Computational codon optimization of synthetic gene for protein expression

Differentially used codons among essential genes in bacteria identified by machine learning-based analysis

Codon usage bias (CUB), the uneven usage of synonymous codons encoding the same amino acid, differs among genes within and across bacteria genomes. CUB is known to be influenced by gene expression and accordingly, CUB differs between the high-expression and low-expression genes in several bacteria. In this article, we have extended codon usage study considering gene essentiality as a feature. Using machine learning (ML) based approaches, we have analysed Relative Synonymous Codon Usage (RSCU) values between essential and non-essential genes in Escherichia coli and thirty-four other bacterial genomes whose gene essentiality features were available in public databases. We observed significant differences in codon usage patterns between essential and non-essential genes for majority of the bacterial genomes and accordingly, ML based classifiers achieved high area under curve (AUC) scores, with a minimum score of 70.0 across twenty-eight organisms. Further, importance of the codons towards classifying genes found to differ among the codons in each genome. Arg codon CGT and Gly codon GGT were observed to be the most preferred codons among essential genes in Escherichia coli. Interestingly, some of the codons like CGT, ATA, GGT and GGG observed to be contributing consistently towards classifying essential genes across thirty-five bacteria genomes studied. In other hand, codons TGY and CAY encoding amino acids Cys and His respectively were among the least contributing codons towards classification among all these bacteria. This study demonstrates the gene essentiality based differences in synonymous codon usage in bacteria genomes and presents a common codon usage pattern across bacteria.

Fusion proteins development strategies and their role as cancer therapeutic agents

Cancer continues to be leading cause of morbidity and mortality despite decades of research and advancement in chemotherapy. Most tumors can be reduced via standard oncology treatments, such as chemotherapy, radiotherapy, and surgical resection, and they frequently recur. Significant progress has been made since targeted cancer therapy inception in creation of medications that exhibit improved tumor-selective action. Particularly in preclinical and clinical investigations, fusion proteins have shown strong activity and improved treatment outcomes for a number of human cancers. Synergistically combining many proteins into one complex allows the creation of synthetic fusion proteins with enhanced characteristics or new capabilities. Signal transduction pathways are important for onset, development, and spread of cancer. As result, signaling molecules are desirable targets for cancer therapies, and significant effort has been made into developing fusion proteins that would act as inhibitors of these pathways. A wide range of biotechnological and medicinal applications are made possible by fusion of protein domains that improves bioactivities or creates new functional combinations. Such proteins may function as immune effectors cell recruiters to tumors or as decoy receptors for various ligands. In this review article, we have outlined the standard methods for creating fusion proteins and covered the applications of fusion proteins in treatment of cancer. This article also highlights the role of fusion proteins in targeting the signaling pathways involved in cancer for effective treatment.

Gene recoding by synonymous mutations creates promiscuous intragenic transcription initiation in mycobacteria

IMPORTANCE

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, one of the deadliest infectious diseases worldwide. Previous studies have established that synonymous recoding to introduce rare codon pairings can attenuate viral pathogens. We hypothesized that non-optimal codon pairing could be an effective strategy for attenuating gene expression to create a live vaccine for Mtb. We instead discovered that these synonymous changes enabled the transcription of functional mRNA that initiated in the middle of the open reading frame and from which many smaller protein products were expressed. To our knowledge, this is one of the first reports that synonymous recoding of a gene in any organism can create or induce intragenic transcription start sites.

Gene recoding by synonymous mutations creates promiscuous intragenic transcription initiation in mycobacteria

Each genome encodes some codons more frequently than their synonyms (codon usage bias), but codons are also arranged more frequently into specific pairs (codon pair bias). Recoding viral genomes and yeast or bacterial genes with non-optimal codon pairs has been shown to decrease gene expression. Gene expression is thus importantly regulated not only by the use of particular codons but by their proper juxtaposition. We therefore hypothesized that non-optimal codon pairing could likewise attenuate Mtb genes. We explored the role of codon pair bias by recoding Mtb genes ( rpoB, mmpL3, ndh ) and assessing their expression in the closely related and tractable model organism M. smegmatis . To our surprise, recoding caused the expression of multiple smaller protein isoforms from all three genes. We confirmed that these smaller proteins were not due to protein degradation, but instead issued from new transcription initiation sites positioned within the open reading frame. New transcripts gave rise to intragenic translation initiation sites, which in turn led to the expression of smaller proteins. We next identified the nucleotide changes associated with these new sites of transcription and translation. Our results demonstrated that apparently benign, synonymous changes can drastically alter gene expression in mycobacteria. More generally, our work expands our understanding of the codon-level parameters that control translation and transcription initiation.

IMPORTANCE

Mycobacterium tuberculosis ( Mtb ) is the causative agent of tuberculosis, one of the deadliest infectious diseases worldwide. Previous studies have established that synonymous recoding to introduce rare codon pairings can attenuate viral pathogens. We hypothesized that non-optimal codon pairing could be an effective strategy for attenuating gene expression to create a live vaccine for Mtb . We instead discovered that these synonymous changes enabled the transcription of functional mRNA that initiated in the middle of the open reading frame and from which many smaller protein products were expressed. To our knowledge, this is the first report that synonymous recoding of a gene in any organism can create or induce intragenic transcription start sites.

Computer-aided genomic data analysis of drug-resistant Neisseria gonorrhoeae for the Identification of alternative therapeutic targets

Neisseria gonorrhoeae is an emerging multidrug resistance pathogen that causes sexually transmitted infections in men and women. The N. gonorrhoeae has demonstrated an emerging antimicrobial resistance against reported antibiotics, hence fetching the attention of researchers to address this problem. The present in-silico study aimed to find putative novel drug and vaccine targets against N. gonorrhoeae infection by the application of bioinformatics approaches. Core genes set of 69 N. gonorrhoeae strains was acquired from complete genome sequences. The essential and non-homologous metabolic pathway proteins of N. gonorrhoeae were identified. Moreover, different bioinformatics databases were used for the downstream analysis. The DrugBank database scanning identified 12 novel drug targets in the prioritized list. They were preferred as drug targets against this bacterium. A viable vaccine is unavailable so far against N. gonorrhoeae infection. In the current study, two outer-membrane proteins were prioritized as vaccine candidates via reverse vaccinology approach. The top lead B and T-cells overlapped epitopes were utilized to generate a chimeric vaccine construct combined with immune-modulating adjuvants, linkers, and PADRE sequences. The top ranked prioritized vaccine construct (V7) showed stable molecular interaction with human immune cell receptors as inferred during the molecular docking and MD simulation analyses. Considerable response for immune cells was interpreted by in-silico immune studies. Additional tentative validation is required to ensure the effectiveness of the prioritized vaccine construct against N. gonorrhoeae infection. The identified proteins can be used for further rational drug and vaccine designing to develop potential therapeutic entities against the multi-drug resistant N. gonorrhoeae.

Nanomedicine for the Delivery of RNA in Cancer

The complexity, and the diversity of the different types of cancers allied to the tendency to form metastasis make treatment efficiency so tricky and often impossible due to the advanced stage of the disease in the diagnosis. In recent years, due to tremendous scientific breakthroughs, we have witnessed exponential growth in the elucidation of mechanisms that underlie carcinogenesis and metastasis. The development of more selective therapies made it possible to improve cancer treatment. Although interdisciplinary research leads to encouraging results, scientists still have a long exploration journey. RNA technology represents a promise as a therapeutic intervention for targeted gene silencing in cancer, and there are already some RNA-based formulations in clinical trials. However, the use of RNA as a therapeutic tool presents severe limitations, mainly related to its low stability and poor cellular uptake. Thus, the use of nanomedicine employing nanoparticles to encapsulate RNA may represent a suitable platform to address the major challenges hampering its therapeutic application. In this review, we have revisited the potential of RNA and RNA-associated therapies to fight cancer, also providing, as support, a general overview of nanoplatforms for RNA delivery.

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

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

Codon pair optimization (CPO): a software tool for synthetic gene design based on codon pair bias to improve the expression of recombinant proteins in Pichia pastoris

Background

Codon optimization is a common method to improve protein expression levels in Pichia pastoris and the current strategy is to replace rare codons with preferred codons to match the codon usage bias. However, codon-pair contexts have a profound effect on translation efficiency by influencing both translational elongation rates and accuracy. Until now, it remains untested whether optimized genes based on codon pair bias results in higher protein expression levels compared to codon usage bias.

Results

In this study, an algorithm based on dynamic programming was introduced to develop codon pair optimization (CPO) which is a software tool to provide simple and efficient codon pair optimization for synthetic gene design in Pichia pastoris. Two reporters (MT1-MMP E2C6 and ADAM17 A9B8 scFvs) were employed to test the effects of codon pair bias and CPO optimization on their protein expression levels. Four variants of MT1-MMP E2C6 and ADAM17 A9B8 for each were generated, one variant with the best codon-pair context, one with the worst codon-pair context, one with unbiased codon-pair context, and another optimized based on codon usage. The expression levels of variants with the worst codon-pair context were almost undetectable by Western blot and the variants with the best codon-pair context were expressed well. The expression levels on MT1-MMP E2C6 and ADAM17 A9B8 were more than five times and seven times higher in the optimized sequences based on codon-pair context compared to that based on codon usage, respectively. The results indicated that the codon-pair context-based codon optimization is more effective in enhancing expression of protein in Pichia pastoris.

Conclusions

Codon-pair context plays an important role on the protein expression in Pichia pastoris. The codon pair optimization (CPO) software developed in this study efficiently improved the protein expression levels of exogenous genes in Pichia pastoris, suggesting gene design based on codon pair bias is an alternative strategy for high expression of recombinant proteins in Pichia pastoris.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-021-01696-y.

mRNA codon optimization with quantum computers

Reverse translation of polypeptide sequences to expressible mRNA constructs is a NP-hard combinatorial optimization problem. Each amino acid in the protein sequence can be represented by as many as six codons, and the process of selecting the combination that maximizes probability of expression is termed codon optimization. This work investigates the potential impact of leveraging quantum computing technology for codon optimization. A Quantum Annealer (QA) is compared to a standard genetic algorithm (GA) programmed with the same objective function. The QA is found to be competitive in identifying optimal solutions. The utility of gate-based systems is also evaluated using a simulator resulting in the finding that while current generations of devices lack the hardware requirements, in terms of both qubit count and connectivity, to solve realistic problems, future generation devices may be highly efficient.

Analysis of 11,430 recombinant protein production experiments reveals that protein yield is tunable by synonymous codon changes of translation initiation sites

Recombinant protein production is a key process in generating proteins of interest in the pharmaceutical industry and biomedical research. However, about 50% of recombinant proteins fail to be expressed in a variety of host cells. Here we show that the accessibility of translation initiation sites modelled using the mRNA base-unpairing across the Boltzmann's ensemble significantly outperforms alternative features. This approach accurately predicts the successes or failures of expression experiments, which utilised Escherichia coli cells to express 11,430 recombinant proteins from over 189 diverse species. On this basis, we develop TIsigner that uses simulated annealing to modify up to the first nine codons of mRNAs with synonymous substitutions. We show that accessibility captures the key propensity beyond the target region (initiation sites in this case), as a modest number of synonymous changes is sufficient to tune the recombinant protein expression levels. We build a stochastic simulation model and show that higher accessibility leads to higher protein production and slower cell growth, supporting the idea of protein cost, where cell growth is constrained by protein circuits during overexpression.

Streptomyces: host for refactoring of diverse bioactive secondary metabolites

Microbial secondary metabolites are intensively explored due to their demands in pharmaceutical, agricultural and food industries. Streptomyces are one of the largest sources of secondary metabolites having diverse applications. In particular, the abundance of secondary metabolites encoding biosynthetic gene clusters and presence of wobble position in Streptomyces strains make it potential candidate as a native or heterologous host for secondary metabolite production including several cryptic gene clusters expression. Here, we have discussed the developments in Streptomyces strains genome mining, its exploration as a suitable host and application of synthetic biology for refactoring genetic systems for developing chassis for enhanced as well as novel secondary metabolites with reduced genome and cleaned background.

Mutation Maker, An Open Source Oligo Design Platform for Protein Engineering

Protein engineering is the discipline of developing useful proteins for applications in research, therapeutic, and industrial processes by modification of naturally occurring proteins or by invention of de novo proteins. Modern protein engineering relies on the ability to rapidly generate and screen diverse libraries of mutant proteins. However, design of mutant libraries is typically hampered by scale and complexity, necessitating development of advanced automation and optimization tools that can improve efficiency and accuracy. At present, automated library design tools are functionally limited or not freely available. To address these issues, we developed Mutation Maker, an open source mutagenic oligo design software for large-scale protein engineering experiments. Mutation Maker is not only specifically tailored to multisite random and directed mutagenesis protocols, but also pioneers bespoke mutagenic oligo design for de novo gene synthesis workflows. Enabled by a novel bundle of orchestrated heuristics, optimization, constraint-satisfaction and backtracking algorithms, Mutation Maker offers a versatile toolbox for gene diversification design at industrial scale. Supported by in silico simulations and compelling experimental validation data, Mutation Maker oligos produce diverse gene libraries at high success rates irrespective of genes or vectors used. Finally, Mutation Maker was created as an extensible platform on the notion that directed evolution techniques will continue to evolve and revolutionize current and future-oriented applications.

Vibrio natriegens as a pET-Compatible Expression Host Complementary to Escherichia coli

Efficient and novel recombinant protein expression systems can further reduce the production cost of enzymes. Vibrio natriegens is the fastest growing free-living bacterium with a doubling time of less than 10 min, which makes it highly attractive as a protein expression host. Here, 196 pET plasmids with different genes of interest (GOIs) were electroporated into the V. natriegens strain VnDX, which carries an integrated T7 RNA polymerase expression cassette. As a result, 65 and 75% of the tested GOIs obtained soluble expression in V. natriegens and Escherichia coli, respectively, 20 GOIs of which showed better expression in the former. Furthermore, we have adapted a consensus "what to try first" protocol for V. natriegens based on Terrific Broth medium. Six sampled GOIs encoding biocatalysts enzymes thus achieved 50-128% higher catalytic efficiency under the optimized expression conditions. Our study demonstrated V. natriegens as a pET-compatible expression host with a spectrum of highly expressed GOIs distinct from E. coli and an easy-to-use consensus protocol, solving the problem that some GOIs cannot be expressed well in E. coli.

Consolidated bioprocessing of raw starch to ethanol by Saccharomyces cerevisiae: Achievements and challenges

Recent advances in amylolytic strain engineering for starch-to-ethanol conversion have provided a platform for the development of raw starch consolidated bioprocessing (CBP) technologies. Several proof-of-concept studies identified improved enzyme combinations, alternative feedstocks and novel host strains for evaluation and application under fermentation conditions. However, further research efforts are required before this technology can be scaled up to an industrial level. In this review, different CBP approaches are defined and discussed, also highlighting the role of auxiliary enzymes for a supplemented CBP process. Various achievements in the development of amylolytic Saccharomyces cerevisiae strains for CBP of raw starch and the remaining challenges that need to be tackled/pursued to bring yeast raw starch CBP to industrial realization, are described. Looking towards the future, it provides potential solutions to develop more cost-effective processes that include cheaper substrates, integration of the 1G and 2G economies and implementing a biorefinery concept where high-value products are also derived from starchy substrates.

Yeast synthetic biology for designed cell factories producing secretory recombinant proteins

Yeasts are prominent hosts for the production of recombinant proteins from industrial enzymes to therapeutic proteins. Particularly, the similarity of protein secretion pathways between these unicellular eukaryotic microorganisms and higher eukaryotic organisms has made them a preferential host to produce secretory recombinant proteins. However, there are several bottlenecks, in terms of quality and quantity, restricting their use as secretory recombinant protein production hosts. In this mini-review, we discuss recent developments in synthetic biology approaches to constructing yeast cell factories endowed with enhanced capacities of protein folding and secretion as well as designed targeted post-translational modification process functions. We focus on the new genetic tools for optimizing secretory protein expression, such as codon-optimized synthetic genes, combinatory synthetic signal peptides and copy number-controllable integration systems, and the advanced cellular engineering strategies, including endoplasmic reticulum and protein trafficking pathway engineering, synthetic glycosylation, and cell wall engineering, for improving the quality and yield of secretory recombinant proteins.

Engineering Biology to Construct Microbial Chassis for the Production of Difficult-to-Express Proteins

A large proportion of the recombinant proteins manufactured today rely on microbe-based expression systems owing to their relatively simple and cost-effective production schemes. However, several issues in microbial protein expression, including formation of insoluble aggregates, low protein yield, and cell death are still highly recursive and tricky to optimize. These obstacles are usually rooted in the metabolic capacity of the expression host, limitation of cellular translational machineries, or genetic instability. To this end, several microbial strains having precisely designed genomes have been suggested as a way around the recurrent problems in recombinant protein expression. Already, a growing number of prokaryotic chassis strains have been genome-streamlined to attain superior cellular fitness, recombinant protein yield, and stability of the exogenous expression pathways. In this review, we outline challenges associated with heterologous protein expression, some examples of microbial chassis engineered for the production of recombinant proteins, and emerging tools to optimize the expression of heterologous proteins. In particular, we discuss the synthetic biology approaches to design and build and test genome-reduced microbial chassis that carry desirable characteristics for heterologous protein expression.

Computational Tools for Discovering and Engineering Natural Product Biosynthetic Pathways

Natural products (NPs), also known as secondary metabolites, are produced in bacteria, fungi, and plants. NPs represent a rich source of antibacterial, antifungal, and anticancer agents. Recent advances in DNA sequencing technologies and bioinformatics unveiled nature's great potential for synthesizing numerous NPs that may confer unprecedented structural and biological features. However, discovering novel bioactive NPs by genome mining remains a challenge. Moreover, even with interesting bioactivity, the low productivity of many NPs significantly limits their practical applications. Here we discuss the progress in developing bioinformatics tools for efficient discovery of bioactive NPs. In addition, we highlight computational methods for optimizing the productivity of NPs of pharmaceutical importance.

A Highly Versatile Expression System for the Production of Multiply Phosphorylated Proteins

Genetic Code Expansion (GCE) can use TAG stop codons to guide site-specific incorporation of phosphoserine (pSer) into proteins. To eliminate prematurely truncated peptides, improve yields, and enhance the production of multiphosphorylated proteins, Release Factor 1 (RF1)-deficient expression hosts were developed, yet these grew slowly and their use was associated with extensive misincorporation of natural amino acids instead of pSer. Here, we merge a healthy RF1-deficient E. coli cell line with a high-efficiency pSer GCE translation system to produce a versatile pSer GCE platform in which only trace misincorporation of natural amino acids is detected even when five phosphoserines were introduced into one protein. Approximately 400 and 200 mg of singly and doubly phosphorylated GFP per liter of culture were obtained. Importantly, the lack of truncated protein permits expression of oligomeric proteins and the use of N-terminal solubility-enhancing proteins to aid phospho-protein expression and purification. To illustrate the enhanced utility of this system, we produce doubly phosphorylated STING (Stimulator of Interferon Genes), as well as triply phosphorylated BAD (Bcl2-associated agonist of cell death) complexed with 14-3-3, in quantity, purity, and homogeneity sufficient for structural biology applications. We anticipate that the facile access to phosphoproteins enabled by this system, which we call pSer-3.1G, will expand studies of the phospho-proteome.

Improved raw starch amylase production by Saccharomyces cerevisiae using codon optimisation strategies

Amylases are used in a variety of industries that have a specific need for alternative enzymes capable of hydrolysing raw starch. Five α-amylase and five glucoamylase-encoding genes were expressed in the Saccharomyces cerevisiae Y294 laboratory strain to select for recombinant strains that best hydrolysed raw corn starch. Gene variants of four amylases were designed using codon optimisation and different secretion signals. The significant difference in activity levels among the gene variants confirms that codon optimisation of fungal genes for expression in S. cerevisiae does not guarantee improved recombinant protein production. The codon-optimised glucoamylase variant from Talaromyces emersonii (temG_Opt) yielded 3.3-fold higher extracellular activity relative to the native temG, whereas the codon-optimised T. emersonii α-amylase (temA_Opt) yielded 1.6-fold more extracellular activity than the native temA. The effect of four terminator sequences was also investigated using temG and temG_Opt as reporter genes, with the ALY2T terminator resulting in a 14% increase in glucoamylase activity relative to the gene cassettes containing the ENO1T terminator. This is the first report of engineered S. cerevisiae strains to express T. emersonii amylase variants, and these enzymes may have potential applications in the industrial conversion of raw starch under fermentation conditions.

Codon optimization significantly enhanced the expression of human 37-kDa iLRP in Escherichia coli

37-kDa immature laminin receptor protein (iLRP), the precursor of 67-kDa laminin receptor protein (LRP), is overexpressed on the surface of most cancer cells and recognized as a universal tumor antigen. The role makes it a potential target for cancer immunotherapy, which has been well-studied. Our study aimed to produce high quality of human iLRP in bacteria so that the needs in research of its clinical application could be met. The powerful system for heterologous protein expression, pET system was used. Two types of DNA sequences encoding the same amino acid sequences were separately cloned into the vector pET30a(+). One of the resulting vectors includes the wild-type iLRP, and other one includes the codon-optimized iLRP. The expression by both genes was then compared in Escherichia coli BL21(DE3). Our results revealed that the performance of codon optimization was crucial for the expression of human iLRP in Escherichia coli. The yield was significantly enhanced up to 300 mg/L of bacterial culture by this approach.

Optimizing assembly and production of native bispecific antibodies by codon de-optimization

When production of bispecific antibodies requires the co-expression and assembly of three or four polypeptide chains, low expression of one chain can significantly limit assembly and yield. κλ bodies, fully human bispecific antibodies with native IgG structure, are composed of a common heavy chain and two different light chains, one kappa and one lambda. No engineering is applied to force pairing of the chains, thus both monospecific and bispecific antibodies are secreted in the supernatant. In this context, stoichiometric expression of the two light chains allows for maximal assembly of the bispecific antibody. In this study, we selected a κλ body with suboptimal characteristics due to low kappa chain expression. Codon optimization to increase expression of the kappa chain did not improve bispecific yield. Surprisingly, progressive introduction of non-optimal codons into the sequence of the lambda chain resulted in lowering its expression for an optimal tuning of the relative distribution of monospecific and bispecific antibodies. This codon de-optimization led to doubling of the κλ body yield. These results indicate that assembly of different proteins into a recombinant complex is an interconnected process and that reducing the expression of one polypeptide can actually increase the overall yield.

Thermostable proteins bioprocesses: The activity of restriction endonuclease-methyltransferase from Thermus thermophilus (RM.TthHB27I) cloned in Escherichia coli is critically affected by the codon composition of the synthetic gene

Obtaining thermostable enzymes (thermozymes) is an important aspect of biotechnology. As thermophiles have adapted their genomes to high temperatures, their cloned genes’ expression in mesophiles is problematic. This is mainly due to their high GC content, which leads to the formation of unfavorable secondary mRNA structures and codon usage in Escherichia coli (E. coli). RM.TthHB27I is a member of a family of bifunctional thermozymes, containing a restriction endonuclease (REase) and a methyltransferase (MTase) in a single polypeptide. Thermus thermophilus HB27 (T. thermophilus) produces low amounts of RM.TthHB27I with a unique DNA cleavage specificity. We have previously cloned the wild type (wt) gene into E. coli, which increased the production of RM.TthHB27I over 100-fold. However, its enzymatic activities were extremely low for an ORF expressed under a T7 promoter. We have designed and cloned a fully synthetic tthHB27IRM gene, using a modified ‘codon randomization’ strategy. Codons with a high GC content and of low occurrence in E. coli were eliminated. We incorporated a stem-loop circuit, devised to negatively control the expression of this highly toxic gene by partially hiding the ribosome-binding site (RBS) and START codon in mRNA secondary structures. Despite having optimized 59% of codons, the amount of produced RM.TthHB27I protein was similar for both recombinant tthHB27IRM gene variants. Moreover, the recombinant wt RM.TthHB27I is very unstable, while the RM.TthHB27I resulting from the expression of the synthetic gene exhibited enzymatic activities and stability equal to the native thermozyme isolated from T. thermophilus. Thus, we have developed an efficient purification protocol using the synthetic tthHB27IRM gene variant only. This suggests the effect of co-translational folding kinetics, possibly affected by the frequency of translational errors. The availability of active RM.TthHB27I is of practical importance in molecular biotechnology, extending the palette of available REase specificities.

Predicting synonymous codon usage and optimizing the heterologous gene for expression in E. coli

Of the 20 common amino acids, 18 are encoded by multiple synonymous codons. These synonymous codons are not redundant; in fact, all of codons contribute substantially to protein expression, structure and function. In this study, the codon usage pattern of genes in the E. coli was learned from the sequenced genomes of E. coli. A machine learning based method, Presyncodon was proposed to predict synonymous codon selection in E. coli based on the learned codon usage patterns of the residue in the context of the specific fragment. The predicting results indicate that Presycoden could be used to predict synonymous codon selection of the gene in the E. coli with the high accuracy. Two reporter genes (egfp and mApple) were designed with a combination of low- and high-frequency-usage codons by the method. The fluorescence intensity of eGFP and mApple expressed by the (egfp and mApple) designed by this method was about 2.3- or 1.7- folds greater than that from the genes with only high-frequency-usage codons in E. coli. Therefore, both low- and high-frequency-usage codons make positive contributions to the functional expression of the heterologous proteins. This method could be used to design synthetic genes for heterologous gene expression in biotechnology.

Assessment and optimization of Theileria parva sporozoite full-length p67 antigen expression in mammalian cells

Delivery of various forms of recombinant Theileria parva sporozoite antigen (p67) has been shown to elicit antibody responses in cattle capable of providing protection against East Coast fever, the clinical disease caused by T. parva. Previous formulations of full-length and shorter recombinant versions of p67 derived from bacteria, insect, and mammalian cell systems are expressed in non-native and highly unstable forms. The stable expression of full-length recombinant p67 in mammalian cells has never been described and has remained especially elusive. In this study, p67 was expressed in human-derived cells as a full-length, membrane-linked protein and as a secreted form by omission of the putative transmembrane domain. The recombinant protein expressed in this system yielded primarily two products based on Western immunoblot analysis, including one at the expected size of 67 kDa, and one with a higher than expected molecular weight. Through treatment with PNGase F, our data indicate that the larger product of this mammalian cell-expressed recombinant p67 cannot be attributed to glycosylation. By increasing the denaturing conditions, we determined that the larger sized mammalian cell-expressed recombinant p67 product is likely a dimeric aggregate of the protein. Both forms of this recombinant p67 reacted with a monoclonal antibody to the p67 molecule, which reacts with the native sporozoite. Additionally, through this work we developed multiple mammalian cell lines, including both human and bovine-derived cell lines, transduced by a lentiviral vector, that are constitutively able to express a stable, secreted form of p67 for use in immunization, diagnostics, or in vitro assays. The recombinant p67 developed in this system is immunogenic in goats and cattle based on ELISA and flow cytometric analysis. The development of a mammalian cell system that expresses full-length p67 in a stable form as described here is expected to optimize p67-based immunization.

East Coast fever, caused by the tick-borne protozoan parasite Theileria parva, is a disease that results in significant bovine morbidity, mortality, and production losses in regions of sub-Saharan Africa. Susceptible cattle develop clinical signs within a 7–14 days of exposure, which often progress to severe pulmonary edema and death. Control of East Coast fever in affected regions of Africa is largely prohibited by the lack of an affordable and efficacious vaccine. Furthermore, pastoralist farmers in affected regions of Africa often lack resources to prevent losses due to East Coast fever, so these production losses play a significant role in food security and protein availability. Experimental immunization of cattle with a recombinant T. parva-derived antigen, p67, has shown promise in preventing East Coast fever, but this antigen is extremely difficult to produce in full-length in sufficient quantities, and results of immunization studies using truncated recombinant p67 products are highly inconsistent. In this study, p67 antigen production was optimized and produced for use in future immunization studies. Optimization of p67-based immunization strategies is an important step forward in the development of a sustainable, next-generation vaccine against T. parva, which is urgently needed to minimize losses associated with East Coast fever.

Synthetic Gene Design Using Codon Optimization On-Line (COOL)

Codon optimization has been widely used for designing native or synthetic genes to enhance their expression in heterologous host organisms. We recently developed Codon Optimization On-Line (COOL) which is a web-based tool to provide multi-objective codon optimization functionality for synthetic gene design. COOL provides a simple and flexible interface for customizing codon optimization based on several design parameters such as individual codon usage, codon pairing, and codon adaptation index. User-defined sequences can also be compared against the COOL optimized ones to show the extent by which the user's sequences can be evaluated and further improved. The utility of COOL is demonstrated via a case study where the codon optimized sequence of an invertase enzyme is generated for the enhanced expression in E. coli.

Codon optimization of Saccharomyces cerevisiae mating factor alpha prepro-leader to improve recombinant protein production in Pichia pastoris

OBJECTIVES

To evaluate different codon optimization parameters on the Saccharomyces cerevisiae-derived mating factor α prepro-leader sequence (MFLS) to improve Candida antarctica lipase B (CAL-B) secretory production in Pichia pastoris.

RESULTS

Codon optimization based on the individual codon usage (ICU) and codon context (CC) design parameters enhanced secretory production of CAL-B to 7 U/ml and 12 U/ml, respectively. Only 3 U/ml was obtained with the wild type sequence while the sequence optimized using both ICU and CC objectives showed intermediate performance of 10 U/ml. These results clearly show that CC is the most relevant parameter for the codon optimization of MFLS in P. pastoris, and there is no synergistic effect achieved by considering both ICU and CC together.

CONCLUSION

The CC optimized MFLS increased secretory protein production of CAL-B in P. pastoris by fourfold.

CodHonEditor: Spreadsheets for Codon Optimization and Editing of Protein Coding Sequences

Gene synthesis is getting more important with the growing availability of low-cost commercial services. The coding sequences are often "optimized" as for the relative synonymous codon usage (RSCU) before synthesis, which is generally included in the commercial services. However, the codon optimization processes are different among different providers and are often hidden from the users. Here, the d'Hondt method, which is widely adopted as a method for determining the number of seats for each party in proportional-representation public elections, is applied to RSCU fitting. This allowed me to make a set of electronic spreadsheets for manual design of protein coding sequences for expression in Escherichia coli, with which users can see the process of codon optimization and can manually edit the codons after the automatic optimization. The spreadsheets may also be useful for molecular biology education.

Multi-omics data driven analysis establishes reference codon biases for synthetic gene design in microbial and mammalian cells

In this study, we analyzed multi-omics data and subsets thereof to establish reference codon usage biases for codon optimization in synthetic gene design. Specifically, publicly available genomic, transcriptomic, proteomic and translatomic data for microbial and mammalian expression hosts, Escherichia coli, Saccharomyces cerevisiae, Pichia pastoris and Chinese hamster ovary (CHO) cells, were compiled to derive their individual codon and codon pair frequencies. Then, host dependent and -omics specific codon biases were generated and compared by principal component analysis and hierarchical clustering. Interestingly, our results indicated the similar codon bias patterns of the highly expressed transcripts, highly abundant proteins, and efficiently translated mRNA in microbial cells, despite the general lack of correlation between mRNA and protein expression levels. However, for CHO cells, the codon bias patterns among various -omics subsets are not distinguishable, forming one cluster. Thus, we further investigated the effect of different input codon biases on codon optimized sequences using the codon context (CC) and individual codon usage (ICU) design parameters, via in silico case study on the expression of human IFNγ sequence in CHO cells. The results supported that CC is more robust design parameter than ICU for improved heterologous gene design.

CDSfold: an algorithm for designing a protein-coding sequence with the most stable secondary structure

Motivation: An important problem in synthetic biology is to design a nucleotide sequence of an mRNA that confers a desirable expression level of a target protein. The secondary structure of protein-coding sequences (CDSs) is one potential factor that could have both positive and negative effects on protein production. To elucidate the role of secondary structure in CDSs, algorithms for manipulating secondary structure should be developed.

Results: We developed an algorithm for designing a CDS with the most stable secondary structure among all possible ones translated into the same protein, and implemented it as the program CDSfold. The algorithm runs the Zuker algorithm under the constraint of a given amino acid sequence. The time and space complexity is O(L3) and O(L2), respectively, where L is the length of the CDS to be designed. Although our algorithm is slower than the original Zuker algorithm, it could design a relatively long (2.7-kb) CDS in approximately 1 h.

Availability and implementation: The CDSfold program is freely available for non-commercial users as stand-alone and web-based software from http://cdsfold.trahed.jp/cdsfold/.

Contacts: terai-goro@aist.go.jp or asai@k.u-tokyo.ac.jp

Supplementary information: Supplementary data are available at Bioinformatics online.

Codon usage and codon context bias in Xanthophyllomyces dendrorhous

Background

Synonymous codons are used differentially in organisms from the three domains of life, a phenomenon referred to as codon usage bias. In addition, codon pair bias, particularly in the 3’ codon context, has also been described in several organisms and is associated with the accuracy and rate of translation. An improved understanding of both types of bias is important for the optimization of heterologous protein expression, particularly in biotechnologically important organisms, such as the yeast Xanthophyllomyces dendrorhous, a promising bioresource for the carotenoid astaxanthin. Using genomic and transcriptomic data, the codon usage and codon context biases of X. dendrorhous open reading frames (ORFs) were analyzed to determine their expression levels, GC% and sequence lengths. X. dendrorhous totiviral ORFs were also included in these analyses.

Results

A total of 1,695 X. dendrorhous ORFs were identified through comparison with sequences in multiple databases, and the intron-exon structures of these sequences were determined. Although there were important expression variations among the ORFs under the studied conditions (different phases of growth and available carbon sources), most of these sequences were highly expressed under at least one of the analyzed conditions. Independent of the culture conditions, the highly expressed genes showed a strong bias in both codon usage and the 3’ context, with a minor association with the GC% and no relationship to the sequence length. The codon usage and codon-pair bias of the totiviral ORFs were highly variable with no similarities to the host ORFs.

Conclusions

There is a direct relation between the level of gene expression and codon usage and 3′ context bias in X. dendrorhous, which is more evident for ORFs that are expressed at the highest levels under the studied conditions. However, there is no direct relation between the totiviral ORF biases and the host ORFs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1493-5) contains supplementary material, which is available to authorized users.

Overcoming the solubility problem in E. coli: available approaches for recombinant protein production

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

Synthetic biology outside the cell: linking computational tools to cell-free systems

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

Developments in the tools and methodologies of synthetic biology

Synthetic biology is principally concerned with the rational design and engineering of biologically based parts, devices, or systems. However, biological systems are generally complex and unpredictable, and are therefore, intrinsically difficult to engineer. In order to address these fundamental challenges, synthetic biology is aiming to unify a “body of knowledge” from several foundational scientific fields, within the context of a set of engineering principles. This shift in perspective is enabling synthetic biologists to address complexity, such that robust biological systems can be designed, assembled, and tested as part of a biological design cycle. The design cycle takes a forward-design approach in which a biological system is specified, modeled, analyzed, assembled, and its functionality tested. At each stage of the design cycle, an expanding repertoire of tools is being developed. In this review, we highlight several of these tools in terms of their applications and benefits to the synthetic biology community.

Synthetic fusion protein design and applications

Synthetic fusion proteins can be designed to achieve improved properties or new functionality by synergistically incorporating multiple proteins into one complex. The fusion of two or more protein domains enhances bioactivities or generates novel functional combinations with a wide range of biotechnological and (bio)pharmaceutical applications. In this review, initially, we summarize the commonly used approaches for constructing fusion proteins. For each approach, the design strategy and desired properties are elaborated with examples of recent studies in the areas of biocatalysts, protein switches and bio-therapeutics. Subsequently, the progress in structural prediction of fusion proteins is presented, which can potentially facilitate the structure-based systematic design of fusion proteins toward identifying the best combinations of fusion partners. Finally, the current challenges and future directions in this field are discussed.

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.

A condition-specific codon optimization approach for improved heterologous gene expression in Saccharomyces cerevisiae

BACKGROUND

Heterologous gene expression is an important tool for synthetic biology that enables metabolic engineering and the production of non-natural biologics in a variety of host organisms. The translational efficiency of heterologous genes can often be improved by optimizing synonymous codon usage to better match the host organism. However, traditional approaches for optimization neglect to take into account many factors known to influence synonymous codon distributions.

RESULTS

Here we define an alternative approach for codon optimization that utilizes systems level information and codon context for the condition under which heterologous genes are being expressed. Furthermore, we utilize a probabilistic algorithm to generate multiple variants of a given gene. We demonstrate improved translational efficiency using this condition-specific codon optimization approach with two heterologous genes, the fluorescent protein-encoding eGFP and the catechol 1,2-dioxygenase gene CatA, expressed in S. cerevisiae. For the latter case, optimization for stationary phase production resulted in nearly 2.9-fold improvements over commercial gene optimization algorithms.

CONCLUSIONS

Codon optimization is now often a standard tool for protein expression, and while a variety of tools and approaches have been developed, they do not guarantee improved performance for all hosts of applications. Here, we suggest an alternative method for condition-specific codon optimization and demonstrate its utility in Saccharomyces cerevisiae as a proof of concept. However, this technique should be applicable to any organism for which gene expression data can be generated and is thus of potential interest for a variety of applications in metabolic and cellular engineering.

Gene and protein sequence optimization for high-level production of fully active and aglycosylated lysostaphin in Pichia pastoris

Lysostaphin represents a promising therapeutic agent for the treatment of staphylococcal infections, in particular those of methicillin-resistant Staphylococcus aureus (MRSA). However, conventional expression systems for the enzyme suffer from various limitations, and there remains a need for an efficient and cost-effective production process to facilitate clinical translation and the development of nonmedical applications. While Pichia pastoris is widely used for high-level production of recombinant proteins, there are two major barriers to the production of lysostaphin in this industrially relevant host: lack of expression from the wild-type lysostaphin gene and aberrant glycosylation of the wild-type protein sequence. The first barrier can be overcome with a synthetic gene incorporating improved codon usage and balanced A+T/G+C content, and the second barrier can be overcome by disrupting an N-linked glycosylation sequon using a broadened choice of mutations that yield aglyscosylated and fully active lysostaphin. The optimized lysostaphin variants could be produced at approximately 500 mg/liter in a small-scale bioreactor, and 50% of that material could be recovered at high purity with a simple 2-step purification. It is anticipated that this novel high-level expression system will bring down one of the major barriers to future development of biomedical, veterinary, and research applications of lysostaphin and its engineered variants.

Modified 'one amino acid-one codon' engineering of high GC content TaqII-coding gene from thermophilic Thermus aquaticus results in radical expression increase

BACKGROUND

An industrial approach to protein production demands maximization of cloned gene expression, balanced with the recombinant host's viability. Expression of toxic genes from thermophiles poses particular difficulties due to high GC content, mRNA secondary structures, rare codon usage and impairing the host's coding plasmid replication.TaqII belongs to a family of bifunctional enzymes, which are a fusion of the restriction endonuclease (REase) and methyltransferase (MTase) activities in a single polypeptide. The family contains thermostable REases with distinct specificities: TspGWI, TaqII, Tth111II/TthHB27I, TspDTI and TsoI and a few enzymes found in mesophiles. While not being isoschizomers, the enzymes exhibit amino acid (aa) sequence homologies, having molecular sizes of ~120 kDa share common modular architecture, resemble Type-I enzymes, cleave DNA 11/9 nt from the recognition sites, their activity is affected by S-adenosylmethionine (SAM).

RESULTS

We describe the taqIIRM gene design, cloning and expression of the prototype TaqII. The enzyme amount in natural hosts is extremely low. To improve expression of the taqIIRM gene in Escherichia coli (E. coli), we designed and cloned a fully synthetic, low GC content, low mRNA secondary structure taqIIRM, codon-optimized gene under a bacteriophage lambda (λ) PR promoter. Codon usage based on a modified 'one amino acid-one codon' strategy, weighted towards low GC content codons, resulted in approximately 10-fold higher expression of the synthetic gene. 718 codons of total 1105 were changed, comprising 65% of the taqIIRM gene. The reason for we choose a less effective strategy rather than a resulting in high expression yields 'codon randomization' strategy, was intentional, sub-optimal TaqII in vivo production, in order to decrease the high 'toxicity' of the REase-MTase protein.

CONCLUSIONS

Recombinant wt and synthetic taqIIRM gene were cloned and expressed in E. coli. The modified 'one amino acid-one codon' method tuned for thermophile-coded genes was applied to obtain overexpression of the 'toxic' taqIIRM gene. The method appears suited for industrial production of thermostable 'toxic' enzymes in E. coli. This novel variant of the method biased toward increasing a gene's AT content may provide economic benefits for industrial applications.

D-Tailor: automated analysis and design of DNA sequences

Motivation: Current advances in DNA synthesis, cloning and sequencing technologies afford high-throughput implementation of artificial sequences into living cells. However, flexible computational tools for multi-objective sequence design are lacking, limiting the potential of these technologies.

Results: We developed DNA-Tailor (D-Tailor), a fully extendable software framework, for property-based design of synthetic DNA sequences. D-Tailor permits the seamless integration of multiple sequence analysis tools into a generic Monte Carlo simulation that evolves sequences toward any combination of rationally defined properties. As proof of principle, we show that D-Tailor is capable of designing sequence libraries comprising all possible combinations among three different sequence properties influencing translation efficiency in Escherichia coli. The capacity to design artificial sequences that systematically sample any given parameter space should support the implementation of more rigorous experimental designs.

Availability: Source code is available for download at https://sourceforge.net/projects/dtailor/

Contact:aparkin@lbl.gov or cambray.guillaume@gmail.com

Supplementary information:Supplementary data are available at Bioinformatics online (D-Tailor Tutorial).

COFACTOR MODIFICATION ANALYSIS: A COMPUTATIONAL FRAMEWORK TO IDENTIFY COFACTOR SPECIFICITY ENGINEERING TARGETS FOR STRAIN IMPROVEMENT

Cofactors, such as NAD(H) and NADP(H), play important roles in energy transfer within the cells by providing the necessary redox carriers for a myriad of metabolic reactions, both anabolic and catabolic. Thus, it is crucial to establish the overall cellular redox balance for achieving the desired cellular physiology. Of several methods to manipulate the intracellular cofactor regeneration rates, altering the cofactor specificity of a particular enzyme is a promising one. However, the identification of relevant enzyme targets for such cofactor specificity engineering (CSE) is often very difficult and labor intensive. Therefore, it is necessary to develop more systematic approaches to find the cofactor engineering targets for strain improvement. Presented herein is a novel mathematical framework, cofactor modification analysis (CMA), developed based on the well-established constraints-based flux analysis, for the systematic identification of suitable CSE targets while exploring the global metabolic effects. The CMA algorithm was applied to E. coli using its genome-scale metabolic model, iJO1366, thereby identifying the growth-coupled cofactor engineering targets for overproducing four of its native products: acetate, formate, ethanol, and lactate, and three non-native products: 1-butanol, 1,4-butanediol, and 1,3-propanediol. Notably, among several target candidates for cofactor engineering, glyceraldehyde-3-phosphate dehydrogenase (GAPD) is the most promising enzyme; its cofactor modification enhanced both the desired product and biomass yields significantly. Finally, given the identified target, we further discussed potential mutational strategies for modifying cofactor specificity of GAPD in E. coli as suggested by in silico protein docking experiments.

Enhanced expression of codon optimized interferon gamma in CHO cells

The human interferon-gamma (IFN-γ) is a potential drug candidate for treating various diseases due to its immunomodulatory properties. The efficient production of this protein can be achieved through a popular industrial host, Chinese hamster ovary (CHO) cells. However, recombinant expression of foreign proteins is typically suboptimal possibly due to the usage of non-native codon patterns within the coding sequence. Therefore, we demonstrated the application of a recently developed codon optimization approach to design synthetic IFN-γ coding sequences for enhanced heterologous expression in CHO cells. For codon optimization, earlier studies suggested to establish the target usage distribution pattern in terms of selected design parameters such as individual codon usage (ICU) and codon context (CC), mainly based on the host's highly expressed genes. However, our RNA-Seq based transcriptome profiling indicated that the ICU and CC distribution patterns of different gene expression classes in CHO cell are relatively similar, unlike other microbial expression hosts, Escherichia coli and Saccharomyces cerevisiae. This finding was further corroborated through the in vivo expression of various ICU and CC optimized IFN-γ in CHO cells. Interestingly, the CC-optimized genes exhibited at least 13-fold increase in expression level compared to the wild-type IFN-γ while a maximum of 10-fold increase was observed for the ICU-optimized genes. Although design criteria based on individual codons, such as ICU, have been widely used for gene optimization, our experimental results suggested that codon context is relatively more effective parameter for improving recombinant IFN-γ expression in CHO cells.