A short translational ramp determines the efficiency of protein synthesis

Automated characterization and analysis of expression compatibility between regulatory sequences and metabolic genes in Escherichia coli

Utilizing standardized artificial regulatory sequences to fine-tuning the expression of multiple metabolic pathways/genes is a key strategy in the creation of efficient microbial cell factories. However, when regulatory sequence expression strengths are characterized using only a few reporter genes, they may not be applicable across diverse genes. This introduces great uncertainty into the precise regulation of multiple genes at multiple expression levels. To address this, our study adopted a fluorescent protein fusion strategy for a more accurate assessment of target protein expression levels. We combined 41 commonly-used metabolic genes with 15 regulatory sequences, yielding an expression dataset encompassing 520 unique combinations. This dataset highlighted substantial variation in protein expression level under identical regulatory sequences, with relative expression levels ranging from 2.8 to 176-fold. It also demonstrated that improving the strength of regulatory sequences does not necessarily lead to significant improvements in the expression levels of target proteins. Utilizing this dataset, we have developed various machine learning models and discovered that the integration of promoter regions, ribosome binding sites, and coding sequences significantly improves the accuracy of predicting protein expression levels, with a Spearman correlation coefficient of 0.72, where the promoter sequence exerts a predominant influence. Our study aims not only to provide a detailed guide for fine-tuning gene expression in the metabolic engineering of Escherichia coli but also to deepen our understanding of the compatibility issues between regulatory sequences and target genes.

A data-driven estimation of the ribosome drop-off rate in S. cerevisiae reveals a correlation with the genes length

Ribosomes are the molecular machinery that catalyse all the fundamental steps involved in the translation of mRNAs into proteins. Given the complexity of this process, the efficiency of protein synthesis depends on a large number of factors among which ribosome drop-off (i.e. the premature detachment of the ribosome from the mRNA template) plays an important role. However, an in vitro quantification of the extent to which ribosome drop-off occurs is not trivial due to difficulties in obtaining the needed experimental evidence. In this work we focus on the study of ribosome drop-off in Saccharomyces cerevisiae by using 'Ribofilio', a novel software tool that relies on a high sensitive strategy to estimate the ribosome drop-off rate from ribosome profiling data. Our results show that ribosome drop-off events occur at a significant rate also when S. cerevisiae is cultured in standard conditions. In this context, we also identified a correlation between the ribosome drop-off rate and the genes length: the longer the gene, the lower the drop-off rate.

N-Terminal Amino Acid Affects the Translation Efficiency at Lower Temperatures in a Reconstituted Protein Synthesis System

The Escherichia coli (E. coli)-based protein synthesis using recombinant elements (PURE) system is a cell-free protein synthesis system reconstituted from purified factors essential for E. coli translation. The PURE system is widely used for basic and synthetic biology applications. One of the major challenges associated with the PURE system is that the protein yield of the system varies depending on the protein. Studies have reported that the efficiency of translation is significantly affected by nucleotide and amino acid sequences, especially in the N-terminal region. Here, we investigated the inherent effect of various N-terminal sequences on protein synthesis using the PURE system. We found that a single amino acid substitution in the N-terminal region significantly altered translation efficiency in the PURE system, especially at low temperatures. This result gives us useful suggestions for the expression of the protein of interest in vitro and in vivo.

Non-specific N-terminal tetrapeptide insertions disrupt the translation arrest induced by ribosome arresting peptide sequences

The nascent polypeptide chains passing through the ribosome tunnel not only serve as an intermediate of protein synthesis but also, in some cases, act as dynamic genetic information, controlling translation through interaction with the ribosome. One notable example is Escherichia coli SecM, in which translation of the ribosome arresting peptide (RAP) sequence in SecM leads to robust elongation arrest. Translation regulations, including the SecM-induced translation arrest, play regulatory roles such as gene expression control. Recent investigations have indicated that the insertion of a peptide sequence, SKIK (or MSKIK), into the adjacent N-terminus of the RAP sequence of SecM behaves as an "arrest canceler". As the study did not provide a direct assessment of the strength of translation arrest, we conducted detailed biochemical analyses. The results revealed that the effect of SKIK insertion on weakening SecM-induced translation arrest was not specific to the SKIK sequence, that is, other tetrapeptide sequences inserted just before the RAP sequence also attenuated the arrest. Our data suggest that SKIK or other tetrapeptide insertions disrupt the context of the RAP sequence rather than canceling or preventing the translation arrest.

Mutational biases favor complexity increases in protein interaction networks after gene duplication

Biological systems can gain complexity over time. While some of these transitions are likely driven by natural selection, the extent to which they occur without providing an adaptive benefit is unknown. At the molecular level, one example is heteromeric complexes replacing homomeric ones following gene duplication. Here, we build a biophysical model and simulate the evolution of homodimers and heterodimers following gene duplication using distributions of mutational effects inferred from available protein structures. We keep the specific activity of each dimer identical, so their concentrations drift neutrally without new functions. We show that for more than 60% of tested dimer structures, the relative concentration of the heteromer increases over time due to mutational biases that favor the heterodimer. However, allowing mutational effects on synthesis rates and differences in the specific activity of homo- and heterodimers can limit or reverse the observed bias toward heterodimers. Our results show that the accumulation of more complex protein quaternary structures is likely under neutral evolution, and that natural selection would be needed to reverse this tendency.

G Protein Activation Occurs via a Largely Universal Mechanism

Understanding how signaling proteins like G proteins are allosterically activated is a long-standing challenge with significant biological and medical implications. Because it is difficult to directly observe such dynamic processes, much of our understanding is based on inferences from a limited number of static snapshots of relevant protein structures, mutagenesis data, and patterns of sequence conservation. Here, we use computer simulations to directly interrogate allosteric coupling in six G protein α-subunit isoforms covering all four G protein families. To analyze this data, we introduce automated methods for inferring allosteric networks from simulation data and assessing how allostery is conserved or diverged among related protein isoforms. We find that the allosteric networks in these six G protein α subunits are largely conserved and consist of two pathways, which we call pathway-I and pathway-II. This analysis predicts that pathway-I is generally dominant over pathway-II, which we experimentally corroborate by showing that mutations to pathway-I perturb nucleotide exchange more than mutations to pathway-II. In the future, insights into unique elements of each G protein family could inform the design of isoform-specific drugs. More broadly, our tools should also be useful for studying allostery in other proteins and assessing the extent to which this allostery is conserved in related proteins.

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.

Molecular insights into capsular polysaccharide secretion

Capsular polysaccharides (CPSs) fortify the cell boundaries of many commensal and pathogenic bacteria1. Through the ABC-transporter-dependent biosynthesis pathway, CPSs are synthesized intracellularly on a lipid anchor and secreted across the cell envelope by the KpsMT ABC transporter associated with the KpsE and KpsD subunits1,2. Here we use structural and functional studies to uncover crucial steps of CPS secretion in Gram-negative bacteria. We show that KpsMT has broad substrate specificity and is sufficient for the translocation of CPSs across the inner bacterial membrane, and we determine the cell surface organization and localization of CPSs using super-resolution fluorescence microscopy. Cryo-electron microscopy analyses of the KpsMT-KpsE complex in six different states reveal a KpsE-encaged ABC transporter, rigid-body conformational rearrangements of KpsMT during ATP hydrolysis and recognition of a glycolipid inside a membrane-exposed electropositive canyon. In vivo CPS secretion assays underscore the functional importance of canyon-lining basic residues. Combined, our analyses suggest a molecular model of CPS secretion by ABC transporters.

Targeting paraptosis in cancer: opportunities and challenges

Cell death can be classified into two primary categories: accidental cell death and regulated cell death (RCD). Within RCD, there are distinct apoptotic and non-apoptotic cell death pathways. Among the various forms of non-apoptotic RCD, paraptosis stands out as a unique mechanism characterized by distinct morphological changes within cells. These alterations encompass cytoplasmic vacuolization, organelle swelling, notably in the endoplasmic reticulum and mitochondria, and the absence of typical apoptotic features, such as cell shrinkage and DNA fragmentation. Biochemically, paraptosis distinguishes itself by its independence from caspases, which are conventionally associated with apoptotic death. This intriguing cell death pathway can be initiated by various cellular stressors, including oxidative stress, protein misfolding, and specific chemical compounds. Dysregulated paraptosis plays a pivotal role in several critical cancer-related processes, such as autophagic degradation, drug resistance, and angiogenesis. This review provides a comprehensive overview of recent advancements in our understanding of the mechanisms and regulation of paraptosis. Additionally, it delves into the potential of paraptosis-related compounds for targeted cancer treatment, with the aim of enhancing treatment efficacy while minimizing harm to healthy cells.

Molecular Mechanisms and the Significance of Synonymous Mutations

Synonymous mutations result from the degeneracy of the genetic code. Most amino acids are encoded by two or more codons, and mutations that change a codon to another synonymous codon do not change the amino acid in the gene product. Historically, such mutations have been considered silent because they were assumed to have no to very little impact. However, research in the last few decades has produced several examples where synonymous mutations play important roles. These include optimizing expression by enhancing translation initiation and accelerating or decelerating translation elongation via codon usage and mRNA secondary structures, stabilizing mRNA molecules and preventing their breakdown before translation, and faulty protein folding or increased degradation due to enhanced ubiquitination and suboptimal secretion of proteins into the appropriate cell compartments. Some consequences of synonymous mutations, such as mRNA stability, can lead to different outcomes in prokaryotes and eukaryotes. Despite these examples, the significance of synonymous mutations in evolution and in causing disease in comparison to nonsynonymous mutations that do change amino acid residues in proteins remains controversial. Whether the molecular mechanisms described by which synonymous mutations affect organisms can be generalized remains poorly understood and warrants future research in this area.

RNA-seq reveals multifaceted gene expression response to Fab production in Escherichia coli fed-batch processes with particular focus on ribosome stalling

BACKGROUND

Escherichia coli is a cost-effective expression system for production of antibody fragments like Fabs. Various yield improvement strategies have been applied, however, Fabs remain challenging to produce. This study aimed to characterize the gene expression response of commonly used E. coli strains BL21(DE3) and HMS174(DE3) to periplasmic Fab expression using RNA sequencing (RNA-seq). Two Fabs, Fabx and FTN2, fused to a post-translational translocation signal sequence, were produced in carbon-limited fed-batch cultivations.

RESULTS

Production of Fabx impeded cell growth substantially stronger than FTN2 and yields of both Fabs differed considerably. The most noticeable, common changes in Fab-producing cells suggested by our RNA-seq data concern the cell envelope. The Cpx and Psp stress responses, both connected to inner membrane integrity, were activated, presumably by recombinant protein aggregation and impairment of the Sec translocon. The data additionally suggest changes in lipopolysaccharide synthesis, adjustment of membrane permeability, and peptidoglycan maturation and remodeling. Moreover, all Fab-producing strains showed depletion of Mg2+, indicated by activation of the PhoQP two-component signal transduction system during the early stage and sulfur and phosphate starvation during the later stage of the process. Furthermore, our data revealed ribosome stalling, caused by the Fabx amino acid sequence, as a contributor to low Fabx yields. Increased Fabx yields were obtained by a site-specific amino acid exchange replacing the stalling sequence. Contrary to expectations, cell growth was not impacted by presence or removal of the stalling sequence. Considering ribosome rescue is a conserved mechanism, the substantial differences observed in gene expression between BL21(DE3) and HMS174(DE3) in response to ribosome stalling on the recombinant mRNA were surprising.

CONCLUSIONS

Through characterization of the gene expression response to Fab production under industrially relevant cultivation conditions, we identified potential cell engineering targets. Thereby, we hope to enable rational approaches to improve cell fitness and Fab yields. Furthermore, we highlight ribosome stalling caused by the amino acid sequence of the recombinant protein as a possible challenge during recombinant protein production.

Implications of tRNA abundance on translation elongation across bovine tissues

Introduction: Translation is a crucial stage of gene expression. It may also act as an additional layer of regulation that plays an important role in gene expression and function. Highly expressed genes are believed to be codon-biased to support increased protein production, in which quickly translated codons correspond to highly abundant tRNAs. Synonymous SNPs, considered to be silent due to the degeneracy of the genetic code, may shift protein abundance and function through alterations in translational efficiency and suboptimal pairing to lowly abundant tRNAs. Methods: Here, we applied Quantitative Mature tRNA sequencing (QuantM-tRNAseq) and ribosome profiling across bovine tissues in order to investigate the relationship between tRNA expression and slowed translation. Results: Moreover, we have identified genes modulated at transcriptional and/or translational levels underlying tissue-specific biological processes. We have also successfully defined pausing sites that depict the regulatory information encoded within the open reading frame of transcripts, which could be related to translation rate and facilitate proper protein folding. This work offers an atlas of distinctive pausing sites across three bovine tissues, which provides an opportunity to predict codon optimality and understand tissue-specific mechanisms of regulating protein synthesis.

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.

The distinct translational landscapes of gram-negative Salmonella and gram-positive Listeria

Translational control in pathogenic bacteria is fundamental to gene expression and affects virulence and other infection phenotypes. We used an enhanced ribosome profiling protocol coupled with parallel transcriptomics to capture accurately the global translatome of two evolutionarily distant pathogenic bacteria-the Gram-negative bacterium Salmonella and the Gram-positive bacterium Listeria. We find that the two bacteria use different mechanisms to translationally regulate protein synthesis. In Salmonella, in addition to the expected correlation between translational efficiency and cis-regulatory features such as Shine-Dalgarno (SD) strength and RNA secondary structure around the initiation codon, our data reveal an effect of the 2nd and 3rd codons, where the presence of tandem lysine codons (AAA-AAA) enhances translation in both Salmonella and E. coli. Strikingly, none of these features are seen in efficiently translated Listeria transcripts. Instead, approximately 20% of efficiently translated Listeria genes exhibit 70 S footprints seven nt upstream of the authentic start codon, suggesting that these genes may be subject to a novel translational initiation mechanism. Our results show that SD strength is not a direct hallmark of translational efficiency in all bacteria. Instead, Listeria has evolved additional mechanisms to control gene expression level that are distinct from those utilised by Salmonella and E. coli.

Molecular bases for strong phenotypic effects of single synonymous codon substitutions in the E. coli ccdB toxin gene

BACKGROUND

Single synonymous codon mutations typically have only minor or no effects on gene function. Here, we estimate the effects on cell growth of ~ 200 single synonymous codon mutations in an operonic context by mutating almost all positions of ccdB, the 101-residue long cytotoxin of the ccdAB Toxin-Antitoxin (TA) operon to most degenerate codons. Phenotypes were assayed by transforming the mutant library into CcdB sensitive and resistant E. coli strains, isolating plasmid pools, and subjecting them to deep sequencing. Since autoregulation is a hallmark of TA operons, phenotypes obtained for ccdB synonymous mutants after transformation in a RelE toxin reporter strain followed by deep sequencing provided information on the amount of CcdAB complex formed.

RESULTS

Synonymous mutations in the N-terminal region involved in translation initiation showed the strongest non-neutral phenotypic effects. We observe an interplay of numerous factors, namely, location of the codon, codon usage, t-RNA abundance, formation of anti-Shine Dalgarno sequences, predicted transcript secondary structure, and evolutionary conservation in determining phenotypic effects of ccdB synonymous mutations. Incorporation of an N-terminal, hyperactive synonymous mutation, in the background of the single synonymous codon mutant library sufficiently increased translation initiation, such that mutational effects on either folding or termination of translation became more apparent. Introduction of putative pause sites not only affects the translational rate, but might also alter the folding kinetics of the protein in vivo.

CONCLUSION

In summary, the study provides novel insights into diverse mechanisms by which synonymous mutations modulate gene function. This information is useful in optimizing heterologous gene expression in E. coli and understanding the molecular bases for alteration in gene expression that arise due to synonymous mutations.

Translational regulation of cell invasion through extracellular matrix-an emerging role for ribosomes

Many developmental and physiological processes require cells to invade and migrate through extracellular matrix barriers. This specialized cellular behavior is also misregulated in many diseases, such as immune disorders and cancer. Cell invasive activity is driven by pro-invasive transcriptional networks that activate the expression of genes encoding numerous different proteins that expand and regulate the cytoskeleton, endomembrane system, cell adhesion, signaling pathways, and metabolic networks. While detailed mechanistic studies have uncovered crucial insights into pro-invasive transcriptional networks and the distinct cell biological attributes of invasive cells, less is known about how invasive cells modulate mRNA translation to meet the robust, dynamic, and unique protein production needs of cell invasion. In this review we outline known modes of translation regulation promoting cell invasion and focus on recent studies revealing elegant mechanisms that expand ribosome biogenesis within invasive cells to meet the increased protein production requirements to invade and migrate through extracellular matrix barriers.

Codon optimality modulates protein output by tuning translation initiation

The impact of synonymous codon choice on protein output has important implications for understanding endogenous gene expression and design of synthetic mRNAs. Previously, we used a neural network model to design a series of synonymous fluorescent reporters whose protein output in yeast spanned a seven-fold range corresponding to their predicted translation speed. Here, we show that this effect is not due primarily to the established impact of slow elongation on mRNA stability, but rather, that an active mechanism further decreases the number of proteins made per mRNA. We combine simulations and careful experiments on fluorescent reporters to argue that translation initiation is limited on non-optimally encoded transcripts. Using a genome-wide CRISPRi screen to discover factors modulating the output from non-optimal transcripts, we identify a set of translation initiation factors including multiple subunits of eIF3 whose depletion restored protein output of a non-optimal reporter. Our results show that codon usage can directly limit protein production, across the full range of endogenous variability in codon usage, by limiting translation initiation.

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.

Improving deep models of protein-coding potential with a Fourier-transform architecture and machine translation task

Ribosomes are information-processing macromolecular machines that integrate complex sequence patterns in messenger RNA (mRNA) transcripts to synthesize proteins. Studies of the sequence features that distinguish mRNAs from long noncoding RNAs (lncRNAs) may yield insight into the information that directs and regulates translation. Computational methods for calculating protein-coding potential are important for distinguishing mRNAs from lncRNAs during genome annotation, but most machine learning methods for this task rely on previously known rules to define features. Sequence-to-sequence (seq2seq) models, particularly ones using transformer networks, have proven capable of learning complex grammatical relationships between words to perform natural language translation. Seeking to leverage these advancements in the biological domain, we present a seq2seq formulation for predicting protein-coding potential with deep neural networks and demonstrate that simultaneously learning translation from RNA to protein improves classification performance relative to a classification-only training objective. Inspired by classical signal processing methods for gene discovery and Fourier-based image-processing neural networks, we introduce LocalFilterNet (LFNet). LFNet is a network architecture with an inductive bias for modeling the three-nucleotide periodicity apparent in coding sequences. We incorporate LFNet within an encoder-decoder framework to test whether the translation task improves the classification of transcripts and the interpretation of their sequence features. We use the resulting model to compute nucleotide-resolution importance scores, revealing sequence patterns that could assist the cellular machinery in distinguishing mRNAs and lncRNAs. Finally, we develop a novel approach for estimating mutation effects from Integrated Gradients, a backpropagation-based feature attribution, and characterize the difficulty of efficient approximations in this setting.

Large-scale analysis of mRNA sequences localized near the start and amber codons and their impact on the diversity of mRNA display libraries

Extremely diverse libraries are essential for effectively selecting functional peptides or proteins, and mRNA display technology is a powerful tool for generating such libraries with over 1012-1013 diversity. Particularly, the protein-puromycin linker (PuL)/mRNA complex formation yield is determining for preparing the libraries. However, how mRNA sequences affect the complex formation yield remains unclear. To study the effects of N-terminal and C-terminal coding sequences on the complex formation yield, puromycin-attached mRNAs containing three random codons after the start codon (32768 sequences) or seven random bases next to the amber codon (6480 sequences) were translated. Enrichment scores were calculated by dividing the appearance rate of every sequence in protein-PuL/mRNA complexes by that in total mRNAs. The wide range of enrichment scores (0.09-2.10 for N-terminal and 0.30-4.23 for C-terminal coding sequences) indicated that the N-terminal and C-terminal coding sequences strongly affected the complex formation yield. Using C-terminal GGC-CGA-UAG-U sequences, which resulted in the highest enrichment scores, we constructed highly diverse libraries of monobodies and macrocyclic peptides. The present study provides insights into how mRNA sequences affect the protein/mRNA complex formation yield and will accelerate the identification of functional peptides and proteins involved in various biological processes and having therapeutic applications.

Molecular interplay between EIF4 family and circular RNAs in cancer: Mechanisms and therapeutics

The eukaryotic translation initiation factor 4 (EIF4) family is a major contributor to the recruitment of mRNAs to ribosomes during the initial translation stage in eukaryotes, whose dysregulation either allows for cancer transformation or prevents disordered cancerous cell growth. Circular RNAs (circRNAs), which exhibit distinctive structures and are widely expressed in eukaryotes, are anticipated to be a clinical diagnostic biomarker for cancer therapy. There is considerable evidence that EIF4s can influence the biogenesis, transport, and function of circRNAs and, in turn, circRNAs can control the expressions of EIF4s through certain molecular pathways. Herein, we primarily review the emerging studies of the EIF4 family and pinpoint the roles of dysregulated EIF4s in cancer. We also evaluate the patterns of intricate interactions between circRNAs and EIF4s and discuss the potential utility of circRNA-based therapeutics targeting EIF4s in clinical cancer research.

Identification of proteins regulated by chlorogenic acid in an ischemic animal model: a proteomic approach

BACKGROUND

Cerebral ischemia is a serious neurological disorder that can lead to high morbidity and mortality. Chlorogenic acid is a polyphenol compound with antioxidant that can regulate proteins in cerebral ischemia. Middle cerebral artery occlusion (MCAO) surgery was performed to induce ischemic brain injury and was maintained for 24 h. Chlorogenic acid (30 mg/kg) or vehicle was administrated into the peritoneal cavity 2 h after MCAO surgery. The cerebral cortical tissues were collected for further study and a proteomic approach was performed to identify the proteins changed by chlorogenic acid in the MCAO animals.

RESULTS

We found that chlorogenic acid alleviated in changes in adenosylhomocysteinase, glycerol-3-phosphate dehydrogenase, eukaryotic translation initiation factor 4A-II, apolipoprotein A-I, and mu-crystallin. These proteins were reduced in MCAO animals with vehicle, and these reductions were attenuated by chlorogenic acid treatment. The mitigation of this reduction by chlorogenic acid was confirmed by the reverse transcription PCR technique. These proteins are associated with energy metabolism, protein synthesis, inflammation, and physiological metabolism. They are involved in the neuroprotective effect of chlorogenic acid. These results showed that chlorogenic acid alleviates the neurological disorders caused by MCAO and regulates the expression of proteins involved in neuroprotection.

CONCLUSIONS

Therefore, our findings provide evidence that chlorogenic acid plays a neuroprotective role in stroke animal models by controlling specific proteins.

Translation initiation consistency between in vivo and in vitro bacterial protein expression systems

Strict on-demand control of protein synthesis is a crucial aspect of synthetic biology. The 5'-terminal untranslated region (5'-UTR) is an essential bacterial genetic element that can be designed for the regulation of translation initiation. However, there is insufficient systematical data on the consistency of 5'-UTR function among various bacterial cells and in vitro protein synthesis systems, which is crucial for the standardization and modularization of genetic elements in synthetic biology. Here, more than 400 expression cassettes comprising the GFP gene under the regulation of various 5'-UTRs were systematically characterized to evaluate the protein translation consistency in the two popular Escherichia coli strains of JM109 and BL21, as well as an in vitro protein expression system based on cell lysate. In contrast to the very strong correlation between the two cellular systems, the consistency between in vivo and in vitro protein translation was lost, whereby both in vivo and in vitro translation evidently deviated from the estimation of the standard statistical thermodynamic model. Finally, we found that the absence of nucleotide C and complex secondary structure in the 5'-UTR significantly improve the efficiency of protein translation, both in vitro and in vivo.

An Aurora B-RPA signaling axis secures chromosome segregation fidelity

Errors in chromosome segregation underlie genomic instability associated with cancers. Resolution of replication and recombination intermediates and protection of vulnerable single-stranded DNA (ssDNA) intermediates during mitotic progression requires the ssDNA binding protein Replication Protein A (RPA). However, the mechanisms that regulate RPA specifically during unperturbed mitotic progression are poorly resolved. RPA is a heterotrimer composed of RPA70, RPA32 and RPA14 subunits and is predominantly regulated through hyperphosphorylation of RPA32 in response to DNA damage. Here, we have uncovered a mitosis-specific regulation of RPA by Aurora B kinase. Aurora B phosphorylates Ser-384 in the DNA binding domain B of the large RPA70 subunit and highlights a mode of regulation distinct from RPA32. Disruption of Ser-384 phosphorylation in RPA70 leads to defects in chromosome segregation with loss of viability and a feedback modulation of Aurora B activity. Phosphorylation at Ser-384 remodels the protein interaction domains of RPA. Furthermore, phosphorylation impairs RPA binding to DSS1 that likely suppresses homologous recombination during mitosis by preventing recruitment of DSS1-BRCA2 to exposed ssDNA. We showcase a critical Aurora B-RPA signaling axis in mitosis that is essential for maintaining genomic integrity.

Quality control of protein synthesis in the early elongation stage

In the early stage of bacterial translation, peptidyl-tRNAs frequently dissociate from the ribosome (pep-tRNA drop-off) and are recycled by peptidyl-tRNA hydrolase. Here, we establish a highly sensitive method for profiling of pep-tRNAs using mass spectrometry, and successfully detect a large number of nascent peptides from pep-tRNAs accumulated in Escherichia coli pth^ts strain. Based on molecular mass analysis, we found about 20% of the peptides bear single amino-acid substitutions of the N-terminal sequences of E. coli ORFs. Detailed analysis of individual pep-tRNAs and reporter assay revealed that most of the substitutions take place at the C-terminal drop-off site and that the miscoded pep-tRNAs rarely participate in the next round of elongation but dissociate from the ribosome. These findings suggest that pep-tRNA drop-off is an active mechanism by which the ribosome rejects miscoded pep-tRNAs in the early elongation, thereby contributing to quality control of protein synthesis after peptide bond formation.

Improving deep models of protein-coding potential with a Fourier-transform architecture and machine translation task

Ribosomes are information-processing macromolecular machines that integrate complex sequence patterns in messenger RNA (mRNA) transcripts to synthesize proteins. Studies of the sequence features that distinguish mRNAs from long noncoding RNAs (lncRNAs) may yield insight into the information that directs and regulates translation. Computational methods for calculating protein-coding potential are important for distinguishing mRNAs from lncRNAs during genome annotation, but most machine learning methods for this task rely on previously known rules to define features. Sequence-to-sequence (seq2seq) models, particularly ones using transformer networks, have proven capable of learning complex grammatical relationships between words to perform natural language translation. Seeking to leverage these advancements in the biological domain, we present a seq2seq formulation for predicting protein-coding potential with deep neural networks and demonstrate that simultaneously learning translation from RNA to protein improves classification performance relative to a classification-only training objective. Inspired by classical signal processing methods for gene discovery and Fourier-based image-processing neural networks, we introduce LocalFilterNet (LFNet). LFNet is a network architecture with an inductive bias for modeling the three-nucleotide periodicity apparent in coding sequences. We incorporate LFNet within an encoder-decoder framework to test whether the translation task improves the classification of transcripts and the interpretation of their sequence features. We use the resulting model to compute nucleotide-resolution importance scores, revealing sequence patterns that could assist the cellular machinery in distinguishing mRNAs and lncRNAs. Finally, we develop a novel approach for estimating mutation effects from Integrated Gradients, a backpropagation-based feature attribution, and characterize the difficulty of efficient approximations in this setting.

Purification and characterization of eukaryotic ATP-dependent transporters homologously expressed in Pichia pastoris for structural studies by cryo-electron microscopy

Membrane proteins play an essential role in all living organisms. Although there have been numerous efforts in the past to elucidate the structure and function of eukaryotic primary active transporters, knowledge about the majority of these membrane proteins is still minimal. This is often due to their low availability and complex handling. In this study, we homologously expressed three ATP-dependent transport proteins, STE6-2p, NEO1-p, and YPK9-p, in Pichia pastoris and subsequently optimized the solubilization and purification processes. Sequential use of different mild detergents and utilization of hydrophilic matrices in the purification procedure allowed us to obtain all three transporters monodisperse and in high purity, enabling initial structural analysis by cryo-electron microscopy. Using the respective substrates, we determined the specific activity of all target proteins using an ATPase assay. This study opens the door to further functional and structural studies of this pharmacologically important class of membrane proteins.

Ultradeep characterisation of translational sequence determinants refutes rare-codon hypothesis and unveils quadruplet base pairing of initiator tRNA and transcript

Translation is a key determinant of gene expression and an important biotechnological engineering target. In bacteria, 5'-untranslated region (5'-UTR) and coding sequence (CDS) are well-known mRNA parts controlling translation and thus cellular protein levels. However, the complex interaction of 5'-UTR and CDS has so far only been studied for few sequences leading to non-generalisable and partly contradictory conclusions. Herein, we systematically assess the dynamic translation from over 1.2 million 5'-UTR-CDS pairs in Escherichia coli to investigate their collective effect using a new method for ultradeep sequence-function mapping. This allows us to disentangle and precisely quantify effects of various sequence determinants of translation. We find that 5'-UTR and CDS individually account for 53% and 20% of variance in translation, respectively, and show conclusively that, contrary to a common hypothesis, tRNA abundance does not explain expression changes between CDSs with different synonymous codons. Moreover, the obtained large-scale data provide clear experimental evidence for a base-pairing interaction between initiator tRNA and mRNA beyond the anticodon-codon interaction, an effect that is often masked for individual sequences and therefore inaccessible to low-throughput approaches. Our study highlights the indispensability of ultradeep sequence-function mapping to accurately determine the contribution of parts and phenomena involved in gene regulation.

Standard Intein Gene Expression Ramps (SIGER) for Protein-Independent Expression Control

Coordination of multigene expression is one of the key challenges of metabolic engineering for the development of cell factories. Constraints on translation initiation and early ribosome kinetics of mRNA are imposed by features of the 5'UTR in combination with the start of the gene, referred to as the "gene ramp", such as rare codons and mRNA secondary structures. These features strongly influence the translation yield and protein quality by regulating the ribosome distribution on mRNA strands. The utilization of genetic expression sequences, such as promoters and 5'UTRs in combination with different target genes, leads to a wide variety of gene ramp compositions with irregular translation rates, leading to unpredictable levels of protein yield and quality. Here, we present the Standard Intein Gene Expression Ramp (SIGER) system for controlling protein expression. The SIGER system makes use of inteins to decouple the translation initiation features from the gene of a target protein. We generated sequence-specific gene expression sequences for two inteins (DnaB and DnaX) that display defined levels of protein expression. Additionally, we used inteins that possess the ability to release the C-terminal fusion protein in vivo to avoid the impairment of protein functionality by the fused intein. Overall, our results show that SIGER systems are unique tools to mitigate the undesirable effects of gene ramp variation and to control the relative ratios of enzymes involved in molecular pathways. As a proof of concept of the potential of the system, we also used a SIGER system to express two difficult-to-produce proteins, GumM and CBM73.

Epistasis between promoter activity and coding mutations shapes gene evolvability

The evolution of protein-coding genes proceeds as mutations act on two main dimensions: regulation of transcription level and the coding sequence. The extent and impact of the connection between these two dimensions are largely unknown because they have generally been studied independently. By measuring the fitness effects of all possible mutations on a protein complex at various levels of promoter activity, we show that promoter activity at the optimal level for the wild-type protein masks the effects of both deleterious and beneficial coding mutations. Mutations that are deleterious at low activity but masked at optimal activity are slightly destabilizing for individual subunits and binding interfaces. Coding mutations that increase protein abundance are beneficial at low expression but could potentially incur a cost at high promoter activity. We thereby demonstrate that promoter activity in interaction with protein properties can dictate which coding mutations are beneficial, neutral, or deleterious.

Evaluating Translational Efficiency of Noncanonical Amino Acids to Inform the Design of Druglike Peptide Libraries

Advances in genetic code reprogramming have allowed the site-specific incorporation of noncanonical functionalities into polypeptides and proteins, providing access to wide swaths of chemical space via in vitro translation techniques like mRNA display. Prior efforts have established that the translation machinery can tolerate amino acids with modifications to both the peptide backbone and side chains, greatly broadening the chemical space that can be interrogated in ligand discovery efforts. However, existing methods for confirming the translation yield of new amino acid building blocks for these technologies necessitate multistep workups and, more importantly, are not relevant for measuring translation within the context of a combinatorial library consisting of multiple noncanonical amino acids. In this study, we developed a luminescence-based assay to rapidly assess the relative translation yield of any noncanonical amino acid in real time. Among the 59 amino acids tested here, we found that many translate with high efficiency, but translational yield is not necessarily correlated to whether the amino acid is proteinogenic or has high tRNA acylation efficiency. Interestingly, we found that single-template translation data can inform the library-scale translation yield and that shorter peptide libraries are more tolerant of lower-efficiency amino acid monomers. Together our data show that the luminescence-based assay described herein is an essential tool in evaluating new building blocks and codon table designs within mRNA display toward the goal of developing druglike peptide-based libraries for drug discovery campaigns.

Development and Characterization of Flavin-Binding Fluorescent Proteins, Part I: Basic Characterization

Flavin-based fluorescent proteins (FbFPs) are small fluorescent proteins derived from light-oxygen-voltage (LOV) domains. The proteins bind ubiquitous endogenous flavins as chromophores and can be used as versatile in vivo reporter proteins under aerobic and anaerobic conditions. This chapter presents the methodology to identify LOV domain sequences in genomic databases; design new FbFPs; characterize their biochemical, spectroscopic, photophysical, and photochemical properties; and conduct basic fluorescence microscopy experiments.

Translational Regulation by eIFs and RNA Modifications in Cancer

Translation is a fundamental process in all living organisms that involves the decoding of genetic information in mRNA by ribosomes and translation factors. The dysregulation of mRNA translation is a common feature of tumorigenesis. Protein expression reflects the total outcome of multiple regulatory mechanisms that change the metabolism of mRNA pathways from synthesis to degradation. Accumulated evidence has clarified the role of an increasing amount of mRNA modifications at each phase of the pathway, resulting in translational output. Translation machinery is directly affected by mRNA modifications, influencing translation initiation, elongation, and termination or altering mRNA abundance and subcellular localization. In this review, we focus on the translation initiation factors associated with cancer as well as several important RNA modifications, for which we describe their association with cancer.

Structural and functional investigation of ABC transporter STE6-2p from Pichia pastoris reveals unexpected interaction with sterol molecules

Adenosine triphosphate (ATP)-binding cassette (ABC) transporters are multidomain transmembrane proteins, which facilitate the transport of various substances across cell membranes using energy derived from ATP hydrolysis. They are important drug targets since they mediate decreased drug susceptibility during pharmacological treatments. For the methylotrophic yeast Pichia pastoris, a model organism that is a widely used host for protein expression, the role and function of its ABC transporters is unexplored. In this work, we investigated the Pichia ABC-B transporter STE6-2p. Functional investigations revealed that STE6-2p is capable of transporting rhodamines in vivo and is active in the presence of verapamil and triazoles in vitro. A phylogenetic analysis displays homology among multidrug resistance (MDR) transporters from pathogenic fungi to human ABC-B transporters. Further, we present high-resolution single-particle electron cryomicroscopy structures of an ABC transporter from P. pastoris in the apo conformation (3.1 Å) and in complex with verapamil and adenylyl imidodiphosphate (AMP-PNP) (3.2 Å). An unknown density between transmembrane helices 4, 5, and 6 in both structures suggests the presence of a sterol-binding site of unknown function.

Depletion of Mdig Changes Proteomic Profiling in Triple Negative Breast Cancer Cells

Triple-negative breast cancers are highly aggressive with an overall poor prognosis and limited therapeutic options. We had previously investigated the role of mdig, an oncogenic gene induced by some environmental risk factors, on the pathogenesis of breast cancer. However, a comprehensive analysis of the proteomic profile affected by mdig in triple-negative breast cancer has not been determined yet. Using label-free bottom-up quantitative proteomics, we compared wildtype control and mdig knockout MDA-MB-231 cells and identified the proteins and pathways that are significantly altered with mdig deletion. A total of 904 differentially expressed (p < 0.005) proteins were identified in the KO cells. Approximately 30 pathways and networks linked to the pathogenicity of breast cancer were either up- or downregulated, such as EIF2 signaling, the unfolded protein response, and isoleucine degradation I. Ingenuity Pathway Analysis established that the differentially expressed proteins have relevant biological actions in cell growth, motility, and malignancy. These data provide the first insight into protein expression patterns in breast cancer associated with a complete disruption of the mdig gene and yielded substantial information on the key proteins, biological processes, and pathways modulated by mdig that contribute to breast cancer tumorigenicity and invasiveness.

Cyst stem cell lineage eIF5 non-autonomously prevents testicular germ cell tumor formation via eIF1A/eIF2γ-mediated pre-initiation complex

BACKGROUND

Stem cell niche maintains stem cell population identity and is essential for the homeostasis of self-renewal and differentiation in Drosophila testes. However, the mechanisms of CySC lineage signals-mediated soma-germline communications in response to external stimuli are unclear.

METHODS

Pre-initiation complex functions were evaluated by UAS-Gal4-mediated cell effects. RNA sequencing was conducted in NC and eIF5 siRNA-treated cells. Genetic interaction analysis was used to indicate the relationships between eIF5 and eIF1A/eIF2γ in Drosophila testes.

RESULTS

Here, we demonstrated that in CySCs, translation initiation factor eIF5 mediates cyst cell differentiation and the non-autonomously affected germ cell differentiation process. CySCs lacking eIF5 displayed unbalanced cell proliferation and apoptosis, forming testicular germ cell tumors (TGCTs) during spermatogenesis. eIF5 transcriptional regulation network analysis identified multiple metabolic processes and several key factors that might be involved in germ cell differentiation and TGCT formation. Importantly, knockdown of eIF1A and eIF2γ, key components of pre-initiation complex, mimicked the phenotype of knocking down eIF5 in the stem cell niche of Drosophila testes. Genetic interaction analysis indicated that eIF5 was sufficient to rescue the phenotype of tumorlike structures induced by down-regulating eIF1A or eIF2γ in CySCs.

CONCLUSIONS

These findings demonstrated that CySC lineage eIF5, together with eIF1A or eIF2γ, mediates soma-germline communications for the stem cell niche homeostasis in Drosophila testes, providing new insights for the prevention of TGCTs.

Deciphering the Rules of Ribosome Binding Site Differentiation in Context Dependence

The ribosome binding site (RBS) is a crucial element regulating translation. However, the activity of RBS is poorly predictable, because it is strongly affected by the local possible secondary structure, that is, context dependence. By the Flowseq technique, over 20 000 RBS variants were sorted and sequenced, and the translation of multiple genes under the same RBS was quantitatively characterized to evaluate the context dependence of each RBS variant in E. coli. Two regions, (-7 to -2) and (-17 to -12), of RBS were predicted with a higher possibility to pair with each other to slow down the translation initiation. Associations between phenotypes and the intrinsic factors suspected to affect translation efficiency and context dependence of the RBS, including nucleotide bias at each position, free energy, and conservation, were disentangled. The results showed that translation efficiency was influenced more significantly by conservation of the SD region (-16 to -8), while an AC-rich spacer region (-7 to -1) was associated with low context dependence. We confirmed these characteristics using a series of synthesized RBSs. The average correlation between multiple reporters was significantly higher for RBSs with an AC-rich spacer (0.714) compared with a GU-rich spacer (0.286). Overall, we proposed general design criteria to improve programmability and minimize context dependence of RBS. The characteristics unraveled here can be adapted to other bacteria for fine-tuning target-gene expression.

iCodon customizes gene expression based on the codon composition

Messenger RNA (mRNA) stability substantially impacts steady-state gene expression levels in a cell. mRNA stability is strongly affected by codon composition in a translation-dependent manner across species, through a mechanism termed codon optimality. We have developed iCodon (www.iCodon.org), an algorithm for customizing mRNA expression through the introduction of synonymous codon substitutions into the coding sequence. iCodon is optimized for four vertebrate transcriptomes: mouse, human, frog, and fish. Users can predict the mRNA stability of any coding sequence based on its codon composition and subsequently generate more stable (optimized) or unstable (deoptimized) variants encoding for the same protein. Further, we show that codon optimality predictions correlate with both mRNA stability using a massive reporter library and expression levels using fluorescent reporters and analysis of endogenous gene expression in zebrafish embryos and/or human cells. Therefore, iCodon will benefit basic biological research, as well as a wide range of applications for biotechnology and biomedicine.

The Ramp Atlas: facilitating tissue and cell-specific ramp sequence analyses through an intuitive web interface

Ramp sequences occur when the average translational efficiency of codons near the 5′ end of highly expressed genes is significantly lower than the rest of the gene sequence, which counterintuitively increases translational efficiency by decreasing downstream ribosomal collisions. Here, we show that the relative codon adaptiveness within different tissues changes the existence of a ramp sequence without altering the underlying genetic code. We present the first comprehensive analysis of tissue and cell type-specific ramp sequences and report 3108 genes with ramp sequences that change between tissues and cell types, which corresponds with increased gene expression within those tissues and cells. The Ramp Atlas (https://ramps.byu.edu/) allows researchers to query precomputed ramp sequences in 18 388 genes across 62 tissues and 66 cell types and calculate tissue-specific ramp sequences from user-uploaded FASTA files through an intuitive web interface. We used The Ramp Atlas to identify seven SARS-CoV-2 genes and seven human SARS-CoV-2 entry factor genes with tissue-specific ramp sequences that may help explain viral proliferation within those tissues. We anticipate that The Ramp Atlas will facilitate personalized and creative tissue-specific ramp sequence analyses for both human and viral genes that will increase our ability to utilize this often-overlooked regulatory region.

Oxygen level regulates N-terminal translation elongation of selected proteins through deoxyhypusine hydroxylation

Hypusine is a post-translational modification on eukaryotic translation initiation factor 5A (eIF5A). The last step of hypusine biosynthesis, deoxyhypusine hydroxylation, is an oxygen-dependent reaction. Here we show that deletion of the deoxyhypusine hydroxylase Lia1 compromises yeast respiration through translation downregulation of selected proteins in the respiration pathway. The translation suppression, because of the lack of deoxyhypusine hydroxylation, mainly affects translation of the N termini of the proteins, independent of the presence of proline residues but likely dependent on the interaction between the N-terminal nascent peptide and the ribosomal peptide exit tunnel. Proteomics and biochemical studies reveal that Lia1 deletion decreases N-terminal translation of proteins involved in mitochondrial respiration, oxidative stress response, and protein folding. Our work uncovers functions of the hypusine modification by considering the substrate requirement of the post-translational modification, highlights the unique challenges of translating the N termini of proteins, and reveals an oxygen-sensing mechanism in eukaryotic cells.

DeepTESR: A Deep Learning Framework to Predict the Degree of Translational Elongation Short Ramp for Gene Expression Control

Controlling translational elongation is essential for efficient protein synthesis. Ribosome profiling has revealed that the speed of ribosome movement is correlated with translational efficiency in the translational elongation ramp. In this work, we present a new deep learning model, called DeepTESR, to predict the degree of translational elongation short ramp (TESR) from mRNA sequence. The proposed deep learning model exhibited superior performance in predicting the TESR scores for 226 981 TESR sequences, resulting in the mean absolute error (MAE) of 0.285 and a coefficient of determination R² of 0.627, superior to the conventional machine learning models (e.g., MAE of 0.335 and R² of 0.571 for LightGBM). We experimentally validated that heterologous fluorescence expression of proteins with randomly selected TESR was moderately correlated with the predictions. Furthermore, a genome-wide analysis of TESR prediction in the 4305 coding sequences of Escherichia coli showed conserved TESRs over the clusters of orthologous groups. In this sense, DeepTESR can be used to predict the degree of TESR for gene expression control and to decipher the mechanism of translational control with ribosome profiling. DeepTESR is available at https://github.com/fmblab/DeepTESR.

A Review: PI3K/AKT/mTOR Signaling Pathway and Its Regulated Eukaryotic Translation Initiation Factors May Be a Potential Therapeutic Target in Esophageal Squamous Cell Carcinoma

Esophageal squamous cell carcinoma (ESCC) is a malignant tumor developing from the esophageal squamous epithelium, and is the most common histological subtype of esophageal cancer (EC). EC ranks 10th in morbidity and sixth in mortality worldwide. The morbidity and mortality rates in China are both higher than the world average. Current treatments of ESCC are surgical treatment, radiotherapy, and chemotherapy. Neoadjuvant chemoradiotherapy plus surgical resection is recommended for advanced patients. However, it does not work in the significant promotion of overall survival (OS) after such therapy. Research on targeted therapy in ESCC mainly focus on EGFR and PD-1, but neither of the targeted drugs can significantly improve the 3-year and 5-year survival rates of disease. Phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway is an important survival pathway in tumor cells, associated with its aggressive growth and malignant progression. Specifically, proliferation, apoptosis, autophagy, and so on. Related genetic alterations of this pathway have been investigated in ESCC, such as PI3K, AKT and mTOR-rpS6K. Therefore, the PI3K/AKT/mTOR pathway seems to have the capability to serve as research hotspot in the future. Currently, various inhibitors are being tested in cells, animals, and clinical trials, which targeting at different parts of this pathway. In this work, we reviewed the research progress on the PI3K/AKT/mTOR pathway how to influence biological behaviors in ESCC, and discussed the interaction between signals downstream of this pathway, especially eukaryotic translation initiation factors (eIFs) and the development and progression of ESCC, to provide reference for the identification of new therapeutic targets in ESCC.

Efficient Unnatural Protein Production by Pyrrolysyl-tRNA Synthetase With Genetically Fused Solubility Tags

Introducing non-canonical amino acids (ncAAs) by engineered orthogonal pairs of aminoacyl-tRNA synthetases and tRNAs has proven to be a highly useful tool for the expansion of the genetic code. Pyrrolysyl-tRNA synthetase (PylRS) from methanogenic archaeal and bacterial species is particularly attractive due to its natural orthogonal reactivity in bacterial and eukaryotic cells. However, the scope of such a reprogrammed translation is often limited, due to low yields of chemically modified target protein. This can be the result of substrate specificity engineering, which decreases the aminoacyl-tRNA synthetase stability and reduces the abundance of active enzyme. We show that the solubility and folding of these engineered enzymes can become a bottleneck for the production of ncAA-containing proteins in vivo. Solubility tags derived from various species provide a strategy to remedy this issue. We find the N-terminal fusion of the small metal binding protein from Nitrosomonas europaea to the PylRS sequence to improve enzyme solubility and to boost orthogonal translation efficiency. Our strategy enhances the production of site-specifically labelled proteins with a variety of engineered PylRS variants by 200–540%, and further allows triple labeling. Even the wild-type enzyme gains up to 245% efficiency for established ncAA substrates.

Enzymatic and structural characterization of HAD5, an essential phosphomannomutase of malaria-causing parasites

The malaria-causing parasite Plasmodium falciparum is responsible for over 200 million infections and 400,000 deaths per year. At multiple stages during its complex life cycle, P. falciparum expresses several essential proteins tethered to its surface by glycosylphosphatidylinositol (GPI) anchors, which are critical for biological processes such as parasite egress and reinvasion of host red blood cells. Targeting this pathway therapeutically has the potential to broadly impact parasite development across several life stages. Here, we characterize an upstream component of parasite GPI anchor biosynthesis, the putative phosphomannomutase (PMM) (EC 5.4.2.8), HAD5 (PF3D7_1017400). We confirmed the PMM and phosphoglucomutase activities of purified recombinant HAD5 by developing novel linked enzyme biochemical assays. By regulating the expression of HAD5 in transgenic parasites with a TetR-DOZI-inducible knockdown system, we demonstrated that HAD5 is required for malaria parasite egress and erythrocyte reinvasion, and we assessed the role of HAD5 in GPI anchor synthesis by autoradiography of radiolabeled glucosamine and thin layer chromatography. Finally, we determined the three-dimensional X-ray crystal structure of HAD5 and identified a substrate analog that specifically inhibits HAD5 compared to orthologous human PMMs in a time-dependent manner. These findings demonstrate that the GPI anchor biosynthesis pathway is exceptionally sensitive to inhibition in parasites and that HAD5 has potential as a specific, multistage antimalarial target.

Identification and Cross-Characterisation of Artificial Promoters and 5′ Untranslated Regions in Vibrio natriegens

Vibrio natriegens has recently gained attention as a novel fast-growing bacterium in synthetic biology applications. Currently, a limited set of genetic elements optimised for Escherichia coli are used in V. natriegens due to the lack of DNA parts characterised in this novel host. In this study, we report the identification and cross-characterisation of artificial promoters and 5′ untranslated regions (artificial regulatory sequence, ARES) that lead to production of fluorescent proteins with a wide-range of expression levels. We identify and cross-characterise 52 constructs in V. natriegens and E. coli. Furthermore, we report the DNA sequence and motif analysis of the ARESs using various algorithms. With this study, we expand the pool of characterised genetic DNA parts that can be used for different biotechnological applications using V. natriegens as a host microorganism.

Directed evolution of the rRNA methylating enzyme Cfr reveals molecular basis of antibiotic resistance

Alteration of antibiotic binding sites through modification of ribosomal RNA (rRNA) is a common form of resistance to ribosome-targeting antibiotics. The rRNA-modifying enzyme Cfr methylates an adenosine nucleotide within the peptidyl transferase center, resulting in the C-8 methylation of A2503 (m8A2503). Acquisition of cfr results in resistance to eight classes of ribosome-targeting antibiotics. Despite the prevalence of this resistance mechanism, it is poorly understood whether and how bacteria modulate Cfr methylation to adapt to antibiotic pressure. Moreover, direct evidence for how m8A2503 alters antibiotic binding sites within the ribosome is lacking. In this study, we performed directed evolution of Cfr under antibiotic selection to generate Cfr variants that confer increased resistance by enhancing methylation of A2503 in cells. Increased rRNA methylation is achieved by improved expression and stability of Cfr through transcriptional and post-transcriptional mechanisms, which may be exploited by pathogens under antibiotic stress as suggested by natural isolates. Using a variant that achieves near-stoichiometric methylation of rRNA, we determined a 2.2 Å cryo-electron microscopy structure of the Cfr-modified ribosome. Our structure reveals the molecular basis for broad resistance to antibiotics and will inform the design of new antibiotics that overcome resistance mediated by Cfr.

Acriflavine, a clinically approved drug, inhibits SARS-CoV-2 and other betacoronaviruses

The COVID-19 pandemic caused by SARS-CoV-2 has been socially and economically devastating. Despite an unprecedented research effort and available vaccines, effective therapeutics are still missing to limit severe disease and mortality. Using high-throughput screening, we identify acriflavine (ACF) as a potent papain-like protease (PL^pro) inhibitor. NMR titrations and a co-crystal structure confirm that acriflavine blocks the PL^pro catalytic pocket in an unexpected binding mode. We show that the drug inhibits viral replication at nanomolar concentration in cellular models, in vivo in mice and ex vivo in human airway epithelia, with broad range activity against SARS-CoV-2 and other betacoronaviruses. Considering that acriflavine is an inexpensive drug approved in some countries, it may be immediately tested in clinical trials and play an important role during the current pandemic and future outbreaks.

Overcoming the Solubility Problem in E. coli: Available Approaches for Recombinant Protein Production

Despite the importance of recombinant protein production in the academy and industrial fields, many issues concerning the expression of soluble and homogeneous products are still unsolved. Several strategies were developed to overcome these obstacles; however, at present, there is no magic bullet that can be applied for all cases. Indeed, several key expression parameters need to be evaluated for each protein. Among the different hosts for protein expression, Escherichia coli is by far the most widely used. In this chapter, we review many of the different tools employed to circumvent protein insolubility problems.