The Synthetic Gene Designer: a flexible web platform to explore sequence manipulation for heterologous expression

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.

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.

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.

mRNA Treatment Rescues Niemann-Pick Disease Type C1 in Patient Fibroblasts

Messenger RNA (mRNA) holds great potential as a disease-modifying treatment for a wide array of monogenic disorders. Niemann-Pick disease type C1 (NP-C1) is an ultrarare monogenic disease that arises due to loss-of-function mutations in the NPC1 gene, resulting in the entrapment of unesterified cholesterol in the lysosomes of affected cells and a subsequent reduction in their capacity for cholesterol esterification. This causes severe damage to various organs including the brain, liver, and spleen. In this work, we describe the use of NPC1-encoded mRNA to rescue the protein insufficiency and pathogenic phenotype caused by biallelic NPC1 mutations in cultured fibroblasts derived from an NP-C1 patient. We first evaluated engineering strategies for the generation of potent mRNAs capable of eliciting high protein expression across multiple cell types. We observed that "GC3" codon optimization, coupled with N1-methylpseudouridine base modification, yielded an mRNA that was approximately 1000-fold more potent than wild-type, unmodified mRNA in a luciferase reporter assay and consistently superior to other mRNA variants. Our data suggest that the improved expression associated with this design strategy was due in large part to the increased secondary structure of the designed mRNAs. Both codon optimization and base modification appear to contribute to increased secondary structure. Applying these principles to the engineering of NPC1-encoded mRNA, we observed a normalization in NPC1 protein levels after mRNA treatment, as well as a rescue of the mutant phenotype. Specifically, mRNA treatment restored the cholesterol esterification capacity of patient cells to wild-type levels and induced a significant reduction in both unesterified cholesterol levels (>57% reduction compared to Lipofectamine-treated control in a cholesterol esterification assay) and lysosome size (157 μm² reduction compared to Lipofectamine-treated control). These findings show that engineered mRNA can correct the deficit caused by NPC1 mutations. More broadly, they also serve to further validate the potential of this technology to correct diseases associated with loss-of-function mutations in genes coding for large, complex, intracellular proteins.

iCodon customizes gene expression based on the codon composition

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

Optimal Design of Synthetic DNA Sequences Without Unwanted Binding Sites

Synthesizing DNA molecules by design has become an essential tool in molecular biology and is expected to become ubiquitous in the coming decade. Successful design of a synthetic DNA molecule often requires satisfying multiple objectives, some of which may conflict with others. One particularly important objective is the elimination of unwanted protein binding sites, which may interfere with the desired function of the synthesized molecule. While most design tools offer this fundamental capability, they do not follow a systematic approach that guarantees elimination of all unwanted sites whenever a feasible solution exists. Furthermore, the algorithms these tools use (when published) are often quite naive and inefficient. We present a formal description of the binding site elimination problem and suggest several efficient algorithms that eliminate unwanted patterns with minimum interference to the desired function of the synthesized sequence. These algorithms are simple, efficient, and flexible and, therefore, can be easily incorporated in all existing DNA design tools, enhancing their design capabilities.

Evolution and host adaptability of plant RNA viruses: Research insights on compositional biases

During recent decades, many new emerging or re-emerging RNA viruses have been found in plants through the development of deep-sequencing technology and big data analysis. These findings largely changed our understanding of the origin, evolution and host range of plant RNA viruses. There is evidence that their genetic composition originates from viruses, and host populations play a key role in the evolution and host adaptability of plant RNA viruses. In this mini-review, we describe the state of our understanding of the evolution of plant RNA viruses in view of compositional biases and explore how they adapt to the host. It appears that adenine rich (A-rich) coding sequences, low CpG and UpA dinucleotide frequencies and lower codon usage patterns were found in the vast majority of plant RNA viruses. The codon usage pattern of plant RNA viruses was influenced by both natural selection and mutation pressure, and natural selection mostly from hosts was the dominant factor. The codon adaptation analyses support that plant RNA viruses probably evolved a dynamic balance between codon adaptation and deoptimization to maintain efficient replication cycles in multiple hosts with various codon usage patterns. In the future, additional combinations of computational and experimental analyses of the nucleotide composition and codon usage of plant RNA viruses should be addressed.

Tailoring Codon Usage to the Underlying Biology for Protein Expression Optimization

For heterologous gene expression, codon optimization is required to enhance the quality and quantity of the protein product. Recently, we introduced the software tool OCTOPOS. This sequence optimizer combines a detailed mechanistic mathematical modeling of in vivo protein synthesis with a state-of-the-art machine learning algorithm to find the sequence that best serves a user's needs. Here, we briefly describe the algorithm and its implementation as well as its application in practice using OCTOPOS.

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.

Optimizing the dynamics of protein expression

Heterologously expressed genes require adaptation to the host organism to ensure adequate levels of protein synthesis, which is typically approached by replacing codons by the target organism’s preferred codons. In view of frequently encountered suboptimal outcomes we introduce the codon-specific elongation model (COSEM) as an alternative concept. COSEM simulates ribosome dynamics during mRNA translation and informs about protein synthesis rates per mRNA in an organism- and context-dependent way. Protein synthesis rates from COSEM are integrated with further relevant covariates such as translation accuracy into a protein expression score that we use for codon optimization. The scoring algorithm further enables fine-tuning of protein expression including deoptimization and is implemented in the software OCTOPOS. The protein expression score produces competitive predictions on proteomic data from prokaryotic, eukaryotic, and human expression systems. In addition, we optimized and tested heterologous expression of manA and ova genes in Salmonella enterica serovar Typhimurium. Superiority over standard methodology was demonstrated by a threefold increase in protein yield compared to wildtype and commercially optimized sequences.

Design Automation in Synthetic Biology

Design automation refers to a category of software tools for designing systems that work together in a workflow for designing, building, testing, and analyzing systems with a target behavior. In synthetic biology, these tools are called bio-design automation (BDA) tools. In this review, we discuss the BDA tools areas-specify, design, build, test, and learn-and introduce the existing software tools designed to solve problems in these areas. We then detail the functionality of some of these tools and show how they can be used together to create the desired behavior of two types of modern synthetic genetic regulatory networks.

Synthetic gene design-The rationale for codon optimization and implications for molecular pharming in plants

Degeneracy in the genetic code allows multiple codon sequences to encode the same protein. Codon usage bias in genes is the term given to the preferred use of particular synonymous codons. Synonymous codon substitutions had been regarded as "silent" as the primary structure of the protein was not affected; however, it is now accepted that synonymous substitutions can have a significant effect on heterologous protein expression. Codon optimization, the process of altering codons within the gene sequence to improve recombinant protein expression, has become widely practised. Multiple inter-linked factors affecting protein expression need to be taken into consideration when optimizing a gene sequence. Over the years, various computer programmes have been developed to aid in the gene sequence optimization process. However, as the rulebook for altering codon usage to affect protein expression is still not completely understood, it is difficult to predict which strategy, if any, will design the "optimal" gene sequence. In this review, codon usage bias and factors affecting codon selection will be discussed and the evidence for codon optimization impact will be reviewed for recombinant protein expression using plants as a case study. These developments will be relevant to all recombinant expression systems; however, molecular pharming in plants is an area which has consistently encountered difficulties with low levels of recombinant protein expression, and should benefit from an evidence based rational approach to synthetic gene design. Biotechnol. Bioeng. 2017;114: 492-502. © 2016 Wiley Periodicals, Inc.

Recombinant production, purification and characterization of vessel dilator in E. coli

Vessel dilator is a 3.9-KDa potent anticancer peptide and a valuable candidate in the treatment of conditions such as congestive heart failure and acute renal failure amongst others. Here we report the recombinant production of vessel dilator in Escherichia coli. Three different synthetic ORF's dubbed VDI, VDII and VDIII, each encoding a trimmer of the vessel dilator peptide attached to a His tag sequence at their C- terminal, were synthesized and placed in pET21c expression vectors. The highest yield, following expression in E. coli BL21 (DE3), was recorded with VDII that carried the shortest fusion partner. Subsequent to the initial capture of the fusion protein by a Ni affinity column, the vessel dilator monomers were cleaved by trypsin treatment, and further purified to at least 90% homogeneity by anion exchange chromatography. De-novo sequencing and in vivo anticancer activity tests were used to verify the peptide sequence and its biological activity, respectively. The final yield was estimated to be approximately 15 mg of the purified vessel dilator per gram wet weight of the bacterial cells.

Design, Construction and Cloning of Truncated ORF2 and tPAsp-PADRE-Truncated ORF2 Gene Cassette From Hepatitis E Virus in the pVAX1 Expression Vector

BACKGROUND

Hepatitis E Virus (HEV) is the causative agent of enterically transmitted acute hepatitis and has high mortality rate of up to 30% among pregnant women. Therefore, development of a novel vaccine is a desirable goal.

OBJECTIVES

The aim of this study was to construct tPAsp-PADRE-truncated open reading frame 2 (ORF2) and truncated ORF2 DNA plasmid, which can assist future studies with the preparation of an effective vaccine against Hepatitis E Virus.

MATERIALS AND METHODS

A synthetic codon-optimized gene cassette encoding tPAsp-PADRE-truncated ORF2 protein was designed, constructed and analyzed by some bioinformatics software. Furthermore, a codon-optimized truncated ORF2 gene was amplified by the polymerase chain reaction (PCR), with a specific primer from the previous construct. The constructs were sub-cloned in the pVAX1 expression vector and finally expressed in eukaryotic cells.

RESULTS

Sequence analysis and bioinformatics studies of the codon-optimized gene cassette revealed that codon adaptation index (CAI), GC content, and frequency of optimal codon usage (Fop) value were improved, and performance of the secretory signal was confirmed. Cloning and sub-cloning of the tPAsp-PADRE-truncated ORF2 gene cassette and truncated ORF2 gene were confirmed by colony PCR, restriction enzymes digestion and DNA sequencing of the recombinant plasmids pVAX-tPAsp-PADRE-truncated ORF2 (aa 112-660) and pVAX-truncated ORF2 (aa 112-660). The expression of truncated ORF2 protein in eukaryotic cells was approved by an Immunofluorescence assay (IFA) and the reverse transcriptase polymerase chain reaction (RT-PCR) method.

CONCLUSIONS

The results of this study demonstrated that the tPAsp-PADRE-truncated ORF2 gene cassette and the truncated ORF2 gene in recombinant plasmids are successfully expressed in eukaryotic cells. The immunogenicity of the two recombinant plasmids with different formulations will be evaluated as a novel DNA vaccine in future investigations.

Soluble expression and purification of the recombinant bioactive peptide precursor BPP-1 in Escherichia coli using a cELP-SUMO dual fusion system

A bioactive peptide precursor (BPP-1, 14.3 kDa/115AA), a newly designed polypeptide that may exert a potential antihypertensive effect in vivo, is composed of many different ACE inhibitory peptides and antioxidant peptides tandemly linked according to the restriction sites of gastrointestinal proteases. In this report, we present a novel method to obtain soluble BPP-1 in Escherichia coli using cationic elastin-like polypeptide and SUMO (cELP-SUMO) tags. The cELP-SUMO-tagged fusion protein was expressed in soluble form at 20 °C for 20 h. After purification based on the inverse transition cycling (ITC) method, the purified cELP-SUMO-CFPP fusion protein was subsequently cleaved by a SUMO protease to release the mature BPP-1. After a subsequent simple salt precipitation process, approximately 167.2 mg of recombinant BPP-1 was obtained from 1 l of bacterial culture with at least 92% purity. The molecular mass (Mr) of the recombinant BPP-1 was confirmed by MALDI-TOF MS to equal 14,347. The purified BPP-1 was subjected to simulated gastrointestinal digestion, and the resulting hydrolysates exhibited notable ACE inhibitory and antioxidant activities in vitro. This report provides the first description of the soluble production of a bioactive peptide multimer with potential ACE inhibitory and antioxidant activities in E. coli using a cELP-SUMO tag.

ATGme: Open-source web application for rare codon identification and custom DNA sequence optimization

Background

Codon usage plays a crucial role when recombinant proteins are expressed in different organisms. This is especially the case if the codon usage frequency of the organism of origin and the target host organism differ significantly, for example when a human gene is expressed in E. coli. Therefore, to enable or enhance efficient gene expression it is of great importance to identify rare codons in any given DNA sequence and subsequently mutate these to codons which are more frequently used in the expression host.

Results

We describe an open-source web-based application, ATGme, which can in a first step identify rare and highly rare codons from most organisms, and secondly gives the user the possibility to optimize the sequence.

Conclusions

This application provides a simple user-friendly interface utilizing three optimization strategies: 1. one-click optimization, 2. bulk optimization (by codon-type), 3. individualized custom (codon-by-codon) optimization. ATGme is an open-source application which is freely available at: http://atgme.org

Genome Calligrapher: A Web Tool for Refactoring Bacterial Genome Sequences for de Novo DNA Synthesis

Recent advances in synthetic biology have resulted in an increasing demand for the de novo synthesis of large-scale DNA constructs. Any process improvement that enables fast and cost-effective streamlining of digitized genetic information into fabricable DNA sequences holds great promise to study, mine, and engineer genomes. Here, we present Genome Calligrapher, a computer-aided design web tool intended for whole genome refactoring of bacterial chromosomes for de novo DNA synthesis. By applying a neutral recoding algorithm, Genome Calligrapher optimizes GC content and removes obstructive DNA features known to interfere with the synthesis of double-stranded DNA and the higher order assembly into large DNA constructs. Subsequent bioinformatics analysis revealed that synthesis constraints are prevalent among bacterial genomes. However, a low level of codon replacement is sufficient for refactoring bacterial genomes into easy-to-synthesize DNA sequences. To test the algorithm, 168 kb of synthetic DNA comprising approximately 20 percent of the synthetic essential genome of the cell-cycle bacterium Caulobacter crescentus was streamlined and then ordered from a commercial supplier of low-cost de novo DNA synthesis. The successful assembly into eight 20 kb segments indicates that Genome Calligrapher algorithm can be efficiently used to refactor difficult-to-synthesize DNA. Genome Calligrapher is broadly applicable to recode biosynthetic pathways, DNA sequences, and whole bacterial genomes, thus offering new opportunities to use synthetic biology tools to explore the functionality of microbial diversity. The Genome Calligrapher web tool can be accessed at https://christenlab.ethz.ch/GenomeCalligrapher  .

Decoding mechanisms by which silent codon changes influence protein biogenesis and function

SCOPE

Synonymous codon usage has been a focus of investigation since the discovery of the genetic code and its redundancy. The occurrences of synonymous codons vary between species and within genes of the same genome, known as codon usage bias. Today, bioinformatics and experimental data allow us to compose a global view of the mechanisms by which the redundancy of the genetic code contributes to the complexity of biological systems from affecting survival in prokaryotes, to fine tuning the structure and function of proteins in higher eukaryotes. Studies analyzing the consequences of synonymous codon changes in different organisms have revealed that they impact nucleic acid stability, protein levels, structure and function without altering amino acid sequence. As such, synonymous mutations inevitably contribute to the pathogenesis of complex human diseases. Yet, fundamental questions remain unresolved regarding the impact of silent mutations in human disorders. In the present review we describe developments in this area concentrating on mechanisms by which synonymous mutations may affect protein function and human health.

PURPOSE

This synopsis illustrates the significance of synonymous mutations in disease pathogenesis. We review the different steps of gene expression affected by silent mutations, and assess the benefits and possible harmful effects of codon optimization applied in the development of therapeutic biologics.

PHYSIOLOGICAL AND MEDICAL RELEVANCE

Understanding mechanisms by which synonymous mutations contribute to complex diseases such as cancer, neurodegeneration and genetic disorders, including the limitations of codon-optimized biologics, provides insight concerning interpretation of silent variants and future molecular therapies.

Proposed data model for the next version of the synthetic biology open language

While the first version of the Synthetic Biology Open Language (SBOL) has been adopted by several academic and commercial genetic design automation (GDA) software tools, it only covers a limited number of the requirements for a standardized exchange format for synthetic biology. In particular, SBOL Version 1.1 is capable of representing DNA components and their hierarchical composition via sequence annotations. This proposal revises SBOL Version 1.1, enabling the representation of a wider range of components with and without sequences, including RNA components, protein components, small molecules, and molecular complexes. It also introduces modules to instantiate groups of components on the basis of their shared function and assert molecular interactions between components. By increasing the range of structural and functional descriptions in SBOL and allowing for their composition, the proposed improvements enable SBOL to represent and facilitate the exchange of a broader class of genetic designs.

A critical analysis of codon optimization in human therapeutics

Codon optimization describes gene engineering approaches that use synonymous codon changes to increase protein production. Applications for codon optimization include recombinant protein drugs and nucleic acid therapies, including gene therapy, mRNA therapy, and DNA/RNA vaccines. However, recent reports indicate that codon optimization can affect protein conformation and function, increase immunogenicity, and reduce efficacy. We critically review this subject, identifying additional potential hazards including some unique to nucleic acid therapies. This analysis highlights the evolved complexity of codon usage and challenges the scientific bases for codon optimization. Consequently, codon optimization may not provide the optimal strategy for increasing protein production and may decrease the safety and efficacy of biotech therapeutics. We suggest that the use of this approach is reconsidered, particularly for in vivo applications.

Advances and computational tools towards predictable design in biological engineering

The design process of complex systems in all the fields of engineering requires a set of quantitatively characterized components and a method to predict the output of systems composed by such elements. This strategy relies on the modularity of the used components or the prediction of their context-dependent behaviour, when parts functioning depends on the specific context. Mathematical models usually support the whole process by guiding the selection of parts and by predicting the output of interconnected systems. Such bottom-up design process cannot be trivially adopted for biological systems engineering, since parts function is hard to predict when components are reused in different contexts. This issue and the intrinsic complexity of living systems limit the capability of synthetic biologists to predict the quantitative behaviour of biological systems. The high potential of synthetic biology strongly depends on the capability of mastering this issue. This review discusses the predictability issues of basic biological parts (promoters, ribosome binding sites, coding sequences, transcriptional terminators, and plasmids) when used to engineer simple and complex gene expression systems in Escherichia coli. A comparison between bottom-up and trial-and-error approaches is performed for all the discussed elements and mathematical models supporting the prediction of parts behaviour are illustrated.

Enhanced expression of GCRV VP6 in CIK cells by relative sequence optimization

Efficient expression of target protein is one of strategies for gene therapy or vaccine design. Many studies showed that codon optimization could enhance the expression of target proteins. In this paper, a target sequence of about 1.26 kb encoding the major capsid protein VP6 of grass carp reovirus (GCRV) and an optimized counterpart were synthesized and inserted into vectors for expressing VP6. The final constructs (named as pcDV6G and pcDV6YG) were transfected in Ctenopharyngodon idellus kidney (CIK) cells. The fluorescence analysis and the Western blot results showed that the gene fragment was transfected and expressed in CIK cells successfully. Although the qRT-PCR results showed no difference at the messenger RNA (mRNA) levels between the different versions of vp6 in the indicated stages, the enzyme-linked immunosorbent assay (ELISA) results showed that the protein level of VP6 expressed by pcDV6YG was higher than that by pcDV6G in the indicated hours. Taken together, these results suggest that the enhanced expression of GCRV VP6 in CIK cells by relative sequence optimization may be a good choice for making DNA vaccine against GCRV.

Expression of soluble and active interferon consensus in SUMO fusion expression system in E. coli

Protein production can be improved if methods for soluble protein expression are developed. Interferon consensus (IFN-con) is used to treat hepatitis C. IFN-con has superior activity compared to other clinically used interferon α subtypes. However IFN-con is a challenging protein to produce in a soluble form using an Escherichia coli expression system. Here we describe the expression of soluble and active recombinant IFN-con in E. coli. The IFN-con gene sequence was optimised for expression in E. coli, which was then cloned into the Champion™ pET SUMO expression vector downstream of the SUMO fusion protein and under strong T7lac promoter. The SUMO-IFN-con fusion protein was efficiently expressed using the SHuffle™ E. coli strain and existed in soluble form as 86-88% of the total IFN-con. After removal of the SUMO fusion partner, approximately 50mg of recombinant IFN-con of at least 98% purity (by RP-HPLC) was obtained from a 1L fermentation culture. Using an A549/EMCV antiviral assay, the specific activity of the recombinant IFN-con was determined to be 960×10(6) IU/mg as calculated to NIBSC standard for IFN-con (3×10(5)pfu/mL virus titre). Comparison of the antiviral activity of the produced IFN-con to IFN α-2a showed that IFN-con displays 2.8 times greater activity, which is in good agreement with what has been reported in the literature for pure protein. IFN-con expression in a soluble form from E. coli allowed us to use a simple, two-step purification process to yield highly pure and active IFN-con which is more efficient than obtaining IFN-con from inclusion bodies.

Expression of codon optimized genes in microbial systems: current industrial applications and perspectives

The efficient production of functional proteins in heterologous hosts is one of the major bases of modern biotechnology. Unfortunately, many genes are difficult to express outside their original context. Due to their apparent “silent” nature, synonymous codon substitutions have long been thought to be trivial. In recent years, this dogma has been refuted by evidence that codon replacement can have a significant impact on gene expression levels and protein folding. In the past decade, considerable advances in the speed and cost of gene synthesis have facilitated the complete redesign of entire gene sequences, dramatically improving the likelihood of high protein expression. This technology significantly impacts the economic feasibility of microbial-based biotechnological processes by, for example, increasing the volumetric productivities of recombinant proteins or facilitating the redesign of novel biosynthetic routes for the production of metabolites. This review discusses the current applications of this technology, particularly those regarding the production of small molecules and industrially relevant recombinant enzymes. Suggestions for future research and potential uses are provided as well.

EuGene: maximizing synthetic gene design for heterologous expression

Numerous software applications exist to deal with synthetic gene design, granting the field of heterologous expression a significant support. However, their dispersion requires the access to different tools and online services in order to complete one single project. Analyzing codon usage, calculating codon adaptation index (CAI), aligning orthologs and optimizing genes are just a few examples. A software application, EuGene, was developed for the optimization of multiple gene synthetic design algorithms. In a seamless automatic form, EuGene calculates or retrieves genome data on codon usage (relative synonymous codon usage and CAI), codon context (CPS and codon pair bias), GC content, hidden stop codons, repetitions, deleterious sites, protein primary, secondary and tertiary structures, gene orthologs, species housekeeping genes, performs alignments and identifies genes and genomes. The main function of EuGene is analyzing and redesigning gene sequences using multi-objective optimization techniques that maximize the coding features of the resulting sequence.

AVAILABILITY

EuGene is freely available for non-commercial use, at http://bioinformatics.ua.pt/eugene.

Tobacco etch virus protease retains its activity in various buffers and in the presence of diverse additives

Tobacco etch virus (TEV) protease is widely used to remove tags from recombinant fusion proteins because of its stringent sequence specificity. It is generally accepted that the high concentrations of salts or other special agents in most protein affinity chromatography buffers can affect enzyme activity, including that of TEV protease. Consequently, tedious desalination or the substitution of standard TEV reaction buffer for elution buffer are often needed to ensure TEV protease activity when removing fusion tags after purifying target proteins using affinity chromatography. To address this issue, we used SOE PCR technology to synthesize a TEV protease gene with a codon pattern adapted to the codon usage bias of Escherichia coli, recovered the purified recombinant TEV protease, and examined its activity in various elution buffers commonly used in affinity chromatography as well as the effects of selected additives on its activity. Our results showed that the rTEV protease maintained high activity in all affinity chromatography elution buffers tested and tolerated high concentrations of additives commonly used in protein purification procedures, such as ethylene glycol, EGTA, Triton X-100, Tween-20, NP-40, CHAPS, urea, SDS, guanidine hydrochloride and β-mercaptoethanol. These results will facilitate the use of rTEV protease in removing tags from fusion proteins.

Suitability of different β-galactosidases as reporter enzymes in Bacillus subtilis

The suitability of three β-galactosidases as reporter enzymes for promoter expression analyses was investigated in Bacillus subtilis with respect to various temperature conditions during cultivation and assay procedures. Starting from the hypothesis that proteins derived from diverse habitats have different advantages as reporters at different growth temperatures, the beta-galactosidases from the thermophilic organism Bacillus stearothermophilus, from the mesophilic bacterium Escherichia coli and from the psychrophilic organism Pseudoalteromonas haloplanktis TAE79 were analysed under control of the constitutive B. subtilis lepA promoter. Subsequent expression of the β-galactosidase genes and determination of specific activities was performed at different cultivation and assay temperatures using B. subtilis as host. Surprisingly, the obtained results demonstrated that the highest activities over a broad cultivation temperature range were obtained using the β-galactosidase from the mesophilic bacterium E. coli whereas the enzymes from the thermophilic and psychrophilic bacteria revealed a more restricted usability in terms of cultivation temperature.

Visual gene developer: a fully programmable bioinformatics software for synthetic gene optimization

Background

Direct gene synthesis is becoming more popular owing to decreases in gene synthesis pricing. Compared with using natural genes, gene synthesis provides a good opportunity to optimize gene sequence for specific applications. In order to facilitate gene optimization, we have developed a stand-alone software called Visual Gene Developer.

Results

The software not only provides general functions for gene analysis and optimization along with an interactive user-friendly interface, but also includes unique features such as programming capability, dedicated mRNA secondary structure prediction, artificial neural network modeling, network & multi-threaded computing, and user-accessible programming modules. The software allows a user to analyze and optimize a sequence using main menu functions or specialized module windows. Alternatively, gene optimization can be initiated by designing a gene construct and configuring an optimization strategy. A user can choose several predefined or user-defined algorithms to design a complicated strategy. The software provides expandable functionality as platform software supporting module development using popular script languages such as VBScript and JScript in the software programming environment.

Conclusion

Visual Gene Developer is useful for both researchers who want to quickly analyze and optimize genes, and those who are interested in developing and testing new algorithms in bioinformatics. The software is available for free download at http://www.visualgenedeveloper.net.

Expression of biologically active human insulin-like growth factor 1 in Arabidopsis thaliana seeds via oleosin fusion technology

Novel protein expression in plant-based systems has become an important tool in producing and studying therapeutic proteins. Among many plant-based systems developed so far, oleosin fusion technology is one of the most cost-effective and convenient methods. In this study, an important therapeutic protein, human insulin-like growth factor 1 (hIGF-1), was expressed in Arabidopsis thaliana seeds via this technology. The plant bias codon usage-optimized hIGF-1 gene was fused to the C-terminal of A. thaliana 18.5 kDa oleosin gene, and the fusion gene driven by an oleosin promoter was transferred into A. thaliana ecotype Col-0. The accumulation of oleosin-hIGF-1 fusion protein in transgenic seeds was up to 0.75% of total seed protein (TSP) and the expression level of hIGF-1 was 0.17% of the TSP, which was eight times higher than previously reported using other plant-based hIGF-1 production systems. The biological activity of the hIGF-1 as an oleosin-hIGF-1 fusion protein in vitro was demonstrated by using human SH-SY5Y neuroblastoma cells.

Codon usage: nature's roadmap to expression and folding of proteins

Biomedical and biotechnological research relies on processes leading to the successful expression and production of key biological products. High-quality proteins are required for many purposes, including protein structural and functional studies. Protein expression is the culmination of multistep processes involving regulation at the level of transcription, mRNA turnover, protein translation, and post-translational modifications leading to the formation of a stable product. Although significant strides have been achieved over the past decade, advances toward integrating genomic and proteomic information are essential, and until such time, many target genes and their products may not be fully realized. Thus, the focus of this review is to provide some experimental support and a brief overview of how codon usage bias has evolved relative to regulating gene expression levels.

Codon adaptation-based control of protein expression in C. elegans

We present a method to control protein levels under native genetic regulation in Caenorhabditis elegans by using synthetic genes with adapted codons. We found that the force acting on the spindle in C. elegans embryos was related to the amount of the G-protein regulator GPR-1/2. Codon-adapted versions of any C. elegans gene can be designed using our web tool, C. elegans codon adapter.

Synthetic physiology strategies for adapting tools from nature for genetically targeted control of fast biological processes

The life and operation of cells involve many physiological processes that take place over fast timescales of milliseconds to minutes. Genetically encoded technologies for driving or suppressing specific fast physiological processes in intact cells, perhaps embedded within intact tissues in living organisms, are critical for the ability to understand how these physiological processes contribute to emergent cellular and organismal functions and behaviors. Such "synthetic physiology" tools are often incredibly complex molecular machines, in part because they must operate at high speeds, without causing side effects. We here explore how synthetic physiology molecules can be identified and deployed in cells, and how the physiology of these molecules in cellular contexts can be assessed and optimized. For concreteness, we discuss these methods in the context of the "optogenetic" light-gated ion channels and pumps that we have developed over the past few years as synthetic physiology tools and widely disseminated for use in neuroscience for probing the role of specific brain cell types in neural computations, behaviors, and pathologies. We anticipate that some of the insights revealed here may be of general value for the field of synthetic physiology, as they raise issues that will be of importance for the development and use of high-performance, high-speed, side-effect free physiological control tools in heterologous expression systems.

Functional expression of porcine aminoacylase 1 in E. coli using a codon optimized synthetic gene and molecular chaperones

Efficient recombinant expression of N-acyl-L-aminoacylase 1 from pig kidney (pAcy1) was achieved in the prokaryotic host Escherichia coli. An optimized nucleotide sequence (codon adaptation index 0.95 for E. coli), was cloned into vector pET-52(b) yielding an E. coli-expressible pAcy1 gene. Formation of inclusion bodies was alleviated by co-expression of molecular chaperones resulting in 2.7- and 4.2-fold increased recovery of active pAcy1 using trigger factor or GroEL-GroES, respectively. Facile purification was achieved via StrepTag affinity chromatography. Overall, more than 80 mg highly active pAcy1 (94 U/mg) was obtained per liter of cultivation broth. The protein was analyzed for structural and functional identity, and the performances of further described expression and purification systems for pAcy1 were compared.

Optimizing the codon usage of synthetic gene with QPSO algorithm

Molecular Biology makes it possible to express foreign genes in microorganism, plants and animals. To improve the heterologous expression, it is important that the codon usage of sequence be optimized to make it adaptive to host organism. In this paper, a novel method based on Quantum-behaved Particle Swarm Optimization (QPSO) algorithm is developed to optimize the codon usage of synthetic gene. Compared to the existing probability methods, QPSO is able to generate better results when DNA/RNA sequence length is less than 6Kb which is the commonly used range. While the software or web service based on probability method may not exclude all defined restriction sites when there are many undesired sites in the sequence, our proposed method can remove the undesired site efficiently during the optimization process.

Spirodela (duckweed) as an alternative production system for pharmaceuticals: a case study, aprotinin

Aprotinin is a small serine protease inhibitor used in human health. Spirodela were transformed, via Agrobacterium, with a synthetic gene encoding the mature aprotinin sequence and a signal peptide for secretion which was driven by the CaMV 35S promoter. A total of 25 transgenic Spirodela lines were generated and aprotinin production was confirmed by northern and western blot analyses. Expression levels of up to 3.7% of water soluble proteins were detected in the plant and 0.65 mg/l in the growth medium. In addition, immunoaffinity purification of the protein followed by amino acid sequencing confirmed the correct splicing of the aprotinin produced in Spirodela and secreted into the growth medium.

OPTIMIZER: a web server for optimizing the codon usage of DNA sequences

OPTIMIZER is an on-line application that optimizes the codon usage of a gene to increase its expression level. Three methods of optimization are available: the ‘one amino acid–one codon’ method, a guided random method based on a Monte Carlo algorithm, and a new method designed to maximize the optimization with the fewest changes in the query sequence. One of the main features of OPTIMIZER is that it makes it possible to optimize a DNA sequence using pre-computed codon usage tables from a predicted group of highly expressed genes from more than 150 prokaryotic species under strong translational selection. These groups of highly expressed genes have been predicted using a new iterative algorithm. In addition, users can use, as a reference set, a pre-computed table containing the mean codon usage of ribosomal protein genes and, as a novelty, the tRNA gene-copy numbers. OPTIMIZER is accessible free of charge at http://genomes.urv.es/OPTIMIZER.

SGDB: a database of synthetic genes re-designed for optimizing protein over-expression

Here we present the Synthetic Gene Database (SGDB): a relational database that houses sequences and associated experimental information on synthetic (artificially engineered) genes from all peer-reviewed studies published to date. At present, the database comprises information from more than 200 published experiments. This resource not only provides reference material to guide experimentalists in designing new genes that improve protein expression, but also offers a dataset for analysis by bioinformaticians who seek to test ideas regarding the underlying factors that influence gene expression. The SGDB was built under MySQL database management system. We also offer an XML schema for standardized data description of synthetic genes. Users can access the database at , or batch downloads all information through XML files. Moreover, users may visually compare the coding sequences of a synthetic gene and its natural counterpart with an integrated web tool at , and discuss questions, findings and related information on an associated e-forum at .

Gene Designer: a synthetic biology tool for constructing artificial DNA segments

Background

Direct synthesis of genes is rapidly becoming the most efficient way to make functional genetic constructs and enables applications such as codon optimization, RNAi resistant genes and protein engineering. Here we introduce a software tool that drastically facilitates the design of synthetic genes.

Results

Gene Designer is a stand-alone software for fast and easy design of synthetic DNA segments. Users can easily add, edit and combine genetic elements such as promoters, open reading frames and tags through an intuitive drag-and-drop graphic interface and a hierarchical DNA/Protein object map. Using advanced optimization algorithms, open reading frames within the DNA construct can readily be codon optimized for protein expression in any host organism. Gene Designer also includes features such as a real-time sliding calculator of oligonucleotide annealing temperatures, sequencing primer generator, tools for avoidance or inclusion of restriction sites, and options to maximize or minimize sequence identity to a reference.

Conclusion

Gene Designer is an expandable Synthetic Biology workbench suitable for molecular biologists interested in the de novo creation of genetic constructs.