributions and provide pros and cons of each method. As well, we compare our algorithm to LinearFold, a linear time and space algorithm, where we find that in practice, SparseRNAFolD has lower memory consumption across all lengths of sequence and a faster time for lengths up to 1000 bases.

CONCLUSION

Our SparseRNAFolD algorithm is an MFE-based algorithm that guarantees optimality of result and employs the most general energy model, including dangle contributions. We provide a basis for applying dangles to sparsified recursion in a pseudoknot-free model that has the potential to be extended to pseudoknots.

AStruct: detection of allele-specific RNA secondary structure in structuromic probing data

BACKGROUND

Uncovering functional genetic variants from an allele-specific perspective is of paramount importance in advancing our understanding of gene regulation and genetic diseases. Recently, various allele-specific events, such as allele-specific gene expression, allele-specific methylation, and allele-specific binding, have been explored on a genome-wide scale due to the development of high-throughput sequencing methods. RNA secondary structure, which plays a crucial role in multiple RNA-associated processes like RNA modification, translation and splicing, has emerged as an essential focus of relevant research. However, tools to identify genetic variants associated with allele-specific RNA secondary structures are still lacking.

RESULTS

Here, we develop a computational tool called 'AStruct' that enables us to detect allele-specific RNA secondary structure (ASRS) from RT-stop based structuromic probing data. AStruct shows robust performance in both simulated datasets and public icSHAPE datasets. We reveal that single nucleotide polymorphisms (SNPs) with higher AStruct scores are enriched in coding regions and tend to be functional. These SNPs are highly conservative, have the potential to disrupt sites involved in m6A modification or protein binding, and are frequently associated with disease.

CONCLUSIONS

AStruct is a tool dedicated to invoke allele-specific RNA secondary structure events at heterozygous SNPs in RT-stop based structuromic probing data. It utilizes allelic variants, base pairing and RT-stop information under different cell conditions to detect dynamic and functional ASRS. Compared to sequence-based tools, AStruct considers dynamic cell conditions and outperforms in detecting functional variants. AStruct is implemented in JAVA and is freely accessible at: https://github.com/canceromics/AStruct .

Highly chromophoric fluorescent-labeled methionyl-initiator tRNAs applicable in living cells

Fluorescent initiator tRNAs (tRNAi) play a crucial role in studying protein synthesis, yet generating highly fluorescent tRNAi complexes remains challenging. We present an optimized strategy to effectively generate highly fluorescent initiator-tRNA complexes in living cells. Our strategy allows the generation of Fluo-Met-tRNAiMet complexes. These complexes can have highly chromogenic N-terminal labeling. For generating such complexes, we use either purified fluorescent methionine (PFM) or non-purified fluorescently labeled methionine (NPFM). Furthermore, PFM promotes the active generation of endogenous tRNAi in cells, leading to highly efficient Fluo-Met-tRNAiMet complexes. Finally, PFM-tRNAiMet complexes also facilitate the visualization of native fluorescently labeled Tat binding to beads. This demonstrates the potential of our approach to advance precision protein engineering and biotechnology applications.

Principles, challenges, and advances in ribosome profiling: from bulk to low-input and single-cell analysis

Ribosome profiling has revolutionized our understanding of gene expression regulation by providing a snapshot of global translation in vivo. This powerful technique enables the investigation of the dynamics of translation initiation, elongation, and termination, and has provided insights into the regulation of protein synthesis under various conditions. Despite its widespread adoption, challenges persist in obtaining high-quality ribosome profiling data. In this review, we discuss the fundamental principles of ribosome profiling and related methodologies, including selective ribosome profiling and translation complex profiling. We also delve into quality control to assess the reliability of ribosome profiling datasets, and the efforts to improve data quality by modifying the standard procedures. Additionally, we highlight recent advancements in ribosome profiling that enable the transition from bulk to low-input and single-cell applications. Single-cell ribosome profiling has emerged as a crucial tool for exploring translation heterogeneity within specific cell populations. However, the challenges of capturing mRNAs efficiently and the sparse nature of footprint reads in single-cell ribosome profiling present ongoing obstacles. The need to refine ribosome profiling techniques remains, especially when used at the single-cell level.

Plant miRNA bol-miR159 Regulates Gut Microbiota Composition in Mice: In Vivo Evidence of the Crosstalk between Plant miRNAs and Intestinal Microbes

New evidence reveals that bol-miR159, an miRNA rich in fruits and vegetables, cross-kingdomly functions in mammalian bodies. However, whether the miRNA could regulate gut microbiota remains unclear. Here, the effect of miR159 on mouse intestinal microbes was comprehensively examined. The results showed that supplementation of miR159 to the chow diet significantly enhanced the diversity of mouse gut microbiota without causing pathological lesions or inflammatory responses on the intestines. At the phylum level, miR159 increased the abundance of Proteobacteria and decreased the Firmicute-to-Bacteroidetes (F/B) ratio. miR159 had prebiotic-like effects on mouse gut microbiota, as it promoted the growth of the bacteria that is beneficial for maintaining gut health. The miRNA can target bacteria genes and get into the bacteria cells. The data provide direct in vivo evidence on the crosstalk between plant miRNAs and intestinal microbes, highlighting the potential for miRNA-based strategies that modulate gut microbes to improve host health.

Precise genome editing of the Kozak sequence enables bidirectional and quantitative modulation of protein translation to anticipated levels without affecting transcription

None of the existing approaches for regulating gene expression can bidirectionally and quantitatively fine-tune gene expression to desired levels. Here, on the basis of precise manipulations of the Kozak sequence, which has a remarkable influence on translation initiation, we proposed and validated a novel strategy to directly modify the upstream nucleotides of the translation initiation codon of a given gene to flexibly alter the gene translation level by using base editors and prime editors. When the three nucleotides upstream of the translation initiation codon (named KZ3, part of the Kozak sequence), which exhibits the most significant base preference of the Kozak sequence, were selected as the editing region to alter the translation levels of proteins, we confirmed that each of the 64 KZ3 variants had a different translation efficiency, but all had similar transcription levels. Using the ranked KZ3 variants with different translation efficiencies as predictors, base editor- and prime editor-mediated mutations of KZ3 in the local genome could bidirectionally and quantitatively fine-tune gene translation to the anticipated levels without affecting transcription in vitro and in vivo. Notably, this strategy can be extended to the whole Kozak sequence and applied to all protein-coding genes in all eukaryotes.

The Dual Role of the Innate Immune System in the Effectiveness of mRNA Therapeutics

Advances in molecular biology have revolutionized the use of messenger RNA (mRNA) as a therapeutic. The concept of nucleic acid therapy with mRNA originated in 1990 when Wolff et al. reported successful expression of proteins in target organs by direct injection of either plasmid DNA or mRNA. It took decades to bring the transfection efficiency of mRNA closer to that of DNA. The next few decades were dedicated to turning in vitro-transcribed (IVT) mRNA from a promising delivery tool for gene therapy into a full-blown therapeutic modality, which changed the biotech market rapidly. Hundreds of clinical trials are currently underway using mRNA for prophylaxis and therapy of infectious diseases and cancers, in regenerative medicine, and genome editing. The potential of IVT mRNA to induce an innate immune response favors its use for vaccination and immunotherapy. Nonetheless, in non-immunotherapy applications, the intrinsic immunostimulatory activity of mRNA directly hinders the desired therapeutic effect since it can seriously impair the target protein expression. Targeting the same innate immune factors can increase the effectiveness of mRNA therapeutics for some indications and decrease it for others, and vice versa. The review aims to present the innate immunity-related 'barriers' or 'springboards' that may affect the development of immunotherapies and non-immunotherapy applications of mRNA medicines.

eIF3i promotes colorectal cancer cell survival via augmenting PHGDH translation

Translational regulation is one of the decisive steps in gene expression, and its dysregulation is closely related to tumorigenesis. Eukaryotic translation initiation factor 3 subunit i (eIF3i) promotes tumor growth by selectively regulating gene translation, but the underlying mechanisms are largely unknown. Here, we show that eIF3i is significantly increased in colorectal cancer (CRC) and reinforces the proliferation of CRC cells. Using ribosome profiling and proteomics analysis, several genes regulated by eIF3i at the translation level were identified, including D-3-phosphoglycerate dehydrogenase (PHGDH), a rate-limiting enzyme in the de novo serine synthesis pathway that participates in metabolic reprogramming of tumor cells. PHGDH knockdown significantly represses CRC cell proliferation and partially attenuates the excessive growth induced by eIF3i overexpression. Mechanistically, METTL3-mediated N6-methyladenosine modification on PHGDH mRNA promotes its binding with eIF3i, ultimately leading to a higher translational rate. In addition, knocking down eIF3i and PHGDH impedes tumor growth in vivo. Collectively, this study not only uncovered a novel regulatory mechanism for PHGDH translation but also demonstrated that eIF3i is a critical metabolic regulator in human cancer.

Recent Advances in Messenger Ribonucleic Acid (mRNA) Vaccines and Their Delivery Systems: A Review

Messenger ribonucleic acid (mRNA) was found as the intermediary that transfers genetic information from DNA to ribosomes for protein synthesis in 1961. The emergency use authorization of the two covid-19 mRNA vaccines, BNT162b2 and mRNA-1273, is a significant achievement in the history of vaccine development. Because they are generated in a cell-free environment using the in vitro transcription (IVT) process, mRNA vaccines are risk-free. Moreover, chemical modifications to the mRNA molecule, such as cap structures and changed nucleosides, have proved critical in overcoming immunogenicity concerns, achieving sustained stability, and achieving effective, accurate protein production in vivo. Several vaccine delivery strategies (including protamine, lipid nanoparticles (LNPs), polymers, nanoemulsions, and cell-based administration) were also optimized to load and transport RNA into the cytosol. LNPs, which are composed of a cationic or a pH-dependent ionizable lipid layer, a polyethylene glycol (PEG) component, phospholipids, and cholesterol, are the most advanced systems for delivering mRNA vaccines. Moreover, modifications of the four components that make up the LNPs showed to increase vaccine effectiveness and reduce side effects. Furthermore, the introduction of biodegradable lipids improved LNP biocompatibility. Furthermore, mRNA-based therapies are expected to be effective treatments for a variety of refractory conditions, including infectious diseases, metabolic genetic diseases, cancer, cardiovascular and cerebrovascular diseases. Therefore, the present review aims to provide the scientific community with up-to-date information on mRNA vaccines and their delivery systems.

Truncated protein isoforms generate diversity of protein localization and function in yeast

Genome-wide measurements of ribosome occupancy on mRNA transcripts have enabled global empirical identification of translated regions. These approaches have revealed an unexpected diversity of protein products, but high-confidence identification of new coding regions that entirely overlap annotated coding regions - including those that encode truncated protein isoforms - has remained challenging. Here, we develop a sensitive and robust algorithm focused on identifying N-terminally truncated proteins genome-wide, identifying 388 truncated protein isoforms, a more than 30-fold increase in the number known in budding yeast. We perform extensive experimental validation of these truncated proteins and define two general classes. The first set lack large portions of the annotated protein sequence and tend to be produced from a truncated transcript. We show two such cases, Yap5 truncation and Pus1 truncation , to have condition-specific regulation and functions that appear distinct from their respective annotated isoforms. The second set of N-terminally truncated proteins lack only a small region of the annotated protein and are less likely to be regulated by an alternative transcript isoform. Many localize to different subcellular compartments than their annotated counterpart, representing a common strategy for achieving dual localization of otherwise functionally identical proteins.

Investigating the NRAS 5' UTR as a target for small molecules

Neuroblastoma RAS (NRAS) is an oncogene that is deregulated and highly mutated in cancers including melanomas and acute myeloid leukemias. The 5' untranslated region (UTR) (5' UTR) of the NRAS mRNA contains a G-quadruplex (G4) that regulates translation. Here we report a novel class of small molecule that binds to the G4 structure located in the 5' UTR of the NRAS mRNA. We used a small molecule microarray screen to identify molecules that selectively bind to the NRAS-G4 with submicromolar affinity. One compound inhibits the translation of NRAS in vitro but showed only moderate effects on the NRAS levels in cellulo. Rapid Amplification of cDNA Ends and RT-PCR analysis revealed that the predominant NRAS transcript does not possess the G4 structure. Thus, although NRAS transcripts lack a G4 in many cell lines the concept of targeting folded regions within 5' UTRs to control translation remains a highly attractive strategy.

c-di-GMP regulates activity of the PlzA RNA chaperone from the Lyme disease spirochete

PlzA is a c-di-GMP-binding protein crucial for adaptation of the Lyme disease spirochete Borrelia (Borreliella) burgdorferi during its enzootic life cycle. Unliganded apo-PlzA is important for vertebrate infection, while liganded holo-PlzA is important for survival in the tick; however, the biological function of PlzA has remained enigmatic. Here, we report that PlzA has RNA chaperone activity that is inhibited by c-di-GMP binding. Holo- and apo-PlzA bind RNA and accelerate RNA annealing, while only apo-PlzA can strand displace and unwind double-stranded RNA. Guided by the crystal structure of PlzA, we identified several key aromatic amino acids protruding from the N- and C-terminal domains that are required for RNA-binding and unwinding activity. Our findings illuminate c-di-GMP as a switch controlling the RNA chaperone activity of PlzA, and we propose that complex RNA-mediated modulatory mechanisms allow PlzA to regulate gene expression during both the vector and host phases of the B. burgdorferi life cycle.

Programmable mammalian translational modulators by CRISPR-associated proteins

Translational modulation based on RNA-binding proteins can be used to construct artificial gene circuits, but RNA-binding proteins capable of regulating translation efficiently and orthogonally remain scarce. Here we report CARTRIDGE (Cas-Responsive Translational Regulation Integratable into Diverse Gene control) to repurpose Cas proteins as translational modulators in mammalian cells. We demonstrate that a set of Cas proteins efficiently and orthogonally repress or activate the translation of designed mRNAs that contain a Cas-binding RNA motif in the 5'-UTR. By linking multiple Cas-mediated translational modulators, we designed and built artificial circuits like logic gates, cascades, and half-subtractor circuits. Moreover, we show that various CRISPR-related technologies like anti-CRISPR and split-Cas9 platforms could be similarly repurposed to control translation. Coupling Cas-mediated translational and transcriptional regulation enhanced the complexity of synthetic circuits built by only introducing a few additional elements. Collectively, CARTRIDGE has enormous potential as a versatile molecular toolkit for mammalian synthetic biology.

Pan-cancer analysis identifies tumor-specific antigens derived from transposable elements

Cryptic promoters within transposable elements (TEs) can be transcriptionally reactivated in tumors to create new TE-chimeric transcripts, which can produce immunogenic antigens. We performed a comprehensive screen for these TE exaptation events in 33 TCGA tumor types, 30 GTEx adult tissues and 675 cancer cell lines, and identified 1,068 TE-exapted candidates with the potential to generate shared tumor-specific TE-chimeric antigens (TS-TEAs). Whole-lysate and HLA-pulldown mass spectrometry data confirmed that TS-TEAs are presented on the surface of cancer cells. In addition, we highlight tumor-specific membrane proteins transcribed from TE promoters that constitute aberrant epitopes on the extracellular surface of cancer cells. Altogether, we showcase the high pan-cancer prevalence of TS-TEAs and atypical membrane proteins that could potentially be therapeutically exploited and targeted.

3' Untranslated Region Structural Elements in CYP24A1 Are Associated With Infantile Hypercalcemia Type 1

Loss-of-function mutations in the CYP24A1 protein-coding region causing reduced 25 hydroxyvitamin D (25OHD) and 1,25 dihydroxyvitamin D (1,25(OH)₂ D) catabolism have been observed in some cases of infantile hypercalcemia type 1 (HCINF1), which can manifest as nephrocalcinosis, hypercalcemia and adult-onset hypercalciuria, and renal stone formation. Some cases present with apparent CYP24A1 phenotypes but do not exhibit pathogenic mutations. Here, we assessed the molecular mechanisms driving apparent HCINF1 where there was a lack of CYP24A1 mutation. We obtained blood samples from 47 patients with either a single abnormality of no obvious cause or a combination of hypercalcemia, hypercalciuria, and nephrolithiasis as part of our metabolic and stone clinics. We used liquid chromatography tandem mass spectrometry (LC-MS/MS) to determine serum vitamin D metabolites and direct sequencing to confirm CYP24A1 genotype. Six patients presented with profiles characteristic of altered CYP24A1 function but lacked protein-coding mutations in CYP24A1. Analysis upstream and downstream of the coding sequence showed single nucleotide variants (SNVs) in the CYP24A1 3' untranslated region (UTR). Bioinformatics approaches revealed that these 3' UTR abnormalities did not result in microRNA silencing but altered the CYP24A1 messenger RNA (mRNA) secondary structure, which negatively impacted translation. Our experiments showed that mRNA misfolding driven by these 3' UTR sequence-dependent structural elements was associated with normal 25OHD but abnormal 1,25(OH)₂ D catabolism. Using CRISPR-Cas9 gene editing, we developed an in vitro mutant model for future CYP24A1 studies. Our results form a basis for future studies investigating structure-function relationships and novel CYP24A1 mutations producing a semifunctional protein. © 2023 The Authors. Journal of Bone and Mineral Research published by Wiley Periodicals LLC on behalf of American Society for Bone and Mineral Research (ASBMR).

N-region of Cry1Ia: A novel fusion tag for Escherichia coli and Pichia pastoris

Secretory signal peptides (SPs) can increase enhanced green fluorescent protein (eGFP) expression in cytosol. In this study, SPs Iasp (Cry1Ia), Vasp (Vip3A), and their local sequences were used as fusion tags to compare their effects on eGFP expression in Escherichia coli MC4100 and Pichia pastoris GS115. In E coli, the solubility was almost opposite between the proteins encoded by Vegfp and Iegfp. This may be because the overall hydrophobicity of the SPs differed. When the hydrophobic H-region and C-region were removed, the negative effects on eGFP solubility of the N-regions of both SPs (IaN and VN) were significantly reduced without compromise on the expression level. IaN promotes eGFP protein yield 7.1-fold more than Iasp, and using this peptide in tandem (Ia3N) further enhanced fluorescent fusion protein solubility with an efficacy similar to that of a polycationic tag. Furthermore, the GS-IaNeGFP strain produced the highest fluorescent signal intensity when these fusion proteins were expressed in P. pastoris, and the expression was higher than in other strains, including eGFP. In conclusion, we revealed the potential of the N-region of Iasp as a fusion tag in both prokaryotic and eukaryotic cells and further demonstrated the value of the N-regions of abundant SPs.

Integrated mRNA sequence optimization using deep learning

The coronavirus disease of 2019 pandemic has catalyzed the rapid development of mRNA vaccines, whereas, how to optimize the mRNA sequence of exogenous gene such as severe acute respiratory syndrome coronavirus 2 spike to fit human cells remains a critical challenge. A new algorithm, iDRO (integrated deep-learning-based mRNA optimization), is developed to optimize multiple components of mRNA sequences based on given amino acid sequences of target protein. Considering the biological constraints, we divided iDRO into two steps: open reading frame (ORF) optimization and 5' untranslated region (UTR) and 3'UTR generation. In ORF optimization, BiLSTM-CRF (bidirectional long-short-term memory with conditional random field) is employed to determine the codon for each amino acid. In UTR generation, RNA-Bart (bidirectional auto-regressive transformer) is proposed to output the corresponding UTR. The results show that the optimized sequences of exogenous genes acquired the pattern of human endogenous gene sequence. In experimental validation, the mRNA sequence optimized by our method, compared with conventional method, shows higher protein expression. To the best of our knowledge, this is the first study by introducing deep-learning methods to integrated mRNA sequence optimization, and these results may contribute to the development of mRNA therapeutics.

Efficient recombinant production of mouse-derived cryptdin family peptides by a novel facilitation strategy for inclusion body formation

BACKGROUND

A number of antimicrobial peptides (AMPs) hold promise as new drugs owing to their potent bactericidal activity and because they are often refractory to the development of drug resistance. Cryptdins (Crps) are a family of antimicrobial peptides found in the small intestine of mice, comprising six isoforms containing three sets of disulfide bonds. Although Crp4 is actively being investigated, there have been few studies to date on the other Crp isoforms. A prerequisite for detailed characterization of the other Crp isoforms is establishment of efficient sample preparation methods.

RESULTS

To avoid degradation during recombinant expression of Crps in E. coli, co-expression of Crps with the aggregation-prone protein human α-lactalbumin (HLA) was used to promote the formation of stable inclusion bodies. Using this method, the production of Crp4 and Crp6 by the BL21 strain was effective, but the expression of other Crp isoforms was not as efficient. The results of a cell-free system study suggested that Crps were degraded, even though a substantial amounts of Crps were synthesized. Therefore, using the Origami™ B strain, we were able to significantly increase the expression efficiency of Crps by promoting the formation of erroneous intermolecular disulfide bonds between HLA and Crps, thereby promoting protein aggregation and inclusion body formation, which prevented degradation. The various Crp isoforms were successfully refolded in vitro and purified using reversed-phase HPLC. In addition, the yield was further improved by deformylation of formyl-Crps. We measured the antibacterial activity of Crps against both Gram-positive and Gram-negative bacteria. Each Crp isoform exhibited a completely different trend in antimicrobial activity, although conformational analysis by circular dichroism did not reveal any significant steric differences.

CONCLUSION

In this study, we established a novel and efficient method for the production of the cryptdin family of cysteine-containing antimicrobial peptides. Additionally, we found that there were notable differences in the antibacterial activities of the various Crp family members. The expression system established in this study is expected to provide new insights regarding the mechanisms underlying the different antibacterial activities of the Crp family of peptides.

The Influence of the Nucleotide Composition of Genes and Gene Regulatory Elements on the Efficiency of Protein Expression in Escherichia coli

Recombinant proteins expressed in Escherichia coli are widely used in biochemical research and industrial processes. At the same time, achieving higher protein expression levels and correct protein folding still remains the key problem, since optimization of nutrient media, growth conditions, and methods for induction of protein synthesis do not always lead to the desired result. Often, low protein expression is determined by the sequences of the expressed genes and their regulatory regions. The genetic code is degenerated; 18 out of 20 amino acids are encoded by more than one codon. Choosing between synonymous codons in the coding sequence can significantly affect the level of protein expression and protein folding due to the influence of the gene nucleotide composition on the probability of formation of secondary mRNA structures that affect the ribosome binding at the translation initiation phase, as well as the ribosome movement along the mRNA during elongation, which, in turn, influences the mRNA degradation and the folding of the nascent protein. The nucleotide composition of the mRNA untranslated regions, in particular the promoter and Shine-Dalgarno sequences, also affects the efficiency of mRNA transcription, translation, and degradation. In this review, we describe the genetic principles that determine the efficiency of protein production in Escherichia coli.

5'UTR sequences influence protein levels in Escherichia coli by regulating translation initiation and mRNA stability

A set of 41 synthetic 5'UTRs with different theoretical translation initiation rates were generated to explore the role of 5'UTRs in the regulation of protein levels in Escherichia coli. The roles of the synthetic 5'UTRs in regulating the expression of different reporter genes were analyzed in vivo. Protein levels varied substantially between the different constructs but for most of the 5'UTRs, protein levels were not correlated with theoretical translation initiation rates. Large variations in mRNA concentrations were measured with the different 5'UTRs even though the same concentration of transcription inducer was used in each case. 5'UTRs were also found to strongly affect mRNA stability, and these changes in mRNA stability often contributed to observed differences in mRNA concentration. Unexpectedly, the effect of the 5'UTRs on mRNA half-lives was found to vary depending on the downstream reporter gene. These results clearly demonstrate that 5'UTRs contribute to gene expression regulation at the level of translation initiation and of mRNA stability, to an extent that depends on the nature of the downstream gene.

Distance-dependent inhibition of translation initiation by downstream out-of-frame AUGs is consistent with a Brownian ratchet process of ribosome scanning

BACKGROUND

Eukaryotic ribosomes are widely presumed to scan mRNA for the AUG codon to initiate translation in a strictly 5'-3' movement (i.e., strictly unidirectional scanning model), so that ribosomes initiate translation exclusively at the 5' proximal AUG codon (i.e., the first-AUG rule).

RESULTS

We generate 13,437 yeast variants, each with an ATG triplet placed downstream (dATGs) of the annotated ATG (aATG) codon of a green fluorescent protein. We find that out-of-frame dATGs can inhibit translation at the aATG, but with diminishing strength over increasing distance between aATG and dATG, undetectable beyond ~17 nt. This phenomenon is best explained by a Brownian ratchet mechanism of ribosome scanning, in which the ribosome uses small-amplitude 5'-3' and 3'-5' oscillations with a net 5'-3' movement to scan the AUG codon, thereby leading to competition for translation initiation between aAUG and a proximal dAUG. This scanning model further predicts that the inhibitory effect induced by an out-of-frame upstream AUG triplet (uAUG) will diminish as uAUG approaches aAUG, which is indeed observed among the 15,586 uATG variants generated in this study. Computational simulations suggest that each triplet is scanned back and forth approximately ten times until the ribosome eventually migrates to downstream regions. Moreover, this scanning process could constrain the evolution of sequences downstream of the aATG to minimize proximal out-of-frame dATG triplets in yeast and humans.

CONCLUSIONS

Collectively, our findings uncover the basic process by which eukaryotic ribosomes scan for initiation codons, and how this process could shape eukaryotic genome evolution.

Translational enhancement by base editing of the Kozak sequence rescues haploinsufficiency

A variety of single-gene human diseases are caused by haploinsufficiency, a genetic condition by which mutational inactivation of one allele leads to reduced protein levels and functional impairment. Translational enhancement of the spare allele could exert a therapeutic effect. Here we developed BOOST, a novel gene-editing approach to rescue haploinsufficiency loci by the change of specific single nucleotides in the Kozak sequence, which controls translation by regulating start codon recognition. We evaluated for translational strength 230 Kozak sequences of annotated human haploinsufficient genes and 4621 derived variants, which can be installed by base editing, by a high-throughput reporter assay. Of these variants, 149 increased the translation of 47 Kozak sequences, demonstrating that a substantial proportion of haploinsufficient genes are controlled by suboptimal Kozak sequences. Validation of 18 variants for 8 genes produced an average enhancement in an expression window compatible with the rescue of the genetic imbalance. Base editing of the NCF1 gene, whose monoallelic loss causes chronic granulomatous disease, resulted in the desired increase of NCF1 (p47phox) protein levels in a relevant cell model. We propose BOOST as a fine-tuned approach to modulate translation, applicable to the correction of dozens of haploinsufficient monogenic disorders independently of the causing mutation.

Association of ABCC2 polymorphism with clopidogrel response in Chinese patients undergoing percutaneous coronary intervention

Aim: In this study, we investigated the association between ABCC2 polymorphism and clopidogrel response as well as the associated hypothetical mechanism.

Methods: Chinese patients (213) with coronary artery disease (CAD) who underwent percutaneous coronary intervention (PCI) and received clopidogrel were recruited. Thereafter, their ADP-induced platelet inhibition rates (PAIR%) were determined via thromboelastometry. Further, the single-nucleotide polymorphisms (SNPs) of ABCC2 were genotyped using high-resolution melting curve (HRM)-PCR, while CYP2C19*2 and *3 polymorphisms were genotyped via real-time PCR.

Results: The allele frequencies of ABCC2 rs717620 were 74.88 and 25.12% for the C and T alleles, respectively. Further, ABCC2 rs717620 TT carriers exhibited significantly higher PAIR% values (72.60 ± 27.69) than both CT (61.44 ± 23.65) and CC carriers (52.72 ± 21.99) (p = 0.047 and p = 0.001, respectively), and ABCC2 rs717620 CT carriers showed significantly higher mean PAIR% values than ABCC2 rs717620 CC carriers (p = 0.011). However, the PAIR% values corresponding to ABCC2 rs2273697 and ABCC2 rs3740066 carriers were not different. Additionally, CYP2C19*2 AA carriers presented significantly lower PAIR% values than CYP2C19*2 GA (p = 0.015) and GG (p = 0.003) carriers, and CYP2C19*3 GA carriers also presented significantly lower PAIR% values than CYP2C19*3 GG carriers (p = 0.041). In patients with CYP2C19 extensive metabolizers (EM), ABCC2 rs717620 TT carriers showed significantly higher PAIR% values (89.77 ± 9.73) than CT (76.76 ± 26.00) and CC carriers (74.09 ± 25.29) (p = 0.040 and p = 0.009, respectively). In patients with CYP2C19 poor metabolizers (PM), ABCC2 rs717620 CC carriers showed significantly lower PAIR% values (51.72 ± 25.78) than CT carriers (75.37 ± 23.57) (p = 0.043). Furthermore, after adjusting for confounding factors, ABCC2 rs717620 was identified as a strong predictor of clopidogrel hyperreactivity.

Conclusion: We proposed a new target, ABCC2 rs717620, in the efflux pathway that affects individual responses to clopidogrel. The TT allele of ABCC2 rs717620 was also identified as an independent risk factor for clopidogrel hyperreactivity, and CYP2C19*2 and *3 showed association with an increased risk for clopidogrel resistance. Additionally, ABCC2 rs717620 may affect individual responses to clopidogrel via post-transcriptional regulation and interaction with CYP2C19. These findings provide new insights that may guide the accurate use of clopidogrel.

Are there roles for heterogeneous ribosomes during sleep in the rodent brain?

The regulation of mRNA translation plays an essential role in neurons, contributing to important brain functions, such as brain plasticity and memory formation. Translation is conducted by ribosomes, which at their core consist of ribosomal proteins (RPs) and ribosomal RNAs. While translation can be regulated at diverse levels through global or mRNA-specific means, recent evidence suggests that ribosomes with distinct configurations are involved in the translation of different subsets of mRNAs. However, whether and how such proclaimed ribosome heterogeneity could be connected to neuronal functions remains largely unresolved. Here, we postulate that the existence of heterologous ribosomes within neurons, especially at discrete synapses, subserve brain plasticity. This hypothesis is supported by recent studies in rodents showing that heterogeneous RP expression occurs in dendrites, the compartment of neurons where synapses are made. We further propose that sleep, which is fundamental for brain plasticity and memory formation, has a particular role in the formation of heterologous ribosomes, specialised in the translation of mRNAs specific for synaptic plasticity. This aspect of our hypothesis is supported by recent studies showing increased translation and changes in RP expression during sleep after learning. Thus, certain RPs are regulated by sleep, and could support different sleep functions, in particular brain plasticity. Future experiments investigating cell-specific heterogeneity in RPs across the sleep-wake cycle and in response to different behaviour would help address this question.

Flow-Seq Method: Features and Application in Bacterial Translation Studies

The Flow-seq method is based on using reporter construct libraries, where a certain element regulating the gene expression of fluorescent reporter proteins is represented in many thousands of variants. Reporter construct libraries are introduced into cells, sorted according to their fluorescence level, and then subjected to next-generation sequencing. Therefore, it turns out to be possible to identify patterns that determine the expression efficiency, based on tens and hundreds of thousands of reporter constructs in one experiment. This method has become common in evaluating the efficiency of protein synthesis simultaneously by multiple mRNA variants. However, its potential is not confined to this area. In the presented review, a comparative analysis of the Flow-seq method and other alternative approaches used for translation efficiency evaluation of mRNA was carried out; the features of its application and the results obtained by Flow-seq were also considered.