Protein Production Processes Research Articles

Closed biotechnological cycles for transport life support systems in deep space exploration

The integration of closed biotechnological cycles in life support systems (LSS) of autonomous transport systems (ATS) is a critical solution for deep space and planetary exploration. Prolonged autonomous existence of integral ecosystems depends on the degree of cyclic use of substances and the coefficient of closure of the ecosystem's mass-exchange processes. In missions lasting over two years, it becomes more beneficial to reproduce necessary substances inside the system instead of relying on external supplies. This research aims to explore the integration of closed biotechnological cycles, with a focus on the biotechnological cycles of methane and carbon dioxide, in the LSS ATS to achieve a high coefficient of closed circulation of substances and nature-like features. Two methods of ATS crew waste processing are described, and the potential of using methane for additional oxygen generation and food protein biosynthesis in the closed-loop cycle of substances transformation is investigated. Additionally, the possibility of applying methane biooxidation technology to existing biotechnological processes of feed and food protein production using methanotrophic bacteria in terrestrial conditions is discussed as a potential method for producing food animal protein in LSS ATS.

Ex-ante life cycle assessment and scale up: A protein production case study

Life cycle assessment (LCA) is a well-known tool that has been able to provide insights into the environmental impact and hotspots of systems and technologies that are established in the market. Nevertheless, both for emerging processes that are only available at laboratory or pilot scale and when more future oriented in its perspective, the application of LCA becomes more complex and difficult. There is as of yet no consensus in the literature on how to conduct ex-ante LCA and many challenges discussed in the literature have yet to be cleared. This paper aims to highlight the implementation of ex-ante LCA with a specific focus on upscaling processes from laboratory to industrial scale. A new production process of proteins obtained from rapeseed cake serves as a case study to illustrate both the challenges encountered as well as the value and necessity of future oriented LCA, LCC and scaleup. The challenges found in this work include data availability, unknown final uses and functions, complexity of upscaling, and uncertainty. The results show a strong difference between laboratory scale and industrial scale costs and impacts, which are when upscaled lower compared to the impact of other protein sources, thus uncovering the environmental benefits of protein obtained from rapeseed cake.

Energy-efficient production of vaccine protein against porcine edema disease from transgenic lettuce (Lactuca sativa L.)

The development of functional protein production systems using transgenic plants as hosts has been rapidly progressing in recent years. Lettuce (Lactuca sativa L.) has been studied as one such host, and it has been reported that the biomass of lettuce per area and target protein expression level can be increased by optimizing the cultivation conditions. Therefore, we investigated methods to minimize the input light energy per target protein to reduce production costs. Herein, we examined the yield of a nontoxic B subunit of Stx2e (Stx2eB) from transgenic lettuce under various cultivation conditions. Stx2eB acts as a vaccine against swine edema disease. The effects of photon flux densities (PPFDs), photoperiod, and light source on Stx2eB production were examined and the findings suggested that 400 μmol m−2 s−1, 24 h, and white LED lamps, respectively, contributed to energy-efficient Stx2eB production. In addition, Stx2eB was produced 1.4 times more efficiently per unit area time using a high plant density (228.5 plants m−2) than a common density (30.4 plants m−2). The findings of the present study can facilitate the development of energy-efficient and low-cost production processes for vaccine protein production, considering temporal and spatial perspectives.

Effects of different concentrations of NaOH on the structure and in vitro digestion of cellulose from sesame kernel

Sesame kernel are a common and popular raw-food materials throughout the world. However, the sesame cellulose-rich residue is often discarded as waste after the industrial production process of oil and protein. In this work, four kinds of cellulose samples were extracted from sesame kernel using different strengths of an alkaline solution (0.5, 1.0, 2.0, 3.0 mol/L NaOH) under laboratory conditions. After in vitro simulated digestion of these samples, the relative amount of glucose increased by 1.09–3.17%, while the contents of xylose, arabinose, galactose and mannose decreased to varying degrees. Many tiny pores on the surface of the digested samples were observed by scanning electron microscope. Their thermal stabilities increased because of the loss of non-cellulose components during digestion. Fourier infrared spectrograms and X-ray diffraction spectra also showed that the structure of these celluloses had changed after digestion. The amounts of reducing sugars and polyphenols released at three digestion stages (oral, gastric, intestinal) were also measured. Overall, the celluloses obtained by 2 and 3 mol/L NaOH (AR-2, AR-3) were highly resistant to digestion compared to those obtained by 0.5 and 1 mol/L NaOH (AR-0.5, AR-1). These analyses provide basic information for the application of sesame cellulose in the food industry.

Intensifying Continuous Production of Gag-HA VLPs at High Cell Density Using Stable Insect Cells Adapted to Low Culture Temperature.

Protein production processes based on stable insect cell lines require intensification to be competitive with the insect cell-baculovirus expression vector system (IC-BEVS). High cell density (HCD) cultures operate continuously, capable of maintaining specific production rates for extended periods of time which may lead to significant improvements in production yields. However, setting up such processes is challenging (e.g., selection of cell retention device and optimization of dilution rate), often demanding the manipulation of large volumes of culture medium with associated high cost. In this study, we developed a process for continuous production of Gag virus–like particles (VLP) pseudotyped with a model membrane protein (influenza hemagglutinin, HA) at HCD using stable insect cells adapted to low culture temperature. The impact of the cell retention device (ATF vs. TFF) and cell-specific perfusion rate (CSPR) on cell growth and protein expression kinetics was evaluated. Continuous production of Gag-HA VLPs was possible using both retention devices and CSPR of 0.04 nL/cell.d; TFF induces higher cell lysis when compared to ATF at later stages of the process (kD = 0.009 vs. 0.005 h−1, for TFF and ATF, respectively). Reducing CSPR to 0.01–0.02 nL/cell.d using ATF had a negligible impact on specific production rates (rHA = 72–68 titer/109 cell.h and rp24 = 12–11 pg/106 cell.h in all CSPR) and on particle morphology (round-shaped structures displaying HA spikes on their surface) and size distribution profile (peaks at approximately 100 nm). Notably, at these CSPRs, the amount of p24 or HA formed per volume of culture medium consumed per unit of process time increases by up to 3-fold when compared to batch and perfusion operation modes. Overall, this work demonstrates the potential of manipulating CSPRs to intensify the continuous production of Gag-HA VLPs at HCD using stable insect cells to make them an attractive alternative platform to IC-BEVS.

Effects of 14 F9 synonymous codon variants on hemophilia B expression: Alteration of splicing along with protein expression.

There is growing evidence that synonymous codon variants (SCVs) can cause disease through the disruption of different processes of protein production. The aim of the study is to investigate whether the 14 SCVs reported in the F9 variant database were the pathogenic causes of hemophilia B. The impacts of SCVs on splicing and protein expression were detected using a combination of in silico prediction, in vitro minigene splicing assay and cell expression detection. The splicing transcripts were identified and quantified by co-amplification fluorescent PCR. The mechanism of splicing was verified by a modified pU1snRNA and pU7snRNA approach. Aberrant splicing patterns were found in eight SCVs. Five of the 8 SCVs produced almost all aberrant splicing isoforms, which were expected to truncate protein, three of them presented a partial defect on both splicing and protein secretion, the overall effects were consistent with the residual Factor IX activity of the affected cases. Neither the pre-messenger RNA (mRNA) splicing process nor the protein function was impaired in the rest six SCVs. In conclusion, our study firstly revealed the pathogenic mechanism of the 14 F9 SCVs and highlighted the importance of performing mRNA splicing analysis and protein expression studies of SCVs in inherited disorders.

Continuous Production of Human Epidermal Growth Factor Using Escherichia coli Biofilm.

Increasing demand for recombinant proteins necessitates efficient protein production processes. In this study, a continuous process for human epidermal growth factor (hEGF) secretion by Escherichia coli was developed by taking advantage of biofilm formation. Genes bcsB, fimH, and csgAcsgB that have proved to facilitate biofilm formation and some genes moaE, yceA, ychJ, and gshB potentially involved in biofilm formation were examined for their effects on hEGF secretion as well as biofilm formation. Finally, biofilm-based fermentation processes were established, which demonstrated the feasibility of continuous production of hEGF with improved efficiency. The best result was obtained from ychJ-disruption that showed a 28% increase in hEGF secretion over the BL21(DE3) wild strain, from 24 to 32 mg/L. Overexpression of bcsB also showed great potential in continuous immobilized fermentation. Overall, the biofilm engineering here represents an effective strategy to improve hEGF production and can be adapted to produce more recombinant proteins in future.

Effects of Ultrasound Combined with Preheating Treatment to Improve the Thermal Stability of Coconut Milk by Modifying the Physicochemical Properties of Coconut Protein.

In the food industry, coconut milk has a unique flavor and rich nutritional value. However, the poor emulsifying properties of coconut proteins restrict its development. In this study, the effect of ultrasound combined with preheating on coconut globulin and coconut milk was evaluated by physicochemical properties and structural characteristics. The results showed that ultrasound and 90 °C preheating gave coconut protein better emulsifying and thermal properties, demonstrated by higher solubility (45.2% to 53.5%), fewer free sulfhydryl groups (33.24 to 28.05 μmol/g) and higher surface hydrophobicity (7658.6 to 10,815.1). Additionally, Fourier transform infrared spectroscopy and scanning electron microscopy showed obvious changes in the secondary structure. Furthermore, the change in the physicochemical properties of the protein brought a higher zeta potential (−11 to −23 mV), decreased the thermal aggregation rate (148.5% to 13.4%) and increased the viscosity (126.9 to 1103.0 m·Pa·s) of the coconut milk, which indicates that ultrasound combined with preheating treatment provided coconut milk with better thermal stability. In conclusion, ultrasound combined with preheating will have a better influence on modifying coconut globulin and increasing the thermal stability of coconut milk. This study provides evidence that ultrasound and other modification technologies can be combined to solve the problems encountered in the processing of coconut protein products.

Towards new carbon–neutral food systems: Combining carbon capture and utilization with microbial protein production

Alternative protein sources such as microbial protein (MP) are currently considered to alleviate the burden that food production exerts on the environment. Even though MP production is highly efficient in land and nutrient utilization, their carbon footprint should be improved. Here we propose the use of CCU as a driver for heterotrophic MP production. By comparing different MP production routes starting from liquid substrates derived from CO2 (i.e., formate, acetate, methanol, and ethanol) and their respective metabolic pathways, the potential of this concept as a carbon–neutral food or feed production process was estimated. Acetate and ethanol appear to be the most beneficial substrates for the integrated CCU-to-MP process in terms of electricity demand (acetate: 25 – 54 kWh/kgproduct, ethanol: 28 – 56 kWh/kgproduct). Moreover, recycling CO2 enables a carbon-negative protein production process by 2030 (considering the projected CO2 emissions from electricity in the EU: 0.096 kgCO2-eq/kWh) for formate, acetate, and ethanol (-1.1 up to 13 kgCO2-eq/kgproduct).

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

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).

Generic model based control of different specific rates in recombinant E. coli Fed-batch processes

In addition to often reported control of the specific growth rate we show in this contribution a novel method to control the biomass specific substrate uptake as well as the protein production rate during the production phase of microbial fed-batch cultures. The control laws base on a calibrated process model including experimental data sets with different constant glycerol feed rates. The model includes changing growth and production behaviour in function of the induced metabolic stress. Based on the method of non-linear feedback linearization, the control laws were derived from the model, using the glycerol feed rate as the manipulable variable. Considering comparable setpoints at three different levels the effectiveness of the controller as well as their potential to improve the production phase was assessed by simulations. The direct control of product formation rates enables to ensure constant production performance and therefore to reach highest product levels in short time. As a drawback, the controller needs high feed adaption towards the end to counteract the advancing decay of the attainable production rates. This, to a lesser extend, also applies for the growth rate. A constant substrate uptake rate resulted in a valuable alternative to a uncontrolled, constant feed rate during the production phase of recombinant protein production processes.

Recombinant Human Erythropoietin Production in Chinese Hamster Ovary Cells Is Enhanced by Supplementation of α-Helix Domain of 30Kc19 Protein

The enhancement of recombinant therapeutic protein production in mammalian cell culture has been regarded as an important issue in the biopharmaceutical industry. Previous studies have reported that the addition of the recombinant 30Kc19 protein, a silkworm-derived plasma protein with simultaneous cell-penetrating and mitochondrial enzyme-stabilizing properties, can enhance the recombinant protein expression in Chinese hamster ovary (CHO) cell culture. Here, we produced an α-helix N-terminal domain of 30Kc19, called (30Kc19α), and investigated its effects on the production of human erythropoietin (EPO), a widely used therapeutic protein for the treatment of anemia, in recombinant CHO cell culture. Similar to the full-length 30Kc19, 30Kc19α was able to be mass-produced in a form of recombinant protein through an Escherichia coli expression system and delivered into EPO-producing CHO (EPO–CHO) cells. Supplementing the medium of EPO–CHO cell culture with 30Kc19α increased the intracellular NADPH/NADP+ ratio related to the flux of metabolic reducing power for protein biosynthesis, subsequently enhancing EPO production in serum-free culture. 30Kc19α is considered to have certain advantages in the downstream purification process of therapeutic protein production when it is used as a medium supplement due to its small size and low isoelectric point compared to the full-length 30Kc19. These results suggest that 30Kc19α has potential use for manufacturing biopharmaceutical proteins.

Recombinant protein production in Pichia pastoris: from transcriptionally redesigned strains to bioprocess optimization and metabolic modelling.

Pichia pastoris is one of the most widely used host for the production of recombinant proteins. Expression systems that rely mostly on promoters from genes encoding alcohol oxidase 1 or glyceraldehyde-3-phosphate dehydrogenase have been developed together with related bioreactor operation strategies based on carbon sources such as methanol, glycerol, or glucose. Although, these processes are relatively efficient and easy to use, there have been notable improvements over the last twenty years to better control gene expression from these promoters and their engineered variants. Methanol-free and more efficient protein production platforms have been developed by engineering promoters and transcription factors. The production window of P. pastoris has been also extended by using alternative feedstocks including ethanol, lactic acid, mannitol, sorbitol, sucrose, xylose, gluconate, formate or rhamnose. Herein, the specific aspects that are emerging as key parameters for recombinant protein synthesis are discussed. For this purpose, a holistic approach has been considered to scrutinize protein production processes from strain design to bioprocess optimization, particularly focusing on promoter engineering, transcriptional circuitry redesign. This review also considers the optimization of bioprocess based on alternative carbon sources and derived co-feeding strategies. Optimization strategies for recombinant protein synthesis through metabolic modelling are also discussed.

Development of Effective Risk Mitigation Strategy for Cell Culture Process of Recombinant Protein Production

Microbial contamination, instability in production yields and cell lines are the challenges that must be faced by any pharmaceutical biotechnology industry when conducting cell culture as one of the stages of its production process. In the past, Company X has experienced twice contamination cases during cell culture process for its recombinant protein products. As a result, Company X suffered financial lossess at approximately 3.05 billion rupiah and resulted in disruption of the stock of recombinant protein drug which are the active pharmaceutical ingredient for most of injection products. Therefore, an effective mitigation strategies are needed to manage any potential risks in the cell culture process. This study aims to design a risk mitigation strategy for risk in cell culture process by using House of Risk (HOR) method. There are two HOR matrices used in this study. HOR1 is used to determine which risk agents should be prioritized for prevention. In HOR2, several effective risk management strategies will be chosen. There are 40 risks events and 31 risk agents identified. Based on risk assessment results and applying Pareto Chart analysis there are two risk agents selected. Five proactive actions to mitigate these risks are proposed. They are training and personnel qualification program periodically, changing workflow become more efficient and convenient, more detailed revision of related documents, changing manual process to semi-automatic process gradually and additional person on each team as a verifier for double-checking.

Construction of Fluorescent Immunosensor Quenchbody to Detect His-Tagged Recombinant Proteins Produced in Bioprocess.

With the widespread application of recombinant DNA technology, many useful substances are produced by bioprocesses. For the monitoring of the recombinant protein production process, most of the existing technologies are those for the culture environment (pH, O2, etc.). However, the production status of the target protein can only be known after the subsequent separation and purification process. To speed up the monitoring of the production process and screening of the higher-yield target protein variants, here we developed an antibody-based His-tag sensor Quenchbody (Q-body), which can quickly detect the C-terminally His-tagged recombinant protein produced in the culture medium. Compared with single-chain Fv-based Q-body having one dye, the Fab-based Q-body having two dyes showed a higher response. In addition, not only was fluorescence response improved but also detection sensitivity by the mutations of tyrosine to tryptophan in the heavy chain CDR region. Moreover, the effect of the mutations on antigen-binding was successfully validated by molecular docking simulation by CDOCKER. Finally, the constructed Q-body was successfully applied to monitor the amount of anti-SARS CoV-2 nanobody secreted into the Brevibacillus culture media.

Integrated process for protein, pigments, and biogas production from baker's yeast wastewater using filamentous fungi

Baker's yeast production industry generates large quantities of high chemical oxygen demand (COD) wastewater. The integration of baker's yeast wastewater (BYW) for an innovative two-step waste biorefinery process by producing protein-rich fungal biomass and biogas along with COD and nutrients removal was the main object of the present research. In the first step, fungal biomass production from BYW was investigated using four species of filamentous fungi. The maximum biomass yield of 5.13 g/L BYW containing 43.8% mycoprotein and 36.3% COD removal was achieved by A. oryzae. In the second step, to produce biogas and further remove organic matter, the effluent of fungal fermentation was subjected to anaerobic digestion and COD removal between 22.4 and 44.2% was obtained. Overall, 1 m3 of BYW yielded 5.13 kg of protein-rich biomass and 1.42 m3 of methane. Additionally, pigment production using N. intermedia was investigated, and 1.54 mg carotenoids/g biomass was produced.

Yeasts of the Blastobotrys genus are promising platform for lipid-based fuels and oleochemicals production.

Strains of the yeast genus Blastobotrys (subphylum Saccharomycotina) represent a valuable biotechnological resource for basic biochemistry research, single-cell protein, and heterologous protein production processes. Species of this genus are dimorphic, non-pathogenic, thermotolerant, and can assimilate a variety of hydrophilic and hydrophobic substrates. These can constitute a single-cell oil platform in an emerging bio-based economy as oleaginous traits have been discovered recently. However, the regulatory network of lipogenesis in these yeasts is poorly understood. To keep pace with the growing market demands for lipid-derived products, it is critical to understand the lipid biosynthesis in these unconventional yeasts to pinpoint what governs the preferential channelling of carbon flux into lipids instead of the competing pathways. This review summarizes information relevant to the regulation of lipid metabolic pathways and prospects of metabolic engineering in Blastobotrys yeasts for their application in food, feed, and beyond, particularly for fatty acid-based fuels and oleochemicals. KEY POINTS: • The production of biolipids by heterotrophic yeasts is reviewed. • Summary of information concerning lipid metabolism regulationis highlighted. • Special focus on the importance of diacylglycerol acyltransferases encoding genes in improving lipid productionismade.

Methane in wastewater treatment plants: status, characteristics, and bioconversion feasibility by methane oxidizing bacteria for high value-added chemicals production and wastewater treatment

Methane is a type of renewable fuel that can generate many types of high value-added chemicals, however, besides heat and power production, there is little methane utilization in most of the wastewater treatment plants (WWTPs) all round the world currently. In this review, the status of methane production performance from WWTPs was firstly investigated. Subsequently, based on the identification and classification of methane oxidizing bacteria (MOB), the key enzymes and metabolic pathway of MOB were presented in depth. Then the production, extraction and purification process of high value-added chemicals, including methanol, ectoine, biofuel, bioplastic, methane protein and extracellular polysaccharides, were introduced in detail, which was conducive to understand the bioconversion process of methane. Finally, the use of methane in wastewater treatment process, including nitrogen removal, emerging contaminants removal as well as resource recovery was extensively explored. These findings could provide guidance in the development of sustainable economy and environment, and facilitate biological methane conversion by using MOB in further attempts.

Translational Control by Ribosome Pausing in Bacteria: How a Non-uniform Pace of Translation Affects Protein Production and Folding.

Protein homeostasis of bacterial cells is maintained by coordinated processes of protein production, folding, and degradation. Translational efficiency of a given mRNA depends on how often the ribosomes initiate synthesis of a new polypeptide and how quickly they read the coding sequence to produce a full-length protein. The pace of ribosomes along the mRNA is not uniform: periods of rapid synthesis are separated by pauses. Here, we summarize recent evidence on how ribosome pausing affects translational efficiency and protein folding. We discuss the factors that slow down translation elongation and affect the quality of the newly synthesized protein. Ribosome pausing emerges as important factor contributing to the regulatory programs that ensure the quality of the proteome and integrate the cellular and environmental cues into regulatory circuits of the cell.

GSCNN: a composition of CNN and Gibb Sampling computational strategy for predicting promoter in bacterial genomes

This paper is about a new computational strategy to find the promoter sequence which is a transcription starting factor in DNA without which the gene sequence cannot be activated for further protein synthesis process. Genes are the hereditary source of organisms’ functionality of living things. Sequence of activities is carried out to reveal the protein production process hidden in the genes. In this regard promoter prediction is essential to bring out correctness of protein synthesis in decoding the genetical information. Also it enables the biologists to find the genetical malfunctions. Nowadays numerous computational methods which have been proposed are helpful to the biologist in related tasks. Earlier works applied Gibb sampling method, Markov Chain Model and machine learning strategies to predict the promoters. In this paper a new computational strategy named as GSCNN is introduced which combines Gibb sampling with Convolution Neural Network (CNN). This model uses Gibb sampling method to select the best profile features of DNA and extract the scores as feature vector with the help of position frequency matrix. Those extracted feature vectors are further fed into Convolution Neural Network to predict the sigma (σ) 54 promoter of bacterial genome. The performance of the proposed system is evaluated with the help of Bacillus subtilis NC_000964 dataset. The sigma (σ) 54 promoter prediction using the proposed GSCNN method achieved significant improvement in performance metrics compared with the traditional machine learning algorithms such as Decision Tree (DT), K-Nearest Neighbor(KNN), Random Forest(RF) and Support Vector Machine(SVM).