Causes and effects of N-terminal codon bias in bacterial genes

High-throughput optimization of peptide-linker for fusing function protein with GFP

Fusion proteins are pivotal in bioengineering, with applications in purification, delivery, and imaging. However, the development of specialized peptide linkers tailored for target fusion proteins remains an unmet challenge. In this study, we demonstrate the optimization of fusing a functional protein with green fluorescent protein (GFP) through the screening of peptide linker sequences. Using seamless cloning methodology, a nanobody protein was fused to the N-terminus of GFP via a randomized 18-amino acid peptide linker library. Initial screening of fusion protein clones was conducted on solid plates to identify those expressing robust GFP fluorescence. A total of 153 clones with unique linker sequences were identified using Sanger sequencing. A wide range of normalized fluorescence signals was observed, revealing significant variability in linker performance. Among the screened linkers, one exhibited high fluorescence activity, outperforming commonly used flexible and rigid linkers. This finding underscores the necessity of optimize linker sequences for specific fusion proteins. Furthermore, the results demonstrated that the screened linker is compatible with diverse N-terminal proteins while maintaining GFP functionality. Additionally, to investigate the effect of linker on the function of target protein, we determined the reverse transcription efficiency of the murine leukemia virus reverse transcriptase (MLV-RT) in the fusion proteins by a two-step RT-qPCR method. In conclusion, this study presents an efficient optimization of peptide linkers, offering a novel methodology for the engineering and application of specialized linkers for fusion proteins.

Translation regulation in Bacillus subtilis and its applications in heterologous protein expression: A review

Bacillus subtilis is widely used for industrial enzyme production due to its food safety and good capability of protein synthesis and secretion. However, the production of heterologous proteins is often inefficient, partly due to poor compatibility and versatility of genetic elements in B. subtilis. Recent study shows that transcription and translation is uncoupled in B. subtilis, which is quite different from general knowledge about the transcription-translation coupling mechanism in bacteria. The uncoupling mechanism in B. subtilis shows that the transcription rate is much faster than translation rate. Therefore, the translation regulation will play an important role in highly-effective synthesis of heterologous protein. To better understanding the different regulation strategies at the translation level in B. subtilis, this review will summarize the translation process in B. subtilis cell and its regulatory mechanisms as well as the differences in comparison to other bacteria. Besides, the genetic engineering strategies for engineering the translation regulatory elements are also summarized.

Functional synonymous mutations and their evolutionary consequences

Synonymous mutations are coding mutations that do not alter protein sequences. Commonly thought to have little to no functional consequence, synonymous mutations have been widely used in evolutionary analyses that require neutral markers, including those foundational for the neutral theory. However, recent studies suggest that synonymous mutations can influence nearly every step in the expression of genetic information and may often be strongly non-neutral. We review the extent and mechanisms of these phenotypic and fitness effects and discuss the implications of the functionality and non-neutrality of synonymous mutations for various analyses and conclusions pertinent to genetics, evolution, conservation and disease.

Expanding the genetic code: Strategies for noncanonical amino acid incorporation in biopolymer

Codon expansion has become a powerful tool for overcoming the limitations of the standard genetic code system, which restricts the building block of proteins to canonical amino acids. The incorporation of non-canonical amino acids (ncAAs) into proteins presents a significant opportunity to expand their functional diversity. The precise incorporation of ncAAs in vivo requires an orthogonal tRNA/aminoacyl-tRNA synthetase pair and a blank codon to assign them. Studies have focused on the biosynthesis of proteins with novel chemical properties alongside biotechnological advancements in codon expansion research. The three principal strategies for codon expansion are: stop codon utilization, quadruplet codon generation, and sense codon compression. Although using stop codons as blank codons remains an effective approach, the need for additional blank codons has expanded research into quadruplet codons and sense-codon compression. This review presents an overview of each strategy by integrating recent advances in research. We discuss the advantages and limitations of these strategies, as well as the challenges encountered. Subsequently, we propose potential approaches to enhance the efficiency and fidelity of ncAA incorporation. The insights presented in this review provide perspectives for future research and facilitate the advancement of codon expansion and its applications in biotechnology.

Energetic and structural control of polyspecificity in a multidrug transporter

Multidrug efflux pumps are dynamic molecular machines that drive antibiotic resistance by harnessing ion gradients to export chemically diverse substrates. Despite their clinical importance, the molecular principles underlying multidrug promiscuity and energy efficiency remain poorly understood. Using multiparametric deep mutational scanning across eight substrates and two energy conditions, we deconvolute the contributions of substrate recognition, energetic coupling, and protein stability, providing an integrated, high-resolution view of multidrug transport. We find that substrate specificity arises from a distributed network of residues extending beyond the binding site, with mutations that reshape binding, coupling, conformational flexibility, and membrane interactions. Further, we apply a pH-based selection scheme to measure the effect of mutation on pH-dependent transport efficiency. By integrating these data, we reveal a fundamental relationship between efficiency and promiscuity: highly efficient variants exhibit broad substrate profiles, while inefficient variants are narrower. These findings establish a direct link between energy coupling and polyspecificity, uncovering the biochemical logic underlying multidrug transport.

Comparative Analysis of Codon Optimization Tools: Advancing toward a Multi-Criteria Framework for Synthetic Gene Design

Codon optimization is an essential technique in synthetic biology and biopharmaceutical production, enhancing recombinant protein expression by fine-tuning genetic sequences to match the translational machinery and codon usage preferences of specific host organisms. This study presents a comprehensive comparative analysis of widely used codon optimization tools, focusing on their capacity to reflect host-specific codon biases, design principles, and parameters. Industrially relevant target proteins were evaluated in Escherichia coli, Saccharomyces cerevisiae, and CHO cells, uncovering significant variability in sequence design and clustering patterns across tools. Tools such as JCat, OPTIMIZER, ATGme, and GeneOptimizer demonstrated strong alignment with genome-wide and highly expressed gene-level codon usage, achieving high codon adaptation index (CAI) values and efficient codon-pair utilization. Conversely, tools like TISIGNER and IDT employed different optimization strategies that frequently produced divergent results. Other key parameters, including GC content, mRNA secondary structure stability (ΔG), and codon-pair bias (CPB), were analyzed to elucidate their influence on translational efficiency. While increased GC content enhanced mRNA stability in E. coli, A/T-rich codons in S. cerevisiae minimized secondary structure formation, and moderate GC content in CHO cells balanced mRNA stability and translation efficiency. Our findings highlight the limitations of single-metric approaches and advocate for a multi-criteria framework that integrates CAI, GC content, mRNA folding energy, and codon-pair considerations. This integrative strategy enables the design of tailored genetic sequences that meet host-specific requirements, advancing synthetic gene design for biotechnological innovation and precision biopharmaceutical applications.

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.

OPT: Codon optimize gene sequences for E. coli protein overexpression

The ability to overexpress proteins is valuable for biotechnology, but not all sequences are compatible with high yield. We previously analyzed the sequence features and mRNA folding stability of a large data set of 6,384 distinct gene constructs, and developed a model for protein yield. Our OPT.williams.edu server (1) predicts the probability an input sequence will produce protein at a high level when overexpressed in E. coli, and (2) returns optimized synonymous sequences designed to boost protein expression. Here we also present experimental evidence of the high yields of our OPT constructs for eight commercially produced proteins.

Predicting gene sequences with AI to study codon usage patterns

Selective pressure acts on the codon use, optimizing multiple, overlapping signals that are only partially understood. We trained AI models to predict codons given their amino acid sequence in the eukaryotes Saccharomyces cerevisiae and Schizosaccharomyces pombe and the bacteria Escherichia coli and Bacillus subtilis to study the extent to which we can learn patterns in naturally occurring codons to improve predictions. We trained our models on a subset of the proteins and evaluated their predictions on large, separate sets of proteins of varying lengths and expression levels. Our models significantly outperformed naïve frequency-based approaches, demonstrating that there are learnable dependencies in evolutionary-selected codon usage. The prediction accuracy advantage of our models is greater for highly expressed genes and is greater in bacteria than eukaryotes, supporting the hypothesis that there is a monotonic relationship between selective pressure for complex codon patterns and effective population size. In S. cerevisiae and bacteria, our models were more accurate for longer proteins, suggesting that the learned patterns may be related to cotranslational folding. Gene functionality and conservation were also important determinants that affect the performance of our models. Finally, we showed that using information encoded in homologous proteins has only a minor effect on prediction accuracy, perhaps due to complex codon-usage codes in genes undergoing rapid evolution. Our study employing contemporary AI methods offers a unique perspective and a deep-learning-based prediction tool for evolutionary-selected codons. We hope that these can be useful to optimize codon usage in endogenous and heterologous proteins.

Amino acid sequence encodes protein abundance shaped by protein stability at reduced synthesis cost

Understanding what drives protein abundance is essential to biology, medicine, and biotechnology. Driven by evolutionary selection, an amino acid sequence is tailored to meet the required abundance of a proteome, underscoring the intricate relationship between sequence and functional demand. Yet, the specific role of amino acid sequences in determining proteome abundance remains elusive. Here we show that the amino acid sequence alone encodes over half of protein abundance variation across all domains of life, ranging from bacteria to mouse and human. With an attempt to go beyond predictions, we trained a manageable-size Transformer model to interpret latent factors predictive of protein abundances. Intuitively, the model's attention focused on the protein's structural features linked to stability and metabolic costs related to protein synthesis. To probe these relationships, we introduce MGEM (Mutation Guided by an Embedded Manifold), a methodology for guiding protein abundance through sequence modifications. We find that mutations which increase predicted abundance have significantly altered protein polarity and hydrophobicity, underscoring a connection between protein structural features and abundance. Through molecular dynamics simulations we revealed that abundance-enhancing mutations possibly contribute to protein thermostability by increasing rigidity, which occurs at a lower synthesis cost.

Advances in recombinant protein production in microorganisms and functional peptide tags

Recombinant protein production in prokaryotic and eukaryotic cells is a fundamental technology for both research and industry. Achieving efficient protein synthesis is key to accelerating the discovery, characterization, and practical application of proteins. This review focuses on recent advances in recombinant protein production and strategies for more efficient protein production, especially using Escherichia coli and Saccharomyces cerevisiae. Additionally, this review summarizes the development of various functional peptide tags that can be employed for protein production, modification, and purification, including translation-enhancing peptide tags developed by our research group.

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.

Genetic Code Expansion History and Modern Innovations

The genetic code is the foundation for all life. With few exceptions, the translation of nucleic acid messages into proteins follows conserved rules, which are defined by codons that specify each of the 20 proteinogenic amino acids. For decades, leading research groups have developed a catalogue of innovative approaches to extend nature's amino acid repertoire to include one or more noncanonical building blocks in a single protein. In this review, we summarize advances in the history of in vitro and in vivo genetic code expansion, and highlight recent innovations that increase the scope of biochemically accessible monomers and codons. We further summarize state-of-the-art knowledge in engineered cellular translation, as well as alterations to regulatory mechanisms that improve overall genetic code expansion. Finally, we distill existing limitations of these technologies into must-have improvements for the next generation of technologies, and speculate on future strategies that may be capable of overcoming current gaps in knowledge.

Identification of the FGB gene polymorphism and analysis of its association with fat deposition traits in Hu sheep

As a crucial economic trait, fat deposition is directly related to carcass quality and feed efficiency in sheep. The purpose of this study was to investigate the polymorphisms of the FGB gene related to fat deposition and detect the expression features of the FGB gene in different adipose tissues of sheep by using Sanger sequencing, MassARRAY® SNP technique, and quantitative real-time PCR (qRT-PCR). Results showed that in the intron region of the FGB gene, a SNP g. 3378953 A > T has been identified, and significant association was found between perirenal fat weight, perirenal fat relative weight, mesenteric fat weight, and mesenteric fat relative weight (P < 0.05). Moreover, qRT-PCR analysis showed that FGB was expressed in all three adipose tissues, and FGB gene expression level in the AA genotype was significantly lower than that in the AT or TT genotypes (P < 0.05). Therefore, the FGB gene can be used as a candidate gene to reduce fat deposition in Hu sheep breeding, and the selection of the AA genotype in Hu sheep in production practice is more conducive to improving production efficiency.

Polymorphism in IGFALS gene and its association with scrotal circumference in Hu lambs

Scrotal circumference is an important reproductive index of breeding rams, which has a high genetic correlation with ejaculation volume and semen quality. In this study, the scrotal circumference of 1353 male Hu sheep at different stages of development was measured and descriptive statistical analysis was performed. The results showed that the coefficient of variation of scrotal circumference at each stage was greater than 10%, and its heritability were moderately to high, ranging from 0.318 to 0.719. We used PCR amplification and Sanger sequencing to scan the polymorphisms of the IGFALS gene, and performed association analysis with the circumference of the scrotum at different stages. We identified a synonymous mutation g.918 G > C in exon 1 of the IGFALS gene, and this mutation was significantly associated with scrotal circumference at 100, 120, 140, 160 and 180 days (p < 0.05). Therefore, IGFALS gene polymorphism can be used as a molecular marker affecting scrotal circumference of Hu sheep, which can provide a reference for future molecular marker-assisted selection of scrotal circumference in sheep.

Immobilized high-performance heparin lyase III for efficient preparation of low molecular weight heparin

Heparin lyase III has garnered widespread attention due to its high specificity and minimal loss of anticoagulant activity during the preparation of low molecular weight heparin (LMWH), a crucial anticoagulant drug in clinical practice. However, low expression levels and complex preparation processes limit its practical application. To address these challenges, high-performance Bacteroides thetaiotaomicron heparin lyase III (Bhep III) variants were engineered and immobilized for LMWH preparation. First, we enhanced enzyme expression by adding a solubility-enhancing tag and optimizing the N-terminal coding sequence, which resulted in a Bhep III activity level of 2.9 × 103 U/L with 8-fold increase. After evolution guided the design of rational mutations, the variant Bhep III K85A/Q95F/S471T generated higher activity (5.4 × 104 U/L in 5-L fermenter), which is, to our knowledge, the highest reported to date in the literature, being 1.7-fold that of the wild type and demonstrating 2-fold increase of the thermal stability. By screening and optimizing the C-terminal self-assembling tag, we successfully immobilized Bhep III, further increasing its thermal stability by 12-fold, and allowing for the multi-batch preparation of LMWH with simple centrifugation. The immobilized heparin lyase III demonstrated sufficient reusability in enzymatic reactions, facilitating efficient industrial-scale production of LMWH.

Strategies to overcome the challenges of low or no expression of heterologous proteins in Escherichia coli

Protein expression is a critical process in diverse biological systems. For Escherichia coli, a widely employed microbial host in industrial catalysis and healthcare, researchers often face significant challenges in constructing recombinant expression systems. To maximize the potential of E. coli expression systems, it is essential to address problems regarding the low or absent production of certain target proteins. This article presents viable solutions to the main factors posing challenges to heterologous protein expression in E. coli, which includes protein toxicity, the intrinsic influence of gene sequences, and mRNA structure. These strategies include specialized approaches for managing toxic protein expression, addressing issues related to mRNA structure and codon bias, advanced codon optimization methodologies that consider multiple factors, and emerging optimization techniques facilitated by big data and machine learning.

Identification of RNA structures and their roles in RNA functions

The development of high-throughput RNA structure profiling methods in the past decade has greatly facilitated our ability to map and characterize different aspects of RNA structures transcriptome-wide in cell populations, single cells and single molecules. The resulting high-resolution data have provided insights into the static and dynamic nature of RNA structures, revealing their complexity as they perform their respective functions in the cell. In this Review, we discuss recent technical advances in the determination of RNA structures, and the roles of RNA structures in RNA biogenesis and functions, including in transcription, processing, translation, degradation, localization and RNA structure-dependent condensates. We also discuss the current understanding of how RNA structures could guide drug design for treating genetic diseases and battling pathogenic viruses, and highlight existing challenges and future directions in RNA structure research.

Integrating Deep Learning and Synthetic Biology: A Co-Design Approach for Enhancing Gene Expression via N-Terminal Coding Sequences

N-terminal coding sequence (NCS) influences gene expression by impacting the translation initiation rate. The NCS optimization problem is to find an NCS that maximizes gene expression. The problem is important in genetic engineering. However, current methods for NCS optimization such as rational design and statistics-guided approaches are labor-intensive yield only relatively small improvements. This paper introduces a deep learning/synthetic biology codesigned few-shot training workflow for NCS optimization. Our method utilizes k-nearest encoding followed by word2vec to encode the NCS, then performs feature extraction using attention mechanisms, before constructing a time-series network for predicting gene expression intensity, and finally a direct search algorithm identifies the optimal NCS with limited training data. We took green fluorescent protein (GFP) expressed by Bacillus subtilis as a reporting protein of NCSs, and employed the fluorescence enhancement factor as the metric of NCS optimization. Within just six iterative experiments, our model generated an NCS (MLD62) that increased average GFP expression by 5.41-fold, outperforming the state-of-the-art NCS designs. Extending our findings beyond GFP, we showed that our engineered NCS (MLD62) can effectively boost the production of N-acetylneuraminic acid by enhancing the expression of the crucial rate-limiting GNA1 gene, demonstrating its practical utility. We have open-sourced our NCS expression database and experimental procedures for public use.

Diverse intrinsic properties shape transcript stability and stabilization in Mycolicibacterium smegmatis

Mycobacteria regulate transcript degradation to facilitate adaptation to environmental stress. However, the mechanisms underlying this regulation are unknown. Here we sought to gain understanding of the mechanisms controlling mRNA stability by investigating the transcript properties associated with variance in transcript stability and stress-induced transcript stabilization. We measured mRNA half-lives transcriptome-wide in Mycolicibacterium smegmatis in log phase growth and hypoxia-induced growth arrest. The transcriptome was globally stabilized in response to hypoxia, but transcripts of essential genes were generally stabilized more than those of non-essential genes. We then developed machine learning models that enabled us to identify the non-linear collective effect of a compendium of transcript properties on transcript stability and stabilization. We identified properties that were more predictive of half-life in log phase as well as properties that were more predictive in hypoxia, and many of these varied between leadered and leaderless transcripts. In summary, we found that transcript properties are differentially associated with transcript stability depending on both the transcript type and the growth condition. Our results reveal the complex interplay between transcript features and microenvironment that shapes transcript stability in mycobacteria.

Transfer learning for cross-context prediction of protein expression from 5'UTR sequence

Model-guided DNA sequence design can accelerate the reprogramming of living cells. It allows us to engineer more complex biological systems by removing the need to physically assemble and test each potential design. While mechanistic models of gene expression have seen some success in supporting this goal, data-centric, deep learning-based approaches often provide more accurate predictions. This accuracy, however, comes at a cost - a lack of generalization across genetic and experimental contexts that has limited their wider use outside the context in which they were trained. Here, we address this issue by demonstrating how a simple transfer learning procedure can effectively tune a pre-trained deep learning model to predict protein translation rate from 5' untranslated region (5'UTR) sequence for diverse contexts in Escherichia coli using a small number of new measurements. This allows for important model features learnt from expensive massively parallel reporter assays to be easily transferred to new settings. By releasing our trained deep learning model and complementary calibration procedure, this study acts as a starting point for continually refined model-based sequence design that builds on previous knowledge and future experimental efforts.

Preparation of reductases for multicomponent oxygenases

Oxygenases catalyze crucial reactions throughout all domains of life, cleaving molecular oxygen (O2) and inserting one or two of its atoms into organic substrates. Many oxygenases, including those in the cytochrome P450 (P450) and Rieske oxygenase enzyme families, function as multicomponent systems, which require one or more redox partners to transfer electrons to the catalytic center. As the identity of the reductase can change the reactivity of the oxygenase, characterization of the latter with its cognate redox partners is critical. However, the isolation of the native redox partner or partners is often challenging. Here, we report the preparation and characterization of PbdB, the native reductase partner of PbdA, a bacterial P450 enzyme that catalyzes the O-demethylation of para-methoxylated benzoates. Through production in a rhodoccocal host, codon optimization, and anaerobic purification, this procedure overcomes conventional challenges in redox partner production and allows for robust oxygenase characterization with its native redox partner. Key lessons learned here, including the value of production in a related host and rare codon effects are applicable to a broad range of Fe-dependent oxygenases and their components.

Selection on synonymous sites: the unwanted transcript hypothesis

Although translational selection to favour codons that match the most abundant tRNAs is not readily observed in humans, there is nonetheless selection in humans on synonymous mutations. We hypothesize that much of this synonymous site selection can be explained in terms of protection against unwanted RNAs - spurious transcripts, mis-spliced forms or RNAs derived from transposable elements or viruses. We propose not only that selection on synonymous sites functions to reduce the rate of creation of unwanted transcripts (for example, through selection on exonic splice enhancers and cryptic splice sites) but also that high-GC content (but low-CpG content), together with intron presence and position, is both particular to functional native mRNAs and used to recognize transcripts as native. In support of this hypothesis, transcription, nuclear export, liquid phase condensation and RNA degradation have all recently been shown to promote GC-rich transcripts and suppress AU/CpG-rich ones. With such 'traps' being set against AU/CpG-rich transcripts, the codon usage of native genes has, in turn, evolved to avoid such suppression. That parallel filters against AU/CpG-rich transcripts also affect the endosomal import of RNAs further supports the unwanted transcript hypothesis of synonymous site selection and explains the similar design rules that have enabled the successful use of transgenes and RNA vaccines.

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.

A new look at the fluorescent protein-based approach for identifying optimal coding sequence for recombinant protein expression in E. coli

Due to the degeneracy of the genetic code, most amino acids are encoded by several codons. The choice among synonymous codons at the N-terminus of genes has a profound effect on protein expression in Escherichia coli. This is often explained by the different contributions of synonymous codons to mRNA secondary structure formation. Strong secondary structures at the 5'-end of mRNA interfere with ribosome binding and affect the process of translation initiation. In silico optimization of the gene 5'-end can significantly increase the level of protein expression; however, this method is not always effective due to the uncertainty of the exact mechanism by which synonymous substitutions affect expression; thus, it may produce nonoptimal variants as well as miss some of the best producers. In this paper, an alternative approach is proposed based on screening a partially randomized library of expression constructs comprising hundreds of selected synonymous variants. The effect of such substitutions was evaluated using the gene of interest fused to the reporter gene of the fluorescent protein with subsequent screening for the most promising candidates according to the reporter's signal intensity. The power of the approach is demonstrated by a significant increase in the prokaryotic expression of three proteins: canine cystatin C, human BCL2-associated athanogene 3 and human cardiac troponin I. This simple approach was suggested which may provide an efficient, easy, and inexpensive optimization method for poorly expressed proteins in bacteria.

Modifications of the 5' region of the CASPONTM tag's mRNA further enhance soluble recombinant protein production in Escherichia coli

BACKGROUND

Escherichia coli is one of the most commonly used host organisms for the production of biopharmaceuticals, as it allows for cost-efficient and fast recombinant protein expression. However, challenging proteins are often produced with low titres or as inclusion bodies, and the manufacturing process needs to be developed individually for each protein. Recently, we developed the CASPONTM technology, a generic fusion tag-based platform process for high-titer soluble expression including a standardized downstream processing and highly specific enzymatic cleavage of the fusion tag. To assess potential strategies for further improvement of the N-terminally fused CASPONTM tag, we modified the 5'UTR and 5' region of the tag-coding mRNA to optimize the ribosome-mRNA interactions.

RESULTS

In the present work, we found that by modifying the 5'UTR sequence of a pET30acer plasmid-based system, expression of the fusion protein CASPONTM-tumour necrosis factor α was altered in laboratory-scale carbon-limited fed-batch cultivations, but no significant increase in expression titre was achieved. Translation efficiency was highest for a construct carrying an expression enhancer element and additionally possessing a very favourable interaction energy between ribosome and mRNA (∆Gtotal). However, a construct with comparatively low transcriptional efficiency, which lacked the expression enhancer sequence and carried the most favourable ∆Gtotal tested, led to the highest recombinant protein formation alongside the reference pET30a construct. Furthermore, we found, that by introducing synonymous mutations within the nucleotide sequence of the T7AC element of the CASPONTM tag, utilizing a combination of rare and non-rare codons, the free folding energy of the nucleotides at the 5' end (-4 to + 37) of the transcript encoding the CASPONTM tag increased by 6 kcal/mol. Surprisingly, this new T7ACrare variant led to improved recombinant protein titres by 1.3-fold up to 5.3-fold, shown with three industry-relevant proteins in lab-scale carbon limited fed-batch fermentations under industrially relevant conditions.

CONCLUSIONS

This study reveals some of the complex interdependencies between the ribosome and mRNA that govern recombinant protein expression. By modifying the 5'UTR to obtain an optimized interaction energy between the mRNA and the ribosome (ΔGtotal), transcript levels were changed, highlighting the different translation efficiencies of individual transcripts. It was shown that the highest recombinant titre was not obtained by the construct with the most efficient translation but by a construct with a generally high transcript amount coupled with a favourable ΔGtotal. Furthermore, an unexpectedly high potential to enhance expression by introducing silent mutations including multiple rare codons into the 5'end of the CAPONTM tag's mRNA was identified. Although the titres of the fusion proteins were dramatically increased, no formation of inclusion bodies or negative impact on cell growth was observed. We hypothesize that the drastic increase in titre is most likely caused by better ribosomal binding site accessibility. Our study, which demonstrates the influence of changes in ribosome-mRNA interactions on protein expression under industrially relevant production conditions, opens the door to the applicability of the new T7ACrare tag in biopharmaceutical industry using the CASPONTM platform process.

Essential factors, advanced strategies, challenges, and approaches involved for efficient expression of recombinant proteins in Escherichia coli

Producing recombinant proteins is a major accomplishment of biotechnology in the past century. Heterologous hosts, either eukaryotic or prokaryotic, are used for the production of these proteins. The utilization of microbial host systems continues to dominate as the most efficient and affordable method for biotherapeutics and food industry productions. Hence, it is crucial to analyze the limitations and advantages of microbial hosts to enhance the efficient production of recombinant proteins on a large scale. E. coli is widely used as a host for the production of recombinant proteins. Researchers have identified certain obstacles with this host, and given the growing demand for recombinant protein production, there is an immediate requirement to enhance this host. The following review discusses the elements contributing to the manifestation of recombinant protein. Subsequently, it sheds light on innovative approaches aimed at improving the expression of recombinant protein. Lastly, it delves into the obstacles and optimization methods associated with translation, mentioning both cis-optimization and trans-optimization, producing soluble recombinant protein, and engineering the metal ion transportation. In this context, a comprehensive description of the distinct features will be provided, and this knowledge could potentially enhance the expression of recombinant proteins in E. coli.

Polymorphisms of PLIN1 and MOGAT1 genes and their association with feed efficiency in Hu sheep

Feed cost accounts for a high proportion of sheep production, and improving sheep's utilization of feed will reduce production costs and improve economic benefits. The purpose of this study was to investigate the expression characteristics of PLIN1 and MOGAT1 genes and the relationship between their polymorphisms and feed efficiency traits in Hu sheep, and to find molecular Genetic marker that can be used in breeding. The expression levels of PLIN1 and MOGAT1 genes in various tissues were determined using quantitative real-time PCR (qRT-PCR). The results showed that PLIN1 and MOGAT1 genes were widely expressed in heart, liver, spleen, lungs, kidneys, rumen, duodenum, muscle, lymph, and tail fat. The PLIN1 gene had the highest expression level in in the tail fat compared to the other nine tissues. The expression levels of MOGAT1 gene in liver, tail fat, lung and heart was significantly higher than in kidney, muscle and lymph. The expression level of MOGAT1 was lowest in muscle compared to the other tissues (heart, liver, spleen, lung, rumen and tail fat). We recorded the body weight (BW80 and BW180) and feed intake (FI) information of 985 male Hu sheep at 80 and 180 days of age, and calculated the daily average feed intake (ADFI), average daily gain (ADG), and feed conversion rate (FCR) from 80 to 180 days of age. Two intronic mutations, g.18517910 A > G and g.224856118 G > C, were identified in PLIN1 and MOGAT1 genes by PCR amplification and Sanger sequencing. MassARRAY ® SNP detection technology was used to genotype the DNA of 985 Hu sheep and analyze its association with feed efficiency traits. The results showed that the SNP g.18517910 A > G was significantly associated with BW80, BW180, FI, ADFI and FCR (P < 0.05), while SNP g.2248561118 G > C was significantly associated with FCR (P < 0.05). Meanwhile, significant differences were also observed in different combinations of genotypes (P < 0.05). Therefore, these two polymorphic loci can serve as candidate molecular markers for improving feed utilization efficiency in Hu sheep.

Specific codons control cellular resources and fitness

As cellular engineering progresses from simply overexpressing proteins to imparting complex phenotypes through multigene expression, judicious appropriation of cellular resources is essential. Since codon use is degenerate and biased, codons may control cellular resources at a translational level. We investigate how partitioning transfer RNA (tRNA) resources by incorporating dissimilar codon usage can drastically alter interdependence of expression level and burden on the host. By isolating the effect of individual codons' use during translation elongation while eliminating confounding factors, we show that codon choice can trans-regulate fitness of the host and expression of other heterologous or native genes. We correlate specific codon usage patterns with host fitness and derive a coding scheme for multigene expression called the Codon Health Index (CHI, χ). This empirically derived coding scheme (χ) enables the design of multigene expression systems that avoid catastrophic cellular burden and is robust across several proteins and conditions.

Interaction with a phage gene underlie costs of a β-lactamase

The fitness cost of an antibiotic resistance gene (ARG) can differ across host strains, creating refuges that allow the maintenance of an ARG in the absence of direct selection for its resistance phenotype. Despite the importance of such ARG-host interactions for predicting ARG dynamics, the basis of ARG fitness costs and their variability between hosts are not well understood. We determined the genetic basis of a host-dependent cost of a β-lactamase, blaTEM-116*, that conferred a significant cost in one Escherichia coli strain but was close to neutral in 11 other Escherichia spp. strains. Selection of a blaTEM-116*-encoding plasmid in the strain in which it initially had a high cost resulted in rapid and parallel compensation for that cost through mutations in a P1-like phage gene, relAP1. When the wild-type relAP1 gene was added to a strain in which it was not present and in which blaTEM-116* was neutral, it caused the ARG to become costly. Thus, relAP1 is both necessary and sufficient to explain blaTEM-116* costs in at least some host backgrounds. To our knowledge, these findings represent the first demonstrated case of the cost of an ARG being influenced by a genetic interaction with a phage gene. The interaction between a phage gene and a plasmid-borne ARG highlights the complexity of selective forces determining the maintenance and spread of ARGs and, by extension, encoding phage and plasmids in natural bacterial communities.IMPORTANCEAntibiotic resistance genes (ARGs) play a major role in the increasing problem of antibiotic resistance in clinically relevant bacteria. Selection of these genes occurs in the presence of antibiotics, but their eventual success also depends on the sometimes substantial costs they impose on host bacteria in antibiotic-free environments. We evolved an ARG that confers resistance to penicillin-type antibiotics in one host in which it did confer a cost and in one host in which it did not. We found that costs were rapidly and consistently reduced through parallel genetic changes in a gene encoded by a phage that was infecting the costly host. The unmutated version of this gene was sufficient to cause the ARG to confer a cost in a host in which it was originally neutral, demonstrating an antagonism between the two genetic elements and underlining the range and complexity of pressures determining ARG dynamics in natural populations.

Synonymous edits in the Escherichia coli genome have substantial and condition-dependent effects on fitness

CRISPR-Cas-based genome editing is widely used in bacteria at scales ranging from construction of individual mutants to massively parallel libraries. This procedure relies on guide RNA-directed cleavage of the genome followed by repair with a template that introduces a desired mutation along with synonymous "immunizing" mutations to prevent re-cleavage of the genome after editing. Because the immunizing mutations do not change the protein sequence, they are often assumed to be neutral. However, synonymous mutations can change mRNA structures in ways that alter levels of the encoded proteins. We have tested the assumption that immunizing mutations are neutral by constructing a library of over 50,000 edits that consist of only synonymous mutations in Escherichia coli. Thousands of edits had substantial effects on fitness during growth of E. coli on acetate, a poor carbon source that is toxic at high concentrations. The percentage of high-impact edits varied considerably between genes and at different positions within genes. We reconstructed clones with high-impact edits and found that 69% indeed had significant effects on growth in acetate. Interestingly, fewer edits affected fitness during growth in glucose, a preferred carbon source, suggesting that changes in protein expression caused by synonymous mutations may be most important when an organism encounters challenging conditions. Finally, we showed that synonymous edits can have widespread effects; a synonymous edit at the 5' end of ptsI altered expression of hundreds of genes. Our results suggest that the synonymous immunizing edits introduced during CRISPR-Cas-based genome editing should not be assumed to be innocuous.

A smart RBS library and its prediction model for robust and accurate fine-tuning of gene expression in Bacillus species

Bacillus species, such as Bacillus subtilis and Bacillus licheniformis, are important industrial bacteria. However, there is a lack of standardized and predictable genetic tools for convenient and reproducible assembly of genetic modules in Bacillus species to realize their full potential. In this study, we constructed a Ribosome Binding Site (RBS) library in B. licheniformis, which provides incremental regulation of expression levels over a 104-fold range. Additionally, we developed a model to quantify the resulting translation rates. We successfully demonstrated the robust expression of various target genes using the RBS library and showed that the model accurately predicts the translation rates of arbitrary coding genes. Importantly, we also extended the use of the RBS library and prediction model to B. subtilis, B. thuringiensis, and B. amyloliquefacie. The versatility of the RBS library and its prediction model enables quantification of biological behavior, facilitating reliable forward engineering of gene expression.

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.

Establishing chromosomal design-build-test-learn through a synthetic chromosome and its combinatorial reconfiguration

Chromosome-level design-build-test-learn cycles (chrDBTLs) allow systematic combinatorial reconfiguration of chromosomes with ease. Here, we established chrDBTL with a redesigned synthetic Saccharomyces cerevisiae chromosome XV, synXV. We designed and built synXV to harbor strategically inserted features, modified elements, and synonymously recoded genes throughout the chromosome. Based on the recoded chromosome, we developed a method to enable chrDBTL: CRISPR-Cas9-mediated mitotic recombination with endoreduplication (CRIMiRE). CRIMiRE allowed the creation of customized wild-type/synthetic combinations, accelerating genotype-phenotype mapping and synthetic chromosome redesign. We also leveraged synXV as a "build-to-learn" model organism for translation studies by ribosome profiling. We conducted a locus-to-locus comparison of ribosome occupancy between synXV and the wild-type chromosome, providing insight into the effects of codon changes and redesigned features on translation dynamics in vivo. Overall, we established synXV as a versatile reconfigurable system that advances chrDBTL for understanding biological mechanisms and engineering strains.

Genes for highly abundant proteins in Escherichia coli avoid 5' codons that promote ribosomal initiation

In many species highly expressed genes (HEGs) over-employ the synonymous codons that match the more abundant iso-acceptor tRNAs. Bacterial transgene codon randomization experiments report, however, that enrichment with such "translationally optimal" codons has little to no effect on the resultant protein level. By contrast, consistent with the view that ribosomal initiation is rate limiting, synonymous codon usage following the 5' ATG greatly influences protein levels, at least in part by modifying RNA stability. For the design of bacterial transgenes, for simple codon based in silico inference of protein levels and for understanding selection on synonymous mutations, it would be valuable to computationally determine initiation optimality (IO) scores for codons for any given species. One attractive approach is to characterize the 5' codon enrichment of HEGs compared with the most lowly expressed genes, just as translational optimality scores of codons have been similarly defined employing the full gene body. Here we determine the viability of this approach employing a unique opportunity: for Escherichia coli there is both the most extensive protein abundance data for native genes and a unique large-scale transgene codon randomization experiment enabling objective definition of the 5' codons that cause, rather than just correlate with, high protein abundance (that we equate with initiation optimality, broadly defined). Surprisingly, the 5' ends of native genes that specify highly abundant proteins avoid such initiation optimal codons. We find that this is probably owing to conflicting selection pressures particular to native HEGs, including selection favouring low initiation rates, this potentially enabling high efficiency of ribosomal usage and low noise. While the classical HEG enrichment approach does not work, rendering simple prediction of native protein abundance from 5' codon content futile, we report evidence that initiation optimality scores derived from the transgene experiment may hold relevance for in silico transgene design for a broad spectrum of bacteria.

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.

gtAI: an improved species-specific tRNA adaptation index using the genetic algorithm

The tRNA adaptation index (tAI) is a translation efficiency metric that considers weighted values (S _ij values) for codon-tRNA wobble interaction efficiencies. The initial implementation of the tAI had significant flaws. For instance, generated S _ij weights were optimized based on gene expression in Saccharomyces cerevisiae, which is expected to vary among different species. Consequently, a species-specific approach (stAI) was developed to overcome those limitations. However, the stAI method employed a hill climbing algorithm to optimize the S _ij weights, which is not ideal for obtaining the best set of S _ij weights because it could struggle to find the global maximum given a complex search space, even after using different starting positions. In addition, it did not perform well in computing the tAI of fungal genomes in comparison with the original implementation. We developed a novel approach named genetic tAI (gtAI) implemented as a Python package (https://github.com/AliYoussef96/gtAI), which employs a genetic algorithm to obtain the best set of S _ij weights and follows a new codon usage-based workflow that better computes the tAI of genomes from the three domains of life. The gtAI has significantly improved the correlation with the codon adaptation index (CAI) and the prediction of protein abundance (empirical data) compared to the stAI.

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.

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 pthts 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.

Nascent MSKIK Peptide Cancels Ribosomal Stalling by Arrest Peptides in Escherichia coli

The insertion of the DNA sequence encoding SKIK peptide adjacent to the M start codon of a difficult-to-express protein enhances protein production in Escherichia coli. In this report, we reveal that the increased production of the SKIK-tagged protein is not due to codon usage of the SKIK sequence. Furthermore, we found that insertion of SKIK or MSKIK just before the SecM arrest peptide (FSTPVWISQAQGIRAGP), which causes ribosomal stalling on mRNA, greatly increased the production of the protein containing the SecM arrest peptide in the E. coli reconstituted cell-free protein synthesis system (PURE system). A similar translation enhancement phenomenon by MSKIK was observed for the CmlA leader peptide, a ribosome arrest peptide, whose arrest is induced by chloramphenicol. These results strongly suggest that the nascent MSKIK peptide prevents or releases ribosomal stalling immediately following its generation during the translation process, resulting in an increase of protein production.

Synonymous Codon Variant Analysis for Autophagic Genes Dysregulated in Neurodegeneration

Neurodegenerative disorders are often a culmination of the accumulation of abnormally folded proteins and defective organelles. Autophagy is a process of removing these defective proteins, organelles, and harmful substances from the body, and it works to maintain homeostasis. If autophagic removal of defective proteins has interfered, it affects neuronal health. Some of the autophagic genes are specifically found to be associated with neurodegenerative phenotypes. Non-functional, mutated, or gene copies having silent mutations, often termed synonymous variants, might explain this. However, these synonymous variant which codes for exactly similar proteins have different translation rates, stability, and gene expression profiling. Hence, it would be interesting to study the pattern of synonymous variant usage. In the study, synonymous variant usage in various transcripts of autophagic genes ATG5, ATG7, ATG8A, ATG16, and ATG17/FIP200 reported to cause neurodegeneration (if dysregulated) is studied. These genes were analyzed for their synonymous variant usage; nucleotide composition; any possible nucleotide skew in a gene; physical properties of autophagic protein including GRAVY and AROMA; hydropathicity; instability index; and frequency of acidic, basic, neutral amino acids; and gene expression level. The study will help understand various evolutionary forces acting on these genes and the possible augmentation of a gene if showing unusual behavior.

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.

Porcine IGF-1R synonymous mutations in the extracellular domain affect proliferation and differentiation of skeletal muscle cells

OBJECTIVE

Miniature pigs are considered ideal organ donors for xenotransplantation in humans, but the mechanism underlying their dwarfism remains to be elucidated. IGF-1R is a crucial factor in body size formation in mammals, including skeletal muscle formation and development. The extracellular domain (ECD) binds to the ligand, a phenomenon that results in the activation of downstream pathways.

METHODS

In this study, the coding sequences of two IGF-1R ECD haplotypes of the large Landrace (LP) pig and the small Bama Xiang (BM) pig were cloned into pcDNA3.1 vectors to generate pcDNA3.1-LP and pcDNA3.1-BM. The two recombinant vectors were then transfected into skeletal muscle cells.

RESULTS

IGF-1R transcript was found to be expressed at higher levels in the pcDNA3.1-LP group than in the pcDNA3.1-BM group. The IGF-1R ECD from LP promoted cell proliferation and CyclinD1 expression, and promoted the phosphorylation of protein kinase B (to yield p-AKT). Moreover, the IGF-1R ECD from LP increased cell differentiation and the expression of myogenic determination factor (MyoD).

CONCLUSION

Our data indicated that the IGF-1R ECD haplotypes between pig breeds with different body sizes affect IGF-1R expression, in turn affecting the proliferation and differentiation of skeletal muscle cells by activating downstream signalling pathways.

Initiation at AUGUG and GUGUG sequences can lead to translation of overlapping reading frames in E. coli

During initiation, the ribosome is tasked to efficiently recognize open reading frames (ORFs) for accurate and fast translation of mRNAs. A critical step is start codon recognition, which is modulated by initiation factors, mRNA structure, a Shine Dalgarno (SD) sequence and the start codon itself. Within the Escherichia coli genome, we identified more than 50 annotated initiation sites harboring AUGUG or GUGUG sequence motifs that provide two canonical start codons, AUG and GUG, in immediate proximity. As these sites may challenge start codon recognition, we studied if and how the ribosome is accurately guided to the designated ORF, with a special focus on the SD sequence as well as adenine at the fourth coding sequence position (A4). By in vitro and in vivo experiments, we characterized key requirements for unambiguous start codon recognition, but also discovered initiation sites that lead to the translation of both overlapping reading frames. Our findings corroborate the existence of an ambiguous translation initiation mechanism, implicating a multitude of so far unrecognized ORFs and translation products in bacteria.

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.

Autoinduction Expression Modules for Regulating Gene Expression in Bacillus subtilis

Although quorum sensing (QS) promoters that can autonomously activate gene expression have been identified and engineered in Bacillus subtilis, researchers focus on quantifying individual promoters while ignoring the interaction between other genetic regulatory elements. Here, we constructed the autoinduction expression modules consisting of promoters responsive to QS ComQXPA, ribosome binding sites (RBSs), and terminators. Using superfolder green fluorescent protein (sfGFP) as a reporter gene, three individual element libraries were generated from 945 promoters, 12,000 RBSs, and 425 terminators by random mutation, de novo design, and database mining strategies, respectively. Then, the efficiency of three libraries in regulating gene expression was further enhanced by engineering the core region of each optimal element. After hybridizing the element libraries, the generated expression modules exhibited a 627-fold range in regulating gene expression without significantly affecting the autoinduction initiation. Here, the hybrid modules with broad expression strength may benefit the application of QS-based autoinduction systems in B. subtilis.

Engineering medicinal plant-derived CYPs: a promising strategy for production of high-valued secondary metabolites

Cytochorme P450s (CYPs) play a critical role in the catalysis of secondary metabolite biosynthetic pathways. For their commercial use, various strategies for metabolic pathway engineering using CYP as a potential target have been explored. Plants produce a vast diversity of secondary metabolites which are being used to treat various ailments and diseases. Some of these metabolites are difficult to obtain in large quantities limiting their industrial use. Cytochrome P450 enzymes (CYPs) are important catalysts in the biosynthesis of highly valued secondary metabolites, and are found in all domains of life. With the development of high-throughput sequencing and high-resolution mass spectrometry, new biosynthetic pathways and associated CYPs are being identified. In this review, we present CYPs identified from medicinal plants as a potential game changer in the metabolic engineering of secondary metabolic pathways. We present the achievements made so far in enhancing the production of important bioactivities through pathway engineering, giving some popular examples. At last, current challenges and possible strategies to overcome the limitations associated with CYP engineering to enhance the biosynthesis of target secondary metabolites are also highlighted.

Computational Design of a Chimeric Vaccine against Plesiomonas shigelloides Using Pan-Genome and Reverse Vaccinology

The swift emergence of antibiotic resistance (AR) in bacterial pathogens to make themselves adaptable to changing environments has become an alarming health issue. To prevent AR infection, many ways can be accomplished such as by decreasing the misuse of antibiotics in human and animal medicine. Among these AR bacterial species, Plesiomonas shigelloides is one of the etiological agents of intestinal infection in humans. It is a gram-negative rod-shaped bacterium that is highly resistant to several classes of antibiotics, and no licensed vaccine against the aforementioned pathogen is available. Hence, substantial efforts are required to screen protective antigens from the pathogen whole genome that can be subjected easily to experimental evaluations. Here, we employed a reverse vaccinology (RV) approach to design a multi-antigenic epitopes based vaccine against P. shigelloides. The complete genomes of P. shigelloides were retrieved from the National Center for Biotechnological Information (NCBI) that on average consist of 5226 proteins. The complete proteomes were subjected to different subtractive proteomics filters, and in the results of that analysis, out of total proteins, 2399 were revealed as non-redundant and 2827 as redundant proteins. The non-redundant proteins were further checked for subcellular localization analysis, in which three were localized in the extracellular matrix, eight were outer membrane, and 13 were found in the periplasmic membrane. All surface localized proteins were found to be virulent. Out of a total of 24 virulent proteins, three proteins (flagellar hook protein (FlgE), hypothetical protein, and TonB-dependent hemoglobin/transferrin/lactoferrin family receptor protein) were considered as potential vaccine targets and subjected to epitopes prediction. The predicted epitopes were further examined for antigenicity, toxicity, and solubility. A total of 10 epitopes were selected (GFKESRAEF, VQVPTEAGQ, KINENGVVV, ENKALSQET, QGYASANDE, RLNPTDSRW, TLDYRLNPT, RVTKKQSDK, GEREGKNRP, RDKKTNQPL). The selected epitopes were linked with each other via specific GPGPG linkers in order to design a multi-epitopes vaccine construct, and linked with cholera toxin B subunit adjuvant to make the designed vaccine construct more efficient in terms of antigenicity. The 3D structure of the vaccine construct was modeled ab initio as no appropriate template was available. Furthermore, molecular docking was carried out to check the interaction affinity of the designed vaccine with major histocompatibility complex (MHC-)I (PDB ID: 1L1Y), MHC-II (1KG0), and toll-like receptor 4 ((TLR-4) (PDB: 4G8A). Molecular dynamic simulation was applied to evaluate the dynamic behavior of vaccine-receptor complexes. Lastly, the binding free energies of the vaccine with receptors were estimated by using MMPB/GBSA methods. All of the aforementioned analyses concluded that the designed vaccine molecule as a good candidate to be used in experimental studies to disclose its immune protective efficacy in animal models.