In silico Analysis of Different Signal Peptides for the Excretory Production of Recombinant NS3-GP96 Fusion Protein in Escherichia coli

Finding Appropriate Signal Peptides for Secretory Production of Recombinant Glucarpidase: An In SilicoMethod

BACKGROUND

Methotrexate (MTX) is a general chemotherapeutic agent utilized to treat a variety of malignancies, woefully, its high doses can cause nephrotoxicity and subsequent defect in the process of MTX excretion. The recombinant form of glucarpidase is produced by engineered E. coli and is a confirmed choice to overcoming this problem.

OBJECTIVE

In the present study, in silico analyses were performed to select suitable SPs for the secretion of recombinant glucarpidase in E. coli.

METHODS

The signal peptide website and UniProt database were employed to collect the SPs and protein sequences. In the next step, SignalP-5.0 helped us to predict the SPs and the position of cleavage sites. Moreover, physicochemical properties and solubility were evaluated using Prot- Param and Protein-sol online software, and finally, ProtCompB was used to predict the final subcellular localization.

RESULTS

Luckily, all SPs could form soluble fusion proteins. At last, it was found that PPB and TIBA could translocate the glucarpidase into the extracellular compartment.

CONCLUSION

This study showed that there are only 2 applicable SPs for the extracellular translocation of glucarpidase. Although the findings were remarkable with high degrees of accuracy and precision based on the utilization of bioinformatics analyses, additional experimental assessments are required to confirm and validate it. Recent patents revealed several inventions related to the clinical aspects of vaccine peptides against human disorders.

In Silico Investigation of Signal Peptide Sequences to Enhance Secretion of CD44 Nanobodies Expressed in Escherichia coli

BACKGROUND

The selection of a suitable signal peptide that can direct recombinant proteins from the cytoplasm to the extracellular space is an important criterion affecting the production of recombinant proteins in Escherichia coli, a widely used host. Nanobodies are currently attracting the attention of scientists as antibody alternatives due to their specific properties and feasibility of production in E. coli.

OBJECTIVE

CD44 nanobodies constitute a potent therapeutic agent that can block CD44/HA interaction in cancer and inflammatory diseases. This molecule may also function as a drug against cancer cells and has been produced previously in E. coli without a signal peptide sequence. The goal of this project was to find a suitable signal peptide to direct CD44 nanobody extracellular secretion in E. coli that will potentially lead to optimization of experimental methods and facilitate downstream steps such as purification.

METHODS

We analyzed 40 E. coli derived signal peptides retrieved from the Signal Peptide database and selected the best candidate signal peptides according to relevant criteria including signal peptide probability, stability, and physicochemical features, which were evaluated using signalP software version 4.1 and the ProtParam tool, respectively.

RESULTS

In this in silico study, suitable candidate signal peptide(s) for CD44 nanobody secretory expression were identified. CSGA, TRBC, YTFQ, NIKA, and DGAL were selected as appropriate signal peptides with acceptable D-scores, and appropriate physicochemical and structural properties. Following further analysis, TRBC was selected as the best signal peptide to direct CD44 nanobody expression to the extracellular space of E. coli.

CONCLUSION

The selected signal peptide, TRBC is the most suitable to promote high-level secretory production of CD44 nanobodies in E. coli and potentially will be useful for scaling up CD44 nanobody production in experimental research as well as in other CD44 nanobody applications. However, experimental work is needed to confirm the data.

Engineering a multi epitope vaccine against SARS-CoV-2 by exploiting its non structural and structural proteins

SARS-CoV-2, the causative agent behind the ongoing pandemic exhibits an enhanced potential for infection when compared to its related family members- the SARS-CoV and MERS-CoV; which have caused similar disease outbreaks in the past. The severity of the global health burden, increasing mortality rate and the emergent economic crisis urgently demands the development of next generation vaccines. Amongst such emergent next generation vaccines are the multi-epitope subunit vaccines, which hold promise in combating deadly pathogens. In this study we have exploited immunoinformatics applications to delineate a vaccine candidate possessing multiple B and T cells epitopes by utilizing the SARS-CoV-2 non structural and structural proteins. The antigenicity potential, safety, structural stability and the production feasibility of the designed construct was evaluated computationally. Furthermore, due to the known role of human TLR-3 immune receptor in viral sensing, which facilitates host cells activation for an immune response, the vaccine construct was examined for its binding efficiency using molecular docking and molecular dynamics simulation studies, which resulted in strong and stable interactions. Finally, the immune simulation studies suggested an effective immune response on vaccine administration. Overall, the immunoinformatics analysis advocates that the proposed vaccine candidate is safe and immunogenic and therefore can be pushed as a lead for in vitro and in vivo investigations.Communicated by Ramaswamy H. Sarma.

Glucose oxidase: Applications, sources, and recombinant production

Glucose oxidase is a subset of oxidoreductase enzymes that catalyzes the transfer of electrons from an oxidant to a reductant. Glucose oxidases use oxygen as an external electron acceptor that releases hydrogen peroxide (H₂ O₂ ). Glucose oxidase has many applications in commercial processes, including improving the color and taste, increasing the persistence of food materials, removing the glucose from the dried egg, and eliminating the oxygen from different juices and beverages. Moreover, glucose oxidase, along with catalase, is used in glucose testing kits (especially in biosensors) to detect and measure the presence of glucose in industrial and biological solutions (e.g., blood and urine specimens). Hence, glucose oxidase is a valuable enzyme in the industry and medical diagnostics. Therefore, evaluating the structure and function of glucose oxidase is crucial for modifying as well as improving its catalytic properties. Finding different sources of glucose oxidase is an effective way to find the type of enzyme with the desired catalysis. Besides, the recombinant production of glucose oxidase is the best approach to produce sufficient amounts of glucose oxidase for various uses. Accordingly, the study of various aspects of glucose oxidase in biotechnology and bioprocessing is crucial.

Functional screening of a Caatinga goat (Capra hircus) rumen metagenomic library reveals a novel GH3 β-xylosidase

Functional screening of metagenomic libraries is an effective approach for identification of novel enzymes. A Caatinga biome goat rumen metagenomic library was screened using esculin as a substrate, and a gene from an unknown bacterium encoding a novel GH3 enzyme, BGL11, was identified. None of the BGL11 closely related genes have been previously characterized. Recombinant BGL11 was obtained and kinetically characterized. Substrate specificity of the purified protein was assessed using seven synthetic aryl substrates. Activity towards nitrophenyl-β-D-glucopyranoside (pNPG), 4-nitrophenyl-β-D-xylopyranoside (pNPX) and 4-nitrophenyl-β-D-cellobioside (pNPC) suggested that BGL11 is a multifunctional enzyme with β-glucosidase, β-xylosidase, and cellobiohydrolase activities. However, further testing with five natural substrates revealed that, although BGL11 has multiple substrate specificity, it is most active towards xylobiose. Thus, in its native goat rumen environment, BGL11 most likely functions as an extracellular β-xylosidase acting on hemicellulose. Biochemical characterization of BGL11 showed an optimal pH of 5.6, and an optimal temperature of 50°C. Enzyme stability, an important parameter for industrial application, was also investigated. At 40°C purified BGL11 remained active for more than 15 hours without reduction in activity, and at 50°C, after 7 hours of incubation, BGL11 remained 60% active. The enzyme kinetic parameters of Km and Vmax using xylobiose were determined to be 3.88 mM and 38.53 μmol.min-1.mg-1, respectively, and the Kcat was 57.79 s-1. In contrast to BLG11, most β-xylosidases kinetically studied belong to the GH43 family and have been characterized only using synthetic substrates. In industry, β-xylosidases can be used for plant biomass deconstruction, and the released sugars can be fermented into valuable bio-products, ranging from the biofuel ethanol to the sugar substitute xylitol.

GP4: an integrated Gram-Positive Protein Prediction Pipeline for subcellular localization mimicking bacterial sorting

Subcellular localization is a critical aspect of protein function and the potential application of proteins either as drugs or drug targets, or in industrial and domestic applications. However, the experimental determination of protein localization is time consuming and expensive. Therefore, various localization predictors have been developed for particular groups of species. Intriguingly, despite their major representation amongst biotechnological cell factories and pathogens, a meta-predictor based on sorting signals and specific for Gram-positive bacteria was still lacking. Here we present GP⁴, a protein subcellular localization meta-predictor mainly for Firmicutes, but also Actinobacteria, based on the combination of multiple tools, each specific for different sorting signals and compartments. Novelty elements include improved cell-wall protein prediction, including differentiation of the type of interaction, prediction of non-canonical secretion pathway target proteins, separate prediction of lipoproteins and better user experience in terms of parsability and interpretability of the results. GP⁴ aims at mimicking protein sorting as it would happen in a bacterial cell. As GP⁴ is not homology based, it has a broad applicability and does not depend on annotated databases with homologous proteins. Non-canonical usage may include little studied or novel species, synthetic and engineered organisms, and even re-use of the prediction data to develop custom prediction algorithms. Our benchmark analysis highlights the improved performance of GP⁴ compared to other widely used subcellular protein localization predictors. A webserver running GP⁴ is available at http://gp4.hpc.rug.nl/

Immunoinformatics and analysis of antigen distribution of Ureaplasma diversum strains isolated from different Brazilian states

BACKGROUND

Ureaplasma diversum has numerous virulence factors that contribute to pathogenesis in cattle, including Lipid-associated membrane proteins (LAMPs). Therefore, the objectives of this study were to evaluate in silico important characteristics for immunobiological applications and for heterologous expression of 36 LAMPs of U. diversum (UdLAMPs) and, also, to verify by conventional PCR the distribution of these antigens in strains of Brazilian states (Bahia, Minas Gerais, São Paulo, and Mato Grosso do Sul). The Manatee database was used to obtain the gene and peptide sequences of the antigens. Similarity and identity studies were performed using BLASTp and direct antigenicity was evaluated by the VaxiJen v2.0 server. Epitope prediction for B lymphocytes was performed on the BepiPred v2.0 and CBTOPE v1.0 servers. NetBoLApan v1.0 was used to predict CD8⁺ T lymphocyte epitopes. Subcellular location and presence of transmembrane regions were verified by the software PSORTb v3.0.2 and TMHMM v2.2 respectively. SignalP v5.0, SecretomeP v2.0, and DOLOP servers were used to predict the extracellular excretion signal. Physico-chemical properties were evaluated by the web-software ProtParam, Solpro, and Protein-sol.

RESULTS

In silico analysis revealed that many UdLAMPs have desirable properties for immunobiological applications and heterologous expression. The proteins gudiv_61, gudiv_103, gudiv_517, and gudiv_681 were most promising. Strains from the 4 states were PCR positive for antigens predicted with immunogenic and/or with good characteristics for expression in a heterologous system.

CONCLUSION

These works contribute to a better understanding of the immunobiological properties of the UdLAMPs and provide a profile of the distribution of these antigens in different Brazilian states.

In silico analysis of signal peptides for secretory production of a-amylase in Bacillus subtilis

α-Amylases are important commercial enzymes and have a broad application in industrial processes and medicine. Gram-positive bacteria such as Bacillus subtilis are possible host organisms for α-amylases secretory production. Secretion of α-amylases to the culture medium versus intracellular production has several advantages such as prevention of inclusion bodies accumulation, higher product stability and solubility. Signal peptides are considered as one of the most essential elements for successful secretory synthesis of the recombinant proteins. Therefore, by the selection of an efficient signal peptide, secretion of the recombinant protein can be enhanced. The goal of this investigation was the in silico evaluation of several peptides to find the most suitable leader peptides for secretory production of α-amylase in B. subtilis. In present work, 30 signal peptides were selected, and numerous online servers such as SignalP, ProtParam, SOLpro, PRED-TAT and ProtComp was used for investigation of suitable signal peptides. According to in silico predictions all other signal peptides connected to α-amylase were stable and soluble except PPBD_BACSU. PPBD_BACSU because of having D-score below cut-off could not be recognized as a suitable signal peptide for α-amylase. Computational analysis identified QOX2_BACSU may direct protein into transmembrane location and was ignored. All 28 remained were predicted as secretory signal peptides which can excrete protein out of the bacteria. The signal peptides recommended by the present study are valuable for rational designing of secretory soluble α-amylase. Although, such information can be useful for future experimental production of these mentioned secretory proteins.

Two Simple Methods for Optimizing the Production of "Difficult-to-Express" GnRH-DFF40 Chimeric Protein

Purpose: GnRH-DFF40 (gonadotropin releasing hormone - DNA fragmentation factor 40) is a humanized recombinant immunotoxin and serves as a prospective candidate for targeted therapy of gonadotropin releasing hormone receptor (GnRHR) overexpressing malignancies. However, its production in Escherichia coli in a soluble and functional form still remains a challenge. Here we introduce two successful and reproducible conditions for production and purification of “difficult-to-express” GnRH-DFF40 protein.

Methods: A synthetic codon optimized GnRH-DFF40 fusion gene was cloned in pET28a plasmid. Two methods including high cell density IPTG induction (HCDI) and autoinduction method (AIM) with a focus on obtaining high cell density have been investigated to enhance the protein production in (E. coli). Moreover, to obtain higher protein production several factors in the AIM method including carbon sources, incubation time and temperature, plasmid stability and double colony selection, were optimized.

Results: Remarkable amounts of soluble GnRH-DFF40 protein were achieved by both methods. Cell density and protein yields in AIM was about 1.5 fold higher than that what obtained using HCDI. Initial screening showed that 25ºC is better to achieve higher protein production in both methods. pH alterations in AIM were maintained in a more constant level at 25ºC and 37ºC temperatures without any detrimental effects on cell growth during protein production phase up to 21 hours after incubation. Plasmid stability during growth and expression induction phase was maintained at a high level of 98% and 96% for AIM and HCDI methods, respectively. After parameter optimization and double colony selection in AIM, a very high yield of recombinant protein was achieved (528.3 mg/L).

Conclusion: With the optimization of these high cell density expression methods, reproducible manifold enhancement of soluble protein yields can be achieved for “difficult-to-express” GnRH-DFF40 compared to conventional expression methods.