Stepwise optimization of recombinant protein production in Escherichia coli utilizing computational and experimental approaches

Scalable, robust, high-throughput expression & purification of nanobodies enabled by 2-stage dynamic control

Nanobodies are single-domain antibody fragments that have garnered considerable use as diagnostic and therapeutic agents as well as research tools. However, obtaining pure VHHs, like many proteins, can be laborious and inconsistent. High level cytoplasmic expression in E. coli can be challenging due to improper folding and insoluble aggregation caused by reduction of the conserved disulfide bond. We report a systems engineering approach leveraging engineered strains of E. coli, in combination with a two-stage process and simplified downstream purification, enabling improved, robust, soluble cytoplasmic nanobody expression, as well as rapid cell autolysis and purification. This approach relies on the dynamic control over the reduction potential of the cytoplasm, incorporates lysis enzymes for purification, and can also integrate dynamic expression of protein folding catalysts. Collectively, the engineered system results in more robust growth and protein expression, enabling efficient scalable nanobody production, and purification from high throughput microtiter plates, to routine shake flask cultures and larger instrumented bioreactors. We expect this system will expedite VHH development.

Tobacco Plant: A Novel and Promising Heterologous Bioreactor for the Production of Recombinant Bovine Chymosin

The natural source of chymosin, a key enzyme in the dairy industry, is insufficient for rapidly growing cheese industries. Large-scale production of recombinant proteins in heterologous hosts provides an efficient alternative solution. Here, the codon-optimized synthetic prochymosin gene, which has a CAI index of 0.926, was subcloned from a cloning vector (pUC57-bCYM) into the pBI121 vector, resulting in the construct named pBI121-bCYM. CAI ranges from 0 to 1 and higher CAI improves gene expression in heterologous hosts. The overexpression of the prochymosin gene was under the control of constitutive CaMV 35S promoter and NOS terminator and was transferred into the tobacco via A. tumefaciens strain LBA4404. Explant type, regeneration method, inoculation temperature, cell density (OD600) of Agrobacterium for inoculation, and acetosyringone concentration were leaf explants, direct somatic embryogenesis, 19 °C, 0.1, and 100 µM, respectively. The successful integration and expression of the prochymosin gene, along with the bioactivity of recombinant chymosin, were confirmed by PCR, RT-PCR, and milk coagulation assay, respectively. Overall, this study reports the first successful overexpression of the codon-optimized prochymosin form of the bovine chymosin enzyme in the tobacco via indirect transformation. Production of recombinant bovine chymosin in plants can be an easy-to-scale-up, safe, and inexpensive platform.

Challenges in developing cell culture media using machine learning

Microbial and mammalian cells are widely used in the food, pharmaceutical, and medical industries. Developing or optimizing culture media is essential to improve cell culture performance as a critical technology in cell culture engineering. Methodologies for media optimization have been developed to a great extent, such as the approaches of one-factor-at-a-time (OFAT) and response surface methodology (RSM). The present review introduces the emerging machine learning (ML) technology in cell culture engineering by combining high-throughput experimental technologies to develop highly efficient and effective culture media. The commonly used ML algorithms and the successful applications of employing ML in medium optimization are summarized. This review highlights the benefits of ML-assisted medium development and guides the selection of the media optimization method appropriate for various cell culture purposes.

Current state of molecular and metabolic strategies for the improvement of L-asparaginase expression in heterologous systems

Heterologous expression of L-asparaginase (L-ASNase) has become an important area of research due to its clinical and food industry applications. This review provides a comprehensive overview of the molecular and metabolic strategies that can be used to optimize the expression of L-ASNase in heterologous systems. This article describes various approaches that have been employed to increase enzyme production, including the use of molecular tools, strain engineering, and in silico optimization. The review article highlights the critical role that rational design plays in achieving successful heterologous expression and underscores the challenges of large-scale production of L-ASNase, such as inadequate protein folding and the metabolic burden on host cells. Improved gene expression is shown to be achievable through the optimization of codon usage, synthetic promoters, transcription and translation regulation, and host strain improvement, among others. Additionally, this review provides a deep understanding of the enzymatic properties of L-ASNase and how this knowledge has been employed to enhance its properties and production. Finally, future trends in L-ASNase production, including the integration of CRISPR and machine learning tools are discussed. This work serves as a valuable resource for researchers looking to design effective heterologous expression systems for L-ASNase production as well as for enzymes production in general.

Functional expansion of the natural inorganic phosphorus starvation response system in Escherichia coli

Phosphorus, an indispensable nutrient, plays an essential role in cell composition, metabolism, and signal transduction. When inorganic phosphorus (Pi) is scarce, the Pi starvation response in E. coli is activated to increase phosphorus acquisition and drive the cells into a non-growing state to reduce phosphorus consumption. In the six decades of research history, the initiation, output, and shutdown processes of the Pi starvation response have been extensively studied. Simultaneously, Pi starvation has been used in biosensor development, recombinant protein production, and natural product biosynthesis. In this review, we focus on the output process and the applications of the Pi starvation response that have not been summarized before. Meanwhile, based on the current status of mechanistic studies and applications, we propose practical strategies to develop the natural Pi starvation response into a multifunctional and standardized regulatory system in four aspects, including response threshold, temporal expression, intensity range, and bifunctional regulation, which will contribute to its broader application in more fields such as industrial production, medical analysis, and environmental protection.

[Approaches for improving L-asparaginase expression in heterologous systems]

L-asparaginase (EC 3.5.1.1) is one of the most demanded enzymes used in the pharmaceutical industry as a drug and in the food industry to prevent the formation of toxic acrylamide. Researchers aimed to improve specific activity and reduce side effects to create safer and more potent enzyme products. However, protein modifications and heterologous expression remain problematic in the production of asparaginases from different species. Heterologous expression in optimized producer strains is rationally organized; therefore, modified and heterologous protein expression is enhanced, which is the main strategy in the production of asparaginase. This strategy solves several problems: incorrect protein folding, metabolic load on the producer strain and codon misreading, which affects translation and final protein domains, leading to a decrease in catalytic activity. The main approaches developed to improve the heterologous expression of L-asparaginases are considered in this paper.

The Influence of the Nucleotide Composition of Genes and Gene Regulatory Elements on the Efficiency of Protein Expression in Escherichia coli

Recombinant proteins expressed in Escherichia coli are widely used in biochemical research and industrial processes. At the same time, achieving higher protein expression levels and correct protein folding still remains the key problem, since optimization of nutrient media, growth conditions, and methods for induction of protein synthesis do not always lead to the desired result. Often, low protein expression is determined by the sequences of the expressed genes and their regulatory regions. The genetic code is degenerated; 18 out of 20 amino acids are encoded by more than one codon. Choosing between synonymous codons in the coding sequence can significantly affect the level of protein expression and protein folding due to the influence of the gene nucleotide composition on the probability of formation of secondary mRNA structures that affect the ribosome binding at the translation initiation phase, as well as the ribosome movement along the mRNA during elongation, which, in turn, influences the mRNA degradation and the folding of the nascent protein. The nucleotide composition of the mRNA untranslated regions, in particular the promoter and Shine-Dalgarno sequences, also affects the efficiency of mRNA transcription, translation, and degradation. In this review, we describe the genetic principles that determine the efficiency of protein production in Escherichia coli.

In silico characterization of fructosyl peptide oxidase properties from Eupenicillium terrenum

Fructosyl peptide oxidase (FPOX) enzyme from Eupenicillium terrenum has a high potential to be applied as a diagnostic enzyme. The aim of the present study is the characterization of FPOX from E. terrenum using different bioinformatics tools. The computational prediction of the RNA and protein secondary structures of FPOX, solubility profile in Escherichia coli, stability, domains, and functional properties were performed. In the FPOX protein, six motifs were detected. The d-amino acid oxidase motif was found as the most important motif that is a FAD-dependent oxidoreductase. The cysteines including 97, 154, 234, 280, and 360 showed a lower score than -10 that have a low possibility for participitation in the formation of the SS bond. The 56.52% of FPOX amino acids are nonpolar. Random coils are dominant in the FPOX sequence, followed by alpha-helix and extended strand. The fpox gene is capable of generating a stable RNA secondary structure (-423.90 kcal/mol) in E. coli. FPOX has a large number of hydrophobic amino acids. FPOX showed a low solubility in E. coli which has several aggregation-prone sites in its 3-D structure. According to the scores, the best mutation candidate for increasing solubility was the conversion of methionine 302 to arginine. The melting temperature of FPOX based on its amino acid sequence was 55°C to 65°C. The amounts of thermodynamic parameters for the FPOX enzyme were -137.4 kcal/mol, -3.59 kcal/(mol K), and -6.8 kcal/mol for standard folding enthalpy, heat capacity, and folding free energy, respectively. In conclusion, the in silico study of proteins can provide a valuable method for better understanding the protein properties and functions for use in our purposes.

Strategies for efficient production of recombinant proteins in Escherichia coli: alleviating the host burden and enhancing protein activity

Escherichia coli, one of the most efficient expression hosts for recombinant proteins (RPs), is widely used in chemical, medical, food and other industries. However, conventional expression strains are unable to effectively express proteins with complex structures or toxicity. The key to solving this problem is to alleviate the host burden associated with protein overproduction and to enhance the ability to accurately fold and modify RPs at high expression levels. Here, we summarize the recently developed optimization strategies for the high-level production of RPs from the two aspects of host burden and protein activity. The aim is to maximize the ability of researchers to quickly select an appropriate optimization strategy for improving the production of RPs.

Dot-Blotting: A Quick Method for Expression Analysis of Recombinant Proteins

Expressing recombinant proteins in heterologous host cells is a prerequisite for purification and other downstream processes. Cell cultures require a protein expression test to optimize incubation time, temperature, and additives (like chemical inducers) to identify the best growth conditions with maximum recombinant protein yield. However, running SDS-PAGE followed by western blotting is cumbersome and results are not quick. Here, I describe a simple protocol to quickly check the presence of recombinant protein in cell cultures using a dot-blot experiment. The cells can be rapidly lysed and directly spotted on the nitrocellulose membrane. Then, the membrane is incubated with a horseradish peroxidase (HRP) conjugated antibody raised against the affinity tag present on the recombinant protein to confirm the protein expression by chemiluminescence. It takes less than an hour to get results. This method rapidly investigates recombinant protein expression in different cell lines and tests other variables. © 2022 Wiley Periodicals LLC. Basic Protocol 1: Protein expression analysis for eukaryotic systems Basic Protocol 2: Protein expression analysis for bacterial systems.

Maximizing the recovery of the native p28 bacterial peptide with improved activity and maintained solubility and stability in Escherichia coli BL21 (DE3)

p28 is a natural bacterial product, which recently has attracted much attention as an efficient cell penetrating peptide (CPP) and a promising anticancer agent. Considering the interesting biological qualities of p28, maximizing its expression appears to be a prominent priority. The optimization of such bioprocesses might be facilitated by utilizing statistical approaches such as Design of Experiment (DoE). In this study, we aimed to maximize the expression of "biologically active" p28 in Escherichia coli BL21 (DE3) host by harnessing statistical tools and experimental methods. Using Minitab, Plackett-Burman and Box-Behnken Response Surface Methodology (RSM) designs were generated to optimize the conditions for the expression of p28. Each condition was experimentally investigated by assessing the biological activity of the purified p28 in the MCF-7 breast cancer cell line. Seven independent variables were investigated, and three of them including ethanol concentration, OD₆₀₀ of the culture at the time of induction, and the post-induction temperature were demonstrated to significantly affect the p28 expression in E. coli. The cytotoxicity, penetration efficiency, and total process time were measured as dependent variables. The optimized expression conditions were validated experimentally, and the final products were investigated in terms of expression yield, solubility, and stability in vitro. Following the optimization, an 8-fold increase of the concentration of p28 expression was observed. In this study, we suggest an optimized combination of effective factors to produce soluble p28 in the E. coli host, a protocol that results in the production of a significantly high amount of the biologically active peptide with retained solubility and stability.

In silico screening and heterologous expression of soluble dimethyl sulfide monooxygenases of microbial origin in Escherichia coli

Abstract

Sequence-based screening has been widely applied in the discovery of novel microbial enzymes. However, majority of the sequences in the genomic databases were annotated using computational approaches and lacks experimental characterization. Hence, the success in obtaining the functional biocatalysts with improved characteristics requires an efficient screening method that considers a wide array of factors. Recombinant expression of microbial enzymes is often hampered by the undesirable formation of inclusion body. Here, we present a systematic in silico screening method to identify the proteins expressible in soluble form and with the desired biological properties. The screening approach was adopted in the recombinant expression of dimethyl sulfide (DMS) monooxygenase in Escherichia coli. DMS monooxygenase, a two-component enzyme consisting of DmoA and DmoB subunits, was used as a model protein. The success rate of producing soluble and active DmoA is 71% (5 out of 7 genes). Interestingly, the soluble recombinant DmoA enzymes exhibited the NADH:FMN oxidoreductase activity in the absence of DmoB (second subunit), and the cofactor FMN, suggesting that DmoA is also an oxidoreductase. DmoA originated from Janthinobacterium sp. AD80 showed the maximum NADH oxidation activity (maximum reaction rate: 6.6 µM/min; specific activity: 133 µM/min/mg). This novel finding may allow DmoA to be used as an oxidoreductase biocatalyst for various industrial applications. The in silico gene screening methodology established from this study can increase the success rate of producing soluble and functional enzymes while avoiding the laborious trial and error involved in the screening of a large pool of genes available.

Key points

• A systematic gene screening method was demonstrated.

• DmoA is also an oxidoreductase capable of oxidizing NADH and reducing FMN.

• DmoA oxidizes NADH in the absence of external FMN.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00253-022-12008-8.

Response Surface Methodology for Optimization Membrane Disruption Using Thermolysis in Lipase Lk2 and Lk3

Lk2 and Lk3 were thermostable recombinant lipase and highly expressed in Escherichia coli BL21 (DE3). However, Lk2 and Lk3 accumulated as an inclusion body. To further characterize both recombinant lipases, the soluble enzyme must be obtained first. This study aimed to optimize the disruption of the cell membrane in order to obtain soluble and active lipases. The effects of temperature lysis, pH, and SDS concentration on lipolytic activity Lk2 and Lk3 were investigated using a three-factor Box-Behnken design response surface methods. The optimum condition for the temperature variables at 50°C, pH 8, and 0.34% SDS which gave a lipolytic activity of 0.9 U for Lk2. Meanwhile, Lk3 lipolytic activity of 0.9 U obtained at the temperature of 50°C, pH 8, and 0.1% SDS. This result showed efficient one-step membrane disruption methods using thermolysis with addition of a low concentration of detergent at pH 8. The methods used were effective and applicable in the production of active and soluble thermostable recombinant lipase.

PERISCOPE-Opt: Machine learning-based prediction of optimal fermentation conditions and yields of recombinant periplasmic protein expressed in Escherichia coli

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The ensemble model considered both fermentation conditions and protein properties.

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Optimal fermentation conditions and periplasmic recombinant protein yield can be predicted.

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Predictor’s accuracy and Pearson correlation coefficient are 75% and 0.91, respectively.

Optimization of the fermentation process for recombinant protein production (RPP) is often resource-intensive. Machine learning (ML) approaches are helpful in minimizing the experimentations and find vast applications in RPP. However, these ML-based tools primarily focus on features with respect to amino-acid-sequence, ruling out the influence of fermentation process conditions. The present study combines the features derived from fermentation process conditions with that from amino acid-sequence to construct an ML-based model that predicts the maximal protein yields and the corresponding fermentation conditions for the expression of target recombinant protein in the Escherichia coli periplasm. Two sets of XGBoost classifiers were employed in the first stage to classify the expression levels of the target protein as high (>50 mg/L), medium (between 0.5 and 50 mg/L), or low (<0.5 mg/L). The second-stage framework consisted of three regression models involving support vector machines and random forest to predict the expression yields corresponding to each expression-level-class. Independent tests showed that the predictor achieved an overall average accuracy of 75% and a Pearson coefficient correlation of 0.91 for the correctly classified instances. Therefore, our model offers a reliable substitution of numerous trial-and-error experiments to identify the optimal fermentation conditions and yield for RPP. It is also implemented as an open-access webserver, PERISCOPE-Opt (http://periscope-opt.erc.monash.edu).

Media optimization for SHuffle T7 Escherichia coli expressing SUMO-Lispro proinsulin by response surface methodology

BACKGROUND

SHuffle is a suitable Escherichia coli (E. coli) strain for high yield cytoplasmic soluble expression of disulfide-bonded proteins such as Insulin due to its oxidative cytoplasmic condition and the ability to correct the arrangement of disulfide bonds. Lispro is an Insulin analog that is conventionally produced in E. coli as inclusion bodies (IBs) with prolonged production time and low recovery. Here in this study, we aimed to optimize cultivation media composition for high cell density fermentation of SHuffle T7 E. coli expressing soluble Lispro proinsulin fused to SUMO tag (SU-INS construct) to obtain high cell density fermentation.

RESULTS

Factors including carbon and nitrogen sources, salts, metal ions, and pH were screened via Plackett-Burman design for their effectiveness on cell dry weight (CDW) as a measure of cell growth. The most significant variables of the screening experiment were Yeast extract and MgCl₂ concentration, as well as pH. Succeedingly, The Central Composite Design was utilized to further evaluate and optimize the level of significant variables. The Optimized media (OM-I) enhanced biomass by 2.3 fold in the shake flask (2.5 g/L CDW) that reached 6.45 g/L (2.6 fold increase) when applied in batch culture fermentation. The efficacy of OM-I media for soluble expression was confirmed in both shake flask and fermentor.

CONCLUSION

The proposed media was suitable for high cell density fermentation of E. coli SHuffle T7 and was applicable for high yield soluble expression of Lispro proinsulin.

Expression of full and fragment-B of diphtheria toxin genes in Escherichia coli for generating of recombinant diphtheria vaccines

Purpose

In the present study, whole diphtheria toxin (dt) and fragment B (dtb) genes from Corynebacterium diphtheriae Park William were cloned into Escherichia coli, the purified expressed proteins were evaluated for ultimately using as a candidate vaccine.

Materials and Methods

The dt and dtb genes were isolated from bacterial strain ATCC (American Type Culture Collection) no. 13812. Plasmid pET29a+ was extracted by DNA-spin TM plasmid purification kit where genes were inserted using BamHI and HindIII-HF. Cloned pET29a+dt and pET29a+dtb plasmids were transformed into E. coli BL21(DE3)PlysS as expression host. The identity of the sequences was validated by blasting the sequence (BLASTn) against all the reported nucleotide sequences in the NCBI (National Center for Biotechnology Information) GenBank. Production of proteins in high yield by different types and parameters of fermentation to determine optimal conditions. Lastly, the purified concentrated rdtx and rdtb were injected to BALB/c mice and antibody titers were detected.

Results

The genetic transformation of E. coli DH5α and E. coli BL21 with the pET-29a(+) carrying the dt and dtb genes was confirmed by colony polymerase chain reaction assay and were positive to grow on Luria-Bertani/kanamycin medium. The open reading frame of dt and dtb sequences consisted of 1,600 bp and 1,000 bp, were found to be 100% identical to dt and dtb sequence of C. diphtheriae (accession number KX702999.1 and KX702993.1) respectively. The optimal condition for high cell density is fed-batch fermentation production to express the rdtx and rdtb at 280 and 240 Lf/mL, dissolved oxygen was about 24% and 22% and the dry cell weight of bacteria was 2.41 g/L and 2.18 g/L, respectively.

Conclusion

This study concluded with success in preparing genetically modified two strains for the production of a diphtheria vaccine, and to reach ideal production conditions to achieve the highest productivity.

Recombinant Protein Production and Purification of Insoluble Proteins

Proteins are synthesized in heterologous systems because of the impossibility to obtain satisfactory yields from natural sources. The efficient production of soluble and functional recombinant proteins is among the main goals in the biotechnological field. In this context, it is important to point out that under stress conditions, protein folding machinery is saturated and this promotes protein misfolding and, consequently, protein aggregation. Thus, the selection of the optimal expression organism and its growth conditions to minimize the formation of insoluble protein aggregates should be done according to the protein characteristics and downstream requirements. Escherichia coli is the most popular recombinant protein expression system despite the great development achieved so far by eukaryotic expression systems. Besides, other prokaryotic expression systems, such as lactic acid bacteria and psychrophilic bacteria, are gaining interest in this field. However, it is worth mentioning that prokaryotic expression system poses, in many cases, severe restrictions for a successful heterologous protein production. Thus, eukaryotic systems such as mammalian cells, insect cells, yeast, filamentous fungus, and microalgae are an interesting alternative for the production of these difficult-to-express proteins.

Evaluating Five Escherichia coli Derivative Strains as a Platform for Arginine Deiminase Overproduction

AIMS

This study attempted to evaluate the five host strains, including BL21 (DE3), Rosetta (DE3), DH5α, XL1-BLUE, and SHuffle, in terms of arginine deiminase (ADI) production and enzyme activity.

BACKGROUND

Escherichia coli is one of the most preferred host microorganisms for the production of recombinant proteins due to its well-characterized genome, availability of various expression vectors, and host strains. Choosing a proper host strain for the overproduction of a desired recombinant protein is very important because of the diversity of genetically modified expression strains. Various E. coli cells have been examined in different patent applications.

METHOD

ADI was chosen as a bacterial enzyme that degrades L-arginine. It is effective in the treatment of some types of human cancers like melanoma and hepatocellular carcinoma (HCC), which are arginine-auxotrophic. Five mentioned E. coli strains were cultivated. The pET-3a was used as the expression vector. The competent E. coli cells were obtained through the CaCl2 method. It was then transformed with the construct of pET3a-ADI using the heat shock strategy. The ADI production levels were examined by 10% SDS-PAGE analysis. The ability of host strains for the expression of the requested recombinant protein was compared. The enzymatic activity of the obtained recombinant ADI from each studied strain was assessed by a colorimetric 96-well microtiter plate assay.

RESULT

All the five strains exhibited a significant band at 46 kDa. BL21 (DE3) produced the highest amount of ADI protein, followed by Rosetta (DE3). The following activity assay showed that ADI from BL21 (DE3) and Rosetta (DE3) had the most activity.

CONCLUSION

There are some genetic and metabolic differences among the various E. coli strains, leading to differences in the amount of recombinant protein production. The results of this study can be used for the efficacy evaluation of the five studied strains for the production of similar pharmaceutical enzymes. The strains also could be analyzed in terms of proteomics.

Statistical Design of Experiments for Synthetic Biology

The design and optimization of biological systems is an inherently complex undertaking that requires careful balancing of myriad synergistic and antagonistic variables. However, despite this complexity, much synthetic biology research is predicated on One Factor at A Time (OFAT) experimentation; the genetic and environmental variables affecting the activity of a system of interest are sequentially altered while all other variables are held constant. Beyond being time and resource intensive, OFAT experimentation crucially ignores the effect of interactions between factors. Given the ubiquity of interacting genetic and environmental factors in biology this failure to account for interaction effects in OFAT experimentation can result in the development of suboptimal systems. To address these limitations, an increasing number of studies have turned to Design of Experiments (DoE), a suite of methods that enable efficient, systematic exploration and exploitation of complex design spaces. This review provides an overview of DoE for synthetic biologists. Key concepts and commonly used experimental designs are introduced, and we discuss the advantages of DoE as compared to OFAT experimentation. We dissect the applicability of DoE in the context of synthetic biology and review studies which have successfully employed these methods, illustrating the potential of statistical experimental design to guide the design, characterization, and optimization of biological protocols, pathways, and processes.