Design parameters to control synthetic gene expression in Escherichia coli

Modeling coding sequence design for virus-based expression in tobacco

Transient expression in Tobacco is a popular way to produce recombinant proteins in plants. The design of various expression vectors, delivered into the plant by Agrobacterium, has enabled high production levels of some proteins. To further enhance expression, researchers often adapt the coding sequence of heterologous genes to the host, but this strategy has produced mixed results in Tobacco. To study the effects of different sequence features on protein yield, we compile a dataset of the yields and coding sequences of previously published expression studies of more than 200 coding sequences. We evaluate various established gene expression models on a subset of the expression studies. We find that use of tobacco codons is only moderately predictive of protein yield as informative sequence features likely extend over multiple codons. Additionally, we show that codon usage of organisms that use tobacco as a host for expression of their proteins in a similar way as the synthetic system, like viruses and agrobacteria, can be used to predict heterologous expression. Other predictive features are related to tRNA supply and demand, the inclusion of a translational ramp of codons with lower adaptation to the tRNA pool at the beginning of the coding region, and the amino acid composition of the recombinant protein. A model based on all the features achieved a correlation of 0.57 with protein yield. We believe that our study provides a practical guideline for coding sequence design for efficient expression in tobacco.

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.

Bacteroides expand the functional versatility of a conserved transcription factor and transcribed DNA to program capsule diversity

The genomes of human gut bacteria in the genus Bacteroides include numerous operons for biosynthesis of diverse capsular polysaccharides (CPSs). The first two genes of each CPS operon encode a locus-specific paralog of transcription elongation factor NusG (called UpxY), which enhances transcript elongation, and a UpxZ protein that inhibits noncognate UpxYs. This process, together with promoter inversions, ensures that a single CPS operon is transcribed in most cells. Here, we use in-vivo nascent-RNA sequencing and promoter-less in-vitro transcription (PIVoT) to show that UpxY recognizes a paused RNA polymerase via sequences in both the exposed non-template DNA and the upstream duplex DNA. UpxY association is aided by 'pause-then-escape' nascent RNA hairpins. UpxZ binds non-cognate UpxYs to directly inhibit UpxY association. This UpxY-UpxZ hierarchical regulatory program allows Bacteroides to generate subpopulations of cells producing diverse CPSs for optimal fitness.

The disordered negatively charged C-terminus of the large HECT E3 ubiquitin ligase HERC2 provides structural and thermal stability to the HECT C-lobe

Homologous to the C-terminus of E6AP (HECT) and RCC1-like domain (RLD)-containing protein 2 (HERC2) is a large, 528 kDa E3 ubiquitin ligase that is associated with cancer, oculocutaneous albanism type 2, Prader-Willi syndrome, and other neurological diseases. HERC2 has been found to contribute to double-stranded DNA break repairs, tumor suppression, maintaining centrosome architecture, and ubiquitylation. The C-terminal portion of the HECT domain (C-lobe) of HERC2 is responsible for transferring ubiquitin to a substrate but the precise function of the other eight domains in HERC2 are unknown. Interestingly, HERC2 contains a unique and negatively charged C-terminal tail adjoined to the C-lobe that is predicted to act as a linker to promote interactions between HERC2 and its binding partners. This study aims to better understand the function and relevance of HERC2 in disease by investigating the structural aspects of the HERC2 C-lobe and HERC2 C-terminal tail using AlphaFold followed by molecular dynamics (MD) simulations, multidimensional nuclear magnetic resonance (NMR), and circular dichroism (CD). Secondary structure content analysis from MD simulations and the fully resonance assigned 1H-15N HSQC spectra of the HERC2 C-lobe and the isolated C-terminal tail confirm that the C-lobe is well-folded but the C-terminal tail is disordered. CD melting curves indicate that the flexible C-terminal tail provides improved stability to the C-lobe. Additionally, MD simulations have identified that the interaction between residues D4829 and R4728 is prevalent among the non-bonded contacts between the tail and the C-lobe. Overall, our results demonstrate that the negatively charged C-terminal tail is disordered, provides stability to the C-lobe, and may act as a flexible scaffold for protein-protein interactions.

Link Between Individual Codon Frequencies and Protein Expression: Going Beyond Codon Adaptation Index

An important role of a particular synonymous codon composition of a gene in its expression level is well known. There are a number of algorithms optimizing codon usage of recombinant genes to maximize their expression in host cells. Nevertheless, the underlying mechanism remains unsolved and is of significant relevance. In the realm of modern biotechnology, directing protein production to a specific level is crucial for metabolic engineering, genome rewriting and a growing number of other applications. In this study, we propose two new simple statistical and empirical methods for predicting the protein expression level from the nucleotide sequence of the corresponding gene: Codon Expression Index Score (CEIS) and Codon Productivity Score (CPS). Both of these methods are based on the influence of each individual codon in the gene on the overall expression level of the encoded protein and the frequencies of isoacceptors in the species. Our predictions achieve a correlation level of up to r = 0.7 with experimentally measured quantitative proteome data of Escherichia coli, which is superior to any previously proposed methods. Our work helps understand how codons determine protein abundances. Based on these methods, it is possible to design proteins optimized for expression in a particular organism.

GenRCA: a user-friendly rare codon analysis tool for comprehensive evaluation of codon usage preferences based on coding sequences in genomes

BACKGROUND

The study of codon usage bias is important for understanding gene expression, evolution and gene design, providing critical insights into the molecular processes that govern the function and regulation of genes. Codon Usage Bias (CUB) indices are valuable metrics for understanding codon usage patterns across different organisms without extensive experiments. Considering that there is no one-fits-all index for all species, a comprehensive platform supporting the calculation and analysis of multiple CUB indices for codon optimization is greatly needed.

RESULTS

Here, we release GenRCA, an updated version of our previous Rare Codon Analysis Tool, as a free and user-friendly website for all-inclusive evaluation of codon usage preferences of coding sequences. In this study, we manually reviewed and implemented up to 31 codon preference indices, with 65 expression host organisms covered and batch processing of multiple gene sequences supported, aiming to improve the user experience and provide more comprehensive and efficient analysis.

CONCLUSIONS

Our website fills a gap in the availability of comprehensive tools for species-specific CUB calculations, enabling researchers to thoroughly assess the protein expression level based on a comprehensive list of 31 indices and further guide the codon optimization.

Bacteroides expand the functional versatility of a universal transcription factor and transcribed DNA to program capsule diversity

Human gut Bacteroides species encode numerous (eight or more) tightly regulated capsular polysaccharides (CPS). Specialized paralogs of the universal transcription elongation factor NusG, called UpxY (Y), and an anti-Y UpxZ (Z) are encoded by the first two genes of each CPS operon. The Y-Z regulators combine with promoter inversions to limit CPS transcription to a single operon in most cells. Y enhances transcript elongation whereas Z inhibits noncognate Ys. How Y distinguishes among cognate CPS operons and how Z inhibits only noncognate Ys are unknown. Using in-vivo nascent-RNA sequencing and promoter-less in vitro transcription (PIVoT), we establish that Y recognizes a paused RNA polymerase via sequences in both the exposed non-template DNA and the upstream duplex DNA. Y association is aided by novel 'pause-then-escape' nascent RNA hairpins. Z binds non-cognate Ys to directly inhibit Y association. This Y-Z hierarchical regulatory program allows Bacteroides to create CPS subpopulations for optimal fitness.

Profiling expression strategies for a type III polyketide synthase in a lysate-based, cell-free system

Some of the most metabolically diverse species of bacteria (e.g., Actinobacteria) have higher GC content in their DNA, differ substantially in codon usage, and have distinct protein folding environments compared to tractable expression hosts like Escherichia coli. Consequentially, expressing biosynthetic gene clusters (BGCs) from these bacteria in E. coli often results in a myriad of unpredictable issues with regard to protein expression and folding, delaying the biochemical characterization of new natural products. Current strategies to achieve soluble, active expression of these enzymes in tractable hosts can be a lengthy trial-and-error process. Cell-free expression (CFE) has emerged as a valuable expression platform as a testbed for rapid prototyping expression parameters. Here, we use a type III polyketide synthase from Streptomyces griseus, RppA, which catalyzes the formation of the red pigment flaviolin, as a reporter to investigate BGC refactoring techniques. We applied a library of constructs with different combinations of promoters and rppA coding sequences to investigate the synergies between promoter and codon usage. Subsequently, we assess the utility of cell-free systems for prototyping these refactoring tactics prior to their implementation in cells. Overall, codon harmonization improves natural product synthesis more than traditional codon optimization across cell-free and cellular environments. More importantly, the choice of coding sequences and promoters impact protein expression synergistically, which should be considered for future efforts to use CFE for high-yield protein expression. The promoter strategy when applied to RppA was not completely correlated with that observed with GFP, indicating that different promoter strategies should be applied for different proteins. In vivo experiments suggest that there is correlation, but not complete alignment between expressing in cell free and in vivo. Refactoring promoters and/or coding sequences via CFE can be a valuable strategy to rapidly screen for catalytically functional production of enzymes from BCGs, which advances CFE as a tool for natural product research.

Sourcing DNA parts for synthetic biology applications in plants

Transgenic approaches are now standard in plant biology research aiming to characterize gene function or improve crops. Recent advances in DNA synthesis and assembly make constructing transgenes a routine task. What remains nontrivial is the selection of the DNA parts and optimization of the transgene design. Early career researchers and seasoned molecular biologists alike often face difficult decisions on what promoter or terminator to use, what tag to include, and where to place it. This review aims to inform about the current approaches being employed to identify and characterize DNA parts with the desired functionalities and give general advice on basic construct design. Furthermore, we hope to share the excitement about new experimental and computational tools being developed in this field.

Biosensor-assisted CRISPRi high-throughput screening to identify genetic targets in Zymomonas mobilis for high d-lactate production

Lactate is an important monomer for the synthesis of poly-lactate (PLA), which is a substitute for the petrochemical plastics. To achieve the goal of high lactate titer, rate, and yield for commercial production, efficient lactate production pathway is needed as well as genetic targets that affect high lactate production and tolerance. In this study, an LldR-based d-lactate biosensor with a broad dynamic range was first applied into Zymomonas mobilis to select mutant strains with strong GFP fluorescence, which could be the mutant strains with increased d-lactate production. Then, LldR-based d-lactate biosensor was combined with a genome-wide CRISPR interference (CRISPRi) library targeting the entire genome to generate thousands of mutants with gRNA targeting different genetic targets across the whole genome. Specifically, two mutant libraries were selected containing 105 and 104 mutants with different interference sites from two rounds of fluorescence-activated cell sorting (FACS), respectively. Two genetic targets of ZMO1323 and ZMO1530 were characterized and confirmed to be associated with the increased d-lactate production, further knockout of ZMO1323 and ZMO1530 resulted in a 15% and 21% increase of d-lactate production, respectively. This work thus not only established a high-throughput approach that combines genome-scale CRISPRi and biosensor-assisted screening to identify genetic targets associated with d-lactate production in Z. mobilis, but also provided a feasible high-throughput screening approach for rapid identification of genetic targets associated with strain performance for other industrial microorganisms.

Ultrasoft platelet-like particles stop bleeding in rodent and porcine models of trauma

Uncontrolled bleeding after trauma represents a substantial clinical problem. The current standard of care to treat bleeding after trauma is transfusion of blood products including platelets; however, donated platelets have a short shelf life, are in limited supply, and carry immunogenicity and contamination risks. Consequently, there is a critical need to develop hemostatic platelet alternatives. To this end, we developed synthetic platelet-like particles (PLPs), formulated by functionalizing highly deformable microgel particles composed of ultralow cross-linked poly (N-isopropylacrylamide) with fibrin-binding ligands. The fibrin-binding ligand was designed to target to wound sites, and the cross-linking of fibrin polymers was designed to enhance clot formation. The ultralow cross-linking of the microgels allows the particles to undergo large shape changes that mimic platelet shape change after activation; when coupled to fibrin-binding ligands, this shape change facilitates clot retraction, which in turn can enhance clot stability and contribute to healing. Given these features, we hypothesized that synthetic PLPs could enhance clotting in trauma models and promote healing after clotting. We first assessed PLP activity in vitro and found that PLPs selectively bound fibrin and enhanced clot formation. In murine and porcine models of traumatic injury, PLPs reduced bleeding and facilitated healing of injured tissue in both prophylactic and immediate treatment settings. We determined through biodistribution experiments that PLPs were renally cleared, possibly enabled by ultrasoft particle properties. The performance of synthetic PLPs in the preclinical studies shown here supports future translational investigation of these hemostatic therapeutics in a trauma setting.

Human GST P1-1 Redesigned for Enhanced Catalytic Activity with the Anticancer Prodrug Telcyta and Improved Thermostability

Protein engineering can be used to tailor enzymes for medical purposes, including antibody-directed enzyme prodrug therapy (ADEPT), which can act as a tumor-targeted alternative to conventional chemotherapy for cancer. In ADEPT, the antibody serves as a vector, delivering a drug-activating enzyme selectively to the tumor site. Glutathione transferases (GSTs) are a family of naturally occurring detoxication enzymes, and the finding that some of them are overexpressed in tumors has been exploited to develop GST-activated prodrugs. The prodrug Telcyta is activated by GST P1-1, which is the GST most commonly elevated in cancer cells, implying that tumors overexpressing GST P1-1 should be particularly vulnerable to Telcyta. Promising antitumor activity has been noted in clinical trials, but the wildtype enzyme has modest activity with Telcyta, and further functional improvement would enhance its usefulness for ADEPT. We utilized protein engineering to construct human GST P1-1 gene variants in the search for enzymes with enhanced activity with Telcyta. The variant Y109H displayed a 2.9-fold higher enzyme activity compared to the wild-type GST P1-1. However, increased catalytic potency was accompanied by decreased thermal stability of the Y109H enzyme, losing 99% of its activity in 8 min at 50 °C. Thermal stability was restored by four additional mutations simultaneously introduced without loss of the enhanced activity with Telcyta. The mutation Q85R was identified as an important contributor to the regained thermostability. These results represent a first step towards a functional ADEPT application for Telcyta.

Profiling Expression Strategies for a Type III Polyketide Synthase in a Lysate-Based, Cell-free System

Some of the most metabolically diverse species of bacteria (e.g., Actinobacteria) have higher GC content in their DNA, differ substantially in codon usage, and have distinct protein folding environments compared to tractable expression hosts like Escherichia coli. Consequentially, expressing biosynthetic gene clusters (BGCs) from these bacteria in E. coli frequently results in a myriad of unpredictable issues with protein expression and folding, delaying the biochemical characterization of new natural products. Current strategies to achieve soluble, active expression of these enzymes in tractable hosts, such as BGC refactoring, can be a lengthy trial-and-error process. Cell-free expression (CFE) has emerged as 1) a valuable expression platform for enzymes that are challenging to synthesize in vivo, and as 2) a testbed for rapid prototyping that can improve cellular expression. Here, we use a type III polyketide synthase from Streptomyces griseus, RppA, which catalyzes the formation of the red pigment flaviolin, as a reporter to investigate BGC refactoring techniques. We synergistically tune promoter and codon usage to improve flaviolin production from cell-free expressed RppA. We then assess the utility of cell-free systems for prototyping these refactoring tactics prior to their implementation in cells. Overall, codon harmonization improves natural product synthesis more than traditional codon optimization across cell-free and cellular environments. Refactoring promoters and/or coding sequences via CFE can be a valuable strategy to rapidly screen for catalytically functional production of enzymes from BCGs. By showing the coordinators between CFE versus in vivo expression, this work advances CFE as a tool for natural product research.

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.

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.

Revealing determinants of translation efficiency via whole-gene codon randomization and machine learning

It has been known for decades that codon usage contributes to translation efficiency and hence to protein production levels. However, its role in protein synthesis is still only partly understood. This lack of understanding hampers the design of synthetic genes for efficient protein production. In this study, we generated a synonymous codon-randomized library of the complete coding sequence of red fluorescent protein. Protein production levels and the full coding sequences were determined for 1459 gene variants in Escherichia coli. Using different machine learning approaches, these data were used to reveal correlations between codon usage and protein production. Interestingly, protein production levels can be relatively accurately predicted (Pearson correlation of 0.762) by a Random Forest model that only relies on the sequence information of the first eight codons. In this region, close to the translation initiation site, mRNA secondary structure rather than Codon Adaptation Index (CAI) is the key determinant of protein production. This study clearly demonstrates the key role of codons at the start of the coding sequence. Furthermore, these results imply that commonly used CAI-based codon optimization of the full coding sequence is not a very effective strategy. One should rather focus on optimizing protein production via reducing mRNA secondary structure formation with the first few codons.

Codon-optimized TDP-43 mediates neurodegeneration in a Drosophila model of ALS/FTLD

Transactive response DNA binding protein-43 (TDP-43) is known to mediate neurodegeneration associated with amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). The exact mechanism by which TDP-43 exerts toxicity in the brains, spinal cord, and lower motor neurons of affected patients remains unclear. In a novel Drosophila melanogaster model, we report gain-of-function phenotypes due to misexpression of insect codon-optimized version of human wild-type TDP-43 (CO-TDP-43) using both the binary GAL4/UAS system and direct promoter fusion constructs. The CO-TDP-43 model showed robust tissue specific phenotypes in the adult eye, wing, and bristles in the notum. Compared to non-codon optimized transgenic flies, the CO-TDP-43 flies produced increased amount of high molecular weight protein, exhibited pathogenic phenotypes, and showed cytoplasmic aggregation with both nuclear and cytoplasmic expression of TDP-43. Further characterization of the adult retina showed a disruption in the morphology and function of the photoreceptor neurons with the presence of acidic vacuoles that are characteristic of autophagy. Based on our observations, we propose that TDP-43 has the propensity to form toxic protein aggregates via a gain-of-function mechanism, and such toxic overload leads to activation of protein degradation pathways such as autophagy. The novel codon optimized TDP-43 model is an excellent resource that could be used in genetic screens to identify and better understand the exact disease mechanism of TDP-43 proteinopathies and find potential therapeutic targets.

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

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

Basis of narrow-spectrum activity of fidaxomicin on Clostridioides difficile

Fidaxomicin (Fdx) is widely used to treat Clostridioides difficile (Cdiff) infections, but the molecular basis of its narrow-spectrum activity in the human gut microbiome remains unknown. Cdiff infections are a leading cause of nosocomial deaths1. Fidaxomicin, which inhibits RNA polymerase, targets Cdiff with minimal effects on gut commensals, reducing recurrence of Cdiff infection2,3. Here we present the cryo-electron microscopy structure of Cdiff RNA polymerase in complex with fidaxomicin and identify a crucial fidaxomicin-binding determinant of Cdiff RNA polymerase that is absent in most gut microbiota such as Proteobacteria and Bacteroidetes. By combining structural, biochemical, genetic and bioinformatic analyses, we establish that a single residue in Cdiff RNA polymerase is a sensitizing element for fidaxomicin narrow-spectrum activity. Our results provide a blueprint for targeted drug design against an important human pathogen.

Engineered bacterial voltage-gated sodium channel platform for cardiac gene therapy

Therapies for cardiac arrhythmias could greatly benefit from approaches to enhance electrical excitability and action potential conduction in the heart by stably overexpressing mammalian voltage-gated sodium channels. However, the large size of these channels precludes their incorporation into therapeutic viral vectors. Here, we report a platform utilizing small-size, codon-optimized engineered prokaryotic sodium channels (BacNav) driven by muscle-specific promoters that significantly enhance excitability and conduction in rat and human cardiomyocytes in vitro and adult cardiac tissues from multiple species in silico. We also show that the expression of BacNav significantly reduces occurrence of conduction block and reentrant arrhythmias in fibrotic cardiac cultures. Moreover, functional BacNav channels are stably expressed in healthy mouse hearts six weeks following intravenous injection of self-complementary adeno-associated virus (scAAV) without causing any adverse effects on cardiac electrophysiology. The large diversity of prokaryotic sodium channels and experimental-computational platform reported in this study should facilitate the development and evaluation of BacNav-based gene therapies for cardiac conduction disorders.

Production of Aldehydes by Biocatalysis

The production of aldehydes, highly reactive and toxic chemicals, brings specific challenges to biocatalytic processes. Absence of natural accumulation of aldehydes in microorganisms has led to a combination of in vitro and in vivo strategies for both, bulk and fine production. Advances in genetic and metabolic engineering and implementation of computational techniques led to the production of various enzymes with special requirements. Cofactor synthesis, post-translational modifications and structure engineering are applied to prepare active enzymes for one-step or cascade reactions. This review presents the highlights in biocatalytical production of aldehydes with the potential to shape future industrial applications.

Genetic and metabolic engineering challenges of C1-gas fermenting acetogenic chassis organisms

Unabated mining and utilisation of petroleum and petroleum resources and their conversion to essential fuels and chemicals have drastic environmental consequences, contributing to global warming and climate change. In addition, fossil fuels are finite resources, with a fast-approaching shortage. Accordingly, research efforts are increasingly focusing on developing sustainable alternatives for chemicals and fuels production. In this context, bioprocesses, relying on microorganisms, have gained particular interest. For example, acetogens use the Wood-Ljungdahl pathway to grow on single carbon C1-gases (CO2 and CO) as their sole carbon source and produce valuable products such as acetate or ethanol. These autotrophs can, therefore, be exploited for large-scale fermentation processes to produce industrially relevant chemicals from abundant greenhouse gases. In addition, genetic tools have recently been developed to improve these chassis organisms through synthetic biology approaches. This review will focus on the challenges of genetically and metabolically modifying acetogens. It will first discuss the physical and biochemical obstacles complicating successful DNA transfer in these organisms. Current genetic tools developed for several acetogens, crucial for strain engineering to consolidate and expand their catalogue of products, will then be described. Recent tool applications for metabolic engineering purposes to allow redirection of metabolic fluxes or production of non-native compounds will lastly be covered.

Soluble Expression and Catalytic Properties of Codon-Optimized Recombinant Bromelain from MD2 Pineapple in Escherichia coli

Bromelain, a member of cysteine proteases, is found abundantly in pineapple (Ananas comosus), and it has a myriad of versatile applications. However, attempts to produce recombinant bromelain for commercialization purposes are challenging due to its expressibility and solubility. This study aims to express recombinant fruit bromelain from MD2 pineapple (MD2Bro; accession no: OAY85858.1) in soluble and active forms using Escherichia coli host cell. The gene encoding MD2Bro was codon-optimized, synthesized, and subsequently ligated into pET-32b( +) for further transformation into Escherichia coli BL21-CodonPlus(DE3). Under this strategy, the expressed MD2Bro was in a fusion form with thioredoxin (Trx) tag at its N-terminal (Trx-MD2Bro). The result showed that Trx-MD2Bro was successfully expressed in fully soluble form. The protein was successfully purified using single-step Ni²⁺-NTA chromatography and confirmed to be in proper folds based on the circular dichroism spectroscopy analysis. The purified Trx-MD2Bro was confirmed to be catalytically active against N-carbobenzoxyglycine p-nitrophenyl ester (N-CBZ-Gly-pNP) with a specific activity of 6.13 ± 0.01 U mg^-1 and inhibited by a cysteine protease inhibitor, E-64 (IC₅₀ of 74.38 ± 1.65 nM). Furthermore, the catalytic efficiency (k_cat/K_M) Trx-MD2Bro was calculated to be at 5.64 ± 0.02 × 10^-2 µM^-1 s^-1 while the optimum temperature and pH were at 50 °C and pH 6.0, respectively. Furthermore, the catalytic activity of Trx-MD2Bro was also affected by ethylenediaminetetraacetic acid (EDTA) or metal ions. Altogether it is proposed that the combination of codon optimization and the use of an appropriate vector are important in the production of a soluble and actively stable recombinant bromelain.

Assessing optimal: inequalities in codon optimization algorithms

BACKGROUND

Custom genes have become a common resource in recombinant biology over the last 20 years due to the plummeting cost of DNA synthesis. These genes are often "optimized" to non-native sequences for overexpression in a non-native host by substituting synonymous codons within the coding DNA sequence (CDS). A handful of studies have compared native and optimized CDSs, reporting different levels of soluble product due to the accumulation of misfolded aggregates, variable activity of enzymes, and (at least one report of) a change in substrate specificity. No study, to the best of our knowledge, has performed a practical comparison of CDSs generated from different codon optimization algorithms or reported the corresponding protein yields.

RESULTS

In our efforts to understand what factors constitute an optimized CDS, we identified that there is little consensus among codon-optimization algorithms, a roughly equivalent chance that an algorithm-optimized CDS will increase or diminish recombinant yields as compared to the native DNA, a near ubiquitous use of a codon database that was last updated in 2007, and a high variability of output CDSs by some algorithms. We present a case study, using KRas4B, to demonstrate that a median codon frequency may be a better predictor of soluble yields than the more commonly utilized CAI metric.

CONCLUSIONS

We present a method for visualizing, analyzing, and comparing algorithm-optimized DNA sequences for recombinant protein expression. We encourage researchers to consider if DNA optimization is right for their experiments, and work towards improving the reproducibility of published recombinant work by publishing non-native CDSs.

A Modelling Framework Linking Resource-Based Stochastic Translation to the Optimal Design of Synthetic Constructs

Simple Summary

In synthetic biology, it is commonplace to design and insert gene expression constructs into cells for the production of useful proteins. In order to maximise production yield, it is useful to predict the performance of these “engineered cells” in advance of conducting experiments. This is typically a complex task, which in recent years has motivated the use of “whole-cell models” (WCMs) that act as computational tools for predicting different aspects of cell growth. Many useful WCMs exist, however a common problem is their over-simplification of ribosome movement on mRNA transcripts during translation. WCMs typically don’t consider that, for constructs with inefficient (“slow”) codons, ribosomes can stall and form “traffic jams”, thereby becoming unavailable for translation of other proteins. To more accurately address these scenarios, we have built a computational framework that combines whole-cell modelling with a detailed account of ribosome movement on mRNA. We show how our framework can be used to link the modular design of a gene expression construct (via its promoter, ribosome binding site and codon composition) to protein yield during continuous cell culture, with a particular focus on how the optimal design can change over time in the presence or absence of “slow” codons.

Abstract

The effect of gene expression burden on engineered cells has motivated the use of “whole-cell models” (WCMs) that use shared cellular resources to predict how unnatural gene expression affects cell growth. A common problem with many WCMs is their inability to capture translation in sufficient detail to consider the impact of ribosomal queue formation on mRNA transcripts. To address this, we have built a “stochastic cell calculator” (StoCellAtor) that combines a modified TASEP with a stochastic implementation of an existing WCM. We show how our framework can be used to link a synthetic construct’s modular design (promoter, ribosome binding site (RBS) and codon composition) to protein yield during continuous culture, with a particular focus on the effects of low-efficiency codons and their impact on ribosomal queues. Through our analysis, we recover design principles previously established in our work on burden-sensing strategies, namely that changing promoter strength is often a more efficient way to increase protein yield than RBS strength. Importantly, however, we show how these design implications can change depending on both the duration of protein expression, and on the presence of ribosomal queues.

Design, Expression and Purification of Strongyloides stercoralis IgG4 Immunoreactive Protein (NIE) in Escherichia coli

Background

Strongyloidiasis is a public health concern in northern regions of Iran, caused by Strongyloides stercoralis. Auto-infection cycle can be resulted in high parasitic load, especially in immunocompromised hosts. Because of low sensitivity of stool culture and stool-based microscopy techniques, detection of antibodies in patient's sera can be an alternative diagnostic technique for detection of the nematode. In the present study, as the first step of the development of an ELISA kit for the detection of antibodies against the nematode, IgG4 immunoreactive protein (NIE) was expressed in Escherichia coli expression system, purified and verified.

Methods

The NIE gene sequence was retrieved from the GenBank. This sequence was codon-optimized for the expression in E. coli BL21 (DE3). The sequence was inserted into the expression vector pET-30b (+). The recombinant vector was then transferred into competent E. coli BL21 (DE3). Transformed colonies were selected and verified by colony PCR. NIE gene expression was induced with IPTG induction. The protein production was evaluated by SDS-PAGE and verified using Western blotting.

Results

The codon-optimized NIE gene had required parameters for expression in E. coli. NIE protein was proved and verified by SDS-PAGE and Western blotting.

Conclusion

NIE recombinant protein was successfully expressed in E. coli expression system in appropriate amounts. The recombinant protein can be used for developing ELISA kit in diagnosis of S. stercoralis.

Codon optimization with deep learning to enhance protein expression

Heterologous expression is the main approach for recombinant protein production ingenetic synthesis, for which codon optimization is necessary. The existing optimization methods are based on biological indexes. In this paper, we propose a novel codon optimization method based on deep learning. First, we introduce the concept of codon boxes, via which DNA sequences can be recoded into codon box sequences while ignoring the order of bases. Then, the problem of codon optimization can be converted to sequence annotation of corresponding amino acids with codon boxes. The codon optimization models for Escherichia Coli were trained by the Bidirectional Long-Short-Term Memory Conditional Random Field. Theoretically, deep learning is a good method to obtain the distribution characteristics of DNA. In addition to the comparison of the codon adaptation index, protein expression experiments for plasmodium falciparum candidate vaccine and polymerase acidic protein were implemented for comparison with the original sequences and the optimized sequences from Genewiz and ThermoFisher. The results show that our method for enhancing protein expression is efficient and competitive.

Determinants of translation efficiency in the evolutionarily-divergent protist Trichomonas vaginalis

BACKGROUND

Trichomonas vaginalis, the causative agent of a prevalent urogenital infection in humans, is an evolutionarily divergent protozoan. Protein-coding genes in T. vaginalis are largely controlled by two core promoter elements, producing mRNAs with short 5' UTRs. The specific mechanisms adopted by T. vaginalis to fine-tune the translation efficiency (TE) of mRNAs remain largely unknown.

RESULTS

Using both computational and experimental approaches, this study investigated two key factors influencing TE in T. vaginalis: codon usage and mRNA secondary structure. Statistical dependence between TE and codon adaptation index (CAI) highlighted the impact of codon usage on mRNA translation in T. vaginalis. A genome-wide interrogation revealed that low structural complexity at the 5' end of mRNA followed closely by a highly structured downstream region correlates with TE variation in this organism. To validate these findings, a synthetic library of 15 synonymous iLOV genes was created, representing five mRNA folding profiles and three codon usage profiles. Fluorescence signals produced by the expression of these synonymous iLOV genes in T. vaginalis were consistent with and validated our in silico predictions.

CONCLUSIONS

This study demonstrates the role of codon usage bias and mRNA secondary structure in TE of T. vaginalis mRNAs, contributing to a better understanding of the factors that influence, and possibly regulate, gene expression in this human pathogen.

An Angelman syndrome substitution in the HECT E3 ubiquitin ligase C-terminal Lobe of E6AP affects protein stability and activity

Angelman syndrome (AS) is a rare neurodevelopmental disorder characterized by speech impairment, intellectual disability, ataxia, and epilepsy. AS is caused by mutations in the maternal copy of UBE3A located on chromosome 15q11-13. UBE3A codes for E6AP (E6 Associated Protein), a prominent member of the HECT (Homologous to E6AP C-Terminus) E3 ubiquitin ligase family. E6AP catalyzes the posttranslational attachment of ubiquitin via its HECT domain onto various intracellular target proteins to regulate DNA repair and cell cycle progression. The HECT domain consists of an N-lobe, required for E2~ubiquitin recruitment, while the C-lobe contains the conserved catalytic cysteine required for ubiquitin transfer. Previous genetic studies of AS patients have identified point mutations in UBE3A that result in amino acid substitutions or premature termination during translation. An AS transversion mutation (codon change from ATA to AAA) within the region of the gene that codes for the catalytic HECT domain of E6AP has been annotated (I827K), but the molecular basis for this loss of function substitution remained elusive. Here, we demonstrate that the I827K substitution destabilizes the 3D fold causing protein aggregation of the C-terminal lobe of E6AP using a combination of spectropolarimetry and nuclear magnetic resonance (NMR) spectroscopy. Our fluorescent ubiquitin activity assays with E6AP-I827K show decreased ubiquitin thiolester formation and ubiquitin discharge. Using 3D models in combination with our biochemical and biophysical results, we rationalize why the I827K disrupts E6AP-dependent ubiquitylation. This work provides new insight into the E6AP mechanism and how its malfunction can be linked to the AS phenotype.

ChimeraUGEM: unsupervised gene expression modeling in any given organism

MOTIVATION

Regulation of the amount of protein that is synthesized from genes has proved to be a serious challenge in terms of analysis and prediction, and in terms of engineering and optimization, due to the large diversity in expression machinery across species.

RESULTS

To address this challenge, we developed a methodology and a software tool (ChimeraUGEM) for predicting gene expression as well as adapting the coding sequence of a target gene to any host organism. We demonstrate these methods by predicting protein levels in seven organisms, in seven human tissues, and by increasing in vivo the expression of a synthetic gene up to 26-fold in the single-cell green alga Chlamydomonas reinhardtii. The underlying model is designed to capture sequence patterns and regulatory signals with minimal prior knowledge on the host organism and can be applied to a multitude of species and applications.

AVAILABILITY AND IMPLEMENTATION

Source code (MATLAB, C) and binaries are freely available for download for non-commercial use at http://www.cs.tau.ac.il/~tamirtul/ChimeraUGEM/, and supported on macOS, Linux and Windows.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Oral immunization of mice with a multivalent therapeutic subunit vaccine protects against Helicobacter pylori infection

Helicobacter pylori is a human class I carcinogen and no effective prophylactic or therapeutic H. pylori vaccine has yet been marketed. H. pylori can escape the host immune response, but the precise immune protection mechanisms in humans remain unknown. In this study, we developed a multivalent, subunit H. pylori vaccine candidate by formulating three commonly used H. pylori antigens, neutrophil-activating protein (NAP), urease subunit A (UreA) and subunit B (UreB) with the mucosal adjuvant, a double-mutant heat-labile toxin (dmLT) from Escherichia coli, and evaluated its immunogenicity and therapeutic efficacy in a mouse model of H. pylori infection. We found that oral immunization of H. pylori-infected mice significantly reduced gastric bacterial colonization at both 2 and 8 weeks after immunization. The reduction in bacterial burdens was accompanied with significantly increased serum antigen-specific IgG responses and mucosal IgA responses. Moreover, oral immunization also induced Th1/Th17 immune responses, which may play a synergistic role with the specific antibodies in the elimination of H. pylori. Thus, our vaccine candidate appears able to overcome the immune evasion mechanism of H. pylori, restore the suppression of Th2 immune responses with the induction of a strong humoral immune response. These results lay the foundation for the development of an optimized oral therapeutic H. pylori vaccine with increased immunogenicity of UreA and UreB, as well as providing long-term immunity.

Synonymous codon substitutions perturb cotranslational protein folding in vivo and impair cell fitness

In the cell, proteins are synthesized from N to C terminus and begin to fold during translation. Cotranslational folding mechanisms are therefore linked to elongation rate, which varies as a function of synonymous codon usage. However, synonymous codon substitutions can affect many distinct cellular processes, which has complicated attempts to deconvolve the extent to which synonymous codon usage can promote or frustrate proper protein folding in vivo. Although previous studies have shown that some synonymous changes can lead to different final structures, other substitutions will likely be more subtle, perturbing predominantly the protein folding pathway without radically altering the final structure. Here we show that synonymous codon substitutions encoding a single essential enzyme lead to dramatically slower cell growth. These mutations do not prevent active enzyme formation; instead, they predominantly alter the protein folding mechanism, leading to enhanced degradation in vivo. These results support a model in which synonymous codon substitutions can impair cell fitness by significantly perturbing cotranslational protein folding mechanisms, despite the chaperoning provided by the cellular protein homeostasis network.

mRNA structure regulates protein expression through changes in functional half-life

Despite widespread recognition that RNA is inherently structured, the interplay between local and global mRNA secondary structure (particularly in the coding region) and overall protein expression has not been thoroughly explored. Our work uses 2 approaches to disentangle the regulatory roles of mRNA primary sequence and secondary structure: global substitution with modified nucleotides and computational sequence design. By fitting detailed kinetic expression data to mathematical models, we show that secondary structure can increase mRNA half-life independent of codon usage. These findings have significant implications for both translational regulation of endogenous mRNAs and the emerging field of mRNA therapeutics.

Messenger RNAs (mRNAs) encode information in both their primary sequence and their higher order structure. The independent contributions of factors like codon usage and secondary structure to regulating protein expression are difficult to establish as they are often highly correlated in endogenous sequences. Here, we used 2 approaches, global inclusion of modified nucleotides and rational sequence design of exogenously delivered constructs, to understand the role of mRNA secondary structure independent from codon usage. Unexpectedly, highly expressed mRNAs contained a highly structured coding sequence (CDS). Modified nucleotides that stabilize mRNA secondary structure enabled high expression across a wide variety of primary sequences. Using a set of eGFP mRNAs with independently altered codon usage and CDS structure, we find that the structure of the CDS regulates protein expression through changes in functional mRNA half-life (i.e., mRNA being actively translated). This work highlights an underappreciated role of mRNA secondary structure in the regulation of mRNA stability.

Hot CoFi Blot: A High-Throughput Colony-Based Screen for Identifying More Thermally Stable Protein Variants

Highly soluble and stable proteins are desirable for many different applications, from basic science to reaching a cancer patient in the form of a biological drug. For X-ray crystallography-where production of a protein crystal might take weeks and even months-a stable protein sample of high purity and concentration can greatly increase the chances of producing a well-diffracting crystal. For a patient receiving a specific protein drug, its safety, efficacy, and even cost are factors affected by its solubility and stability. Increased protein expression and protein stability can be achieved by randomly altering the coding sequence. As the number of mutants generated might be overwhelming, a powerful protein expression and stability screen is required. In this chapter, we describe a colony filtration technology, which allows us to screen random mutagenesis libraries for increased thermal stability-the Hot CoFi blot. We share how to create the random mutagenesis library, how to perform the Hot CoFi blot, and how to identify more thermally stable clones. We use the Tobacco Etch Virus protease as a target to exemplify the procedure.

A novel framework for evaluating the performance of codon usage bias metrics

The unequal utilization of synonymous codons affects numerous cellular processes including translation rates, protein folding and mRNA degradation. In order to understand the biological impact of variable codon usage bias (CUB) between genes and genomes, it is crucial to be able to accurately measure CUB for a given sequence. A large number of metrics have been developed for this purpose, but there is currently no way of systematically testing the accuracy of individual metrics or knowing whether metrics provide consistent results. This lack of standardization can result in false-positive and false-negative findings if underpowered or inaccurate metrics are applied as tools for discovery. Here, we show that the choice of CUB metric impacts both the significance and measured effect sizes in numerous empirical datasets, raising questions about the generality of findings in published research. To bring about standardization, we developed a novel method to create synthetic protein-coding DNA sequences according to different models of codon usage. We use these benchmark sequences to identify the most accurate and robust metrics with regard to sequence length, GC content and amino acid heterogeneity. Finally, we show how our benchmark can aid the development of new metrics by providing feedback on its performance compared to the state of the art.

Developing a codon optimization method for improved expression of recombinant proteins in actinobacteria

Codon optimization by synonymous substitution is widely used for recombinant protein expression. Recent studies have investigated sequence features for codon optimization based on large-scale expression analyses. However, these studies have been limited to common host organisms such as Escherichia coli. Here, we develop a codon optimization method for Rhodococcus erythropolis, a gram-positive GC-rich actinobacterium attracting attention as an alternative host organism. We evaluate the recombinant protein expression of 204 genes in R. erythropolis with the same plasmid vector. The statistical analysis of these expression data reveals that the mRNA folding energy at 5’ regions as well as the codon frequency are important sequence features for codon optimization. Intriguingly, other sequence features such as the codon repetition rate show a different tendency from the previous study on E. coli. We optimize the coding sequences of 12 genes regarding these sequence features, and confirm that 9 of them (75%) achieve increased expression levels compared with wild-type sequences. Especially, for 5 genes whose expression levels for wild-type sequences are small or not detectable, all of them are improved by optimized sequences. These results demonstrate the effectiveness of our codon optimization method in R. erythropolis, and possibly in other actinobacteria.

Efficient expression of a novel thermophilic fungal β-mannosidase from Lichtheimia ramosa with broad-range pH stability and its synergistic hydrolysis of locust bean gum

β-Mannosidase (EC 3.2.1.25) is an exoglycosidase specific for the hydrolysis of terminal β-1,4-glycosidic linkage in mannan which can be applied in the food manufacture, animal feed, bioethanol making and coffee extraction industries. A novel β-mannosidase gene (Lrman5A) from Lichtheimia ramosa was synthesized and recombinantly expressed in Pichia pastoris X33. Lrman5A encodes 444 amino acids with a calculated molecular mass of 51.0 kDa which shares the highest identity (73%) with the β-mannosidase from Rhizomucor miehei. Purified recombinant Lrman5A showed the maximal activity at pH 6.0 and 65°C, had broad-range pH stability (retaining >65% activity after incubation at pH 3.0-8.5 at 37°C for 24 h), and was highly thermostable (retaining >80% activity after incubation at 65°C for 10 min). The specific activity, and K_m of Lrman5A was 17.5 U/mg and 1.377 mM, respectively. Lrman5A and GH5 β-mannanase displayed significant synergistic effects on the degradation of locust bean gum (LBG) and released more mannose (up to 2.89 folds) by simultaneous or sequential addition. Due to its hydrolytic properties, Lrman5A may have potential applications in the area of bioenergy, feed and food processing.

Identification of non-conserved residues essential for improving the hydrocarbon-producing activity of cyanobacterial aldehyde-deformylating oxygenase

BACKGROUND

Cyanobacteria produce hydrocarbons corresponding to diesel fuels by means of aldehyde-deformylating oxygenase (ADO). ADO catalyzes a difficult and unusual reaction in the conversion of aldehydes to hydrocarbons and has been widely used for biofuel production in metabolic engineering; however, its activity is low. A comparison of the amino acid sequences of highly active and less active ADOs will elucidate non-conserved residues that are essential for improving the hydrocarbon-producing activity of ADOs.

RESULTS

Here, we measured the activities of ADOs from 10 representative cyanobacterial strains by expressing each of them in Escherichia coli and quantifying the hydrocarbon yield and amount of soluble ADO. We demonstrated that the activity was highest for the ADO from Synechococcus elongatus PCC 7942 (7942ADO). In contrast, the ADO from Gloeobacter violaceus PCC 7421 (7421ADO) had low activity but yielded high amounts of soluble protein, resulting in a high production level of hydrocarbons. By introducing 37 single amino acid substitutions at the non-conserved residues of the less active ADO (7421ADO) to make its sequence more similar to that of the highly active ADO (7942ADO), we found 20 mutations that improved the activity of 7421ADO. In addition, 13 other mutations increased the amount of soluble ADO while maintaining more than 80% of wild-type activity. Correlation analysis showed a solubility-activity trade-off in ADO, in which activity was negatively correlated with solubility.

CONCLUSIONS

We succeeded in identifying non-conserved residues that are essential for improving ADO activity. Our results may be useful for generating combinatorial mutants of ADO that have both higher activity and higher amounts of the soluble protein in vivo, thereby producing higher yields of biohydrocarbons.

Systems Metabolic Engineering Strategies for Non-Natural Microbial Polyester Production

Plastics, used everyday, are mostly synthetic polymers derived from fossil resources, and their accumulation is becoming a serious concern worldwide. Polyhydroxyalkanoates (PHAs) are naturally produced polyesters synthesized and intracellularly accumulated by many different microorganisms. PHAs are good alternatives to petroleum-based plastics because they possess a wide range of material properties depending on monomer types and molecular weights. In addition, PHAs are biodegradable and can be produced from renewable biomass. Thus, producing PHAs through the development of high-performance engineered microorganisms and efficient bioprocesses gained much interest. In addition, non-natural polyesters comprising 2-hydroxycarboxylic acids as monomers have been produced by fermentation of metabolically engineered bacteria. For example, poly(lactic acid) and poly(lactic acid-co-glycolic acid), which have been chemically synthesized using the corresponding monomers either fermentatively or chemically produced, can be produced by metabolically engineered bacteria by one-step fermentation. Recently, PHAs containing aromatic monomers could be produced by fermentation of metabolically engineered bacteria. Here, metabolic engineering strategies applied in developing microbial strains capable of producing non-natural polyesters in a stepwise manner are reviewed. It is hoped that the detailed strategies described will be helpful for designing metabolic engineering strategies for developing diverse microbial strains capable of producing various polymers that can replace petroleum-derived polymers.

Screening and purification of nanobodies from E. coli culture supernatants using the hemolysin secretion system

BACKGROUND

The hemolysin (Hly) secretion system of E. coli allows the one-step translocation of hemolysin A (HlyA) from the bacterial cytoplasm to the extracellular medium, without a periplasmic intermediate. In this work, we investigate whether the Hly secretion system of E. coli is competent to secrete a repertoire of functional single-domain VHH antibodies (nanobodies, Nbs), facilitating direct screening of VHH libraries and the purification of selected Nb from the extracellular medium.

RESULTS

We employed a phagemid library of VHHs obtained by immunization of a dromedary with three protein antigens from enterohemorrhagic E. coli (EHEC), namely, the extracellular secreted protein A (EspA), the extracellular C-terminal region of Intimin (Int280), and the translocated intimin receptor middle domain (TirM). VHH clones binding each antigen were enriched and amplified by biopanning, and subsequently fused to the C-terminal secretion signal of HlyA to be expressed and secreted in a E. coli strain carrying the Hly export machinery (HlyB, HlyD and TolC). Individual E. coli clones were grown and induced in 96-well microtiter plates, and the supernatants of the producing cultures directly used in ELISA for detection of Nbs binding EspA, Int280 and TirM. A set of Nb sequences specifically binding each of these antigens were identified, indicating that the Hly system is able to secrete a diversity of functional Nbs. We performed thiol alkylation assays demonstrating that Nbs are correctly oxidized upon secretion, forming disulphide bonds between cysteine pairs despite the absence of a periplasmic intermediate. In addition, we show that the secreted Nb-HlyA fusions can be directly purified from the supernatant of E. coli cultures, avoiding cell lysis and in a single affinity chromatography step.

CONCLUSIONS

Our data demonstrate the Hly secretion system of E. coli can be used as an expression platform for screening and purification of Nb binders from VHH repertories.

Applications of Protein Engineering and Directed Evolution in Plant Research

Engineered proteins can be used to optimize desired traits in plants; even though recent advances have resulted in new application areas, certain methodological challenges remain.

The fitness consequences of synonymous mutations in Escherichia coli: Experimental evidence for a pleiotropic effect of translational selection

Codon usage bias (CUB) is a universal feature of genomes, and in most species CUB of protein coding genes is positively correlated with expression level and degree of evolutionary conservation. There is mounting experimental evidence that CUB is due in part to selection for translational efficiency and/or accuracy, i.e., translational selection. However, there is a paucity of experimental data on whether and how CUB acts in trans - does the usage of preferred codons in a highly expressed gene affect the translation of other genes by freeing up more ribosomes, thereby increasing their availability to translate all mRNA transcripts in the cell? We investigated this question by creating two extreme versions of the highly expressed Escherichia coli β-lactamase (bla) gene, one comprised almost entirely of unpreferred codons, and a second comprised almost entirely of preferred codons. We monitored the fitness effects of these synonymous mutations over hundreds of generations in two selective environments that allowed us to disentangle translational effects acting in cis from those acting in trans. In a selective environment for maximizing translational efficiency in trans of a gene (tetA) encoding a tetracycline resistance protein, unpreferred synonymous mutations had a negative impact on long-term fitness, whereas preferred mutations had a positive impact on long-term fitness, providing strong experimental evidence for a pleiotropic effect of translational selection.

Protein production in Escherichia coli is guided by the trade-off between intracellular substrate availability and energy cost

Background

In vivo protein formation is a crucial part of cellular life. The process needs to adapt to growth conditions and is exploited for the production of technical and pharmaceutical proteins in microbes such as Escherichia coli. Accordingly, the elucidation of basic regulatory mechanisms controlling the in vivo translation machinery is of primary interest, not only to improve heterologous protein production but also to elucidate fundamental regulation regimens of cellular growth.

Results

The current modeling analysis elucidates the impact of diffusion for the stochastic supply of crucial substrates such as the elongation factor EFTu, and tRNA species, all regarded as key elements for ensuring optimum transcriptional elongation. Together with the consideration of cellular ribosome numbers, their impact on the proper functioning of the translation machinery was investigated under different in vivo and in vitro conditions and utilizing the formation of non-native GFP and native EFTu as target proteins. The results show that translational elongation was diffusion limited. However, this effect was much more pronounced for the translation of non-native proteins than for the formation of codon-optimized native proteins.

Conclusions

Cellular ATP requirements constrain the options of improving protein production. In the case of non-native protein sequences, an optimized tRNA supply may be the most economical solution, as cells necessarily have to invest in ATP-costly ribosome synthesis to boost translation and increase growth rates.

Design of Experiments Methodology to Build a Multifactorial Statistical Model Describing the Metabolic Interactions of Alcohol Dehydrogenase Isozymes in the Ethanol Biosynthetic Pathway of the Yeast Saccharomyces cerevisiae

Multifactorial approaches can quickly and efficiently model complex, interacting natural or engineered biological systems in a way that traditional one-factor-at-a-time experimentation can fail to do. We applied a Design of Experiments (DOE) approach to model ethanol biosynthesis in yeast, which is well-understood and genetically tractable, yet complex. Six alcohol dehydrogenase (ADH) isozymes catalyze ethanol synthesis, differing in their transcriptional and post-translational regulation, subcellular localization, and enzyme kinetics. We generated a combinatorial library of all ADH gene deletions and measured the impact of gene deletion(s) and environmental context on ethanol production of a subset of this library. The data were used to build a statistical model that described known behaviors of ADH isozymes and identified novel interactions. Importantly, the model described features of ADH metabolic behavior without explicit a priori knowledge. The method is therefore highly suited to understanding and optimizing metabolic pathways in less well-understood systems.

Genetic control of ColE1 plasmid stability that is independent of plasmid copy number regulation

ColE1-like plasmid vectors are widely used for expression of recombinant genes in E. coli. For these vectors, segregation of individual plasmids into daughter cells during cell division appears to be random, making them susceptible to loss over time when no mechanisms ensuring their maintenance are present. Here we use the plasmid pGFPuv in a recA relA strain as a sensitized model to study factors affecting plasmid stability in the context of recombinant gene expression. We find that in this model, plasmid stability can be restored by two types of genetic modifications to the plasmid origin of replication (ori) sequence: point mutations and a novel 269 nt duplication at the 5' end of the plasmid ori, which we named DAS (duplicated anti-sense) ori. Combinations of these modifications produce a range of copy numbers and of levels of recombinant expression. In direct contradiction with the classic random distribution model, we find no correlation between increased plasmid copy number and increased plasmid stability. Increased stability cannot be explained by reduced levels of recombinant gene expression either. Our observations would be more compatible with a hybrid clustered and free-distribution model, which has been recently proposed based on detection of individual plasmids in vivo using super-resolution fluorescence microscopy. This work suggests a role for the plasmid ori in the control of segregation of ColE1 plasmids that is distinct from replication initiation, opening the door for the genetic regulation of plasmid stability as a strategy aimed at enhancing large-scale recombinant gene expression or bioremediation.

Accessibility of the Shine-Dalgarno Sequence Dictates N-Terminal Codon Bias in E. coli

Despite considerable efforts, no physical mechanism has been shown to explain N-terminal codon bias in prokaryotic genomes. Using a systematic study of synonymous substitutions in two endogenous E. coli genes, we show that interactions between the coding region and the upstream Shine-Dalgarno (SD) sequence modulate the efficiency of translation initiation, affecting both intracellular mRNA and protein levels due to the inherent coupling of transcription and translation in E. coli. We further demonstrate that far-downstream mutations can also modulate mRNA levels by occluding the SD sequence through the formation of non-equilibrium secondary structures. By contrast, a non-endogenous RNA polymerase that decouples transcription and translation largely alleviates the effects of synonymous substitutions on mRNA levels. Finally, a complementary statistical analysis of the E. coli genome specifically implicates avoidance of intra-molecular base pairing with the SD sequence. Our results provide general physical insights into the coding-level features that optimize protein expression in prokaryotes.