Coding-sequence determinants of gene expression in Escherichia coli

A statistical-physics approach for codon usage optimisation

The concept of "codon optimisation" involves adjusting the coding sequence of a target protein to account for the inherent codon preferences of a host species and maximise protein expression in that species. However, there is still a lack of consensus on the most effective approach to achieve optimal results. Existing methods typically depend on heuristic combinations of different variables, leaving the user with the final choice of the sequence hit. In this study, we propose a new statistical-physics model for codon optimisation. This model, called the Nearest-Neighbour interaction (NN) model, links the probability of any given codon sequence to the "interactions" between neighbouring codons. We used the model to design codon sequences for different proteins of interest, and we compared our sequences with the predictions of some commercial tools. In order to assess the importance of the pair interactions, we additionally compared the NN model with a simpler method (Ind) that disregards interactions. It was observed that the NN method yielded similar Codon Adaptation Index (CAI) values to those obtained by other commercial algorithms, despite the fact that CAI was not explicitly considered in the algorithm. By utilising both the NN and Ind methods to optimise the reporter protein luciferase, and then analysing the translation performance in human cell lines and in a mouse model, we found that the NN approach yielded the highest protein expression in vivo. Consequently, we propose that the NN model may prove advantageous in biotechnological applications, such as heterologous protein expression or mRNA-based therapies.

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.

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.

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

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

Functional characterization of 2,832 JAG1 variants supports reclassification for Alagille syndrome and improves guidance for clinical variant interpretation

Pathogenic variants in the JAG1 gene are a primary cause of the multi-system disorder Alagille syndrome. Although variant detection rates are high for this disease, there is uncertainty associated with the classification of missense variants that leads to reduced diagnostic yield. Consequently, up to 85% of reported JAG1 missense variants have uncertain or conflicting classifications. We generated a library of 2,832 JAG1 nucleotide variants within exons 1-7, a region with a high number of reported missense variants, and designed a high-throughput assay to measure JAG1 membrane expression, a requirement for normal function. After calibration using a set of 175 known or predicted pathogenic and benign variants included within the variant library, 486 variants were characterized as functionally abnormal (n = 277 abnormal and n = 209 likely abnormal), of which 439 (90.3%) were missense. We identified divergent membrane expression occurring at specific residues, indicating that loss of the wild-type residue itself does not drive pathogenicity, a finding supported by structural modeling data and with broad implications for clinical variant classification both for Alagille syndrome and globally across other disease genes. Of 144 uncertain variants reported in patients undergoing clinical or research testing, 27 had functionally abnormal membrane expression, and inclusion of our data resulted in the reclassification of 26 to likely pathogenic. Functional evidence augments the classification of genomic variants, reducing uncertainty and improving diagnostics. Inclusion of this repository of functional evidence during JAG1 variant reclassification will significantly affect resolution of variant pathogenicity, making a critical impact on the molecular diagnosis of Alagille syndrome.

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.

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

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

Escherichia coli as a versatile cell factory: Advances and challenges in recombinant protein production

E. coli plays a substantial role in recombinant protein production. Its importance increased with the discovery of recombinant DNA technology and the subsequent production of the first recombinant insulin in E. coli. E. coli is a widely used and cost-effective host to produce recombinant proteins. It is also noteworthy that a significant portion of the approved therapeutic proteins have been produced in this organism. Despite these advantages, it has some disadvantages, such as toxicity and lack of eukaryotic post-translational modifications that can lead to the production of misfolded, insoluble, or dysfunctional proteins. This study focused on the challenges and engineering approaches for improved expression and solubility in recombinant protein production in E. coli. In this context, solution strategies such as strain and vector selection, codon usage, mRNA stability, expression conditions, translocation to the periplasmic region and addition of fusion tags in E. coli were discussed.

Systems engineering Escherichia coli for efficient production p-coumaric acid from glucose

P-coumaric acid (p-CA), a pant metabolite with antioxidant and anti-inflammatory activity, is extensively utilized in biomedicine, food, and cosmetics industry. In this study, a synthetic pathway (PAL) for p-CA was designed, integrating three enzymes (AtPAL2, AtC4H, AtATR2) into a higher l-phenylalanine-producing strain Escherichia coli PHE05. However, the lower soluble expression and activity of AtC4H in the PAL pathway was a bottleneck for increasing p-CA titers. To overcome this limitation, the soluble expression of AtC4H was enhanced through N-terminal modifications. And an optimal mutant, AtC4HL373T/G211H, which exhibited a 4.3-fold higher kcat/Km value compared to the wild type, was developed. In addition, metabolic engineering strategies were employed to increase the intracellular NADPH pool. Overexpression of ppnk in engineered E. coli PHCA20 led to a 13.9-folds, 1.3-folds, and 29.1% in NADPH content, the NADPH/NADP+ ratio and p-CA titer, respectively. These optimizations significantly enhance p-CA production, in a 5-L fermenter using fed-batch fermentation, the p-CA titer, yield and productivity of engineered strain E. coli PHCA20 were 3.09 g/L, 20.01 mg/g glucose, and 49.05 mg/L/h, respectively. The results presented here provide a novel way to efficiently produce the plant metabolites using an industrial strain.

The Effects of Codon Usage on Protein Structure and Folding

The rate of protein synthesis is slower than many folding reactions and varies depending on the synonymous codons encoding the protein sequence. Synonymous codon substitutions thus have the potential to regulate cotranslational protein folding mechanisms, and a growing number of proteins have been identified with folding mechanisms sensitive to codon usage. Typically, these proteins have complex folding pathways and kinetically stable native structures. Kinetically stable proteins may fold only once over their lifetime, and thus, codon-mediated regulation of the pioneer round of protein folding can have a lasting impact. Supporting an important role for codon usage in folding, conserved patterns of codon usage appear in homologous gene families, hinting at selection. Despite these exciting developments, there remains few experimental methods capable of quantifying translation elongation rates and cotranslational folding mechanisms in the cell, which challenges the development of a predictive understanding of how biology uses codons to regulate protein folding.

Analysing the genetic code degeneracy: a consequence towards bacterial staining

As 20 naturally occurring amino acids are coded by 61 mRNA codons out of 64, it is obvious that 61→20 cannot have one-to-one mapping which generates the problem of codon degeneracy. Despite several efforts there is no specific outcome which can describe this well-known enigmatic degeneracy of the codon table. Since, every biological behaviour is regulated by protein which in turn consists of amino acids bearing the inherent characteristics of degeneracy among mRNA codons (Crick F.H.C. The Origin of the Genetic Code. J. Mol. Biol.1968; 38: 367-379), it is worthy to analyse the impact of such degeneracy on biological behaviours. Here, based on mathematical models using the concept of b-type of the nucleotide bases and hamming distances, an effort has been initiated to understand the impact of biasness of genetic code degeneracy on biological behaviours. The proposed models have been utilized to understand the characteristic features of bacterial genes of gram-positive and gram-negative bacteria. To the best of our knowledge, this is the first mathematical model to capture the effect of genetic code degeneracy, showing a paradigm towards understanding the behavioural difference between gram-positive and gram-negative bacteria, and thereby opening a new avenue for revealing differential biological properties.Communicated by Ramaswamy H. Sarma.

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.

An Integer Linear Programming Model to Optimize Coding DNA Sequences By Joint Control of Transcript Indicators

A Coding DNA Sequence (CDS) is a fraction of DNA whose nucleotides are grouped into consecutive triplets called codons, each one encoding an amino acid. Because most amino acids can be encoded by more than one codon, the same amino acid chain can be obtained by a very large number of different CDSs. These synonymous CDSs show different features that, also depending on the organism the transcript is expressed in, could affect translational efficiency and yield. The identification of optimal CDSs with respect to given transcript indicators is in general a challenging task, but it has been observed in recent literature that integer linear programming (ILP) can be a very flexible and efficient way to achieve it. In this article, we add evidence to this observation by proposing a new ILP model that simultaneously optimizes different well-grounded indicators. With this model, we efficiently find solutions that dominate those returned by six existing codon optimization heuristics.

Microdiversity of Salmonella Kentucky During Long-Term Colonization of a Dairy Herd

Salmonella enterica subsp. enterica serovar Kentucky was repeatedly isolated from a commercial dairy herd that was enrolled in a longitudinal study where feces of asymptomatic dairy cattle were sampled intensively over an 8-year period. The genomes of 5 Salmonella Kentucky isolates recovered from the farm 2 years before the onset of the long-term colonization event and 13 isolates collected during the period of endemicity were sequenced. A phylogenetic analysis inferred that the Salmonella Kentucky strains from the farm were distinct from poultry strains collected from the same region, and three subclades (K, A1, and A2) were identified among the farm isolates, each appearing at different times during the study. Based on the phylogenetic analysis, three separate lineages of highly similar Salmonella Kentucky were present in succession on the farm. Genomic heterogeneity between the clades helped identify regions, most notably transcriptional regulators, of the Salmonella Kentucky genome that may be involved in competition among highly similar strains. Notably, a region annotated as a hemolysin expression modulating protein (Hha) was identified in a putative plasmid region of strains that colonized a large portion of cows in the herd, suggesting that it may play a role in asymptomatic persistence within the bovine intestine. A cell culture assay of isolates from the three clades with bovine epithelial cells demonstrated a trend of decreased invasiveness of Salmonella Kentucky isolates over time, suggesting that clade-specific interactions with the animals on the farm may have played a role in the dynamics of strain succession. Results of this analysis further demonstrate an underappreciated level of genomic diversity within strains of the same Salmonella serovar, particularly those isolated during a long-term period of asymptomatic colonization within a single dairy herd.

Utilizing 5' UTR Engineering Enables Fine-Tuning of Multiple Genes within Operons to Balance Metabolic Flux in Bacillus subtilis

The application of synthetic biology tools to modulate gene expression to increase yield has been thoroughly demonstrated as an effective and convenient approach in industrial production. In this study, we employed a high-throughput screening strategy to identify a 5' UTR sequence from the genome of B. subtilis 168. This sequence resulted in a 5.8-fold increase in the expression level of EGFP. By utilizing the 5' UTR sequence to overexpress individual genes within the rib operon, it was determined that the genes ribD and ribAB serve as rate-limiting enzymes in the riboflavin synthesis pathway. Constructing a 5' UTR library to regulate EGFP expression resulted in a variation range in gene expression levels exceeding 100-fold. Employing the same 5' UTR library to regulate the expression of EGFP and mCherry within the operon led to a change in the expression ratio of these two genes by over 10,000-fold. So, employing a 5' UTR library to modulate the expression of the rib operon gene and construct a synthetic rib operon resulted in a 2.09-fold increase in riboflavin production. These results indicate that the 5' UTR sequence identified and characterized in this study can serve as a versatile synthetic biology toolkit for achieving complex metabolic network reconstruction. This toolkit can facilitate the fine-tuning of gene expression to produce target products.

Quantifying negative selection on synonymous variants

Widespread adoption of DNA sequencing has resulted in large numbers of genetic variants, whose contribution to disease is not easily determined. Although many types of variation are known to disrupt cellular processes in predictable ways, for some categories of variants, the effects may not be directly detectable. A particular example is synonymous variants, that is, those single-nucleotide variants that create a codon substitution, such that the produced amino acid sequence is unaffected. Contrary to the original theory suggesting that synonymous variants are benign, there is a growing volume of research showing that, despite their "silent" mechanism of action, some synonymous variation may be deleterious. Here, we studied the extent of the negative selective pressure acting on different classes of synonymous variants by analyzing the relative enrichment of synonymous singleton variants in the human exomes provided by gnomAD. Using a modification of the mutability-adjusted proportion of singletons (MAPS) metric as a measure of purifying selection, we found that some classes of synonymous variants are subject to stronger negative selection than others. For instance, variants that reduce codon optimality undergo stronger selection than optimality-increasing variants. Besides, selection affects synonymous variants implicated in splice-site-loss or splice-site-gain events. To understand what drives this negative selection, we tested a number of predictors in the aim to explain the variability in the selection scores. Our findings provide insights into the effects of synonymous variants at the population level, highlighting the specifics of the role that these variants play in health and disease.

Improvement of thermostability and catalytic efficiency of xylanase from Myceliophthora thermophilar by N-terminal and C-terminal truncation

Introduction

Extracting xylanase from thermophilic filamentous fungi is a feasible way to obtain xylanase with good thermal stability.

Methods

The transcriptomic data of Myceliophthora thermophilic destructive ATCC42464 were differentially expressed and enriched. By comparing the sequences of Mtxylan2 and more than 10 xylanases, the N-terminal and C-terminal of Mtxylan2 were truncated, and three mutants 28N, 28C and 28NC were constructed.

Results and discussion

GH11 xylan Mtxylan2 was identified by transcriptomic analysis, the specific enzyme activity of Mtxylan2 was 104.67 U/mg, and the optimal temperature was 65°C. Molecular modification of Mtxylan2 showed that the catalytic activity of the mutants was enhanced. Among them, the catalytic activity of 28C was increased by 9.3 times, the optimal temperature was increased by 5°C, and the residual enzyme activity remained above 80% after 30 min at 50-65°C, indicating that redundant C-terminal truncation can improve the thermal stability and catalytic performance of GH11 xylanase.

Differential Selection for Translation Efficiency Shapes Translation Machineries in Bacterial Species

Different bacterial species have dramatically different generation times, from 20-30 min in Escherichia coli to about two weeks in Mycobacterium leprae. The translation machinery in a cell needs to synthesize all proteins for a new cell in each generation. The three subprocesses of translation, i.e., initiation, elongation, and termination, are expected to be under stronger selection pressure to optimize in short-generation bacteria (SGB) such as Vibrio natriegens than in the long-generation Mycobacterium leprae. The initiation efficiency depends on the start codon decoded by the initiation tRNA, the optimal Shine-Dalgarno (SD) decoded by the anti-SD (aSD) sequence on small subunit rRNA, and the secondary structure that may embed the initiation signals and prevent them from being decoded. The elongation efficiency depends on the tRNA pool and codon usage. The termination efficiency in bacteria depends mainly on the nature of the stop codon and the nucleotide immediately downstream of the stop codon. By contrasting SGB with long-generation bacteria (LGB), we predict (1) SGB to have more ribosome RNA operons to produce ribosomes, and more tRNA genes for carrying amino acids to ribosomes, (2) SGB to have a higher percentage of genes using AUG as the start codon and UAA as the stop codon than LGB, (3) SGB to exhibit better codon and anticodon adaptation than LGB, and (4) SGB to have a weaker secondary structure near the translation initiation signals than LGB. These differences between SGB and LGB should be more pronounced in highly expressed genes than the rest of the genes. We present empirical evidence in support of these predictions.

Rational design of soluble expressed human aldehyde dehydrogenase 2 with high stability and activity in pepsin and trypsin

Acetaldehyde dehydrogenase 2 (ALDH2) is a crucial enzyme in alcohol metabolism, and oral administration of ALDH2 is a promising method for alcohol detoxification. However, recombinant ALDH2 is susceptible to hydrolysis by digestive enzymes in the gastrointestinal tract and is expressed as inactive inclusion bodies in E. coli. In this study, we performed three rounds of rational design to address these issues. Specifically, the surface digestive sites of pepsin and trypsin were replaced with other polar amino acids, while hydrophobic amino acids were incorporated to reshape the catalytic cavity of ALDH2. The resulting mutant DE2-852 exhibited a 45-fold increase in soluble expression levels, while its stability against trypsin and pepsin increased by eightfold and twofold, respectively. Its catalytic efficiency (kcat/Km) at pH 7.2 and 3.2 improved by more than four and five times, respectively, with increased Vmax and decreased Km values. The enhanced properties of DE2-852 were attributed to the D457Y mutation, which created a more compact protein structure and facilitated a faster collision between the substrate and catalytic residues. These results laid the foundation for the oral administration and mass preparation of highly active ALDH2 and offered insights into the oral application of other proteins.

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.

Identification and characterization of an ene-reductase from Corynebacterium casei

The asymmetric reduction of α, β-unsaturated compounds conjugated with electron-withdrawing group by ene-reductases (ERs) is a valuable method for the synthesis of enantiopure chiral compounds. This study introduced an ER from Corynebacterium casei (CcER) which was heterologously expressed in Escherichia coli BL21(DE3), and the purified recombinant CcER was characterized for its biocatalytic properties. CcER exhibited the highest specific activity at 40 °C and pH 6.5, and showcased appreciable stability below 40 °C over a pH range of 6.0-7.0. The enzyme displayed high resistance to methanol. CcER accepted NADH or NADPH as a cofactor and exhibited a broad substrate spectrum towards α, β-unsaturated compounds. It achieved complete conversion of 2-cyclohexen-1-one and good performance for stereoselective reduction of (R)-carvone (conversion 98 %, diastereoselectivity 96 %). This study highlights the robustness and potential of CcER.

The TAM, a Translocation and Assembly Module for protein assembly and potential conduit for phospholipid transfer

The assembly of β-barrel proteins into the bacterial outer membrane is an essential process enabling the colonization of new environmental niches. The TAM was discovered as a module of the β-barrel protein assembly machinery; it is a heterodimeric complex composed of an outer membrane protein (TamA) bound to an inner membrane protein (TamB). The TAM spans the periplasm, providing a scaffold through the peptidoglycan layer and catalyzing the translocation and assembly of β-barrel proteins into the outer membrane. Recently, studies on another membrane protein (YhdP) have suggested that TamB might play a role in phospholipid transport to the outer membrane. Here we review and re-evaluate the literature covering the experimental studies on the TAM over the past decade, to reconcile what appear to be conflicting claims on the function of the TAM.

"Metabolic burden" explained: stress symptoms and its related responses induced by (over)expression of (heterologous) proteins in Escherichia coli

BACKGROUND

Engineering bacterial strains to redirect the metabolism towards the production of a specific product has enabled the development of industrial biotechnology. However, rewiring the metabolism can have severe implications for a microorganism, rendering cells with stress symptoms such as a decreased growth rate, impaired protein synthesis, genetic instability and an aberrant cell size. On an industrial scale, this is reflected in processes that are not economically viable.

MAIN TEXT

In literature, most stress symptoms are attributed to "metabolic burden", however the actual triggers and stress mechanisms involved are poorly understood. Therefore, in this literature review, we aimed to get a better insight in how metabolic engineering affects Escherichia coli and link the observed stress symptoms to its cause. Understanding the possible implications that chosen engineering strategies have, will help to guide the reader towards optimising the envisioned process more efficiently.

CONCLUSION

This review addresses the gap in literature and discusses the triggers and effects of stress mechanisms that can be activated when (over)expressing (heterologous) proteins in Escherichia coli. It uncovers that the activation of the different stress mechanisms is complex and that many are interconnected. The reader is shown that care has to be taken when (over)expressing (heterologous) proteins as the cell's metabolism is tightly regulated.

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

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

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.

HyCas9-12aGEP: an efficient genome editing platform for Corynebacterium glutamicum

Corynebacterium glutamicum plays a crucial role as a significant industrial producer of metabolites. Despite the successful development of CRISPR-Cas9 and CRISPR-Cas12a-assisted genome editing technologies in C. glutamicum, their editing resolution and efficiency are hampered by the diverse on-target activities of guide RNAs (gRNAs). To address this problem, a hybrid CRISPR-Cas9-Cas12a genome editing platform (HyCas9-12aGEP) was developed in C. glutamicum in this study to co-express sgRNA (corresponding to SpCas9 guide RNA), crRNA (corresponding to FnCas12a guide RNA), or hfgRNA (formed by the fusion of sgRNA and crRNA). HyCas9-12aGEP improves the efficiency of mapping active gRNAs and outperforms both CRISPR-Cas9 and CRISPR-Cas12a in genome editing resolution and efficiency. In the experiment involving the deletion of the cg0697-0740 gene segment, an unexpected phenotype was observed, and HyCas9-12aGEP efficiently identified the responsible genotype from more than 40 genes. Here, HyCas9-12aGEP greatly improve our capability in terms of genome reprogramming in C. glutamicum.

Cas9-assisted biological containment of a genetically engineered human commensal bacterium and genetic elements

Sophisticated gene circuits built by synthetic biology can enable bacteria to sense their environment and respond predictably. Engineered biosensing bacteria outfitted with such circuits can potentially probe the human gut microbiome to prevent, diagnose, or treat disease. To provide robust biocontainment for engineered bacteria, we devised a Cas9-assisted auxotrophic biocontainment system combining thymidine auxotrophy, an Engineered Riboregulator (ER) for controlled gene expression, and a CRISPR Device (CD). The CD prevents the engineered bacteria from acquiring thyA via horizontal gene transfer, which would disrupt the biocontainment system, and inhibits the spread of genetic elements by killing bacteria harboring the gene cassette. This system tunably controlled gene expression in the human gut commensal bacterium Bacteroides thetaiotaomicron, prevented escape from thymidine auxotrophy, and blocked transgene dissemination. These capabilities were validated in vitro and in vivo. This biocontainment system exemplifies a powerful strategy for bringing genetically engineered microorganisms safely into biomedicine.

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.

Proteomics revealed an association between ribosome-associated proteins and amyloid beta deposition in Alzheimer's disease

Most scholars believe that amyloid-beta (Aβ) has the potential to induce apoptosis, stimulate an inflammatory cascade, promote oxidative stress and exacerbate the pathological progression of Alzheimer's disease (AD). Therefore, it is crucial to investigate the deposition of Aβ in AD. At approximately 6 months of age, APP/PS1 double transgenic mice gradually exhibit the development of plaques, as well as spatial and learning impairment. Notably, the hippocampus is specifically affected in the course of AD. Herein, 6-month-old APP/PS1 double transgenic mice were utilized, and the differentially expressed (DE) proteins in the hippocampus were identified and analyzed using 4D label-free quantitative proteomics technology and parallel reaction monitoring (PRM). Compared to wild-type mice, 29 proteins were upregulated and 25 proteins were downregulated in the AD group. Gene Ontology (GO) enrichment analysis of biological processes (BP) indicated that the DE proteins were mainly involved in 'ribosomal large subunit biogenesis'. Molecular function (MF) analysis results were primarily associated with '5.8S rRNA binding' and 'structural constituent of ribosome'. In terms of cellular components (CC), the DE proteins were mainly found in 'polysomal ribosome', 'cytosolic large ribosomal subunit', 'cytosolic ribosome', and 'large ribosomal subunit', among others. Furthermore, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis demonstrated that the results were mainly enriched in the 'Ribosome signaling pathway'. The key target proteins identified were ribosomal protein (Rp)l18, Rpl17, Rpl19, Rpl24, Rpl35, and Rpl6. The PRM verification results were consistent with the findings of the 4D label-free quantitative proteomics analysis. Overall, these findings suggest that Rpl18, Rpl17, Rpl19, Rpl24, Rpl35, and Rpl6 may have potential therapeutic value for the treatment of AD by targeting Aβ.

No Evidence that Selection on Synonymous Codon Usage Affects Patterns of Protein Evolution in Bacteria

Bias in synonymous codon usage has been reported across all kingdoms of life. Evidence suggests that codon usage bias is often driven by selective pressures, typically for translational efficiency. These selective pressures have been shown to depress the rate at which synonymous sites evolve. We hypothesize that selection on synonymous codon use could also slow the rate of protein evolution if a non-synonymous mutation changes the codon from being preferred to unpreferred. We test this hypothesis by looking at patterns of protein evolution using polymorphism and substitution data in two bacterial species, Escherichia coli and Streptococcus pneumoniae. We find no evidence that non-synonymous mutations that change a codon from being unpreferred to preferred are more common than the opposite. Overall, selection on codon bias seems to have little influence over non-synonymous polymorphism or substitution patterns.

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.

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.

Causes, functions, and therapeutic possibilities of RNA secondary structure ensembles and alternative states

RNA secondary structure plays essential roles in encoding RNA regulatory fate and function. Most RNAs populate ensembles of alternatively paired states and are continually unfolded and refolded by cellular processes. Measuring these structural ensembles and their contributions to cellular function has traditionally posed major challenges, but new methods and conceptual frameworks are beginning to fill this void. In this review, we provide a mechanism- and function-centric compendium of the roles of RNA secondary structural ensembles and minority states in regulating the RNA life cycle, from transcription to degradation. We further explore how dysregulation of RNA structural ensembles contributes to human disease and discuss the potential of drugging alternative RNA states to therapeutically modulate RNA activity. The emerging paradigm of RNA structural ensembles as central to RNA function provides a foundation for a deeper understanding of RNA biology and new therapeutic possibilities.

Antibody production relies on the tRNA inosine wobble modification to meet biased codon demand

Antibodies are produced at high rates to provide immunoprotection, which puts pressure on the B cell translational machinery. Here, we identified a pattern of codon usage conserved across antibody genes. One feature thereof is the hyperutilization of codons that lack genome-encoded Watson-Crick transfer RNAs (tRNAs), instead relying on the posttranscriptional tRNA modification inosine (I34), which expands the decoding capacity of specific tRNAs through wobbling. Antibody-secreting cells had increased I34 levels and were more reliant on I34 for protein production than naïve B cells. Furthermore, antibody I34-dependent codon usage may influence B cell passage through regulatory checkpoints. Our work elucidates the interface between the tRNA pool and protein production in the immune system and has implications for the design and selection of antibodies for vaccines and therapeutics.

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.

Epitranscriptional m6A modification of rRNA negatively impacts translation and host colonization in Staphylococcus aureus

Macrolides, lincosamides, and streptogramin B (MLS) are structurally distinct molecules that are among the safest antibiotics for prophylactic use and for the treatment of bacterial infections. The family of erythromycin resistance methyltransferases (Erm) invariantly install either one or two methyl groups onto the N6,6-adenosine of 2058 nucleotide (m6A2058) of the bacterial 23S rRNA, leading to bacterial cross-resistance to all MLS antibiotics. Despite extensive structural studies on the mechanism of Erm-mediated MLS resistance, how the m6A epitranscriptomic mark affects ribosome function and bacterial physiology is not well understood. Here, we show that Staphylococcus aureus cells harboring m6A2058 ribosomes are outcompeted by cells carrying unmodified ribosomes during infections and are severely impaired in colonization in the absence of an unmodified counterpart. The competitive advantage of m6A2058 ribosomes is manifested only upon antibiotic challenge. Using ribosome profiling (Ribo-Seq) and a dual-fluorescence reporter to measure ribosome occupancy and translational fidelity, we found that specific genes involved in host interactions, metabolism, and information processing are disproportionally deregulated in mRNA translation. This dysregulation is linked to a substantial reduction in translational capacity and fidelity in m6A2058 ribosomes. These findings point to a general "inefficient translation" mechanism of trade-offs associated with multidrug-resistant ribosomes.

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.

Recent Developments and Applications of Biocatalytic and Chemoenzymatic Synthesis for the Generation of Diverse Classes of Drugs

Biocatalytic and chemoenzymatic biosynthesis are powerful methods of organic chemistry that use enzymes to execute selective reactions and allow the efficient production of organic compounds. The advantages of these approaches include high selectivity, mild reaction conditions, and the ability to work with complex substrates. The utilization of chemoenzymatic techniques for the synthesis of complicated compounds has lately increased dramatically in the area of organic chemistry. Biocatalytic technologies and modern synthetic methods are utilized synergistically in a multi-step approach to a target molecule under this paradigm. Chemoenzymatic techniques are promising for simplifying access to essential bioactive compounds because of the remarkable regio- and stereoselectivity of enzymatic transformations and the reaction diversity of modern organic chemistry. Enzyme kits may include ready-to-use, reproducible biocatalysts. Its use opens up new avenues for the synthesis of active therapeutic compounds and aids in drug development by synthesizing active components to construct scaffolds in a targeted and preparative manner. This study summarizes current breakthroughs as well as notable instances of biocatalytic and chemoenzymatic synthesis. To assist organic chemists in the use of enzymes for synthetic applications, it also provides some basic guidelines for selecting the most appropriate enzyme for a targeted reaction while keeping aspects like cofactor requirement, solvent tolerance, use of whole cell or isolated enzymes, and commercial availability in mind.

Hyper-production of porcine contagious pleuropneumonia subunit vaccine proteins in Escherichia coli by developing a bicistronic T7 expression system

The ApxII toxin and the outer membrane lipoprotein (Oml) of Actinobacillus pleuropneumoniae are important vaccine antigens against porcine contagious pleuropneumonia (PCP), a prevalent infectious disease affecting the swine industry worldwide. Previous studies have reported the recombinant expression of ApxII and Oml in Escherichia coli; however, their yields were not satisfactory. Here, we aimed to enhance the production of ApxII and Oml by constructing a bicistronic expression system based on the widely used T7 promoter. To create efficient T7 bicistronic expression cassettes, 16 different fore-cistron sequences were introduced downstream of the T7 promoter. The expression of three vaccine antigens Oml1, Oml7, and ApxII in the four strongest bicistronic vectors were enhanced compared to the monocistronic control. Further optimization of the fermentation conditions in micro-well plates (MWP) led to improved production. Finally, the production yields reached unprecedented levels of 2.43 g L-1 of Oml1, 2.59 g L-1 of Oml7, and 1.21 g L-1 of ApxII, in a 5 L bioreactor. These three antigens also demonstrated well-protective immunity against A. pleuropneumoniae infection. In conclusion, this study establishes an efficient bicistronic T7 expression system that can be used to express recombinant proteins in E. coli and achieves the hyper-production of PCP vaccine proteins.

Ribosome Profiling Methods Adapted to the Study of RNA-Dependent Translation Regulation in Staphylococcus aureus

Noncoding RNAs, including regulatory RNAs (sRNAs), are instrumental in regulating gene expression in pathogenic bacteria, allowing them to adapt to various stresses encountered in their host environments. Staphylococcus aureus is a well-studied model for RNA-mediated regulation of virulence and pathogenicity, with sRNAs playing significant roles in shaping S. aureus interactions with human and animal hosts. By modulating the translation and/or stability of target mRNAs, sRNAs regulate the synthesis of virulence factors and regulatory proteins required for pathogenesis. Moreover, perturbation of the levels of RNA modifications in two other classes of noncoding RNAs, rRNAs, and tRNAs, has been proposed to contribute to stress adaptation. However, the study of how these various factors affect translation regulation has often been restricted to specific genes, using in vivo reporters and/or in vitro translation systems. Genome-wide sequencing approaches offer novel perspectives for studying RNA-dependent regulation. In particular, ribosome profiling methods provide a powerful resource for characterizing the overall landscape of translational regulation, contributing to a better understanding of S. aureus physiopathology. Here, we describe protocols that we have adapted to perform ribosome profiling in S. aureus.

Evaluation of the impact of polypeptide-p on diabetic rats upon its cloning, expression, and secretion in Saccharomyces boulardii

This study was designed to evaluate the effectiveness of recombinant polypeptide-p derived from Momordica charantia on diabetic rats. In this research, the optimized sequence of polypeptide-p gene fused to a secretion signal tag was cloned into the expression vector and transformed into probiotic Saccharomyces boulardii. The production of recombinant secretion protein was verified by western blotting, HPLC, and mass spectrometry. To assay recombinant yeast bioactivity in the gut, diabetic rats were orally fed wild-type and recombinant S. boulardii, in short SB and rSB, respectively, at two low and high doses as well as glibenclamide as a reference drug. In untreated diabetic and treated diabetic + SB rats (low and high doses), the blood glucose increased from 461, 481, and 455 (mg/dl), respectively, to higher than 600 mg/dl on the 21st day. Whereas glibenclamide and rSB treatments showed a significant reduction in the blood glucose level. The result of this study promised a safe plant-source supplement for diabetes through probiotic orchestration.

Host translation machinery is not a barrier to phages that interact with both CPR and non-CPR bacteria

IMPORTANCE

Here, we profiled putative phages of Saccharibacteria, which are of particular importance as Saccharibacteria influence some human oral diseases. We additionally profiled putative phages of Gracilibacteria and Absconditabacteria, two Candidate Phyla Radiation (CPR) lineages of interest given their use of an alternative genetic code. Among the phages identified in this study, some are targeted by spacers from both CPR and non-CPR bacteria and others by both bacteria that use the standard genetic code as well as bacteria that use an alternative genetic code. These findings represent new insights into possible phage replication strategies and have relevance for phage therapies that seek to manipulate microbiomes containing CPR bacteria.

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.

New Insights into Phylogenetic Relationship of Hydrocotyle (Araliaceae) Based on Plastid Genomes

Hydrocotyle, belonging to the Hydrocotyloideae of Araliaceae, consists of 95 perennial and 35 annual species. Due to the lack of stable diagnostic morphological characteristics and high-resolution molecular markers, the phylogenetic relationships of Hydrocotyle need to be further investigated. In this study, we newly sequenced and assembled 13 whole plastid genomes of Hydrocotyle and performed comparative plastid genomic analyses with four previously published Hydrocotyle plastomes and phylogenomic analyses within Araliaceae. The plastid genomes of Hydrocotyle exhibited typical quadripartite structures with lengths from 152,659 bp to 153,669 bp, comprising a large single-copy (LSC) region (83,958-84,792 bp), a small single-copy (SSC) region (18,585-18,768 bp), and a pair of inverted repeats (IRs) (25,058-25,145 bp). Each plastome encoded 113 unique genes, containing 79 protein-coding genes, 30 tRNA genes, and four rRNA genes. Comparative analyses showed that the IR boundaries of Hydrocotyle plastomes were highly similar, and the coding and IR regions exhibited more conserved than non-coding and single-copy (SC) regions. A total of 2932 simple sequence repeats and 520 long sequence repeats were identified, with specificity in the number and distribution of repeat sequences. Six hypervariable regions were screened from the SC region, including four intergenic spacers (IGS) (ycf3-trnS, trnS-rps4, petA-psbJ, and ndhF-rpl32) and two coding genes (rpl16 and ycf1). Three protein-coding genes (atpE, rpl16, and ycf2) were subjected to positive selection only in a few species, implying that most protein-coding genes were relatively conserved during the plastid evolutionary process. Plastid phylogenomic analyses supported the treatment of Hydrocotyle from Apiaceae to Araliaceae, and topologies with a high resolution indicated that plastome data can be further used in the comprehensive phylogenetic research of Hydrocotyle. The diagnostic characteristics currently used in Hydrocotyle may not accurately reflect the phylogenetic relationships of this genus, and new taxonomic characteristics may need to be evaluated and selected in combination with more comprehensive molecular phylogenetic results.

Multi-scale models of whole cells: progress and challenges

Whole-cell modeling is "the ultimate goal" of computational systems biology and "a grand challenge for 21st century" (Tomita, Trends in Biotechnology, 2001, 19(6), 205-10). These complex, highly detailed models account for the activity of every molecule in a cell and serve as comprehensive knowledgebases for the modeled system. Their scope and utility far surpass those of other systems models. In fact, whole-cell models (WCMs) are an amalgam of several types of "system" models. The models are simulated using a hybrid modeling method where the appropriate mathematical methods for each biological process are used to simulate their behavior. Given the complexity of the models, the process of developing and curating these models is labor-intensive and to date only a handful of these models have been developed. While whole-cell models provide valuable and novel biological insights, and to date have identified some novel biological phenomena, their most important contribution has been to highlight the discrepancy between available data and observations that are used for the parametrization and validation of complex biological models. Another realization has been that current whole-cell modeling simulators are slow and to run models that mimic more complex (e.g., multi-cellular) biosystems, those need to be executed in an accelerated fashion on high-performance computing platforms. In this manuscript, we review the progress of whole-cell modeling to date and discuss some of the ways that they can be improved.

An exploratory in silico comparison of open-source codon harmonization tools

BACKGROUND

Not changing the native constitution of genes prior to their expression by a heterologous host can affect the amount of proteins synthesized as well as their folding, hampering their activity and even cell viability. Over the past decades, several strategies have been developed to optimize the translation of heterologous genes by accommodating the difference in codon usage between species. While there have been a handful of studies assessing various codon optimization strategies, to the best of our knowledge, no research has been performed towards the evaluation and comparison of codon harmonization algorithms. To highlight their importance and encourage meaningful discussion, we compared different open-source codon harmonization tools pertaining to their in silico performance, and we investigated the influence of different gene-specific factors.

RESULTS

In total, 27 genes were harmonized with four tools toward two different heterologous hosts. The difference in %MinMax values between the harmonized and the original sequences was calculated (ΔMinMax), and statistical analysis of the obtained results was carried out. It became clear that not all tools perform similarly, and the choice of tool should depend on the intended application. Almost all biological factors under investigation (GC content, RNA secondary structures and choice of heterologous host) had a significant influence on the harmonization results and thus must be taken into account. These findings were substantiated using a validation dataset consisting of 8 strategically chosen genes.

CONCLUSIONS

Due to the size of the dataset, no complex models could be developed. However, this initial study showcases significant differences between the results of various codon harmonization tools. Although more elaborate investigation is needed, it is clear that biological factors such as GC content, RNA secondary structures and heterologous hosts must be taken into account when selecting the codon harmonization tool.

Heterologous expression of a deacetylase and its application in L-glufosinate preparation

With potent herbicidal activity, biocatalysis synthesis of L-glufosinate has drawn attention. In present research, NAP-Das2.3, a deacetylase capable of stereoselectively resolving N-acetyl-L-glufosinate to L-glufosinate mined from Arenimonas malthae, was heterologously expressed and characterized. In Escherichia coli, NAP-Das2.3 activity only reached 0.25 U/L due to the formation of inclusive bodies. Efficient soluble expression of NAP-Das2.3 was achieved in Pichia pastoris. In shake flask and 5 L bioreactor fermentation, NAP-Das2.3 activity by recombinant P. pastoris reached 107.39 U/L and 1287.52 U/L, respectively. The optimum temperature and pH for N-acetyl-glufosinate hydrolysis by NAP-Das2.3 were 45 °C and pH 8.0, respectively. The Km and Vmax of NAP-Das2.3 towards N-acetyl-glufosinate were 25.32 mM and 19.23 μmol mg-1 min-1, respectively. Within 90 min, 92.71% of L-enantiomer in 100 mM racemic N-acetyl-glufosinate was converted by NAP-Das2.3. L-glufosinate with high optical purity (e.e.P above 99.9%) was obtained. Therefore, the recombinant NAP-Das2.3 might be an alternative for L-glufosinate biosynthesis.